Reviewerly/exHarmony huggingface dataset:
Static Analysis Warnings and Automatic Fixing: A Replication for C# Projects

Static analyzers have become increasingly popular both as developer tools and as subjects of empirical studies. Whereas static analysis tools exist for disparate programming languages, the bulk of the empirical research has focused on the popular Java programming language. In this paper, we investigate to what extent some known results about using static analyzers for Java change when considering C#-another popular object-oriented language. To this end, we combine two replications of previous Java studies. First, we study which static analysis tools are most widely used among C# developers, and which warnings are more commonly reported by these tools on open-source C# projects. Second, we develop and empirically evaluate EagleRepair: a technique to automatically fix code in response to static analysis warnings; this is a replication of our previous work for Java [20]. Our replication indicates, among other things, that 1) static code analysis is fairly popular among C# developers too; 2) Re-Sharper is the most widely used static analyzer for C#; 3) several static analysis rules are commonly violated in both Java and C# projects; 4) automatically generating fixes to static code analysis warnings with good precision is feasible in C#. The EagleRepair tool developed for this research is available as open source.
Developing a Modern Educational Environment in the Digital Space at the Institution of Professional (Vocational-Technical) Education

The purpose of this article is to substantiate and analyze the digital space of the information development and educational environment of IP(VT)E and identify current issues. The current state of the digitalization process in institutions of professional (vocational-technical) education [IP(VT)E] and its impact on the development of information and educational environment are studied. Teachers and students are faced with problems in training and production processes, including distance learning, brought about by quarantine restrictions during the Covid-19 pandemic. These issues were determined and an analysis of the activities of IP(VT)E in Ukrainian regions made with respect to the creation and development of an information and educational environment. This was achieved by developing models and implementing individual components of the digitalization process, and the development of electronic educational literature and introduction of 3D modeling technologies. The example is presented of an information and educational environment created by the Educational and Practical Center of Electrical Technologies in Kryvyi Rih and based on an electronic educational platform.
Egypt’s path to prosperity

Egypt is among Africa’s industrial heavyweights. The first chapter of the PTPR of Egypt discusses the country’s economic performance, focusing on structural determinants such as industry, trade and innovation. The country is upgrading its domestic industrial capabilities and has identified strengthened international partnerships and enhanced ties with Africa as major opportunities for advancing on its march towards prosperity. This chapter clarifies that scaling-up productive investments and innovation are needed to unlock opportunities for all.
Face Detection in Distorted Images Based on Image Restoration and Meta-learning

Face detection in distorted images is a challenging task, and a natural idea is to conduct image restoration before face detection. Most of current image restoration techniques focus on improving the perceptual quality of the output image for single type of distortion, without taking the subsequent high-level detection task and unknown distortion into account. In this paper, we propose a restoration-based face detector in which the images are restored based on the detection loss instead of the perceptual quality loss, leading to better performance on subsequent detection task. Furthermore, we employ meta-learning to initialize the model with more appropriate parameters, thus our detector can adapt quickly to unseen distortions only using few examples with the corresponding distortion. Experiments on public datasets show that our proposed method could improve the performance of face detection in distorted images, and have a better generalization ability when applied to images with unseen distortions.
Topic identification from news blog in Spanish language

Currently exist a large amount of news in a digital format that need to be classified or labeled automatically according to their content. LDA is an unsupervised technique that automatically creates topics based on words in documents. The present work aims to apply LDA in order to analyze and extract topic from digital news in Spanish language. A total of 198 digital news was collected from a university news blog. A data pre-processing and representation in vector spaces was carried out and k values were selected based on coherence metric. A TF_IDF matrix and a combination of unigrams and bigrams produce topics with a variety of terms and topics related to university activities like study programs, research, projects for innovation and social responsibility. Furthermore, with the manual validation process, terms in topics correspond with hashtags written by the communication professionals.
Theoretical Considerations Concerning the Adoption of Blockchain as a Competitive Strategy

With an increasing focus on blockchain technology, this paper synthesizes competitive dynamics and the resource-based view of the firm to consider the impacts of blockchain technology on strategic decision-making. This paper offers an expanded and reconceptualized version of the AMC framework to propel both management considerations for and academic research on blockchain. Additionally, the paper considers potential drivers and barriers to blockchain technology adoption and usage. It presents three propositions detailing how a combination of a firm’s specific internal resources and external competitive environment influences strategic managerial decision-making surrounding blockchain.
Directions for reorganizing the Ministry of Education to establish the future-oriented educational governance

본 연구는 정부 조직개편 과정에서 교육부가 직면하고 거시적인 상황과 맥락에 대한 이해를 바탕으로 교육거버넌스 관점에서 교육부의 역할과 행태를 분석하고, 미래지향적 교육거버넌스를 지향하는 교육부의 역할과 기능의 조화를 통해 어떻게 재구조화할 것인지를 탐색적으로 기획하는 데 목적을 두었다. 정권교체기의 정부 조직개편 과정에서 나타나는 정치적 현상은 정치체제적 접근과 역사적 제도주의적 관점에서 조망될 수 있다. 본 연구에서는 역사적 제도주의 접근을 채택하여 정부 조직개편을 구조, 제도, 행위자 수준에서 분석하고 통합적으로 정부 조직개편의 거시적 맥락을 제시하고자 하였다. 구체적으로, 교육부 조직개편의 미시적 맥락을 이해하기 위하여 교육부 조직을 SWOT 분석을 실시하였고, 현재 교육부의 조직개편론을 폐지론, 통폐합론, 존치론으로 나누어 살펴보았다. 마지막으로, 교육부 조직개편에 대한 거시적·미시적 맥락에 대한 이해를 바탕으로 교육거버넌스 관점과 역할-기능 조화론을 채택하여 조직개편의 방향을 탐색하였다. 향후, 교육부 조직은 정부 조직개편 시즌에 종속변수로서 폐지와 존치의 갈림길에서, 과거의 경험처럼 적당히 중간 수준에서 통폐합되거나 적절한 수준에서 기능이 축소되는 타협적인 존치로 마무리될 가능성이 크다. 그러나 교육부 조직개편은 결과와 상관없이 시대사회적인 환경의 변화와 국가사회적 요구에 직면하여 어떤 형태로든 진행될 필요가 있다. 이에 교육부 조직개편은 곧 거버넌스 재구조화이며, 교육부가 존재해야 할 이유와 명분을 먼저 살피는 구조기능 재편에 선행하는 역할의 정립에 중점을 두어야 할 것이다. This study was intended to analyze roles and practice of the Ministry of Education from the perspective of educational governance, based on the understanding of macro-level situation and context facing the Ministry, and to plan in search for how to reorganize the Ministry with the harmony between its roles and functions. At the era of regime change, political phenomena appeared in the process of restructuring the governmental organization can be approached from the political system and historical institutionalism perspectives. This study analyzed the restucturing of governmental organization at the levels of structure, institution, and actor, and unitedly tried to understand its macro contexts. In detail, the study implemented the SWOT analysis on the Ministry organization and examined the restructuring into its abolition, merger, and maintenance in order to understand its micro contexts. Then the study adopted the perspectives of educational governance and role-function harmony for restructuring the Ministry organization and examined their characteristics and methods. At the crossroad of its abolition and maintenance the organization would be likely to be finished as a compromised maintenance in ways of integrating into some appropriate level of its large functions or minimizing its functions fewer. Regardless of its results, however, the Ministry reorganization needs to be continued, especially facing the times of changing societal environments and the demands of the nation and society. Therefore, what the Ministry reorganization call means its governance restructuring, so that it will focus on the establishments of its roles that care about the reasons and justification of why the Ministry should exist, ahead of arguing the reorganization of its structures and functions.
Analysis of Policy Changes in the School Record-based Screening Method: Using Kingdon's Policy Stream Model and Topic Modeling

본 연구는 학생부종합전형의 정책변동과정 분석을 통해 학생부종합전형과 대입정책 개선을 위한 시사점을 도출하는 것을 목적으로 한다. 최근 두 차례의 정책변동을 분석하기 위하여 Kingdon의 정책흐름모형과 구조적 토픽 모형을 사용하였으며 정책변동에 영향을 미친 정책흐름을 확인하고 도출된 토픽을 통하여 그 영향력을 확인함으로써 연구자의 해석에 의존하는 이론적 틀의 한계점을 보완하고 보다 실증적인 분석 결과를 제시하였다. 분석 결과 첫째, 학생부종합전형 위축기의 정책 쟁점은 부모의 경제력에 따라 유리할 수 있는 비교과 평가요소의 공정성 문제에서 기인하며 두 차례의 정책변동은 학종의 쟁점을 전혀 해소하지 못하였다. 둘째, 학생부종합전형 2차 위축기의 정책변동이 지난 정책이 적용되기도 전에 이루어진 것은 졸속이며 정책변동-적용-환류를 통한 대입개편이 이루어져야 한다. 셋째, 정부는 정책 추진방식 및 방향성이 정책의 개선점보다는 정책변동의 방식에 초점이 맞추어진 것을 반성하고 교육전문가 집단의 의견에 귀 기울여야 한다. 마지막으로 대입제도가 정치권의 영향에 따라 변동되는 일이 없도록 장기적인 정책연구를 통하여 큰 틀 안에서 법제화하여야 한다. The purpose of this study is to derive implications for the improvement of the school record-based screening method and university admission policies through the analysis of the policy change process of the school record-based screening method. Kingdon's policy stream model and STM were used to analyze the two recent policy changes. By confirming the policy stream that affected the policy change and confirming the influence through the derived topic, the limitations of the framework were supplemented and more empirical analysis results were presented. As a result, first, the policy issue in the declining period stems from the issue of fairness in the extracurricular, which can be advantageous depending on the economic power of parents. Second, the policy change of the 2nd declining period was made before the policy was applied, and policy reorganization through policy change-application-feedback must be made. Third, the government should reflect on the fact that the policy implementation method and direction are focused on the method rather than the improvement point, and listen to the opinions of the education expert group. Lastly, the university admission system should be legislated so that the system does not change according to the influence of the political circles.
Research Trend Analysis of Superintendent of Education

본 연구는 지방교육자치제 도입 이후 교육감 관련 연구 동향을 분석하였다. 구체적으로 출판연도, 게재 학술지, 연구자 특성, 연구주제 및 연구방법 등을 분석하였다. 본 연구에서 분석된 학술논문들은 KERIS 학술연구정보서비스에서 교육감과 관련된 등재(후보)지에 게재된 160편이었다. 분석 결과, 첫째, 교육감 관련 논문은 교육감 선거 직후 증가하였고, 교육 및 비교육 분야 학술지에서 출판되었으며, 교육행정 교수와 법학, 행정학, 정치학 전공 교수들 모두가 교육감 연구에 관심을 갖고 있었다. 둘째, 교육감 관련 연구주제는 교육감의 선거, 교육감 제도 및 정책 분석에 치중되어 있었다. 셋째, 문헌, 법규 및 판례 등을 분석한 문헌연구를 통해 수행되는 경향이 높았다. 향후 연구에서는 교육감 관련 개인 및 조직 차원의 연구주제에 대한 양적 및 질적연구의 확대, 즉 스트레스와 대처, 교육 및 변혁적 리더십, 당사자 간 소통과 협력, 의사결정, 조직풍토와 조직효과성 등과 같은 연구주제에 대한 실증적 분석을 위한 양적 및 질적연구가 활성화될 필요가 있다. This study analyzed the research trends related to the superintendent of education after the introduction of the local education autonomous system. Specifically, the publication year, published journal, researcher characteristics, research topic and research method were analyzed. The academic papers analyzed in this study were 160 published in the registered (candidate) journals related to the Superintendent of Education in the Academic Research Information Service of KERIS. The research results are as follows. First, the superintendent-related research increased after the election of the superintendent, and were published in academic and non-educational academic journals. Second, research topics were focused on the election of the superintendent, and analysis of the superintendent's system and policy. Third, there tended to conduct literature research by analyzing literature and law. In future research, quantitative and qualitative research needs to be activated to secure empirical evidences of individual and organizational variables, namely, stress and coping, education and transformational leadership, communication and cooperation between parties, decision making, organizational climate and organizational effectiveness.
Effects of Drinking Motivation on Drinking Problems in College/University Students : Focusing on the Mediating Effect of COVID-19 Risk Perception, and Coping Method

Objectives: The purpose of this study is to provide the theoretical background for alcohol intervention for College/University students by analyzing the relevance between drinking motivation, COVID-19 risk perception, coping method and drinking problem under any pandemic situations like COVID-19 pandemic situation. Methods: An output from the Capstone Design Class of the college in Daegu area has been utilized as a secondary source for this study. The data was collected via a Social media survey in a random sampling method from 20th November 2020 to 6th December 2020 during the second semester of the school. 217 people have answered the survey and all the data of 217 respondents have been used in the statistic. Results: The results were as follows. First, the drinking motivation has a direct effect on the COVID-19 risk perception, while it shows both direct and indirect effects on the coping method and the drinking problem. Second, the COVID-19 risk perception has a direct effect on the coping method and drinking problem. Finally, the coping method has not a direct and indirect effect on the drinking problem. Conclusions: COVID-19 risk perception showed mediation effect between drinking motivation and coping method as well as between drinking motivation and drinking problems.
Plasma Trained to Play Tic-Tac-Toe: A Programmable Intelligent Material

The rate coefficient of an inelastic collision in plasmas can be determined by an Arrhenius-like mathematical relation. This is similar to the weights in an artificial neural network (ANN) determined by the activation functions. Therefore, a chemical pathway network (CPN) that massive chemical species are connected by the cause-effect chemical reaction pathways shares a similar mathematical ability with ANN: a functional mapping between the input space and output space. Based on such a similarity, we propose a programmable material intelligence by training a He-air plasma, considering the CPN as an ANN, to play a board game Tic-Tac-Toe. In each turn, the board information is sent to the plasma discharge units by feeding a gas combination, and the plasma returns spectra to show its next move. After training, the plasma shows a significantly high winning rate when playing against a random-move player in a 500-game test. This work thus reveals the potential of any matter that has a complicated chemical reaction system that can be used as a carrier of artificial intelligence. In other words, a material can be programmed and process data through its own molecular collisions, and thus can be considered as an analog computer at the molecular level.
Co-Ability Practices

This paper explores philosophical and strategic possibilities to understand the concept of co-Ability, and generate critical and new insights to our value system in human centred societal challenges. I apply an experimental approach of research through design, analysed from an interpretive point of view to prove a grounded theory. The paper starts from a prosthesis development presented as a tangible pragmatic procedure. The purpose of the case study is the notion of care through practical design that is marked with concern since the probability of harm can be incised by pure design decisions. Instead of describing the politics of roles and ethics in a situation characterised by ‘design for care’ inspirations, I use reflection on design practice to understand embodied thoughts concerning relationships and the ways of doing. In the second part of the paper, I proceed with literature review in disability research and parallel design strategies. In the final section – in relation to co-design – I introduce the term of ‘co-Ability’ that is rooted in the critical approach of posthuman disability studies outlined by scholars such as Rosi Braidotti. It serves as a broad umbrella term under which we can reconsider the potentials of various entities (biological and artificial) enhancing the shared competence rather than dwelling on the oppressive nature of human-centred norms. Overall, I suggest that the dominant normative vision manifesting in societal challenges is in relational matter with multiple body representations.
Global Cooperation Framework to Mitigate a Technology-Regulation Gap in Blockchain

The research investigates the sunrise issue of the financial regulations for virtual assets from the architectural perspective. The Financial Action Task Force’s revision of recommendations transits virtual assets from a vague area between legal and illegal economies. However, lawmakers and regulators warn that the stretching adoption of the regulations might invalidate the financial regulations for virtual assets, called a sunrise issue. The research explains the unsatisfying regulatory compliance, relying on the gaps between technological architecture and regulatory framework. Furthermore, it recommends a modular architecture in the regulatory framework and elaborate message format. The research contribute technology-regulation gaps to regulation compliance studies and global cooperation to blockchain-based financial sectors.
Cybershaming: Conceptualizing Organizational Shaming in the Digital Age

Recent years have seen a dramatic rise in the cases of Cybershaming of businesses. Social media has enhanced organizational transparency to actors both within and outside, consequently disrupting institutional arrangements and logics. Actors defend the institutional logics they cherish, and any contradiction between competing logics may trigger conflict and uncertainty. In the absence of clear institutional illegality, various actors on social media will amplify competing ideological bases and logics. Outgroup actors may resort to Cybershaming to secure compliance and enforce community prescriptions, thereby ensuring respect for inclusivity and capacity for rich, meaningful lives for everybody. Our conceptual paper seeks to theorize how organizational ingroup actors may choose to respond to Cybershaming from outgroups through the lens of confrontation, disruption, and resettlement of logics on social media. When confronted with disruption from institutional complexity, how will institutional ingroup actors react to restoring or defending cherished logics? Specifically, how will this play out amidst the transparency and visibility afforded by social media? Given the emergent and evolving nature of this phenomenon, we build on the theoretical foundations of institutional logics and complexity while simultaneously drawing from a wide range of empirical sources, including studies on internet policy, cybercrime, activism, business ethics, news articles, popular books, and traditional group-based Shame studies. Ultimately, we seek to contribute to the urgent and opportune discussion on institutional complexity and disruption in the digital age.
Using Data Mining Techniques for Early Diagnosis of Breast Cancer

Aim: The present study aimed to compare six data mining approaches and find the best methods for predicting breast cancer.&#x0D; Method: In this study, six classification methods, including Random Forest (RF), Neural Network (NN), Support Vector Machine (SVM), Auto Multilayer Perceptron (AutoMLP), Naïve Bayes (NB), and Deep Learning (DL) were applied for breast cancer detection. Data related to 116 patients and healthy people from the UCI repository with nine predictors were used for training and testing. To develop the model, data were first divided into two parts: training and testing. The data of the training set (70%) produced the models, and the data of the test set (30%) was applied to validate the models.&#x0D; Results: To compare the performance of the techniques used to diagnose breast cancer, accuracy, recall, precision, AUC (Area Under the ROC Curve), sensitivity, and specificity were calculated and reported for all approaches. Evaluation of data mining algorithms revealed that deep learning with 81.89% accuracy performed better than other techniques. The results of one-way ANOVA for performance in six modeling methods showed no statistically significant difference between the methods (P-value &lt;0.05).&#x0D; Conclusion: Choosing the most effective computer diagnostic methods can provide a comprehensive system for the early detection of breast cancer. By reducing the cost of treating patients and increasing the quality of services offered, these intelligent methods take practical steps to improve medicine and lead to a systematic diagnosis.
Scientific Phone Apps and Mobile Devices

Scientific (Phone) Applications and Mobile Devices (SAMD) is a peer-reviewed open access journal published under APD SKEG Pte Ltd. The first specialized journal in this field, it publishes high quality scientific reports on mobile apps and smartphone dependent devices such as add-on sensors or modifications. Allowing for not only academic recognition for the broader scientific community, it also brings awareness to the general public on the development of such tools.&nbsp;
Good sequencings of partial Steiner systems

A partial $(n,k,t)_\lambda$-Steiner system is a pair $(X,\mathcal{B})$ where $X$ is an $n$-set of vertices and $\mathcal{B}$ is a collection of $k$-subsets of $X$ called blocks such that each $t$-set of vertices is a subset of at most $\lambda$ blocks. An $\ell$-good sequencing of such a system is a labelling of its vertices with distinct elements of $\{0,\ldots,n-1\}$ such that no block is contained in a set of $\ell$ vertices with consecutive labels. Here we give a short proof that, for fixed $k$, $t$ and $\lambda$, any partial $(n,k,t)_\lambda$-Steiner system has an $\ell$-good sequencing for some $\ell=\Theta(n^{1/t})$ as $n$ becomes large. This improves on results of Blackburn and Etzion, and of Stinson and Veitch. Unlike those results, which are proved constructively, our proof relies on an application of the Lov\'{a}sz local lemma. Our result is perhaps of most interest in the case $k=t+1$ where results of Kostochka, Mubayi and Verstra\"{e}te show that the value of $\ell$ cannot be increased beyond $\Theta((n \log n)^{1/t})$. A special case of our result shows that every partial $(n,3,2)_1$-Steiner system has an $\ell$-good sequencing for each positive integer $\ell \leq 0.0908\,n^{1/2}$.