Reviewerly/exHarmony huggingface dataset:
Deep Learning for Software Defect Prediction: An LSTM-based Approach

Software defect prediction is an important aspect of software development, as it helps developers and organizations to identify and resolve bugs in the software before they become major issues. In this paper, we explore the use of machine learning algorithms for software defect prediction. We discuss the different types of machine learning algorithms that have been used for software defect prediction and their advantages and disadvantages. We also provide a comprehensive review of recent studies that have used machine learning algorithms for software defect prediction. The paper concludes with a discussion of the challenges and opportunities in using machine learning algorithms for software defect prediction and the future directions of research in this field. This paper surveys the existing literature on software defect prediction, focusing specifically on deep learning techniques. Compared to existing surveys on the topic, this paper offers a more in-depth analysis of the strengths and weaknesses of deep learning approaches for software defect prediction. It explores the use of LSTMs for this task, which have not been extensively studied in previous surveys. Additionally, this paper provides a comprehensive review of recent research in the field, highlighting the most promising deep learning models and techniques for software defect prediction. The results of this survey demonstrate that LSTM-based deep learning models can outperform traditional machine learning approaches and achieve state-of-the-art results in software defect prediction. Furthermore, this paper provides insights into the challenges and limitations of deep learning approaches for software defect prediction, highlighting areas for future research and improvement. Overall, this paper offers a valuable resource for researchers and practitioners interested in using deep learning techniques for software defect prediction..
APPLICATION OF E-LEARNING IN JORDANIAN PUBLIC AND PRIVATE UNIVERSITIES: PROPOSALS FOR IMPROVEMENT

The study aimed to identify the application of e-learning in Jordanian public and private universities: Proposals for improvement, the study adopted the qualitative approach, and the two researchers conducted interviews with (25) A faculty member from both public and private Jordanian universities. The results of these interviews showed that Faculty members presented six proposals to improve the application of e-learning in universities The Jordanian government and private sector included the adoption of modern technical and technological strategies that are appropriate to reality Education in Jordanian public and private universities is handled by highly qualified educational leaders High and effective, Jordanian universities seek to accept the change in educational environments universities and adapting to smart digital developments and adopting them in successful ways, universities adopt a methodology It has its own electronic system that is distinguished and unique to it internationally and globally, which increases its competitive advantage among universities The Jordanian Ministry of Higher Education aims to increase financial allocations in support of e-learning and acceptance of community partnership Based on cooperation and partnership for the advancement of university education at all stages and levels, activation Jordanian universities use targeted educational platforms that are commensurate with the skills of workers And their technical capabilities, spreading the culture of e-learning among all employees in Jordanian universities and its importance Keeping pace with the currents of digitization in the current era. The study recommended taking into account the proposals of a sample Studying the activation and promotion of elearning in Jordanian universities.
Pengaruh Konsep Gamifikasi Dalam Model Pembelajaran IMPROVE Terhadap Kemampuan Berpikir Kritis Matematis Siswa SMP

All students should develop their mathematical critical thinking skills to aid their learning and overcome various mathematical challenges. The purpose of this study is to find out how the idea of gamification of IMPROVE learning model affects students' mathematical critical thinking skills. This study used a quasi-experimental design to collect data by using a test in the form of description questions. Normality test and homogeneity test are the two data analysis procedures used. One-way ANOVA test was used in testing the hypothesis of this study. Based on the results of the study, the idea of gamification of IMPROVE learning model has an impact on students' mathematical critical thinking skills.
Handwritten Number Recognition Using CNN and Comparison of Performances of Models Varying by Layers

Now-a-days, the emerging technologies like Deep Learning (DL) leads a drastic turn in the area of Machine Learning (ML) by translating into Artificially Intelligent (AI). DL has several fields of applications viz. medicine, health, surveillance, drones, sports, robotics. In DL, Convolutional Neural Network (CNN) is at the centre of amazing advances that accelerates the field of visual imagery classifications. CNN has utilized broadly in face-recognition, pattern-recognition, handwritten digit-recognition, text categorization, document analysis. The objective of this work is to detect the accuracy distinction of CNN for the classification of handwritten digits via several numbers of layers and epochs. In addition to this, evaluation of the accurateness is incorporated. CNN performance was validated by Modified National Institute of Standards and Technology (MNIST) dataset. By comparing all models varying by layers, a highest validation accuracy of 99.64 % has been reported and the lowest loss gained is 0.0239.
MENDETEKSI KERUSAKAN JARINGAN INTERNET PADA CELEBES MEDIA JARINGAN (BNET) MENGGUNAKAN ALGORITMA FUZZY LOGIC DAN NAÏVE BAYES

The use of cable internet service at home is often disrupted by problems or damage to the network. Not all cable internet service users understand how to solve problems on their internet network. While there are many ways to solve this problem, it often takes administrators and technicians a long time to find and fix the problem. Therefore, the purpose of this research is to develop an expert system that can detect and solve problems on the Celebes Media Network (Bnet) internet network. An expert system is a system that can store knowledge from an expert and use that knowledge to solve problems with the help of a computer. This expert system was created using the Fuzzy Logic method with Naive Bayes, where Fuzzy Logic can be used to change and transform the uncertainty of the value given by the user into a definite value, which is then processed and processed by Naive Bayes to calculate the weight of the user's answer. This method is particularly suitable for expert systems that require reliable safeguards to ensure the accuracy of defined values. The Expert System Development Life Cycle (ESDLC) method was used to develop this system. The benefit of this system is the ability to quickly and easily detect and solve problems on the internet network, which can assist administrators and technicians in dealing with problems on the network. The test results are then analyzed and optimized by administrators and technicians, resulting in an accuracy rate of 85% between the system and the original expert.
THE IMPACT OF THE DIGITAL ECONOMY ON THE ACHIEVEMENT OF SUSTAINABLE DEVELOPMENT GOALS, A STUDY OF A SAMPLE OF ARAB COUNTRIES

In conjunction with the fourth industrial revolution, whose outputs changed today's global landscape, the importance and role of the digital economy in stimulating sustainable development in its social, economic and environmental dimensions has emerged. In this regard, this paper aims to investigate the impact of the digital economy on the achievement of the sustainable development goals of a sample of 12 out of 22 Arab countries divided into two groups. The first group comprises six digitally leading Gulf countries, namely, Emirates, Saudi Arabia, Bahrain, Qatar, Oman and Kuwait, while the second group also includes six digitally promising countries, namely Egypt, Jordan, Lebanon, Morocco, Tunisia and Algeria,. For this purpose, the Arab Digital Economy Index 2022 based on five strategic dimensions (digital government, digital foundations, digital citizen, innovation, digital business) was considered as an independent variable and sustainable development goals were adopted as a dependent variable. Using SPSS 23, specifically the Student test and the Levene’s test to compare averages and regression model. The research results confirmed that there were significant differences between the average Arab digital economy index of the sample and the average benchmark index of comparator countries of Malaysia and Singapore. There are also significant differences between the average Arab digital economy index for the sample and the average index for the Arab region. There are significant differences between the average digital index in the first group and the second group. The significant impact of the Arab Digital Index on the achievement of the seven sustainable development goals most affected by digital transformation was verified. While there is no significant impact of the Arab Digital Index on the achievement of all 17 sustainable development goals. The recommendation is that the digital transformation of the Arab countries should be accelerated to develop a secure digital business environment, catch-up and benefit from the gains of the digital economy
Training on Making 3D Models of Augmented Reality Based Hydrology Education Tools for Teachers

Augmented reality in its development in Indonesia has Lots used as an auxiliary medium classroom teaching for learning to become more interactive between teacher and student. Students get Study independent with an observed tool developed augmented reality display without need guided. However sadly Still how difficult development augmented reality application, making Not yet how many teachers can develop application based on augmented reality. on the basis problem such, he did activity devotion to public in form training creation of 3D models based on augmented reality followed by representatives from teachers from all over Palopo as many as 15 teachers. Activity training is shared into 3 sessions, ie session First through method lecture, session second guided tutorial methods and sessions final with practice. Result of implementation training This is a capable teacher making augmented reality application for free independent and capable tool display hydrology based on augmented reality that can be used for enrich classroom learning.
The role of semi-supervised learning in harnessing unlabeled data for model training

The ever-growing availability of vast amounts of unlabeled data poses a significant opportunity for enhancing machine learning models. Semi-supervised learning (SSL) has emerged as a powerful paradigm to harness the potential of unlabeled data by combining it with limited labeled samples. This review paper provides a comprehensive overview of the role of semi-supervised learning in model training, focusing on its applications, methodologies, and advancements. The paper begins by elucidating the challenges associated with traditional supervised learning paradigms, emphasizing the scarcity of labeled data in many real-world scenarios. It then delves into the principles of semi-supervised learning, elucidating how it enables models to learn from both labeled and unlabeled data, thereby capitalizing on the abundance of unannotated information.A critical analysis of various SSL techniques is presented, ranging from traditional methods such as self-training and co-training to more recent advancements like consistency regularization and generative adversarial networks. The review also explores the effectiveness of SSL across different domains, including computer vision, natural language processing, and speech recognition, showcasing its versatility and widespread applicability. Furthermore, the paper discusses challenges and open research questions in the field of semi-supervised learning, addressing issues such as model robustness, scalability, and generalization to diverse datasets. The evolving landscape of SSL is highlighted, including recent breakthroughs and emerging trends that shape the future of utilizing unlabeled data for model training.
Approach to Grayscale Image Enhancement by Noise Reduction

With the rise in the quantity of digital photos taken each day, there is a rising desire for more accurate and aesthetically appealing images. More precisely, noise is a problem for photos in terms of corruption since certain sounds may be introduced to the image automatically during capture. Additionally, camera sensors and lighting conditions contribute to the noise that might be added to the picture. This is referred to as additive noise. Noise reduction is critical for achieving a beautiful picture. describe a robust approach for decreasing noise in photos based on the heat equation in this study. Additionally, we compare our proposed technique against many existing methods using denoising performance indicators.
Some Properties of Fuzzy Ideals of Unit Regular Semigroups

This paper introduces the concept of unit-regular fuzzy ideals of semi groups, which is a generalization of regular fuzzy ideals. Several of their significant related properties have been examined. According to the unit-regular semi group, the fuzzy-interior-ideal, fuzzy-ideal, fuzzy-bi-ideal, and fuzzy-generalized-bi-ideal have all been described.
Evaluating the Performance of a Photovoltaic System Using Acceptance Ration (AR)

The use of fossil fuels for energy production has several negative impacts on the environment and human health. Therefore, renewable energy is needed as an environmentally friendly source. Solar energy is one of the renewable energy produced from solar radiation using photovoltaic (PV). The explanations given by science about how the sun works are in line with what is stated in the Qur'an. One verse in the Quran speaks of Allah's Greatness and His Mercy, and it is found in: “And there He created a shining moon and made the sun a (brilliant) lamp. (Q.S. Nuh: 16)”. However, one of the problems in using PV systems is that the energy produced is unstable because it is influenced by the environment. Therefore, it is necessary to evaluate the performance of the PV system from time to time. In this research, the performance of the PV system is being done by determining the Acceptance Ratio (AR). AR is used to define the ratio of actual AC power to expected AC power. The largest expected output power value is 436.4788 W, on May 26. The acceptance ratio (AR) obtained ranges from 0.921 to 0.982, which should be worth approximately 0.9. This is influenced by the output power generated and the expected AC power generation data obtained from the calculation. The expected AC power generation value is different for each data depending on the weather conditions whether it is cloudy or sunny.
Instrumental Express Analysis of Ferromanganese Ores by Nuclear-geophysical Method

There is given the rationale for the effectiveness of using a selective filter in the X-ray fluorescence analysis of ores for the purpose of separate determining the concentration of iron and manganese. The analysis of updated methods of taking into account the interfering effect of elements with close atomic number is presented. The main destabilizing factors affecting the accuracy and selectivity of instrumental X-ray fluorescence analysis of ferromanganese ores have been studied. There is theoretically and experimentally substantiated the method of express determining iron and manganese based on measurements of the fluorescent radiation of the determined elements intensity with a selective filter and without a filter. In the process of experimental studies of ferromanganese ores of various material compositions, the accuracy of instrumental fluorescence analysis has been obtained that is satisfactory for solving technological problems.
Formation of Spiritual Needs of Students in the Higher Education System

The article is devoted to the philosophical understanding of the peculiarities of the formation and development of the spiritual needs of students. The conclusions are substantiated that the attitude of students to the profession depends not only on the level of conformity of ideas about the profession, but also on its social significance. The authors also claim that the attitude of students to the profession depends on the dynamics of the assessment of their professional maturity. The system of spiritual needs is considered as the most important component of the life of society, reflecting the selective attitude of students to social values. They determine the line of their behavior aimed at achieving these values. The authors substantiate the idea that higher professional education should become not only a tool for the professional training of future specialists, their socialization and adaptation to life in a market society, but also an equal component of the formation of the spiritual needs of young people
Model of Design and Engineering of Educational Programs

A model of design and engineering of higher education programs is presented taking into account the recommendations of ESG on the example of the North Kazakhstan University named after M. Kozybayev. The main purpose of the study was to determine a number of organizational and methodological stages that ensure compliance of the developed educational programs with the requirements of all stakeholders. Special attention is paid to the stage of formation of the university graduate model. The evaluation indicators of educational programs are presented, demonstrating the effectiveness of the implemented model.
Determining which sine wave frequencies correspond to signal and which correspond to noise in eye-tracking time-series

The Fourier theorem states that any time-series can be decomposed into a set of sinusoidal frequencies, each with its own phase and amplitude. The literature suggests that some frequencies are important to reproduce key qualities of eye-movements (“signal”) and some of frequencies are not important (“noise”). To investigate what is signal and what is noise, we analyzed our dataset in three ways: (1) visual inspection of plots of saccade, microsaccade and smooth pursuit exemplars; (2) analysis of the percentage of variance accounted for (PVAF) in 1,033 unfiltered saccade trajectories by each frequency band; (3) analyzing the main sequence relationship between saccade peak velocity and amplitude, based on a power law fit. Visual inspection suggested that frequencies up to 75 Hz are required to represent microsaccades. Our PVAF analysis indicated that signals in the 0-25 Hz band account for nearly 100% of the variance in saccade trajectories. Power law coefficients (a, b) return to unfiltered levels for signals low-pass filtered at 75 Hz or higher. We conclude that to maintain eye- movement signal and reduce noise, a cutoff frequency of 75 Hz is appropriate. We explain why, given this finding, a minimum sampling rate of 750 Hz is suggested.
Reflection Influence on the Thought Process of Students with Distance Learning

The issues of reflection and its relevance as a tool in the student education system for rethinking their activities and changing the direction of the students’ thought process, prerequisites and advantages of using reflection in the education system and its influence on the students’ thought process are given. The final result (product) of education (knowledge, skills, abilities, personal qualities) is created jointly by the teacher and the student, since the basis for the successful learning of the material is cooperation between them and a conclusion made by the student independently or with the teacher’s help. In the course of the learning process, there increases the information flow for educational purposes (the World Wide Web, databases and electronic libraries, forums, conferences, computer models, indicators and simulators, network applications that facilitate organization of «virtual» collaboration, etc.). A description of the «portfolio» technology is given, that plays an important role in organizing the educational process and establishing connections between the teacher and the student and is the most important assessment tool. In the course of studying, reflection was considered as a phenomenon in the student’s mind that arose after rethinking his activities and changing the direction of the thought process.
Employee Empowerment and Job Satisfaction in Nepalese Commercial Banks

The discourse surrounding the issue of employee empowerment (EE) has consistently been of great importance on a global level. The aim of this study is to assess the status, relationship, and impact of employee empowerment and job satisfaction in Nepalese commercial banks. The study employed a deductive approach with descriptive and analytical research designs. The study population includes all employees working in Nepalese commercial banks in Sunsari, totaling 258 individuals. A structured questionnaire was designed to collect primary data through convenience sampling with a five-point Likert scale. SPSS was used to manage and analyze data. Cronbach alpha was used to test the reliability of constructs and descriptive statistics were used to assess the status of employee empowerment and job satisfaction. Furthermore, inferential statistics were used to analyze the relationship and level of significance between variables and measure the impact of employee empowerment on job satisfaction. The research findings indicate that employees have a positive response towards all dimensions of employee empowerment and job satisfaction. Furthermore, the finding revealed a significant impact of employee empowerment on job satisfaction. Thus, commercial banks should continuously work on programs empowering employees to enhance job satisfaction.
Construction of Substitution Boxes Using Finite Fields

Substitution boxes (S-boxes) play a crucial role in modern cryptographic algorithms, providingnon-linear transformations that enhance the security of data encryption. S-boxes are essentialcomponents of symmetric key ciphers, such as Advanced Encryption Standard (AES) and DataEncryption Standard (DES). Non-linearity is a fundamental property that resists linear attacksand enhances the cryptographic strength of S-boxes. Constructing secure and efficient S-boxeswith high non-linearity is a critical challenge in cryptography. The problem of this research isto develop a systematic approach for constructingsubstitution boxes (S-boxes) using finite fields,with a particular focus on achieving optimal non-linearity to enhance the security of cryptographicalgorithms.
Comparison of Clean Energy Trading Method in Microgrid by using Blockchain Technique

The old conventional energy distriution system cannot fulfill the demand of the prosumers in providing secure energy trading and with minimum losses in energy transmission. Because it is centralized system and user has no freedom to trade energy without involving the third party. In conventional grid there are lot of issues such as controlling the losses and forecasting the demand and reliability. One major issue is theft of electricity and losses. The new blockchain system has potential to provide secure energy trading in network without involvement of third party. The combination of blockchain and Microgrid has all features to resolve the issues related to the current grid such as controlling power, Forecasting the demand and reliability. In this paper the combination of Microgrid and blockchain for trading energy will be analyzed and energy trading method in P2P Network based will be investigated to find best method for trading enegy in network. For the simulation the matlab tool will be used.