Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1064
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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Study of Recent Charge Pump Circuits in Phase Locked Loop
Статья научная
This paper reviews the design of phase locked loop (PLL) using recently reported charge pump circuits. Lock time, phase noise, lock range and reference spur of each charge pump circuit are investigated. Though improved charge pump circuits are designed recently, their performance is not as effective as the basic charge pump PLL (CP-PLL). Initially the design of PLL using the basic charge pump is completed in this paper and then the PLL using improved charge pumps are redesigned in CMOS 180 nm technology and simulated using Cadence Virtuoso Analog Design Environment. Finally all the charge pumps are compared with respect to the PLL performances. The current starved voltage controlled oscillator (VCO) used for the design of PLL brings about a tuning range of 119.5 MHz to 2.3 GHz. The PLL using different charge pumps produces a lock time which varies from 204 ns to 329 ns. The other parameters like lock range, phase noise and reference spur are also examined.
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Study of Task Scheduling in Cloud Computing Environment Using Soft Computing Algorithms
Статья научная
Cloud computing is a popular computing concept that performs processing of huge volume of data using highly accessible geographically distributed resources that can be accessed by users on the basis of Pay as per Use policy. Requirements of different users may change so the amount of processing involved in such paradigm also changes. Sometimes they need huge data processing. Such highly volumetric processing results in higher computing time and cost which is not a desirable part of a good computing model. So there must be some intelligent distribution of user's work on the available resources which will result in an optimized computing environment. This paper gives a comprehensive survey on such problems and provide a detailed analysis of some best scheduling techniques from the domain of soft computing with their performance in cloud computing.
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Study of performance evaluation of binary search on merge sorted array using different strategies
Статья научная
Search algorithm, is an efficient algorithm, which performs an important task that locates specific data among a collection of data. Often, the difference among search algorithms is the speed, and the key is to use the appropriate algorithm for the data set. Binary search is the best and fastest search algorithm that works on the principle of ‘divide and conquer’. However, it needs the data collection to be in sorted form, to work properly. In this paper, we study the efficiency of binary search, in terms of execution time and speed up, by evaluating the performance improvement of the combined search algorithms, which are sorted into three different strategies: sequential, multithread, and parallel using message passing interface. The experimental code is written in ‘C language’ and applied on an IMAN1 supercomputer system. The experimental results show that the decision variables are generated from the IMAN1 supercomputer system, which is the most efficient. It varied for the three different strategies, which applies binary search algorithm on merge sort. The improvement in performance evaluation gained by using parallel code, greatly depends on the size of data set used, and the number of processors that the speed-up of the parallel codes on 2, 4, 8, 16, 32, 64, 128, and 143 processors is best executed, using between a 50,000 and 500,000 dataset size, respectively. Moreover, on a large number of processors, parallel code achieves the best speed-up to a maximum of 2.72.
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Study on Challenges, Opportunities and Predictions in Cloud Computing
Статья научная
Cloud computing is transforming the way IT is owned and utilized in the present day business scenario. Several predictions by the researchers and analytical enterprises have predicted unprecedented growth for this emerging paradigm. This work is an attempt to analyze the cloud future based on the various reports and predictions published recently. We have explored the various opportunities that will drive the cloud growth. We have also highlighted the effect of cloud in Indian and US market. Significance of the study is validated by conducting the Strength, weakness, opportunity, and Threat (SWOT) analysis. Based on the findings, we have identified the intensity of challenges faced by the various types of cloud deployment model. Correspondingly, we have recommended the critical challenges that need to be addressed first, in order to facilitate the cloud in gaining further momentum.
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Study on Extenics Information Fusion Method and It’s Application
Статья научная
This paper makes analysis on theories of D-S evidential reasoning, rough sets, and extenic sets; and indicates that there are some similarities among the three theories in defining uncertainty sets. Therefore, it’s feasible to introduce relevant theories and methods of extenics into information fusion and a method of extenics fusion (MEF) is presented as well. The method combines extenic correlation function with Dempster rule and is considered a good solution for problems of evidence collision and BPA function in information fusion method based on D-S evidential reasoning. The simulation test shows that MEF is better than the traditional D-S evidential reasoning and is applicable to assess all kinds of problems. Using the method of this paper to evaluate surface water in one area of Northern China, the results were consistent with the fact.
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Study on Overburden's Destructive Rules Based on Similar Material Simulation
Статья научная
Analysis on the current research status, this article studies on the dynamic subsidence principles of overburden rock strata during coal mining based on similar material simulation test. Close ranged industrial photogram metric system was introduced to collect data. After coordinate transformation, matching and model amendment, dynamic subsidence curves which can be used to analyze the continuity characteristics of overburden subsidence, changes of boundary angle and displacement angle, volume transferring law from rock to surface, etc. were got. The result is useful in further study of the dynamic rule of overburden strata and enriches mining subsidence principles.
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Suitability and Contribution of Agile Methods in Mobile Software Development
Статья научная
Boom of mobile app market is phenomenal and so are the challenges for developing these mobile applications. With changing mobile market technology and trends, various technical constraints for building these mobile apps also cropped up with time. Tradition development approaches are unable to tackle these challenges and technical limitations of mobile market. Analyzing this situation researchers have proposed numerous agile practices to develop people oriented mobile app which embrace their changing needs. This paper provides a brief overview of some effective and commonly used agile approaches that adds value to mobile software business. Suitability of these approaches to fit mobile needs is also discussed in this paper. It is suggested that agile innovations offer a solution for mobile applications and examine developer who are in quest of building high quality products.
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