Reviewerly/exHarmony huggingface dataset:
Metasystem organization of subject determinants of professional activity

Theoretical-methodological and empirical-experimental materials are presented that reveal and explain the specifics of the organization of the most important category of subjective determinants of labor activity - professional competencies. It is shown that its main principle is the principle of metasystem organization. From these positions, a new solution is given to the key problem of the psychology of activity - the problem of the correlation of two main classes of professional competencies, denoted by the concepts of «hard» and «soft» skills (hard-skills and soft-skills). The formulated theoretical provisions are concretized in relation to the tasks of psychological analysis of one of the most significant and decisive types of professional activity in the structure of the modern division of labor - information, implemented on the basis of computer technologies.
Firewall guidelines and policies

Information systems must be protected by firewalls, which are designed to control traffic flowing between private andpublic networks, allowing and denying requests made by the different networks in order to protect them from threats. Thereare different types of firewalls that are used depending on the filtering techniques to be implemented, according to the TCP/IP protocol stack, they can work at network, transport and application level. A good firewall policy design strengthensnetwork security by controlling certain types of data traffic.
Methodology for the Study of Meteorological Information Distribution between Regions

In this work a network is studied, the nodes being the regions between which it is necessary to distribute meteorological information coming from its source. The subject of the study is weather stations (the main components of the network) and meteorological information produced by them. Any weather stations are complex techno-economic systems, which are conjoined by the need to supply them with the main resource for the meteorological information production and the need for its distribution. The authors developed a model of the meteorological information distribution between the regions with certain conditions based on the model of obtaining, distributing and transmitting meteorological information in a general form. Using the model, based on the initial data, it is possible to decide how to distribute the produced meteorological information between the regions so as to maximize the profit of weather stations. The described model includes a sub-task solution. The purpose of the model study is to maximize profit based on the initial data.
Chaos Prediction of Power Systems by Using Deep Learning

Ensuring the stability of power systems is an important issue that should be considered in order to ensure the social and economic development of a country. Therefore, predicting the chaotic behavior of power systems in order to develop protection measures and keep power systems stable is vital. In this paper, a deep learning algorithm was proposed to predict the chaotic behavior of power systems by using deep long short-term memory (DLSTM) networks, which have two forms: deep long short-term memory with static scenario (DLSTM-s) and deep long-term memory with dynamic scenario (DLSTM-d). The genetic algorithm was used to optimize the hyperparameters of the networks. Then, taking interconnected power systems as an example, the effectiveness of the proposed DLSTM network was verified via numerical simulation. Finally, the experimental results of the DLSTM network were compared with those of the echo state network, multi-recurrent neural network, deep gated recurrent unit, and long short-term memory. Experimental results illustrated that a trained DLSTM network can predict the chaotic behavior of power systems by using the time series data of a single state variable. Moreover, the DLSTM-s network proposed in this paper can achieve competitive prediction performance compared with other baseline methods.
Cloud computing in technical and social perspective view

The term cloud computing is a recent buzzword in the IT world. Behind this fancy poetic phrase there lies a true picture of the future of Computing for both in technical perspective and social perspective. Though the term \Cloud Computing" is recent but the idea of centralizing computation and storage in distributed data centers maintained by third party companies is not new but it came in way back in 1990s along with distributed computing approaches like grid computing.
基於深度學習之改良式多功能影像編碼快速畫面內模式決策研究

&lt;p&gt;H.266/Versatile Video Coding (VVC) 是針對 4K 以上的超高畫質影片，且能適用在高動態範圍(High Dynamic Range Imaging, HDR)及廣色域(wide color gamut, WCG)中，但基於四元樹加二元樹(Quadtree plus Binary Tree, QTBT)的編碼單元(Coding Unit, CU)結構增加了 H.266/VVC 編碼的計算複雜性。本論文提出了一種基於深度學習之改良式多功能影像編碼快速畫面內模式決策方法，減少 H.266/VVC 內編碼複雜性以加快H.266/VVC 的編碼速度，並將畫面內影像編碼結合卷積神經網路(Convolutional Neural Networks, CNN)在 H.266/VVC 畫面內編碼的模式預測決策，以達到比原始編碼方式(JEM7.0)更好的編碼效能。&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;H.266/VVC is ultra-high-definition video over 4K, and can be applied in High Dynamic Range Imaging (HDR) and wide color gamut (WCG). However, it has high coding computational complexity based on the coding unit (CU) structure of a quadtree plus binary tree (QTBT). This plan first proposes a fast coding unit spatial features decision method to reduce the coding complexity in H.266/VVC such that the H.266/VVC coding can be speed up. Another important contribution of this plan is to combine video coding with Convolutional Neural Networks (CNNs) in H.266/VVC in-frame coding mode prediction decision. It can be shown that the proposed methods can achieve better encoding performance than the original encoding method (JEM7.0).&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Bounding Puzzles

This chapter introduces the Indicative and Subjunctive Bounding Puzzles, showing the central tension they reveal in the role played by these conditionals in our cognitive lives.
Anomaly detection of industrial control systems based on transfer learning

Industrial Control Systems (ICSs) are the lifeline of a country. Therefore, the anomaly detection of ICS traffic is an important endeavor. This paper proposes a model based on a deep residual Convolution Neural Network (CNN) to prevent gradient explosion or gradient disappearance and guarantee accuracy. The developed methodology addresses two limitations: most traditional machine learning methods can only detect known network attacks and deep learning algorithms require a long time to train. The utilization of transfer learning under the modification of the existing residual CNN structure guarantees the detection of unknown attacks. One-dimensional ICS flow data are converted into two-dimensional grayscale images to take full advantage of the features of CNN. Results show that the proposed method achieves a high score and solves the time problem associated with deep learning model training. The model can give reliable predictions for unknown or differently distributed abnormal data through short-term training. Thus, the proposed model ensures the safety of ICSs and verifies the feasibility of transfer learning for ICS anomaly detection.&#x0D;
Perceptual Reference Requires Perceptual Attribution

Chapter 5 argues in detail that perceptual reference is always guided by perceptual attribution, and that, in the case of every successful perceptual reference (perception of something), at least one perceptual attributive is accurate of the referent. The arguments are taken to be apriori. Discrimination that occurs in perceptual representation differs from other types of discrimination. Attempts to maintain that perceptual reference occurs without there being any accurate perceptual attribution to the referent are shown to be confused.
Academism in the Assessments of Professors of Classical Universities

The article presents the results of an empirical study of academism in the assessments of professors of Russian classical universities. In total, 50 experts from various universities of Russia took part in the online survey. The aim of the study was to assess the role of academism in the development of university, maintaining the quality of education and maintaining the authority of professors at the university. The article gives a definition of the concept of academism, and reveals its structure. Basically, academism represents academic freedoms and the intellectual potential of the individual. The main results of the study include the following provisions: 1) academism is an integral part of a modern university and influences the formation of relevant values and traditions of university life; 2) academism influences the quality of students’ education, the preservation of high requirements in the educational process; 3) academism determines the authority of professors and teachers, promotes their active involvement in the social and cultural life of the university.
Object Detection Technique Using a Fast R-CNN Based Technique

Abstract: Object detection stands as the current interest in locating the objects. Reducing the run time of the algorithms holds a challenge in this field. Deep Convolutional Neural Network (CNN) like SPPnet, Fast R-CNN etc. had been effectively proposed to reduce the execution time. Encouraged by these networks, a Region Program Network (RPN) has been proposed here to portray features of images with less computational cost and time. This network is capable of predicting the bounds of an object and generates scores at each position. In the proposed network, Fast R-CNN is also integrated with RPN so that exceptional region programs can be generated, and entire network can easily understand which area should be focused. The proposed network has been tested on MS COCO, PASCAL VOC 2007, 2012 datasets. Results infer that the proposed RPN along with Fast R-CNN outperforms some popular models like deep VGG-16 [3], ImageNet, YOLO etc. in terms of all the accuracy parameters.
Pratiche di stesura della tesi di laurea in italiano LS

In the Italian academic discourse research, Master’s degree theses used to be studied mainly from the perspective of linguistic competencies of their authors. However, strictly linguistic skills are not the only challenge for undergraduate, who must also convey intellectual content in appropriate discursive and rhetorical forms. The paper explores the patterns of a peculiar form of “collaborative writing”, i.e. the cooperation between the thesis supervisor and the student. Using the example of Master’s theses in lin- guistics, written in Italian as a foreign language, three basic didactic approaches are discussed in the paper. In the didactics of content the supervisors emphasize knowledge, i.e. linguistic concepts expected to be applied in a Master’s thesis. In the didactics of forms, the supervisors focus on the linguistic code, that is, on grammatical and lexical correctness of the Master’s thesis. In the didactics of forms of content the supervisors use regularities observed in academic discourse, such as genre and rhetorical structures, as valuable teaching resources likely to help students develop metacommunicative awareness.
PR-SZZ: How pull requests can support the tracing of defects in software  repositories

The SZZ algorithm represents a standard way to identify bug fixing commits as well as inducing counterparts. It forms the basis for data sets used in numerous empirical studies. Since its creation, multiple extensions have been proposed to enhance its performance. For historical reasons, related work relies on commit messages to map bug tickets to possibly related code with no additional data used to trace inducing commits from these fixes. Therefore, we present an updated version of SZZ utilizing pull requests, which are widely adopted today. We evaluate our approach in comparison to existing SZZ variants by conducting experiments and analyzing the usage of pull requests, inner commits, and merge strategies. We base our results on 6 open-source projects with more than 50k commits and 35k pull requests. With respect to bug fixing commits, on average 18% of bug tickets can be additionally mapped to a fixing commit, resulting in an overall F-score of 0.75, an improvement of 40 percentage points. By selecting an inducing commit, we manage to reduce the false-positives and increase precision by on average 16 percentage points in comparison to existing approaches.
Collaborative Writing Workflows in the Data-Driven Classroom: A Conversation Starter

To paraphrase John Tukey, the beauty of working with data is that you get to “play in everyone’s backyard.” A corollary to this statement is that working with data necessitates collaboration. Although students often learn technical workflows to wrangle and analyze data, these workflows may break down or require adjustment to accommodate the different stages of the writing process when it is time to face the communication phase of the project. In this article, I propose two writing workflows for use by students in a final-project setting. One workflow involves version control and aims to minimize the chance of a merge conflict throughout the writing process, and the other aims to add some level of reproducibility to a Google-Doc-heavy writing workflow (i.e., avoid manual copying and pasting). Both rely on a division of the labor, require a plan (and structure) to be created and followed by members of a team, and involve communication outside of the final report document itself. This article does not aim to solve all collaborative writing pain points but instead aims to start the conversation on how to explicitly teach students not only how to code collaboratively but to write collaboratively.
REDES NEURAIS ARTIFICIAIS PARA ESTIMATIVA DA CARGA TÉRMICA RADIANTE NO INTERIOR DE GALPÕES

Are UPOV descriptors a useful and feasible tool?.Acta horticulturae, (
How Online Information Sources Affects Law Enforcement Perceptions

practices are still adapting to the internet. One stumbling block to adapting policing research and practice to the internet is a limited understanding of the various online information sources affecting law enforcement and security. The internet is an information technology. Many laws governing information and crime developed under assumptions about information that may no longer hold. Incorrect assumptions about information can frustrate police and criminologists as they work to apply existing, otherwise valid, theories and practices in the new information environment. Legal systems and law enforcement need to adapt their extant laws and policing practices to the internet’s novel information topography
The Emergence of Decentralized Business Models: Blockchain Interruption and Decentralized Finance

Abstract: Blockchain technology has the ability to lower transaction costs, build distributed trust, and empower decentralised platforms, providing a foundation for new decentralised business models. Blockchain technology enables the growth of decentralised financial services in the financial industry, which are more decentralised, inventive, compatible, borderless, and transparent. Decentralized financial services, driven by blockchain technology, have the potential to expand financial inclusion, allow open access, stimulate permissionless innovation, and open new doors for entrepreneurs and innovators. In this paper, we examine the advantages of decentralised finance, as well as existing business models, obstacles, and limitations. Decentralized finance, as a new area of financial technology, has the potential to transform current finance and provide a new landscape for entrepreneurship and creativity, exhibiting the benefits and drawbacks of decentralised business models
Research on Handwritten Chinese Character Recognition Based on BP Neural Network

The application of pattern recognition technology enables us to solve various human-computer interaction problems that were difficult to solve before. Handwritten Chinese character recognition, as a hot research object in image pattern recognition, has many applications in people’s daily life, and more and more scholars are beginning to study off-line handwritten Chinese character recognition. This paper mainly studies the recognition of handwritten Chinese characters by BP (Back Propagation) neural network. Establish a handwritten Chinese character recognition model based on BP neural network, and then verify the accuracy and feasibility of the neural network through GUI (Graphical User Interface) model established by Matlab. This paper mainly includes the following aspects: Firstly, the preprocessing process of handwritten Chinese character recognition in this paper is analyzed. Among them, image preprocessing mainly includes six processes: graying, binarization, smoothing and denoising, character segmentation, histogram equalization and normalization. Secondly, through the comparative selection of feature extraction methods for handwritten Chinese characters, and through the comparative analysis of the results of three different feature extraction methods, the most suitable feature extraction method for this paper is found. Finally, it is the application of BP neural network in handwritten Chinese character recognition. The establishment, training process and parameter selection of BP neural network are described in detail. The simulation software platform chosen in this paper is Matlab, and the sample images are used to train BP neural network to verify the feasibility of Chinese character recognition. Design the GUI interface of human-computer interaction based on Matlab, show the process and results of handwritten Chinese character recognition, and analyze the experimental results.
The Problem of Existence of Virtual Objects

I considered the problem of existence of virtual objects, mainly the mode of existence of these objects, while I omitted the issue of the criteria of their existence. I present a brief exposition of alternative the concepts of modes (forms, kinds) of existence of virtual objects proposed in the literature on the subject, and then I demonstrate my position on this issue.
THE UTILIZATION RATE OF THE LIBRARY SCIENCE STUDY PROGRAM’S E-JOURNAL "KHIZANAH AL-HIKMAH" DURING COVID-19 PANDEMIC BY THE STUDENTS OF THE LIBRARY SCIENCE DEPARTMENT AT UIN ALAUDDIN MAKASSAR

The main problem in this study is how much is the utilization rate of the e-journal of the library science study program "khizanah al-hikmah" during the covid-19 pandemic by students of the library science department at UIN Alauddin Makassar. The main problem is further described into several sub-problems, including: How high is the frequency of use of the e-journal of the Library science study program "Khizanah al-hikmah" by students majoring in library science at UIN Alauddin Makassar and what factors influence and the rate of utilization by students majoring in library science at UIN Alauddin Makassar. In this study, the researcher used a descriptive type of research with a quantitative approach, which is a method that uses data in the form of numeric numbers. In this study, the population was all active students majoring in library science in all classes, namely 620 people. The sample in this study was 32% of the population, while 32% of 620 was 198. So the number of respondents in this study was 198 students. Based on the study results, 68.7% of the students knew about the existence of library science e-journals, and 31.3% did not know about library science e-journals. As for the utilization rate of the khizanah al-hikmah e-journal from a total of 68.7% of students who responded to the end or 145 students of a total of 198 respondents, it shows the data used by students of the Library Science study program was 90.1% or was in very high category. As for the rate of utilization of each indicator, that is a factor of utilization by students; on average, it is in the high category.
Meta-Labeling: Theory and Framework

Meta-labeling is a machine learning (ML) layer that sits on top of a base primary strategy to help size positions, filter out false-positive signals, and improve metrics such as the Sharpe ratio and maximum drawdown. This article consolidates the knowledge of several publications into a single work, providing practitioners with a clear framework to support the application of meta-labeling to investment strategies. The relationships between binary classification metrics and strategy performance are explained, alongside answers to many frequently asked questions regarding the technique. The author also deconstructs meta-labeling into three components, using a controlled experiment to show how each component helps to improve strategy metrics and what types of features should be considered in the model specification phase.
The Egyptian Policeman jurisdictions in cyber crime

The original terms of reference of the Egyptian Police in cybercrimes are represented in receiving reports and complaints, examining the crime scene, taking fingerprints and editing the record, listening to witness statements, preserving the tools used in cybercrimes in normal circumstances, in addition to giving the legislator police officers exceptional powers to initiate certain procedures in cybercrimes including arresting the accused without permission. Inspection, seizure, and scarring for the investigation of cybercrimes, through this research paper will discuss all these original and exceptional terms of reference.
The Case Studies as an Efficient Method for the Formation of Students’ Multicultural Competence

The article describes the features of students’ multicultural competence formation with the case study method. Presented an analysis of modern psychological and pedagogical approaches in teaching English of students. Described concepts and types of case technologies used in teaching English. Analyzed the system of work in teaching English-speaking high school students by means of situational tasks. Stressed, that Case technology solves complex of some problems: develops communication skills, helps to establish emotional contacts between students; solves the content and information problem, as they provide students with the necessary information, without which it is impossible to carry out joint activities; develops special skills of critical thinking (analysis, synthesis, goal setting etc.), provides solutions to educational problems, a learning task, as students are taught to work in a team, listen to other people's opinions. Analyzed methodological recommendations, techniques, methods and pedagogical conditions of students' work with case technology in the process of learning English speaking helped to expand the range of speech genres, including appeals, requests, explanations and more. Explained students skills of talking to an opponent, colleagues, presentation speech, dialogue monologue and more as multicultural competence.