Search results for: statistical machine learning

Authors: Ya-Ting Carolyn Yang, Ping-Han Cheng, Shi-Hui Gilbert Chang, Terry Yuan-Fang Chen, Chih-Chieh Li

Abstract:

Nanotechnology is widely applied in various areas so professionals in the related fields have to know more than nano knowledge. In the study, we focus on adopting ICT-assisted PBL in college general education to foster professionals who possess multiple abilities. The research adopted a pretest and posttest quasi-experimental design. The control group received traditional instruction, and the experimental group received ICT-assisted PBL instruction. Descriptive statistics will be used to describe the means, standard deviations, and adjusted means for the tests between the two groups. Next, analysis of covariance (ANCOVA) will be used to compare the final results of the two research groups after 6 weeks of instruction. Statistics gathered in the end of the research can be used to make contrasts. Therefore, we will see how different teaching strategies can improve students’ understanding about nanotechnology and learning skills.

Keywords: Nanotechnology, science education, project-based learning, information and communication technology.

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Authors: Ahmed Abbas Helmy, M. R. M. Rizk, Mohamed El-Sayed

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A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.

Keywords: Adaptive control, model predictive control, dynamic matrix control, online model identification

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Authors: M. Sedighizadeh, A. Rezazadeh

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Wind turbines with double output induction generators can operate at variable speed permitting conversion efficiency maximization over a wide range of wind velocities. This paper presents the performance analysis of a wind driven double output induction generator (DOIG) operating at varying shafts speed. A periodic transient state analysis of DOIG equipped with two converters is carried out using a hybrid induction machine model. This paper simulates the harmonic content of waveforms in various points of drive at different speeds, based on the hybrid model (dqabc). Then the sinusoidal and trapezoidal pulse-width–modulation control techniques are used in order to improve the power factor of the machine and to weaken the injected low order harmonics to the supply. Based on the frequency spectrum, total harmonics distortion, distortion factor and power factor. Finally advantages of sinusoidal and trapezoidal pulse width modulation techniques are compared.

Keywords: DOIG, Harmonic Analysis, Wind.

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Authors: U. Bottigli, R.Chiarucci, B. Golosio, G.L. Masala, P. Oliva, S.Stumbo, D.Cascio, F. Fauci, M. Glorioso, M. Iacomi, R. Magro, G. Raso

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Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.

Keywords: Neural Networks, K-Nearest Neighbours, Support Vector Machine, Computer Aided Detection

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Authors: J. Georgiou, K. Dimitropoulos, A. Manitsaris

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Simulations play a major role in education not only because they provide realistic models with which students can interact to acquire real world experiences, but also because they constitute safe environments in which students can repeat processes without any risk in order to perceive easier concepts and theories. Virtual reality is widely recognized as a significant technological advance that can facilitate learning process through the development of highly realistic 3D simulations supporting immersive and interactive features. The objective of this paper is to analyze the influence of virtual reality-s use in chemistry instruction as well as to present an integrated web-based learning environment for the simulation of chemical experiments. The proposed application constitutes a cost-effective solution for both schools and universities without appropriate infrastructure and a valuable tool for distance learning and life-long education in chemistry. Its educational objectives are the familiarization of students with the equipment of a real chemical laboratory and the execution of virtual volumetric analysis experiments with the active participation of students.

Keywords: Chemistry, simulations, experiments, virtual reality.

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Authors: Ahmad Ghayoumi, Mehdi Ghayoumi

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Intelligent schools are those which use IT devices and technologies as media software, hardware and networks to improve learning process. On the other hand management improvement is best described as the process from which managers learn and improve their skills not only to benefit themselves but also their employing organizations Here, we present a model Management improvement System that has been applied on some schools and have made strict improvement.

Keywords: Intelligent school, Management development system, Learning station, Teaching station

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Authors: A. Pedram, M. R. Jamali, T. Pedram, S. M. Fakhraie, C. Lucas

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Local Linear Neuro-Fuzzy Models (LLNFM) like other neuro- fuzzy systems are adaptive networks and provide robust learning capabilities and are widely utilized in various applications such as pattern recognition, system identification, image processing and prediction. Local linear model tree (LOLIMOT) is a type of Takagi-Sugeno-Kang neuro fuzzy algorithm which has proven its efficiency compared with other neuro fuzzy networks in learning the nonlinear systems and pattern recognition. In this paper, a dedicated reconfigurable and parallel processing hardware for LOLIMOT algorithm and its applications are presented. This hardware realizes on-chip learning which gives it the capability to work as a standalone device in a system. The synthesis results on FPGA platforms show its potential to improve the speed at least 250 of times faster than software implemented algorithms.

Keywords: LOLIMOT, hardware, neurofuzzy systems, reconfigurable, parallel.

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Authors: Ahmad Ghayoumi, Mehdi Ghayoumi

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Intelligent schools are those which use IT devices and technologies as media software, hardware and networks to improve learning process. On the other hand Strategic management is a field that deals with the major intended and emergent initiatives taken by general managers on behalf of owners, involving utilization of resources, to enhance the performance of firms in their external environments. Here, we present a model Strategic Management System that has been applied on some schools and have made strict improvement.

Keywords: Intelligent school, Strategic management system, Learning station, Teaching station

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Authors: Ahmed Shuhaiber

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The explosion of the World Wide Web and the electronic trend of university teaching have transformed the learning style to become more learner-centered, which has popularized the digital delivery of mediated lectures as an alternative or an adjunct to traditional lectures. Despite its potential and popularity, virtual lectures have not been adopted yet in Jordanian universities. This research aimed to fill this gap by studying the factors that influence students’ willingness to accept virtual lectures in one Jordanian University. A quantitative approach was followed, by obtaining 216 survey responses and statistically applying the UTAUT model with some modifications. Results revealed that performance expectancy, effort expectancy, social influences, and self-efficacy could significantly influence students’ attitudes towards virtual lectures. Additionally, Facilitating conditions and attitudes towards virtual lectures were found with significant influence on students’ intention to take virtual lectures. Research implications and future work were specified afterwards.

Keywords: E-Learning, Student willingness, UTAUT, Virtual Lectures, Web-based learning systems.

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Authors: Ahmet Ok, Banu Yücel Toy

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Promoting critical thinking (CT) in an educational setting has been appraised in order to enhance learning and intellectual skills. In this study, a pedagogical course in a vocational teacher education program in Turkey was designed by integrating CT skill-based strategies/activities into the course content and CT skills were means leading to intended course objectives. The purpose of the study was to evaluate the importance of the course objectives, the attainment of the objectives, and the effectiveness of teachinglearning strategies/activities from prospective teachers- points of view. The results revealed that although the students mostly considered the course objectives important, they did not feel competent in the attainment of all objectives especially in those related to the main topic of Learning and those requiring higher order thinking skills. On the other hand, the students considered the course activities effective for learning and for the development of thinking skills, especially, in interpreting, comparing, questioning, contrasting, and forming relationships.

Keywords: Critical thinking, critical thinking-based instruction, higher order thinking skills, teacher education

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Authors: N. Ismail, O. Thammajinda, U. Thongpanya

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Games-based learning (GBL) has become increasingly important in teaching and learning. This paper explains the first two phases (analysis and design) of a GBL development project, ending up with a prototype design based on students’ and teachers’ perceptions. The two phases are part of a full cycle GBL project aiming to help secondary school students in Thailand in their study of Comprehensive Sex Education (CSE). In the course of the study, we invited 1,152 students to complete questionnaires and interviewed 12 secondary school teachers in focus groups. This paper found that GBL can serve students in their learning about CSE, enabling them to gain understanding of their sexuality, develop skills, including critical thinking skills and interact with others (peers, teachers, etc.) in a safe environment. The objectives of this paper are to outline the development of GBL variables from the research question(s) into the developers’ flow chart, to be responsive to the GBL beneficiaries’ preferences and expectations, and to help in answering the research questions. This paper details the steps applied to generate GBL variables that can feed into a game flow chart to develop a GBL prototype. In our approach, we detailed two models: (1) Game Elements Model (GEM) and (2) Game Object Model (GOM). There are three outcomes of this research – first, to achieve the objectives and benefits of GBL in learning, game design has to start with the research question(s) and the challenges to be resolved as research outcomes. Second, aligning the educational aims with engaging GBL end users (students) within the data collection phase to inform the game prototype with the game variables is essential to address the answer/solution to the research question(s). Third, for efficient GBL to bridge the gap between pedagogy and technology and in order to answer the research questions via technology (i.e. GBL) and to minimise the isolation between the pedagogists “P” and technologist “T”, several meetings and discussions need to take place within the team.

Keywords: Games-based learning, design, engagement, pedagogy, preferences, prototype, variables.

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Authors: Jānis Zuters

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There are a lot of extensions made to the classic model of multi-layer perceptron (MLP). A notable amount of them has been designed to hasten the learning process without considering the quality of generalization. The paper proposes a new MLP extension based on exploiting topology of the input layer of the network. Experimental results show the extended model to improve upon generalization capability in certain cases. The new model requires additional computational resources to compare to the classic model, nevertheless the loss in efficiency isn-t regarded to be significant.

Keywords: Learning algorithm, multi-layer perceptron, topology.

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Authors: Muhammad Ridhuan Tony Lim Abdullah, Zulqarnain Abu Bakar, Razol Mahari Ali, Ibrahima Faye, Hilmi Hasan

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This paper describes a research project on Year 3 primary school students in Malaysia in their use of computer-based video game to enhance learning of multiplication facts (tables) in the Mathematics subject. This study attempts to investigate whether video games could actually contribute to positive effect on children-s learning or otherwise. In conducting this study, the researchers assume a neutral stand in the investigation as an unbiased outcome of the study would render reliable response to the impact of video games in education which would contribute to the literature of technology-based education as well as impact to the pedagogical aspect of formal education. In order to conduct the study, a subject (Mathematics) with a specific topic area in the subject (multiplication facts) is chosen. The study adopts a causal-comparative research to investigate the impact of the inclusion of a computer-based video game designed to teach multiplication facts to primary level students. Sample size is 100 students divided into two i.e., A: conventional group and B conventional group aided by video games. The conventional group (A) would be taught multiplication facts (timetables) and skills conventionally. The other group (B) underwent the same lessons but with supplementary activity: a computer-based video game on multiplication which is called Timez-Attack. Analysis of marks accrued from pre-test will be compared to post- test using comparisons of means, t tests, and ANOVA tests to investigate the impact of computer games as an added learning activity. The findings revealed that video games as a supplementary activity to classroom learning brings significant and positive effect on students- retention and mastery of multiplication tables as compared to students who rely only upon formal classroom instructions.

Keywords: Technology for education, Gaming for education, Computer-based video games, Cognitive learning

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Authors: C. W. Kan

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Cotton fibre is a commonly-used natural fibre because of its good fibre strength, high moisture absorption behaviour and minimal static problems. However, one of the main drawbacks of cotton fibre is wrinkling after washing, which is recently overcome by wrinkle-resistant treatment. 1,2,3,4-butanetetracarboxylic acid (BTCA) could improve the wrinkle-resistant properties of cotton fibre. Although the BTCA process is an effective method for wrinkle resistant application of cotton fabrics, reduced fabric strength was observed after treatment. Therefore, this paper would explore the use of atmospheric pressure plasma treatment under different discharge powers as a pretreatment process to enhance the application of BTCA process on cotton fabric without generating adverse effect. The aim of this study is to provide learning information to the users to know how the atmospheric pressure plasma treatment can be incorporated in textile finishing process with positive impact.

Keywords: Learning materials, atmospheric pressure plasma treatment, cotton, wrinkle-resistant, BTCA.

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Authors: Mohammed A. Gharawi, Majed M. Khoja

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This paper is a report on the findings of a study conducted at the Institute of Public Administration (IPA) in Saudi Arabia. The paper applied both qualitative and quantitative approaches to assess the levels of basic computer applications’ skills among students enrolled in the preparatory programs of the institution. Qualitative data have been collected from semi-structured interviews with the instructors who have previously been assigned to teach Introduction to information technology courses. Quantitative data were collected by executing a self-report questionnaire and a written statistical test. Three hundred eighty enrolled students responded to the questionnaire and one hundred forty two accomplished the statistical test. The results indicate the lack of necessary skills to deal with computer applications among most of the students who are enrolled in the IPA’s preparatory programs.

Keywords: Assessment, Computer Applications, Computer Literacy, Institute of Public Administration, Saudi Arabia.

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.

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Authors: Hae Young Lee, Tae Ho Cho

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In many sensor network applications, sensor nodes are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the node's cryptographic keys. False sensing report can be injected through compromised nodes, which can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false reports during the forwarding process. In this scheme, the choice of a security threshold value is important since it trades off detection power and overhead. In this paper, we propose a fuzzy logic for determining a security threshold value in the SEF based sensor networks. The fuzzy logic determines a security threshold by considering the number of partitions in a global key pool, the number of compromised partitions, and the energy level of nodes. The fuzzy based threshold value can conserve energy, while it provides sufficient detection power.

Keywords: Fuzzy logic, security, sensor network.

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Authors: Wasiu O. Ajagbe, Habeeb O. Hamzat, Waris A. Adebisi

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Structural failures occur due to a number of reasons. These may include under design, poor workmanship, substandard materials, misleading laboratory tests and lots more. Reinforcing steel bar is an important construction material, hence its properties must be accurately known before being utilized in construction. Understanding this property involves carrying out mechanical tests prior to design and during construction to ascertain correlation using steel testing machine which is usually not readily available due to the location of project. This study was conducted to determine the reliability of reinforcing steel testing machines. Reconnaissance survey was conducted to identify laboratories where yield and ultimate tensile strengths tests can be carried out. Six laboratories were identified within Ibadan and environs. However, only four were functional at the time of the study. Three steel samples were tested for yield and tensile strengths, using a steel testing machine, at each of the four laboratories (LM, LO, LP and LS). The yield and tensile strength results obtained from the laboratories were compared with the manufacturer’s specification using a reliability analysis programme. Structured questionnaire was administered to the operators in each laboratory to consider their impact on the test results. The average value of manufacturers’ tensile strength and yield strength are 673.7 N/mm² and 559.7 N/mm² respectively. The tensile strength obtained from the four laboratories LM, LO, LP and LS are given as 579.4, 652.7, 646.0 and 649.9 N/mm² respectively while their yield strengths respectively are 453.3, 597.0, 550.7 and 564.7 N/mm². Minimum tensile to yield strength ratio is 1.08 for BS 4449: 2005 and 1.15 for ASTM A615. Tensile to yield strength ratio from the four laboratories are 1.28, 1.09, 1.17 and 1.15 for LM, LO, LP and LS respectively. The tensile to yield strength ratio shows that the result obtained from all the laboratories meet the code requirements used for the test. The result of the reliability test shows varying level of reliability between the manufacturers’ specification and the result obtained from the laboratories. Three of the laboratories; LO, LS and LP have high value of reliability with the manufacturer i.e. 0.798, 0.866 and 0.712 respectively. The fourth laboratory, LM has a reliability value of 0.100. Steel test should be carried out in a laboratory using the same code in which the structural design was carried out. More emphasis should be laid on the importance of code provisions.

Keywords: Reinforcing steel bars, reliability analysis, tensile strength, universal testing machine, yield strength.

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: Artificial Neural Network, Taguchi Method, Real Estate Valuation Model.

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Authors: Pirada Techaratpong

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This qualitative research has 2 objectives: to study marketing management of the cultural learning center in Suansunandha Rajabhat University and to suggest guidelines to improve its marketing management. This research is based on a case study of the Arts and Culture Office in Suansunandha Rajabhat University, Bangkok. This research found the Art and Culture Office has no formal marketing management. However, the marketing management is partly covered in the overall business plan, strategic plan, and action plan. The process can be divided into 5 stages. The marketing concept has long been introduced to its policy but not apparently put into action due to inflexible system. Some gaps are found in the process. The research suggests the Art and Culture Office implement the concept of marketing orientation, meeting the needs and wants of its target customers and adapt to the changing situation. Minor guidelines for improvement are provided.

Keywords: Marketing, management, museum, cultural learning center.

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Authors: Pan Long, Bi Dongjie, Li Xifeng, Xie Yongle

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The near-field synthetic aperture radar (SAR) imaging is an advanced nondestructive testing and evaluation (NDT&E) technique. This paper investigates the complex-valued signal processing related to the near-field SAR imaging system, where the measurement data turns out to be noncircular and improper, meaning that the complex-valued data is correlated to its complex conjugate. Furthermore, we discover that the degree of impropriety of the measurement data and that of the target image can be highly correlated in near-field SAR imaging. Based on these observations, A modified generalized sparse Bayesian learning algorithm is proposed, taking impropriety and noncircularity into account. Numerical results show that the proposed algorithm provides performance gain, with the help of noncircular assumption on the signals.

Keywords: Complex-valued signal processing, synthetic aperture radar (SAR), 2-D radar imaging, compressive sensing, Sparse Bayesian learning.

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

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The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter.

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Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva

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Every year, fog formation over the Indo-Gangetic Plains (IGPs) of Indian region during the winter months of December and January is believed to create numerous hazards, inconvenience, and economic loss to the inhabitants of this densely populated region of Indian subcontinent. The aim of the paper is to analyze the spatial and temporal variability of winter fog over IGPs. Long term ground observations of visibility and other meteorological parameters (1971-2010) have been analyzed to understand the formation of fog phenomena and its relevance during the peak winter months of January and December over IGP of India. In order to examine the temporal variability, time series and trend analysis were carried out by using the Mann-Kendall Statistical test. Trend analysis performed by using the Mann-Kendall test, accepts the alternate hypothesis with 95% confidence level indicating that there exists a trend. Kendall tau’s statistics showed that there exists a positive correlation between time series and fog frequency. Further, the Theil and Sen’s median slope estimate showed that the magnitude of trend is positive. Magnitude is higher during January compared to December for the entire IGP except in December when it is high over the western IGP. Decade wise time series analysis revealed that there has been continuous increase in fog days. The net overall increase of 99 % was observed over IGP in last four decades. Diurnal variability and average daily persistence were computed by using descriptive statistical techniques. Geo-statistical analysis of fog was carried out to understand the spatial variability of fog. Geo-statistical analysis of fog revealed that IGP is a high fog prone zone with fog occurrence frequency of more than 66% days during the study period. Diurnal variability indicates the peak occurrence of fog is between 06:00 and 10:00 local time and average daily fog persistence extends to 5 to 7 hours during the peak winter season. The results would offer a new perspective to take proactive measures in reducing the irreparable damage that could be caused due to changing trends of fog.

Keywords: Fog, climatology, Mann-Kendall test, trend analysis, spatial variability, temporal variability, visibility.

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Authors: Sh. Yasini, M. B. Naghibi-Sistani, A. Karimpour

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This paper employs a new approach to regulate the blood glucose level of type I diabetic patient under an intensive insulin treatment. The closed-loop control scheme incorporates expert knowledge about treatment by using reinforcement learning theory to maintain the normoglycemic average of 80 mg/dl and the normal condition for free plasma insulin concentration in severe initial state. The insulin delivery rate is obtained off-line by using Qlearning algorithm, without requiring an explicit model of the environment dynamics. The implementation of the insulin delivery rate, therefore, requires simple function evaluation and minimal online computations. Controller performance is assessed in terms of its ability to reject the effect of meal disturbance and to overcome the variability in the glucose-insulin dynamics from patient to patient. Computer simulations are used to evaluate the effectiveness of the proposed technique and to show its superiority in controlling hyperglycemia over other existing algorithms

Keywords: Insulin Delivery rate, Q-learning algorithm, Reinforcement learning, Type I diabetes.

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Authors: Sivapalan, S., Subramaniam, G., Clifford, M.J., Balbir Singh, M.S., Abdullah, A

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Higher education has an important role to play in advocating environmentalism. Given this responsibility, the goal of higher education should therefore be to develop graduates with the knowledge, skills and values related to environmentalism. However, research indicates that there is a lack of consciousness amongst graduates on the need to be more environmentally aware, especially when it comes to applying the appropriate knowledge and skills related to environmentalism. Although institutions of higher learning do include environmental parameters within their undergraduate and postgraduate academic programme structures, the environmental boundaries are usually confined to specific engineering majors within an engineering programme. This makes environmental knowledge, skills and values exclusive to certain quarters of the higher education system. The incorporation of environmental literacy within higher education institutions as a whole is of utmost pertinence if a nation-s human capital is to be nurtured to become change agents for the preservation of environment. This paper discusses approaches that can be adapted by institutions of higher learning to include environmental literacy within the graduate-s higher learning experience.

Keywords: Higher education, engineering education, environmental literacy, Malaysia.

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Authors: Abbas Al-Refaie

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This paper aims at improving the performance of the tableting process using statistical quality control and fuzzy goal programming. The tableting process was studied. Statistical control tools were used to characterize the existing process for three critical responses including the averages of a tablet’s weight, hardness, and thickness. At initial process factor settings, the estimated process capability index values for the tablet’s averages of weight, hardness, and thickness were 0.58, 3.36, and 0.88, respectively. The L₉ array was utilized to provide experimentation design. Fuzzy goal programming was then employed to find the combination of optimal factor settings. Optimization results showed that the process capability index values for a tablet’s averages of weight, hardness, and thickness were improved to 1.03, 4.42, and 1.42, respectively. Such improvements resulted in significant savings in quality and production costs.

Keywords: Fuzzy goal programming, control charts, process capability, tablet optimization.

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Authors: Hikmat A. M. Abd-El-Jaber, Tengku M. T. Sembok

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The information on the Web increases tremendously. A number of search engines have been developed for searching Web information and retrieving relevant documents that satisfy the inquirers needs. Search engines provide inquirers irrelevant documents among search results, since the search is text-based rather than semantic-based. Information retrieval research area has presented a number of approaches and methodologies such as profiling, feedback, query modification, human-computer interaction, etc for improving search results. Moreover, information retrieval has employed artificial intelligence techniques and strategies such as machine learning heuristics, tuning mechanisms, user and system vocabularies, logical theory, etc for capturing user's preferences and using them for guiding the search based on the semantic analysis rather than syntactic analysis. Although a valuable improvement has been recorded on search results, the survey has shown that still search engines users are not really satisfied with their search results. Using ontologies for semantic-based searching is likely the key solution. Adopting profiling approach and using ontology base characteristics, this work proposes a strategy for finding the exact meaning of the query terms in order to retrieve relevant information according to user needs. The evaluation of conducted experiments has shown the effectiveness of the suggested methodology and conclusion is presented.

Keywords: information retrieval, user profiles, semantic Web, ontology, search engine.

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Authors: Jaebum Park, Vladimir M. Zatsiorsky

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The performance results of the athletes competed in the 1988-2008 Olympic Games were analyzed (n = 166). The data were obtained from the IAAF official protocols. In the principal component analysis, the first three principal components explained 70% of the total variance. In the 1st principal component (with 43.1% of total variance explained) the largest factor loadings were for 100m (0.89), 400m (0.81), 110m hurdle run (0.76), and long jump (–0.72). This factor can be interpreted as the 'sprinting performance'. The loadings on the 2nd factor (15.3% of the total variance) presented a counter-intuitive throwing-jumping combination: the highest loadings were for throwing events (javelin throwing 0.76; shot put 0.74; and discus throwing 0.73) and also for jumping events (high jump 0.62; pole vaulting 0.58). On the 3rd factor (11.6% of total variance), the largest loading was for 1500 m running (0.88); all other loadings were below 0.4.

Keywords: Decathlon, principal component analysis, Olympic Games, multivariate statistical analysis.

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Authors: Chad Goldsworthy, B. Rajeswari Matam

Abstract:

The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: Convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation.

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Authors: Joel S. Mtebe, Aron Kondoro, Mussa M. Kissaka, Elia Kibga

Abstract:

Sub-Saharan Africa is described as the second fastest growing in mobile phone penetration in the world more than in the United States or the European Union. Mobile phones have been used to provide a lot of opportunities to improve people’s lives in the region such as in banking, marketing, entertainment, and paying for various bills such as water, TV, and electricity. However, the potential of mobile phones to enhance teaching and learning has not been explored. This study presents an experience of developing and delivering SMS based quiz questions used to assess mastery of subject content knowledge of science and mathematics secondary school teachers in Tanzania. The SMS quizzes were used as a follow up support mechanism to 500 teachers who participated in a project to upgrade subject content knowledge of teachers in science and mathematics subjects in Tanzania. Quizzes of 10-15 questions were sent to teachers each week for 8 weeks and the results were analyzed using SPSS. Results show that teachers who participated in chemistry and biology subjects have better performance compared to those who participated in mathematics and physics subjects. Teachers reported some challenges that led to poor performance, This research has several practical implications for those who are implementing or planning to use mobile phones in teaching and learning especially in rural secondary schools in sub-Saharan Africa.

Keywords: Mobile learning, e-learning, educational technologies, SMS, secondary education, assessment.

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