Reviewerly/exHarmony huggingface dataset:
El peso de la historia: desafíos de la policía en la gobernanza del cibercrimen en España

Cybercrime presents a myriad of challenges for law enforcement agencies, including the complexity and global nature of criminal activities, the difficulties in tracing activities within cyberspace, and the perpetual evolution of these unlawful practices. This article employs the conceptual framework of historical and discursive institutionalism to investigate the hurdles faced by the police in governing cybercrime in Spain. The study emphasizes the importance of situating law enforcement within the cybersecurity governance system to comprehend their challenges and adaptations. By analyzing 36 key documents, it argues that cybersecurity policies’ origins and evolution were rooted in narratives focused on information protection and enhancing society’s trust in digital technologies, narratives distinct from the discourse centered on cybercrime. The Spanish case study enriches the literature on cybersecurity governance by examining how historical evolution and narratives impact the roles of actors involved in the governance system.
Deep Random Forest and AraBert for Hate Speech Detection from Arabic Tweets

Nowadays, hate speech detection from Arabic tweets attracts the attention of many researchers. Numerous systems and techniques have been proposed to address this classification challenge. Nonetheless, three major limits persist: the use of deep learning models with an excess of hyperparameters, the reliance on hand-crafted features, and the requirement for a huge amount of training data to achieve satisfactory performance. In this study, we propose Contextual Deep Random Forest (CDRF), a hate speech detection approach that combines contextual embedding and Deep Random Forest. From the experimental findings, the Arabic contextual embedding model proves to be highly effective in hate speech detection, outperforming the static embedding models. Additionally, we prove that the proposed CDRF significantly enhances the performance of Arabic hate speech classification.
Innovations in the Sphere of Regulatory Provision of Russian Culture, Information Security, Copyright Protection, Development of Librarianship

The article presents information about recent organizational solutions and events in the sphere of preservation and development of Russian Culture information security for children, copyright protection, development and integration of libraries into united national system, including new regions of the Russian Federation; international relations and cooperation of the main libraries of Russia, Belarus and China.
Local History Reference Editions for Children and Youth (Published in the Russian Federation in 1992—2023)

The article presents reference publications about the regions of modern Russia, addressed to children and youth audience. This topic becomes especially relevant in a complex geopolitical situation, when it is necessary to involve the younger generation in studying the history of not only the country as a whole, but also of their small homeland. That is why the article reveals some peculiarities of preparing and publishing such literature. For the first time the term “local history reference books for children and youth” (regional encyclopedias, reference books, guides for children) is proposed, the dynamics of publication by years and regions is traced. The value of such editions in both informational and patriotic aspects is revealed. The problem of low activity of book publishing in this area is raised. The bibliographic list of local history reference books for children and youth, published in the Russian Federation in 1992—2023, identified at the moment of writing, is presented for the first time.
EVALUATING DEAR AND BAG-IW FOR ELEMENTARY GRADE LEARNERS’ READING COMPREHENSION: (An Action Research)

This study delves into the effects of integrating Drop Everything and Read (DEAR) and Boosting and Gaining Individual Word Understanding (BAG-IW) materials on the reading comprehension abilities of elementary learners. The research presents compelling evidence regarding the efficacy of these materials in enhancing the reading comprehension of these learners. While the majority of students generally fall within the instructional reading level, only a minority face challenges in grasping the meaning of texts. The study advocates for the sustained use of DEAR and BAG-IW materials to further augment the reading proficiency of elementary learners in Baguio City and Mt. Province. Remarkably, these interventions have yielded success in moving some students from the frustration level to the instructional level, with an additional six learners reaching the instructional level. This underscores the significant impact of DEAR and BAG-IW on students' reading abilities, substantiated by the results of the chi-square analysis. Consequently, this research highlights the imperative of continued investment in these programs, emphasizing their value as instrumental tools for enhancing reading comprehension among learners. The implications of these findings are far-reaching, extending to educators and policymakers who seek to improve the reading proficiency of primary school students, ultimately contributing to their academic success and overall development.
Learning From How Humans Correct

&lt;p&gt;In industry NLP application, our manually labeled data has a certain number of noisy data. We present a simple method to find the noisy data and relabel them manually, meanwhile we collect the correction information. Then we present novel method to incorporate the human correction information into deep learning model. Human know how to correct noisy data. So the correction information can be inject into deep learning model. We do the experiment on our own text classification dataset, which is manually labeled, because we relabel the noisy data in our dataset for our industry application. The experiment result shows that our learn-on-correction method improve the classification accuracy from 91.7% to 92.5% in test dataset. The 91.7% accuracy is trained on the corrected dataset, which improve the baseline from 83.3% to 91.7% in test dataset. The accuracy under human evaluation achieves more than 97%.&lt;/p&gt;
Automatic Cheating Detection In Exam Hall

&lt;p&gt;Exams are a widely used evaluation tool in educational institutions to assess students' strengths and weaknesses. However, students tend to cheat during physical exams by exchanging papers, using hidden notes, or fulfilling their parents' expectations, among other things. Due to physical limitations, traditional invigilation methods cannot effectively monitor exams while maintaining their integrity. To address this issue, a study proposes an automated method based on computer vision that uses closed- circuit television (CCTV) cameras to detect suspicious behavior during physical exams. The proposed method employs You Only Look Once (YOLOv3) with residual networks as the backbone architecture to inspect cheating. The results demonstrate that the proposed method is reliable and efficient, achieving 88.03% accuracy in detecting cheating in the classroom environment. Overall, this work shows promising results for invigilating students during exams.&lt;/p&gt;
An interference model for visual and verbal working memory.

Research on working memory (WM) has followed two largely independent traditions: One concerned with memory for sequentially presented lists of discrete items, and the other with short-term maintenance of simultaneously presented arrays of objects with simple, continuously varying features. Here we present a formal model of WM, the interference model (IM), that explains benchmark findings from both traditions: The shape of the error distribution from continuous reproduction of visual features, and how it is affected by memory set size; the effects of serial position for sequentially presented items, the effect of output position, and the intrusion of nontargets as a function of their distance from the target in space and in time. We apply the model to two experiments combining features of popular paradigms from both traditions: Lists of colors (Experiment 1) or of nonwords (Experiment 2) are presented sequentially and tested through selection of the target from a set of candidates, ordered by their similarity. The core assumptions of the IM are: Contents are encoded into WM through temporary bindings to contexts that serve as retrieval cues to access the contents. Bindings have limited precision on the context and the content dimension. A subset of the memory set-usually one item and its context-is maintained in a focus of attention with high precision. Successive events in an episode are encoded with decreasing strength, generating a primacy gradient. With each encoded event, automatic updating of WM reduces the strength of preceding memories, creating a recency gradient and output interference. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Artificial intelligect and human nature

The article presents the main transformational processes of scientific understanding of the role and interaction of «artificial» and «natural» intellect. The aim of the work is to analyze and summarize the most promising results of modern scientific research in the context of supporting the priority of solving «intellectual» problems by «natural intellect» and the role of «artificial intellect». Attention is drawn to the specifics of the artificial intellect functioning, which is significantly limited by the fundamental incompleteness of semantic information and the absence of axiological information. The article is based on the data of scientific developments in the field of natural and historical sciences. The natural intellect is presented as a social phenomenon that arose from the interaction of individual cerebral structures, the optimal characteristics of which were formed as a result of previous evolution, and therefore these characteristics allow to understand and make any dominant decisions. The material summarized in the article allowed to formulate some conclusions. In particular, that an artificial non-biological structure cannot be «smarter» than a person – regardless of how quickly and according to what programmes it processes the information, since it does not have its own goals. But the artificial intellect is a powerful tool for society in its interaction with the outside world. A tool – but in no case an agent that determines its goals and objectives. The artificial intellect as an auxiliary means is and will be created in future by people to achieve the same goal that «natural» intellect serves – better possible satisfaction of the needs of society as a whole and the individual in particular.
Advancing Security: Machine Learning-Based Signature Forgery Detection in Document Authentication Systems

Handwritten signatures play a vital role in our lives. From banks to institutions to organizations, signatures are a way of identifying a person. However, signings come with a lot challenges because any two signatures can look very similar with slight differences written the same person. Therefore, the identification of real and fake signatures is very difficult. To avoid similar identity related crimes committed in banks and many others companies, the counterfeit detection system is the solution to this problem along with the help concepts of machine learning and CNN. For better performance and time efficiency, Parallelization concepts are used in software implementation. This software can be used to verify signatures on many platforms such as loans, signing legal documents, applications signing, applications and much more.
Is Criminology a Science? If Yes the How it is Related and What are Its Theoris

criminology is considered a social science that studies the causes, consequences and prevention of criminal behavior, while it is not a physical science or natural science the research paper analysis it all.
Study of Metaverse Prospect, Implications and Sustainability Based on Perception of University Students in Indonesia

Technological advancement is accelerating in this Industry 4.0 era, resulting in numerous changes in human life.As university students or so-called agents of change, we expected to adapt quickly.Metaverse is one of the hotly debated topics these days.Thus, the goal of this research is to look at the metaverse's prospects, implications, and sustainability through the eyes of university students in Indonesia.Purposive sampling was used as the research method.We also designed a metaverse environment simulation room and invited our respondents to come in to experience the world of the metaverse there, followed by filling out the questionnaire.The simulation is held to collect valid data on respondents' perceptions related to the ease of use, usefulness, and intention to use metaverse based on their real simulation experience, not just on their assumptions.The findings indicated that the metaverse's prospects are very decent, but the societies and existing infrastructure are still insufficient to implement the metaverse.Meanwhile, the metaverse's ease of use has a significant impact on the intention to use.As a result, we need to prepare several things carefully during transition and adaptation.Especially in terms of infrastructure readiness and accessibility.
Investigating the components of virtual education development based on the four-frame model of organizational development

Background &amp; Objective: The development of virtual education is one of the important needs of universities and one of the main policies of higher education. The present research was conducted based on Bolman and Deal's four-frame model (1991) to compare the existing situation and the importance of the components of virtual education development (structural, human resources, political, and symbolic) from faculty members' perspectives. Materials &amp; Methods: This descriptive survey study was conducted in 2019-2020. The research community was the faculty members of Shiraz University of Medical Sciences in 2019 with at least one year of experience (700 people). The sample size was calculated at 220 cases using Cochran's formula, and 156 participants provided complete questionnaires. The research tool was a researcher-made questionnaire consisting of 32 items in four domains- structural, political, human resources, and symbolic (cultural). Form and content validity were confirmed from the perspectives of 10 experts, and construct validity was confirmed with KMO=0.944. Bartlett's Sphericity index was P&lt;0.001, and reliability was reported with Cronbach's alpha of 0.973. Data were analyzed in SPSS software (version 24) using paired t-test, independent t-test, ANOVA, and Pearson's correlation. Results: There was a significant difference between the existing situation and the importance of the components (favorable) (P&lt;0.001). Based on the four-frame model, the mean scores of human resources, symbolic, structural, and political components were reported as 3.44±0.86, 3.13±1.10, 3.11±0.92, and 2.93±1.07, respectively. There was no significant difference in the mean of the components by gender and years of employment (P&gt;0.05); nonetheless, it was different by academic rank, disciple, and faculty (P&lt;0.05). There was a significant correlation among the components (P&lt;0.001). Conclusion: As evidenced by the obtained results, the development of virtual education requires close attention to organizational, cultural, human, and political variables. Furthermore, the development is also affected by the culture of the discipline; therefore, a comprehensive examination is needed in the analysis of issues and provision of solutions.
Certificate Verification and Counterfeit Detection using Blockchain

Abstract: Certificates help students not only to prove their achieved goals and milestones but also ensure that he/she maintains a high level of knowledge in that particular field. An estimated total of 25.57 crore Indian students have been enrolled for primary to higher education in 2020–21 and nearly 65 lakhs of them graduate each year. Throughout this journey, a student generates a myriad number of certificates that may include results, transcripts, degrees, diplomas, etc. A student has to submit these certificates to apply for a job or seek higher admission in any particular organization. A major problem today is manually verifying and authenticating these certificates. Many hardworking people with genuine certificates get rejected and suffer because of the lack of a system that can differentiate original certificates from fake ones. With easy access to cheap and advanced software, document forgery has become a matter of concern nowadays. This scenario demands an updated system that could not only store documents safely but also help verify and authenticate them, their issuers, and holders in a way that is much simpler, effective, and secure. Blockchain technology comes up as a solution to all these problems. Blockchain has recently emerged as a potential means for the document-authentication process and can be easily used to tackle document forgery and counterfeiting as it follows a decentralized approach. Our proposed model includes several methods such as unique hash generation, key cryptography, digital ledgers, proof of work, digital signatures, and distributed storage which has made the document-verification process easier and more secure for both the certificate-generating organization and the holder of the certificate. The SHA-256 algorithm has been used to assign a unique hash to each uploaded document which can be used to validate its authenticity. Thus, this system meets up all the criteria for a document verification system by overcoming the drawbacks and difficulties currently faced in the traditional methods of document verification.
Twitter Sentiment Analysis on Chatgpt Tweets

Abstract: This study investigates multilingual sentiment analysis within tweets on ChatGPT, an AI conversational model, employing Support Vector Machines (SVM) and BERT, an advanced language model. It aims to detect and classify emotions, including emoji identification, embedded within diverse messages across multiple languages on Twitter. By leveraging SVM's text classification and BERT's contextual understanding in various languages, the research delves into preprocessing techniques and feature engineering for sentiment analysis, encompassing multilingual and emoji detection. Furthermore, it explores the fusion of traditional SVM methods with BERT's state-of-the-art model for multilingual sentiment analysis, emphasizing emotion and emoji detection in AI-generated content on multilingual social media platforms like Twitter. This research yields insights into the successful detection of multilingual sentiment nuances and emotions, including emoji identification. It offers implications for advancing multilingual sentiment analysis in natural language processing across diverse linguistic contexts.
Blockchain and Smart Contract System for Digital Certificate

Abstract: An millions of students Graduates per year. A student generates lots of certificates during their education. For further studies or Apply for job at any company requires these certificates. So sometimes student need these certificate on urgent basis. But according to university guidelines generating certificate process takes time. This problem is solved by Digital Certificate System. While recruiting employees in company, company needs to verify their certificate because issue of fake certificate is very common in India. Anyone can get fake certificate very easily. Many companies spend large amount of money on verifying this certificate. To overcome these problem Blockchain technology is used. Blockchain is decentralized distributed ledger. Blockchain is immutable in which no one can easily modify the data.
FACTORS ASSOCIATED WITH POST PARTUM HEMORRHAGE

Postpartum hemorrhage is bleeding or blood loss of more than 500cc that occurs after the child is born either before, during or after the birth of the placenta. Several risk factors increase the incidence of postpartum hemorrhage, namely prolonged labour, more than one baby in the fetus, episiotomy (the act of opening the birth canal by providing a cut around the birth canal), large babies of more than 4000 grams, history of bleeding, anemia during pregnancy, age too late pregnancy.Purpose: Research to determine the factors associated with the incidence of postpartum hemorrhage.Research method: This research is a quantitative study with a cross sectional approach. The sample was part of post partum mothers from the medical records of Regional public hospital H.Padjonga Dg.Ngalle, totaling 40 people. The sampling technique is accidental sampling. The method of data collection in this study was secondary data by opening the register of patients who experienced post partum bleeding at the Regional public hospital H. Padjonga Dg. Ngalle, Takalar Regency. After that retrieve the data and select complete data based on the specified criteria. Data were analyzed using chi-square.
Banjarese College Students’ Positive Politeness toward Their Lecturers Through Online Chats

The research aimed to describe the positive politeness strategy which was applied by undergraduate students toward their lecturers in online conversations. It was also to find the form of violations of politeness that occurred in the conversation and to describe factors that influenced the violation. Data were gathered from online conversations between students and lecturers through chat applications such as WhatsApp and Line on lecturers' and students’ devices. Then the data were grouped and analyzed according to Brown and Levinson's (1987) positive politeness strategy along with their theory on Distance, Power, and Ranking of Imposition. The results show that positive politeness strategies appear in eleven utterances out of forty-three utterances. The violation of politeness is shown in five utterances, all of which threaten the negative face of the addressee. In addition, five factors influence the violation: distance, context, desire to over-praise the addressee, deliberately asking for reasons, and rejection. Overall, social factors still influence the way students communicate online with their lecturers. To some extent, students apply positive politeness strategies toward their lecturers even though the interaction happens through online chat applications.
Evaluation of the Multimedia Coursebook Material in Listening 1 Course: Audio, Video, and Interactive Activities

The research aimed to evaluate the multimedia coursebook materials that had been applied in the Listening 1 course at one university in Indonesia, to know whether the coursebook used was presented well and still suitable to the student’s needs. The audio, video, and interactive activity provided in multimedia coursebook materials needed to be evaluated to determine their suitability for students, lecturers, and the institution. A qualitative method was applied, and the evaluation form was used to gather the data from two linguists of English Applied Linguistics, one Listening 1 lecturer, three students who had used the coursebook, and three students who had not used them. The data were summarized, analyzed, and qualitatively described. The finding shows that the audio, video, and interactive activity in the multimedia coursebook material applied in the Listening 1 course are presented well. To begin with, the audio provided is clear, and the accent is understandable. Then, the clarity of the video’s image, gestures, and facial expressions aid the students’ comprehension of the video’s content. The material, exercise, the application needed, and the link provided in the interactive activity are varied and appropriate to student needs and level of ability. The evaluation result can be used to improve the quality of multimedia coursebook material in the Listening 1 course. Finally, the research has the practical application of facilitating students’ learning needs by offering learning media resources in the form of multimedia coursebook materials.