International Journal of Modern Education and Computer Science @ijmecs
Journal articles - International Journal of Modern Education and Computer Science
All articles: 1173
Hybrid Ensemble Learning Technique for Software Defect Prediction
Scientific article
The reliability of software depends on its ability to function without error. Unfortunately, errors can be generated during any phase of software development. In the field of software engineering, the prediction of software defects during the initial stages of development has therefore become a top priority. Scientific data are used to predict the software's future release. Study shows that machine learning and hybrid algorithms are change benchmarks in the prediction of defects. During the past two decades, various approaches to software defect prediction that rely on software metrics have been proposed. This paper explores and compares well-known supervised machine learning and hybrid ensemble classifiers in eight PROMISE datasets. The experimental results showed that AdaBoost support vector machines and bagging support vector machines were the best performing classifiers in Accuracy, AUC, recall and F-measure.
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Scientific article
Software testing is the significant part of the software development process to guarantee software quality with testing a program for discovering the software bugs. But, the software testing has a long execution time by using huge number of test suites in the software development process. In order to overcome the issue, a novel technique called Hybridized Buffalo and Truncation Cyclic Gene Optimization-based Densely Connected Deep Neural Network (HBTCGO-DCDNN) introduced to improve the software testing accuracy with minimal time consumption. At first, the numbers of test cases are given to the input layer of the deep neural network layer. In the first hidden layer, the test suite generation process is carried out by applying the improved buffalo optimization technique with different objective functions namely time and cost. The improved buffalo optimization selects optimal test cases and generates the test suites. After the generation, the redundant test cases from the test suite are eliminated in the reduction process in the second hidden layer. The Truncative Cyclic Uniformed Gene Optimization technique is applied for the test suite reduction process based on thefault coverage rate. Finally, the reduced test suites are obtained at the output layer of the deep neural network The experimental evaluation of the HBTCGO-DCDNN and existing methods are discussed using the test suite generation time, test suite reduction rate as well as fault coverage rate. The comparative results of proposed HBTCGO-DCDNN technique provide lesser the generation time by 48% and higher test suit reduction rate by 19% as well as fault coverage rate 18% than the other well-known methods.
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Hypermedia E-book as a Pedagogical Tool in a Graduation Course
Scientific article
The e-book (www.design-educacao-tecnologia.com) is a support for teaching Hypermedia Design, which constitutes a didactic material to support teaching and research activities for the Design area. The book will gather issues about Design, Education and Hypermedia aimed at offering resources to enhance the use of multiple languages that converge in hypermedia environments, their applicability, techniques and methods in light of Design in Situations of Teaching-Learning. This paper is divided into five parts: the first part introduce the paper subject, the second part shows the e-book Design, Education and Technology, the third part presents the use of this hypermedia e-book as a pedagogical tool in a graduation course in Design, some of the results developed by the students, the fourth part presents the main questions observed about this digital environment and the last part is the conclusion.
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ICT in Higher Education: Wiki-based Reflection to Promote Deeper Thinking Levels
Scientific article
The main purpose of higher education is to produce skilled graduates so that they can think critically and solve real world problems. Presenting a group based solution in a face-to-face class is a common activity in the higher education classroom where other students/peers can actively participate in the follow-up question/answer sessions. Working out a solution together as a group engages students’ independent thinking ability and promotes active learning. This means, that they have the opportunity to reflect on their own thinking and take it to deeper levels of thinking. However, recent trends show that online support to the higher education class - a form of blended learning is growing day by day. This paper proposes a wiki-based (one of the ICT tools) reflection method to follow up regular existing face-to-face classroom presentation activities to promote deeper thinking levels of students in higher education. In this article, Lee’s Model of thinking levels is-used for analyzing the thinking levels of students during their wiki work. The findings of this research work (through experiments) show that the wiki-based reflection method could be an effective way to promote thinking levels of students and hence can be used as a blended learning model to promote reflective and in-depth thinking.
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INSPECT- an intelligent and reliable forensic investigation through virtual machine snapshots
Scientific article
Cloud computing is emerging as a popular paradigm that provides significant advances and utility-oriented services over shared virtualized resources. Despite the advantage of the cloud services, the majority of cloud users are reluctant to access the cloud due to unprecedented security threats in the cloud environment. The increasing cloud vulnerability incidences show the significance of cloud forensic techniques for the criminal investigation. It is challenging to gather the evidence from the abundant cloud data and identifying the source of the attack from the crime scene. Moreover, the Cloud Service Provider (CSP) confines the investigator to carry out the forensic investigation due to the prime concerns in the multi-tenant cloud infrastructure. To cope up with these constraints, this paper presents INSPECT, an investigation model that accomplishes adaptive evidence acquisition with adequate support for dynamic Chain of Custody presentation. By utilizing the VM log files, the INSPECT approach forensically acquires the corresponding evidence from the cloud data storage based on the location of malicious activity. It enhances the evidence acquisition and analysis process by optimally selecting and exploiting the required forensic fields alone instead of analyzing the entire log information. The INSPECT applies the Modified Fuzzy C-Means (M-FCM) clustering with contextual initialization method on the acquired evidence to recognize the source of the attack and improves the trustworthiness of the evidence through the submission of the chain of custody. By analyzing the Service Level Agreement (SLA) of the cloud users, it facilitates the source of attack identification from the clustered data. Furthermore, it isolates the evidence to avert deliberate modification by an adversary in the multi-tenant cloud. Eventually, INSPECT presents the evidence along with the chain of custody information regarding the crime scene. It enables the law enforcement authority to explore the evidence through the chain of custody information and to reconstruct the crime scene using the VM snapshots associated with timestamp data. The experimental results reveal that the INSPECT approach accomplishes a high level of accuracy in the investigation with the improved trustworthiness over the multi-tenant cloud infrastructure.
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IScrum: An Improved Scrum Process Model
Scientific article
Resolving a wide domain of issues and offering a variety of benefits to software engineering, makes the Agile process models attractive for researchers. Scrum has been recognized as one of the most promising and successfully adopted agile process models at software industry. The reason behind vast recognition is its contribution towards increased productivity, improved collaboration, quick response to fluctuating market needs and faster delivery of quality product. Though Scrum performs better for small projects but there are certain challenges that practitioners encounter while implementing it. Experts have made some efforts to adapt the Scrum in a way that could remove those drawbacks and limitations, however, no single effort addresses all the issues. This paper is intended to present a tailored version of Scrum aimed at improving documentation, team’s performance, and visibility of work, testing, and maintenance. The proposed model involves adapting and innovating the traditional Scrum practices and roles to overcome the problems while preserving the integrity and simplicity of the model.
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Scientific article
Medical imaging is the technique and process used to create images of the human body or medical science. Digital image processing is the use of computer algorithms to perform image processing on digital images. Microscope image processing dates back a half century when it was realized that some of the techniques of image capture and manipulation, first developed for television, could also be applied to images captured through the microscope. This paper presents semi-automated segmentation and identification of adenovirus particles using active contour with multi grid segmentation model. The geometric features are employed to identify the adenovirus particles in digital microscopic image. The min-max, 3 rules are used for recognition of adenovirus particles. The results are compared with manual method obtained by microbiologist.
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Scientific article
Producing skilled workforce according to industry required skills is quite challenging. Knowledge of trainee’s enrollment behavior and trainee’s course selection variables can help to address this issue. Prior knowledge of both can help to plan and target right geographic locations and right audience to produce industry required skilled workforce. Globally Technical and Vocational Education Training (TVET) is used to provide skilled workforce for the industry. TVET is an educational stream which focus learning through more practicing with less theory knowledge. In this article, we have analyzed TVET actual enrollment data of 2017 – 2018 session from a TVET training provider organization of Punjab, Pakistan. The purpose of this analysis is to understand trainee’s enrollment behavior and course selection variables which plays an important role in TVET course selection by the trainees. This enrollment behavior and course selection variables can be used to monitor and control industry required and produced skilled TVET workforce. We developed a framework which contain series of steps to perform this analysis to extract knowledge. We used educational data mining techniques of association, clustering and classification to extract knowledge. The analysis reveals that central Punjab youth is getting more TVET education as compare to south and north Punjab, Pakistan. Similarly, trainee’s ‘age group’, ‘qualification’, ‘gender’, ‘religion’ and ‘marital status’ are potential variables which can play important role in TVET course selection. By controlling these variables and integrating TVET training provider institutes, funding agencies and industry, we can smartly produce TVET skilled workforce required for industry nationally and internationally.
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Scientific article
Unnatural patterns in the control charts can be associated with a specific set of assignable causes for process variation. Hence pattern recognition is very useful in identifying process problem. This paper presents a novel hybrid intelligent method for recognition of common types of control chart patterns (CCPs). The proposed method includes three main modules: the feature extraction module, the classifier module and the optimization module. In the feature extraction module, a proper set of the shape features and statistical features is proposed as the efficient characteristic of the patterns. In the classifier module adaptive neuro-fuzzy inference system (ANFIS) is investigated. In ANFIS training, the vector of radius has very important role for its recognition accuracy. Therefore, in the optimization module, cuckoo optimization algorithm (COA) is proposed for finding of optimum vector of radius. Simulation results show that the proposed system has high recognition accuracy.
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Identifying Key Challenges in Performance Issues in Cloud Computing
Scientific article
Cloud computing is a harbinger to a newer era in the field of computing where distributed and centralized services are used in a unique way. In cloud computing, the computational resources of different vendors and IT services providers are managed for providing an enormous and a scalable computing services platform that offers efficient data processing coupled with better QoS at a lower cost. The on-demand dynamic and scalable resource allocation is the main motif behind the development and deployment of cloud computing. The potential growth in this area and the presence of some dominant organizations with abundant resources (like Google, Amazon, Salesforce, Rackspace, Azure, GoGrid), make the field of cloud computing more fascinating. All the cloud computing processes need to be in unanimity to dole out better QoS i.e., to provide better software functionality, meet the tenant’s requirements for their desired processing power and to exploit elevated bandwidth.. However, several technical and functional e.g., pervasive access to resources, dynamic discovery, on the fly access and composition of resources pose serious challenges for cloud computing. In this study, the performance issues in cloud computing are discussed. A number of schemes pertaining to QoS issues are critically analyzed to point out their strengths and weaknesses. Some of the performance parameters at the three basic layers of the cloud — Infrastructure as a Service, Platform as a Service and Software as a Service — are also discussed in this paper.
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Scientific article
The "Igniting Curiosity: A STEAM Journey for Young Minds" (IC-SJYM) program integrates Science, Technology, Engineering, Art, and Mathematics (STEAM) into early childhood education to enhance linguistic and scientific engagement among 5 to 6-year-olds. This study uses a mixed-methods design to evaluate the program's effectiveness, utilizing the Kaufman Survey of Early Academic and Language Skills (K-SEALS) and the Teacher Rating Scale of Children's Motivation for Science (TRS-CMS), alongside qualitative feedback from educators. Results show that the experimental group, following the IC-SJYM program, demonstrated significant improvements in academic performance and motivation towards science compared to a control group with a traditional curriculum. Additionally, qualitative analyses highlight the program's positive impact on expressive language skills, innovative thinking, and a sustained interest in scientific inquiry. These findings suggest that an integrative STEAM curriculum can significantly enhance early learning experiences, advocating for its broader adoption. The IC-SJYM program's success in fostering intellectual curiosity and academic excellence underscores the critical role of STEAM in early childhood education and calls for further research into its potential to revolutionize educational paradigms for young learners.
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Image Watermarking Using 3-Level Discrete Wavelet Transform (DWT)
Article
We have implemented a robust image watermarking technique for the copyright protection based on 3-level discrete wavelet transform (DWT). In this technique a multi-bit watermark is embedded into the low frequency sub-band of a cover image by using alpha blending technique. The insertion and extraction of the watermark in the grayscale cover image is found to be simpler than other transform techniques. The proposed method is compared with the 1-level and 2-level DWT based image watermarking methods by using statistical parameters such as peak-signal-to-noise-ratio (PSNR) and mean square error (MSE). The experimental results demonstrate that the watermarks generated with the proposed algorithm are invisible and the quality of watermarked image and the recovered image are improved.
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Scientific article
The widespread use of Generative Artificial Intelligence tools among students across different educational levels is reshaping students’ attitude and education experience. They use it in various fields, including idea generation, writing assistance, and content creation. This study investigates the impact of the Modern Digital Skills course offered by the University of Jordan on students' digital literacy in Generative Artificial Intelligence. The study will employ a quantitative approach by conducting pre- and post-course surveys to measure changes in students' knowledge, skills, and attitudes across approximately 1,000 undergraduates from different majors at the university. Key variables include students' understanding of Generative Artificial Intelligence, their confidence in using Generative Artificial Intelligence tools, and their ability to critically evaluate AI-generated content and its ethical implications. The findings will determine whether the course significantly enhances students' knowledge, proficiency, critical thinking, and ethical awareness, while also exploring challenges and opportunities in integrating such a course into the academic curriculum. Ultimately, this study aims to provide insights for curriculum committees and decision-makers at universities in Jordan and the Middle East, emphasizing the importance of designing educational programs that foster essential Artificial Intelligence competencies and prepare students for a professional landscape increasingly shaped by Artificial Intelligence technologies.
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Impact of Cognitive and Emotional Intelligence on Quality Education
Scientific article
At present school and colleges are expanding very much quantitatively but less attention is being paid at the quality of education. In order to improve the quality of any course, the present study will be conducted, and this study is related to the improvement of the selection criterion of candidates by introducing the significance of testing emotional intelligence also. Till now the gold standard of selection the candidates for any course, has been cognitive intelligence tests. Previous researches had proved that emotional intelligence is much more important than cognitive intelligence. Then it should also be measured or tested. In other words if a student is cognitively intelligent, will he/she also be emotionally intelligent relatively or not. Is it different according to sex, locality etc. so in order to find out the difference between cognitive and emotional intelligence of students we have performed this study.
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Impact of Foreign Language Proficiency and English Uses on Intercultural Sensitivity
Scientific article
The main purpose of this study was to examine the impact of English uses and English proficiency on inter-cultural sensitivity among 292 Taiwanese participants. Results indicate that there is a significant differential level of English uses across three groups of the participants (high, moderate and low frequency of English uses). Post-hoc comparison indicated that high-frequency English usesrs have significantly higher inter-cultural sensitivity than moderate and low-frequency users. However, the results do not support the hypothesized linkage between foreign language proficiency and inter-cultural sensitivity. The implications from these findings suggest that the frequency of English uses will better equip EFL learners with sufficient socio-linguistic competences and communicative skills compared with English proficiency. Moreover, inter-cultural sensitivity is a skill learned through authentic interaction in an intercultural context. Thus, the MOF in Taiwan should rethink of washback effect of the English Benchmark Policy.
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Impact of Telecommunication Service Quality in Bangladesh on Online Education during Covid-19
Scientific article
The pandemic situation due to covid-19 has disrupted routine activities such as attending classes physically in educational institutions, which insisted on moving towards online education with the help of advent and increased uses of new telecommunication services. Service quality is the prerequisite for customer satisfaction. Service quality assessment is crucial to ensure increased customer satisfaction in any service. Typically, it is not easy to evaluate service quality because of opacity in the information, and incompleteness characteristics of problems. With the collected data through an online survey, this study aims to analyze the facts that influence the students’ perception regarding the impact of telecommunication service quality on online education during the pandemic situation. Initially, some relevant criteria are derived from literature reviews. The proposed model is exerted to evaluate the quality of the online education and telecommunication service in Bangladesh during the covid-19 pandemic with the participation of 350 students answering 39 questions. The collected data is analyzed to assess the current state of service quality by evaluating the students’ satisfaction using the entropy technique. The findings of the study suggest that the online education system in Bangladesh is not interactive enough, and the telecommunication service quality here is not sufficient for this purpose. Telecommunication challenges such as poor network quality, overpricing structure of telecommunication services and slow connection speed must be resolved to ensure satisfactory quality of online education.
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Impacts of AR in Learning Tribal Bodo Language
Scientific article
The objective of this study is to determine the effect of augmented reality compared to traditional approaches for language learning in primary education. We reported BodoAR, a marker-based AR application suitable for teaching the Bodo language, a tribal language of India in this work. The proposed application was developed using UNITY. To find the efficacy of the proposed BodoAR, five research questions were formed. An empirical study was conducted in five primary schools on two distinct user groups: native and non-native speakers of the Bodo language. All the participants were again randomly divided into two other groups- the experimental and the control group. A mixed-method approach was employed to collect the data, utilizing quantitative and qualitative methodologies. Analysis of empirical data shows native Bodo speakers' learning - in terms of academic achievements was significantly improved using the proposed application. For non-native students, experimental groups performed better than the controlled group. Both the native and non-native experimental groups experienced low anxiety, positive attitudes, and high levels of satisfaction while using the BodoAR application. Additionally, the academic achievements and attitudes of the native students in the experimental group were positively and significantly correlated. In contrast, the achievement of non-native students exhibits a positive and significant relationship with usability. The findings show increased satisfaction and academic performance among students who used the BodoAR application, affirming its effectiveness in enhancing Bodo language learning for primary school children. Thus, AR can be a useful tool for incorporating into children’s language learning for children.
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Implementation of Convolutional Neural Network to Classification Gender based on Fingerprint
Scientific article
Gender is one of the vital information to identify someone. If we can decide with conviction whether an individual is male or female, it will restrain the inquiry list and abbreviate the pursuit time. The way toward distinguishing fingerprints is one of the significant, simple to do assortment strategies, the cost is cheap, and a dactyloscopy authority does the particular outcome. The classification of the image gets the issues in computer vision, where a computer can mimic the capacity of an individual to comprehend the data in the image. Process of classifying image can be performing with deep learning where the process like the working of the brain in thinking and trying to reproduce part of its functions by using units associated with relationship, like a neuron. Convolutional neural network is one type of deep learning. In this research, will be doing to classification gender based on fingerprint using method Convolutional Neural Network, and then we will make three models to determined gender, with a total of 49270 image data that included test data and training data by classifying two categories, male and female. Of the three models, we are taking the highest accuracy to use in making this application. Results of this research is we get Model2 will be used as a model CNN with the accuracy level of 99.9667%.
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Implementation of Instructional Design Models without Considering Inclusive Education
Scientific article
At present, education is a matter of global concern and it is the responsibility of all States to be able to provide the ideal conditions so that it is accessible to the entire population. As indicated by one of the objectives of the 2030 Agenda which seeks to guarantee inclusive and equitable education quality. Different studies indicate that instructional design models allow the creation of optimal educational environments for all people and that their correct application allows students to generate satisfactory learning, however, there is an important group of people who are not considered in the tests of these models making it is impossible to reach the goal of achieving the desired educational inclusion. Therefore, the stated objective is to demonstrate that people with some type of disability have not been considered to work and to validate the studies that use different models, approaches or techniques to develop virtual learning environments. The results are worrisome as they demonstrate that of the 90 scientific articles analyzed, only 4.44% have included topics related to disability and of the total sample of participants that total 11,732 people, only 42, that is, 0.36%, had some type of disability. This shows that we are very far from being able to meet the sustainable development goal that seeks to guarantee inclusive and equitable quality education. Based on the results achieved, it is intended to sensitize governments, educational institutions and teachers around the world to work responsibly to close the gap that marginalizes people with disabilities and build appropriate virtual learning environments that guarantee that everyone can access and learn in the best way.
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Scientific article
This research aimed to create a decision support system for admission selection of PMDK scholarship pathway using the SMART (Simple Multi-Attribute Rating Technique) method with web-based and if this research was successful, it could help STMIK Widya Cipta Dharma to select PMDK scholarship should be given to a student of STMIK Widya Cipta Dharma. PMDK is the tittle of scholarship for interest and talent scouting. This research was conducted at STMIK Widya Cipta Dharma Samarinda, a method of data collection used interviews, that asked questions related to the selection of PMDK scholarship admissions by observation directly to STMIK Widya Cipta Dharma Samarinda. This research development system method used the development of a decision support system method. The software model used PHP programming language and database using MYSQL. The final result of this research is a decision support system for admission selection of the PMDK scholarship pathway using the SMART (Simple Multi-Attribute Rating Technique) method with web-based, can help selection of PMDK scholarship faster by admin, and provide information to students. So contribution of this paper is gives a best recommendation for selection of PMDK scholarship using decision support systems.
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