Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1064
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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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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E-Mail Spam Detection Using SVM and RBF
Статья научная
In today's life internet is an important part. We spend most of our time on internet. One of the important features of internet is communication. Email is a mode of communication which is used for the personal and business purpose. Spam emails are the emails recipient does not wish to take delivery of; it is also called unwanted bulk email. Emails are used each day by number of user to converse around the world. At present large volumes of spam emails are reasoning serious trouble for Internet user and Internet service. Such as it degrade user investigate knowledge, it assists transmission of virus in network, it increases load on network traffic. It also misuses user time, and energy for legal emails among the spam. For evade spam there are so many conventional anti-spam technique includes Bayesian based sort, rule based system, IP blacklist, Heuristic based filter, White list and DNS black holes. These methods are based on satisfied of the post or links of the mail. In this paper we proposed an efficient spam filtering technique based on neural network. The technique used is RBF a neural network technique in which neuron are trained. The results obtained by using this technique are compared with SVM. The parameter meter for comparison is precision and accuracy. On the basis of these two parameters we compared the proposed technique with SVM.
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E-learning Tools to Improve Students’ Learning Experience: a case study
Статья научная
E-learning refers to the way people communicate and learn electronically which has only recently emerged as a key source of competitive advantage in the information society. With the development of the Information and Communication Technologies, E-Learning is argued to become a new and effective learning method and environment besides classroom based learning. Although still an emerging field, many researchers suggest that it offers many benefits that are radically different from a conventional classroom-based learning environment and can still generate result for students. It could be providing independent learning programme for internal students, external students, distant students, and training purpose. However, it is also revealed in literature that E-Learning has been used more indirectly as a tool for organising study courses and educational programmes. The questions such as “can E-Learning be made as a learning strategy” and “can E-Learning replace classroom-based modes of learning and teaching” remain unanswered. This research intends to explore various aspects with regards to how and to what extent E-Learning has been used to improve teaching and learning activities using the University of Bolton as a case study. It also intends to verify the main findings from the literature review via employing a case study approach and hence make comparisons between the national trends of E-Learning usage and the chosen case. The main research findings from this study are presented in this paper.
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EMCAR: Expert Multi Class Based on Association Rule
Статья научная
Several experimental studies revealed that expert systems have been successfully applied in real world domains such as medical diagnoses, traffic control, and many others. However, one of the major drawbacks of classic expert systems is their reliance on human domain experts which require time, care, experience and accuracy. This shortcoming also may result in building knowledge bases that may contain inconsistent rules or contradicting rules. To treat the abovementioned we intend to propose and develop automated methods based on data mining called Associative Classification (AC) that can be easily integrated into an expert system to produce the knowledge base according to hidden correlations in the input database. The methodology employed in the proposed expert system is based on learning the rules from the database rather than inputting the rules by the knowledge engineer from the domain expert and therefore, care and accuracy as well as processing time are improved. The proposed automated expert system contains a novel learning method based on AC mining that has been evaluated on Islamic textual data according to several evaluation measures including recall, precision and classification accuracy. Furthermore, five different classification approaches: Decision trees (C4.5, KNN, SVM, MCAR and NB) and the proposed automated expert system have been tested on the Islamic data set to determine the suitable method in classifying Arabic texts.
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Статья научная
In this paper we have shown how to use conductive sensor, Zigbee and 74HC14 Inverter to monitor the water level and to control the working of pump. This project is designed to automatically fill the over head tank when it gets empty and monitor the water level in it. The motor is switched ON when the water level in the overhead tank drops below a pre fixed low level (on point) and puts off the motor when water level rises up to pre fixed high level (off point).The motor is also switched off during the following conditions: when the sump water is exhausted before filling overhead tank, pump running dry, mains voltage fluctuations. We also introduce an energy efficient routing protocol for Wireless Sensor Networks (ERPWS) for Conductive Sensor based Water Level Monitoring and Control System using Zigbee (XBEE 802.15.4) in terms of energy consumptions, the packet loss ratio, network lifetime and the average delivery delay. The XBEE used here is XBEE Pro Series 1(XBP24-AWI-001) and IC used is 74HC14 Hex Inverting Schmitt trigger. Simulation results have been obtained by using NS2 simulator. The evaluation results show that the energy consumption of routing using ERPWS is significantly lower than LEACH and traditional routing protocols.
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Статья научная
This project intends to develop an effective educational media that is not only rich in cultural content but also feasible in the museum setting. We want to introduce the Mao-Kung Ting, one of the most valuable collections of the National Palace Museum, to the public in two key aspects—its aesthetic beauty as an antique bronze cauldron, and its historical significance of carrying the longest bronze inscriptions ever discovered among unearthed bronze in China, which has made it plays an important role in the evolution of Chinese characters. Our mission is to develop an interactive installation that could help the audiences to understand this critical cultural heritage with ease. The major techniques that have been employed to facilitate this process include intuitive interactive interface, computer graphics animation, as well as an immersive environment with audio and video. Finally, two case studies were presented to show how the use of multimedia technology is helping to enhance visitors’ experience while the key challenges of the contemporary curatorial tasks are being discussed.
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Economic Designing of PV/FC/Wind Hybrid System Considering Components Availability
Статья научная
This paper presents an Optimization Sizing of a stand-alone PV/FC/Wind Hybrid System (PFWHS) to optimize the sizes of components of PFWHS. Based on PSO algorithm, one optimal sizing method was developed to determine the optimal configuration of system that can achieve the load required power supply probability (Reliability) with a minimum overall cost of energy (OCE).PFWHS costs involve investments, operation and maintenance as well as loss of load costs. The applied wind and radiation datasets belong to northwest region (Jolfa, latitude: 38_56, longitude: 45_37, altitude: 710, m) of Iran. In this paper the impact of availability of PFWHS components is investigated on optimal sizing. So, to investigating the impact of component availability rate on PFWHS costs and reliability due to failure and repair rate of PFWHS components and uncertainty in wind speed and solar irradiance, two scenarios are considered. In first scenario the availability of all components is considered 1 and in second scenario isn’t considered 1 because of failure and repair rate of components and uncertainty in wind speed and solar irradiance. Obtained results prove that while the overall cost of energy is optimized, the reliability indices are within a satisfactory bound with regard to the reliability standards. Also the results indicate that considering complete availability of components causes more reliability rate, so to achieve the actual behavior of PFWHS, the rate of components availability must be considered in suitable insight to designer for supply the load.
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