Reviewerly/exHarmony huggingface dataset:
Developing the Teaching Materials of Proverb Menaing with A Contructivism Aproach on Inquisitive Semantics

This study aimed to produce teaching materials for the meaning of proverbs with a constructivism approach based on inquisitive semantics for high school students. The research was conducted in the Riau Province high school equivalent. A performance test on the interpretation of constructivism approach proverbs that meets the standards of content validity was the main research instrument, along with questionnaires for teachers and a team of experts. A strategy based on constructivism and eight procedures were utilized to create instructional materials for proverbial meaning. The first is a preliminary study. Second, compiling the initial product design. Third, develop the initial product design. Fourth, initial product trials on a limited scale. Fifth, evaluation and revision of the initial product. Sixth, testing the revised product on a broad scale. Based on the study results, the pre-test on the meaning of proverbs was included in the low category, where there was no difference in the category of pre-test results per school group. A high category of post-test results on the meaning of proverbs was discovered, with disparities in the category of post-test results by a school group. There was no variation in categories per class, though. Furthermore, a substantial difference in the use of proverbs was discovered based on the findings of the pre-test and post-test. The seventh stage is to determine and revise the revised product. The eighth step is to present the final product. Because the F count value was 0.283 &amp;lt; the F table value which was 3.15, the test results of teaching materials were of high quality, with no significant differences in the ability to interpret proverbs. This finding suggests that the availability of teaching materials fulfills the feasibility of content, presentation, language, and graphic feasibility, and is appropriate for use in assisting in learning activities.
Viewpoint: The Physics in the New Era of Computing

The 21st century is the Information Age, characterised by an economy based on information computerisation. In this new era of computing, the role of physics is becoming crucial and practical. Thus, physics is not seen anymore as an abstract and purely academic endeavour. This study addresses physics inventions' contributions to computer science, society, and the economy. In particular, the physics discoveries in superconductivity, quantum mechanics, elementary particle physics, vacuum tubes, transistors and integrated circuits, electronic digital computer, fibre optics, lasers, and quantum computers will be discussed.
Text Summarization and Conversion of Speech to Text

Abstract: This article describes the fusion of recurrent neural networks and deep learning algorithms for text summarization systems and analysis of the text learning process. Next, the text analytics learning model is summarized. In addition, applications of deep learning-based text analysis are also introduced. Language is the most important part of communication between people. Although there are many ways to express our thoughts and feelings, language is considered the most important medium of communication. Speech recognition is the process by which machines recognize different people's voices based on specific words and phrases. End-to-end deep learning techniques can be used to identify and simplify spatial representations of text data and semantic information. This study considers text analysis based on deep learning
Exploring Sound Generation and Processing in Mechatronic Systems through Digital Signal Processing: A MATLAB-Based Investigation

Digital signal processing (DSP) encompasses various applications such as convolution, censoring, and filtering. These techniques find relevance in diverse fields, including computer games consoles, tone generation for mobile cellular devices, and theatrical performances. For computer engineers facing limited memory budgets in their devices, generating new sounds by convolving with existing sounds or noises becomes a significant challenge. The objective of this paper is to elucidate and demonstrate the generation of sounds through sound and recorded sound processing. These operations form the foundation of DSP, particularly digital filtering. Sound processing involves modifying prerecorded sound clips using different types of digital filters and processors. The entire process, including sound recording and processing, will be implemented and tested using MATLAB, the widely adopted technical computing software. This project aims to provide valuable archival material that complements the learning and expertise of computer engineering students and specialists.
Design pattern for conversational agents handling data-driven requests

The aim of this research project is to identify design principles for the development of CAs.In the context of this thesis, the research questions are: "According to which design principles are Conversational Agents developed?"and "How can these design principles be meaningfully categorized and described?".For the aggregation of the design principles, the first step was a systematic literature search according to Vom Brocke et al. ( 2009).The systematic literature review was followed by a qualitative literature analysis according to Kuckartz (2018).The result of this work is the identification of 15 meta-requirements that could be categorised by means of three main categories and a further seven subcategories.This was followed by the declaration of seven design principles based on the subcategories and their meta-requirements.
Research in the Use of Artificial Intelligence Technology in Media Integration in China

This paper studies about the continues growth of national economy and innovation of science and technology the level of construction and development of China's artificial intelligence field has made a qualitative leap.The reasonable application of artificial intelligence technology is the most important and indispensable key element of the modern media integration process, which can not only maximize the role of the media in the social scope of communication functions, but also effectively give the advantages of diversified media communication, realize the real time interactive communication between the media and the market users, and comprehensively enhance the core competitiveness of mainstream media.This essay will future analyze and discuss the use of artificial intelligence technology in media convergence, aiming to provide scientific reference opinions for the same industry in China.
THE EFFECT OF VERBAL VIOLENCE ON SELF-CONFIDENCE AND LEARNING OUTCOMES OF VINTAGE VOCATIONAL SCHOOL STUDENTS IN CLASS V SD NEGERI 83 SINGKAWANG

This study aims to determine the effect of verbal violence on self-confidence and learning outcomes of PPKn grade V students. This research was conducted at SD Negeri 83 Singkawang. The type of research used is quantitative research with a simple regression method. The population in this study were fifth-grade students at SD Negeri 83 Singkawang. This study uses a type of total sampling, namely the sample taken is the entire population. The prerequisite test is the normality test using the chi-square formula and the linearity test to find out whether the two or more variables tested have a linear relationship or not. The data were analyzed with a significance level of 5% (0.05), to test the hypothesis using a simple regression test. The results showed that: 1) There was an influence of verbal violence on the self-confidence of fifth-grade students. The calculation results obtained F_count &gt; F_table, namely F_count = 4.8694 &gt; F_table = 4.17, then Ha was accepted and HO was rejected; 2) There is an influence of verbal violence on the learning outcomes of Grade V PPKn students. The calculation results are obtained F_count &gt; F_table, namely F_count = 4.6325 &gt; F_table = 4.17, then Ha is accepted and HO is rejected.
STRUCTURED NUMBER HEADS AND NUMBERED HEAD TOGETHER MODELS ON THEMATIC LEARNING OUTCOMES

The purpose of this research is to find out and compare thematic learning outcomes using the Structured Numbered Heads (SNH) and Numbered Heads Together (NHT) models for fourth-grade students at SD Negeri 42 Palembang. The type of research used is a quantitative research experiment. The number of samples in this study amounted to 44 people from 2 classes through the technique of simple random sampling. Data collection techniques using a questionnaire (questionnaire), interviews, and tests. The data analysis technique used is the t-test and questionnaire analysis. The results obtained in this study were no significant comparison between using the SNH and NHT models. It is based on criteria testing the t-test hypothesis obtained t = -1.51 and t = 1.68, then -t or t – 1.68 -1.51 which means accepted and rejected. It means the second model is just as good and thing This is seen from the average result of the class test experiment I and experiment II between classes SNH and NHT difference No significant. No way direct results This shows that between the second model This No there's better and use the second model it can be customized with condition participant educate.
Knowledge of Information Security Awareness and Practices for Home Users: Case Study in Libya

The abundance of information available through the internet, mobile applications, and cloud computing has made it convenient for users to access a wide range of information. However, this convenience comes at a cost, as this information is constantly at risk of being compromised by cybercriminals and hackers. While the recognition of the potential dangers of information security is increasing in developed countries, in regions like Libya in North Africa, the level of protection for this information is insufficient. The purpose of this study is to examine the various factors that may influence or affect users' practices and awareness at home. The investigated factors are policy, behavior, training, knowledge of IT, and education. To accomplish the goals of this study, a quantitative methodology was implemented. Specifically, a survey was created to assess the correlation between key factors and security awareness and practices in the home environment. The survey attracted 220 respondents and was analyzed using Bivariate/Pearson Correlation to determine the relationship between the independent variable and the dependent variable. The results of the study showed a moderate positive correlation between policy, knowledge of IT, and education with security awareness and practice, but the behavior factor had a low correlation. These results indicate that the security awareness and practice level of employees at home is mostly at a moderate level. It is hoped that the present study provides an initial step in focusing on security training sessions among higher education employees to emphasize the importance of security training and increase knowledge of information security. It is hoped that the findings of this study will serve as a starting point for further research and a focus on providing security information for the public, which will help disseminate new knowledge on the importance of security training and increase awareness of information security.
Visual Discovery Engine

Abstract: A visual discovery engine is a technology that uses image recognition, natural language processing, and machine learning algorithms to analyze and interpret visual content such as images and videos. The engine extracts features from the visual content and matches them to relevant metadata, including textual descriptions, tags, and user-generated content. It then provides personalized recommendations and insights to users based on their search queries, browsing history, and contextual information. The visual discovery engine has many applications, including e-commerce, social media, digital marketing, and content curation. It enables users to explore, discover, and engage with visual content in a more efficient, intuitive, and personalized way, enhancing their online experience and driving business growth.
EUCLIDA: 3D Augmented Reality Card for Learning Numeracy about Geometry

Students consider that spatial geometry is tough, they require equipped mastery of concepts and visualized 2D object. This study is addressed to develop and evaluate EUCLIDA card integrated with AR using 4D model. The EUCLIDA card was claimed to satisfy the valid standard, because it achieves a percentage of 90%, from the appraisal data of two specialists and one practitioner. Moreover, EUCLIDA card also fulfills the utility aspects, because it obtained a percentage of 93% based on the outcome of learning activities observed and gained 97% from the student feedback survey on operating EUCLIDA card. It can be concluded that the EUCLIDA card is considered valid and useful.
Pengaruh Penggunaan Media Big Book terhadap Keterampilan Membaca Permulaan Siswa Kelas I Sekolah Dasar Negeri 75 Pontianak Barat

Beginning reading is the initial stage for students to recognize letter symbols in a simple scope. The use of appropriate media in learning can raise enthusiasm in learning to read early. The purpose of this study was to obtain information about the effect of using big book media on the initial reading skills of grade I students at State Elementary School 75 West Pontianak. The method used in this study is an experimental method with the form of Experimental Quasy. The number of samples in this study was 60 students from 91 students selected using purposive sampling.techniques. In collecting research data using measurement techniques and data collection tools in research is a test in the form of a preliminary.reading.test. The data analysis used is using the mean and t-test. The results of the study can be concluded that: (1) There is an influence on students' initial reading skills after being taught using big book media in grade I students of State Elementary School 75 West Pontianak; (2) There was a significant difference between the use of big.book media on.students'.initial reading skills in experimental and control classes.
Enhanced Semantic Representation Learning for Sarcasm Detection by Integrating Context-Aware Attention and Fusion Network

Sarcasm is a sophisticated figurative language that is prevalent on social media platforms. Automatic sarcasm detection is significant for understanding the real sentiment tendencies of users. Traditional approaches mostly focus on content features by using lexicon, n-gram, and pragmatic feature-based models. However, these methods ignore the diverse contextual clues that could provide more evidence of the sarcastic nature of sentences. In this work, we propose a Contextual Sarcasm Detection Model (CSDM) by modeling enhanced semantic representations with user profiling and forum topic information, where context-aware attention and a user-forum fusion network are used to obtain diverse representations from distinct aspects. In particular, we employ a Bi-LSTM encoder with context-aware attention to obtain a refined comment representation by capturing sentence composition information and the corresponding context situations. Then, we employ a user-forum fusion network to obtain the comprehensive context representation by capturing the corresponding sarcastic tendencies of the user and the background knowledge about the comments. Our proposed method achieves values of 0.69, 0.70, and 0.83 in terms of accuracy on the Main balanced, Pol balanced and Pol imbalanced datasets, respectively. The experimental results on a large Reddit corpus, SARC, demonstrate that our proposed method achieves a significant performance improvement over state-of-art textual sarcasm detection methods.
Android App for Creating a Map of the College to be used with visitor localization

It creates problem to visitor to reach easily and timely to their desired location.So, there must be a system that will guide and help visitor and also students to get to their desired places from their current location.Almost all people including students use smart phones.Almost all people including students uses smartphones.So a map application will be most helpful to locate desired place and shortest path from current location.Finding a place in a new location where visitors have no experience and clueless about it.This seems like getting lost in a maze and there is no easy way to reach out destination.This paper introduces an application for android mobile, which is implemented to provide the android mobile user to add, remove and review specific locations on the online map.The proposed applications also presents the basics navigation operations like showing directions with the optimal path between source and destination and calculating the distance and expected driving time.Google Maps APIs, Google Direction APIs, PHP, JSON and MySQL have been integrated and used in this application to obtain solutions keywords-UUB i.e.
Voice Recognition Systems for The Disabled Electorate: Critical Review on Architectures and Authentication Strategies

An inevitable factor that makes the concept of electronic voting irresistible is the fact that it offers the possibility of exceeding the manual voting process in terms of convenience, widespread participation, and consideration for People Living with Disabilities. The underlying voting technology and ballot design can determine the credibility of election results, influence how voters felt about their ability to exercise their right to vote, and their willingness to accept the legitimacy of electoral results. However, the adoption of e-voting systems has unveiled a new set of problems such as security threats, trust, and reliability of voting systems and the electoral process itself. This paper presents a critical literature review on concepts, architectures, and existing authentication strategies in voice recognition systems for the e-voting system for the disabled electorate. Consequently, in this paper, an intelligent yet secure scheme for electronic voting systems specifically for people living with disabilities is presented.
Short Course Digital Marketing sebagai Sarana Meningkatkan Animo Pendaftar Peserta Didik Baru di SD Muhammadiyah Kalangan

The location of SD Muhammadiyah Kalangan is located in Baturetno Banguntapan Village, Bantul, located within the village and not located on the edge of the highway, so that the location is less strategic to get the attention of the community. Promotion of new student admissions at SD Muhammadiyah Kalangan every year is carried out conventionally and has not used digital marketing media. This condition makes it difficult for SD Muhammadiyah Kalangan to compete with elementary schools located near the location. Based on these conditions, a special strategy is needed so that SD Muhammadiyah Kalangan can be better known by the public in general. This community service aims to provide insight and training to schools on digital marketing as a means to increase the interest of new student registrants. The method used in this community service is by conducting Short Course Digital Marketing activities as well as assisting in the creation of digital marketing media by utilizing websites and social media. The Short Course will start on August 6-10, 2021, and will be attended by 10 participants, namely teachers and employees of SD Muhammadiyah Kalangan. Community service shows a good impact seen from the pre-test and post-test scores of the implementation of the Digital Marketing Short Course, namely there is an increase in understanding and skills about Digital Marketing to be used as a strategy to increase the interest of new student registrants and be able to compete with other schools in the environment in the digital age.
DICoE@FinSim-3: Financial Hypernym Detection using Augmented Terms and Distance-based Features

We present the submission of team DICoE for FinSim-3, the 3rd Shared Task on Learning Semantic Similarities for the Financial Domain. The task provides a set of terms in the financial domain and requires to classify them into the most relevant hypernym from a financial ontology. After augmenting the terms with their Investopedia definitions, our system employs a Logistic Regression classifier over financial word embeddings and a mix of hand-crafted and distance-based features. Also, for the first time in this task, we employ different replacement methods for out-of-vocabulary terms, leading to improved performance. Finally, we have also experimented with word representations generated from various financial corpora. Our best-performing submission ranked 4th on the task's leaderboard.
VoxDet: Voxel Learning for Novel Instance Detection

Detecting unseen instances based on multi-view templates is a challenging problem due to its open-world nature. Traditional methodologies, which primarily rely on 2D representations and matching techniques, are often inadequate in handling pose variations and occlusions. To solve this, we introduce VoxDet, a pioneer 3D geometry-aware framework that fully utilizes the strong 3D voxel representation and reliable voxel matching mechanism. VoxDet first ingeniously proposes template voxel aggregation (TVA) module, effectively transforming multi-view 2D images into 3D voxel features. By leveraging associated camera poses, these features are aggregated into a compact 3D template voxel. In novel instance detection, this voxel representation demonstrates heightened resilience to occlusion and pose variations. We also discover that a 3D reconstruction objective helps to pre-train the 2D-3D mapping in TVA. Second, to quickly align with the template voxel, VoxDet incorporates a Query Voxel Matching (QVM) module. The 2D queries are first converted into their voxel representation with the learned 2D-3D mapping. We find that since the 3D voxel representations encode the geometry, we can first estimate the relative rotation and then compare the aligned voxels, leading to improved accuracy and efficiency. In addition to method, we also introduce the first instance detection benchmark, RoboTools, where 20 unique instances are video-recorded with camera extrinsic. RoboTools also provides 24 challenging cluttered scenarios with more than 9k box annotations. Exhaustive experiments are conducted on the demanding LineMod-Occlusion, YCB-video, and RoboTools benchmarks, where VoxDet outperforms various 2D baselines remarkably with faster speed. To the best of our knowledge, VoxDet is the first to incorporate implicit 3D knowledge for 2D novel instance detection tasks.
Matrix Information Theory for Self-Supervised Learning

The maximum entropy encoding framework provides a unified perspective for many non-contrastive learning methods like SimSiam, Barlow Twins, and MEC. Inspired by this framework, we introduce Matrix-SSL, a novel approach that leverages matrix information theory to interpret the maximum entropy encoding loss as matrix uniformity loss. Furthermore, Matrix-SSL enhances the maximum entropy encoding method by seamlessly incorporating matrix alignment loss, directly aligning covariance matrices in different branches. Experimental results reveal that Matrix-SSL outperforms state-of-the-art methods on the ImageNet dataset under linear evaluation settings and on MS-COCO for transfer learning tasks. Specifically, when performing transfer learning tasks on MS-COCO, our method outperforms previous SOTA methods such as MoCo v2 and BYOL up to 3.3% with only 400 epochs compared to 800 epochs pre-training. We also try to introduce representation learning into the language modeling regime, achieving 72.3% on the GSM8K dataset by fine-tuning a 7B model using matrix cross-entropy loss, with a margin of 3.1% over the standard cross-entropy loss. Code available at https://github.com/yifanzhang-pro/Matrix-SSL.