Reviewerly/exHarmony huggingface dataset:
African Development Bank—AfDB

Established in 1964, the Bank began operations in July 1966, with the aim of financing economic and social development in African countries. The Bank and two other institutions, the African Development Fund and the Nigeria Trust Fund, constitute the African Development Bank Group. The President—who is elected for a five-year term and serves as the Chairperson of the Board of Directors—is responsible for the organization and the day-to-day operations of the Bank, under the guidance of the Board of Directors. The Bank has the following divisions: Power, Energy, Climate, and Green Growth; Agriculture, Human and Social Development; Private Sector, Infrastructure and Industrialization; Regional Development, Integration and Business Delivery; Economic Governance and Knowledge Management; Finance; and Human Resources and Corporate Services. The Development and Business Delivery Model that was endorsed by the Board in April 2016 aimed to transform the Bank's internal organization in alignment with its 2013-22 Strategy and High 5 priorities.
The Use of e-databases and e-journals by Research Scholars in Pakistani Universities: An Evaluative Study

This research was conducted to achieve three objectives; 1) to investigate the usage andacceptability of e-databases and e-journals among the research scholars in selecteduniversities of Pakistan, 2) to indicate the preferred information resource being used byresearchers, and 3) to explore barriers faced by them when consulting these resourcesfor research endeavors. Out of a total population of 4282, a sample of 1031 respondentsfrom four major disciplines were used for the study. The research tool used in thecollection of data was a closed ended questionnaire. Key findings of the study revealedthat most of the respondents accessed e-databases and e-Journals “2-3 times” a week,and have widely accepted the “importance” of these resources in research activities. Inaddition, the respondents usually preferred to use electronic databases, e-books and ejournals(open access) over printed collection. Though, restrictions on e-resources, slowinternet connection, students’ awareness and training were the major obstacles in usinge-resources effectively.
Study on Temperature Variance for SimCLR based Activity Recognition

Human Activity Recognition (HAR) is a process to automatically detect human activities based on stream data generated from various sensors, including inertial sensors, physiological sensors, location sensors, cameras, time, and many others. In this paper, we propose a robust SimCLR model for human activity recognition with a temperature variance study. In this work, SimCLR, a contrasting learning technique is optimized via regulating the temperature for visual representations, is incorporated for improving the HAR performance in healthcare.
온라인 플랫폼을 활용한 베트남어 교수･학습 : 사이버한국외국어대학교에서의 과목개발을 중심으로

With the rise of the 4th Industrial Revolution, a paradigm shift is being demanded across society, and this change is seen in the rapid increase of learners who want online classes that can be taken relatively freely compared to traditional classes that are constrained by time and space. Cyber university’s learning method using an online platform has the advantage of overcoming the limitations of teaching-learning methods and university education in a limited space, and providing educational opportunities to people who need education anytime, anywhere. However, in cyber universities, issues have also been raised about the stability of the educational system, the quality of educational contents, and the appropriateness of educational services. Thus, in order to maximize the learning effect in cyber universities, a system that supports and manages learning participation activities of learners is required so that not only high-quality contents but also various interactions in the teaching-learning process are activated. In this thesis, based on the author’s own experience in subject development and operation, I would like to examine the effects that the interaction between instructor-tutor-learners through the role of a subject-dedicated tutor and the teaching-learning method using an online platform.
Dense-Sparse Deep CNN Training for Image Denoising

Recently, deep learning (DL) methods such as convolutional neural networks (CNNs) have gained prominence in the area of image denoising. This is owing to their proven ability to surpass state-of-the-art classical image denoising algorithms such as BM3D. Deep denoising CNNs (DnCNNs) use many feedforward convolution layers with added regularization methods of batch normalization and residual learning to improve denoising performance significantly. However, this comes at the expense of a huge number of trainable parameters. In this paper, we address this issue by reducing the number of parameters while achieving a comparable level of performance. We derive motivation from the improved performance obtained by training networks using the dense-sparse-dense (DSD) training approach. We extend this training approach to a reduced DnCNN (RDnCNN) network resulting in a faster denoising network with significantly reduced parameters and comparable performance to the DnCNN.
Pengembangan Media Audio Lirik Lagu Untuk Meningkatkan Motivasi Belajar Sejarah Siswa di Sekolah Menengah Atas

The study aims to develop Audio Media and Song Lyrics Collection Book as a medium of learning history that is feasible and practically used by teachers in history subjects in Senior High Schools. Type of research is research and development using the ADDIE model (Analyze, Design, Development, Implementation and Evaluation). The subjects of this research trial were 34 students of class X MIPA1 and 33 students of class X MIPA2 in SMAN 3 Padang Panjang. Data collection instruments used in this study was a questionnaire consisting of media validation test questionnaire, material validation test questionnaire, practicality test questionnaire by teachers and practicality test questionnaire by students. The research data were analyzed by qualitative and quantitative analysis techniques. The results showed that the validity of audio media and song lyric collection books based on the validation research of the material experts obtained an average of 3.59 and 3.50 media experts with very decent criteria. The practicality results obtained by the teacher averaged 3.36 with very practical criteria, while the practicality results obtained by students averaged 3.39 with very practical criteria. Thuse the audio media and song Lyric collection books developed are very feasible and practical to increase student’s motivation to learn history in high school.
Minimization of State Uncertainty in Planning using ML Algorithms

We present a novel methodology for diminishing state vulnerability in arranging before tackling the arranging issue. This is finished by making predictions about the state based on available information, utilizing machine learning techniques. For areas where vulnerability is high, we define an active learning measure for distinguishing which information, when detected, will best improve the accuracy of predictions. We exhibit that a specialist can care for issues with vulnerabilities in the state with less arranging effort contrasted with standard arranging techniques. Also, specialists can tackle issues for which they couldn't and legitimate plans without utilizing predictions. Test results also exhibit that using our active learning measure to distinguish information to be detected prompts gathering information that improves the prediction measure.
Opinion Mining through Enhanced Lexicon Approach

Abstract The World Wide Web’s rapid growth has enhanced online communication. One of the approaches to putting user views is the use of social networking sites. The user’s opinion needs to be analyzed by studying user’s input text using techniques of machine learning with subjectivity, emotion, sentiment analysis or polarity calculation. Most of the existing work in the field of opinion mining has largely focused on identifying sentiment polarity as positive, negative, or neutral. This paper presents an evaluation of sentiments from the 2016 Kashmir Unrest tweets to find people’s opinions as peace or protest during the unrest using enhanced lexicon approach. Lexicon-based approach has three methods of opinion mining: manual based method, dictionary-based method and corpus-based method. Dictionary-based method is used in this paper where two lexicons, the lexicon for peace and the lexicon for protest are created and then expanded using Word2Vec to determine opinion of general public during 2016 Kashmir Unrest.
Quadtree partitioning scheme of color image based

Image segmentation is an essential complementary process in digital image processing and computer vision, but mostly utilizes simple segmentation techniques, such as fixed partitioning scheme and global thresholding techniques due to their simplicity and popularity, in spite of their inefficiency. This paper introduces a new split-merge segmentation process for a quadtree scheme of colour images, based on exploiting the spatial and spectral information embedded within the bands and between bands, respectively. The results show that this technique is efficient in terms of quality of segmentation and time, which can be used in standard techniques as alternative to a fixed partitioning scheme.
ANALYSIS OF FACILITIES AND INFRASTRUCTURE MANAGEMENT IN SMPN SATAP 4 BARRU SCHOOL

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Event-Based Feature Tracking in Continuous Time with Sliding Window Optimization

We propose a novel method for continuous-time feature tracking in event cameras. To this end, we track features by aligning events along an estimated trajectory in space-time such that the projection on the image plane results in maximally sharp event patch images. The trajectory is parameterized by $n^{th}$ order B-splines, which are continuous up to $(n-2)^{th}$ derivative. In contrast to previous work, we optimize the curve parameters in a sliding window fashion. On a public dataset we experimentally confirm that the proposed sliding-window B-spline optimization leads to longer and more accurate feature tracks than in previous work.
Pembekalan Ilmu Perhitungan Digital Berbasis Stand Alone dan Cloud Melalui Excel dan Spreadsheet

The current prolonged pandemic requires every individual to do social distancing and physical distancing. This made a difference study and work patterns. In order to overcome this and prepare workforce in the future, it requires an habituation of learning patterns and work through devices you own from your home or residence. To improve the performance of the learning process, an additional learning mechanism is needed on the use of technology, especially in the field of digital calculations. In order to solve this problem on the partner's side, the team made a solution, namely in the form of provisioning with a training pattern using Microsoft Excel which is the basis for a general calculation pattern commonly used both in the world of education and in the world of work and also the use of Google Spreadsheets. The method used in this debriefing is learning by doing, which is a method where every student who follows it will go directly to practice by following instructions from the training instructor from the PKM team. Based on the training provided, the average post test result is 76.6 from the 0-100 range, or increasment 23,28% at from Pre Test to Post test
A Survey on Simulation Sickness in Virtual Environments

Virtual Reality(VR) is an emerging technology with a broad range of application in training, entertainment, and business. To maximize the potentials of virtual reality as a medium, the unwelcome feeling of simulation sickness needs to be minimized. Even with advancements in VR, the usability concerns are barriers for a wide-spread acceptance. Several factors (hardware, software, human) play a part towards a pleasant VR experience. The reviewed scientific articles are mostly part of documents indexed in digital libraries. In this paper, we review the potential factors which cause simulation sickness and minimize the usability of virtual reality systems. We review the best practices from a developer&amp;rsquo;s perspective and some of the safety measures a user must follow while using the VR systems from existing research. Even after following some of the guidelines and best practices VR environments do not guarantee a pleasant experience for users. Limited research in VR environments towards requirement specification, design, and development for maximum usability and adaptability was the main motive for this work.
UUBE for Secure Sharing of Personal Health Records in Cloud

Cloud based Personal Health Record (PHR) is a prominent cloud based platform for switching a person’s health information in a secure manner. They are next generation cloud platform making possible for well organized , reliable & scalable data access to foster the public care. There happen numerous security issues when records of the data owners are reevaluated through the outsider cloud suppliers. The health records which are kept secret should be put away and recovered through a protected source with no misfortune in the information. Nonetheless sharing and probing of the data is the bottom line, but when it is outsourced beyond doubt it is a burdensome task. It might prompt reveal the delicate data thus the records may get helpless against the technocrats. In this article, we have suggested a novel access control structure called as User Usage Based Encryption (UUBE) constructed on the searchable attribute based encryption to guarantee the data protection. Utilization is planned as credential with a time span to each private attribute. The client can decipher only if there is a match between the accreditation's related with the attributes.  Utilizing the feature extraction the accessible encryption plot empowers a predictable directing of encoded credits. Prior to starting the encryption conspire we apply the singular value decomposition algorithm to the non-utilized or less utilized credits to diminish the trait set. Moreover the information client privacy traps are handled utilizing the semantic grouping. To save the client secrecy a solid overlay protection convention is planned. We show a total security investigation with the goal that our suggested framework rules the cutting-edge approaches regarding communication and encoding cost.
Using Process Writing Approach (PWA) to Teach Writing Descriptive Text

The research aim was to find out whether or not there was a significant difference in students' writing performance from descriptive passage among learners who practiced using the Process Writing Approach and those who were not. The design of that research used quasi-experimental. Participants were selected from X TKJ 3 being the experimental group and X TKJ 2 being the control group. Instruments of this study used a written test. There were five topics about the descriptive text in which students chose one of the issues. A paired sample t-test and independent-sample t-test were used to investigate the data. The outcome acquired from the paired sample t-test confirmed that students' writing achievement increased in the descriptive text after using the process writing approach. Independent-samples t-test analysis revealed that pvalue (0.008) was lower than άvalu (0.05). Further analysis indicated a significant difference in students' writing performance from a descriptive passage within learners who practiced using the Process Writing Approach.
EFEKTIVITAS MEDIA E-LEARNING BERBASIS EDMODO TERHADAP HASIL BELAJAR SISWA KELAS V SDN 02 NGABUL JEPARA

This study aims to analyze the effectiveness of Edmodo-based E-Learning media on the learning outcomes of fifth grade students on the theme of 6 Heat and the Transfer of Indonesian Language and PPKn SDN 02 Ngabul Jepara in the academic year 2020/2021. This research uses pre-experimental designs with one-group pretest-posttest design. The use of Edmodo-based E-Learning media on the learning outcomes of fifth grade students on the theme of 6 Heat and Transfers of Indonesian and PPKn content shows that in the pretest results on Indonesian language content there are 20 students declared complete while on PPKn content 25 students are declared complete and on the posttest results In the Indonesian language content, 34 students were declared complete while in the PPKn content there were 35 declared complete. The statistical test showed that there was the effectiveness of Edmodo-based E-Learning media on the learning outcomes of the theme of 6 Heat and Its Transfer in Indonesian content, the t count was -8.241 and the sig (2-tailed) value was 0.000 0.05 and PPKn was obtained. the result of t count is -9.031 and the sig value (2-tailed) is 0.000 0.05. Based on the results of these statistical tests, it can be concluded that the use of Edmodo-based E-Learning media is effective in using the learning outcomes of fifth grade students on the theme of 6 Heat and the Transfer of Indonesian Language and PPKn content.
Replacing DWT with DTCWT in blind image rotation angle estimation

During the image tampering, rotation is often involved to make the forgery more convincing. Hence, estimating the rotation angle accurately and locally is of forensic importance. Recently, a novel rotation angle estimation scheme was proposed based on linear pattern (LP), achieving state of the art performance especially in the case when the rotation angle is small. However, due to the limitations of the involved discrete wavelet transform (DWT), the existing LP based method cannot always accurately detect rotated linear pattern from a rotated image. To fill this gap, we propose to extract the rotated LP using dual tree complex wavelet transform (DTCWT). Thanks to the good directional selectivity of DTCWT, the proposed method can extract the LP more accurately. Experiments show that our proposed method performs better than the state of the art in rotation angle estimation, and is also a promising forensic tool for tampering localization.
CORRELATION AMONG GRAMMAR MASTERY AND VOCABULARY SIZE TOWARD TRANSLATION ABILITY ON REPORT TEXT

The crucial problem of translating Indonesia to English language are the students’ lack of knowledge and mother tongue (source language) that two of them are grammar and vocabulary. The researcher focused to measure the correlation among grammar mastery and vocabulary size toward translation ability on report text at seventh semester students in State Islamic Institute of Palangka Raya that use quantitative method with a correlational design. The researcher’s instruments were three test which were grammar mastery, vocabulary size, and translation test that were tested to the 32 students’ translation class in academic year 2017/2018. The numerical data were analyzed by Pearson Product Moment that showed that: (1) the most students got “fail” (43.75%) grammar mastery, (2) the most students got “excellent” (46.875%) vocabulary size, (3) the most students got “enough” (87.5%) translation ability. The significant correlation among three variables were proved by correlation coefficient 0.604 (strong category), Fchange &gt; Ftable = 8.349 &gt; 3.33, and the contribution of grammar mastery and vocabulary size delivered 36.5%. Thus, it sums that students’ grammar mastery and vocabulary size correlate with the quality of students’ translation ability on report text at seventh semester students in academic year 2017/2018. Keywords: Grammar Mastery, Vocabulary, Translation
The use of information technologies in the field of online drug crime as a threat to public safety

Today, the issue of drugs distribution through the Internet is especially urgent, since the World Wide Web has become an integral part of the life of the population, especially among adolescents and the youth. The article reveals the problem of the contact-free sale of narcotic drugs through virtual networks, which poses a threat to state and public security. Factors for the growth of cybercrime in the fi eld of drug trafficking have been identifi ed. The author defined the main aspects of the state legal regulation of committing drug crimes in the Internet space. English version of the article on pp. 80-84 available at URL: https://panor.ru/articles/usage-of-information-technologies-in-narcotic-drug-crime-system-as-a-threat-to-public-security/61600.html
Likelihood estimation of sparse topic distributions in topic models and its applications to Wasserstein document distance calculations

This paper studies the estimation of high-dimensional, discrete, possibly sparse, mixture models in topic models. The data consists of observed multinomial counts of $p$ words across $n$ independent documents. In topic models, the $p\times n$ expected word frequency matrix is assumed to be factorized as a $p\times K$ word-topic matrix $A$ and a $K\times n$ topic-document matrix $T$. Since columns of both matrices represent conditional probabilities belonging to probability simplices, columns of $A$ are viewed as $p$-dimensional mixture components that are common to all documents while columns of $T$ are viewed as the $K$-dimensional mixture weights that are document specific and are allowed to be sparse. The main interest is to provide sharp, finite sample, $\ell_1$-norm convergence rates for estimators of the mixture weights $T$ when $A$ is either known or unknown. For known $A$, we suggest MLE estimation of $T$. Our non-standard analysis of the MLE not only establishes its $\ell_1$ convergence rate, but reveals a remarkable property: the MLE, with no extra regularization, can be exactly sparse and contain the true zero pattern of $T$. We further show that the MLE is both minimax optimal and adaptive to the unknown sparsity in a large class of sparse topic distributions. When $A$ is unknown, we estimate $T$ by optimizing the likelihood function corresponding to a plug in, generic, estimator $\hat{A}$ of $A$. For any estimator $\hat{A}$ that satisfies carefully detailed conditions for proximity to $A$, the resulting estimator of $T$ is shown to retain the properties established for the MLE. The ambient dimensions $K$ and $p$ are allowed to grow with the sample sizes. Our application is to the estimation of 1-Wasserstein distances between document generating distributions. We propose, estimate and analyze new 1-Wasserstein distances between two probabilistic document representations.
Rape Goes Cyber: Online Violations of Sexual Autonomy

Rape is the most severe sexual offense, involving one of the most feared and reviled acts a person can inflict on another. But what makes something rape? Initially, only penial-vagina forceful penetration; then, other forceful penial penetrations were added, oral and anal; and later the forceful insertion of inanimate objects as well. The requirement of using force lost its exclusiveness and much of its normative power, paving the way for other kinds of rape: sex by non-forceful coercion, sex by sedation, sex with incompetent victims, sex by fraud, and other forms of problematic sex. The normative debate about each form is ongoing, and in a manner of speaking, rape is a limitless idea. Where will the rape offense go next?Cyberspace, apparently. The Israeli Supreme Court has recently affirmed convictions of rape performed by distant words. The perpetrators conversed with children, teenagers and adult women online, using fraud and blackmail to manipulate them into masturbation and self-penetration. This groundbreaking judicial development is the inspiration to a normative analysis, revolving around Western notions of rape. Should such ill-intended communications constitute rape?The article will normatively scrutinize the virtual rape thesis. It will analytically deconstruct the normative notion of rape into three facets, and examine each separately: the physics of the offensive scenario; the settings thereof, the manner in which sexual autonomy is violated; and finally, the matter of proper criminal labeling. It will conclude that while sexual autonomy is indeed under attack in cyberspace, the framework of rape is unsuitable to handle this form of offensiveness.