Relevant bibliographies by topics / User Behavioral Analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'User Behavioral Analysis'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "User Behavioral Analysis"

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Xia, Chunyan. "Research on User Interface Design of Home Appliances Based on Behavioural Logic." SHS Web of Conferences 152 (2023): 05003. http://dx.doi.org/10.1051/shsconf/202315205003.

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It is to solve the usability problem of user interface of home appliances under the development trend of home appliance automation, informatization and multi-function through the design of home appliance user interface dominated by user behavioral logic. It uses the methods of comparative analysis and empirical analysis, and it's distilled and compared the main difference between behavioral logic-based user interface and the functional logic-based user interface of home appliances, and then it summarizes and analyzes the main characteristics and advantages of behavioural logic-based user interface. The design ideas of behavioral logic-based user interface based on design psychology and other theories are provided, including that the behavioural logic-based user interface design of home appliances should be based on the user's mental model, and the user's cognitive experience of the task scene and its elements of decision-making process should be extracted, and the user interface should be organized according to the information of common operation scenes and the operation paths, and so on.
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Wang, Yaoxuan. "Research on User Profile and User Behavior of Integrating Big Data Platforms." Transactions on Economics, Business and Management Research 8 (August 8, 2024): 446–54. http://dx.doi.org/10.62051/3a6dex21.

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This paper discusses the construction and analysis method of user behavioral portrait by the data provided by the electric power platform in the big data environment. Firstly, it introduces the construction and analysis of user profiles based on big data platforms, which covers the construction of user basic attribute profiles, user behavioral characteristics profiles, user product characteristics profiles and user interaction characteristics profiles from different dimensions. Secondly, for the electric power sector, the article discusses the analysis of big data provided by electric power platforms to better understand user behavior and trends in energy consumption. The article proposes a method for constructing a behavioral portrait of power users based on big data analysis, including the construction and management of a user label library and the process of constructing a behavioral portrait of power users based on the improved K-mean algorithm. Finally, the effectiveness and accuracy of the method of this paper are verified by experimental analysis. Overall, this paper provides some guidance and reference for the analysis of user behavior in the field of electric power by exploring the method of user behavior portrait construction with the data provided by the electric power platform in the big data environment.
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Hidayah, Nur Aeni, Meinarini Catur Utami, and Irfan Nur Rizki. "Behavioral Intentions of Generation Z and Millennial Users of Telemedicine: A UTAUT 2 Analysis from the Halodoc User Perspective." Journal of Information Systems and Informatics 6, no. 3 (2024): 1373–99. http://dx.doi.org/10.51519/journalisi.v6i3.786.

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The rapid development of telemedicine has significantly transformed health services, leveraging technological sophistication to enhance medical consultations and treatments. Halodoc, a leading telemedicine application, has positively impacted the health sector. However, user reviews on the Google Play Store indicate issues that may affect user satisfaction and behavioral intention. Despite Millennials and Generation Z being major digital platform users, Generation X reports the highest satisfaction with telemedicine services. This study aims to validate the factors influencing and interrelating user satisfaction and behavioral intention in using the Halodoc application. Employing a quantitative approach with PLS-SEM data analysis, the study integrates the UTAUT 2 model with the Delone & McLean model. The results reveal that out of eight hypotheses, seven are supported, with Effort Expectancy on User Satisfaction being the only rejected hypothesis. The findings highlight that User Satisfaction significantly influences Behavioral Intention, underscoring the importance of enhancing user experience to improve telemedicine adoption.
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Qiao, Yu, Kaixian Xu, and Alan Wilson. "Real-Time Personalized Ad Recommendation Based on User Behavioral Analysis." Artificial Intelligence Advances 7, no. 1 (2025): 10–21. https://doi.org/10.30564/aia.v7i1.9761.

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Real-time personalized ad recommendation systems are crucial for enhancing user engagement and satisfaction. To address the challenge of delivering highly relevant ads in a dynamic, large-scale environment, this paper proposes a novel approach that integrates real-time user behavior analysis with advanced time series modeling and stream processing techniques. Specifically, the system leverages Long Short-Term Memory (LSTM) networks to capture both short-term and long-term user preferences, ensuring accurate and personalized ad recommendations. By utilizing stream processing frameworks like Apache Kafka and Apache Flink, the system supports high-throughput data ingestion and low-latency processing, even under high user concurrency. Experimental results demonstrate that the proposed system outperforms traditional methods and state-of-the-art models in terms of recommendation accuracy, response time, and user satisfaction. This approach offers significant advantages in real-time ad delivery and provides a scalable, efficient solution for personalized advertising in large-scale applications.
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Liang, He, Sufri Muhammad, and M. N. Shah Zainudin. "Data-Driven User Personas in Requirement Engineering with NLP and Behavior Analysis." JOIV : International Journal on Informatics Visualization 8, no. 4 (2024): 2033. https://doi.org/10.62527/joiv.8.4.3625.

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As technology rapidly evolves, software development faces growing complexity, requiring adaptation to dynamic user expectations. This study addresses a critical gap in the existing literature by integrating behavioral data and sentiment analysis into the user persona development process within the requirement engineering framework. The primary objective is to create more accurate and representative user personas that better guide software design and development. To achieve this, the research employs advanced Natural Language Processing (NLP) techniques to systematically analyze extensive behavioral and sentiment data collected from social media platforms. The integration process involves segmenting user data into behavioral patterns and emotional states, which are then synthesized to develop nuanced user personas. These personas are expected to significantly improve the accuracy of user requirements, leading to enhanced software performance, increased user satisfaction, and greater development efficiency. The target application area for this research is mobile telecommunications, where precise user understanding is critical. The results indicate that this approach not only refines the traditional persona method but also addresses the evolving needs of users more holistically. By advancing the methodology for user-centered design, this study contributes to the broader field of requirement engineering. Future research will validate and refine this approach across diverse domains, ensuring its adaptability and effectiveness in different contexts. This paper thus has the potential to make a significant impact on how user personas are developed and utilized in software engineering.
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Praneeth, Praneeth, Naresh Naresh, Sai Kiran, Anvesh Anvesh, and Deepak Deepak. "Smart Attendance and Behavioural Analysis." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42936.

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This project introduces the Smart Attendance and Behavioural Analytic System, designed to enhance student engagement and learning outcomes in modern educational environments. Utilizing advanced voice recognition technology, the system automates attendance marking, allowing students to check in simply by stating their name or a designated phrase. This automation significantly reduces the time and effort required for manual attendance procedures. The system incorporates Natural Language Processing (NLP) and Machine Learning (ML) techniques to analyze students' vocal expressions, tone, and speech patterns, providing real-time insights into their emotional and engagement states during classes, such as attentiveness, confusion, and interest. Equipped with a user-friendly dashboard, educators can effortlessly track attendance, visualize engagement metrics, and identify behavioural patterns over time. Equipped with a user-friendly dashboard, educators can effortlessly track attendance, visualize engagement metrics, and identify behavioral patterns over time. The system also issues alerts for drops in student engagement or persistent absenteeism, facilitating timely interventions. By integrating with Learning Management Systems (LMS), it streamlines attendance reporting and behavioural analysis, allowing institutions to monitor and support students effectively. The system also issues alerts for drops in student engagement or persistent absenteeism, facilitating timely interventions. By integrating with Learning Management Systems (LMS), it streamlines attendance reporting and behavioral analysis, allowing institutions to monitor and support students effectively.
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Cai, Xiaobo, Jiajin Zhang, Yue Zhang, Xiaoshan Yang, and Ke Han. "LIME-Mine: Explainable Machine Learning for User Behavior Analysis in IoT Applications." Electronics 13, no. 16 (2024): 3234. http://dx.doi.org/10.3390/electronics13163234.

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In Internet of Things (IoT) applications, user behavior is influenced by factors such as network structure, user activity, and location. Extracting valuable patterns from user activity traces can lead to the development of smarter, more personalized IoT applications and improved user experience. This paper proposes a LIME-based user behavior preference mining algorithm that leverages Explainable AI (XAI) techniques to interpret user behavior data and extract user preferences. By training a black-box neural network model to predict user behavior using LIME and approximating predictions with a local linear model, we identify key features influencing user behavior. This analysis reveals user behavioral patterns and preferences, such as habits at specific times, locations, and device states. Incorporating user behavioral information into the resource scheduling process, combined with a feedback mechanism, establishes an active discovery network of user demand. Our approach, utilizing edge computing capabilities, continuously fine-tunes and optimizes resource scheduling, actively adapting to user perceptions. Experimental results demonstrate the effectiveness of feedback control in satisfying diverse user resource requests, enhancing user satisfaction, and improving system resource utilization.
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Qu, Li. "Optimization Strategies for Intelligent Book Reading Based on User Behavior Analysis." Journal of Social Science and Humanities 7, no. 4 (2025): 141–45. https://doi.org/10.53469/jssh.2025.7(04).24.

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This study addresses the issues of user attention fragmentation and cognitive mismatch caused by static content presentation in digital reading platforms, proposing intelligent book reading optimization strategies grounded in user behavior analysis. By capturing interaction frequency, temporal continuity, and composite behavioral data, we developed a multi-dimensional indicator model to reflect reading states and employed clustering algorithms, temporal pattern analysis, and association rule mining to decode behavioral patterns. Building on these insights, a three-tiered optimization framework was designed, integrating personalized content recommendations, adaptive interaction adjustments, and attention-sustainment mechanisms to dynamically refine content presentation formats, page-turning speed, and auxiliary tools. Experimental results demonstrate that this strategy system significantly enhances reading efficiency and user experience, offering both theoretical foundation and methodological guidance for the development of intelligent reading systems.
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Rahul, C. R., and A. Rengarajan. "Behavioural Biometrics as a User Authentication Mechanism in ISMS." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 03 (2024): 1699–706. http://dx.doi.org/10.15680/ijircce.2024.1203054.

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Securing sensitive data and mitigating cyber threats necessitates robust user authentication mechanisms within Information Security Management Systems (ISMS). Conventional authentication approaches, such as passwords and static biometric identifiers, exhibit vulnerabilities, urging the adoption of more sophisticated solutions. Behavioral biometrics, which analyzes unique behavioral patterns like typing rhythm and mouse movements, offers a promising avenue for enhancing authentication security while optimizing user experience. This paper examines the integration of behavioral biometrics into ISMS for user verification, emphasizing its advantages including continuous, multimodal, risk-based, and adaptive authentication. Additionally, it addresses considerations like data privacy, regulatory compliance, user experience enhancement, and monitoring and analysis to ensure successful implementation and efficacy. By leveraging behavioral biometrics as part of a holistic authentication strategy, organizations can fortify their security posture, mitigate threats, and adapt to evolving cybersecurity challenges.
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Fuchs, Beth E., Cristina M. Thomsen, Randolph G. Bias, and Donald G. Davis. "Behavioral Citation Analysis: Toward Collection Enhancement for Users." College & Research Libraries 67, no. 4 (2006): 304–24. http://dx.doi.org/10.5860/crl.67.4.304.

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A pilot study was developed to determine use of the University of Texas at Austin General Libraries’ research collections in the fields of civil engineering and educational psychology and to investigate the research behavior of graduate students. First, the authors sampled bibliographic citations from dissertations completed during the years 1997 and 2002 in the above-named fields. Then, a survey was sent to the dissertation writers to gain insight into use and opinions of library services for their graduate research. Analysis of information provided by both collection-and user-centered data-gathering techniques serves to underscore the value of the merged evaluation methods.
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Dissertations / Theses on the topic "User Behavioral Analysis"

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Hiler, Marzena M. "Electronic Cigarette User Plasma Nicotine Concentration and Puff Topography: Influence of Liquid Nicotine Concentration and User Experience." VCU Scholars Compass, 2016. http://scholarscompass.vcu.edu/etd/4613.

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Electronic cigarettes (ECIGs) aerosolize an often nicotine-containing solution for user inhalation. ECIG nicotine delivery may depend on liquid nicotine concentration and user puffing behavior (topography). This study examined the relationship among liquid nicotine concentration, puff topography, and plasma nicotine concentration. Thirty-three ECIG-experienced and 31 ECIG-naïve individuals completed four laboratory sessions that differed by ECIG liquid nicotine concentration (0, 8, 18, or 36 mg/ml). A 3.3 volt “eGo” ECIG battery attached to a 1.5 Ohm dual coil “cartomizer” filled with 1 ml of 70% propylene glycol/30% vegetable glycerin nicotine liquid was used in two ECIG-bouts (10 puffs; 30 s IPI). Plasma nicotine concentration, puff topography, and HR were evaluated. Some ECIG/liquid combinations can deliver physiologically active doses of nicotine to users, and nicotine delivery depends on liquid nicotine concentration and user puffing behavior. Liquid contents, device characteristics, and user behavior should be considered when regulating ECIGs.
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Rawstorne, Patrick. "A systematic analysis of the theory of reasoned action, the theory of planned behaviour and the technology acceptance model when applied to the prediction and explanation of information systems use in mandatory usage contexts." Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20060815.154410/index.html.

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Sisk, Jakob. "A non-visible user input-based CAPTCHA." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-13694.

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During the last decade, there has been an increase in the number of automated programs (bots) that perform tasks such as harvesting information or making posts on social media. CAPTCHA was developed as a defense against bots, but several common CAPTCHAs have usability issues and are difficult for users to solve. This project aims to determine if a non-visible user input-based CAPTCHA can help solve this problem. The CAPTCHA looks for patterns in the user input, that is, signs that the input is controlled by scripted logic. The CAPTCHA is evaluated by looking at how capable it is at identifying patterns, human mouse movements and bot-controlled mouse movements. Additionally, it is investigated if there exists a data sequence size at which the pattern recognition algorithm can most successfully detect patterns and avoid false negatives. The results showed that interval sizes 40-50 provide the best results. Using these sizes, the pattern recognition algorithm was able to fulfill the commonly accepted rates of at least a 99 % success rate and at most a 10 % false negative rate. This shows that the CAPTCHA is robust under the circumstances investigated.
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Cook, Henry Ernest IV. "EFFECT OF ENACTIVE-INTERFACE CONSTRAINTS ON USER BEHAVIOR IN VIRTUAL ENVIRONMENTS." Miami University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=miami1366718517.

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Manandhar, Sachit. "A behavioral analysis of two spaces in Kansas State University's Hale Library based on psychologist Roger Barker's behavior setting theory." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/17918.

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Master of Science<br>Department of Architecture<br>David Seamon<br>This thesis uses behavioral mapping to analyze two contrasting spaces in Kansas State University’s Hale Library. One of the spaces is meant for computer use; and the other for general library use, including study-group work. The conceptual approach chosen to describe and analyze these two library spaces is the behavior-setting theory developed by psychologist Roger Barker, who defines behavior settings as independent units of space, with temporal and spatial boundaries, that have “great coercive power over the behaviors that occur within them” (Barker, 1968, p. 17). The behavioral observations for the two Hale Library spaces were analyzed and compared with findings from other studies of library usage and behaviors. In the first chapter of the thesis, I introduce my study topic and discuss recent developments in libraries. In the second chapter, I provide a broad overview of library history and library use. I also overview behavior-setting theory and present examples of research on behavior settings and libraries. In the third chapter, I discuss research methods for this thesis, starting with how library spaces can be described as behavior settings. I then discuss specific methodological procedures involved in the behavioral study of activities in the two library spaces. In the fourth chapter, I discuss the two spaces studied in Hale Library, first, describing their physical features and then discussing their behavior-setting attributes. In the fifth chapter, I present my behavioral observations and compare and contrast the two Hale Library spaces in terms of user behaviors and as behavior settings. In the sixth and final chapter of this thesis, I compare my research results with other library research and offer my speculative ideas on the future of the academic library. The overarching theme of this thesis is evaluating how recent digital technologies have affected libraries, and how traditional library spaces and spaces designated for digital technology can be integrated in future libraries.
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Shrestha, Subik Kumar. "A plaza design to promote sociability for Kansas State University’s North Quadrangle based on observational analysis of user behaviors." Thesis, Kansas State University, 2015. http://hdl.handle.net/2097/20548.

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Master of Science<br>Department of Architecture<br>David Seamon<br>This thesis draws on observations of user behaviors in Kansas State University’s North Quadrangle to propose a plaza design for a site within the quadrangle adjacent to Cardwell Hall. As a practical method for conducting environment-behavior research, the thesis gathered observations of moving and resting behaviors to understand the North Quadrangle’s current usages. The observations of moving behaviors provided evidence for identifying potential spaces within the North Quadrangle where a plaza might be designed and built. In turn, observations of resting behaviors provided an understanding of sitting and standing behaviors in the North Quadrangle plaza. In terms of research related to plaza behavior and design, the most significant work drawn upon was William Whyte’s The Social Life of Small Urban Spaces (Whyte, 1980). According to Whyte, a plaza is sociable if large numbers of people are drawn to it informally in the course of their everyday activities and movements. In this regard, the design aim of the proposed plaza is to promote sociability within the North Quadrangle by attracting pedestrians traversing the North Quadrangle’s busiest pathways and thus drawing them into the plaza. More specifically, to promote plaza sociability, the design makes use of the three most important plaza-design factors identified by Whyte: (1) location; (2) street-plaza relationship; and (3) seating. In other words, first, the plaza should be located near large pools of potential users; second, the plaza should be designed as an extension of the most heavily trafficked pathways; and third, the plaza should incorporate sitting opportunities for users via seating that is physically and socially comfortable. The behavioral observations and guidance provided by the literature review have been used to generate twelve design guidelines on which the proposed plaza design is based. The presentation of final plaza design incorporates explanations of these twelve guidelines followed by illustrated design schemes.
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Mamun, Md Rasel. "An Analysis of Information Technology (IT) Post-Adoption Behavior." Thesis, University of North Texas, 2020. https://digital.library.unt.edu/ark:/67531/metadc1707339/.

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The primary focus of this research is explicating the role of emotion in IT post-adoption behavior. Studied in the context of intelligent personal assistants (IPA), a class of conversational artificial intelligence (AI), the first study integrates elements from computer science, communications, and IS disciplines. The research identifies two constructs vital for speech-based technologies, natural language understanding, and feedback, and examines their role in use decisions. This work provides guidance to practice on how best to allocate R&D investments in conversational AI. The second essay examines the IT continuance through the theoretical lens of the expectation-confirmation model (ECM), incorportating cognitive and emotional satisfaction into the ECM framework. Empirical testing of the model suggests that it offers additional clarity on IT continuance phenomena and provides a significant improvement to the explanatory power of ECM in the context of an emerging technology. The third essay is one of the earliest efforts to conceptualize and test a theoretical model that considers emotional attachment in IT continuance behavior. This essay develops a novel model to investigate this phenomenon based on emotional attachment theory, and empirically validates the proposed model in the context of conversational artificial intelligence systems. While the existing theories of IT continuance focus on purely rational, goal-oriented factors, this study incorporates non-cognitive aspects by including the emotional consequences of IT continuance and offers evidence that attachment can exist even in the absence of cognitive factors.
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Zhang, Yichi. "Residential Network Traffic and User Behavior Analysis." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-27001.

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Internet usage is changing and the demands on the broadband networks are ever increasing. So it is still crucial to understand today's network traffic and the usage patterns of the end users, which will lead to more efficient network design, energy and costs savings, and improvement of the service offered to end users. This thesis aims at finding hidden patterns of traffic and user behavior in a residential fiber based access network. To address the problem, a systematic framework of traffic measurement and analysis is developed. It involves PacketLogic traffic data collecting, MySQL database storing, and traffic and user behavior analysis by using Python scripts.   Our approach provides new insights on residential network traffic properties and Internet user habits of households, covering topics of aggregated traffic pattern, household traffic modeling, traffic and user penetration for applications, grouping analysis by cluster and subscriber, and concurrent application analysis. The analysis solutions we provide are based on open source tools without proprietary, giving the most flexibility for codes modification and distribution.
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Ochalek, Taylor Anne. "Examining sucrose subjective response among individuals with opioid use disorder." ScholarWorks @ UVM, 2020. https://scholarworks.uvm.edu/graddis/1185.

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Aims: Opioid use disorder (OUD) is associated with significant morbidity and mortality, and opioid agonist treatment (OAT) with methadone or buprenorphine represents the most efficacious treatment. However, data suggest that chronic administration of opioids may be associated with significant weight gain, possibly by altering an organism’s perception of and preference for sweet foods. The primary aim of this laboratory study was to rigorously examine sucrose subjective response among adults receiving OAT and a comparison sample without OUD. As secondary outcomes, we also sought to compare the groups on additional baseline characteristics that may influence subjective sucrose response and weight gain during treatment. Methods: Participants were 40 adults receiving treatment for OUD (OUD+) and a comparison sample of 40 adults without OUD (OUD-). All participants completed an initial screening visit that included questionnaires on eating behaviors, diet and nutrition, recent substance use, and measurement of body mass index. Eligible participants completed two, same-day outpatient laboratory sessions during which they sampled six experimenter-administered concentrations of sucrose solution (0, 0.1, 0.25, 0.5, 0.75, and 1.0M in distilled water) each three times under double-blind counterbalanced conditions. Following each exposure, participants rated the pleasantness and intensity of each sample using 100-point visual analog scales. Results: OUD+ participants rated sucrose solutions as less pleasant than OUD- participants (p<0.001). However, this effect was limited to the three lowest sucrose concentrations (0, 0.1, 0.25M), and at higher concentrations there were no group differences. There were no between-group differences on ratings of intensity (p=0.35). Given these baseline group differences in placebo (0M) responding, sucrose response was also examined in terms of change from baseline. In this analysis, there was a significant group effect, with a higher magnitude of change in pleasantness ratings and a lower magnitude of change in intensity ratings from 0M in OUD+ vs. OUD- participants (p’s<0.05). With regard to baseline characteristics that may influence sucrose response and eating behavior more generally, the OUD+ group had a higher prevalence of obesity, food insecurity, unhealthy eating behaviors, high sugar consumption, and nutrition knowledge deficits compared to the OUD- group (p’s<0.05). Conclusion: Data from preclinical and clinical research have suggested that opioid agonist medications may enhance subjective response to sweet flavors. In the present study, OUD+ participants exhibited a higher magnitude of change in pleasantness ratings from placebo compared to OUD- participants. However, this effect was largely driven by pronounced group differences in perceived pleasantness of essentially unsweet solutions. On the outcome of sucrose intensity, findings were more mixed with no consistent differences between OUD+ and OUD- participants. In contrast, group differences were far more pronounced in participants’ daily eating behaviors and nutrition knowledge, with OUD+ participants presenting with a consistently more severe profile. These data highlight the significant risk factors experienced by OUD+ individuals that extend beyond drug-related risks and may inform future scientific and clinical efforts to improve health outcomes in this vulnerable population.
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Strickland, Justin Charles. "EXAMINING THE UTILITY OF BEHAVIORAL ECONOMIC DEMAND IN ADDICTION SCIENCE." UKnowledge, 2019. https://uknowledge.uky.edu/psychology_etds/154.

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The marriage of perspectives from behavioral economic theory and learning theory has the potential to advance an understanding of substance use and substance use disorder. Behavioral economic demand is a central concept to this interdisciplinary approach. Evaluating demand in the laboratory and clinic can improve previous research on the relative reinforcing effects of drugs by accounting for the multi-dimensional nature of reinforcement rather than viewing reinforcement as a unitary construct. Recent advances in the commodity purchase task methodology have further simplified the measurement of demand values in human participants. This dissertation project presents a programmatic series of studies designed to demonstrate the utility of using a behavioral economic demand framework and the purchase task methodology for understanding substance use disorder through basic and applied science research. Experiments are presented spanning a continuum from theoretical and methodological development to longitudinal work and clinical application. These experiments demonstrate three key conclusions regarding behavioral economic demand. First, behavioral economic demand provides a reliable and valid measure of drug valuation that is applicable to varied drug types and participant populations. Second, behavioral economic demand is a stimulus-selective measure specifically reflecting valuation for the commodity under study. Third, behavioral economic demand provides incremental information about substance use in the laboratory and clinical setting above and beyond traditional measures of reinforcer valuation and other behavioral economic variables. These findings collectively highlight the benefits of behavioral economic demand and provide an important platform for future work in addiction science.
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Books on the topic "User Behavioral Analysis"

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Rotterdam, Erasmus Universiteit, ed. User participation and the success of information system development: An integrated model of user-specialist relationships. Thesis Publishers, 1994.

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Meiselwitz, Gabriele, ed. Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49570-1.

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Paek, Kyŏng-mi. Ch'ungch'ŏng-bukto konggong tosŏgwan sŏngbyŏl yŏnghyang p'yŏngka: Sisŏl kwa p'ŭrogŭraem ŭl chungsim ŭro. Ch'ungch'ŏng-bukto Yŏsŏng Palchŏn Sent'ŏ, 2010.

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D, Frank Lawrence, Washington (State). Dept. of Transportation. Urban Planning Office., Washington (State). Dept. of Transportation. Research Office., United States. Federal Highway Administration., Washington State Transportation Commission, and Lawrence Frank & Company., eds. Travel behavior, emissions, & land use correlation analysis in the Central Puget Sound. Washington State Dept. of Transportation, 2005.

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Amato, Alberto. Semantic Analysis and Understanding of Human Behavior in Video Streaming. Springer New York, 2013.

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Zuenkova, Yuliya, and Milan Stamenkovich. Cluster analysis and MANOVA in marketing and economic research. INFRA-M Academic Publishing LLC., 2025. https://doi.org/10.12737/2186588.

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The monograph introduces the reader to the basics of using multidimensional statistical methods — cluster analysis and MANOVA analysis — in marketing and economic research. Data is an indispensable product of any activity and the basis for making objective management decisions. Big data has had a significant impact on marketing and the development of its tools. The collection, accumulation and processing of information about customers and the market is the basis of information support for marketing activities. Multidimensional statistics methods, cluster analysis and MANOVA analysis in particular, open up new opportunities for marketers due to the great applied potential of their use. The areas of marketing application of cluster analysis and the MANOVA method are described in detail, a step-by-step plan for the implementation of statistical procedures and recommendations for the researcher on data preparation and evaluation of statistical analysis results are given. Multidimensional statistics methods allow marketers to identify complex behavioral patterns, predict consumer behavior, find new approaches to customer segmentation, and thus develop new marketing strategies and tactics in the market. It is intended for practicing marketers and researchers, economists and statisticians, university students and teachers, as well as all those who are interested in expanding their capabilities in big data processing to open new strategic horizons.
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Piotrowski, Stephan. Land property rights and natural resource use: An analysis of household behavior in rural China. Peter Lang, 2009.

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Kalmykov, Sergey, and Nikolay Pashin. Social advertising: designing effective interaction with the target audience. INFRA-M Academic Publishing LLC., 2017. http://dx.doi.org/10.12737/23289.

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The monograph analyzes the possibility of managing the process of socio-advertising influence on socio-demographic groups. The developed methodological bases with the use of the multivariate paradigmatic status of sociological knowledge allowed us to form: principles of designing social advertising interaction, factors of efficiency (quality) of social advertising, a system of sociological quality assurance of social advertising.&#x0D; Insufficiently studied problems of efficiency and quality of social advertising are investigated. The coefficients of the importance of its efficiency factors (quality) are established. Stable interrelations of social advertising influence at the level of revealed correlation coefficients of behavioral reactions of various categories of target audience with their characteristics are proved. The results obtained are summarized in the developed model of behavior of the target audience on the basis of social advertising interaction, and the content modules of the mechanism of controllability of the specified process are proposed.
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Frank, Lawrence D. An analysis of relationships between urban form (density, mix, and jobs: housing balance) and travel behavior (mode choice, trip generation, trip length, and travel time). Washington State Dept. of Transportation, 1994.

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Grigor'ev, Anatoliy, and Evgeniy Isaev. Methods and algorithms of data processing. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1032305.

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The tutorial deals with selected methods and algorithms of data processing, the sequence of solving problems of processing and analysis of data to create models behavior of the object taking into account all the components of its mathematical model. Describes the types of technological methods for the use of software and hardware for solving problems in this area. The algorithms of distributions, regressions vremenny series, transform them with the aim of obtaining mathematical models and prediction of the behavior information and economic systems (objects).&#x0D; The second edition is supplemented by materials that are in demand by researchers in the part of the correct use of clustering algorithms. Are elements of the classification algorithms to identify their capabilities, strengths and weaknesses. Are the procedures of justification and verify the adequacy of the results of the cluster analysis, conducted a comparison and evaluation of different clustering techniques, given information about visualization of multidimensional data and examples of practical application of clustering algorithms.&#x0D; Meets the requirements of Federal state educational standards of higher education of the last generation.&#x0D; For students of economic specialties, specialists, and graduate students.
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Book chapters on the topic "User Behavioral Analysis"

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Rodrigues, Eulerson, Ernesto Filgueiras, and João Valente. "Behavioral Analysis of eSports Spectators: A Research Proposal." In Design, User Experience, and Usability: Design for Contemporary Technological Environments. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78227-6_27.

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Jiang, Frank, Mingdong Tang, and Quang Anh Tran. "User Preference-Based Spamming Detection with Coupled Behavioral Analysis." In Security, Privacy, and Anonymity in Computation, Communication, and Storage. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49148-6_38.

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Sarker, Iqbal H., and Flora D. Salim. "Mining User Behavioral Rules from Smartphone Data Through Association Analysis." In Advances in Knowledge Discovery and Data Mining. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93034-3_36.

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Banks, George C., Haley M. Woznyj, Ryan S. Wesslen, and Roxanne L. Ross. "A Review of Best Practice Recommendations for Text Analysis in R (and a User-Friendly App)." In Key Topics in Behavioral Sciences. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19922-6_8.

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Li, Yunqin, Nobuyoshi Yabuki, and Tomohiro Fukuda. "A Virtual Reality-Based Tool with Human Behavior Measurement and Analysis for Feedback Design of the Indoor Light Environment." In Computational Design and Robotic Fabrication. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8637-6_16.

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AbstractHuman behavior data provides essential feedback information for architects to improve a human-centered indoor light environment design. However, architects have difficulty capturing the complex, multidimensional, and unpredictable behavior of humans, often struggle to get users’ feedback on time in the schematic phase. This paper proposes a new virtual reality-based behavioral measurement and assessment tool that quantitatively collects and analyzes individual behavioral data, including travel trajectory, travel time, and gaze points, to reveal user experience and interaction of light, aiming to better help architects get timely feedback from users and create human-centered indoor light environment designs in the scheme optimization phase. To showcase this tool, we utilize an exhibition hall of a museum design as an illustrative example. The experiment demonstrates the feasibility of the proposed tool, and its results suggest that different lighting schemes influence human behavior patterns and that the introduction of natural light usually stimulates more movement. The developed virtual reality tool prototype provides valuable visual information and statistics for analyzing human behavior and evaluating indoor light environment design schemes.
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Alharbi, Ahmed Sulaiman M., and Elise DeDoncker. "Enhance a Deep Neural Network Model for Twitter Sentiment Analysis by Incorporating User Behavioral Information." In Intelligent Computing Theories and Application. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63309-1_8.

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Marczal, Denise, and Plinio Thomaz Aquino Junior. "Behavioural Variables Analysis in Mobile Environments." In Design, User Experience, and Usability: Users and Interactions. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20898-5_12.

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Govorova, Svetlana, Egor Govorov, Vitalii Lapin, and E. A. Mary Anita. "Comparative Analysis and Development of Recommendations for the Use of Machine Learning Methods to Identify Network Traffic Anomalies in the Development of a Subsystem for User Behavioral Analysis." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-77229-0_8.

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Abreu, Eduardo Coelho, and Elizeu Borloti. "Establishing and Abolishing Contingencies of Crack Use: User Descriptions of a CAPSad." In Behavior Analysis and Substance Dependence. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75961-2_6.

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Raubal, Martin, Dominik Bucher, and Henry Martin. "Geosmartness for Personalized and Sustainable Future Urban Mobility." In Urban Informatics. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8983-6_6.

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AbstractUrban mobility and the transport of people have been increasing in volume inexorably for decades. Despite the advantages and opportunities mobility has brought to our society, there are also severe drawbacks such as the transport sector’s role as one of the main contributors to greenhouse-gas emissions and traffic jams. In the future, an increasing number of people will be living in large urban settings, and therefore, these problems must be solved to assure livable environments. The rapid progress of information and communication, and geographic information technologies, has paved the way for urban informatics and smart cities, which allow for large-scale urban analytics as well as supporting people in their complex mobile decision making. This chapter demonstrates how geosmartness, a combination of novel spatial-data sources, computational methods, and geospatial technologies, provides opportunities for scientists to perform large-scale spatio-temporal analyses of mobility patterns as well as to investigate people’s mobile decision making. Mobility-pattern analysis is necessary for evaluating real-time situations and for making predictions regarding future states. These analyses can also help detect behavioral changes, such as the impact of people’s travel habits or novel travel options, possibly leading to more sustainable forms of transport. Mobile technologies provide novel ways of user support. Examples cover movement-data analysis within the context of multi-modal and energy-efficient mobility, as well as mobile decision-making support through gaze-based interaction.
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Conference papers on the topic "User Behavioral Analysis"

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Wu, Ruoge, Wenyan Mao, Dexuan Pan, Linqi Cheng, and Yan Tu. "Rumor Spreading and User Behavioral Characteristics Based on Social Network Analysis and Co-Word Network Analysis." In 2024 2nd International Conference on Big Data and Privacy Computing (BDPC). IEEE, 2024. http://dx.doi.org/10.1109/bdpc59998.2024.10649200.

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Wigell, Christopher, Xiaohui Tao, Lin Li, Grace Y. Wang, Ji Zhang, and Yuan Sun. "Sentiment Analysis for Detection of Depressive Users on Social Networks." In 2024 11th International Conference on Behavioural and Social Computing (BESC). IEEE, 2024. https://doi.org/10.1109/besc64747.2024.10780472.

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Gopalakrishnan, Abinaya, Xujuan Zhou, Revathi Venkataraman, et al. "A Combined Sentiment Analysis of Twitter for Identifying Users with Depression." In 2024 11th International Conference on Behavioural and Social Computing (BESC). IEEE, 2024. https://doi.org/10.1109/besc64747.2024.10780637.

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Chimienti, Michela, Ivan Danzi, Vincenzo Gattulli, Donato Impedovo, Giuseppe Pirlo, and Davide Veneto. "Behavioral Analysis for User Satisfaction." In 2022 IEEE Eighth International Conference on Multimedia Big Data (BigMM). IEEE, 2022. http://dx.doi.org/10.1109/bigmm55396.2022.00027.

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Jiang, Frank, Jin Gan, Yuanyuan Xu, and Guandong Xu. "Coupled behavioral analysis for user preference-based email spamming." In 2016 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC). IEEE, 2016. http://dx.doi.org/10.1109/besc.2016.7804482.

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Zhu, Youmin, Yanchun Tan, and Yunhui Zhu. "User Behavioral Preference Analysis Based on Location Information." In 2020 International Wireless Communications and Mobile Computing (IWCMC). IEEE, 2020. http://dx.doi.org/10.1109/iwcmc48107.2020.9148281.

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Bhagat, Amol P., Kiran A. Dongre, and Priti A. Khodke. "Cut-based classification for user behavioral analysis on social websites." In 2015 International Conference on Green Computing and Internet of Things (ICGCIoT). IEEE, 2015. http://dx.doi.org/10.1109/icgciot.2015.7380427.

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Feng, Chen, and Ruijiu Mao. "Interpretable User Behavioral Analysis and Personalized Recommendation with Side Information." In 2022 Winter Simulation Conference (WSC). IEEE, 2022. http://dx.doi.org/10.1109/wsc57314.2022.10015443.

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Khan, Abdur Rehman, Umer Rashid, Ayesha Saadia, and Amanullah Yasin. "A Heuristic Multimedia Verticals Aggregated Search Approach and User Behavioral Analysis." In 2024 International Conference on Engineering & Computing Technologies (ICECT). IEEE, 2024. http://dx.doi.org/10.1109/icect61618.2024.10581027.

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Jia, Zhuosheng, and Zhen Han. "Research and Analysis of User Behavior Fingerprint on Security Situational Awareness Based on DNS Log." In 2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC). IEEE, 2019. http://dx.doi.org/10.1109/besc48373.2019.8963120.

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Reports on the topic "User Behavioral Analysis"

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Corscadden, Louise, and Arpaporn Sutipatanasomboon. What Is Operant Behavior And How To Study It. Maze Engineers, 2022. http://dx.doi.org/10.55157/me2022127.

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Operant behavior describes a type of voluntary goal-directed actions in animals based on the repercussions of previous occurrences. It develops when animals learn to specifically respond to recurring situations based on the outcome of their past experience. American psychologist B.F. Skinner was the first to use operant to describe the behaviors he observed in his landmark experiments in laboratory animals. Operant behavior and conditioning refine the nuance between conscious and unconscious behavioral responses, which influence psychology, and applied behavior analysis, and improve our understanding of addiction, substance dependence, child development, and decision-making.
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Turcotte, Melissa, and Juston Shane Moore. User Behavior Analytics. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1345176.

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Sierra, Ricardo, Inder J. Ruprah, and Heather Sutton. Sex, Violence, and Drugs Among Latin American and Caribbean Adolescents: Do Engaged Parents Make a Difference? Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0011727.

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This paper uses data from the Global School-based Student Health Survey toinvestigate the prevalence of health risk behaviors, in particular substance use, risky sexual behavior, and violence among adolescents in 15 Latin American and Caribbean countries. Using logit regressions and meta-analysis, we find that having parents engaged in raising their children is associated with significantly reduced problem behaviors in adolescents. That said, in the Caribbean the prevalence of health risk behaviors in adolescents is higher and engaged parents is lower than in Latin America, and the correlation between engaged parenting and reduced risk behaviors is generally weaker. Nonetheless, for both subgroups of countries, engaged parents do appear to make a difference.
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Sarofim, Samer, and Aly Tawfik. Creating Safer Communities for the Use of Active Transportation Modes in California: The Development of Effective Communication Message Strategy for Vulnerable Road Users. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2021.2030.

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Despite increased efforts to improve safety in recent years (e.g., the Focus Cities Program in California), California continues to have a high rate of pedestrian and bicyclist fatalities. Currently, the state currently lacks a cohesive messaging strategy to improve behaviors related to pedestrian and cyclist traffic safety practices. To fulfill this need, this research showcases the differential effect of message framing on attitudes and intended behaviors related to pedestrian and cyclists traffic safety practices. This project investigated factors &amp; risky behaviors contributing to accidents involving vulnerable road users, preventive measures to decrease accidents involving vulnerable road users, and more. The qualitative analysis presented a significant lack of coherent, long-term, evidence-based communication strategies that aimed at enhancing the safety of vulnerable road users in California. Quantitatively, this research also experimentally investigated various messages, employing different time horizons and regulatory focus message framings. Findings indicate that the messages with a limited time horizon tend to be associated with better safety perceptions and attitudes than messages with an expansive time horizon. California transportation authorities, professionals, and advocacy groups will be able to use this information to effectively allocate the communication effort and spending to induce attitudinal and behavioral change that can impact the safety of active transportation modes.
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Sarofim, Samer, and Aly Tawfik. Creating Safer Communities for the Use of Active Transportation Modes in California: The Development of Effective Communication Message Strategy for Vulnerable Road Users. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2030.

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Despite increased efforts to improve safety in recent years (e.g., the Focus Cities Program in California), California continues to have a high rate of pedestrian and bicyclist fatalities. Currently, the state currently lacks a cohesive messaging strategy to improve behaviors related to pedestrian and cyclist traffic safety practices. To fulfill this need, this research showcases the differential effect of message framing on attitudes and intended behaviors related to pedestrian and cyclists traffic safety practices. This project investigated factors &amp; risky behaviors contributing to accidents involving vulnerable road users, preventive measures to decrease accidents involving vulnerable road users, and more. The qualitative analysis presented a significant lack of coherent, long-term, evidence-based communication strategies that aimed at enhancing the safety of vulnerable road users in California. Quantitatively, this research also experimentally investigated various messages, employing different time horizons and regulatory focus message framings. Findings indicate that the messages with a limited time horizon tend to be associated with better safety perceptions and attitudes than messages with an expansive time horizon. California transportation authorities, professionals, and advocacy groups will be able to use this information to effectively allocate the communication effort and spending to induce attitudinal and behavioral change that can impact the safety of active transportation modes.
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Davis, Austin. Overview of a rapid discrete infrared acquisition system and method for automated behavioral analysis of multiple emissive objects. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49564.

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Many animal species form congregations on the landscape. These concentrations of animals provide an opportunity for biologists to conduct efficient population monitoring efforts. While general use of these sites is easy to document, continual monitoring is often problematic due to limited resources (time, expertise, etc.), potential for human disturbance on animal population and behavior, and an inability to determine an accurate assessment of counts. To allow for accurate and efficient assessment of animal numbers and usage of an area, an automated technology has been developed to monitor and characterize large animal concentrations. This automated technology provides information on population size, movement behavior characteristics, and other behavioral aspects of the target species.
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Bernal, Pedro, Giuliana Daga, and Florencia Lopez Boo. Do Behavioral Drivers Matter for Healthcare Decision-making in Times of Crisis?: A study of Low-Income Women in El Salvador During the COVID-19 Pandemic. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005094.

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Understanding health-seeking behaviors and their drivers is key for governments to manage health policies. There is a growing literature on the role of cognitive biases and heuristics in health and care-seeking behaviors, but little is known of how they might be influenced during a context of heightened anxiety and uncertainty. This study analyzes the relationship between four behavioral predictors the internal locus of control, impatience, optimism bias, and aspirations and healthcare decisions among low-income women in El Salvador. We find positive associations between internal locus of control and preventive health behaviors during the COVID-19 pandemic (use of masks, distance, hand washing, and COVID-19 vaccination) and in general (prenatal checkups, iron-rich diets for children and hypertension tests). Measures of impatience negatively correlate with COVID-19 prevention behaviors and mothers micronutrient treatment adherence for children, and optimism bias and educational aspirations with healthcare-seeking behaviors during the COVID-19 pandemic. Some associations were more robust during the pandemic, suggesting that feelings of uncertainty and stress could enhance behavioral drivers influence on health-related behaviors, a novel and relevant finding in the literature relevant for the design of policy responses for future shocks.
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Balali, Vahid. Connected Simulation for Work Zone Safety Application. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2021.2137.

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Every year, over 60,000 work zone crashes are reported in the United States (FHWA 2016). Such work zone crashes have resulted in over 4,400 fatal and 200,000 non-fatal injuries in the last 5 years (FHWA 2016, BLS 2014). Apart from the physical and emotional trauma, the annual cost of these injuries exceeds $4 million-representing significant wasted resources. To improve work zone safety, this research developed a system architecture for unveiling high-risk behavioral patterns among highway workers, equipment operators, and drivers within dynamic highway work zones. This research implemented the use of a connected virtual environment, which is an immersive hyper-realistic and virtual environment where multiple agents (e.g. workers, drivers, and equipment handlers) control independent simulators but experience an interactive and shared experience. For this project, the team conducted an in-depth analysis of accident investigation, simulated accident scenarios, and tested diverse interventions to prevent high-risk behavior. Overall, the research improved understanding of behavioral patterns that lead to injuries and fatalities of highway workers in order to better protect them in high-risk work environments. As part of making transportation smarter, this project contributes to smart behavioral safety analysis.
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Shynenko, Mykola, and Olga Pinchuk. Activity of users of the web resource "Electronic Library of the National Academy of Sciences of Ukraine" during crisis events. Institute for Digitalization of Education, 2022. http://dx.doi.org/10.33407/lib.naes.733438.

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The monitoring of the use of the web resource "Electronic Library of the National Academy of Sciences of Ukraine" is aimed at providing informational and methodological support by means of the Google Analytics service in order to track the processes of visiting and using electronic resources, as well as to increase the efficiency of the development, improvement and maintenance of the electronic library site. A comparative analysis of the use of library resources for the period from March 1-May 31, 2022 to September 1-November 30, 2022 during the full-scale Russian invasion of Ukraine was performed. Also, to identify trends in changes in the activity of users of the web resource, a comparative analysis of the use of library resources was performed for the period: 2021. - 2022. The monitoring of the use of the website of the electronic library of the National Academy of Sciences of Ukraine is carried out according to the following indicators: overview of visitors, demographics of visitors, behavior of visitors on the website of the electronic library, technologies for visiting the site, mobile devices used, traffic, information of the statistical module. For scientists, post-graduate students, heads of scientific institutions of the National Academy of Sciences of Ukraine and specialists in the field of librarianship.
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Harkema, Marcel, Dick Quartel, Rob van der Mei, and Bart Gijsen. JPMT: A Java Performance Monitoring Tool. Centre for Telematics and Information Technology (CTIT), 2003. http://dx.doi.org/10.3990/1.5152400.

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This paper describes our Java Performance Monitoring Toolkit (JPMT), which is developed for detailed analysis of the behavior and performance of Java applications. JPMT represents internal execution behavior of Java applications by event traces, where each event represents the occurrence of some activity, such as thread creation, method invocation, and locking contention. JPMT supports event filtering during and after application execution. Each event is annotated by high-resolution performance attributes, e.g., duration of locking contention and CPU time usage by method invocations. JPMT is an open toolkit, its event trace API can be used to develop custom performance analysis applications. JPMT comes with an event trace visualizer and a command-line event trace query tool for scripting purposes. The instrumentation required for monitoring the application is added transparently to the user during run-time. Overhead is minimized by only instrumenting for events the user is interested in and by careful implementation of the instrumentation itself.
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