Reviewerly/exHarmony huggingface dataset:
Artificial intelligence applied to support the breast cancer diagnosis

Breast cancer is a more common neoplasm among women (not considering non-melanoma skin cancer). The estimate for the coming years is still growing and poses a threat to human health. Currently, the methods used in the diagnosis of breast cancer are performed through analysis of mammography images. Allowed, an analysis made by two specialists, which are subject to errors due to factors such as fatigue and lack of capacity. Not only the factor of human errors in diagnoses, certainly the long periods of time until the final diagnosis is another factor to be taken into account, because cancer is a progressive disease over time. In this sense, the present work applied a solution through the automatic classification of mammography images, in order to determine as normal or cancer. In addition, for simulations, two machine learning techniques were added independently, as they can eventually serve as a support in the diagnosis of breast cancer, that is, a CAD system, which means “computer-aided diagnosis”. As machine learning techniques applied for classification referenced as convolutional neural networks and support vector machines. Subsequently, the construction of the classification algorithms, they were subjected to the testing phase, which was found to be more than 85% accurate in the classification of mammography images.
A martyr and a warrior : guerilla open access movement and the continuing battle for radical access to scholarly literature

Anubha Sinha (Centre for Internet and Society, Bengaluru)Title: Guerilla open access and its relevance for Indian research communityAnubha will reflect on the arc of the guerilla open access movement, and its turning points such as Aaron Swartz's prosecution, Libgen's and Sci-hub's missions, and more. She will also highlight the movement's connections and relevance for Indian researchers.Arul George Scaria (National Law University Delhi)Title: Sci-Hub Litigation in India: Why the courts should protect the public interest in access to knowledge resources?Arul will be providing an overview of the legal issues involved in the litigation initiated in India by three major publishers against Sci-Hub and Libgen. He will discuss the specific facts of the case and examine whether there are any legitimate grounds for granting a dynamic against Sci-Hub ad Libgen. As part of the remarks, he will discuss the factors that a court needs to take into consideration while deciding on an injunction application. During his remarks, he will also touch upon some of the important lessons for the global community from the prosecution of Aaron Swartz in the US and the tragic end of that prosecution.
The Game of Capital: Prosperity or Exploitation?

With the rapid development of digital economy, the Internet platform economy has become a new momentum of world economic development because of its unique advantages.However, with the continuous improvement of ultra-large Internet platforms and the market concentration, there are "Two Choose One[1]" and "Data Haunting[2]" and other phenomena, which hinder orderly competition and damage the rights and interests of consumers, thus attracting wide attention from all walks of society.For the platform economy, on the one hand, we hope to use the sales network it has established to facilitate the public and provide trading opportunities for small and medium-sized merchants, but we are deeply concerned about the monopoly caused by it.Therefore, this paper starts with the operation mode of several large platform enterprises in China and the United States, analyzes the performance and causes of Internet platform monopoly, and realizes that the Monopoly is caused by three reasons:"Information Monopoly"," Algorithm Cage" and "Capital Occupation".To this end, this paper also thinks about the possible solutions, that is, to establish a trading system based on Blockchain technology, and make the use of Blockchain decentralization, non-tampering and other characteristics to change the current platform monopoly pattern.
Curriculum Semantic Retrieval System based on Distant Supervision

Knowledge Graph is a semantic network that reveals the relationship between entities, which construction is to describe various entities, concepts and their relationships in the real world. Since knowledge graph can effectively reveal the relationship between the different knowledge items, it has been widely utilized in the intelligent education. In particular, relation extraction is the critical part of knowledge graph and plays a very important role in the construction of knowledge graph. According to the different magnitude of data labeling, entity relationship extraction tasks of deep learning can be divided into two categories: supervised and distant supervised. Supervised learning approaches can extract effective entity relationships. However, these approaches rely on labeled data heavily resulting in the time-consuming and laborconsuming. The distant supervision approach is widely concerned by researchers because it can generate the entity relation extraction automatically. However, the development and application of the distant supervised approach has been seriously hindered due to the noises, lack of information and disequilibrium in the relation extraction tasks. Inspired by the above analysis, the paper proposes a novel curriculum points relationship extraction model based on the distant supervision. In particular, firstly the research of the distant supervised relationship extraction model based on the sentence bag attention mechanism to extract the relationship of curriculum points. Secondly, the research of knowledge graph construction based on the knowledge ontology. Thirdly, the development of curriculum semantic retrieval platform based on Web. Compared with the existing advanced models, the AUC of this system is increased by 14.2%; At the same time, taking "big data processing" course in computer field as an example, the relationship extraction result with F1 value of 88.1% is realized. The experimental results show that the proposed model provides an effective solution for the development and application of knowledge graph in the field of intelligent education.
빅데이터 양성 교육 교과과정 개선을 위한 회귀분석 기반의 만족도 조사에 관한 연구

Big data is structured and unstructured data that is so difficult to collect, store, and so on due to the huge amount of data. Many institutions, including universities, are building student convergence systems to foster talents for data science and AI convergence, but there is an absolute lack of research on what kind of education is needed and what kind of education is required for students. Therefore, in this paper, after conducting the correlation analysis based on the questionnaire on basic surveys and courses to improve the curriculum by grasping the satisfaction and demands of the participants in the “2019 Big Data Youth Talent Training Course” held at K University, Regression analysis was performed. As a result of the study, the higher the satisfaction level, the satisfaction with class or job connection, and the self-development, the more positive the evaluation of program efficiency.
THE EFFECTIVE PREDICTION MODEL BASED ON EMPLOYMENT POSITIONS FOR COMPUTER CURRICULUMS USING CLASSIFICATION TECHNIQUES

Data mining techniques were used to build a prediction model prototype based on employment positions for computer majors in the Faculty of Science and Technology, Suratthani Rajabhat University.This study investigated the impact factors of employment positions of computer careers, compared model performances that consisted of six classification techniques and developed a web application using the effective prediction model that could be implemented in four majors using data collected from the graduates of sessions 2016-2020.The results of this research demonstrated that factors of seven courses and cumulative grade point average predicted employment positions.The models with best performances were rule-based and naive Bayes methods with a classification accuracy of 89.66%, precision of 90.48%, and recall of 90.00%.Therefore, a web application of the prediction model was developed using PHP programming.In practice, this application can suitably predict employment positions for computer majors.
Research on Urban Public Security Risk Management under the Background of Tobacco Control

Objectives: Through the reflection on the city’s response to the crisis in the process of tobacco control, a comprehensive and systematic public safety prevention and control system will be built to help cities cope with future risks and challenges. Methods: By using the methodological principle of the unity of subject and object and systematic research, this paper analyzes the problems from the three aspects of subject, object and means, and puts forward three important links of prevention, response and guarantee to construct a large urban public security system, and these three links support each other form a closed loop of risk prevention and control urban public security. Results: Under the background of tobacco control, it is feasible to a reliable whole-cycle management system for urban emergency response and accident rescue, a sound basic public safety guarantee system and a whole-society participation system. Conclusions: Due to the change of global climate conditions and the increase of flow people in the social environment, human beings will face a more complex living environment in the future and may encounter more extreme problems. It can be said that at present and even in the future, global urban public security risk management work is facing a grim situation. WHO research shows that smoking will increase the risk of new crown virus infection among smokers and their surrounding population.China is a big smoking country and in the stage of rapid urbanization. Many citiesare densely populated. Once there is an epidemic infection, the cities will face a severe public security situation. Smoking will not only have an adverse impact on personal health, but also the fires in factories, homes and forests caused by smoking.Since the Chinese government’s tobacco control in 2014, various accidents caused by smoking have caused great adverse effects.Smoking in public places has great hidden dangers of public safety, which leads us to think about the risk management of urban public safety.In the context of tobacco control, we should use scientific thinking and methods to construct a new pattern of urban public security risk management. Another important concept is to implement the risk management concept and the value of prevention first in the management of public affairs, so as to create a situation of risk sharing and coordinated response of the whole society.
IMPLEMENTASI DASHBOARD BUSINESS INTELLIGENCE UNTUK VISUALISASI DATA DONATUR (STUDI KASUS: HUMAN INITIATIVE RIAU)

Human Initiative Riau is one of the humanitarian institutions located in Pekanbaru City which focuses on four areas of work, namely economy, health, education and emergency response. Based on interviews with the Human Initiative, information was obtained that there were several obstacles faced in supporting the activities and programs that were being carried out. The data currently held is still managed conventionally by each division head so that the human initiative is constrained to ascertain whether the program is being implemented according to the target or not. Therefore, a solution is needed that can be used by human initiatives to see the development of donors, donors, beneficiaries and marketers which will later be used as material for evaluating marketer performance and determining future strategies that can improve the performance of human initiatives. This system was built by implementing business intelligence technology with visualization in the form of column-charts and graphs. designed using the codeigniter framework, the programming language PHP and MySQL as its DBMS. This system is tested using testing data transformations, user acceptance test (UAT) and efficiency so that users can find out what improvements they want. Based on the user acceptance test (UAT) that has been carried out, it shows that 96,76% of the systems that have been built are acceptable to users and can help human initiatives in making decisions.
A case study on the implementation of marketing competencies for deaf children in entrepreneurship education

This study aims to determine the aspects related to marketing competence developed in deaf children in entrepreneurship education. It uses the case study approach applying in-depth interview techniques in its data collection. The results of this study indicate that teachers and deaf children discuss and conduct surveys as a need for research in society. The teacher invites the deaf children to analyze existing competitors’ products. Deaf children are also encouraged to use digital applications to expand their marketing range. The teacher also guides them on how to serve customers so they are satisfied.
Technology of modeling current and prospective roles and responsibilities of teaching staff for general education settings

Introduction. This study analyses how changing requirements for results and processes of general education determine new or updated roles and responsibilities of teachers in the context of building a qualification framework in the field of education. The purpose of the research is to develop and test a technology for modeling roles and responsibilities and corresponding professional qualifications of general education teachers determined by changing requirements of the labor market and employers. Materials and Methods. The study follows the process approach and methodology of structural and functional analysis of professional practice. The authors applied the following research methods: modeling, questionnaires, approbation, comparative analysis, generalization, classification, interpretation as well as methods of graphical representation of information in data processing and interpretation. In order to collect empirical data, the authors developed a questionnaire through modeling roles and responsibilities of teaching staff based on legislative materials as well as theoretical and practical evidence reflecting the requirements for processes and results of general education in the Russian Federation. Results. The article presents a technology for modeling prospective roles and responsibilities and corresponding professional qualifications of general education teachers developed and tested by the authors. The system of current roles and responsibilities of subject teachers, class teachers and academic counselors has been established. The authors developed a set of prospective roles and responsibilities for education practitioners, the institutionalization of which is required for an appropriate response of a general education setting to changing requirements for processes and results of its work. The study reveals how employers evaluate the importance of current roles and responsibilities of education practitioners and the demand for prospective ones. The authors summarize the ideas of employers about pursuing a career in the field of education. The study reveals an apparent discrepancy between the employers’ recognition of diversification of professional activities within educational settings and the stable professional and social stereotype of a ‘universal teacher’. The hypothesis about the hybridization of teachers’ roles and responsibilities as a basic way of developing the qualification framework in the field of education has been tested and confirmed. Conclusions. The efficiency of the developed technology for modeling prospective roles and responsibilities and corresponding professional qualifications of general education teachers in accordance with the changing requirements of the labor market has been proved.
Real-Time Power Analysis of Smart Sensors Using Advanced Debugging Methods

To achieve a good estimate of the power consumption of an embedded system, including its firmware, is a crucial step in the development of systems with a severely constrained power supply. This is especially true for cases where the device is powered by a small battery or through energy harvesting. The state-of-the-art approaches to measure or estimate the power consumption are formal methods, using power debugging tools with the real hardware or simulation based estimations. In the work at hand, a novel method to estimate the power consumption is proposed, it utilizes the sensor-in-the-loop architecture and enhancing it with a power estimation functionality. The proposed method combines the benefits of former methods, allowing for run-time analysis of the power-consumption in a reproducible way using recorded data without the need for power debugging hardware. In the experiments it is shown that, once set up, the proposed method is able to estimate the power consumption with an error of less than 1% compared to a power debugging hardware. Thus, the proposed method provides a reliable and fast way to estimate the systems power consumption.
Students Satisfaction Description Based on Classical and Multivalent Discovery Techniques

Like most of the ongoing organizations, educational ones need to evaluate the quality of their provided services. “Quality” is understood as to how this organization satisfies its student's expectations to contribute to the image those students have about it. Although the perceived quality in the received service is strongly related to students’ needs, it is possible to extract objective indicators like their satisfaction as an essential factor in addressing the higher education quality. This paper presents the results of an exploratory study about the satisfaction of 112 students of the Facultad de Ciencias Exactas, Físicas y Naturales de la Universidad Nacional de San Juan during the 2017 year. Through the use of data mining techniques and bivalent and multivalent logic-based procedures, we discovered relationships between linguistic states of a data set (fuzzy predicates) that met the form \({\varvec{P}}\boldsymbol{ }\to \boldsymbol{ }{\varvec{S}}{\varvec{a}}{\varvec{t}}{\varvec{i}}{\varvec{s}}{\varvec{f}}{\varvec{a}}{\varvec{c}}{\varvec{t}}{\varvec{i}}{\varvec{o}}{\varvec{n}}\). We consider that the information found is valuable for making institutional decisions to improve educational quality.
Quantum computing methods for electronic states of the water molecule

ABSTRACTWe compare recently proposed methods to compute the electronic state energies of the water molecule on a quantum computer. The methods include the phase estimation algorithm based on Trotte...
An intelligence technique to maximize power generation using solar panel and its maintenance

The Earth receives the maximum amount (174 Peta Watts) of radiation from the upper atmosphere. Approximately 30% is reflected to space while the remainder is absorbed. Solar energy is an alternate for fossil fuels because it is non-polluting, clean, reliable, and renewable source of energy. It does not pollute the air by releasing harmful gases to the environment like carbon dioxide, nitrogen oxide or Sulphur oxide. So, the risk of damage is reduced. Thus, the utilization of solar devices was more suggested and therefore the traffic light and streetlights in villages was installed using solar array, but the solar PV modules are generally employed within the dusty environments and therefore the dust gets accumulated on the front surface of the module and blocks the incident light form the sun and it reduces the facility generation capacity of the module, the power output reduces if the module is not cleaned for a frequently.In order to regularly clean the dust, this research presents a control application of a sun tracker that can follow the sun with high accuracy and clean the dust on the panel without requiring a precise process of installation or recalculation. The designed tracking system include sensors, microcontroller, drivers for dc motors and gear- bearing arrangements with supports and mountings. DC motor is used to move the system panel in order that sun’s beam is in a position to stay aligned with the solar array and also clean the dust on the panel by wiping the panel using wipers which improves the efficiency of the solar array. Simulation and experimental results are obtained from a low-cost single axis solar tracker and exposed. Energy saving factors are taken under consideration, which means that, among other factors, the sun is not constantly tracked with an equivalent accuracy, to stop energy over consumption by the motors.
Chapter 2. DRM and the Law

In chapter 2 of Library Technology Reports (vol. 56, no. 1), “Digital Rights Management and Books,” Roncevic looks at DRM from a multidisciplinary perspective, paying attention to intersection between DRM systems and copyright laws.
Reflections of syntactic structures in non­autoregressive language models

Since the popularization of the Transformer as a generalpurpose feature encoder for NLP, many studies have attempted to decode linguistic structure from its novel multihead attention mechanism.However, much of such work focused almost exclusively on autoregressive style of decoding.In this study, we present decoding experiments on Nonautoregessive models in order to test the generalizability of the claim that dependency syntax is reflected in attention patterns.
Inference and prediction in language testing

This chapter reviews how different kinds of inferences are used in language testing validation. The approaches include frequentist inference and Bayesian inference, and the different interpretive inferential steps associated with the test use the argument approach to validation. Ambiguities that frequently attend validity inferences based on correlational evidence affected by non-random samples and aggregated data are discussed. The chapter reviews test validation based on truncated data without counterfactual conditions and the corrective strategies validity researchers typically use. The chapter turns to the issue of prediction and analytical approaches to establishing the predictive validity of language tests and aptitude tests used for candidate selection. Analysis methods such as correlation, regression, discriminant analysis, and structural equation modeling are discussed in light of the advantages and limitations each has in drawing inferences about predictive validity.
INTERFERENSI BAHASA INDONESIA KE DALAM BAHASA INGGRIS PADA UJIAN TRANSLATION (NON-ENGLISH STUDY PROGRAM STUDENTS)

The  research  is  aimed  not  only  at   discussing on  an  interference  of Indonesian language into English language as shown in teranslation test for non English study program students, in this study is the students of FISIP Universitas PGRI Palangka Raya, but also at the description on the kinds of interference. In this study, there are 130 students of three  classes which just 30 students takken as the  sample. The method applied in this research is descriptive with distributional and similarity analysis. The data is collected from translation test for non English study program students, in this case the tudents of FISIP Universitas PGRI Palangka Raya 2015/2016 academic year. The results indicate that there are three kinds of interferences, namely: morphological, syntactic and semantic interferences. Morphology interference happens such as in verb form for the third person, plural form, and possessive. Syntactic interference includes the form of phrase and passive voice, parallelism, and the omission of to be and article. Semantic interference consists of addition and substitution.