Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 968
An efficient clustering algorithm for spatial datasets with noise
Статья научная
Clustering is the technique of finding useful patterns in a dataset by effectively grouping similar data items. It is an intense research area with many algorithms currently available, but practically most algorithms do not deal very efficiently with noise. Most real-world data are prone to containing noise due to many factors, and most algorithms, even those which claim to deal with noise, are able to detect only large deviations as noise. In this paper, we present a data-clustering method named SIDNAC, which can efficiently detect clusters of arbitrary shapes, and is almost immune to noise – a much desired feature in clustering applications. Another important feature of this algorithm is that it does not require apriori knowledge of the number of clusters – something which is seldom available.
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An environment aware learning-based self-adaptation technique with reusable components
Статья научная
Self-adaptive systems appeared in order to reduce the effort of manual software maintenance. Apart from software attributes, for example, different alternative software modules, self-adaptation decisions depend on environmental attributes, for example, service rate, bandwidth etc. Current well-known self-adaptation approaches can be further improved by incorporating environmental attributes. Moreover, reducing maintenance effort includes minimizing both operational and development effort. To reduce the effort of developing self-adaptive software, the constituent components should be reusable. This paper proposes a technique to incorporate environmental attributes to learning-based self-adaptation and to increase the reuse potential of self-adaptive system components. The environmental attributes are provided as a constraint to an optimization problem which results in an optimal software attribute selection. Design patterns for self-adaptive system components are proposed to improve its reusability. The proposed technique was validated on a news serving website called Znn.com. According to renowned reusability metrics such as Lines of Code (LOC), Message Passing Coupling (MPC) and Lack of Cohesion of Methods 4 (LCOM4), the proposed technique improved reuse potential. The website was further tested for adaptation effectiveness under two scenarios – adaptation and without adaptation. According to our experiments, Adaptation gradually improved the main goal response time of the website where it performed poorly without adaptation.
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An evolutionary model for selecting relevant textual features
Статья научная
From a philosophical point of view, the words of a text or a speech are not held just for informational purposes, but they act and react; they have the power to react on their counterparts. Each word, evokes similar or different senses that can influence and interact with the following words, it has a vibratory property. It's not the words themselves that have the impact, but the semantic reaction behind the words. In this context, we propose a new textual data classification approach while trying to imitate human altruistic behavior in order to show the semantic altruistic stakes of natural language words through statistical, semantic and distributional analysis. We present the results of a word extraction method, which combines a distributional proximity index, a selection coefficient and a co-occurrence index with respect to the neighborhood.
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Статья научная
The intention of this paper is to analyze how a behavior of a student will influence us in gauging their performance level rather than considering their traditional examination scores. This approach is considered to be one of the informal approaches which guide many school managements to identify good, average and poor category of students. The main criteria used here is behavioral science which explores activities and interactions among the student community when they are inside the school campus. School-Wide Positive Behavior Support can assist in addressing the issues related to the prevention, educational identification and effective intervention implementation through its systemic logic, data-based decision making, and capacity building within and across schools. Clustering is the process of grouping a set of data objects into multiple groups or clusters with high similarities and dissimilarities. Dissimilarities and Similarities are assessed on the attribute values describing the objects and often involve distance measures. Clustering acts as a data mining tool by having its roots in many application areas such as biology, security, business intelligence, web search etc. In this survey, we have involved 200 + students who are currently studying engineering streams in various classes that includes first semester to final semester. Their age group was in the range of 18 to 22 years. Their behavioral survey has been conducted over a span of 4 to 6 months by closely observing their activities, mannerisms and then evaluated by entering in to this system by using the evaluation interface. This evaluation interface consists of 15 features with 4 optional choices. Each choice is rated with a specific numeric value. By taking one of the choices among all the 15 features for each of the student, at the end, he/she will get some score which will be stored in a database. With the help of this score, a manual grouping was done. Later, for the same dataset, a soft computing technique has been applied by working with self organizing feature map algorithm for grouping the students.
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Статья научная
Synchronous and asynchronous e-learning are two popular e-learning modes that are commonly used in distant learning education. The study investigates how synchronous and asynchronous e-learning affect the academic performance of students. A questionnaire was used to collect data for this study from some students of the National Open University of Nigeria. The findings showed that students' attitude to synchronous and asynchronous e-learning affect their academic performance. The results demonstrated that only 60% of the respondents understand what asynchronous and synchronous e-learning means. Also, only 55% of the respondents believed that asynchronous and synchronous e-learning mode has a positive impact on their academic performance. Moreover, only 52% of the respondents are of the opinion that the curriculum in use at National Open University needs to be updated to increase the impact of the e-learning mode on the learners.
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Статья научная
Currently, the online discussion forums have become the focal point for e-learning in many Higher Learning Institutions (HLIs); this is due to the ubiquitous of Information and Communication Technology (ICT) tools, significant rate and fast growing technology adoption and use in many fields including education. However, developing countries, such as Tanzania, are experiencing technical adoption difficulties, such as limited access to computers, problems with Internet connections as well as the technological reliance gap between tutors and learners; these affect the use of technology in Teaching and Learning (T/L). This study aims to use an Online Discussion Platform (onlineDP) to bridge the technological reliance gap between the tutors and learners in HLIs in Tanzania. In this study, the literature review and qualitative research methods were conducted to develop the prototype of the platform. The UMBC semantic similarity service was used to develop the contents filter used to reduce the number of duplicate discussion questions. The application was mainly developed using Laravel Pre-processor (PHP) framework and My Structured Query Language (MySQL) database. The result is the web-based application prototype that enhances the collaborative learning environment in HLIs in Tanzania. The technologies to be used for T/L, should consider both sides of tutors and learners as well as the theoretical framework for their implementations.
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An optimized approach towards reversible adder/subtractor design on QCA
Статья научная
In the present era of miniaturization, higher power dissipation in form of heat has become a very critical issue for the digital Circuits. This excessive heat may result in the lower chip reliability and even destroy it. Due to this reason a substitute is required for the traditional CMOS technology, Reversible logic is a paradigm in this direction. This paper encompasses of the newly proposed SA reversible logic and basic combinational implementations using a single SA building block only resulting in lower circuit level complexity as well as hardware requirement. The output responses and energy dissipation of proposed SA reversible logic are verified and calculated with the help of QCADesigner and QCADesigner-E simulation tools respectively.
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Analyses of impacting factors of ICT in education management: case study
Статья научная
Research studies and attitudes towards ICT use in education management are shifting, and often significantly. This is likely to have a major impact upon ICT and education management. However, the real significance of the impact for educational management has yet to be seen within this research study. The focus of the research study is to investigate and analyses the ICT usage in Education Management. ICT in teaching has an important role and its impact on the advancement of educational processes related to effective teaching and learning, and modern research in this field is almost irreplaceable. Another important element is the use of different software platforms that facilitate learning visible and make it more concrete, more practical and applicable to everyday life. In order to analyze the data a combination of qualitative and quantitative methodology has been used. In order to analyze this, Case study analysis of high schools in city of Skopje, Macedonia is realized. Insights and recommendations are provided.
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Analysis of Experimental Research Results Focused on Improving Student Psychological Health
Статья научная
The students' psychological health in high education is still being a problematic issue. This article describes the importance of ensuring students' psychological health in higher education today and related empirical research results. The aim of this paper is exploring and analysis research results focused on students' psychological health. To determine the students' psychological health there were used special psychodiagnostic methods. The components of the psychological health were divided as 1) satisfaction level; 2) perceptions of a healthy lifestyle; 3) emotional stability; 4) psychoemotional state; and 5) attitude towards themselves. Obtained results on students' psychological health indicate specific conclusions about various psychological health indicators and the relationship between behaviour and internal health, including in emotional, cognitive and behavioural areas. The results of this research work showed that one of the important indicators of students' psychological health is a decrease in the level of emotional distress and emotional instability (neuroticism, nervousness), a positive change in students' internal state, and an increase in students' satisfaction with their educational environment. The results could be used in the high education system, especially measuring and monitoring students' psychological health.
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Статья научная
The development of the Internet in Indonesia is quite rapid, it is marked by the increasing use of social networks, especially Twitter. Not only to share status or stories, Twitter has become become a means of promotion and campaign for elections. The Twitter data can be used to find out the political polarization in Indonesia that is needed in the 2019 presidential election. The method used in this research is sentiment analysis using naïve bayes classifier and social network analysis using the calculation of network attribute values and centrality values. 8.814 Twitter data was collected using data crawling method. The data are divided into three subsets consisting of jokowi’s sentiments, prabowo’s sentiments, and pilpres’s sentiments. Final result of the sentiment analysis is classified sentiments into positives, negatives, and neutral. The average value of the classification results was 91.27% positive sentiment, 7.56% negatives sentiment, and 1.17% neutral sentiment. This classification yielded the average accuracy of 69.2% for jokowi’s sentiments and 100% for prabowo sentiments. The classification accuracy calculation uses ROCs method. Final results of the social network analysis based on the calculation of network attributes yielded 277 nodes, 7.950 edges, 57,401 average degree, 56.44 average weighted degree, network diameter is 4, 1.853 average path length, 0.201 density, and 5 of number communities. Centrality values generates the 5 most influential actors in social network interactions are jokowi’s of first rank, 2nd SBYudhoyono’s, 3rd detikcom, 4th yjuniardi, 5th mohmahfudmd.
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Analysis of Large Set of Images Using MapReduce Framework
Статья научная
Due to the limitations of a physical memory, it is quite difficult to analyze and process big datasets. The Hadoop MapReduce algorithm has been widely used to process and mine such large sets of data using the Map and Reduce functions. The main contribution of this paper is to implement MapReduce programming algorithm to analyze large set of fingerprint images which cannot be normally processed due to a limited physical memory in order to find the features of these images at once. At first, the images are maintained in an image data store in order to be preprocessed and to extract the features for the biometric trait of each user, and then store them in a database. The algorithm preprocesses and extracts the features (ridges and bifurcation) from multiple fingerprint images at the same time. The extracted points are detected using the Crossing Number (CN) concept based on the proposed algorithm. It is validated using data taken from the National Institute of Standards and Technology’s (NIST) Special Database 4. The data consist of fingerprint images for many users. Our experiments on these large set of fingerprint images shows a significant reducing in the processing time to a nearly half when extracting the features of these images using our proposed MapReduce approach.
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Analysis of PV-FC Hybrid System Operation Considering Sale Electricity
Статья научная
This paper presents a hybrid power generation system modeling and simulation with the objective of electricity sale to distribution network (DN) which consists of photovoltaic (PV) module, proton exchange membrane (PEM) fuel cell (FC), hydrogen storage tank (HST) and electrolyzer (EL).Since last researches in optimal FC and PV application aimed in power electronic approach, In this paper the application between FC and PV is considered with the aim of maximizing profit gained due to electricity sale revenue to DN. The revenue from electricity sale to DN considering electricity price in low load, shoulder load and peak load hours is considered as the system profit. Also in a sensitivity analysis the impact of technical parameters of hybrid system components is investigated on system profit. The results showed that the system saves the electricity by hydrogen storage in HST in low load hours and sale it with more prices in shoulder load hours to DN. Also the obtained results show that several technical parameters of PV and PEM FC have considerable impact on system operation and profit.
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Analysis of Students' Performance by Using Different Data Mining Classifiers
Статья научная
Data mining is the analysis of a large dataset to discover patterns and use those patterns to predict the likelihood of the future events. Data mining is becoming a very important field in educational sectors and it holds great potential for the schools and universities. There are many data mining classification techniques with different levels of accuracy. The objective of this paper is to analyze and evaluate the university students' performance by applying different data mining classification techniques by using WEKA tool. The highest accuracy of classifier algorithms depends on the size and nature of the data. Five classifiers are used NaiveBayes, Bayesian Network, ID3, J48 and Neural Network Different performance measures are used to compare the results between these classifiers. The results shows that Bayesian Network classifier has the highest accuracy among the other classifiers.
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Analysis on Energy Optimized Data Collection in Tree Based Ad-Hoc Sensor Network
Статья
Fast and energy efficient data collection in an energy constraint ad-hoc sensor network is always a challenging issue. The network topology and interferences causes significant effects on data collection and hence on sensors’ energy usage. Various approaches using single channel, multichannel and convergecasting had already been proposed. Here in this paper we have shown data collection performance using multi-frequency in channel assignment, and effect of network topology, for moderate size networks of about 50-100 nodes. For the study we have used some realistic simulation models under many-to-one communication paradigm called convergecast, a single frequency channel and TDMA technique to have minimum time slots for convergecasting.
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Статья научная
A well designed website using various search engine optimization (SEO) techniques can help to survive in the competition. Thus, for the students who are likely to be web developer in future; learning the theoretical concept of SEO is not enough. The way in which SEO strategy is being drafted varies as per the purpose of website. Hence along with the concept assimilation, instructor needs to make the student think critically to identify the problem and solve it in best possible way. Hence to explore the board panorama of SEO techniques, experiential and collaborative leaning techniques are used. The main objective of the study is to analyses the impact of these modern techniques on depth of concept assimilation by students. To ascertain the effect of these learning techniques, analytical data of the entire website is analyzed. Also feedback is taken from student to know their perception about the whole process. It has been found that students enjoyed the whole learning process. The analytical data proves that the website performed really well which in turn proves that student got in depth understanding of the concept and they were able to implement it commendably in real world scenario.
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Analyzing the Influencing Factors of Group Learning: A Mixed Approach
Статья научная
The purpose of this paper is to explore which factors influence group learning content, and content analysis is chosen as the research method. The sample for this study is the literature of group learning. 35 books and 1 paper was examined. The coding system for the content analysis is an opened and a self-expanded system in this study, which means that the original coding system can be updated if the new coding item is developed during the data collection. A total of 62 influencing factors are identified in terms of the content analysis. In order to organise them systematically, we categorised them into four aggregations according to one model of the group learning processes:planning, organising, learning process, and evaluation. The result of this study may be used to design a questionnaire and to model group learning process in our further research.
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Analyzing the Performance of SVM for Polarity Detection with Different Datasets
Статья научная
Social media and micro-blogging websites have become the popular platforms where anyone can express his/her thoughts about any particular news, event or product etc. The problem of analyzing this massive amount of user-generated data is one of the hot topics today. The term sentiment analysis includes the classification of a particular text as positive, negative or neutral, is known as polarity detection. Support Vector Machine (SVM) is one of the widely used machine learning algorithms for sentiment analysis. In this research, we have proposed a Sentiment Analysis Framework and by using this framework, analyzed the performance of SVM for textual polarity detection. We have used three datasets for experiment, two from twitter and one from IMDB reviews. For performance evaluation of SVM, we have used three different ratios of training data and test data, 70:30, 50:50 and 30:70. Performance is measured in terms of precision, recall and f-measure for each dataset.
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Analyzing the performance of various clustering algorithms
Статья научная
Clustering is one of the extensively used techniques in data mining to analyze a large dataset in order to discover useful and interesting patterns. It partitions a dataset into mutually disjoint groups of data in such a manner that the data points belonging to the same cluster are highly similar and those lying in different clusters are very dissimilar. Furthermore, among a large number of clustering algorithms, it becomes difficult for researchers to select a suitable clustering algorithm for their purpose. Keeping this in mind, this paper aims to perform a comparative analysis of various clustering algorithms such as k-means, expectation maximization, hierarchical clustering and make density-based clustering with respect to different parameters such as time taken to build a model, use of different dataset, size of dataset, normalized and un-normalized data in order to find the suitability of one over other.
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Anatomy and Diseases of Human Biliary System: An Analysis by Mathematical Model
Статья научная
The objective of this paper is to develop an understanding of the diseases related with gallbladder, liver, and biliary tract. The study focuses on human biliary system that is how bile flows in the human body. This can be done by developing an understanding of gallbladder and bile flowing in the body and related organs very briefly. Gallstone is an important disease of gallbladder and is closely related to pressure drop. A small model for the human biliary system is also analyzed in this study. The cylindrical model of gallbladder and ducts in contraction and extension phase is used for the study. The amount of substances present in the organ varies in these cases. With the help of this study it is concluded that the flux decreases on increasing the radius and length of the cylinder. It is observed that the behavior of flow of bile in gallbladder is similar to the flow of bile in the ducts.
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Application of QFD on Planning courses of Industrial Engineering
Статья научная
Courses are the link between teachers and students. The matching degree of the curriculum and the students’ future development largely affects the future competitiveness of students and students’ satisfaction with the school specialty. Based on industrial engineering specialty of Nanchang University, this article applies fishbone diagram to analyze the direction of students’ future development, and uses questionnaire to collect students’ preference of the future development, and analyzes the collecting data by AHP (analytical hierarchy process). Combining with the weight of the direction of future development and the importance of courses, we find a new combination of curriculum and a plan of rearrangement. By comparing the results with the existing curriculum program, we ultimately find a more scientific way to rearrange the curriculum.
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