Search results for: Azure machine learning.

Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

Abstract:

The purpose of this research aims to discover the knowledge for analysis student motivation behavior on e-Learning based on Data Mining Techniques, in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The data mining techniques was applied in this research including association rules, classification techniques. The results showed that using data mining technique can indicate the important variables that influence the student motivation behavior on e-Learning.

Keywords: association rule mining, classification techniques, e- Learning, Moodle log Motivation Behavior

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Authors: Osama Abufanas

Abstract:

This paper aims to build an Arabic learning language tool using Flash CS4 professional software with action script 3.0 programming language, based on the Computer Aided Language Learning (CALL) material. An extra intention is to provide a primary tool and focus on learning Arabic as a second language to adults. It contains letters, words and sentences at the first stage. This includes interactive practices, which evaluates learners’ comprehension of the Arabic language. The system was examined and it was found that the language structure was correct and learners were satisfied regarding the system tools. The learners found the system tools efficient and simple to use. The paper's main conclusion illustrates that CALL can be applied without any hesitation to second language learners

Keywords: Arabic Language, Computer Aided Language Learning (CALL), Learner, Material.

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Authors: Abdullah Abu-Tineh, Carol Murphy, Nigel Calder, Nasser Mansour

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This paper reports on an aspect of e-learning in developing inquiry-based learning (IBL). We present data on the views of teachers and students in Qatar following a professional development programme intended to help teachers implement IBL in their science and mathematics classrooms. Key to this programme was the use of WebQuests. Views of the teachers and students suggested that WebQuests helped students to develop technical skills, work collaboratively and become independent in their learning. The use of WebQuests also enabled a combination of digital and non-digital tools that helped students connect ideas and enhance their understanding of topics.

Keywords: Digital technology, inquiry-based learning, mathematics and science education, professional development.

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Authors: Gowrishankar Kasilingam

Abstract:

This paper proposes a swarm intelligence method that yields optimal Proportional-Integral-Derivative (PID) Controller parameters of a power system stabilizer (PSS) in a single machine infinite bus system. The proposed method utilizes the Particle Swarm Optimization (PSO) algorithm approach to generate the optimal tuning parameters. The paper is modeled in the MATLAB Simulink Environment to analyze the performance of a synchronous machine under several load conditions. At the same operating point, the PID-PSS parameters are also tuned by Ziegler-Nichols method. The dynamic performance of proposed controller is compared with the conventional Ziegler-Nichols method of PID tuning controller to demonstrate its advantage. The analysis reveals the effectiveness of the proposed PSO based PID controller.

Keywords: Particle Swarm Optimization, PID Controller, Power System Stabilizer.

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Authors: Jameela Ali Alkrimi, Loay E. George, Azizah Suliman, Abdul Rahim Ahmad, Karim Al-Jashamy

Abstract:

Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. Anemia is a lack of RBCs is characterized by its level compared to the normal hemoglobin level. In this study, a system based image processing methodology was developed to localize and extract RBCs from microscopic images. Also, the machine learning approach is adopted to classify the localized anemic RBCs images. Several textural and geometrical features are calculated for each extracted RBCs. The training set of features was analyzed using principal component analysis (PCA). With the proposed method, RBCs were isolated in 4.3secondsfrom an image containing 18 to 27 cells. The reasons behind using PCA are its low computation complexity and suitability to find the most discriminating features which can lead to accurate classification decisions. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network RBFNN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained within short time period, and the results became better when PCA was used.

Keywords: Red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC.

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Authors: Koyu Chinen, Haruka Mikamori

Abstract:

A new multi-step comprehensive experience-based learning program was developed and carried out so that the students understood about what was the principle of the circuit function and how the designed circuit was used in actual advanced applications.

Keywords: Electronic circuit education, Experience based learning, Comprehensive education,

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Authors: S. Assi, M. Haffar

Abstract:

Teaching statistics is a critical and challenging issue especially to students from multidisciplinary and diverse postgraduate backgrounds. Postgraduate research students require statistics not only for the design of experiments; but also for data analysis. Students often perceive statistics as a complex and technical subject; thus, they leave data analysis to the last moment. The lecture needs to be simple and inclusive at the same time to make it comprehendible and address the learning needs of each student. Therefore, the aim of this work was to design a simple and comprehendible statistics lecture to postgraduate research students regarding ‘Research plan, design and data collection’. The lecture adopted the constructive alignment learning theory which facilitated the learning environments for the students. The learning environment utilized a student-centered approach and used interactive learning environment with in-class discussion, handouts and electronic voting system handsets. For evaluation of the lecture, formative assessment was made with in-class discussions and poll questions which were introduced during and after the lecture. The whole approach showed to be effective in creating a learning environment to the students who were able to apply the concepts addressed to their individual research projects.

Keywords: Teaching, statistics, lecture, multidisciplinary, postgraduate, learning theory, learning environment, student-centered approach, data analysis.

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Authors: Vasanthi Muniasamy, Intisar Magboul Ejalani, M. Anandhavalli, K. Gauthaman

Abstract:

Social Media (SM) is websites increasingly popular and built to allow people to express themselves and to interact socially with others. Most SMT are dominated by youth particularly College students. The proliferation of popular social media tools, which can accessed from any communication devices has become pervasive in the lives of today’s student life. Connecting traditional education to social media tools are a relatively new era and any collaborative tool could be used for learning activities. This study focuses (i) how the social media tools are useful for the learning activities of the students of faculty of medicine in King Khalid University (ii) whether the social media affects the collaborative learning with interaction among students, among course instructor, their engagement, perceived ease of use and perceived ease of usefulness (TAM) (iii) overall, the students satisfy with this collaborative learning through Social media.

Keywords: Social Media, Web 2.0, Perceived ease of use, perceived usefulness, Collaborative Learning.

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Authors: M. H. Moradi, S. M. Moosavi, A. R. Reisi

Abstract:

The main objective of this paper is to investigate the enhancement of power system stability via coordinated tuning of Power System Stabilizers (PSSs) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem. Chaotic catfish particle swarm optimization (C-Catfish PSO) algorithm is used to minimize the ITAE objective function. The proposed algorithm is evaluated on a two-area, 4- machines system. The robustness of the proposed algorithm is verified on this system under different operating conditions and applying a three-phase fault. The nonlinear time-domain simulation results and some performance indices show the effectiveness of the proposed controller in damping power system oscillations and this novel optimization algorithm is compared with particle swarm optimization (PSO).

Keywords: Power system stabilizer, C-Catfish PSO, ITAE objective function, Power system control, Multi-machine power system

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Authors: Hossein Shahinzadeh, Ladan Darougaran, Ebrahim Jalili Sani, Hamed Yavari, Mahdi Mozaffari Legha

Abstract:

This paper present a new method for design of power system stabilizer (PSS) based on sliding mode control (SMC) technique. The control objective is to enhance stability and improve the dynamic response of the multi-machine power system. In order to test effectiveness of the proposed scheme, simulation will be carried out to analyze the small signal stability characteristics of the system about the steady state operating condition following the change in reference mechanical torque and also parameters uncertainties. For comparison, simulation of a conventional control PSS (lead-lag compensation type) will be carried out. The main approach is focusing on the control performance which later proven to have the degree of shorter reaching time and lower spike.

Keywords: Power system stabilizer (PSS), multi-machine power system, sliding mode control

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Authors: Byoung-Tak Zhang, Chan-Hoon Park

Abstract:

Hypernetworks are a generalized graph structure representing higher-order interactions between variables. We present a method for self-organizing hypernetworks to learn an associative memory of sentences and to recall the sentences from this memory. This learning method is inspired by the “mental chemistry" model of cognition and the “molecular self-assembly" technology in biochemistry. Simulation experiments are performed on a corpus of natural-language dialogues of approximately 300K sentences collected from TV drama captions. We report on the sentence completion performance as a function of the order of word-interaction and the size of the learning corpus, and discuss the plausibility of this architecture as a cognitive model of language learning and memory.

Keywords: Linguistic recall memory, sentence completion task, self-organizing hypernetworks, cognitive learning and memory.

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Authors: Najmeh Bolbolamiri, Maryam Setayesh Sanai, Ahmad Mirabadi

Abstract:

This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.

Keywords: stator currents monitoring, railway points, point failures, fault detection and diagnosis, Kolmogorov-Smirnov test, time-domain analysis.

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Authors: N.B. Adams

Abstract:

This article discusses the concept of student ownership of knowledge and seeks to determine how to move students from knowledge acquisition to knowledge application and ultimately to knowledge generation in a virtual setting. Instructional strategies for fostering student engagement in a virtual environment are critical to the learner-s strategic ownership of the knowledge. A number of relevant theories that focus on learning, affect, needs and adult concerns are presented to provide a basis for exploring the transfer of knowledge from teacher to learner. A model under development is presented that combines the dimensions of knowledge approach, the teacher-student relationship with regards to knowledge authority and teaching approach to demonstrate the recursive and scaffolded design for creation of virtual learning environments.

Keywords: Virtual learning environments, learning theory, teaching model, online learning.

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Authors: P. Sawitri, S. Cdr. Sittha, T. Kritsana

Abstract:

Flow forming is widely used in many industries, especially in defence technology industries. Pressure vessels requirements are high precision, light weight, seamless and optimum strength. For large pressure vessels, flow forming by 3 rollers machine were used. In case of long range rocket motor case flow forming and welding of pressure vessels have been used for manufacturing. Due to complication of welding process, researchers had developed 4 meters length pressure vessels without weldment by 4 rollers flow forming machine. Design and preparation of preform work pieces are performed. The optimization of flow forming parameter such as feed rate, spindle speed and depth of cut will be discussed. The experimental result shown relation of flow forming parameters to quality of flow formed tube and prototype pressure vessels have been made.

Keywords: Flow forming, Pressure vessel, four rollers, feed rate, spindle speed, cold work.

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Authors: Adesina, Olusola Joseph

Abstract:

The use of Technological tools in the classroom setting has drawn the interest of researchers all over the world in the recent time. Technology has been identified in the recent time as potentials tools to aid learning especially during early childhood stage. The main objective of this is to assist the upcoming younger generations to acquire necessary skills for cognitive development which later enhances effective teaching learning process. The integration of Technology in early childhood requires a careful selection of devices that will both assist the children and the teachers or care givers. This paper therefore, examines some selected literature evidences and highlighted the efficacy of various technologies tools in enhancing the development and learning of children (0 – 5 years). Conclusion and recommendations were also drawn in this paper. 

Keywords: Development, Efficacy, Learning, Technological Device.

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Authors: Nur Sarma, Paul M. Tuohy, Siniša Djurović

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This paper presents an in-depth investigation of the effects of several grid supply harmonic voltages on the stator currents of an example wound rotor induction machine. The observed effects of higher order grid supply harmonics are identified using a finite element time stepping transient model, as well as a time-stepping electromagnetic model. In addition, a number of analytical equations to calculate the spectral content of the stator currents are presented in the paper. The presented equations are validated through comparison with the obtained spectra predicted using the finite element and electromagnetic models. The presented study provides a better understanding of the origin of supply harmonic effects identified in the stator currents of the example wound rotor induction machine. Furthermore, the study helps to understand the effects of higher order supply harmonics on the harmonic emissions of the wound rotor induction machine.  

Keywords: Wound rotor induction machine, supply harmonics, current spectrum, power spectrum, power quality, harmonic emissions, finite element analysis.

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Authors: A. Retbi, M. Khalidi Idrissi, S. Bennani

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The success of an e-learning system is highly dependent on the quality of its educational content and how effective, complete, and simple the design tool can be for teachers. Educational modeling languages (EMLs) are proposed as design languages intended to teachers for modeling diverse teaching-learning experiences, independently of the pedagogical approach and in different contexts. However, most existing EMLs are criticized for being too abstract and too complex to be understood and manipulated by teachers. In this paper, we present a visual EML that simplifies the process of designing learning scenarios for teachers with no programming background. Based on the conceptual framework of the activity theory, our resulting visual EML focuses on using Domainspecific modeling techniques to provide a pedagogical level of abstraction in the design process.

Keywords: Educational modeling language, Domain Specific Modeling, authoring systems, learning scenario.

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Authors: Yaşar Baykul, Musa Gürsel, Hacı Sulak, Erhan Ertekin, Ersen Yazıcı, Osman Dülger, Yasin Aslan, Kağan Büyükkarcı

Abstract:

The reliability of the tools developed to learn the learning styles is essential to find out students- learning styles trustworthily. For this purpose, the psychometric features of Grasha- Riechman Student Learning Style Inventory developed by Grasha was studied to contribute to this field. The study was carried out on 6th, 7th, and 8th graders of 10 primary education schools in Konya. The inventory was applied twice with an interval of one month, and according to the data of this application, the reliability coefficient numbers of the 6 sub-dimensions pointed in the theory of the inventory was found to be medium. Besides, it was found that the inventory does not have a structure with 6 factors for both Mathematics and English courses as represented in the theory.

Keywords: Learning styles, Grasha-Riechmann, reliability, validity.

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Authors: Argaw T. Gurmu, Muhammad N. Mahmood

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The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: Building measurement, construction management, learning challenges, evaluate survey.

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Authors: Samson T. Obafemi, Seraphin D. Eyono Obono

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Information and Communication Technologies (ICTs) are pervasive nowadays, including in education where they are expected to improve the performance of learners. However, the hope placed in ICTs to find viable solutions to the problem of poor academic performance in schools in the developing world has not yet yielded the expected benefits. This problem serves as a motivation to this study whose aim is to examine the perceptions of educators on the advantages and disadvantages of e-learning. This aim will be subdivided into two types of research objectives. Objectives on the identification and design of theories and models will be achieved using content analysis and literature review. However, the objective on the empirical testing of such theories and models will be achieved through the survey of educators from different schools in the Pinetown District of the South African Kwazulu-Natal province. SPSS is used to quantitatively analyse the data collected by the questionnaire of this survey using descriptive statistics and Pearson correlations after assessing the validity and the reliability of the data. The main hypothesis driving this study is that there is a relationship between the demographics of educators’ and their adherence to learning theories on one side, and their perceptions on the advantages and disadvantages of e-learning on the other side, as argued by existing research; but this research views these learning theories under three perspectives: educators’ adherence to self-regulated learning, to constructivism, and to progressivism. This hypothesis was fully confirmed by the empirical study except for the demographic factor where teachers’ level of education was found to be the only demographic factor affecting the perceptions of educators on the advantages and disadvantages of e-learning.

Keywords: Academic performance, e-learning, Learning theories, Teaching and Learning.

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Authors: Kemal Polat

Abstract:

In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: Fuzzy C-means clustering, Fuzzy C-means clustering based attribute weighting, Pima Indians diabetes dataset, SVM.

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Authors: K. M. Faraoun, A. Boukelif

Abstract:

In the present work, we propose a new technique to enhance the learning capabilities and reduce the computation intensity of a competitive learning multi-layered neural network using the K-means clustering algorithm. The proposed model use multi-layered network architecture with a back propagation learning mechanism. The K-means algorithm is first applied to the training dataset to reduce the amount of samples to be presented to the neural network, by automatically selecting an optimal set of samples. The obtained results demonstrate that the proposed technique performs exceptionally in terms of both accuracy and computation time when applied to the KDD99 dataset compared to a standard learning schema that use the full dataset.

Keywords: Neural networks, Intrusion detection, learningenhancement, K-means clustering

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Authors: Wafa' S.Al-Sharafat, Reyadh Naoum

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Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportunity for malicious users to do their damage becomes very great and lucrative. The objective of this paper is to incorporate different techniques into classier system to detect and classify intrusion from normal network packet. Among several techniques, Steady State Genetic-based Machine Leaning Algorithm (SSGBML) will be used to detect intrusions. Where Steady State Genetic Algorithm (SSGA), Simple Genetic Algorithm (SGA), Modified Genetic Algorithm and Zeroth Level Classifier system are investigated in this research. SSGA is used as a discovery mechanism instead of SGA. SGA replaces all old rules with new produced rule preventing old good rules from participating in the next rule generation. Zeroth Level Classifier System is used to play the role of detector by matching incoming environment message with classifiers to determine whether the current message is normal or intrusion and receiving feedback from environment. Finally, in order to attain the best results, Modified SSGA will enhance our discovery engine by using Fuzzy Logic to optimize crossover and mutation probability. The experiments and evaluations of the proposed method were performed with the KDD 99 intrusion detection dataset.

Keywords: MSSGBML, Network Intrusion Detection, SGA, SSGA.

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Authors: Danielle Morin, Jennifer D.E.Thomas, Raafat G. Saade

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While computers are known to facilitate lower levels of learning, such as rote memorization of facts, measurable through electronically administered and graded multiple-choice questions, yes/no, and true/false answers, the imparting and measurement of higher-level cognitive skills is more vexing. These require more open-ended delivery and answers, and may be more problematic in an entirely virtual environment, notwithstanding the advances in technologies such as wikis, blogs, discussion boards, etc. As with the integration of all technology, merit is based more on the instructional design of the course than on the technology employed in, and of, itself. With this in mind, this study examined the perceptions of online students in an introductory Computer Information Systems course regarding the fostering of various higher-order thinking and team-building skills as a result of the activities, resources and technologies (ART) used in the course.

Keywords: Critical thinking, deep learning, distance learning, elearning, online learning, virtual environments.

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Authors: Ran Bernstein, Tal Shafir, Rachelle Tsachor, Karen Studd, Assaf Schuster

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Laban Movement Analysis (LMA), developed in the dance community over the past seventy years, is an effective method for observing, describing, notating, and interpreting human movement to enhance communication and expression in everyday and professional life. Many applications that use motion capture data might be significantly leveraged if the Laban qualities will be recognized automatically. This paper presents an automated recognition method of Laban qualities from motion capture skeletal recordings and it is demonstrated on the output of Microsoft’s Kinect V2 sensor.

Keywords: Laban Movement Analysis, Kinect, Machine Learning.

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Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones are continually upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described more refined, complex and detailed. In this context, we analyzed a set of experimental data, obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model become extremely challenging. After a series of feature selection and parameters adjustments, a well-performed SVM classifier has been trained. 

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Fahad Suleiman

Abstract:

The aim of this paper is to study students’ view on mathematics learning in Katsina State Senior Secondary Schools of Nigeria, such as their conceptions of mathematics, attitudes toward mathematics learning, etc. A questionnaire was administered to a random sample of 1,225 senior secondary two (SS II) students of Katsina State in Nigeria. The data collected showed a clear picture of the hurdles that affect the teaching and learning of mathematics in our schools. Problems such as logistics and operational which include shortage of mathematics teachers, non–availability of a mathematics laboratory, etc. were identified. It also depicted the substantial trends of changing views and attitudes toward mathematics across secondary schools. Students’ responses to the conception of mathematics were consistent and they demonstrated some specific characteristics of their views in learning mathematics. This survey has provided useful information regarding students’ needs and aspirations in mathematics learning for curriculum planners and frontline teachers for future curriculum reform and implementation.

Keywords: Attitude, education, mathematics, students.

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Authors: Sari Myréen

Abstract:

The aim of this study was to evaluate the role of multisensory elements in enhancing and facilitating foreign language acquisition among adult students in a language classroom. The use of multisensory elements enables the creation of a student-centered classroom, where the focus is on individual learner’s language learning process, perceptions and motivation. Multisensory language learning is a pedagogical approach where the language learner uses all the senses more effectively than in a traditional in-class environment. Language learning is facilitated due to multisensory stimuli which increase the number of cognitive connections in the learner and take into consideration different types of learners. A living lab called Multisensory Space creates a relaxed and receptive state in the learners through various multisensory stimuli, and thus promotes their natural foreign language acquisition. Qualitative and quantitative data were collected in two questionnaire inquiries among the Finnish students of a higher education institute at the end of their basic French courses in December 2014 and 2016. The inquiries discussed the effects of multisensory elements on the students’ motivation to study French as well as their learning outcomes. The results show that the French classes in the Multisensory Space provide the students with an encouraging and pleasant learning environment, which has a positive impact on their motivation to study the foreign language as well as their language learning outcomes.

Keywords: Foreign language acquisition, foreign language learning, higher education, multisensory learning, pedagogical approach, transcultural learning.

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Authors: David W.S. Tai, Ren-Cheng Zhang, Sheng-Hung Chang, Chin-Pin Chen, Jia-Ling Chen

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This study reports results of a meta-analytic path analysis e-learning Acceptance Model with k = 27 studies, Databases searched included Information Sciences Institute (ISI) website. Variables recorded included perceived usefulness, perceived ease of use, attitude toward behavior, and behavioral intention to use e-learning. A correlation matrix of these variables was derived from meta-analytic data and then analyzed by using structural path analysis to test the fitness of the e-learning acceptance model to the observed aggregated data. Results showed the revised hypothesized model to be a reasonable, good fit to aggregated data. Furthermore, discussions and implications are given in this article.

Keywords: E-learning, Meta Analytic Path Analysis, Technology Acceptance Model

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Authors: Sajjad Hashemi, Seyyed Yasser Hashemi

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In today's world, success of most systems depend on the use of new technologies and information technology (IT) which aimed to increase efficiency and satisfaction of users. One of the most important systems that use information technology to deliver services is the education system. But for educational services in the form of E-learning systems, hardware and software equipment should be containing high quality, which requires substantial investment. Because the vast majority of educational establishments can not invest in this area so the best way for them is reducing the costs and providing the E-learning services by using cloud computing. But according to the novelty of the cloud technology, it can create challenges and concerns that the most noted among them are security issues. Security concerns about cloud-based E-learning products are critical and security measures essential to protect valuable data of users from security vulnerabilities in products. Thus, the success of these products happened if customers meet security requirements then can overcome security threats. In this paper tried to explore cloud computing and its positive impact on E- learning and put main focus to identify security issues that related to cloud-based E-learning efforts which have been improve security and provide solutions in management challenges.

Keywords: Cloud computing, E-Learning, Security.

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