Reviewerly/exHarmony huggingface dataset:
Application of Traffic Ethics to Instill Disciplined Driving Behavior

This study examines traffic ethics for students of the social science education faculty at the Indonesian University of Education, which aims to find out whether traffic ethics has been applied and whether the provisions are correct. Is it important to apply this ethic in traffic that we often see on the highway and whether it will result in obedience to every citizen. This research uses a survey method (survey research) with a descriptive design. This data collection method was carried out by distributing questionnaires taken from 100 students which showed that students of the social science education faculty at the Indonesian University of Education were categorized as adhering to traffic ethics. The participants in this study were students of the social sciences education faculty at the Indonesian University of Education. From the results of the questionnaire with the background of the students of the social sciences education faculty at the Indonesian University of Education, namely (1) use ethics when driving. (2) Obey traffic rules.
Application of Mixed Reality for Assembly Line in Manufacturing Plants

Abstract: Augmented reality and mixed reality-based applications are used widely in different areas for last decade. Using AR/MR for AI simulation and training is not a new thing for many trainings simulations AR/MR is used in areas like military and medical. Although same cannot be said with the manufacturing industry there is need in manufacturing plants for training new employees/visitors about the process and machines along with instructions to use them. This can be done using mixed reality and marker less detection. Assembly line in Manufacturing plants is a brief process which needs to be followed by workers for better efficiency and quality. Using mixed reality for training workers by walking though assembly line will help immensely as mixed reality-based applications are very intuitive and they help in learning. This study focusses on finding challenges and proof of concept android mobile application while benchmarking them with various metrics which will help in further developments in area.
The Application of the Two Stay Two Stray (TSTS) Cooperative Learning Model in Improving the Ability to Understand the Main Idea of Paragraphs

The purpose of this study was to describe the planning of the Two Stay Two Stray Cooperative Learning model in improving students' ability to understand the main ideas of paragraphs at Parungkadongdong Elementary School. To describe the implementation of the Two Stay Two Stray Cooperative Learning model in improving the ability to understand class V at SDN Parungkadongdong. To describe the improvement of the Two Stay Two Stray Cooperative Learning model on student learning outcomes in determining the main ideas of paragraphs. This article is Classroom Action Research. The results of the study: Planning, in Indonesian language lessons the subject matter of paragraphs using the Cooperative Learning Type Two Stay Two Stray (TSTS) model in class V SDN Parungkadongdong is said to be successful. This can be seen from the results of the teacher's ability to design lesson plans. In cycle I the teacher's ability to design lesson plans reached 85% in the high category and in cycle II the teacher's ability to design lesson plans reached 93% in the very high category. Implementation, in Indonesian lessons the subject matter of paragraphs using the Cooperative Learning Type Two Stay Two Stray (TSTS) model in class V SDN Parungkadongdong was said to be successful. This can be seen from the results of teacher activities in managing learning and student activities in carrying out learning have increased in each cycle. Teacher activity in cycle I reached 89% and in cycle II reached 93%. While student activity in cycle I reached 83% and in cycle II reached 91%. Observation (Observation) Increasing Students' Ability to Understand Main Ideas of Paragraphs, in Indonesian language lessons the main ideas of paragraphs using the Cooperative Learning Type Two Stay Two Stray (TSTS) model in class V SDN Parungkadongdong are said to be successful. This can be seen from the results of improving students' ability to understand the main ideas of paragraphs. In the pre-action it reached 68%, the first cycle reached 75% and the second cycle reached 86%.
Landmark and Tourist Spots Using Augmented Reality

It takes seriously a lot of time to build a system design like this, but why not use the rising technology to build an Augmented Reality design? Using the appropriate technology can help minimize the time needed in building one, plus it can show other people that society is catching up in terms of the new applications and technologies. For one, Augmented Reality (AR) is a technology that overlays digital information on a live view of the physical world to create a blended experience. Augmented Reality has now progressed to the point where real-time applications are considered and needed. Consequently, in this study, Augmented Reality is used to show the 3D model of the selected Landmark and the whole Municipality of Dumangas, Iloilo by just pointing the Android mobile device to the provided Landmark marker. However, it is important that synthetic elements are rendered and aligned in the scene in an accurate and visually acceptable way. In order to address these issues real-time, robust, and efficient model-based tracking was proposed for a mobile camera - a virtual map for the Municipality of Dumangas, Iloilo. This would help not only the Municipality of Dumangas to promote their tourist attraction but also the people who want to locate different tourist spots in Dumangas, Iloilo. This application would also provide the user with information about the specified Landmarks. The Landmark Tourist Spots Using Augmented Reality would test the user to know the Landmark in Dumangas, Iloilo.
Pelatihan Design Grafis Online Menggunakan Aplikasi Canva Bagi Remaja Majelis Ta’lim Hidayatul Mubtadiin

Training or workshop is one way to hone one's interests and deepen one's talents. In this community service that has been carried out for the odd 2022-2023 period, we as Nusa Mandiri University lecturers carry out community service activities by carrying out Canva training. The Canva application that we use as a learning media tool for the youth of the Hidayatul Mubtadiin ta'lim assembly. This Canva training was attended by teenagers and the parents of the board of directors of the Hidayatul Mubtadiin ta'lim assembly in Tangerang City. This training aims to improve the ability of millennial youth in mastering Graphic Design, which is useful for increasing youth creativity in entrepreneurship such as making billboards, making banner posters. Logo, template for branding on social media. The method used is Waterfall, with a focus on building products or works using the Canva application. We obtained the results of the training through the distribution of questionnaires. The results of the training showed that 98% of the youth partners of the ta'lim assembly were satisfied with the activity. The assessment variables are mastery of the material, discipline, and satisfaction, each of which gets a score of Very Satisfactory Grade A.&#x0D; Keywords: servant, Canva
Konsep Keamanan Untuk Anak Bermain di Kali Kendedes, Kecamatan Singosari, Kabupaten Malang

Kali Kendedes in Singosari District, Malang Regency is a stream of water originating from a local source. This river is used as a children's playground. The observation results show that there is a potential for danger during activities, especially when children are swimming or playing in water. The writing of this article is aims to develop a safety concept for children playing in the Kendedes river. The technical application designed is a ladder up and down like a ladder in a swimming pool and hangers for visitors' things.
Automatic Hindi Speech Recognition: Challenges and Future Scop

Automatic Speech Recognition (ASR) field is the witness of remarkable improvement over the last few years. Deep learning architectures are the main reason for ASR evaluation. Deep learning techniques tremendously improve ASR performance, but these architectures are data-hungry. There are more than 5000 languages in India that do not have such a huge amount of resources. Hindi is one of them. The lack of freely available Large Vocabulary Hindi speech datasets is the major hurdle for developing Hindi ASR. In this paper, we investigate the various work available for Hindi ASR. The available resource is also discussed with issues and challenges in Hindi ASR. This paper provides a detailed analysis of various techniques available in ASR with comparison to Hindi ASR. The future scope of Hindi ASR is also presented.
Path Planning of Mobile Robots Based on Improved Genetic Algoritm

With the development of intelligent manufacturing, whether from the consideration of capacity, efficiency, or convenience, the requirements for mobile robots are increasing, reasonable regional path planning is one of the most critical needs, and a genetic algorithm is the best way to solve this problem, but in some complex working environments, traditional genetic algorithms will cause some problems, such as the path is not smooth, the steering angle is too large, the number of turns is large, etc. In this paper, an improved genetic algorithm is utilized to optimize the path-planning problem of mobile robots to circumvent the common issues arising from other approaches. The Improved Genetic Algorithm (IGA) has emerged as a significant advancement in the field of optimization techniques. By incorporating adaptive features, this refined approach yields enhanced performance and accuracy when compared to traditional genetic algorithms. Building on the foundational principles of evolutionary computation, the IGA employs innovative strategies, such as adaptive crossover and mutation operators, to navigate complex solution spaces effectively. It can also reduce computation time and increase efficiency by considering various considerations, such as environmental constraints and avoiding obstacle.
FORMATION OF STUDENTSINFORMATION-ANALYTICAL COMPETENCE DURING LECTURES IN THE DISTANCE EDUCATIONCONDITIONS

Problem formulation. The purpose of the study is findig ways to form information and analytical competence of students during a lecture in the distance learning. Materials and methods. To study the problem, the authors used theoretical analysis and systematization. Methods of comparison, systematization and generalization were used during obtaining and analysis of results and formulation of conclusions. Results. The authors provide the process analysis of formation students information and analytical competence during a lecture in a distance education. They identify the main components of information and analytical activities of students, namely: motivational, cognitive, activity and subjective. It is determined that the low level of information-analytical formation&nbsp; intelection affects the ability of students to self-education. The article presents statistics of the student surveys results on the type of lectures. The authors of the article found that students prefer lectures-consultations. The lecture-consultation consists of stages: preparatory, stage of discussion, stage of control. The level of students information-analytical competence formation during a lecture in distance education is determined by the following criteria: the student is able to writening in a logical sequence of essential ideas, lecture basic provisions, which are the result of analysis and synthesis of their own thinking, develop theoretical thinking; the student generalizes and systematizes the content of the lecture, separates the secondary from the main; the student can define fundamental concepts and compare them, establish causal relationships between them; the student formulates questions, discusses, is able to prove or disprove; the student demonstrates an understanding of the general structure of the discipline, its connection with others, understands and uses methods of critical analysis. Conclusions. Analyzing the results of experimental work, we can conclude that the highest level of information-analytical competence of future professionals can be achieved during the lecture-consultation and lecture-conference, implementing bilateral student-teacher and teacher-student relations.
Path Following and Avoiding Obstacle for Mobile Robot Under Dynamic Environments Using Reinforcement Learning

Obstacle avoidance for mobile robot to reach the desired target from a start location is one of the most interesting research topics. However, until now, few works discuss about working of mobile robot in the dynamic and continuously changing environment. So, this issue is still the research challenge for mobile robots. Traditional algorithm for obstacle avoidance in the dynamic, complex environment had many drawbacks. As known that Q-learning, the type of reinforcement learning, has been successfully applied in computer games. However, it is still rarely used in real world applications. This research presents an effectively method for real time dynamic obstacle avoidance based on Q-learning in the real world by using three-wheeled mobile robot. The position of obstacles including many static and dynamic obstacles and the mobile robot are recognized by fixed camera installed above the working space. The input for the robot is the 2D data from the camera. The output is an action for the robot (velocities, linear and angular parameters). Firstly, the simulation is performed for Q-learning algorithm then based on trained data, The Q-table value is implemented to the real mobile robot to perform the task in the real scene. The results are compared with intelligent control method for both static and dynamic obstacles cases. Through implement experiments, the results show that, after training in dynamic environments and testing in a new environment, the mobile robot is able to reach the target position successfully and have better performance comparing with fuzzy controller.
Gaze Assisted Transaction

Abstract: Automated Teller Machine (ATM) was introduced in the year 1959 for encouraging self service in retail banking. The single smart card ATM for multiple bank accounts is used for security applications for withdrawing cash from ATM machines. Eye tracking has been introduced as a way of direct interaction which could pave the way for new technologies and devices to be introduced for end-users. It is becoming a popular way of interaction. Gaze coordinates could be used to pinpoint the target selected by the user on the screen, then proceed to do a command more efficiently. We hypothesize that the limitations and disadvantages mentioned for touch screen interfaces can be improved by adding gaze capabilities. It is worth mentioning that gaze along with the touch method. Therefore, the targeting can be done via gaze and the selection by touch, which will improve the efficiency and also the screen is not obscured by hand during targeting and even increases the security. The proposed project is based on Event based architecture. CNN algorithm has been chosen to improve the efficiency of the project. The model is easily adaptable to complex, often chaotic environments and the system is easily extendable when new event types appear. The User interface will be designed to be user friendly and comfortable. The design uses a toolkit DLIB for making real world machine learning and data analysis applications. Dlib is majorly used for face detection and facial landmark detection. The system can be divided into two parts. The first part consists of eye typing implementation and the second part is text entry into the system.
Online Public Shaming on Social Media: Detection, Analysis and Mitigation

Abstract: Social networking networks have billions of users worldwide. Users' participation in various social networking sites, like twitter, can occasionally have major and unfavourable effects on day-to-day living. Large social media platforms have evolved into a place where users can spread a lot of unwanted and pointless content. Twitter, one of the biggest social media platforms ever, has become the most popular microblogging site for the spread of useless information. In this project idea, the duty of identifying public scandal on Twitter is changed. Spam and non spam are the two subcategories of embarrassing tweets. It is apparent that the majority of people who engage and provide comments on a particular incident have a tendency to defame the victim.
Virtual Try-ON Clothes

Abstract: The increasing popularity of e-commerce and the desire for personalized shopping experiences have led to the development of virtual trial room applications. In this research paper, we present a novel approach to outfit prediction in a webbased virtual trial room. Our system utilizes machine learning techniques to analyze input images of shirts and pants and provides accurate outfit recommendations tousers. The application, developed using Python, Flask, HTML, CSS, JavaScript, Bootstrap, and OpenCV, offers users the ability to virtually try on different outfits without physically trying them on. We discuss the design, implementation, and evaluation of our system, highlighting its effectiveness in accurately predicting outfit combinations and improving the user experience.Digital try-on systems for e-commerce have the potential to change people’s lives and provide notable economic benefits.
Dynamic Approval Matrix Application Design for Technical Department Document Change Request Application

This study discusses problems on the website of the NPPS companywhich will also be used by its branch company, namely NPPSLK.While the website currently only supports one company, it isnecessary to develop the website to become multicompany. If thewebsite is made multicompany, then the applications in it areautomatically adjusted. One of the applications on the website is anapplication with systematic approval, namely the Dynamic ApprovalMatrix (DAM). DAM was developed to be able to supportmulticompany, support flow management features, status, andapproval actions for each company. So, a multi-company configuration is carried out on one system, and using the waterfall method with steps. Advance Dynamic ApprovalMatrix (ADAM) was created as multi-enterprise support DAMdevelopment. So, it can be used by multi-company. ADAM is madeusing waterfall method using Odoo with Python, XML, andPostgreSQL. The app contains forms to manage related apps, approvalflow settings, multi-company, status settings, and Call-to-Actionbuttons to facilitate document approval. The ADAM application has been tested on the TDCR application using black box indicator with the conclusion that website results aremore effective and efficient because it can be used by multicompany,and administrators can freely adjust according to company needs.
Sarcasm Recognition on News Headlines Using Multiple Channel Embedding Attention BLSTM

Sarcasm is a statement that conveys an opposing viewpoint via positive or exaggeratedly positive phrases. Due to this intentional ambiguity, sarcasm identification has become one of the important factors in sentiment analysis that make many researchers in natural language processing intensively study sarcasm detection. This research is using multiple channels embedding the attention bidirectional long-short memory (MCEA-BLSTM) model that explored sarcasm detection in news headlines and has different approach from previous research-developed models that lexical, semantic, and pragmatic properties. This research found that multiple channels embedding attention mechanism improve the performance of BLSTM, making it superior to other models. The proposed method achieves 96.64% accuracy with an f-measure of 97%
Selection of Home Wifi Internet: Machine Learning Implementation With Decision Tree C4.5 Algorithm Method

The multiple bandwidths that internet service providers offer make it difficult for people to choose, especially for regular people unfamiliar with the internet; therefore, most people choose because the price is reasonable. Numerous users also lament the difficulty and slow internet usage. The issue is then concentrated on internet service providers, who are thought to be poor at offering services. The quantity of bandwidth consumed, which does not correspond to the user’s needs, is one factor contributing to slow internet. As a result, the appropriate bandwidth must be chosen based on the requirements of each user. Compared to other algorithms, the C4.5 decision tree method can deliver the best and correct decision, according to the current literature. As a result, this project will develop a web application based on the C4.5 decision tree algorithm that can assist in determining bandwidth and internet following community needs. Using this C4.5 Decision Tree, decisions are based on patterns identified in previously collected data. Predictions about various forms of internet use in the neighborhood may subsequently be produced from these patterns. Based on the calculation, the accuracy obtained is 0.54, or a percentage of 54%. The black box testing indicated that the bandwidth determination application was functioning correctly
Comparison of Support Vector Machines and K-Nearest Neighbor Algorithm Analysis of Spam Comments on Youtube Covid Omicron

Every time a new variant of Coronavirus (Covid-19) appears, themedia or news platforms review it to find out whether the new variantis more dangerous or contagious than before. One of the media orplatforms that is fast in presenting news in videos is YouTube.YouTube is a social media that can upload videos, watch videos, andcomment on the video. The comment field on YouTube videos cannotbe separated from spam comments that annoy other users who want tofollow or participate in the comment column. Indication of spamcomments is still done by observing one by one; this is very inefficientand time-consuming. This study aims to create a model that canclassify spam on YouTube comments. The classification method uses the SVM (Support Vector Machines) algorithm and the KNN (K-Nearest Neighbor) algorithm to identify spam comments or not with comment data taken from Omicron's Covid-19 news video on national news channels. The classification results show that the SVM method is superior inaccuracy with the Linear SVC algorithm of 75.12%, SVC of 76.11%, and Nu-SVC of 77.11%. While the KNN algorithm with k=2 is 65.67%, k=4 is 64.51%, k=6 is 62.35%.