Search results for: logistic performance

Authors: Sagir Abubakar

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Organization must move along with the employees, because organization should adapt itself to the changing environment. The paper examines the effect of training and development on employee performance. Training and development has an important role in improve the performance, skills and attitude of employee in an organization. Training and development will also help an employee to do his present job or to prepare him for a higher position with increased responsibilities. The paper analyses the employee performance towards training and development conducted in some selected banks within Bauchi metropolis. Review of related literature was done on, training, training objectives, methods and development and its method. A census survey was carried out using staff of GTB and Skye Banks Bauchi branch where a total of 40 questionnaires were administered personally by the researcher and there were 100% responses. Correlation analysis was adopted for the analysis of data collected. The study concludes that 95% of respondents agreed that training and development are vital for both employee and organizations performance. They also suggest that training and development should be made compulsory for all categories of employee in an organization. Training and Development programmes are necessary in any organization for improving the quality of work of the employee.

Keywords: training, development, employee, performance, banks

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Authors: Ahmed BenSaïda

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This paper investigates the association between financial technology (FinTech) growth and bank performance in the Gulf Cooperation Council (GCC) region. Application is conducted on a panel dataset containing the annual observations of banks covering the period from 2012 to 2021. FinTech growth is set as an explanatory variable on three proxies of bank performance. These proxies are the return on assets (ROA), return on equity (ROE), and net interest margin (NIM). Moreover, several control variables are added to the model, including bank-specific and macroeconomic variables. The results are significant as all the proxies of the bank performance are negatively affected by the growth of FinTech startups. Consequently, banks are urged to proactively invest in FinTech startups and engage in partnerships to avoid the risk of disruption.

Keywords: financial technology, bank performance, GCC countries, panel regression

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Authors: Sung-yong Choi, Woo-tai Jung, Young-hwan Park

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This study intends to improve the bond performance of the polypropylene fiber used as reinforcing fiber for concrete by changing its shape into double crimped type through the enhancement its fabrication process. The bond performance of such double crimped fiber is evaluated by applying the JCI SF-8 (dog-bone shape) testing method. The test results reveal that the double crimped fiber develops bond performance improved by more than 19% compared to the conventional crimped type fiber.

Keywords: Bond, Polypropylene, fiber reinforcement, macro fiber, shape change

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Authors: Hala Shaari, Nuredin Ahmed

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Teaching computer programming is recognized to be difficult and a real challenge. The biggest problem faced by novice programmers is their lack of understanding of basic programming concepts. A visualized learning tool was developed and used by volunteered first-year students for two semesters. The purposes of this paper are firstly, to emphasize factors which directly affect the performance of our students negatively. Secondly, to examine whether the proposed tool would improve their performance and learning progression. The results of adopting this tool were conducted using a pre-survey and post-survey questionnaire. As a result, students who used the learning tool showed better performance in their programming subject.

Keywords: factors, novice, programming, visualization

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Authors: Sungwon Jung

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The percentage of 20 years or older apartment houses in South Korea is approximately 20% (1.55 million houses), and the explosive increase of aged houses is expected around the first planned new towns. Accordingly, we should prepare for social issues such as difficulty of housing lease and degradation of housing performance. The improvement of performance of aged houses is essential for achieving the national energy and carbon reduction goals, and we should develop techniques to respond to the changing construction environment. Furthermore, we should develop a performance evaluation system that is appropriate for the demands of residents such as the improvement of remodeling floor plan by performance improvement in line with the residence type of the housing vulnerable groups such as low-income group and elderly people living alone. For this purpose, remodeling techniques and business models optimized for the target complexes must be spread through the development of various business models. In addition, it is necessary to improve the remodeling business by improving the laws and systems related to the improvement of the residential performance and to prepare techniques to respond to the increasing business demands. In other words, performance improvement and evaluation and knowledge systems need to be researched as new issues related to remodeling that has not been addressed in the existing research.

Keywords: remodelling, performance evaluation, web-based system, big data

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Authors: Pin-Ju Juan, Peng-Yu Juan, Yi-Shan Chen

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The main purpose of this paper is to present a fuzzy Analytic Network Process (ANP) model for the hostel organizational performance selection. In this article, we created 39 criteria for selecting hostel organizational performance acquired from literature's review and experts method practical investigations, and the methods of fuzzy analytic network process are used to consolidate decision-makers’ assessments about criteria weightings. Finally, we selected organizational performance of a hostel in Taiwan to determine the effectiveness of the proposed evaluation model in this paper.

Keywords: Fuzzy ANP, hostel, organizational performance, strategy management

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Authors: Zachary Pan

Abstract:

Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Taknaz Banihashemi, Jiangang Fei, Peggy Shu-Ling Chen

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Reverse logistics (RL) is a part of the logistics of companies and its aim is to reclaim value from the returned products in an environmentally friendly manner. In recent years, RL has attracted significant attention among both practitioners and academics due to environmental directives and governmental legislation, consumer concerns and social responsibilities for environment, awareness of the limits of natural resources and economic potential. Sustainability development is considered as a critical goal for organisations due to its impact on competitive advantage. With growing environmental concerns and legal regulations related to green and sustainability issues, product disposition through RL can be considered as an environmental, economic and social sound way to achieve sustainable development. When employed properly, RL can help firms to improve their sustainability performance. The aim of this paper is to investigate the sustainability issues in the context of RL in the perspective of the triple-bottom-line approach. Content analysis was used to collect the information. The findings show that there is a research gap to investigate the relationship between RL and sustainability performance. Most of the studies have focused on performance evaluation of RL by considering the factors related to economic and environmental performance. RL can have significant effects on social issues along with economic and environmental issues. The inclusion of the social aspect in the sustainability performance will provide a complete and holistic picture of how RL may impact on the sustainability performance of firms. Generally, there is a lack of research on investigating the relationship between RL and sustainability by integrating the three pillars of triple-bottom-line sustainability performance. This paper provides academics and researchers a broad view of the correlations between RL and sustainability performance.

Keywords: verse Logistics, review, sustainability, sustainability performance

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Authors: Jianyang Zhu, Lin Jiang, Tixian Tian

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Inspired by the increasing interesting on the wind power associated with production of clear electric power, a numerical experiment is applied to investigate the aerodynamic performance of straight type vertical axis wind turbine with different thickness and solidity, where the incompressible Navier-Stokes (N-S) equations coupled with dynamic mesh technique is solved. By analyzing the flow field, as well as energy coefficient of different thickness and solidity turbine, it is found that the thickness and solidity can significantly influence the performance of vertical axis wind turbine. For the turbine under low tip speed, the mean energy coefficient increase with the increasing of thickness and solidity, which may improve the self starting performance of the turbine. However for the turbine under high tip speed, the appropriate thickness and smaller solidity turbine possesses better performance. In addition, delay stall and no interaction of the blade and previous separated vortex are observed around appropriate thickness and solidity turbine, therefore lead better performance characteristics.

Keywords: vertical axis wind turbine, N-S equations, dynamic mesh technique, thickness, solidity

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Authors: Yibeltal T. Bayou, Yohana S. Mashalla, Gloria Thupayagale-Tshweneagae

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Background: According to the World Health Organization, caesarean section delivery rates of more than 10-15% caesarean section deliveries in any specific geographic region in the world are not justifiable. The aim of the study was to describe the level and analyse determinants of caesarean section delivery in Addis Ababa. Methods: Data was collected in Addis Ababa using a structured questionnaire administered to 901 women aged 15-49 years through a stratified two-stage cluster sampling technique. Binary logistic regression model was employed to identify predictors of caesarean section delivery. Results: Among the 835 women who delivered their last birth at healthcare facilities, 19.2% of them gave birth by caesarean section. About 9.0% of the caesarean section births were due to mother’s request or service provider’s influence without any medical indication. The caesarean section delivery rate was much higher than the recommended rate particularly among the non-slum residents (27.2%); clients of private healthcare facilities (41.1%); currently married women (20.6%); women with secondary (22.2%) and tertiary (33.6%) level of education; and women belonging to the highest wealth quintile household (28.2%). The majority (65.8%) of the caesarean section clients were not informed about the consequences of caesarean section delivery by service providers. The logistic regression model shows that older age (30-49), secondary and above education, non-slum residence, high-risk pregnancy and receiving adequate antenatal care were significantly positively associated with caesarean section delivery. Conclusion: Despite the unreserved effort towards achieving MDG 5 through safe skilled delivery assistance among others, the high caesarean section rate beyond the recommend limit, and the finding that caesarean sections done without medical indications were also alarming. The government and city administration should take appropriate measures before the problems become setbacks in healthcare provision. Further investigations should focus on the effect of caesarean section delivery on maternal and child health outcomes in the study area.

Keywords: Addis Ababa, caesarean section, mode of delivery, slum residence

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Authors: Ruba Hamed, Khaled Hussainey, Basiem Al-Shattarat, Wasim Al-Shattarat

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This paper examines how the influence of mandating corporate social responsibility reporting (CSR) on subsequent financial performance through accounting-based measures and market-based measures. We provide evidence about the negative impact of reporting CSR voluntarily on the firm’s future performance due to the increased spending on and costs related to such activities. On the contrary, mandating CSR reporting enhances firms’ future performance by signalling to the market about the firm’s positive stance towards sustainability issues in the UK. Our findings are of interest to regulation setters and stakeholders with respect to mandatory CSR reporting and provide further insight and feedback into accounting and reporting practices.

Keywords: accounting-based performance, mandatory CSR, mandatory regulation, market-based performance

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Authors: B. G. Abiona, T. D. Odetayo, S. O. Adeogun, O. E. Fakoya

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This study determined the effects of workplace power on employees’ job performance in selected federal universities of agriculture in Nigeria. Two hundred and twenty-seven (227) employees were randomly drawn from the selected universities through a multistage sampling procedure. The mean age of the employees was 38 years, mostly (60.8%) male. Results indicated that the overall job performance was significantly influenced by an expert (b = 0.287, p<0.01) and legitimate power (b = -0.279, p<0.05). The findings clearly showed that supervisor has considerable professional experience to draw from in helping subordinates to do their work better because they have specialized training in their field of study, and subordinates prefer to do what the supervisor suggests because of their professional expertise, which greatly influences employees’ job performance. A policy that will ensure transparency in all administrative procedures, with a formal line of authority that will enhance the thriving of legitimate power, should be established within organisation is recommended.

Keywords: workplace power, employees, job performance, agricultural unversities

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Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, multiobjective optimization, ZDT test functions, evolutionary algorithms

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Authors: Yue-Tzu Yang, Peng-Jen Chen

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The present study deals with the numerical optimization of wavy channel with the help of genetic algorithm (GA). Three design variables related to the wave amplitude (A), the wavelength (λ) and the channel aspect ratio (α) are chosen and their ranges are decided through preliminary calculations of three-dimensional Navier-stokes and energy equations. A parametric study is also performed to show the effects of different design variables on the overall performance of the wavy channel. Objective functions related to the heat transfer and pressure drop, performance factor (PF) is formulated to analyze the performance of the wavy channel. The numerical results show that the wave amplitude and the channel aspect ratio have significant effects on the thermal performance. It can improve the performance of the wavy channels by increasing wave amplitude or decreasing the channel aspect ratio. Increasing wavelengths have no significant effects on the heat transfer performance.

Keywords: wavy channel, genetic algorithm, optimization, numerical simulation

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Authors: Angela U. Makolo

Abstract:

Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Janusz Getta, Zhaoxi Pan

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Performance-based quality evaluation of database conceptual schemas is an important aspect of database design process. It is evident that different conceptual schemas provide different logical schemas and performance of user applications strongly depends on logical and physical database structures. This work presents the entire process of performance-based quality evaluation of conceptual schemas. First, we show format. Then, the paper proposes a new specification of object algebra for representation of conceptual level database applications. Transformation of conceptual schemas and expression of object algebra into implementation schema and implementation in a particular database system allows for precise estimation of the processing costs of database applications and as a consequence for precise evaluation of performance-based quality of conceptual schemas. Then we describe an experiment as a proof of concept for the evaluation procedure presented in the paper.

Keywords: conceptual schema, implementation schema, logical schema, object algebra, performance evaluation, query processing

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Authors: Bulus Kpame, Mukhtar Mohammed Alhaji, Garba Jibril

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In any team sport, the most important variables that should be used to measure performance are physical condition, and technical and tactical performance. In a complex game like football, it is extremely difficult to measure the relative importance of each of these variables. However, physical fitness itself has been shown to consist of several components, like endurance, strength, flexibility, agility, coordination and speed. Each of these components has been shown to consist of several subcomponents. This paper attempts to describe a test battery to assess and evaluate physical performance in football players. This battery comprises a functional, structured training session of about 2.5hrs. it consists of quality rating of the warm-up procedure, tests of flexibility, football skills, power, speed, and endurance. Acceptable values for performance in each of the tests are also presented under each test. It is hoped that this battery of tests will be helpful to the coach in determining the effect of a specific training program. It would also be helpful to train physician and trainer, to monitor progress during rehabilitation after sustaining any injury.

Keywords: assessment, evaluation, performance, programs

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Authors: Narender Singh Thakur, Sunil Chamoli

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The use of roughness geometry in the rectangular channel duct is an effective technique to enhance the rate of heat transfer to the working fluid. The present research concentrates on the performance comparison of a rectangular channel with different roughness geometry of the test plate. The performance enhancement is compared by considering the statistical correlations developed by the various investigators for Nusselt number and friction factor. Among all the investigated geometries multiple v-shaped rib roughened rectangular channel found thermo hydraulically better than other investigated geometries under similar current and operating conditions.

Keywords: nusselt number, friction factor, thermohydraulic, performance parameter

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Authors: Gayathri P. Nair

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The focus of this study is to identify whether the board structure has any significant impact on the firm performance and finding out any evidence of being listed in the Fortune 500 list compiled and published by the American business magazine, Fortune and published globally by Time Inc., as the world’s wealthiest companies. The list has been released based on the ranking obtained for the total revenues for the respective fiscal year which has ended on or before March 31st. The study has been conducted on the Indian companies that were listed in the Fortune 500 list for the past 10 years. This study employs a logical regression between the variables, firm performance and board composition as mentioned in the clause 49 of companies act 1956 and 2013. For getting the firm performance, ROA has selected as the key performance metric, as it focuses the management attention on the assets required to run the business. The highlight of the study is that the tools had been applied between public and private sector firms so that, it reveals whether the board composition is helping out to maintain the position in the list. In addition, the findings reveal that apart from independent directors, all other variables have significant impact on firm performance.

Keywords: board structure, Fortune 500 company, firm performance, India

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Hussain Bunyan, Wesam Ali

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In this paper we will study the performance of a Silicon Photovoltaic (PV) system with different tilt angle arrangement in Kuwait (latitude 30˚ N). In this study the PV system is installed facing south, collecting maximum solar radiation at noon, and their angles are from 00 to 900 respectively, during full year at the Solstice and Equinox periods and aiming for a higher angle than 300 with competitive output power. The results show that the performance and the output power of the PV system with 50˚ tilt angle, is equivalent to the latitude tilt angle (30˚) during a full year.

Keywords: photovoltaic model, tilt angle, solar collector, PV system performance, State of Kuwait

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Authors: Hussain Bunyan, Wesam Ali

Abstract:

In this paper we will study the performance of a Silicon Photovoltaic (PV) system with different tilt angle arrangement in Kuwait (latitude 30˚ N). In the study the PV system is installed facing South, collecting maximum solar radiation at noon, and their angles are from 00 to 900 respectively, during full year at the Solstice and Equinox periods, aiming for a higher angle than 300 with competitive output power. The results show that the performance and the output power of the PV system with 50˚ tilt angle, is equivalent to the latitude tilt angle (30˚) during a full year.

Keywords: photovoltaic model, tilt angle, solar collector, PV system performance, State of Kuwait

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Authors: Ratnawati Mohd Asraf, Hazlina Abdullah

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Numerous studies on boys’ performance relative to girls’ have been conducted around the globe. However, little has been done in relation to the literacy of primary school boys in the Malaysian context. This paper discusses the results of a study that sought to determine the literacy performance of Grades 1, 2, and 3 primary school students in the state of Selangor, Malaysia. Data on approximately 85,000 students from each grade level were obtained from the Ministry of Education Malaysia, which conducts national screening on literacy and numeracy, or LINUS, in all government primary schools. Teachers’ views were also sought through focus group interviews and journal entries. The results show that although there is an overall improvement in literacy performance in the Malay language among the students as they go into Grades 2 and 3, girls are found to outperform boys in every screening for all grade levels.

Keywords: boys’ underperformance, literacy, literacy performance, reading

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Johna Bernice Ablaza, Bryan Lim Corpuz, Joanna Marie Estrada, Mary Ann Cristine Olgado, Rhina Recato

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This study aimed to describe the mathematical beliefs and attitudes in relation to the mathematics performance of freshman college students. The descriptive design using the correlational study was used to describe the relationship among mathematical beliefs, attitudes, and performance of freshman college students. This study involved one hundred fifty (150) freshman college students of Philippine Normal University during the third trimester of school year 2015-2016. The research instruments used to gather the information needed in the study are the beliefs about Mathematics Questionnaire, the KIM-Project Questionnaire, and the ACT Compass Mathematics Test. The data gathered were analyzed using the percentages, mean, standard deviation, and Pearson r-moment correlation. The results of this study have shown that although students believe that Mathematics is significant in their lives, the overall result on their beliefs and attitudes are positively low. There is a significant relationship between the students’ mathematical beliefs and mathematics performance. Likewise, their attitudes in mathematics have significant relationship to mathematics performance.

Keywords: attitudes, diligence, interest, mathematical beliefs, mathematical performance, self-confidence

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Authors: Ayodele Ajayi, John Ajayi

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This paper investigates the effect of corporate governance with a view to determining the relationship between board size and bank performance. Data for the study were obtained from the audited financial statements of five sampled banks listed on the Nigerian Stock Exchange. Panel data technique was adopted and analysis was carried out with the use of multiple regression and pooled ordinary least square. Results from the study show that the larger the board size, the greater the profit implying that corporate governance is positively correlated with bank performance.

Keywords: corporate governance, banks performance, board size, pooled data

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Authors: Bella Llego

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The purpose of this study was to explain and empirically test the influence of attitude towards work, job satisfaction and organizational commitment of SSRU employee’s evaluation and performance. Data used in this study was primary data which were collected through Organizational Commitment Questionnaire with 1-5 Likert Scale. The respondent of this study was 200 managerial and non-managerial staff of SSRU. The statistics to analyze the data provide the descriptive by the mean, standard deviation and test hypothesis by the use of multiple regression. The result of this study is showed that attitude towards work have positive but not significant effect to job satisfaction and employees evaluation and performance. Different with attitude towards work, the organizations commitment has positive and significant influence on job satisfaction and employee performance at SSRU. It means every improvement in organization’s commitment has a positive effect toward job satisfaction and employee evaluation and performance at SSRU.

Keywords: attitude towards work, employee’s evaluation and performance, jobs satisfaction, organization commitment

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Authors: Elizabeth Malebogo Mosepele

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Road transport has become increasingly common in the world; people rely on road networks for transportation purpose on a daily basis. However, environmental impact of roads on surrounding landscapes extends their potential effects even further. This study investigates the impact of road network on natural vegetation. The study will provide baseline knowledge regarding roadside vegetation and would be helpful in future for conservation of biodiversity along the road verges and improvements of road verges. The general hypothesis of this study is that the amount and condition of road side vegetation could be explained by road network conditions. Remote sensing techniques were used to analyze vegetation conditions. Landsat 8 OLI image was used to assess vegetation cover condition. NDVI image was generated and used as a base from which land cover classes were extracted, comprising four categories viz. healthy vegetation, degraded vegetation, bare surface, and water. The classification of the image was achieved using the supervised classification technique. Road networks were digitized from Google Earth. For observed data, transect based quadrats of 50*50 m were conducted next to road segments for vegetation assessment. Vegetation condition was related to road network, with the multinomial logistic regression confirming a significant relationship between vegetation condition and road network. The null hypothesis formulated was that 'there is no variation in vegetation condition as we move away from the road.' Analysis of vegetation condition revealed degraded vegetation within close proximity of a road segment and healthy vegetation as the distance increase away from the road. The Chi Squared value was compared with critical value of 3.84, at the significance level of 0.05 to determine the significance of relationship. Given that the Chi squared value was 395, 5004, the null hypothesis was therefore rejected; there is significant variation in vegetation the distance increases away from the road. The conclusion is that the road network plays an important role in the condition of vegetation.

Keywords: Chi squared, geographic information system, multinomial logistic regression, remote sensing, road side vegetation

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Authors: Theresia Dwi Hastuti, Kristiana Haryanti, Agustine Eva Maria Soekesi

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Today's family business continues to grow in big cities and in rural areas throughout Indonesia in line with the development of the business world and global competition. This study aims to analyze the effect of company value, leadership, and ownership succession on the financial performance of the family business. The research method was carried out quantitatively with multiple regression. The respondent amounted to 63 entrepreneurs. This study found that company value, leadership succession, relationships, and communication affect the financial performance of the family business.

Keywords: company value, family business, financial performance, leadership succession, ownership succession

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Authors: Mohammad Q. M. Momani

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The objective of this study is to examine whether the value relevance of ownership structure changed as the Amman Stock Exchange market conditions changed. Using data from 2005 to 2014, the study finds that the performance of portfolios that contain firms with concentrated ownership structure declines significantly during the post-crisis period. These portfolios exhibit poor performance relative to portfolios that contain firms with dispersed ownership structure during the post-crisis period. The results argue that uninspired performance of the Amman Stock Exchange during the post-crisis period, increased the incentives for controlling shareholders to expropriate. Investors recognized these incentives and discounted firms that were more likely to expropriate.

Keywords: value relevance, ownership structure, portfolio performance, Jordan, ASE

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