Relevant bibliographies by topics / Human Performance Optimization

Academic literature on the topic 'Human Performance Optimization'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Human Performance Optimization"

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Deuster, Patricia A., and Francis G. OʼConnor. "Human Performance Optimization." Journal of Strength and Conditioning Research 29 (November 2015): S52—S56. http://dx.doi.org/10.1519/jsc.0000000000001118.

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Nindl, Bradley C., Dianna P. Jaffin, Michael N. Dretsch, Samuel N. Cheuvront, Nancy J. Wesensten, Michael L. Kent, Neil E. Grunberg, et al. "Human Performance Optimization Metrics." Journal of Strength and Conditioning Research 29 (November 2015): S221—S245. http://dx.doi.org/10.1519/jsc.0000000000001114.

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Hatfield, Bradley D., Calvin M. Lu, and Jo B. Zimmerman. "Optimization of Human Performance." Kinesiology Review 9, no. 1 (February 1, 2020): 1–3. http://dx.doi.org/10.1123/kr.2019-0065.

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Austin, Krista G., and Patricia A. Deuster. "Monitoring Training for Human Performance Optimization." Journal of Special Operations Medicine 15, no. 2 (2015): 102. http://dx.doi.org/10.55460/evu4-w8lw.

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Russell, Adam, and Patricia A. Deuster. "Human Performance Optimization and Precision Performance: The Future of Special Operations Human Performance Efforts." Journal of Special Operations Medicine 17, no. 1 (2017): 80. http://dx.doi.org/10.55460/xfyj-equn.

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Chi, Chia-Fen, and Colin Drury. "Limits to human optimization in inspection performance." International Journal of Systems Science 32, no. 6 (January 2001): 689–701. http://dx.doi.org/10.1080/00207720117646.

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Sell, Timothy C., Robert H. Lutz, and Mallory S. Faherty. "The Warrior Model for Human Performance Optimization." Sports Medicine and Arthroscopy Review 27, no. 3 (September 2019): 99–106. http://dx.doi.org/10.1097/jsa.0000000000000248.

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Xu, Yangsheng, Jingyan Song, Michael C. Nechyba, and Yeung Yam. "Performance evaluation and optimization of human control strategy." Robotics and Autonomous Systems 39, no. 1 (April 2002): 19–36. http://dx.doi.org/10.1016/s0921-8890(02)00169-0.

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Zhang, Pinggai, Ling Wang, Jiaojie Du, Zixiang Fei, Song Ye, Minrui Fei, and Panos M. Pardalos. "Differential Human Learning Optimization Algorithm." Computational Intelligence and Neuroscience 2022 (April 30, 2022): 1–19. http://dx.doi.org/10.1155/2022/5699472.

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Human Learning Optimization (HLO) is an efficient metaheuristic algorithm in which three learning operators, i.e., the random learning operator, the individual learning operator, and the social learning operator, are developed to search for optima by mimicking the learning behaviors of humans. In fact, people not only learn from global optimization but also learn from the best solution of other individuals in the real life, and the operators of Differential Evolution are updated based on the optima of other individuals. Inspired by these facts, this paper proposes two novel differential human learning optimization algorithms (DEHLOs), into which the Differential Evolution strategy is introduced to enhance the optimization ability of the algorithm. And the two optimization algorithms, based on improving the HLO from individual and population, are named DEHLO1 and DEHLO2, respectively. The multidimensional knapsack problems are adopted as benchmark problems to validate the performance of DEHLOs, and the results are compared with the standard HLO and Modified Binary Differential Evolution (MBDE) as well as other state-of-the-art metaheuristics. The experimental results demonstrate that the developed DEHLOs significantly outperform other algorithms and the DEHLO2 achieves the best overall performance on various problems.
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Liu, Hao, Gang Xu, Gui-yan Ding, and Yu-bo Sun. "Human Behavior-Based Particle Swarm Optimization." Scientific World Journal 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/194706.

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Particle swarm optimization (PSO) has attracted many researchers interested in dealing with various optimization problems, owing to its easy implementation, few tuned parameters, and acceptable performance. However, the algorithm is easy to trap in the local optima because of rapid losing of the population diversity. Therefore, improving the performance of PSO and decreasing the dependence on parameters are two important research hot points. In this paper, we present a human behavior-based PSO, which is called HPSO. There are two remarkable differences between PSO and HPSO. First, the global worst particle was introduced into the velocity equation of PSO, which is endowed with random weight which obeys the standard normal distribution; this strategy is conducive to trade off exploration and exploitation ability of PSO. Second, we eliminate the two acceleration coefficientsc1andc2in the standard PSO (SPSO) to reduce the parameters sensitivity of solved problems. Experimental results on 28 benchmark functions, which consist of unimodal, multimodal, rotated, and shifted high-dimensional functions, demonstrate the high performance of the proposed algorithm in terms of convergence accuracy and speed with lower computation cost.
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Dissertations / Theses on the topic "Human Performance Optimization"

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Pranoto, Yudi. "Effects of Human Decision Bias in Supply Chain Performance." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7545.

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Studies in newsvendor decision-making have shown that human decisions systematically deviate from analytical solutions found in many utility models of the single period problem (SPP). Yet for the most part the impacts of this human decision bias in systems of newsvendor type products have not been investigated. We study bias in human decision-making to determine how different factors affect the performance of systems of newsvendor type products. We extended the state of the arts utility models of SPP to analyze the effects of individuals wealth on individual decision-making. Our theoretical and empirical results proved that individuals wealth significantly affected individual decision-making. Specifically, our analysis concluded that wealthier individual ordered more than poorer individual did when presented with the same investment opportunity. We created a human decision bias (HDB) model to include different newsvendor ordering policies that individuals could use to determine their order quantities. This model is set up to investigate individuals reliance on different ordering policies under different experimental conditions. We designed multi period newsvendor experiments to study effects of factors such as item profit margin, wealth, value of learning, and salvage value on decision-maker's order quantity. We found that wealth and profit margin factors significantly affected individual newsvendor decision-making. Learning, gender, and salvage value factor did not exhibit significant effects in our empirical studies. We designed multi period multi echelon newsvendor experiments to study effects of factors such as the relationship between newsvendors, item profit margin, and newsvendors' wealth on the performance of two-echelon newsvendors system. We found item profit margin, wealth, and relationship between supplier and retailer to significantly affect newsvendor decision-making. Finally, we present a case study of US fresh produce industry to illustrate the impacts of human decision bias on the performance of a supply chain system.
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Marang, Ah Zau. "Analysis of web performance optimization and its impact on user experience." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231445.

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User experience (UX) is one of the most popular subjects in the industry nowadays and plays a significant role in the business success. As the growth of a business depends on customers, it is essential to emphasize on the UX that can help to enhance customer satisfaction. There has been statements that the overall end-user experience is to a great extent influenced by page load time, and that UX is primarily associated with performance of applications. This paper analyzes the effectiveness of performance optimization techniques and their impact on user experience. Principally, the web performance optimization techniques used in this study were caching data, fewer HTTP requests, Web Workers and prioritizing content. A profiling method Manual Logging was utilized to measure performance improvements. A UX survey consists of User Experience Questionnaire (UEQ) and three qualitative questions, was conducted for UX testing before and after performance improvements. Quantitative and qualitative methods were used to analyze collected data. Implementations and experiments in this study are based on an existing tool, a web-based application. Evaluation results show an improvement of 45% on app load time, but no significant impact on the user experience after performance optimizations, which entails that web performance does not really matter for the user experience. Limitation of the performance techniques and other factors that influence the performance were found during the study.
Användarupplevelse (UX) är idag en av de mest populära ämnena inom IT-branschen och spelar en viktig roll i affärsframgångar. Eftersom tillväxten av ett företag beror på kunder är det viktigt att betona på UX som kan bidra till att öka kundnöjdheten. Det har konstaterats att den övergripande slutanvändarupplevelsen i stor utsträckning påverkas av sidladdningstiden och att UX huvudsakligen är förknippad med applikationernas prestanda. I denna studie analyseras effektiviteten av optimeringstekniker och deras inverkan på användarupplevelse. Huvudsakligen, optimeringstekniker som användes i denna studie var cache-lösning, färre HTTP-förfrågningar, Web Workers och prioritering av innehåll. Profileringsmetoden "Manual Logging" användes för att mäta prestandaförbättringar. En enkätutvärdering som består av User Experience Questionnaire (UEQ) och tre kvalitativa frågor, genomfördes med fokus på användarupplevelsen före och efter prestandaförbättringar. Kvantitativa och kvalitativa metoder användes för att analysera insamlade data. Implementeringar och experiment i denna studie är baserade på ett befintligt verktyg, en webbaserad applikation. Utvärderingsresultatet visar en förbättring på 45% när det gäller sidladdningstid men ingen signifikant inverkan på användarupplevelsen efter prestandaförbättringar, vilket innebär att webbprestanda inte spelar någon roll för användarupplevelsen. Begränsning av optimeringstekniker och andra faktorer som påverkar prestationen hittades under studien.
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Al, Khatib Sultan. "A comparative study of the relative performance and real-world suitability of optimization approaches for Human Resource Allocation." Thesis, University of East Anglia, 2018. https://ueaeprints.uea.ac.uk/68211/.

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The problem of Staffing and Scheduling a Software Project (SSSP), where we consider Human Resource Allocation (HRA) to minimize project time, offers a management challenge for Project Managers (PM’s). Unlike the general HRA problem, SSSP involves determination of the assignment of a fixed amount of resources to teams and the allocation of these teams to project’s jobs. SSSP problem arises across a diverse range of resources’ and project characteristics (discrete variables), and this variety has offered a wide range of HRA methods. The general consensus is that the benchmark for SSSP are Meta-heuristic optimization techniques using deterministic or stochastic simulation of time. However, different HRA methods and project attributes are considered by SSSP approaches, and their solutions need to be compared against each other. The majority of SSSP approaches provide their approximation using Genetic Algorithm (GA) validated by a synthetic data or empirical method such as Quasi-experiment. Limited studies offer the comparison between these SSSP approaches, either by a comprehensive survey or systematic literature review for qualitative concepts. We aim to answer a set of research questions including: what is the best way to show the quality and performance differences between SSSP approaches? And, are these SSSP approaches suitable for industrial adoption? Our thesis is that the best methodology is to identify according to the conceptual models used by the approaches a set of challenging data levels. In support of our thesis, we propose a systematic benchmarking and evaluation approach that encompass the data levels, and a set of quality measures. Next, we propose an empirical study that assess how PMs from software industry perform the allocation given the same datasets. The results of both works demonstrate significant differences between the approaches, highlighted four methods that advances the research filed, and provide interesting discussion on the PMs’ practices on SSSP.
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De, las Casas Zolezzi Humberto Jose. "Model-Free Optimization of Trajectory and Impedance Parameters on Exercise Robots with Applications to Human Performance and Rehabilitation." Cleveland State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=csu1625490714196286.

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Lahiani, Nouha. "Méthode hybride d'affectation des ressources humaines pour l'amélioration de la performance de la maintenance." Thesis, Paris 8, 2015. http://www.theses.fr/2015PA080037.

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Cette thèse propose un outil d’aide à la décision pour la gestion de processus de maintenance basée surune affectation optimale des ressources humaines afin d’améliorer la performance de la maintenance.En effet, une bonne performance de la fonction maintenance est indispensable pour maintenir laproductivité des installations industrielles, et donc de la compétitivité des entreprises manufacturières.L’approche que nous développons dans ce manuscrit procure un cadre de référence des leviersd’actions envisageables pour mesurer, évaluer, améliorer et optimiser la performance de lamaintenance. Nous prenons en considération un problème d’affectation des ressources humaines, quiprend en compte non seulement leurs disponibilités et compétences, mais aussi la gestion des urgencesd’intervention sur terrain.La méthode que nous proposons est basée sur un modèle de simulation à événements discrets,reproduisant au mieux un service de maintenance. Ceci nous a permis d’évaluer la situation via desindicateurs de performance présélectionnés. Pour optimiser le système, nous proposons un couplagedu modèle de simulation avec un module d’optimisation indépendant qui se réfère à une métaheuristiquebasée sur une approche Pareto. Notre proposition a été testée dans une entrepriseindustrielle réelle.L’approche que nous proposons donne un ensemble de solutions d’affectation des ressourceshumaines, aidant le décideur à mieux gérer l’indisponibilité de ses outils. Nous obtenons de bonsrésultats en un temps raisonnable
In this thesis, a decision-making tool for maintenance management process based on assignment ofhuman resources is proposed in order to improve maintenance performance. An optimal maintenanceperformance is indispensable to guarantee the productivity and competitiveness of manufacturingcompanies.The proposed approach provides a framework of different possible levers to measure, evaluate,improve and optimize the maintenance performance. The assignment of human resources problem isconsidered. It takes into account different constraints like human resources availability, competences,urgency degree management of interventions requests etc.The proposed method is based on a discrete event simulation model, providing a better presentation ofthe maintenance service and better comprehensive thanks to the performance indicators. To improveuntil optimize the model, a simulation-based Pareto optimization method is introduced. Optimizationmodule was coded on independent programs in order to provide an opportunity of control thesimulation based optimization process.The proposed simulation based optimization method find good solutions in a reasonable amount oftime. Applying this technique on an industrial case-study, we show that it is more effective indetecting real faults than existing alternatives. The approach can be extended to cover other domainsand other types of simulation models
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Lefebvre, Mickael. "Gestion automatisée de l’énergie d’un avion de transport civil : application aux phases de descente et d’approche." Thesis, Toulouse, ISAE, 2012. http://www.theses.fr/2012ESAE0016.

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La première année de thèse a permis de mettre en avant deux aspects concernant la problématique de gestion de l’énergie, à savoir le contrôle court terme et le contrôle long terme de l’énergie respectivement. La première problématique a été étudiée pendant la deuxième année de thèse et a débouché sur la proposition d’une architecture de contrôle multi-actionneurs utilisant les moteurs et les aérofreins dans l’objectif d’augmenter l’autorité de contrôle de l’énergie de l’avion. La seconde problématique a été étudiée pendant la troisième année et a débuté par une étude préliminaire reposant sur le calcul d’une séquence optimale de commandes des becs/volets et train d’atterrissage permettant d’amener l’avion à un certain niveau d’énergie en approche tout en minimisant l’utilisation des moteurs et des aérofreins. Par la suite, l’étude a été étendue afin de prendre en compte la régulation des moteurs, l’utilisation des aérofreins et la modification de la trajectoire verticale. Finalement,une solution basée sur un calcul d’optimisation a été développée puis intégrée au sein d’un simulateur de bureau temps-réel, testée avec une interface homme machine adéquat et pour finir présentée à des pilotes d’essais pour validation
The first year of thesis allowed to foreground two aspects of the energy management issue,namely the short term control and the long term control, respectively. The first issue was studied during the second year and ended with the proposition of a solution mixing both the airbrakes and engines. The second and last issue started with a preliminary study which consisted of computing an optimal slat/flap command sequence bringing the aircraft to theright energy level in approach while minimizing the use of engines and airbrakes. Then, this study was extended in order to take into account the regulation of engines and airbrakes aswell as vertical trajectory modification. Finally, this optimization-based solution has been integrated within an accurate real-time desktop simulator, tested with a human-machine interface, and then presented to flight test pilots for validation
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Ramos, Calderón Antonio José. "Computational and accuracy benchmarking of simulation and system-theoretic models for production systems engineering." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19877.

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The modern industry has an increasing demand for simulation software able to help workers and decision-makers visualize the outputs of a specific process in a fast, accurate way. In this report, a comparative study between FACTS (Factory Analyses in ConcepTual phase using Simulation), Plant Simulation, and PSE (Production System Engineering) Toolbox is done regarding their capacity to simulate models with increasing complexity, how accurate they are in their outputs with different optimized buffer allocations, and how well they perform on the task of detecting the bottlenecks of a process. Benchmarking simulation software requires an experimental approach, and for gathering and organizing all the data generated using external programs like MATLAB, C, Excel, and R are used. A high level of automatization is required as otherwise the manual input of data would take too long to be effective.The results conclude on major concordances among FACTS and Plant Simulation as the most used commercial DES (Discrete Event Simulation) software and a more mathematical-theoretical approach coming from PSE Toolbox. The optimization done in the report links to sustainability, with an enhanced TH improving the ecological, social and economic aspects, and to Lean philosophy using lean buffers that smooth and improve the production flow.
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Gomes, Alcindo Delgado. "Rentabilização de Capital Humano." Master's thesis, 2016. http://hdl.handle.net/10400.26/15044.

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A Escola Naval apresenta uma taxa de insucesso na ordem dos 64%, acabando por perder, durante o decorrer do curso, mais de metade dos indivíduos admitidos. Este projeto surge com o intuito de perceber as causas associadas ao baixo rendimento, através da análise dos dados dos indivíduos desde a candidatura ao término do curso, para identificar as caraterísticas (designadas de variáveis) dos indivíduos com maior e com menor probabilidade de sucesso na Escola Naval. Os dados são inicialmente analisados graficamente, onde os candidatos são analisados de forma independente, e os admitidos e os finalistas são analisados em conjunto para se avaliar o comportamento das variáveis no início e no fim dos cursos. Um aumento do peso de uma variável no grupo dos finalistas em relação ao grupo dos admitidos é interpretado como um indicador de bom desempenho. É, ainda, utilizada uma análise estatística para avaliar a associação entre o sucesso e cada uma das variáveis no grupo dos admitidos, e, também, para validar as ilações obtidas através da análise gráfica. O estudo revelou que os indivíduos que entram para a Escola Naval com melhores notas e os indivíduos que tomam conhecimento do concurso de candidatura através da internet são os que apresentam uma maior predisposição para o sucesso, enquanto os indivíduos que têm ambos os pais no ativo são os que apresentam menor probabilidade de sucesso.
The Portuguese Naval Academy has an academic failure rate of around 64%. More than half of the admitted students do not finish the course. This project arises in order to understand the causes associated to the low performance, by analyzing the data of individuals from the beginning to the end of the course, to identify the characteristics (called variables) of individuals with higher and lower probability of success at the Naval Academy. Initially the data is studied graphically, where candidates are analyzed independently. Then the admitted students and the finalists are analyzed together to assess the behavior of the variables at the beginning and at the end of the courses. An increase of a weight of a variable in the group of finalists in relation to the group of admitted students is interpreted as an indicator of a good performance. It is also used a statistical analysis to evaluate the relationship between success and each variable in the group of the admitted student and also to validate the conclusions obtained from graphical analysis. The study indicates that individuals who enter the Naval Academy with better grades and individuals who found out about the application process over the internet have greater predisposition for success. On the other hand, individuals whose both parents are professionally active have less probability to succeed.
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Books on the topic "Human Performance Optimization"

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Matthews, Michael D., and David M. Schnyer, eds. Human Performance Optimization. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190455132.001.0001.

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Advances in cognitive neuroscience, engineering, and related fields suggest new ways of optimizing human performance. Especially for organizations that operate in high-stakes, high-stress, and competitive settings, helping individual workers and teams improve and sustain performance represents a desirable outcome. Moreover, to the extent that strategies to improve performance allow individuals to grow and flourish, enhancing performance is also a desirable outcome for workers. This volume addresses state-of-the-art scientifically grounded approaches to optimizing human performance. Collectively, the topics addressed integrate performance optimization strategies across several disciplines that speak to performance enhancement. A common theme is the need to include ethical considerations in any decision to implement human performance optimization strategies. The book concludes with a summary and synthesis of currently attainable approaches to performance enhancement and approaches that may emerge in the near future based on further research and development.
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Matthews, Michael D., and David M. Schnyer. Human Performance Optimization: The Science and Ethics of Enhancing Human Capabilities. Oxford University Press, Incorporated, 2019.

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Bi, Xiaojun, Brian Smith, Tom Ouyang, and Shumin Zhai. Soft Keyboard Performance Optimization. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198799603.003.0006.

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Optimization techniques have played a vital role in improving the performance (i.e., input speed and accuracy) of soft keyboards. This chapter introduces the challenges, methodologies, and results of keyboard performance optimization. Leveraging the robust human motor control phenomena manifested in text entry, we used the Metropolis random walk algorithm, and Pareto multi-objective optimization method to optimize the keyboard layout and a soft keyboard decoder. The optimization led to layouts that shorten finger travel distance and improve the input speed as well as accuracy over the Qwerty layout, and a soft keyboard decoder with improved correction and completion ability.
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Matthews, Michael D. Head Strong. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190870478.001.0001.

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Since the publication of the first edition of Head Strong: How Psychology Is Revolutionizing War in 2014, developments in military psychology have been rapid and important—so much so that this revised edition is necessary to accurately capture the vital role that psychology continues to play in twenty-first-century military success. The ideas contained in the first edition influenced emerging doctrine in the Army’s Human Dimension and informed military leaders around the globe of ways that psychological science and practice may be leveraged to improve combat effectiveness. Many of the predictions made in the first edition have come true, and new and exciting products of military psychology now offer novel ways of impacting military outcomes. This revised edition of Head Strong updates the 13 chapters included in the first edition with breaking news in military psychology and adds new material to augment those chapters. Two entirely new chapters are included in this edition. The first focuses on human performance optimization. It captures rapid developments in psychology, cognitive neuroscience, and other disciplines that may help the military optimize soldier and unit performance. The second dives deeply into character and discusses how to measure it, how to develop it, and how character plays a vital role in the performance of individual soldiers and their units. Like the other topics in Head Strong, these two new chapters have significant applicability to nonmilitary organizations including schools, corporations, and sports teams.
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Book chapters on the topic "Human Performance Optimization"

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Gao, Shuo, Shuo Yan, Hang Zhao, and Arokia Nathan. "Performance Optimization." In Touch-Based Human-Machine Interaction, 109–54. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68948-3_5.

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Connaboy, Christopher, Matthew E. Darnell, Shawn Eagle, Caleb D. Johnson, and Bradley C. Nindl. "Emerging Concepts in Human Performance Optimization." In Return to Play in Football, 17–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-55713-6_2.

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Wu, Xiaoli, Chengqi Xue, Feng Zhou, Linlin Wang, Weiwei Zhang, Tingting Zhang, and Ling Xia. "Optimization of Information Interaction Interface Based on Error-Cognition Mechanism." In Advances in Human Error, Reliability, Resilience, and Performance, 142–54. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20037-4_13.

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Zhang, Cheng, Zhe Sun, Pingbo Tang, Shawn W. St. Germain, and Ronald Boring. "Simulation-Based Optimization of Resilient Communication Protocol for Nuclear Power Plant Outages." In Advances in Human Error, Reliability, Resilience, and Performance, 20–29. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60645-3_3.

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Block, Joachim, and Stefan Pickl. "A Human Resource Model for Performance Optimization to Gain Competitive Advantage." In Operations Research Proceedings 2013, 43–48. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07001-8_7.

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Meghvansi, Mukesh Kumar, Richa Arya, N. K. Tripathi, Vijai Pal, and A. K. Goel. "Inoculum Optimization Strategies for Improving Performance of Anaerobic Biodigester: Current Trends and Future Perspectives." In Anaerobic Biodigesters for Human Waste Treatment, 233–48. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4921-0_12.

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Messeri, Costanza. "Enhancing the Quality of Human-Robot Cooperation Through the Optimization of Human Well-Being and Productivity." In Special Topics in Information Technology, 15–25. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15374-7_2.

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AbstractIn human-robot interaction frameworks maximizing the team efficiency is crucial. However, it is also essential to mitigate the physical and cognitive workload experienced by the shop-floor worker during the collaborative task. In this chapter we first investigate the impact of the robot interaction role (whether being leader or follower during cooperation) on both the human physiological stress and production rate. Based on that, a game-theoretic approach is proposed to model the trade-off between the maximization of the human performance and the minimization of the human cognitive stress. Then, we describe a closed-loop robot control strategy that, based on the proposed game-theoretic model, enables the robot to simultaneously minimize the human cognitive stress and maximize his/her performance during cooperation, by adjusting its role. Eventually, a real-time task allocation strategy is proposed to both ensure the minimization of the human physical fatigue and the effectiveness of the production process. This method relies on a new sophisticated musculoskeletal model of the human upper-body. All these methodologies have been experimentally tested in realistic human-robot collaborative scenarios involving several volunteers and the ABB IRB 14000 dual-arm “YuMi" collaborative robot.
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Sanwal, Tanushree, and Puja Sareen. "Social Intelligence as a Tool for Human Performance Optimization During Post COVID 19: A Review." In Lecture Notes in Mechanical Engineering, 292–301. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9523-0_33.

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Pérez-Blanco, C. D. "Navigating Deep Uncertainty in Complex Human–Water Systems." In Springer Climate, 169–78. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86211-4_20.

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AbstractComplex human–water systems are deeply uncertain. Policymakers are not aware of all possible futures (deep uncertainty type 2), while the probability of those futures that can be identified ex-ante is typically unknown (deep uncertainty type 1). In this context, standard decision-making based on a complete probabilistic description of future conditions and optimization of expected performance is no longer appropriate; instead, priority should be given to robustness, through the identification of policies that are (i) insensitive to foreseeable changes in future conditions (classical robustness that addresses deep uncertainty type 1) and (ii) adaptive to unforeseen contingencies (adaptive robustness that addresses deep uncertainty type 2). This research surveys recent advances in (socio-)hydrology and (institutional) economics toward robust decision-making. Despite significant progress, integration among disciplines remains weak and allows only for a fractioned understanding and partial representation of uncertainty. To bridge this gap, I will argue that science needs to further underpin the development and integration of two pieces of ex-ante information: (1) a modeling hierarchy of human–water systems to assess policy performance under alternative scenarios and model settings, so as to navigate deep uncertainty type 1 and (2) a longitudinal accounting and analysis of public transaction costs to navigate deep uncertainty type 2.
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Sharif, Muddsair, Charitha Buddhika Heendeniya, and Gero Lückemeyer. "ARaaS: Context-Aware Optimal Charging Distribution Using Deep Reinforcement Learning." In iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, 199–209. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92096-8_12.

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AbstractElectromobility has profound economic and ecological impacts on human society. Much of the mobility sector’s transformation is catalyzed by digitalization, enabling many stakeholders, such as vehicle users and infrastructure owners, to interact with each other in real time. This article presents a new concept based on deep reinforcement learning to optimize agent interactions and decision-making in a smart mobility ecosystem. The algorithm performs context-aware, constrained optimization that fulfills on-demand requests from each agent. The algorithm can learn from the surrounding environment until the agent interactions reach an optimal equilibrium point in a given context. The methodology implements an automatic template-based approach via a continuous integration and delivery (CI/CD) framework using a GitLab runner and transfers highly computationally intensive tasks over a high-performance computing cluster automatically without manual intervention.
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Conference papers on the topic "Human Performance Optimization"

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Colella, Fabio, Pedram Daee, Jussi Jokinen, Antti Oulasvirta, and Samuel Kaski. "Human Strategic Steering Improves Performance of Interactive Optimization." In UMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3340631.3394883.

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Marler, Timothy, Kimberly Farrell, Joo Kim, Salam Rahmatalla, and Karim Abdel-Malek. "Vision Performance Measures for Optimization-Based Posture Prediction." In 2006 Digital Human Modeling for Design and Engineering Conference. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2006. http://dx.doi.org/10.4271/2006-01-2334.

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Zlatkin, Audrey, Costas Koufogazos, and Gwen Campbell. "Behavior-based performance optimization in military training environments." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002420.

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The quality of instruction Warfighters receive can substantially influence mission readiness. As such, it is important that military instructors develop and maintain instructional competencies to adequately promote relevant knowledge and skills among trainees. However, unlike K-12 educators, active-duty military instructors are not often provided opportunities for formal instructional training; that is, training on how to teach (Malone, Vogel-Walcutt, Ross, & Phillips, 2014). While their content, domain knowledge, and leadership skills are strong, military instructors lack “expert instructor techniques” and skill in implementing useful strategies to convey their knowledge to trainees. They are typically not afforded time and resources to develop these skills prior to taking charge of training new members of the Armed Forces. There was a need to design training tools for accelerating mastery among military instructors via rapid acquisition of high-quality instructional skills to ensure effective learning and retention among trainees.To address this challenge, Design Interactive developed an adaptive training tool, the Interactive Military Instructor Training and Assessment Technology (IMITATE). There was a focus on incorporating research-based training interventions such as video self-modeling, prompting, performance reflection, practice and feedback to support accelerated mastery of observable skills. The goal of the IMITATE program was to optimize the learning experience for military instructors with a tool that they could utilize to sharpen and receive interactive feedback on the skills that are crucial to being a good instructor. The system implements customizable rating systems made up of key performance areas (KPAs), broken down into observable behaviors with detailed rating anchors. This creates a competency- based approach for instructors, who through IMITATE, can receive structured, personalized feedback to quickly bridge performance gaps. IMITATE utilizes a three-stage approach for training – Prepare, Practice, and Assess. The Prepare stage provides introductory video-based observation and training that identifies the KPAs and behaviors and illustrates expert performance in the form of lessons. In the Practice stage, instructors practice their skills while receiving standardized, behavior-based assessment through an intuitive rating tool that provides observers with guidance on how to rate, promoting consistency between observers. The final stage, Assess, is where results are captured and displayed for immediate, actionable, structured and personalized feedback. A video-based after-action review offers session playback paired with time-synced ratings to highlight effective or ineffective performance. Built-in analytics enable performance comparisons between individuals and groups over time. Usability for IMITATE is consistently being assessed and refined based on end-user feedback. This iterative, user-centered design process enables a learning tool that is easy to use and applicable across a variety of domains. Integrating these research-based training interventions with a user-centered design process enabled the Design Interactive team to build upon existing military training protocols to enhance instructor competence, reduce instructor development costs, and improve mission readiness. This method is currently informing additional R&Defforts across the Marine Corps and Air Force and has been tested across a wide range of use cases from military, medical, academic, and industrial settings.
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Faruqui, Nuruzzaman, and Mohammad Abu Yousuf. "Performance-accuracy Optimization of Face Detection in Human Machine Interaction." In 2019 5th International Conference on Advances in Electrical Engineering (ICAEE). IEEE, 2019. http://dx.doi.org/10.1109/icaee48663.2019.8975661.

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Savaş, Serkan, Nurettin Topaloğlu, Ömer Kazcı, and Pınar Nercis Koşar. "Performance Comparison of Carotid Artery Intima Media Thickness Classification by Deep Learning Methods." In International Congress on Human-Computer Interaction, Optimization and Robotic Applications. SETSCI, 2019. http://dx.doi.org/10.36287/setsci.4.5.025.

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Ahmed, Ali Hameed, Saif H. Alrubaee, Hussein Kadhim Hasan, and Alaa Hamid Mohammed. "Energy Efficiency Performance For Next Generation Wireless Communications." In 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE, 2022. http://dx.doi.org/10.1109/hora55278.2022.9800054.

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Tutuncu, Bilal. "Microstrip Antenna for 5G Communication: Design and Performance Analysis." In 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE, 2020. http://dx.doi.org/10.1109/hora49412.2020.9152855.

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Adegboye, Oluwatayomi Rereloluwa, and Ezgi Deniz Ulker. "A Quick Performance Assessment for Artificial Electric Field Algorithm." In 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE, 2022. http://dx.doi.org/10.1109/hora55278.2022.9799867.

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Zhou, Dongdong, Xiaobing Chen, Chuangchuang Zhang, Shuxin Guo, Khadka Ashim, and Jianchu Lin. "Research on Topological Deformation of 3D Human Image Based on Laplace Optimization." In 2022 International Conference on High Performance Big Data and Intelligent Systems (HDIS). IEEE, 2022. http://dx.doi.org/10.1109/hdis56859.2022.9991706.

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Kun-fa, Li, Chen Jing-chun, and Wang Yan-xi. "Big Data Informatization Applied to Optimization of Human Resource Performance Management." In the 2019 2nd International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3357292.3357302.

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Reports on the topic "Human Performance Optimization"

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Al-Qadi, Imad, Egemen Okte, Aravind Ramakrishnan, Qingwen Zhou, and Watheq Sayeh. Truck Platooning on Flexible Pavements in Illinois. Illinois Center for Transportation, May 2021. http://dx.doi.org/10.36501/0197-9191/21-010.

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Truck platoons have many benefits over traditional truck mobility. Truck platoons have the potential to improve safety and reduce fuel consumption between 5% and 15%, based on platoon configuration. In Illinois, trucks carry more than 50% of freight tonnage and constitute 25% of the traffic on interstates. Therefore, expected fuel savings would be significant for trucks. Deployment of truck platoons within interstate highways may have a direct effect on flexible pavement performance, as the time between consecutive axle loads (i.e., resting time) is expected to decrease significantly. Moreover, platoons could potentially accelerate pavement damage accumulation due to trucks’ channelized position, decreasing pavement service life and increasing maintenance and rehabilitation costs. The main objective of this project was to quantify the effects of truck platoons on pavements and to provide guidelines to control corresponding potential pavement damage. Finite-element models were utilized to quantify the impact of rest period on pavement damage. Recovered and accumulated strains were predicted by fitting exponential functions to the calculated strain profiles. The results suggested that strain accumulation was negligible at a truck spacing greater that 10 ft. A new methodology to control pavement damage due to truck platoons was introduced. The method optimizes trucks’ lateral positions on the pavements, and an increase in pavement service life could be achieved if all platoons follow this optimization method. Life cycle assessment and life cycle cost analysis were conducted for fully autonomous, human-driven, and mixed-traffic regimes. For example, for an analysis period of 45 years, channelized truck platoons could save life cycle costs and environmental impacts by 28% and 21% compared with human-driven trucks, respectively. Furthermore, optimum truck platoon configuration could reduce life cycle costs and environmental impacts by 48% and 36%, respectively, compared with human-driven trucks. In contrast, channelized traffic could increase pavement roughness, increasing fuel consumption by 15%, even though platooning vehicles still benefit from reduction in air drag forces. Given that truck platoons are expected to be connected only in the first phase, no actions are required by the agency. However, in the second phase when truck platoons are also expected to be autonomous, a protocol for driving trends should be established per the recommendation of this study.
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