Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1064
Support Vector Machine as Feature Selection Method in Classifier Ensembles
Статья научная
In this paper, we suggest classifier ensembles that can incorporate Support Vector Machine (SVM) as feature selection method into classifier ensembles models. Consequences of choosing different number of features are monitored. Also, the goal of this research is to present and compare different algorithmic approaches for constructing and evaluating systems that learn from experience to make the decisions and predictions and minimize the expected number or proportion of mistakes. Experimental results demonstrate the effectiveness of selecting features with SVM in various types of classifier ensembles.
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Статья научная
An electromyography (EMG) is an analytical tool used to record muscles' electrical activity, which produces an electrical signal proportional to the level of muscle activity. EMG signal plays a vital role in bio-mechatronic engineering for designing intelligent prostheses and other rehabilitation devices. Analysis of EMG signals with powerful and advanced methodologies is an essential requirement in EMG signal processing, as the EMG signal is a complex nonlinear, non-stationary signal in nature. It is required to use advanced signal processing techniques rather than conventional methods to exact EMG signals' features. Fourier transforms (FT) are not the most appropriate tool for analyzing non-stationary signals such as EMG. In this work, we have developed a system that can be useful for disabled persons to get a regular lifestyle using a functioning part of the body. Here, we studied the electrocution gram behavior of human body parts to feature extraction and trained the neural network to simulate the movements of mechanical actuators such as robotic arms. The wavelet transformation has been used to get high-quality feature extraction from electro cardio grapy and develops proper faltering methods for cardio systems' electrical signals. Finally, an artificial neural network (ANN) is used to classify the EMG signals through exacted features. Classification results are presented in this paper.
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Статья научная
Integrated development environment as a software system that aids programmers in developing software applications quickly and effectively has been perceived to also serve as an inappropriate tool for beginning programmers when it is specially developed with some complex features. This complexity in features as perceived leaves the programmers with a double role of studying complexity found in the environment and the semantics with syntaxes of the concerned programming language. This paper categorizes few of the available integrated development environments based on program building tools that are integrated in them and also considers an experimental survey on their adverse effects on novice programmers by sampling programmers' opinions using closed ended questionnaires. The population was randomly selected from some tertiary institutions in Nigeria. The opinions were statistically analyzed using chi square and based on the analysis, beginning programmers learning strengths are found greatly influenced by the type of integrated development environment used.
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Статья научная
The paper comprehends an impending accost of intensifying biometric stationed authentication protocol(BSAP) bestowing meta-heuristic genetic algorithm for securing MANET. Biometric authentication using fingerprint, facial, iris scan, voice recognition etc. have gain a lot of importance in recent years to provide security in MANET. Biometrics are more advantageous and secure as compared to prevailing data security techniques like password or token mechanisms. A higher level of security is achieved in our impending approach using genetic algorithm to overcome the security and privacy concerns that exist in biometric technology. The foremost requirement of our protocol is to overcome various data attacks such as wormhole, cache poisoning, invisible node attack etc. that are confronted by MANET and make the network more secure.
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Статья научная
This paper presents the electronic marketing application for users involved with the food industry in Thailand. The purpose of this research is to study and develop the supply chain management and the Thai food export to global market. Moreover, this project will improve the knowledge entrepreneurship in this industry to export the food products to the world market through the electronic marketing system. This research will be focused in the two provinces of Thailand that are Phrae and Phayao. The sample group of this research includes the food export manufacturers, the raw material suppliers, and the family business trainees. The research methodology exploits the system development process with the cycle of information system development. The process will develop all fundamentals of the system in every part, which are analysis, design, development, installation, performance testing, and user’s application training. According to the study, the sample users demand the chain management system to produce and export their products. The reason is that they need a tool to assist all sectors of stakeholders; upstream, midstream and downstream. As the results, the proposed system provides functionality that covers the needs of all stakeholders, which are the raw material suppliers, the customers (franchise and restaurant), and the managers (manufacturing, procurement, inventory, restaurant, and sales). From the system's efficiency evaluation by our sample group, the proposed system has been given a satisfied result of system performance from all users: the food export manufacturers (good: = 3.64), the raw material suppliers (good: = 3.63), and the family business trainees (good: = 3.63).
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Статья научная
Text summarization is the process of creating a shorter version of a longer text document while retaining its most important information. There have been a number of methods proposed for text summarization, but the existing method does not provide better results and has a problem with sequence classification. To overcome these limitations, a tangent search long short term memory with adaptive reinforcement transient learning-based extractive and abstractive document summarization is proposed in this manuscript. In abstractive phase, the features of the extractive summary are extracted and then the optimal features are selected by Adaptive Flamingo Optimization (AFO). With these optimal features, the abstractive summary is generated. The proposed method is implemented in python. For extractive text summarization, the proposed method attains 42.11% ROUGE-1 Score, 23.55% ROUGE-2 score and 41.05% ROUGE-L score using Gigaword. Additionally, 57.13% ROUGE-1 Score, 28.35% ROUGE-2 score and 52.85% ROUGE-L score using DUC-2004 dataset. For abstractive text summarization the proposed method attains 47.05% ROUGE-1 Score, 22.02% ROUGE-2 score and 48.96% ROUGE-L score using Gigaword. Also, 35.13% ROUGE-1 Score, 20.35% ROUGE-2 score and 35.25% ROUGE-L score using DUC-2004 dataset.
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Task-based Approach in College English Teaching of Digital-based Context
Статья научная
With the wide employment of modern educational technology, college English teaching is going on a process of replacing traditional educational media with modern ones, which are closely connected with multimedia computers and internet technology to raise its efficiency and quality. However, some problems and challenges still exist in the college English teaching. In order to solve the problems, this article designs a test and collects data to check the effectiveness of the task-based approach within the Internet-assisted multimedia in college English teaching. The results show that Linguistic form was analyzed and practiced with task-based approach which may help the learners notice the linguistic problems and try out new language forms and structures, and that Internet-assisted multimedia has been effective in intriguing learners' interests and greatly enhanced their self-esteem.
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Taxonomy learning from health care social communities to improve EHR implementation
Статья научная
In this paper, we propose an approach to extract ontological structures from datasets generated by health care users of social networking sites. The objective of this approach is to exploit the user generated implicit semantics as a complement to more formalized knowledge representations. We aim for this latter to leverage the adoption level of the Electronic Health Record systems that are complaining from the shortage in standards and controlled vocabularies.
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Teachers’ Use of Technology and Constructivism
Статья научная
Technology has changed the way we teach and the way we learn. Many learning theories can be used to apply and integrate this technology more effectively. There is a close relationship between technology and constructivism, the implementation of each one benefiting the other. Constructivism states that learning takes place in contexts, while technology refers to the designs and environments that engage learners. Recent efforts to integrate technology in the classroom have been within the context of a constructivist framework. The purpose of this paper is to examine the definition of constructivism, incorporating technology into the classroom, successful technology integration into the classroom, factors contributing to teachers’ use of technology, role of technology in a constructivist classroom, teacher’s use of learning theories to enable more effective use of technology, learning with technology: constructivist perspective, and constructivism as a framework for educational technology. This paper explains whether technology by itself can make the education process more effective or if technology needs an appropriate instructional theory to indicate its positive effect on the learner.
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Teaching Cyber Security Course in the Classrooms of NMIMS University
Статья научная
The paper aims at implementing new pedagogy and assessment practices from rigorous literature survey perusing quality papers and articles. The appropriate pedagogy and relevant assessment always go hand in hand. One cannot achieve effective teaching by compromising the other component. In engineering, pedagogy and assessment play extremely important roles. In recent years, engineering education has lost track of the big picture of what the curriculum has to be. In Computer Science Engineering, the course contents often change according to the demands for new technology in the market. Adhering to this fact, the courses must be designed either practical-based or case study based. Rote teaching-learning methods are not as effective as far as the curriculum design in the computing field is concerned. Cyber Security is one such course where students are expected to learn how to create a protective environment for computing and computing resources. The course must be designed in such a way that, students must learn how to identify the vulnerabilities in computing resources and methodologies to mitigate them. This course aims such that students must learn some popular attacks which help them to identify what are the possible ways from where the attacks could happen. The paper makes use of strategic assessment tools for the Cyber Security course (Taught to post-graduation students) and discusses outcomes through course outcome attainment analysis as per the threshold value of attainment set by the Computer Engineering Department to adhere to the accreditation standards. Through course attainment analysis it is observed that, Viva voce assessment tool is not suitable for evaluation of the course as it does not impose the technical details and working of Cyber Security concepts. The overall attainment was 55.55% which is 15% less than the threshold set by Computer Engineering Department.
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Teaching Programming Courses Online using Cloud System: Practices and Future Challenges
Статья научная
Acceptance of cloud systems as the future has given way to a large number of cloud application installations. They have their presence across domains be it banking, gaming, education and others. A cloud based solution brings down the cost of ownership and maintenance for the host organization. For the users a resilience to use any type of end device being it a workstation, laptop, netbook or even a smartphone to access the application. A typical cloud based LMS was developed with appropriate pedagogy to teach programming courses. Necessary software required are made available on the cloud, with a bare minimum hardware spec requirement at the user end. The paper highlights the adaptability to such pure online course by the students and their learning outcomes. The paper also discusses the issues and challenges both in terms of technology and pedagogy which needs to be addressed when such online courses are planned.
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Teaching artificial intelligence and robotics to undergraduate systems engineering students
Статья научная
The skills of artificial intelligence (AI) and robotics provide a wide window of job opportunities for the following professionals: computer scientists, mechanical engineers, system engineers, computer engineers, biomedical engineers, and electrical engineers. Additionally, other professionals benefiting from AI and robotics’ job opportunities are information technologists, informatic engineers, electronic engineers, data scientists, industrial engineers, big data engineers, and related specialists in the dynamic field of engineering robotics. Therefore, the purpose of this research was to study the effort of teaching AI and robotics to undergraduate systems engineering students at the Polytechnic University Institute “Santiago Mariño” in Barinas, Venezuela. Consequently, the methodology used in this academic research was the case study approach, which included three phases, namely Initiation Phase, Fieldwork Phase, and Closing Phase. In that sense, the design of research adopted in this study was based on the development of an exploratory single case study method. As a result, the Theoretical Framework created as a cornerstone of this research highlighted the following three research variables: (1) Robotic Applications, (2) Mechanics of Robotic Manipulation and Computer Vision, and (3) Object-oriented Analysis and Design (OOAD) and Object-oriented (OO) High-level Programming Languages. In conclusion, two nondirectional null hypotheses were tested, leading to the positive answers of the following research questions: (1) “Can undergraduate systems engineering students apply OOAD and OO High-level Programming Languages to analyze, design, and develop Robotic Applications?” and (2) “Can undergraduate systems engineering students use Mechanics of Robotic Manipulation and Computer Vision to analyze, design, and develop Robotic Applications?” as stated in this case study.
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Test Bank Management System Applying Rasch Model and Data Encryption Standard (DES) Algorithm
Статья научная
Online examinations are of great importance to education. It has become a powerful tool for evaluating students' knowledge and learning. Adopting modern technology that saves time and ensures security. The researcher developed a Test Bank Management System that can store test items in any subjects. The system is capable of conducting item analysis using the Rasch model scale. Items that undergo analysis based on Rasch scale helped faculty by quantifying each item as "good", "rejected", or "revised". For securing items in the test bank, Data Encryption Standard (DES) algorithm was successfully applied thus ensuring the safety and reliability of the questions in the test bank. Only items that are ready for deployment to the student's computer during the examinations will be decrypted. In conclusion, the system passed the evaluation process and eliminates redundancy of manual work.
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Test Case Prioritization based on Fault Dependency
Статья научная
Software testers should prioritize test cases so that important ones are run earlier in the regression testing process to reduce the cost of regression testing. Test case prioritization techniques schedule test cases for execution in an order that improves the performance of regression testing. One of the performance goals i.e. the fault detection rate, measures how quickly faults are detected during the testing process. Improved rate of fault dependency detection can provide faster feedback on software and let developers debug the leading faults at first that cause other faults to appear later. Another performance goal i.e. severity detection rate among faults, measures how quickly more severe faults are detected earlier during testing process. Previous studies addressed the second goal, but did not consider dependency among faults. In this paper an algorithm is proposed to prioritize test cases based on rate of severity detection associated with dependent faults. The aim is to detect more severe leading faults earlier with least amount of execution time and to identify the effectiveness of prioritized test case.
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Text classification using SVM enhanced by multithreading and CUDA
Статья научная
With the sudden growth of the internet and digital documents available on the web, the task of organizing text data has become a major problem. In recent times, text classification has become one of the main techniques for organizing text data. The idea behind text classification is to classify a given piece of text to a predefined class or category. In the present research work, SVM has been used with linear kernel using the One-V-Rest strategy. The SVM is trained using various data sets collected from various sources. It may so happen that some particular words were not so common around 5-6 years ago, but are currently prevalent due to recent trends. Similarly, new discoveries may result in the coinage of new words. This process can also be applied to text blogs which can be crawled and then analyzed. This technique should in theory be able to classify blogs, tweets or any other document with a significant amount of accuracy. In any text classification process, preprocessing phase takes the most amount of time – cleaning, stemming, lemmatization etc. Hence, the authors have used a multithreading approach to speed up the process. The authors further tried to improve the processing time of the algorithm using GPU parallelism using CUDA.
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Статья научная
There is a growing body of attention to importance of document summarization in most NLP tasks. So far, full coverage information, coherence of output sentences and lack of similar sentences (non-redundancy) are the main challenges faced to many experiments in compacted summaries. Although some research has been carried out on compact summaries, there have been few empirical investigations into coherence of output sentences. The aim of this essay is to explore a comprehensive and useful methodology to generate coherent summaries. The methodological approach taken in this study is a mixed method based on most likely n-grams and word2vec algorithm to convert separated sentences into numeric and normalized matrices. This paper attempts to extract statistical properties from numeric matrices. Using a greedy approach, the most relevant sentences to main document subject are selected and placed in the output summary. The proposed greedy method is our backbone algorithm, which utilizes a repeatable algorithm, maximizes two features of conceptual coherence and subject matter diversity in the summary. Suggested approach compares its result to similar model Q_Network and shows the superiority of its algorithm in confronting with long text document.
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Texture Analysis Based on Micro Primitive Descriptor (MPD)
Статья научная
Texture classification is an important application in all the fields of image processing and computer vision. This paper proposes a simple and powerful feature set for texture classification, namely micro primitive descriptor (MPD). The MPD is derived from the 2×2 grid of a motif transformed image. The original image is divided into 2×2 pixel grids. Each 2×2 grid is replaced by a motif shape that minimizes the local ascent while traversing the 2×2 grid forming a motif transformed image. The proposed feature set extracts textural information of an image with a more detailed respect of texture characteristics. The results demonstrate that it is much more efficient and effective than representative feature descriptors, such as Random Threshold Vector Technique (RTV) features and Wavelet Transforms Based on Gaussian Markov Random Field (WTBGMF) approach for texture classification.
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The Application of Bayesian Classification Theories in Distance Education System
Статья научная
With the vigorous application of distance education in recent years, the biggest challenge that the learners and managers are facing today is how to institute the training courses and choose the learning resources according to the personal characteristics of learners. It is subjective to arbitrarily decide the learning resources. This study presents a new constructional method, based on the Bayesian networks of courses relationship. This method uses the feedback of learning resources from the learners and examination results of training courses as data samples. And a new procedure is presented, joining quantitative value of RFM model and naïve Bayesian algorithm, to classify the learners and offer more support to make decision. Moreover, the experimental results demonstrate that the algorithm is efficient and accurate, and the Bayesian network method can be used in other Electronic Commerce System
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This study aims at investigating the effect of post-task activities on the TEFL students' fluency and accuracy in oral production. In particular, the study seeks to discover the effect of different types of repeated performance (i.e., public and private) as post-task activities on fluency and accuracy of oral production. Our premise is in line with Ellis's (1994) idea that these types of activities can promote learning. The participants were all TEFL students studying at Iranian universities and institutes. They were assigned into four groups. They all participated in pre and post interview sessions. The students in group A repeated their performance in private. The students in group B repeated their performance in front of the class and the students in group C as the last experimental group repeated their performance both in public and private. The students in group D as the control group didn't have any repeated performance. The results indicated that group B outperformed all other groups in fluency. Concerning accuracy, the students in group C outperformed the students in all other groups.
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Статья научная
This research purpose was to know the differences of student's learning outcome between the students which is learn through the implementation of authentic assessment development result based on ICT with the students which is learn through conventional assessment at grade V cluster V Sukasada sub district Buleleng regency in the academic year 2013/2014. This research was quasi-experiment research. The population of this research is all the grade V students at cluster V Sukasada sub district in amount of five classes. The sample of this research is the grade V students at SD N 2 Pacung which is consist of 23 students and the grade V students at SD N 1 Julah which is consist of 23 students, the sampling technique used was random sampling. The data collected by test instrument that is 35 questions of objective test and then analysis by descriptive statistic and inferential statistic (t-test). Based on the data analysis, provable that tcount = 3.67 and ttable (at significant standard 5%) = 2.02. This is means that tcount > ttable, so it can be interpreted that there is significant differences of learning outcome between the students which is learn through the implementation of authentic assessment development result based on ICT in learning process by 2013 curriculum with the students which is learn through conventional assessment. By arithmetic average, it can be known that the average score of the experiment group student's is 26.35 and the average score of the control group student's is 23.30. It's mean that the average score of experiment group > the average score of control group, so it can be conclude that the implementation of authentic assessment development result based on ICT in learning process by 2013 curriculum had an positive effect through the students grave V learning outcome at cluster V Sukasada sub district, Buleleng regency.
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