Reviewerly/exHarmony huggingface dataset:
Effects of Non-face-to-face Class Experience on Cosmetology Majors' Learning Apathy and Self-efficacy

In the field of education, there has been a general change in the learning situation with non-face-to-face classes, as well as phenomena related to adaptation to university life. However, non-face-to-face classes have more side effects than traditional face-to-face classes, and research on the experience of non-face-to-face classes, learning apathy, and self-efficacy among cosmetology majors is incomplete. Therefore, as a result of analyzing this study, we analyzed the influence of non-face-to-face class experience on learning apathy among college students majoring in cosmetology, and found that there was a statistically significant effect on learning apathy(β=-.621, p&lt;.001) and an analysis of the effect on self-efficacy revealed that social efficacy(β=.632, p&lt;.001) and self-regulatory efficacy(β=.340, p &lt;.001)was shown to have a statistically significant effect on failure anxiety and efficacy(β =.124, p&lt;.001) The results of this study revealed that the experience of non-face-to-face classes had a significant impact on learning apathy and self-efficacy among cosmetology majors. Through this study, we hope to stimulate discussion about the non-face-to-face class experiences, learning apathy, and sense of self-efficacy among cosmetology majors.
The Influence of Empathic Response of Watching SNS Broadcasting Clip on the Curiosity and Viewing Intention of Live program

This study analyzes the effect of empathic response of watching SNS broad- casting clips on the Curiosity and viewing intention of live program. Results indicated that empathetic understanding, identification, and vicarious emotional response have immediate effects on Curiosity. The Curiosity for the main broadcast had a positive effect on the viewing intention of live program, thus the mediating effect was verified. This shows that empathic response plays significant roles in developing Curiosity and viewing intention of watching the main show while viewing SNS broadcasting clips.
Implementasi Sistem Manajemen Transakasi Pemesanan Laundry Sepatu Berbasis Website pada Jivin Clean dengan metode Waterfall

The purpose of this research is to develop a transaction management system for shoe laundry booking at Jivin Clean, which can assist the owner of Jivin Clean in recording laundry orders. The method used to complete this system is the waterfall method, which consists of several stages, including system requirements analysis, system design, implementation, testing, and maintenance. The outcome of this research is a web-based application for managing shoe laundry booking transactions. In the system, the admin can add and modify order data. Additionally, customers can check the status of their laundry progress. This helps customers know whether their laundry is still in progress or has been completed. The transaction management system for laundry orders at Jivin Clean can assist and facilitate Jivin Clean in recording laundry orders. Furthermore, the system operates efficiently, as evidenced by black-box testing results showing 100% success in testing 15 features.
A Study on Reeducation Courses for Korean Language Teachers in the CIS Region

The purpose of this study is to derive the priorities of the re-education programs most necessary for Korean language teachers in the CIS region to improve the educational ability of Korean language teachers. To this end, after analyzing the re-education program for Korean language teachers in the CIS area 2016 to 2022, an importance-performance analysis (IPA) analysis was conducted based on this. As a result of the analysis, Korean language classes and cultural experiences are areas that should be maintained continuously, and the areas with low performance compared to the demands felt by teachers were in the area of Korean teaching methods. Culture/history teaching methods, Korean language studies, and visits to attractions were not high priorities, so they could be considered as future programs, and it was analyzed that the proportion of other programs such as cultural/historical contents and exchange programs should be lower than the present.
A Study on the Communication Ability and Interaction of Practical Beauty Learners

The purpose of this study was to provide basic data for the development of teaching and learning methods for beauty practical education by studying the effect of communication skills of beauty major students on practical class interaction. The data collection was conducted from March 14 to April 17, 2023 on college students majoring in beauty at domestic universities, and a total of 413 copies were analyzed using the SPSS WIN 21.0 program. The research conclusions are as follows. First, students with higher communication skills showed the highest interaction during class. Second, the higher the communication ability, the higher the correlation between class time interaction. Third, linguistic communication skills have been shown to affect interaction. Therefore, as a way to increase interaction, it is necessary to apply subjects and teaching methods that can increase linguistic communication skills. In addition, interactions such as mutual conversation and emotional exchange, listening and rejection, recognition and understanding should be activated by appropriately using textbooks, practical classes, and materials. It is believed that communication skills should be cultivated through various classes such as discussion and presentation as a professional beauty person.
sistem informasi penjualan pada toko raja vapor gebog berbasi web dengan metode cross selling

Right Now Raja Vapor Gebog its sales are still dependent on direct sales. That is, promoting products to customers by coming directly to the store introduced products using makeshift media. With the system running still using the manual way in today's fierce competition, it is difficult to achieve the development of the company. From this problem, Raja Vapor Gebog needs to make changes to achieve these goals. One of the solutions offered to overcome these problems is to create a sales system website. For that in sales at Raja Vapor using the method of cross selling where when the buyer buys the desired item then the seller will offer a product that is felt to have a relationship with the product that the buyer wants to buy.&#x0D; With the aim of this system application can help customers and owners to facilitate each other in making transactions. The application will be built using waterfall development method by analyzing the needs using observation and interview method. System design is UML (Unified Modeling Language), So it can be applied using a responsive web with the creation of applications using PHP programming language and MYSQL database.&#x0D; &#x0D; Keywords: Shop; Sale; Cross Selling; Waterfall.
The Effect of Cooking Contents Information Quality on User Satisfaction and Intention for Continuous Use: Focusing on the Mediating Effect of User Satisfaction

The study examined the effect of cooking contents information quality on user satisfaction and intention for continuous use with a specific focus on subscribers of You Tube cooking contents. This study also analyzed the mediating effect that user satisfaction has on the intention for continuous use. A total of 220 surveys were used in the study. As a result of the analysis, First, among the cooking contents information quality, reliability, usefulness, recency, and playfulness has been found out to have a significant positive effect on intention for continuous use. Second, user satisfaction was discovered to have a significant positive effect on intention for continuous use. Third, user satisfaction was found to have a significant a partial mediating effect in the relationship between cooking contents information for continuous use. Such results of the study are expected to contribute to improving the quality of cooking contents on You Tube.
The Effects of Early Childhood Teacher’s job satisfaction and work environment on sensitivity

The purpose of this study is researching the effect of early childhood teachers' job satisfaction and working environment on sensitivity. From June to July, 2019, the 329 early childhood teachers working at the early childhood education institutions in Busan and Gyeongnam, South Korea, were the subjects of this study. A correlation analysis and step-by-step multiple regression analysis were conducted with SPSS 23.0 for analyzing the collected data.&#x0D; The main results of this study are as follows. First, the early childhood teachers' sensitivities have a positive relation with the job satisfaction excluding work loads. The working environment have a positive correlation with the sensitivity in all sub-factors. Second, it was shown that the early childhood teachers' job satisfaction and working environment affect the sensitivity. In terms of explanation power, it was shown total 30% including 28% for the job satisfaction and 2% for the working environment. Therefore, it is required to enhance the job satisfaction of early childhood teachers and provide a proper working environment to increase the sensitivity of early childhood teachers.
The Study on the Development of Diagnosis Tool for Creativity Convergence Competencies

The purpose of this study is to develop a diagnostic tool for Creativity· Convergence competencies for adults in Korea. Literature review, expert review, Delphi surveys, and a questionnaire survey were used as research methods, and the diagnostic tool of Creativity· Convergence competencies was developed and verified in a scientific and systematic way. After expert review and Delphi surveys, the questionnaire survey was conducted targeting 1,000 adults. As a results, construct validity, discriminant validity, criterion validity, and measurement equivalence across gender of the items were verified, and the reliability of the items was found to be very high at Cronbach’ alpha .947. Through the overall analysis process, 12 final items were finally confirmed.
A Case Study on Learning Behavior in Online English Reading Class of an On-off Course

This study is a case study on investigating students’ learning behavior in the online English reading class of an on-off course. For this purpose, a survey was conducted on a total of 77 students from an English listening and reading course and phone interview with 5 students was implemented. The findings revealed that regularity of learning interval and learning sequence need to be improved through student management in order to increase the effect of online learning. In case of lecture watching, the students are good at utilizing the strengths of taped lecture, such as using pause and repeating watching. However, more research need to be done on how to develop online lecture to enhance students’ understanding of the lecture. Regarding the offline review quiz that is supposed to stimulate students into their more positive watching of the lecture, it is suggested that a few of its related elements such as the online learning period and the number of quiz questions be corrected for its better effect.
Analisis Emosi pada Media Sosial Twitter Menggunakan Metode Multinomial Naive Bayes dan Synthetic Minority Oversampling Technique

Twitter social media is often used to express one's emotions through tweets. Much research has been conducted on emotional analysis in the social media Twitter. Machine learning is a tool that is widely used to categorize emotions. However, an imbalance in the amount of data between classes is often a problem. So, this research aims to determine the performance of the combined Multinomial Naïve Bayes (MNB) and Synthetic Minority Oversampling Technique (SMOTE) methods for emotional analysis of tweets from the social media Twitter. Each tweet through data preprocessing in this research includes case folding, data cleaning, convert slangword, convert negation, tokenization, stopword removal, and stemming. For feature extraction the n-gram method is used and for feature weighting the term frequency method is used. Testing was carried out using K-Fold Cross Validation. Based on the test results, using SMOTE an average accuracy of 0.65 or 65% was obtained and an average f1-score value of 0.66 or 66%. Meanwhile, without SMOTE, an average accuracy of 0.64 or 64% was obtained and an average f1-score of 0.65 or 65%. Although in this study it can be shown that the results using SMOTE are 1% better in categorizing emotions. However, the results obtained are not optimal, and other methods of data balancing and machine learning still need to be studied.
SISTEM INFORMASI PENJUALAN PADA DISTRO SATRIANI NEW STORE BERBASIS WEB

Distro Satriani is a shop that sells t-shirts, jackets, bags, etc. which is located on Jl. Hasanudin No. 2A, Terbono, Selosari, Kec. Magetan, Magetan Regency. The sales, marketing and promotion system used today is still using a manual system. It is very necessary to facilitate service for customers who are far from out of town. To realize an application by conducting research that aims to help Distro Satriani in expanding the scope of promotions, helping customers who come from outside the city to keep shopping and maximize product sales. So it was built an online sales system on web-based Satriani distribution using the PHP programming language and MySQL database. By using the waterfall research method. As well as testing is done using Blackbox Testing to check whether the system that has been created is in accordance with the business processes running in the company and can overcome existing problems. Based on the results of system testing, the Sales Information System at Distro Satriani can handle the sales process effectively. In addition, this system can display sales-related reports easily and quickly
Product Sales Information System on Teak Wood Furniture “UD. Jati Setia” Web-Based Using the CodeIgniter Framework

Computerized technology in a company is a necessity today. It has brought significant changes to the business world. So, UD Jati Setia, as a teak wood furniture company engaged in furniture, wishes to implement these advances in technology and information. Currently, the marketing and buying, and selling process that is carried out is still using conventional methods and has not implemented a computerized information technology system. Regarding product introduction among the wider community, the UD Jati Setia company is still not optimal. The operational activities are still manual using a note. Therefore, this causes the development of a company to be prolonged, and its efficiency is not optimal. This study created a web-based sales information system to maximize, simplify and save time in managing and promoting products and companies. A web-based sales information system uses the Waterfall application development method, while system testing uses the Black Box. This system can assist the owner in managing transactions and promotions among the wider community.
INFORMATION SYSTEM WEB-BASED ACCEPTANCE OF NEW STUDENTS (CASE STUDY: SMK N KARTOHARJO MAGETAN)

The development of information technology today cannot be separated from all human activities, information technology also affects the field of education. In this case, the Admission of New Students at SMKN Kartoharjo Magetan still applies a manual registration system, namely by coming directly to the school to get a registration form from the school. To solve the problem above, an application was made entitled "Web-Based New Student Admission Information System (Case Study of SMKN Kartoharjo Magetan)". This study uses the waterfall development research method. The modeling used is a Unified Modeling Language with diagrams used use case diagrams, activity diagrams, sequence diagrams. This new admissions information system was built using the PHP programming language and utilizes the MySQL database as a database server. The test results from the New Student Admission Information System get results that are in line with expectations with the Blackbox Testing test. So it can be concluded that the accurate percentage of system success is 100%.&#x0D;
Sistem Informasi Pemesanan Bus Pariwisata Berbasis Web pada “Dikma Transport”

Dikma Transport Company is a service company engaged in transportation. In the process of ordering transactions still using the manual method, so the data has not been computerized. This causes the slow search of customer data in the rental process and preparing bus booking reports. In addition, customers must also come to the location directly to place an order or obtain the required information. The purpose of making this information system is to make it easier for company owners to manage transaction data and make reports, so that the data can be computerized properly. In addition, the existence of this information system is expected to increase customer satisfaction. This information system is made using the codeigniter framework and the development method is the waterfall with the stages of literature study, observation data collection, and software development. The result of this research is the creation of a tourism bus ordering information system on a web-based "Dikma Transport" that can provide convenience to company owners to manage transaction data and report generation. In addition, the data processing process which was previously still manual using paper media, is now computerized so as to increase efficiency and effectiveness.
Research on Weibo New Word Recognition based on Weibo Data and Statistical Information

One of the key challenges in the field of Chinese information processing is the recognition of Weibo new words, which has a profound impact on machine translation and text classification. As Weibo has become the most used social platform for internet users, mining new vocabulary from Weibo data not only helps to deeply understand the data itself, but also provides personalized recommendation services for users. Although a large amount of research has focused on the recognition of Weibo new words, specialized research in this field is still scarce. In this article, we propose a Weibo new word recognition strategy that combines Weibo content features and statistical information. Firstly, extract repetitive vocabulary from Weibo topic names, and then use various methods such as absolute frequency, relative frequency, mutual information, and information entropy to filter for incorrect vocabulary. The experimental results show that by setting appropriate thresholds, incorrect vocabulary can be effectively filtered out, thereby improving recognition performance.
Remote Sensing Target Detection Algorithm based on CBAM-YOLOv5

With the continuous improvement of traditional target detection algorithms, remote sensing targets have become a research hotspot. Aiming at the problems of low recognition accuracy caused by small target size and high background complexity in remote sensing images taken from overhead view, this paper proposes a remote sensing aircraft detection algorithm based on CBAM-YOLOv5. By introducing the lightweight convolutional attention module CBAM module into the YOLOv5 network, the feature extraction capability of the algorithm is improved to solve the problem that the small-size remote sensing target has little or even lost information on the feature map after multiple downsampling operations. The mAP of the proposed algorithm reaches 93.1%, which is 1% higher than that of the original algorithm, and the recognition of small-size remote sensing targets has been significantly improved.
Based on YOLO v3 Target Recognition Algorithm as Vehicle Tracking Algorithm Analysis

Traditional traffic information acquisition and acquisition are mainly implemented by sensors, and these traditional acquisition and acquisition systems have some great drawbacks. However, with the popularity of traffic monitoring, computer vision technology gradually has a platform foundation that can be applied to identify and track traffic conditions. In this paper, through the research of traditional and Deep learning-based multi-target recognition algorithms and two common multi-target tracking algorithms, a solution of YOLO v3 network combined with deep-sort algorithm is proposed. In this paper, a video of traffic information of urban roads is directly collected for areas with relatively large traffic flow. Interval frames are extracted from the video data set to make relevant data sets for training and verification of YOLO v3 neural networks. Combined with the test results, an open source vehicle depth model dataset is used to train the vehicle depth feature weight file, and Deep-SORT algorithm is used to achieve the target tracking, which can realize the real-time and more accurate multi-target recognition and tracking of moving vehicles.
Research on Object Trajectory Detection System Based on Computer Vision

The main task of object trajectory detection is to collect and synthesize all kinds of information generated in the process of object motion, and get the displacement information of object in 3D space. Vision is one of the important ways for human beings to perceive the external environment and the cognitive world, and it plays a very important role in human life. With the development of computer technology and signal processing technology, a computer vision discipline based on the principle of simulating human eyes has gradually formed. In this paper, an object trajectory detection system based on computer vision is studied to realize object trajectory detection. In this paper, an improved particle filter algorithm is used to track moving objects. The research results show that the improved particle filter algorithm effectively reduces the influence of calculation error and nonlinear error on the measurement system and improves its accuracy. The practical application results show that the measurement error of the system can be controlled at about 5% when considering various error factors, which can meet the needs of practical application.
Joint Modelling of Slot Filling and Intent Detection in Constrained Resource Scenarios

In the era of pervasive smart devices, natural language understanding (NLU) holds a pivotal role for facilitating intelligent interactions and decision-making. Core to NLU are slot filling and intent recognition, essential tasks for comprehending user input. While joint modelling of these tasks has gained prominence, the challenges of realizing efficient joint models on resource-constrained devices have emerged as significant. These devices possess limited computational capacity and real-time requirements, necessitating lightweight and efficient models. In this study, we explore the design of a resource-efficient joint model for slot filling and intent recognition. Through leveraging BERT, , graph neural networks, and mask mechanisms, our model achieves the dual goals of semantic slot prediction and intent classification. We focus on model design, training, and real-time inference, aiming to contribute to the paradigm of resource-constrained natural language understanding. Our investigation demonstrates the efficacy of our approach, even when working with a reduced dataset, underscoring the model's applicability to real-world scenarios with limited resources.
Next Generation Blockchain Trends

Blockchain technology is a decentralized technology that distributes and stores the ledger containing transaction details to all members participating in the transaction, and is a core technology for next-generation service security. This paper begins with a brief introduction to the basic principles of blockchain processing, followed by the latest technology and standardization of blockchain 3.0, as well as application service trends such as NFT (Non-Fungible Token), DID (Decentralized ID), and DAO (Decentralized Autonomous Organization). Analyze. In addition, future research topics include expanding scalability, strengthening security, protecting personal information by encrypting transaction information, and reducing power consumption to overcome the limitations of blockchain.