Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1064
English Pronunciation Practice Method with CG Animations Representing Mouth and Tongue Movements
Статья научная
Method for English pronunciation practice utilizing Computer Graphics: CG animation representing tongue movements together with mouse movements is proposed. Pronunciation practice system based on personalized CG animation of mouth movement model is proposed. The system enables a learner to practice pronunciation by looking at personalized CG animations of mouth movement model , and allows him/her to compare them with his/her own mouth movements. In order to evaluate the effectiveness of the system by using personalized CG animation of mouth movement model, Japanese vowel and consonant sounds were read by 8 infants before and after practicing with the proposed system, and their pronunciations were examined. Remarkable improvement on their pronunciations is confirmed through a comparison to their pronunciation without the proposed system based on identification test by subjective basis. In addition to the mouth movement, tongue movement is represented by CG animation. Experimental results show 20 to 40 % improvement is confirmed by adding tongue movements for pronunciations of "s" and "th".
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Статья научная
The Recurrent Neural Network (RNN) is well suited for emotional speech recognition because its uses constantly time shifting property. Even though RNN gives better results GRU, LSTM and BILSTM solves the gradient problem and overfitting problem joins the path to reduces the efficiency. Hence in this paper five deep learning architecture is designed in order to overcome the major issues using data augmentation and spatial feature. Five different architectures like: Enhanced Deep Hierarchal LSTM & GRU (EDHLG), EDHBG, EDHGL, EDHGB & EDHGG are developed with dropout layers. The raw data learned from LSTM will be given as the input to GRU layer for deepest learning. Thus, the gradient problem is reduced, and accuracy of each emotion was increased. Also, to enhance the accuracy level spatial features were concatenated with MFCC. Thus, in all models, the experimental evaluation with the Tamil emotional dataset yielded the best results. EDHLG has a 93.12% accuracy, EDHGL has a 92.56 percent accuracy, EDHBG has a 95.42 percent accuracy, EDHGB has a 96 percent accuracy, and EDHGG has a 94 percent accuracy. Furthermore, the average accuracy rate of a single individual LSTM layer is 74%, while BILSTM is 77%. EDHGB outperforms almost all other systems, by an optimal system of 94.27 percent and then a maximum overall accuracy of 95.99 percent. For the Tamil emotion data, emotional states such as happy, fearful, angry, sad, and neutral have a 100% prediction accuracy, while disgust has a 94 percent efficiency rate and boredom has an 82 percent accuracy rate. Also, the training time and evaluation time utilized by EDHGB is 4.43 mins and 0.42 mins which is less when compared with other models. Hence by changing the LSTM, BILSTM and GRU layers large analysis of experiment on Tamil dataset is done and EDHGB is superior to other models, and when compared with basic models LSTM and BILSTM around 26% more efficiency is gained.
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Enhanced Learning with Abacus and its Analysis Using BCI Technology
Статья научная
Although technology is successfully being used these days as a tool to improve education at all levels, its improper usage is curbing the imagination of the student community, leading to a diminution in their thinking capacity and ability to focus and concentrate. As attention is a vital cognitive feature of any learning process, students these days are not coping well with this process. This study attempts to analyse the focusing capacity of students from two different backgrounds; students who have undergone training in mental arithmetic and usage of the abacus and students without any formal mental arithmetic training. The analysis is done through a simple Electroencephalogram (EEG) based gaming software, which measures the time needed for the players to focus and reach a specific attention level. An EEG device measures brain invoked potentials. Due to the availability of low cost commercial grade EEG devices, usage of these devices today, is not confined only to research and clinical purposes, but is being used beyond these applications. This study is an attempt to apply Brain Computer Interface (BCI) Technology to assess cognition. The performance of the first category was found to be better than the second set of students.
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Статья научная
With the outgrowth of cloud computing, a large amount of private information is stored over cloud servers, which is in encrypted format. But searching over encrypted data is very difficult. Earlier search schemes were based on Boolean search through keywords. But don't consider relevance of files. After that ranked search comes into its role, which uses searchable symmetric encryption (SSE). To achieve more practical and efficient design method was further modified to "Order preserving symmetric encryption" (OPSE), which uses primitives and indexed metadata files used in ranked SSE. In this proposed work further enhancements are done to reduce storage space for encrypted metadata using Porter Stemming method. Improvements in retrieval time are also done by using Boyer Moore's searching algorithm.
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Enhanced Ring Signatures Schemes for Privacy Preservation in Wireless Sensor Networks
Статья научная
Advancements in the domains of low-data-rate wireless networking and micro-electro-mechanical systems enabled the inception of a new networking domain, called wireless sensor network. These ad-hoc kind of networks have diversified applications in battlefield surveillance, disaster monitoring, intrusion detection etc. These networks consist plethora of sensor nodes which are severely resource constrained. As the application of the wireless sensor network is increasing, there is an emerging need for the security and privacy scheme which makes the network secure from various attacks and hide the ongoing activities in the network from a non-network entity. Privacy in wireless sensor network is yet a challenging domain to work on. Lot of work has been done to ensure privacy in the network. These relate to provide privacy in terms of the network entity and the privacy of the sensed information. Most of the solutions till date is based upon routing in the network layer, random walk based flooding, dummy data injection and cross layer solutions. Each of the schemes induce some overhead in the network. A light weight scheme is always desired for resource constraint wireless sensor networks. In this work we will propose a scheme which assures the privacy of the nodes in the network along with the privacy of the event generated in the network through a self organizing scheme. Through various simulation results the validity of our scheme among different network scenarios will be shown. We will also prove through graphical results that our proposed scheme enhances network lifetime quite satisfactorily.
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Enhancement of energy aware hierarchical cluster-based routing protocol for WSNs
Статья научная
Wireless sensor networks are present almost everywhere because of their extensive variety of utilization. However, sensor nodes are battery constrained. Therefore, proficient utilization of power turns into testing issues. Aggregated data at the base station, by individual nodes cause a flood of information which results in greater power consumption. To avoid or minimize this issue a new technique of data aggregation has been proposed. In this paper, we proposed enhanced novel energy aware hierarchical cluster-based (ENEAHC) routing protocol with the aim to: minimizing as much as total energy consumption and to enhance the performance of the energy efficient protocol by using inter-cluster based data aggregation. LZW based data aggregation likewise connected to the Cluster head (CH) to improve more results. Performance results show ENEAHC scheme reduce the end-to-end energy consumption and prolong the lifetime of the network compared to well known clustering algorithms i.e. LEACH and NEAHC. We design the actual relay node selecting issue like a non-linear programming issue and make use of property of compress sensing to find the optimal solution. The results are evaluated at the end of this paper through simulation.
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Статья научная
This research study aims to compare the learning achievements of first-year students in an algorithm and programming course before and after participating in cooperative blended learning activities focused on variables, expressions, and control commands. By utilizing problem-based learning methods, the researchers sought to meticulously analyze the profound impact of these activities on students’ academic advancement. The research tools deployed encompassed satisfaction questionnaires and achievement tests. The research cohort encompassed seven experienced specialists within higher education institutions, each endowed with a minimum of ten years of pedagogical experience, along with twenty-five participating students. Employing rigorous statistical analysis via T-tests, the study conclusively revealed a statistically noteworthy enhancement in student achievement post the program, underscoring the affirmative influence of cooperative blended learning activities. Moreover, the overall satisfaction level among learners engaging in the proposed learning activities was remarkably elevated, evident through an average satisfaction rating of 4.54 and a standard deviation of 0.73. These empirical insights succinctly underscore the demonstrable effectiveness of assimilating cooperative blended learning methods within algorithm and programming education, thereby accentuating the pivotal role of these pedagogical approaches in shaping contemporary educational practices.
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Enhancing Efficient Study Plan for Student with Machine Learning Techniques
Статья научная
This research aims to enhance the achievement of the students on their study plan. The problem of the students in the university is that some students cannot design the efficient study plan, and this can cause the failure of studying. Machine Learning techniques are very powerful technique, and they can be adopted to solve this problem. Therefore, we developed our techniques and analyzed data from 300 samples by obtaining their grades of students from subjects in the curriculum of Computer Science, Faculty of Science and Technology, Sakon Nakhon Rajabhat University. In this research, we deployed CGPA prediction models and K-means models on 3rd-year and 4th-year students. The results of the experiment show high performance of these models. 37 students as representative samples were classified for their clusters and were predicted for CGPA. After sample classification, samples can inspect all vectors in their clusters as feasible study plans for next semesters. Samples can select a study plan and predict to achieve their desired CGPA. The result shows that the samples have significant improvement in CGPA by applying self-adaptive learning according to selected study plan.
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Enhancing Emotion Detection with Adversarial Transfer Learning in Text Classification
Статья научная
Emotion detection in text-based content, such as opinions, comments, and textual interactions, holds pivotal significance in enabling computers to comprehend human emotions. This symbiotic understanding between machines and human languages, powered by technological advancements like Natural Language Processing and artificial intelligence, has revolutionized the dynamics of human-computer interaction. The complexity of emotion detection, although challenging, has surged in importance across diverse domains, encompassing customer service, healthcare, and surveillance of social media interactions. Within the realm of text analysis, the quest for accurate emotion detection necessitates a profound exploration of cutting-edge methodologies. This pursuit is further intensified by the imperative to fortify models against adversarial attacks, a pressing concern in deep learning-based approaches. To address this critical challenge, this paper introduces a pioneering technique—adversarial transfer learning—specifically tailored for emotion classification in text analysis. By infusing adversarial training into the model architecture, the proposed approach emerges a solution that not only mitigates the vulnerabilities of existing methods but also fortifies the model against adversarial intrusions. In realizing the potential of the proposed approach, a diverse array of datasets is harnessed for comprehensive training. The empirical results vividly demonstrate the efficacy of this approach, showcasing its superior performance when compared to state-of-the-art methodologies. Notably, the suggested approach yields in advancements in classification accuracy. In particular, the deployment of the Adversarial transfer learning methodology has increased in accuracy of 17.35%. This study, therefore, encapsulates a dual achievement: the introduction of an innovative approach that leverages adversarial transfer learning for emotion classification, and the subsequent empirical validation of its unparalleled efficiency. The implications reverberate across multiple sectors, extending the horizons of accurate emotion detection and laying a foundation for the next stride in human-computer interaction and emotion analysis.
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Enhancing Information Systems Students' Soft Skill – a Case Study
Статья научная
Information Systems (IS) curricula should provide students with both technical and non-technical (soft) skills. The technical aspects are covered by various courses. However, soft skills like teamwork, interpersonal communication, presentation delivery, and others are hardly covered. Employers, who consider both technical and soft skills to be equally important, search for professional Information Systems employees possessing both sets of skills. These employers often complain that finding an IS graduate with both types of skills is quite difficult. The IS 2010 Model Curriculum refers to both types of skills, considering them an essential part of the graduate knowledge base. However, in many cases the soft skills are not sufficiently addressed, and even if they are, it is not necessarily in the context of software development projects. The Systems Analysis and Design (SAD) course provides an important foundation for the IS profession. This is especially true due to the emerging role of the programmer-analyst who is responsible not only for programming but also for some analysis work. In order to strengthen the soft skills in the context of system analysis and design, we suggest a workshop structure emphasizing these soft skills while students analyze and design a complete information system. Our SAD workshop includes some face to face lectures and team-based collaborations. The students undertake many online activities, including teamwork, interviews with simulated clients, team-based peer reviews, presentation delivery, and so forth. The workshop employs a grade difference calculation mechanism that revealed, along with the students' reflections, that the workshop structure enhanced the students' ability to cope with the workshop assignments while strengthening their soft skills and preparing them for their future analysis and design challenges.
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Enhancing Leakage Power in CPU Cache Using Inverted Architecture
Статья научная
Power consumption is an increasingly pressing problem in modern processor design. Since the on-chip caches usually consume a significant amount of power so power and energy consumption parameters have become one of the most important design constraint. It is one of the most attractive targets for power reduction. This paper presents an approach to enhance the dynamic power consumption of CPU cache using inverted cache architecture. Our assumption tries to reduce dynamic write power dissipation based on number of ones and zeros in the in-coming cache block data using bit to indicate is the block is mostly one or zero. This architecture reduces the dynamic write power by 17 %. We use Proteus Simulator to test that proposed circuit and performed the experiments on a modified version of the cacti6.0 simulator.
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Статья научная
There is a growing interest in integrating active learning and computer-based approaches in the teaching and learning of mathematics in elementary schools. In this study, we introduce Digital Game-Based Learning (DGBL) of Mathematics targeting students in the 5th and 6th grades following a design-to-implementation strategy. We first developed an edutainment Mathematics game and then tested it with 196 pupils from 9 public elementary schools in Morocco. The rationale of the study is to probe the effect of DGBL in lessening pupils’ mathematical anxiety and improving classroom experience. Students in our study were more engaged and less anxious towards learning Mathematics. Our designed pedagogical edutainment game made students more comfortable when dealing with numerical arithmetic assignments. The study suggests that edutainment games lead to positive individual attitudes towards mathematics and to a better math classroom experience, thus more effective teaching and learning of mathematics.
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Enhancing the Project-Based Learning Experience Through the Use of Live Web Data
Статья научная
Project-based learning (PBL) was proven to be a very useful model to give students hands on experiences and allow them to be active learners rather than passive listeners. In this paper we introduce a tool to help enhance the project development experiences for information technology (IT) students. The main purpose of this tool is to help reuse web information to enable IT projects for students. This tool is called InetRetriever and it can be easily used by students to retrieve, in real-time, any required real information from the web and to implement, execute, and test their projects with real life data. As PBL is becoming an integral part of many information technology (IT) courses, and in many cases real data is essential for many types of projects, it becomes important to make such data available and accessible easily. In various cases, students focus gets shifted from the real objectives of a project when they spend a lot of their time trying to find data or create methods to get them this data. Furthermore, many projects fail and cannot demonstrate their real capabilities when they are tested and demonstrated using small sets of sample data or some fabricated data sets because the students could not include real data available on the Internet. Another possibility here is that students could not even complete their projects because of the difficulties in retrieving the required data and the excess amount of time they spend on that tasks rather than on the real tasks in the project. Therefore, InetRetriever was developed to overcome this obstacle. It was tested in different information technology courses to enable effective and realistic project-based learning. Using this tool we observed increased student interest in the project development and higher levels of interactions and learning.
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Статья научная
Engineering education plays a pivotal role in the development of technologies, society, nation, economy and employment. It is well evident that in the information age, technology is developing very fast and correspondingly the demand for highly skilled and qualified professionals is also increasing. One of the most critical issues in engineering education is handling placement of young technocrats from an industrial perspective to prepare the required workforce in the 21st century. The trajectory of development of Electronics Engineering (EE) has intersected every walk of human life. The last decade has also witnessed an assorted increase in Electronics Engineering Education in India. Infact, most of the engineering institutes imparting EE education countrywide focus only on domain knowledge and a mere 25% of the engineering professionals are actually employable. Along with domain knowledge, there are non-technical skills and competencies which play a significant part in contributing to an individual's effective and successful participation in the workplace. This article throws light on career opportunities that will go a large way towards ensuring successful career planning and handling placement prospects. The paper addresses the career prospects in a broader domain of electronics engineering and other allied fields. The study will also focus on ongoing activities and initiatives at BPSMV State University in Haryana.
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Error Measurement & its Impact on Bilateral -Canny Edge Detector-A Hybrid Filter
Статья научная
Image Processing, a subset of Computer Vision, is an important branch in modern technology. Edge detection is a subset of segmentation to detect object of interest. Different image edge detection filters and their evaluating parameters are introducing rapidly. But the performance of an edge detector is an open problem. In this paper different performance measures of edge detection have been discussed in details and their application on a hybrid filter using Bilateral and Canny is proposed. Its parametric performance has been evaluated and other well established or classical existing edge detecting filters have been compared with it to measure its efficiency.
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Evaluating and comparing the performance of using multiple controllers in software defined networks
Статья научная
In Software Defined Networks (SDN) the control plane is removed to a separate device called the controller. The controller is the most important and main part in SDN architecture and large SDN networks may consist of multiple controllers or controller domains that distribute the network management between them. Because of the controller importance, it has been given a proper attention and many studies have been made to compare, test, and evaluate the performance of the controllers. This paper aims to evaluate and compare the performance of different SDN controllers which are Open Network Operating System (ONOS), OpenDaylight, POX and Ryu, using Two performance tests; the first test includes connecting two controllers of each of the four controllers to linear topology with different number of switches; and the other test includes connecting different number of controllers of each of the four controllers to linear topology with fixed number of switches. Then for these tests, the performance in terms of some Quality of Service (QoS) parameters such as average Round-Trip Time (RTT), throughput, and jitter are measured between the two end hosts in each network. After the evaluation of the performance has been completed, it had been seen that the controllers showed different behaviors, and that POX controller showed more stable and good performance results than other controllers.
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Evaluating the Effect of JPEG and JPEG2000 on Selected Face Recognition Algorithms
Статья научная
Continuous miniaturization of mobile devices has greatly increased its adoption and use by people in various facets of our lives. This has also increased the popularity of face recognition and image processing. Face recognition is now being employed for security purpose opening up the need for further research in recent time. Image compression becomes useful in cases when images need to be transmitted across networks in a less costly way by increasing data volume while reducing transmission time. This work discusses our findings on image compression and its effect on face recognition systems. We studied and implemented three well known face recognition algorithms and observed their recognition accuracy when gallery / probe images were compressed and/or uncompressed as one would naturally expect. For compression purposes, we adopted the JPEG and JPEG2000 coding standard. The face recognition algorithms studied are PCA, ICA and LDA. As a form of an extensive research, experiments conducted include both in compressed and uncompressed domains where the three algorithms have been exhaustively analyzed. We statistically present the results obtained which showed no significant depreciation in the recognition accuracies.
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Evaluating the Potentials of Educational Systems to Advance Implementing Multimedia Technologies
Статья научная
Implementing multimedia in education has proven to be quite beneficial to the educational processes by enhancing the students' cognitive abilities, accelerating of memorization and learning, and easing the understanding of abstract entities. But, for an educational system, whether it is a single institution, regional system, or even a state level system, the information that multimedia technologies provide enhancements to the educational processes is not sufficient to achieve the acclaimed advancements. To improve learning by implementing multimedia, decisions about actions and investments should be based on a specific analysis of the current condition of the educational system. In this manner, this research presents an evaluation methodology that supports the purposes of strategic planning and investments in education, in the context of advancements implementing multimedia. The methodology takes into account three key aspects: i) multimedia equipment and IT resources, ii) teachers' competencies and their interest in adding multimedia to their lectures, and iii) promotional events about using multimedia in education. As a case study, a segment of the educational system in a municipality in R. Macedonia was evaluated, where the results showed the system's strong and weak aspects, giving a profound direction in which the future enhancement efforts should be conducted.
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Evaluating the Project based Organizational Teaching-Learning Process
Статья научная
Organizational Training and Learning are among the 22 key process areas in CMM. These two processes are subject for improvement based on its framework and execution. In this paper, we have worked on project-based frameworks for organizational training and learning and have attempted to validate them in the software developmental organizations and in an institution teaching software engineering. The empirical validation is carried out with those case studies and significant results are obtained in assessing the improvement in the two process areas. Moreover, this work is also extended to accommodate improvement in the regular conventional OTL processes.
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Evaluating the Undergraduate Course based on a Fuzzy AHP-FIS Model
Статья научная
Course evaluation is a critical part of undergraduate curriculum in computer science. Most existing evaluation methods are based on questionnaire by analyzing the satisfaction rate of the respondents. However, there are many indicators such as attendance rate, activity level and average score that can reflect the overall effectiveness of the course. Limited research has taken all those indicators into account during course evaluation. This research chooses an innovative perspective that considers course evaluation as a multiple criteria decision-making problem. A hybrid model is proposed to measure the course effectiveness regarding various indicators. The indicators are first prioritized by a fuzzy Analytic Hierarchical Process (AHP) model which applies fuzzy numbers to deal with the uncertainty brought by subjective judgement. A hierarchical fuzzy inference system (FIS) is then designed to evaluate the course effectiveness, which reduces the number of the fuzzy IF-THEN rules and increases the efficiency compared to the traditional FIS. A numerical example is presented to demonstrate the application. The proposed model helps not only judge an individual course based on a comprehensive view but also rank multiple courses.
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