Search results for: progressive sports operational model

Authors: Ankit Nagar, Dinesh Kumar Nauriyal, Sukhpal Singh

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This paper examines the key determinants of farmers’ access to agricultural extension services, sources of agricultural extension services preferred and accessed by the farmers. An ordered logistic regression model was used to analyse the data of the 360 sample households based on a primary survey conducted in western Uttar Pradesh, India. The study finds that farmers' decision to engage in the agricultural extension programme is significantly influenced by factors such as education level, gender, farming experience, social group, group membership, farm size, credit access, awareness about the extension scheme, farmers' perception, and distance from extension sources. The most intriguing finding of this study is that the progressive farmers, which have long been regarded as a major source of knowledge diffusion, are the most distrusted sources of information as they are suspected of withholding vital information from potential beneficiaries. The positive relationship between farm size and ‘Access’ underlines that the extension services should revisit their strategies for targeting more marginal and small farmers constituting over 85 percent of the agricultural households by incorporating their priorities in their outreach programs. The study suggests that marginal and small farmers' productive potential could still be greatly augmented by the appropriate technology, advisory services, guidance, and improved market access. Also, the perception of poor quality of the public extension services can be corrected by initiatives aimed at building up extension workers' capacity.

Keywords: agriculture, access, extension services, ordered logistic regression

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Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

Procedia PDF Downloads 375

Authors: Elena C. Tamaş, Grațiela M. Țârlea, Gianni Flamaropol, Dragoș Hera

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This article is referring to a comparative study regarding the electrical energy consumption for lighting on diverse types of big sizes commercial buildings built in Romania after 2007, having 3, 4, 5 versus 8, 9, 10 operational years. Some buildings have installed building management systems (BMS) to monitor also the lighting performances starting with the opening days till the present days but some have chosen only local meters to implement. Firstly, for each analyzed building, the total required energy power and the energy power consumption for lighting were calculated depending on the lamps number, the unit power and the average daily running hours. All objects and installations were chosen depending on the destination/location of the lighting (exterior parking or access, interior or covering parking, building interior and building perimeter). Secondly, to all lighting objects and installations, mechanical counters were installed, and to the ones linked to BMS there were installed the digital meters as well for a better monitoring. Some efficient solutions are proposed to improve the power consumption, for example the 1/3 lighting functioning for the covered and exterior parking lighting to those buildings if can be done. This type of lighting share can be performed on each level, especially on the night shifts. Another example is to use the dimmers to reduce the light level, depending on the executed work in the respective area, and a 30% power energy saving can be achieved. Using the right BMS to monitor, the energy consumption depending on the average operational daily hours and changing the non-performant unit lights with the ones having LED technology or economical ones might increase significantly the energy performances and reduce the energy consumption of the buildings.

Keywords: commercial buildings, energy performances, lightning consumption, maintenance

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Authors: Gang Liu, Can Wang, Runnan Zhang, Quan Wang, Huimin Song, Shaomin Ji

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Biba model can protect information integrity but might deny various non-malicious access requests of the subjects, thereby decreasing the availability in the system. Therefore, a mechanism that allows exceptional access control is needed. Break the Glass (BTG) strategies refer an efficient means for extending the access rights of users in exceptional cases. These strategies help to prevent a system from stagnation. An approach is presented in this work for integrating Break the Glass strategies into the Biba model. This research proposes a model, BTG-Biba, which provides both an original Biba model used in normal situations and a mechanism used in emergency situations. The proposed model is context aware, can implement a fine-grained type of access control and primarily solves cross-domain access problems. Finally, the flexibility and availability improvement with the use of the proposed model is illustrated.

Keywords: Biba model, break the glass, context, cross-domain, fine-grained

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Authors: Ferhat Demir

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Even if strategic management is highly critical for all types of organizations, only a few maturity models have been proposed in business literature for the area of strategic management activities. This paper updates previous studies and presents a new conceptual model for assessing the maturity of strategic management in any organization. Strategic management maturity model (S-3M) is basically composed of 6 maturity levels with 7 dimensions. The biggest contribution of S-3M is to put innovation into agenda of strategic management. The main objective of this study is to propose a model to align innovation with business strategies. This paper suggests that innovation (breakthrough new products/services and business models) is the only way of creating sustainable growth and strategy studies cannot ignore this aspect. Maturity models should embrace innovation to respond dynamic business environment and rapidly changing customer behaviours.

Keywords: strategic management, innovation, business model, maturity model

Procedia PDF Downloads 194

Authors: Muhammad Tariq, Hammad Tahir, Fawwad Mahmood Butt

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Purpose: This study attempts to examine the best forecasting methodologies in the time series. The time series forecasting models such as VAR, ARCH and the ARMA are considered for the analysis. Methodology: The Bench Marks or the parameters such as Adjusted R square, F-stats, Durban Watson, and Direction of the roots have been critically and empirically analyzed. The empirical analysis consists of time series data of Consumer Price Index and Closing Stock Price. Findings: The results show that the VAR model performed better in comparison to other models. Both the reliability and significance of VAR model is highly appreciable. In contrary to it, the ARCH model showed very poor results for forecasting. However, the results of ARMA model appeared double standards i.e. the AR roots showed that model is stationary and that of MA roots showed that the model is invertible. Therefore, the forecasting would remain doubtful if it made on the bases of ARMA model. It has been concluded that VAR model provides best forecasting results. Practical Implications: This paper provides empirical evidences for the application of time series forecasting model. This paper therefore provides the base for the application of best time series forecasting model.

Keywords: forecasting, time series, auto regression, ARCH, ARMA

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Authors: Deepak Singh, Rail Kuliev

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The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

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Authors: Athmane Bakhta, Sebastien Leclaire, David Vidal, Francois Bertrand, Mohamed Cheriet

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This work presents a new three-dimensional variational model proposed for the simulation of ink seepage into paper sheets at the fiber level. The model, inspired by the Hising model, takes into account a finite volume of ink and describes the system state through gravity, cohesion, and adhesion force interactions. At the mesoscopic scale, the paper substrate is modeled using a discretized fiber structure generated using a numerical deposition procedure. A modified Monte Carlo method is introduced for the simulation of the ink dynamics. Besides, a multiphase lattice Boltzmann method is suggested to fine-tune the mesoscopic variational model parameters, and it is shown that the ink seepage behaviors predicted by the proposed model can resemble those predicted by a method relying on first principles.

Keywords: fibrous media, lattice Boltzmann, modelling and simulation, Monte Carlo, variational model

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Authors: Nathaniel C. Villanueva, Ian K. H. Chun, Alyssa S. Fujiwara, Emily R. Leibovitch, Brennan E. Yamamoto, Loren G. Yamamoto

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Introduction: In previous studies of high school sports, over 15% of concussions were attributed to contact with the playing surface. While artificial turf fields are increasing in popularity due to lower maintenance costs, artificial turf has been associated with more ankle and knee injuries, with inconclusive data on concussions. In this study, natural grass and artificial football fields were compared in terms of deceleration on fall impact. Methods: Accelerometers were placed on the forehead, apex of the head, and right ear of a Century Body Opponent Bag (BOB) manikin. A Riddell HITS football helmet was secured onto the head of the manikin over the accelerometers. This manikin was dropped onto natural grass (n = 10) and artificial turf (n = 9) high school football fields. The manikin was dropped from a stationary position at a height of 60 cm onto its front, back, and left side. Each of these drops was conducted 10 times at the 40-yard line, 20-yard line, and endzone. The net deceleration on impact was calculated as a net vector from each of the three accelerometers’ x, y, and z vectors from the three different locations on the manikin’s head (9 vector measurements per drop). Results: Mean values for the multiple drops were calculated for each accelerometer and drop type for each field. All accelerometers in forward and backward falls and one accelerometer in side falls showed significantly greater impact force on synthetic turf compared to the natural grass surfaces. Conclusion: Impact force was higher on synthetic fields for all drop types for at least one of the accelerometer locations. These findings suggest that concussion risk might be higher for athletes playing on artificial turf fields.

Keywords: concussion, football, biomechanics, sports

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Authors: Saba Shams Bidhendi, Steven Goh, Andrew Wandel

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The implementation of lean manufacturing initiatives has produced significant impacts in improving operational performance and reducing manufacturing wastes in the production process. However, selecting an appropriate set of lean strategies is critical to avoid misapplication of the lean manufacturing techniques and consequential increase in non-value-adding activities. To the author’s best knowledge, there is currently no methodology to select lean strategies that considers their impacts on manufacturing wastes and performance metrics simultaneously. In this research, a multi-objective methodology is proposed that suggests an appropriate set of lean initiatives based on their impacts on performance metrics and manufacturing wastes and within manufacturers’ resource limitation. The proposed methodology in this research suggests the best set of lean initiatives for implementation that have highest impacts on identified critical performance metrics and manufacturing wastes. Therefore, manufacturers can assure that implementing suggested lean tools improves their production performance and reduces manufacturing wastes at the same time. A case study was conducted to show the effectiveness and validate the proposed model and methodologies.

Keywords: lean manufacturing, lean strategies, manufacturing wastes, manufacturing performance, optimisation, decision making

Procedia PDF Downloads 193

Authors: Suparman

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Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: piecewise regression, bayesian, reversible jump MCMC, segmentation

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Authors: Batuhan Kocaoglu

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Although using powerful systems like ERP (Enterprise Resource Planning), companies still cannot benchmark their processes and measure their process performance easily based on predefined SCOR (Supply Chain Operation References) terms. The purpose of this research is to identify common and corresponding processes to present a conceptual model to model and measure the purchasing process of an organization. The main steps for the research study are: Literature review related to 'procure to pay' process in ERP system; Literature review related to 'sourcing' process in SCOR model; To develop a conceptual model integrating 'sourcing' of SCOR model and 'procure to pay' of ERP model. In this study, we examined the similarities and differences between these two models. The proposed framework is based on the assumptions that are drawn from (1) the body of literature, (2) the authors’ experience by working in the field of enterprise and logistics information systems. The modeling framework provides a structured and systematic way to model and decompose necessary information from conceptual representation to process element specification. This conceptual model will help the organizations to make quality purchasing system measurement instruments and tools. And offered adaptation issues for ERP systems and SCOR model will provide a more benchmarkable and worldwide standard business process.

Keywords: SCOR, ERP, procure to pay, sourcing, reference model

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Authors: M. Nita-Lazar, E. Manea, C. Bumbac, A. Banciu, C. Stoica

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The population and economic growth have generated a significant new number of pollutant compounds which have to be degraded before reaching the environment. The wastewater treatment plants (WWTPs) have been the last barrier between the domestic and/or industrial wastewaters and the environment. At present, the conventional WWTPs have very high operational costs, most of them linked to the aeration process (60-65% from total energy costs related to wastewater treatment). In addition, they have had a low efficiency in pollutants removal such as pharmaceutical and other resilient anthropogenic compounds. In our study, we have been focused on new wastewater treatment strategies to enhance the efficiency of pollutants removal and decrease the wastewater treatment operational costs. The usage of mixed microalgae-bacteria granules technology generated high efficiency and low costs by a better harvesting and less expensive aeration. The intertrophic relationships between microalgae and bacteria have been characterized by the structure of the population community to their metabolic relationships. The results, obtained by microscopic studies, showed well-organized and stratified microalgae-bacteria granules where bacteria have been enveloped in the microalgal structures. Moreover, their population community structure has been modulated as well as their nitrification, denitrification processes (analysis based on qPCR genes expression) by the type of the pollutant compounds and amounts. In conclusion, the understanding and modulation of intertrophic relationships between microalgae and bacteria could be an economical and technological viable alternative to the conventional wastewater treatment. Acknowledgements: This research was supported by grant PN-III-P4-ID-PCE-2016-0865 from the Romanian National Authority for Scientific Research and Innovation CNCS/CCCDI-UEFISCDI.

Keywords: activated sludge, bacteria, granules, microalgae

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Authors: Magdy Abouzeid

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Introduction: Physical activity has been shown to have a positive effect on bone mineral density (BMD) and bone mineral content (BMC) among children, adolescents, and adults. Sports characterized by little or moderate weight bearing or impact have a low osteogenic effect. However, the action of such sports on bone turnover remains unclear. Swimming, as a non-weight-bearing sport, has been considered to be insignificant in the maintenance of bone mass. Purpose: To examine this issue we measured (BMD) and(BMC) of the lumbar spine, proximal femur via dual energy x-ray absorptiometry in the group of elite male swimmers, and determine the effect of swimming training on bone health and compared the results with matched controls group in age, body weight and height. Materials and Methods: Twenty-five male swimmers (age 20.7+/-0.8 years) training for 12-15 hours/week; and the controls group consisted of 25 non-active male (age 21.3 +/-1.3 years) were studied BMD and BMC of lumbar spine, femur were assessed via (DXA) absorptiometry. Results: There was significant difference between swimmers and control group in BMD and BMC, BMD of Swimmers was significantly greater than controls at all sites. The lumbar spine (1, 08 +/-0.202 vs., 0717+0.57 gxcm (-2), right proximal femur (1, 02 +/-, 044 vs., 771+/-, 027 gxcm (-2), and left proximal femur (1.374+/-0.212 vs. 1.01 +/-0.141 gxcm (-2). Swimmers were significantly taller, and had greater BMC and BMD compared to the controls group (P<0.001). Conclusions: These results suggest that swimming training may be beneficial in the prevention or therapy of OSTEOPENIA, and may lead to increased (BMD) and (BMC) for male swimmers. Swimming may be an effective non-pharmacological intervention for the adults and adolescent. Further research with younger athletes of another type of aquatics sport is warranted to better identify the periods of BMD development during which Aquatics sport has the greatest impact on bone health.

Keywords: bone mineral density, lumbar spine, femur, swimming, DXA absorptiometry

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Authors: M. Kumpugdee-Vollrath, T. G. D. Phu, M. Helmis

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A suitable model membrane to study the pharmacological effect of pharmaceutical products is human stratum corneum because this layer of human skin is the outermost layer and it is an important barrier to be passed through. Other model membranes which were also used are for example skins from pig, mouse, reptile or fish. We are interested in fish skins in this project. The advantages of the fish skins are, that they can be obtained from the supermarket or fish shop. However, the fish skins should be freshly prepared and used directly without storage. In order to understand the effect of different model drugs e.g. lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid on the properties of the model membrane from various types of fishes e.g. trout, salmon, cod, plaice permeation tests were performed and differential scanning calorimetry was applied.

Keywords: fish skin, model membrane, permeation, DSC, lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid

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Authors: Rahele Mosleh

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This paper gives a survey of results on global stability of extended Ross model for malaria by constructing some elegant Lyapunov functions for two cases of epidemic, including disease-free and endemic occasions. The model is a nonlinear seven-dimensional system of ordinary differential equations that simulates this phenomenon in a more realistic fashion. We discuss the existence of positive disease-free and endemic equilibrium points of the model. It is stated that extended Ross model possesses invariant solutions for human and mosquito in a specific domain of the system.

Keywords: global stability, invariant solutions, Lyapunov function, stationary points

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Authors: Insaf Sayar, Moôtez Marzougui, Abderraouf Ben Abderrahman

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Background: Physical Education and Sports (PES) plays an important role in the overall education of the student. It has physical, affective, psychological, and social repercussions. In fact, overweight children are sometimes underestimated by their lower physical performance and suffer from discriminatory attitudes by their peers and their physical education (PE) teachers. Objectives: The aim of this study was to investigate the impacts of both teacher’s pedagogy and overweight or obesity on the inclusion of obese students in physical education classes in the school setting in the Emirate of Ajman (United Arab Emirates) and to understand how physical education and sports (PES) teachers adapt their pedagogical interventions towards this category. Methods: A sample of 48 overweight or obese students and 20 teachers were approached from different schools in Ajman Emirate. Two standardized questionnaires for obese students and PSE teachers were used. Overweight and obesity were defined using age and sex-specific Body Mass Index (BMI). Results: Our results showed that the average BMI of the surveyed students is 28.58 ± 3.14 kg/m². According to the collected data, 85.42% of obese students report that they do not practice physical activity or rarely practice outside of school, and 73.42% go to school by bus or car. In addition, 66.7% of the surveyed students said that being overweight is a barrier to PES practice, and 100% of obese or overweight students do not prefer some physical activities such as running and jumping. Similarly, 75% of the surveyed teachers said that obese students are not integrated into the PES course, but only 55% of teachers reported that the obese student became an obstacle in PES sessions, while 80% of teachers reported that obese or overweight students were marginalized by their colleagues. In the same way, most of them (75%) said that obese students are exempted from PES courses. Conclusion: Overweight/obesity is prevalent among school children in the Emirate of Ajman, with a high correlation with sedentary behavior. The study confirmed an urgent need and effective teaching strategies/ pedagogies for including overweight or obese students in physical education engagement and learning.

Keywords: adolescent, mainstreaming, obesity, PES education, UAE

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Authors: Sina Saadati, Mohammadreza Razzazi

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Since Java is an object-oriented language, It can be used to solve a wide range of problems. One of the considerable usages of this language can be found in Agent-based modeling and simulation. Despite the significant power of Java, There is not an easy method to render a 3-dimensional human model. In this article, we are about to develop a library which helps modelers present a 3D human model and control it with Java. The library runs two server programs. The first one is a web page server that can connect to any browser and present an HTML code. The second server connects to the browser and controls the movement of the model. So, the modeler will be able to develop a simulation and display a good-looking human model without any knowledge of any graphical tools.

Keywords: agent-based modeling and simulation, human model, graphics, Java, distributed systems

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Authors: Mehmet Akif Aslan, Mehmet Simsek, Eyup Sensoy

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Big Data stands for today’s cutting-edge technology. As the technology becomes widespread, so does Data. Utilizing massive data sets enable companies to get competitive advantages over their adversaries. Out of many area of Big Data usage, logistics has significance role in both commercial sector and military. This paper lays out what big data is and how it is used in both military and commercial logistics.

Keywords: big data, logistics, operational efficiency, risk management

Procedia PDF Downloads 641

Authors: Yizhi Zhang, Xiaozan Wang, Mingming Guo, Pengpeng Li

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Introduction: The purpose of this study is to examine the effectiveness of after-school football training in improving the physical fitness of primary school students, so as to provide corresponding suggestions for carrying out after-school football training in primary schools. Methods: A total of 72 students from the experimental primary school of Mouping district, Yantai city, Shandong province, participated in this experiment. The experiment was conducted for two semesters. During the experiment period, the experimental group conducted one-hour football training after school from Monday to Thursday afternoon every week, and two hours of football training on Saturday morning every week. The control group conducted sports teaching and extracurricular activities as usual without other intervention. Before and after the experiment, both the experimental group and the control group underwent physical fitness tests according to the physical fitness test standards of Chinese students, including lung capacity, 50-meter run, one-minute skipping rope, sitting forward flexor, and one-minute sit-ups. The test results were all converted to the 100-point system according to the scoring standards. Results: (1) Before the experiment, there was no significant difference between the experimental group and the control group in various physical fitness indicators (p > 0.05). (2) After the experiment, the lung capacity score (T = 3.108, p < 0.05), the 50-meter run score (T = 6.593, p < 0.05), the skipping score (T = 9.227, p < 0.05), the sitting forward flexor score (T = 3.742, p < 0.05), and the sit-up score (T = 5.210, p < 0.05) of the experimental group were significantly higher than that of the control group. Conclusion: This study shows that the physical fitness of primary school students can be improved by football training in their spare time. It is suggested to carry out after-school football training activities in primary schools so as to effectively improve the physical fitness of pupils.

Keywords: after-school football training, physical fitness, primary school students, school sports

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Authors: Iulian Clain

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In contemporary public administration, the demand for greater accountability, transparency, and efficient governance has intensified, particularly in the face of increasing public scrutiny and fiscal constraints. Internal auditing has emerged as a vital tool in strengthening governance structures, enhancing the effectiveness of public sector institutions, and ensuring compliance with regulatory frameworks. This paper examines the evolving role of internal auditing within public administration, with an emphasis on risk management, regulatory compliance, and fraud prevention. Building on institutional theory and risk management frameworks, this study explores how internal audits contribute to identifying operational inefficiencies, minimizing financial irregularities, and promoting ethical governance practices. Through case studies and comparative analysis of auditing practices across OECD nations, this research provides insights into how strategic internal audits can be harnessed to reinforce public sector governance, thereby improving the delivery of public services. The paper argues that the integration of internal audit findings into decision-making processes enhances not only financial accountability but also policy outcomes, fostering greater public trust in government institutions. Key recommendations are presented on how public institutions can further integrate internal auditing processes to enhance governance outcomes, focusing on best practices for institutionalizing audit functions within public sector governance frameworks. These findings are particularly relevant for policymakers, audit professionals, and public administration leaders striving to achieve better governance, operational efficiency, and integrity in the public sector.

Keywords: internal auditing role, public administration sciences, public administration audit, internal auditing in universities

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Tolulope Aremu

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The key process steps to produce liquid detergent products will introduce potential defects, such as formulation, mixing, filling, and packaging, which might compromise product quality, consumer safety, and operational efficiency. Real-time identification and characterization of such defects are of prime importance for maintaining high standards and reducing waste and costs. Usually, defect detection is performed by human inspection or rule-based systems, which is very time-consuming, inconsistent, and error-prone. The present study overcomes these limitations in dealing with optimization in defect characterization within the process for making liquid detergents using Machine Learning algorithms. Performance testing of various machine learning models was carried out: Support Vector Machine, Decision Trees, Random Forest, and Convolutional Neural Network on defect detection and classification of those defects like wrong viscosity, color deviations, improper filling of a bottle, packaging anomalies. These algorithms have significantly benefited from a variety of optimization techniques, including hyperparameter tuning and ensemble learning, in order to greatly improve detection accuracy while minimizing false positives. Equipped with a rich dataset of defect types and production parameters consisting of more than 100,000 samples, our study further includes information from real-time sensor data, imaging technologies, and historic production records. The results are that optimized machine learning models significantly improve defect detection compared to traditional methods. Take, for instance, the CNNs, which run at 98% and 96% accuracy in detecting packaging anomaly detection and bottle filling inconsistency, respectively, by fine-tuning the model with real-time imaging data, through which there was a reduction in false positives of about 30%. The optimized SVM model on detecting formulation defects gave 94% in viscosity variation detection and color variation. These values of performance metrics correspond to a giant leap in defect detection accuracy compared to the usual 80% level achieved up to now by rule-based systems. Moreover, this optimization with models can hasten defect characterization, allowing for detection time to be below 15 seconds from an average of 3 minutes using manual inspections with real-time processing of data. With this, the reduction in time will be combined with a 25% reduction in production downtime because of proactive defect identification, which can save millions annually in recall and rework costs. Integrating real-time machine learning-driven monitoring drives predictive maintenance and corrective measures for a 20% improvement in overall production efficiency. Therefore, the optimization of machine learning algorithms in defect characterization optimum scalability and efficiency for liquid detergent companies gives improved operational performance to higher levels of product quality. In general, this method could be conducted in several industries within the Fast moving consumer Goods industry, which would lead to an improved quality control process.

Keywords: liquid detergent manufacturing, defect detection, machine learning, support vector machines, convolutional neural networks, defect characterization, predictive maintenance, quality control, fast-moving consumer goods

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Authors: Josef Brychta, Jiri Kratochvil, Marek Pagac

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The group of progressive cutting materials can include non-traditional, emerging and less-used materials that can be an efficient use of cutting their lead to a quantum leap in the field of machining. This is essentially a “superhard” materials (STM) based on polycrystalline diamond (PCD) and polycrystalline cubic boron nitride (PCBN) cutting performance ceramics and development is constantly "perfecting" fine coated cemented carbides. The latter cutting materials are broken down by two parameters, toughness and hardness. A variation of alloying elements is always possible to improve only one of each parameter. Reducing the size of the core on the other hand doing achieves "contradictory" properties, namely to increase both hardness and toughness.

Keywords: grained cutting materials difficult to machine materials, optimum utilization, mechanic, manufacturing

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Authors: Jeffrey Tzu-Hao Tsai, Yi-Shan Wong

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This article proposes a cohort-age-period (CAP) model to characterize multi-population mortality processes using cohort, age, and period variables. Distinct from the factor-based Lee-Carter-type decomposition mortality model, this approach is empirically based and includes the age, period, and cohort variables into the equation system. The model not only provides a fruitful intuition for explaining multivariate mortality change rates but also has a better performance in forecasting future patterns. Using the US and the UK mortality data and performing ten-year out-of-sample tests, our approach shows smaller mean square errors in both countries compared to the models in the literature.

Keywords: longevity risk, stochastic mortality model, multivariate mortality rate, risk management

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Authors: Hadi Farhadian, Homayoon Katibeh

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Groundwater inflow to the tunnels is one of the most important problems in tunneling operation. The objective of this study is the investigation of model dimension effects on tunnel inflow assessment in discontinuous rock masses using numerical modeling. In the numerical simulation, the model dimension has an important role in prediction of water inflow rate. When the model dimension is very small, due to low distance to the tunnel border, the model boundary conditions affect the estimated amount of groundwater flow into the tunnel and results show a very high inflow to tunnel. Hence, in this study, the two-dimensional universal distinct element code (UDEC) used and the impact of different model parameters, such as tunnel radius, joint spacing, horizontal and vertical model domain extent has been evaluated. Results show that the model domain extent is a function of the most significant parameters, which are tunnel radius and joint spacing.

Keywords: water inflow, tunnel, discontinues rock, numerical simulation

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Authors: Ranjit Singh

Abstract:

Body fat % lean body mass and body type play vital role in sports performance. A sports person who is having optional body composition can show its performance flawlessly whereas other who is not physical fit may be more prone to injury. Competitive swimming is an association of plethora of aspects like morphological, physiological, biochemical, biomechanical and psychological. The primary key of the present research is to examine the correlation among selected morphological dimensions such as height, weight, body fat%, lean body mass, somatotype and swimming performance. The present study also focused to investigate by potential deficiencies if any and to find out remedial measures to curb the training stresses. Thirty (age group 10-14 years) swimmers undergoing training under skilled and professional coaches were selected in the present study. The morphological variables and performance criterion like 50 meter swimming time and speed were calculated by using standard training methodology. Correlation coefficient among body composition, somatotype and performance variables were assessed by using standard statistical package SPSS. Mean height, weight, fat% and lean body mass of the present group is 150.97±8.68 cm, 44.0±9.34 kg., 15.97±4.42 % and 37.10±8.77 kg respectively. Somatotype of the young swimmers of this research is revealed ectomorphic mesomorph. The analysis of the results Illustrated that swimming performance is significantly correlated (p<0.05) with height, body weight, mesomorphoic component and lean body mass. Body fat is significantly and negatively correlated (p<0.05) with mesomorphic component, lean body mass and swimming speed. From this present study, it can be concluded that along with techniques and tactics other the physical attributes also play significant role in swimming performance which can help the swimmers to excel in higher level of competition and swimmers having improved morphological qualities can ultimately perform well.

Keywords: body fat, mass, mesomorphic component, somatotype

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Authors: Lojaine Okacha

Abstract:

In the past half-century, researchers started paying attention to enhancing the performance of urban spaces. Their idea of performance comprised urban climate performance, space synthesis, economic performance, and enhancing the quality of life in space. However, they all agreed that the key to achieving any of the previously mentioned development projects is good governance. Having good governance allows citizens to participate freely in the urbanization or development projects within cities. Consequently, using the city resources and assets as efficiently as possible, and ensures the fulfillment of the users’ needs and requests. This paper aims to propose an effective participation framework to help citizens have their voices heard and participate in the decisions that will affect their living situation. The framework allows governments to use their public resources to their best. However, this study focuses on public participation in third-world countries with unitary decentralized governance systems such as Egypt. It summarizes the challenges facing the participation practices, identifies the keys to a successful participation process, and draws on dominant effective participation practice lying on the relationship between the levels of participation, stakeholders participating, the urban development stages, the city-systems, and participation process. These components are integrated to create a real-world effective participation Framework. The results of the analysis were incredible and produced a functional and progressive approach for effective public participation to introduce to the governments. The model itself is combined with additional principles allowing the best practice to the process. The framework is finally compared with a real case of urban development.

Keywords: public participation, good governance, urban development, city systems

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Authors: Jasmina Pluncevic Gligoroska, Sanja Manchevska, Vaska Antevska, Lidija Todorovska, Beti Dejanova, Sunchica Petrovska, Ivanka Karagjozova, Elizabeta Sivevska

Abstract:

Introduction: Anthropometric measurements are integral part of regular medical examinations of athletes. In addition to the quantification of the size of the body, these measurements indicate the quality of the physical status, because of its association with sports performance. The purpose of this study was to examine whether there are differences in anthropometric parameters and body mass components in female athletes who participate in two different types of sports. Methods: A total of 27 athletes, 15 handball players and 12 basketball players, at the average age of 22.7 years (age span from 17 to 30 years) entered the study. Anthropometric method by Matiegka was used for determination of body components. Sixteen anthropometric measures were taken: height, weight, four diameters of joints, four circumferences of limbs and six skin folds. Results: Handball players were 169.6±6.7 cm tall and 63,75±7.5 kg heavy. Their average relative muscle mass (absolute mass in kg) was 51% (32.5kg), while bone component was 16.8% (10.7kg) and fat component was 14.3% (7.74kg). The basketball players were 177.4±8.2cm tall and 70.37±12.1kg heavy. Their average relative muscle mass (absolute mass in kg) was 51.9 % (36.6kg), bone component was 16.37% (11.5kg) and fat component was 15.36% (9.4kg). The comparison of anthropometric values showed that basketball players were statistically significantly higher and heavier than handball players (p<0.05). Statistically significant difference (p<0.05) was observed in the range of upper leg circumference (higher in basketball players) and the forearm skin fold (higher in the basketball players). Conclusion: Handball players and basketball players significantly differed in basic anthropometric measures (height and weight), but the body components had almost identical values. The anthropometric measurements that have been taken did not show significant difference between handball and basketball female players despite the different physical demands of the games.

Keywords: anthropometry, body components, basketball, handball female players

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Authors: E. Cenderelli, E. Bruno, G. Iacoviello, A. Lazzini

Abstract:

The financial sector is exposed to the risk of cyber-attacks like any other industrial sector. Furthermore, the topic of CybeRisk (cyber risk) has become particularly relevant given that Information Technology (IT) attacks have increased drastically in recent years, and cannot be stopped by single organizations requiring a response at international and national level. IT risk is never a matter purely for the IT manager, although he clearly plays a key role. A bank's risk management function requires a thorough understanding of the evolving risks as well as the tools and practical techniques available to address them. Upon the request of European and national legislation regarding CybeRisk in the financial system, banks are therefore called upon to strengthen the operational model for CybeRisk management. This will require an important change with a more intense collaboration with the structures that deal with information security for the development of an ad hoc system for the evaluation and control of this type of risk. The aim of the work is to propose a framework for the management and control of CybeRisk that will bridge the gap in the literature regarding the understanding and consideration of CybeRisk as an integral part of business management. The IT function has a strong relevance in the management of CybeRisk, which is perceived mainly as operational risk, but with a positive tendency on the part of risk management to the identification of CybeRisk assessment methods that are increasingly complete, quantitative and able to better describe the possible impacts on the business. The paper provides answers to the research questions: Is it possible to define a CybeRisk governance structure able to support the comparison between risk and security? How can the relationships between IT assets be integrated into a cyberisk assessment framework to guarantee a system of protection and risks control? From a methodological point of view, this research uses a case study approach. The choice of “Monte dei Paschi di Siena” was determined by the specific features of one of Italy’s biggest lenders. It is chosen to use an intensive research strategy: an in-depth study of reality. The case study methodology is an empirical approach to explore a complex and current phenomenon that develops over time. The use of cases has also the advantage of allowing the deepening of aspects concerning the "how" and "why" of contemporary events, on which the scholar has little control. The research bases on quantitative data and qualitative information obtained through semi-structured interviews of an open-ended nature and questionnaires to directors, members of the audit committee, risk, IT and compliance managers, and those responsible for internal audit function and anti-money laundering. The added value of the paper can be seen in the development of a framework based on a mapping of IT assets from which it is possible to identify their relationships for purposes of a more effective management and control of cyber risk.

Keywords: bank, CybeRisk, information technology, risk management

Procedia PDF Downloads 232