Reviewerly/exHarmony huggingface dataset:
Applying Flash as an Interactive Media in Mastering Simple Present Tense at Junior High School

Learning grammar is complicated, since it must understand the structure or formula in it, then there are many rules and patterns interrelated. The Simple Present Tense (SPT) is part of the grammar taught in junior high school. Learning the SPT for most students is very confusing, because the subject is considered quite difficult. And to minimize those difficulties faced by students in learning SPT, so the teachers try to make students understand the material by trying to make breakthroughs through the use of innovative learning media. Start from there, many creations related to the use of technology were created. Learning by involving technological sophistication more or less has a positive influence on students, since in addition to make it easier for them to learn, the teacher will also focus more on the material conveyed.&#x0D; Multimedia is a new concept and technology in the field of information technology, in where text, images, sound, animation and video are put together on a computer to be stored, processed and presented both linearly and interactively. This study aims to describe the implementation of interactive multimedia and to describe the success rate of grade VIII students of SMP Muhammadiyah 1 Surakarta in learning SPT. This study used a quantitative research approach, and it was a quasi-experiment. The experimental design was randomized pre-test and post-test comparison group design. The sample was class VIII PK-1 as the experimental group 1, while class VIII PK-2 as the experimental group 2. The sample was taken by using cluster random sampling technique. With this interactive multimedia learning method, it is expected that the participants’ ability in mastering English grammar can be improved.
The Effectiveness of Media Zoom Meetings as Online Learning during the Covid-19 Pandemic.

This research is descriptive. The purpose of this study was to determine the effectiveness of the Zoom meeting media as a distance learning medium during the covid-19 pandemic to suppress the spread of the virus. This research was carried out at Sawerigading University Makassar, especially for English education department students who are active in the writing I course. The research instruments used were test instruments and questionnaires. The instrument test was carried out to determine student learning outcomes in the form of an essay test of 20 questions with a completion time of 90 minutes while the positive response questionnaire aimed to see student responses to the effectiveness of the Zoom meeting media as a learning medium. The results of student learning outcome using zoom are complete as much as 86% the results obtained were 26 students scored 70-95 and 4 students scored below 70. While the results of the positive response questionnaire students met the effectiveness criteria with above 80% so that it can be categorized as learning media using zoom during the covid-19 pandemic for writing I course is effective.&#x0D; Keywords: Effectiveness, Zoom Meeting, Writing I
The Effect of Using the Trainchinese Dictionary on the Learning Outcomes of Chinese Students in Class X in High School

Understanding Chinese is not just about the spoken word, but also the written word. Chinese has thousands of strokes that need to be understood, one of the oldest being the ?? (hànzi) strokes. In the scope of education, teaching ?? (hànzi) strokes and Chinese sentence construction is a challenge. The reason is that students have not found it easy to learn the material. The results of Chinese ?? (hànzi) strokes and sentence construction are the variables to be tested. Using a quantitative approach with an experimental nonequivalent control group design, this study involved 45 students who were divided into experimental and control groups. The results showed a significant improvement in the learning outcomes of the experimental group after being assisted with the Trainchinese digital dictionary
Legal problems of using the virtual space of the metaverse in the educational process of the university

Introduction. On the one hand, traditional forms, methods and means of teaching are used in the educational process of a university, on the other hand, education cannot be static, it must meet modern requirements and challenges. Artificial intelligence technologies are rapidly developing in society, and their introduction into education will provide students with a modern, high-quality education. The Russian higher education system needs digital transformation; it requires the introduction of the latest learning technologies into the educational process to ensure competitiveness in the global education market. Theoretical analysis. To qualitatively improve the learning process at a university and train highly qualified personnel, it is necessary to use the latest teaching technologies, such as augmented and virtual reality. Virtual reality technologies in the form of virtual campuses and laboratories make it possible to organize the learning process in a highly motivated way for students, to achieve the effect of complete immersion in the processes and phenomena being studied. Currently, there is positive experience in using virtual space as an interactive teaching method when modeling practice-oriented cases. Еmpirical analysis. It was revealed that the problems of using the virtual space of the metaverse in the process of university education lie in the legal field. Legal problems of the metaverse include problems of cybersecurity, confidentiality of personal data, problems with automated data collection systems Big Data and others. One of the main problems is that of information security, the solution to which is the development of domestic software, local standards in the field of using virtual space technologies as part of the educational process of the university. Results. The author has proven the need to improve the current legislation of higher education in accordance with the specifics of the use of the virtual space of the metaverse by the educational process of the university; to develop local regulatory legal acts regulating the specifics of using metaverses when training a specific specialist.
EXTREME LEARNING MACHINE AND CHAOTIC BASED SPHYRAENA CHRYSOTAENIA OPTIMIZATION ALGORITHMS FOR LOSS LESSENING AND POWER STABILITY MAGNIFICATION

In this paper Extreme Learning Machine and Chaotic based Sphyraena Chrysotaenia Optimization Algorithms are applied for solving the Real Power loss lessening problem. Key objective of this work are Real power loss decreasing, power divergence restraining, and power constancy amplification. Extreme Learning machine and chaotic are integrated in the algorithm to obtain the better solutions. Candidate solutions in the projected Sphyraena Chrysotaenia optimization are Sphyraena Chrysotaenia and population in the inspection region is quixotically enthused. Spasmodically impressive solutions can be erroneous while restructuring the position of inspection agents and renewed positions may be inadequate one than the previous positions so magnificent selection is engaged. Domination comprises recurrence the self-effacing fitting solution to ensuing generation. In Extreme Learning Machine based Sphyraena Chrysotaenia Optimization Algorithm (ELMSC) initial phases of iteration, the Sphyraena Chrysotaenia Optimization Algorithm contestants are diversified in position and exponential standby generates unrestricted impulsive calculations which endow the rudiments to accommodate the entire revelation area. Compatibly, all over end stage of iterations, fundamentals are enclosed by Sphyraena Chrysotaenia Optimization Algorithm contestants and all an optimal condition with equivalent scheme. Chaotic sequences are combined into the Sphyraena Chrysotaenia Optimization Algorithm (CSCO). This amalgamation will augment the Exploration and Exploitation. Tinkerbell chaotic map fabricating tenets are employed. Proposed ELMSC and CSCO are corroborated in IEEE 30, 57, 118, 300, and 354 bus test systems. True power loss lessening, power divergence curtailing, and power constancy augmentation has been achieved. In future proposed ELMSC and CSCO can be applied to solve the others problems in Electrical engineering and also can be applied to resolve the problems in other engineering domains.
Penerapan UI/UX Pada Perancangan Sistem Informasi Penjadwalan Study Case SMK Negeri 2 Kota Tangerang Selatan

The User Interface (UI) serves as the design framework guiding user interactions within a system, whereas the User Experience (UX) encompasses the holistic user journey, including activities like data input and report generation. In the context of the scheduling system, the integration of UI/UX is strategically employed to deliver a user-centric experience, emphasizing seamless interaction with system menus. This methodology is expressly designed to optimize usability and cultivate high levels of user satisfaction. This article explores the nuanced interplay between UI and UX within the scheduling system, shedding light on how their collaborative implementation contributes to an enhanced overall user experience. The study delves into the specifics of design strategies aimed at promoting user-friendly interactions, ultimately fostering a positive and efficient user experience.
A Correlational Study of Gadget Used Towards Reading Interest

The purpose of this study was to determine the relationship between the use of gadgets and reading interest of class XII students in one of the high schools. The approach in this study uses descriptive quantitative methods with a correlation approach. The population of this study were all XII grade students and the sample used was 30 students. The technique used in sampling is proportional stratified random sampling. Data collection was carried out using questionnaires, observation and documentation. Variable measurement was carried out using a questionnaire with a Likert scale. The data analysis technique is descriptive analysis and correlation test. The results of this study found that there is a relationship, where the use of smartphones affects students' reading interest. Based on the result the product moment correlation test analysis with a value of X ̅ = 67,77 and Y ̅ = 80,4 resulting in r = 0,949 meaning that there is a significant correlation between gadget used toward reading interest. This evidenced by the value of the product moment coefficient which shows that r&gt; 0.01. Therefore, Teachers/parents are expected to be able to minimise students' gadget use, in addition, the role of teachers/parents in motivating providing reading materials or reading activities can be one aspect of supporting students' interest in reading.
Verb Polysemy and Compounding Productivity in Chinese: A Quantitative Study

In Mandarin Chinese, monosyllabic verbs (V characters) are particularly rich in polysemy and morphologically productive in compounding. The senses of V characters are usually associated with their related compounds. This chapter will examine the relationship between the polysemy and compounding productivity of V characters both qualitatively and quantitatively. A morphological phenomenon called “compounding-abbreviation loop” has been proposed as a way to enrich the polysemy of V characters. It has been argued that the compounding-abbreviation loop accounts for the strong semantic ties between V characters and their related compounds. Supporting this view, this chapter will present a quantitative study that examined the association between the polysemy and compounding productivity of V characters. The data on the characters, compounds, and word senses used in the study were collected from the Academia Sinica Balanced Corpus, Thesaurus of Chinese Words 同義詞詞林 Tóngyìcí Cílín, and the Chinese dictionary 漢語大詞典 Hanyu Da Cidian. The results showed a positive correlation between the mean number of senses and the number of related compounds.
Does Information Sharing Will Create New Services On Indonesia Pre-School?

Preschools manage information from parents to create excellent learning programs. The learning program becomes a form of joint service value creation between managers and users of preschool education services. The study aims to examine the importance of customer orientation, knowledge creation proce
A mini review on Bio-piracy with special reference to NE India

The study is a short review on the instances of bio-piracy of various bio-resources in the states of North-Eastern India specifically in the state of Nagaland, Assam and Sikkim. The main aim of this short study is to provide a view on how the diverse biodiversity of North-East India are facing issues related to bio-piracy and which are in need of appropriate legal legislations to deal with these issues in the immediate future. There is a strong need for developing law pertaining to bio-piracy and as such efficient enforcing agencies are the need of the hour to control these illicit acts of bio-piracy.
Machine Learning Methods for Handwriting Recognition

Machine learning is a fundamental aspect of artificial intelligence that involves the development of algorithms and models that allow computers to learn and make predictions or decisions without explicit programming. With the development of neural networks, back-propagation algorithms and deep learning, machine learning has made breakthroughs in the fields of image recognition, natural language processing and handwriting recognition using machine learning techniques. The advent of deep learning has revolutionized the field of handwriting recognition, using convolutional neural networks, recurrent neural networks, and sequence-to-sequence models to provide solutions that go beyond machine learning methods and significantly improve the accuracy and robustness of handwriting recognition systems. But challenges remain, including the need for large labelled datasets, computational resources and addressing potential biases. As research in deep learning techniques continues to drive handwriting recognition closer towards realisability, machine learning approaches remain at the forefront.
Fantasy on a theme by G. Enescu for clarinet and orchestra by Oleg Negruţa

In the present study, we propose to identify the structural elements of sound discourse, as well as their manifestation in the concept of the work Fantasy on a theme by G. Enescu for clarinet and orchestra by Oleg Negruţa. The author’s compositional records include vocal, instrumental chamber, concert and symphonic music. Most of his creations are attributed to concert and chamber music. The work that we are going to analyze serves as proof of the novelty of the genre, form and elements of writing. Fantasy as a genre represents an instrumental or orchestral work with a fairly free architecture, and the basic principle is improvisation. In this piece, we highlight one of the distinctive features of the composer, namely the folkloric stylistic direction - the use of folkloric species such as doina, sarba, hora, organically combined with elements of the classical language - genre, form, theme, etc. Equally important is the use of the quote, which O. Negruţa creatively develops and exposes in different sections, creating a thematic core, but also a sound reagent for the entire musical discourse.
Software implementation of image steganography based on LSB algorithm with Caesar’s cipher

The purpose of this work is to conduct a study of computer steganography methods and the implementation of image steganography using the LSD algorithm and the Caesar cipher. The development of global computer networks allows fast and efficient transfer of electronic documents, but at the same time there is a risk of illegal copying and distribution of materials. Confidentiality of important information is an extremely responsible matter. Therefore, there is a need to develop methods and software tools for hiding information in various types of files, in particular images. Steganography is a mechanism for hiding messages in cloaking objects such as images, audio, text, video, and network protocol so that the hidden message cannot be detected by the naked eye or attackers
Approach Allowing Design Adaptive View Models

The problem of setting interface settings for global software development processes is actual now. Successful solving of this problem can be source many benefits in view models, other words interface representation designing. Thus, in turn, allow to increase amount of web-site visitors and web applications users. Other advantage is to allow different developers to understand interface well and design application using n-tired architectural style. One of the important task is to archive dynamic localization for switching interface languages. Paper represents an approach of view models designing in context of dynamic localization for desktop application using WPF technology. Paper contains the review of existing frameworks for flexible interface designing supporting localization process. Approach touches some mathematical foundation of interface components representation, recommendation for framework designing, touching design patterns. Paper contains some practical examples of preparation interface using different languages.
A NEW RELATIONSHIP FOR ECONOMICS AND EDUCATIONAL SCIENCES: FINANCIAL EDUCATION

Among the many areas of dialogue between economics and educational sciences, one common object of study has now clearly emerged: economic and financial education, which was created to raise the literacy levels of the adult population and young people. Indeed, more and more decisions in everyday life are linked to economic and financial aspects. The current economic and financial knowledge of the population is not adequate to the needs as it comes mainly from financial socialisation processes; it is instead necessary for schools and not only the banking and insurance world to deal with these new educational processes. However, in order to introduce these topics, schools must train teachers who do not have adequate knowledge. In Romania, this is a recent issue, which is why it was decided to launch a new research project.
MONET: Modality-Embracing Graph Convolutional Network and Target-Aware Attention for Multimedia Recommendation

In this paper, we focus on multimedia recommender systems using graph convolutional networks (GCNs) where the multimodal features as well as user-item interactions are employed together. Our study aims to exploit multimodal features more effectively in order to accurately capture users' preferences for items. To this end, we point out following two limitations of existing GCN-based multimedia recommender systems: (L1) although multimodal features of interacted items by a user can reveal her preferences on items, existing methods utilize GCN designed to focus only on capturing collaborative signals, resulting in insufficient reflection of the multimodal features in the final user/item embeddings; (L2) although a user decides whether to prefer the target item by considering its multimodal features, existing methods represent her as only a single embedding regardless of the target item's multimodal features and then utilize her embedding to predict her preference for the target item. To address the above issues, we propose a novel multimedia recommender system, named MONET, composed of following two core ideas: modality-embracing GCN (MeGCN) and target-aware attention. Through extensive experiments using four real-world datasets, we demonstrate i) the significant superiority of MONET over seven state-of-the-art competitors (up to 30.32% higher accuracy in terms of recall@20, compared to the best competitor) and ii) the effectiveness of the two core ideas in MONET. All MONET codes are available at https://github.com/Kimyungi/MONET.
SlowTrack: Increasing the Latency of Camera-based Perception in Autonomous Driving Using Adversarial Examples

In Autonomous Driving (AD), real-time perception is a critical component responsible for detecting surrounding objects to ensure safe driving. While researchers have extensively explored the integrity of AD perception due to its safety and security implications, the aspect of availability (real-time performance) or latency has received limited attention. Existing works on latency-based attack have focused mainly on object detection, i.e., a component in camera-based AD perception, overlooking the entire camera-based AD perception, which hinders them to achieve effective system-level effects, such as vehicle crashes. In this paper, we propose SlowTrack, a novel framework for generating adversarial attacks to increase the execution time of camera-based AD perception. We propose a novel two-stage attack strategy along with the three new loss function designs. Our evaluation is conducted on four popular camera-based AD perception pipelines, and the results demonstrate that SlowTrack significantly outperforms existing latency-based attacks while maintaining comparable imperceptibility levels. Furthermore, we perform the evaluation on Baidu Apollo, an industry-grade full-stack AD system, and LGSVL, a production-grade AD simulator, with two scenarios to compare the system-level effects of SlowTrack and existing attacks. Our evaluation results show that the system-level effects can be significantly improved, i.e., the vehicle crash rate of SlowTrack is around 95% on average while existing works only have around 30%.
Adversarial Robustness on Image Classification with $k$-means

In this paper we explore the challenges and strategies for enhancing the robustness of $k$-means clustering algorithms against adversarial manipulations. We evaluate the vulnerability of clustering algorithms to adversarial attacks, emphasising the associated security risks. Our study investigates the impact of incremental attack strength on training, introduces the concept of transferability between supervised and unsupervised models, and highlights the sensitivity of unsupervised models to sample distributions. We additionally introduce and evaluate an adversarial training method that improves testing performance in adversarial scenarios, and we highlight the importance of various parameters in the proposed training method, such as continuous learning, centroid initialisation, and adversarial step-count.
Leveraging Language ID to Calculate Intermediate CTC Loss for Enhanced Code-Switching Speech Recognition

In recent years, end-to-end speech recognition has emerged as a technology that integrates the acoustic, pronunciation dictionary, and language model components of the traditional Automatic Speech Recognition model. It is possible to achieve human-like recognition without the need to build a pronunciation dictionary in advance. However, due to the relative scarcity of training data on code-switching, the performance of ASR models tends to degrade drastically when encountering this phenomenon. Most past studies have simplified the learning complexity of the model by splitting the code-switching task into multiple tasks dealing with a single language and then learning the domain-specific knowledge of each language separately. Therefore, in this paper, we attempt to introduce language identification information into the middle layer of the ASR model's encoder. We aim to generate acoustic features that imply language distinctions in a more implicit way, reducing the model's confusion when dealing with language switching.