Reviewerly/exHarmony huggingface dataset:
Comparative Analysis of K-NN and Naïve Bayes Methods to Predict Stock Prices

Abstract— Buying and selling shares is a transaction that is widely carried out at this time, especially buying and selling stocks online which are widely available in the market, to make buying and selling shares require ability or knowledge so that the buying and selling of shares are profitable, to be able to help economic players predict prices. Profit shares or not purchased in the future, this research will conduct stock price predictions using classification methods, namely K-Nearest Neighbor and Naïve Bayes, to predict the stock price data used for one month in minute levels totalling 39065 data, based on prediction results. The highest results obtained were using Naïve Bayes with an accuracy value of 69.38 then the K-Nearest Neighbor method with a K = 5 value of 67.25%, based on these results it can be concluded that the use of the K-Nearest Neighbor and Naïve Bayes methods for prediction share price not yet owned I high accuracy, so it can be combined with other methods or by using other variable predictors.
The Role Of Scientific Leadership In Blended Learning In Postgraduate Education

Currently, the issues of updating the model of training scientific and pedagogical personnel in post-graduate school are regularly raised.This is due to the fact that the development of science and the self-reproduction of scientific personnel in post-graduate school are important conditions for maintaining the country's competitiveness.An important condition for the successful work of a post-graduate student on a dissertation is scientific leadership.Considering the change in the status of Russian post-graduate studies in recent years, the decrease in the statistics of successful defenses makes it necessary to identify the motivation of post-graduate students to study, which should be taken into account when organizing training for highly qualified personnel.The emergence and widespread introduction of distance educational technologies leaves an imprint on the interaction of a postgraduate student with a scientific advisor.This study is aimed at exploring the change in the phenomenon of scientific leadership of a post-graduate student during the transition from traditional face-to-face format to online education.The purpose of the article is to conduct an empirical study of the satisfaction of post-graduate students with scientific leadership and identify expectations from interaction with a scientific advisor in an online format.The article reveals the issues of motivating post-graduate students to study in post-graduate school and their expectations from the supervisor when working in person and online.The authors reveal similar and distinctive features, the most important for post-graduate students in the implementation of scientific leadership.
A Prognostic Tool for COVID-19 Decision Support: The Intermountain Risk Score Predicts Major Adverse Health Events in Patients Positive for COVID-19

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Confidence in Causal Discovery with Linear Causal Models

Structural causal models postulate noisy functional relations among a set of interacting variables. The causal structure underlying each such model is naturally represented by a directed graph whose edges indicate for each variable which other variables it causally depends upon. Under a number of different model assumptions, it has been shown that this causal graph and, thus also, causal effects are identifiable from mere observational data. For these models, practical algorithms have been devised to learn the graph. Moreover, when the graph is known, standard techniques may be used to give estimates and confidence intervals for causal effects. We argue, however, that a two-step method that first learns a graph and then treats the graph as known yields confidence intervals that are overly optimistic and can drastically fail to account for the uncertain causal structure. To address this issue we lay out a framework based on test inversion that allows us to give confidence regions for total causal effects that capture both sources of uncertainty: causal structure and numerical size of nonzero effects. Our ideas are developed in the context of bivariate linear causal models with homoscedastic errors, but as we exemplify they are generalizable to larger systems as well as other settings such as, in particular, linear non-Gaussian models.
Application of Social Big Data in Crime Data Mining

The increased fame of the Internet and technology has motivated criminals a lot to commit their evil actions with the help of its various facilities such as social media, e-commerce and so on. Nowadays, almost everything exists on the Internet either to store or to access personal as well as professional data. This helpful nature of the Internet and technology has proved a boon for criminals to find their vulnerable targets. It also provides many options for investigators and police officials to track and catch the criminals. The regular use of the Internet has led to a huge amount of big data that made investigators and police officials hard to analyze and predict crime and criminals. But a combination of crime analysis and computer science or information technology can make it easier and user-friendly for investigators and police officials to fetch useful data from the social big data. By applying data mining approaches, we can help the investigative department to predict and prevent crime based on past crime data. The main focus of this paper is to perform an in-depth analysis of some cyber-crimes that frequently occurred in the Union Territories of India per year from 2014 to 2018. Two open-source data mining tools, namely RapidMiner and Weka, are used with the application of the k-means clustering technique. The results of the two tools are compared, and it is found that though Weka outperforms RapidMiner in execution time, it lacks in accuracy and visualization. But, in general, both help in finding an application for investigation and the police department in predicting patterns of crime occurrences.
Emotion Modeling for Emotion-based Personalization Service

This study suggests the emotion space modeling and emotion inference methods suitable for personalized services based on psychological and emotional models. For personalized emotion space modeling taking into account the subjective disposition based on the empirical assessment of the personal emotions felt by the personalization process of emotion space was used as a decision support tool, the Analytic Hierarchy Process. This confirmed that the special learning to perform personalized emotion space modeling without considering the subjective tendencies. In particular to check the possible reasoning based on fuzzy emotion space modeling and sensitivity for the quantification and vague human emotion to it based on the inherent human sensitivity.
영국의 사이버 보안 거버넌스 모델과 정책 시사점에 대한 고찰

An examination of national cyber security governance is uncharted territory due to a lack of empirical evidence and data inaccessibility. This article describes how national cyber security governance in the UK is constructed and examines whether cyber threats and cybercrime against businesses are dealt with properly. It aims to find out its characteristics and suggest policy implications to other countries, based on critical analyses and evaluations of the UK governance. The national governance consists of three dimensions: (1) national structure, (2) initiatives to implement national strategies, and (3) reporting mechanisms. Analyses suggest that the UK’s model highlights the alignment of hierarchical strategies, program-based approach to implement the national strategies, and centralised reporting mechanisms. The key finding is that there is strong national leadership in the UK governance. The strong national leadership resulted in two things: (1) its orientation to proactive measures, and (2) the structured interdepartmental and public-private sector coordination. Given that cyber threats are increasingly asymmetric, automated, and global in a larger scale, it would be appropriate to have a governance which is driven by a centrally-led national framework. It is expected that the critical analyses of the UK’s cyber security governance should be of value to future studies which evaluate cyber security strategies or policies on the national level.
Communication Behaviour of Deaf Children in SLB Negeri 1 Tabanan: Ethnographic Communication Perspective

The aim of the research is to identify and interpret field data on subcultures, total communication approaches, communication components forming communication events, patterns and communication skills of deaf children at the research site. Three important things have been identified in this research. First the subculture and overall communication approach of deaf children has been identified as a typical culture of deaf children in SLB Negeri 1 Tabanan. Second, the dominant communication components shaping the communication events of deaf children in SLB Negeri 1 Tabanan are (1) Settings, including the ideal distance to communicate, physical asp. The three patterns and communication skills of deaf children in SLB Negeri Tabanan identified were (1) patterns of communication between deaf children and normal people and (2) patterns of communication between deaf children and deaf children. The patterns of communication with normal people are divided into patterns of communication with older people and patterns of communication with peers.
Una mirada a los efectos de la pandemia global Covid19: Realidades y desafíos actuales en el Bachillerato y la Educación Superior

The COVID-19 health emergency has brought a new and unforeseen situation in education in Mexico and around the world. This report shows the results of an online survey applied to high school (CETYS abbreviated in Spanish) and bachelor degree (TecNM abbreviated in Spanish) students at the Mérida and Tuxtla Gutiérrez campus. Out of 846 students, 501 answered the survey. Most of them live in municipal seat, some of them in rural communities 28.5 are high school students and 71.5% are bachelor degree students. 48.1% of students responded that they would not like to continue receiving classes online and 44.1% that in this modality their learning was the same as face -to- face lessons. They face organizational, technological, pedagogical and, to a lesser extent, information issues. They mainly use the WhatsApp application as well, as Microsoft Teams for synchronous work and virtual interviews, they consider it suitable for their virtual sessions. The responses to the coverage of the educational program were similar, the fifth part reached between 90 and 100%; The students showed irregularities during the setting of this educational modality and the main problem was the failure of the Internet connection, and the least was the lack of sensitivity of the teacher. Objectives: Need to obtain information on the opinion of students regarding their academic development during the school period that occurred during the Covid-19 pandemic, that would allow knowing the problems they are facing and proposing alternatives to support students Methodology:A survey was applied to undergraduate and high school students to find out their opinion regarding their problems in school development, the data were analyzed using predetermined scales and the SPSS program to determine the possible correlation between the mentioned variables. Contribution: Problems related to student performance were verified, most have their own computer and have internet service, they still do not adapt to taking virtual classes and express disapproval to continue with this form of learning, factors to be taken into consideration in the immediate future.
Medical Code Prediction from Discharge Summary: Document to Sequence BERT using Sequence Attention

Clinical notes are unstructured text generated by clinicians during patient encounters. Clinical notes are usually accompanied by a set of metadata codes from the International Classification of Diseases(ICD). ICD code is an important code used in various operations, including insurance, reimbursement, medical diagnosis, etc. Therefore, it is important to classify ICD codes quickly and accurately. However, annotating these codes is costly and time-consuming. So we propose a model based on bidirectional encoder representations from transformers (BERT) using the sequence attention method for automatic ICD code assignment. We evaluate our approach on the medical information mart for intensive care III (MIMIC-III) benchmark dataset. Our model achieved performance of macro-averaged F1: 0.62898 and micro-averaged F1: 0.68555 and is performing better than a performance of the state-of-the-art model using the MIMIC-III dataset. The contribution of this study proposes a method of using BERT that can be applied to documents and a sequence attention method that can capture important sequence in-formation appearing in documents.
Features of modern classification of intellectual property items

This article determines modern classification of intellectual property objects, which identified in international regulations and presumed by scientists, studding problematic issues in sphere of intellectual property. The defined, which the most common is classification, with distribution criterion of objects in group to the institutions of intellectual property: copyright and related rights; industrial property law. The individual scientists have their own approach regarding inclusion in different classification groups. The offered with given the content of international law and scientific research of scientists, classify of intellectual property objects by several criteria in depending: from the assignment of objects to a specific legal institutions of intellectual property; from the legal nature of objects which without fail subject to patenting or state registration or on them spread of presumption of authorship; from the title of protection, which issued based on patenting result or state registration of specific objects. By these criteria expediently to highlight such groups and subgroups of intellectual property objects: objects of copyright and related rights with separate subgroup copyright objects and subgroup related rights objects; objects of the institution of industrial property law, where to highlight the patent law objects, the objects, where individualize of participants in civil transaction, goods, services and subgroup of unconventional objects. Determined the need in modern realities of virtualization of legal realities to additions to the list intellectual property objects, which is defined in article 420 Civil code of Ukraine, such facilities of domain name and website. The domain name include in subgroups of industrial property law objects, which individualize of participants in civil transaction, goods and services, and website include in group objects of copyright and related rights, guided by the legislator’s position. The legislator secured concept of website in the law of Ukraine «On copyright and related rights».
Prior-Aware Distribution Estimation for Differential Privacy

Joint distribution estimation of a dataset under differential privacy is a fundamental problem for many privacy-focused applications, such as query answering, machine learning tasks and synthetic data generation. In this work, we examine the joint distribution estimation problem given two data points: 1) differentially private answers of a workload computed over private data and 2) a prior empirical distribution from a public dataset. Our goal is to find a new distribution such that estimating the workload using this distribution is as accurate as the differentially private answer, and the relative entropy, or KL divergence, of this distribution is minimized with respect to the prior distribution. We propose an approach based on iterative optimization for solving this problem. An application of our solution won second place in the NIST 2020 Differential Privacy Temporal Map Challenge, Sprint 2.
1st international workshop on software architectures and human values (SAHVA):13th European Conference on Software Architecture, ECSA 2019

Sustainable software systems require an in-depth understanding about the role that software systems play in our society at a scale and along time frames that are often difficult to grasp and envisage. We argue that a values 'first' software engineering (SE) perspective can offer new insights not only about the human and social aspects that shape SE decision-making processes, but also the potential uses, misuses, and vulnerabilities of complex socio-technical systems afforded by high-level design decisions. While the area of values-based SE has explored means for identifying and making sense of values in the analysis of software production, more effort is required to investigate how values are ultimately instantiated in the architectural structuring of software systems, and the long-term implications of such design decisions. This workshop provides a unique forum where students, researchers, and practitioners working on requirements engineering, software processes, societal aspects of SE, and software sustainability can come together to advance the field of value-based software architectures. © 2019 Authors.
The quality of modern pedagogical teachings and its main indicators

In this article, the quality of education and education in modern pedagogy, pedosophical principles of education, quality of education, quality education criteria, quality management criteria, quality management such as strategy. The interpretation of the quality and efficiency of the education system, as a social category characterizing the state of education, will inevitably impoverishment of the subjectivity of quality indicators inevitably the subjectivity. The needs of different social groups can vary, and this creates a contradiction between the hopes of education and their implementation
Multifactorial approach to preparing Russian young people for a future profession

This article examines the theory and practice of a multi-level system of continuous innovative education. The pedagogical system of multilevel continuous creative education is considered in detail, and sufficient creative pedagogical methods are put forward for the formation of creative thinking and the development of students' creative abilities. Creative approach provides teachers and students with intellectual tools for the formation of creative systems thinking, teaches them to look at the world systematically and manage thought processes. Innovative teaching methods in the continuous formation of a multilevel system of creative thinking provide the basic principles of teaching by changing the structure of the lessons and implementing their original content. Using them, it is possible to significantly accelerate the solution of a pressing problem in Russia: formation of a creative personality of students.
A Differentiable Point Process with Its Application to Spiking Neural Networks

This paper is concerned about a learning algorithm for a probabilistic model of spiking neural networks (SNNs). Jimenez Rezende & Gerstner (2014) proposed a stochastic variational inference algorithm to train SNNs with hidden neurons. The algorithm updates the variational distribution using the score function gradient estimator, whose high variance often impedes the whole learning algorithm. This paper presents an alternative gradient estimator for SNNs based on the path-wise gradient estimator. The main technical difficulty is a lack of a general method to differentiate a realization of an arbitrary point process, which is necessary to derive the path-wise gradient estimator. We develop a differentiable point process, which is the technical highlight of this paper, and apply it to derive the path-wise gradient estimator for SNNs. We investigate the effectiveness of our gradient estimator through numerical simulation.
금성전투와 쿠이토 쿠아나발레(Cuito uanavale) 전투에 대한 비교 연구: 용병술 차원의 관점에서

Even though Korea is far from Angola in Africa, Korean war and Angolan war have many similarities. This thesis comparatively reinterpreted Gumsung and Cuito Cuanavale battles with the levels of war(strategic, operational, and tactical level). With studying reciprocal relations among strategic objectives, operational maneuvers, and tactical actions, this thesis compared the reasons and results of the two battles to extract the relative success or failure.Despite the battle is a part of the war, the decisive battle influences on the war''s whole scale. On the two Gumsung and Cuito Cuanavale battles in the period of ending wars, analyzing linkages for levels of warfare was useful to study factors of relative success or failure. As a result, COF excluded ROKF to sign KAA and ITF eliminated UNITA to join NYA harmonized operational maneuvers and tactical actions to strategic objectives. On the other hand, UNF and LBF failed to clear strategic objectives, rather tried to expand operations to strategic levels or respond operational maneuvers with tactical actions.Consequently, a lesson learned from this study is that the relative success of battles come from clear strategic objectives supported by operational maneuvers and tactical actions. The lesson is almost a kind of military doctrine across all ages and countries was reconfirmed through this study. In addition, this case study took a important look at the hierarchy of ‘Politics → Diplomacy → Military(Strategic → Operational → Tactical).’ Because strategic objectives was effective when those aligned to the political purpose with diplomatic negotiations controlling levels of warfare during the period of ending wars.
Enhancement of Dehazing Methods Using DNN and Filtering

Murkiness in pictures is because of common ecological wonders, which makes the picture in a white shade commotion. Fog evacuation is one of the most significant research subjects nowadays to the due prevalence of utilizations progressively reconnaissance from rambles or any region under security. Both indoor and outside pictures are significant for testing cloudiness and its expulsion. Many picture-handling methods are made by analysts to evacuate cloudiness in a solitary picture. Murkiness force can be determined by a parameter known as perceptual fog density measure (PFD). It is critical to investigate this parameter for all the strategies in order to get a thought of progress. In this postulation, another methodology is made by applying an all-inclusive guided sifting procedure with a profound neural system. This proposed calculation is executed on MATLAB programming, and results are gotten by figuring the PFD in the current and proposed method. The four methods are compared with one another. The methods are global image filtering (GIF), weighted global image filtering (WGIF), globally guided image filtering (GGIF), and a proposed strategy, for example, comprehensively guided sifting with deep neural network (DNN). In GIF, the fine structure of the picture is commonly not safeguarded and an unreasonable picture is acquired. In WGIF, the PFD got is most noteworthy. In GGIF, PFD is lower and structure is not safeguarded, yet in the proposed calculation, the PDF is least with fine structure, and shading power of the image is of the best quality.
A High-Quality Journal for a Digital Society

I have accepted with great honor and a sense of responsibility the invitation of the Insights Publisher sponsored by The Bonoi Academy of Science and Education (BASE) to be an EiC – Sociology & Education Section of the Science INSIGHTS® journal. I appreciate the trust placed in me and hope to collaborate with the journal’s development.