Search results for: logistic performance

Authors: Alfred M. Caronia

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The aim of this pilot study was to explore an NCAA Division 1 female volleyball players’ experience of a strength and conditioning program and the result this has on self-efficacy of sport skill performance. This phenomenological study comprised of 10 college aged participants that have strength training program experience. Data was collected using semi-structured interviews and a reflective journal; the transcribed interviews were analyzed using qualitative content analysis. From the analysis, four themes emerged: performance enhancement, injury prevention, motivational experience, and learning experience. From the players’ perspective, care needs to be taken to explain the purpose of an exercise and the benefit it will have for a play performance. Other factors that play an important role in a strength training program are team motivation, individual goal setting, bonding, and communication with the strength coach, as all these items appear to be fundamentals of coaching.

Keywords: self-efficacy, skill performance, sports performance, strength training

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Authors: Hadis Mahmoodsalehi, Elham Shakoor, Maryam Koushkie Jahromi

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Background and aims: Given the importance of health promotion in elderly and attention to health factors including physical activity and self-image reinforcing, this study aimed to investigate the relationship between exercise attitude and performance with self-image concept in elderly men. Methods: In this descriptive–correlational study, 50 different daily exercise activities of the elderly men living in Iran (mean age: 60.94 years) were selected through simple sampling method. Participants completed a questionnaire regarding exercise attitude and performance and Beck self-image concept. Pearson correlation test was used for analysis of the data. Results: The results showed the significant correlation between optimism and exercise performance (p = 0.012) and exercise attitude (p = 0.005). Conclusion: Findings show that exercise performance and attitude are associated positively with optimism in elderly women. So, increasing exercise or improving attitude toward exercise can lead to improving optimism.

Keywords: elderly, exercise performance and attitude, self-image, descriptive–correlational study

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: artificial neural networks (ANNs), classifier algorithms, credit risk assessment, logistic regression, machine Learning, support vector machines

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

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Authors: Kasif Khan, Azlan Allahwala, Moiz Ali, Hasan Lodhi, Umer Amjad

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The number of runs scored by batsmen and wickets taken by bowlers serves as a natural way of quantifying the performance of a cricketer. Traditionally the batsmen and bowlers are rated on their batting or bowling average respectively. However, in a game like Cricket, it is not sufficient to evaluate performance on the basis of average. The biasness in selecting batsman and bowler on the basis of their past performance. The objective is to predict the best player and comparing their performance on the basis of venue, opponent, weather, and particular position. On the basis of predictions and analysis, and comparison the best team is selected for next upcoming series of Pakistan. The system is based and will be built to aid analyst in finding best possible team combination of Pakistan for a particular match and by providing them with advisories so that they can select the best possible team combination. This will also help the team management in identifying a perfect batting order and the bowling order for each match.

Keywords: data analysis, Pakistan cricket players, quantifying individual performance, cricket

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Authors: Syed Atif Ali, Farzan Yahya

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This research paper covers the issue of risk management impact on the company performance. Degree of financial leverage (DFL), degree of operating leverage (DOL) and the working capital ratio (WCR) are taken as independent variables which are the representative of risk and the earning price per share (EPS), return on assets (ROA), return on equity (ROE), Sales and Net profits which are the representative of performance. Last 10 years (2004-2013) of Cement sector of Pakistan data is chosen as sample for analyze their relations by multiple regression technique. Through analyses, it is found that WCR impact adequately on the company performance because if company has enough liquidity than it perform its operations smoothly and enhance its performance very well. DFL should be control moderately because enough DFL leads performance of company downward. On the other hand, the DOL should be less because it causes the less profitability for a company from its operations.

Keywords: degree of financial leverage (DFL), degree of operating leverage (DOL), working capital ratio (WCR), earning per share (EPS), return on equity (ROE), return on assets (ROA)

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Authors: Widjojo Suprapto, Zeplin Jiwa Husada Tarigan, Sautma Ronni Basana

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Business process reengineering can be conducted by some procedure rationalization for all related departments in a company so that all data and business processes are connected. The changing of any business process is used to set up the working standard so that it gives an impact to the implementation of ERP and the company performance. After collecting and processing the data from 77 manufacturing companies, it is obtained that BPR (Business Process Reengineering) has no direct impact on the implementation of ERP (Enterprise Resource Planning) in the companies and manufacturing performance; however, it influences the implementation of TQM. The implementation of TQM influences directly the implementation of ERP, but it does not influence directly the company performance. The implementation of ERP gives a significant increase in the work performance of the manufacturing companies in East Java.

Keywords: enterprise resources planning, business process reengineering, TQM, company performance

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Authors: Wisdom Dordudnu, George M. Y. Owusu, Samuel N. Y. Simpson

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The recent failures of many corporate giants have generated intense research interest in the factors that influence accountants’ job performance. Against the backdrop that these factors also create an enabling environment for success at the work place, this study contributes to literature on job performance of accountants by exploring the impact of two psycho-spiritual factors: religiosity and spiritual intelligence on job performance of accountants in Ghana. The study employs a survey approach using questionnaires as the principal means of data collection to elicit responses from accountants working in the 222 certified firms of Institute of Chartered Accountants Ghana (ICAG). A structural equation modeling-based approach is employed to examine the relationship among the study constructs. Results of this study indicate that there is a positive relationship between these factors and accountants’ performance. It is expected that this study provides strong evidence and highlight the need for specific action from managers to look critically at the non-material aspect of accountants in accounting firms.

Keywords: job performance, psycho-spiritual, religiosity, spiritual intelligence

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Authors: Lubena Achmad, Herman Kristanto, Julian Dewantiningrum

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Background: The Bishop score is a standard method used to predict the success of induction. This examination tends to be subjective with high inter and intraobserver variability, so it was presumed to have a low predictive value in terms of the outcome of labor induction. Cervical length measurement using transvaginal ultrasound is considered to be more objective to assess the cervical length. Meanwhile, this examination is not a complicated procedure and less invasive than vaginal touché. Objective: To compare transvaginal ultrasound and Bishop score in predicting successful induction. Methods: This study was a prospective cohort study. One hundred and twenty women with singleton pregnancies undergoing induction of labor at 37 – 42 weeks and met inclusion and exclusion criteria were enrolled in this study. Cervical assessment by both transvaginal ultrasound and Bishop score were conducted prior induction. The success of labor induction was defined as an ability to achieve active phase ≤ 12 hours after induction. To figure out the best cut-off point of cervical length and Bishop score, receiver operating characteristic (ROC) curves were plotted. Logistic regression analysis was used to determine which factors best-predicted induction success. Results: This study showed significant differences in terms of age, premature rupture of the membrane, the Bishop score, cervical length and funneling as significant predictors of successful induction. Using ROC curves found that the best cut-off point for prediction of successful induction was 25.45 mm for cervical length and 3 for Bishop score. Logistic regression was performed and showed only premature rupture of membranes and cervical length ≤ 25.45 that significantly predicted the success of labor induction. By excluding premature rupture of the membrane as the indication of induction, cervical length less than 25.3 mm was a better predictor of successful induction. Conclusion: Compared to Bishop score, cervical length using transvaginal ultrasound was a better predictor of successful induction.

Keywords: Bishop Score, cervical length, induction, successful induction, transvaginal sonography

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Pablo Enrique Sartor Del Giudice

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Penalty shootouts often decide the outcome of important soccer matches. Although usually referred to as ”lotteries”, there is evidence that some national teams and clubs consistently perform better than others. The outcomes are therefore not explained just by mere luck, and therefore there are ways to improve the average performance of players, naturally at the expense of some sort of effort. In this article we study the payoff of player performance improvements in terms of the performance of the team as a whole. To do so we develop an analytical model with static individual performances, as well as Monte Carlo models that take into account the known influence of partial score and round number on individual performances. We find that within a range of usual values, the team performance improves above 70% faster than individual performances do. Using these models, we also estimate that the new ABBA penalty shootout ordering under test reduces almost all the known bias in favor of the first-shooting team under the current ABAB system.

Keywords: football, penalty shootouts, Montecarlo simulation, ABBA

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Authors: Mukesh Khadka, Alexander Paz, Hanns de la Fuente-Mella

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Typically, pavement performance models are developed in two steps: (i) pavement segments with similar characteristics are grouped together to form a cluster, and (ii) the corresponding performance models are developed using statistical techniques. A challenge is to select the characteristics that define clusters and the segments associated with them. If inappropriate characteristics are used, clusters may include homogeneous segments with different performance behavior or heterogeneous segments with similar performance behavior. Prediction accuracy of performance models can be improved by grouping the pavement segments into more uniform clusters by including both characteristics and a performance measure. This grouping is not always possible due to limited information. It is impractical to include all the potential significant factors because some of them are potentially unobserved or difficult to measure. Historical performance of pavement segments could be used as a proxy to incorporate the effect of the missing potential significant factors in clustering process. The current state-of-the-art proposes Clusterwise Linear Regression (CLR) to determine the pavement clusters and the associated performance models simultaneously. CLR incorporates the effect of significant factors as well as a performance measure. In this study, a mathematical program was formulated for CLR models including multiple explanatory variables. Pavement data collected recently over the entire state of Nevada were used. International Roughness Index (IRI) was used as a pavement performance measure because it serves as a unified standard that is widely accepted for evaluating pavement performance, especially in terms of riding quality. Results illustrate the advantage of the using CLR. Previous studies have used CLR along with experimental data. This study uses actual field data collected across a variety of environmental, traffic, design, and construction and maintenance conditions.

Keywords: clusterwise regression, pavement management system, performance model, optimization

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Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

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Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

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Authors: Hurgesa Hundera, Samuel Shibeshibikeko, Tarike Daba, Tesfaye Ganamo

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The study aimed at examining the ongoing adaptation strategies used by smallholder farmers in response to climate variability in Boset district. It also assessed the socioeconomic factors that influence the choice of adaptation strategies of smallholder farmers to climate variability risk. For attaining the objectives of the study, both primary and secondary sources of data were employed. The primary data were obtained through a household questionnaire, key informant interviews, focus group discussions, and observations, while secondary data were acquired through desk review. Questionnaires were distributed and filled by 328 respondents, and they were identified through systematic random sampling technique. Descriptive statistics and binary logistic regression model were applied in this study as the main analytical methods. The findings of the study reveal that the sample households have utilized multiple adaptation strategies in response to climate variability, such as cropping early mature crops, planting drought resistant crops, growing mixed crops on the same farm lands, and others. The results of the binary logistic model revealed that education, sex, age, family size, off farm income, farm experience, access to climate information, access to farm input, and farm size were significant and key factors determining farmers’ choice of adaptation strategies to climate variability in the study area. To enable effective adaptation measures, Ministry of Agriculture and Natural Resource, with its regional bureaus and offices and concerned non–governmental organizations, should consider climate variability in their planning and budgeting in all levels of decision making.

Keywords: adaptation strategies, boset district, climate variability, smallholder farmers

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Authors: Yassir AbdelRazig, Eren Ozguven, Ren Moses

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While there exists a greater understanding of the differences between the driving behaviors of older and younger drivers, there is still a need to further understand how the two groups perform when attempting to perform complex intersection maneuvers. This paper looks to determine if, and to what extent, these differences exist when drivers encounter permissive left-hand turns, pedestrian traffic, two and four-lane intersections, heavy fog, and night conditions. The study will utilize a driving simulator to develop custom drivable scenarios containing one or more of the previously mentioned conditions. 32 younger and 32 older (+65 years) participants perform driving simulation scenarios and have their velocity, time to the nearest oncoming vehicle, accepted and rejected gaps, etc., recorded. The data collected from the simulator is analyzed via Raff’s method and logistic regression in order to determine and compare the critical gaps values of the two cohorts. Out of the parameters considered for this study, only the age of the driver, their experience (if they are a younger driver), the size of a gap, and the presence of pedestrians on the crosswalk proved significant. The results did not support the hypothesis that older drivers would be significantly more conservative in their critical gaps judgment and acceptance.

Keywords: older drivers, simulation, left-turn, human factors

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Authors: Catherine Maware, Olufemi Adetunji

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The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: impact measurement model, lean bundles, lean manufacturing, organizational performance

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Authors: Odunayo E. Popoola, Charles A. Aladesaye, Sunday O. Gbenro

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The study investigated the impact of technological advancement on the academic performance of Mathematics students in tertiary institutions in Ekiti State, Nigeria. The quasi-experimental research design was adopted for the study. The population for the study consisted of all the 100 level undergraduates and all Mathematics lecturers in the Department of Mathematics in all the five tertiary institutions in the State. The sample of this study was made of one hundred (100) students and fifty (50) lecturers randomly selected using stratified sampling technique. Hypotheses were postulated to find out whether (i) advancement in technology influences the academic performance of students in Mathematics (ii) teaching method and gender disparity influences the academic performance of students in Mathematics. The study revealed that teaching method, gender, and technology influence academic performance of students in Mathematics. Based on the findings, it is recommended that curriculum and assessment in school Mathematics should explicitly require that all undergraduate become proficient in using digital technologies for mathematical purposes so as to enhance the better performance of students in Mathematics.

Keywords: mathematics, performance, tertiary institutions, technology

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Authors: Ejaz Ali, Muhammad Younas, Tahir Saeed

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In this age of information technology, organizations are revisiting their approach in great deal. E-administration is the most popular area to proceed with. Organizations in order to excel over their competitors are spending a substantial chunk of its resources on E-Administration as it is the most effective, transparent and efficient way to achieve their short term as well as long term organizational goals. E-administration being a tool of ICT plays a significant role towards effective management of HR practices resulting into optimal performance of an organization. The present research was carried out to analyze the impact of moderating role of e-administration in the relationships training and performance appraisal aligned with perceived organizational performance. The study is based on RBV and AMO theories, advocating that use of latest technology in execution of human resource (HR) functions enables an organization to achieve and sustain competitive advantage which leads to optimal firm performance.

Keywords: e-administration, human resource management, ict, performance appraisal, training

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Authors: Eung Ryeol Seo, Hee Tae Lim, Eunsuk Bang, Soon Cheol Kweon, Jeoung-Kyo Jeoung, Ji-Hoon Choic

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The object of this study is to investigate the effect of pulsator on washing performance quantitatively for front-loading washer. The front-loading washer with pulsator shows washing performance improvement of 18% and the particle-based body simulation technique has been applied to figure out the relation between washing performance and mechanical forces exerted on textile during washing process. As a result, the mechanical forces, such as collision force and strain force, acting on the textile have turned out to be about twice numerically. The washing performance improvement due to additional pulsate system has been utilized for customers to save 50% of washing time.

Keywords: front-loading washer, mechanical force, fabric movement, pulsator, time-saving

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Authors: Sonia Rebai, Mohamed Naceur Azaiez, Dhafer Saidane

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In this study, we develop a performance evaluation model based on a multi-attribute utility approach aiming at reaching the sustainable banking (SB) status. This model is built accounting for various banks’ stakeholders in a win-win paradigm. In addition, it offers the opportunity for adopting a global measure of performance as an indication of a bank’s sustainability degree. This measure is referred to as banking sustainability performance index (BSPI). This index may constitute a basis for ranking banks. Moreover, it may constitute a bridge between the assessment types of financial and extra-financial rating agencies. A real application is performed on three French banks.

Keywords: multi-attribute utility theory, performance, sustainable banking, financial rating

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Authors: Bijaya Kumar Sahoo

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The effect of III-V nitride semiconductors on performance of a graphene-on-gold surface plasmon resonance (SPR) biosensor has been investigated theoretically. III-V nitrides (AlN, GaN and InN) have been grown between gold (Au) and graphene layers. The sensitivity and performance of the biosensor have been computed for with and without semiconductors. Due to superior electronic and optical properties, III-V nitrides demonstrate high sensitivity and performance over Si and Ge. The enhancement of evanescent electric field due to III-V nitrides have been computed and found highest for InN. The analysis shows that for a high-sensitive imaging biosensor the required optimal thickness of gold, InN and graphene are respectively 49 nm, 11 nm and 0.34 nm for the light of wavelength =633 nm (red He-Ne laser). This study suggests that InN would be a better choice for fabrication of new imaging SPR biosensors.

Keywords: SPR biosensor, optical properties, III-V nitrides, sensitivity, enhancement of electric field, performance of graphene gold SPR biosensor

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Authors: Songul Cinaroglu

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Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: Chen Chan Wei

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The purpose of this study was to investigate the impact of swim 1500m, 10000m run, VO2 max, and body fat on Olympic distance triathlon competition performance. The subjects were thirteen college triathletes with endurance training, with an average age, height and weight of 20.61±1.04 years (mean ± SD), 171.76±8.54 cm and 65.32±8.14 kg respectively. All subjects were required to take the tests of swim 1500m, run 10000m, VO2 max, body fat, and participate in the Olympic distance triathlon competition. First, the swim 1500m test was taken in the standardized 50m pool, with a depth of 2m, and the 10000m run test on the standardized 400m track. After three days, VO2 max was tested with the MetaMax 3B and body fat was measured with the DEXA machine. After two weeks, all 13 subjects joined the Olympic distance triathlon competition at the 2016 New Taipei City Asian Cup. The relationships between swim 1500m, 10000m run, VO2 max, body fat test, and Olympic distance triathlon competition performance were evaluated using Pearson's product-moment correlation. The results show that 10000m run and body fat had a significant positive correlation with Olympic distance triathlon performance (r=.830, .768), but VO2 max has a significant negative correlation with Olympic distance triathlon performance (r=-.735). In conclusion, for improved non-draft Olympic distance triathlon performance, triathletes should focus on running than swimming training and can be measure VO2 max to prediction triathlon performance. Also, managing body fat can improve Olympic distance triathlon performance. In addition, swimming performance was not significantly correlated to Olympic distance triathlon performance, possibly because the 2016 New Taipei City Asian Cup age group was not a drafting competition. The swimming race is the shortest component of Olympic distance triathlons. Therefore, in a non-draft competition, swimming ability is not significantly correlated with overall performance.

Keywords: triathletes, olympic, non-drafting, correlation

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Authors: Hadi Molaei, Yasavoli Davoud, Keshavarz, Mozhde Poordana

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The present study aimed was to prediction the academic performance based on academic motivation, self-efficacy and Resiliency in the students. The present study was descriptive and correlational. Population of the study consisted of all students in Arak schools in year 1393-94. For this purpose, the number of 304 schools students in Arak was selected using multi-stage cluster sampling. They all questionnaires, self-efficacy, Resiliency and academic motivation Questionnaire completed. Data were analyzed using Pearson correlation and multiple regressions. Pearson correlation showed academic motivation, self-efficacy, and Resiliency with academic performance had a positive and significant relationship. In addition, multiple regression analysis showed that the academic motivation, self-efficacy and Resiliency were predicted academic performance. Based on the findings could be conclude that in order to increase the academic performance and further progress of students must provide the ground to strengthen academic motivation, self-efficacy and Resiliency act on them.

Keywords: academic motivation, self-efficacy, resiliency, academic performance

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Authors: Hatane Semuel, Foedjiawati, Michelle Sunur

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This study took the research object of fifteen legal travel agencies in Surabaya. The respondents are taken through purposive sampling of a number of 100 employees out of Fifteen travel agencies which are varied in its division. Service orientation is constructed based on several dimensions; such as, service leadership practices, service encounter practices, human resources management practices, and service system practices. Service skills are constructed with dimensions; namely: technical skills, interpersonal skills, and problem-solving skill. While employee performance is constructed with dimensions; namely: quantity of work, quality of work, timeliness of work and organization of work. The results show that there is a direct positive influence on employee performance service orientation. Additionally, service orientation influences indirectly positive on employee performance through the service skills. Therefore, the total effect of service orientation on employee performance is proven stronger.

Keywords: employee performance, service orientation, service skills, travel agencies

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Authors: Niti Kammuang-lue, Kritsada On-ai, Phrut Sakulchangsatjatai, Pradit Terdtoon

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The objectives of this paper are to investigate effects of dimensionless numbers on thermal performance of the vertical closed-loop pulsating heat pipe (VCLPHP) and to establish a correlation to predict the thermal performance of the VCLPHP. The CLPHPs were made of long copper capillary tubes with inner diameters of 1.50, 1.78, and 2.16mm and bent into 26 turns. Then, both ends were connected together to form a loop. The evaporator, adiabatic, and condenser sections length were equal to 50 and 150 mm. R123, R141b, acetone, ethanol, and water were chosen as variable working fluids with constant filling ratio of 50% by total volume. Inlet temperature of heating medium and adiabatic section temperature was constantly controlled at 80 and 50oC, respectively. Thermal performance was represented in a term of Kutateladze number (Ku). It can be concluded that when Prandtl number of liquid working fluid (Prl), and Karman number (Ka) increases, thermal performance increases. On contrary, when Bond number (Bo), Jacob number (Ja), and Aspect ratio (Le/Di) increases, thermal performance decreases. Moreover, the correlation to predict more precise thermal performance has been successfully established by analyzing on all dimensionless numbers that have effect on the thermal performance of the VCLPHP.

Keywords: vertical closed-loop pulsating heat pipe, working fluid, thermal performance, dimensionless parameter

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Authors: Ahmad Abubakar Sadiq, Nwohu Ndubuka Mark, Jacob Tsado, Ahmad Adam Asharaf, Agbachi E. Okenna, Enesi E. Yahaya, Ambafi James Garba

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Transmission system performance analysis is vital to proper planning and operations of power systems in the presence of deregulation. Key performance indicators (KPIs) are often used as measure of degree of performance. This paper gives a novel method to determine the transmission efficiency by evaluating the ratio of real power losses incurred from a specified transfer direction. Available Transmission Transfer Efficiency (ATTE) expresses the percentage of real power received resulting from inter-area available power transfer. The Tie line (Rated system path) performance is seen to differ from system wide (Network response) performance and ATTE values obtained are transfer direction specific. The required sending end quantities with specified receiving end ATC and the receiving end power circle diagram are obtained for the tie line analysis. The amount of real power loss load relative to the available transfer capability gives a measure of the transmission grid efficiency.

Keywords: performance, transmission system, real power efficiency, available transfer capability

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Authors: S. Forughi, A. De Zoysa, S. Bhati

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The present study focuses on the environmental performance of the companies in the electricity-producing sector and its relationship with their financial performance. We will review the major studies that examined the relationship between the environmental and financial performance of firms in various industries. While the classical economic debates consider the environmental friendly activities costly and harmful to a firm’s profitability, it is claimed that firms will be rewarded with higher profitability in long run through the investments in environmental friendly activities. In this context, prior studies have examined the relationship between the environmental and financial performance of firms operating in different industry sectors. Our study will employ an environmental indicator to increase the accuracy of the results and be employed as an independent variable in our developed econometric model to evaluate the impact of the financial performance of the firms on their environmental friendly activities in the context of companies operating in the Australian electricity-producing sector. As a result, we expect our methodology to contribute to the literature and the findings of the study will help us to provide recommendations and policy implications to the electricity producers.

Keywords: Australian electricity sector, efficiency measurement, environmental-financial performance interaction, environmental index

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Authors: Kahil Amar, Boukais Said, Kezmane Ali, Hannachi Naceur Eddine, Hamizi Mohand

Abstract:

The principle of the seismic performance evaluation methods is to provide a measure of capability for a building or set of buildings to be damaged by an earthquake. The common objective of many of these methods is to supply classification criteria. The purpose of this study is to present a method for assessing the seismic performance of structures, based on Pushover method, we are particularly interested in reinforced concrete frame structures, which represent a significant percentage of damaged structures after a seismic event. The work is based on the characterization of seismic movement of the various earthquake zones in terms of PGA and PGD that is obtained by means of SIMQK_GR and PRISM software and the correlation between the points of performance and the scalar characterizing the earthquakes will be developed.

Keywords: seismic performance, pushover method, characterization of seismic motion, harmfulness of the seismic

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Authors: Fahad Alam

Abstract:

Work stress directly affects job performance, specifically in a worse environment. Consequently, a social provision plays a crucial part for enhancement. Therefore, the current research investigates the direct and moderating effect between religious activities, sustainability and peer support on job performance at hospitals in Khyber PakhtunKhwa (KPK), Pakistan. Both primary and secondary data are collected through 261 questionnaires of medical employees from four district hospitals in Khyber PakhtunKhwa, Pakistan, in 2018. The analysis was carried out by SPSS16 and SMART PLS3, to test the direct effect of religious activities, sustainability and social support on job performance and the effect of moderating variable 'work environment' on job performance. The finding confirmed that direct and moderating variables play a significant positive effect among religious activities, sustainability and peer support on job performance, the variables help to diminish the strain level or the stress level, consequently helps in the job completed. Affirmative social approaches produce desirable effects on job performance. The research revealed that social provisions are significant triggers for superior practices. Moreover, the results are stimulating because some of the past literature revealed an insignificant correlation between social provision and performance. This study found that there is a significant relationship which persuades health care organizations.

Keywords: job performance, peer’s support, religious activities, sustainability, work environment

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