Reviewerly/exHarmony huggingface dataset:
COVID-19 Public Tweets Sentiment Analysis using TF-IDF and Inductive Learning Models

The fact of appearing of the handheld devices offers forthright entree to the internet and social networking sites. Sentiment analysis and opinion mining is the study of sentiments or opinions shared by different users in social networking sites like, Twitter, Facebook, Reddit, Instagram etc., on diverse social phenomena. In this article, sentiment analysis of different tweets on the ongoing epidemic COVID-19, Corona virus disease is performed. COVID-19 is declared as epidemic by the World Health Organization (WHO) in the mid of March 2020. The statistical and machine learning based analyses are implemented on 40,000 tweets, which were collected in two different mutually exclusive time frames. Tweets are collected from Twitter site between 3/07/2020 to 11/07/2020 and 01/08/2020 to 06/08/2020, using Tweepy python library. Various Python based libraries are applied for data acquisition, data pre-processing and data analysis processes.  As a data pre-processing phase initially sentences are cleaned. Then by calculating the polarity and subjectivity measures tweets are categorized into three groups (viz., negative, neutral, and positive}). Thereafter, in the later phase by applying the Term frequency-inverse document frequency (TF-IDF) feature extraction scheme with the help of uni-gram, bi-gram, and tri-gram techniques different features are extracted to prepare the datasets to feed it into the prediction models. 70% of the datasets are used to train Gaussian Naive Bayes (G-NB), Bernoulli's Naive Bayes (B-NB), Random forest (RF), and Support vector machine (SVM) classifiers to generate different prediction models. Finally, 30% of the data is tested on those learning models. Experimental results suggest that RF and B-NB models performed better than the other two classifier models. The execution computational cost of SVM is very high.
Toward the Third Dimension in WebGL

We completed the previous chapter with a red rectangle painted into the window of a web browser. The process to make the rectangle included the following steps: setting up data inside a vertex and fragment shader; storing the information in buffers; and commanding the WebGL application to execute its drawing instructions. If these steps make up the state and behavior of a WebGL program that rasterizes 2D content, and every WebGL program is a machine that operates on state, then how can we use what we have already created to add a third dimension to our scene?
Developing Android-Based Instructional Media of Economic Subject for Senior High School

This research aims at identifying the utilization of YouTube as an instructional media of Economic subject for senior high school students. This research employed a Research and Development approach (RD it was conducted twice. The results confirmed that the media developed is feasible and acceptable to be used which obtained 83.01 percent of an average score.
RISK ANALYSIS OF INSAN UNIVERSITY SYSTEM USING ISO 27001

This study aims to apply the governance of Information and Communication Technology (ICT) at Bina Insani University. Governance itself has become a necessity and a demand in the application of ICT management. This study uses the ISO 27001 standard in measuring and assessing information security risks. Data collection is done by using the method of observation and interviews. The stages of research carried out in a row are (1) Identification of assets, (2) identification of security threats and vulnerabilities, (3) assessing CIA risk (Confidentiality integrity availability), (4) BIA business impact assessment (5) Resulting risk value is accepted or carried out management until risk evaluation Risk evaluation results show that there are still many activities that must be improved such as information disclosure and malware spread and implemented to improve the security of assets at the university of human development.
Solving the Message Classification Problem in Voice Interaction Systems

A method for solving the problem of classifying short-text messages in the form of sentences of customers uttered in talking via the telephone line of organizations is considered. To solve this problem, a classifier was developed, which is based on using a combination of two methods: a description of the subject area in the form of a hierarchy of entities and plausible reasoning based on the case-based reasoning approach, which is actively used in artificial intelligence systems. In solving various problems of artificial intelligence-based analysis of data, these methods have shown a high degree of efficiency, scalability, and independence from data structure. As part of using the case-based reasoning approach in the classifier, it is proposed to modify the TF-IDF (Term Frequency - Inverse Document Frequency) measure of assessing the text content taking into account known information about the distribution of documents by topics. The proposed modification makes it possible to improve the classification quality in comparison with classical measures, since it takes into account the information about the distribution of words not only in a separate document or topic, but in the entire database of cases. Experimental results are presented that confirm the effectiveness of the proposed metric and the developed classifier as applied to classification of customer sentences and providing them with the necessary information depending on the classification result. The developed text classification service prototype is used as part of the voice interaction module with the user in the objective of robotizing the telephone call routing system and making a shift from interaction between the user and system by means of buttons to their interaction through voice.
More Efficient Amortization of Exact Zero-Knowledge Proofs for LWE.

We propose a practical zero-knowledge proof system for proving knowledge of short solutions \(\mathbf {s},\mathbf {e}\) to linear relations \(\mathbf {A}\mathbf {s}+\mathbf {e}=\mathbf {u}\pmod q\) which gives the most efficient solution for two naturally-occurring classes of problems. The first is when \(\mathbf {A}\) is very “tall”, which corresponds to a large number of LWE instances that use the same secret \(\mathbf {s}\). In this case, we show that the proof size is independent of the height of the matrix (and thus the length of the error vector \(\mathbf {e}\)) and rather only linearly depends on the length of \(\mathbf {s}\). The second case is when \(\mathbf {A}\) is of the form \(\mathbf {I} \otimes \mathbf {A}'\), which corresponds to proving many LWE instances (with different secrets) that use the same samples \(\mathbf {A}'\). The length of this second proof is square root in the length of \(\mathbf {s}\), which corresponds to a square root of the length of all the secrets. Our constructions combine recent advances in “purely” lattice-based zero-knowledge proofs with the Reed-Solomon proximity testing ideas present in some generic zero-knowledge proof systems – with the main difference that the latter are applied directly to lattice instances without going through intermediate problems.
IMPROVING STUDENTS’ SPEAKING ABILITYBY BOARD GAME FOR THE SECOND GRADE STUDENTS OF MTS NW DARUSSOLIHIN KALIJAGAIN ACADEMIC YEAR 2019/2020

In teaching and learning speaking process, there are some problems of the teachers such as: the mastery of approach and methods.  English teachers have to try to find out and apply proper some strategies in the teaching learning speaking process. As the motivator for students,the teacher should be look carefully and able to overcome and lookcoused of the problem for the problem solving of their students’ problems. They have to apply appropriate method and approach based on the situation and condition of the students and their environment. In this case, board game is one of approaches which is expected to be able to increase students’ speaking ability. In this research, the writer formulated two problems: (1) To what extent is the student's speaking ability for the eighth grade of MTs NW Darussolihin Kalijagain the school year 2019-2020? and (2) What is the effect of board game in  improving the students’ speaking ability at the second grade of MTs NW Darussolihin Kalijagain the school year 2019/2020. ? This research was an experimental study. The sample of the study was divided into two groups; experimental group and control group, then the two groups were given the same test. Furthermore, this research used speaking test as the instrument to collect the data. Moreover, the researcher used hypothesis testing to measure the students speaking ability. After that,analyzed the data which were obtained from the experimental group in which they were taught by applying scaffolding talk and the control group was taught by using traditional method.The result of the data analysis indicated that the eighth grade students of MTs NW Darussolihn Kalijaga  attained high score on the post test for experimental group.  It was the fact that the effectiveness of board game talk was indicated by the mean score of the students that was 58.65. Furthermore, it was also indicated by the result of hypothesis testing that the alternative hypothesis was accepted. It was provable that the t-table was lower than t-test in which the t-table was 1.68 and t-test 7.16. Therefore, it can be concluded that the experimental group had higher ability in speaking skill than the control group.
COMPARISON BETWEEN ONLINE EDUCATIONAL PRACTICES OF BULGARIAN AND GERMAN UNIVERSITIES UNDER LOCKDOWN

L. Parijkova1, K. Petrova2 1University of Library Studies and Information Technologies (BULGARIA) 2Friedrich-Alexander University Erlangen-Nürnberg (GERMANY)
Robust image stitching with multiple registrations

Panorama creation is one of the most widely deployed techniques in computer vision. In addition to industry applications such as Google Street View, it is also used by millions of consumers in smartphones and other cameras. Traditionally, the problem is decomposed into three phases: registration, which picks a single transformation of each source image to align it to the other inputs, seam finding, which selects a source image for each pixel in the final result, and blending, which fixes minor visual artifacts. Here, we observe that the use of a single registration often leads to errors, especially in scenes with significant depth variation or object motion. We propose instead the use of multiple registrations, permitting regions of the image at different depths to be captured with greater accuracy. MRF inference techniques naturally extend to seam finding over multiple registrations, and we show here that their energy functions can be readily modified with new terms that discourage duplication and tearing, common problems that are exacerbated by the use of multiple registrations. Our techniques are closely related to layer-based stereo, and move image stitching closer to explicit scene modeling. Experimental evidence demonstrates that our techniques often generate significantly better panoramas when there is substantial motion or parallax.
Armacost Library: Armacost Library COVID-19 Updates & Resources: Streaming Media for Online Learning

Find relevant information on Armacost Library's current operations, including access to remote services and helpful links, while we continue learning and teaching away from campus. Please watch this page for continuing changes to Library operations.
Explanation Ontology in Action: A Clinical Use-Case.

We addressed the problem of a lack of semantic representation for user-centric explanations and different explanation types in our Explanation Ontology (this https URL). Such a representation is increasingly necessary as explainability has become an important problem in Artificial Intelligence with the emergence of complex methods and an uptake in high-precision and user-facing settings. In this submission, we provide step-by-step guidance for system designers to utilize our ontology, introduced in our resource track paper, to plan and model for explanations during the design of their Artificial Intelligence systems. We also provide a detailed example with our utilization of this guidance in a clinical setting.
Contested Spaces, Shared Concerns

Roadways are sociocultural spaces constructed for human travel which embody intersections of technology, transportation, and culture. In order to navigate these spaces successfully, autonomous vehicles must be able to respond to the needs and practices of those who use the road. We conducted research on how cyclists, solid waste truck drivers, and crossing guards experience the driving behaviors of other road users, to inform the development of autonomous vehicles. We found that the roadways were contested spaces, with each road user group enacting their own social constructions of the road. Furthermore, the three groups we worked with all felt marginalized by comparison with car drivers, who were ideologically and often physically dominant on the road. This article is based on research for the Nissan Research Center - Silicon Valley, which took place as part of a Design Anthropology course at the University of North Texas.
Research on Service Innovation of Distance Education Platform Under the Background of Coronavirus : – Case Study Based on Tencent Classroom

Nowadays, distance education is becoming more and more important as a way of recharging learning. Tencent Classroom is based on online education and is the leading online education platform in China. This paper takes Tencent Classroom as an example to analyze the service innovation of distance education platform under the background of coronavirus. It is found that though it has made brilliant achievements, Tencent Classroom still face some problems, such as the week profitability of the courses, relatively low specialization level, and the lack of humanization in client interaction. According to these problems, the innovation profit model, the implementation of “expert program”, the improvement of the specialization and the client interaction from the perspective of the users are future service innovation strategies for Tencent Classroom. In the 5G era, artificial intelligence and big data are also necessary for Tencent Classroom.
Methodological Support for Master's Theses on Legal Regulation of Educational Relations

The article is devoted to the topic, the relevance of which is due to the existing contradiction in the system of master's training: between the objective need to form a methodological culture among graduates of the master's program, which allows them to design, implement and evaluate the results of research work competently and in accordance with the requirements, on the one hand, and their lack of readiness for methodological support of research activities, on the other hand. The purpose of the study: to identify and systematize typical shortcomings in the methodological support of master's studies on the legal regulation of educational relations. Research objectives: 1) to reveal the essence and content of the concept of "methodological support for master's research"; 2) to identify and systematize the main methodological characteristics of typical shortcomings of master's research on the legal regulation of educational relations. Research methods: theoretical methods were used in the work: analysis of master's studies on legal regulation of educational relations; study of scientific and pedagogical literature on the problem: systematization, generalization. The paper shows that despite the recent increase in the attention of researchers and experts to the methodology of pedagogical research, in the actual practice of master's theses, including on the problems of legal regulation of educational relations, there are still certain shortcomings in the methodological support of research of this kind. The contribution to pedagogical science is to identify and systematize typical shortcomings of master's studies on legal regulation of educational relations, concerning their methodological support (relevance, contradiction, problem, goal, hypothesis, tasks, etc.).
ScholarChain: The Scholarship Management Platform with Blockchain and Smart Contracts Technology

A smart contract is a set of computer code that works on a blockchain and creates set of rules that are agreed upon by all the entities involved in the contract. It means that when a milestone of a contract is reached and the payments are made, it is registered in the blockchain so that neither party can manipulate the truth or validity or registration. All of these provide additional security, transparency and efficiency. In the higher education sector, although there are blockchain studies that are focusing mainly on the originality of documents and information, studies involving smart contracts are less common. In this study, a blockchain and smart contracts-based platform is presented as scholarship management model in order to create and store contracts between students and the Credit and Hostels Institution (CHI) in Turkey. Then it is confirmed on the Higher Education Information System of Turkey that the student fulfills the continuation requirements at the end of the academic year and automatically authorizes the scholarship. The proposed scholarship management model involves many parties and processes, provides transparency and document integrity, and the most importantly, provides authorization of those who are entitled to receive a scholarship by automated rules.
GAME TECHNOLOGIES AS A GUARANTEE OF EDUCATIONAL EFFECTIVENESS OF TEACHING

I. Balandina, M. Zhukova, T. Moskvitina, E. Frolova, K. Shishkina, L. YuzdovaSouth Ural State Humanitarian Pedagogical University (RUSSIAN FEDERATION)
Σχεδιασμός και υλοποίηση ψηφιακού αποθετηρίου για οργανισμούς του δημόσιου τομέα

In the present diploma, a digital repository was developed to serve the purposesof public organizations. The idea, in essence, is to have all the files posted byan organization stored in a repository, so that both ordinary citizens and publicemployees can search and find the files they are looking for easily and quickly.Initially, a study was conducted on the usefulness of digital repositories, whichstems mainly from the interoperability and easy search method they offer. Then,the features that a repository should have, in order to be useful, were studied,but also the existing repository software was compared, in order to find theappropriate one. In order to find the appropriate software, first the specialfeatures that govern the operation of the public sector in Greece were studiedand secondly the ways of searching for documents offered by each software.Once the initial study was completed, the documents to be used were selectedand these are the general documents and circulars posted on the e-EFKAwebsite. Then, the way to download them through automation was studied.These files were examined to identify the information that could be retrievedfrom them and later used as metadata to describe them. The software chosento be used based on the above study is DSpace. This software is the mostsuitable for posting text documents, but also for describing them. Specifically,it offers 4 metadata schemas (metadata schemas), which are specifications thatdefine the structure and syntax for writing metadata, from which the Dublin CoreMetadata Schema was used. The specific software was selected, as it hasmetadata fields, which are extremely useful for describing the files that havebeen selected for use in this dissertation. Also, this software offers thepossibility of creating new metadata fields in addition to the existing ones. Therequired changes were made after installing the software. Specifically, someformatting was done on the website, but also some new metadata fields werecreated. Finally, the files and their related transmissions were posted. Thereare two ways to upload files, either through the UI (User Interface) provided bythe software, or automatically. The implementation of the automation wasperformed through a script code for obtaining metadata through API(Application Programming Interface) and writing them in a file, so that they canbe used and posted together with the documents described by them in therepository.
Conference 3rd International Conference Forensic Research and Technology YRF of Forensic Research 2021

Meeting International is announcing Young Scientist Awards through 3rd International Conference on Forensic Research & Technology (Forensic Research 2020) which is scheduled at Hong Kong, China during July 20-21, 2020. This Forensic Research conference focuses on “ACCELERATING NEW RESEARCH AND INNOVATIONS OF FORENIC RESERCH AND TECHNOLOGY”.
Sistem Informasi Presensi Untuk Pengembangan PembelajaranTeaching Factory Di SMK Muhammadiyah 02 Andong Boyolali

SMK (Vocational High School) Muhammadiyah 02 Andong is a reference school with ISO (International Organization for Standardization) standard and accredited A. At the beginning of the study, attendance management at SMK Muhammdiyah 02 Andong was still manual, using attendance lists, and there was no database as a medium. storage. This system is intended to make it easier for teachers to attend students during learning time so that at that time it is also recorded and stored in the database so that the picket teacher can monitor it easily and quickly. Based on these problems, the authors conducted research to develop an information system for the development of teaching factory learning at SMK Muhammadiyah 02 Andong Boyolali using PHP as a programming language and codeigniter framework. This system was developed using the waterfall method and system testing using the black box testing method and the System Usability Scale (SUS). The usefulness of this system can help handle attendance recaps quickly, effectively and efficiently so that it can make it easier for the picket teacher to manage the student database at the school. The results of the test showed that 84.3% of respondents received this system well and it can be concluded that this system is included in the good and accepted category.
Page Replacement Technique on the Basis of Frequency of Occurrence of Pages

The problem with the past generation computers was less primary memory. Present-day computers also face the problem of availability of memory both cache and primary memory in terms of cost and space. Age-old algorithms like LRU, FIFO, and Optimal did exist though it was almost impossible to implement optimal algorithm practically. So, experimentation has been made in this paper where a new algorithm has been proposed and it is noticed to have better hit ratio than the existing ones. For this, a frequency-based page indices mechanism has been proposed and it is seen that in many cases of reference string it gives the better result.
Effect of Age and Gender on Facial Emotion Recognition

New research fields and applications on human computer interaction will emerge based on the recognition of emotions on faces. With such aim, our study evaluates the features extracted from faces to recognize emotions. To increase the success rate of these features, we have run several tests to demonstrate how age and gender affect the results. The artificial neural networks were trained by the apparent regions on the face such as eyes, eyebrows, nose, mouth, and jawline and then the networks are tested with different age and gender groups. According to the results, faces of older people have a lower performance rate of emotion recognition. Then, age and gender based groups are created manually, and we show that performance rates of facial emotion recognition have increased for the networks that are trained using these particular groups.
Characterizing Quantum Detectors by Wigner Functions

We propose a scheme for characterizing a photodetector by directly reconstructing the Wigner functions of the detector’s Positive-Operator-Valued Measure (POVM) elements, using displaced thermal mixtures as probes. We report our experimental progress on characterizing a superconducting transition-edge sensor.