Reviewerly/exHarmony huggingface dataset:
Exploring the Notion of Risk in Code Reviewer Recommendation

Reviewing code changes allows stakeholders to improve the premise, content, and structure of changes prior to or after integration. However, assigning reviewing tasks to team members is challenging, particularly in large projects. Code reviewer recommendation has been proposed to assist with this challenge. Traditionally, the performance of reviewer recommenders has been derived based on historical data, where better solutions are those that recommend exactly which reviewers actually performed tasks in the past. More recent work expands the goals of recommenders to include mitigating turnover-based knowledge loss and avoiding overburdening the core development team. In this paper, we set out to explore how reviewer recommendation can incorporate the risk of defect proneness. To this end, we propose the Changeset Safety Ratio (CSR) – an evaluation measurement designed to capture the risk of defect proneness. Through an empirical study of three open source projects, we observe that: (1) existing approaches tend to improve one or two quantities of interest, such as core developers workload while degrading others (especially the CSR); (2) Risk Aware Recommender (RAR) – our proposed enhancement to multi-objective reviewer recommendation – achieves a 12.48% increase in expertise of review assignees and a 80% increase in CSR with respect to historical assignees, all while reducing the files at risk of knowledge loss by 19.39% and imposing a negligible 0.93% increase in workload for the core team; and (3) our dynamic method outperforms static and normalization-based tuning methods in adapting RAR to suit risk-averse and balanced risk usage scenarios to a significant degree (Conover's test, α < 0.05; small to large Kendall's W).
Research on the Application of Artificial Intelligence Technology in the Three-dimensional Teaching Field

Conventional online teaching video lectures can’t display teaching resources in three dimensions, and the Three-dimensional integrated teaching field can realize the Three-dimensional scenes that can’t be satisfied by ordinary online teaching, and bring realistic teaching experiences for teachers and students in other places, but the existing virtual reality equipment is too expensive and can’t meet the needs of most people. This paper uses artificial intelligence techniques and the unity3D engine to study techniques that can be used to interact with ordinary devices and 3D scenes. Firstly, we use a neural network to implement gesture recognition, and after experiments, we found that Faster R-CNN is faster and more accurate, and Faster R-CNN is selected as the training network for gesture recognition. Then call the recognition interface in the scene, when a certain gesture is recognized or a certain voice is received, the teaching resources in the unity3D scene will run the corresponding animation, to achieve a more realistic display effect. Finally, artificial intelligence technology and virtual reality are successfully combined. The cost of the interaction technology we use is at least 70% lower than that of other devices, which can meet the needs of most scenarios.
ConveXplainer for Graph Neural Networks

Graph neural networks (GNNs) have become the most prominent framework for representation learning on graph-structured data. Nonetheless, cue to its black-box nature, they often suffer from the same plague that afflicts many deep learning systems: lack of interpretability. To mitigate this issue, many recent approaches have been proposed to explain GNN predictions. In this paper, we propose a simple explanation method for graph neural networks. Drawing inspiration from recent works showing that GNNs can often be simplified without any impact on performance, we propose distilling GNNs into simpler (linear) models and explaining the latter instead. After distillation, we extract explanations by solving a convex optimization problem which identifies the most relevant nodes for a given node-level prediction. Experiments on synthetic and real-world benchmarks show that our method is competitive with, if not outperforms, state-of-the-art explainers for GNNs.
ATTITUDE OF STUDENTS, FUTURE TEACHERS TOWARDS THE QUALIFICATION AND QUALITY OF EDUCATION

The provision of quality education and the creation of conditions for lifelong learning in the preparation of pupils and students ensure the continuous progress of their achievements, the development of research and technology and enhance the impact that acquired competencies have on economic and social life. The article presents the main characteristics of the quality of higher and secondary education. Follows the attitude to the qualification and motivation for self-development and self-improvement of students from the University of Shumen „Bishop Konstantin Preslavski“ as a guarantor of the quality of preschool and school education. According to the studied opinion of the students, on the one hand their self-assessment of the acquired competencies for practicing the profession „teacher“ is monitored and analysed and on the other – the factors for successful qualification activity and their motivation to participate in trainings. The results of the study serve to provide recommendations for improving the quality of university education and continuing education.
Exploring appropriate ERP framework towards Indian small and medium enterprises using decision tree

Small and medium enterprises (SMEs) enhance the outcome of the various business processes through implementing an ERP framework. However, they face the problem of selecting the appropriate ERP, as it entails a large upfront capital expense, leading to question the sustainability of SMEs, especially during the pandemic. A cloud-based ERP system can reduce the risk to a certain level due to their low infrastructure cost and flexible payment options but this has its own constraints. Thus, selection of the appropriate ERP is always a challenge, which motivates the current researchers to explore a decision tree-based technique to predict the most suitable framework that needs to be adopted by a SME in a specific situation. The inferences drawn from the decision tree clearly shows the efficacy of the implemented technique as the right decision can be derived easily by traversing the tree.
Quality Assessment of Sonar Images

In many underwater applications such as biometric tracking and underwater rescue, it is necessary to analyze sonar images that contain a large amount of important information like submarine geomorphology, marine organisms, and wreck remains. Traditional optical imaging and analysis methods are inapplicable due to the limited penetration depth of visible light, so sonar imaging techniques play important roles in marine applications. Sonar image signals usually need to be transmitted via the underwater acoustic channel (UAC) for further analysis. Nonetheless, the sonar images presented to users by the terminal are subject to typical underwater distortion because of the poor UAC condition. For the QA of sonar images, this chapter first shows the sonar image database and the full-reference QA methods on account of local entropy, and statistical and structural information to capture the underwater distortion in sonar images. Second, it introduces task- and perception-oriented reduced-reference QA methods on account of the human visual system to evaluate the sonar images with poor quality in complex environments. Third, to address the issue of inaccessibility of reference sonar images in dynamic underwater environments, it presents the no-reference QA method based on contour degradation measurement. In the end, the QA methods mentioned above are validated on relevant databases, and the necessity of establishing efficient sonar image QA methods is indicated.
Digital Mindsets: Notion, Theoretical Foundation and Examination Access

The study of cognitions in managerial and organisational research is increasingly attracting interest. The Managerial and Organizational Cognition (MOC) division of the US Academy of Management (AOM) describes this interest as being ‘devoted to understanding individual, relational, and collective cognition in organizational contexts’ (MOC—Managerial and Organizational Cognition Division, n.d.). As Secchi and Adamsen (2017) outline, the roots of this interest in cognitions as part of organisational behaviour can be traced to the ‘cognitive revolution’ in management and organisational studies (MOS).
Pengaruh Pembelajaran Online Berbasis Zoom Cloud Meeting dan Google Classroom Terhadap Hasil Belajar

The research has a goal, namely 1) Knowing the effect of learning with zoom cloud meetings on learning outcomes. 2) Knowing the effect of learning with google classroom has an impact on learning outcomes. 3) The effect of learning with zoom cloud meeting and google classroom together has an impact on the learning outcomes of inferential statistics for undergraduate accounting students at Pamulang University. A quantitative approach with associative type is used in this study. Methods of collecting research data with questionnaires and documentation. Test the validity and reliability for the instrument, test prerequisites before analysis, and test the hypothesis with regression. This study obtained the following results: (1) Online learning with zoom cloud meeting has an impact on learning outcomes, (2) online learning with google classroom has an impact on learning outcomes, (3) online learning with zoom cloud meeting and google classroom jointly have an impact on the learning outcomes of inferential statistics students of S1 Accounting at Pamulang University.Keywords: Zoom; Google Classroom; Learning Outcomes.
Quality Assessment of Enhanced Images

In the field of image processing, image enhancement and quality assessment (QA) techniques have received much attention due to their great potential in practical applications, such as object detection, recognition, and so on. Image enhancement technique has the ability to alter the visual perceived quality of images, and it is generally accepted that the enhanced images have better visual quality than the original images. However, enhancement techniques usually introduce noise and artifacts into the visual attention regions of images, resulting in over-enhancement. Therefore, it has been a hot issue in recent years to optimize the model structures and parameters to realize appropriate enhancement on the basis of enhanced image QA. For the QA of enhanced images, this chapter first constructs the contrast-changed image QA database and introduces the reduced-reference QA methods that are based on phase congruency and histogram statistics. Second, it shows the no-reference QA methods based on the fusion of non-structural information, sharpness and naturalness, and feature extraction and regression. Third, it presents the automatic contrast enhancement technique based on evaluation criteria guidance. In the end, the QA methods introduced in this chapter are validated on relevant databases, and the necessity of constructing efficient enhanced image QA methods is stated.
The Use of Role Play Method to Increase Students Interest in Learning English After the Implementation of Online Learning due to The Covid-19 Pandemic

The objective of this research was to find out the contribution of applying role play method in learning English for the students of SMP Negeri 5 Maiwa. This study tried to find a learning method that can be used to increase student interest in learning after the implementation of online learning due to the covid-19 pandemic. The research used descriptive method. It involved one group of students, which was taught English through role play method. The population was the class VIII students of SMP Negeri 5 Maiwa in first semester 2021/ 2022 academic year. The population consisted of 50 students with two classes. The research used cluster random sampling by taking only one class as a sample namely class VIII A. The number of sample was 30 students. There are two variables in this research. It consists of independent and dependent variable. The first is the students’ interest as dependent variable and the second is role play method as independent variable. The instrument of the research was questionnaire which was given after teaching learning process in two meetings. The research found that most of the students choose strongly agree(very interested) and agree(interested) in the questionnaire related to the students’ interest in learning English through role play method.
MANAGEMENT OF SYSTEM COMMUNICATIONS IN SCIENTIFIC AND EDUCATIONAL ORGANIZATIONS DURING THE PANDEMIC

Society is facing new challenges caused by the COVID-19 pandemic. The global problems associated with this affected, among other things, the sphere of management, system connections in it, and also served as an incentive and prerequisite for the development and improvement of information technologies. Such technologies help to minimize the spread of the virus and at the same time allow organizations to continue their functioning.
Gender Political Inclusion and Inclusive Finance in Africa

At the 2010 G20 Summit, the use of formal financial services was recognized as one of the main pillars of the global development agenda. At the same time, the fifth goal of the Sustainable development agenda outlined the importance of gender inclusion for sustainable development. Empirical research on the effect of gender inclusion on inclusive finance has however been limited to micro level studies. This study aims to verify the effect of gender political inclusion on financial inclusion on a sample of 37 African countries from 2004-2020. The empirical methodology involves the Ordinary Least Squares (OLS), the Tobit regression and the System Generalized Method of Moments (GMM) methodologies. The results from these methods show that gender political inclusion is enhancing on financial inclusion in Africa, and this finding is robust across alternative specifications of gender inclusion and inclusive finance. Besides, governance exhibits a positive synergy effect with gender political inclusion on inclusive finance. Policy implications are discussed.
Control points searching algorithm for multiple mobile robots

In the robotic field, the important issue is to find the adequate path for the mobile robot navigation with free collision. This paper describes the development of the navigation strategy for multiple mobile robots. The present work investigates two types of navigation strategies: navigation with one robot and navigation with two robots. The proposed algorithm is based on searching the value of the visibility condition of the trajectory to detect the collision problem. Then, control points are selected to find the safe path for navigation. On the other hand, a sliding mode controller (SMC) is used for tracking the planned trajectory. Hence, to improve the performance given by the SMC, a fuzzy logic control approach is applied for tracking the desired trajectory. Finally, simulation results are given to highlight the applicability of the proposed approach.
TEACHER PERFORMANCE IN LARGE SCALE ASSESSMENT AT SCHOOL LEVEL EDUCATION

Assessment is an educational tool that aims is to monitor and improve quality education and thus, It can be a key factor in transforming schools into places of quality learning for all students. To identify why students performed below the average, the teaching quality is one of the key components in this regard. The present study is aimed to determine the teacher performance in different content domains of mathematics at the school level. For this purpose, the achievement test 2016 which was conducted at the national level is used as a research instrument. The study included school teachers of Islamabad and Azad Jammu &amp; Kashmir which participated in National Achievement Test (NAT) 2016. Data was gathered from National Education Assessment System (NEAS) after seeking permission from the Ministry of Federal Education and Professional Training (MOFE&amp;PT). The collected data was analyzed by Percentage. Result of the study showed the teachers performed average in NAT 2016. Another very concerning finding is that the AJK teachers were not well prepared to teach several mathematics topics such as measurement, multiples, and numbers as they have basic content knowledge comparatively to Islamabad teachers who were quite adequately prepared to teach all topics as they have the proficient knowledge level. Results are discussed and recommendations for teachers and policy making are offered. Keyword: Assessment, Large-Scale Assessment, Teacher Performance, National Achievement test
FEATURES OF VIRTUALIZATION TECHNOLOGIES IN IT INFRASTRUCTURE OF HIGHER EDUCATIONAL INSTITUTIONS

This article describes specific virtualization technology in university IT infrastructure taking into account security threats.
Deep Learning Representations in Automatic Misogyny Identification: What Do We Gain and What Do We Miss?

In this paper, we address the problem of automatic misogyny identification focusing on understanding the representation capabilities of widely adopted embeddings and addressing the problem of unintended bias. The proposed framework, grounded on Sentence Embeddings and Multi-Objective Bayesian Optimization, has been validated on an Italian dataset. We highlight capabilities and weaknesses related to the use of pre-trained language, as well as the contribution of Bayesian Optimization for mitigating the problem of biased predictions.
Reform and Innovation of the Educating Mode of Advanced English on Mosoteach Platform in the Time of Big Data

With the rapid development of information technologies, the whole world is gradually entering the time of big data. It affects many fields in which English teaching is involved. Taking full use of big data to promote the quality of college English education is an inevitably trend. As a main course for the senior English majors, Advanced English is essential to improve the essential language skills and critical thinking of the students. However, the current Advanced English teaching mode could not meet the requirement in the time of big data due to the monotonicity in teaching methods. Therefore, it is vital to study the combination of the teaching mode and some efficient teaching platforms. This paper studies the opportunities and challenges of Advanced English Teaching in the time of big data, and offers reforming and innovative advice from three major aspects of the teaching mode, the teaching contents and the teaching evaluations.
Towards Large-Scale Silicon Photonic Programmable Optical Processors for Machine Learning and Optical Quantum Computing

We discuss the progress made towards large-scale programmable optical processors on Silicon Photonics for ultrafast and energy efficient computing.
A new generalization of Renyi’s entropy of order β with coding theory in fuzzy environment

The main problem in coding theorem is to transfer the message on noiseless medium and length of code should be selected in such a way that average code length is minimized. Therefore, a new approach of generalization of Renyi’s entropy of parameter β has been discussed in this paper. We have also considered a number of its characteristics in comparison with Shannon and other existing entropies. Thereafter, we discussed the monotonous behavior of MCWL (Mean Code Word Length) using the noiseless coding theorem with the different values of β. We also proved that entropy function is lower bound of average code word length i.e. average code word length is upper bound of entropy value. Additionally, we proposed a new information measure for fuzzy set and proved its validation. To demonstrate the better results attained by proposed measure, numerical examples are also provided. Further, comparison has been given with other entropies which shows the reliability and supremacy of proposed measure.
Concept of digital twin construction scheme for flood storage space in mid-lower Yangtze River

&lt;p&gt;The integration of the digital twin with the water industry is a new generation of information technology and communication technology in the integrated application of the water industry, is an important implementation path to promote the new stage of high-quality water development. The current level of wisdom in the water conservancy industry is still low, and there is relatively little research and application for the digital twin. For this reason, the basic connotation and development concept of the digital twin is discussed in depth, and research is conducted focusing on the problems that may be faced in the construction process of the digital twin in the flood storage space. The study gives a general scheme of flood storage space construction with data base construction, digital scene construction, intelligent simulation and accurate decision support construction as the main axes. The related results can provide constructive planning ideas for future smart river basin construction.&lt;/p&gt;
Index Behaviors

In the previous chapter, I introduced the core indexes within SQL Server, both rowstore and columnstore, clustered and nonclustered. This chapter takes that information and adds additional functionality to those indexes. I’ll also introduce some new indexes in this chapter. There are a number of index settings that affect their behavior we’ll also discuss.
The implementation of mathematical e-learning assisted by storyboard

The purpose of this research was to describe the implementation of mathematical e-learning assisted by storyboard which was oriented towards students learning achievement. The types of this research were descriptive quantitative research. This research was conducted on 25 students of junior high school in Yogyakarta. Data collection techniques were tests and questionnaires. The results of this research indicated that the data obtained regarding student learning achievement from 25 students, the highest student learning achievement got a score of 100. The lowest was 50 with an average student learning achievement was 86.5, it was included in the high criteria, where 88% of the learning achievement obtained by students were scattered in the medium, high, and very high categories. Then, based on data obtained from the questionnaire responses of students during the e-learning that assisted by storyboard showed that 100% of students' responses were scattered in the medium, high, and very high categories. The result showed that storyboard media had a positive influence on mathematical e- learning. Therefore, storyboard can be utilized to support mathematics e-learning and increase the student motivation in learning activities.