搜索结果：Psychology of sport and exercise

We present a transformer decoder based sports simulation engine, SportsNGEN, trained on sports player and ball tracking sequences, that is capable of generating sustained gameplay and accurately mimicking the decision making of real players. By training on a large database of professional tennis tracking data, we demonstrate that simulations produced by SportsNGEN can be used to predict the outcomes of rallies, determine the best shot choices at any point, and evaluate counterfactual or what if scenarios to inform coaching decisions and elevate broadcast coverage. By combining the generated simulations with a shot classifier and logic to start and end rallies, the system is capable of simulating an entire tennis match. We evaluate SportsNGEN by comparing statistics of the simulations with those of real matches between the same players. We show that the model output sampling parameters are crucial to simulation realism and that SportsNGEN is probabilistically well-calibrated to real data. In addition, a generic version of SportsNGEN can be customized to a specific player by fine-tuning on the subset of match data that includes that player. Finally, we show qualitative results indica

Digital twins belong to ten of the strategic technology trends according to the Gartner list from 2019, and have encountered a big expansion, especially with the introduction of Industry 4.0. Sport, on the other hand, has become a constant companion of the modern human suffering a lack of a healthy way of life. The application of digital twins in sport has brought dramatic changes not only in the domain of sport training, but also in managing athletes during competitions, searching for strategical solutions before and tactical solutions during the games by coaches. In this paper, the domain of digital twins in sport is reviewed based on papers which have emerged in this area. At first, the concept of a digital twin is discussed in general. Then, taxonomies of digital twins are appointed. According to these taxonomies, the collection of relevant papers is analyzed, and some real examples of digital twins are exposed. The review finishes with a discussion about how the digital twins affect changes in the modern sport disciplines, and what challenges and opportunities await the digital twins in the future.

The psychological science of artificial intelligence (AI) can be broadly defined as an emerging field of psychology that examines all AI-related mental and behavioral processes from the perspective of psychology. This field has been growing exponentially in the recent decade. This review synthesizes the existing literature on the psychological science of AI with a goal to provide a comprehensive conceptual framework for planning, conducting, and assessing scientific research in the field. It consists of six parts, starting with an overview of the entire field of the psychological science of artificial intelligence, then synthesizing the literature in each of the four specific areas (i.e., Psychology of designing AI, psychology of using AI, AI for examining psychological processes, and AI for advancing psychological methods), and concluding with an outlook on the field in the future.

Sports analytics -- broadly defined as the pursuit of improvement in athletic performance through the analysis of data -- has expanded its footprint both in the professional sports industry and in academia over the past 30 years. In this paper, we connect four big ideas that are common across multiple sports: the expected value of a game state, win probability, measures of team strength, and the use of sports betting market data. For each, we explore both the shared similarities and individual idiosyncrasies of analytical approaches in each sport. While our focus is on the concepts underlying each type of analysis, any implementation necessarily involves statistical methodologies, computational tools, and data sources. Where appropriate, we outline how data, models, tools, and knowledge of the sport combine to generate actionable insights. We also describe opportunities to share analytical work, but omit an in-depth discussion of individual player evaluation as beyond our scope. This paper should serve as a useful overview for anyone becoming interested in the study of sports analytics.

This position paper explores the intricate relationship between social psychology and secure software engineering, underscoring the vital role social psychology plays in the realm of engineering secure software systems. Beyond a mere technical endeavor, this paper contends that understanding and integrating social psychology principles into software processes are imperative for establishing robust and secure software systems. Recent studies in related fields show the importance of understanding the social psychology of other security domains. Finally, we identify critical gaps in software security research and present a set of research questions for incorporating more social psychology into software security research.

When students make a mistake in an exercise, they can consolidate it by ``similar exercises'' which have the same concepts, purposes and methods. Commonly, for a certain subject and study stage, the size of the exercise bank is in the range of millions to even tens of millions, how to find similar exercises for a given exercise becomes a crucial technical problem. Generally, we can assign a variety of explicit labels to the exercise, and then query through the labels, but the label annotation is time-consuming, laborious and costly, with limited precision and granularity, so it is not feasible. In practice, we define ``similar exercises'' as a retrieval process of finding a set of similar exercises based on recall, ranking and re-rank procedures, called the \textbf{FSE} problem (Finding similar exercises). Furthermore, comprehensive representation of the semantic information of exercises was obtained through representation learning. In addition to the reasonable architecture, we also explore what kind of tasks are more conducive to the learning of exercise semantic information from pre-training and supervised learning. It is difficult to annotate similar exercises and the annotatio

The main objective of this article is to describe the physics of Speed Skydiving, world's fastest non-motorized sport practiced under FAI -- Fédération Aéronautique Internationale (World Air Sports Federation), a recognized body by the International Olympic Committee -- with the help of standard physics and mathematics taught during the first or second year for undergraduate students in physics worldwide. Although this discipline of air sports has been around since the middle of the 1990s and has been a part of major international sport events, it is not yet well-known to the wider public and has not been addressed thoroughly in physics textbooks as the physics of various other sports. It is hoped that this paper will introduce and engage physics teachers/instructors new to this air sport discipline -- pedagogically. University or high school students may find this article helpful while studying a subject of terminal speeds, which is thoroughly discussed herein. This article can also serve as a background for further studies in physics of skydiving and aerodynamics.

This paper presents a qualitative analysis of participants' perceptions of a robotic coach conducting Positive Psychology exercises, providing insights for the future design of robotic coaches. Participants (n = 20) took part in a single-session (avg. 31 +- 10 minutes) Human-Robot Interaction study in a laboratory setting. We created the design of the robotic coach, and its affective adaptation, based on user-centred design research and collaboration with a professional coach. We transcribed post-study participant interviews and conducted a Thematic Analysis. We discuss the results of that analysis, presenting aspects participants found particularly helpful (e.g., the robot asked the correct questions and helped them think of new positive things in their life), and what should be improved (e.g., the robot's utterance content should be more responsive). We found that participants had no clear preference for affective adaptation or no affective adaptation, which may be due to both positive and negative user perceptions being heightened in the case of adaptation. Based on our qualitative analysis, we highlight insights for the future design of robotic coaches, and areas for future inv

Historically, females were excluded from clinical research due to their reproductive roles, hindering medical understanding and healthcare quality. Despite guidelines promoting equal participation, females are underrepresented in exercise science, perpetuating misconceptions about female physiology. Even less attention has been given to exercise in the pregnant population. Research on pregnancy and exercise has evolved considerably from the initial bedrest prescriptions but concerns about exercise risks during pregnancy persisted for many decades. Recent guidelines endorse moderate-intensity physical activity during pregnancy, supported by considerable evidence of its safety and benefits. Mental health during pregnancy, often overlooked, is gaining traction, with exercise showing promise in reducing depression and anxiety. While pregnancy guidelines recommend moderate-intensity physical activity, there remains limited understanding of optimal frequency, intensity, type and time (duration) for extremes like elite athletes or those with complications. Female participation in elite sport and physically demanding jobs is rising, but research on their specific needs is lacking. Traditio

Over the last decade, there has been a significant increase in the development of mobile applications to deliver various services in sports, including psychological skills training (PST) for athletes. While there are numerous PST-related apps available, little attention has been given to their objective quality. This study aimed to assess the current offerings of PST apps in sports, rate their quality, and provide recommendations for future app development. A scoping review of PST-related apps available on the Apple App Store was conducted, resulting in the retention of 19 apps. The apps used different media types to develop the PST. Of the 19 apps, videos were used by 8 (42%), audios by 7 (37%), articles by 3 (16%), assessment by 4 (21%), ebook by 1 (5%), and both cognitive tasks and personalized journals by 2 (10%). Overall, the app quality measured through the Mobile App Rating Scale (MARS) failed to meet acceptable standards, with a mean rating of 2.78 and only 6 of the apps receiving a score that met the acceptable standards. The findings highlight the need for improvement in the development of PST apps to enhance their quality and usability.

Sport climbing, which made its Olympic debut at the 2020 Summer Games, generally consists of three separate disciplines: speed climbing, bouldering, and lead climbing. However, the International Olympic Committee (IOC) only allowed one set of medals each for men and women in sport climbing. As a result, the governing body of sport climbing, rather than choosing only one of the three disciplines to include in the Olympics, decided to create a competition combining all three disciplines. In order to determine a winner, a combined scoring system was created using the product of the ranks across the three disciplines to determine an overall score for each climber. In this work, the rank-product scoring system of sport climbing is evaluated through simulation to investigate its general features, specifically, the advancement probabilities and scores for climbers given certain placements. Additionally, analyses of historical climbing contest results are presented and real examples of violations of the independence of irrelevant alternatives are illustrated. Finally, this work finds evidence that the current competition format is putting speed climbers at a disadvantage.

Education artificial intelligence aims to profit tasks in the education domain such as intelligent test paper generation and consolidation exercises where the main technique behind is how to match the exercises, known as the finding similar exercises(FSE) problem. Most of these approaches emphasized their model abilities to represent the exercise, unfortunately there are still many challenges such as the scarcity of data, insufficient understanding of exercises and high label noises. We release a Chinese education pre-trained language model BERT$_{Edu}$ for the label-scarce dataset and introduce the exercise normalization to overcome the diversity of mathematical formulas and terms in exercise. We discover new auxiliary tasks in an innovative way depends on problem-solving ideas and propose a very effective MoE enhanced multi-task model for FSE task to attain better understanding of exercises. In addition, confidence learning was utilized to prune train-set and overcome high noises in labeling data. Experiments show that these methods proposed in this paper are very effective.

Large language models (LLMs) exhibit expert-level performance in tasks across a wide range of different domains. Ethical issues raised by LLMs and the need to align future versions makes it important to know how state of the art models reason about moral and legal issues. In this paper, we employ the methods of experimental psychology to probe into this question. We replicate eight studies from the experimental literature with instances of Google's Gemini Pro, Anthropic's Claude 2.1, OpenAI's GPT-4, and Meta's Llama 2 Chat 70b. We find that alignment with human responses shifts from one experiment to another, and that models differ amongst themselves as to their overall alignment, with GPT-4 taking a clear lead over all other models we tested. Nonetheless, even when LLM-generated responses are highly correlated to human responses, there are still systematic differences, with a tendency for models to exaggerate effects that are present among humans, in part by reducing variance. This recommends caution with regards to proposals of replacing human participants with current state-of-the-art LLMs in psychological research and highlights the need for further research about the distincti

The aim of this paper is to promote quantum logic as one of the basic tools for analyzing human reasoning. We compare it with classical (Boolean) logic and highlight the role of violation of the distributive law for conjunction and disjunction. It is well known that nondistributivity is equivalent to incompatibility of logical variables -- the impossibility to assign jointly the two-valued truth values to these variables. A natural question arises as to whether quantum logical nondistributivity in human logic can be tested experimentally. We show that testing the response replicability effect (RRE) in cognitive psychology is equivalent to testing nondistributivity -- under the prevailing conjecture that the mental state update generated by observation is described as orthogonal projection of the mental state vector (the projective update conjecture of Wang and Busemeyer). A simple test of RRE is suggested. In contrast to the previous works in quantum-like modeling, we proceed in the state-dependent framework; in particular, distributivity, compatibility, and RRE are considered in a fixed mental state. In this framework, we improve the previous result on the impossibility to combine

This paper is a shortened version of the full paper that was published in the journal Frontiers of Psychology in May 2022. In recent decades, the scientific study of consciousness has significantly increased our understanding of this elusive phenomenon. Yet, despite critical development in our understanding of the functional side of consciousness, we still lack a fundamental theory regarding its phenomenal aspect. The phenomenal aspect of consciousness is the first-person answer to what it is like question, and it has thus far proved recalcitrant to direct scientific investigation. The question of how the brain, or any cognitive system, can create conscious experience out of neural representations poses a great conundrum to science. Naturalistic dualists argue that it is composed of a primitive, private, nonreductive element of reality. Illusionists, on the other hand, argue that it is merely a cognitive illusion. We contend that both the dualist and illusionist positions are flawed because they tacitly assume consciousness to be an absolute property that does not depend on the observer. We developed a conceptual and a mathematical argument for a relativistic theory of consciousnes

There are numerous opportunities for engaging in research at the intersection of psychology and visualization. While most opportunities taken up by the VIS community will likely focus on the psychology of users, there are also opportunities for studying the psychology of designers. In this position paper, I argue the importance of studying design cognition as a necessary component of a holistic program of research on visualization psychology. I provide a brief overview of research on design cognition in other disciplines, and discuss opportunities for VIS to build an analogous research program. Doing so can lead to a stronger integration of research and design practice, can provide a better understanding of how to educate and train future designers, and will likely surface both challenges and opportunities for future research.

The prediction of the long-term impact of a scientific article is challenging task, addressed by the bibliometrician through resorting to a proxy whose reliability increases with the breadth of the citation window. In the national research assessment exercises using metrics the citation window is necessarily short, but in some cases is sufficient to advise the use of simple citations. For the Italian VQR 2011-2014, the choice was instead made to adopt a linear weighted combination of citations and journal metric percentiles, with weights differentiated by discipline and year. Given the strategic importance of the exercise, whose results inform the allocation of a significant share of resources for the national academic system, we examined whether the predictive power of the proposed indicator is stronger than the simple citation count. The results show the opposite, for all discipline in the sciences and a citation window above two years.

Background. There are many factors that can make of group exercises a challenging setting for older adults. A major one in the elderly population is the difference in the level of skills. In this paper we report on the physical, psychological and social wellbeing outcomes of a novel virtual gym that enables online group-exercises in older adults with different levels of skills. Methods. A total of 37 older adults (65-87 years old) followed a personalized exercise program based on the OTAGO program for fall prevention, for a period of eight weeks. Participants could join online group exercises using a tablet-based application. Participants were assigned either to a Control group (individual training) or Social group (online group-exercising). Pre- and post- measurements were taken to analyze the physical, psychological and social wellbeing outcomes. The study received ethical approval from the CREATE-NET Ethics Committee on ICT Research Involving Human Beings (Application N. 2014-001). Results. There were improvements in both the Social and Control groups in terms of physical outcomes. Interestingly though, while in the Control group fitter individuals tended to adhere more to the t

We present a novel method for the numerical pricing of American options based on Monte Carlo simulation and the optimization of exercise strategies. Previous solutions to this problem either explicitly or implicitly determine so-called optimal exercise regions, which consist of points in time and space at which a given option is exercised. In contrast, our method determines the exercise rates of randomized exercise strategies. We show that the supremum of the corresponding stochastic optimization problem provides the correct option price. By integrating analytically over the random exercise decision, we obtain an objective function that is differentiable with respect to perturbations of the exercise rate even for finitely many sample paths. The global optimum of this function can be approached gradually when starting from a constant exercise rate. Numerical experiments on vanilla put options in the multivariate Black-Scholes model and a preliminary theoretical analysis underline the efficiency of our method, both with respect to the number of time-discretization steps and the required number of degrees of freedom in the parametrization of the exercise rates. Finally, we demonstrate