Reviewerly/exHarmony huggingface dataset:
Regarding the possibility of endowing artificial intelligence with the status of a subject of cross-border copyright relations

The article is devoted to the evaluation of the place of artificial intelligence (hereinafter — AI) in intellectual property law. Due to the recent developments, AI has ceased to be just an assistant and a tool for creativity in the world of human authors. Rather it itself has become capable of creating works. The article considers the rules of copyright applied in various States and enshrining the concept of an “author” and the possibility of recognizing AI as a subject of copyright creating a copyrightable work. The article also considers the rulesapplied to determine and regulate the process of creating a creative work. A conflict-of-laws issue is raised regarding the possibility of granting protection to works created by AI within the framework of cross-border relations, when, under the law of the state of origin (lex loci originis), the work is not subject to protection, but is protected under the law of the state where protection is sought (lex loci protectionis). Thus, crossborder copyright relations related to AI are mainly implemented on the Internet, where the most effective mechanism for protecting author’s rights is implemented by means of Creative Commons licenses. However, the lack of the human author’s participation and the original creativity element makes it impossible forthe AI to be recognized as a subject of law and, as a result, prevents copyright protection of the works created by the AI. Therefore, the author proposes to allocate the works created by AI to the public domain.
RETRACTED: Research on 3D Fluid Simulation Technology Based on Computer Simulation Technology

Abstract With the progress and development of science and technology, D fluid simulation technology is gradually moving towards a more systematic and comprehensive development. Of course, more and more people use the three D fluid simulation technology, which further promotes its development. In order to make the three fluid simulation technology more advanced and the whole society, it needs to be studied and improved [1].
Developing Novel and Relevant Theoretical Contributions with Literature Reviews

Authors of standalone literature reviews aim to develop scholarly knowledge and offer theoretical contributions, but beyond guidance for summarizing the literature, there is limited guidance on details for discovering insights for theoretical contributions that are scholastically novel and practically relevant. In this article, we present methodological guidelines for discovering novel and relevant theoretical insights from literature reviews, particularly using theoretical concept reviews, and then presenting them in a research agenda that highlights these theoretical contributions. We present perspectives on focusing on the value of scholarly articles in general and of literature reviews in particular; we delineate three kinds of value of the contributions of propositions and research questions in literature reviews according to if they summarize literature, reconcile conflicts in the literature, or develop insights that depart from the literature; and we explain the value of theoretical concept reviews for discovering theoretical insights.
Finding and Fixing Design Debt

In this talk I will discuss a common and pernicious form of technical debt–called design debt, or architecture debt. I will briefly present the theoretical foundation behind this form of debt and present a broad set of evidence demonstrating its dramatic effects on project outcomes. That is the bad news. The good news is that we can fully automatically pinpoint the causes and scope of such debt. I will describe how we can automatically locate it, measure it, and create the business case for removing it. Finally, I will explain how we can remove–pay down–this debt via refactoring. I will also sketch some of my experiences in transitioning the tooling to do so with industrial partners, and describe some of their experiences and outcomes.
미국의 테러이용수단으로서의 생물ᆞ화학 물질 관리사례 연구

A terror attack using weapons of mass destruction(WMD) such as biological and chemical materials is one of very threatening terror attacks. According to the classification of the United States, WMD means chemical, biological, and radiological & nuclear materials, and explosive devices including such materials which can cause massive casualties in case of a terrorist use. In response to such a possibility, the U.S. government prevents terrorists or malicious actors from accessing to such materials, grasps and responds to technological trends associated with WMD, and prepares and practices countermeasures to strengthening the response capability of governmental agencies and civilian corporations which handle and store materials related to WMD. Such a case of the United States becomes a good reference for the South Korean counterterrorism policy. In South Korea, propositions and discussions on the strengthening safety management of means of terrorists’ use have continued. In this context, this paper examines the U.S. case of the management of biological and chemical materials and proposes lessons. Particularly, this paper investigates policy practices and laws on the U.S, safety management of biological and chemical materials. Also, it introduces scientific and innovative practices of research institutions established for the support of counterterrorism activities. content analysis on various academic articles and governmental reports is used for the study. Based on the investigation of the U.S. case, some policy responses are also suggested for the development of the South Korean counterterrorism measures.
A Contextual Biodiversity Handbook to Identify Bintan Coastal Invertebrates

Abstract Contextual teaching and learning is quite important to be applied due to students weakness in connecting between what they learn and how the knowledge will be used. It is a learning system that matches the performance of the brain, to construct patterns that embody meaning, by linking the academic content with the context of learners’ everyday life. By applying contextual teaching and learning the information received is not only stored in short-term memory, which is easily forgotten, but can be stored in long-term memory. Contextual teaching and learning can be applied through various learning components. One of them is by applying appropriate learning resources/learning media to facilitate contextual learning. Through research and development applying Plomp model, a handbook has been developed to identify specific invertebrates exist on the coast of Bintan (the Province of Kepulauan Riau). This handbook was developed through processes namely; (1) collecting invertebrates of the coastal area of Bintan, (2) identifying invertebrates using research publications, (3) displaying content in the form of handbooks applying attractive designs, (4) suggestions for improvements by validators, and (5) test the feasibility through trials in learning. These processes drive the handbook different from most learning resources on this topic that do not specifically provide information about invertebrates exist in Bintan or Kepulauan Riau. The using of handbook encourages 100% completeness in learning mastering for 21 students. Furthermore, it increases learning motivation in a high increasing category.
Emotional classification model of review text based on topic and sentiment characteristics

Research on the impact of the high dimension of comment text features and the implicitness of text expression on sentiment classification performance, a deep learning sentiment classification model based on topic and sentiment features is proposed for sentiment classification of comment texts. Firstly, the model uses dependency syntax analysis combined with sentiment dictionary to extract sentiment elements, and uses the implicit LDA topic model to reduce the dimension of the extracted sentiment elements and extract feature items; secondly, the generated feature items are vectorized and combined with the text The vector fusion forms the feature vector of the text; finally, the LSTM model in deep learning is used for text sentiment classification. Experiments show that this model is better than traditional methods for text sentiment classification, and can effectively improve the performance of sentiment classification.
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The autocorrelation properties of Boolean functions are closely related to the Shannon’s concept of diffusion and can be accompanied with other cryptographic criteria (such as high nonlinearity and algebraic degree) for ensuring an overall robustness to various cryptanalytic methods. In a series of recent articles [14,9,15], the design methods of n-variable balanced Boolean functions n is strictly even) with small absolute indicator Δf < 2n/2 have been considered. Whereas the two first articles managed to solve this problem for relatively large n⩾46, a recent approach [15] has introduced a generic design framework achieving Δf < 2n/2 for even n⩾22. Based on a suitable modification of the method of Rothaus, used to construct new bent functions from known ones, we provide a generic iterative framework for designing balanced functions satisfying the condition Δf < 2n/2 and having overall good cryptographic properties for any even n⩾12. Even though the problem of specifying functions having Δf < 2n/2 for smaller n has been considered in [14,9,15] using various search algorithms, our method for the first time provides relatively simple iterative framework for variable spaces of more practical interest. Moreover, our approach can be efficiently applied to certain classes of initial functions (derived from partial spread bent functions) for deriving balanced functions with Δf < 2n/2 for relatively large n, namely for n⩾48 satisfying n≡0 mod 4 and n⩾54 with n≡2 mod 4. In the latter case, our nonlinearity bound is better than the one presented in [14].
Party Building Innovation in Judicial Professional Colleges in the Context of Big Data

In the context of big data, judicial vocational colleges must respond to the trends of society and conduct innovative party building research based on the context of big data. This paper looks at the problems of judicial professional schools in their party building and innovation efforts to analyze their Influencing factors and giving strategies for solving party building innovation work in the context of big data.
An Effective Algorithm for Multiple Sensitive Attributes to Preserve Data Privacy

To make various statistics about any medical data huge amount of data gets collected from the public. The collected information contains sensitive information about the individual. Individual's sensitive information includes data such as previous health condition, travel history, political affinity and family background. The collected data is published to perform various statistics, carry out research and to make decisions. However, there might be an intruder in the crowd who uses the published data to gain more information about a particular person that leads to privacy threat. Privacy Preserving Data Publishing (PPDP) aims at anonymizing such data so that it becomes difficult for an intruder to infer a various attribute of particular person from the published data and to gain more information about a him. When the data is anonymized, there are chances of data loss, hence the anonymization algorithm, must balance between the anonymity and the utility of the published data. Most of the existing privacy algorithm concentrate on preserving privacy of single sensitive attributes, but many domains require anonymizing multiple sensitive attributes such as healthcare/ hospital dataset, census dataset etc., that need to be preserved. In this paper an effective algorithm is proposed that preserves the privacy of multiple sensitive attributes with minimal information loss.
Structural Prior Guided Image Inpainting for Complex Scene

One of the main challenges faced by many existing image inpainting methods is that they fail to generate clear boundaries between different objects in a complex scene. To address this problem, we propose a novel two-stage image completion framework with semantic segmentation maps as the structure prior to restrain texture generation. Our framework consists of a PSP-based adversarial network called SP-Net, which can generate a semantic segmentation map for the corrupted image and an SG-Net using domain alignment and correlation matrix to get the feature correspondence between structural prior and known region. Combining the structural prior and feature correspondence, the image completion network fills the missing region with distinct boundaries and fine details. The proposed method was evaluated over Outdoor Scenes and Cityscapes datasets. Experimental results demonstrate that our approach outperforms other structural prior based approaches in terms of visual quality and quantitative measurements.
Educational Trajectories Modeling for Practice-Oriented Higher Education

This article is devoted to modeling and managing educational trajectories for competitive graduates learning in knowledge-intensive professional areas of practice-oriented higher education. The authors propose the educational space and educational trajectories models of the practical-oriented programs of study (PoS). These models consider numerous factors of influence—changes in the regulatory framework of profiles and trends in the professional field, planned and achieved student learning outcomes. The educational space's main feature is its redundancy—it contains the maximum possible number of planned learning outcomes. The model involves detailing elementary ones’ primary competence and then comparing them with the educational space Q’s expected learning outcomes. The model in the form of a hyper-graph (plan-graph) establishes causal relationships between learning outcomes, including planned ones. The authors propose a method of managing educational trajectories based on a multi-layer plan-graph of the workshop. This research result is the educational space and the plan-graph of PoS “Computer Systems and Technologies” of ITMO University. With these models’ help, two versions of the “Network Protocols” course workshop were developed and implemented in the educational process (in 2019 and 2020 years). The workshop was tested by students of the 3rd semester of the master's program. The expert community in network technologies evaluated the achieved results of training in this discipline in the form of a course project. To assess the effectiveness of the workshops’ updated versions, the authors used the degree of closeness of students’ tasks in the course project to real professional tasks. For the last academic year, it was 73%, and after the implementation of the modified version of the workshop in the current academic year—90%.
Smart-Tracking Systems Development with QR-Code and 4D-BIM for Progress Monitoring of a Steel-Plant Blast-Furnace Revamping Project in Korea

Blast furnace revamping in the steel industry is one of the most important works to complete the complicated equipment within a short period of time-based on the interfaces of various types of work. P company has planned to build a Smart Tracking System based on the wireless tag system to comply with the construction period and reduce costs, ahead of the revamping of blast furnace scheduled for construction in February next year. It combines detailed design data with wireless detection technology to grasp the stage status of design, storage, and installation. Then, it graphically displays the location information of each member to the plan and the actual status in connection with Building Information Modeling (BIM) 4D Simulation. QR Code is used as a wireless tag to check the receiving status of core equipment considering the characteristics of each item. Then, DB in the server system is built, status information is input. By implementing BIM 4D Simulation data using DELMIA, the information on location and status is provided. In terms of logistics digitization, the system’s features allow suppliers to monitor the real-time status of the 4D system provided on a Web basis, enabling suppliers to accurately identify and supply the delivery times for the facilities they need to manufacture and supply. Besides, the project progress control can be managed quickly and accurately by identifying the location of major delivered facilities in real-time to maximize the efficiency of construction, and by identifying the status information of major facilities, i.e. installation status in real-time. This digitalization ultimately results in savings in the manpower involved in the project and contributes to lower investment costs as a whole.
Cross-Compiler Bipartite Vulnerability Search

Open-source libraries are widely used in software development, and the functions from these libraries may contain security vulnerabilities that can provide gateways for attackers. This paper provides a function similarity technique to identify vulnerable functions in compiled programs and proposes a new technique called Cross-Compiler Bipartite Vulnerability Search (CCBVS). CCBVS uses a novel training process, and bipartite matching to filter SVM model false positives to improve the quality of similar function identification. This research uses debug symbols in programs compiled from open-source software products to generate the ground truth. This automatic extraction of ground truth allows experimentation with a wide range of programs. The results presented in the paper show that an SVM model trained on a wide variety of programs compiled for Windows and Linux, x86 and Intel 64 architectures can be used to predict function similarity and that the use of bipartite matching substantially improves the function similarity matching performance.
ELECTRONIC DOCUMENT EXCHANGE AND DIGITIZATION OF THE ATTESTATION PROCESS RELATED TO SCIENTIFIC DEGREES

The paper describes the development of the "Complex-analytical information system of scientific degrees" for electronic document exchange and digitization of the attestation process for scientific degrees in the field of attestation of highly qualified scientific and scientific-pedagogical personnel, modules that make up the system, their functions, also information security of the system, requirements for functions performed by the system, client-server architecture of data processing in information system.
Historical and Pedagogical Analysis of the Online Education

In modern information society, there is no edge between the traditional and distant education because of the popularity of online teaching technologies among the students and teachers in process of training. There is a wide amount of information that offers the Internet world network. It helps the researchers and scientists to retrieve the required information and shortens the duration of the scientific inquiry. E-learning is considered as the demonstration of the virtualization of the society and is one of the worthwhile trends in the education system. It makes possible the organization of the training different specialists without discontinuing work, to get an education from the house. The Internet world network is quite young phenomenon, but the history of E-learning is quite old and not always was on such high level. And the authors suggest the consideration of the developmental history of E-learning.
How have high-impact scientific studies designing their experiments on mixed data clustering? A systematic map to guide better choices

Many scientific works on grouping mixed data have chosen different experimental scenarios to structure their findings, which involve deciding from the programming language to the use of real-world and/or simulated datasets and performance measures, for example. Due to these characteristics directly influence the conclusion of the studies and the way new scientific works are proposed, it would be useful to have a wide map with the main choices that have been done by the authors of high-impact scientific documents so that the community can reflect on the thematic direction, identify best practices, and propose new paths for future research. To the best of our knowledge, such a map does not exist, neither a methodological procedure to build it. Therefore, this paper proposes a systematic methodology to reach such maps and provides a wide and in-depth map of the main choices the authors of high-impact scientific documents on mixed data clustering and surrounding studies have done in their experiments. As a result, 160 documents were systematically selected and classified into one of the six class of data clustering approaches, besides individually tabulated. From the tables for each class, we found, for instance, that real-world datasets are used more frequently than simulated ones, the documents used more external indices, followed by internal and relative ones, it is not common for the authors to inform the programming language they have used, except in the partitional class. We also provided the address of the algorithms’ code when they are made available by the authors.
Socio-psychological components of success of personality life choice

The article reveals the socio-psychological components of the success of life choices. A multilevel socio-psychological program of optimization of the process of life choice of a person in early adulthood is proposed, which consisted of motivational-diagnostic, correctional-developmental and analytical-monitoring stages using methods and techniques of existential, cognitive, behavioral correction, creative self-therapy and therapy. It is shown that the correctional and developmental work carried out within the program had a positive effect on the semantic sphere of the participants. There is a significant positive dynamics of indicators on the subscales of semantic life orientations, which indicates an increase in understanding of life, the emergence of goals in life, confidence in achieving goals; favorable emotional perception of the life process as a whole. Changes in the semantic sphere of personality in early adulthood had a positive effect on its value sphere, which was expressed, in particular, in increasing the value of achievements, and indicated the growing importance of social recognition, success in life, competence, purposefulness and optimization of life choice. early adulthood. Key words: personality, life choice, socio-psychological correction, socio-psychological components of success of life choice.
A Partial Matching Convolution Neural Network for Source Retrieval of Plagiarism Detection

Source retrieval is the primary task of plagiarism detection. It searches the documents that may be the sources of plagiarism to a suspicious document. The state-of-the-art approaches usually rely on the classical information retrieval models, such as the probability model or vector space model, to get the plagiarism sources. However, the goal of source retrieval is to obtain the source documents that contain the plagiarism parts of the suspicious document, rather than to rank the documents relevant to the whole suspicious document. To model the “partial matching” between documents, this paper proposes a Partial Matching Convolution Neural Network (PMCNN) for source retrieval. In detail, PMCNN exploits a sequential convolution neural network to extract the plagiarism patterns of contiguous text segments. The experimental results on PAN 2013 and PAN 2014 plagiarism source retrieval corpus show that PMCNN boosts the performance of source retrieval significantly, outperforming other state-of-the-art document models.