Reviewerly/exHarmony huggingface dataset:
Twitter Sentiment Analysis Model

Social networks are the main resources to gather information about people’s opinion towards different topics as they spend hours daily on social media and share their opinion. Twitter is one of the social media that is gaining popularity. Twitter offers organizations a fast and effective way to analyze customers’ perspectives toward the critical to success in the market place. Developing a program for sentiment analysis is an approach to be used to computationally measure customers’ perceptions. .We use natural language processing and machine learning concepts to create a model for analysis . In this paper we are discussing how we can create a model for analysis of twittes which is trained by various nlp , machine learning and Deep learning Approach.
A Survey on Crime Detection And Prediction Techniques

Abstract: Crime is a preeminent issue where the main concern has been worried by individual, the local area and government. Wrongdoing forecast utilizes past information and in the wake of investigating information, anticipate the future wrongdoing with area and time. In present days sequential criminal cases quickly happen so it is a provoking assignment to anticipate future wrongdoing precisely with better execution. This paper examines about various wrongdoing expectation and location. A productive wrongdoing forecast framework speeds up the method involved with addressing violations.. Wrongdoing Prediction framework utilizes recorded information and examinations the information utilizing a few dissecting strategies and later can anticipate the examples and patterns of wrongdoing utilizing any of the underneath referenced methodologies. Keywords: Crime Analysis, Data Mining, Classifiaction , Clustering
PRESERVING PRIVACY FOR PAGERANK ALGORITHM

Data mining has been emergingly applied in many fields to discover the knowledge from the huge data. To do that, information has been sent forward and backward among data owners, users, and maybe third parties. In this situation, it is necessary to design systems to exchange the data between the data owner, the client and third parties during data mining process without scarifying the sensitiveness of data. Hence, we need a privacy preserving mechanism while mining to protect the data as in the situation of sophisticated cyber-attack. In this work, we describe a model for ensuring the privacy in ranking on the graph using PageRank and Shamir Secure Sharing scheme. Specifically, Shamir Secure Sharing scheme has been applied to share the information of graph from the data owner to many servers (i.e. third party). Then, the share of graph on each server will be ranked separately. When the users need the results of ranking and make a request, the information from servers will be combined for the users. Doing this way, the third party doesn’t know the meaning of data but still run analyzing the data. Hence, data owner preserves the privacy of his data while users still retrieve a piece of the information as needed.
Examining Employee Social Media Deviance: A Psychological Contract Breach Perspective

With the prevalence of social media, employees' deviant behaviors on social media can go viral and result in unpredictable negative outcomes beyond the workplace.This paper investigates the relationship between abusive supervision and employee social media deviance from the theoretical perspective of psychological contract breach (PCB), and examines the moderating role of social media controls.Building on prior studies of abusive supervision and employee workplace deviance, this paper argues that abusive supervision plays a crucial motivational role in triggering employee social media deviance.Our results demonstrate that employees who experience abusive supervision are more likely to perceive PCB, and thus engage in social media deviance.User awareness of social media policy and informal sanctions can weaken the positive relationship between employee perceived PCB and social media deviance.
Knowledge Graph-based Framework for Domain Expertise Elicitation and Reuse in e-Learning

Reusing knowledge expertise of different domains in e-learning is an ideal approach to sustain knowledge and disseminate it throughout the different organizations' processes.This approach generates a valuable source for instruction which can enrich significantly the quality of teaching and training as it uses effortlessly expertise from its original sources.It is also very useful for teaching activities since it connects learners with reallife scenarios involving field experts and reliefs instructors from the tedious task of authoring teaching material.In this paper we propose a framework that allows gathering automatically expertise from domain experts while doing their activities and then represents it in a form that can be shared and reused in elearning by different types of learners.The framework relies on knowledge graphs that are knowledge representation structures which facilitate mapping expertise to e-learning objects.A case study is presented showing how inspector reports are handled to generate on-demand e-courses specifically adapted to learners' needs.
ViMQ: A Vietnamese Medical Question Dataset for Healthcare Dialogue System Development

Existing medical text datasets usually take the form of question and answer pairs that support the task of natural language generation, but lacking the composite annotations of the medical terms. In this study, we publish a Vietnamese dataset of medical questions from patients with sentence-level and entity-level annotations for the Intent Classification and Named Entity Recognition tasks. The tag sets for two tasks are in medical domain and can facilitate the development of task-oriented healthcare chatbots with better comprehension of queries from patients. We train baseline models for the two tasks and propose a simple self-supervised training strategy with span-noise modelling that substantially improves the performance. Dataset and code will be published at https://github.com/tadeephuy/ViMQ.
Forming Students’ Humanitarian Culture Through Digitalization Of Additional Foreign Language Education

The article considers and defines such concepts as "humanitarian culture", "students’ humanitarian culture", "digitalization of education". A special attention is paid to the role of additional education, in particular, foreign language education, in the formation of humanitarian culture, which is considered as an important part of lifelong education. An important issue is also the transformation of additional foreign language education within the framework of digitalization of all aspects of life and how the formation of students’ humanitarian culture should be carried out in this context. The authors of this work justify scientifically methodological, theoretical and technological foundations of the strategy of forming humanitarian culture of students within the framework of digitalization of additional foreign language education. These foundations play a significant role in the socio-cultural development of students, in improving their intellectual and creative abilities, determine the readiness for professional and other activities in conditions of uncertainty, and influence the formation of global citizenship of the younger generation by means of a foreign language based on the digital dialogue of cultures. Thus, the aim of the study was to give a scientific description of the strategy for developing students’ humanitarian culture in the context of the digitalization of additional foreign language education.
Comparison of the Use of Discourse Markers in English Speeches between Non-Native and Native Speakers of English

This study revealed the comparison of the use of discourse markers in English speeches between non-native and native speakers of English. The study focused on the types of discourse markers, the similarities and the differences between non-native and native speakers in using discourse markers. This study employed a qualitative research design with the data from the spoken discourse. The findings of the study showed that there were ten sub-categories of discourse markers that are practiced by non-native speakers, namely: assessment marker, manner of a speaking marker, evidential markers, hearsay markers, contrastive discourse markers, elaborative discourse markers, inferential discourse markers, discourse management markers, topic orientation markers, and attention markers. On the contrary, there were nine sub-categories of discourse markers that existed in English speeches, especially delivered by the native speakers such as assessment marker, manner of a speaking marker, evidential markers, hearsay markers, contrastive discourse markers, elaborative discourse markers, inferential discourse markers, topic orientation markers, and attention markers. The total of discourse markers produced by the non-native speakers was 301 utterances while native speakers of English were 269 utterances. Therefore, it is concluded that discourse markers were useful in English speeches either by non-native speakers or native speakers
Pelatihan Penyusunan Perangkat Pembelajaran BDR Bagi Guru Pendidikan Anak Usia Dini di Kota Jayapura

This community service activity is a training "Development of BDR Learning Tools for PAUD Teachers" in Jayapura City.This activity was carried out for PAUD teachers in Jayapura City.The number of targets who attended the activity was 23 teachers.The purpose of this activity is to facilitate and provide training to PAUD teachers in Jayapura City to be able to develop BDR learning tools and the ability to choose and determine the right media in BDR learning.This method is in the form of lectures and questions and answers as well as direct practice (demonstration).The results of the evaluation of community service on training in the preparation of BDR learning tools for PAUD teachers in Jayapura City were declared successful.This can be seen from the evaluation results, from 23 participants there were 20 participants (86.96%) in the very good category and 2 participants (8.69%) in the good category and 1 participant (4.35%) in the good category.pretty good category. .In other words, this training has been successful and can improve the knowledge, insight, understanding, and skills of participants in developing BDR learning tools and choosing the right BDR learning media.
MODEL PEMBELAJARAN SKEMA PADA PELAJARAN BAHASA INDONESIA DAPAT MENINGKATKAN KETERAMPILAN MEMBACA PEMAHAMAN TEKS ULASAN SISWA KELAS VIII MADRASAH TSANAWIYAH NEGERI BINJAI

This study aims to find out that the implementation of the schema learning model in Indonesian lessons can improve reading comprehension skills for grade VIII Madrasah Tsanawiyah Negeri Binjai students in the Odd Semesters of the 2019/2020 Academic Year. The results showed that the schema learning model in Indonesian lessons could improve reading comprehension skills of the VIII grade students of Madrasah Tsanawiyah Negeri Binjai in the Odd Semesters of the 2019/2020 Academic Year. This can be seen from the results of the calculation in the first cycle between the value of the first daily test and the score of the second daily test, the Product Moment value is 0.823 with a t-test of 8.198. And the second cycle between the second block test scores and the third daily test scores obtained a Product Moment value of 0.903 with a t-test value of 11.902, while the results of the calculation showed that it was greater than the results in the table, of 0.478 and 2.725. Likewise, the average score for the first daily exam was 86.35, and the second daily exam was 87.53 in the first cycle, as well as the average score for the third daily exam was 88.53 and the fourth daily exam was 90.71 in the second cycle. there is an increase. while the minimum completeness criteria value (KKM is 84). Keywords: Schematic Learning Model, Reading Comprehension Skills Review Text
Implementasi BGP dan Resource Public Key Infrastructure menggunakan BIRD untuk Keamanan Routing

The validity of the routing advertisements sent by one router to another is essential for Internet connectivity. To perform routing exchanges between Autonomous Systems (AS) on the Internet, a protocol known as the Border Gateway Protocol (BGP) is used. One of the most common attacks on routers running BGP is prefix hijacking. This attack aims to disrupt connections between AS and divert routing to destinations that are not appropriate for crimes, such as fraud and data breach. One of the methods developed to prevent prefix hijacking is the Resource Public Key Infrastructure (RPKI). RPKI is a public key infrastructure (PKI) developed for BGP routing security on the Internet and can be used by routers to validate routing advertisements sent by their BGP peers. RPKI utilizes a digital certificate issued by the Certification Authority (CA) to validate the subnet in a routing advertisement. This study aims to implement BGP and RPKI using the Bird Internet Routing Daemon (BIRD). Simulation and implementation are carried out using the GNS3 simulator and a server that acts as the RPKI validator. Experiments were conducted using 4 AS, 7 routers, 1 server for BIRD, and 1 server for validators, and there were 26 invalid or unknown subnets advertised by 2 routers in the simulated topology. The experiment results show that the router can successfully validated the routing advertisement received from its BGP peer using RPKI. All invalid and unknown subnets are not forwarded to other routers in the AS where they are located such that route hijacking is prevented.&#x0D;
Emotional Response in the Interaction of Instructional Video as Teaching Support for Teachers in Initial Training

Students of initial training develop in an atmosphere full of emotions that go unnoticed by university teachers, coupled with the little expertise to face preprofessional pedagogical practice especially in this distance learning modality due to COVID-19, using various technological resources. This article aims to analyze the associations between the perception of the instructional videos and the positive and negative emotions experienced by students in the subject Mathematical Thinking II. The study is descriptive correlational, carried out on 42 students of the Primary Education career. Applying two instruments to measure the quality of the instructional video and the emotions generated after viewing it and the teacher's participation. A significant relationship has been found between instructional video and positive emotions. The result allows establishing greater preferences for emotion, enthusiasm, happiness, and enjoyment that allows students through teaching practice to face personal and professional emotions in their learning experiences by evaluating the instructional video. The main finding shows moments of intensity towards positive rather than negative emotions promoting healthy pedagogical activities in the classroom strengthened by non-face-to-face teaching.
The Antifa Marketing Model: Examination, Application, and Implications for Future Research

This paper analyzes the online presence of antifa from a marketing perspective to identify its marketing communication and brand-building tactics for comparison to those of other radical groups. Positioning itself as victim within a well-established grievance ideology is central to the antifa brand narrative, which uses a “persecution appeal” to persuade individuals to pursue a higher purpose by taking action against monolithic and powerful oppressors, thus transforming themselves into intellectually fascinating and emotionally compelling protagonists. The antifa model is used as a framework for analysis of Choose Democracy, another activist site. Similarities between the groups suggest that the antifa marketing model can be useful for analyzing and countering online radicalization.
Fast and Accurate Deep Learning Architecture on Vehicle Type Recognition

Vehicle Type Recognition has a significant problem that happens when people need to search for vehicle data from a video surveillance system at a time when a license plate does not appear in the image. This paper proposes to solve this problem with a deep learning technique called Convolutional Neural Network (CNN), which is one of the latest advanced machine learning techniques. In the experiments, researchers collected two datasets of Vehicle Type Image Data (VTID I &amp; II), which contained 1,310 and 4,356 images, respectively. The first experiment was performed with 5 CNN architectures (MobileNets, VGG16, VGG19, Inception V3, and Inception V4), and the second experiment with another 5 CNNs (MobileNetV2, ResNet50, Inception ResNet V2, Darknet-19, and Darknet-53) including several data augmentation methods. The results showed that MobileNets, when combine with the brightness augmented method, significantly outperformed other CNN architectures, producing the highest accuracy rate at 95.46%. It was also the fastest model when compared to other CNN networks.
Book review: Fleming, Peter (2021). Dark academia. How universities die. Pluto Press.

Dark academia's declared purpose is a description and explanation of the hidden psychological injuries endured by students and academics in contemporary universities.
PENGEMBANGAN VIDEO PEMBELAJARAN BERBASIS TPACK DALAM MATERI PECAHAN UNTUK SISWA KELAS IV SD

This study aims to develop TPACK-based learning videos in fraction material for fourth grade elementary school students that are valid, practical and have a potential effect on student learning outcomes. This research is research and development using the ADDIE model with five stages, namely analysis, design, development, implementation, and evaluation. The research took place at SDN 79 Prabumulih. The research subjects were 20 fourth grade elementary school students. Data collection was carried out by means of a media expert validation questionnaire, material expert, student response questionnaire, and student test questions. The data are analyzed quantitatively and qualitatively. The validation results of the validators got an average validation score of 95.43% with a very valid category. The results of student responses based on small group trials got an average score of 94.87% with a very practical category. The results of the large group trial get an average of 88.25% in the very good category or have a potential effect on student learning outcomes. It can be concluded based on the results of data analysis of TPACK-based learning videos in fraction material for fourth grade elementary school students including learning videos that are valid, practical, and have a potential effect on learning outcomes. Overall, TPACK-based learning videos in fraction material for fourth grade elementary school students have been suitable for use in learning Keywords : Development Of Learning Videos, TPACK, Fractions
The Facts Speak for Themselves: the Monographic Research by T. A. Konstantinova on the History of National Archives in Eastern Transbaikalia

In her monograph T. A. Konstantinova investigates the formation and development of archival work in Eastern Transbaikalia over the course of 100 years. The author examined step by step the working conditions, the multilateral activities of archival institutions and, first of all, the State Archives of the Trans-Baikal Territory. The factual material is new, with a few exceptions. It testifies that the period of formation of archival work in the region lasted from 1917 to 1939, and the period of its development ‒ from 1939 to 1991. The style of the study is characterized by the maximum setting for the facts to speak for themselves. They are presented with a laconic author’s accompaniment. There are only few estimates by T. A. Konstantinova. The volume context is minimal. The chapters’ titles have the context property. The first three chapters reveal the formation of archival affairs in the years when the Soviet government overcame the grave consequences of the Civil War and carried out a deep reconstruction of the country. The last three chapters reflect the development of archiving in the context of a stable state of government. The final chapter covers the period of 1991‒2018. It shows that archival work has not fallen apart together with the Soviet state. It has withstood and rebuilt in the new historical realities. The text and the Appendix of the monograph contain rich material on personalities, identified by the author on the basis of archival data.
The Value of Seligman’s Optimism in Disorder Novel as Teaching Materials of Indonesian Language in SMA

This study aims to describe and explain the value of Sellingman's optimism contained in the novel Disorder by Akmal Nasery Basral so that it can be used as Indonesian language teaching material in high school.The method used in this study is a qualitative descriptive method.The data in this study are in the form of words, phrases, clauses, sentences, and paragraphs that contain information about the value of Sellingman's optimism in the novel.The structural approach is used as a scalpel because it is used to describe the findings in the novel structure.The validity of the data used is investigator triangulation.Data analysis resulted in finding the presence of Sellingman's optimism value in Novel Disorder in the novel, namely permanence, pervasiveness, and personalization.
Content of the Humanitarian Disciplines in the when Training Students in Technical Universities

Using the example of studying at the Moscow Automobile and Road State Technical University (MADI), the paper examines the specifics of the content of the disciplines of the humanities cycle, in particular the integrated course “Russian language and the skill of business communication”. The course content is structured by topics, it combines materials from such disciplines as the Russian language, Speech culture, Public speaking and Communication psychology. The features of methodical classroom and extracurricular work during the study of the discipline are shown. A number of practical tasks aimed at increasing the motivation of students in the study of this course are proposed
The Status and Trend of Chinese News Forecast Based on Graph Convolutional Network Pooling Algorithm

It is always a hot issue in the intelligence analysis field to predict the trend of news description by pre-trained language models and graph neural networks. However, there are several problems in the existing research: (1) there are few Chinese data sets on this subject in academia and industry; and (2) using the existing pre-trained language models and graph classification algorithms cannot achieve satisfactory results. The method described in this paper can better solve these problems. (1) We built a Chinese news database predicted by more than 9000 annotated news time trends, filling the gaps in this database. (2) We designed an improved method based on the pre-trained language model and graph neural networks pooling algorithm. In the graph pooling algorithm, the Graph U-Nets Pooling method and self-attention are combined, which can better solve the analysis of the problem of forecasting the development trend of news events. The experimental results show that the effect of this method compared with the baseline graph classification algorithm is improved, and it also solves the shortcomings of the pre-trained language model that cannot handle very long texts. Therefore, it can be concluded that our research has strong processing capabilities for analyzing and predicting the development trend of Chinese news events.