Search results for: sport services model

Authors: Nor Azlina A. Rahman, Jamaliah Said, Salwana Hassan

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Prompt changes in global business environment, such as passionate competition, managerial/operational, changing governmental regulation and innovation in technology have significant impacts on the organizations. At present, global business environment demands for more proactive institutions on microfinance to provide an opportunity for the business success. Microfinance providers in Malaysia still accelerate its activities of funding by cash and cheque. These institutions are at high risk as the paper-based system is deemed to be slow and prone to human error, as well as requiring a major annual reconciliation process. The global transformation of financial services, growing involvement of technology, innovation and new business activities had progressively made risk management profile to be more subjective and diversified. The persistent, complex and dynamic nature of risk management activities in the institutions arise due to highly automated advancements of technology. This may thus manifest in a variety of ways throughout the financial services sector. This study seeks out to examine current operational risks management being experienced by microfinance providers in Malaysia; investigate the process of current practices on facilitator control factor mechanisms, and explore how the adoption of technology, innovation and use of management accounting practices would affect the risk management process of operation system in microfinance providers in Malaysia. A case study method was employed in this study. The case study also need to find that the vital past role of management accounting will be used for mitigation of risk management activities towards accountability as an information or guideline to microfinance provider. An empirical element obtainable with qualitative method is needed in this study, where multipart and in-depth information are essential to understand the issues of these institution phenomena. This study is expected to propose a theoretical model for implementation of technology, innovation and management accounting practices into the system of operation to improve internal control and subsequently lead to mitigation of risk management activities among microfinance providers to be more successful.

Keywords: microfinance, accountability, operational risks, management accounting practices

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Authors: Samaneh Pouyanfar, Michael Oliff

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The industry of home appliances may beone of theindustries which has the highest competition, and actually what can guarantee the survival of this industry is discovering the superior services. A trend to provide quality products and services plays an important role in this industry because discovering the services is counted as a vital affair for Manufacturing Organizations’ survival and profitability. Given the importance of the topic, this paper attempts to investigate the relative priority of the factors influencing the customer satisfaction in gaining the competitive advantage in Pars-Khazar Company. In sum, 96 executives of Pars-Khazar Company where investigated in a census. For this purpose, after reviewing the research literature and performing deep interviews between pundits and experts active in the industry, the research questionnaire was made based on variables affecting customer satisfaction and components determining business competitive advantage. Determining the content validity took place by judgement of the experts. The reliability of each structure was measured based on Cronbach’s alpha coefficient. Since the value of Cronbach's alpha was higher than 0.7 for each structure, internal consistency of statements was high and the reliability of the questionnaire was acceptable. The data analysis was also done with Kulmgrf-asmyrnf test and Friedman test using SPSS software. The results showed that in dimension of factors affecting customer satisfaction, the History of trade name (brand), Familiarity with the product brand, Brand reputation and Safety have the highest value of priority respectively, and the variable of firm growth has the highest value of priority among the components determining the performance of competitive advantage.

Keywords: customer satisfaction, competitive advantage, brand history, safety, growth

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Authors: Aymen Rhouma, Khaled Hcheichi, Sami Hafsi

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The article presents an application of Fractional Model Predictive Control (FMPC) to a fractional order thermal system using Controlled Auto Regressive Integrated Moving Average (CARIMA) model obtained by discretization of a continuous fractional differential equation. Moreover, the output deviation approach is exploited to design the K -step ahead output predictor, and the corresponding control law is obtained by solving a quadratic cost function. Experiment results onto a thermal system are presented to emphasize the performances and the effectiveness of the proposed predictive controller.

Keywords: fractional model predictive control, fractional order systems, thermal system, predictive control

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Authors: Y. S. Yusoff, G. Streftaris, H. R Waters

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Death within 30 days is an important factor to be looked into, as there is a significant risk of deaths immediately following or soon after, Myocardial Infarction (MI) or stroke. In this paper, we will model the deaths within 30 days following a Myocardial Infarction (MI) or stroke in the UK. We will see how the probabilities of sudden deaths from MI or stroke have changed over the period 1981-2000. We will model the sudden deaths using a Generalized Linear Model (GLM), fitted using the R statistical package, under a Binomial distribution for the number of sudden deaths. We parameterize our model using the extensive and detailed data from the Framingham Heart Study, adjusted to match UK rates. The results show that there is a reduction for the sudden deaths following a MI over time but no significant improvement for sudden deaths following a stroke.

Keywords: sudden deaths, myocardial infarction, stroke, ischemic heart disease

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Authors: C. Castro-Egler, A. Durán-Escalante, A. García-González

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This paper presents a method to generate a finite element model of the human auditory inner ear system. The geometric model has been realized using 2D images from a virtual model of temporal bones. A point cloud has been gotten manually from those images to construct a whole mesh with hexahedral elements. The main difference with the predecessor models is the spiral shape of the cochlea with its three scales completely defined: scala tympani, scala media and scala vestibuli; which are separate by basilar membrane and Reissner membrane. To validate this model, numerical simulations have been realised with two models: an isolated inner ear and a whole model of human auditory system. Ideal conditions of displacement are applied over the oval window in the isolated Inner Ear model. The whole model is made up of the outer auditory channel, the tympani, the ossicular chain, and the inner ear. The boundary condition for the whole model is 1Pa over the auditory channel entrance. The numerical simulations by FEM have been done using a harmonic analysis with a frequency range between 100-10.000 Hz with an interval of 100Hz. The following results have been carried out: basilar membrane displacement; the scala media pressure according to the cochlea length and the transfer function of the middle ear normalized with the pressure in the tympanic membrane. The basilar membrane displacements and the pressure in the scala media make it possible to validate the response in frequency of the basilar membrane.

Keywords: finite elements method, human auditory system model, numerical analysis, 3D modelling cochlea

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.

Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition

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Authors: K. Mellou, G. Anastopoulos, T. Zakinthinos, C. Botsi, A. Terzidis

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‘PHILOS – Emergency health response to refugee crisis’ is a programme of the Greek Ministry of Health, implemented by the Hellenic Center for Disease Control and Prevention (HCDCP). The programme is funded by the Asylum, Migration and Integration Fund (AMIF) of EU’s DG Migration and Home Affairs. With the EU Member States accepting, the last period, accelerating migration flows, Greece inevitably occupies a prominent position in the migratory map due to this geographical location. The main objectives of the programme are a) reinforcement of the capacity of the public health system and enhancement of the epidemiological surveillance in order to cover refugees/migrant population, b) provision of on-site primary health care and psychological support services, and c) strengthening of national health care system task-force. The basic methods for achieving the aforementioned goals are: a) implementation of syndromic surveillance system at camps and enhancement of public health response with the use of mobile medical units (Sub-action A), b) enhancement of health care services inside the camps via increasing human resources and implementing standard operating procedures (Sub-action B), and c) reinforcement of the national health care system (primary healthcare units, hospitals, and emergency care spots) of affected regions with personnel (Sub-action C). As a result, 58 health professionals were recruited under sub-action 2 and 10 mobile unit teams (one or two at each health region) were formed. The main actions taken so far by the mobile units are the evaluation, of syndromic surveillance, of living conditions at camps and medical services. Also, vaccination coverage of children population was assessed, and more than 600 catch-up vaccinations were performed by the end of June 2017. Mobile units supported transportation of refugees/migrants from camps to medical services reducing the load of the National Center for Emergency Care (more than 350 transportations performed). The total number of health professionals (MD, nurses, etc.) placed at camps was 104. Common practices were implemented in the recording and collection of psychological and medical history forms at the camps. Protocols regarding maternity care, gender based violence and handling of violent incidents were produced and distributed at personnel working at camps. Finally, 290 health care professionals were placed at primary healthcare units, public hospitals and the National Center for Emergency Care at affected regions. The program has, also, supported training activities inside the camps and resulted to better coordination of offered services on site.

Keywords: migrants, refugees, public health, syndromic surveillance, national health care system, primary care, emergency health response

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Authors: Michal Christina Steven, Mohd. Yusof Hj Ibrahim, Haryati Abdul Karim, Prabakaran Dhanaraj, Kelly Alexius Mansin

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After 27 years, Malaysia reported polio cases in 2019 involving the children of the undocumented migrants living in Sabah. These undocumented migrants present a significant challenge in achieving the elimination of vaccine-preventable diseases (VPD). Due to the recent polio outbreak among the undocumented migrant children in Sabah, an in-depth interview was conducted among the caregivers of undocumented migrant children to identify the barriers and drivers towards vaccinating their children. Financial barriers, legal citizenship status, language barrier, the COVID-19 pandemic, and physical barriers have been the barriers to access vaccination services by undocumented migrants. Five significant drivers for undocumented migrants to vaccinate their children are social influence, fear of disease, parental trust in healthcare providers, good support, and vaccine availability. Necessary action should be taken immediately to address the problems of vaccinating the children of undocumented migrants to prevent the re-emergence of VPD.

Keywords: Malaysia, polio, Sabah, undocumented migrants

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Authors: Jia-Jang Wu

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This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.

Keywords: torsional vibration, full-size model, scale model, scaling laws

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Authors: Shahram Payandeh

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This paper presents an overview of a model which can be used as a part of a decision support system when fusing information from multiple sensing environment. Data fusion has been widely studied in the past few decades and numerous frameworks have been proposed to facilitate decision making process under uncertainties. Multi-sensor data fusion technology plays an increasingly significant role during people tracking and activity recognition. This paper presents an overview of a quantum model as a part of a decision-making process in the context of multi-sensor data fusion. The paper presents basic definitions and relationships associating the decision-making process and quantum model formulation in the presence of uncertainties.

Keywords: quantum model, sensor space, sensor network, decision support

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Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

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Authors: Eszter Repasi, Akos Koller

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Our genetic information determines our look, physiology, sports performance and all our features. Maximizing the performances of athletes have adopted a science-based approach to the nutritional support. Nowadays genetics studies have blended with nutritional sciences, and a dynamically evolving, new research field have appeared. Nutritional genomics is needed to be used by nutritional experts. This is a recent field of nutritional science, which can provide a solution to reach the best sport performance using correlations between the athlete’s genome, nutritions, molecules, included human microbiome (links between food, microbiome and epigenetics), nutrigenomics and nutrigenetics. Nutritional genomics has a tremendous potential to change the future of dietary guidelines and personal recommendations. Experts need to use new technology to get information about the athletes, like nutritional genomics profile (included the determination of the oral and gut microbiome and DNA coded reaction for food components), which can modify the preparation term and sports performance. The influence of nutrients on the genes expression is called Nutrigenomics. The heterogeneous response of gene variants to nutrients, dietary components is called Nutrigenetics. The human microbiome plays a critical role in the state of health and well-being, and there are more links between food or nutrition and the human microbiome composition, which can develop diseases and epigenetic changes as well. A nutritional genomics-based profile of athletes can be the best technic for a dietitian to make a unique sports nutrition diet plan. Using functional food and the right food components can be effected on health state, thus sports performance. Scientists need to determine the best response, due to the effect of nutrients on health, through altering genome promote metabolites and result changes in physiology. Nutritional biochemistry explains why polymorphisms in genes for the absorption, circulation, or metabolism of essential nutrients (such as n-3 polyunsaturated fatty acids or epigallocatechin-3-gallate), would affect the efficacy of that nutrient. Controlled nutritional deficiencies and failures, prevented the change of health state or a newly discovered food intolerance are observed by a proper medical team, can support better sports performance. It is important that the dietetics profession informed on gene-diet interactions, that may be leading to optimal health, reduced risk of injury or disease. A special medical application for documentation and monitoring of data of health state and risk factors can uphold and warn the medical team for an early action and help to be able to do a proper health service in time. This model can set up a personalized nutrition advice from the status control, through the recovery, to the monitoring. But more studies are needed to understand the mechanisms and to be able to change the composition of the microbiome, environmental and genetic risk factors in cases of athletes.

Keywords: gene-diet interaction, multidisciplinary team, microbiome, diet plan

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Authors: Manas Tripathi, Arunabha Mukhopadhyay

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In Cloud computing environment, cloud servers, sometimes may crash after receiving huge amount of request and cloud services may stop which can create huge loss to users of that cloud services. This situation is called Denial of Service (DoS) attack. In Distributed Denial of Service (DDoS) attack, an attacker targets multiple network paths by compromising various vulnerable systems (zombies) and floods the victim with huge amount of request through these zombies. There are many solutions to mitigate this challenge but most of the methods allows the attack traffic to arrive at Cloud Service Provider (CSP) and then only takes actions against mitigation. Here in this paper we are rather focusing on preventive mechanism to deal with these attacks. We analyze network topology and find most vulnerable paths beforehand without waiting for the traffic to arrive at CSP. We have used Dijkstra's and Yen’s algorithm. Finally, risk assessment of these paths can be done by multiplying the probabilities of attack for these paths with the potential loss.

Keywords: cloud computing, DDoS, Dijkstra, Yen’s k-shortest path, network security

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Authors: Yenisleidy Martínez-Martínez, Yannay Casas-Ledón, Jo Dewulf

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Wind power constitutes a cleaner energy source with smaller unfavorable impacts on the environment than fossil fuels. Its development could be an alternative to fight climate change while meeting energy demands. However, wind energy development requires first determining the existing potential and areas with aptitude. Also, potential socio-economic and environmental impacts should be analyzed to prevent social rejection of this technology. In this context, this work performs a suitability assessment on a GIS environment to locate suitable areas for wind energy expansion in South-Central Chile. In addition, suitable areas were characterized in terms of potential goods and services to be produced as a proxy for analyzing potential impacts and trade-offs. First, layers of annual wind speed were generated as they represent the resource potential, and layer representing previously defined territorial constraints were created. Zones depicting territorial constraints were removed from resource measurement layers to identify suitable sites. Then, the appropriation of the primary production in suitable sites was determined to measure potential ecosystem services derived from human interventions in those areas. Results show that approximately 52% of the total surface of the study area has a good aptitude to install wind farms. In this area, provisioning services like food crops production, timber, and other forest resources like firewood play a key role in the regional economy and thus are the main cause of human interventions. This is reflected by human appropriation of the primary production values of 0.71 KgC/m².yr, 0.36 KgC/m².yr, and 0.14 KgC/m².yr, respectively. In this sense, wind energy development could be compatible with croplands, which is the predominant land use in suitable areas, and provide farmers with cheaper energy and extra income. Also, studies have reported changes in local temperature associated with wind turbines, which could be beneficial to crop growth. The results obtained in this study prove to be useful for identifying available areas for wind development, which could be very useful in decision-making processes related to energy planning.

Keywords: net primary productivity, provisioning services, suitability assessment, wind energy

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Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

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Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo

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Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.

Keywords: PEMFC, neural network, nonlinear modeling, NNARX

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Authors: Shuen-Tai Wang, Hsi-Ya Chang

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Cloud computing is becoming more and more matured over the last few years and consequently the demands for better cloud services is increasing rapidly. One of the research topics to improve cloud services is the desktop computing in virtualized environment. This paper aims at the development of an adaptive virtual desktop service in cloud computing platform based on our previous research on the virtualization technology. We implement cloud virtual desktop and application software streaming technology that make it possible for providing Virtual Desktop as a Service (VDaaS). Given the development of remote desktop virtualization, it allows shifting the user’s desktop from the traditional PC environment to the cloud-enabled environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote desktop service represents the next significant step to the mobile workplace, and it lets users access their desktop environments from virtually anywhere.

Keywords: cloud computing, virtualization, virtual desktop, VDaaS

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Authors: Kaori Narita, Juan de Dios Tena Horrillo, Claudio Detotto

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Decisions on replacement of leaders are of significance and high prevalence in any organization, and concerns many of its stakeholders, whether it is a leader in a political party or a CEO of a firm, as indicated by high media coverage of such events. This merits an investigation into the consequences and implications of a leadership change on the performances and behavior of organizations and their workers. Sport economics provides a fruitful field to explore these issues due to the high frequencies of managerial changes in professional sports clubs and the transparency and regularity of observations of team performance and players’ abilities. Much of the existing research on managerial change focuses on how this affects the performance of an organization. However, there is scarcely attention paid to the consequences of such events on the behavior of individuals within the organization. Changes in behavior and attitudes of a group of workers due to a managerial change could be of great interest in management science, psychology, and operational research. On the other hand, these changes cannot be observed in the final outcome of the organization, as this is affected by many other unobserved shocks, for example, the stress level of workers with the need to deal with a difficult situation. To fill this gap, this study shows the first attempt to evaluate the impact of managerial change on players’ behaviors such as attack intensity, aggressiveness, and efforts. The data used in this study is from the top tier Italian football league (“Serie A”), where an average of 13 within season replacements of head coaches were observed over the period of seasons from 2000/2001 to 2017/18. The preliminary estimation employs Pooled Ordinary Least Square (POLS) and club-season Fixed Effect (FE) in order to assess the marginal effect of having a new manager on the number of shots, corners and red/yellow cards after controlling for a home-field advantage, ex ante abilities and current positions in the league of a team and their opponent. The results from this preliminary estimation suggest that the teams do not show a significant difference in their behaviors before and after the managerial change. To build on these preliminary results, other methods, including propensity score matching and non-linear model estimates, will be used. Moreover, the study will further investigate these issues by considering other measurements of attack intensity, aggressiveness, and efforts, such as possessions, a number of fouls and the athletic performance of players, respectively. Finally, the study is going to investigate whether these results vary over the characteristics of a new head coach, for example, their age and experience as a manager and a player. Thus far, this study suggests that certain behaviours of individuals in an organisation are not immediately affected by a change in leadership. To confirm this preliminary finding and lead to a more solid conclusion, further investigation will be conducted in the aforementioned manner, and the results will be elaborated in the conference.

Keywords: behaviour, effort, manager characteristics, managerial change, sport economics

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Authors: El Hadji Mamadou Sonko, Ndiogou Sankhare, Maïmouna Lo, Jean Birane Gning, Cheikh Diop

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In Senegal, access to water, hygiene, and sanitation in small island towns is a particular problem, which is still poorly understood by the public authorities and development aid actors. The main objective of this study carried out in the Municipality of Foundiougne is to contribute to the knowledge of the problems related to the supply of drinking water, access to sanitation, and hygiene in small island towns in Senegal. The methodology adopted consisted of a literature review and quantitative surveys of a sample of 100 households in the Municipality. Semi-structured interviews using interview guides and informal interviews were also conducted with mechanical and manual emptiers, municipal authorities, public toilet managers, and neighbourhood leaders. Direct observation with photography was also used. The results show that, with regard to access to drinking water, 35% of households have unimproved water services, 46% have a limited level of service, and 19% have a basic level of service. Regarding sanitation, 77% of households are considered to have access to basic sanitation services, compared to 23% with limited sanitation services. However, these figures hide the dysfunctions of the sanitation system. Indeed, manual emptying is practiced exclusively by 4% of households, while 17% of households combine it with mechanical emptying. In addition, domestic wastewater is mainly evacuated outside the sanitation facilities, and all the sludge extracted from the pits is discharged directly into the environment without treatment. As a matter of fact, the surveys showed that 52% of households do not have access to a basic level of hygiene-related to handwashing when leaving the toilet. These results show that there is real work to be done at the level of small urban centres if we want to achieve MDG 6.

Keywords: Foundiougne, Senegal, small island, small town, water-sanitation, hygiene

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Authors: Till Gramberg, Erwin Gross, Christoph Birenbaum

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This paper presents the approach of the Easy2IoT research project. Easy2IoT aims to enable companies in the prefabrication sheet metal and sheet metal processing industry to enter the Industrial Internet of Things (IIoT) with a low-threshold and cost-effective approach. It focuses on the development of physical hardware and software to easily capture machine activities from on a sawing machine, benefiting various stakeholders in the SME value chain, including machine operators, tool manufacturers and service providers. The methodological approach of Easy2IoT includes an in-depth requirements analysis and customer interviews with stakeholders along the value chain. Based on these insights, actions, requirements and potential solutions for smart services are derived. The focus is on providing actionable recommendations, competencies and easy integration through no-/low-code applications to facilitate implementation and connectivity within production networks. At the core of the project is a novel, non-invasive measurement and analysis system that can be easily deployed and made IIoT-ready. This system collects machine data without interfering with the machines themselves. It does this by non-invasively measuring the tension on a sawing machine. The collected data is then connected and analyzed using artificial intelligence (AI) to provide smart services through a platform-based application. Three Smart Services are being developed within Easy2IoT to provide immediate benefits to users: Wear part and product material condition monitoring and predictive maintenance for sawing processes. The non-invasive measurement system enables the monitoring of tool wear, such as saw blades, and the quality of consumables and materials. Service providers and machine operators can use this data to optimize maintenance and reduce downtime and material waste. Optimize Overall Equipment Effectiveness (OEE) by monitoring machine activity. The non-invasive system tracks machining times, setup times and downtime to identify opportunities for OEE improvement and reduce unplanned machine downtime. Estimate CO2 emissions for connected machines. CO2 emissions are calculated for the entire life of the machine and for individual production steps based on captured power consumption data. This information supports energy management and product development decisions. The key to Easy2IoT is its modular and easy-to-use design. The non-invasive measurement system is universally applicable and does not require specialized knowledge to install. The platform application allows easy integration of various smart services and provides a self-service portal for activation and management. Innovative business models will also be developed to promote the sustainable use of the collected machine activity data. The project addresses the digitalization gap between large enterprises and SME. Easy2IoT provides SME with a concrete toolkit for IIoT adoption, facilitating the digital transformation of smaller companies, e.g. through retrofitting of existing machines.

Keywords: smart services, IIoT, IIoT-platform, industrie 4.0, big data

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Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

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Authors: Liu Yi, Bao Liyong

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Aiming at the problem of low efficiency of pipelined scheduling in periodic query-qualified service, this paper proposes a system service resource scheduling strategy with parallel optimized qualified service polling control. The paper constructs the polling queuing system and its mathematical model; firstly, the first-order and second-order characteristic parameter equations are obtained by partial derivation of the probability mother function of the system state variables, and the complete mathematical, analytical expressions of each system parameter are deduced after the joint solution. The simulation experimental results are consistent with the theoretical calculated values. The system performance analysis shows that the average captain and average period of the system have been greatly improved, which can better adapt to the service demand of delay-sensitive data in the dense data environment.

Keywords: polling, parallel scheduling, mean queue length, average cycle time

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Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

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Authors: Moomen Chaari, Wolfgang Ecker, Thomas Kruse, Bogdan-Andrei Tabacaru

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In our daily life, we frequently interact with complex systems which facilitate our mobility, enhance our access to information, and sometimes help us recover from illnesses or diseases. The reliance on these systems is motivated by the established evaluation and assessment procedures which are performed during the different phases of the design and manufacturing flow. Such procedures are aimed to qualify the system’s delivered services with respect to their availability, reliability, safety, and other properties generally referred to as dependability attributes. In this paper, we propose a metamodel based generic characterization of dependability concepts and describe an automation methodology to customize this characterization to different standards and contexts. When integrated in concrete design and verification environments, the proposed methodology promotes the reuse of already available dependability assessment tools and reduces the costs and the efforts required to create consistent and efficient artefacts for fault injection or error simulation.

Keywords: dependability analysis, model-driven development, metamodeling, code generation

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Authors: Tak Mau Simon Chan, Ying Chuen Lance Chan

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Homelessness has been a popular and controversial debate in Hong Kong, a city which is densely populated and well-known for very expensive housing. The constitution of the homeless as threats to the community and environmental hygiene is ambiguous and debatable in the Hong Kong context. The lack of an intervention model is the critical research gap thus far, aside from the tangible services delivered. The life story approach (LSA), with its unique humanistic orientation, has been well applied in recent decades to depict the needs of various target groups, but not the homeless. It is argued that the life story approach (LSA), which has been employed by health professionals in the landscape of dementia, and health and social care settings, can be used as a reference in the local Chinese context through indigenization. This study, therefore, captures the viewpoints of service providers and users by constructing an indigenous intervention model that refers to the LSA in serving the chronically homeless. By informing 13 social workers and 27 homeless individuals in 8 focus groups whilst 12 homeless individuals have participated in individual in-depth interviews, a framework of LSA in homeless people is proposed. Through thematic analysis, three main themes of their life stories was generated, namely, the family, negative experiences and identity transformation. The three domains solidified framework that not only can be applied to the homeless, but also other disadvantaged groups in the Chinese context. Based on the three domains of family, negative experiences and identity transformation, the model is applied in the daily practices of social workers who help the homeless. The domain of family encompasses familial relationships from the past to the present to the speculated future with ten sub-themes. The domain of negative experiences includes seven sub-themes, with reference to the deviant behavior committed. The last domain, identity transformation, incorporates the awareness and redefining of one’s identity and there are a total of seven sub-themes. The first two domains are important components of personal histories while the third is more of an unknown, exploratory and yet to-be-redefined territory which has a more positive and constructive orientation towards developing one’s identity and life meaning. The longitudinal temporal dimension of moving from the past – present - future enriches the meaning making process, facilitates the integration of life experiences and maintains a more hopeful dialogue. The model is tested and its effectiveness is measured by using qualitative and quantitative methods to affirm the extent that it is relevant to the local context. First, it contributes to providing a clear guideline for social workers who can use the approach as a reference source. Secondly, the framework acts as a new intervention means to address problem saturated stories and the intangible needs of the homeless. Thirdly, the model extends the application to beyond health related issues. Last but not least, the model is highly relevant to the local indigenous context.

Keywords: homeless, indigenous intervention, life story approach, social work practice

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Authors: Ling Qi, Matloob Khushi, Josiah Poon

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This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

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Authors: Jung–Min Yang

Abstract:

Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the desired input/output behavior. A matrix expression is presented to address reachability of switched asynchronous sequential machines with output equivalence with respect to a model. The presented reachability condition for the controller design is validated in a simple example.

Keywords: asynchronous sequential machines, corrective control, model matching, input/output control

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Authors: Hycham Aboutaleb, Bruno Monsuez

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Current systems complexity has reached a degree that requires addressing conception and design issues while taking into account all the necessary aspects. Therefore, one of the main challenges is the way complex systems are specified and designed. The exponential growing effort, cost and time investment of complex systems in modeling phase emphasize the need for a paradigm, a framework and a environment to handle the system model complexity. For that, it is necessary to understand the expectations of the human user of the model and his limits. This paper presents a generic framework for designing complex systems, highlights the requirements a system model needs to fulfill to meet human user expectations, and defines the refined functional as well as non functional requirements modeling tools needs to meet to be useful in model-based system engineering.

Keywords: system modeling, modeling language, modeling requirements, framework

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Authors: Alexander K. Edwards

Abstract:

Introduction: The moral dimension of teacher education globally has assumed a new paradigm of thinking based on the public gain (return-on-investments), value-creation (quality), professionalism (practice), and business strategies (innovations). Abundant literature reveals an interesting revolutionary trend in complimenting the raising of teachers and academic performances. Because of the global competition in the knowledge-creation and service areas, the C21st teacher at all levels is expected to be resourceful, strategic thinker, socially intelligent, relationship aptitude, and entrepreneur astute. This study is a significant contribution to practice and innovations to raise exemplary or primal teachers. In this study, the qualities needed were considered as ‘Quadrant Intelligence (Q-i)’ model for a primal teacher leadership beyond the classroom. The researcher started by examining the issue of the majority of teachers in Ghana Education Services (GES) in need of this Q-i to be effective and efficient. The conceptual framing became determinants of such Q-i. This is significant for global employability and versatility in teacher education to create premium and primal teacher leadership, which are again gaining high attention in scholarship due to failing schools. The moral aspect of teachers failing learners is a highly important discussion. In GES, some schools score zero percent at the basic education certificate examination (BECE). The question is what will make any professional teacher highly productive, marketable, and an entrepreneur? What will give teachers the moral consciousness of doing the best to succeed? Method: This study set out to develop a model for primal teachers in GES as an innovative way to highlight a premium development for the C21st business-education acumen through desk reviews. The study is conceptually framed by examining certain skill sets such as strategic thinking, social intelligence, relational and emotional intelligence and entrepreneurship to answer three main burning questions and other hypotheses. Then the study applied the causal comparative methodology with a purposive sampling technique (N=500) from CoE, GES, NTVI, and other teachers associations. Participants responded to a 30-items, researcher-developed questionnaire. Data is analyzed on the quadrant constructs and reported as ex post facto analyses of multi-variances and regressions. Multiple associations were established for statistical significance (p=0.05). Causes and effects are postulated for scientific discussions. Findings: It was found out that these quadrants are very significant in teacher development. There were significant variations in the demographic groups. However, most teachers lack considerable skills in entrepreneurship, leadership in teaching and learning, and business thinking strategies. These have significant effect on practices and outcomes. Conclusion and Recommendations: It is quite conclusive therefore that in GES teachers may need further instructions in innovations and creativity to transform knowledge-creation into business venture. In service training (INSET) has to be comprehensive. Teacher education curricula at Colleges may have to be re-visited. Teachers have the potential to raise their social capital, to be entrepreneur, and to exhibit professionalism beyond their community services. Their primal leadership focus will benefit many clienteles including students and social circles. Recommendations examined the policy implications for curriculum design, practice, innovations and educational leadership.

Keywords: emotional intelligence, entrepreneurship, leadership, quadrant intelligence (q-i), primal teacher leadership, strategic thinking, social intelligence

Procedia PDF Downloads 292