Reviewerly/exHarmony huggingface dataset:
Economics of open source versus open science

Common postman (&lt;em&gt;Heliconius melpomene&lt;/em&gt;) on a &lt;em&gt;Lantana&lt;/em&gt; Almost two years ago I started participating on the then-new (now-archived) npm forum. I had been using npm for a few years at that point, and I had some free time to spend providing technical support, for fun. I fixed a number of bugs in the CLI, and users thanked me for those. My impact was limited, but the work was fulfilling. That is, until the developers at npm I had been working with got laid off.
Face Recognition Attendance System: A Deep Learning Approach For Efficient Monitoring

The face recognition attendance monitoring system is a modern, reliable and accurate system that automates the process of recording attendance by recognizing human faces.This system uses computer vision and machine learning algorithms to identify the unique facial features of individuals and match them with preexisting records to determine their presence or absence.The system is comprised of a camera that captures the image of individuals as they approach a designated area.The image is then analyzed by the system to extract facial features such as the distance between eyes, shape of the nose, and the contour of face.These features are then compared to the pre-existing records to determine the identity of the individual.This system has numerous advantages over existing attendance recording methods.Firstly, it eliminates the need for manual recording and processing, reducing the risk of errors and increasing accuracy.Additionally, the system is efficient and can process large volumes of individuals in a short time, reducing waiting times and congestion.Finally, it enhances security by providing an additional layer of identity verification
Smart Meter using Blockchain

Meters are widely recognized as cutting-edge technologies within the smart grid, owing to their exceptional capabilities in communication and real-time monitoring.Smart meters offer numerous benefits, including energy-saving features and cost-effective control of the grid.By utilizing our smart meter, service providers can efficiently analyze location-specific data and make early predictions for additional current supply.Our proposed project aims to develop an automated device capable of recording energy consumption and securely storing the data in blockchain, which is facilitated to purchase energy as pre-paid through cryptocurrency.Given the potential privacy concerns associated with real-time data collection, we have implemented blockchain technology to ensure user confidentiality.In addition to enhanced privacy, our smart meter incorporates built-in fire and gas detectors, providing enhanced security for both devices and households.Furthermore, the smart meter includes a home automation system that allows users to control smart appliances.Moreover, it offers wireless control of electronic devices through a mobile application.The smart meter also employs environmental sensors to automatically adjust cooling appliances (fans, AC, etc.) based on temperature and lighting conditions, turning on when the environment is dark and offwhen it detects light.
Pengaruh kualitas sistem, kualitas informasi, dan kualitas layanan terhadap kepuasan pengguna e–learning di Perguruan Tinggi

E-learning as a learning system is expected to improve the quality of student learning. Satisfaction of using the system is influenced by the quality of the system, the quality of information and the quality of service. This study aims to test and obtain empirical evidence on the effect of system quality, information quality, and service quality on user satisfaction of e-learning system in learning at Islamic Education Study Program of Universitas Muhammadiyah Yogyakarta This type of research was quantitative research with survey method. The population in this study was Islamic Education students of Universitas Muhammadiyah Yogyakarta Batch of 2017, 2018, and 2019, with a sample of 252 respondents. Data collection method used proportional random sampling with questionnaire instrument. Data analysis used regression analysis with the help of IBM SPSS Statistic ver. 26 software. The results of this study showed that System Quality had a significant positive effect on User Satisfaction. Information Quality had a significant positive effect on User Satisfaction. The Service Quality had a significant positive effect on User Satisfaction.
Perancangan Mesin CNC Acrylic Cutting 3 Axis Dengan Menggunakan Laser Tube CO2

Almost all activities are carried out with the help of technology. It is as if technology has become a basic need for human life today. Of all the areas that have made progress, machinery is the one that has had the greatest effect. Lots of machines have emerged with new innovations with very diverse functions, one of which is the Computer Numerical Control (CNC) machine. A CNC machine is a machine used in the manufacturing industry to quickly produce large quantities of components for the engineering sector. As the name of the CNC itself, every work from CNC uses a computer system that has been well formed to produce goods that are in accordance with what is desired. Departing from some of the problems above, the author concluded to make a similar technology at a much cheaper price with a more practical work system, therefore the author made a 3 Axis Acrylic Cutting CNC Machine Using a CO2 Laser Tube".
Metode Bidirectional Associative Memory (BAM) Kontinu Pengenalan Pola Karakter Untuk Keamanan Data

Artificial Neural Networks have a paradigm for processing information with the concept of working using biology in processing information similar to how the human brain works. Artificial neural networks solve many problems using the concept of uncertainty such as the discussion in the material, namely the introduction of Continuous BAM Character Patterns. The problem in this research is the lack of data security in maintaining information so that a lot of data can be accessed by people who do not have authority. The main objective of this research is to maintain data security using the Continuous BAM concept. The BAM Kontine method is a method that has the ability to have associative memory or content addressable memory that can be called by using the part stored in the memory itself. The Continuous BAM method will change input to output more smoothly with values that lie in the range [0,1]. The activation function used is the sigmoid function. The results obtained from x1 = [7,-11], x2= [7,13] and x3=[-1,9], All Signs can be recognized by the Continuous BAM algorithm. All Sign Patterns have the same target but have different values.
Klasifikasi Sentimen Tragedi Kanjuruhan Pada Twitter Menggunakan Algoritma Naïve Bayes

The Kanjuruhan Malang incident occurred on October 1 and resulted in 132 deaths, 96 serious injuries and 484 minor injuries. The cause of the riot occurred due to provocation between Arema Malang supporters and Persebaya Surabaya supporters who mentioned harsh words and other provocative actions that caused anger on both sides. Sentiment analysis of the Kanjuruhan tragedy using the Naive Bayes method was conducted through tweets taken through Twitter to understand the public's perception of the incident. The Naïve Bayes algorithm is performed for the sentiment classification of tweet data which is applied by processing the tweet text and classifying it into positive, negative, and neutral. In this study using data as much as 4843 data and carried out with tweet data that has been crawled resulting in 2,042 data. This research aims to classify sentiment and determine the level of accuracy in the Multinomial Naïve Bayes algorithm in the Kanjuruhan tragedy using a dataset in the form of tweets from twitter social media. The processed tweet data is divided into two types, namely 90% training data and 10% test data. The results of this classification get a Naïve Bayes accuracy of 75% with a precission of 73%, recall of 75%, and f1-score value of 74%. The results of the tweet data used in this study can be concluded that the Naïve Bayes algorithm has a fairly good accuracy value.
"The Impact of Social Responsibility on Perceived Service Quality among Graduates of Onaizah Colleges in Saudi Arabia"

The study aims to determine the relationship between social responsibility and perceived quality of service from the point of view of graduate students, a sample of 180 graduates from one college. The only response was 82.5% 148 and the survey list was designed using Google models to measure study variables. Statistical analyses were conducted using (SPSS.V.25), and study assumptions were tested using descriptive methods such as averages, percentages, and standard deviation, as well as analytical methods such as simple linear regression, and study results: most important: 1. The social responsibility dimensions of qualified colleges have a morally positive impact on the perceived quality of service from the perspective of graduate students. The study made many recommendations that could help relevant colleges strengthen the dimensions of social responsibility and improve the quality of service, most importantly by providing standards and methods for measuring social responsibility and perceived quality of service to college clients periodically.
Klasifikasi Sentimen Transformasi dan Reformasi Sepak Bola Indonesia Pada Twitter Menggunakan Algoritma Bernoulli Naïve Bayes

Federation Internationale de Football Association (FIFA) carried out Transformations and Reformations to Indonesian Football with one of them Indonesia was chosen as the Host of the U-20 World Cup in 2023. The transformations and reformations carried out cause people to often provide opinions through social media Twitter. Opinions given by the public can be positive or negative. The research uses Text Mining to classify sentiment in 2 categories with the Bernoulli Naïve Bayes algorithm. This research aims to classify positive and negative sentiments and determine the level of accuracy value of the sentiment classification results of Indonesian Football Transformation and Reformation. The research stages carried out are data collection, text preprocessing, data labeling, TF-IDF weighting, Bernoulli Naïve Bayes classification, and evaluation. Based on the research results from 4907 data there is duplicate data and only uses 2125 data which is divided into 90% training data and 10% testing data, so as to get accuracy with a high category value of 88%. The classification results show that many tweets are positive sentiments.
Spectral Bayesian network theory

A Bayesian Network (BN) is a probabilistic model that represents a set of variables using a directed acyclic graph (DAG). Current algorithms for learning BN structures from data focus on estimating the edges of a specific DAG, and often lead to many ‘likely’ network structures. In this paper, we lay the groundwork for an approach that focuses on learning global properties of the DAG rather than exact edges. This is done by defining the structural hypergraph of a BN, which is shown to be related to the inverse-covariance matrix of the network. Spectral bounds are derived for the normalized inverse-covariance matrix, which are shown to be closely related to the maximum indegree of the associated BN.
Computer Vision in Human Analysis: From Face and Body to Clothes

For decades, researchers of different areas, ranging from artificial intelligence to computer vision, have intensively investigated human-centered data, i [...].
Determining the Scale of Military Echelon Using Deep Learning-Based Object Detection and Tracking Techniques

4차 산업혁명 기술의 발전과 인구절벽 등 여러 요인으로 인해 군이 맞닥뜨리게 될 미래 작전환경에서 전투행위의 주체는 무인 중심으로 전환될 것이다. 그중 감시정찰 분야는 가장 먼저 무인체계에 의해 임무가 대체 되어가고 있다. 본 논문에서는 딥러닝 기반의 알고리즘을 활용하여 지상 감시 간 기동하는 군 제대의 규모를 판단하기 위한 연구를 수행하였다. 딥러닝 알고리즘 중 객체탐지와 객체추적 기법을 활용하여 영상 내 특정 무기체계를 식별하고 탐지된 객체의 계수를 통해 제대 규모를 판단하였다. 특히 기동 및 화력 무기체계인 자주포, 전차, 장갑차를 기준으로 제대규모를 판단하였으며, 제대의 규모를 판단할 수 있는 특정 무기체계에 대한 탐지와 추적, 계수에 집중하였다. 모델은 객체탐지 알고리즘인 YOLOv8s를 객체 검출기, 다중 객체추적 알고리즘에서 높은 성능을 보여주는 BYTE 알고리즘을 추적기로 구성하여 객체탐지와 추적을 수행한다. 마지막으로 객체탐지와 추적에 이어 클래스별로 객체를 계수하고 계수된 값에 의해 규모를 판단하는 알고리즘을 추가하여 모델을 완성하였다. 학습 데이터는 지상에서 촬영된 이미지를 클래스별로 수집하였고 클래스는 자주포, 전차, 장갑차 3가지로 구성하였다. 모델 평가를 위해 제대규모를 반영한 테스트 영상으로 모델의 정확도를 확인하였으며 80%의 정확도를 나타내었다. 본 연구를 통해 향후 지상 감시장비를 활용해 군 제대규모를 판단할 수 있는 방법을 제시하였다는 것에 의의가 있다. The development of the Fourth Industrial Revolution, along with factors, such as population decline, will lead to a shift towards uncrewed systems in the future battlefield. The military will increasingly rely on uncrewed systems to carry out operations. Among them, uncrewed systems are replacing the surveillance and reconnaissance field. In this study, deep learning-based algorithms were used to judge the scale of ground-based military echelons moving in the surveillance area. A specific military unit was identified in the video using object detection and tracking techniques, and the scale of the military echelons was determined based on the count of detected objects. In particular, this study focused on detecting, tracking, and counting specific weapon units, such as self-propelled artillery, tanks, and armored vehicles. The model consists of the YOLOv8s object detection algorithm as an object detector and the BYTE algorithm as a multi-object tracking algorithm, showing high performance in object detection and tracking. Finally, the model was completed by adding algorithms that count objects by class and judge the size based on the counting. The training data was collected by the three types of classes from images taken from a ground perspective: self-propelled artillery, tanks, and armored vehicles. This study evaluated the model accuracy using test videos, and the result had an accuracy of 80%.
Like, Subscribe, Follow, and Connect to JNEB

You may have noticed that JNEB is popping up in new ways and places across social media: new platforms, graphics, and content. If you haven't seen this change, please connect with our various social media platforms to avoid missing out on the excitement! More on where to find us in a minute. What's behind this shift and expansion? This effort is very intentional and for YOU! We are strategically pushing to expand how we engage with our contributors and readers. Why? We want JNEB to be more than just a periodic journal for you. As a nutrition education and behavior professional, we want you to see us as your home journal and a consistent, reliable resource. Regularly engaging with our journal brings so much professional and personal benefit. The more touch points you have with JNEB, the more you can stay connected with what is happening across nutrition education and behavior research, practice, and policy. This connectedness will lead to more professional development and success. Additionally, we can provide you with important information that can increase your success in publishing your work in our journal and make you a better peer reviewer as a service to your profession. Social media has become a prominent resource for professionals to receive pertinent information that helps them solve problems and advance their work. JNEB is embracing this. We want to meet you where you are. We want to reach you in places where you like to receive information. So follow us on Twitter. Connect with and follow us on LinkedIn. On these platforms, we post content, tips, and even polls so you can have a voice in improving JNEB. Listen to our monthly Featured Article Podcasts on Spotify, YouTube (please like and subscribe!), and Apple Podcasts. They are a perfect listen for when you are driving or walking around. There is so much great JNEB content across so many platforms. We want increased information exchange with our readers and contributors. We want you to know what is happening at JNEB and what we are interested in publishing. We want to know from you: What topics are you most interested in? How can we better engage and share information with you? How can we help you be a peer reviewer to serve your profession? What can we do to facilitate you contributing your research and practice materials to JNEB? So please engage with us and take advantage of these great opportunities to provide us with input across our social media channels. We would love to connect with you! Find us here: Twitter: @JNEBOnline LinkedIn: Journal of Nutrition Education and Behavior Youtube: Journal of Nutrition Education and Behavior (JNEB) Spotify: Journal of Nutrition Education and Behavior (JNEB) Apple Podcasts: Journal of Nutrition Education and Behavior With more to come…
Tangible Cultural Properties of Abucay, Bataan, Philippines: Significance, Issues, and Conservation Measures

The rich history and culture of Abucay, Bataan is reflected in its tangible cultural properties. Hence, this study aimed to document the tangible cultural properties of Abucay, Bataan specifically its significance, issues, and conservation measures. Following participatory cultural mapping as an approach to this research, this study employs the Cultural Mapping System of the National Commission for Culture and the Arts. Using the Cultural Mapping Toolkit of NCCA, a semi-structured interview questionnaire, and documentary analysis, this study identified and documented nineteen movable tangible cultural properties and seven immovable tangible cultural properties. This study found that cultural properties of Abucay, Bataan are now threatened by environmental disasters, sensitivity of the materials, and a lack of training and knowledge on the proper handling of tangible cultural properties. Nonetheless, the locals are quite receptive to conserving these properties. Indeed, the study demonstrates the conventional thinking that history and culture are inextricably linked. They are strongly intertwined and may be explored concurrently using material objects, both movable and immovable. Thus, the study recommends collaboration among the local government unit, academic institutions, and private organizations in promoting Abucay, Bataan’s cultural and historical treasures. Finally, the identified tangible cultural propertiees must be included in mainstream curricula particularly in teaching Social Studies in basic education through the collaborative effort and support of the Department of Education, the National Commission for Culture and the Arts, and the Municipal Government of Abucay. Keywords: Abucay; immovable; movable; tangible cultural heritage
Research Trends Related to Korean Pronunciation Education for Chinese Learners

This paper reviews trends in Korean pronunciation education and related research on Chinese learners from 2011 to the end of 2022, revealing problems and suggesting future issues. It reviews past research findings on Chinese learners, analyses them by year, research topic, and details, and describes trends in research on Korean pronunciation education for Chinese learners. Based on the results of this analysis, it is clear that research on pronunciation education for Chinese learners has been ongoing and that there is a trend towards more sophisticated research. Several problems revealed by the research results are also presented, and the future direction of Korean pronunciation education for Chinese learners is explored. From the problem of the large number of papers with similar content and composition to the problem of how the contradiction between standard pronunciation and linguistic reality has developed into the problem of Korean pronunciation education in foreign languages, several suggestions are made. The significance of this paper is that it not only grasps the direction of research in Korean pronunciation education for Chinese learners over the last decade or so, but also reveals the problems that exist and suggests future topics.
Implementasi Data Mining Memprediksi Penjualan Crude Palm Oil Berdasarkan Kapasitas Tangki Menggunakan Multiple Linear Regression

Data mining is a process of discovering information from data that can be used to improve business, product development, and other decision-making processes. One application of data mining is in PT. Kerry Sawit Indonesia, which is an agribusiness company in the Wilmar Group that deals with processing crude palm oil (CPO). Sales of CPO are crucial for palm oil plantation companies. To increase efficiency and profitability, palm oil plantation companies can predict CPO sales to optimize sales and CPO inventory. One method that can be used to predict CPO sales is through data mining techniques. In this study, the data mining technique used is multiple linear regression. Multiple linear regression is used to determine the relationship between the tank capacity variable and CPO sales. The data used in this study are CPO production data, CPO sales data, and tank capacity data obtained from palm oil plantation companies over the last five years. The results of the Multiple Linear Regression calculation in this case study show that the coefficient of determination (R-squared) value is 0.9546, indicating that 95.46% of the CPO delivery variability can be explained by the independent variables. Additionally, the MAPE and RMSE tests show that the regression model obtained has good accuracy in predicting CPO deliveries. Therefore, this regression model can be used to predict CPO deliveries in the future, considering the predetermined independent variable values.
Imparting Systems Engineering Experience via Interactive Fiction Serious Games

Serious games for education are becoming increasing popular. Interactive fiction games are some of the most popular in app stores and are also beginning to be heavily used in education to teach analysis and decision-making. Noting that it is difficult for systems engineers to experience all necessary situations which prepare them for the role of a chief engineer, in this paper, we explore the use of interactive fiction serious games to impart systems engineering experience and to teach systems engineering principles. The results of a cognitive viability, qualitative viability, and replayability analysis of 14 systems engineering serious games developed in the interactive fiction genre are presented. The analysis demonstrates that students with a systems engineering background are able to learn the Twine gaming engine and create a serious game aligned to the Apply level of Bloom’s Taxonomy which conveys a systems engineering experience and teaches a systems engineering principle within a four-week period of time. These quickly generated games cognitive, quality, and replayability scores indicate they provide some opportunity for high-level thinking, are of high quality, and with above average replayability, are likely to be played multiple times and/or recommended to others.