International Journal of Modern Education and Computer Science @ijmecs
Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1096
Designing a Universal Data-Oriented Random Number Generator
Статья научная
Data-oriented is new and applied theory which provides method that models the concepts with data structure. If the concept is modeled by using sufficient data in modeling, required inferences and calculations can be done fast with less complexity. Random variable was modeled with digital probability graph, by using Ahmad Fact and probability density function. Some data-oriented random generators have been presented based on data-oriented approach. In this paper a universal data-oriented random number generator is introduced which is able to generate random numbers with uniform, normal, exponential and chi-square distributions.
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Статья научная
The use of wind turbines based on induction generator is very popular to generate electrical power and it has been noted by researchers because of its many advantages compared to conventional methods of electrical energy generation. Factors of uncertainty in the nature of the wind cause variable voltage in amplitude and frequency on the induction generator. It is not appropriate to apply such voltage to the load. So a controller must be designed to be kept constant voltage and frequency. In this paper, a fuzzy controller is used as state feedback to stabilize the voltage, frequency and voltage amplitude. The variable AC voltage generated by generator is converted by rectifier to a variable DC voltage. The variable DC voltage causes a change in the output voltage of the inverter. The PWM switching property is used to stabilize frequency and state feedback is used to stabilize the output voltage amplitude. The obtained error signal with its derivative is applied to the fuzzy controller as input to generate the considered control signal by controller to generate appropriate firing pulses to apply to PWM inverter. Therefore, frequency and amplitude of the output voltage is kept constant with switching control and so maximum power of wind is resulted. Simulation results show that by design the appropriate controller for the considered system output voltage can be stabilized in constant amplitude and frequency.
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Detecting Anomalies in Students' Results Using Decision Trees
Статья научная
Examinations are one of the most important activities that take place in institutions of learning. In many Nigerian universities, series of meetings are held to manually examine and approve computed student examination results. During such meetings, students' results are scrutinized. Reasonable explanations must be provided for any anomaly that is discovered in a result before the result is approved. This result approval process is prone to some challenges such as fatigue arising from the long duration of the meetings and wastage of man-hours that could have been used for other productive tasks. The aim of this work is to build decision tree models for automatically detecting anomalies in students' examination results. The Waikato Environment for Knowledge Analysis (WEKA) data mining workbench was used to build decision tree models, which generated interesting rules for each anomaly. Results of the study yielded high performances when evaluated using accuracy, sensitivity and specificity. Moreover, a Windows-based anomaly detection tool was built which incorporated the decision tree rules.
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Detecting and Removing the Motion Blurring from Video Clips
Статья научная
In this paper, we give a framework to deblur the blurry frame in a video clip. Two kinds of motion blurring effects can be removed in the video, one is the blurring effect caused by hand shaking, the other is the blurring effect caused by a fast moving object. For the blurring caused by hand shaking, PSF is estimated by comparing the stable area in blurry frame and non-blurry frame, so the Richardson-Lucy algorithm can restore the blurry frame by non-blind deconvolution. We also propose a framework to deblur the motion blurring objects which move fast in the video. The background is reconstructed by the algorithm in each frame, so an accurate matte of blurry object can be extracted to deblur the moving object by alpha matting. Results show our method is effective.
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Detection of False Income Level Claims Using Machine Learning
Статья научная
Data driven social security fraud detection has been given limited attention in research. Recently, social schemes have seen significant expansion across many developing countries including India. The fundamental aims of social schemes are to alleviate poverty, enhance the quality of life of the most vulnerable and offer greater chances to those relegated to the fringe of society to engage more enthusiastically in the society. Although governments channel billions of dollars every year in support of these social schemes, quite significant number of the eligible people are excluded from the program mainly through fraud and dishonesty. Although fraud is considered an illegal offence and morally reprehensible, it is unfortunate that the prevalence of fraud in social benefit schemes is rampant and a significant challenge to address. In this paper, we studied the viability of machine learning techniques in identifying fraudulent transactions in the context of social schemes. We focus on the detection of the false income level claims made by the fake beneficiaries to get the privileges of government scheme. We used the standard classifiers like Logistic Regression, Decision Trees, Random Forests, Support Vector Machine (SVM), Multi-Layer Perceptron and Naïve Bayes to identify fake beneficiaries of the government scheme from those deserving people. The results show that the Random Forest Classifier perform best providing an accuracy of 99.3% with F1 score of 0.99. The outcome of this research can be used by the government agencies entrusted with the management of the schemes to wade out the abusers and provide the required benefits to the right and deserving recipients.
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Detection of Tumours in Digital Mammograms Using Wavelet Based Adaptive Windowing Method
Статья научная
Mammography is the most effective procedure for the early detection of breast diseases. Mammogram analysis refers the processing of mammograms with the goal of finding abnormality presented in the mammogram. In this paper, the tumour can be detected by using wavelet based adaptive windowing technique. Coarse segmentation is the first step which can be done by using wavelet based histogram thresholding where, the thereshold value is chosen by performing 1-D wavelet based analysis of PDFs of wavelet transformed images at different channels. Fine segmentation can be done by partitioning the image into fixed number of large and small windows. By calculating the mean, maximum and minimum pixel values for the windows a threshold value has been obtained. Depending upon the threshold values the suspicious areas have been segmented. Intensity adjustment is applied as a preprocessing step to improve the quality of an image before applying the proposed technique. The algorithm is validated with mammograms in Mammographic Image Analysis Society Mini Mammographic database which shows that the proposed technique is capable of detecting lesions of very different sizes.
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Detection of botnet using flow analysis and clustering algorithm
Статья научная
With the increase of digital data on the internet, computers are at higher risk of getting corrupted through cyber-attacks. Criminals are adopting more and more sophisticated techniques to steal sensitive information from the web. The botnet is one of the most aggressive threats as it combines lots of advanced malicious techniques. Detection of the botnet is one of the most serious concerns and prominent research area among the researchers. This paper proposes a detection model using the clustering algorithm to group bot traffic and normal traffic into two different clusters. Our contribution focused on applying K-means clustering algorithm to detect botnets based on their detection rate (true and false positives). Experimental results clearly demonstrate the fact that with the help of clustering we were able to separate the complete dataset into two entirely distinguishable clusters, where one cluster is representing the botnet traffic and other one representing the normal traffic.
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Determining proficient time quantum to improve the performance of round robin scheduling algorithm
Статья научная
Process scheduling is considered as a momentous and instinct task accomplished by operating system. Round robin is one of the extensively utilized algorithms for scheduling. Various noticeable scheduling algorithms based on round robin strategy have been introduced in last decade. The most sensitive issue of round robin algorithm is time quantum because it determines and controls the time of achieving resources for a process during execution. Different types of approaches are available for determining time quantum related to round robin. This paper represents a new round robin algorithm having proficient time quantum that has been determined by considering the maximum difference among differences of adjacent consecutive processes into the ready queue. The proposed methodology is an endeavor to increase the outcomes of round robin as well as system performance. The algorithm is experimentally and comparatively better than the mentioned round robin algorithms in this paper. From the consideration against the referred algorithms, it decreases average turn-around-time, average waiting-time and the number of context-switching along with other CPU scheduling criteria.
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Developing E-Business Strategies Curriculum Case Study in the Information Systems Department
Статья научная
E-Business Strategies (EBS) is an elective course in the Information Systems Department, Faculty of Computing & Information Technology at King Abdulaziz University, Jeddah. In this course, students learn many concepts regarding e-business, such as strategies, models, relationships and so on. Also, they improve their leadership skills, such as analyzing the business environment and take the decisions. In this paper, we address the main challenges faced by the EBS course developers and study all the components of the existing EBS course. We then determine a learning strategy using an Outcomes-based Education (OBE) approach and redesign the course using an Active Learning Approach. This paper provides comprehensive information concerning an EBS course in terms of its importance, goals, textbook and evaluation tools.
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Developing a Compact and Practical Online Quiz System
Статья научная
Thanks to the open technologies around the world wide web, the authors as just college teachers have been able to develop a compact and practical online quiz system we call QDB to satisfy needs in their classes. In this paper, first we introduce our system to give ideas what the system can do. Then we show the effectiveness of the system by describing the effects of practical uses of the system in our classes for years including the effect of the recently added retry-functionality. Then as an example of the feasibility of our development we explain how simple to implement the retry-functionality because of the compactness of the system and again the great power the open technologies give us and show the speed of the system. As conclusion we suggest possibilities of a compact and flexible system as a form (or a part) of e-learning systems made to your order.
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Статья научная
Although the philosophy of education of many universities began shifted gradually towards using computers and information and communication technologies to establish effective education environment, the traditional style of examinations (that suffering from real problems related to the type of using paper and pen) is still used in these technological environments. The current e-Exam systems that have been used in modern education environment are still suffering from many problems, but in spite they solved some traditional exam problems, the authors highlighted these issues and developed a new e-Exam platform to provide a better quality exam in terms of saving cost, time, effort and cheating probability. The developed e-Exam was implemented upon client/server network architecture on three computer laboratories at the department of IT in LFU. This e-Exam is being used by 14 lecturers to make daily quizzes, midterm and final exams for 142 morning and evening students to replace most of the paper based examinations since October 2015. The developed e-Exam platform includes three main subsystems which are integrated and working together to generate e-Exam Packages and to deliver the e-Examinations. A special e-Exam Browser was implemented using C Sharp to establish the client/server model. A usability test of e-Exam platform and questionnaires for both lecturers and students were carried out to assess satisfaction and effectiveness. Finally, the empirical outcomes were achieved and mentioned in this paper. To the best of our knowledge based to review literature and our e-Exam adoption survey, the implemented platform represents the first official e-Exam platform in Kurdistan Region of Iraq.
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Статья научная
With the explosive growth of internet, there are a big amount of data being collected in terms of text document, that attracts many researchers in text mining. Traditional data mining methods are found to be trapped while dealing with the scale of text data. Such large scale data can be handled by using parallel computing frameworks such as: Hadoop and MapRedue etc. However, they are also not away from challenges.On the other hand, Naive Bayes (NB) and its variant Multinomial Naive Bayes (MNB) plays an important role in text mining for their simplicity and robustness but if anything or everything from number of words, documents and labels go beyond the linear scaling, then MNB is intractable and will soon be out of memory while dealing in a single computer. Looking into the high dimensional sparse nature of the documents in text datasets, a scalable sparse generative Naive Bayes (SGNB) classifier is also proposed to develop a good text classification model. Unlike parallelization, SGNB reduces the time complexity non-linearly and hence expected to provide best results. In this paper, an efficient Lovins stemmer in combination with snowball based stopword calculation and word tokenizer is proposed for text pre-processing. The extensive experiments conducted on publicly available very well known text datasets opines the effectiveness of the proposed approach in terms of accuracy, F-score and time in comparison to many baseline methods available in the recent literature.
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Статья научная
In this work, we have developed a research grant management system in Haramaya University. The main aim of this project was to automate the manual working system in order to facilitate grant application process, improve time efficiency, save manual cost, improve the flow of information among researchers, and eliminate work delay. In the process of developing the system, researchers conducted a survey research which helps to identify the stakeholders and experts view. Delphi technique was used to identify the view of stakeholders. Whereas a questionnaire was used to collect data from purposely selected researchers to undertake user acceptance test. Finally, we adopted an iterative and incremental method. For the design, we used the UML Modeling language and PHP, JavaScript, Jquery, Json, Bootstrap and CSS used for the implementation. The user acceptance test found the system is acceptable with an average of 94.45%. Through all this process the system was successfully developed, tested and deployed.
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Статья научная
The Information Technology system use visualization to represent data in different forms. Some new researches in this field working on extract Knowledge, rapid information retrieval from the graphical diagram. Therefore, data visualization now trends to use ontology approach to build a robust knowledge-based system. The proposed of this paper is to developed ontology approach and use software tools to improve visualized knowledge. Moreover, study data visualization subject in term of ontology and how to facilitate understanding it on the end user. Computer networks ontology adopted as a case study to prove the important of this approach. The Object Role Modeling (ORM) is a visualized notation used to build the prototype for ontology, and OntoGraf module in the Protégé tool used to build ontology.
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Development and Application of an Autonomous Learning System for Engineering Graphics Education
Статья научная
Autonomous learning plays an important role in raising students’ learning effect and innovation ability in university education. An effective e-learning environment is indispensable in autonomous learning. This paper studies a web based e-learning system and examines students’ autonomous learning ability and perceptions of e-learning taking students at University of Jinan in China as an example. In this paper, a web-based e-learning system for engineering graphics course is developed. The characteristics, the design idea and strategies fit for engineering graphics are introduced. The architecture and system composition are discussed. The key technologies and implementation methods of each module of system are described in detail. The students had experiences on the network learning system for two years. The practical application indicates that it can enhance students’ perceptual cognition to the teaching contents, increase their learning interests, develop their learning initiative and make them master the teaching contents more quickly.
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Development of A New Efficient Routing Scheme for WiMAX Mesh Networks
Статья научная
The emerging WiMAX (Worldwide Interoperability for Microwave Access) technology (IEEE 802.16) can offer low-cost, high speed and long-range communications. The WiMAX supports a point-to-multipoint (PMP) topology and a mesh topology. A WiMAX network is composed of a Base Station (BS) and multiple Subscriber Station (SS). A BS is the mother node and the SS is the child node, though a SS can also be a mother node of a SS if the child node is connected with him to reach to the BS. The BS serves as a gateway connecting to external networks such as the Internet. Number of nodes situated beside a node is called neighbor nodes. In PMP architecture, there is a multi-hop mesh that can be used to gain the high speed wide area network. Again in mesh topology, it increases the wireless coverage and reconfigures ability. In this mode performance depends on a good routing and scheduling protocol. Routing is the way by which a SS will connect with the BS. A good and efficient routing algorithm along with a scheduling algorithm can improve the total network performance significantly. Scheduling algorithm gives the time slot to all SS in a way so that a SS can transmit data or signal in that time slot. There are many research scopes on IEEE 802.16 mesh network especially in routing and scheduling protocol. The purpose of our thesis work is to propose a new routing algorithm to maximize the performance of the network.
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Development of Blended Learning Content based on Tri Kaya Parisudha-superitem in Kelase Platform
Статья научная
Blended learning can be carried out well if it is supported by good content. Good content consists of the subject, performance assignments, discussion forums, and quiz questions that are packaged in an interesting and structured manner. Good content must also be used to measure students’ abilities in the cognitive, affective, and psychomotor domains. One of the efforts that can be made to realize good blended learning content is to develop content by inserting the Tri Kaya Parisudha and Superitem concepts into the Kelase platform. The Tri Kaya Parisudha concept is used as a basis for measuring students’ abilities in the cognitive, affective, and psychomotor domains. Superitem concept is used as the basis for structured content creation (especially on quiz questions and performance tasks) starting from the lowest to the highest level of complexity. Referring to some of those things, this research aimed to provide an overview of the stages of developing blended learning content that integrated the Tri Kaya Parisudha concept and the Superitem concept in the Kelase platform (a case study of Senior High Schools/Vocational High Schools in Bali). This research used the 4D method, which consists of 4 stages, including Define, Design, Develop, and Disseminate. The subjects involved in content testing were four experts. The tools used to collect data were interview guides, photo documentation, and questionnaires. The technique used to analyze the data was descriptive quantitative. The analysis technique in this research was carried out by making a comparison between the five-scale reference effectiveness standard with the percentage level of effectiveness of the blended learning content. The results showed the level of effectiveness of the blended learning content based on Tri Kaya Parisudha-Superitem in the good category with a percentage was 88.667%.
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Статья научная
There appears to be a tendency for the strategies and methods that have been offered in OOP course learning to affect the improvement of individual skills only. There is a significant need for learning strategies which are relevant and able of improving collaborative working skills. The purpose of this study is to develop a Collaborative Learning and Programming model suitable for Object-Oriented Programming courses and assess its validity, practicality, and effectiveness. The implementation of the CLP model was conducted using the ADDIE development procedure by involving 7 experts, 35 experimental class students, 23 control class students and 4 lecturers of the Object-Oriented Programming course. The survey results showed that the CLP model was valid, practical, and effective in achieving these goals. The validity test results were verified based on experts' assessment, indicating that the aspects contained in the CLP model were valid with an Aiken's value V =0.89. The practicality test results indicated that the model was highly practical with the practicality value of 89.95% from students and 89.67% from lecturers. Finally, using the CLP model demonstrated its effectiveness in reducing the abstraction and complexity of OOP courses and improving student collaboration, particularly in programming tasks. The significance of conducting this survey is that it provides evidence for the effectiveness of the CLP model in achieving its intended goals and can inform the development of future OOP courses and programming tasks. The survey was conducted well, as it used both expert assessment and student and lecturer feedback to assess the validity, practicality, and effectiveness of the CLP model.
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Статья научная
Biometric passports is to prevent the illegal entry of traveler into a specific country and limit the use of counterfeit documents by more accurate identification of an individual. The e-passport, as it is sometimes called,represents a bold initiative in the deployment of two new technologies: Cryptography security and biometrics face and fingerprints. The privacy and security implications of this impending worldwide experiment in biometrics face and fingerprints authentication technology. An overall security process that involves people, technology and procedures can overcome limitations of the Cryptography security and face and fingerprint biometric passport using ASP.Net.
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Development of Networked Virtual Experiment System Based on Virtual Campus
Статья научная
China’s higher education has been going through a period of rapid expansion in undergraduate population,and this means a much heavier demand on teaching resources such as laboratories, experiments, teaching staff,etc., which cannot possibly be made available all of a sudden.To deal with this situation, we found virtual reality (VR) technology very helpful. Virtual reality (VR) has found many applications in education; and the resources of virtual education such as virtual campus, virtual laboratory etc. are used more and more widely, especially in the field of higher education. But so far virtual campus was mainly regarded as a means of image exhibition, and virtual laboratories were no more than 2D display of experimental processes and equipments. To make better use of these resources, this paper puts forward the concept of networked virtual experiment systems based on virtual campus by combining the virtual laboratory and virtual campus with the technique of LAN (Local area network), and establishes its theoretical model. Finally, a networked virtual experiment system based on virtual campus is developed using VRML and 3DSMAX. Networked virtual experiment system based on virtual campus has a promising future for various applications in higher education.
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