International Journal of Modern Education and Computer Science @ijmecs
Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1123
Статья научная
This paper discusses teaching-learning experiences for children using today games and digital interactive activities in order to understand the benefits and difficulties for their use. This study also contextualizes the subject under the light of authors from the fields of design and education, resulting in conclusions about the relationship between the advancement of technology, its integration into the school and the effectiveness of new digital materials designed today.
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Dimensionality reduction using an improved whale optimization algorithm for data classification
Статья научная
Whale optimization algorithm is a newly proposed bio-inspired optimization technique introduced in 2016 which imitates the hunting demeanor of hump-back whales. In this paper, to enhance solution accuracy, reliability and convergence speed, we have introduced some modifications on the basic WOA structure. First, a new control parameter, inertia weight, is proposed to tune the impact on the present best solution, and an improved whale optimization algorithm (IWOA) is obtained. Second, we assess IWOA with various transfer functions to convert continuous solutions to binary ones. The pro-posed algorithm incorporated with the K-nearest neighbor classifier as a feature selection method for identifying feature subset that enhancing the classification accuracy and limiting the size of selected features. The proposed algorithm was compared with binary versions of the basic whale optimization algorithm, particle swarm optimization, genetic algorithm, antlion optimizer and grey wolf optimizer on 27 common UCI datasets. Optimization results demonstrate that the proposed IWOA not only significantly enhances the basic whale optimization algorithm but also performs much superior to the other algorithms.
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Direction to Prepare Item Bank for the Purpose of On-Line Evaluation
Статья научная
Straight forward meaning of On-Line Evaluation is that, few questions are extracted from the question bank and user is asked to "mark" the response. Normally, questions are assumed to be of "objective type". In this paper, this traditional idea is extended and abstract concept of "Item Bank" is introduced. The researchers have developed and tested Item Bank software earlier. The guidelines discussed in the paper are the outcome of this real life experience. The scope of the Item bank would not be confined only the Evaluation of competency of respondents but it covers assessment of the person for fresh recruitments/ Assignments or for the Reward or to Accredit the achievement of the employee performance with the use of client server architecture.
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Discovery of Association Rules from University Admission System Data
Статья научная
Association rules discovery is one of the vital data mining techniques. Currently there is an increasing interest in data mining and educational systems, making educational data mining (EDM) as a new growing research community. In this paper, we present a model for association rules discovery from King Abdulaziz University (KAU) admission system data. The main objective is to extract the rules and relations between admission system attributes for better analysis. The model utilizes an apriori algorithm for association rule mining. Detailed analysis and interpretation of the experimental results is presented with respect to admission office perspective.
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Discrete Model of Commensalism Between Two Species
Статья научная
This paper deals with an investigation on discrete model of host commensal pair. The model comprises of a commensal (S1), a host (S2) that benefit S1, without getting effected either positively or adversely. The model is characterized by a couple of first order non-linear ordinary differential equations. In all, four equilibrium points of the model would exist and their stability criteria is discussed. The model would be stable if each of the eigen values is numerically less than one. Further the growth rates of the species are numerically estimated using Runge-Kutta fourth order scheme.
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Discussion on Adolescent Internet Addiction Counseling Strategies through DEMATEL
Статья научная
Internet addiction and other such problems stem from the high frequency of Internet usage of adolescents. The study aims at working out the counseling strategy proposed to prevent internet addiction among the youth. In this study, DEMATEL was the avenue for creating a discussion with families, schools, the society and analyzing regulations & policies so as to find out the cause- and-effect relationship among them and work out the most efficient counseling strategy. The study result shows that the family plays the most crucial role in curing the adolescents’ Internet addiction through action.
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Distributed Denial of Service Attacks: A Review
Статья научная
A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices using sensors to monitor physical or environmental conditions.WSN is a fluorishing network that has numerous applications and could be used in diverse scenarios. DDoS (Distributed Denial of Service) is an attack where a number of compromised systems attack a single target, thereby causing denial of service for users of the targeted system. The flood of incoming messages to the target system essentially forces it to shut down, thereby denying service to the system to legitimate users.Not much research work has been done in DDoS in WSN.We are conducting a review on DDoS attack to show its impact on networks and to present various defensive, detection and preventive measures adopted by researchers till now.
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Distribution System Planning With Distributed Generations Considering Benefits and Costs
Статья научная
One of the methods used in the design and utilization of distribution systems to improve power quality and reliability of load power supply of consumers, is the application of distributed generation (DG) sources. In this paper, a new method is proposed for the design and utilization of distribution networks with DG resources application by finding the optimal sitting and sizing of generated power of DG with the aim of maximization of its benefits to costs. The benefits for DG are considered as system losses reduction, system reliability improvement and benefits from the sale electricity or from lack of purchase of electricity from the main system. The costs of DG are considered as initial capital, maintenance and operation cost and investment cost. In this paper to solve the optimal sitting and sizing problem a Modified particle swarm optimization (PSO) is applied. Simulations are presented on a 69-bus test distribution system to verify the effectiveness of the proposed method. Results showed that the proposed high-power method to find the optimal points of problem is faster and application of DG resources reduced the losses, costs and improved the system voltage profile.
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Document Summarization Based on Information Retrieval Using Query Search Ranking Method
Статья научная
This work proposes a Query Searching Based Ranking Summarization Data Retrieval (QS-RSDR) method for document summarization based on information retrieval. QS-RSDR ranks query-based retrieval of important information, enabling the creation of a detailed report of information requirements using generated sections of sample documents. Relating Keyword Query Search Summarization (RKQSS) generates the main summary from the most relevant document in the query and then the summary from the other documents. The method resolves similarity terms related to the query using the Word Frequency (WF) method. Sentence ranking weights and sentence frequency improve the accuracy of the retrieved documents. Simulation results show improved accuracy in information retrieval. The proposed method can help address unclear and short queries and understand the nature of the required information behind the query. The paper concludes that QS-RSDR is an effective solution for document summarization based on information retrieval using the query search ranking method.
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Статья научная
In recent years there has been a massive growth in textual information in textual information especially in the internet. People now tend to read more e-books than hard copies of the books. While searching for some topic especially some new topic in the internet it will be easier if someone knows the pre-requisites and post- requisites of that topic. It will be easier for someone searching a new topic. Often the topics are found without any proper title and it becomes difficult later on to find which document was for which topic. A text categorization method can provide solution to this problem. In this paper domain based ontology is created so that users can relate to different topics of a domain and an automated text categorization technique is proposed that will categorize the uncategorized documents. The proposed idea is based on Term Frequency – Inverse Document Frequency (tf -idf) method and a dependency graph is also provided in the domain based ontology so that the users can visualize the relations among the terms.
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Driver behaviour profiling using dynamic Bayesian network
Статья научная
In the recent past, there has been a rapid increase in the number of vehicles and diversification of road networks worldwide. The biggest challenge now lies on how to monitor and analyse behaviours of vehicle drivers as a catalyst to road safety. Driver behaviour depends on the state and nature of the road, the state of the driver, vehicle conditions, and actions of other road users among other factors. This paper illustrates the ability of Dynamic Bayesian Networks towards determination of driving styles with respect to acceleration, cornering and braking patterns. Bayesian Networks are probabilistic graphical models that map a set of variables and their conditional dependencies. Sample test results showed that the 2-Time-slice Bayesian Network model is suitable for generation of driver profiles using only four GPS data parameters namely speed, altitude, direction and signal strength against time. The model classifies driver profiles into two sets of observations: driver behaviour and nature of operational environment. Adoption of the model could offer a cost effective, easy to implement and use solution that could find many applications in vehicle driver recruiting firms, vehicle insurance companies and transport and road safety authorities among other sectors.
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Статья научная
Most programmers and users resort to find individual solution per problem depending on the data and nature of problem, that will lead to solve a specific problem using an algorithm without the ability of this solution to solve a new problem. This variance comes from the difference in algorithm parameters from one problem to another, as these parameters related to data nature, its size, and values it carried that can affect the way algorithm work. Individual solutions lead to increase in time cost and effort spent on solving a new problem, which the new problem requires to work on programming new criteria for algorithm solution. That is prompted us to highlight necessaries to develop main components for algorithms used in practical life, such as data mining algorithms so that a solution designed for one problem can be more easily adapted to new problems with different data structures, within the general scope of decision tree applicability. These algorithm components need control mechanism settings, so when using component to solve problem, there is no need to develop algorithm settings again, regardless data size and data structure. We found that the dynamic solution saves effort and time needed to solve problems with same algorithm. In this paper, we present our methodology for using ID3 decision tree algorithm to mine data dynamically, and the mechanism used to achieve the dynamic solution, that provides a flexible and reusable solution for a wide range of problems that require decision tree support, reducing the need to redesign or reimplement models for each new task The proposed model was tested on three datasets. The proposed model achieved an accuracy of 97%, 97%, and 93% on the breast cancer, heart disease, and diabetes datasets, respectively.
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Dynamic Effort Allocation Problem Using Genetic Algorithm Approach
Статья научная
Effort distribution plays a major role in software engineering field. Because the limited price projects are becoming common today, the process of effort estimation becomes crucial, to control the budget agreed upon. In last 10 years, numerous software reliability growth models (SRGM) have been developed but majority of model are under static assumption. The basic goal of this article is to explore an optimal resource allocation plan to minimize the software cost throughout the testing phase and operational phase under dynamic condition using genetic algorithm technique. This article also studies the resource allocation problems optimally for various conditions by investigating the activities of the model parameters and also suggests policies for the optimal release time of the software in market place.
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Статья научная
In the recent era, there has been a significant surge in the demand for cloud computing due to its versatile applications in real-time situations. Cloud computing efficiently tackles extensive computing challenges, providing a cost-effective and energy-efficient solution for cloud service providers (CSPs). However, the surge in task requests has led to an overload on cloud servers, resulting in performance degradation. To address this problem, load balancing has emerged as a favorable approach, wherein incoming tasks are allocated to the most appropriate virtual machine (VM) according to their specific needs. However, finding the optimal VM poses a challenge as it is considered a difficult problem known as NP-hard. To address this challenge, current research has widely adopted meta-heuristic approaches for solving NP-hard problems. This research introduces a novel hybrid optimization approach, integrating the particle swarm optimization algorithm (PSO) to handle optimization, the gravitational search algorithm (GSA) to improve the search process, and leveraging fuzzy logic to create an effective rule for selecting virtual machines (VMs) efficiently. The integration of PSO and GSA results in a streamlined process for updating particle velocity and position, while the utilization of fuzzy logic assists in discerning the optimal solution for individual tasks. We assess the efficacy of our suggested method by gauging its performance through various metrics, including throughput, makespan, and execution time. In terms of performance, the suggested method demonstrates commendable performance, with average load, turnaround time, and response time measuring at 0.168, 18.20 milliseconds, and 11.26 milliseconds, respectively. Furthermore, the proposed method achieves an average makespan of 92.5 milliseconds and average throughput performance of 85.75. The performance of the intended method is improved by 90.5%, 64.9%, 36.11%, 24.72%, 18.27%, 11.36%, and 5.21 in comparison to the existing techniques. The results demonstrate the efficacy of this approach through significant improvements in execution time, CPU utilization, makespan, and throughput, providing a valuable contribution to the field of cloud computing load balancing.
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Dynamic Malware Analysis and Detection in Virtual Environment
Статья научная
The amount and the complexity of malicious activity increasing and evolving day by day. Typical static code analysis is futile when challenged by diverse variants. The prolog of new malware samples every day is not uncommon and the malware designed by the attackers have the ability to change as they propagate. Thus, automated dynamic malware analysis becomes a widely preferred technique for the identification of unknown malware. In this paper, an automated malware detection system is presented based on dynamic malware analysis approach. The behavior of malware is observed in the controlled environment of the popular malware analysis system. It uses the clustering and classification of embedded malware behavior reports to identify the presence of malicious behavior. Based on the experimentation and evaluation it is evident that the proposed system is able to achieve better F-measures, FPR, FNR, TPR and TNR values resulting in accurate classification leading to more efficient detection of unknown malware compared to the traditional hierarchical classification approach.
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Dynamics of Love and Happiness: A Mathematical Analysis
Статья научная
The human behavior is a combination of several feelings. There are two cases whether a person likes other individual or not. The liking of an individual leads to love and finally happiness. The feelings of love may be in different forms but here considered to be partners' love. There are three aspects of love for the partner: forgetting process (oblivion), the pleasure of being loved (return), and the reaction to the appeal of the partner (instinct). Along with that the appeals and the personalities of the two individuals do not vary in time. This model proves that if the geometric mean reactive-ness to love is smaller than the geometric mean forgetting coefficient and the system is asymptotically stable if the ratio of appeals is greater than the reciprocal of ratio of mutual intensiveness coefficient.
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E-Learning and Its Impact on Rural Areas
Статья научная
E-Learning is referred to as teaching and learning by using electronic media. This methodology supports the use of networking and communications technology in teaching and learning. E-Learning is generally meant for remote learning or distance learning, but can also be used in face-to-face mode. In this paper we have made study about the awareness and impact of E-Learning in selected rural areas in India, the providers and learners ratio and an analysis on the collected data has been made to find the advantages of E-Learning resources and their affect on social and mental development of the individuals belonging to rural areas.
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E-Learning at Private Universities in Kurdistan Region: A Comparative Field Study
Статья научная
Higher education is encountering major alteration in many countries. As well, many innovative learning techniques are emerging due to the speedy growths of technology, internet and communication tools. This thrive of technology has changed various features and conceptions of the traditional learning environments. Recently, the attention has focused on electronic learning (e-learning), which is a form of education that has begun to find its way into different developing countries due to its high potential in improving the educational process. However, different real-world challenges emerged, in which they hampered the application of e-learning in developing countries. Thus, this study aims to identify the status of the actual level of e-learning application among private universities in the Kurdistan region of Iraq. It is believed that the results of this study will greatly ameliorate the currently utilized educational systems.
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Статья научная
Web 2.0 is about social networking and collaboration between the creator and the user. Web 3.0 is termed as intelligent web or semantic web with technologies like big data, linked data, cloud computing, 3D visualization, augmented reality and more to make passive learner into active learner in the learning process. This paper identifies the characteristics of the different generations of web and its effect on the different generations of e-learning and also identifies the various issues related with web 3.0. Finally a study is made on the user preferences and recorded in this paper.
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E-Mail Spam Detection Using Refined MLP with Feature Selection
Статья научная
Electronic Mail (E-mail) has established a significant place in information user’s life. E-Mails are used as a major and important mode of information sharing because emails are faster and effective way of communication. Email plays its important role of communication in both personal and professional aspects of one’s life. The rapid increase in the number of account holders from last few decades and the increase in the volume of emails have generated various serious issues too. Emails are categorised into ham and spam emails. From past decades spam emails are spreading at a tremendous rate. These spam emails are illegitimate and unwanted emails that may contain junk, viruses, malicious codes, advertisements or threat messages to the authenticated account holders. This serious issue has generated a need for efficient and effective anti-spam filters that filter the email into spam or ham email. Spam filters prevent the spam emails from getting into user’s inbox. Email spam filters can filter emails on content base or on header base. Various spam filters are labelled into two categories learning and non-machine learning techniques. This paper will discuss the process of filtering the emails into spam and ham using various techniques.
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