Many colleges with NCAA Division I Football Bowl Subdivision (FBS) programs lose money by participating in postseason bowl games. Despite these losses, most colleges are eager to accept invites to play in bowl games on the premise that playing in these games brings increased attention and notoriety to their institution. In particular, football coaches often state that playing in a bowl game positively impacts their ability to recruit future student-athletes. This study used regression discontinuity design to estimate whether bowl game participation affects recruiting class quality. Contrary to previous research, I found no statistically significant relationship between bowl game participation and reciting class quality.
Recreation leadership. Administration of recreation services, Sports
Service-based architecture (SBA) has gained attention in industry and academia as a means to modernize legacy systems. It refers to a design style that enables systems to be developed as suites of small, loosely coupled, and autonomous components (services) that encapsulate functionality and communicate via language-agnostic APIs. However, defining appropriately sized services that capture cohesive subsets of system functionality remains challenging. Existing work often relies on the availability of documentation, access to project personnel, or a priori knowledge of the target number of services, assumptions that do not hold in many real-world scenarios. Our work addresses these limitations using a deep reinforcement learning-based approach to identify appropriately sized services directly from implementation artifacts. We present Rake, a reinforcement learning-based technique that leverages available system documentation and source code to guide service decomposition at the level of implementation methods. Rake does not require specific documentation or access to project personnel and is language-agnostic. It also supports a customizable objective function that balances modularization quality and business capability alignment, i.e., the degree to which a service covers the targeted business capability. We applied Rake to four open-source legacy projects and compared it with two state-of-the-art techniques. On average, Rake achieved 7-14 percent higher modularization quality and 18-22 percent stronger business capability alignment. Our results further show that optimizing solely for business context can degrade decomposition quality in tightly coupled systems, highlighting the need for balanced objectives.
The analysis of the impact of Community Based Tourism (CBT) has revealed a significant divergence in assessments. This paper aims to analyse the factors contributing to the observed "Duality Dilemma" in CBT projects. The research seeks to leave behind a simplistic binary perspective that categorises CBT solely as either beneficial or problematic. The paper identifies three key variables contributing to this dual perspective: a) the Context Variable, which displays how the outcomes of CBT projects m can vary based on the specific circumstances in which they are implemented; b) the Methodological Variable, which underlines the importance of developing long-term and longitudinal fieldwork to avoid a biased analysis based on the short-term observations; c) the Paradigm Variable which takes into account that the researcher's theoretical framework inevitably shapes their focus, potentially emphasising certain outcomes over others. Finally, the paper draws on empirical evidence based on a 30-year longitudinal ethnographic study conducted on Amantaní island (Lake Titicaca, Peruvian Andes).
Recreation leadership. Administration of recreation services
Heba A. Abdeen, Rufaida M. Bakry, Nesreen G. El Nahas
et al.
Background and purpose
Fibromyalgia (FM) is a chronic illness affecting the immune system. Women are more likely than men to be diagnosed with this condition. It causes widespread muscle and bone pain and is most commonly experienced by people between the ages of 20 and 60. Recent studies have shown that people with fibromyalgia may experience heart abnormalities and arrhythmias after exercise. This study explores how different aerobic exercise levels affect pain, cholesterol levels, and overall quality of life (QoL) for women with fibromyalgia.
Materials and Methods
In a study conducted at Abu-Kabir Central Hospital in Al Sharquia, 60 women diagnosed with fibromyalgia were randomly allocated to a moderate-intensity aerobic exercise (AE) (n=30) or a low-intensity aerobic exercise AE (n=30). The women were between the ages of 30 and 40 and had a body mass index (BMI) between 20 and 26 kg/m2. Before and after the intervention, all patients in both groups were evaluated using a visual analog scale (VAS), Fibromyalgia Impact Questionnaire (FIQ), symptom severity scale (SS-scale), and cholesterol level measurements.
Results
After the intervention, the group that engaged in moderate-intensity aerobic exercise showed significant improvements in all measured outcomes compared to the group that engaged in low-intensity aerobic exercise. The effect size was high for VAS (MD = -3.73; ES = 0.395 and p = 0.001), cholesterol level (MD = -52.19; ES = 0.681 and p = 0.001), FIQ (MD=-36.26; ES = 0.746 and p = 0.001), and symptom severity scale (MD = -473; ES = 0.273 and p = 0.001).
Conclusion
Our research has shown that moderate-intensity AE performed at 60% to 70% of maximum heart rate, is more effective in reducing pain, improving overall QoL, and lowering cholesterol levels than low-intensity AE at 45% to 55%.
Sports, Recreation leadership. Administration of recreation services
El desarrollo turístico en la provincia de Santiago del Estero, específicamente en la ciudad de Las Termas de Río Hondo, se ha destacado por la importancia que se le ha dado al turismo como motor de desarrollo económico y social en la región, a través de la inversión en infraestructura turística y la diversificación de la oferta turística. Sin embargo, la falta de políticas públicas eficientes ha limitado un desarrollo turístico sustentable y sostenible, con impactos negativos como la estacionalidad del empleo y la migración de los trabajadores por generaciones. A partir de ello, la investigación tiene como objetivo analizar el desarrollo turístico en la ciudad de Las Termas de Río en los últimos 15 años, identificando las acciones del gobierno provincial, municipal y los actores que la componen. Mediante un análisis documental, se estudiarán diversas fuentes de información que den cuenta del fenómeno y su explicación.
Recreation. Leisure, Recreation leadership. Administration of recreation services
Multimedia services over mobile networks pose several challenges, such as the efficient management of radio resources or the latency induced by network delays and buffering requirements on the multimedia players. In Long Term Evolution (LTE) networks, the definition of multimedia broadcast services over a common radio channel addresses the shortage of radio resources but introduces the problem of network error recovery. In order to address network errors on LTE multimedia broadcast services, the current standards propose the combined use of forward error correction and unicast recovery techniques at the application level. This paper shows how to efficiently synchronize the broadcasting server and the multimedia players and how to reduce service latency by limiting the multimedia player buffer length. This is accomplished by analyzing the relation between the different parameters of the LTE multimedia broadcast service, the multimedia player buffer length, and service interruptions. A case study is simulated to confirm how the quality of the multimedia service is improved by applying our proposals.
Kaushik Dey, Satheesh K. Perepu, Pallab Dasgupta
et al.
The dynamic and evolutionary nature of service requirements in wireless networks has motivated the telecom industry to consider intelligent self-adapting Reinforcement Learning (RL) agents for controlling the growing portfolio of network services. Infusion of many new types of services is anticipated with future adoption of 6G networks, and sometimes these services will be defined by applications that are external to the network. An RL agent trained for managing the needs of a specific service type may not be ideal for managing a different service type without domain adaptation. We provide a simple heuristic for evaluating a measure of proximity between a new service and existing services, and show that the RL agent of the most proximal service rapidly adapts to the new service type through a well defined process of domain adaptation. Our approach enables a trained source policy to adapt to new situations with changed dynamics without retraining a new policy, thereby achieving significant computing and cost-effectiveness. Such domain adaptation techniques may soon provide a foundation for more generalized RL-based service management under the face of rapidly evolving service types.
The cost competitiveness of green hydrogen production via electrolysis presents a significant challenge for its large-scale adoption. One potential solution to make electrolyzers profitable is to diversify their products and participate in various markets, generating additional revenue streams. Electrolyzers can be utilized as flexible loads and participate in various frequency-supporting ancillary service markets by adjusting their operating set points. This paper develops a mixed-integer linear model, deriving an optimal scheduling strategy for an electrolyzer providing Frequency Containment Reserve (FCR) services in the Nordic synchronous region. Depending on the hydrogen price and demand, results show that the provision of various FCR services, particularly those for critical frequency conditions (FCR-D), could significantly increase the profit of the electrolyzer.
Elise Dumas, Anne-Sophie Hamy, Sophie Houzard
et al.
While the emergence of large administrative claims data provides opportunities for research, their use remains limited by the lack of clinical annotations relevant to disease outcomes, such as recurrence in breast cancer (BC). Several challenges arise from the annotation of such endpoints in administrative claims, including the need to infer both the occurrence and the date of the recurrence, the right-censoring of data, or the importance of time intervals between medical visits. Deep learning approaches have been successfully used to label temporal medical sequences, but no method is currently able to handle simultaneously right-censoring and visit temporality to detect survival events in medical sequences. We propose EDEN (Event DEtection Network), a time-aware Long-Short-Term-Memory network for survival analyses, and its custom loss function. Our method outperforms several state-of-the-art approaches on real-world BC datasets. EDEN constitutes a powerful tool to annotate disease recurrence from administrative claims, thus paving the way for the massive use of such data in BC research.
Recent technological and economic developments have transformed the healthcare sector towards more personalized and IoT-based healthcare services. These services are realized through control and monitoring applications that are typically developed using artificial intelligence/machine learning-based algorithms, which play a significant role in highlighting the efficiency of traditional healthcare systems. Current personalized healthcare services are dedicated to a specific environment to support technological personalization. However, they are unable to consider different interrelated health conditions, leading to inappropriate diagnoses and affecting sustainability and the long-term health of patients. To this end, current Healthcare 5.0 technology has evolved that supersede previous healthcare technologies. The goal of healthcare 5.0 is to achieve an autonomous healthcare service, that takes into account the interdependent effect of different health conditions of a patient. This paper conducts a comprehensive survey on personalized healthcare services. In particular, we first present an overview of key requirements of comprehensive personalized healthcare services in modern healthcare Internet of Things (HIoT), including the definition of personalization and an example use case scenario as a representative for modern HIoT. Second, we explored a fundamental three-layer architecture for IoT-based healthcare systems using AI and non-AI-based approaches, considering key requirements for CPHS followed by their strengths and weaknesses in the frame of personalized healthcare services. Third, we highlighted different security threats against each layer of IoT architecture along with the possible AI and non-AI-based solutions. Finally, we propose a methodology to develop reliable, resilient, and personalized healthcare services that address the identified weaknesses of existing approaches.
Azadeh Ghari Neiat, Athman Bouguettaya, Mohammed Bahutair
We develop a novel framework for efficiently and effectively discovering crowdsourced services that move in close proximity to a user over a period of time. We introduce a moving crowdsourced service model which is modelled as a moving region. We propose a deep reinforcement learning-based composition approach to select and compose moving IoT services considering quality parameters. Additionally, we develop a parallel flock-based service discovery algorithm as a ground-truth to measure the accuracy of the proposed approach. The experiments on two real-world datasets verify the effectiveness and efficiency of the deep reinforcement learning-based approach.
Senda Romdhani, Genoveva Vargas-Solar, Nadia Bennani
et al.
This paper proposes a QoS-based trust evaluation model for black box data services. Under the black-box model, data services neither export (meta)-data about conditions in which they are deployed and collect and process data nor the quality of data they deliver. Therefore, the black-box model creates blind spots about the extent to which data providers can be trusted to be used to build target applications. The trust evaluation model for black box data services introduced in this paper originally combines QoS indicators, like service performance and data quality, to determine services trustworthiness. The paper also introduces DETECT: a Data sErvice as a black box Trust Evaluation arChitecTure, that validates our model. The trust model and its associated monitoring strategies have been assessed in experiments with representative case studies. The results demonstrate the feasibility and effectiveness of our solution.
Globally, the discourse of e-government has gathered momentum in public service delivery. No country has been left untouched in the implementation of e-government. Several government departments and agencies are now using information and communication technology (ICTs) to deliver government services and information to citizens, other government departments, and businesses. However, most of the government departments have not provided all of their services electronically or at least the most important ones. Thus, this creates a phenomenon of e-government service gaps. The objective of this study was to investigate the contextual factors enhancing e-government service gaps in a developing country. To achieve this aim, the TOE framework was employed together with a qualitative case study to guide data collection and analysis. The data was collected through semi-structured interviews from government employees who are involved in the implementation of e-government services in Zimbabwe as well as from citizens and businesses. Eleven (11) factors were identified and grouped under the TOE framework. This research contributes significantly to the implementation and utilisation of e-government services in Zimbabwe. The study also contributes to providing a strong theoretical understanding of the factors that enhance e-government service gaps explored in the research model.
A pandemia da COVID-19 surpreendeu o mercado turístico no ano de 2020, com queda significativa da atividade e preocupante impacto econômico para o setor, para além das questões sanitárias. A Rede Brasileira de Observatórios de Turismo – RBOT, criou uma pesquisa online, aplicada por todos os representantes, coordenada pelo Observatório de Turismo do Paraná – OBSTUR/PR. O objetivo é discutir esses resultados da Sondagem Empresarial dos Impactos da COVID-19 e o papel dos observatórios, a fim de conhecer e buscar meios de mitigar os desdobramentos de tais impactos com ênfase no setor de turismo do Paraná. A metodologia foi exploratória baseada no survey descritivo, isolando dados relativos ao Paraná. Como resultados, destacam-se a importância dos observatórios e da informação, além da relevância dessa interação; a predominância das micro e pequenas empresas no turismo e como não foram satisfatoriamente contempladas pelas políticas nacionais de recuperação; e, como principal resultado, a preservação dos empregos mais intensa em empresas menores.
Recreation leadership. Administration of recreation services, Urban groups. The city. Urban sociology
Andrew Daw, Antonio Castellanos, Galit B. Yom-Tov
et al.
In customer support contact centers, every service interaction involves a messaging dialogue between a customer and an agent; together, they exchange information, solve problems, and collectively co-produce the service. Because the service progression is shaped by the history of conversation so far, we propose a bivariate, marked Hawkes process cluster model of the customer-agent interaction. To evaluate our stochastic model of service, we apply it to an industry contact center dataset containing nearly 5 million messages. Through both a novel residual analysis comparison and several Monte Carlo goodness-of-fit tests, we show that the Hawkes cluster model indeed captures dynamics at the heart of the service and also surpasses classic models that do not incorporate the service history. Furthermore, in an entirely data-driven simulation, we demonstrate how this history-dependent model can be leveraged operationally to inform a prediction-based routing policy. We show that widely-used and well-studied customer routing policies can be outperformed with simple modifications according to the Hawkes model. Through analysis of a stylized model proposed in the contact center literature, we prove that service heterogeneity can cause this underperformance and, moreover, that such heterogeneity will occur if service closures are not carefully managed.
The proliferation of Web services makes it difficult for users to select the most appropriate one among numerous functionally identical or similar service candidates. Quality-of-Service (QoS) describes the non-functional characteristics of Web services, and it has become the key differentiator for service selection. However, users cannot invoke all Web services to obtain the corresponding QoS values due to high time cost and huge resource overhead. Thus, it is essential to predict unknown QoS values. Although various QoS prediction methods have been proposed, few of them have taken outliers into consideration, which may dramatically degrade the prediction performance. To overcome this limitation, we propose an outlier-resilient QoS prediction method in this paper. Our method utilizes Cauchy loss to measure the discrepancy between the observed QoS values and the predicted ones. Owing to the robustness of Cauchy loss, our method is resilient to outliers. We further extend our method to provide time-aware QoS prediction results by taking the temporal information into consideration. Finally, we conduct extensive experiments on both static and dynamic datasets. The results demonstrate that our method is able to achieve better performance than state-of-the-art baseline methods.
Isabela Lima Pinheiro da Camara, Ari da Silva Fonseca Filho
O Rio de Janeiro é conhecido como: cidade maravilhosa, cidade do carnaval e cidade hospitaleira. Nesse sentido, a proposta do presente artigo é a de compreender se o destino Rio de Janeiro é realmente hospitaleiro, por meio das categorias de hospitalidade na cidade (Grinover, 2006): acessibilidade, legibilidade e identidade. Assim, este trabalho tem como objetivo geral analisar a hospitalidade de alguns pontos turísticos da cidade do Rio de Janeiro pelo olhar do turista intercambista que estudou na Universidade Federal Fluminense (UFF). A metodologia para este estudo foi descritiva com uso de diferentes técnicas: uma pesquisa quantitativa por meio de questionário aplicado a 54 intercambistas, uma pesquisa qualitativa com entrevistas semiestruturadas aplicadas a seis intercambistas e a análise de dados qualitativamente de acordo com o estudo bibliográfico. Para os intercambistas da UFF, existem evidências de hospitalidade nos lugares turísticos do Rio de Janeiro, mas todas as categorias – acessibilidade, legibilidade e identidade – precisam ser melhoradas. Sobre as pessoas, o resultado da pesquisa indicou que os moradores locais se demonstraram receptivos com estrangeiros.
Geography. Anthropology. Recreation, Recreation leadership. Administration of recreation services
Nuria Guitart Casalderrey, Jessica Alcalde Garcia, Anna Pitarch Mach
et al.
El fenómeno de la turismofobia y los problemas de convivencia turística son el objeto de estudio del presente artículo, realizado en base a un análisis comparativo de las ciudades de Ámsterdam, Barcelona y Berlín. El objetivo principal es estudiar el concepto turismofobia con la finalidad de conocer las características comunes que provocan la aparición de varios problemas de convivencia turística.
Para el estudio de la extensión del fenómeno se ha llevado a cabo una búsqueda de cifras y artículos divulgativos con el objetivo de definir los problemas provocados por la actividad turística en las tres ciudades. Paralelamente se han realizado entrevistas a 27 personalidades del sector, pertenecientes tanto a la administración pública como a asociaciones vecinales, al mundo académico y al sector privado.
Los resultados llevan a considerar que la concepción del término turismofobia, teniendo en cuenta su significado etimológico, se aleja de las líneas más extendidas. Las tres ciudades presentan distintos problemas de convivencia entre turistas y residentes provocados, principalmente, por la masificación de los espacios públicos y por la mala planificación del entorno, hechos que causan malestar entre la ciudadanía y que ha sido entendido como odio al turismo tanto por diversos actores del sector como por los medios de comunicación.
Recreation leadership. Administration of recreation services, The city as an economic factor. City promotion
Driven by the vision of edge computing and the success of rich cognitive services based on artificial intelligence, a new computing paradigm, edge cognitive computing (ECC), is a promising approach that applies cognitive computing at the edge of the network. ECC has the potential to provide the cognition of users and network environmental information, and further to provide elastic cognitive computing services to achieve a higher energy efficiency and a higher Quality of Experience (QoE) compared to edge computing. This paper firstly introduces our architecture of the ECC and then describes its design issues in detail. Moreover, we propose an ECC-based dynamic service migration mechanism to provide an insight into how cognitive computing is combined with edge computing. In order to evaluate the proposed mechanism, a practical platform for dynamic service migration is built up, where the services are migrated based on the behavioral cognition of a mobile user. The experimental results show that the proposed ECC architecture has ultra-low latency and a high user experience, while providing better service to the user, saving computing resources, and achieving a high energy efficiency.