International Journal of Modern Education and Computer Science @ijmecs
Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1096

Spatial and Transform Domain Filtering Method for Image De-noising: A Review
Статья научная
Present investigation reveals the quantum of work carried in the filtering methods for image de-noising. An image is often gets corrupted by various noises that are visible or invisible while being gathered, coded, acquired and transmitted. Noise influences various process parameters that may cause a quality problem for further image processing. De-noising of natural images is appears to be very simple however when considered under practical situations becomes complex. It has been cited by various author that parameter such as type and quantum of noise, image etc. through single algorithm or approach becomes cumbersome when results are optimized. In order to improve the quality of an image noise must be removed when the image is pre-processed and the important signal features like edge details should be retained as much as possible. The search on efficient image de-noising methods is still a valid challenge at the crossing of functional analysis and statistics. This paper reviews significant de-noising methods (spatial and transform domain method) and their salient features and applications. One filter in each category has been taken in consideration to understand the characteristics of both spatial and transform domain filters.
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Specialization Impact on Internet Resource Usage: Omani Undergraduate Learner’s Perspectives
Статья научная
The current educational processes need various tools and technological supports in order to attain the required level of knowledge. The learning processes have been simplified with the help of different resources including internet resources. The usage of internet resources usage depends on the learner’s requirements in the field of study. This research had identified the significant impacts of the specialization of the learners on the internet resource usage. Also, the paper identified some specializations that have major influences in using such internet resources in learning processes. The study had been conducted in Omani undergraduate student’s environment with respect to selected specializations. The specialization impacts on the frequency of using internet resources, places of searching and purpose of using internet resources in the learning processes were analyzed using conditional probabilities and impacts had been identified with the help of decision tree diagram. The results showed that the students studying Information Technology specialization had greater impact in using internet resources in their learning processes compared to others at undergraduate levels.
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Specific queries optimization using Jaya approach
Статья научная
The Fast query engine is a requirement as a supporting tool for the semantic web technology application such as Electronic Commerce environ. As the large data is represented using the effective data representation called RDF. The focus of this paper is to optimize the specific type of the query called Cyclic query and star query on main-memory RDF data model using ARQ query engine of Jena. For the considered problem, we ruminate a Jaya algorithm for rearrangement of the order of triple pattern and also compare the results with an already proposed approach in the literature. The evaluation result shows that Jaya performs better in terms of execution time in comparison to Ant Colony Optimization.
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Speed Learning: Maximizing Student Learning and Engagement in a Limited Amount of Time
Статья научная
Active learning has warranted great promise in improving student engagement and learning. It is not a new thought and has been promoted and encouraged as early as the 1980s. Due to the many benefits of active learning it is being practiced by many faculty in their classrooms. Faculty are urged to self-reflect on their teaching styles and work on improving the pedagogies to capture and maintain student interest by increasing student engagement. Although active learning has been used as an instrument to engage students and ultimately increase learning, it has seldom been implemented to directly impact learning relative to time. This paper explores the application of active learning pedagogy to help achieve maximum learning in a limited period of time. The active learning method employed in this study is grounded in classic pedagogies that have been developed based on various psychological theories of learning, motivation and engagement. After the employment of a series of this active learning technique a survey of the students revealed an increase in student learning.
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Stabilitty of Anti-periodic Solutions for Certain Shunting Inhibitory Cellular Neural Networks
Статья научная
In this paper, the existence and exponential stability of anti-periodic solutions for shunting inhibitory cellular neural networks (SICNNs) with continuously distributed delays are considered by constructing suitable Lyapunov fuctions and applying some critial analysis techniques. Our results remove restrictive conditions of the global Lipschitz and bounded conditions of activation functions and new sufficient conditions ensuring the exist-ence and exponential stability of anti-periodic solutions for SICNNs are obtained. Moreover, an example is given to illustrate the feasibility of the conditions in our results.
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Steganography on RGB Images Based on a “Matrix Pattern” using Random Blocks
Статья научная
In this paper, we describe a novel spatial domain method for steganography in RGB images where a secret message is embedded in the blue layer of certain blocks. In this algorithm, each block first chooses a unique t1xt2 matrix of pixels as a “matrix pattern” for each keyboard character, using the bit difference of neighbourhood pixels. Next, a secret message is embedded in the remaining part of the block, those without any role in the “matrix pattern” selection procedure. In this procedure, each pattern sums up with the blue layer of the image. For increasing the security, blocks are chosen randomly using a random generator. The results show that this algorithm is highly resistant against the frequency and spatial domain attacks including RS, Sample pair, X2 and DCT based attacks. In addition, the proposed algorithm could provide more than 84.26 times of capacity comparing with a competitive method. Moreover, the results indicated that stego-image has almost 1.73 times better transparency than the competitive algorithm.
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Stereo rectification of calibrated image pairs based on geometric transformation
Статья научная
The objective of stereo rectification is to make the corresponding epipolar lines of image pairs be parallel to the horizontal direction, so that the efficiency of stereo matching is improved as the corresponding points stay in the same horizontal lines of both images. In this paper,a simple and convenient rectification method of calibrated image pairs based on geometric transformation is proposed, which can avoid the complicated calculation of many previous algorithms such as based on epipolar lines, based on fundamental matrix or directly depend on corresponding points. This method is divided into two steps including coordinate system transformation and re-projection of image points. Firstly, we establish two virtual cameras with parallel optical axis by coordinate system transformation based on the pose relationship of the two cameras from calibration result. Secondly, we re-project the points of the original image onto new image planes of the virtual cameras through geometrical method, and then realized the stereo rectification. Experiments of real stereo image pairs show that the proposed method is able to realize the rectification of stereo image pairs accurately and efficiently.
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Stochastic game with lexicographic payoffs
Статья научная
Stochastic games are discussed as a priva-te class of a general dynamic games. A certain class of lexicographic noncooperative games is studied - lexi-cographic stochastic matrix games . The problem of the existence of Nash equilibrium is studied with two analyses - standard and nonstandard way. Standard means using the same kind of mixed strategies in case of scalar games. In this case in lexi-cographic stochastic matrix game Nash equilibrium may not be existed. Its existence takes place in relevant stochastic affine matrix game to the existence of Nash equilibrium. In game a set of Nash equi-librium is given by means of relevant stochastic affine matrix game's set of equilibrium. The sufficient condi-tions of the existance such affine game is proved. In nonstandard way of analyses we use such mixed stra-tegies, they use components with lexicog-raphic probabilites. In this case the kinds of subsets of a set of equilibrium in game are described.
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Статья научная
Purpose – Achieving organizational excellence requires high-levels of commitment and coordination of multiple dimensions throughout an organization. One dimension that most organizational excellence frameworks highlight is the necessity of having a comprehensive learning system, which focuses on knowledge and training. Therefore, a proper understanding of knowledge management is important to identify the factors that drive the achievement of high organizational performance and excellence. Design/methodology/approach – A case study approach has been used, which utilized in-depth interviews with key personnel to obtain valuable insights into the use of strategic knowledge management to drive operational excellence. While the survey was conducted to assist in analyzing certain perspectives related to knowledge management within the organization. Findings – The main findings highlight how the emerging enterprise social network systems have played a major role in institutionalizing collaboration and corporate socializing within the organization, which are both important factors for strategic knowledge management to be successful. Based on the study, a framework has been proposed to assist in the successful implementation of strategic knowledge management for the achievement of organizational excellence. Research limitations/implications – Due to the research approach used some of the findings may include varying degrees of bias in the responses obtained. In addition, due to the lack of time available the proposed framework was not evaluated. Originality/value – Investigating the link and relationship between strategic knowledge management and organizational performance that lead to higher levels of organizational excellence.
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Strategies of Nonsolidary Behavior in Teaching Organization
Статья научная
A system of interpersonal relationship and its modeling in the form of finite noncooperative game is studied in this article by means of payoff functions. In such games for the main principle of optimality Nash’s Equilibrium Situation is acknowledged. The stages of development of Game Theory are analyzed including the modern situation. Two groups – nonsolidary and solidary of different behaviors characterized for the relationship are defined. The strategies of nonsolidary behavior characterized for the strategic relationships of the players are described and the strategies of solidary behavior are connected with negotiations and agreements. Teaching organization is defined as a management of system comprising a p teacher (professor) and K = {1,2,..., n} collective of pupils (students). Each participant of s system has its own interest and difference from each other. This situation gives us a ground to consider some aspects of Game Theory model for optimal management of s.
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Structural Protein Function Prediction - A Comprehensive Review
Статья научная
The large amounts of available protein structures emerges the need for computational methods for protein function prediction. Predicting protein function is mainly based on finding similarities between proteins with unknown function with already annotated proteins. This may be achieved using different protein characteristics: sequences, interactions, localization, structure and or psychochemical. A lot of review papers mainly focus on sequence and psychochemical features-based methods. This is because sequence and psychochemical data are easy to deal with and to interpret the results, and much available compared to protein structures. However, structure-based computational methods provide additional accuracy and reliability of protein function prediction. Therefore, unlike many review papers, this paper presents an up-to-date review on the structure-based protein function prediction. The aim was to provide a recent and comprehensive review of protein structure related topics: function aspects, structural classification, databases, tools and methods.
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Student Learning Ability Assessment using Rough Set and Data Mining Approaches
Статья научная
All learners are not able to learn anything and everything complete. Though the learning mode and medium are different in e-learning mode and in classroom learning, similar activities are required in both the modes for teachers to observe and assess the learner(s). Student performance varies considerably depending upon whether a task is presented as a multiple-choice question, an open-ended question, or a concrete performance task [3]. Due to the dominance of e-learning, there is a strong need for an assessment which would report the learning ability of a learner based on the learning skills under various stages. This paper focuses on assessment through multiple choice questions at the beginning and at the end of learning. The learning activities of the learner are tracked during the learning phase through a Continuous Assessment test to realize the understanding level of the learner. The scores recorded in the database is analyzed using a Rough Set Approach based Decision System. The effectiveness of teaching learning process indicates the learning ability of the learner, presented in a Graphical form. It is evident from the results that the entry behavior and the behavior while learning determine the actual learning. Students generate internal opinion as they monitor their engagement with learning activities and tasks and also assess progress towards goals. Those who are effective at self-regulation, however, produce better feedback or are able to use the self-opinion they generate to achieve their desired goals. The tool developed assists the teacher to be aware of the learning ability of learners before preparing the content and the presentation structure towards complete learning. In other words, the developed tool helps the learner to self-assess the learning ability and thereby identify and focus to gain the lacking skills.
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Student testing and monitoring system (STMS) using Nlp
Статья научная
In the domain of knowledge, there is a rising demand for such a System to provide learning support via a platform which can generate any sort of questions automatically from provided source either (PDF) books or simply any keyword against a user needs to perform a test where STMS serves the purpose. Regarding Keyword operation, the System scraps all the text from Wikipedia and converts it into multiple choice questions. Moreover, it summarizes raw text from Wikipedia and parse the text from provided content to generate Multiple-Choice Questions(MCQs). The System also finds all the Named Entities and POS (Parts of speech tags) in the content to create relevant questions. The questions include Multiple-Choice Questions(MCQs), Cloze based questions and WH- questions (why, where, when etc.). In addition, when users score standard points in the test then they qualify for earning zone where they can earn money ($ Dollars) for scoring points in each test. The Income comes from AdSense applied on the website and other Local ads, Affiliating marketing and advertisements. All in all, the System would help in educational learning by providing helping material in the lacking knowledge areas after analyzing the tests users have performed while the Web-Traffic is the key to Success for monetary benefits.
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Student-centered Role-based Case Study Model to Improve Learning in Decision Support Systems
Статья научная
One of the important learning objectives of our bachelor course on "Techniques in Decision Support Systems" is to develop understanding of core decision making process in real-life business situations. The conventional teaching methods are unable to explain complexities of real-life business. Although the classroom discussions can be effective to understand general factors, such as opportunity cost, return on investment, etc. affecting business decisions, the effects of factors like dynamic business environment, incomplete information, time pressure etc. can not be truly explained through such simple discussions. In this paper, we describe our experience of adopting student-centered, role-based, case study to deal with this situation. The interactive case-based study not only provided students with experiential learning, but also gave them liberty to test their thoughts. As a result, we observed improved students' learning as well as improved grades. In addition, this approach made classes more dynamic and interesting.
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Students Classification With Adaptive Neuro Fuzzy
Статья научная
Identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. In this article, we have tried to design an intelligent system which can separate and classify student according to learning factor and performance. a system is proposed through Lvq networks methods, anfis method to separate these student on learning factor . In our proposed system, adaptive fuzzy neural network(anfis) has less error and can be used as an effective alternative system for classifying students.
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Students' Understanding of Selected Aspects of Interface Class in Java
Статья научная
This study examines the understanding of various aspects relating to the concept of interface class by Management Information Systems students. The examined aspects were: definition, implementation, class hierarchy and polymorphism. The main contributions of this paper are as follows: we developed a questionnaire addressing the above aspects; we classified and analysed the students' responses to determine the students' understanding of the above aspects and to highlight common faulty solutions. The results obtained reveal that majority of the students demonstrated understanding of definition and implementation of interface class, however, only two- thirds of the students demonstrated understanding of interface class in the context of class hierarchy and only one third of them demonstrated understanding of polymorphism in the context of interface class. The students’ utterances from the interviews shed light on their difficulties.
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Статья научная
Machine learning-based prediction models are valuable prediction tools for assessing university performance as well as decision support tools for university governance and higher education system design. The prediction of student outcomes to enhance learning and teaching quality is one subject that has attracted considerable attention for different purposes. The first objective of this study is to develop and validate a prediction model using Machine Learning algorithms that predict students' outcomes in the case of Moroccan universities based only on the outcomes of courses taken in the previous semesters of university studies. This prediction model can be used as a basis for many subsequent studies on different aspects of higher education such as governance, pedagogy, etc. As a first application, we explore the responses of this prediction tool to analyze the outputs of the online learning experience that took place during the Covid-19 pandemic period. To achieve this, four machine learning algorithms are tested such as J48 decision tree, Random Forest, Multilayer Perceptron, and Naïve Bayes. The experimentations are developed by using Weka and the two metrics “accuracy” and “ROC Area” enable to assess the predictive performance of the models. The obtained results show that the Random Forest-based model provides superior results, as evidenced by its accuracy-ROC area, which reached an accuracy of 90% with a ROC Area of 95%. The use of this model to explore the outcomes of the distance learning experience taken during the Covid-19 pandemic, reveals a failure in the prediction performance of the model during the Covid-19 pandemic period, which indicates a change in the system's behavior during this period when teaching moved to the full online version in the year 2019/2020 and returned fully face-to-face in the 2021/2022 year. The failure in the machine learning algorithms' performance when the system changes its behavior can be a limitation of using prediction models based on machine learning in this context. On the other hand, these models can be used if they are properly designed to identify changes in the behavior of a system as shown in this study. Therefore, the proposed Random Forest-based model has the capability to forecast student outcomes accurately and can be applied for diverse analyses within the Moroccan education system. These analyses include but are not limited to identifying students at risks, guiding student orientation, assessing the influence of teaching approaches on student achievement, and evaluating training effectiveness, among others.
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Studies on ICT Usage in the Academic CampusUsing Educational Data Mining
Статья научная
Inthe era of competition, change and complexity, innovation in teaching and learning practices in higher education sector has become unavoidable criteria.One of the biggest challenges that higher education system faces today is to assessthe services provided through Information and Communication Technology(ICT) facilities installed in the campus. This paper studies the responses collected through survey on ICT, in the campusof the University of Burdwan, among the students and research scholarswith the help ofan effective data mining methodology - Variable Consistency Dominance-based Rough Set Approach (VC-DRSA) model to extract meaningful knowledge to improve the quality of managerial decisions in this sphere. It is an extended version of Dominance Rough Set Approach (DRSA) and is applied here to generate a set of recommendations that can help the university to improvise the existing services and augmenting the boundaries of ICT in future development.
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Статья научная
The FPGA (Field Programmable Gate Array) circuits contain programmable logic components and are increasingly popular in implementing the applications for obtaining and processing signals. FPGA represents a modern development trend in digital electronics. The integration in the work with students of this trend is a difficult task, but also useful, because many students face problems when they must use a design environment. The application of FPGA technology can be useful to students either for the laboratory work on advanced topics, or for obtaining skills to use an industry standard design environment. The purpose of this paper is to conduct studies on the need to integrate the FPGA digital electronics trend in the laboratory didactic activity of the students. As case study, we present the design of a control circuit and its implementation in a FPGA, i.e. on a Basys2 board with Xilinx programming environment.
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Study of Blended Learning Process in Education Context
Статья научная
Education is one of the areas that are experiencing phenomenal changes as a result of the advancement and use of information technology. Mobile and e-learning are already facilitating the teaching and learning experience with the use of latest channels and technologies. Blended learning is a potential outcome of advanced technology based learning system. The charm of blended learning approach lies in the adaptation of technology aided learning methods in addition to the existing traditional based learning. With the introduction of technology, the overall learning as well as teaching experience is considerably enhanced by covering negative aspects of the traditional approach. In this paper a blended learning model for higher education where traditional classroom lectures are supported via e-learning.
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