Reviewerly/exHarmony huggingface dataset:
The phenomenon of pathostreaming and pathological content in the face of media policy

Pathological online communication behaviours and their detrimental effects have remained a significant component of Internet research ever since it became a field of study in media science. It is safe to say that, in addition to the valuable content posted on social media, one can also find content that can be threatening given the media reality of today’s online audience. In the author’s opinion, pathostreaming and pathological content should certainly be considered as such. Pathostreaming is a new phenomenon in the media space, which involves posting of online recordings or images containing obscene, vulgar and sexual content, as well as, spreading hate speech on various digital platforms. Its peculiarity has contributed to the emergence of new media entities – the pathostreamer, the pathoinfluencer and the pathouser. The author of this article attempts to analyse the activities of obscene content creators and their viewers using content analysis and interviews. The paper’s goals are to demonstrate the phenomenon of pathostreaming as the risk of social pathologies being transmitted into the online space and to outline media policy towards this media problem.
РОЗРОБКА ВЕБ-ДОДАТКІВ ТА СЕРВІСІВ НА ПЛАТФОРМІ NODE.JS

The work provides an overview of distance learning systems, highlights their positive and negative sides, and also describes the theory and practical application of the Node.js platform. Functionality requirements for the developed software are formulated. A description of design solutions, tools and approaches to the development of software for a remote task system in the form of a telegram service for viewing the schedule has been made. Designed and developed a Telegram bot for viewing the schedule of classes as a separate service. The implementation of the schedule viewing service through the Telegram bot includes the development of both the Telegram bot service and the server logic of the distance learning system. After the user has been authorized in the system, he should have access to the Telegram bot, with the help of which he will be able to view the schedule by his own groups. In order to start working with the Telegram bot, the user must go to the settings of his account in the system, where there should be a button to connect to the Telegram bot, after clicking which a transition should be made to the page with the Telegram bot for further authorization of the user in him After successful authorization, the Telegram bot provides access to the main menu keyboard, where there are three buttons: “Schedule for today”, “Schedule for tomorrow” and “Schedule for a week”. After pressing the “Schedule for the hour” button, the telegram bot should send the schedule for today for all courses of the user, according to the name, and in the case of clicking the button “Schedule for tomorrow”, also in both cases there should be a keyboard under the message about the schedule, which will allow you to switch between days. In turn, after pressing the “Schedule for the week” button, the schedule for the current week should be sent, and it is also possible to switch to the next or previous weeks using the arrows at the bottom of the message. If there is no schedule or it cannot be obtained, the Telegram bot should report that there is no schedule. The developed software of the distance learning system is placed on the host service, users can access it at any time. The developed system is the result of the automation of the educational process in a remote form. That is why it covers the basic needs of students and teachers in the educational process. The results of the development were implemented in the initial process of the Poltava University of Economics and Trade.
The development of university students’ self-organization with remote tutor support

The article studies remote tutoring as a possible resource for the development of selforganization components of university students. The concepts were given and revealed: selfrealization, support, tutoring, individualization, as well as methodological features were identified and the concept of remote tutor support was derived. It is concluded that self-determination, selforganization of university students is the subject of a tutor's work. Modern technologies, new social tools offer students access to knowledge, as well as the ability to interact with peers in the context of learning. Remote tracking has additional advantages: synchronicity and asynchrony; effective access to information; reducing social distance; open redundant educational environment.
Research Significance of Reversible Data Hiding in Encrypted Domain under Cloud Technology

Reversible data hiding in encrypted domain, which combines encryption technology and data hiding technology, can not only realize privacy protection of data content on open channel, but also realize reversible embedding of information, which is of great significance to meet the increasingly complex application requirements in the cloud era.This paper mainly discusses the research significance of reversible data hiding in encrypted domain from four application scenarios: encrypted data management, covert communication of intelligence, military cooperative operation, and technology fusion innovation.
Construction of Financial Data Supervision Mode Based on Blockchain Technology

To address the issues of low system throughput and poor financial data sharing in traditional enterprise financial data management systems, a financial data supervision model based on blockchain technology is proposed.This model utilizes Internet of Things (IoT) technology to establish a data sharing system consisting of a perception layer, network layer, data layer, and application layer.The RESTful architecture of REST information sharing services (ROA) is chosen to provide the sharing services for the system.The system collects enterprise financial data using sensing devices, and the collected data is transmitted to the data layer through a gateway composed of certificate management, data reception, and Fabric SDK.The data layer preprocesses the collected data for storage and sharing, while ensuring the security of data storage and sharing within the system through decentralized blockchain technology.The design of the enterprise financial data sharing system is completed.The testing results indicate that the designed system enables effective sharing of financial data and improves the performance of the financial data management system.
A Cloud Computing Task Scheduling Method Based on Genetic Algorithm

ANSTRACT:In order to solve the traditional Internet service ability and expanding an acute shortage of, cloud computing has come into being, and has universal service in today's Internet services.Due to the huge scale of cloud computing and the diversity of applications and tasks, the performance requirements of cloud computing have been significantly improved.The characteristics of cloud computing brings the challenge of task scheduling, affect the performance and reliability of the system.To solve these problems, this paper puts forward cloud computing task scheduling algorithm based on genetic algorithm method.Firstly, the model of task and cloud computing resources and the objective function were established.Then, based on the task and cloud resource model, the gene genetic algorithm for task scheduling was proposed.Finally, through the experiment show that the algorithm has good results on the cloud resource scheduling, can reduce the total cost of users, to reduce the energy consumption.
Visual Analysis of Computer Hot Technology Based on CSDN

With the progress of information technology, there are more and more data on the Internet.How to make good use of these massive data and dig out useful values has become a topic that many researchers are studying.In this paper, massive data of CSDN Q&A are collected, and Python's powerful third-party libraries are used to visually analyze hot technologies, their development trends and technical categories.Scikit-Learn library is used for machine learning, and random forest regression algorithm is used to train hot technology prediction modules, optimize parameters and make predictions.Based on the research above, this paper finds that the computer technology will be further common, and the skills that programmers need will also increase.
Design and Implementation of Enterprise Financial Management Information System Based on Internet

In order to improve the accuracy and precision of enterprise financial management information, this paper puts forward a design method of enterprise financial management information system based on Internet.This paper analyzes and expounds the requirements of financial management information system of electric power enterprises; Under the guidance of the design idea and scheme of electric power enterprise management information system, the overall structure and data flow of electric power enterprise management information system are analyzed and described, and the business framework and organizational structure of electric power enterprise financial management information system are designed in detail.Finally, the full text is summarized, and the follow-up ideas of financial management information system of electric power enterprises are put forward.
Financial Prediction Model Based on Data Mining Technology

It is difficult for traditional audit methods to find various financial problems hidden in massive data.With interdisciplinary thinking, this paper uses data mining technology, fault diagnosis theory based on expert knowledge and financial audit theory, and uses data mining technology in financial forecasting to build three single financial models, namely, BP neural network, support vector machine and random forest model, Through experimental analysis, the most suitable model for use in financial auditing and the support vector machine model have been identified, which can improve efficiency and reduce risks for future financial auditing work.
Simulating primary visual cortex to improve robustness of CNN neural network structures

Abstract： The robustness of convolutional neural network (CNN) models is usually improved by deepen• ing the number of network layers to ensure the accuracy of the results.However， increasing the number of network layers will make the network more complex and occupy more space.This paper proposes an im •
Achieving Higher Quality Levels for Information Systems Project Management

This paper aims to achieve higher quality levels for information systems project management through proposing a quality assurance model for Information Systems Projects Management (IS-PM). This paper presents important quality concepts and fundamentals related to IS-PM. In addition, it presents the life cycle, phases, and activities of IS-PM. Depending on the proposed steps and a combination of statistical techniques, this paper introduces a proposed quality assurance model for IS-PM activities. This proposed model can be used for building a software tool for the quality assurance of IS-PM.
Multi-Hop Knowledge Graph Reasoning in Few-Shot Scenarios

Reinforcement learning (RL)-based multi-hop reasoning has become an interpretable way for knowledge graph reasoning owing to its persuasive explanations for the predicted results, but the reasoning performance of these methods drops significantly over few-shot relations (only contain few triplets). To address this problem, recent studies introduce meta-learning into RL-based reasoning methods. However, the performance of these studies is still limited due to the following points: (1) the overall reasoning accuracy is impaired due to the low reasoning accuracies over some hard relations; (2) the reasoning process becomes laborious and ineffective owing to the existence of noisy data; (3) the generalizability is negatively affected due to the lack of knowledge-sharing. To tackle these challenges, we propose a novel model <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HMLS</b> consisting of two modules <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HHML</b> ( <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</b> ierarchical <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</b> ardness-aware <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</b> eta-reinforcement <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</b> earning) and <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HHS</b> ( <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</b> ierarchical <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</b> ardness-aware <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</b> ampling). Specifically, <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HHML</b> contains the following two components: (1) a hardness-aware RL conducts multi-hop reasoning by training hardness-aware batches and reducing noise; (2) a knowledge-sharing meta-learning adapts to few-shot relations by exploiting common features in the hierarchical relation structure. The other module <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HHS</b> generates hardness-aware batches from relation and relation-cluster levels. The experimental results demonstrate that this work notably outperforms the state-of-the-art approaches in few-shot scenarios.
Accelerating GNN Training by Adapting Large Graphs to Distributed Heterogeneous Architectures

Graph neural networks (GNNs) have been successfully applied to many important application domains on graph data. As graphs become increasingly large, existing GNN training frameworks typically use mini-batch sampling during feature aggregation to lower resource burdens, which unfortunately suffer from long memory accessing latency and inefficient data transfer of vertex features from CPU to GPU. This paper proposes 2PGraph, a system that addresses these limitations of mini-batch sampling and feature aggregation and supports fast and efficient single-GPU and distributed GNN training. First, 2PGraph presents a locality awareness GNN-training scheduling method that schedules the vertices based on the locality of the graph topology, significantly accelerating the sampling and aggregation, improving the data locality of vertex access, and limiting the range of neighborhood expansion. Second, 2PGraph proposes a GNN-layer-aware feature caching method on available GPU resources with a hit rate up to 100%, which avoids redundant data transfer between CPU and GPU. Third, 2PGraph presents a self-dependence cluster-based graph partition method, achieving high sampling and cache efficiency for distributed environments. Experimental results on real-world graph datasets show that 2PGraph reduces memory access latency by up to 90% mini-batch sampling, and data transfer time by up to 99%. For distributed GNN training over an 8-GPU cluster, 2PGraph achieves up to 8.7× performance speedup over state-of-the-art approaches.
Pemanfaatan Sistem Klasifikasi dan Selving Bahan Pustaka: Upaya Memenuhi Temu Kembali Informasi di Perpustakaan Politeknik Negeri Sriwijaya

This article discusses the Utilization of an Effective Classification and Shelving System for Library Materials in Meeting Information Retrieval Needs at UPT. Sriwijaya State Polytechnic Library. The purpose of this study was to determine the use of a classification system and an effective shelving of library materials in meeting the needs of information retrieval at UPT. Sriwijaya State Polytechnic Library and how effective the use of alphabetical shelving is to facilitate the information retrieval system. The research method in this article is a type of qualitative descriptive research. Qualitative descriptive research is research that aims to describe a situation or event in the way it is. The result of the analysis in this article is the determination of the classification number based on the subject and the predetermined chart. If you can analyze the subject correctly and can follow the instructions on the classification chart, you are expected to get the right subject and get the right notation. So that the placement of library materials on the shelves in the correct position and the information retrieval system along with the process of searching or searching for information is easy to do quickly and precisely. Shelving process carried out at UPT. The Sriwijaya State Polytechnic Library for general works refers to the classification number on a regular basis and is matched with the classification number provided on each bookshelf.
An Interactive Preposition Game to Improve the Usage of Preposition of Place Among Grade 4 Students

The purpose of this research was to enhance students' grasp of grammar, focusing particularly on prepositions of place, by utilizing the Interactive Preposition Game (IPG) as a method for teaching and learning.. The study involved fourth-grade students from an elementary school as participants, with the researcher who carried out the action research in the classroom also serving as the teacher. The intervention cycle was executed a single time. The gathered information consisted of tests, along with interviews, and the teacher's reflective journal. The data revealed progress, as evidenced by a rise in average scores from the second test (25%) to the first test (82%). Furthermore, it was discovered that the Interactive Preposition Game (IPG) was able to improve students' comprehension, motivation, and foster an enjoyable learning atmosphere within the classroom. The study's outcomes revealed that the students exhibited favorable behaviors and reactions when the Interactive Preposition Game (IPG) was employed as a tool for learning grammar.
EMPIRICAL STUDY OF FEATURE EXTRACTION APPROACHES FOR IMAGE CAPTIONING IN VIETNAMESE

Image captioning is a challenging task that is still being addressed in the 2020s. The problem has the input as an image, and the output is the generated caption that describes the context of the input image. In this study, I focus on the image captioning problem in Vietnamese. In detail, I present the empirical study of feature extraction approaches using current state-of-the-art object detection methods to represent the images in the model space. Each type of feature is trained with the Transformer-based captioning model. I investigate the effectiveness of different feature types on two Vietnamese datasets: UIT-ViIC and VieCap4H, the two standard benchmark datasets. The experimental results show crucial insight into the feature extraction task for image captioning in Vietnamese.
Bindings Summer/Fall 2022

Past, present, and future. This issue of BINDINGS reflects on the University of Iowa’s 179th anniversary celebration, including an exhibit at the Main Library Gallery titled “We Are Hawkeyes.”Also in this issue: news about Libraries staff accomplishments and updates on grant funding that will support efforts of the Libraries’ Iowa Women’s Archives, Sackner Archive, and Hardin Library for the Health Sciences.
Perancangan Sistem Jurnal Online Berbasis Android di Perpustakaan

The development of information technology allows the development of an innovative library service system, one of which is the development of a journal management system. Research purposes to develop an android-based online journal system in library. The research method uses a prototype system development method with five stages. The results of this study succeeded in developing an android-based online journal system with several search, submit and review journal features. The results of the system testing show that the web design is attractive to users with a score of 4.0; realibility is good enough to get a mean of 3.0; (c) Responsiness is quite good with a score of 3.0; security 3.0 the system's ability to maintain user data security is good enough; Functionality is quite good with 3.0; Attractivess is very interested in the 5.0 score; Personalization 3.0, this shows that the availability of information to ask questions is good enough.
Rancang Bangun Perpustakaan Buku Digital (E-Book) Berbasis Web

One of the efforts to improve the quality of human resources is to foster interest and reading habits. For this reason, the library is expected to become a center for activities that foster interest and reading habits. Libraries have a great responsibility to increase and develop interest and enthusiasm for reading. Information and communication technology (ICT) has become a part of human life today. Therefore, all institutions are competing in the integration of ICT to build and strengthen their knowledge-based talents, to be able to compete in the global era. The need for information technology (IT) is closely related to the role of libraries as a driving force in the preservation and dissemination of scientific information, which develops along with people's activities of writing, printing, educating, and meeting their information needs. The writing of this study uses the descriptive qualitative method and STMIK Pringsewu as the object of the study. The Web-Based Digital Book Library is designed to be easily accessible to readers. Uploaded e-books are created in PDF format. The digital library system can only be accessed locally in the STMIK Pringsewu environment.
Pengaruh Media Sosial Instagram Terhadap Minat Baca Masyarakat (Studi Kasus di Akun @KOMUNITASPEMBACABUKU)

This research is entitled The Effect of Instagram Social Media on People's Reading Interest (Case Study on the @komunitaspembacabuku account). The purpose of this study was to find out how the influence of Instagram social media on reading interest in the case study community on the Instagram account @komunitaspembacabuku. The method used in this research is a quantitative method with the type of case study research. Data collection techniques using questionnaires, observation, and documentation. The population in this study amounted to 24,300 followers with a sample of 100 respondents. Based on the results of data analysis, it can be seen that there is a simultaneous positive and significant effect between Instagram social media on people's reading interest (a case study on the Instagram account @komunitaspembacabuku) with a calculated f value of 53.474 3.938 or (f count ftable) so that Ho is rejected and Ha accepted. based on the coefficient of determination of the Instagram social media variable (X) it affects people's reading interest (Y) by 35% while the remaining 65% is influenced by other factors not examined in this study.
Persepsi Guru SMA Negeri 1 Kotaagung Terhadap Literasi Digital di Masa COvid 19

The Corona Virus Diseases 19 (COVID-19) pandemic causes uncertainty, many educational institutions are unable to carry out face-to-face learning processes due to the impact of distance restrictions. Advances in communication and information technology in the world of education, one of the supporters of educators in developing learning media, utilizes the e-learning system to increase the flexibility of learning and teaching. By using digital literacy, learning media can be easily accessed anytime and anywhere. The use of computers and smartphones proves that SMAN 1 Kotaagung (Public Senior High School 1 Kotaagung) has started using digital literacy in the teaching and learning process as well as when looking for sources of learning materials, such as text, images, and video teaching materials that are carried out by both teachers and students.