Reviewerly/exHarmony huggingface dataset:
Evaluation of Digital Forensic Tools in MongoDB Database Forensics

Wide usage of online applications has increased the risk of misuse of data by affecting privacy and security policies. Digital forensics is a process of solving criminal cases related to digital devices. Technical growth in this area is the expansion of forensic tools to collect the pieces of evidence. Database forensics is one of the categories of digital forensics. Database forensics covers the scanning of various parts of it for data recovery or finding data tampering. Forensic tools are available for most of the relational databases. Very few tools are available in the market for NoSQL databases. This paper is an attempt to present available digital forensic tools and to experiment with relevant free tools on the MongoDB database to check the usefulness.
FusionRNN: Shared Neural Parameters for Multi-Channel Distant Speech Recognition

Distant speech recognition remains a challenging application for modern deep learning based Automatic Speech Recognition (ASR) systems, due to complex recording conditions involving noise and reverberation.Multiple microphones are commonly combined with well-known speech processing techniques to enhance the original signals and thus enhance the speech recognizer performance.These multi-channel follow similar input distributions with respect to the global speech information but also contain an important part of noise.Consequently, the input representation robustness is key to obtaining reasonable recognition rates.In this work, we propose a Fusion Layer (FL) based on shared neural parameters.We use it to produce an expressive embedding of multiple microphone signals, that can easily be combined with any existing ASR pipeline.The proposed model called FusionRNN showed promising results on a multi-channel distant speech recognition task, and consistently outperformed baseline models while maintaining an equal training time.
Personalized Multimorbidity Management for Patients with Type 2 Diabetes Using Reinforcement Learning of Electronic Health Records

Comorbid chronic conditions are common among people with type 2 diabetes. We developed an Artificial Intelligence algorithm, based on Reinforcement Learning (RL), for personalized diabetes and multi-morbidity management with strong potential to improve health outcomes relative to current clinical practice. In this paper, we modeled glycemia, blood pressure and cardiovascular disease (CVD) risk as health outcomes using a retrospective cohort of 16,665 patients with type 2 diabetes from New York University Langone Health ambulatory care electronic health records in 2009 to 2017. We trained a RL prescription algorithm that recommends a treatment regimen optimizing patients' cumulative health outcomes using their individual characteristics and medical history at each encounter. The RL recommendations were evaluated on an independent subset of patients. The results demonstrate that the proposed personalized reinforcement learning prescriptive framework for type 2 diabetes yielded high concordance with clinicians' prescriptions and substantial improvements in glycemia, blood pressure, cardiovascular disease risk outcomes.
Manajemen Pendidikan Seni Dan Budaya Dalam Kaitannya Dengan Pertumbuhan Budi Pekerti Siswa SMP

The aims of this study was to find out the implementation of management function consist of planning, organizing actuating, and controling art and culture education in relation with student's character growth, supporting and inhibitor factors implementation of management in art and culture education, management of character growth education can be reached by art and culture education in SMP Negeri 1 Bantul.The research subject were principals, the teachers of art and culture education, and students.Data collection is done through observation, interviews and documentation.Data analysis used in this study is descriptive qualitative analysis.The data analysis is divided by four stage: data collection, data reduction, presenting data and concluding.The result of the study showed that the management of art and culture cducation in relation with student's character growth in SMP Negeri 1 Bantul at 2018 had gone well.The inhibitor factors of management art and culture education implementation in SMP N 1 Bantul has no effect to management art and culture education implementation
Development of Virtual Textile Chemistry Laboratory in Learning Making Cellulose-Based Regeneration Fibers Based on Learning Paradigms in the Industrial Revolution 4.0 Era

This study aims to design and create a virtual chemical textile laboratory model as an effort to improve students' understanding of learning Textile Chemistry, especially on the subject of making cellulose-based regenerative textile fibers that have a high level of abstraction and complexity. Theoretical learning in the form of verbal symbols, empirically is not representative enough to explain the concept of the system that is needed, so that the possibility is not affordable (likely to inaccessible) by students which effected to the lessen of learning experiences. These conditions have implications for the lack of student understanding of these processes which is indicated by the acquisition of low learning outcomes. The specific target of this research is to produce a virtual laboratory device as a simulation medium for learning textile chemistry on the subject of making effective cellulose-based regenerative fibers. Furthermore, the model developed is validated to get input from experts related to the technology used, design and process content in the developed model. The validation results show that this model is suitable for use in the study of textile chemistry and can be used to improve students' understanding of the material for making cellulose-based regenerative textile fibers. In the limited trials that have been carried out, there are some features, image choices, and some simulations that need to be refined to avoid students' misinterpretations of the planned chemical process concept. Students involved in the trials are more motivated to continue learning related concepts that have been learned. In subsequent studies this model will be tested on a broader scale to measure its effect on the mastery of concepts and its ability to improve learning outcomes in textile chemistry courses, on the material for making cellulose-based regenerative fibers.
ONTOLOGY OF EXHIBITION ACTIVITY

The article is devoted to theoretical modeling of the ontology of exhibition activity. The meaningful “frame” for expressing the desired ontology is the methodological presentation of activity. The method of schematization is used as the main tool for the formal expression of content. The methodological basis for theoretical modeling is the activity approach, the genetically constructive approach, the ontologization method and the constant method. In the construction special attention paid to the main variants of the source material of the exhibition activity and its product, as well as to the subject who perceives the exhibition in the conditions of its functioning. The resulting methodological construction can be used in theoretical studies of various aspects related to exhibition activity and in work that directly implies the implementation of the exhibition activity itself.
Uncovering a scene-defining feature using converging stimuli-based, behavioral and neural approaches

Humans are incredibly good and fast at recognizing places, or “scenes”. Not surprisingly then, there are cortical processes specialized for scene recognition; however, it remains unknown how humans recognize scenes from non-scene stimuli, such as faces and objects. Here, we hypothesize that, just like faces always have two eyes above a nose, above a mouth, there also exists some scene-defining visual features that enable the human brain to recognize scenes. To identify a potential scene-defining feature, we analyzed thousands of highly variable naturalistic scene images and found that, across most scenes, there is a vertical asymmetry in luminance, with the upper half brighter than the lower half. Next, we asked if this vertical luminance asymmetry (VLA) is not only a common scene feature, but also necessary to engage human visual scene processing. We predicted that if VLA is indeed necessary to engage scene processing, then a 90-degree image rotation that disrupts the VLA of a scene will impair scene recognition. Consistent with our hypothesis, we found people are worse at recognizing scenes that are rotated away from their upright, canonical orientations (90-degree, 180-degree, 270-degree rotation), while object recognition is unaffected by image rotation. Similarly, using functional magnetic resonance(fMRI), we found that the cortical scene processing system shows a diminished response to rotated scene images, whereas the cortical object processing system does not differentiate objects across different orientations. Taken together, these results provide converging stimuli-based, behavioral, and neural evidence that VLA is a scene-defining feature that enables the human brain to differentiate scenes from non-scene stimuli.
Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection

Dimensionality reduction is a crucial first step for many unsupervised learning tasks including anomaly detection and clustering. Autoencoder is a popular mechanism to accomplish dimensionality reduction. In order to make dimensionality reduction effective for high-dimensional data embedding nonlinear low-dimensional manifold, it is understood that some sort of geodesic distance metric should be used to discriminate the data samples. Inspired by the success of geodesic distance approximators such as ISOMAP, we propose to use a minimum spanning tree (MST), a graph-based algorithm, to approximate the local neighborhood structure and generate structure-preserving distances among data points. We use this MST-based distance metric to replace the Euclidean distance metric in the embedding function of autoencoders and develop a new graph regularized autoencoder, which outperforms a wide range of alternative methods over 20 benchmark anomaly detection datasets. We further incorporate the MST regularizer into two generative adversarial networks and find that using the MST regularizer improves the performance of anomaly detection substantially for both generative adversarial networks. We also test our MST regularized autoencoder on two datasets in a clustering application and witness its superior performance as well.
Capacity-achieving codes: a review on double transitivity

Recently it was proved that if a linear code is invariant under the action of a doubly transitive permutation group, it achieves the capacity of erasure channel. Therefore, it is of sufficient interest to classify all codes, invariant under such permutation groups. We take a step in this direction and give a review of all suitable groups and the known results on codes invariant under these groups. It turns out that there are capacity-achieving families of algebraic geometric codes.
New non-binary quantum codes from skew constacyclic codes over the ring F p m +v{F p m +v 2 F p m .

In this article, we construct new non-binary quantum codes from skew constacyclic codes over finite commutative non-chain ring $\mathcal{R}= \mathbb{F}_{p^m}[v]/\langle v^3 =v \rangle$ where $p$ is an odd prime and $m \geq 1$. In order to obtain such quantum codes, first we study the structural properties of skew constacyclic codes and their Euclidean duals over the ring $\mathcal{R}$. Then a necessary and sufficient condition for skew constacyclic codes over $\mathcal{R}$ to contain their Euclidean duals is established. Finally, with the help of CSS construction and using Gray map, many new non-binary quantum codes are obtained over $\mathbb{F}_{p^m}$.
The Progess That Natural Language Processing Has Made Towards Human-level AI

First of all, in this paper we will briefly introduce the development of Natural Language Processing (NLP) over time and then discuss how this technology benefit our humans, like what initial problems which beat human are being solved by this technology. We also summarise how this technology is being used upon various domains. Last but not least, we predict the future development of NLP by putting forward detailed understanding of the past and present in the context of artificial intelligence.
A Study on the Policy Making Process of Act on Support for Work in Parallel with Vocational Training on the Industrial Field : Focusing on the Kingdon's Policy Stream Framework

이 연구는 2013년에 한국형 도제식 교육훈련제도인 ‘일학습병행’이 정책적으로 도입된 후 여러 해가 지나서 관련 법률이 제정될 필요가 있었는가에 대한 의문에서 출발하였다. 이를 위하여 2019년에 제정된‘일학습병행법’의 제정 배경과 정책형성과정을 Kingdon의 정책흐름모형을 분석틀로 하여, 문제의 흐름, 정치(의사결정)의 흐름, 정책대안의 흐름을 고찰하였다. 연구 결과는 다음과 같다. 첫째, 정책초기 일학습병행법 제정이 정치&#8228;사회적 관심 이슈가 아니다 보니 제정의 필요성에 대한 문제의식과 정책대안에 대한 논의는 있었지만 정책입안자들의 관심은 높지 않았다. 둘째, 정책결정과정에서 여전히 공식적 참여자의 역할이 중요한 우리나라에서 동법 제정과정에 주도적인 역할을 보인 정책선도가는 고용노동부와 국회의원이었고, 일학습병행법 제정의 주안점이 훈련생 보호, 교육훈련의 질 관리 체계, 참여기업&#8228;학교&#8228;훈련생 지원체계, 교육성과의 평가&#8228;인증 및 통용성에 두다보니 학습근로자의 OJT, 학습권 보장 등을 통괄하는 교육부의 역할은 상대적으로 한계를 보였다고 할 수 있다. 셋째, 정권교체와 다수당의 변화도 의미가 있었지만 일학습병행법 제정 필요성은 청년실업 해소, 학력철폐를 통한 능력중심사회 구현, 현장실습생의 학습권 보장 및 근로기준관련 법령의 형해화(形骸化) 방지, 일학습병행 교육훈련 이수자의 자격인증 등 정책차원의 요구가 주요하였다. 이러한 연구결과를 토대로 일학습병행 연구의 이론적 확장, 향후 법률의 위임사항, 하위규범인 명령 및 규칙제정의 시사점 제공 등을 기대한다.This study started with the question of whether an efficient and systematic policy based on separate laws was needed in several years after the introduction of the policy in 2013. This study analyzed by dividing the background of enactment of Act on Support for Work in Parallel with Vocational Training on the Industrial Field(Act on WPVT) and the process of policy making into problem stream, political stream, and policy stream, using Kingdon s Policy Stream Framewor. The details of the study were as follows: First, although there was a sense of the need for legislation and discussion of alternatives, legislation was not a political and social issue. Policymakers interest was not high. Second, according to the PSF, policy entrepreneurs can be anyone who has official or unofficial position in the political system. Third, the change of regime and majority party were also meaningful, but the necessity of Act on WPVT was the main for the normative requirement for WPVT at the policy levels such as eliminating youth unemployment, realizing a competence-oriented society through diploma discrimination, and certification of completion. It is expected to provide direction to the theoretical expansion of WPVT, and are expected to provide direction to the delegation of legislation, enforcement decree and rules.
Meta-hyperband: Hyperparameter Optimization with Meta-learning and Coarse-to-Fine

Hyperparameter optimization is one of the main pillars of machine learning algorithms. In this paper, we introduce Meta-Hyperband: a Hyperband based algorithm that improves the hyperparameter optimization by adding levels of exploitation. Unlike Hyperband method, which is a pure exploration bandit-based approach for hyperparameter optimization, our meta approach generates a trade-off between exploration and exploitation by combining the Hyperband method with meta-learning and Coarse-to-Fine modules. We analyze the performance of Meta-Hyperband on various datasets to tune the hyperparameters of CNN and SVM. The experiments indicate that in many cases Meta-Hyperband can discover hyperparameter configurations with higher quality than Hyperband, using similar amounts of resources. In particular, we discovered a CNN configuration for classifying CIFAR10 dataset which has a 3% higher performance than the configuration founded by Hyperband, and is also 0.3% more accurate than the best-reported configuration of the Bayesian optimization approach. Additionally, we release a publicly available pool of historically well-performed configurations on several datasets for CNN and SVM to ease the adoption of Meta-Hyperband.
Professional Standards and Training of Staff for Different Levels of Social Work: on the Issue of Adapting Educational and Professional Standards

The formation of a national framework of qualifications for social professionals is an incomplete process. The replenishment of professional standards raises the question of adapting and forming a single structured system for training personnel of specialists in the social sphere. The article discusses the practice of developing educational standards for different levels of social work, connecting educational standards and professional standards for social workers, specialists of social workers and heads of social service organizations on the basis of continuity and continuity.
ABILITY OF READING COMPREHENSION USING COOPERATIVE SCRIPT FOR NON-ENGLISH DEPARTMENT

The objectives of this study are implementation, and evaluation using Cooperative Script method in reading comprehension. It also to determine whether or not there is an increase in reading comprehension results using the Cooperative Script method. This research referred as qualitative research, which is an action thought on a particular object. The type of this research is Classroom Action Research. Classroom action research is a digestion of learning activities in the form of an action, which is deliberately raised and occurs in a class together. The process of reading comprehension in this study uses the Cooperative Script method, which consists of 2 cycles of 5 meetings. The first cycle consisted of two meetings and the second cycle of two meetings, one meeting was used for the pre-test. In planning, the researcher compiles a learning implementation plan, makes learning media compile an observation instrument to observe students in learning activities. The process of implementing evaluation in this learning is carried out at the end of each cycle. The assessment is carried out to determine the ability of students' reading comprehension in using the methods that have been applied. The success rate in each cycle has increased, starting from the pre-test which increased on average 45 in cycle I to 61.10 then increased again in cycle II to 72.3. From the results of the assessment it can be proven that the application of the Cooperative Script method can improve students' reading comprehension.
MUCOR: A Multiparty Conversation Based Robotic Interface to Evaluate Job Applicants

“MUCOR” is a robotic interface made up of three small-sized, table-top robots that go through Linkedin profiles of job applicants and discuss the applicants’ information. Robots categorize applicants into ordered levels based on their competencies mentioned. Robots built following minimalist design concepts consist of a cylindrical head and a body that occupy less space. A score is calculated for each candidate and categorized into levels by a model built including Agglomerative Clustering and Gaussian Mixture Model. The model itself identifies the number of levels into which the applicants can be categorized, through the iterations. MUCOR is built for job recruiters who spend more time to find background information about applicants prior to an interview. Conversation among robots and the user creates a Passive Social Interface in which the user does not involve in the conversation, but gain knowledge by listening. The recruiter only has to input the LinkedIn IDs into a mobile application and listen to the conversation among robots. MUCOR was experimented with professional recruiters and their feedback highlighted that the synchronization of speech with the robot’s body movements has a fair impact on the user experience about the robot behavior.
Information System for Internship and Final Project Management Based on Laravel Framework

The Development of Portal Elektro Information System is carried out to create solutions for administrative problems related to Internship and Final Project, especially students, lecturers, and Electrical Engineering staff. Moreover it is an effort to improve the quality of the system to be more innovative and support the needs of Electrical Engineering study program. The System of Portal Elektro covers student needs to carry out internship or final project, starting from implementation guidelines, proposal writing, until becomes final report. This information system is developed with Rapid Application Development method, and use Laravel framework with the concept of MVC (Model, View, Controller) which can separate application based on application components, such as: manipulation data, controller, and user interface. With the RAD method and Laravel framework, application development can be done quickly and structured making it easier for further development in the future. The developed system has been successfully tested and applied in the Electrical Engineering study program at UNS and is planned to be implemented in several other study programs.
SPECIFIC FEATURES OF MUSIC REVIEWS IN CONVERGENT JOURNALISM

The article is devoted to the analysis of music reviews as affected by transformation of the genre and its framework in the convergent media environment. The proposed original structure of analysis is developed and reasoned based on the ideas presented in works by Russian and foreign scholars on the specific features of the review as a genre (Ye. A. Nabiyeva, A. A. Tertychnyi, and others), media convergence (H. Jenkins, T. Rogers, and others), interpretation of music images (T. Adorno, Yu. Strakovich, and others), suggestiveness of media texts (A. Beck, D. Burns, J. Baron and others). The analysis structure includes three basic sections: content, environment of publication, communicative tactics; each section is expanded in several criteria grades. The review is considered as an analytical genre that is traditionally based on suggestion as the leading communicative strategy. However, today this genre is transforming intensively in the mutable deinstitutionalized environment of the network mass media. Distortions, which are inevitable in conversion of an artistic image into a text, become especially identifiable in music reviews and increase subjectivity initially typical for this genre. The structure of analysis elaborated in the article engages particularly a classification of heuristics, or cognitive biases, which are considered to be cognitive distortions turning in opinion journalism into the means of expression and suggestion. These means are regarded as the foundation for the genesis of local media myths. The proposed method is tested on the review published at the Colta web portal. In conclusion, the paper emphasizes the significance of the research done for some general issues of communication studies, and in particular notes the method’s applicability to the analysis of inner cognitive triggers a person feels exposed to in the network society.
스토리텔링 지원을 위한 효율적인 VR 콘텐츠 저작도구 개발

With the development of virtual reality (VR)-related technology and the advent of the 5G era, VR-based streaming games or content have been developed and transmitted at high speed. Although VR technology is also being applied in education, health care, manufacturing, and production fields, its main application is for entertainment. VR technology has been developed based on hardware and various contents have been developed accordingly; however, the number of VR content with high entertainment value is insufficient, and there are primarily hands-on contents. In this paper, we propose a method for developing an writing tool that can enhance the productivity in the development and editing of VR content and create VR contents based on a timeline by reflecting the storytelling rather than by a simple empirical type to solve the bias in content style. The proposed VR content writing tool is expected to increase the productivity in VR content development and contribute to the creation of various styles of content. Its implementation can enable developers to create specific stories in a timeline and support several animation effects.