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Artículos de revistas sobre el tema "Experience-Driven Optimization"

Autor: Grafiati

Publicado: 14 de octubre de 2023

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1

Cheng, Yihua, Xu Zhang, and Junchen Jiang. "Enabling Perception-Driven Optimization in Networking." ACM SIGMETRICS Performance Evaluation Review 51, no. 2 (2023): 103–5. http://dx.doi.org/10.1145/3626570.3626608.

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Service providers struggle to catch up with the rapid growth in bandwidth and latency demand of Internet videos and other applications. An essential contributor to this resource contention is the assumption that users are equally sensitive to service quality everywhere, so any low-quality incidents must be avoided. However, this assumption is not true. For example, our work and other parallel efforts have shown that more video users can be served with better quality of experience (QoE) if we embrace the fact that the QoE's sensitivity to video quality varies greatly with the video content. To

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2

P, Dr Periasamy, and Dr Dinesh N. "Data Driven Marketing Strategic Trends in 2022." International Journal of Science, Engineering and Management 9, no. 6 (2022): 24–27. http://dx.doi.org/10.36647/ijsem/09.06.a005.

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This paper is an attempt to find out the significant data driven marketing strategic trends. The author has developed a model which will help the readers to under the data driven marketing strategies in the recents trends in the world very easily. This model is called EPCMASQ , a model of the author, That is Ethical Information, Personalized Marketing Automation, Better Customer Experience, Multi-channel Experience, Artificial Intelligence, Search Engine Optimization and Qualitative Data. With which the concept of data driven marketing strategies explained well.

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3

Shailesh, K. S., and P. V. Suresh. "Performance Driven Development Framework for Web Applications." Global Journal of Enterprise Information System 9, no. 1 (2017): 75. http://dx.doi.org/10.18311/gjeis/2017/15870.

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The performance of web applications is of paramount importance as it can impact end-user experience and the business revenue. Web Performance Optimization (WPO) deals with front-end performance engineering. Web performance would impact customer loyalty, SEO, web search ranking, SEO, site traffic, repeat visitors and overall online revenue. In this paper we have conducted the survey of state of the art tools, techniques, methodologies of various aspects of web performance optimization. We have identified key web performance patterns and proposed novel web performance driven development framewor

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4

SONG, WEI, DIAN TJONDRONEGORO, and MICHAEL DOCHERTY. "EXPLORATION AND OPTIMIZATION OF USER EXPERIENCE IN VIEWING VIDEOS ON A MOBILE PHONE." International Journal of Software Engineering and Knowledge Engineering 20, no. 08 (2010): 1045–75. http://dx.doi.org/10.1142/s0218194010005067.

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Compared with viewing videos on PCs or TVs, mobile users have different experiences in viewing videos on a mobile phone due to different device features such as screen size and distinct usage contexts. To understand how mobile user's viewing experience is impacted, we conducted a field user study with 42 participants in two typical usage contexts using a custom-designed iPhone application. With user's acceptance of mobile video quality as the index, the study addresses four influence aspects of user experiences, including context, content type, encoding parameters and user profiles. Accompanyi

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5

Wu, Xiaojing, Zijun Zuo, and Long Ma. "Aerodynamic Data-Driven Surrogate-Assisted Teaching-Learning-Based Optimization (TLBO) Framework for Constrained Transonic Airfoil and Wing Shape Designs." Aerospace 9, no. 10 (2022): 610. http://dx.doi.org/10.3390/aerospace9100610.

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The surrogate-assisted optimization (SAO) process can utilize the knowledge contained in the surrogate model to accelerate the aerodynamic optimization process. The use of this knowledge can be regarded as the primary form of intelligent optimization design. However, there are still some difficulties in improving intelligent design levels, such as the insufficient utilization of optimization process data and optimization parameters’ adjustment that depends on the designer’s intervention and experience. To solve the above problems, a novel aerodynamic data-driven surrogate-assisted teaching-lea

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6

Pairet, Eric, Constantinos Chamzas, Yvan R. Petillot, and Lydia Kavraki. "Path Planning for Manipulation Using Experience-Driven Random Trees." IEEE Robotics and Automation Letters 6, no. 2 (2021): 3295–302. http://dx.doi.org/10.1109/lra.2021.3063063.

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7

Endress, Felix, Jasper Rieser, and Markus Zimmermann. "ON THE TREATMENT OF REQUIREMENTS IN DFAM: THREE INDUSTRIAL USE CASES." Proceedings of the Design Society 3 (June 19, 2023): 2815–24. http://dx.doi.org/10.1017/pds.2023.282.

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AbstractOptimization-driven design offers advantages over traditional experience-based mechanical design. As an example, topology optimization can be a powerful tool to generate body shapes for Additive Manufacturing (AM). This is helpful, when (1) load paths are non-intuitive due to complex design domains or boundary conditions, or (2) the design process is to be automated to minimize effort associated with experience-based design. However, practically relevant boundary conditions are often difficult to put into a formal mathematical language to, for example, either feed it into a topology op

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8

Borba Evangelista, Gustavo, Guilherme Conceição Rocha, and Wlamir Olivares Loesch Vianna. "Aircraft Troubleshooting Optimization Using Case-based Reasoning and Decision Analysis." Annual Conference of the PHM Society 12, no. 1 (2020): 8. http://dx.doi.org/10.36001/phmconf.2020.v12i1.1170.

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   The Fault Isolation Manual (FIM) can be seen as a specialist system that carries the expectations and expertise of engineers and technical team concerning the aircraft components and systems operation. It is basically a manual that supports the maintainers regarding the actions to perform in determined situations to properly isolate a fault. Although the FIM is the most common tool that assists maintainer on the troubleshooting process today, it does not adequately consider field experience and it does not explore situations where the maintenance operator has limited resou

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9

Na, Chongzheng, and Huixin Liu. "A Historical Experience Surrogate Model Assisted Particle Swarm Optimization for Expensive Black-box Problems." Highlights in Science, Engineering and Technology 7 (August 3, 2022): 83–88. http://dx.doi.org/10.54097/hset.v7i.1021.

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This paper proposed a new historical experience surrogate model assisted particle swarm optimization method. This method extends the particle swarm optimization by adding new surrogate-based phase. In the classic phase, the particle swarm optimization runs the same way as the original algorithm, and the real function value evaluated are collected into the global database. In the surrogate phase, sub-swarms are generated following the distribution of the history data and evaluated by the surrogate model(s). The purpose of the surrogate phase is to explore the possible better solutions of the se

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10

Enríquez-Urbano, Juana, Marco Antonio Cruz-Chávez, Rafael Rivera-López, Martín H. Cruz-Rosales, Yainier Labrada-Nueva, and Marta Lilia Eraña-Díaz. "Metaheuristic to Optimize Computational Convergence in Convection-Diffusion and Driven-Cavity Problems." Mathematics 9, no. 7 (2021): 748. http://dx.doi.org/10.3390/math9070748.

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This work presents an optimization proposal to better the computational convergence time in convection-diffusion and driven-cavity problems by applying a simulated annealing (SA) metaheuristic, obtaining optimal values in relaxation factors (RF) that optimize the problem convergence during its numerical execution. These relaxation factors are tested in numerical models to accelerate their computational convergence in a shorter time. The experimental results show that the relaxation factors obtained by the SA algorithm improve the computational time of the problem convergence regardless of user

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11

Atri, Roozbeh, J. Marquez, Connie Leung, et al. "Smart Data-Driven Optimization of Powered Prosthetic Ankles Using Surface Electromyography." Sensors 18, no. 8 (2018): 2705. http://dx.doi.org/10.3390/s18082705.

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The advent of powered prosthetic ankles provided more balance and optimal energy expenditure to lower amputee gait. However, these types of systems require an extensive setup where the parameters of the ankle, such as the amount of positive power and the stiffness of the ankle, need to be setup. Currently, calibrations are performed by experts, who base the inputs on subjective observations and experience. In this study, a novel evidence-based tuning method was presented using multi-channel electromyogram data from the residual limb, and a model for muscle activity was built. Tuning using this

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12

Chen, Dongdong, Linwei Wang, Xingjun Luo, et al. "Recent Development and Perspectives of Optimization Design Methods for Piezoelectric Ultrasonic Transducers." Micromachines 12, no. 7 (2021): 779. http://dx.doi.org/10.3390/mi12070779.

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A piezoelectric ultrasonic transducer (PUT) is widely used in nondestructive testing, medical imaging, and particle manipulation, etc., and the performance of the PUT determines its functional performance and effectiveness in these applications. The optimization design method of a PUT is very important for the fabrication of a high-performance PUT. In this paper, traditional and efficient optimization design methods for a PUT are presented. The traditional optimization design methods are mainly based on an analytical model, an equivalent circuit model, or a finite element model and the design

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13

Kong, Xiangsong, Changqing Shi, Hang Liu, Pengcheng Geng, Jiabin Liu, and Yasen Fan. "Performance Optimization of a Steam Generator Level Control System via a Revised Simplex Search-Based Data-Driven Optimization Methodology." Processes 10, no. 2 (2022): 264. http://dx.doi.org/10.3390/pr10020264.

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A Steam generator is a crucial device of a nuclear power plant. Control performance of the steam generator level control system is key to its normal operation. To improve its performance, the control system parameters should be optimized by utilizing a proper optimization method. Furthermore, the method’s efficiency is critical for its operability in the actual plant. However, the steam generator level process is a complex process, with high nonlinearity and time-varying properties. Traditional parameters tuning methods are experience-based, cumbersome, and time-consuming. To address the chall

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14

Shi, Zheyuan Ryan. "AI for Social Good: Between My Research and the Real World." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 18 (2021): 15732–33. http://dx.doi.org/10.1609/aaai.v35i18.17863.

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AI for social good (AI4SG) is a research theme that aims to use and advance AI to improve the well-being of society. My work on AI4SG builds a two-way bridge between the research world and the real world. Using my unique experience in food waste and security, I propose applied AI4SG research that directly addresses real-world challenges which have received little attention from the community. Drawing from my experience in various AI4SG application domains, I propose bandit data-driven optimization, the first iterative prediction-prescription framework and a no-regret algorithm PROOF. I will ap

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15

Kang, Liuwang, Ankur Sarker, and Haiying Shen. "Velocity Optimization of Pure Electric Vehicles with Traffic Dynamics and Driving Safety Considerations." ACM Transactions on Internet of Things 2, no. 1 (2021): 1–24. http://dx.doi.org/10.1145/3433678.

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As Electric Vehicles (EVs) become increasingly popular, their battery-related problems (e.g., short driving range and heavy battery weight) must be resolved as soon as possible. Velocity optimization of EVs to minimize energy consumption in driving is an effective alternative to handle these problems. However, previous velocity optimization methods assume that vehicles will pass through traffic lights immediately at green traffic signals. Actually, a vehicle may still experience a delay to pass a green traffic light due to a vehicle waiting queue in front of the traffic light. Also, as velocit

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16

Tantawy, Alshaimaa A., Zenat Ahmed, and Mahmoud M. Ali. "Applying Big Data Analytics to Retail for Improved Supply Chain Visibility." American Journal of Business and Operations Research 4, no. 1 (2021): 39–46. http://dx.doi.org/10.54216/ajbor.040104.

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Retail supply chains generate huge volumes of data that can provide valuable insights if analyzed effectively. This paper explores how retailers can leverage Big Data analytics techniques on supply chain data to gain enhanced visibility into their operations. We examine three use cases of data-driven supply chain visibility: (1) predictive replenishment to anticipate future demand and optimize inventory levels; (2) personalized assortment optimization to tailor product selections for local customer segments; and (3) optimized order fulfillment to improve delivery times and reduce transportatio

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17

Peng, Shuai, Jialu Hu, Han Xiao, Shujie Yang, and Changqiao Xu. "Viewport-Driven Adaptive 360◦ Live Streaming Optimization Framework." Journal of Networking and Network Applications 1, no. 4 (2022): 139–49. http://dx.doi.org/10.33969/j-nana.2021.010401.

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Virtual reality (VR) video streaming and 360◦ panoramic video have received extensive attention in recent years, which can bring users an immersive experience. However, the ultra-high bandwidth and ultra-low latency requirements of virtual reality video or 360◦ panoramic video also put tremendous pressure on the carrying capacity of the current network. In fact, since the user’s field of view (a.k.a viewport) is limited when watching a panoramic video and users can only watch about 20%∼30% of the video content, it is not necessary to directly transmit all high-resolution content to the user. T

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18

Chotikunnan, Phichitphon, Rawiphon Chotikunnan, Anuchit Nirapai, Anantasak Wongkamhang, Pariwat Imura, and Manas Sangworasil. "Optimizing Membership Function Tuning for Fuzzy Control of Robotic Manipulators Using PID-Driven Data Techniques." Journal of Robotics and Control (JRC) 4, no. 2 (2023): 128–40. http://dx.doi.org/10.18196/jrc.v4i2.18108.

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In this study, a method for optimizing membership function tuning for fuzzy control of robotic manipulators using PID-driven data techniques is presented. Traditional approaches for designing membership functions in fuzzy control systems often rely on the experience and knowledge of the system designer, which can lead to suboptimal performance. By utilizing data collected from a PID control system, the proposed method aims to enhance the precision and controllability of robotic manipulators through improved fuzzy logic control. A Mamdani-type fuzzy logic controller was developed and its perfor

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19

Kupchak, Connor, Jerry Battista, and Jake Van Dyk. "Experience-driven dose-volume histogram maps of NTCP risk as an aid for radiation treatment plan selection and optimization." Medical Physics 35, no. 1 (2007): 333–43. http://dx.doi.org/10.1118/1.2815943.

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20

Li, Jiajia. "Data-Driven Prediction of Students’ Online Learning Needs and Optimization of Knowledge Library Management." International Journal of Emerging Technologies in Learning (iJET) 18, no. 18 (2023): 150–64. http://dx.doi.org/10.3991/ijet.v18i18.43503.

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Thanks to the advancement of information technology, online learning has become a crucial tool of modern education, and the management of modern education is facing the challenges of how to effectively predict students’ learning needs and how to optimize the management of the knowledge library to support these needs. However, existing data-driven prediction approaches are flawed in handling complex learning environments and timely adapting to changes, so this study attempts to solve these questions by exploring the correlation between learning needs, the extraction of knowledge linkages, and t

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21

Wang, Gaofeng, and Changhoon Shin. "Influencing Factors of Usage Intention of Metaverse Education Application Platform: Empirical Evidence Based on PPM and TAM Models." Sustainability 14, no. 24 (2022): 17037. http://dx.doi.org/10.3390/su142417037.

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We explored the influencing factors of the usage intention of a metaverse education application platform that directly influence the optimization of its service function, improve the usage intention, and realize the promotion and application of metaverse technology in the education domain. Based on the characteristics of the metaverse education application platform, we integrated the PPM (push–pull–mooring) model and the TAM (technology acceptance model) to construct the model of influencing factors of usage intention. Ultimately, 275 valid questionnaires were collected through expert demonstr

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22

Du, Zhuoming, Junfeng Zhang, and Bo Kang. "A Data-Driven Method for Arrival Sequencing and Scheduling Problem." Aerospace 10, no. 1 (2023): 62. http://dx.doi.org/10.3390/aerospace10010062.

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Decision support tools for arrival sequencing and scheduling could assist air traffic controllers in managing the arrival aircraft in terminal areas. However, one critical issue is that the current method for dealing with the arrival sequencing and scheduling problem does not consider the dynamic traffic situation and the human working experience, which results in a deviation between the scheduled and actual landing sequences. This paper develops a data-driven method to address this issue. Firstly, the random forest model is applied to predict the estimated time of arrival (ETA). During the ET

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23

Ming, Zhao, Xiuhua Li, Chuan Sun, Qilin Fan, Xiaofei Wang, and Victor C. M. Leung. "Sleeping Cell Detection for Resiliency Enhancements in 5G/B5G Mobile Edge-Cloud Computing Networks." ACM Transactions on Sensor Networks 18, no. 3 (2022): 1–30. http://dx.doi.org/10.1145/3512893.

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The rapid increase of data traffic has brought great challenges to the maintenance and optimization of 5G and beyond, and some smart critical infrastructures, e.g., small base stations (SBSs) in cellular cells, are facing serious security and failure threats, causing resiliency degradation concerns. Among special smart critical infrastructure failures, the sleeping cell failure is hard to address since no alarm is generally triggered. Sleeping cells can remain undetected for a long time and can severely affect the quality of service/quality of experience to users. To enhance the resiliency of

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24

Bertoni, Alessandro. "MITIGATING UNCERTAINTY IN CONCEPTUAL DESIGN USING OPERATIONAL SCENARIO SIMULATIONS: A DATA-DRIVEN EXTENSION OF THE EVOKE APPROACH." Proceedings of the Design Society 3 (June 19, 2023): 2665–74. http://dx.doi.org/10.1017/pds.2023.267.

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AbstractThe paper presents an approach where the iterative replication of Discrete Event Simulations on future operational scenarios is used to derive data-driven design merit functions. The presented contribution proposes an extension of the EVOKE (Early Value Oriented Design Exploration with Knowledge Maturity) approach determining when and how the experience-based judgment about maximization, minimization, optimization, and avoidance functions, correlating value drivers and quantified objectives, can be substituted by data-driven mathematical functions obtained by scenarios simulations. The

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25

Ye, Lixiao, Nan Zhang, Guanghui Li, Dungang Gu, Jiaqi Lu, and Yuhang Lou. "Intelligent Optimization Design of Distillation Columns Using Surrogate Models Based on GA-BP." Processes 11, no. 8 (2023): 2386. http://dx.doi.org/10.3390/pr11082386.

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The design of distillation columns significantly impacts the economy, energy consumption, and environment of chemical processes. However, optimizing the design of distillation columns is a very challenging problem. In order to develop an intelligent technique to obtain the best design solution, improve design efficiency, and minimize reliance on experience in the design process, a design methodology based on the GA-BP model is proposed in this paper. Firstly, a distillation column surrogate model is established using the back propagation neural network technique based on the training data from

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26

Xu, Chen, Decun Dong, Dongxiu Ou, and Changxi Ma. "Time-of-day Control Double-Order Optimization of Traffic Safety and Data-Driven Intersections." International Journal of Environmental Research and Public Health 16, no. 5 (2019): 870. http://dx.doi.org/10.3390/ijerph16050870.

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This paper proposes a novel two-order optimization model of the division of time-of-day control segmented points of road intersection to address the limitations of the randomness of artificial experience, avoid the complex multi-factor division calculation, and optimize the traditional model over traffic safety and data-driven methods. For the first-order optimization—that is, deep optimization of the model input data—we first increase the dimension of traditional traffic flow data by data-driven and traffic safety methods, and develop a vector quantity to represent the size, direction, and ti

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27

Aldrich, Susan E. "Recommender Systems in Commercial Use." AI Magazine 32, no. 3 (2011): 28–34. http://dx.doi.org/10.1609/aimag.v32i3.2368.

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Commercial recommender systems are deployed by marketing teams to increase revenue and/or personalize user experience. Marketers evaluate recommender systems not on its algorithms but on how well the vendor‘s expertise and interfaces will support achieving business goals. Driven by a business model that pays based on recommendation success, vendors guide clients through continuous optimization of recommendations. While recommender technology is mature, the solutions and market are still young. As a result, solutions are not fully integrated with other business systems and technology platforms.

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28

Pimentel-Niño, M. A., Paresh Saxena, and M. A. Vazquez-Castro. "Reliable Adaptive Video Streaming Driven by Perceptual Semantics for Situational Awareness." Scientific World Journal 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/394956.

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A novel cross-layer optimized video adaptation driven by perceptual semantics is presented. The design target is streamed live video to enhance situational awareness in challenging communications conditions. Conventional solutions for recreational applications are inadequate and novel quality of experience (QoE) framework is proposed which allows fully controlled adaptation and enables perceptual semantic feedback. The framework relies on temporal/spatial abstraction for video applications serving beyond recreational purposes. An underlying cross-layer optimization technique takes into account

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29

Bekasiewicz, Adrian, Slawomir Koziel, Piotr Plotka, and Krzysztof Zwolski. "EM-Driven Multi-Objective Optimization of a Generic Monopole Antenna by Means of a Nested Trust-Region Algorithm." Applied Sciences 11, no. 9 (2021): 3958. http://dx.doi.org/10.3390/app11093958.

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Antenna structures for modern applications are characterized by complex and unintuitive topologies that are difficult to develop when conventional, experience-driven techniques are of use. In this work, a method for the automatic generation of antenna geometries in a multi-objective setup has been proposed. The approach involves optimization of a generic spline-based radiator with an adjustable number of parameters using a nested, trust region-based algorithm. The latter iteratively increases the dimensionality of the radiator in order to gradually improve its performance. The method has been

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30

Lehmann, Daniel, Diego Hidalgo Rodriguez, and Michel Brack. "Optimized operation of large scale battery systems." at - Automatisierungstechnik 70, no. 1 (2022): 67–78. http://dx.doi.org/10.1515/auto-2021-0114.

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Abstract In the decentralized renewable driven electric energy system, economically viable battery systems become increasingly important for providing grid-related services. End of 2016, STEAG has successfully started the commercial operation of six 15 MW large scale battery systems which have been incorporated in STEAG’s primary control pool. During the commissioning phase, extensive effort has been spent in optimizing the operational efficiency of these systems with promising results. However, the operation experience has shown that there is still significant potential for improving the syst

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Li, Bin, Xifan Yao, Yongxiang Li, Wei Tan, Huidong Lou, and Dongyuan Ge. "Simulation & Optimization of the Gear System of a 6-DOF Manipulator Using Flexible Dynamic of ANSYS." Open Mechanical Engineering Journal 8, no. 1 (2014): 69–76. http://dx.doi.org/10.2174/1874155x01408010069.

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This paper presents a novel way for a structural dynamic simulation analysis on a three-dimensional (3-D) finite element (FE) model of a 6-DOF Manipulator using ANSYS Workbench 13.0 that allows integrated optimization. The load between driving and driven gear is delivered by elastic frictional contact, which leads to some non-liner contact problems, and the contact problems are solved according to the FE parametric programming method. This study particularly focused on investigating static, dynamic, and fatigue behaviors of the gear system in a 6-DOF robot mechanism, which is modeled using Sol

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Li, Zhengyuan, Jie Chen, Yanmei Meng, et al. "Multi-Objective Optimization of Sugarcane Milling System Operations Based on a Deep Data-Driven Model." Foods 11, no. 23 (2022): 3845. http://dx.doi.org/10.3390/foods11233845.

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The extraction of sugarcane juice is the first step of sugar production. The optimal values of process indicators and the set values of operating parameters in this process are still determined by workers’ experience, preventing adaptive adjustment of the production process. To address this issue, a multi-objective optimization framework based on a deep data-driven model is proposed to optimize the operation of sugarcane milling systems. First, the sugarcane milling process is abstracted as the interaction of material flow, energy flow, and information flow (MF–EF–IF) by introducing synergetic

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Liu, Xingdong, Daolin Xu, Hui Peng, XiaoChuan Xu, HuiDeng Liu, and Xin Zhang. "Research on Data-Driven Distribution Network Planning Method." Scientific Programming 2022 (August 16, 2022): 1–7. http://dx.doi.org/10.1155/2022/7838269.

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With the development of the intelligent and interactive power system, the elements of distribution network planning continue to increase. The distribution network connects the transmission system and individuals, directly affects the individual’s power consumption experience, and is a key link in the power system. A reasonable planning scheme can not only improve the power supply capacity and reliability of the distribution network but also fully apply the data of each system in the distribution network to realize the optimal planning of the medium-voltage distribution network driven by data.

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Tang, Wenyun, Le Xu, and Jianxiao Ma. "Modeling Autonomous Vehicles’ Altruistic Behavior to Human-Driven Vehicles in the Car following Events and Impact Analysis." Journal of Advanced Transportation 2023 (April 10, 2023): 1–14. http://dx.doi.org/10.1155/2023/4060451.

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To explore the impact of autonomous vehicles (AVs) on human-driven vehicles (HDVs), a solution for AV to coexist harmoniously with HDV during the car following period when AVs are in low market penetration rate (MPR) was provided. An extension car following framework with two possible soft optimization targets was proposed in this article to improve the experience of HDV followers with different following strategies by deep deterministic policy gradient (DDPG) algorithm. The pretreated Next Generation Simulation (NGSIM) dataset was used for the experiments. 1027 car following events with being

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Wang, Yimeng, Mridul Agarwal, Tian Lan, and Vaneet Aggarwal. "Learning-Based Online QoE Optimization in Multi-Agent Video Streaming." Algorithms 15, no. 7 (2022): 227. http://dx.doi.org/10.3390/a15070227.

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Video streaming has become a major usage scenario for the Internet. The growing popularity of new applications, such as 4K and 360-degree videos, mandates that network resources must be carefully apportioned among different users in order to achieve the optimal Quality of Experience (QoE) and fairness objectives. This results in a challenging online optimization problem, as networks grow increasingly complex and the relevant QoE objectives are often nonlinear functions. Recently, data-driven approaches, deep Reinforcement Learning (RL) in particular, have been successfully applied to network o

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Yu, Ran, Hongsheng Cheng, Yun Ye, et al. "Optimization of the Territorial Spatial Patterns Based on MOP and PLUS Models: A Case Study from Hefei City, China." International Journal of Environmental Research and Public Health 20, no. 3 (2023): 1804. http://dx.doi.org/10.3390/ijerph20031804.

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Optimization of the territorial spatial patterns can promote the functional balance and utilization efficiency of space, which is influenced by economic, social, ecological, and environmental factors. Consequently, the final implementation of spatial planning should address the issue of sustainable optimization of territorial spatial patterns, driven by multiple objectives. It has two components—the territorial spatial scale prediction and its layout simulation. Because a one-sided study of scale or layout is divisive, it is necessary to combine the two to form complete territorial spatial pat

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Kaliuta, K. "Personalizing the user experience in Salesforce using AI technologies." COMPUTER-INTEGRATED TECHNOLOGIES: EDUCATION, SCIENCE, PRODUCTION, no. 52 (September 24, 2023): 48–53. http://dx.doi.org/10.36910/6775-2524-0560-2023-52-06.

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Artificial intelligence (AI) technology has transformed the interactive marketing experience of clients. Despite a large number of studies investigating the use of AI in interactive marketing, customization as a significant concept remains unexplored in marketing using AI research and practice. authors investigate appropriate research as well as insights on Salesforce interactive advertising. The authors highlight practice challenges at various points of the customer experience and give critical managerial advice as a solution to such problems. Personalization may help your business in a varie

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Naddeo, Alessandro, and Nicola Cappetti. "Comfort driven design of innovative products: A personalized mattress case study." Work 68, s1 (2021): S139—S150. http://dx.doi.org/10.3233/wor-208013.

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BACKGROUND: Human-centred design asks for wellbeing and comfort of the customer/worker when interacting with a product. Having a good perception-model and an objective method to evaluate the experienced (dis)comfort by the product user is needed for performing a preventive comfort evaluation as early as possible in the product development plan. The mattress of a bed is a typical product whose relevance in everyday life of people is under-evaluated. Fortunately, this behaviour is quickly changing, and the customer wants to understand the product he/she buys and asks for more comfortable and for

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Alizard, F., A. Cadiou, L. Le Penven, B. Di Pierro, and M. Buffat. "Space–time dynamics of optimal wavepackets for streaks in a channel entrance flow." Journal of Fluid Mechanics 844 (April 6, 2018): 669–706. http://dx.doi.org/10.1017/jfm.2018.191.

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The laminar–turbulent transition of a plane channel entrance flow is revisited using global linear optimization analyses and direct numerical simulations. The investigated case corresponds to uniform upstream velocity conditions and a moderate value of Reynolds number so that the two-dimensional developing flow is linearly stable under the parallel flow assumption. However, the boundary layers in the entry zone are capable of supporting the development of streaks, which may experience secondary instability and evolve to turbulence. In this study, global optimal linear perturbations are compute

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Wei, Hechuan, Boyuan Xia, Zhiwei Yang, and Zhexuan Zhou. "Model and Data-Driven System Portfolio Selection Based on Value and Risk." Applied Sciences 9, no. 8 (2019): 1657. http://dx.doi.org/10.3390/app9081657.

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System portfolio selection is a kind of tradeoff analysis and decision-making on multiple systems as a whole to fulfill the overall performance on the perspective of System of Systems (SoS). To avoid the subjectivity of traditional expert experience-dependent models, a model and data-driven approach is proposed to make an advance on the system portfolio selection. Two criteria of value and risk are used to indicate the quality of system portfolios. A capability gap model is employed to determine the value of system portfolios, with the weight information determined by correlation analysis. The

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41

Liu, Yuting, Wenchong Tian, Jun Xie, Weizhong Huang, and Kunlun Xin. "LSTM-Based Model-Predictive Control with Rationality Verification for Bioreactors in Wastewater Treatment." Water 15, no. 9 (2023): 1779. http://dx.doi.org/10.3390/w15091779.

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With the increasing demands for higher treatment efficiency, better effluent quality, and energy conservation in Urban Wastewater Treatment Plants (WWTPs), research has already been conducted to construct an optimized control system for Anaerobic-Anoxic-Oxic (AAO) process using a data-driven approach. However, existing data-driven optimization control systems for AAO mainly focus on improving effluent water quality and reducing energy consumption, therefore they lack consideration for the stability of bioreactors. Meanwhile, safety in the optimization control process is still missing, resultin

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42

Burns, Geoffrey T., Kenneth M. Kozloff, and Ronald F. Zernicke. "Biomechanics of Elite Performers: Economy and Efficiency of Movement." Kinesiology Review 9, no. 1 (2020): 21–30. http://dx.doi.org/10.1123/kr.2019-0058.

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Movement is essential to the human experience, and efficient biomechanics facilitate effective action across the breadth of tasks one encounters in life. The concept of movement efficiency has been investigated and explored through a variety of means including biomechanical modeling, simulation, and experimental manipulation. Observations of elite performers for a given movement task serve as an additional line of insight into efficiency, as their movements have been driven toward optimization via competitive pressure. The authors first discuss the concept of efficiency in biomechanics from a

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43

Brain, Jennifer. "Visual Representation of Safety Cases." Measurement and Control 45, no. 3 (2012): 82–86. http://dx.doi.org/10.1177/002029401204500303.

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Historically, safety cases in the nuclear industry have tended to follow a visually similar approach; descriptive text using a (gradually evolving) template driven in part by a desire to minimise the scope of changes to legacy safety cases. However, a number of recent factors are beginning to challenge this approach. Academic work and developments in other industries are proposing new structured and diagrammatic techniques and tools such as Claims-Arguments-Evidence and Goal Structured Notation. Additionally, new build projects are offering a ‘clean-sheet’ and an opportunity to break away from

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Liu, Sixin, Yuhan Chen, Chaopeng Luo, et al. "Particle Swarm Optimization-Based Variational Mode Decomposition for Ground Penetrating Radar Data Denoising." Remote Sensing 14, no. 13 (2022): 2973. http://dx.doi.org/10.3390/rs14132973.

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Ground Penetrating Radar (GPR) has become a widely used technology in geophysical prospecting. The Variational Mode Decomposition (VMD) method is a fully non-recursive signal decomposition method with noise robustness for GPR data processing. The VMD algorithm determines the central frequency and bandwidth of each Intrinsic Mode Function (IMF) by iteratively searching for the optimal solution of the variational mode and is capable of adaptively and effectively dividing the signal in the frequency domain into the many IMFs. However, the penalty parameter α and the number of IMFs K in VMD proces

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45

Liu, Risheng, Yuxi Zhang, Shichao Cheng, Xin Fan, and Zhongxuan Luo. "A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 4368–75. http://dx.doi.org/10.1609/aaai.v33i01.33014368.

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Magnetic Resonance Imaging (MRI) is one of the most dynamic and safe imaging techniques available for clinical applications. However, the rather slow speed of MRI acquisitions limits the patient throughput and potential indications. Compressive Sensing (CS) has proven to be an efficient technique for accelerating MRI acquisition. The most widely used CS-MRI model, founded on the premise of reconstructing an image from an incompletely filled k-space, leads to an ill-posed inverse problem. In the past years, lots of efforts have been made to efficiently optimize the CS-MRI model. Inspired by dee

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Cheung, Chi Fai, Wing Bun Lee, Sandy To, H. F. Li, and Su Juan Wang. "A Framework of a Model-Based Simulation System for Prediction of Surface Generation in Fast Tool Servo Machining of Optical Microstructures." Key Engineering Materials 339 (May 2007): 407–11. http://dx.doi.org/10.4028/www.scientific.net/kem.339.407.

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The fabrication of high-quality optical microstructural surfaces is based on fast tool servo (FTS) machining. It makes use of auxiliary piezo-electric driven servos to rapidly actuate the diamond tool with a fine resolution and a sufficiently high bandwidth for machining optical microstructures with submicrometer form accuracy and a nanometric surface finish without the need for any subsequent post processing. However, the achievement of a superior mirror finish and form accuracy still depends largely on the experience and skills of the machine operators, acquired through an expensive trial-an

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VASYLKIVSKYI, Mikola, Ganna VARGATYUK, and Olga BOLDYREVA. "INTELLIGENT RADIO INTERFACE WITH THE SUPPORT OF ARTIFICIAL INTELLIGENCE." Herald of Khmelnytskyi National University. Technical sciences 217, no. 1 (2023): 26–32. http://dx.doi.org/10.31891/2307-5732-2023-317-1-26-32.

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The peculiarities of the implementation of the 6G intelligent radio interface infrastructure, which will use an individual configuration for each individual subscriber application and flexible services with lower overhead costs, have been studied. A personalized infrastructure consisting of an AI-enabled intelligent physical layer, an intelligent MAC controller, and an intelligent protocol is considered, followed by a potentially novel AI-based end-to-end (E2E) device. The intelligent controller is investigated, in particular the intelligent functions at the MAC level, which may become key com

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48

Li, Yan. "Federated Deep Reinforcement Learning-Based Caching and Bitrate Adaptation for VR Panoramic Video in Clustered MEC Networks." Electronics 11, no. 23 (2022): 3968. http://dx.doi.org/10.3390/electronics11233968.

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Virtual reality (VR) panoramic video is more expressive and experiential than traditional video. With the accelerated deployment of 5G networks, VR panoramic video has experienced explosive development. The large data volume and multi-viewport characteristics of VR panoramic videos make it more difficult to cache and transcode them in advance. Therefore, VR panoramic video services urgently need to provide powerful caching and computing power over the edge network. To address this problem, this paper establishes a hierarchical clustered mobile edge computing (MEC) network and develops a data p

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Shahbazi, Zeinab, and Slawomir Nowaczyk. "Enhancing Energy Efficiency in Connected Vehicles for Traffic Flow Optimization." Smart Cities 6, no. 5 (2023): 2574–92. http://dx.doi.org/10.3390/smartcities6050116.

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In urban settings, the prevalence of traffic lights often leads to fluctuations in traffic patterns and increased energy utilization among vehicles. Recognizing this challenge, this research addresses the adverse effects of traffic lights on the energy efficiency of electric vehicles (EVs) through the introduction of a Multi-Intersections-Based Eco-Approach and Departure strategy (M-EAD). This innovative strategy is designed to enhance various aspects of urban mobility, including vehicle energy efficiency, traffic flow optimization, and battery longevity, all while ensuring a satisfactory driv

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50

Drivas, Ioannis C., Damianos P. Sakas, Georgios A. Giannakopoulos, and Daphne Kyriaki-Manessi. "Big Data Analytics for Search Engine Optimization." Big Data and Cognitive Computing 4, no. 2 (2020): 5. http://dx.doi.org/10.3390/bdcc4020005.

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In the Big Data era, search engine optimization deals with the encapsulation of datasets that are related to website performance in terms of architecture, content curation, and user behavior, with the purpose to convert them into actionable insights and improve visibility and findability on the Web. In this respect, big data analytics expands the opportunities for developing new methodological frameworks that are composed of valid, reliable, and consistent analytics that are practically useful to develop well-informed strategies for organic traffic optimization. In this paper, a novel methodol

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