Reviewerly/exHarmony huggingface dataset:
A Gestalt and Semiotic Analysis of Brand Communication on Disability Inclusion: The Case of Malaysia and The US

The Sustainable Development Goals (SDGs) underscore the United Nations’ effort in advocating disability inclusion in education and the infrastructure of member countries. Brands can also play their role by promoting disability inclusion through their brand messages. Brand messages are powerful as they advocate causes and ideals that include disability inclusion through repetitive and omnipresent messages whose ultimate goal is to influence the target audience’s behaviour. This multiple case study compared brand communication from ten brands each originating from Malaysia and the United States using Saussure's model of semiotics. It was found that Common Fate is the fundamental gestalt principle in most brands’ communication on disability inclusion of both countries and that positive nomenclature was used as the signifier that underlined the organisations' positive perception of disability inclusion. Our moral obligation is to include persons with disabilities (PwDs) in society, and brands can play their role by promoting the universal ideal of disability inclusion. This study was borne out of the intrigue in understanding how images in brand communication have been incorporating disability inclusion. Brand messages are ubiquitous and powerful as they can set the agenda on disability inclusion by giving it appropriate prominence. The proposed multiple case study will examine brand communication from ten brands, each originating from Malaysia and the United States. The criteria used to select the brands will be vital as confirmed by the industry in the case of Malaysian brands and the highly indexed brands deemed by the Disability Equality Index (DEI) for U.S. brands. Saussure's model of semiotic analysis will be used to examine the brand messages in terms of their communication on disability inclusion. The model of semiotics to be adopted is broken into components such as a sign, signifier, and signified, thus providing us with an insight into the sign in the form of websites by brands, the dominant symbols (signifier), and the interpretations of these symbols (signified). It was found that Common Fate was the key gestalt principle found in the communication on disability inclusion by all brands in Malaysia and the US and that positive nomenclature was adopted as signifiers that promoted the organisations’ positive perception of disability inclusion.
Pelatihan Peningkatan Kompetensi Programming Berbasis Desktop Menggunakan Software Visual Studio Net Pada SMK Swasta Islam Proyek UISU Siantar

Technology in this era is growing rapidly, especially in the field of computers and technology. Where we can see that these developments can facilitate the work of humans or employees and employees. In the education sector, computer science is needed so that teachers can easily provide up-to-date material and are not left behind in today's very rapid technological developments. For this reason, training on programming-based computer science is needed. Many teachers or employees in their understanding of knowing computers are only limited to Ms. Because of that, Office is often used in daily activities. In computer science, there are actually many applications/programs that can make work easier. For this reason, this training was created to introduce one of the application programs in computer science, namely the Visual Studio Net application and the PHPMyAdmin Database. In the training activities carried out at the UISU Siantar Project Islamic Private Vocational School to build a desktop-based information system development process or an application embedded in a computer. Application designed with offline software that has been prepared by the school
PENGARUH STRATEGI (CTL) OLEH GURU PENDIDIKAN AGAMA KRISTEN TERHADAP KEAKTIFAN BELAJAR SISWA KELAS V DAN VI DI SD NEGERI 173366 PARMONANGAN TAHUN AJARAN 2021/2022

Abstract, The purpose of this study was to determine the effect of Strategy (CTL) by Christian Religion Teachers on the learning activity of Grade V and VI students at SD Negeri 173366 Parmonangan for the 2021/2022 Academic Year. The method used in this research is inferential statistical method. The population is all students of grades V and VI at SD Negeri 173366 Parmonangan with a total of 225 people and a sample of 90 people.&#x0D; Data was collected using a closed questionnaire consisting of 35 items compiled by the author himself. The results of the data analysis show that there is a positive and significant effect of Strategy (CTL) by the Christian Religion Teacher on the learning activity of Class V and VI students at SD Negeri 173366 Parmonangan for the 2021/2022 Academic Year with the following data analysis: 1) Test the analysis requirements: a) A positive relationship test obtained rxy = 0.66&gt; rtable = 0.207 b) A significant relationship test obtained tcount = 3.52&gt; ttable = 1.671 thus there is a significant relationship between variable X and variable Y. 2) Test the effect : a) Test the regression equation, the regression equation is obtained with the regression coefficient of determination (r2) = 0.43% and Fcount &gt; Ftable, namely 91.25 &gt; 1.25, thus H0 is rejected and Ha is accepted. That is, there is a positive and significant influence between the effect of strategy (CTL) and the learning activity of class V and VI students of SD Negeri 173366 Parmonangan 2021/2022.
UPAYA MENINGKATKAN HASIL BELAJAR SISWA MELALUI PENERAPAN METODE PEMBELAJARAN TEAM GAMES TOURNAMENT

ABSTRACT, The formulation of the problem in this study is whether after implementing the team games team games tournament learning method can improve student learning outcomes in Class VI SD Negeri 177041 Simarhompa. The number of subjects in this study were 21 students from Class VI in the 2021/2022 school year. To obtain data in this study, the authors conducted data collection research by means of a member test. This type of research is classroom action research (CAR) using an inquiry learning model.&#x0D; This study consisted of 2 cycles, cycle I and cycle II, each of which had two meetings. At each meeting the researchers conducted a test of student learning outcomes, to determine the level of student learning completeness. In cycle I for the class average value of 79.18% in cycle II increased to 83.04% or an increase of 3.86%. The results of the study show that through the application of team games team games tournament learning methods can improve student learning outcomes in Class VI SD Negeri 177041 Simarhompa
PENGARUH PROFESIONALISME GURU PAK TERHADAP MINAT BELAJAR SISWA KELAS V SD SWASTA SANTA MARIA TARUTUNG T.P. 2021/2022

ABSTRACT, The purpose of this study was to find out whether there was a positive and significant effect of the professionalism of PAK teachers on the learning interests of Class V students at Santa Maria Tarutung Private Elementary School T.P.2021/2022. The population in this study were all students of Class V SD Santa Maria Tarutung T.P. 2021/2022 there are 35 Protestant Christians. The entire population was used as a sample, namely 35 people.&#x0D; The research data was analyzed in the following steps: 1) Testing the regression which consisted of: a) Looking for the regression equation Y over X to get the regression equation 81.18 + 0.77X, b) Obtained the value of Fcount = 5.43 &gt; Ftable(0.05 ,1.35-2=33) = 4.17 indicates that the influence of the professionalism of PAK teachers on the learning interest of Class V students of Santa Maria Tarutung Private Elementary School T.P.2021/2022 is linear, c) The large percentage of the influence of professionalism of PAK teachers on class student learning interest V Santa Maria Tarutung Private Elementary School are: (r2) x 100% = 0.1414 x 100% = 14.14%, 2) It is known that the value of tcount &gt; ttable is 2.333 &gt; 2.042. From the results of the significance test, it can be concluded that the research hypothesis is accepted, namely that there is a positive and significant influence between the professionalism of PAK teachers on the learning interest of Class V students at Santa Maria Tarutung Private Elementary School T.P.2021/2022.
The Detection of Fraudulent Smart Contracts Based on ECA-EfficientNet and Data Enhancement

With the increasing popularity of Ethereum, smart contracts have become a prime target for fraudulent activities such as Ponzi, honeypot, gambling, and phishing schemes. While some researchers have studied intelligent fraud detection, most research has focused on identifying Ponzi contracts, with little attention given to detecting and preventing gambling or phishing contracts. There are three main issues with current research. Firstly, there exists a severe data imbalance between fraudulent and non-fraudulent contracts. Secondly, the existing detection methods rely on diverse raw features that may not generalize well in identifying various classes of fraudulent contracts. Lastly, most prior studies have used contract source code as raw features, but many smart contracts only exist in bytecode. To address these issues, we propose a fraud detection method that utilizes Efficient Channel Attention EfficientNet (ECA-EfficientNet) and data enhancement. Our method begins by converting bytecode into Red Green Blue (RGB) three-channel images and then applying channel exchange data enhancement. We then use the enhanced ECA-EfficientNet approach to classify fraudulent smart contract RGB images. Our proposed method achieves high F1-score and Recall on both publicly available Ponzi datasets and self-built multi-classification datasets that include Ponzi, honeypot, gambling, and phishing smart contracts. The results of the experiments demonstrate that our model outperforms current methods and their variants in Ponzi contract detection. Our research addresses a significant problem in smart contract security and offers an effective and efficient solution for detecting fraudulent contracts.
FPGA Optimized Accelerator of DCNN with Fast Data Readout and Multiplier Sharing Strategy

With the continuous development of deep learning, Deep Convolutional Neural Network (DCNN) has attracted wide attention in the industry due to its high accuracy in image classification. Compared with other DCNN hardware deployment platforms, Field Programmable Gate Array (FPGA) has the advantages of being programmable, low power consumption, parallelism, and low cost. However, the enormous amount of calculation of DCNN and the limited logic capacity of FPGA restrict the energy efficiency of the DCNN accelerator. The traditional sequential sliding window method can improve the throughput of the DCNN accelerator by data multiplexing, but this method’s data multiplexing rate is low because it repeatedly reads the data between rows. This paper proposes a fast data readout strategy via the circular sliding window data reading method, it can improve the multiplexing rate of data between rows by optimizing the memory access order of input data. In addition, the multiplication bit width of the DCNN accelerator is much smaller than that of the Digital Signal Processing (DSP) on the FPGA, which means that there will be a waste of resources if a multiplication uses a single DSP. A multiplier sharing strategy is proposed, the multiplier of the accelerator is customized so that a single DSP block can complete multiple groups of 4, 6, and 8-bit signed multiplication in parallel. Finally, based on two strategies of appeal, an FPGA optimized accelerator is proposed. The accelerator is customized by Verilog language and deployed on Xilinx VCU118. When the accelerator recognizes the CIRFAR-10 dataset, its energy efficiency is 39.98 GOPS/W, which provides 1.73 × speedup energy efficiency over previous DCNN FPGA accelerators. When the accelerator recognizes the IMAGENET dataset, its energy efficiency is 41.12 GOPS/W, which shows 1.28 × −3.14 × energy efficiency compared with others.
Modeling a Novel Hyper-Parameter Tuned Deep Learning Enabled Malaria Parasite Detection and Classification

A theoretical methodology is suggested for finding the malaria parasites’ presence with the help of an intelligent hyper-parameter tuned Deep Learning (DL) based malaria parasite detection and classification (HPTDL-MPDC) in the smear images of human peripheral blood. Some existing approaches fail to predict the malaria parasitic features and reduce the prediction accuracy. The trained model initiated in the proposed system for classifying peripheral blood smear images into the non-parasite or parasite classes using the available online dataset. The Adagrad optimizer is stacked with the suggested pre-trained Deep Neural Network (DNN) with the help of the contrastive divergence method to pre-train. The features are extracted from the images in the proposed system to train the DNN for initializing the visible variables. The smear images show the concatenated feature to be utilized as the feature vector in the proposed system. Lastly, hyper-parameters are used to fine-tune DNN to calculate the class labels’ probability. The suggested system outperforms more modern methodologies with an accuracy of 91%, precision of 89%, recall of 93% and F1-score of 91%. The HPTDL-MPDC has the primary application in detecting the parasite of malaria in the smear images of human peripheral blood.
MENINGKATKAN KEMAMPUAN ANAK DALAM BERHITUNG MELALUI METODE BERNYANYI DENGAN MEDIA FLASH CARDS (Studi Deskriptif di RA Al-Furqon Kabupaten Ciamis)

This research is motivated by the lack of numeracy skills of 1-10 students at RA Al-Furqon. This study aims to determine how the planning, implementation and results of using the singing method using flash cards media to improve children's numeracy skills. This study uses a qualitative descriptive research method. Sources of data used through questionnaires, interviews, observations, documentation and literature studies. From the results of this study, it was concluded that the singing method through flash cards was proven to improve numeracy skills in group A children in RA Al Furqon, Ciamis Regency.
DEVELOPMENT OF EVALUATION TOOLS USING QUIZIZZ APPLICATION IN MATHEMATICS

Internet technology is indispensable today for the distance learning process. In order for the material to be delivered even though it is distance learning, the teacher must be creative in this regard. Fourth grade teachers at SDN Jatirangga 3 Bekasi use an easy-to-use application to track students during the learning process. Besides being able to help teachers, students are also more enthusiastic when learning through the applications used. The purpose of this study is to develop an evaluation tool using the Quizizz application. research methods used to produce a particular product, and test the effectiveness of that product. The development of an evaluation tool in the form of an online test using the Quizizz application in the Mathematics subject arithmetic operations with integers gets a percentage of 80% in the appropriate category and media experts get a percentage of 85% in the very feasible category. Evaluation validation obtained 6 invalid questions and 14 valid questions, reliability obtained 0.801, Student assessment responses to the evaluation tool using the quizizz application get a very interesting percentage of information of 84.67%. The final product in this research and development is 14 questions to develop an evaluation tool in the form of an online test using the Quizizz application in Mathematics, integer arithmetic operations for grade IV elementary school.
Analyzing Trends in Interaction Research for Korean Teaching and Learning

This study analyzed the trends of interaction research in the field of Korean language education and suggested implications and future research tasks. The papers analyzed for research trends were theses published in the Korea Research Foundation's nomination lists by October 2023. Since the aspects and methods of interaction are quite different depending on whether the teaching-learning space is offline or online, I first categorized papers according to these two criteria, and then subdivided them into sub-areas in terms of research topics and methods.&#x0D; Research on interaction in the field of Korean language education began to appear in the 2000s. The major turning points in the transformation of offline and online teaching and learning environments were around 2010. Until the early 2010s, almost all classes were held face-to-face, so research on interaction was centered on classroom instruction. The commercialization of high-speed internet in the 2010s greatly improved the environment for online education and diversified educational media. In the field of Korean language education, attempts have also been made to utilize online educational media and contents. Serious research on interaction in online educational environments has also been conducted since the mid-2010s. However, at this time, online classes were mostly based on stored contents. Then, in 2020, due to the COVID-19 pandemic, almost all classes were shifted to a non-face-to-face online format. As a result, online education mediums have diversified to include learning management systems (LMS), YouTube, mobile apps, online video lecture platforms, metaverses, and social media. As a result, interaction in online educational environments has emerged as an important issue, spurring research.&#x0D; Interaction research in offline teaching and learning environments has been focused on observing and analyzing the interaction patterns between teachers and learners and between learners and teachers. However, most of the research is limited to analyzing the interaction patterns. Therefore, it is necessary to find specific ways to apply them to future classes and teacher training. Next, in the case of interaction research in online-based teaching and learning environments, online learning is becoming more popular. However, the lack of interaction between instructor and learner, learner and learner, and learner and learning contents is still a problem that needs to be solved. And a new aspect of interaction in language education is worth paying attention to. This is the interaction with ChatGPT. The emergence of generative AI such as ChatGPT is revolutionizing the paradigm of mass education systems based on achievement standards and achievement levels. Therefore, research on interaction based on this is also an important future research task.
The Use of ChatGPT for Grammatical Error Analysis in EFL Writing: A Case of Korean University Students

This study examines the use of ChatGPT in analyzing grammatical errors in English writing. The purpose is to explore the effectiveness and accuracy of ChatGPT’s error analysis in comparison to human raters. Seventy-seven paragraphs written by Korean university students were analyzed by ChatGPT and two human raters based on fifteen error types. The results showed disparities in error frequencies between ChatGPT and human raters. The only similarity in error frequency identified was that both ChatGPT and human raters marked word choice error as the most frequent. However, ChatGPT detected sentence structure and informal language errors more frequently than human raters. Furthermore, ChatGPT’s analysis on individual students’ error frequency differed from that of human raters. In addition to the quantitative result of error frequency, the researcher conducted a qualitative analysis of ChatGPT’s error analysis. The results demonstrated that ChatGPT sometimes identified errors that did not exist in the students’ original texts and failed to consider the context of the original text. In many instances, ChatGPT exhibited inconsistencies in determining the appropriate error types. The findings of this study suggest that, while ChatGPT represents state-of-the-art technology, educators should be mindful of its strengths and limitations when integrating it into English writing instruction.
외국어로서의 한일 자국어 교육정책 비교 연구: 법제화 과정을 중심으로

This paper compares the language policies implemented in Korea and Japan based on the Korean Language Basic Law and the Promotion of Japanese Language Education Act. The research examines the purpose, background, key policy agencies, measures taken, and achievements of legislation in order to gain insight into the philosophy behind and direction of national language education as a foreign language. The findings are summarized as follows: Firstly, there are differences between Korea and Japan in terms of the process and background of enacting policies for native language education as a foreign language. But in both cases, the legislation regarding language policies carries significant meaning as it imposes obligations on responsible bodies. Secondly, there are points worth noting regarding the content aspect that constitutes educational curricula. Within educational curricula frameworks lie ideological values inherent within them. Both Korean and Japanese languages’ educational curricula as foreign languages fundamentally embrace multilingualism and interculturalism.
Present and future of CosmoLattice

We discuss the present state and planned updates of CosmoLattice, a cutting-edge code for lattice simulations of non-linear dynamics of scalar-gauge field theories in an expanding background. We first review current capabilities of the code, including the simulation of interacting singlet scalars and of Abelian and non-Abelian scalar-gauge theories. We also comment on new features recently implemented, such as the simulation of gravitational waves from scalar and gauge fields. Secondly, we discuss new extensions of CosmoLattice that we plan to release publicly. On the one hand, we comment on new physics modules, which include axion-gauge interactions $\phi F \widetilde{F}$, non-minimal gravitational couplings $\phi^2 R$, creation and evolution of cosmic defect networks, and magneto-hydro-dynamics (MHD). On the other hand, we discuss new technical features, including evolvers for non-canonical interactions, arbitrary initial conditions, simulations in 2+1 dimensions, and higher accuracy spatial derivatives.
Generalized Neural Networks for Real-Time Earthquake Early Warning

Deep learning enhances earthquake monitoring capabilities by mining seismic waveforms directly. However, current neural networks, trained within specific areas, face challenges in generalizing to diverse regions. Here, we employ a data recombination method to create generalized earthquakes occurring at any location with arbitrary station distributions for neural network training. The trained models can then be applied to various regions with different monitoring setups for earthquake detection and parameter evaluation from continuous seismic waveform streams. This allows real-time Earthquake Early Warning (EEW) to be initiated at the very early stages of an occurring earthquake. When applied to substantial earthquake sequences across Japan and California (US), our models reliably report earthquake locations and magnitudes within 4 seconds after the first triggered station, with mean errors of 2.6-6.3 km and 0.05-0.17, respectively. These generalized neural networks facilitate global applications of real-time EEW, eliminating complex empirical configurations typically required by traditional methods.