Search results for: improving performance and health

Authors: My Linh Hoang, Van Dung Hoang

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Environmental, Social, and Governance (ESG) factors have become a focus for companies globally, as businesses are now focusing on long-term sustainable goals rather than only operating for the goals of profit maximization. According to recent research, in several countries, companies have shown positive results in their financial performance by improving their ESG performance. The construction industry is one of the most crucial components of social and economic development; as a result, considerations for ESG factors are becoming more and more essential for companies in this sector. In Vietnam, the construction industry has been growing rapidly in recent years; however, it has yet to be discussed and studied extensively in Vietnam how ESG factors create impacts on corporate financial performance in general and construction corporations’ financial performance in particular. This research aims to examine the relationship between ESG factors and financial indicators in construction companies from 2011 to 2021 through panel data analysis of 75 listed construction companies in Vietnam and to provide insights into how these companies can better integrate ESG considerations into their operations to enhance their financial performance. The data was analyzed through 3 main methods: descriptive statistics, correlation coefficient analysis applied to all dependent, explanatory and control variables, and panel data analysis method. In panel data analysis, the study uses the fixed effects model (FEM) and random effects model (REM). The Hausman test will be used to select which model is suitable to be used. The findings indicate that maintaining a strong commitment to ESG principles can have a positive impact on financial performance. Finally, FGLS estimation will be performed when the problem of autocorrelation and variable variance appears in the model. This is significant for all parties involved, including investors, company managers, decision-makers, and industry regulators.

Keywords: ESG, financial performance, construction company, Vietnam

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Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

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Sport performance analysis is a technique that is becoming every year more important for athletes of every level. Many techniques have been developed to measure and analyse efficiently the performance of athletes in some sports, but in combat sports these techniques found in many times their limits, due to the high interaction between the two opponents during the competition. In this paper the problem will be framed. Moreover the physical performance measurement problem will be analysed and three different techniques to manage it will be presented. All the techniques have been used to analyse the performance of 22 high level Judo athletes.

Keywords: sport performance, physical performance, judo, performance coefficients

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Authors: Shatha Ahmad Alharthi

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Prior research suggests that reduced social interaction can negatively affect well-being and impair mental health (e.g., depression and anxiety), resulting in lower academic performance. The COVID-19 pandemic has significantly limited social interaction among Saudi Arabian school children since the government closed schools and implemented lockdown restrictions to reduce the spread of the disease. These restrictions have resulted in prolonged remote learning for middle school students with unknown consequences for perceived academic performance, mental health, and well-being. This research project explores how middle school Saudi students’ current remote learning practices affect their mental health (e.g., depression and anxiety) and well-being during the lockdown. Furthermore, the study will examine the association between social interaction, mental health, and well-being pertaining to students’ perceptions of their academic achievement. Research findings could lead to a better understanding of the role of lockdown on depression, anxiety, well-being and perceived academic performance. Research findings may also inform policy-makers or practitioners (e.g., teachers and school leaders) about the importance of facilitating increased social interactions in remote learning situations and help to identify important factors to consider when seeking to re-integrate students into a face-to-face classroom setting. Potential implications for future educational research include exploring remote learning interventions targeted at bolstering students’ mental health and academic achievement during periods of remote learning.

Keywords: depression, anxiety, academic performance, social interaction

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Authors: Tomola Obamuyi

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The banking system in Nigeria adopted innovative banking, with the aim of enhancing financial inclusion, and making financial services readily and cheaply available to majority of the people, and to contribute to the efficiency of the financial system. Some of the innovative services include: Automatic Teller Machines (ATMs), National Electronic Fund Transfer (NEFT), Point of Sale (PoS), internet (Web) banking, Mobile Money payment (MMO), Real-Time Gross Settlement (RTGS), agent banking, among others. The introduction of these payment systems is expected to increase bank efficiency and customers' satisfaction, culminating in better performance for the commercial banks. However, opinions differ on the possible effects of the various innovative payment systems on the performance of commercial banks in the country. Thus, this study empirically determines how commercial banks use innovation to gain competitive advantage in the specific context of Nigeria's finance and business. The study also analyses the effects of financial innovation on the performance of commercial banks, when different periods of analysis are considered. The study employed secondary data from 2009 to 2018, the period that witnessed aggressive innovation in the financial sector of the country. The Vector Autoregression (VAR) estimation technique forecasts the relative variance of each random innovation to the variables in the VAR, examine the effect of standard deviation shock to one of the innovations on current and future values of the impulse response and determine the causal relationship between the variables (VAR granger causality test). The study also employed the Multi-Criteria Decision Making (MCDM) to rank the innovations and the performance criteria of Return on Assets (ROA) and Return on Equity (ROE). The entropy method of MCDM was used to determine which of the performance criteria better reflect the contributions of the various innovations in the banking sector. On the other hand, the Range of Values (ROV) method was used to rank the contributions of the seven innovations to performance. The analysis was done based on medium term (five years) and long run (ten years) of innovations in the sector. The impulse response function derived from the VAR system indicated that the response of ROA to the values of cheques transaction, values of NEFT transactions, values of POS transactions was positive and significant in the periods of analysis. The paper also confirmed with entropy and range of value that, in the long run, both the CHEQUE and MMO performed best while NEFT was next in performance. The paper concluded that commercial banks would enhance their performance by continuously improving on the services provided through Cheques, National Electronic Fund Transfer and Point of Sale since these instruments have long run effects on their performance. This will increase the confidence of the populace and encourage more usage/patronage of these services. The banking sector will in turn experience better performance which will improve the economy of the country. Keywords: Bank performance, financial innovation, multi-criteria decision making, vector autoregression,

Keywords: Bank performance, financial innovation, multi-criteria decision making, vector autoregression

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Authors: Anand Choudhary

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Following the global economic crisis in 2008, businesses and more especially the big multinational conglomerates were increasingly viewed by the people world over as one of the major causes of the economic problems faced by millions globally, in terms of job loss and lifetime savings being wiped out as banks and pension funds went bankrupt and people stared at an insecure financial future. This caused a lot of resentment in the public against big businesses and fueled several protest movements by the people such as “Occupy Wall Street” in different parts of the world. This forced the big businesses to respond to the challenge by adopting more people-centric policies and initiatives for local communities in societies where they operate as part of their corporate social responsibility (CSR), in order to regain their social acceptance among the people whilst earning their ‘social license to operate’. The current paper studies many of such large MNCs across the United States of America, India and South Africa, which changed the way they did business earlier, following the global economic crisis in 2008, by incorporating capacity building initiatives for local communities as part of their CSR strategy and explores whether it has contributed to improving their financial performance. It is a conceptual research paper using secondary source data. The findings reveal that there is a positive correlation between the companies’ corporate social performance and corporate financial performance. In addition, the findings also bring to light that the MNCs examined as part of the current paper have improved their image in the eyes of their stakeholders following the change in their CSR strategy and initiatives.

Keywords: corporate social responsibility (CSR), Corporate Social Performance (CSP), Corporate Financial Performance (CFP), local communities

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Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

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Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

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We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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Authors: Mohammad Soliman, Mohamed A. Abou-Shouk

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Knowledge management focuses on the development, storage, retrieval, and dissemination of information and expertise. It has become an important tool to improve performance in tourism enterprises. This includes improving decision-making, developing customer services, and increasing sales and profits. Knowledge management adoption depends on human, organizational and technological factors. This study aims to explore the concept of knowledge management in travel agents in Egypt. It explores the requirements of adoption and its impact on performance in these agencies. The study targets Category A travel agents in Egypt. The population of the study encompasses Category A travel agents having online presence. An online questionnaire is used to collect data from managers of travel agents. This study is useful for travel agents who are in urgent need to restructure their intermediary role and support their survival in the global travel market. The study sheds light on the requirements of adoption and the expected impact on performance. This could help travel agents identify their situation and the determine the extent to which they are ready to adopt knowledge management. This study is contributing to knowledge by providing insights from the tourism sector in a developing country where the concept of knowledge management is still in its infancy stages.

Keywords: knowledge management, knowledge management adoption, performance, travel agents

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Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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Authors: Mohammad Ranjbar, Mohammad Bazyar, Blake Angell, Thomas Lung, Yibeltal Assefa

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Background: Current health insurance programs in Iran suffer from low enrolment and are not sufficient to attain the country to universal health coverage (UHC). We hypothesize that improving the enrollment rate and moving towards a more sustainable UHC can be achieved by improving the benefits package and providing new incentives. The objective of this study is to assess public preferences and willingness to pay (WTP) for social health insurance (SHI) in Iran. Methods: A discrete choice experiment (DCE) was conducted in 2021, using a self-administered questionnaire on 500 participants to estimate WTP and determine individual preferences for the SHI in Yazd, Iran. Respondents were presented with an eight-choice set and asked to select their preferred one. In each choice set, scenarios were described by eight attributes with varying levels. The conditional logit regression model was used to analyze the participants' preferences. Willingness to pay for each attribute was also calculated. Results: Most included attributes were significant predictors of the choice of a health insurance package. The maximum coverage of hospitalization costs in the private sector, ancillary services such as glasses, canes, etc., as well as coverage for hospitalization costs in the public sector and drug costs, were the most important determining factors for this choice. Coverage of preventive dental care did not significantly influence respondent choices. Estimating WTP showed that individuals are willing to pay more for higher financial protection, particularly against private sector costs; the WTP to increase the coverage of hospitalization costs in the private sector from 50% to 90% is estimated at 362,068 IR, Rials per month. Conclusion: This study identifies the key factors that the population value with regard to health insurance and the tradeoffs they are willing to make between them. Hospitalization, drugs, and ancillary services were the most important determining factors for their choice. The data suggest that additional resources coming into the Iranian health system might best be prioritized to cover hospitalization and drug costs and those associated with ancillary services.

Keywords: social health insurance, preferences, discrete choice experiment, willingness to pay

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Authors: Lana Migla

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Phase change materials (PCMs) have an important role in improving the efficiency of thermal heat storage. As these materials are characterized by low thermal conductivity, it is necessary to develop heat transfer techniques to improve their thermophysical properties. This scientific article focuses on the geometrical configurations of encapsulated PCM containers and the impact of designs to improve the performance of the solar thermal cooling system. The literature review showed that in-depth research is being conducted on different methods of improving the efficiency of PCM heat transfer, which is the main design task for the containers. Techniques such as microencapsulated PCMs, adding fins and different combinations of fins and nanoparticles are used. The use of graphite, metal foam and doping of high photothermal materials is also being studied. To determine most efficient container configuration, the article looks at different designs of PCM containers with fins for the storage tank. This paper experimentally investigates the effect of the encapsulation design on the performance of a lab-scale thermal energy storage tank. The development of optimized energy storage with integrated phase change material containers reduces auxiliary heater energy consumption, increases the COP of the solar cooling system, and reduces the environmental impact of the cooling system. The review shows that in the cylindrical construction, the ratio between the radius of shell and tube is significant, which means this ratio is the main issue to enhance transfer efficiency and to increase the value of stored heat. Therefore, three cylindrical tube containers with different radiuses 20mm, 35mm, 50mm filled with commercial phase change material were tested. The results show that using a smaller radius achieved a higher power, leading to a reduction in the charging and discharging time. The three fins were added to the selected cylindrical tube to determine their effects on heat exchanging efficiency. The observed optimized performance given by the fin’s arrangement achieved a 40% reduction of PCM's melting time compared to the heat exchanging without fins. The exact dimensions of the PCM containers and fins placements will be presented on-site.

Keywords: energy performance, PCM containers, solar thermal cooling, storage tank

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Authors: Hanlin Liu, Hua Li, Yintan AI

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Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routingoriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

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Authors: Sabri Sulaiman, Siti Hajar Abu Bakar Ah, Haris Abd Wahab

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Street children is a global phenomenon and declared as a social problem by social researcher and scholars across the world. The insecure street environment exposes street children into various risk factors. One of them is the health and psychological problem. The objective of this study is to assess the health problem and psychological wellbeing of street children in Kuala Lumpur, Malaysia. The cross-sectional study involved 303 street children in Chow Kit, Kuala Lumpur. The study confirmed that the majority (95.7%) of street children who participated in the study have a health problem. The findings also demonstrated that the majority of them have issues related to their psychological wellbeing. The inputs from this study are instrumental for the suggestion of specific intervention to improve the health and psychology wellbeing of street children in Malaysia. Agencies which are responsible for the street children well-being can utilise the inputs to framing and improving the social care programmes for the children.

Keywords: street children, health status, psychology wellbeing, homeless

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Authors: Zehra Aybike Kılıç, Alpin Köknel Yener

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Daylight is a powerful driver in terms of improving human health, enhancing productivity and creating sustainable solutions by minimizing energy demand. A proper daylighting system allows not only a pleasant and attractive visual and thermal environment, but also reduces lighting energy consumption and heating/cooling energy load with the optimization of aperture size, glazing type and solar control strategy, which are the major design parameters of daylighting system design. Particularly, in high-rise buildings where large openings that allow maximum daylight and view out are preferred, evaluation of daylight performance by considering the major parameters of the building envelope design becomes crucial in terms of ensuring occupants’ comfort and improving energy efficiency. Moreover, it is increasingly necessary to examine the daylighting design of high-rise residential buildings, considering the share of residential buildings in the construction sector, the duration of occupation and the changing space requirements. This study aims to identify a proper daylighting design solution considering window area, glazing type and solar control strategy for a high-residential building in terms of visual comfort and lighting energy efficiency. The dynamic simulations are carried out/conducted by DIVA for Rhino version 4.1.0.12. The results are evaluated with Daylight Autonomy (DA) to demonstrate daylight availability in the space and Daylight Glare Probability (DGP) to describe the visual comfort conditions related to glare. Furthermore, it is also analyzed that the lighting energy consumption occurred in each scenario to determine the optimum solution reducing lighting energy consumption by optimizing daylight performance. The results revealed that it is only possible that reduction in lighting energy consumption as well as providing visual comfort conditions in buildings with the proper daylighting design decision regarding glazing type, transparency ratio and solar control device.

Keywords: daylighting , glazing type, lighting energy efficiency, residential building, solar control strategy, visual comfort

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Authors: Aliasghar Baziar, Hassan Masoumi, Alireza Ale Saadi

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The control of the response of electric motors plays a significant role in the damping of transient responses. In this regard, this paper presents a static VAR compensator (SVC) based on a fuzzy logic which is applied to an industrial power network consisting of three phase synchronous, asynchronous and DC motor loads. The speed and acceleration variations of a specific machine are the inputs of the proposed fuzzy logic controller (FLC). In order to verify the effectiveness and proficiency of the proposed Fuzzy Logic based SVC (FLSVC), several non-linear time-domain digital simulation tests are performed. The proposed fuzzy model can properly control the response of electric motors. The results show that the FLSVC is successful to improve the voltage profile significantly over a wide range of operating conditions and disturbances thus improving the overall dynamic performance of the network.

Keywords: fuzzy logic controller, VAR compensator, single cage asynchronous motor, DC motor

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Authors: Mohamad Reza Khodabakhsh

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Physical activity is important because it affects the stress and mental health of the elderly. The purpose of this research is to examine the relationship between the physical activity of the elderly and stress and mental health. The current research is correlational research, and the studied population includes all the elderly who are engaged in sports in the parks of Mashhad city in 2021. The whole community consists of 200 people. Sampling was done by the headcount method. The tool used in this research is a questionnaire. The physical activity questionnaire is Likert. General GHQ is based on the self-report method. The study method is correlation type to find the relationship between predictor and predicted variables, and the multiple regression method was used for the relationships between the sub-components. And the results showed that physical activity has the effect of reducing the stress of the elderly and improving their mental health. In general, the results of this research indicate the confirmation of the research hypotheses.

Keywords: relationship, physical activity, stress, mental health, elderly

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Authors: Mohsen Azarmjoo, Navid Sharifi, Zahra Alikhani Koopaei

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This article aims to conserve energy and optimize the performance of solar water heaters using modern modeling systems. In this study, a large-scale solar water heater is modeled using an AVR microcontroller, which is a digital processor from the AVR microcontroller family. This mechatronic system will be used to analyze the performance and design of solar collectors, with the ultimate goal of improving the efficiency of the system being used. The findings of this research provide insights into optimizing the performance of solar water heaters. By manipulating the arrangement of solar panels and controlling the water flow through them using the AVR microcontroller, researchers can identify the optimal configurations and operational protocols to achieve the desired temperature and flow conditions. These findings can contribute to the development of more efficient and sustainable heating and cooling systems. This article investigates the optimization of solar water heater performance. It examines the impact of solar panel layout on system efficiency and explores methods of controlling water flow to achieve the desired temperature and flow conditions. The results of this research contribute to the development of more sustainable heating and cooling systems that rely on renewable energy sources.

Keywords: energy conservation, solar water heaters, solar cooling, simulation, mechatronics

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Authors: Mohieldin Elmashad, Salwa Yassin

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Expansive soils regarded as one of the most problematic unsaturated formations in the Egyptian arid zones and present a great challenge in civil engineering, in general, and geotechnical engineering, in particular. Severe geotechnical complications and consequent structural damages have been arising due to an excessive and differential volumetric change upon wetting and change in water content. Different studies have been carried out concerning the swelling performance of the expansive soils using different additives including phospho-gypsum as an industrial waste product. However, this paper describes the results of a comprehensive testing programme that was carried out to investigate the effect of phospho-gypsum (PG) and sodium chloride (NaCl), as an additive mixture, on the swelling performance of constituent samples of swelling soils. The constituent samples comprise commercial bentonite collected from a natural site, mixed with different percentages of PG-NaCl mixture. The testing programme had been scoped to cover the physical and chemical properties of the constituent samples. In addition, a mineralogical study using x-ray diffraction (XRD) was performed on the collected bentonite and the mixed bentonite with PG-NaCl mixture samples. The obtained results of this study showed significant improvement in the swelling performance of the tested samples with the increase of the proposed PG-NaCl mixture content.

Keywords: expansive soils, industrial waste, mineralogical study, swelling performance, X-ray diffraction

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Authors: Chiao-Wen Lan, David Gere

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Background and Significance: Performance has a rich history of imparting information and encouraging reflection, yet there is a paucity of literature on applying performance as a method of analysis and not as a medium for health education. This study aimed to apply ethnodrama strategies to the issue of HIV-related stigma in rural China and to use a critical performance as a vehicle for communication of health research. Methods: The program, titled 'STOP STIGMA,' included dance, narratives and original quotes from people living with HIV/AIDS in China, and spectacle such as photographs, set, and props corresponding to the history of HIV in rural China. Results: The performance represented a step away from a completely textual interpretation of data towards a theatrical style that begins to privilege what arts-based research scholars Rossiter and colleagues have termed 'an embodied, theatrical representation of data.' It offered an opportunity to deliver individual and collective stories that represent how HIV-positive people experience living with HIV/AIDS in China, which could play an integral part in the formulation of actions to effect change. Discussion: This method of communicating health research has implications for fostering dialogue among researchers, community members, and medical practitioners. Although arts-based approaches are not new to the scientific community, the integration of dance, video, ethnodrama, and sciences provides opportunities to innovate in non-traditional research dissemination and communication.

Keywords: health communication, HIV/AIDS, stigma, vulnerable populations

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Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: Qian Mao, Xiaozan Wang, Jiarong Zhong, Xiaolin Zou

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Introduction: As a result of the decline of students' physical health level and the increase of study pressure, students’ academic performance is not so good. Objective: This study aims to verify whether the Brain-Break intervention in the fourth-grade classroom of primary school can improve students' physical health and academic performance. Methods: According to the principle of no difference in pre-test data, students from two classes of grade four in Fuhai Road Primary School, Fushan district, Yantai city, Shandong province, were selected as experimental subjects, including 50 students in the experimental class (25 males and 25 females) and 50 students in the control class (24 males and 26 females). The content of the experiment was that the students were asked to perform a 4-minute Brain-Berak program designed by the researcher in the second class in the morning and the afternoon, and the intervention lasted for 12 weeks. In addition, the lung capacity, 50-meter run, sitting body forward bend, one-minute jumping rope and one-minute sit-ups stipulated in the national standards for physical fitness of students (revised in 2014) were selected as the indicators of physical health. The scores of Chinese, Mathematics, and English in the unified academic test of the municipal education bureau were selected as the indicators of academic performance. The independent-sample t-test was used to compare and analyze the data of each index between the two classes. The paired-sample t-test was used to compare and analyze the data of each index in the two classes. This paper presents only results with significant differences. Results: in terms of physical health, lung capacity (P=0.002, T= -2.254), one-minute rope skipping (P=0.000, T=3.043), and one-minute sit-ups (P=0.045, T=6.153) were significantly different between the experimental class and the control class. In terms of academic performance, there is a significant difference between the Chinese performance of the experimental class and the control class (P=0.009, T=4.833). Conclusion: Adding Brain-Berak intervention in the classroom can effectively improve the cardiorespiratory endurance (lung capacity), coordination (jumping rope), and abdominal strength (sit-ups) of fourth-grade students. At the same time, it can also effectively improve their Chinese performance. Therefore, it is suggested to promote micro-sports in the classroom of primary schools throughout the country so as to help students improve their physical health and academic performance.

Keywords: academic performance, brain break, fourth grade, physical health

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Authors: Muluken Biadgelegn Wollele, Mebratu Assaye Mengistu

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Nanotechnology has created new opportunities for improving industrial efficiency and performance. One of the proposed approaches to improving the effectiveness of temperature exchangers is the use of nanofluids to improve heat transfer performance. The thermal conductivity of nanoparticles, as well as their size, diameter, and volume concentration, all played a role in influencing the rate of heat transfer. Nanofluids are commonly used in automobiles, energy storage, electronic component cooling, solar absorbers, and nuclear reactors. Convective heat transfer must be improved when designing thermal systems in order to reduce heat exchanger size, weight, and cost. Using roughened surfaces to promote heat transfer has been tried several times. Thus, both active and passive heat transfer methods show potential in terms of heat transfer improvement. There will be an added advantage of enhanced heat transfer due to the two methods adopted; however, pressure drop must be considered during flow. Thus, the current research aims to increase heat transfer by adding a twisted tap insert in a plain tube using a working fluid hybrid nanofluid (Al₂O₃-Cu) with a base fluid of water. A circular duct with inserts, a tube length of 3 meters, a hydraulic diameter of 0.01 meters, and tube walls with a constant heat flux of 20 kW/m² and a twist ratio of 125 was used to investigate Al₂O₃-Cu/H₂O hybrid nanofluid with inserts. The temperature distribution is better than with conventional tube designs due to stronger tangential contact and swirls in the twisted tape. The Nusselt number values of plain twisted tape tubes are 1.5–2.0 percent higher than those of plain tubes. When twisted tape is used instead of plain tube, performance evaluation criteria improve by 1.01 times. A heat exchanger that is useful for a number of heat exchanger applications can be built utilizing a mixed flow of analysis that incorporates passive and active methodologies.

Keywords: nanofluids, active method, passive method, Nusselt number, performance evaluation criteria

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Authors: Nela Milosevic, Sladjana Barjaktarovic Rakocevic, Sladjana Benkovic, Nemanja Milanovic

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Nowadays, performance measurement systems play a key role in evaluating the strategic performances of an organization. On the other hand, there has been a shift towards the Balanced Scorecard (BSC), which has been recognized as a valuable managerial approach. The main goal of this paper is to analyze the main performances of Serbian banks measured at the branches level, through the usage of the Balanced Scorecard framework. Although an extensive number of practitioners have an interest in the Balanced Scorecard approach, little empirical research has been conducted on the implementation of its concept in the service sector like banks, especially within developing countries. From the beginning of August till the end of September 2015, authors have been conducting in-depth interviews among a number of experts from the most successful banks in Serbia. The results show that the non-financial measures, especially, customer oriented indicators and product/ service oriented indicators, seem to be very important factors for improving not only the financial situation within the bank, but also overall business performances. Additionally, the findings prove that there is the cause-effect relationship between non-financial and financial dimensions of the Balanced Scorecard. Having in mind that the banks are still using outdated performance evaluation systems, such as annual, quarterly and monthly reports, we hope that this paper will contribute to the knowledge of how banks in Serbia may apply the Balanced Scorecard approach to evaluate their performance on the most efficient and effective way.

Keywords: balanced scorecard approach, bank management, performance measurement systems, strategic performances

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Authors: Shibei Huang

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In deep energy retrofits, the thermal performance of existing building envelopes is often difficult to determine with a high level of accuracy. For older buildings, the records of existing assemblies are often incomplete or inaccurate. To obtain greater baseline performance accuracy for energy models, in-field measurement tools can be used to obtain data on the thermal performance of the existing assemblies. For a known assembly, these field measurements assist in validating the U-factor estimates. If the field-measured U-factor consistently varies from the calculated prediction, those measurements prompt further study. For an unknown assembly, successful field measurements can provide approximate U-factor evaluation, validate assumptions, or identify anomalies requiring further investigation. Using case studies, this presentation will focus on the non-destructive methods utilizing a set of various field tools to validate the baseline U-factors for a range of existing buildings with various wall assemblies. The lessons learned cover what can be achieved, the limitations of these approaches and tools, and ideas for improving the validity of measurements. Key factors include the weather conditions, the interior conditions, the thermal mass of the measured assemblies, and the thermal profiles of the assemblies in question.

Keywords: existing building, sensor, thermal analysis, retrofit

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Authors: Rogerio Vieira Dos Reis

Abstract:

Countries like Brazil that despite fighting hard against corruption are not improving their corruption perception, especially due to systemic political corruption, should review their corruption prevention strategies. This thesis brings a case study based on an alternative way of preventing corruption: addressing the corruption drivers in public policies that lead to poor economic performance. After discussing the Brazilian industrial policies adopted recently, especially the measures towards the automotive sector, two corruption issues in this sector are analyzed: facilitating payment for fiscal benefits and buying the extension of fiscal benefits. In-depth interviews conducted with a policymaker and an executive of the automobile sector provide insights for identifying three main corruption drivers: excessive and unnecessary bureaucracy, a complex tax system and the existence of a closed market without setting performance requirements to be achieved by the benefited firms. Both the identification of the drivers of successful industrial policies and the proposal of anti-corruption strategies to ensure developmental outcomes are based on the economic perspective of industrial policy advocated by developmental authors and on the successful South Korean economic development experience. Structural anti-corruption measures include tax reform, the regulation of lobbying and legislation to allow corporate political contribution. Besides improving policymakers’ technical capabilities, measures at the ministry level include redesigning the automotive regimes as long-term policies focused on national investment with simple and clear rules and making fiscal benefits conditional upon performance targets focused on suppliers. This case study is of broader interest because it recommends the importance of adapting performance audits conducted by anti-corruption agencies, to focus not only on the delivery of public services, but also on the identification of potentially highly damaging corruption drivers in public policies that grant fiscal benefits to achieve developmental outcomes.

Keywords: Brazilian automotive sector, corruption, economic development, industrial policy, Inovar-Auto

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Authors: Saidia Houari

Abstract:

The current coronavirus pandemic (COVID-19) is a special and unusual reality. It can affect people physically, but also psychologically. Indeed, in such a context, many people will experience reactions of stress, anxiety and depression, and Sports is known to be a great in improving the effectiveness of the nervous system and mental health. Professor Ango Frubuze“many studies proved that sports play an important role in fighting psychological tension and some other psychological problems, such as depression and sleep difficulties, but on condition of practicing them properly,choosing the kind that generates comfort and happiness for man “ .The sports university professor in the German city of Cologne added that the effort exerted during the exercise works on restoring balance to the stress hormones like cortisol.The case report provides an insight into the COVID-19 current situation and represents a picture of the current state of mental health and an overview of novel coronavirus (Covid-19) outbreaks in some countries of the world. Some procedures taken to combat the coronavirus. We proposed the practice of physical activities during the quarantine period, and we showed their importance and their positive effects.

Keywords: COVID-19, psycholiqical impacts, stress, physical activities

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Authors: Sadık Ata, Kevser Dincer

Abstract:

In this study, the performance of proton exchange membrane (PEM) fuel cell was experimentally investigated and modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Coating on the anode side of the PEM fuel cell was accomplished with the spin method by using Yttria-stabilized zirconia (YSZ). Input-output parameters were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6),High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of performance PEM fuel cell.

Keywords: proton exchange membrane (PEM), fuel cell, rule-based mamdani-type fuzzy (RMBTF) modelling, Yttria-stabilized zirconia (YSZ)

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Authors: Bita Mashayekhi, Amin Jahangard, Milad Samavat, Saeid Homayoun

Abstract:

In the modern competitive business environment, one cannot overstate the importance of corporate social responsibility. The controversial link between the social and financial performance of firms has become a topic of interest for scholars. Hence, this study examines the social and financial performance link by taking into account the mediating role of innovation performance. We conducted the Covariance-based Structural Equation Modeling (CB-SEM) method on an international sample of firms provided by the ASSET4 database. In this research, to explore the black box of the social and financial performance relationship, we first examined the effect of social performance separately on financial performance and innovation; then, we measured the mediation role of innovation in the social and financial performance link. While our results indicate the positive effect of social performance on financial performance and innovation, we cannot document the positive mediating role of innovation. This possibly relates to the long-term nature of benefits from investments in innovation.

Keywords: ESG, financial performance, innovation, social performance, structural equation modeling

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Authors: Jamila Garba Audu, Shehu Usman Hassan

Abstract:

The widespread failure in the financial information quality has created the need to improve the financial information quality and to strengthen the control of managers by setting up good firms structures. Published accounting information in financial statements is required to provide various users - shareholders, employees, suppliers, creditors, financial analysts, stockbrokers and government agencies – with timely and reliable information useful for making prudent, effective and efficient decisions. The relationship between corporate governance and performance to financial reporting quality is imperative; this is because despite rapid researches in this area the findings obtained from these studies are constantly inconclusive. Data for the study were extracted from the firms’ annual reports and accounts. After running the OLS regression, a robustness test was conducted for the validity of statistical inferences; the data was empirically tested. A multiple regression was employed to test the model as a technique for data analysis. The results from the analysis revealed a negative association between all the regressors and financial reporting quality except the performance of listed manufacturing firms in Nigeria. This indicates that corporate governance plays a significant role in mitigating earnings management and improving financial reporting quality while performance does not. The study recommended among others that the composition of audit committee should be made in accordance with the provision for code of corporate governance which is not more than six (6) members with at least one (1) financial expert.

Keywords: corporate governance, financial reporting quality, manufacturing firms, Nigeria, performance

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Authors: Tacho Rubby Kong

Abstract:

Community health workers’ performances are known to influence members’ behaviours and practices while translating policies into service delivery. However, little remains known about the extent to which this remains true within interventions aimed at addressing malaria burden in low-resource settings like Cameroon. The objective of this study was to examine the health workers’ performance and their influence on the adoption of strategies to address the malaria burden at a subnational level health system in Cameroon. A qualitative exploratory design was adopted on a purposively selected sample of 18 key informants. The study was conducted in Konye health district among sub-national health systems, managers, health facility in-charges, and frontline community health workers. Data was collected using semi-structured interview guides in a face-to-face interview with respondents. The analysis adopted a thematic approach utilising journals, credible authors, and peer review articles for data management. Participants acknowledged that workplace networks were influential during the implementation of policies to address malaria. The influence exerted was in form of linkage with other services, caution, and advice regarding strict adherence to policy recommendations, perhaps reflective of the level of trust in providers’ ability to adhere to policy provisions. At the district health management level and among non-state actors, support in perceived areas of weak performance in policy implementation was observed. In addition, timely initiation of contact and subsequent referral was another aspect where community health workers exerted influence while translating policies to address the malaria burden. While the level of support from among network peers was observed to influence community health workers’ adoption and implementation of strategies to address the malaria burden, different mechanisms triggered subsequent response and level of adherence to recommended policy aspects. Drawing from the elicited responses, it was infer that community health workers’ performance influence the direction and extent of success in policy implementation to address the malaria burden at the subnational level.

Keywords: subnational, community, malaria, strategy

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