Hasil untuk "Recreation leadership. Administration of recreation services"

Congcong Chen, Xinyu Liu, Kaifeng Huang et al.

Graph Neural Networks (GNNs) have marked significant impact in traffic state prediction, social recommendation, knowledge-aware question answering and so on. As more and more users move towards cloud computing, it has become a critical issue to unleash the power of GNNs while protecting the privacy in cloud environments. Specifically, the training data and inference data for GNNs need to be protected from being stolen by external adversaries. Meanwhile, the financial cost of cloud computing is another primary concern for users. Therefore, although existing studies have proposed privacy-preserving techniques for GNNs in cloud environments, their additional computational and communication overhead remain relatively high, causing high financial costs that limit their widespread adoption among users. To protect GNN privacy while lowering the additional financial costs, we introduce Panther, a cost-effective privacy-preserving framework for GNN training and inference services in cloud environments. Technically, Panther leverages four-party computation to asynchronously executing the secure array access protocol, and randomly pads the neighbor information of GNN nodes. We prove that Panther can protect privacy for both training and inference of GNN models. Our evaluation shows that Panther reduces the training and inference time by an average of 75.28% and 82.80%, respectively, and communication overhead by an average of 52.61% and 50.26% compared with the state-of-the-art, which is estimated to save an average of 55.05% and 59.00% in financial costs (based on on-demand pricing model) for the GNN training and inference process on Google Cloud Platform.

Subasish Das

This paper introduces HyperSumm-RL, a hypertext-aware summarization and interaction analysis framework designed to investigate human perceptions of social robot leadership through long-form dialogue. The system utilizes a structured Natural Language Processing (NLP) workflow that combines transformer-based long dialogue summarization, leadership style modeling, and user response analysis, enabling scalable evaluation of social robots in complex human-robot interaction (HRI) settings. Unlike prior work that focuses on static or task-oriented HRI, HyperSumm-RL captures and hypertextually organizes dynamic conversational exchanges into navigable, semantically rich representations which allows researchers to trace interaction threads, identify influence cues, and analyze leadership framing over time. The contributions of this study are threefold: (1) we present a novel infrastructure for summarizing and linking long, multi-turn dialogues using leadership-style taxonomies; (2) we propose an interactive hypertext model that supports relational navigation across conversational themes, participant responses, and robot behavior modes; and (3) we demonstrate the utility of this system in interpreting participant trust, engagement, and expectation shifts during social robot leadership scenarios. The findings reveal how hypertextual workflows can augment HRI research by enabling transparent, interpretable, and semantically grounded analysis of emergent social dynamics.

Sarah Mercer, Daniel P. Martin, Phil Swatton

Generative agents powered by Large Language Models demonstrate human-like characteristics through sophisticated natural language interactions. Their ability to assume roles and personalities based on predefined character biographies has positioned them as cost-effective substitutes for human participants in social science research. This paper explores the validity of such persona-based agents in representing human populations; we recreate the HEXACO personality inventory experiment by surveying 310 GPT-4 powered agents, conducting factor analysis on their responses, and comparing these results to the original findings presented by Ashton, Lee, & Goldberg in 2004. Our results found 1) a coherent and reliable personality structure was recoverable from the agents' responses demonstrating partial alignment to the HEXACO framework. 2) the derived personality dimensions were consistent and reliable within GPT-4, when coupled with a sufficiently curated population, and 3) cross-model analysis revealed variability in personality profiling, suggesting model-specific biases and limitations. We discuss the practical considerations and challenges encountered during the experiment. This study contributes to the ongoing discourse on the potential benefits and limitations of using generative agents in social science research and provides useful guidance on designing consistent and representative agent personas to maximise coverage and representation of human personality traits.

M. J. Reilly, Ling Wang, K. Rosenman

INTRODUCTION In 2014, the Federal Occupational Safety and Health Administration (OSHA) enacted a standard requiring employers to report work-related amputations to OSHA within 24 hours. We studied the characteristics of the injured workers and employer compliance with the regulation in Michigan. METHODS Two independent data sets were used to compare work-related amputations from 2016 to 2018: employer reports to OSHA and the Michigan Multi-Source Injury and Illness Surveillance System (MMSIISS). We deterministically linked employer reports to OSHA with the MMSIISS by employee name, employer name, date, and type of amputation. RESULTS We identified 1366 work-related amputations from 2016 to 2018; 575 were reported by employers to OSHA and 1153 were reported by hospitals to the MMSIISS. An overlap of 362 workers were reported in both systems, while 213 workers were only reported by employers to OSHA and 791 workers were only reported by hospitals. Employer compliance with the regulation was 42.1%. Employer compliance with reporting was significantly less in: agriculture, forestry, fishing, and hunting (14.6%); construction (27.4%); retail trade (20.7%); arts, entertainment, and recreation (7.7%); accommodation and food services (13.0%); and other services (27.0%). Large employers and unionized employers were significantly more likely (67.9% and 92.7%, respectively) and small employers were significantly less likely (18.2%) to comply with the reporting rule. Enforcement inspections at 327 workplaces resulted in 403 violations; of those, 179 (54.7%) employers had not corrected the amputation hazard before the time of inspection. DISCUSSION Michigan employers reported less than half of the work-related amputations required by OSHA's reporting regulation. Noncompliance was greatest in small employers, and agriculture, forestry, fishing, and hunting; construction; arts, entertainment, and recreation; accommodation and food services; and retail and other service industries. Inspections found that over half of the employers had not corrected the hazard that caused the amputation at the time of the inspection's initial opening date; in these cases, abatement of any hazards identified would have occurred after the inspection. Improved compliance in employer reporting of work-related amputations will identify hazards posing a high risk of recurrence of injury to other workers from the same injury source. Greater compliance can also help target safety-related preventive and intervention efforts in industries that might otherwise be overlooked.

Sehun Oh, M. Cano, Yeonwoo Kim

BACKGROUND Drug mortality risks vary among industries, creating distinctive geographic patterns across US counties. However, less is known about how local labor market structure relates to drug overdose mortality amid the synthetic opioid era in the United States. This study investigates the relationship between industry-specific job composition and drug overdose mortality at the county level while exploring how fentanyl's presence in illicit drug supplies may moderate the relationship. METHODS Data were derived from the National Center for Health Statistics' Multiple Cause of Death files for the rates of drug overdose mortality of any intent, linked with four other sources on industry-specific job shares, drug supply, and county-level sociodemographic characteristics and opioid prescribing rates from the US Census Bureau, the CDC, and the Drug Enforcement Administration. Negative binomial regression models were employed to examine associations between county industry-specific job composition and drug overdose mortality, with tests for moderating effects of state-level fentanyl seizure rates. RESULTS Our models indicate negative associations between job shares of manufacturing, retail trade, and educational services industries and drug overdose mortality. Positive associations were found for arts/entertainment/recreation and public administration. State-level fentanyl seizure rates had moderating effects on administrative/support/waste management/remediation (A/S/WM/R) and educational services. CONCLUSION Counties with a higher concentration of arts/entertainment/recreation and public administration jobs need targeted efforts to mitigate drug-related overdose risks. Additionally, areas with higher concentrations of A/S/WM/R service jobs, particularly where fentanyl seizure rates are higher, may require proactive harm reduction strategies for reducing overdose risks.

Claudia-Elena Țuclea

Renli Wu, Christopher Esposito, James Evans

Major shifts in the global system of science and technology are destabilizing the global status order and demonstrating the capacity for emerging countries like China and India to exert greater influence. In order to measure changes in the global scientific system, we develop a framework to assess the hierarchical position of countries in the international scientific collaboration network. Using a machine-learning model to identify the leaders of 5,966,623 scientific teams that collaborated across international borders, we show that Chinese scientists substantially narrowed their leadership deficit with scientists from the US, UK, and EU between 1990 and 2023 in absolute terms. Consequently, China and the US are on track to reach an equal number of team leaders engaged in bilateral collaborations between 2027 and 2028. Nevertheless, Chinese progress has been considerably slower in per-collaborator terms: after adjusting for the number of non-leaders from each country, our models do not predict parity between the US and China until after 2087. These dynamics extend to 11 critical technology areas central to ongoing diplomacy between the two nations, such AI, Semiconductors, and Advanced Communications, and to China's scientific leadership with respect to the European Union and the United Kingdom. Thus, while China's elite scientists are achieving leadership in the international scientific community, China's scientific enterprise continues to face developmental constraints. We conclude by reviewing several steps that Chinese science is taking to overcome these constraints, by increasing its engagement in scientific training and research in signatory nations to the Belt and Road Initiative.

Hongjia Wu, Hui Zeng, Zehui Xiong et al.

Timely updating of Internet of Things data is crucial for achieving immersion in vehicular metaverse services. However, challenges such as latency caused by massive data transmissions, privacy risks associated with user data, and computational burdens on metaverse service providers (MSPs) hinder the continuous collection of high-quality data. To address these challenges, we propose an immersion-aware model trading framework that enables efficient and privacy-preserving data provisioning through federated learning (FL). Specifically, we first develop a novel multi-dimensional evaluation metric for the immersion of models (IoM). The metric considers the freshness and accuracy of the local model, and the amount and potential value of raw training data. Building on the IoM, we design an incentive mechanism to encourage metaverse users (MUs) to participate in FL by providing local updates to MSPs under resource constraints. The trading interactions between MSPs and MUs are modeled as an equilibrium problem with equilibrium constraints (EPEC) to analyze and balance their costs and gains, where MSPs as leaders determine rewards, while MUs as followers optimize resource allocation. To ensure privacy and adapt to dynamic network conditions, we develop a distributed dynamic reward algorithm based on deep reinforcement learning, without acquiring any private information from MUs and other MSPs. Experimental results show that the proposed framework outperforms state-of-the-art benchmarks, achieving improvements in IoM of 38.3% and 37.2%, and reductions in training time to reach the target accuracy of 43.5% and 49.8%, on average, for the MNIST and GTSRB datasets, respectively. These findings validate the effectiveness of our approach in incentivizing MUs to contribute high-value local models to MSPs, providing a flexible and adaptive scheme for data provisioning in vehicular metaverse services.

Francesco Vona, Miladin Ćeranić, Irma Rybnikova et al.

Given that experience is a pivotal dimension of learning processes in the field of leadership, the ongoing and unresolved issue is how such experiential moments could be provided when developing leadership skills and competencies. Role-plays and business simulations are widely used in this context as they are said to teach relevant social leadership skills, like those required by everyday communication to followers, by decision-making on compensation, evaluating performance, dealing with conflicts, or terminating contracts. However, the effectiveness of simulations can highly vary depending on the counterpart's ability to act in the given scenarios. In our project, we deal with how immersive media could create experiential learning based on simulations for leadership development. In recent years different variations of extended reality got significant technological improvements. Head-mounted displays are an easy and cost-efficient way to present high-resolution virtual environments. For groups of people that are part of an immersive experience, cave automatic virtual environments offer an excellent trade-off between actual exchange with other humans and interaction with virtual content simultaneously. The work presented is based on developing a user-centered simulation of leadership situations for cave automatic virtual environments and includes the results of a first usability study. In the future, the presented results can help to support the development and evaluation of simulated situations for cave automatic virtual environments with an emphasis on leadership-related scenarios.

I. V. Andreeva, A. V. Puzanov, Choygan N. Sambyla

Nataliya M. Sembay, Yevhen Matviyishyn

Training specialists for the food industry is essential from the viewpoint of public administration, as it requires interaction between various stakeholders, including government organizations, educational institutions, professional associations, and the private sector. Understanding this aspect is crucial for establishing and improving the training system to meet the current needs of the sector and labor market requirements. The article aims to study higher education in the food industry in Ukraine, focusing on the quality of training of specialists. The article analyzes the quality of education provided by Ukrainian higher educational institutions in the field of the food industry. The focus is on the competencies of bachelor's and master's degree graduates in food technology, which helps identify these educational institutions' unique characteristics. The article addresses the diversification of educational services, which include preparatory courses, postgraduate education, doctoral studies, and certificate programs. The study results indicate the need to improve the rating positions of these specialized institutions and ensure a more balanced representation in different regions of Ukraine. The article provides an analysis of the institutional environment in the field of higher education, which shows that training in the field of food technology is carried out in various educational institutions. These include specialized institutions in food technology and institutions focusing on related disciplines, such as trade, hotel and restaurant business, agriculture, biotechnology, medicine, and recreation, as well as general universities where food technology is one of the specialties. This diversity poses challenges in training qualified specialists, requiring universities to focus on transforming quantitative learning outcomes into qualitative results. Keywords: food industry, innovation technology, efficiency, higher education, higher educational institutions, specialties, administration.

Jeffrey Wielgus, M. Grasso, C. Colgan et al.

In an effort to measure and track marine-dependent economic activities, the United States National Oceanic and Atmospheric Administration (NOAA) has developed two statistical tools: The Economics: National Ocean Watch (ENOW) and the Marine Economy Satellite Account (MESA). In both efforts, the focus has been on certain activities in selected sectors of the economy. MESA is developed within the framework of the System of National Accounts (SNA) and includes only economic activities that use essential marine inputs, produce goods or services to be used predominantly in the marine environment, take place in the marine environment, or need to be placed in proximity to the coast to take place. In addition, MESA only employs data on the annual flows of market-based values related to the marine activities. As an SNA-based tool, MESA also fails to systematically keep track of the contribution of the environment to the economy by properly accounting for the changes (both additions and reductions) in the environmental capital stock values. This paper proposes an initial extension of MESA to include natural capital considerations by employing key elements of the System of Environmental-Economic Accounts Central Framework (SEEA-CF) adopted as the initial international statistical standard for environmental-economic accounting by the United Nations Statistical Commission in 2012. In addition to reporting the economic activities captured by the SNA structure, the SEEA-CF requires measuring both additions to the environmental capital stocks (due to natural growth or improved resource management) and reductions in these stocks (resulting from depletion from use in the production process or removal of resources from the natural stock). Considering the complexity involved in the measurement of the natural capital foundations of the ocean-related economy, the paper proposes to launch the MESA extension as a pilot project focusing only on selected data rich marine activities defined in MESA, namely, offshore oil and gas, commercial fishing, and beach recreation.

Uwe M. Borghoff, Nicol Matzner-Vogel, Siegfried Rapp

Digitalization is conquering and stressing out the federal administration. Using selected large-scale ICT projects, we show how complex and interdisciplinary the tasks are. The federal administration's IT strategy requires well-trained specialists for all defined fields of action. This scarce resource is increasingly being trained academically in separate, tailor-made degree courses that are developed specifically for the needs of the German ministries and authorities. We use the example of administrative informatics courses to explain their necessity and success story. Using a Bachelor's/Master's program developed by the authors for the ITZBund and the Federal Ministry of Finance, we look at a concrete implementation and justify two of our design decisions in the development of the course, namely transdisciplinarity and design thinking. We adopt a German perspective throughout the paper. However, the conclusions also apply to other countries.

Houyi Qi, Minghui Liwang, Seyyedali Hosseinalipour et al.

By opportunistically engaging mobile users (workers), mobile crowdsensing (MCS) networks have emerged as important approach to facilitate sharing of sensed/gathered data of heterogeneous mobile devices. To assign tasks among workers and ensure low overheads, a series of stable matching mechanisms is introduced in this paper, which are integrated into a novel hybrid service trading paradigm consisting of futures trading mode and spot trading mode to ensure seamless MCS service provisioning. In the futures trading mode, we determine a set of long-term workers for each task through an overbooking-enabled in-advance many-to-many matching (OIA3M) mechanism, while characterizing the associated risks under statistical analysis. In the spot trading mode, we investigate the impact of fluctuations in long-term workers' resources on the violation of service quality requirements of tasks, and formalize a spot trading mode for tasks with violated service quality requirements under practical budget constraints, where the task-worker mapping is carried out via onsite many-to-many matching (O3M) and onsite many-to-one matching (OMOM). We theoretically show that our proposed matching mechanisms satisfy stability, individual rationality, fairness and computational efficiency. Comprehensive evaluations also verify the satisfaction of these properties under practical network settings, while revealing commendable performance on running time, participators' interactions, and service quality.

Yifeng Zheng, Shuangqing Xu, Songlei Wang et al.

Vertical federated learning (VFL) has recently emerged as an appealing distributed paradigm empowering multi-party collaboration for training high-quality models over vertically partitioned datasets. Gradient boosting has been popularly adopted in VFL, which builds an ensemble of weak learners (typically decision trees) to achieve promising prediction performance. Recently there have been growing interests in using decision table as an intriguing alternative weak learner in gradient boosting, due to its simpler structure, good interpretability, and promising performance. In the literature, there have been works on privacy-preserving VFL for gradient boosted decision trees, but no prior work has been devoted to the emerging case of decision tables. Training and inference on decision tables are different from that the case of generic decision trees, not to mention gradient boosting with decision tables in VFL. In light of this, we design, implement, and evaluate Privet, the first system framework enabling privacy-preserving VFL service for gradient boosted decision tables. Privet delicately builds on lightweight cryptography and allows an arbitrary number of participants holding vertically partitioned datasets to securely train gradient boosted decision tables. Extensive experiments over several real-world datasets and synthetic datasets demonstrate that Privet achieves promising performance, with utility comparable to plaintext centralized learning.

Si Zhang, Philip W. L. Fong

This paper proposes a computational model for policy administration. As an organization evolves, new users and resources are gradually placed under the mediation of the access control model. Each time such new entities are added, the policy administrator must deliberate on how the access control policy shall be revised to reflect the new reality. A well-designed access control model must anticipate such changes so that the administration cost does not become prohibitive when the organization scales up. Unfortunately, past Access Control research does not offer a formal way to quantify the cost of policy administration. In this work, we propose to model ongoing policy administration in an active learning framework. Administration cost can be quantified in terms of query complexity. We demonstrate the utility of this approach by applying it to the evolution of protection domains. We also modelled different policy administration strategies in our framework. This allowed us to formally demonstrate that domain-based policies have a cost advantage over access control matrices because of the use of heuristic reasoning when the policy evolves. To the best of our knowledge, this is the first work to employ an active learning framework to study the cost of policy deliberation and demonstrate the cost advantage of heuristic policy administration.

O. Bezlyubchenko, T. Apatenko

The article considers Land Management as an effective technique for improving the quality of life in cities. It emphasizes the importance of the distribution of socio-economic activities according to various parameters to increase the efficiency of the use of the urban area. Major categories of activities such as residential, commercial, transport, public and government institutions are considered in order to maintain a balance between them. The article also notes the importance of land use planning for sustainable development and optimal use of resources in conditions of limitation. It highlights that urban areas with high population density should be developed according to master plans that include land use plans. The article also notes that urbanization needs adequate leadership, which is provided through regional planning, urban planning, land use planning, transport policy, and public administration. The paper also highlights the advantages of compact cities with multiple uses, such as reducing fuel consumption, urban land use, and ensuring sociocultural development. Studying the experience of Europe, the USA and Australia proved the expediency of promoting spatially compact cities with various goals. It has been studied that compact cities offer the opportunity to reduce fuel consumption for travel, as homes, work and recreation are located close to each other. They are also favored because urban land can be reused, while rural land outside the city is protected. A good quality of life is believed to be supported by a high concentration of people, which provides social conditions conducive to liveliness, vivacity, and cultural production and consumption.

Raquel da Silveira, Ariane Corrêa Pacheco, Carolina Caneva da Silva et al.

ABSTRACT Porto Alegre became a pioneer city in public leisure services in 1926. Since then, leisure has gained weight as a matter of ‘social interest’ and ‘public interest’, which materialised in the interventionist stance of the City, when it created the Municipal Department of Sports, Recreation and Leisure (MDS) in 1993. However, the administration that took office in 2017 suppressed that ‘public interest’ character and eventually closed the Department. The political-administrative procedure lasted seven months, and a collective protest emerged from it/in it to defend the Department, led by women from different neighbourhoods who enjoyed leisure activities. Mostly elderly, they started to fight for their right to leisure. This study, based on pragmatic sociology, looked into these women’s struggle to maintain that Department. We conducted ethnographic research in which we participated in their collective action, especially in identifying and taking advantage of political opportunities to guarantee leisure as a social right. Ten interviews were conducted with female leaders of that action, showing that the leisure activities offered by the Department were important for the lives of these women and their ageing processes, and that their political role in defending the Department exposed inequalities in access to leisure.

Andri Asrul Setiyawan, Agus Kristiyanto, Sapta Kunta Purnama

Purpose: This study aims to: 1) Determine the anthropometric factors (height, arm length, foot length) that most determine the ability of men's volleyball jump service. 2) Knowing the biomotor factors (leg muscle power, abdominal muscle strength, arm and shoulder muscle power, eye-hand coordination, togok flexibility and kinesthetic perception) that most determine the ability of men's volleyball jump service. Material and methods. The population of this study were all male athletes of the Volleyball Student Activity with a total of 36 people. The approach taken in this study is a quantitative approach, using a confirmatory factor analysis design. Data were processed and analyzed using the Computerized Statistical Program with the SPSS (Statistical Product and Service Solutions) Version 22 system and using the Kaiser-Meyer-Olkin and Bartlett's Test. Results. Based on the results of the research and the results of the data analysis that has been carried out, the following conclusions are obtained: First, the anthropometric factor that is the most dominant in determining the ability of volleyball jump service for male athletes in the UNS student activity unit is the length of the feet with a value of 0.879. Second, the biomotor factor that most dominantly determines the ability of volleyball jump service for male athletes in the UNS student activity unit is leg muscle power with a value of 0.864. Conclusions. Anthropometric factors and biomotor factors that determine the ability of volleyball jump service to male athletes in the UNS student activity unit consist of seven factors, namely height, arm length, leg length, leg muscle power, abdominal muscle strength, arm muscle power and flexibility, togok.

Mohammad Reza Parish

The aim of the study is to develop a comprehensive model on the risk factors of injury/re-injury and factors affecting the recovery process. Material and methods. Systematic analysis and scientific generalization of the latest theoretical and analytical studies on the factors affecting risk of injury, assessment, prevention and recovery of injuries in athletes. Results. The conducted comprehensive analysis allowed to build a theoretical model on the injury-recovery cycle. The model includes 3 main groups of factors affecting the risk of injury, namely: internal, caused by physiological processes; external, caused by training conditions and equipment; fear, which is related to the personal psychological and emotional characteristics and external surroundings. At the same time, implementation of preventive measurements can reduce the risk of injuries. The model highlighted the positive impact of social support and interactions between a patient and a therapist in the process of injury recovery. Conclusions. In order to minimize the risk of injury and stimulate the recovery process in athletes the following recommendation should be taken in place: to promote the spreading of information on possible ways of injury prevention; to provide educational services for those who are involved in sports and other physical activities; to spread the information about the main types of injury and the treatment approaches to make athletes familiar with that, which can increase their competence and reduce the fear of injury; to encourage communication and interaction between teammates, with their trainers and coaches during the period of recovery to eliminate the level of isolation of injured athletes.