Reviewerly/exHarmony huggingface dataset:
Penerapan Scoring System Dalam Penilaian Latihan Pemahaman Materi Toefl

Nowadays, computer skills can be used in various fields to teach, provide information, and provide entertainment. Computers can also be used to assist in the teaching and learning process. To facilitate the delivery of material, it can be packaged attractively in the form of an Android-based application, which is educational and entertaining for students. The topic of this discussion is the design of the toefl understanding training application using the Android-based scoring system method. Where to use this application can help students in learning computerized toefl material. Therefore the authors apply the scoring system method to determine the scores and categories in the toefl assessment, there are three categories, namely less good, good and very good. The purpose of this study was to design an Android-based toefl material application, where the training scores were implemented using the scoring system method. This application will make it easier for students to learn toefl, because the application system is already in the form of android so that it adds to the attractiveness of students.
Teacher’s Perception toward the Use of English for Communication Science Book

&lt;table width="645" border="1" cellspacing="0" cellpadding="0" align="left"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td valign="top" width="439"&gt;&lt;p&gt;&lt;strong&gt;Abstract: &lt;/strong&gt;This study aimed at investigating the teachers’ perception toward the use of English for Communication Science book and how it facilitates the teaching learning process. Descriptive qualitative research was applied in this study. According to the data obtained from questionnaire and interview, the textbook has fulfilled several criteria of a good book: practicality, language use and content, topics, and tasks. However, it has not fulfilled other criteria: suitability to students, skills mastery, relation to syllabus, and design and organization. In addition, the criteria which facilitate the teaching learning process are language use and content and topics.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Abstrak: &lt;/strong&gt;Penelitian ini bertujuan untuk mengetahui persepsi guru terhadap penggunaan buku English for Communication Science dan bagaimana buku tersebut memudahkan dalam proses belajar mengajar. Metode yang digunakan adalah deskriptif kualitatif. Menurut data yang diperoleh dari kuesioner dan interview, buku tersebut telah memenuhi kriteria buku yang baik dalam hal kepraktisan, bahasa dan isi, topic, dan soal latihan, sedangkan belum terpenuhi dalam hal kesesuaian terhadap mahasiswa, penguasaan ketrampilan, kesesuaian dengan silabus, dan desain organisasi. Dengan demikian, kriteria yang dapat memudahkan dalam proses belajar mengajar adalah bahasa dan isi dan topik yang berhubungan dengan jurusan ilmu komunikasi.&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;
Locally Differentially Private Analysis of Graph Statistics

Differentially private analysis of graphs is widely used for releasing statistics from sensitive graphs while still preserving user privacy. Most existing algorithms however are in a centralized privacy model, where a trusted data curator holds the entire graph. As this model raises a number of privacy and security issues -- such as, the trustworthiness of the curator and the possibility of data breaches, it is desirable to consider algorithms in a more decentralized local model where no server holds the entire graph. In this work, we consider a local model, and present algorithms for counting subgraphs -- a fundamental task for analyzing the connection patterns in a graph -- with LDP (Local Differential Privacy). For triangle counts, we present algorithms that use one and two rounds of interaction, and show that an additional round can significantly improve the utility. For $k$-star counts, we present an algorithm that achieves an order optimal estimation error in the non-interactive local model. We provide new lower-bounds on the estimation error for general graph statistics including triangle counts and $k$-star counts. Finally, we perform extensive experiments on two real datasets, and show that it is indeed possible to accurately estimate subgraph counts in the local differential privacy model.
Introduction of Database Management System

Database management system (DBMS) is computer software designed to manage the database in efficiently and conveniently. The main purpose of DBMS is to store and retrieve the data in the convenient and efficient way. This paper presents the overview of the database management system such as its components, data model which describing how data is to be arranged for a specific purpose. Major aim of database is to supply users with an abstract view of data. In database development process normalization play an important role. By using DBMS developers can eliminate duplication data and develop standards by which all data can be measured. It allows organizations to conveniently develop and use databases for various applications by database administrators (DBAs). Currently database management systems (DBMS) are not capable of supporting such flexibility. With the increase of data to be indexed and retrieved and the increasing heavy workloads, modern search engines suffer from Scalability, reliability, distribution and performance problems. This paper presents a new and simple way for integration and compares the performance of our system to the current implementations based on storing the full text index directly on the file system.
Design and Implementation of a Fuzzy Logic Controller for Power Plant Temperature Monitoring and Control using Fuzzylite

Design and implementation of a fuzzy logic controller for power plant temperature monitoring and control used fuzzy lite software to simulate using triangular method and compared with bell shape membership function. Fuzzy logic technology was deployed; the motor temperature and RPM being used as crisp inputs to the fuzzy logic controller with appropriate membership function definitions. The fuzzy logic was designed and simulated using the Fuzzy Lite and Proteus software. It was implemented as firmware written in C++ programming language being executed on the PIC16F877A microcontroller. The results gotten from the simulations and implementation were in concordance as variations in motor temperature influenced motor speed. Triangular method used in this work was compared with Bell shape method used in previous work to ascertain its contribution to knowledge and also discovered that triangular method is more precise in its result.
Educational Game Application for Hijaiyah Letter Recognition for Early Childhood Based on Android

For Muslims, there is an obligation to read, understand, and practice the contents of the Qur'an. But in order to practice and understand the contents of the Koran, you must first be able to read and recognize the hijaiyah letters. To introduce hijaiyah letters to children, it is necessary to use an effective and fun method, which is intended so that children do not experience boredom and stay focused on what is being taught. The case study in the research object was carried out in Babatan village in Katibung District, where the hijaiyah letter recognition method still uses conventional methods, namely using a guidebook called IQRA, besides teaching and learning activities at TPQ are also constrained by rainy weather and holidays that result in learning activities teaching at TPQ will be closed. Based on the description of these problems and increasingly sophisticated technological advances, the researcher proposes to make a game application in the form of educational animation that can make it easier for children in hijaiyah letter recognition patterns, especially ages 3-10 years. The results of this study are the hijaiyah letter recognition educational game application system has been running in accordance with the initial objectives of the study where, the application is able to know and understand the form of letters, distinguish letter forms, how to read letters and sounds of Hijaiyah letters properly and correctly and with the Recognizing Letter Game. The Hijaiyah system is able to attract children's interest in learning at TPQ Al-Muhajirin Babatan Village, Kec. Katibung.
The Impact of Blockchain on the Accounting Profession

The implementation of the blockchain technology in accounting highlights the automation of traditional accounting functions and the transparency, significantly mitigates the risk of internal fraud and increases the importance of the financial information provided and the trust in that information.Professional accountants need to prepare to accept digitalisation as a challenge to become more experienced and to consolidate their status as a reliable third party.In this article we present the blockchain technology and its probable impact on the accounting profession.The aim of this study is to analyse the research on information technologies in accounting and the way these technologies could modify the industries and professions in time.
Tontemboan Affixes Notes in Teaching English Tenses

Teaching English language is a big challenge in Minahasa. Students are still unable to master or even comprehend English even after eleven years learning the language at primary and secondary levels. This research entitled “Tontemboan Affixes Relates to English Tenses” aims to identify, classify and describe the affixes and analyze the similarities and differences of affixes used in both languages, English and Tontemboan. This research used descriptive method, which includes preparation, collecting the data, and analyzing the data. The result showed that some affixes in Totemboan language have different functions of affixes in English. Simple present tense functions the habitual action by adding ma’ before the morpheme, following the verb. The present continuous tense which is formed by adding ma’ as prefix has a global meaning. Past continuous tense indicated by adding the prefix ma’ and simple past tensi indicated by adding a base prefix and infix with the initials are consonant.
Students’ Perceptions of PJOK-AKTIF Learning Strategy

Real contribution in Physical, Sport, and Health Education learning taught in schools at the elementary school level is currently very much needed, not only limited to physical activity practice but is expected to contribute to real learning outcomes, such as fun, varied physical activities and teaching values through physical activity and can increase physical fitness.The research objective was to explore students' attitudes toward the Physical Education Study Program at Universitas PGRI Adi Buana Surabaya to develop PJOK-AKTIF learning strategies whether or not they are applied in elementary level Physical, Sport, and Health Education learning.The type of research method is descriptive quantitative, and the population is students of Physical Education Study Programs.The sample is semester V students of the study program who have taken the Physical Education course; the number of samples is 99 students in the 2018 academic year.The research instrument used a questionnaire developed by the researcher.The data collection technique used a questionnaire distributed using Google form via WhatsApp Group sent to students.The data analysis technique used quantitative descriptive.The results showed that students gave very good responses at 54.00%, students gave good responses at 44.00%, and students gave poor responses at 2%.The conclusion is that the development of PJOK-AKTIF learning strategies based on student attitudes is declared feasible to be applied in Physical, Sport, and Health Education learning at the elementary school level.
Information Security Risk Assessment of Industrial Control System Based on Hybrid Genetic Algorithms

In order to solve the problem of quantitative assessment of information security risks in industrial control systems, this paper proposes a method of information security risk assessment for industrial control systems based on modular hybrid genetic algorithm. Combining with the characteristics of industrial control systems, the use of hybrid genetic algorithm evidence theory to identify, evaluate and assess assets and threats, and ultimately come to the order of the size of the impact of security threats on the specific industrial control system information security. This method can provide basis for making decisions to reduce information security risks in the control system from qualitative and quantitative aspects.
Development of Programmed Robot Scavenger

The proposed programmed automation has been devised keeping in mind the choking of drainage channels due to sludge formation leading to flooding of streets during natural calamities or because of incessant rains. This project also aims at preventing occupational hazards to sewer cleaners. This device will be placed into the drainage system using a telescopic handle. The device has caterpillar track maneuvre. It has a spraying head for water. An elevated conveyor belt will be attached to bring the sludge till the inlet of the vacuum. The suction mechanism collects the debris in a septic treatment bin outside.
Using Multitouch e-Books in Nursing Education

By Jeanne Moore, DNP, FNP-BC, and Leigh Montejo, DNP, FNP-BC, Conway School of Nursing, The Catholic University of America, Washington, DC, [email protected].
Factors Affecting Speaking Anxiety of Thai Students During Oral Presentation: Faculty of Education in TSAI

The objective of this research is to find out the effectiveness to use Foreign Language Classroom Anxiety Questionnaire as a tool that adapted in Speaking skills from first-year until a fourth-year grade of Thai students in TSAI. This study used a Quantitative Method with Survey research by implementing the design of an online questionnaire. In this study, the participants are all Thai students, the Faculty of Education in TSAI who have been studying in Jakarta and west Jawa with 46 Participants. The data were collected by giving Foreign Language Classroom Anxiety Questionnaire as the instruments. The result of significant scores of Thai students after examined the Foreign Language Classroom Anxiety Questionnaire is x 3 556 within the high-anxiety level, it can be said that there are major factors that affecting speaking anxiety during English oral presentation skills of Thai students, the Faculty of Education in TSAI.
An Analysis of Errors in English Writing: A Case Study the Third Semester Students of UBSI

The objectives of this research are to know the errors in the third semester students' writing of Bina Sarana Informatika University and the most frequent error. It is concerned to the grammatical and semantic and substance errors. The data is analyzed by using James' theory in (Mungungu, 2010). The findings show that errors done by the students are spelling 50.9%, fragment 15.7%, punctuation 9.8%, adjective 3%, subject- verb agreement 3.9%, preposition 3.9%, capitalization 3.9%, tenses 2%, verb 2%, literal translation 2%. It can be concluded that the most frequent error is spelling. It because the students missed a letter, added more letter in a word, and exchange the letter. While In grammatical category, the most frequent error is fragment. It is because the most students do not put a subject in a sentence.
Impact of Gender Debiased Word Embeddings in Language Modeling

Gender, race and social biases have recently been detected as evident examples of unfairness in applications of Natural Language Processing. A key path towards fairness is to understand, analyse and interpret our data and algorithms. Recent studies have shown that the human-generated data used in training is an apparent factor of getting biases. In addition, current algorithms have also been proven to amplify biases from data. To further address these concerns, in this paper, we study how an state-of-the-art recurrent neural language model behaves when trained on data, which under-represents females, using pre-trained standard and debiased word embeddings. Results show that language models inherit higher bias when trained on unbalanced data when using pre-trained embeddings, in comparison with using embeddings trained within the task. Moreover, results show that, on the same data, language models inherit lower bias when using debiased pre-trained emdeddings, compared to using standard pre-trained embeddings.
Evaluation of Single-Input Single-Output Radial Basis Function Neural Network in Modelling Empirical 4G Traffic

The fast improvement in the telecommunication sector in general and the accompanying revolution in the mobile communication sector provide a challenging task to telecommunication vendors and operators in satisfying the huge subscribers. To address this challenge, appropriate forecasting models must be provided. This study has developed fourteen different single input single output (SISO) Radial basis function neural network (RBFNN) with Levenberg-Marquardt (LM) and Resilient backpropagation (Rprop) algorithms. Two models, Rprop-SISO RBFNN (1-20-1) and LM-SISO RBFNN (1-20-1) were selected based on computational time and minimum values of prediction. When the performance of the models were compared with empirical 4G hourly traffic data collected from an operator in Ghana, Rprop-SISO RBFNN (1-20-1) gave a better computational time while LM-SISO RBFNN (1-20-1) results indicate minimal values of MSE and NRMSE. Therefore LM-SISO RBFNN (1-20-1) model was selected as the appropriate model to predict 4G hourly traffic.
Separating Chinese Character from Noisy Background Using GAN

Separating printed or handwritten characters from a noisy background is valuable for many applications including test paper autoscoring. The complex structure of Chinese characters makes it difficult to obtain the goal because of easy loss of fine details and overall structure in reconstructed characters. This paper proposes a method for separating Chinese characters based on generative adversarial network (GAN). We used ESRGAN as the basic network structure and applied dilated convolution and a novel loss function that improve the quality of reconstructed characters. Four popular Chinese fonts (Hei, Song, Kai, and Imitation Song) on real data collection were tested, and the proposed design was compared with other semantic segmentation approaches. The experimental results showed that the proposed method effectively separates Chinese characters from noisy background. In particular, our methods achieve better results in terms of Intersection over Union (IoU) and optical character recognition (OCR) accuracy.
Direct Position Determination for Coherently Distributed Noncircular Source Based on Symmetric Shift Invariance

The existing Direct Position Determination (DPD) algorithm of Coherently Distributed (CD) sources rely on the distribution model of CD sources with huge computation cost, which is not practical. To improve further the localization performance, a novel DPD algorithm of CD sources that profits from the characteristics of noncircular signals is proposed based on the symmetric shift invariance of the centrosymmetric array. With the parameterization assumption of CD sources, the direct position determination model is firstly constructed by combining the characteristics of noncircular signals. Then, it is proved that for any centrosymmetric array, the generalized steering vector of CD sources has the property of symmetric shift invariance. Base on this characteristic, the positions of CD sources are directly estimated by fusing the information of all observation stations with no need to consider the distribution model, which reduces the dimension of the parameter to be estimated. Simulation results validate that, compared with the existing localization algorithms of CD sources, the proposed algorithm improves the localization accuracy, and avoids the dependence on the distribution model of CD sources, which is of great practical value.
Robust video content analysis schemes for human action recognition

Introduction: Action recognition is a challenging time series classification task that has received much attention in the recent past due to its importance in critical applications, such as surveillance, visual behavior study, topic discovery, security, and content retrieval. Objectives: The main objective of the research is to develop a robust and high-performance human action recognition techniques. A combination of local and holistic feature extraction methods used through analyzing the most effective features to extract to reach the objective, followed by using simple and high-performance machine learning algorithms. Methods: This paper presents three robust action recognition techniques based on a series of image analysis methods to detect activities in different scenes. The general scheme architecture consists of shot boundary detection, shot frame rate re-sampling, and compact feature vector extraction. This process is achieved by emphasizing variations and extracting strong patterns in feature vectors before classification. Results: The proposed schemes are tested on datasets with cluttered backgrounds, low- or high-resolution videos, different viewpoints, and different camera motion conditions, namely, the Hollywood-2, KTH, UCF11 (YouTube actions), and Weizmann datasets. The proposed schemes resulted in highly accurate video analysis results compared to those of other works based on four widely used datasets. The First, Second, and Third Schemes provides recognition accuracies of 57.8%, 73.6%, and 52.0% on Hollywood2, 94.5%, 97.0%, and 59.3% on KTH, 94.5%, 95.6%, and 94.2% on UCF11, and 98.9%, 97.8% and 100% on Weizmann. Conclusion: Each of the proposed schemes provides high recognition accuracy compared to other state-of-art methods. Especially, the Second Scheme as it gives excellent comparable results to other benchmarked approaches.
A COVID-19 Horizon Scan Looking for Post-Pandemic Implications for Design

So far 137 million people have been infected by the COVID-19 virus worldwide, and over 2.96 million lives have been lost. The urgent and sustained response to COVID-19 has impacted on everyone’s life in one way or another. This paper contributes to the collective and reflective appraisal of COVID-19’s impact by conducting a horizon scan in search for some of the post-pandemic implications for design research. After reviewing some general implications, we investigate two focus areas: (1) supply chain disruptions, and; (2) post-pandemic cities. While some measures may remain temporary and ad hoc, our analysis suggests it is imperative to derive a learning dividend and legacy from this traumatic and profound experience. We conclude with some remarks on community activism and ways for design to evolve in order to create more socially and ecologically just practices and outcomes in the aftermath of this global crisis.
Does Fear of Covid-19 Trigger Fear Of Bitcoin / COVID-19 Korkusu Bitcoin Korkusunu Tetikler mi

This study aims that Bitcoin prices are considered as dependent variables, and the total number of Coronavirus cases in the world, Ethereum Prices, Gold Prices, Coronavirus Google Trend Index, and Crypto Money Google Trend Index are considered as independent variables. Using the ARDL model, it was analyzed with a daily data set between 21.01.2020 - 04.04.2020. It is concluded that the relationship between the variables included in the analysis and Bitcoin prices exists co-integrated in the long term. Within the framework of the findings, investors' fears were interpreted by associating them with Bitcoin and Covid-19.
Application of multimedia technologies in web-education

The development of multimedia technology and network technology, multimedia network training has become inevitable. Multimedia is the best means of communication, education of a society with its own characteristics. In this article, we discuss the model for teaching multimedia technologies in web education and its necessity, and also fully consider multimedia applications in web education.