Reviewerly/exHarmony huggingface dataset:
Separating Use and Reuse to Improve Both

Context: Trait composition has inspired new research in the area of code reuse for object oriented (OO) languages. One of the main advantages of this kind of composition is that it makes possible to separate subtyping from subclassing; which is good for code-reuse, design and reasoning. However, handling of state within traits is difficult, verbose or inelegant. Inquiry: We identify the this-leaking problem as the fundamental limitation that prevents the separation of subtyping from subclassing in conventional OO languages. We explain that the concept of trait composition addresses this problem, by distinguishing code designed for use (as a type) from code designed for reuse (i.e. inherited). We are aware of at least 3 concrete independently designed research languages following this methodology: TraitRecordJ, Package Templates and DeepFJig. Approach: In this paper, we design $42_\mu$ a new language, where we improve use and reuse and support the This type and family polymorphism by distinguishing code designed for use from code designed for reuse. In this way $42_\mu$ synthesise the 3 approaches above, and improves them with abstract state operations: a new elegant way to handle state composition in trait based languages. Knowledge and Grounding: Using case studies, we show that $42_\mu$'s model of traits with abstract state operations is more usable and compact than prior work. We formalise our work and prove that type errors cannot arise from composing well typed code. Importance: This work is the logical core of the programming language 42. This shows that the ideas presented in this paper can be applicable to a full general purpose language. This form of composition is very flexible and could be used in many new languages.
A Study on the Problems and Improvement of Local Bookstore Management

서점 진흥을 위하여 다양한 정책, 제도와 방안 및 지원책이 제시되고 있지만 출판유관 업계 간의 협력은 부족한 편이다. 지역 소형서점의 가장 큰 문제점은 대부분의 서점들이 운영이 불가능할 정도로 수익이 악화되었다는 것이다. 이에 본 연구는 지역 소형서점의 유통상의 문제점과 그에 대한 개선방안에 대해 살펴보았으며, 연구 결과는 다음과 같다. 첫째, 출판사와 도매상은 소형서점이 도서 구매를 할 경우에 즉시 현금 구매를 요구하고 있는데, 지역서점에게는 지불 유예 기간 보장과 반품을 허락해야 하고 둘째, 지역서점의 영업이익률을 보장하고 특히 출판사는 서점이 일정 정도의 마진을 확보할 수 있도록 합당한 표준 공급률을 유지해야 하며 셋째, 출판사와 출판유통회사는 도매상과 협의하여 일일 배송 시스템을 구축해야 하고 넷째, 재정적으로 안정된 운영을 위하여 지역서점도 도서 납품 사업에 적극적으로 참여해야 한다. 마지막으로 지역 서점은 인터넷 서점을 운영하여 전자책의 확대에도 대비해야 한다.Various policies, systems, plans, and support measures are being proposed for bookstore promotion, but cooperation among publishing-related industries is insufficient. The biggest problem with local small bookstores is that profits deteriorated to the point that most bookstores were unable to operate. Therefore, this study examined the distribution problems of local small bookstores and measures to improve them, and the results of the study are as follows. First, publishers and wholesalers require immediate cash purchases when purchasing books at small bookstores. Local bookstores must be granted a grace period guarantee and returns. Second, local bookstores are guaranteed an operating margin, especially for bookstores. A reasonable standard supply rate must be maintained in order to secure a certain margin. Third, publishers and publishing distribution companies must establish a daily delivery system in consultation with wholesalers. Fourth, local bookstores are also supplying books for financially stable operation. You must be actively involved in Finally, local bookstores should prepare for the expansion of e-books by operating an internet bookstore.
Цифровизация образовательного пространства: риски и перспективы

At present, we are witnessing a profound transformation of all spheres of society»s life, including the education system. Changes are taking place in the direction of digitalization - an actual trend in the modern educational space. However, there is no single interpretation of the concept of digitalization, so digitalization occurs in a situation of conceptual uncertainty. In addition, the scientific literature uses different terms to refer to digital education: «digitalization of education», «smart education», «digital education», etc. Hence, there is also terminological uncertainty. The article contains several definitions of the term «digitalization», a list of normative documents aimed at regulating the educational process in relation to digitalization, stages of digitalization of education, and its prospects and risks. It is noted that it is necessary to take into account the advantages and disadvantages of digitalization of education, in accordance with this, to adjust changes in the educational space. We believe in education, you need to use the advantages of digital learning, which should be a complement to traditional (mixed education), while it is important to update the ethical aspect of education, save in the educational process moral component. We agree with M. A. Manikovskaya, who notes that the solution to the problem «is seen in its new turn, which indicates the prospect of identifying and preserving in the transforming education the constructive possibilities of optimal and harmonious coupling of digital and humanitarian technologies that ensure aperson»s moral identity». The theoretical and methodological basis of the research is the works devoted to the problem of digitalization of the educational space.
Instrumental-Dimension-Based Video Quality Modeling

In this section, an approach to estimate the perceptual video quality dimensions from instrumentally obtained scores is presented. To create estimation models for each video quality dimension, the VQI developed by the Video Quality Group at the AGH University of Science Krakow (comp.
Sistem Pengambilan Keputusan Penjurusan Akademik Sekolah Menengah Atas Berdasarkan Kemampuan Akademik, Potensi Psikologi dan Minat bakat Siswa Menggunakan Fuzzy Inference System Metode Sugeno Dua Lapis

Fuzzy logic is a rule-based decision-making process that aims to solve a difficult problem and uncertainty. This research aims to develop a computer-based system which can assist in the decision maker to determine students’ academic major of senior high school based on their competence, psychology potential and talent-interest. The system is modeled using the fuzzy inference system with Sugeno inference method. The results show that the proposed system succeeds to provide recommendation subject in highly accurate, and it is more efficient than the manual decision-making process.
A Qualitative-Driven Study of Irreversible Data Anonymizing Techniques in Databases

Nowadays, privacy remains one of the most important challenges for the enterprises that handle personal data. Many mechanisms are widely used to tackle this challenge and make the use of Internet more secure and respectful of the privacy. For this aim, anonymizing data in database, by reversible or irreversible techniques, is one of such used mechanisms. Varieties of implementation of these techniques are provided and available, however, the choice of the suitable category and technique for a specific context is not an easy task. In this paper we focus on irreversible anonymizing category in database and we propose an approach that can help to make this choice easier based on classification according to criteria. Some of these last are well known on research fields and we define others related to the application context and data nature. As a result, the security officer could identify the most suitable technique to preserve privacy.
CNN-Driven Quasiconformal Model for Large Deformation Image Registration.

Image registration has been widely studied over the past several decades, with numerous applications in science, engineering and medicine. Most of the conventional mathematical models for large deformation image registration rely on prescribed landmarks, which usually require tedious manual labeling and are prone to error. In recent years, there has been a surge of interest in the use of machine learning for image registration. However, most learning-based methods cannot ensure the bijectivity of the registration, which makes it difficult to establish a 1-1 correspondence between the images. In this paper, we develop a novel method for large deformation image registration by a fusion of convolutional neural network (CNN) and quasiconformal theory. More specifically, we propose a new fidelity term for incorporating the CNN features in our quasiconformal energy minimization model, which enables us to obtain meaningful registration results without prescribing any landmarks. Moreover, unlike other learning-based methods, the bijectivity of our method is guaranteed by quasiconformal theory. Experimental results are presented to demonstrate the effectiveness of the proposed method. More broadly, our work sheds light on how rigorous mathematical theories and practical machine learning approaches can be integrated for developing computational methods with improved performance.
MODEL DYNAMIC OF WATER QUALITY INDEX BOD-BASED IN INDONESIA

Pollution is a human problem in the present and a problem in the future of human life. Household waste and industrial waste without adequate treatment then flow into waterways, rivers and coastal waters have a significant impact on flora and fauna in the water. Domestic waste, especially increasing Biological oxygen demand (BOD) can reduce dissolved oxygen, which causes anoxic conditions. The system dynamics approach was used by simulating time series data related to BOD pollution in waters from all provinces in Indonesia. Scenarios that can be done to reduce BOD are optimistic scenarios. In the optimistic scenario, it can improve the index by 0.28 while in the moderate scenario reduce the index by 0.15. In an optimistic scenario, 2045 is included in the good category.
Seeing The Preference Of The Genres Of Literature And The Four Primary Temperament Types As An Indicator Of Efl Reading Achievement

This paper described the study which tried to explore the impact of the four primary temperament types (Sanguine, Choleric, Phlegmatic, and Melancholic) and the preference of the genres of literature toward the achievement of reading like a foreign language. Hence, the objectives of the study were (1) to find out the impact of the four primary temperament types and the preference of the genres of literature toward EFL reading achievement, (2) to seek which more influential variable among the four primary temperament types and the preference of the genres of literature on EFL reading achievement. The population (N=43) of the study was the eleventh-grade students of SMA Muhammadiyah 2 Surabaya in the academic year of 2017/2018. The quantitative method was utilized in this study with the Multiple Linear Regression as a research design. In collecting the data, the researcher administered the reading preference questionnaire which consisted of 20 items and ready-made of the temperament type questionnaire consisted of 48 items. After administering the two questionnaires to the sample of the study, then the researcher conducted the IELTS-like test to obtain the score of reading achievement. In analysing the data, Multiple Linear Regression in SPSS 23.0 was utilized. The findings of the study revealed that there were simultaneous impacts of the variables of the Preference for Fiction (X1), Preference for Non-fiction (X2), and Temperament types (X3) toward Reading Achievement variable (Y). Moreover, only one independent variable which was the preference for fiction (X1) that had more influence toward the dependent variable. Therefore, it could be implied that the variable of preference for fiction (X1) had a significant impact on reading achievement (Y) Keywords: Temperaments Type; Preference of the Genres of Literature; Reading Achievement.
Interaction representation-based subspace learning for domain adaptation

Generally, Transfer Learning (TL) or Domain Adaptation (DA) are used to solve domain inconsistency, but the conventional domain adaptation methods mostly only consider local information and ignore global information, and only consider one-way data and ignore the possibility of two-way data.Therefore, in this paper, we proposed an interactive representation-based framework for domain adaptation.In the novel framework, two low-rank based interactive representation models are built on both of source and target domains, which can be used to better align distribution discrepancy.Then, a distance constraint is designed to model the subspace relationship between source and target domain.Finally, the label-based regression is jointly used to earn extra discrimination for classification.Experiments on a number of public databases demonstrate that our method has competitive performance among comparison methods.
Predicting Clinical Trial Results by Implicit Evidence Integration

Clinical trials provide essential guidance for practicing Evidence-Based Medicine, though often accompanying with unendurable costs and risks.To optimize the design of clinical trials, we introduce a novel Clinical Trial Result Prediction (CTRP) task.In the CTRP framework, a model takes a PICO-formatted clinical trial proposal with its background as input and predicts the result, i.e. how the Intervention group compares with the Comparison group in terms of the measured Outcome in the studied Population.While structured clinical evidence is prohibitively expensive for manual collection, we exploit large-scale unstructured sentences from medical literature that implicitly contain PICOs and results as evidence.Specifically, we pre-train a model to predict the disentangled results from such implicit evidence and fine-tune the model with limited data on the downstream datasets.Experiments on the benchmark Evidence Integration dataset show that the proposed model outperforms the baselines by large margins, e.g., with a 10.7% relative gain over BioBERT in macro-F1.Moreover, the performance improvement is also validated on another dataset composed of clinical trials related to COVID-19.
Organizational And Pedagogical Factors Of A Specialists’ Professional Development In Modern Conditions

Problems of professional development of a specialist’s personality are considered from many points of view, such as: theoretical basis of professional development in the process of intellectual activity; various aspects of self-management and personal efficiency management; professional success of specialists in various fields of studies; the essence of the process of personal professional development, etc. We have determined a task - to study the system processes and features of specialists’ personal professional development, to reveal the features of their professional development in modern market relations and to identify causal factors of the pedagogical structure of their professional development. Using the theoretical analysis and modern practice techniques enabled us to develop the following confinement models: “Personal factors of a specialist’s professional development”, “Organizational factors of a specialist’s personal professional development”, “System of socio-psychological relations as a factor of a specialist’s personal professional development”; all of these models act as a complex of organizational and pedagogical factors of a specialist’s professional development. The study is relevant from the practical point view as this three-group complex of factors serves as a means of a specialist’s personal professional development; this complex is recommended to be adopted in the education system as a means of specialists’ professional development during their work. A binary-structured system of psychological and pedagogical support is recommended to be used in corporate education to ensure a more effective professional development of specialists, the system is also recommended to be implied during higher professional education.
Comparative Analysis of Research Trends Regarding Corruption in Northeast Asia : Focusing on North Korea, China and Russia

본 연구는 우선 동북아지역내 부패에 관한 연구 동향을 조사하였다. 이를 바탕으로 각 국가별 연구동향을 비교 분석하는 기초연구를 진행하였다. 특히 동북아 지역내 북한, 중국, 러시아는 사회주의 체제를 유지하고 있거나 유지하였던 국가로서 공통점을 가진다. 향후 북한이 정치와 경제체제가 전환되었을 시 중국이나 러시아의 모델을 따르게 될 확률이 높을 것이다. 중국처럼 사회주의 체제를 유지하면서 시장경제를 받아들이는 방향이나 러시아와 같이 정치와 경제체제를 모두 전환하는 방향으로 나아가게 될 가능성이 높다. 이에 대비하여 현재 동북아지역내 국가별 부패문제를 연구하고 부패에 관한 국내 연구 동향을 종합적으로 파악하고자 하였다. 연구 결과 첫째, 연구시기별 연구 동향은 연도별로 연구량의 증감이 일정하지는 않지만 꾸준하게 연구되고 있는 주제임을 알 수 있다. 둘째, 연구 대상 국가별 연구동향 비교분석 결과 중국의 부패관련 연구가 가장 많이 이루이고 있었다. 셋째, 연구 내용별 연구 동향은 북한과 러시아는 행정관료 및 경제, 사회부패 연구가 많이 이루어졌고 중국은 행정 관료 및 정치, 제도 부패 연구가 많이 이루어지고 있었으며 전체적으로 행정관료와 관련된 부패 연구가 많이 이루어지고 있었다. 연구 방법별 연구동향 결과 혼합연구와 질적연구가 많이 이루어지고 있었다. 이러한 연구결과를 토대로 북한, 중국 및 러시아의 부패문제를 비교 분석하여 문제점과 해결책을 도출해내고자 하였다. 향후 북한이 정상적인 국가로서 발전하기 위해서 부패문제는 결국 해결해야 할 당면 과제이기 때문이다. 동북아지역내 부패와 관련한 이러한 선행연구를 바탕으로 학계와 민관의 활동을 지원할 수 있는 부패연구가 지속적으로 이루어지기를 기대해 본다.First of all, this study investigated the research trends on corruption in Northeast Asia. Based on this, basic research was conducted to compare and analyze the research trends of each country. In particular, North Korea, China, and Russia in the Northeast Asian region have a common point as countries that are maintaining or have maintained a socialist system. In the future, when the political and economic system changes, there is a high probability that North Korea will follow the model of China or Russia. There is a high possibility that it will move toward a direction of accepting a market economy while maintaining a socialist system like China, or a direction of shifting both political and economic systems, like Russia. In preparation for this, it was intended to study the current corruption issues by country in Northeast Asia and to comprehensively understand the domestic research trends on corruption. As the first research result, it can be seen that the research trend by research period is a subject that is constantly being studied, although the increase and decrease of research volume by year is not constant. Second, as a result of comparative analysis of research trends by country to be studied, the most research on corruption is being done regarding the Chinese corruption case. Third, research trends by content of research include various studies on administrative bureaucracy, economic, and social corruption in North Korea and Russia, while many studies on corruption in administrative bureaucracy, politics, and institutions have been conducted on China. As a result of research trends by research method, both mixed and qualitative studies were extensively conducted . Based on those findings, this thesis aimed at drawing questions and solutions by comparing and analyzing corruption problems in North Korea, China, and Russia. This is because, in order for North Korea to develop as a normal state in the future, the issue of corruption is an immediate task that must be resolved. Based on these preceding studies on corruption in Northeast Asia, I hope that corruption studies that can support academic and public-private activities will continue to be conducted.
Live Programming Environment for Deep Learning with Instant and Editable Neural Network Visualization

Artificial intelligence (AI) such as deep learning has achieved significant success in a variety of application domains. Several visualization techniques have been proposed for understanding the overall behavior of the neural network defined by deep learning code. However, they show visualization only after the code or network definition is written and it remains complicated and unfriendly for newbies to build deep neural network models on a code editor. In this paper, to help user better understand the behavior of networks, we augment a code editor with instant and editable visualization of network model, inspired by live programming which provides continuous feedback to the programmer.
Patent Law Based Concepts for Promoting Creation and Sharing of Innovations in the Age of Artificial Intelligence ('AI') and Internet of Everything ('IoE')

When the Venetians created the first patent system in the 14th Century, the role thereof, as it is widely believed by scholars, lawyers and users of today’s patent systems, has been to encourage inventors not to keep their inventions secret anymore, rather to disclose them through a governmental channel to the public. That would, according to the intention of the creators of the first patent system and still believed to be applicable today, give “followers,” i.e. “improvers” of certain technologies that otherwise would have to be held secret to stand, as Isaac Newton has expressed it, on the shoulders of giants etc., thereby improving the speed of technological developments.
Learning Online Data Association

When an agent interacts with a complex environment, it receives a stream of percepts in which it may detect entities, such as objects or people. To build up a coherent, low-variance estimate of the underlying state, it is necessary to fuse information from multiple detections over time. To do this fusion, the agent must decide which detections to associate with one another. We address this data-association problem in the setting of an online filter, in which each observation is processed by aggregating into an existing object hypothesis. Classic methods with strong probabilistic foundations exist, but they are computationally expensive and require models that can be difficult to acquire. In this work, we use the deep-learning tools of sparse attention and representation learning to learn a machine that processes a stream of detections and outputs a set of hypotheses about objects in the world. We evaluate this approach on simple clustering problems, problems with dynamics, and a complex image-based domain. We find that it generalizes well from short to long observation sequences and from a few to many hypotheses, outperforming other learning approaches and classical non-learning methods.
Penerapan Pelajaran Kooperatif Tipe Snowball Throwing Untuk Meningkatkan Aktivitas Dan Hasil Belajar IPS Siswa Kelas IV Semester II SD Negeri 4 Pertima

This study aims to improve student learning activities and outcomes on social studies subjects through the implementation of the snowball throwing type cooperative learning model. The research was conducted in two cycles, with the research subjects namely fourth grade students of Semester II SD Negeri 4 Pertima in the Third Year with a total of 31 students. This type of research is Classroom Action Research using observation methods to measure student learning activities and test methods to measure student learning outcomes. After the data is collected, then it is analyzed using descriptive statistical methods. The results obtained from this study are, in the first cycle the percentage of student learning activities reaches 66.8% and in the second cycle the percentage of student learning activities increases to 81%. Thus student learning activities have increased by 14.2%. In addition to student learning activities, student learning outcomes also increased, in the first cycle the percentage of student learning outcomes reached 66.1% with learning completeness of 67.74%. In the second cycle the percentage of student learning outcomes increased to 70.16% with learning completeness that had reached 100%. Thus student social studies learning outcomes increased by 3.55% and student learning completeness increased by 32.26%. For this reason the Cooperative Learning Throwing Type model if applied in Social Studies Lessons in Grade II of semester II in SD Negeri 4 Pertima is very effective, so that education services become more qualified and recognized by the community supporting education in SD Negeri 4 Pertima Karangasem District, Karangasem Regency.