Online-Journals.org (International Association of Online Engineering)
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Post-Refactoring Recovery of Unit Tests: An Automated Approach
Get PDF— In application development lifecycle, specifically in test-driven development, refactoring plays a crucial role in sustaining ease. However, in-spite of bringing ease, refactoring does not ensure the desired behaviour of code after it is applied. Because refactoring tends to worsen the alignments between source code and its corresponding units. One significant solution to the aforementioned issue is the technique called unit testing. As unit testing enable the developers to confidently apply refactoring while avoiding undesired code behaviour. Unit testing provides effective preventive measures for avoiding bugs by providing immediate feedback, thus assisting to mitigate the fear of change. In this work, we present a tool called GreenRefPlus which efficiently enables the developers to maintain the veracity of code after the process of refactoring is applied. The proposed tool provides automatic recovery for the unit tests after the code is refactored. In this work, we consider Java as our target programming language and we focus on five various types of refactoring, which include Rename Method, Extract Method, Move Method, Parameter Addition and Parameter Removal. Our experiments indicate that the proposed tool GreenRefPlus enables us to consistently refactor the code and apply unit tests. The results presented in our work reveal that the proposed tool assists developers in saving approximately 43% of the total time required to manually recover from broken unit tests
A Comparative Study for SDN Security Based on Machine Learning
Get PDFIn the past decade, traditional networks have been utilized to transfer data between more than one node. The primary problem related to formal networks is their stable essence, which makes them incapable of meeting the requirements of nodes recently inserted into the network. Thus, formal networks are substituted by a Software Defined Network (SDN). The latter can be utilized to construct a structure for intensive data applications like big data. In this paper, a comparative investigation of Deep Neural Network (DNN) and Machine Learning (ML) techniques that uses various feature selection techniques is undertaken. The ML techniques employed in this approach are decision tree (DT), Naïve Bayes (NB), Support Vector Machine (SVM). The proposed approach is tested experimentally and evaluated using an available NSL–KDD dataset. This dataset includes 41 features and 148,517 samples. To evaluate the techniques, several estimation measurements are calculated. The results prove that DT is the most accurate and effective approach. Furthermore, the evaluation measurements indicate the efficacy of the presented approach compared to earlier studies
Online Language Learning Strategies in Institutes of Higher Learning (IPT) Malaysia Post Covid-19
Get PDFThe Covid-19 pandemic that spreaded around the world in March 2020 has changed the nation’s education landscape. Standard Operating Procedures that demand presence at respective residences have made online learning one of the best platforms that replace face-to-face learning in educational institutions across the country. Thus, this study aims to propose an effective online language learning strategy to be a reference for educators and students to master language skills using post-Covid19 educational technology. This research employs quantitative methods cross sectional studies supported by qualitative data. The research instruments is questionnaires. A total of 280 respondents consisting of university students in the Arabic field at Malaysian universities answered the questionnaire. The results showed that the respondents know how to learn through online learning with a mean rate of 4.24 and the respondents agreed that the instructions given during online learning should be clear with a highest mean rate of 4.46. Among the online learning strategies used by students are always sharing opinions during online learning, responding using chat rooms to engage in discussions and making notes to improve understanding. Respondents are also satisfied with online learning platforms such as google meet, Webex and zoom.
 
Clinical Text Classification with Word Representation Features and Machine Learning Algorithms
Get PDFClinical text classification of electronic medical records is a challenging task. Existing electronic records suffer from irrelevant text, misspellings, semantic ambiguity, and abbreviations. The approach reported in this paper elaborates on machine learning techniques to develop an intelligent framework for classification of the medical transcription dataset. The proposed approach is based on four main phases: the text preprocessing phase, word representation phase, features reduction phase and classification phase. We have used four machine learning algorithms, support vector machines, naïve bayes, logistic regression and k-nearest neighbors in combination with different word representation models. We have applied the four algorithms to the bag of words, to TF-IDF, to word2vec. Experimental results were evaluated based on precision, recall, accuracy and F1 score. The best results were obtained with the combination of the k-NN classifier, and the word represented by Word2vec achieving an accuracy of 92% to correctly classify the medical specialties based on the transcription text
Design and Implementation Unit Cell for 6G Reconfigurable Intelligent Surface Application
Get PDFThis article presents a model through which the reflection coefficient amplitude as well as phase of reflective intelligent surfaces can be estimated accurately. The reconfigurability of the surface was achieved by incorporating the varactor diodes into the surface of the cell unit. The manipulation of the phase of the reflection coefficient can be achieved by making adjustments to the biasing state of the varactors. The model, which makes use of a physics-based methodology and is based on a transmission-line circuit description of the Reconfigurable Intelligent surfaces (RIS) unit cells, considers every pertinent electrical and geometrical characteristics of the proposed surface. With the method proposed in this paper, fast and accurate RIS-based communication lines can be created. The recommended accuracy of the proposed method was confirmed through the use of a CST microwave studio full-wave simulations
Smartphones Online Marketing: A Bibliometric and Visualized Analysis
Get PDFSmartphones and high-speed network connections allow businesses to deliver information to customers faster and more efficiently than ever before. This study analyses the most-cited articles on smartphone online marketing. A bibliometric mapping analysis was used to search for articles related to smartphone online marketing between 2010 and 2020, retrieved from the Scopus database. The title, a number of citations, publishing year, journal, country, subject area, and authors were all recorded and evaluated. VOSviewer was used for the bibliometric study. The search yielded a total of 120 articles, with citation counts ranging from 17 to 225. All of the articles were authored in English. The United States was the region with the most articles published. The highest publication source is the Journal of Business Research. Management, accounting, and business dominated the articles. This study benefits the company and marketers with the marketing strategies used in online marketing with smartphones. In terms of marketing activities and research areas, this study suggests future research directions
 
Design and Implementation Digital Invitation System Based on Secure Hash Algorithm 3
Get PDFDigital invitation system become one of the important systems due to the pandemic consequences specially in E-learning domains. The digital invitation needed to be secure enough for several reasons specially in the user demands. In this paper designed and implemented a digital invitation system based on secure hash algorithm which achieving multilevel of security. The first security level, that is the hash code generated for the digital invitation link used in the encryption process not only for the invitation date but also for the invitation time. on the other hand, the second security level achieved through out using the hash code as map for the hiding mechanism. The generated hash will be used for the data integrity as well. The proposed system evaluating the final stego-image as digital invitation using PSNR metric and the maximum value reach 64.28 while the minimum value reach 58.21
Automatically Avoiding Overfitting in Deep Neural Networks by Using Hyper-Parameters Optimization Methods
Get PDFOverfitting is one issue that deep learning faces in particular. It leads to highly accurate classification results, but they are fraudulent. As a result, if the overfitting problem is not fully resolved, systems that rely on prediction or recognition and are sensitive to accuracy will produce untrustworthy results. All prior suggestions helped to lessen this issue but fell short of eliminating it entirely while maintaining crucial data. This paper proposes a novel approach to guarantee the preservation of critical data while eliminating overfitting completely. Numeric and image datasets are employed in two types of networks: convolutional and deep neural networks. Following the usage of three regularization techniques (L1, L2, and dropout), apply two optimization algorithms (Bayesian and random search), allowing them to select the hyperparameters automatically, with regularization techniques being one of the hyperparameters that are automatically selected. The obtained results, in addition to completely eliminating the overfitting issue, showed that the accuracy of the image data was 97.82% and 90.72 % when using Bayesian and random search techniques, respectively, and was 95.3 % and 96.5 % when using the same algorithms with a numeric dataset.
 
Exploring English Major Students’ Self-Directed Technology Use for Language Learning
Get PDFEnglish, as a foreign language education, requires students to be taught in the classroom and participate in additional hands-on activities outside the classroom using technology resources or non-technology. However, language learners rarely use technology to learn outside the classroom, and types of technology have been limited. Therefore, it is crucial to provide language learners with various technology resources to enhance their learning experience and motivate them to continue practicing outside the classroom. The study aimed to provide insights into factors influencing students’ self-directed technology use for language learning. The study findings can help design effective language-learning programs integrating technology and enhancing self-directed learning. The study, which included 167 English major students, employed quantitative methods and an adapted questionnaire. Multiple Linear Regression, Pearson Correlation, and descriptive statistics helped quantitatively analyze the data. The findings show that the three factors—attitude toward an act or behavior, subjective norm, and perceived behavioral control—are highly correlated. Furthermore, the subjective norm was the most significant influence, and attitude toward action or behavior was the least. Teachers should focus on creating a positive social norm around self-directed technology use for language learning and encourage students to perceive it as socially desirable. Additionally, they can work on improving students’ attitudes toward technology by highlighting its benefits and providing opportunities for hands-on practice
Influences of Anchored Instruction on Fragmented Learning Outcomes of University Students
Get PDFWith the rapid development of information technology (IT), the traditional knowledge media can no longer meet the needs of students to acquire knowledge and instant messages quickly in the information era. Various online learning platforms have been developed accordingly to provide continuous access to fragmented knowledge and information. IT has been extensively applied in the field of education, offering extensive development spaces and technological supports to establish an “anchored” teaching mode based on the constructivism theory. This has made fragmented learning outcomes, which extensively use IT technology, a salient topic in anchored instruction. The present study draws data from 252 Traffic Engineering students to analyze the influence of anchored instruction on the fragmented learning outcomes of university students. The results indicate the good reliability and validity of the questionnaire, with the five aspects of anchored instruction—context setup, problem identification, independent study, cooperative learning and effectiveness evaluation—all capable of significantly improve the fragmented learning outcomes of university students. Different course types, such as practice courses and theory courses, yield different learning outcomes. The research conclusions provide important references to construct a knowledge network of fragmented knowledge based on anchored instruction, facilitate students to extend existing research contents in fragmented deep learning, and discuss the convenient information environment for anchored instruction based on information technology