International Journal of Modern Education and Computer Science @ijmecs
Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1080
Статья научная
Data security is one of the biggest concerns in cloud computing environment. Although the advantages of storing data in cloud computing environment is extremely high, there arises a problem related to data missing. CyberLiveApp (CLA) supports secure application development between multiple users, even though cloud users distinguish their vision privileges during storing of data. But CyberLiveApp failed to integrate the system with certain cloud-based computing environments on multi-server. Environmental Decision Support Systems (EDSS) move away the technical load and focus mainly on decision-making activities. EDDS does not have a secure collaborative decision-making experience on cloud services. To integrate the security level for multi-server cloud infrastructure, Information Interpretation Code on Multi-Server (IICM-S) is proposed in this paper. To ensure the information with relevance to security on cloud-based computing environments, Information Interpretation Code (IIC) algorithm is initially developed. Thus, IIC guarantee that all information pertaining to cloud is in secured condition in order to prove the trustworthiness of data. In addition, the multi-sever cloud infrastructure in IIC provides access point for secure information recovery from cloud data server. The multi-server cloud infrastructure with IIC algorithm performs the recovery task on multi-server cloud infrastructure. The Multi-server Information (MI) scheme measures the integrity level with effective data recovery process. The integrity level on multi-server cloud infrastructure is ensured using two components, verifier and verify shifter. MI scheme proficiently check integrity using these two components so that not only the data integrity is provided as well as security is ensured in all cases using IICM-S. Experiment is conducted in the Cloudsim platform on the factors such as average integration time on multi-server, security level, recovery efficiency level.
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Information Literacy and its Application in Nursing Education
Статья научная
Information literacy has been embedded by the university into the first year nursing curriculum. Embedding this literacy will not necessarily ensure the nursing graduates will apply this skill to the provision of high quality evidence-based health care. For this to happen information literacy skills gained in the classroom must contribute to sound decision making based on best practice evidence. This paper discusses the findings of a three phases research project designed to (i) determine the information literacy skills, confidence and problem solving abilities of students entering the university’s Bachelor of Nursing Program; (ii) determine if information literacy skills, confidence and problem solving abilities improve as a result of embedding information literacy instruction into a nursing course; and iii) ascertain whether there are any differences in information literacy skills, confidence and problem solving abilities based on the students demographic information. Data were collected in two sequential semesters using a questionnaire administered to the students. The response rates in semester one and two were 45 and 56 per cent respectively. Student confidence and awareness regarding information literacy is positively affected by learning experiences from semester one to semester two. Students indicated that they need both specific and regular instruction to adequately retain learning. Overall the study suggests that embedding information literacy instruction into the first year, first semester nursing program is beneficial. By the second semester the information literacy confidence and awareness of students increased as a result of intra-curricular instruction, however, problem solving skills need to be improved.
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Статья научная
A method of choosing swarm optimization algorithms and using swarm intelligence for solving a certain class of optimization tasks in industry-specific geographic information systems was developed considering the stationarity characteristic of such systems. The method consists of 8 stages. Classes of swarm algorithms were studied. It is shown which classes of swarm algorithms should be used depending on the stationarity, quasi-stationarity or dynamics of the task solved by an industry geographic information system. An information model of geodata that consists in a formalized combination of their spatial and attributive components, which allows considering the relational, semantic and frame models of knowledge representation of the attributive component, was developed. A method of choosing optimization methods designed to work as part of a decision support system within an industry-specific geographic information system was developed. It includes conceptual information modeling, optimization criteria selection, and objective function analysis and modeling. This method allows choosing the most suitable swarm optimization method (or a set of methods).
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Information Technology for Gender Voice Recognition Based on Machine Learning Methods
Статья научная
The growing use of social networks and the steady popularity of online communication make the task of detecting gender from posts necessary for a variety of applications, including modern education, political research, public opinion analysis, personalized advertising, cyber security and biometric systems, marketing research, etc. This study aims to develop information technology for gender voice recognition by sound based on supervised learning using machine learning algorithms. A model, methods and means of recognition and gender classification of voice speech samples are proposed based on their acoustic properties and machine learning. In our voice gender recognition project, we used a model built based on the neural network using the TensorFlow library and Keras. The speaker’s voice was analysed for various acoustic features, such as frequency, spectral characteristics, amplitude, modulation, etc. The basic model we created is a typical neural network for text classification. It consists of the input layer, hidden layers, and the output layer. For text processing, we use a pre-trained word vector space such as Word2Vec or GloVe. We also used such techniques as dropout to prevent model overtraining, such activation functions as ReLU (Rectified Linear Unit) for non-linearity, and a softmax function in the last layer to obtain class probabilities. To train a model, we used the Adam optimizer, which is a popular gradient descent optimization method, and the “sparse categorical cross-entropy” loss function, since we are dealing with multi-class classification. After training the model, we saved it to a file for further use and evaluation of new data. The application of neural networks in our project allowed us to build a powerful model that can recognize a speaker’s gender by voice with high accuracy. The intelligent system was trained using machine learning methods with each of the methods being analysed for accuracy: K-Nearest Neighbours (98.10%), Decision Tree (96,69%), Logistic Regression (98.11%), Random Forest (96.65%), Support Vector Machine (98.26%), neural networks (98.11%). Additional techniques such as regularization and optimization can be used to improve model performance and prevent overtraining.
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Information Technology for Generating Lyrics for Song Extensions Based on Transformers
Статья научная
The article develops technology for generating song lyrics extensions using large language models, in particular the T5 model, to speed up, supplement, and increase the flexibility of the process of writing lyrics to songs with/without taking into account the style of a particular author. To create the data, 10 different artists were selected, and then their lyrics were selected. A total of 626 unique songs were obtained. After splitting each song into several pairs of input-output tapes, 1874 training instances and 465 test instances were obtained. Two language models, NSA and SA, were retrained for the task of generating song lyrics. For both models, t5-base was chosen as the base model. This version of T5 contains 223 million parameters. The analysis of the original data showed that the NSA model has less degraded results, and for the SA model, it is necessary to balance the amount of text for each author. Several text metrics such as BLEU, RougeL, and RougeN were calculated to quantitatively compare the results of the models and generation strategies. The value of the BLEU metric is the most diverse, and its value varies significantly depending on the strategy. At the same time, Rouge metrics have less variability and a smaller range of values. In total, for comparison, we used 8 different decoding methods for text generation supported by the transformers library, including Greedy search, Beam search, Diverse beam search, Multinomial sampling, Beam-search multinomial sampling, Top-k sampling, Top-p sampling, and Contrastive search. All the results of the lyrics comparison show that the best method for generating lyrics is beam search and its variations, including ray sampling. The contrastive search usually outperformed the usual greedy approach. The top-p and top-k methods do not have a clear advantage over each other, and in different situations, they produced different results.
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Innovative Approaches to Higher Education: Blended Learning in Kazakhstan
Статья научная
The research problem is based on the study of the possibilities of expanding methodological approaches, educational technologies, and educational programs for the implementation of blended learning and increasing the level of its effectiveness in the educational system of Kazakhstan. This study aims to identify the best conditions for implementing blended learning that would meet the technical capabilities of the university, the educational programs, and the interests and needs of all participants of the educational process. For this, the following data collection methods were used: online surveys, quantitative and qualitative analyses, and facilitation tools, such as World Café, Future Search, ranking, and Spearman's correlation analysis. The results show that more than half of the students (58%) and teachers (65%) were not satisfied with the existing structure of blended learning at the university. This research suggests involving all participants in the educating process when adopting the blended mode of learning to enhance the efficacy of the blended learning program. The practical significance of this research lies in its determination of the optimal conditions for implementing blended learning in the university programs of Kazakhstan. The engagement of all stakeholders in the Learning pathway in decision-making regarding hybrid education, taking into account the technical capabilities of universities and the individual needs of students and instructors, aims not only to address current issues but also to enhance the quality of education and prepare graduates to meet the demands of the contemporary labor market. Such an approach to research and innovation implementation in Kazakhstan's education could foster the development of more flexible, adaptive, and effective educational systems that meet the requirements of the modern world.
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Integrating Apple iPads into University Computing Courses
Статья научная
The use of mobile devices is becoming increasingly common in both society and in the K-12 environment. Products such as the Apple iPad and the Microsoft Surface, among others, have matured to a point where university faculty are striving to integrate this increasingly ubiquitous technology into the classroom and the curriculum. This paper represents a case study examining one attempt to integrate the use of tablets into five university-level computing courses during the 2015-2016 academic year. The author used a set of iPads and accompanying classroom technology (e.g. Apple TV, keyboards) in an attempt to engage students and build their problem-solving and collaborative skills. Student feedback suggests that students were engaged, and the results for the iPad's impact on problem-solving and collaborative skills improved over the course of the year. A number of challenges were observed, including inadequate student knowledge of tablets, wireless connectivity issues, student resistance to the group learning afforded by the iPads, and keeping the tablets charged and clean. Future plans for the study intend to address the challenges uncovered, using student and instructor feedback as an impetus for future development. This paper serves as an experiential report designed to inform other faculty who may be looking into similar projects.
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Integration Colour and Texture Features for Content-based Image Retrieval
Статья научная
Content-Based Image Retrieval offers an automatic way to extract visual image contents such as colour, texture, and shape so-called extracted features. Due to growing volume of digital images, Content-Based Image Retrieval is emerged to store and retrieved images from large scale databases. However, Content-Based Image Retrieval faces a challenge of meaning “Semantic gap” between machine and human conceptual. How to reduce this gap between colour and/or texture features that represent an object in the image? It is still the challenge that basically related to the effectiveness of image representation by extracted features and similarity measures between a query image features and database image features. Hence, different visual features have been proposed such as Gary Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP), and Discrete Wavelet Transform (DWT) texture features that are extracted from gray-scale images. This paper presents an unsupervised algorithm that exploits data and score-level fusion to address the semantic gap. The algorithm first extracts mentioned features from colour images in HSV and YCbCr colour spaces to increase the effectiveness of image representation by integrating texture and colour visual information in terms of data-level fusion. Resulted similarity retrieval values are then fused in three versions of score-level fusion, summing values without weights, fixed, and adaptive weights using linear regression to raise relevant images in a ranked retrieved images list. WANG standard colour images are used to implement the algorithm. Rates of achievement in image retrievals are enhanced at both levels.
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Статья научная
The implementation of the concept of building an information society implies a widespread introduction of IT in all areas of modern society, including in the field of science. Here, the further progressive development and deepening of scientific research and connections presuppose a special role of e-science. E-science is closely connected with the innovative potential of IT, including the Internet technologies, the Internet of things, cyber-physical systems, which provide the means and solutions to the problems associated with the collection of scientific data, their storage, processing, and transmission. The integration of cyber-physical systems is accompanied by the exponential growth of scientific data that require professional management, analysis for the acquisition of new knowledge and the qualitative development of science. In the framework of e-science, cloud technologies are now widely used, which represent a centralized infrastructure with its inherent characteristic that is associated with an increase in the number of connected devices and the generation of scientific data. This ultimately leads to a conflict of resources, an increase in processing delay, losses, and the adoption of ineffective decisions. The article is devoted to the analysis of the current state and problems of integration of cyber-physical systems in the environment of e-science and ways to effectively solve key problems. The environment of e-science is considered in the context of a smart city. It presents the possibilities of using the cloud, fog, dew computing, and blockchain technologies, as well as a technological solution for decentralized processing of scientific data.
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Статья научная
The article develops a technology for finding tweet trends based on clustering, which forms a data stream in the form of short representations of clusters and their popularity for further research of public opinion. The accuracy of their result is affected by the natural language feature of the information flow of tweets. An effective approach to tweet collection, filtering, cleaning and pre-processing based on a comparative analysis of Bag of Words, TF-IDF and BERT algorithms is described. The impact of stemming and lemmatization on the quality of the obtained clusters was determined. Stemming and lemmatization allow for significant reduction of the input vocabulary of Ukrainian words by 40.21% and 32.52% respectively. And optimal combinations of clustering methods (K-Means, Agglomerative Hierarchical Clustering and HDBSCAN) and vectorization of tweets were found based on the analysis of 27 clustering of one data sample. The method of presenting clusters of tweets in a short format is selected. Algorithms using the Levenstein Distance, i.e. fuzz sort, fuzz set and Levenshtein, showed the best results. These algorithms quickly perform checks, have a greater difference in similarities, so it is possible to more accurately determine the limit of similarity. According to the results of the clustering, the optimal solutions are to use the HDBSCAN clustering algorithm and the BERT vectorization algorithm to achieve the most accurate results, and to use K-Means together with TF-IDF to achieve the best speed with the optimal result. Stemming can be used to reduce execution time. In this study, the optimal options for comparing cluster fingerprints among the following similarity search methods were experimentally found: Fuzz Sort, Fuzz Set, Levenshtein, Jaro Winkler, Jaccard, Sorensen, Cosine, Sift4. In some algorithms, the average fingerprint similarity reaches above 70%. Three effective tools were found to compare their similarity, as they show a sufficient difference between comparisons of similar and different clusters (> 20%). The experimental testing was conducted based on the analysis of 90,000 tweets over 7 days for 5 different weekly topics: President Volodymyr Zelenskyi, Leopard tanks, Boris Johnson, Europe, and the bright memory of the deceased. The research was carried out using a combination of K-Means and TF-IDF methods, Agglomerative Hierarchical Clustering and TF-IDF, HDBSCAN and BERT for clustering and vectorization processes. Additionally, fuzz sort was implemented for comparing cluster fingerprints with a similarity threshold of 55%. For comparing fingerprints, the most optimal methods were fuzz sort, fuzz set, and Levenshtein. In terms of execution speed, the best result was achieved with the Levenshtein method. The other two methods performed three times worse in terms of speed, but they are nearly 13 times faster than Sift4. The fastest method is Jaro Winkler, but it has a 19.51% difference in similarities. The method with the best difference in similarities is fuzz set (60.29%). Fuzz sort (32.28%) and Levenshtein (28.43%) took the second and third place respectively. These methods utilize the Levenshtein distance in their work, indicating that such an approach works well for comparing sets of keywords. Other algorithms fail to show significant differences between different fingerprints, suggesting that they are not adapted to this type of task.
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Intelligent Control for a Swarm of Two Wheel Mobile Robot with Presence of External Disturbance
Статья научная
This paper proposed an optimization algorithm in order to improve path maintaining of swarm of two wheel mobile robots with presence of external disturbance. The three robots forms use the leader-follower strategy, the best path for leader is determined using A* algorithm ,the other two robots follow the leader path. Two PID controller are used in each robot to control the angular and velocity torque of wheel. Each PID controller is tuned using intelligent optimization control method which are Particle swarm optimization ,random occurring distributed time delay particle swarm optimization and hybrid particle swarm optimization and genetic after that the proposed algorithm is used for tuning. The new algorithm is the contribution of this article. It is built by combine the random occurring distributed time delayed and genetic algorithm .The combination of these two algorithms takes the advantage of them by using the historical best global position of particles in random occurring distributed time delayed particle swarm optimization algorithm to update velocity of new population generated by genetic algorithm. The integral absolute error (IAE) is computed for system in each algorithm for comparison between them. The performance of intelligent control systems for controlling the three robots path is tested with presence of external disturbance in environment .Two type of external disturbance is tested, these are constant external disturbance and dynamic external disturbance. The performance of the same optimization algorithm is tested in pure environments. From the obtained result ,the new combination method is the best in both disturbance environments (constant or dynamic) and pure.
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Intelligent Controller for Synchronization New Three Dimensional Chaotic System
Статья научная
One of the most important phenomena of some systems is chaos which is caused by nonlinear dynamics. In this paper, the new 3 dimensional chaotic system is first investigated and then utilized an intelligent controller based on brain emotional learning (BELBIC), this new chaotic system is synchronized. The BELBIC consists of reward signal which accepts positive values. Improper selection of the parameters causes an improper behavior which may cause serious problems such as instability of the system. It is needed to optimize these parameters. Genetic Algorithm (GA), Cuckoo Optimization Algorithm (COA), Particle Swarm Optimization Algorithm (PSO) and Imperialist Competitive Algorithm (ICA) are used to compute the optimal parameters for the reward signal of BELBIC. These algorithms can select appropriate and optimal values for the parameters. These minimize the Cost Function, so the optimal values for the parameters will be founded. Selected cost function is defined to minimizing the least square errors. Cost function enforces the system errors to decay to zero rapidly. Numerical simulation will show that this method much better, faster and more effective than previous methods can be new 3D chaotic system mode to bring synchronized.
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Статья научная
Nowadays with improvement in computer science, distributed systems have attracted remarkable attention and increasingly becoming an indispensable factor in our life. Massive-scale data processing, weather forecasting, industrial control systems, medical science, multi-tire architectures in enterprise applications, and aerospace to name but a few are the cases in point that distributed systems play a notable role. Inter-Process Communication or in a short form, IPC is specified as the heart of all distributed systems, therefore they are not formed without IPC. Numerous methods concerning IPC have been proposed so far that are utilized in diverse circumstances. According to the physical location of communication processes in applications, IPC could be established among either multiple processes on the same computer or several computers across a network. From the communication pattern’s perspective, these IPCs can be classified into two broad groups namely, shared memory and message passing. Although, it is not true to say when processes are performed on the same computer definitely employ shared memory to communicate if processes are executed on the different systems they inevitably communicate through message passing. By way of illustration, pipes use message passing patterns to make a connection between various processes but all of the processes are carried out on the same system. The aim of this research is to depict a categorization of the some IPC methods, give a brief description of them, and assess their performance in terms of transferring rate by sending multiple files in different sizes between client and server. As we expected, socket as the basic IPC, since it does not perform extra operations on the input data to be sent had a desirable performance compared to others. Although, to achieve some of the capabilities, like eliminating platform dependencies and asynchronous communication, it needs to add additional layers that make poor performance.
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Introducing TCD-D for Creativity Assessment: A Mobile App for Educational Contexts
Статья научная
This paper presents the Test of Creativity and Divergent Thinking-Digital (TCD-D) mobile application, a digital version of the Williams Test for assessing creativity through graphic production. The Test of Creativity and Divergent Thinking-Digital is a new, simple and intuitive mobile application developed by a team of psychologists and computer scientists to remain faithful to the paper version of the test but to provide a faster assessment of divergent thinking. In fact, creativity assessment tests are currently still administered in paper form, which requires a lot of time and human resources for scoring, especially when administered to large samples, as is the case in educational studies. Several digital prototypes of creativity assessment instruments have been developed over the past decade, some of which are derived from paper instruments and some of which are completely new. Of all these attempts, no one has yet worked on a digital version of the Williams Test of Creativity and Divergent Thinking, although this instrument is widely used in Europe and Asia. Moreover, of all the prototypes of digital tools in the literature, none has been developed as a mobile app for tablets, a tool very close to the younger generation. The app was developed to provide a quicker and more contemporary assessment that accommodates the technological interests of digital natives through the use of touch in drawing and adds some additional indices to those of the paper tool for assessing fluency, flexibility, originality and creative elaboration. The application for Android tablets speeds up the assessment of divergent thinking and supports the monitoring of creative potential in educational and learning contexts. The paper discusses how the application works, the preferences and opinions of the students who tested it, and the future developments planned for the implementation of the application.
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Статья научная
The increasing growth of internet and e-commerce had bartered the customer’s purchasing feature and service providers’ service policies. Moreover, there is no other criterion for quality of service (QoS) on the online network. Here the paper’s objective is to employ the importance of QoS to measure the utility quality of monetary enterprise on internet (e.g., Facebook (FB)). In this paper, the Weighted Sum method and Weighted Product method (WSM and WPM) are implemented using FB for their promotion and advertisement and then utilized the intuitionistic fuzzy value for the measuring of the QoS. The proposed methods are generally based on IF-aggregation operators and criterion weights. To calculate criterion weight, new intuitionistic fuzzy divergence is developed. Additionally, the IF-TOPSIS (technique for order preference by similarity to ideal) algorithm is also applied to check the validity of the result. This research examine not only the dimensions of QoS that users on FB liked and major brands are ‘preferred by’ by them, and which results as the most highly ranked features.
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Статья научная
In this paper, we have tried to identify the prominent factors of Rice production of all the three seasons of the year (Aus, Aman, and Boro) by applying K-Means clustering on climate and soil variables' data warehoused using Fact Constellation schema. For the clustering, the popular machine-learning tool Weka was used whose visualization feature was principally useful to determine the patterns, dependencies, and relationships of rice yield on different climate and soil factors of rice production.
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Investigating the redundancy effect in the learning of C++ computer programming using screencasting
Статья научная
The purpose of this study is to investigate whether does the redundancy principle occurs or not in the learning of C++ computer programming using screencasting. This principle was discovered by Mayer’s Cognitive Theory of Multimedia Learning (CTML) and stated that students learn better from graphics, and narrations than from graphics, narrations and on-screen text. There were mix outcomes pertaining to this principle, and the result might be due to the various topics learn by the students. Therefore, the subject introduction to C++ computer programming was chosen in this study to determine whether the redundancy principle occurs or not in the learning of C++ computer programming using screencasting. A true experimental pre-test and post-test research design was conducted, and sample were 65 first-year undergraduate students (aged 19-22). Samples were chosen based on the criteria that they have never attended any formal computer programming course prior to the study and were randomly assigned to two types of learning modes. The first group received the screencasting and narration (SN) mode whereas the second group received the screencasting, text, and narration (STN) mode. Results showed that the SN mode students outperformed the STN mode students in the post-test.
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Investigation of Facilities for an M-learning Environment
Статья научная
The paper projected to study the field of m-learning focusing on investigating the facilities required to initiate an m-learning environment. Facilities and regular practices of conventional learning and e-learning was considered to find the potential facilities for m-learning environment. We used Integrated Tertiary Educational Supply Chain Model framework that stands on conventional education and illustrates the combined form of education supply chain and research supply chain model. Two surveys were conducted to collect data from students and teachers of higher education. The responses from both of the surveys have been presented and later compared with the findings from our studies of the existing learning environments. The significance of this research is in identifying the facilities for a learner and educator centric m-learning environment.
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Investigation of Participation and Quality of Online Interaction
Статья научная
Advances in computer mediated communication technologies have sparked and continue to facilitate the proliferation of online courses, degree programs, and educational institutions. Leading the way with these advances has been the use of asynchronous discussion forums. However merely setting up a discussion forum does not always ensure quality participation and interaction. The way the course is managed has an impact on the participation as well. This paper compares the difference in course management over four study periods and discusses the resulting consequences on the participation and achievement of the students. This paper also investigates the quality of interaction as perceived by fully online students. The main benefits of this research are that it provides a guideline regarding what course management factors can make the difference in online participation in fully online courses, and how the quality of interaction can be designed.
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Статья научная
To determine the need for simulated training of e-commerce activities prior to working in the real environment, we studied the views of undergraduates and college teachers from several aspects. Two hundred university students while also 200 college teachers were asked what the real problem was when they learned or taught in the e-commerce courses. Next, they were surveyed to inquire what knowledge they really need when students go to work positions and what type of job do they expect to have. Finally, they were asked whether using a simulated training platform would be beneficial. Through analysis, the aspects which are contained above we know that simulation should be incorporated into the education of e-commerce to students as a tool to practice their hands-on abilities prior to working. And from the survey we also obtain some useful information and references that may help us to design our electronic commerce training platform.
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