Search results for: indoor network performance

Authors: G. Arockiasamy, B. Sujeevan Kumar, Surendheran

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Human progress and development are highly influenced by the power of information access and technology. A global and multi-national transformation all over the word is possible due to digitalization. In the process of exchanging information, experience, and resources, there is a radical shift in who controls them. Mass media has turned the world into a global village by strengthening communication network. As a result, a new digital culture has emerged as a social network commonly known as new media. Today the advancement of technology is at the doorstep of everyone linking to anywhere. The traditional social restrictions are broken down by the new type of virtual communication modality that transcends people beyond boundaries At the same time media empire has invaded every nook and corner of the world through great expansion. Media activism is growing stronger and stronger but the truth and true meaning lost in the process. This paper explores the peoples’ attitude to media activism and tracing its direction. The methodology employed is random sampling survey and content analysis method. Both qualitatively and quantitatively measured. The findings tend to show 60 percent indicate media activism as positive and others indicate as negative. As a conclusion, media activism has danger within but depends on nature of the development of human orientation.

Keywords: media activism, media industry, program, truth information, orientation and nature

Procedia PDF Downloads 195

Authors: Robson C. Santos, David D. Oliveira, Matheus M. Reis, Gerson G. Cunha, Marcos A. C. Moreira

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The project demonstrates the construction of a solar power generation, integrated inverter equipment to a "Grid-Tie" by converting direct current generated by solar panels, into alternating current, the same parameters of frequency and voltage concessionaire distribution network. The energy generated is quantified by smart metering module that transmits the information in specified periods of time to a microcontroller via GSM modem. The modem provides the measured data on the internet, using networks and cellular antennas. The monitoring, fault detection and maintenance are performed by a supervisory station. Employed board types, best inverter selection and studies about control equipment and devices have been described. The article covers and explores the global trend of implementing smart distribution electrical energy networks and the incentive to use solar renewable energy. There is the possibility of the excess energy produced by the system be purchased by the local power utility. This project was implemented in residences in the rural community of the municipality of Cabo Frio/RJ. Data could be seen through daily measurements during the month of November 2013.

Keywords: rural residence, supervisory, smart grid, solar energy

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Authors: Sahil Kapahi

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A Formula SAE competition is characterized by typical track layouts having slaloms, tight corners and short straights, which favor a particular range of engine speed for a given set of gear ratios. Therefore, it is imperative that the power-train is optimized for the corresponding engine rpm band. This paper describes the process of designing, simulating and validating an air intake manifold for an inline four cylinder four-stroke internal combustion gasoline engine based on analysis of required vehicle performance. The requirements for the design of subject intake were set considering the rules of FSAE competitions and analysis of engine performance patterns for typical competition scenarios, carried out using OPTIMUMLAP software. Manifold geometry was optimized using results of air flow simulations performed on ANSYS CFX, and subsequent effect of this geometry on the engine was modeled using 1D simulation on Ricardo WAVE. A design was developed to meet the targeted performance standards in terms of engine torque output and volumetric efficiency. Finally, the intake manifold was manufactured and assembled onto the vehicle, and the engine output of the vehicle with the designed intake was studied using a dynamometer. The results of the dynamometer testing were then validated against predicted values derived from the Ricardo WAVE modeling and benefits to performance of the vehicle were established.

Keywords: 1 D Simulation, air flow simulation, ANSYS CFX, four-stroke engine, OPTIMUM LAP, Ricardo WAVE

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Authors: Yonatan Sverdlov, Shimon Ullman

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Artificial neural networks encounter a notable challenge known as continual learning, which involves acquiring knowledge of multiple tasks over an extended period. This challenge arises due to the tendency of previously learned weights to be adjusted to suit the objectives of new tasks, resulting in a phenomenon called catastrophic forgetting. Most approaches to this problem seek a balance between maximizing performance on the new tasks and minimizing the forgetting of previous tasks. In contrast, our approach attempts to maximize the performance of the new task, while ensuring zero forgetting. This is accomplished through the introduction of task-specific modulation parameters for each task, and only these parameters are learned for the new task, after a set of initial tasks have been learned. Through comprehensive experimental evaluations, our model demonstrates superior performance in acquiring and retaining novel tasks that pose difficulties for other multi-task models. This emphasizes the efficacy of our approach in preventing catastrophic forgetting while accommodating the acquisition of new tasks.

Keywords: continual learning, life-long learning, neural analogies, adaptive modulation

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled DNI field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: artificial neural networks, resilient propagation, solar radiation, time series forecasting

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Authors: Juliana Osman, David Gilbert, Caroline Tan

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Innovation capability is recognized as a critical factor that contributes to promoting firm growth and wealth creation. While studies on innovation are in abundance, few empirical studies have been undertaken to examine the relationships of intellectual capital with innovation capability, and research investigating the combinations of strategic orientation dimensions is limited and virtually nothing in regard to the Malaysian context. This research investigates the impact of intellectual capital and three strategic orientations on the innovation capability and firm performance of Malaysian ICT SMEs. Data was collected from 213 firms relating to intellectual capital and the three strategic orientations; market orientation, learning orientation and technology orientation. Using partial least squares structural equation modelling (PLS-SEM) to analyse the data, results indicate that while market orientation has a direct negative relationship to firm performance, it is positively related to performance through the mediating effect of innovation capability. Learning orientation and technology orientation are mediated by innovation capability, while intellectual capital was found to be partially mediated by innovation capability. Findings indicate that firm performance is positively and significantly related to innovation capability and that market orientation, learning orientation, technology orientation and intellectual capital are all significant and positively related to innovation capability. The developed model indicates that Malaysian ICT SMEs would perform better with greater emphasis on developing innovation capability through enhancement of intellectual capital and the strategic orientations measured in this study.

Keywords: innovation capability, intellectual capital, strategic orientations, PLS-SEM

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Mohammed Gamil Montasser, Angelo Battaglia

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Tourism is making its presence felt across the Sultanate of Oman. The story is one of the most recognized phenomena as a sustainable solid growth and is considered a remarkable outcome for any destination. The competitive situation and challenges within the tourism industry worldwide entail a better understanding of the destination position and its image to achieve Oman’s aspiration to retain its international reputation as one of the most desirable destinations in the Middle East. To access general perceptions of Oman’s attributes, their importance and their influences among U.S. tourists, an online survey was conducted with 522 American travelers who have traveled internationally, including non-visitors, virtual-visitors and visitors to Oman. This research involved a total of 36 attributes in the survey. Participants were asked to rate their agreement on how each attribute represented Oman and how important each attribute was for selecting destinations on 5- point Likert Scale. They also indicated if each attribute has a positive, neutral or negative influence on their destination selection. Descriptive statistics and importance performance analysis (IPA) were conducted. IPA illustrated U.S. tourists’ perceptions of Oman’s destination attributes and their importance in destination selection on a matrix with four quadrants, divided by actual mean value in each grid for importance (M=3.51) and performance (M=3.57). Oman tourism organizations and destination managers may use these research findings for future marketing and management efforts toward the U.S. travel market.

Keywords: analysis of importance, performance, destination attributes, Oman's position, U.S. tourists

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Authors: Boonrat Plangsorn

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Using ebooks can make not only a meaningful learning and achievement for students, but also can help teacher effectively enhance and improve their teaching. Nowadays, teachers try to develop ebooks for their class but it does not success in some cases because they do not have clear understanding on how to design, develop, and using ebooks that align with their teaching and learning objectives. Thus, the processes of using, designing, and producing ebooks have become one of important competency for teacher because it will enhance teacher’s knowledge for ebooks production. The purposes of this research were: (1) to develop the competency of producing and using ebooks of teachers in Chachengsao and (2) to promote the using ebooks of teachers in Chachengsao. The research procedures were divided into four phases. Phase I (study components and process of the designing and development of ebooks) was an interview in which the qualitative data were collected from five experts in instructional media. Phase II (develop teachers’ competency of producing ebooks) was a workshop for 28 teachers in Chachengsao. Phase III (study teachers’ using ebooks) was an interview in which the qualitative data were collected from seven teachers. Phase IV (study teachers’ using ebooks) was an interview in which the qualitative data were collected from six teachers. The research findings were as follows: 1. The components of ebooks comprised three components: ebooks structure, multimedia, and hyperlink. The eleven processes of design ebooks for education included (1) analyze the ebooks objective, (2) analyze learner characteristics, (3) set objective, (4) set learning content, (5) learner’s motivation, (6) design and construct activity, (7) design hyperlink, (8) produce script and storyboard, (9) confirm storyboard by expert, (10) develop ebooks, and (11) evaluate ebooks. 2. The evaluation of designing and development of ebooks for teacher workshop revealed the participants’ highest satisfaction (M = 4.65). 3. The teachers’ application of ebooks were found that obstacles of producing an ebooks: Time period of producing ebooks, a readiness of school resources, and small teacher network of producing and using ebooks. The result of using ebooks was students’ motivation. 4. The teachers’ ebooks utilization through educational research network of teacher in Chachengsao revealed that the characteristic of ebooks consist of picture, multimedia, voice, music, video, and hyperlink. The application of ebooks caused students interested in the contents; enjoy learning, and enthusiastic learning.

Keywords: ebooks, producing ebooks competency, using ebooks competency, educational research network

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Authors: Hamid Reza Behnood, Esmaeel Ayati, Tom Brijs, Mohammadali Pirayesh Neghab

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Investment projects in road safety planning can benefit from an effectiveness evaluation regarding their expected safety outcomes. The objective of this study is to develop a decision support system (DSS) to support policymakers in taking the right choice in road safety planning based on the efficiency of previously implemented safety measures in a set of regions in Iran. The measures considered for each region in the study include performance indicators about (1) police operations, (2) treated black spots, (3) freeway and highway facility supplies, (4) speed control cameras, (5) emergency medical services, and (6) road lighting projects. To this end, inefficiency measure is calculated, defined by the proportion of fatality rates in relation to the combined measure of road safety performance indicators (i.e., road safety measures) which should be minimized. The relative inefficiency for each region is modeled by the Data Envelopment Analysis (DEA) technique. In a next step, a fuzzy decision-making system is constructed to convert the information obtained from the DEA analysis into a rule-based system that can be used by policy makers to evaluate the expected outcomes of certain alternative investment strategies in road safety.

Keywords: performance indicators, road safety, decision support system, data envelopment analysis, fuzzy reasoning

Procedia PDF Downloads 331

Authors: Zhaoqi He

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Research Context: Endurance performance in hot environments is influenced by the interplay of hydration status and physiological responses. This study aims to investigate how dehydration, up to 2.11% body weight loss, affects the 3 km running performance of trained male athletes under conditions mimicking high temperatures. Methodology: In a randomized crossover design, five male athletes participated in two trials – euhydrated (EU) and dehydrated (HYPO). Both trials included a 70-minute preload run at 55-60% VO2max in 32°C and 50% humidity, followed by a 3-kilometer time trial. Fluid intake was restricted in HYPO to induce a 2.11% body weight loss. Physiological metrics, including heart rate, core temperature, and oxygen uptake, were measured, along with perceptual metrics like perceived exertion and thirst sensation. Findings: The 3-kilometer run completion times showed no significant differences between EU and HYPO trials (p=0.944). Physiological indicators, including heart rate, core temperature, and oxygen uptake, did not significantly vary (p>0.05). Thirst sensation was markedly higher in HYPO (p=0.013), confirming successful induction of dehydration. Other perceptual metrics and gastrointestinal comfort remained consistent. Conclusion: Contrary to the hypothesis, the study reveals that dehydration, inducing up to 2.11% body weight loss, does not significantly impair 3 km running performance in trained male athletes under hot conditions. Thirst sensation was notably higher in the dehydrated state, emphasizing the importance of considering perceptual factors in hydration strategies. The findings suggest that trained runners can maintain performance despite moderate dehydration, highlighting the need for nuanced hydration guidelines in hot-weather running.

Keywords: hypohydration, euhydration, hot environment, 3km running time trial, endurance performance, trained athletes, perceptual metrics, dehydration impact, physiological responses, hydration strategies

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: T. P. Singh, Vijay Gautam

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Gladiolus is an important cash crop and is grown mainly for its elegant spikes. Traditionally the gladiolus corms are planted manually which is very tedious, time consuming and labor intensive operation. So far, there is no planter available for planting of gladiolus corms. With a view to mechanize the planting operation of this horticultural crop, a prototype of 4-row gladiolus planter was developed and its performance was evaluated in-situ condition. Cup-chain type metering device was used to singulate the gladiolus corms while planting. Three levels of corm spacing viz 15, 20 and 25 cm and four levels of forward speed viz 1.0, 1.5, 2.0 and 2.5 km/h was taken as evaluation parameter for the planter. The performance indicators namely corm spacing in each row, coefficient of uniformity, missing index, multiple index, quality of feed index, number of corms per meter length, mechanical damage to the corms etc. were determined during the field test. The data was statistically analyzed using Completely Randomized Design (CRD) for testing the significance of the parameters. The result indicated that planter was able to drop the corms at required nominal spacing with minor variations. The highest deviation from the mean corm spacing was observed as 3.53 cm with maximum coefficient of variation as 13.88%. The highest missing and quality of feed indexes were observed as 6.33% and 97.45% respectively with no multiples. The performance of the planter was observed better at lower forward speed and wider corm spacing. The field capacity of the planter was found as 0.103 ha/h with an observed field efficiency of 76.57%.

Keywords: coefficient of uniformity, corm spacing, gladiolus planter, mechanization

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Authors: Pouya Taraghi, Yong Li, Nader Yoosef-Ghodsi, Muntaseer Kainat, Samer Adeeb

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Buried pipelines play a crucial role in the transportation of energy products such as oil, gas, and various chemical fluids, ensuring their efficient and safe distribution. However, these pipelines are often susceptible to ground movements caused by geohazards like landslides, fault movements, lateral spreading, and more. Such ground movements can lead to strain-induced failures in pipes, resulting in leaks or explosions, leading to fires, financial losses, environmental contamination, and even loss of human life. Therefore, it is essential to study how buried pipelines respond when traversing geohazard-prone areas to assess the potential impact of ground movement on pipeline design. As such, this study introduces an approach called the Physics-Informed Neural Network (PINN) to predict the strain demand in inelastic pipes subjected to permanent ground displacement (PGD). This method uses a deep learning framework that does not require training data and makes it feasible to consider more realistic assumptions regarding existing nonlinearities. It leverages the underlying physics described by differential equations to approximate the solution. The study analyzes various scenarios involving different geohazard types, PGD values, and crossing angles, comparing the predictions with results obtained from finite element methods. The findings demonstrate a good agreement between the results of the proposed method and the finite element method, highlighting its potential as a simulation-free, data-free, and meshless alternative. This study paves the way for further advancements, such as the simulation-free reliability assessment of pipes subjected to PGD, as part of ongoing research that leverages the proposed method.

Keywords: strain demand, inelastic pipe, permanent ground displacement, machine learning, physics-informed neural network

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Authors: Hillary Jo Muyalde

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Introduction: Elite athletes train regularly to enhance their physical endurance, but sometimes, training sessions are not enough. When competition comes, these athletes struggle to find focus. Mental imagery is a psychological technique that helps condition the mind to focus and eventually help improve performance. This study aims to help elite competitive swimmers of the University of the East improve their performance with Mental Imagery as an auxiliary tool. Methodology: The study design used was quasi-experimental with a purposive sampling technique and a within-subject design. It was conducted with a total of 41 participants. The participants were given a Sport Imagery Ability Questionnaire (SIAQ) to measure imagery ability and the Mental Imagery Program. The study utilized a Paired T-test for data analysis where the participants underwent six weeks of no mental imagery training and were compared to six weeks with the Mental Imagery Program (MIP). The researcher recorded the personal best time of participants in their respective specialty stroke. Results: The results of the study showed a t-value of 17.804 for Butterfly stroke events, 9.922 for Backstroke events, 7.787 for Breaststroke events, and 17.440 in Freestyle. This indicated that MIP had a positive effect on participants’ performance. The SIAQ result also showed a big difference where -10.443 for Butterfly events, -5.363 for Backstroke, -7.244 for Breaststroke events, and -10.727 for Freestyle events, which meant the participants were able to image better than before MIP. Conclusion: In conclusion, the findings of this study showed that there is indeed an improvement in the performance of the participants after the application of the Mental Imagery Program. It is recommended from this study that the participants continue to use mental imagery as an auxiliary tool to their training regimen for continuous positive results.

Keywords: mental Imagery, personal best time, SIAQ, specialty stroke

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Authors: Tori Reddy Dodla, Laura Ann Jones

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The objective of this study was to propose strategies to improve the efficiency of Knowledge Management Systems (KMS). This study highlights best practices from various industries to create an overall summary of Knowledge Management (KM) and efficiency in organizational performance. Results indicated eleven best practices for maximizing the efficiency of organizational KMS that can be divided into four categories: Designing the KMS, Identifying Case Studies, Implementing the KMS, and Promoting adoption and usage. Our findings can be used as a foundation for scholars to conduct further research on KMS efficiency.

Keywords: artificial intelligence, knowledge management efficiency, knowledge management systems, organizational performance

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Authors: Rui Fonseca-Pinto, Emanuel Silva, Rui Rijo, Ricardo Martinho, Bruno Carreira

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The sedentary lifestyle is associated to the development of chronic noncommunicable diseases (obesity, hypertension, Diabetes Mellitus Type 2) and the World Health Organization, given the evidence that physical activity is determinant for individual and collective health, defined the Physical Activity Level (PAL) as a vital signal. Strategies for increasing the practice of physical activity in all age groups have emerged from the various social organizations (municipalities, universities, health organizations, companies, social groups) by increasingly developing innovative strategies to promote motivation strategies and conditions to the practice of physical activity. The adaptation of cities to the new paradigms of sustainable mobility has provided the adaptation of urban training circles and mobilized citizens to combat sedentarism. This adaptation has accompanied the technological evolution and makes possible the use of mobile technology to monitor outdoor training programs and also, through the network connection (IoT), use the training data to make personalized recommendations. This work presents a physical activity counseling platform to be used in the physical maintenance circuits of urban centers, the MOVIDA.polis. The platform consists of a back office for the management of circuits and training stations, and for a mobile application for monitoring the user performance during workouts. Using a QRcode, each training station is recognized by the App and based on the individual performance records (effort perception, heart rate variation) artificial intelligence algorithms are used to make a new personalized recommendation. The results presented in this work were obtained during the proof of concept phase, which was carried out in the PolisLeiria training circuit in the city of Leiria (Portugal). It was possible to verify the increase in adherence to the practice of physical activity, as well as to decrease the interval between training days. Moreover, the AI-based recommendation acts as a partner in the training and an additional challenging factor. The platform is ready to be used by other municipalities in order to reduce the levels of sedentarism and approach the weekly goal of 150 minutes of moderate physical activity. Acknowledgments: This work was supported by Fundação para a Ciência e Tecnologia FCT- Portugal and CENTRO2020 under the scope of MOVIDA project: 02/SAICT/2016 – 23878.

Keywords: physical activity, mHealth, urban training circuits, health promotion

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Authors: B. O. Diyaolu

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The web created by sport in academics has made it difficult for it to be separated from adolescent educational development. The enthusiasm expressed towards sport by students in higher institutions is quite enormous. Primarily, academic performance should be the pride of all students but whether sports affect the academic performance of student-athletes remain an unknown fact. This study investigated the influence of sports participation on academic performance among Afe Babalola University student-athletes. Ex post facto research design was used. Two groups of students were used for the study; Student-athlete (SA) and Regular Students (RS). Purposive sampling technique was used to select 224 student-athletes, only those that are regular in the university sports team training were considered and their records (i.e. name, department, level, matriculation number, and phone number) were collected through the assistance of their coaches. For the regular students, purposive sampling technique was used to select 224 participants, only those that have no interest in sports were considered and their records were retrieved from the college registration officer. The first and second semester examination results of the two groups were compared in 10 general study courses without their knowledge, using descriptive statistics of frequency counts, mean, and standard deviation. Out of the 10 compared courses, 7 courses result showed no significant difference between students-athlete and regular students while student-athletes perform better in 3 practically oriented courses. Sports role in academics is quite significant. Exposure to sports can help build the confidence that athletes need especially when it comes to practical courses. Student-athletes can perform better in academics if the environment is friendly and not intimidating. Lecturers and coaches need to work together in order to build a well cultured and intelligent graduate.

Keywords: academic performance, regular students, sports participation, student-athlete, university sports team

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Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

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Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: construction safety, contractor selection, decision support system, relational database

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Avinash Kharel

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Background: - Linear sprint training is one possible approach to developing sprint performance, a crucial skill to focus on in soccer. Numerous methods, including various on-field training options, can be employed to attain this goal. However, the effect of In-season linear sprint training on sprint performance and related kinetics changes are unknown in a professional setting. The study aimed to investigate the effect of in-season linear sprint training on the sprint kinematics of amateur soccer players. Methods: - After familiarization, a 4-week training protocol was completed with sprint performance and Force Velocity (FV) profiles was compared before and after the training. Eighteen amateur soccer male players (Age 22 ± 2 years: Height: 178 ± 7cm; body-mass: 74 ± 8 Kg, 30-m split-time: 4.398 ± s) participated in the study. Sprint kinematics variables, including maximum Sprint Velocity (V0), Theoretical Maximum Force (F0), Maximum Force Output per kilogram of body weight (N/KG), Maximum Velocity (V(0)), Maximum Power Output (P MAX (W)), Ratio of Force to Velocity (FV), and Ratio of Force to Velocity at Peak power were measured. Results: - Results showed significant improvements in Maximum Sprint Velocity (p<0.01, ES=0.89), Theoretical Maximum Force (p<0.05, ES=0.50), Maximum Force Output per kilogram of body weight (p<0.05, ES=0.42), Maximum Power Output (p<0.05, ES=0.52), and Ratio of Force to Velocity at Peak Power (RF PEAK) (p<0.05, ES=0.44) post-training. There were no significant changes in the ratio of Force to Velocity (FV) and Maximum Velocity V (0) post-training (p>0.05). Conclusion: - These findings suggest that In-season linear sprint training can effectively improve certain sprint kinematics variables in amateur soccer players. Coaches and players should consider incorporating linear sprint training into their in-season training programs to improve sprint performance.

Keywords: sprint performance, training intervention, soccer, kinematics

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Authors: Christo Nicholls

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The National Electricity Grid (NEG) in South Africa has been under strain for the last five years. This overburden of the NEG led Eskom (the State-Owned Entity responsible for the NEG) to implement a blunt methodology to assist them in reducing the maximum demand (MD) on the NEG, when required, called Loadshedding. The challenge of this methodology is that not only does it lead to immense technical issues with the distribution network equipment, e.g., transformers, due to the frequent abrupt off and on switching, it also has a broader negative fiscal impact on the distributors, as their key consumers (commercial & industrial) are now grid defecting due to the lack of Electricity Security Provision (ESP). This paper provides a pragmatic alternative methodology utilizing specific functionalities embedded within direct-connect single and three-phase Advanced Meter Infrastructure (AMI) Solutions deployed within the distribution network, in conjunction with a Multi-Agent Systems Based AI implementation focused on Automated Negotiation Peer-2-Peer trading. The results of this research clearly illustrate, not only does methodology provide a factual percentage contribution towards the NEG MD at the point of consideration, it also allows the distributor to leverage the real-time MD data from key consumers to activate complex, yet impact-measurable Demand Response (DR) programs.

Keywords: AI, AMI, demand response, multi-agent

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Authors: Raquel Camprubí

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Cultural tourism has been postulated as relevant motivation for tourist over the world during the last decades. In this context, museums are the main attraction for cultural tourists who are seeking to connect with the history and culture of the visited place. From the point of view of an urban destination, museums and other cultural resources are essential to have a strong tourist supply at the destination, in order to be capable of catching attention and interest of cultural tourists. In particular, museums’ challenge is to be prepared to offer the best experience to their visitors without to forget their mission-based mainly on protection of its collection and other social goals. Thus, museums individually want to be competitive and have good positioning to achieve their strategic goals. The life cycle of the destination and the level of maturity of its tourism product influence the need of tourism agents to cooperate and collaborate among them, in order to rejuvenate their product and become more competitive as a destination. Additionally, prior studies have considered an approach of different models of a public and private partnership, and collaborative and cooperative relations developed among the agents of a tourism destination. However, there are no studies that pay special attention to museums and the strategic alliances developed to obtain mutual benefits. Considering this background, the purpose of this study is to analyze in what extent museums of a given urban destination have established strategic links and relations among them, in order to improve their competitive position at both individual and destination level. In order to achieve the aim of this study, the city of Girona (Spain) and the museums located in this city are taken as a case study. Data collection was conducted using in-depth interviews, in order to collect all the qualitative data related to nature, strengthen and purpose of the relational ties established among the museums of the city or other relevant tourism agents of the city. To conduct data analysis, a Social Network Analysis (SNA) approach was taken using UCINET software. Position of the agents in the network and structure of the network was analyzed, and qualitative data from interviews were used to interpret SNA results. Finding reveals the existence of strong ties among some of the museums of the city, particularly to create and promote joint products. Nevertheless, there were detected outsiders who have an individual strategy, without collaboration and cooperation with other museums or agents of the city. Results also show that some relational ties have an institutional origin, while others are the result of a long process of cooperation with common projects. Conclusions put in evidence that collaboration and cooperation of museums had been positive to increase the attractiveness of the museum and the city as a cultural destination. Future research and managerial implications are also mentioned.

Keywords: cultural tourism, competitiveness, museums, Social Network analysis

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Authors: Rasheed Owolabi Oloyede, Joseph Olusegun Adelusi, Seun Oluwadare

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Sleep has been found to have many recuperative and restorative beneficial effects on athletic recovery. When a person is deprived of sleep this can have many effects on their immune and endocrine systems. Both of these systems are extremely important for the recovery process of any athlete and when we deprive ourselves of sleep, we are depriving ourselves of recovery. This study examined how sleep deprivation can hinder sport performance among selected athletes representing Adeyemi College of Education at Nigeria Colleges of Education Games (NICEGA) competitions at Minna. A total of 32 athletes were sampled for the study. They were exposed to two different activities. Each activity was performed before and after sleep deprivation, the activities were 100m dash, shuttle relay. The athletes were randomly assigned to two groups that are experimental and control groups. Pretest were conducted on both groups before apply treatment to the other group. A day before the activities to be performed the control group was denied of sleep between 10p.m to 5a.m for a period of 6 weeks. The analysis of the data showed that athletes performance in the two selected activities performed on equal basis before the sleep deprivation. After sleep deprivation the performance of experimental group was a little better than the control group that were denied of sleep. It was concluded that sleep allows the body to spend less energy resources on body processes needed while awake, it was concluded that sleep deprivation enables the body system work effectively. The body can expend needed energy, balance and adequate reaction time if it is allowed to have enough rest. Lack of adequate sleep results to dullness of the brain, nervousness and anxiety which all have negative effect on performance of activities by athletes. Based on the findings, it was recommended that extend nightly sleep for several week to reduce your sleep debt before competition. Maintain a low sleep debt by obtaining a sufficient amount of nightly sleep (seven to eight hours for adults, nine or more hours for teens and young adults). Keep a regular sleep-wake schedule, going to bed and waking up at the same times every day.

Keywords: activities, deprivation, performance, sleep

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Authors: Jonida Canaj

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A simple method of extraction and determination of fifteen priority polycyclic aromatic hydrocarbons (PAHs) from drinking water using high performance liquid chromatography (HPLC) has been validated with limits of detection (LOD) and limits of quantification (LOQ), method recovery and reproducibility, and other factors. HPLC parameters, such as mobile phase composition and flow standardized for determination of PAHs using fluorescent detector (FLD). PAH was carried out by liquid-liquid extraction using dichloromethane. Linearity of calibration curves was good for all PAH (R², 0.9954-1.0000) in the concentration range 0.1-100 ppb. Analysis of standard spiked water samples resulted in good recoveries between 78.5-150%(0.1ppb) and 93.04-137.47% (10ppb). The estimated LOD and LOQ ranged between 0.0018-0.98 ppb. The method described has been used for determination of the fifteen PAHs contents in drinking water samples.

Keywords: high performance liquid chromatography, HPLC, method validation, polycyclic aromatic hydrocarbons, PAHs, water

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Authors: Meng Xu, Alexis K. H. Lau, Ming Xu, Bill Barron, Narges Shahraki

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As an emerging unconventional energy, shale gas has been an economically viable step towards a cleaner energy future in U.S. China also has shale resources that are estimated to be potentially the largest in the world. In addition, China has enormous unmet for a clean alternative to substitute coal. Nonetheless, the geological complexity of China’s shale basins and issues of water scarcity potentially impose serious constraints on shale gas development in China. Further, even if China could replicate to a significant degree the U.S. shale gas boom, China faces the problem of transporting the gas efficiently overland with its limited pipeline network throughput capacity and coverage. The aim of this study is to identify the potential bottlenecks in China’s gas transmission network, as well as to examine the shale gas development affecting particular supply locations and demand centers. We examine this through application of three scenarios with projecting domestic shale gas supply by 2020: optimistic, medium and conservative shale gas supply, taking references from the International Energy Agency’s (IEA’s) projections and China’s shale gas development plans. Separately we project the gas demand at provincial level, since shale gas will have more significant impact regionally than nationally. To quantitatively assess each shale gas development scenario, we formulated a gas pipeline optimization model. We used ArcGIS to generate the connectivity parameters and pipeline segment length. Other parameters are collected from provincial “twelfth-five year” plans and “China Oil and Gas Pipeline Atlas”. The multi-objective optimization model uses GAMs and Matlab. It aims to minimize the demands that are unable to be met, while simultaneously seeking to minimize total gas supply and transmission costs. The results indicate that, even if the primary objective is to meet the projected gas demand rather than cost minimization, there’s a shortfall of 9% in meeting total demand under the medium scenario. Comparing the results between the optimistic and medium supply of shale gas scenarios, almost half of the shale gas produced in Sichuan province and Chongqing won’t be able to be transmitted out by pipeline. On the demand side, the Henan province and Shanghai gas demand gap could be filled as much as 82% and 39% respectively, with increased shale gas supply. To conclude, the pipeline network in China is currently not sufficient in meeting the projected natural gas demand in 2020 under medium and optimistic scenarios, indicating the need for substantial pipeline capacity expansion for some of the existing network, and the importance of constructing new pipelines from particular supply to demand sites. If the pipeline constraint is overcame, Beijing, Shanghai, Jiangsu and Henan’s gas demand gap could potentially be filled, and China could thereby reduce almost 25% its dependency on LNG imports under the optimistic scenario.

Keywords: energy policy, energy systematic analysis, scenario analysis, shale gas in China

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Authors: Nurullah Ekmekci, Omer Akkaya, Vural Cagliyan

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Increased use of the Internet has resulted in the emergence of a new retail types called online shopping or electronic retail (e-retail). The rapid growth of the Internet has enabled customers to search information about the product and buy these products or services from e-retailers. Although this new form of shopping has grown in a remarkable way because of offering easiness to people, it is not an easy task to capture the success by distinguishing from competitors in this environment which millions of players takes place. For the success, e-retailers should determine the factors which the customers take notice while they are buying from e-retailers. This paper aims to identify the factors that provide preferability for the online shopping websites and the importance levels of these factors. These main criteria which have taken notice are Customer Service Performance (CSP), Website Performance (WSP), Criteria Related to Product (CRP), Ease of Payment (EP), Security/Privacy (SP), Ease of Return (ER), Delivery Service Performance (DSP) and Order Fulfillment Performance (OFP). It has benefited from Analytic Hierarchy Process to determine the priority of the criteria. Based on analysis, Security/Privacy (SP) criteria seems to be most important criterion with 22 % weight. Companies should attach importance to the security and privacy for making their online website more preferable among the online shoppers.

Keywords: AHP (analytical hierarchy process), multi-criteria decision making, online shopping, shopping

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Authors: Siti Khadijah Che Osmi, Syed Mohd Ahmad

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This paper presents a methodology to develop fragility curves for shallow tunnels so as to describe a relationship between seismic hazard and tunnel vulnerability. Emphasis is given to the influence of surrounding soil material properties because the dynamic behaviour of the tunnel mostly depends on it. Four ground properties of soils ranging from stiff to soft soils are selected. A 3D nonlinear time history analysis is used to evaluate the seismic response of the tunnel when subjected to five real earthquake ground intensities. The derived curves show the future probabilistic performance of the tunnels based on the predicted level of damage states corresponding to the peak ground acceleration. A comparison of the obtained results with the previous literature is provided to validate the reliability of the proposed fragility curves. Results show the significant role of soil properties and input motions in evaluating the seismic performance and response of shallow tunnels.

Keywords: fragility analysis, seismic performance, tunnel lining, vulnerability

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Authors: Trang Pham

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Approximately 70% of the Vietnamese population lives in rural areas where the main livelihood is farming. For many years, the Vietnamese Government has been working towards improving farmers’ quality of life. In 2008, the Government issued the decree 115/2008/ND-CP to subsidize farmers’ water fees. The subsidy covers operation and management costs of major water infrastructure. Water users have only to pay for the operation and management of minor or tertiary canal systems. But the “subsidized water fee” has become contentious; there are two opposing schools of thought. One view is that the subsidy lessens the burden on farmers in terms of reducing their production costs, at the same time generating a sufficient budget for Irrigation Management Companies (IMCs) and Water User Association (WUAs). The alternate point of view is that the subsidy negatively effects irrigation performance, especially in tertiary canals. The aim of this study was to gain clear awareness of the perceptions of farmers, WUA members, and IMC staffs in regard to irrigation performance and management since the introduction of subsidies and local water fees. In order to find out how the government intervention has affected local farming communities, a series of questionnaires and interviews were administered in 2013. Four case studies were chosen which represent four different agricultural areas and four different irrigation systems in Vietnam. Interviews were conducted with IMC staffs and WUA members and questionnaires were used to gather information from farmers. The study compares the difference in operation and management costs across the four case studies both before and after the implementation of the decree. The results disclose factors behind the subsidized water fee that either allow or hinder improved irrigation performance and better irrigation management.

Keywords: water fee, irrigation performance, local farming, tertiary canal systems

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Authors: Rym Ghariani, Younes Boujelbene

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This study aimed to examine the impact of digitalization and supply chain integration on the financial performance of companies in the agro-industrial sector in Tunisia, highlighting the growing importance of digital technologies in modern economies. The results were analyzed using a questionnaire and using principal component analysis, as well as linear regression modeling with SPSS26. The results demonstrate that the digitalization and integration of the supply chain have a significant impact on the financial results of Tunisian agro-industrial companies. In theory, this study provides a better understanding of the effects of digital advancements and supply chain strategies on financial results in this specific area. This study, therefore, studies the relationship between these variables and financial efficiency, highlighting the significant impacts of these technological and strategic elements on the financial results of agro-industrial companies in Tunisia.

Keywords: digitalization, supply chain integration, financial performance, Tunisian agro-industrial sector

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