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Zayour, Iyad. "Reverse engineering: A cognitive approach, a case study and a tool." Thesis, University of Ottawa (Canada), 2002. http://hdl.handle.net/10393/6075.
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Software maintenance (SM) for large legacy systems is a very inefficient process; on average, 70% of software costs are spent on maintenance [Swanson 89]. The inefficiency of SM has been related to the difficulty comprehending software systems; therefore program comprehension is considered to be a key bottleneck of SM. Reverse engineering tools have been used to alleviate this bottleneck with lower than expected success. We present a cognitively based approach for reverse engineering tool development. We use ideas from cognitive psychology and other disciplines to formulate the approach. We also describe a case study in which we applied the approach in a telecommunication company. The case study resulted in the development of DynaSee, a reverse engineering tool which helps software engineers analyze dynamic program information. DynaSee reads routine call traces, and provides several processing and visualization features that make the use of traces much more useful for software maintenance and program comprehension. Next, we describe and evaluate the various features of DynaSee that compress, abstract and augment traces to make them comprehensible and useful for SM tasks. Finally, based on our experience in developing DynaSee, we generalize the aspects of our findings and techniques that are based on psychology by relating them to the mainstream psychological literature and to other disciplines where similar techniques have been used.
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Goodman, Katherine Ann. "The Transformative Experience in Engineering Education." Thesis, University of Colorado at Boulder, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3743651.
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<p> This research evaluates the usefulness of transformative experience (TE) in engineering education. With TE, students 1) apply ideas from coursework to everyday experiences without prompting <i>(motivated use);</i> 2) see everyday situations through the lens of course content <i>(expanded perception);</i> and 3) value course content in new ways because it enriches everyday affective experience <i>(affective value).</i> In a three-part study, we examine how engineering educators can promote student progress toward TE and reliably measure that progress.</p><p> For the first study, we select a mechanical engineering technical elective, Flow Visualization, that had evidence of promoting <i>expanded perception </i> of fluid physics. Through student surveys and interviews, we compare this elective to the required Fluid Mechanics course. We found student interest in fluids fell into four categories: complexity, application, ubiquity, and aesthetics. Fluid Mechanics promotes interest from application, while Flow Visualization promotes interest based in ubiquity and aesthetics. Coding for <i> expanded perception,</i> we found it associated with students’ engineering identity, rather than a specific course. In our second study, we replicate atypical teaching methods from Flow Visualization in a new design course: Aesthetics of Design. Coding of surveys and interviews reveals that open-ended assignments and supportive teams lead to increased ownership of projects, which fuels risk-taking, and produces increased confidence as an engineer.</p><p> The third study seeks to establish parallels between <i>expanded perception</i> and measurable perceptual expertise. Our visual expertise experiment uses fluid flow images with both novices and experts (students who had passed fluid mechanics). After training, subjects sort images into laminar and turbulent categories. The results demonstrate that novices learned to sort the flow stimuli in ways similar to subjects in prior perceptual expertise studies. In contrast, the experts’ significantly better results suggest they are accessing conceptual fluids knowledge to perform this new, visual task. The ability to map concepts onto visual information is likely a necessary step toward expanded perception.</p><p> Our findings suggest that open-ended aesthetic experiences with engineering content unexpectedly support engineering identity development, and that visual tasks could be developed to measure conceptual understanding, promoting expanded perception. Overall, we find TE a productive theoretical framework for engineering education research.</p>
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Dreany, Harry Hayes. "Safety Engineering of Computational Cognitive Architectures within Safety-Critical Systems." Thesis, The George Washington University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10688677.
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<p> This paper presents the integration of an intelligent decision support model (IDSM) with a cognitive architecture that controls an autonomous non-deterministic safety-critical system. The IDSM will integrate multi-criteria, decision-making tools via intelligent technologies such as expert systems, fuzzy logic, machine learning, and genetic algorithms. </p><p> Cognitive technology is currently simulated within safety-critical systems to highlight variables of interest, interface with intelligent technologies, and provide an environment that improves the system’s cognitive performance. In this study, the IDSM is being applied to an actual safety-critical system, an unmanned surface vehicle (USV) with embedded artificial intelligence (AI) software. The USV’s safety performance is being researched in a simulated and a real-world, maritime based environment. The objective is to build a dynamically changing model to evaluate a cognitive architecture’s ability to ensure safe performance of an intelligent safety-critical system. The IDSM does this by finding a set of key safety performance parameters that can be critiqued via safety measurements, mechanisms, and methodologies. The uniqueness of this research lies in bounding the decision-making associated with the cognitive architecture’s key safety parameters (KSPs). Other real-time applications (RTAs) that would benefit from advancing cognitive science associated with safety are unmanned platforms, transportation technologies, and service robotics. Results will provide cognitive science researchers with a reference for the safety engineering of artificially intelligent safety-critical systems. </p><p>
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Horine, Brent. "Bootstrapping Cognitive Radio Networks." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5306.
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Cognitive radio networks promise more efficient spectrum utilization by leveraging degrees of freedom and distributing data collection. The actual realization of these promises is challenged by distributed control, and incomplete, uncertain and possibly conflicting knowledge bases. We consider two problems in bootstrapping, evolving, and managing cognitive radio networks. The first is Link Rendezvous, or how separate radio nodes initially find each other in a spectrum band with many degrees of freedom, and little shared knowledge. The second is how radio nodes can negotiate for spectrum access with incomplete information. To address the first problem, we present our Frequency Parallel Blind Link Rendezvous algorithm. This approach, designed for recent generations of digital front-ends, implicitly shares vague information about spectrum occupancy early in the process, speeding the progress towards a solution. Furthermore, it operates in the frequency domain, facilitating a parallel channel rendezvous. Finally, it operates without a control channel and can rendezvous anywhere in the operating band. We present simulations and analysis on the false alarm rate for both a feature detector and a cross-correlation detector. We compare our results to the conventional frequency hopping sequence rendezvous techniques. To address the second problem, we model the network as a multi-agent system and negotiate by exchanging proposals, augmented with arguments. These arguments include information about priority status and the existence of other nodes. We show in a variety of network topologies that this process leads to solutions not otherwise apparent to individual nodes, and achieves superior network throughput, request satisfaction, and total number of connections, compared to our baselines. The agents independently formulate proposals based upon communication desires, evaluate these proposals based upon capacity constraints, create arguments in response to proposal rejections, and re-evaluate proposals based upon received arguments. We present our negotiation rules, messages, and protocol and demonstrate how they interoperate in a simulation environment.<br>Ph.D.<br>Doctorate<br>Electrical Engineering and Computer Science<br>Engineering and Computer Science<br>Electrical Engineering
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Alhanai, Tuka(Tuka Waddah Talib Ali Al Hanai). "Detecting cognitive impairment from spoken language." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122724.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 141-165).<br>Dementia comes second only to spinal cord injuries in terms of its debilitating effects; from memory-loss to physical disability. The standard approach to evaluate cognitive conditions are neuropsychological exams, which are conducted via in-person interviews to measure memory, thinking, language, and motor skills. Work is on-going to determine biomarkers of cognitive impairment, yet one modality that has been relatively less explored is speech. Speech has the advantage of being easy to record, and contains the majority of information transmitted during neuropsychological exams. To determine the viability of speech-based biomarkers, we utilize data from the Framingham Heart Study, that contains hour-long audio recordings of neuropsychological exams for over 5,000 individuals. The data is representative of a population and the real-world prevalence of cognitive conditions (3-4%). We first explore modeling cognitive impairment from a relatively small set of 92 subjects with complete information on audio, transcripts, and speaker turns. We loosen these constraints by modeling with only a fraction of audio (~2-3 minutes), of which the speaker segments are defined through text-based diarization. We next apply this diarization method to extract audio features from all 7,000+ recordings (most of which have no transcripts), to model cognitive impairment (AUC 0.83, spec. 78%, sens. 79%). Finally, we eliminate the need for feature-engineering by training a neural network to learn higher-order representations from filterbank features (AUC 0.85, spec. 81%, sens. 82%). Our speech models exhibit strong performance and are comparable to the baseline demographic model (AUC 0.85, spec. 93%, sens. 65%). Further analysis shows that our neural network model automatically learns to detect specific speech activity which clusters according to: pause followed by onset of speech, short burst of speech, speech activity in high-frequency spectral energy bands, and silence.<br>by Tuka Alhanai.<br>Ph. D.<br>Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Hu, Hongzhan. "Exploring the concept of feedback with perspectives from psychology and cognitive science." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-107090.
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This study explores the concept of feedback from various perspectives in psychology and cognitive science. Specifically, the theories of ecological psychology, situated and Distributed Cognition, Cognitive Systems Engineering and Embodied cognition are investigated and compared. Cognitive Systems Engineering provides a model of feedback and related constructs, to understand human behavior in complex working environments. Earlier theories such as ecological psychology, considered feedback as direct perception. Situated cognition clearly inherits ideas from ecological psychology, whereas distributed cognition provides a deeper understanding of feedback through artifact use. Cognitive Systems Engineering provides a systematic view of feedback and control. This framework is a suitable perspective to understanding feedback in human-machine settings.
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McWhirter, Nathan Daniel. "Teaching Engineering Students About Cognitive Barriers During Design for Sustainable Infrastructure." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/81310.
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Sustainability is a complex socio-technical challenge that requires new ways of thinking. To help meet this challenge, I have created three case-based modules that teach engineering students how to apply sustainability principles and help them recognize potential cognitive traps, or barriers, that may prevent more consideration for sustainability during design. Each of my three case studies is built into a PowerPoint-guided module for undergraduate engineering classes, which may be taught in 1-3 class days. I have implemented each of the three modules in senior-level classes at Virginia Tech, assessed survey data, and scored student assignments. This work and the underlying literature background is reflected in three journal papers, one for each module. My case study modules, along with all associated teaching materials, are shared in the Center for Sustainable Engineering repository for other instructors to adapt and use.
Each module includes a case study about an infrastructure project recognized and awarded by the Envision rating system, demonstrating a case of sustainability done well. Adaptable PowerPoint slides are used to teach about the Envision rating system and credits particularly relevant to the project. Active learning assignments allow students to apply the Envision framework and design criteria to complex and ill-structured problems related to the case study. Slides also cover the relation of three selected behavioral decision science concepts to each case study; these include cognitive biases and barriers which tend to inhibit sustainability outcomes, as well as some potential solutions to mitigate or overcome such barriers. Paired with the decision-making framework of Envision, awareness of these transdisciplinary concepts will allow students to more effectively manage the complex decisions found in real-world projects.
Results were assessed through a variety of methods to determine the modules' level of effectiveness in accomplishing defined student learning outcomes. Pre-module and post-module student surveys were employed to measure several indicators: changes in self-assessed confidence levels, perceptions of sustainable design (characteristics and barriers), and accuracy of module concept definitions. Each of several active learning assignments was scored on a simple rubric. Concept maps were also tested as further type of assessment, and scored with both traditional and holistic methods. However, fully integrating the concept mapping approach is left to the future work of others.
These modules are a significant contribution to engineering education, as they integrate diverse topics and disciplines into a unified and relevant teaching package. Over 350 students have already been reached through the three modules, and sharing the materials in a peer-reviewed repository allows for expansion, adaptation, and capacity building. Each module's content and pedagogy align with ABET accreditation requirements and ASCE's Body of Knowledge, making them relevant tools for equipping the future generation of engineers. Future development of similar case studies can build partnerships between academia and industry, as well as increase cross-disciplinary collaboration. These efforts will both improve undergraduate education and advance the profession.<br>Master of Science
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Zheng, Xijia Ph D. Massachusetts Institute of Technology. "Cognitive optical network architecture in dynamic environments." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/126997.
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Thesis: Ph. D. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020<br>Cataloged from the official PDF of thesis.<br>Includes bibliographical references (pages 149-154).<br>Emerging network traffic requires a more agile network management and control system to deal with the dynamic network environments than today's networks use. The bursty and large data transactions introduced by new technological applications can cause both high costs and extreme congestion in networks. The prohibitive cost of massive over-provisioning will manifest as huge congestions during peak demand periods. The network management and control system must be able to sense the traffic changes and reconfigure in a timely manner (in tens of milliseconds instead of minutes or hours) to use network resources efficiently. We propose the use of cognitive techniques for fast and adaptive network management and control of future optical networks. The goal of this work is to provide timely network reconfigurations in response to dynamic traffic environments and prevent congestion from building up.<br>We make a simplified model of the expected traffic arrival rate changes as a multistate Markov process based on the characteristics of the dynamic, bursty, and high granularity traffic. The traffic is categorized into different network traffic environments by the length of the network coherence time, which is the time that the traffic is unvarying. The tunneled network architecture is adopted due to its supremacy in reducing the control complexity when the traffic volume is at least one wavelength. In the long coherence time regime where traffic changes very slowly, the traffic detection performances of two Bayesian estimators and a stopping-trial (sequential) estimator are examined, based on the transient behaviors of networks. The stopping trial estimator has the fastest response time to the changes of traffic arrival statistics. We propose a wavelength reconfiguration algorithm with continuous assessment where the system reconfigures whenever it deems necessary.<br>The reconfiguration can involve addition or subtraction of multiple wavelengths. Using the fastest detection and reconfiguration algorithm can reduce queueing delays during traffic surges without over-provisioning and thus can reduce network capital expenditure and prevent wasting resources on erroneous decisions when surges occur. For traffic with moderate coherence time (where traffic changes at a moderate rate) and the short coherence time (where traffic changes quickly), the stopping-trial estimator still responds to the traffic changes with a short detection time. As long as the inter-arrival times of traffic transactions are independent, the algorithm is still optimum. The algorithm provides no prejudice on the exact network traffic distribution, avoiding having to sense and estimate detailed arrival traffic statistics.<br>To deal with fast-changing traffic, we model the transient convergent behaviors of network traffic drift as a result of traffic transition rate changes and validate the feasibility and utility of the traffic prediction. In a simple example when the network traffic rate changes monotonically in a linear model, the sequential maximum likelihood estimator will capture the traffic trend with a small number of arrivals. The traffic trend prediction can help to provide fast reconfiguration, which is very important for maintaining quality of service during large traffic shifts. We further investigate the design of an efficient rerouting algorithm to maintain users' quality of service when the incremental traffic cannot be accommodated on the primary path. The algorithm includes the fast reconfiguration of wavelengths in the existing lit and spatially routed fibers, and the setting up and lighting of new fibers.<br>Rerouting is necessary to maintain users' quality of service when the queueing delay on the primary path (determined by shortest path routing) exceeds the requirement. Our algorithm triggers reconfiguration when a queueing delay threshold is crossed on the primary path. The triggering by a threshold on the queueing delay is used due to its simplicity, and it is directly measurable by the exact traffic transaction sizes and the queue size, which reflect both the current network traffic environment and the network configurations. A dynamic rerouting algorithm implemented with a shortest path algorithm is proposed to find the secondary paths for rerouting. We make the conjecture that it is desirable that the alternate paths for rerouting have small numbers of hops and are disjoint with other busy paths when the hops on the path are independent. In addition, the conjecture suggests that a good candidate network topology should have high edge-connectivity.<br>Wavelength reservation for rerouted traffic does not maximize wavelength utilization. We make the conjecture that traffic with different sizes should be broken up into multi-classes with dedicated partitioned resources and the queueing delay should be normalized by the transmission time for rerouting triggering to realize better network utilization.<br>by Xijia Zheng.<br>Ph. D. in Computer Science and Engineering<br>Ph.D.inComputerScienceandEngineering Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Rezaee, Arman. "Towards a cognitive network management and control system." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/128329.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2020<br>Cataloged from PDF of thesis.<br>Includes bibliographical references (pages 155-159).<br>Future networks have to accommodate an increase of 3-4 orders of magnitude in data rates with heterogeneous session sizes and strict time deadline requirements. The dynamic nature of scheduling of large transactions and the need for rapid actions by the network management and control system, require timely and judicious collection of network state information. Within this context we will focus on the problem of shortest path routing, and identify pragmatic schemes that allow a central controller to collect relevant delay statistics from various links and nodes within the network. We present Significant Sampling as an adaptive monitoring technique to collect and disseminate network state information when it can be of significant value to the optimal operation of the network, and in particular when it can help in identifying the shortest routes.<br>We start by developing an analytical framework that can identify the optimal time for the collection of such information in a small but realistic setting, when the underlying delay model is a continuous-time diffusion process (e.g. Wiener process or Ornstein-Uhlenbeck process) and its parameters are known by the controller. We show that this technique balances the need for updated state information against the collection and dissemination costs and provides an algorithm that yields near optimum performance. We then extend the results by introducing a reinforcement learning framework that learns the aforementioned optimal policy from its own interactions with the network, and without any prior assumptions regarding the underlying delay model. In addition to achieving a performance comparable to the analytically derived policies, the deep reinforcement learning solution is more flexible and general and can accommodate a diverse set of network environments.<br>This is particularly important because it can provide good solutions for complex network environments where analytically tractable solutions are not feasible. We conclude our work by noting that sensible network controllers should continue to deliver a good performance between distinct instances of state collection and thus any meaningful solution should strive to meet application demands despite the unavoidable uncertainty about the instantaneous state of the network. To that end, we introduce a novel diversity routing scheme that can accommodate requirements regarding delay variations despite a controller's relative uncertainty about the instantaneous state of the network. More specifically we utilize mean-variance analysis as the basis for traffic distribution and route selection, and show that this technique can improve the users' quality of service by taking into account the correlated nature of delay across different paths.<br>We conclude this work by commenting on the potential application of this method to general transportation networks.<br>by Arman Rezaee.<br>Ph. D.<br>Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Liang, Wei. "Cooperative communication for cognitive radio networks." Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/382935/.
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A Cooperative Cognitive Radio (CCR) network, which integrates a conventional cooperative system and cognitive radios (CRs) into a holistic system, is a promising paradigm for the next generation mobile communication systems. The spectral efficiency, power efficiency, bandwidth reduction and system complexity in CCR networks are the fundamental parameters of our system design and optimization. In this thesis, we focus our attention on opportunistically exploiting the underutilized spectrum band in the CR network with the aid of cooperative protocols. Furthermore, we invoke channel coding schemes in our CCR system in order to improve the overall system throughput. In our CCR system, the overlay based cooperation scheme of Primary Users (PUs) and Cognitive Users (CUs) is considered, which has the potential of leading to a transmission power reduction and transmission rate improvement for both the PU and the CU. More explicitly, our cooperative protocol allows a group of CUs to serve as Relay Nodes (RNs) for relaying the signal of the PUs’ transmitters to the PUs’ intended destinations. To elaborate further, both one way relaying and two-way relaying schemes are used in our proposed system, so that the bandwidth requirement of the PUs is reduced. Alternatively, the freed bandwidth may be leased to a group of CUs for their secondary communications. Our numerical and simulation results show that the bandwidth reduction attained by the proposed two-way relaying based CR scheme may approach as much as 80% of the PU’s bandwidth. Moreover, an Adaptive Dynamic Network Coding (ADNC) scheme is also conceived for this overlay CCR system, which is designed for supporting communications between multiple PUs and a common Base Station (BS). More particularly, the near-instantaneously Adaptive Turbo Trellis Coded Modulation (ATTCM) is employed for appropriately adjusting both the modulation mode as well as the channel coding rate and the network coding rate, according to the near-instantaneous channel conditions. In order to facilitate the recovery of the source information at the BS, the CUs invoke the ADNC technique, which is assisted by our cooperative protocol operating by exchanging the CCR-based control information between the near-instantaneously ATTCM and network coding codec as well as between the CUs and the BS. Additionally, the network encoder may also be activated in its adaptive mode for supporting the CUs, depending on the Boolean value of the feedback flags generated based on the success/failure of the ATTCMdecoder and of the network decoder, which is evaluated and fed back by the BS. Quantitatively, it was found that the joint holistic design of our ATTCM-ADNC-CCR scheme is either capable of freeing up an approximately 40% of the PU’s bandwidth in comparison to its non-cooperative counterpart, or increasing the attainable throughput by as much as 2 bit/symbol. Furthermore, a Pragmatic Distributed Algorithm (PDA) is proposed for supporting the efficient spectral access of multiple PUs and CUs in CCR networks. The novelty of our PDA is that the Pus negotiate with the CUs concerning the specific amount of relaying and transmission time, and the CU will decide either to accept or to decline this offer. These CUs relay the signal received from the PUs to the PUs’ receiver, but only when both the PUs’ and the CUs’ minimum rate requirements are satisfied. Moreover, we show that the cooperative spectral access based on our PDA reaches an equilibrium, when it is repeated for a sufficiently long duration. These benefits are achieved, because the PUs are motivated to cooperate by the incentive of achieving a higher PU rate, whilst defecting from cooperation can be discouraged with the aid of a limited-duration punishment. Therefore, our proposed PDA outperforms the benchmark, despite its significantly lower overhead and lower complexity. Finally, we present the joint design of coding, modulation, user-cooperation and CR techniques, which may lead to significant mutual benefits for both the PUs and the CUs.
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Li, Shuang. "MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1365089959.
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Farah, Hanna Ibrahim. "Applying cognitive patterns to support software tool development." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27354.
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This research was motivated by the development of a set of cognitive patterns [3], and the hypothesis that those patterns could lead to innovative and useful features in software development environments. Cognitive patterns are descriptions of ways people think and act when exploring or explaining software. In this research we focused on the Temporal Details cognitive patterns, which describe the dynamics of the changes in someone's mental model.
The main objective of this research, therefore, is to determine to what extent software engineering tool features could be derived from the cognitive patterns, specifically belonging to the Temporal Details hierarchy.
As the first step in our research, we analysed current tool support for cognitive patterns. The second step was to create and evaluate a list of potential new features based on the cognitive patterns. Thirdly, we developed a prototype for our most promising feature entitled Temporal Model Explorer (TME). This prototype helps people understand and manipulate the history of a software model. Users can use a slider to browse the history of the construction of a UML diagram from its point of creation to its current state. Navigation can be performed at different levels of granularity. Design rationale can be included at any point in the history. The final step was to evaluate the TME prototype with twelve participants from different backgrounds. The participants found the tool useful, and agreed that they would use it if it was available in their work environment.
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Andrews, Charles K. "Utilizing Traditional Cognitive Measures of Academic Preparation to Predict First-Year Science, Technology, Engineering, and Mathematics (STEM) Majors' Success in Math and Science Courses." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1574.
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For the past several years, U.S. colleges and universities have faced increased pressure to improve retention and graduation rates. At the same time, educational institutions have placed a greater emphasis on the importance of enrolling more students in STEM (science, technology, engineering and mathematics) programs and producing more STEM graduates. The resulting problem faced by educators involves finding new ways to support the success of STEM majors, regardless of their pre-college academic preparation. The purpose of my research study involved utilizing first-year STEM majors’ math SAT scores, unweighted high school GPA, math placement test scores, and the highest level of math taken in high school to develop models for predicting those who were likely to pass their first math and science courses. In doing so, the study aimed to provide a strategy to address the challenge of improving the passing rates of those first-year students attempting STEM-related courses. The study sample included 1018 first-year STEM majors who had entered the same large, public, urban, Hispanic-serving, research university in the Southeastern U.S. between 2010 and 2012. The research design involved the use of hierarchical logistic regression to determine the significance of utilizing the four independent variables to develop models for predicting success in math and science. The resulting data indicated that the overall model of predictors (which included all four predictor variables) was statistically significant for predicting those students who passed their first math course and for predicting those students who passed their first science course. Individually, all four predictor variables were found to be statistically significant for predicting those who had passed math, with the unweighted high school GPA and the highest math taken in high school accounting for the largest amount of unique variance. Those two variables also improved the regression model’s percentage of correctly predicting that dependent variable. The only variable that was found to be statistically significant for predicting those who had passed science was the students’ unweighted high school GPA. Overall, the results of my study have been offered as my contribution to the literature on predicting first-year student success, especially within the STEM disciplines.
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Robbins, Bryan T. "COGNITIVE FACTORS IN PERSPECTIVE-BASED READING (PBR): A PROTOCOL ANALYSIS STUDY." MSSTATE, 2009. http://sun.library.msstate.edu/ETD-db/theses/available/etd-04032009-161814/.
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The following study applied the protocol analysis method from the field of cognitive science to the investigation of perspective-based reading (PBR), an individual reading technique used within software document inspections. Protocol analysis allows PBR to be understood within the broader context of human cognition by coding concurrent verbal reports collected from the subject during PBR task performance. A coding scheme is derived from relevant literature in cognitive psychology. Using a systematic literature review, several hypotheses from the software engineering literature regarding PBR performance are considered, and three are chosen for analysis. Based on correlational comparisons and frequency statistics, the merit of the proposed coding scheme is evaluated. The selected hypotheses are supported by the experiment. Lessons learned regarding the protocol analysis technique and its application to software engineering research are stressed, with an emphasis on future work.
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Li, Ji. "Efficient Distributed Rendezvous Schemes And Spectrum Management For Cognitive Radio Networks." Thesis, The University of North Carolina at Charlotte, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10266021.
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<p> Cognitive radio emerges as a technology to realize the dynamic spectrum access by dynamically configuring its transmission parameters. In a cognitive radio network (CRN), there are two types of users: primary users (PUs) and secondary users (SUs). PUs are the licensed users or the traditional wireless users who can access a specific licensed spectrum band. SUs are the unlicensed users equipped with cognitive radios that can opportunistically use currently unoccupied channels to transmit, but have to vacate channels for the returning PUs, and then switch to other available channels for continuous transmissions. When two SUs want to establish a link, they have to meet on the same channel that must be available for both of them simultaneously. This process is called <i>rendezvous.</i> </p><p> Past research works on rendezvous only focused on designing the channel hopping sequence for the rendezvous process while ignoring some practical problems like rendezvous in wide-band CRNs, rendezvous without a predetermined sender and receiver, rendezvous considering directional antennas, and how to maximize the number of common available channels. In this dissertation, we propose five schemes to realize efficient rendezvous and spectrum management considering these practical problems under different scenarios. We first propose a rendezvous and communication framework for wide-band CRNs. Furthermore, we propose two efficient rendezvous schemes without predetermined sender and receiver. Moreover, we propose a rendezvous scheme specifically for SUs equipped with directional antennas. Last, we propose a power control protocol to maximize the number of common available channels. All of the proposed schemes can realize both efficient rendezvous and spectrum management with practical assumptions under different scenarios.</p>
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Kamvysselis, Manolis 1977, and Ovidiu 1975 Marina. "Imagina : a cognitive abstraction approach to sketch-based image retrieval." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/16724.
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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.<br>Includes bibliographical references (leaves 151-157).<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>As digital media become more popular, corporations and individuals gather an increasingly large number of digital images. As a collection grows to more than a few hundred images, the need for search becomes crucial. This thesis is addressing the problem of retrieving from a small database a particular image previously seen by the user. This thesis combines current findings in cognitive science with the knowledge of previous image retrieval systems to present a novel approach to content based image retrieval and indexing. We focus on algorithms which abstract away information from images in the same terms that a viewer abstracts information from an image. The focus in Imagina is on the matching of regions, instead of the matching of global measures. Multiple representations, focusing on shape and color, are used for every region. The matches of individual regions are combined using a saliency metric that accounts for differences in the distributions of metrics. Region matching along with configuration determines the overall match between a query and an image.<br>by Manolis Kamvysselis and Ovidiu Marina.<br>S.B.and M.Eng.
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Vargas, Gregory G. "A cognitive categorization-based approach for understanding identity representation online." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/76994.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 99-100).<br>Computationally representing social identities using social networking profiles traditionally involves the reduction of identities to fit into simplistic categories such as "friends." In contrast, this thesis proposes that the data structures underlying user identities can be algorithmically processed and interpreted in ways that assist in understanding more nuanced aspects of identity such as "subculture" or"personality" Building upon an interdisciplinary computational identity model developed by Fox Harrell in his NSF-supported Advanced Identity Representation Project, this thesis proposes an algorithm based on theories of cognitive categorization[6, 7] to reveal implicit categories in computational identity systems. The algorithm has been applied to social networking site Facebook and a suite of graphical user interfaces was developed to enable users to explore individual and group identities. In a qualitative study, we found that most of the generated categories coherently represented social groups and would be useful for applications such as expressing the groups' collective identities.<br>by Gregory G. Vargas.<br>M.Eng.
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Arsenio, Artur Miguel Do Amaral 1972. "Cognitive-developmental learning for a humanoid robot : a caregiver's gift." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28716.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.<br>Includes bibliographical references (p. 319-341).<br>(cont.) which are then applied to developmentally acquire new object representations. The humanoid robot therefore sees the world through the caregiver's eyes. Building an artificial humanoid robot's brain, even at an infant's cognitive level, has been a long quest which still lies only in the realm of our imagination. Our efforts towards such a dimly imaginable task are developed according to two alternate and complementary views: cognitive and developmental.<br>The goal of this work is to build a cognitive system for the humanoid robot, Cog, that exploits human caregivers as catalysts to perceive and learn about actions, objects, scenes, people, and the robot itself. This thesis addresses a broad spectrum of machine learning problems across several categorization levels. Actions by embodied agents are used to automatically generate training data for the learning mechanisms, so that the robot develops categorization autonomously. Taking inspiration from the human brain, a framework of algorithms and methodologies was implemented to emulate different cognitive capabilities on the humanoid robot Cog. This framework is effectively applied to a collection of AI, computer vision, and signal processing problems. Cognitive capabilities of the humanoid robot are developmentally created, starting from infant-like abilities for detecting, segmenting, and recognizing percepts over multiple sensing modalities. Human caregivers provide a helping hand for communicating such information to the robot. This is done by actions that create meaningful events (by changing the world in which the robot is situated) thus inducing the "compliant perception" of objects from these human-robot interactions. Self-exploration of the world extends the robot's knowledge concerning object properties. This thesis argues for enculturating humanoid robots using infant development as a metaphor for building a humanoid robot's cognitive abilities. A human caregiver redesigns a humanoid's brain by teaching the humanoid robot as she would teach a child, using children's learning aids such as books, drawing boards, or other cognitive artifacts. Multi-modal object properties are learned using these tools and inserted into several recognition schemes,<br>by Artur Miguel Do Amaral Arsenio.<br>Ph.D.
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Sethi, Amita. "Potential denial of service threat assessment for cognitive radios." Connect to online resource, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1453572.
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Wells, Wilfred Henry. "Development of a cognitive work analysis framework tutorial using Systems Modeling Language." Doctoral diss., University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4720.
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At the present time, most systems engineers do not have access to cognitive work analysis information or training in terms they can understand. This may lead to a disregard of the cognitive aspect of system design. The impact of this issue is system requirements that do not account for the cognitive strengths and limitations of users. Systems engineers cannot design effective decision support systems without defining cognitive work requirements. In order to improve system requirements, integration of cognitive work requirements into the systems engineering process has to be improved. One option to address this gap is the development of a Cognitive Work Analysis (CWA) framework using Systems Modeling Language (SysML). The study had two phases. The first involved aligning the CWA terminology with the SysML to produce a CWA framework using SysML. The second was the creation of an instruction using SysML to inform systems engineers of the process of integrating cognitive work requirements into the systems engineering process. This methodology provides a structured framework to define, manage, organize, and model cognitive work requirements. Additionally, it provides a tool for systems engineers to use in system design which supports a user's cognitive functions, such as situational awareness, problem solving, and decision making.<br>ID: 030646182; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (Ph.D.)--University of Central Florida, 2011.; Includes bibliographical references (p. 243-255).<br>Ph.D.<br>Doctorate<br>Industrial Engineering and Management Systems<br>Engineering and Computer Science<br>Industrial Engineering
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Zhang, Tao. "Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks." Wright State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1364171144.
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Zhang, Xingjian. "Compressive spectrum sensing in cognitive IoT." Thesis, Queen Mary, University of London, 2018. http://qmro.qmul.ac.uk/xmlui/handle/123456789/44700.
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With the rising of new paradigms in wireless communications such as Internet of things (IoT), current static frequency allocation policy faces a primary challenge of spectrum scarcity, and thus encourages the IoT devices to have cognitive capabilities to access the underutilised spectrum in the temporal and spatial dimensions. Wideband spectrum sensing is one of the key functions to enable dynamic spectrum access, but entails a major implementation challenge in terms of sampling rate and computation cost since the sampling rate of analog-to-digital converters (ADCs) should be higher than twice of the spectrum bandwidth based on the Nyquist-Shannon sampling theorem. By exploiting the sparse nature of wideband spectrum, sub-Nyquist sampling and sparse signal recovery have shown potential capabilities in handling these problems, which are directly related to compressive sensing (CS) from the viewpoint of its origin. To invoke sub-Nyquist wideband spectrum sensing in IoT, blind signal acquisition with low-complexity sparse recovery is desirable on compact IoT devices. Moreover, with cooperation among distributed IoT devices, the complexity of sampling and reconstruc- tion can be further reduced with performance guarantee. Specifically, an adaptively- regularized iterative reweighted least squares (AR-IRLS) reconstruction algorithm is proposed to speed up the convergence of reconstruction with less number of iterations. Furthermore, a low-complexity compressive spectrum sensing algorithm is proposed to reduce computation complexity in each iteration of IRLS-based reconstruction algorithm, from cubic time to linear time. Besides, to transfer computation burden from the IoT devices to the core network, a joint iterative reweighted sparse recovery scheme with geo-location database is proposed to adopt the occupied channel information from geo- location database to reduce the complexity in the signal reconstruction. Since numerous IoT devices access or release the spectrum randomly, the sparsity levels of wideband spec-trum signals are varying and unknown. A blind CS-based sensing algorithm is proposed to enable the local secondary users (SUs) to adaptively adjust the sensing time or sam- pling rate without knowledge of spectral sparsity. Apart from the signal reconstruction at the back-end, a distributed sub-Nyquist sensing scheme is proposed by utilizing the surrounding IoT devices to jointly sample the spectrum based on the multi-coset sam- pling theory, in which only the minimum number of low-rate ADCs on the IoT devices are required to form coset samplers without the prior knowledge of the number of occu- pied channels and signal-to-noise ratios. The models of the proposed algorithms are derived and verified by numerical analyses and tested on both real-world and simulated TV white space signals.
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Sklivanitis, Georgios. "Software-Defined Architectures for Spectrally Efficient Cognitive Networking in Extreme Environments." Thesis, State University of New York at Buffalo, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10744705.
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<p> The objective of this dissertation is the design, development, and experimental evaluation of novel algorithms and reconfigurable radio architectures for spectrally efficient cognitive networking in terrestrial, airborne, and underwater environments. Next-generation wireless communication architectures and networking protocols that maximize spectrum utilization efficiency in congested/contested or low-spectral availability (extreme) communication environments can enable a rich body of applications with unprecedented societal impact. In recent years, underwater wireless networks have attracted significant attention for military and commercial applications including oceanographic data collection, disaster prevention, tactical surveillance, offshore exploration, and pollution monitoring. Unmanned aerial systems that are autonomously networked and fully mobile can assist humans in extreme or difficult-to-reach environments and provide cost-effective wireless connectivity for devices without infrastructure coverage. </p><p> Cognitive radio (CR) has emerged as a promising technology to maximize spectral efficiency in dynamically changing communication environments by adaptively reconfiguring radio communication parameters. At the same time, the fast developing technology of software-defined radio (SDR) platforms has enabled hardware realization of cognitive radio algorithms for opportunistic spectrum access. However, existing algorithmic designs and protocols for shared spectrum access do not effectively capture the interdependencies between radio parameters at the physical (PHY), medium-access control (MAC), and network (NET) layers of the network protocol stack. In addition, existing off-the-shelf radio platforms and SDR programmable architectures are far from fulfilling runtime adaptation and reconfiguration across PHY, MAC, and NET layers. Spectrum allocation in cognitive networks with multi-hop communication requirements depends on the location, network traffic load, and interference profile at each network node. As a result, the development and implementation of algorithms and cross-layer reconfigurable radio platforms that can jointly treat space, time, and frequency as a unified resource to be dynamically optimized according to inter- and intra-network interference constraints is of fundamental importance. </p><p> In the next chapters, we present novel algorithmic and software/hardware implementation developments toward the deployment of spectrally efficient terrestrial, airborne, and underwater wireless networks. In Chapter 1 we review the state-of-art in commercially available SDR platforms, describe their software and hardware capabilities, and classify them based on their ability to enable rapid prototyping and advance experimental research in wireless networks. Chapter 2 discusses system design and implementation details toward real-time evaluation of a software-radio platform for all-spectrum cognitive channelization in the presence of narrowband or wideband primary stations. All-spectrum channelization is achieved by designing maximum signal-to-interference-plus-noise ratio (SINR) waveforms that span the whole continuum of the device-accessible spectrum, while satisfying peak power and interference temperature (IT) constraints for the secondary and primary users, respectively. In Chapter 3, we introduce the concept of all-spectrum channelization based on max-SINR optimized sparse-binary waveforms, we propose optimal and suboptimal waveform design algorithms, and evaluate their SINR and bit-error-rate (BER) performance in an SDR testbed. Chapter 4 considers the problem of channel estimation with minimal pilot signaling in multi-cell multi-user multi-input multi-output (MIMO) systems with very large antenna arrays at the base station, and proposes a least-squares (LS)-type algorithm that iteratively extracts channel and data estimates from a short record of data measurements. Our algorithmic developments toward spectrally-efficient cognitive networking through joint optimization of channel access code-waveforms and routes in a multi-hop network are described in Chapter 5. Algorithmic designs are software optimized on heterogeneous multi-core general-purpose processor (GPP)-based SDR architectures by leveraging a novel software-radio framework that offers self-optimization and real-time adaptation capabilities at the PHY, MAC, and NET layers of the network protocol stack. Our system design approach is experimentally validated under realistic conditions in a large-scale hybrid ground-air testbed deployment. Chapter 6 reviews the state-of-art in software and hardware platforms for underwater wireless networking and proposes a software-defined acoustic modem prototype that enables (i) cognitive reconfiguration of PHY/MAC parameters, and (ii) cross-technology communication adaptation. The proposed modem design is evaluated in terms of effective communication data rate in both water tank and lake testbed setups. In Chapter 7, we present a novel receiver configuration for code-waveform-based multiple-access underwater communications. The proposed receiver is fully reconfigurable and executes (i) all-spectrum cognitive channelization, and (ii) combined synchronization, channel estimation, and demodulation. Experimental evaluation in terms of SINR and BER show that all-spectrum channelization is a powerful proposition for underwater communications. At the same time, the proposed receiver design can significantly enhance bandwidth utilization. Finally, in Chapter 8, we focus on challenging practical issues that arise in underwater acoustic sensor network setups where co-located multi-antenna sensor deployment is not feasible due to power, computation, and hardware limitations, and design, implement, and evaluate an underwater receiver structure that accounts for multiple carrier frequency and timing offsets in virtual (distributed) MIMO underwater systems.</p><p>
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McWhorter, Tanner Maxwell. "Cognitive Electronic Warfare System." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1595708553000249.
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Debroy, Saptarshi. "Spectrum Map and its Application in Cognitive Radio Networks." Doctoral diss., University of Central Florida, 2014. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6265.
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Recent measurements on radio spectrum usage have revealed the abundance of underutilized bands of spectrum that belong to licensed users. This necessitated the paradigm shift from static to dynamic spectrum access. Cognitive radio based secondary networks that utilize such unused spectrum holes in the licensed band, have been proposed as a possible solution to the spectrum crisis. The idea is to detect times when a particular licensed band is unused and use it for transmission without causing interference to the licensed user. We argue that prior knowledge about occupancy of such bands and the corresponding achievable performance metrics can potentially help secondary networks to devise effective strategies to improve utilization.
In this work, we use Shepard's method of interpolation to create a spectrum map that provides a spatial distribution of spectrum usage over a region of interest. It is achieved by intelligently fusing the spectrum usage reports shared by the secondary nodes at various locations. The obtained spectrum map is a continuous and differentiable 2-dimension distribution function in space. With the spectrum usage distribution known, we show how different radio spectrum and network performance metrics like channel capacity, secondary network throughput, spectral efficiency, and bit error rate can be estimated. We show the applicability of the spectrum map in solving the intra-cell channel allocation problem in
centralized cognitive radio networks, such as IEEE 802.22. We propose a channel allocation scheme where the base station allocates interference free channels to the consumer premise equipments (CPE) using the spectrum map that it creates by fusing the spectrum usage information shared by some CPEs. The most suitable CPEs for information sharing are chosen on a dynamic basis using an iterative clustering algorithm. Next, we present a contention based media access control (MAC) protocol for distributed cognitive radio network. The unlicensed secondary users contend among themselves over a common control channel. Winners of the contention get to access the available channels ensuring high utilization and minimum collision with primary incumbent. Last, we propose a multi-channel, multi-hop routing protocol with secondary transmission power control. The spectrum map, created and maintained by a set of sensors, acts as the basis of finding the best route for every source destination pair. The proposed routing protocol ensures primary receiver protection and maximizes achievable link capacity.
Through simulation experiments we show the correctness of the prediction model and how it can be used by secondary networks for strategic positioning of secondary transmitter-receiver pairs and selecting the best candidate channels. The simulation model mimics realistic distribution of TV stations for urban and non-urban areas. Results validate the nature and accuracy of estimation, prediction of performance metrics, and efficiency of the allocation process in an IEEE 802.22 network. Results for the proposed MAC protocol show high channel utilization with primary quality of service degradation within a tolerable limit. Performance evaluation of the proposed routing scheme reveals that it ensures primary receiver protection through secondary power control and maximizes route capacity.<br>Ph.D.<br>Doctorate<br>Electrical Engineering and Computing<br>Engineering and Computer Science<br>Computer Engineering
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Blom, Örjan. "Integrating Cognitive Science into Software Systems Development: Developing a User Interface for Fighter Control." Thesis, Linköping University, Department of Computer and Information Science, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2494.
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<p>The purpose of this thesis was to integrate cognitive science into an existing organization of software systems development, and to display the benefits and importance of applying the theory and methodology of this interdisciplinary field onto this type of research. This was to be accomplished through participating in a project at ISD Datasystem AB, with the objective to investigate and develop new principles of man - machine interaction for fighter control, and build an appropriate workstation prototype. The participation spanned across the first iteration of the project’s development cycle, specified in accordance to the Rational Unified Process. A field study was conducted and several LoFi-prototypes of the graphical and physical man - machine interface (MMI) were made, as well as an evaluation of the developed prototype. The evaluation was performed with the help of end-users, who valuated the prototype in an inquiry and an interview after having performed a scenario interacting with it. The results showed that the prototype’s usability was highly valuated by the users.Data collected during the evaluation could also be used to guide further development of the prototype. The theoretical research and the empirical work in the project both showed that cognitive science is a valuable, and perhaps, an indispensable asset to software systems development, and that the knowledge and tools of cognitive science can be used in order to develop computer systems that are to be integrated in distributed man -machine systems of high complexity.</p>
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Aviles, Walter Antonio. "The role of multimodal sensorimotor involvement in the learning of cognitive skills." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/40600.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.<br>Includes bibliographical references (leaves 24-26).<br>by Walter Antonio Aviles.<br>M.S.
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Zhong, Bo. "Cross-layer QoE improvement with dynamic spectrum allocation in OFDM-based cognitive radio." Thesis, Queen Mary, University of London, 2014. http://qmro.qmul.ac.uk/xmlui/handle/123456789/9103.
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Rapid development of devices and applications results in dramatic growth of wireless traffic, which leads to increasing demand on wireless spectrum resources. Current spectrum resource allocation policy causes low efficiency in licensed spectrum bands. Cognitive Radio techniques are a promising solution to the problem of spectrum scarcity and low spectrum utilisation. Especially, OFDM based Cognitive Radio has received much research interest due to its flexibility in enabling dynamic resource allocation. Extensive research has shown how to optimise Cognitive Radio networks in many ways, but there has been little consideration of the real-time packet level performance of the network. In such a situation, the Quality of Service metrics of the Secondary Network are difficult to guarantee due to fluctuating resource availability; nevertheless QoS metric evaluation is actually a very important factor for the success of Cognitive Radio. Quality of Experience is also gaining interest due to its focus on the users' perceived quality, and this opens up a new perspective on evaluating and improving wireless networks performance. The main contributions of this thesis include: it focuses on the real-time packet level QoS (packet delay and loss) performance of Cognitive Radio networks, and evaluates the effects on QoS of several typical non-configurable factors including secondary user service types, primary user activity patterns and user distance from base station. Furthermore, the evaluation results are unified and represented using QoE through existing mapping techniques. Based on the QoE evaluation, a novel cross layer RA scheme is proposed to dynamically compensate user experience, and this is shown to significantly improve QoE in scenarios where traditional RA schemes fail to provide good user experience.
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Maree, Marinda. "The role of self-efficacy in the careers of women in the field of Science Technology Engineering and Mathematics (STEM)." Thesis, University of Pretoria, 2017. http://hdl.handle.net/2263/62650.
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This study was undertaken to investigate the role of self-efficacy in the career trajectories of women who are currently employed in STEM fields and women who had studied in any of these fields, but either never worked in STEM, or decided to leave at some stage. The assumption was that women remain in STEM careers because of the motivational effect of STEM self-efficacy. In order to do this investigation, two studies were included in a parallel convergent mixed-methods design and two samples were studied. The first sample of 15 women, which included both women in STEM (n = 8) and women who had left STEM (n = 7), were interviewed and invited to talk about their STEM studies and careers. The interviews were conducted according to a semi-structured interview. The second sample, which consisted of 108 participants of whom 88 were actively involved in STEM and 20 had left the field, completed an online survey that contained a biographical section, three self-efficacy scales and an Exploratory Questionnaire (EQ) that covered aspects such as motivation to study and work in STEM and barriers experienced. The three self-efficacy scales used were the General Self-Efficacy Scale (GSES), the New General Self-Efficacy Scale (NGSES) and the Occupational Self-Efficacy Scale (OSES). Bandura's Social Cognitive Theory (SCT) was chosen as the conceptual framework for the study and the development of Social Cognitive Career Theory (SCCT) was described from its inception to its current integrated models of career development, as applied to women in STEM careers. The integrated models show that a combination of self-efficacy and outcome expectations is crucial as a predictor of career success in the STEM fields, which can also be influenced by additional variables, such as career decision making, career and study satisfaction, persistence, contextual support and barriers. The Social Cognitive Theory (SCT) and Social Cognitive Career Theory (SCCT) provided the theoretical framework for themes for the qualitative thematic analysis. A top-down identification of themes was done by using the transcripts of interviews. Self-efficacy, outcome expectations and barriers were among the twelve themes that were identified. The survey data was described and statistically analysed. Descriptive statistics were provided for the selfefficacy scales and biographical information. The STEM and non-STEM groups were compared with a series of contingency tables on biographical information. A t-test was used to compare the self-efficacy scales by STEM status in order to find significant differences. The EQ was subjected to an exploratory principal component analysis (PCA) and 10 factors or components were identified. The factors ranged from motivation, barriers and perceptions about gender to STEM and education. Finally, the factors were compared with the qualitative themes to explore the role of self-efficacy in the careers of STEM and non-STEM women. The contribution made by this study is that it highlights the importance of the sources of selfefficacy in ensuring that women remain in their chosen fields. A frequently under-emphasised aspect is that of the emotional source of self-efficacy, which this study found to be the passion, focus, enjoyment and satisfaction that motivate women to remain in STEM. The relevant literature frequently observes that girls and women do not like STEM subjects and activities. However, the passion and commitment of women witnessed by the researcher while conducting this study counters this observation. Some women do enjoy science and it is by no means a proven fact that a lack of interest in STEM is gendered. Programmes focusing on motivating women to enter and remain in STEM ought to take this particular source of selfefficacy into account. The question is, of course, whether one can create interest, instil passion and make STEM attractive to women. However, this is a separate topic for further study. One of the clear findings of this study relates to the importance of inner-circle support and motivation to enter and remain in STEM. Programmes should find a way to encourage families who are already involved in STEM to include children, and especially girls. The very personal nature of encouragement, motivation and support received from parents and close family members function as a major source of self-efficacy. This calls for a creative approach to motivational programmes in order to make commitment to STEM inclusive. Another point that was emphasised by women in the qualitative sample, as well as in the quantitative results, was the major importance of personal interest in the field of science. In fact, this was even more important than the motivational support provided by close family. In essence, it relates to the passion expressed by women in STEM, but the importance of developing a strong interest in science cannot be overstated. Finally, several of the respondents working either in or outside STEM mentioned the pressures experienced in an attempt to balance family and work responsibilities. Some women manage this successfully, even though they are in STEM careers, while others deal with the problem by leaving STEM. However, one should point out that even in non-STEM careers the pressures and expectations of family life and children exist. Programmes dealing with women in STEM should take this problem very seriously and should assist women in effectively managing and dealing with the combined pressures of family and work.<br>Thesis (PhD)--University of Pretoria, 2017.<br>Psychology<br>PhD<br>Unrestricted
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Timmerman, Kathleen. "Educational Methods for Inverted-lecture Computer Science and Engineering Classrooms to Overcome Common Barriers to STEM Student Success." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1482406667753693.
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Souillard-Mandar, William. "Learning classification models of cognitive conditions from subtle behaviors in the digital Clock Drawing Test." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100623.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 91-95).<br>The Clock Drawing Test -- a simple pencil and paper test -- has been used for more than 50 years as a screening tool to differentiate normal elderly individuals from those with cognitive impairment, and has proven useful in helping to diagnose dementias, such as Alzheimer's disease, Parkinson's disease, and other conditions. A group of hospitals and clinics have been administering the test using a digitizing ballpoint pen that reports its position with considerable spatial and temporal precision, making available far more detailed data about the subject's performance. Using categorized stroke data from these drawings, we designed and computed a large collection of features, then explored the tradeoffs in performance and interpretability in classifiers built using a number of different subsets of these features and a variety of different machine learning techniques. We used traditional machine learning methods to build prediction models that achieve high accuracy. We operationalized widely used existing scoring algorithms so that we could use them as benchmarks for our models. We worked with clinicians to define guidelines for model interpretability, and constructed sparse linear models and decision lists designed to be as easy to use as scoring algorithms currently used by clinicians, but more accurate. We also extract insights from the data about the behavioral aspect of these conditions on patients. While our models will require additional testing with subjects for validation, they offer the possibility of substantial improvement in detecting cognitive impairment earlier than currently possible, a development with considerable potential impact in practice.<br>by William Souillard-Mandar.<br>M. Eng.
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Rein, Harry A. "Hive thinking : a theory on the evolution of cognitive specialization and applications to digital marketing." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106107.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>Cataloged from PDF version of thesis.<br>The purpose of this work is to put forward a theory of the evolution of cognitive specialization and demonstrate its significance towards the future development of human and computer interaction by demonstrating it in a modern context. For millennia, great minds have wrestled to build a typing model to classify the differences in human behavior. Recent theories have driven towards a theory of four functional abilities of the mind coming in two attitudes that drive asymmetrical development resulting in cognitive types, or personalities. Modern digital systems currently have rudimentary models of human cognition, it is this document's belief that by encoding a typing model our systems will begin to understand and act in a manner more similar to human behavior. The theoretical, more human extension of this work is to observe the evolution of a single 'hive consciousness' - a collection of individual minds acting as a single sustaining entity - with the underlying belief that it is the development of an optimal hive structure, not the development of an optimal individual mind, that results in the emergent seemingly specialized cognitive styles. The grounded, implementation based extension of this work is to demonstrate in a simple web-based digital marketing implementation - a system that can drive user actions, monitor those actions as to create an understanding of that particular user's cognitive type, and finally adapt it's contents as to optimally convince the user to consider a purchase decision.<br>by Harry A. Rein.<br>M. Eng.
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Jang, Esther (Esther Han Beol). "Characterization and performance analysis of a cognitive routing scheme for a metropolitan-area sensor network." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106121.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 47-48).<br>This MEng thesis is an exploration of the notion of cognitive methods for routing in a network, and the resulting potential for improvements in network performance. In cognitive routing, individual network nodes gain information about the state of the network in a distributed fashion, by measuring observable data such as packet arrival counts and timing. The nodes then use inference and estimation methods on the network traffic to modify the parameters of their routing protocols and/or routing tables, in order to improve some performance metric such as packet delay or network throughput. In this project we provide an example of the performance improvements possible through cognitive routing, by demonstrating a simple but nontrivial use of network measurement and inference to minimize the maximum average packet delay, and increase the max load that the network can handle. With more information-rich metrics that are available to be passively gathered by a routing protocol, such as source-destination IDs, the sizes of packets passing through a node, and packet loss rates, cognitive routing protocols may be able to predict congestion or link failures, potentially leading to much greater efficiency gains than are described in this project.<br>by Esther Jang.<br>M. Eng.
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Felix, Allison. "Design Based Science and Higher Order Thinking." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/71746.
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Technological/engineering design based learning (T/E DBL) provides a context in which students may utilize content knowledge and skills to develop prototype solutions to real-world problems. In science education, design based science (DBS) utilizes technological/engineering design based approaches in science education as a means for enhancing the purpose of and relevance for scientific inquiry by contextualizing it within the goal of developing a solution to a real-world problem. This study addressed the need to investigate the ways in which students utilize higher order thinking skills, demonstrated through the use of knowledge associated with declarative, schematic, and strategic cognitive demand when in engaged in DBS activities.
The purpose of this study was to determine what relationships exist between engagement in DBS and changes in students' depth of understanding of the science concepts associated with the development of design solutions. Specifically, the study determined how students' abilities to demonstrate an understanding of the science concepts, required by assessments of different cognitive demand, change as they were engaged in a design-based science unit associated with heat transfer. Utilizing two assessment instruments, a pre/post-1/post-2 test and content analysis of student design portfolios based on Wells (2012) and utilizing Li's (2001) system to code student responses, the following research question was addressed: What changes in students' science concept knowledge (declarative, schematic, and strategic demand) are evidenced following engagement in design based learning activities?
Although the results are not generalizable to other populations due to the limitations associated with the study, it can be concluded that design based learning activities incorporated in science courses can foster higher order thinking. Results from the study suggests that students' abilities to demonstrate their understanding of certain science concepts through higher order thinking, including utilizing concept knowledge strategically in open-ended problem solving, increased following engagement in design based learn activities. Results have implications in technological/engineering design education, in science education, and in integrative STEM education. Implications include the utility of design portfolios as both an assessment instrument and learning tool to ensure that concept knowledge is explicitly connected to and used in the design activity.<br>Ed. D.
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Atahary, Tanvir. "Acceleration of Cognitive Domain Ontologies." University of Dayton / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1460734067.
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Jahncke, Helena. "Cognitive performance and restoration in open-plan office noise." Doctoral thesis, Luleå tekniska universitet, Arbetsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-18374.
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This dissertation presents four experimental studies (in four papers) with the overall aim to investigate the effects of office noise on cognitive performance and restoration. In the first two papers the focus was on the effects of different sound levels (i.e., the mean level from all sound sources at an office, such as speech, phones, people walking) on performance, fatigue and stress. In the last two papers the focus was on the effects of background speech, as this has previously been shown to be the most disturbing noise source in open-plan offices. Paper I demonstrated decreased word memory performance, increased fatigue and motivational deficits when the background sound level increased by 12 dB, from 39 to 51 dB LAeq. Paper II showed that the sound level effects were more pronounced for individuals with a hearing impairment. Unexpectedly, no effects were found of acute noise exposure on the participant´s stress hormone levels (Paper I and Paper II).Regarding effects of irrelevant speech, Paper III showed that cognitive performance decreased as a function of background speech intelligibility, the higher the intelligibility depicted by the Speech Transmission Index (STI), the worse the performance. The results indicated that the STI-value must be less than 0.50, to avoid a negative influence on performance. Further, both Paper III and IV showed that performance is more impaired by background speech if the focal task requires episodic memory and rehearsal—such as word memory and information search. Interestingly, some tasks were insensitive for speech.The restorative effects of a break were addressed in Paper I and II (i.e., directly after the work sessions in noise). The break period differed in content between the participants. Paper I showed that a break with a nature movie with corresponding sound increased energy ratings compared to just listening to river sounds or office noise. Continued exposure to office noise gave the lowest ratings of motivation after the break. Paper II showed improved arithmetic performance and motivation after the break with a nature movie and decreased performance and motivation after continued noise exposure. For the hearing impaired participants, however, continued noise during the break increased motivation and performance, while the movie did not.Taken together, the current thesis demonstrates that open-plan office noise can have a negative impact on fatigue, motivation and performance. How much performance is impaired varies with the cognitive processes required by the tasks performed and hearing status. Moreover, continued noise exposure during a short break can further decrease motivation and subsequent performance.<br><p>Godkänd; 2012; 20120831 (heljah); DISPUTATION Ämne: Teknisk psykologi/Engineering Psychology Opponent: Docent Mats Nilsson, Psykologiska institutionen, Stockholms universitet Ordförande: Professor Håkan Alm, Institutionen för ekonomi, teknik och samhälle, Luleå tekniska universitet Tid: Fredag den 23 november 2012, kl 10.30 Plats: F719J, Luleå tekniska universitet</p>
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Ljung, Robert. "Room acoustics and cognitive load when listening to speech." Doctoral thesis, Luleå tekniska universitet, Arbetsvetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-18057.
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The present thesis investigated the effects of background noise or a long reverberation time in learning situations. All studies used spoken texts that were presented above the speech intelligibility threshold, but were degraded enough to make listening more effortful. The basic hypothesis for the whole project was that listening to speech in a bad acoustic environment should increase the cognitive load for the listener, which should impair memory of the text. In Paper I the auditory stimuli were lists of words and sentences that were degraded by a background noise. Paper II was a replication of the experiment from paper I, but the independent variable was changed from the level of the background noise to reverberation time. Paper III included two experiments where the stimulus material was 10 minutes lectures.Paper IV included two studies. The first experiment investigated whether serial recall performance is affected when words are presented in long reverberation time (Exp 1a). In experiment 1b word lists were presented in long or short reverberation time or with a background noise. The stimuli were recorded in one classroom with extremely good and one with very bad acoustic design. In experiment 2 word lists with many or few phonological neighbours were presented with long or short reverberation time. In all studies some measure of working memory capacity was included. Taken together, the overall results could be summarized in two sentences: Hearing what is said is a necessary but not a sufficient criterion for people to remember what is said, which means that spoken information should be heard without special effort, otherwise proper learning is jeopardized. No consistent relation was found between working memory capacity and the learning effect in the unfavorable listening conditions.<br><p>Godkänd; 2010; 20100416 (roblju); DISPUTATION Ämnesområde: Teknisk psykologi/Engineering Psychology Opponent: Docent Mats E. Nilsson, Stockholms universitet Ordförande: Professor Håkan Alm, Luleå tekniska universitet Tid: Torsdag den 3 juni 2010, kl 14.00 Plats: F 436, Luleå tekniska universitet</p>
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Qin, Zhijin. "Compressive sensing over TV white space in wideband cognitive radio." Thesis, Queen Mary, University of London, 2016. http://qmro.qmul.ac.uk/xmlui/handle/123456789/24244.
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Spectrum scarcity is an important challenge faced by high-speed wireless communications. Meanwhile, caused by current spectrum assignment policy, a large portion of spectrum is underutilized. Motivated by this, cognitive radio (CR) has emerged as one of the most promising candidate solutions to improve spectrum utilization, by allowing secondary users (SUs) to opportunistically access the temporarily unused spectrum, without introducing harmful interference to primary users. Moreover, opening of TV white space (TVWS) gives us the con dence to enable CR for TVWS spectrum. A crucial requirement in CR networks (CRNs) is wideband spectrum sensing, in which SUs should detect spectral opportunities across a wide frequency range. However, wideband spectrum sensing could lead to una ordably high sampling rates at energy-constrained SUs. Compressive sensing (CS) was developed to overcome this issue, which enables sub-Nyquist sampling by exploiting sparse property. As the spectrum utilization is low, spectral signals exhibit a natural sparsity in frequency domain, which motivates the promising application of CS in wideband CRNs. This thesis proposes several e ective algorithms for invoking CS in wideband CRNs. Speci cally, a robust compressive spectrum sensing algorithm is proposed for reducing computational complexity of signal recovery. Additionally, a low-complexity algorithm is designed, in which original signals are recovered with fewer measurements, as geolocation database is invoked to provide prior information. Moreover, security enhancement issue of CRNs is addressed by proposing a malicious user detection algorithm, in which data corrupted by malicious users are removed during the process of matrix completion (MC). One key spotlight feature of this thesis is that both real-world signals and simulated signals over TVWS are invoked for evaluating network performance. Besides invoking CS and MC to reduce energy consumption, each SU is supposed to harvest energy from radio frequency. The proposed algorithm is capable of o ering higher throughput by performing signal recovery at a remote fusion center.
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Roy, Arnab. "Evolving spike neural network based spatio-temporal pattern classifiers with an application to identifying the alcoholic brain." Thesis, State University of New York at Binghamton, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3630956.
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<p> We introduce a novel approach to evolving spike neural network (SNN) based Spatio-temporal (ST) pattern classifiers that can detect occurrences of hidden structures in a ST data. We test this learning paradigm to find characteristic electrical patterns in visually evoked response potentials (VERPs) generated by an alcoholic brain. </p><p> We cast the alcoholic classification task as a multiple feature selection (FS) problem. The FS problems are grouped under 2 classes: the spatial task and the temporal task. The objective of the spatial FS task is to choose a correct subset of electroencephalogram (EEG) leads (the spatial-features) along with the lead-weighs (numeric attributes) using which a composite signal can be created. The temporal FS task involves detecting temporal patterns that occur more frequently in the alcoholic composite signals than in the control signals. To facilitate the evolution of such a classifier, we introduce design rules for SNN based temporal pattern detectors (TPDs) and novel crossover operators for the simultaneous FS task. </p><p> The conventional techniques for characterizing the alcoholic VERPs use the information in the gamma-band (30 to 50 Hz) to develop a set of feature vectors and then train a classifier using these feature vectors. Using the SNN based evolutionary learning paradigm we were able to solve this problem in 1 step; the SNN performed both temporal feature extraction and classification. Unlike the conventional techniques we did not make any specific assumptions regarding the spectral characteristics of the data; we did not implement a gamma-band filter. Also, we located regions on the skull of an alcoholic subject that produced abnormal electrical activity compared to the controls. These regions are consistent with prior findings in the literature. The classification accuracy was measured as the area under the receiver operator characteristic curve (ROC). The area under the ROC curve for the training set varied from 90.32% to 98.83% and for the testing set it varied from 87.17% to 95.9%.</p>
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Mitra, Paromita. "Human Systems Integration of an Extravehicular Activity Space Suit Augmented Reality Display System." Thesis, Mississippi State University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10843754.
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<p> During an extravehicular activity (EVA), the role of an astronaut involves a multitude of complex tasks. Whether that task is a science experiment aboard the International Space Station, or traversing extraterrestrial terrain – attention, communication, and instruction are essential. As an aid, augmented reality (AR) can portray suit informatics and procedures within line-of-sight while minimizing attentional loss. Currently, there exists little research highlighting the human systems considerations to qualify AR systems for space suit applications. This study quantifies user interface (UI) and human performance measures for an AR prototype on the Mark III space suit. For user testing, 21 military pilots and personnel (11 men, 10 women) evaluated UI search tasks and completed a series of AR-instructed EVA dexterity tasks in an elevated luminosity, background clutter, and workload scenario. UI results suggest correlations for readability and usability; whereas, human performance results provide situational awareness, workload, and task performance data.</p><p>
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Braunschweig, Brandt Benedict. "Measuring shared understanding in software design teams." Thesis, University of Maryland, Baltimore County, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10118999.
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<p> <b>Background:</b> Software engineering teams must have a shared understanding of the system design in order to work independently but successfully integrate their code. These issues of understanding are important to project success but difficult to investigate with current approaches. Current techniques for investigating shared understanding, such as interviews or questionnaires, are limited by the difficulty of team members to externalize knowledge relevant to shared understanding. </p><p> <b>Aims:</b> This research has two goals. The first goal is to identify and validate a measure of shared understanding that researchers can use to investigate issues of shared understanding in software design. The second goal is to evaluate the potential for this measure to be used by practitioners to improve the software design process. </p><p> <b>Method:</b> A measure of shared understanding was developed by adapting an approach from the Team Mental Models literature. Five student teams and two industrial teams were recruited to evaluate the measure empirically. The validity of the measure, the significance of the differences in understanding found, and the applicability for design process improvement were investigated using qualitative techniques, including group interviews, observation, and questionnaires. </p><p> <b>Results:</b> When ranked by the measure of shared understanding, high ranking design concepts were generally, but not consistently, found to be associated with greater similarity of understanding than low ranking concepts. This supports a finding that the measure is valid, but imprecise. Although no specific misunderstandings were identified within the team, some team members found the discussion, guided by the measured differences, valuable for improving shared understanding generally. </p><p> <b>Conclusions:</b> The results support the use of the measure as a tool to investigate shared understanding so long as consideration is given to its limitations. It is premature for practitioners to use the measure to improve the design process. The results are based on only two industrial teams without a history of failures related to shared understanding. Future research should re-evaluate the measurement in different contexts. Guidance is given for additional research to refine the measurement.</p>
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Nickles, George McLeland. "Work Action Analysis to Structure Planning and Formative Evaluation of an Engineering Course Using a Course Management System." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4795.
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Cognitive engineering, by identifying behavior-shaping constraints, provides methods for design and evaluation of complex socio-technical systems. However, traditional methods examine only one type of constraint, either cognitive or environmental. In learning service systems such as education, both cognitive and environmental constraints must be examined together. Improved methods of planning and formative evaluation are needed for engineering education and other learning service systems. Therefore, this dissertation develops a new cognitive engineering method, Work Action Analysis (WAA), that is able to capture cognitive and environmental constraints in a single model. The WAA model represents a learning service system on three dimensions: means-end decomposition, parts-whole decomposition, and roles of cognitive agents. WAA also provides methods for developing and using this model in planning and formative evaluation. The WAA method for planning evaluation explicitly represents the evaluators mental model of a learning service system and examines its alignment to guide its design. The WAA method for formative evaluation then takes the WAA model and interprets evaluation measures in the context of the model. As a demonstration, the methods for planning and formative evaluation are applied to a portion of an undergraduate engineering course. To provide measures for formative evaluation of a course, a centralized evaluation component that collects performance, perception, and process measures was added to an Internet-based course management system. The WAA methods provide insights to the design and operation of this learning service system, including recommendations that could be implemented during instruction. The theoretical implications of the WAA model of learning service systems, and further extensions of WAA, are also discussed.
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Anders, Shilo H. "Projecting trajectories of functional use for a new technology the electronic ICU /." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1213369071.
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Fiorella, C. L. "Text versus verbal real-time feedback during simulation-based training of higher-order cognitive skills." Master's thesis, University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4659.
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A crucial component of instructional design for simulation-based training systems involves optimizing the presentation of complex material in order to maximize knowledge acquisition and application. One approach toward facilitating the learning of this complex information is to instantiate instructional strategies within the training systems themselves. However, there are few established guidelines in place which are meant specifically for real-time guidance strategies within simulation-based environments. Consequently, this study aims to apply findings from the literature on instructional information presentation to drive decisions for how to most effectively provide real-time feedback during training of simulated decision-making tasks. Research has shown that presenting text information in an auditory mode during direct instruction of operational tasks enhances learning and reduces the probability of learners experiencing cognitive overload. Similar effects have been found regarding the presentation modality of feedback during operational tasks. In the current study, this principle was extended by comparing text versus verbal real-time feedback presentation during learning of higher-level cognitive skills in a virtual environment. Participants were instructed on how to perform a simulated decision-making task, while receiving text, verbal or no instructional feedback in real-time, based on their performance. Participants then completed an assessment scenario in which no feedback was provided to any group. It was hypothesized that a linear relationship would exist across each of the three conditions, with the verbal group making the best decisions, followed by the text group, and then by the control group. Additionally, reduced cognitive load was expected throughout the instructional process for those receiving verbal feedback prompts compared to those receiving text prompts and the control.; Analyses revealed several significant linear trends across conditions regarding measures of knowledge acquisition and application. The results provide support for the hypothesis that verbal real-time feedback is more effective than text during training of primarily visual tasks for the acquisition of higher-order cognitive skills such as decision making. There were no significant linear trends regarding the amount of cognitive load subjectively reported during training and assessment. The results of this study indicate that instructional systems intended to train primarily visual tasks should present real-time feedback in verbal rather than text form.<br>ID: 029050250; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (M.S.)--University of Central Florida, 2010.; Includes bibliographical references (p. 57-64).<br>M.S.<br>Masters<br>Engineering
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Farokhian, Suzana. "Human-computer interaction using eye-gaze : Formation of user interface design guidelines from a cognitive science perspective." Thesis, Södertörns högskola, Medieteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-38506.
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Motor and communication disabilities are common conditions that may implicate restrictions in daily life. With development of eye tracking technology, a solution referred to as eye-gaze interaction has been generated to support people with their limiting conditions to solve communication and computer access issues. By using eye tracking technology, which calculates the user’s eye-gaze location on a computer screen, user’s are able to control computers with their eyes as an input. This interaction method is quite unique and complex since the eyes serves both as an input and output source. Usability aspects revolving human information processing are therefore important to consider when designing user interfaces. In collaboration with Tobii AB, the study evaluated two separate eye-gaze interaction systems for controlling computers. 7 participants conducted user tests, one for each application, and answered interview questions during the tests regarding their usability experience. Based on the collected data,17 design guidelines was established with a purpose to enhance usability for eye-gaze interaction systems.
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Graham, James T. "Development of Functional Requirements for Cognitive Motivated Machines." Ohio University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1455711952.
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Rusnock, Christina. "Simulation-Based Cognitive Workload Modeling and Evaluation of Adaptive Automation Invoking and Revoking Strategies." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5857.
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In human-computer systems, such as supervisory control systems, large volumes of incoming and complex information can degrade overall system performance. Strategically integrating automation to offload tasks from the operator has been shown to increase not only human performance but also operator efficiency and safety. However, increased automation allows for increased task complexity, which can lead to high cognitive workload and degradation of situational awareness. Adaptive automation is one potential solution to resolve these issues, while maintaining the benefits of traditional automation. Adaptive automation occurs dynamically, with the quantity of automated tasks changing in real-time to meet performance or workload goals. While numerous studies evaluate the relative performance of manual and adaptive systems, little attention has focused on the implications of selecting particular invoking or revoking strategies for adaptive automation. Thus, evaluations of adaptive systems tend to focus on the relative performance among multiple systems rather than the relative performance within a system. This study takes an intra-system approach specifically evaluating the relationship between cognitive workload and situational awareness that occurs when selecting a particular invoking-revoking strategy for an adaptive system. The case scenario is a human supervisory control situation that involves a system operator who receives and interprets intelligence outputs from multiple unmanned assets, and then identifies and reports potential threats and changes in the environment. In order to investigate this relationship between workload and situational awareness, discrete event simulation (DES) is used. DES is a standard technique in the analysis of systems, and the advantage of using DES to explore this relationship is that it can represent a human-computer system as the state of the system evolves over time. Furthermore, and most importantly, a well-designed DES model can represent the human operators, the tasks to be performed, and the cognitive demands placed on the operators. In addition to evaluating the cognitive workload to situational awareness tradeoff, this research demonstrates that DES can quite effectively model and predict human cognitive workload, specifically for system evaluation. This research finds that the predicted workload of the DES models highly correlates with well-established subjective measures and is more predictive of cognitive workload than numerous physiological measures. This research then uses the validated DES models to explore and predict the cognitive workload impacts of adaptive automation through various invoking and revoking strategies. The study provides insights into the workload-situational awareness tradeoffs that occur when selecting particular invoking and revoking strategies. First, in order to establish an appropriate target workload range, it is necessary to account for both performance goals and the portion of the workload-performance curve for the task in question. Second, establishing an invoking threshold may require a tradeoff between workload and situational awareness, which is influenced by the task's location on the workload-situational awareness continuum. Finally, this study finds that revoking strategies differ in their ability to achieve workload and situational awareness goals. For the case scenario examined, revoking strategies based on duration are best suited to improve workload, while revoking strategies based on revoking thresholds are better for maintaining situational awareness.<br>Ph.D.<br>Doctorate<br>Industrial Engineering and Management Systems<br>Engineering and Computer Science<br>Industrial Engineering
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Pan, Yan. "A cognitive ergonomic approach for user code design : from PIN-code to face." Licentiate thesis, Luleå tekniska universitet, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-26549.
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The overall goal the research upon which this thesis is based concerns the development of personal security coding that is superior to today's systems that use digit-based codes. In exploring alternate coding strategies, emphasis has been on identification of methods/systems that are more user-friendly. Within populations such as the elderly and disabled, there are groups that experience considerable difficulty when using today's personal identification systems. Speed of movement and rapidity of recall are some of the challenges faced by these two groups that the line of research reported in the thesis seeks to address. Four studies and a narrative summary are contained in the thesis. The four studies report on the following: Study I. The aim of the study was to gather empirical data on the use of code focusing among disabled persons. It was conducted during the exploratory phase of a larger research program dealing with security and memory aspects on codes used in different contexts. Study II. The study purpose is to compare how well people remember two types of codes: picture codes and number codes. Study III. The main objective of this study was to test whether the residential experience in an other-race country effects face recognition performance. Study IV. In this paper the processes of usability evaluation of codes that are based on portraits of human faces is described.<br>Godkänd; 2001; 20070314 (ysko)
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Bram, Staffan. "Everybody's Business? : A Qualitative Assessment of Safety Culture at SSAB EMEA." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-75429.
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Many modern-day industries share features of tight coupling and high complexity, making it difficult to describe incidents in terms of direct attribution. This situation has been answered by novel theories on the bonds between people and their environment. Cognitive Systems Engineering (CSE) offers a new way of analysing human activities, acknowledging the impact of complex interaction and unpredictability. Doing so allows for innovative ways of pursuing work safety. In this study, the concept of safety culture has been interpreted from a CSE perspective and applied in a qualitative assessment of current safety work of at SSAB EMEA. A total number of 26 SSAB employees were interviewed, probing attitudes, perceptions and safety system structures at the Oxelösund steel mill, rolling mill and upper organizational layers. Additional data was collected using informers, SSAB documentation and participatory observation. Data was processed using a combination of top-down and bottom-up analytical approaches, creating a qualitative assessment of safety culture from salient themes. Results reveal an advanced state of safety management. However, management’s intentions are inhibited by issues in management presence and communication, management training, worker influence, forms and content of operator training, reporting, feedback, flow of communication and safety-related core assumptions. Revisiting lessons learned within the field of CSE, suggestions are made to possible areas of improvement and future research. These suggestions concern employee involvement in safety work, work identities, forms of training, manager roles and communication.
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Carr, Bruce Henry Ph D. "Examining the Relationship of Ethnicity, Gender and Social Cognitive Factors with the Academic Achievement of First-year Engineering Students." University of Dayton / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1343941032.
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