Search results for: competitive performance importance-performance analysis
Commenced in January 2007
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Edition: International
Paper Count: 37000

Search results for: competitive performance importance-performance analysis

33190 Tolerance of Ambiguity in Relation to Listening Performance across Learners of Various Linguistic Backgrounds

Authors: Amin Kaveh Boukani

Abstract:

Foreign language learning is not straightforward and can be affected by numerous factors, among which personality features like tolerance of ambiguity (TA) are so well-known and important. Such characteristics yet can be affected by other factors like learning additional languages. The current investigation, thus, opted to explore the possible effect of linguistic background (being bilingual or trilingual) on the tolerance of ambiguity (TA) of Iranian EFL learners. Furthermore, the possible mediating effect of TA on multilingual learners' language performance (listening comprehension in this study) was expounded. This research involved 68 EFL learners (32 bilinguals, 29 trilinguals) with the age range of 19-29 doing their degrees in the Department of English Language and Literature of Urmia University. A set of questionnaires, including tolerance of ambiguity (Herman et. al., 2010) and linguistic background information (Modirkhameneh, 2005), as well as the IELTS listening comprehension test, were used for data collection purposes. The results of a set of independent samples t-test and mediation analysis (Hayes, 2022) showed that (1) linguistic background (being bilingual or trilingual) had a significant direct effect on EFL learners' TA, (2) Linguistic background had a significant direct influence on listening comprehension, (3) TA had a substantial direct influence on listening comprehension, and (4) TA moderated the influence of linguistic background on listening comprehension considerably. These results suggest that multilingualism may be considered as an advantageous asset for EFL learners and should be a prioritized characteristic in EFL instruction in multilingual contexts. Further pedagogical implications and suggestions for research are proposed in light of effective EFL instruction in multilingual contexts.

Keywords: tolerance of ambiguity, listening comprehension, multilingualism, bilingual, trilingual

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33189 Relationship between the Yo-Yo Intermittent Recovery Test Level 1 and Anaerobic Performance Tests in Youth Soccer Players

Authors: Turgay Ozgur, Bahar Ozgur, Gurcan Yazici

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The aims of the study were to investigate the relationship between the Yo-Yo intermittent recovery test level 1 (YYIR1) and relatively easy to conduct anaerobic power tests such as Sergeant (SJ) and Standing Broad Jump (SBJ), the flexibility Sit&Reach test (S&R) and Hexagon Agility (HA) test in twenty youth soccer players, aged 14 years. Players completed YYIR1 and other performance tests [(SJ), (SBJ] in two consecutive days. The mean YYIR1 distances for the players was 1454 ± 420 m. Peak Anaerobic Power (PAPw) was calculated using SJ (cm) scores. The mean PAPw was 2966,83w. Spearman’s correlation test results revealed that there is a statistically significant negative correlation between HA and YYIR1 tests (r = -0.72, p=0.000) and no significant correlation was found between anaerobic power tests and YYIR1. In conclusion, as a test to measure player’s intermittent aerobic capacity YYIR1 test and anaerobic power test results have not shown significant correlation. Although the YYIR1 test has been used in talent identification, anaerobic qualifications of player’s should be assessed using designated performance tests.

Keywords: yo-yo test, anaerobic power, soccer, sergeant jump test

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33188 Evaluation of the Effect of Learning Disabilities and Accommodations on the Prediction of the Exam Performance: Ordinal Decision-Tree Algorithm

Authors: G. Singer, M. Golan

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Providing students with learning disabilities (LD) with extra time to grant them equal access to the exam is a necessary but insufficient condition to compensate for their LD; there should also be a clear indication that the additional time was actually used. For example, if students with LD use more time than students without LD and yet receive lower grades, this may indicate that a different accommodation is required. If they achieve higher grades but use the same amount of time, then the effectiveness of the accommodation has not been demonstrated. The main goal of this study is to evaluate the effect of including parameters related to LD and extended exam time, along with other commonly-used characteristics (e.g., student background and ability measures such as high-school grades), on the ability of ordinal decision-tree algorithms to predict exam performance. We use naturally-occurring data collected from hundreds of undergraduate engineering students. The sub-goals are i) to examine the improvement in prediction accuracy when the indicator of exam performance includes 'actual time used' in addition to the conventional indicator (exam grade) employed in most research; ii) to explore the effectiveness of extended exam time on exam performance for different courses and for LD students with different profiles (i.e., sets of characteristics). This is achieved by using the patterns (i.e., subgroups) generated by the algorithms to identify pairs of subgroups that differ in just one characteristic (e.g., course or type of LD) but have different outcomes in terms of exam performance (grade and time used). Since grade and time used to exhibit an ordering form, we propose a method based on ordinal decision-trees, which applies a weighted information-gain ratio (WIGR) measure for selecting the classifying attributes. Unlike other known ordinal algorithms, our method does not assume monotonicity in the data. The proposed WIGR is an extension of an information-theoretic measure, in the sense that it adjusts to the case of an ordinal target and takes into account the error severity between two different target classes. Specifically, we use ordinal C4.5, random-forest, and AdaBoost algorithms, as well as an ensemble technique composed of ordinal and non-ordinal classifiers. Firstly, we find that the inclusion of LD and extended exam-time parameters improves prediction of exam performance (compared to specifications of the algorithms that do not include these variables). Secondly, when the indicator of exam performance includes 'actual time used' together with grade (as opposed to grade only), the prediction accuracy improves. Thirdly, our subgroup analyses show clear differences in the effect of extended exam time on exam performance among different courses and different student profiles. From a methodological perspective, we find that the ordinal decision-tree based algorithms outperform their conventional, non-ordinal counterparts. Further, we demonstrate that the ensemble-based approach leverages the strengths of each type of classifier (ordinal and non-ordinal) and yields better performance than each classifier individually.

Keywords: actual exam time usage, ensemble learning, learning disabilities, ordinal classification, time extension

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33187 Astronomical Object Classification

Authors: Alina Muradyan, Lina Babayan, Arsen Nanyan, Gohar Galstyan, Vigen Khachatryan

Abstract:

We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of ∼> 65000 color templates for comparison with observed objects. The method aims for extracting the information content of object colors in a statistically correct way, and performs a classification as well as a redshift estimation for galaxies and quasars in a unified approach based on the same probability density functions. For the redshift estimation, we employ an advanced version of the Minimum Error Variance estimator which determines the redshift error from the redshift dependent probability density function itself. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a wide variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where the method provides high reliability (6 errors among 151 objects with R < 24), especially for the quasar selection, and redshifts accurate within σz ≈ 0.03 for galaxies and σz ≈ 0.1 for quasars. For an optimization of future survey efforts, a few model surveys are compared, which are designed to use the same total amount of telescope time but different sets of broad-band and medium-band filters. Their performance is investigated by Monte-Carlo simulations as well as by analytic evaluation in terms of classification and redshift estimation. If photon noise were the only error source, broad-band surveys and medium-band surveys should perform equally well, as long as they provide the same spectral coverage. In practice, medium-band surveys show superior performance due to their higher tolerance for calibration errors and cosmic variance. Finally, we discuss the relevance of color calibration and derive important conclusions for the issues of library design and choice of filters. The calibration accuracy poses strong constraints on an accurate classification, which are most critical for surveys with few, broad and deeply exposed filters, but less severe for surveys with many, narrow and less deep filters.

Keywords: VO, ArVO, DFBS, FITS, image processing, data analysis

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33186 Molecular Engineering of High-Performance Nanofiltration Membranes from Intrinsically Microporous Poly (Ether-Ether-Ketone)

Authors: Mahmoud A. Abdulhamid

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Poly(ether-ether-ketone) (PEEK) has received increased attention due to its outstanding performance in different membrane applications including gas and liquid separation. However, it suffers from a semi-crystalline morphology, bad solubility and low porosity. To fabricate membranes from PEEK, the usage of harsh acid such as sulfuric acid is essential, regardless its hazardous properties. In this work, we report the molecular design of poly(ether-ether-ketones) (iPEEKs) with intrinsic porosity character, by incorporating kinked units into PEEK backbone such as spirobisindane, Tröger's base, and triptycene. The porous polymers were used to fabricate stable membranes for organic solvent nanofiltration application. To better understand the mechanism, we conducted molecular dynamics simulations to evaluate the possible interactions between the polymers and the solvents. Notable enhancement in separation performance was observed confirming the importance of molecular engineering of high-performance polymers. The iPEEKs demonstrated good solubility in polar aprotic solvents, a high surface area of 205–250 m² g⁻¹, and excellent thermal stability. Mechanically flexible nanofiltration membranes were prepared from N-methyl-2-pyrrolidone dope solution at iPEEK concentrations of 19–35 wt%. The molecular weight cutoff of the membranes was fine-tuned in the range of 450–845 g mol⁻¹ displaying 2–6 fold higher permeance (3.57–11.09 L m⁻² h⁻¹ bar⁻¹) than previous reports. The long-term stabilities were demonstrated by a 7 day continuous cross-flow filtration.

Keywords: molecular engineering, polymer synthesis, membrane fabrication, liquid separation

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33185 Thermal Performance and Environmental Assessment of Evaporative Cooling Systems: Case of Mina Valley, Saudi Arabia

Authors: A. Alharbi, R. Boukhanouf, T. Habeebullah, H. Ibrahim

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This paper presents a detailed description of evaporative cooling systems used for space cooling in Mina Valley, Saudi Arabia. The thermal performance and environmental impact of the evaporative coolers were evaluated. It was found that the evaporative cooling systems used for space cooling in pilgrims’ accommodations and in the train stations could reduce energy consumption by as much as 75% and cut carbon dioxide emission by 78% compared to traditional vapour compression systems.

Keywords: evaporative cooling, vapor compression, electricity consumption, CO2 emission

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33184 Predictive Analysis for Big Data: Extension of Classification and Regression Trees Algorithm

Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

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33183 Assessing Performance of Data Augmentation Techniques for a Convolutional Network Trained for Recognizing Humans in Drone Images

Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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33182 A Critique of the Neo-Liberal Model of Economic Governance and Its Application to the Electricity Market Industry: Some Lessons and Learning Points from Nigeria

Authors: Kabiru Adamu

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The Nigerian electricity industry was deregulated and privatized in 2005 and 2014 in line with global trend and practice. International and multilateral lending institutions advised developing countries, Nigeria inclusive, to adopt deregulation and privatization as part of reforms in their electricity sectors. The ideological basis of these reforms are traceable to neoliberalism. Neoliberalism is an ideology that believes in the supremacy of free market and strong non-interventionist competition law as against government ownership of the electricity market. This ideology became a state practice and a blue print for the deregulation and privatization of the electricity markets in many parts of the world. The blue print was used as a template for the privatization of the Nigerian electricity industry. In this wise, this paper, using documentary analysis and review of academic literatures, examines neoliberalism as an ideology and model of economic governance for the electricity supply industry in Nigeria. The paper examines the origin of the ideology, it features and principles and how it was used as the blue print in designing policies for electricity reforms in both developed and developing countries. The paper found out that there is gap between the ideology in theory and in practice because although the theory is rational in thinking it is difficult to be implemented in practice. The paper argues that the ideology has a mismatched effect and this has made its application in the electricity industry in many developing countries problematic and unsuccessful. In the case of Nigeria, the article argues that the template is also not working. The article concludes that the electricity sectors in Nigeria have failed to develop into competitive market for the benefit of consumers in line with the assumptions and promises of the ideology. The paper therefore recommends the democratization of the electricity sectors in Nigeria through a new system of public ownership as the solution to the failure of the neoliberal policies; but this requires the design of a more democratic and participatory system of ownership with communities and state governments in charge of the administration, running and operation of the sector.

Keywords: electricity, energy governance, neo-liberalism, regulation

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33181 Effect of Yeast Culture (Saccharomyces cerevisiae) Supplementation on Growth Performance, Nutrients Digestibility, and Blood Metabolites in Beetal Male Goats

Authors: Saeed Ahmed, Tamoor Abbas, M. Amir, M. S. Iqbal, D. Hussain

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This study was conducted to evaluate the effect of supplementation of different levels of yeast culture (Saccharomyces cerevisiae) in Beetal male goats diets on growth performance, digestibility of nutrients and selected blood metabolites. Another objective was to determine the inclusion level of yeast culture for optimal growth performance of Beetal male goats. Eighteen (n=18) Beetal male goats were randomly assigned to three total mixed ration treatments (n=6 goats/treatment): T1, T2 and T3 containing 0gm, 3gm and 6gm/day yeast culture (YC) mixed with total mixed ration (TMR). The diets were iso-nitrogenous and iso-caloric having crude protein 15.2% and ME 2.6Mcal/kg. The total duration of the experiment was 8 weeks. Beetal bucks were fed on TMR diets (T1, T2 and T3) having blend of oat silage, Lucerne hay and concentrate mixed with yeast culture (YC). Bucks were housed individually and feed was offered @ 4% of body weight on dry matter basis. Samples of fresh feed and refusal were collected twice weekly of moisture percentage using hot air oven. Data for daily dry matter intake, body weight gain, nutrient digestibility and selected blood metabolites were analyzed through one-way ANOVA technique under Complete randomised design (SAS Institute Inc, 2002-03). Results were declared significant at P≤0.05. Overall, DMI was not affected (P≥0.05) by dietary treatments. Body weight gain, digestibility of crude protein and crude fibre were improved. Blood glucose concentration was detected higher in the group having supplementation of yeast culture (YC) 6gm/day compared to other two dietary treatments. This study suggested the positive impact of inclusion of yeast culture (YC) up to 6gm/day in the TMR diet for optimal growth performance and digestibility of nutrients in Beetal male goats.

Keywords: yeast culture, growth performance, digestibility, beetle goat

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33180 Identification, Isolation and Characterization of Unknown Degradation Products of Cefprozil Monohydrate by HPTLC

Authors: Vandana T. Gawande, Kailash G. Bothara, Chandani O. Satija

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The present research work was aimed to determine stability of cefprozil monohydrate (CEFZ) as per various stress degradation conditions recommended by International Conference on Harmonization (ICH) guideline Q1A (R2). Forced degradation studies were carried out for hydrolytic, oxidative, photolytic and thermal stress conditions. The drug was found susceptible for degradation under all stress conditions. Separation was carried out by using High Performance Thin Layer Chromatographic System (HPTLC). Aluminum plates pre-coated with silica gel 60F254 were used as the stationary phase. The mobile phase consisted of ethyl acetate: acetone: methanol: water: glacial acetic acid (7.5:2.5:2.5:1.5:0.5v/v). Densitometric analysis was carried out at 280 nm. The system was found to give compact spot for cefprozil monohydrate (0.45 Rf). The linear regression analysis data showed good linear relationship in the concentration range 200-5.000 ng/band for cefprozil monohydrate. Percent recovery for the drug was found to be in the range of 98.78-101.24. Method was found to be reproducible with % relative standard deviation (%RSD) for intra- and inter-day precision to be < 1.5% over the said concentration range. The method was validated for precision, accuracy, specificity and robustness. The method has been successfully applied in the analysis of drug in tablet dosage form. Three unknown degradation products formed under various stress conditions were isolated by preparative HPTLC and characterized by mass spectroscopic studies.

Keywords: cefprozil monohydrate, degradation products, HPTLC, stress study, stability indicating method

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33179 Performance Evaluation of Arrival Time Prediction Models

Authors: Bin Li, Mei Liu

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Arrival time information is a crucial component of advanced public transport system (APTS). The advertisement of arrival time at stops can help reduce the waiting time and anxiety of passengers, and improve the quality of service. In this research, an experiment was conducted to compare the performance on prediction accuracy and precision between the link-based and the path-based historical travel time based model with the automatic vehicle location (AVL) data collected from an actual bus route. The research results show that the path-based model is superior to the link-based model, and achieves the best improvement on peak hours.

Keywords: bus transit, arrival time prediction, link-based, path-based

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33178 Modelling and Control of Electrohydraulic System Using Fuzzy Logic Algorithm

Authors: Hajara Abdulkarim Aliyu, Abdulbasid Ismail Isa

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This research paper studies electrohydraulic system for its role in position and motion control system and develops as mathematical model describing the behaviour of the system. The research further proposes Fuzzy logic and conventional PID controllers in order to achieve both accurate positioning of the payload and overall improvement of the system performance. The simulation result shows Fuzzy logic controller has a superior tracking performance and high disturbance rejection efficiency for its shorter settling time, less overshoot, smaller values of integral of absolute and deviation errors over the conventional PID controller at all the testing conditions.

Keywords: electrohydraulic, fuzzy logic, modelling, NZ-PID

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33177 The Difference in Basic Skills among Different Positional Players in Football

Authors: Habib Sk, Ashoke Kumar Biswas

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Football is a team game. Eleven players of each team are arranged in different positions of play to serve the specific task during a game situation. Some such basic positions in a soccer game are (i) goal keepers (ii) defenders (iii) midfielders and (iv) forwards. Irrespective of the position, it is required for all football players to learn and get skilled in basic soccer skills like passing, receiving, heading, throwing, dribbling, etc. The purpose of the study was to find out the difference in these basic soccer skills among positional players in football if any. A total of thirty-nine (39) teen aged football players between 13 to 19 years were selected from Hooghly district in West Bengal, India, as subjects. Out of them, there were seven (7) goal keepers, twelve (12) defenders, thirteen (13) midfielders, and seven (7) forwards. Passing, dribbling, tackling, heading, and receiving were the selected basic soccer skills. The performance of the subjects of different positional groups in different selected soccer skills was tested using a standard test for each. On the basis of results obtained through statistical analysis of data, following results were obtained: i) there was significant difference among the groups in passing, dribbling and heading but not in receiving; ii) the goal keepers and defenders were the weakest in all selected soccer skills; iii) midfielders were found better in receiving than other three skills of passing, dribbling and heading; and iv) the forward group of players was found to be the better in passing, dribbling and heading but weakest in receiving than other groups.

Keywords: performance, difference, skill, fundamental, soccer, position

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33176 Effect of Open-Ended Laboratory toward Learners Performance in Environmental Engineering Course: Case Study of Civil Engineering at Universiti Malaysia Sabah

Authors: N. Bolong, J. Makinda, I. Saad

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Laboratory activities have produced benefits in student learning. With current drives of new technology resources and evolving era of education methods, renewal status of learning and teaching in laboratory methods are in progress, for both learners and the educators. To enhance learning outcomes in laboratory works particularly in engineering practices and testing, learning via hands-on by instruction may not sufficient. This paper describes and compares techniques and implementation of traditional (expository) with open-ended laboratory (problem-based) for two consecutive cohorts studying environmental laboratory course in civil engineering program. The transition of traditional to problem-based findings and effect were investigated in terms of course assessment student feedback survey, course outcome learning measurement and student performance grades. It was proved that students have demonstrated better performance in their grades and 12% increase in the course outcome (CO) in problem-based open-ended laboratory style than traditional method; although in perception, students has responded less favorable in their feedback.

Keywords: engineering education, open-ended laboratory, environmental engineering lab

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33175 Advancements in Mathematical Modeling and Optimization for Control, Signal Processing, and Energy Systems

Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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33174 Application of Global Predictive Real Time Control Strategy to Improve Flooding Prevention Performance of Urban Stormwater Basins

Authors: Shadab Shishegar, Sophie Duchesne, Genevieve Pelletier

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Sustainability as one of the key elements of Smart cities, can be realized by employing Real Time Control Strategies for city’s infrastructures. Nowadays Stormwater management systems play an important role in mitigating the impacts of urbanization on natural hydrological cycle. These systems can be managed in such a way that they meet the smart cities standards. In fact, there is a huge potential for sustainable management of urban stormwater and also its adaptability to global challenges like climate change. Hence, a dynamically managed system that can adapt itself to instability of the environmental conditions is desirable. A Global Predictive Real Time Control approach is proposed in this paper to optimize the performance of stormwater management basins in terms of flooding prevention. To do so, a mathematical optimization model is developed then solved using Genetic Algorithm (GA). Results show an improved performance at system-level for the stormwater basins in comparison to static strategy.

Keywords: environmental sustainability, optimization, real time control, storm water management

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33173 Human Resource Management Functions; Employee Performance; Professional Health Workers In Public District Hospitals

Authors: Benjamin Mugisha Bugingo

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Healthcare staffhas been considered as asignificant pillar to the health care system. However, the contest of human resources for health in terms of the turnover of health workers in Uganda has been more distinct in the latest years. The objective of the paper, therefore, were to investigate the influence Role Human resource management functions in on employeeperformance of professional health workers in public district hospitals in Kampala. The study objectives were: to establish the effect of performance management function, financialincentives, non-financial incentives, participation, and involvement in the decision-making on the employee performance of professional health workers in public district hospitals in Kampala. The study was devised in the social exchange theory and the equity theory. This study adopted a descriptive research design using quantitative approaches. The study used a cross-sectional research design with a mixed-methods approach. With a population of 402 individuals, the study considered a sample of 252 respondents, including doctors, nurses, midwives, pharmacists, and dentists from 3 district hospitals. The study instruments entailed a questionnaire as a quantitative data collection tool and interviews and focus group discussions as qualitative data gathering tools. To analyze quantitative data, descriptive statistics were used to assess the perceived status of Human resource management functions and the magnitude of intentions to stay, and inferential statistics were used to show the effect of predictors on the outcome variable by plotting a multiple linear regression. Qualitative data were analyzed in themes and reported in narrative and verbatim quotes and were used to complement descriptive findings for a better understanding of the magnitude of the study variables. The findings of this study showed a significant and positive effect of performance management function, financialincentives, non-financial incentives, and participation and involvement in decision-making on employee performance of professional health workers in public district hospitals in Kampala. This study is expected to be a major contributor for the improvement of the health system in the country and other similar settings as it has provided the insights for strategic orientation in the area of human resources for health, especially for enhanced employee performance in relation with the integrated human resource management approach

Keywords: human resource functions, employee performance, employee wellness, profecial workers

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33172 Assessing Artificial Neural Network Models on Forecasting the Return of Stock Market Index

Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

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Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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33171 Enhancement of Mechanical Properties and Thermal Conductivity of Oil Palm Shell Lightweight Concrete Reinforced with High Performance Polypropylene Fibres

Authors: Leong Tatt Loh, Ming Kun Yew, Ming Chian Yew, Lip Huat Saw, Jing Han Beh, Siong Kang Lim, Foo Wei Lee

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Oil palm shell (OPS) is the solid waste product from the palm oil sector of the agricultural industry and can be used as alternative coarse aggregates to substitute depleting conventional raw materials. This research aims to investigate the incorporation of various high-performance polypropylene (HPP) fibres with different geometry to enhance the mechanical properties and thermal conductivity of OPS lightweight concrete. The effect of different volume fractions (Vf) (0.05%, 0.10% and 0.15%) were studied for each fibre. The results reveal that the effectiveness of HPP fibres to increase the compressive strength at later ages was more pronounced than at early age. It is found that the use of HPP fibres reinforced OPS lightweight concrete (LWC) induced the advantageous of improving mechanical properties (compressive strength, flexural strength and splitting tensile strength) and thermal conductivity. Hence, this HPP fibres is a promising alternative solution to compensate lower mechanical properties as well as contribute to energy efficiency building material in the construction industry.

Keywords: oil palm shell, high performance polypropylene fibre, lightweight concrete, mechanical properties, thermal conductivity

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33170 Performance of the SrSnO₃/SnO₂ Nanocomposite Catalyst on the Photocatalytic Degradation of Dyes

Authors: H. Boucheloukh, N. Aoun, M. Denni, A. Mahrouk, T. Sehili

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Perovskite materials with strontium alkaline earth metal have attracted researchers in photocatalysis. Thus, nanocomposite-based strontium has been synthesized by the sol-gel method, calciened at 700 °C, and characterized by different methods such as X-ray difraction (DRX), Fourier transformed infrared (FTIR), and diffuse relectance spectroscopy (DRS). After that, the photocatlytic performance of SrNO3/SnO2 has been tested under sunlight in an aqueous solution for two dyes methylene blue and congo-red. The results reveal that 70% of methylene blue has already been degraded after 45 minutes of exposure to sun light, while 80% of Congo red has been eliminated by adsorption on SrSnO₃/SnO₂ in 120 minutes of contact.

Keywords: congo-red, methylene blue, photocatalysis, perovskite

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33169 On the Blocked-off Finite-Volume Radiation Solutions in a Two-Dimensional Enclosure

Authors: Gyo Woo Lee, Man Young Kim

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The blocked-off formulations for the analysis of radiative heat transfer are formulated and examined in order to find the solutions in a two-dimensional complex enclosure. The final discretization equations using the step scheme for spatial differencing practice are proposed with the additional source term to incorporate the blocked-off procedure. After introducing the implementation for inactive region into the general discretization equation, three different problems are examined to find the performance of the solution methods.

Keywords: radiative heat transfer, Finite Volume Method (FVM), blocked-off solution procedure, body-fitted coordinate

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33168 Financial Performance Model of Local Economic Enterprises in Matalam, Cotabato

Authors: Kristel Faye Tandog

Abstract:

The State Owned Enterprise (SOE) or also called Public Enterprise (PE) has been playing a vital role in a country’s social and economic development. Following this idea, this study focused on the Factor Structures of Financial Performance of the Local Economic Enterprises (LEEs) namely: Food Court, Market, Slaughterhouse, and Terminal in Matalam, Cotabato. It aimed to determine the profile of the LEEs in terms of organizational structure, manner of creation, years in operation, source of initial operating requirements, annual operating budget, geographical location, and size or description of the facility. This study also included the different financial ratios of LEE that covered a five year period from Calendar Year 2009 to 2013. Primary data using survey questionnaire was administered to 468 respondents and secondary data were sourced out from the government archives and financial documents of the said LGU. There were 12 dominant factors identified namely: “management”, “enforcement of laws”, “strategic location”, “existence of non-formal competitors”, “proper maintenance”, “pricing”, “customer service”, “collection process”, “rentals and services”, “efficient use of resources”, “staffing”, and “timeliness and accuracy”. On the other hand, the financial performance of the LEE of Matalam, Cotabato using financial ratios needs reformatting. This denotes that refinement as to the following ratios: Cash Flow Indicator, Activity, Profitability and Growth is necessary. The cash flow indicator ratio showed difficulty in covering its debts in successive years. Likewise, the activity ratios showed that the LEE had not been effective in putting its investment at work. Moreover, profitability ratios revealed that it had operated in minimum capacity and had incurred net losses and thus, it had a weak profit performance. Furthermore, growth ratios showed that LEE had a declining growth trend particularly in net income.

Keywords: factor structures, financial performance, financial ratios, state owned enterprises

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33167 Integration of EEG and Motion Tracking Sensors for Objective Measure of Attention-Deficit Hyperactivity Disorder in Pre-Schoolers

Authors: Neha Bhattacharyya, Soumendra Singh, Amrita Banerjee, Ria Ghosh, Oindrila Sinha, Nairit Das, Rajkumar Gayen, Somya Subhra Pal, Sahely Ganguly, Tanmoy Dasgupta, Tanusree Dasgupta, Pulak Mondal, Aniruddha Adhikari, Sharmila Sarkar, Debasish Bhattacharyya, Asim Kumar Mallick, Om Prakash Singh, Samir Kumar Pal

Abstract:

Background: We aim to develop an integrated device comprised of single-probe EEG and CCD-based motion sensors for a more objective measure of Attention-deficit Hyperactivity Disorder (ADHD). While the integrated device (MAHD) relies on the EEG signal (spectral density of beta wave) for the assessment of attention during a given structured task (painting three segments of a circle using three different colors, namely red, green and blue), the CCD sensor depicts movement pattern of the subjects engaged in a continuous performance task (CPT). A statistical analysis of the attention and movement patterns was performed, and the accuracy of the completed tasks was analysed using indigenously developed software. The device with the embedded software, called MAHD, is intended to improve certainty with criterion E (i.e. whether symptoms are better explained by another condition). Methods: We have used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 years old pre-schoolers). During the painting of three segments of a circle using three distinct colors (red, green, and blue), absolute power for delta and beta EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task (CPT) i.e., separation of the various colored balls from one table to another. We have used our indigenously developed software for the statistical analysis to derive a scale for the objective assessment of ADHD. We have also compared our scale with clinical ADHD evaluation. Results: In a limited clinical trial with preliminary statistical analysis, we have found a significant correlation between the objective assessment of the ADHD subjects with that of the clinician’s conventional evaluation. Conclusion: MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Keywords: ADHD, CPT, EEG signal, motion sensor, psychometric test

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33166 The Impact of Music on Social Identity Formation and Intergroup Relations in American-Born Korean Skaters in 2018 Winter Olympics

Authors: Sehwan Kim, Jepkorir Rose Chepyator Thomson

Abstract:

Music provides opportunities to affirm social identities and facilitate the internalization of one’s identity. The purpose of this study was to examine the role of music in breaking down boundaries between the in-group and out-of-group sport participants. Social identity theory was used to guide an understanding of two American-born South Korean skaters—Yura Min and Alexander Gamelin—who used a Korean representative traditional folk song, Arirang, at the 2018 Winter Olympics. This was an interpretive case study that focused on 2018 Winter Olympic participants whose performance and use of music was understood through the lenses of Koreans. Semi-structured interviews were conducted with 15 Korean audiences who watched two American-born South Korean skaters’ performances. Data analysis involved the determination of themes in the data collected. The findings of this study are as follows: First Koreans viewed the skaters as the out-group based on ethnic appearances and stereotypes. Second, Koreans’ inter-group bias against the skaters was meditated after Koreans watched the skaters as they used Arirang song in performance. Implications for this study include the importance of music as an instrument of unity across diverse populations, including intergroup relations. Music can also offer ways to understand people’s cultures and bridge gaps between age and gender across categories of naturalization.

Keywords: impact of music, intergroup relations, naturalized athletes, social identity theory

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33165 The Impact of E-Learning on the Performance of History Learners in Eswatini General Certificate of Secondary Education

Authors: Joseph Osodo, Motsa Thobekani Phila

Abstract:

The study investigated the impact of e-learning on the performance of history learners in Eswatini general certificate of secondary education in the Manzini region of Eswatini. The study was guided by the theory of connectivism. The study had three objectives which were to find out the significance of e-learning during the COVID-19 era in learning History subject; challenges faced by history teachers’ and learners’ in e-learning; and how the challenges were mitigated. The study used a qualitative research approach and descriptive research design. Purposive sampling was used to select eight History teachers and eight History learners from four secondary schools in the Manzini region. Data were collected using face to face interviews. The collected data were analyzed and presented in thematically. The findings showed that history teachers had good knowledge on what e-learning was, while students had little understanding of e-learning. Some of the forms of e-learning that were used during the pandemic in teaching history in secondary schools included TV, radio, computer, projectors, and social media especially WhatsApp. E-learning enabled the continuity of teaching and learning of history subject. The use of e-learning through the social media was more convenient to the teacher and the learners. It was concluded that in some secondary school in the Manzini region, history teacher and learners encountered challenges such as lack of finances to purchase e-learning gadgets and data bundles, lack of skills as well as access to the Internet. It was recommended that History teachers should create more time to offer additional learning support to students whose performance was affected by the COVID-19 pandemic effects.

Keywords: e-learning, performance, COVID-19, history, connectivism

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33164 Evaluation of Critical Rate in Mature Oil Field with Dynamic Oil Rim Fluid Contacts in the Niger Delta

Authors: Stanley Ibuchukwu Onwukwe

Abstract:

Most reservoir in mature oil fields are vulnerable to challenges of water and/or gas coning as the size of their oil column reduces due to long period of oil production. These often result to low oil production and excessive water and/or gas production. Since over 50 years of oil production in the Niger delta, it is apparent that most of the oil fields in the region have reached their mature stages, thereby susceptible to coning tendencies. As a result of these, a good number of wells have been shut-in and abandoned, with significant amount of oil left unproduced. Analysis of the movement of fluid contacts in the reservoir is a significant aspect of reservoir studies and can assist in the management of coning tendencies and production performance of reservoirs in a mature field. This study, therefore, seeks to evaluate the occurrence of coning through the movement of fluid contacts (GOC and OWC) and determine the critical rate for controlling coning tendencies in mature oil field. This study applies the principle of Nodal analysis to calibrate the thin oil column of a reservoir of a mature field, and was graphically evaluated using the Joshi’s equation of critical rate for gas-oil system and oil-water system respectively. A representative Proxy equation was developed and sensitivity analysis carried out to determine the trend of critical rate as the oil column is been depleted. The result shows the trend in the movement of the GOC and OWC, and the critical rate, beyond which will result in excessive water and gas production, resulting to decreasing oil production from the reservoir. This result of this study can be used as a first pass assessment in the development of mature oil field reservoirs anticipated to experience water and/or gas coning during production.

Keywords: coning, fluid contact movement, mature oil field, oil production

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33163 A Dynamic Ensemble Learning Approach for Online Anomaly Detection in Alibaba Datacenters

Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

Abstract:

Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

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33162 Implementation of Human Resource Management in Greek Law Enforcement Agencies

Authors: Konstantinos G. Papaioannou, Panagiotis K. Serdaris

Abstract:

This study, examines the level of implementation of Human Resource Management (HRM) activities in law enforcement agencies in Greece. Recognizing that HRM is crucial for maximizing organizational performance, the study aims to evaluate its application within Greek law enforcement. A quantitative-descriptive survey was conducted, involving 996 executives from Greek Law Enforcement Agencies (477 from the Hellenic Police and 519 from the Hellenic Coast Guard), through random sampling. The survey, revealed significant concerns regarding the minimal implementation of HRM practices, in both agencies. The findings indicate that HRM practices, such as HR planning, recruitment, job position, selection, training and development, personnel management, compensation, labor relations and health and safety, are minimally applied. Neither the Hellenic Police nor the Hellenic Coast Guard appears to follow a comprehensive HRM plan. The study, contributes both theoretically and practically by highlighting the lack of HRM implementation in these agencies. The data suggest that by adopting strategic HRM practices, these organizations can enhance personnel performance and better fulfill their societal roles. Future research should extend to law enforcement agencies in other countries to draw more representative conclusion.

Keywords: coastguard, human resources management, law enforcement agencies, performance management, police

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33161 The Effect of Hydrogen on Performance and Emissions of a Methanol Si-Engine at Part Load

Authors: Junaid Bin Aamir, Ma Fanhua

Abstract:

Methanol and hydrogen are the most suitable alternative fuel resources for the existing and future internal combustion engines. This paper experimentally examined the effects of hydrogen addition on the performance and emission characteristics of a spark-ignition engine fueled with methanol at part load conditions. The experiments were carried out for various engine speeds and loads. Hydrogen-rich syngas was used to enhance the performance of the test engine. It was formed by catalytic dissociation of methanol itself, and volumetric hydrogen fraction in syngas was about 67%. A certain amount of syngas dissociated from methanol was injected into the intake manifold in each engine cycle, and the low heating value (LHV) of hydrogen-rich syngas used was 4% of methanol in each cycle. Both the fuels were injected separately using port fuel injectors. The results showed that brake thermal efficiency of the engine was enhanced by 3-5% with hydrogen addition, while brake specific fuel consumption and exhaust gas temperature were reduced. There was a significant reduction (90-95%) in THC and (35-50%) in CO emissions at the exhaust. NOx emissions from hydrogen blended methanol increased slightly (10-15%), but they can be reduced by using lean fuel-air mixture to keep the cylinder temperature low.

Keywords: hydrogen, methanol, alternative fuel, emissions, spark ignition engines

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