Reviewerly/exHarmony huggingface dataset:
DESAIN MODUL LAPORAN KEUANGAN UNTUK MENINGKATKAN HASIL BELAJAR KOGNISI SISWA KELAS X PERBANKAN SYARIAH DI SMK MUHAMMADIYAH KOTA CIREBON

The research purpose is (1) to arrange or Design learning material of financial statement in a modul. (2) To know implementation process of financial statement module in learning process, and (3) To know improvement of student’s score on accounting subject, especially on financial statement. Subject of this report is accounting class X in SMK Muhammadiyah Cirebon school year 2018/2019 consist of 36 student.Technique of collecting data in this research in unstructured interview, observation, documentation, questionnaire , and test which is analysed by descriptive quantitative and qualitative method. The research result is (1) Designing financial statement module based on research design model 4D that modified into 3D. Define, students need learning materials that can improve their study result. Design, learning materials based on what student needed, it is a financial statement module. Develope, financial statement module that proper with notability average 3,94 through validation by the experts, revise as their criticism and a trial using on X accounting class. (2)Implementation of financial statement module STAD and allocation of 7 lesson hours for three times meeting. (3) Study result are improve significantly based on analysis and wilcoxon trial, average pretest 46,50 and posttest 80,54 with 34,04 improvement, and z= -5,232 sig. 0,000 &lt; 0,05 that showed the improvement of study result between pretest into posttest.
Library History as a Current Topic of Scholarly Discourse

On 23—24 May 2023 the Russian State Library (RSL) hosted the International Scientific and Practical Conference “History of Libraries: New Approaches, Methods, Sources, Results” in a face-to-face format. It was organized by RSL and the Russian Library Association. The aim of the event was to contribute to the development of research work in the field of library history. The conference brought together over 200 representatives of public, academic, higher education and school libraries, institutes of culture, institutes of the Russian Academy of Science and other cultural, education and science institutions from seven CIS countries, including Azerbaijan, Armenia, Belarus, Kazakhstan, Kirgizia, Uzbekistan and 44 Russian regions. According to the results of online broadcasting of the sessions, organised on the YouTube channel of RSL, more than 1280 views were recorded. The conference program included plenary and breakout sessions (“Library as an Object of Historical and Library Studies”, “Library Biography as a Field of Historical and Library Studies”, “History of a Single Library”, “Current State and Prospects of Research in the Field of Library History”). A special conference session was dedicated to the study of library’s history during the Great Patriotic War (1941—1945). A total of 53 reports were presented by full-time and distance participants from Azerbaijan, Belarus and 18 Russian regions. The reports of the Conference discussed the theoretical and methodological grounds for studying the history of libraries as an interdisciplinary scientific field; presented the experience and results of the research conducted both by the largest libraries — centers of library science (national and academic libraries, institutes of culture of Russia, Azerbaijan and Belarus) and other libraries of CIS member states (central regional, city, rural, university and museum libraries).
Grigory Alexandrovich Pushkin — an Employee of the State Library of the USSR Named after V.I. Lenin

The biography of Colonel Grigory Alexandrovich Pushkin (1868—1940), grandson of Alexander Pushkin, is reconstructed on the basis of unknown materials of the Manuscripts Department and the Archive of the Russian State Library (RSL). The article told about his service in the Imperial and Red Armies, his family and difficult financial situation after 1917. It is shown what bureaucratic difficulties accompanied the assignment of his personal pension in 1923 and subsequent assistance. Particular attention is paid to the solution of the housing problem and obtaining accommodation in Moscow. The Letters of G.A. Pushkin to G.P. Georgievsky (1919), V.D. Bonch-Bruevich (1933) and P.S. Popov (1933), are published in full for the first time, as well as letters from Yu.N. Pushkina to V.S. Nechaeva (1936) and from V.D. Bonch-Bruevich to G.A. Pushkin (1933), which are kept in the Manuscript Department of Russian State Library. Article restores the history of G.A. Pushkinʼs working at the State Library of the USSR named after V.I. Lenin based on the Personnel Files. From 1936 till 1938 he signed temporary employment contracts, while he worked on a permanent position only from January 1939 to January 1940. G.A. Pushkin’s biography is analyzed in the context of the social history of the Russian nobility after 1917 and its adaptation to the Soviet reality. The author concludes that the official persecution of the former elite promoted the appearance of the staff with wide knowledge, proficiency in foreign languages and organizational experience in the State Library of the USSR named after V.I. Lenin. They influenced the development of the library as a research center.
Analysis of needs for development of earthquake disaster mitigation animation videos for disabilities elementary school children

Earthquakes are frequent disasters in Indonesia. This disaster often causes many fatalities, so reducing the risk of an earthquake is necessary. Disaster risk reduction can be carried out with government programs, namely disaster risk reduction education which aims to reduce the threat of victims due to disasters. However, in implementing this program, there are deficiencies in media accessibility and learning media for elementary school children with disabilities. The purpose of this study was to describe the results of the needs analysis for the development of earthquake disaster mitigation animation videos. This research is a type of qualitative research. The data from this study were obtained from filling out a needs analysis questionnaire by 161 students and 121 teachers from 13 special schools in Klaten Regency, data analysis using interactive analysis. Based on the results of filling out the questionnaire to analyze the needs of students and teachers, it is known that students and teachers of SLB throughout Klaten Regency need an animated video on earthquake disaster mitigation to become one of the learning media. Students agree as much as 97.70%, and teachers agree as much as 99.20% to develop an animated earthquake disaster mitigation video. The development of earthquake disaster mitigation animation videos must follow the needs of students and teachers regarding material, language, presentation, and graphics.
Analisis Kemampuan Kognitif Siswa Sd Melalui Media Video Pembelajaran Youtube

In the current era, learning activities in schools require teachers to use innovative learning media, teachers in schools often use communication tools as a tool to assist learning activities in class, there are many learning media used by teachers, one of which is YouTube learning video media. With the existence of YouTube learning video media, it makes it easier students understand the material provided and can instill students' cognitive abilities on theme 6 (energy sources and changes) in class III. The purpose of this study was to describe and analyze students' cognitive abilities through the media of YouTube learning videos in class III SDN Gedangan. Researchers use descriptive qualitative research methods, with the type of case study research where researchers can understand and search for cases and look for these results. From the data on the cognitive ability test results of class III students at SDN Gedangan obtained the following scores: obtaining a score of 100 with a percentage of 38%, a score of 96 with a percentage of 41%, a score of 92 with a percentage of 15% and a score of 88 with a percentage of 5%. From the average student overall score data, it is known that the percentage is 96.42% of the overall score of students' cognitive ability test scores. Where this figure is included in the "very good" category. Based on the results of the study, it can be concluded that the use of YouTube learning video media can improve the cognitive abilities of class III students at SDN Gedangan.
Meningkatkan Kemampuan Membaca Intensif Dengan Metode Cooperative Integrated Reading Composition Pada Peserta Didik

The subjects of this study were 32 class VIII 9 students of SMP Negeri 2 Palangka Raya, consisting of 16 boys and 16 girls. The ability to read intensively to find main ideas using the Cooperative Integrated Reading and Composition method has been shown to increase. The results of the knowledge test on the initial conditions of the class average score from 70 rose to 79 in cycle I, then rose again to 84 in cycle II. Mastery learning results of the knowledge test, initial conditions of 10 students or 31% increased to 23 students or 72%, in cycle I. Cycle II increased again by 29 students or 91%. The results of the intensive reading skills test to find the main idea of the initial condition of the class average acquisition of 60 with completeness of 4 students or 13%. Cycle I average class of 76 with the number of students completing as much as 17 or 53%. Cycle II the average class score was 82 with the number of students completing 29 students or 91%. The positive behavior of students after participating in intensive reading skills learning to find the main ideas has also increased. Based on the results of observations of student behavior, the percentage of the first cycle was 51%, in the second cycle it increased to 81%. Big increase of 30%. The results of this study concluded that the Cooperative Integrated Reading and Composition method can improve intensive reading skills to find the main ideas in reading texts and positive behavior in student learning.
The Data Analysis of Determining Potential Flood-Prone Areas in DKI Jakarta Using Classification Model Approach

The study aims to analyze the flood data in the five Jakarta areas. The focus is to determine areas that are potentially prone to flooding. Currently, there is no identification of potential flood areas in Jakarta based on actual parameters such as total rainfall, altitude, and population density. Based on this problem, a data-driven method is applied using the C4.5 algorithm. Decision trees are used to assist the classification process in determining areas that have the potential to be prone to flooding have potential flooding in the DKI Jakarta area. The 10-fold cross validation is employed along with the confusion matrix to evaluate the model between the actual and predicted results. The study shows that this algorithm can model the Jakarta potential flood-prone areas with an accuracy value of 87.20% with precision and recall values of 90.62% and 94.84%. Based on the model, the predicted flooding area can be identified utilizing the parameters.
Evolução da gestão de riscos de ativos e facilities em um datacenter

This technical report aims to identify the additional benefits for managing the risks of assets and facilities in a datacenter through DCIM in a public company in the IT sector, without prejudice to performance and availability.Currently, said company has the ability to monitor its datacenter, but it does not meet the desired requirements.It is expected that with the implementation of monitoring tools it is possible to obtain a good practice of IT asset management, accelerating the process and security in decision making, allowing the management of monitoring in a virtual way and tracking the current and futures by barcode.
The Concept of Online Education After the Outbreak of COVID-19 And Its Influence on Education, Families, Students and Educators

COVID-19 has created numerous modifications to human life and altered people's outlooks on life.In this study, the effects of Corona on education, family life, students, and teachers were examined, and the findings were discussed.First, the concept of online education, which has become an integral part of our lives, was emphasized.The transition to online education's challenges and the overall studies on the subject were examined.During the second phase, the positive and negative effects and outcomes of the pandemic on family life were documented.In the final section, the impacts of education on educators and students, the two inseparable components of education, were underlined, and the obstacles encountered in this process, technical challenges, and disparities in education between urban and rural locations were studied.
Aspect-Based Sentiment Analysis: A Survey of Deep Learning Methods

The process of analyzing, processing, concluding, and inferring the sentiment of subjective texts is known as sentiment analysis (Shandilya et al. in Aspect-based sentiment analysis survey of deep-learning. IEEE [1]). Sentiment analysis is used by businesses to better understand their customers public opinion polling, market research, and brand evaluation reputation, comprehension of customer experiences, and social media research the media's influence. Depending on the various aspect requirements granularity is classified as positive, negative and neutral of the sentiment analysis. This article provides an overview of recently proposed methods for dealing with a sentiment analysis problem based on aspects (Liu et al. in Aspect-based sentiment analysis-a survey of deep learning methods. IEEE [2]). There are currently three popular approaches: deep learning, lexicon-based, and traditional machine learning methods.
U-Net based GAN with deformable convolution for CT image denoising

CT 영상에서 잡음 제거는 환자들의 방사선 피폭을 줄이면서 영상 판독 향상을 위해 중요한 기술이다. 본 논문에서는 딥러닝의 GAN (Generative Adversarial Networks) 기반 U-DeCGAN (U-Net Based GAN with Deformable Convolution) 모델을 이용하여 CT 영상에서 잡음 제거하고자 한다. GAN 모델은 두 개의 네트워크 즉, 생성자(generator)와 판별자 (discriminator)로 구성되어 있고 이 둘은 적대적 경쟁 관계에서 학습이 이루어진다. 제안된 U-DeCGAN 모델은 U-Net 구조의 생성자와 변형 가능한 컨볼루션 층(deformable convolution layer)을 갖고 있는 판별자로 구성되고, U-DeCGAN의 손실함수는 기존의 GAN 학습의 불안정을 완화하기 위해 GAN 손실 (adversarial loss)과 MSE 손실 (mean square error loss)의 가중한 형태이다. 본 논문에서 제안된 U-DeCGAN 모델의 성능 평가를 위해 여러 가지 잡음 즉, 가우시안 잡음 (Gaussian noise), 포아송 잡음 (Poisson noise), 그리고 스팩클 잡음 (speckle noise)에 의해 훼손된 CT 영상에서 기존의 BM3D 방법, DnCNN 모델, CDAE 모델, 그리고 U-Net GAN 모델과 비교하였다. 성능 실험 결과, 제안된 U-DeCGAN 모델은 정성적 평가와 더불어 PSNR (Peak Signal-to-Noise Ratio)과 SSIM (Structural Similarity Index Measure) 척도에 의한 정량적 평가에서 좋은 성능을 보였다.
<i>r</i>-primitive <i>k</i>-normal elements in arithmetic progressions over finite fields

AbstractLet Fqn be a finite field with qn elements. For a positive divisor r of qn−1, the element α∈Fqn* is called r-primitive if its multiplicative order is (qn−1)/r. Also, for a non-negative integer k, the element α∈Fqn is k-normal over Fq if gcd(αxn−1+αqxn−2+⋯+αqn−2x+αqn−1,xn−1) in Fqn[x] has degree k. In this paper we discuss the existence of elements in arithmetic progressions {α,α+β,α+2β,…α+(m−1)β}⊂Fqn with α+(i−1)β being ri-primitive and at least one of the elements in the arithmetic progression being k-normal over Fq. We obtain asymptotic results for general k,r1,…,rm and concrete results when k=ri=2 for i∈{1,…,m}.KEYWORDS: Arithmetic progressionsfinite fieldsk-normal elementr-primitive element2020 MATHEMATICS SUBJECT CLASSIFICATION: 12E2011T24 AcknowledgmentsThe authors would like to thank the referee for the careful reading and helpful comments that improved the presentation of the paper.Additional informationFundingThe authors were partially supported by FAPEMIG grant RED-00133-21, the second and fourth authors were partially supported by FAPEMIG grant APQ-02546-21, the third author was partially supported by FAPEMIG grant APQ-00470-22, and the fourth author was also partially supported by NAWI Graz Postdoctoral Program.
Kajian Kebijakan Keamanan Sistem Informasi Sebagai Bentuk Perlindungan Kerahasiaan Pribadi Karyawan Perusahaan BFI Finance

Technology that connects computers around the world makes it possible to exchange information and data and even communicate with each other in the form of images and videos. The more valuable information is, the more security standards are needed to protect that information. The goal of computer security, among others, is to protect information. The higher the security standards provided, the higher the privacy protection of information. Protection of employee privacy in a company is one of the factors that must be considered in the implementation of information systems. Information system security policies include: System maintenance, risk management, setting access rights and human resources, security and control of information assets and server security policies. The policies that have been reviewed will not only be a form of protection for company information, but also a form of protection for the personal privacy of employees of BFI Finance Company..
News Categorisation Based on Pre-Trained Transformer Models

The rise of digital journalism, the amount of news and the continuous number of people accessing these contents, often generates that third parties, through web platforms and social networks, have the opportunity to persuade readers with content that alters their opinion or behaviour on a topic, so it is necessary to classify news using Natural Language Processing (NLP) techniques. This work seeks to experiment with pre-trained Transformer models using transfer learning and fine tuning to obtain a model capable of determining whether a news item is satire, opinion or information. To do so, we use a labelled dataset of news in English presented for the SemEval 2023 campaign, translating it into Spanish to experiment also in this language. We use pre-trained Transformer models for text classification tasks in the mentioned languages, thus, we compare several models and their predictions using evaluation metrics. The results give indications of the goodness of the models considering the subjective type of news, in the case of satire and opinion, and objective for information, thus contributing to future research related to text classification, specifically news categorisation.
HSMH: A Hierarchical Sequence Multi-Hop Reasoning Model With Reinforcement Learning

The incompleteness of knowledge graphs (KGs) negatively impacts the performance of KGs in downstream applications (e.g., recommendation systems and information retrieval). This phenomenon has brought an increasing rise in research related to knowledge graph reasoning. Recently, emerged reinforcement learning (RL)-based multi-hop reasoning methods can infer missing information through multi-hop reasoning according to the existing information in KGs, which has better reasoning performance and interpretability. However, these methods always use relation-entity pairs that have been pre-cropped as the action space of agents for path reasoning, which leads to two problems: 1) insufficient learning and reasoning ability of reasoning models and 2) the hard convergence of the training process of agents. To address these problems, we propose a <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">S</b> equence <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</b> ulti <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</b> op (HSMH) reasoning framework, which consists of the interactive search reasoning model, local-global knowledge fusion mechanism, and action optimization mechanism. We use interactive search reasoning models to select relations and entities independently, thus fully mining the semantic information of relations and entities and improving the learning and reasoning ability of reasoning models. In the HSMH framework, we design the local-global knowledge fusion and action optimization mechanisms for path reasoning, which can enhance agents' state information and action space. Specifically, the local-global knowledge fusion mechanism is designed to acquire the local knowledge of entities and neighboring relations and the global knowledge about KG structure. This local-global knowledge can improve the learning ability of reasoning models. In addition, the action optimization mechanism can combine the filtered action space and the additional action space for efficient path reasoning for agents. Experimental results on five benchmark datasets show that our proposed HSMH framework comprehensively outperforms the state-of-the-art multi-hop reasoning model.
Improving predictive modeling of polymeric materials using a hybrid approach of machine learning and expert intervention

This work describes a hybrid methodology that combines machine learning and expert intervention to improve the predictive modeling of high-interest properties of polymeric materials. Although these materials have many advantages, developing a new material with specific properties, from a new molecular structure, is a great challenge and a costly and time-consuming task. The demand for materials with very specific properties continues to grow, so machine learning techniques have been applied for the prediction of these properties. The hybrid methodology was developed in an evolutionary way from expert intervention at the end of the machine learning process to a more determinative intervention throughout the cycle. This allows for more robust and reliable models for the design of new materials, which can help designers obtain property profiles for prototypes prior to the synthesis stage, saving time and resources.
Blockchain and Cloud Computing used in Preservation of Crime Scene Evidences

Rapid increment in the adoption of various digitalized technologies like blockchain and cloud computing in crime scene evidences have been widely observed. Crime scene evidence attains great emphasis via collection, preservation & analysis of data collected with the help of technologies which enhances the authenticity and safety of evidences. Insights and recommendations to better harness the technological innovation in crime scene evidences have been broadly evaluated with considering the Sustainable Development Goals (SDGs). The role of blockchain and cloud computing to attain sustainability have been demonstrated in the current work. Based on the analysis, this study identified that technological innovation provides enhancement in data security as well as storage of data. Finally, based on thorough analysis a framework is recommended and various challenges have been discussed which gave the way to future advancement via inclusion of technology in crime scene evidence.
Blind Image Deblurring with Extreme Gradient and Dark Channel Priors

This paper presents a novel blind image deblurring algorithm based on extreme gradient and dark channel priors. Traditional methods relying solely on local maximum or minimum gradient priors to estimate the latent image often suffer from ringing artifacts or loss of high frequency information in low gradient areas. To solve those problems, we combine local minimum and maximum gradient prior information to better constrain the solution space. Experimental results show that the proposed algorithm achieves better restoration performance with detail preservation, noise suppression, and robustness on blurry images including face, low light scene, and text. In addition, our algorithm outperforms other methods on Levin and Köhler datasets, with significant improvement in PSNR and SSIM.