Reviewerly/exHarmony huggingface dataset:
Aktivitas Belajar Mahasiswa dalam Perkuliahan Pendidikan IPS dengan Menerapkan Model Pembelajran Kooperatif Tipe Make A Match

The low level of student activity in Social Studies Education courses is a problem for students' ability to interact well with fellow students, lecturers and learning resources. This condition requires the application of an effective learning model to increase student learning activity in the classroom. This study answered two research questions, namely how student learning activities in Social Studies Education courses use Make a Match cooperative learning and how to apply Make a Match cooperative learning models in increasing student learning activities in Social Studies Education for Elementary School courses. This research is a Classroom Action Research (CAR). The subjects of this study were the fifth semester students of Class C of the Elementary School Teacher Education Study Program who attended the Social Studies Education for Elementary School course as many as 47 students. Research data were collected through observation. The data analysis technique used was descriptive analysis. The results showed that (1) the dominant aspects of learning activities in Social Studies Education courses with the Make a Match type cooperative learning model were aspects of group interaction and aspects of answering questions; and (2) Social Studies Education for Elementary School courses with the Make a Match type cooperative learning model can increase student learning activities, the indications are that the percentage score of student learning activities is above 70 (78.72%).
FlowVocoder: A small Footprint Neural Vocoder based Normalizing Flow for Speech Synthesis

Recently, non-autoregressive neural vocoders have provided remarkable performance in generating high-fidelity speech and have been able to produce synthetic speech in real-time. However, non-autoregressive neural vocoders such as WaveGlow are far behind autoregressive neural vocoders like WaveFlow in terms of modeling audio signals due to their limitation in expressiveness. In addition, though NanoFlow is a state-of-the-art autoregressive neural vocoder that has immensely small parameters, its performance is marginally lower than WaveFlow. Therefore, in this paper, we propose a new type of autoregressive neural vocoder called FlowVocoder, which has a small memory footprint and is able to generate high-fidelity audio in real-time. Our proposed model improves the expressiveness of flow blocks by operating a mixture of Cumulative Distribution Function(CDF) for bipartite transformation. Hence, the proposed model is capable of modeling waveform signals as well as WaveFlow, while its memory footprint is much smaller thanWaveFlow. As shown in experiments, FlowVocoder achieves competitive results with baseline methods in terms of both subjective and objective evaluation, also, it is more suitable for real-time text-to-speech applications.
Pengaruh Media Mobile Learning Berbasis Android “ChemOndro” Pada Model Discovery Learning Terhadap Hasil Belajar Peserta Didik Kelas X SMA Negeri 8 Bone (Studi Pada Materi Pokok Larutan Elektrolit dan Nonelektrolit)

This study is a quasi-experimental research that aimed to know the effect of mobile learning “ChemOnDro” android based media in discovery learning to student achievement of class X SMA Negeri 8 Bone on subject matter of electrolyte and nonelectrolyte solution. The study design used is "pretest-posttest control group design". The population was all the student of class X MIPA SMA Negeri 8 Bone which is consists of six classes. The sampling technique is random sampling, that the sample are a class X MIPA 1 as an experimental class and class X MIPA 2 as a control class. The independent variable is mobile learning “ChemOnDro” android based media in discovery learning model and discovery learning model without mobile learning “ChemOnDro” android based media, and the dependent variable is student achievement. Result of analysis prerequirement of inferential statistic toward n-gain result, show that the data in experiment class and control class didn’t distributed normaly, but it has homogen varians. The hypothesis test done using with parametric test by Man-Withney with ∝=0.05 was done with zcalculated &gt; ztable (2.07&gt;1,64). Based on these data, it can be concluded that there is an effect of mobile learning “ChemOnDro” android based in discovery learning to student achievement of class X SMA Negeri 8 Bone with subject matter of electrolyte and nonelectrolyte solution.
Development of an Employee Retention Plan: A Case Study of Lebanon

Nowadays the employee turnover is very high in the organizations the thing which incurs high costs on the organization in terms of both money and time investments because every skilled employee resigns needs time to be trained and in order to cope with the workplace environment. The study aims to identify the main reasons behind the resignation of the employees in order to reduce the turnover rate in the organization and maximize performance. After identifying the leading causes of the resignation, the next step will be putting strategies in order to retain employees and ensure job satisfaction. Interviews and questionnaires will be distributed along Company X to collect data. Both methods, qualitative and quantitative, will be used to analyze the data collected to validate the hypothesis. The findings will show that there is a positive relationship between employee retention and employees performance in Company X. As employee retention increase, the performance of Company X is likely to increase.
CONCEPT FOR DEVELOPMENT OF EMOTIONAL COMPETENCES AND CONFLICT MANAGEMENT SKILLS THROUGH MEDIATION METHODS AT THE AGE OF 3-7 YEARS

This report examines the concept of developing emotional competencies at the age of 3 - 7 years, which is the basis of an innovative for Bulgaria model for conflict management in preschools. The conclusions raise as relevant and important the question of the difference between emotional intelligence and emotional competence and how they are integrated into the educational methodology of preschool education at the moment.
Inverse Learning Approach to Reward Design for Deadlock-free Route Planning Problems for Automated Guided Vehicles

In recent years, with the development of IoT technologies such as 5G, it is expected to operate large-scale route planning for many AGVs (Automated Guided Vehicles). Deadlock is caused on the routing of AGVs when the route us conducted by conventional reinforcement learning approach. In this study, we propose a route planning method that avoids deadlocks by using inverse reinforcement learning to design a reward that is close to the route planning optimization method. We compare the proposed method with conventional deadlock avoidance methods to verify the usefulness of the proposed method.
Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective

Backdoor attacks have been considered a severe security threat to deep learning. Such attacks can make models perform abnormally on inputs with predefined triggers and still retain state-of-the-art performance on clean data. While backdoor attacks have been thoroughly investigated in the image domain from both attackers' and defenders' sides, an analysis in the frequency domain has been missing thus far. This paper first revisits existing backdoor triggers from a frequency perspective and performs a comprehensive analysis. Our results show that many current backdoor attacks exhibit severe high-frequency artifacts, which persist across different datasets and resolutions. We further demonstrate these high-frequency artifacts enable a simple way to detect existing backdoor triggers at a detection rate of 98.50% without prior knowledge of the attack details and the target model. Acknowledging previous attacks' weaknesses, we propose a practical way to create smooth backdoor triggers without high-frequency artifacts and study their detectability. We show that existing defense works can benefit by incorporating these smooth triggers into their design consideration. Moreover, we show that the detector tuned over stronger smooth triggers can generalize well to unseen weak smooth triggers. In short, our work emphasizes the importance of considering frequency analysis when designing both backdoor attacks and defenses in deep learning.
Analisis Effect Size Pengaruh Bahan Ajar E-Book terhadap Literasi Sains Peserta Didik pada Abad 21 dalam Pembelajaran Fisika

The research objective was to see the effect size of the e-book on students' scientific literacy. The effect size analysis was observed from 20 international and national journals with the analysis category in terms of grade level, teaching materials and scientific literacy. This research uses descriptive method with respondents from previous research from journals. Data were analyzed using descriptive statistics. The results showed that the effect size of the effect of e-books on scientific literacy in the 21st century in learning physics in terms of materials and classes at the high school level is classified as high effect size 1.12. As for the analysis of the effect size of the results of scientific literacy based on three categories of knowledge with an effect size of 1.12 having a very high effect on e-books, skills with an effect size of 0.87 have a high effect on e-books and attitudes with an effect size of 0.57. moderate effect. Based on the analysis of the effect size of the e-book on literacy, it was found that the effect size of the three categories had a high effect.
International Crimes in the Digital Age: Challenges and Opportunities Shaped by Social Media

Due to the growing influence of social media on the dynamics of international criminal law, the investigation and prosecution of international crimes have taken an entirely new dimension. Particularly, the increasing use of these platforms has led to the rise of new types of evidence, namely user-generated evidence thus creating considerable opportunities, but also unique legal challenges. Indeed, while social media became a source of evidence for public authorities, these same platforms are used to fuel offline brutality and atrocities. This article thus provides a comprehensive insight into the advantages and disadvantages produced by the growth of user-generated evidence. It also calls for a necessary legal change to accommodate the digital age. Indeed, it is imperative to adjust the existing legal framework in order to contain the downsides of user-generated evidence on the one hand, and promote their effective use in the International Criminal Court to promote justice and transform UGE in the much needed mine of evidence.
소셜미디어 활용 영어학습이 대학생들의 인식과 정의적 요인에 미치는 영향 분석

The purpose of this study is to analyze the effects of English learning through social media on the perception and affective factors of college students. To this end, researchers examined whether the educational use of YouTube and KakaoTalk, popular among college students in Korea, differs according to English improvement, affective factors, and English level. The subjects of this study were 63 freshmen majoring in Medical Convergence, who were taking college English at C University located in Gangwon-do. An online questionnaire was used for data collection. The collected data were analyzed using Jamovi, a statistical program. The results are as follows. First, the participants positively changed the perception that the use of social media had on the overall improvement of English. Second, the affective domains such as self-confidence, attitudes, values, beliefs, and interests of the participants also changed positively. Finally, it was confirmed that social media has educational value regardless of English level.
VR-technologies in Animation

The article analyzes animated VR-experiences created by immersing an animation director or artist in virtual reality. Computer technologies, combined with the talent and creative skills of animators, allow us to find new approaches to creating narratives in virtual reality during experiments. When creating stories in VR-environments directors face questions about changing the principles of editing animated works, changing the limiting borders of the frame, about the lack of control over the viewer's gaze and actions, the answers to which allow the authors to come to their own stylistic decisions and find new artistic approaches to creating animated narrative. In virtual reality, the artist controls the sensor manipulators and the functionality of a VR modeling software tool in order to create a special spectacle and enhance the viewer's experience by creating interesting compositional solutions and stylistically interesting visual images, exciting storylines. Immersing the recipient in a virtual narrative has more emotional impact than watching an animated work on screen. The immersion effect, accompanies by new sensations, is achieved by switching perceptual organs from visual images, to sound or tactile sensations, for interactive participation with the possibility of interaction with objects of animation or surrounding space. The progress of technology and the growing number of users stimulate animators to create experiments in virtual reality. These experiments provide the basis for studying animated works created in VR and for viewing in VR, in terms of its artistic, aesthetic and emotional components, as well as its perception by the viewer.
THEME PATTERNS IN INTRODUCTION SECTIONS OF RESEARCH ARTICLES WRITTEN BY UNDERGRADUATE STUDENTS

This study analyzed theme patterns of 41 introduction sections of research articles written by undergraduate students of Indonesia, especially students of the English department in Universitas Negeri Padang. The sources of data are from e-journal archives of E-journal English Language and Literature (JELL) and Journal of English Language Teaching (JELT) of Universitas Negeri Padang. The data were analyzed by classifying the theme and rheme structure of clause sequences and then determining the patterns. This research is a descriptive study with a qualitative approach. The result of the findings shows that a simple linear pattern (42,70%) found to be the most dominant pattern of the theme found in the data. In addition, new patterns (27,35%) are also frequently used in the data. These findings indicate that most students tend to write their ideas more cohesive than coherent as the lack of using an interpersonal theme and derived hyper-theme pattern found in the data.
Deep Learning for Recognition of Digital Modulations: A Detailed Study

The automatic modulation recognition of the received signal is very attractive in both military and civilian applications. In recent years, deep learning techniques have received much attention since their excellent performance in signal, audio, image and video processing. This paper examines the feasibility of using deep learning algorithms on automatic recognition of the received radio signals' modulation schemes. Modulation recognition has been performed on eight digital modulation types with a signal-to-noise ratio (SNR) from -20dB to 20dB. First, a vanilla neural network is used to classify the type of modulation. Then, convolutional neural networks (CNN) and recurrent neural networks are applied for modulation recognition. These neural networks are widely used in image and signal processing applications. This is followed by designing the other architectures, including densely connected neural network (DenseNet), inception network, recurrent neural network (RNN), long-short term memory network (LSTM), and convolutional long short-term memory deep neural network (CLDNN) for modulation recognition problem, and their results are presented. During this investigation, a basic model is initially considered for each architecture, and then the network performance is studied by adjusting its parameters. The simulation results show that the proposed modified CLDNN model can provide an accuracy of 98% in high SNRs.
Wavelet Transform-Based Photorealistic Style Transfer Using Optimal Transport

스타일 변환(style transfer)은 컨텐츠 이미지(content image)의 공간 정보를 유지하면서도 컨텐츠 이미지의 스타일을 스타일 이미지(style image)의 스타일로 바꾸는 과정이다. 기존 연구로는 스타일 분포(style distribution)의 second-order statistics가 같아지도록 그람 행렬(Gram matrix)을 이용하는 방법과 instance normalization을 이용하는 방법 등이 있다. 본 논문은 이 방법들을 일반화시킨 최적 전송(optimal transport)을 웨이블릿(Wavelet) 변환에 적용해서 사진과 비슷한 이미지를 생성하는 실사적 스타일 변환(photorealistic style transfer)에서 스타일 변환 성능을 개선하는 방법을 제안한다.
An Assistance to keep track of Senior Individuals

In current day world, monitoring your cherished elderly person is becoming a tough job. Monitoring the health condition of the elderly person at home is a tough job. In particular, elderly patients should be regularly checked and their loved ones should be updated from time to time about their health condition at work. Thus, this is an innovative method that easily automates this process. This technology provides support to monitor the protection of the elderly who utilize sensors to watch their senior health and use the Internet, in case of any problems, to notify their loved one.
Circular Interval-valued Computers and Simulation of (Red-green) Turing Machines

Interval-valued computing is a kind of massively parallel computing. It operates on specific subsets of the interval [0,1) – unions of subintervals. They serve as basic data units and are called interval-values. It was established in [9], by a rather simple observation, that interval-valued computing, as a digital computing model, has computing power equivalent to Turing machines. However, this equivalence involves an unlimited number of interval-valued variables. In [14], the equivalence with Turing machines is established using a simulation that uses only a fixed number of interval-valued variables and this number depends only on the number of states of the Turing machine – in a logarithmic way. The simulation given there allows us to extend interval-valued computations into infinite length to capture the computing power of red-green Turing machines. In this extension of [14], based on the quasi-periodic techniques used in the simulations in that paper, a reformulation of the interval-valued computations is given, named circular interval-valued computers. This reformulation enforces the finiteness of the number of used interval-valued variables by building the finiteness into the syntax rules.
Multi-Features Skipping Rope / Mohamad Izrul Hafiz Hamzah

The product that being sell by this company is multi-feature skipping rope. There are three additional function in this product which are heartbeat monitor, jumping counter and body temperature monitor. The target market of this product is people that involve in sport activities especially teenagers and adults. There is no product of skipping rope in the market that provide three functions altogether in market nowadays. This is the first product that come with three important functions for human. The price of this product is RM85. The profit of this products is 30% of the product price which is RM35. There are six top managements team in this company and we also have partners with another company that will manufacture our product. The company that will manufacture our product is DF Robotic Company.
Fault Tolerant Arithmetic and Logic Unit in Reversible Logic for Low Power Applications

To meet expectations of the futuristic technologies, thrust is on fast communication, low power, high computational speeds with delay intolerance. VLSI technology is laboring to meet the demands by incorporating low-power solutions to improve performance. Component size has come to Nano scales however, it has challenges of managing heat dissipation and physical limitations in fabrication. Reversible logic technology has gained momentum in research due to its prominence in Quantum computing and zero power dissipation. The arithmetic and Logic Unit is the significant component of any computing architecture, carrying out operations rigorously while consuming power for the endurance of performance. The proposed approach of designing the fault-tolerant Arithmetic and Logical Unit (ALU) in reversible logic for future computers. Analysis of the proposed design to existing designs is on the quantum cost (QC), garbage output (GO), ancilla input (AI), gate utilization (GC) and number of operations achieved. Improvements observed is at an average of 70% in AI and GC, 59% in QC , 53% in GO and operations are up by 33% to cater to the least power consumption applications.
PEMBELAJARAN MENULIS TEKS NEGOSIASI DENGAN MENGGUNAKAN METODE DISCOVERY LEARNING SETTING DECISION MAKING

This study aims to describe the implementation of learning to write negotiation text using discovery learning method of decision making setting, and to describe the students' ability in writing negotiation text. The research was conducted using a qualitative descriptive method. The subjects in this study were 22 high school class X students. Based on the results of the observer's assessment that 94.64% of teachers were able to carry out learning activities well. Based on the results of the observer's assessment that 96.42% of students were able to follow the learning process of writing negotiating texts well. The results of the research conducted showed that students had difficulty understanding aspects of spelling. The results of the test of the ability to write negotiation text for class X MIPA I high school students got an average final score of 81.79.
Pengaruh Motivasi Belajar dan Perhatian Orang Tua terhadap Prestasi Belajar Matematika Siswa Kelas VIII SMPK

This study aims to determine the effect of learning motivation and parental attention on mathematics learning achievement of grade VIII students at SMPK Tunas Daud Mataram 2020/2021. This type of research is ex-post facto. The sample class was selected using a saturated sampling technique, obtained 34 students consisting of 2 classes. Data retrieval in this study was carried out by providing a questionnaire on learning motivation and parental attention and a number pattern test. Analysis of SPSS 21 program data, consisting of prerequisite tests and hypothesis testing. The prerequisite test on the data analysis used, namely the normality test of the results obtained on learning motivation, namely 0.245 and parental attention, namely 0.162 so that it is said that the data is normally distributed, the linearity test of the results obtained on learning motivation is 0.958 and parents' attention is 0.597 so that The data has a relationship with learning achievement and the multicollinearity test of the results obtained is 1.340, namely there is no relationship between independent variables. The contribution of learning motivation to mathematics learning achievement was 19.6% and parents' attention to mathematics learning achievement was 19.2%. The existence of a positive relationship between learning motivation and learning achievement and parents' attention to learning achievement is indicated by a positive correlation coefficient. A positive coefficient value indicates that the higher the motivation to learn and the attention of parents, the higher the student's learning achievement.