Search Results (47)

Virtual reality (VR) has become increasingly popular and has started entering homes, schools, and clinics, yet evidence on how children interact during free-form, unguided play remains limited. Understanding how interaction dynamics relate to player performance is essential for designing more accessible and engaging VR experiences, especially in educational contexts. For this reason, we developed VRBloons, a child-friendly VR game about popping balloons. The game logs real-time gameplay telemetry such as total hand movement, accuracy, throw rate, and other performance related gameplay data. By analyzing several feature-engineered metrics using unsupervised clustering and non-parametric statistical validation, we aim to identify distinct behavioral patterns. The analysis revealed several associations between input preferences, movement patterns, and performance outcomes, forming clearly distinct clusters. From the performed analysis, input preference emerged as an independent dimension of play style, supporting the inclusion of redundant input mappings to accommodate diverse motor capabilities. Additionally, the results highlight the opportunities for performance-sensitive assistance systems that adapt the difficulty of the game in real time. Overall, this study demonstrates how telemetry-based profiling can shape the design decisions in VR experiences, offering a methodological framework for assessing varied interaction styles and a diverse player population. Full article

Background/Objectives: The integration of strength training in grassroots youth soccer remains limited, often due to persistent myths regarding its safety and utility. This study evaluated the effectiveness of a tailored, playful strength training program in young players and analyzed the influence of the Relative Age Effect (RAE) on physical development and training response. Methods: A 14-week quasi-experimental pretest–posttest design was conducted with 27 federated male soccer players aged 9–10 years (experimental: n = 15; control: n = 12). The intervention consisted of twice-weekly, game-based strength training sessions integrated into the regular team routine. Outcomes included validated anthropometric (BMI) and functional (handgrip strength, standing long jump, Illinois agility test) indicators. RAE was analyzed according to birth quartile. Non-parametric statistical analyses and effect size (r) calculations were used. Results: The experimental group achieved significantly greater pre–post gains in handgrip strength than controls (right and left). Agility and standing long jump improved within the experimental group, but between-group differences were not significant. BMI decreased within the experimental group, yet the net between-group difference in BMI change was not significant in the context of a higher baseline BMI (p = 0.047). Although the Relative Age Effect (RAE) influenced baseline BMI, no moderating effect was detected on performance variables or training-induced changes in this sample. Conclusions: In U10 soccer players, a playful, context-integrated strength program produced superior gains in handgrip strength compared with usual practice. Improvements in agility and standing long jump were observed within the intervention group, but did not exceed those of the controls. BMI changes were not different between the groups and must be interpreted with caution, given baseline imbalances. In this sample, RAE did not moderate training response. Full article

Purpose: Pickleball, the fastest-growing sport in the United States, has seen a rapid increase in participation across all age groups, particularly among older adults. However, the sport introduces specific risks for ocular injuries due to the unique dynamics of gameplay and the physical properties of the pickleball. This study aims to explore the mechanisms of pickleball-related eye injuries, utilizing finite element modeling (FEM) to simulate ocular trauma and better understand injury mechanisms. Methods: A multi-modal approach was employed to investigate pickleball-related ocular injuries. Finite element modeling (FEM) was used to simulate blunt trauma to the eye caused by a pickleball. The FEM incorporated detailed anatomical models of the periorbital structures, cornea, sclera, and vitreous body, using hyperelastic material properties derived from experimental data. The simulations evaluated various impact scenarios, including changes in ball velocity, angle of impact, and material stiffness, to determine the stress distribution, peak strain, and deformation in ocular structures. The FEM outputs were correlated with clinical findings to validate the injury mechanisms. Results: The FE analysis revealed that the rigid, hard-plastic construction of a pickleball results in concentrated stress and strain transfer to ocular structures upon impact. At velocities exceeding 30 mph, simulations showed significant corneal deformation, with peak stresses localized at the limbus and anterior sclera. Moreover, our results show a significant stress applied to lens zonules (as high as 0.35 MPa), leading to potential lens dislocation. Posterior segment deformation was also observed, with high strain levels in the retina and vitreous, consistent with clinical observations of retinal tears and vitreous hemorrhage. Validation against reported injuries confirmed the model’s accuracy in predicting both mild injuries (e.g., corneal abrasions) and severe outcomes (e.g., hyphema, globe rupture). Conclusions: Finite element analysis provides critical insights into the biomechanical mechanisms underlying pickleball-related ocular injuries. The findings underscore the need for preventive measures, particularly among older adults, who exhibit age-related vulnerabilities. Education on the importance of wearing protective eyewear and optimizing game rules to minimize high-risk scenarios, such as close-range volleys, is essential. Further refinement of the FEM, including parametric studies and integration of protective eyewear, can guide the development of safety standards and reduce the socio-economic burden of these injuries. Full article

Emerging trends in technology are providing opportunities for a broader range of accessible and assistive technologies (AATs) to positively impact persons with disabilities in terms of independent living and employment within and across built environments. However, such technologies typically require significant investments by entities that offer such options. It is not clear how such firms compete in a market with other firms that may not provide such options. Understanding such competition can help to promote greater investments in accessibility infrastructure within built environments by entities and provide insights into how federal efforts can further boost such efforts. To this end, this paper presents a game-theoretic framework of market competition between two firms where one invests in accessibility (bearing additional upfront costs) and compares it with another one that does not. Numerical evaluations demonstrate the range of parametric values where accessibility investments pay off. Furthermore, case studies are presented to demonstrate the practical feasibility of these parameter values. The results indicate that any firm considering making accessibility investments can expect to make profits and also gain an advantage over its competitors if the expected increase in the average user experience is significant (quantified as 20% or more for the parameters considered in this work) across all potential users. Full article

Background: Basketball matches involve numerous conditioning factors which, when put together, make for a complex prediction event. However, unraveling all these elements in different studies allows the control of certain conditioning factors of the game, giving rise to more stable and controlled games. Objectives: Due to the absence of studies that analyze professional matches in women’s basketball, the aim of the present research is to analyze the influence of the result, partial result and specific positions on the load in official competition between two women’s teams that play a match simultaneously. Methods: Using an ex post facto design, 19 professional players were measured in an official match of the Spanish second division of women’s basketball, monitoring both opponents simultaneously, obtaining at all times the contrast of loads between both teams. Inertial devices were used to measure the external and internal load of each player. Parametric and non-parametric statistical difference analyses were performed, as well as two linear mixed models. Results: The results reveal significant differences in external loading when loads are analyzed as a function of match outcome. Differences between external and internal load are found when taking into account specific positions, and when including several comparisons in the analysis. The team that obtained the highest kinematic and neuromuscular load demands was the one that won the match. The specific position of guard obtained a greater physical load at the end of the match than the centers. Conclusions: Coaches should prioritize high-intensity training that replicates match demands, considering positional differences in workload to optimize player conditioning and recovery strategies for sustained performance. Full article

Demand response management (DRM) significantly influences the prospective advancement of electricity smart grids. This paper introduces three distinct game-theoretic duopoly models for the smart grid demand response management problem. It delineates several rational assumptions regarding the model variables, functions, and parameters. The first model adopts a Cournot duopoly form, offering a unique closed-form equilibrium solution. The second model adopts a Stackelberg duopoly structure, also providing a unique closed-form equilibrium solution. Following a comparison of the economic viability of the two model equilibria and an assessment of their sensitivity to parametric changes, the paper proposes a third model with a Cartel structure and discusses its advantages over the earlier models. Finally, the paper examines how demand forecasting affects the equilibrium quantities and pricing solutions of each model. Full article

With the advent of big data, the swift advancement of diverse algorithmic technologies has enhanced the transaction efficiency of the e-commerce business. Nevertheless, it is crucial to acknowledge that e-commerce platforms might employ algorithmic technology to enforce differential pricing for various consumers with the aim of maximizing profits, thus infringing upon the lawful rights and interests of consumers. This paper focuses on the algorithmic price discrimination commonly observed on e-commerce platforms. To effectively regulate this behavior, the paper utilizes evolutionary game theory (EGT) to analyze the strategies employed by e-commerce platforms, consumers, and market regulators to achieve stability. This research employs a real-life situation and utilizes parametric simulation to visualize and analyze the process and outcomes of the three-party evolutionary game. The results demonstrate the credibility and feasibility of the article’s findings. Based on our research, we have reached the following findings: During the process of evolution, the strategic decisions made by the game participants from the three parties will mutually impact each other, and various elements exert varying degrees of influence on the strategic choices made by the game participants from each party. Collaborative governance can enable consumers and market regulators to regulate the discriminatory pricing behavior of e-commerce platforms effectively. This article offers valuable insights into the governance of violations in the e-commerce sector based on robust data and model research. Full article

This research aimed to propose a new methodological approach for analyzing relative age effect (RAE) in different sports or samples named “Relative age effect overall scale” (RAEOS). The sample consisted of 1455 male and female young athletes who competed in four different sports (basketball, n = 159; handball, n = 215; swimming, n = 981; taekwondo, n = 100) at the Youth Olympic Games (YOG) in Buenos Aires in 2018. To construct the new model, the sample was classified into four unified quartiles of a specific range depending on the sport (swimming: 48-month range, taekwondo: 24-month range, and basketball and handball: 36-month range). Expected and observed frequencies for each sport, the winners/all athletes, and differences between team and individual sports were analyzed using a non-parametric Chi-square test. The obtained results confirm the existence of the RAE in all four analyzed sports (p > 0.01) in a sample of all participants and the sample of gold medalists. Differences between team and individual sports in the analyzed sample have also been found. The proposed methodological approach (RAEOS) is a simple and applicable tool that provides opportunities for comparison and analysis of different sports and competition formats, as well as improvement of the sports talent system in the context of RAE issues. It is suggested to the sports decision-makers to improve the YOG qualification and competition system to enable fairer competition and reduce the influence of RAE on the performance and development of young athletes. Full article

This article investigates the performance of the Weighted Shortest Processing Time (WSPT) rule as a local sequencing policy in a scheduling game for uniformly related parallel machines, where the social objective is the total weighted completion time. Our research aims to establish improved upper bounds for the price of anarchy in this game. We determine two bounds, incorporating parameters that characterize the instance family, such as the speed of the fastest machine ($s_m$) and the number of machines (m). One bound establishes a fixed upper bound for the price of anarchy, while the other outperforms the parametric upper bound found in the existing literature. These newly derived bounds provide better insights into the performance of the scheduling game under study, proving that the price of anarchy is upper bounded by $min\left\{s_m\left(1+1/2s_m-1/2m\right),m,4\right\}$. Full article

Objective: To assess the quality and readability of online information on holmium laser enucleation of the prostate in managing benign prostate hyperplasia using the most-used search engine worldwide, Google. Methods: Google search terms “Holmium laser surgery” and “enlarged prostate” were used to generate 150 search results. Two independent authors (i) excluded any paywall, scientific literature, or advertisement and (ii) conducted an independent assessment on information quality, which was based on DISCERN, QUEST, and JAMA criteria, and readability, which was based on the FKG, GFI, SMOG, and FRE scores on qualified webpages. A third author was involved if there were any discrepancies between the assessments. Results: 107 qualified webpages were included in the data analysis. The median DISCERN score was 42 out of 80 (IQR 35–49). The median JAMA score was 0 out of 4 (IQR 0–1). The median QUEST score was 9 out of 28 (IQR 9–12). Using the non-parametric ANOVA and post hoc Games–Howell test, significant differences were identified between rankings of webpages. Sponsorship had no influence on the quality of webpages. The overall readability level required a minimum reading level of grade 11. Linear regression analysis showed that a higher ranked webpage is a positive predictor for all three quality assessment tools. Conclusions: The overall quality of online information on HoLEP is poor. We identify that the top-ranked google searches have a higher DISCERN score and are a positive predictor for DISCERN/QUEST/JAMA. Quality online information can benefit patients but should be used in conjunction with professional medical consultation. Full article

We consider a class of finite-dimensional variational inequalities where both the operator and the constraint set can depend on a parameter. Under suitable assumptions, we provide new estimates for the Lipschitz constant of the solution, which considerably improve previous ones. We then consider the problem of computing the mean value of the solution with respect to the parameter and, to this end, adapt an algorithm devised to approximate a Lipschitz function whose analytic expression is unknown, but can be evaluated in arbitrarily chosen sample points. Finally, we apply our results to a class of Nash equilibrium problems, and generalized Nash equilibrium problems on networks. Full article

The conditions for safe Internet access and the development of skills enabling full participation in online environments are recognized in the Council of Europe’s strategy for child rights, from 2022. The guarantee of this right has implications for experiences inside and outside the school context. Therefore, this study aims to compare the perceptions of students from different educational levels, who participated in a digital storytelling workshop, regarding online safety, searching habits, and digital competences. Data were collected through a questionnaire survey completed by 84 Portuguese students from elementary and secondary schools. A non-parametric multivariate analysis of variance was used to identify differences as children advanced across educational stages. The results revealed that secondary students tended to spend more time online and demonstrated more advanced search skills. Interestingly, the youngest children exhibited higher competences in creating games and practicing safety measures regarding online postings. These findings emphasize the importance of schools, in a joint action with the educational community, including parents, teachers and students, in developing a coordinated and vertically integrated approach to digital education that considers the children’s current knowledge, attitudes, and skills as a starting point for pedagogical intervention. Full article

Color visualization of the DNA of diverse living beings can help in the exploration of the issue of chromatic differentiation of functional mappings of the nucleotide composition of DNA molecules. By “chromatic differentiation”, we mean the coloring of these mappings. Algorithms for coloring genetic representations improve the perception of complex genetic information using color. Methodologically, to build the chromatic differentiation of functional mappings of the nucleotide composition of DNA, we employed the system of nucleotide Walsh functions and the Chaos Game Representation (CGR) algorithm. The authors compared these two approaches and proposed a modified CGR algorithm. The work presents various algorithms of chromatic differentiation based on the nucleotide Walsh functions at a specific location of the fragment in the nucleotide chain and on the frequencies of those fragments. The results of the analysis provide examples of chromatic differentiation in a variety of parametric spaces. The paper describes various approaches to coloring and video animation of DNA molecules in their chromatically differentiated spans of physicochemical parameters. Full article

In recent years, Model Based Systems Engineering (MBSE) has continued to develop as a standard for designing, managing, and maintaining increasingly complex systems. Unlike the document centric approach, MBSE puts the model at the heart of system design. Among the various MBSE language development efforts, “Systems Modeling Language (SysML)”, is the most anticipated and broadly utilized in the research and in industrial practice. SysML originated from Unified Modeling Language (UML) and follows the Object-Oriented Systems Engineering Method (OOSEM). SysML diagrams help users create various systems engineering artifacts, including requirements, use cases, operational concepts, system architecture, system behaviors, and parametric analyses of a system model. In the early days of implementation, MBSE languages, including SysML, typically relied on static viewpoints and limited simulation support to depict and analyze a system model. Due the continuous improvement efforts and new implementation approaches by researchers and organizations, SysML has advanced vastly to encompass dynamic viewpoints, in-situ simulation and enable integration with external modeling and simulation (M&S) tools. Virtual Reality (VR) has emerged as a user interactive and immersive visualization technology and can depict reality in a virtual environment at different levels of fidelity. VR can play a crucial role in developing dynamic and interactive viewpoints to improve the MBSE approach. In this research paper, the authors developed and implemented a methodology for integrating SysML and VR, enabling tools to achieve three dimensional viewpoints, an immersive user experience and early design evaluations of the system of interest (SOI). The key components of the methodology being followed in this research paper are the SysML, a VR environment, extracted data and scripting languages. The authors initially developed a SysML for a ground-based telescope system following the four pillars of SysML: Structure, Requirements, Behavior and Parametrics. The SysML diagram components are exported from the model using the velocity template language and then fed into a virtual reality game engine. Then, the SysML diagrams are visualized in the VR environment to enable better comprehension and interaction with users and Digital Twin (DT) technologies. In addition, a VR simulation scenario of space objects is generated based on the input from the SysML, and the simulation result is sent back from the VR tool into the model with the aid of parametric diagram simulation. Hence, by utilizing the developed SysML-VR integration methodology, VR environment scenarios are successfully integrated with the SysML. Finally, the research paper mentions a few limitations of the current implementation and proposes future improvements. Full article

Deep generative models, such as deep Boltzmann machines, focused on models that provided parametric specification of probability distribution functions. Such models are trained by maximizing intractable likelihood functions, and therefore require numerous approximations to the likelihood gradient. This underlying difficulty led to the development of generative machines such as generative stochastic networks, which do not represent the likelihood functions explicitly, like the earlier models, but are trained with exact backpropagation rather than the numerous approximations. These models use piecewise linear units that are having well behaved gradients. Generative machines were further extended with the introduction of an associative adversarial network leading to the generative adversarial nets (GANs) model by Goodfellow in 2014. The estimations in GANs process two multilayer perceptrons, called the generative model and the discriminative model. These are learned jointly by alternating the training of the two models, using game theory principles. However, GAN has many difficulties, including: the difficulty of training the models; criticality in the selection of hyper-parameters; difficulty in the control of generated samples; balancing the convergence of the discriminator and generator; and the problem of modal collapse. Since its inception, efforts have been made to tackle these issues one at a time or in multiples at several stages by many researchers. However, most of these have been handled efficiently in the boundary equilibrium generative adversarial networks (BEGAN) model introduced by Berthelot et al. in 2017. In this work we presented the advent of adversarial networks, starting with the history behind the models and c developments done on GANs until the BEGAN model was introduced. Since some time has elapsed since the proposal of BEGAN, we provided an up-to-date study, as well as future directions for various aspects of adversarial learning. Full article