Reviewerly/exHarmony huggingface dataset:
Hierarchical Structure of Texts: : Algorithm shows the Semantic Object, its characteristics, and functions

This article discusses the importance of hierarchy in the text for a full understanding. Natural language processing algorithms may be used to identify primary and secondary ideas, semantic objects, and their features and functions in texts. By following these steps from general concepts to more specific ones depending on the complexity and size of the text as well as its purpose, such algorithms allow for deeper analysis of textual content. However, full comprehension still requires human skills such as making inferences and interpreting figurative language.
RFID application for attendance control in scientific events

This work presents the various development stages of an information system that aims to control attendance at scientific events, through radiofrequency identification. This solution involves both hardware and software. This system was designed to manage the participants of multiple scientific events, process that occurred manually at the Federal Institute of Education, Science and Technology of Mato Grosso do Sul - IFMS Campus Três Lagoas/Brasil, demanding considerable time from the organizers and requiring extra effort to certify those present at events. In this solution, each participant receives an RFID tag that uniquely identifies them during an event. In each space of events where activities take place, a case with a Wemos coupled to an RFID capture module will be available. Participants, through their RFID tags (Radio Frequency Identification), register their frequencies in activities in the capture modules, which send the numbers of the tags read to the Wemos microcontroller. Then, the processing of the capture data takes place, a process that involves all the logic of processing and manipulating the reading data before sending the information to the server. The transfer of capture data occurs through a WebSocket server, which makes a bidirectional communication with Wemos customers and ensures that the system is online, to meet their simultaneous requests. After the validation of the captures is finished, the data is persisted in a PostgreSQL database. The $\mathrm{C}++$ programming language and the QT Creator were used for development of the desktop graphical interfaces. Reports of attendance at activities to subsidize the certification of events were made available.
Using Visual Resources to Assist in the Teaching-Learning Process of Operating Systems Through the Development of a Simulator

Tools like analogies, games and simulators have been used to facilitate the teaching of abstract concepts, providing a more playful environment that favors the teaching-learning process. Courses in technology area are composed of abstract concepts that are difficult to learn, such as the subject of Operating Systems. Thus, this work presents the SOSimulador development and evaluation, a visual tool developed to assist in the teaching-learning process of Operating Systems courses. This project was developed following the Software Engineering concepts defined in the agile methods and its validation was carried out with a case study, in which the participants evaluated the tool positively, with an average rating of 4.33 (between 0 and 5) points.
Educational Flexibility and its impact on the Hybrid Modality

the digital transformation has generated unprecedented changes worldwide, in this sense; the education sector has undergone significant changes in the way in which technology-mediated curricular content is offered, hence the importance of analyzing the role of technology. educational flexibility in the hybrid education model, particularly in the post-pandemic stage in university students, precisely, one of the effects after the confinement by COVID-19 has been the incorporation of new methodologies to education, which are mediated by the technology, where the acquisition and transmission of knowledge have been adapted to meet training needs at the higher level.The impact of educational flexibility in hybrid education is evaluated in business administration undergraduate students. Young people between the ages of 17 and 23 from the Faculty of Accounting and Administration of the Autonomous University of Baja California, Mexico, are taken as a study sample.Data processing is carried out using a correlational model of structural equations under the principal component rotation method, to define the degree of regression between the independent variable (Educational Flexibility) with respect to the dependent variable (Hybrid Education).The AMOS (Analysis of Moment Structures) software is used, which allows the design and validation of a structural statistical model that defines and identifies goodness-of-fit coefficients of the predictive investigative model, derived from the theoretical analysis, to estimate the hypotheses that support the results as a structural model, which helps to determine the degree of involvement of variables.The results show the preference of the students for the educational offer in hybrid modality over the face-to-face modality since it broadens the academic offer, their intellectual possibilities to achieve a better standard of living, therefore educational flexibility has a fundamental role in the adoption of educational modalities in hybrid format.
The State of Shared Leadership Research

Shared leadership is an emerging leadership style that emphasises collaboration, participation and sharing between leaders and team members. The purpose of this paper is to review the current state of research on shared leadership, including definitions, characteristics, influencing factors, and impacts on individuals and organisations. By reviewing and summarising and analysing the relevant literature, it can be found that shared leadership has positive effects in improving employee creativity, reducing employee stress and enhancing employee satisfaction. Future research should further explore the implementation mechanisms and ways of shared leadership, as well as the study of shared leadership in different cultural contexts.
The Impact of Online Teaching Using Interactive Learning Methods on the Utilization of Learning Resources

The management of learning resources is based on educational information technology, and the interactive learning method can improve teaching efficiency in colleges and universities. However, the diversity of resources leads to differences in teaching levels and attributes. To further improve students’ utilization of learning resources and the level of teaching in colleges and universities, the impact of online teaching using interactive learning methods on the utilization of learning resources was explored, and the application of database teaching in online teaching platform was analyzed. Based on this platform, the structure of an interactive learning-based intelligent Q&amp;A module was established to determine the impact of online teaching on the utilization of learning resources using interactive learning methods. Results indicate that the proposed method can effectively save students learning time while improving learning efficiency. The proportion of students who are not interested in online teaching using interactive learning methods is reduced to 0%. The application of the method described in this study is beneficial for enhancing students’ interest in online teaching using interactive learning methods, improving their learning outcomes, and increasing their academic achievements.
Sentiment Analysis Using Text Mining: A Survey

Sentiment analysis, also known as opinion mining, is a data mining technique used to extract and analyze sentiments expressed in textual data.It involves automatically determining the polarity (positive, negative, or neutral) of opinions or emotions conveyed in a large volume of text.By applying various natural language processing and machine learning algorithms, sentiment analysis enables the identification and classification of sentiments in an automated and scalable manner.This technique has gained significant importance due to the exponential growth of user-generated content on social media platforms, product reviews, customer feedback, and other sources.The abstract of sentimental analysis using data mining encapsulates the extraction of sentiments from text data, providing insights into public opinion, customer satisfaction, brand perception, and emerging trends.By analyzing sentiments, businesses can make data-driven decisions, improve customer experiences, detect emerging issues, and tailor their products or services to meet customer needs more effectively.
ICT Security Tools and Techniques among Higher Education Institutions: A Critical Review

Higher education institutions (HEIs) are increasingly relying on digital technologies for classroom and organizational management, but this puts them at higher risk for information and communication (ICT security attacks. Recent studies show that HEIs have experienced more security breaches in ICT security composed of both cybersecurity an information security. A literature review was conducted to identify common ICT security practices in HEIs over the last decade. 11 journal articles were profiled and analyzed, revealing threats to HEIs’ security and protective measures in terms of organizational security, technological security, physical security, and standards and frameworks. Security tools and techniques were grouped into categories with specific ways to protect ICT security. HEIs also implement general security standards and guidelines, such as the ISO 27000-series and Center for Internet Security (CIS) controls, in their framework. Through synthesis and analysis of ICT security tools and techniques among HEIs, this critical review hopes to provide research directions on IT governance that academic and technical administrators can further explore to secure their information resources.
ANALISIS KESULITAN BELAJAR SISWA DALAM PEMBELAJARAN MATEMATIKA PADA MATERI PERBANDINGAN DI SMPN 58 JAKARTA KELAS VII.2

The daily test results for student of class VII.2 SMPN 58 Jakarta on the Comparison material showed that 30 out of 36 students got scores below the MCML (Minimum Criteria of Mastery Learning). The low test results were not always caused by the level of students’ intellegence, but it could occur because students have difficulty learning, as a student with difficulty learning do not necessarily have inadequate intellegence. The research aimed to determine the type or form of learning difficulties and the causes for students during their learning. The research used qualitative method with a descriptive qualitative approach. The population in this research were 30 students of class VII.2 SMPN 58 Jakarta who got daily test scores below the MCML for Comparison material. The interview subjects were 6 out 30 students who were selected through purposive proportional random sampling, and a Math teacher in this class. The results obtained based on the test analysis and interviews found student difficulties, such as in interpreting language, in unsderstanding and using concepts, in using data, and in technical difficulty (counting). Then, the results obtained based on the anlysis questionnaire analysis and interviews found that students had difficulties due to their lack of confidence and mortification in learning, and teacher who didn’t understand each student personally.
Depth-Based Region Proposal: Multi-Stage Real-Time Object Detection

Many real-time object recognition systems operate on two-dimensional images, degrading the influence of the involved objects' third-dimensional (i.e., depth) information. The depth information of a captured scene provides a thorough understanding of an object in fulldimensional space. During the last decade, several region proposal techniques have been integrated into object detection. scenes’ objects are then localized and classified but only in a two-dimensional space. Such techniques exist under the umbrella of two-dimensional object detection models such as YOLO and SSD. However, these techniques have the issue of being uncertain that an object's boundaries are properly specified in the scene. This paper proposes a unique region proposal and object detection strategy based on retrieving depth information for localization and segmentation of the scenes’ objects in a real-time manner. The obtained results on different datasets show superior accuracy in comparison to the commonly implemented techniques with regards to not only detection but also a pixel-by-pixel accurate localization of objects.
STRATEGY FOR INCREASING INTEREST IN READING THE YELLOW BOOK OF STUDENTS AT THE AL-FATTAH 3 SIMAN LAMONGAN ISLAMIC BOARDING SCHOOL

This article aims to describe the planning and implementation of learning activities in improving the reading quality of the yellow book at the Al-Fattah 3 Siman Sekaran Lamongan Islamic boarding school and to analyze the pedagogic competence of teachers in the yellow book learning activities at the Al-Fattah 3 Siman Sekaran Lamongan Islamic boarding school. This study uses a descriptive qualitative approach using a type of research, namely a case study. Data collection techniques were carried out using unstructured interviews, participant observation, and documentation. This article produces: (1) planning of learning activities in improving the quality of reading the yellow book at the Al-Fattah 3 Siman Sekaran Lamongan Islamic boarding school is carried out by preparing books according to the specified curriculum and the process of learning activities is guided by the book being taught with the main target being able to memorize and understand the meaning in it so that they are able to practice it in their lives. (2) Teacher pedagogic competence in learning the yellow book at Pondok Pesantren Al-Fattah 3 Siman Sekaran Lamongan is included in the good category because almost all of it is implemented.
Logistic Regression Method for Sentiment Analysis Application on Google Playstore

Now days, there are a lot of social media. Each of social media has their one purpose. Each of application has their own function. We can download social media application from Playstore like Google Play or Appstore. Each Playstore gives users the opportunity to provide rating and review. Ratings and reviews from users can give conclusions about the application. Applications with a rating of 5 usually have good comments so that they are more worthy to be downloaded and used. Ratings with a small value cause other users not to use the application. Application owners need to know the results of comments from users which sometimes do not match the value given in the rating. So that the owner or application developer conducts an analysis of user comments on various social media, one of which is on the Playstore. Social media analysis is one way to get public opinion on a topic. One of them is used to analyze various applications provided in the Playstore. Various methods are used to perform social media analysis. This study uses the logistic regression method to analyze public comments into positive or negative comments. We analyze comments from social media applications on Google Play for android users. We get an accuracy value of 81% from 4 social media applications, with a total of 2268 comment data.
K-Means Algorithm and Clustering Technique for A Recommender System

Most of netizens are fond of traveling. Though they are interested to travel, majority of them are confused about where to go. Whenever the netizens planed for a travel, they spent hours searching for an interesting place that matches their point of interest. Therefore, there is a need for a recommender system which can recommend several interesting travel venues based on their preferences. Hence, information regarding different users prefers different travel locations are required. In this paper, Google review is used as a reference to divide the users into clusters of similar interests. The data has been divided into six scenarios which consist of the original data, scaled data, Principal Component Analysis (PCA) data, PCA scaled data, MinMax scaled data and Robust scaled data. The distance metric technique is performed in all these scenarios. Minkowski distance metric is used to measure the distance between the data points in the dataset and the elbow method to these scenarios to know the inertia values. This has revealed that the PCA with scaled data has lower distance and inertia value. The K-Means clustering is performed on this PCA-scaled data which divided the data into four different clusters. The results revealed are imperative to build any recommender system based on the users' preference.
An Effective Hybrid Encryption Model using Biometric Key for Ensuring Data Security

Cybersecurity becomes a key concern in many applications as cybercrimes exploit system weaknesses. Cryptography helps protect sensitive data in everyday transactions and communications using passwords or tokens. However, the power of the encryption/decryption algorithms always depends on their ability to secure the data in any situation. This paper presents an effective hybrid encryption/decryption model that makes use of a biometric key along with an effective password to ensure data security. The biometric key utilised in the proposed model is generated from the fingerprint, which is a unique physical characteristic of an individual. The model initially encodes the data to be securely transmitted. The symmetric key encryption that makes use of a biometric key is applied over the encoded data. Another layer of defence is built by applying asymmetric key encryption to the encrypted data along with the details of the fingerprint. The Advanced Encryption Standard (AES) algorithm and Elgamal Encryption using Elliptical Curve Cryptography (E3C2) are used for symmetric and asymmetric encryptions. Experimental analysis is performed to analyse the model's computing speed and security and is compared with existing models and encoding/encryption techniques
Blake–Zisserman Model of Segmentation Method for Low-Contrast and Piecewise Smooth Image

Although extensively investigated, image segmentation is still a challenging topic, particularly for new and developing imaging modalities with different levels of extremely strong noise. Edge-based models and region-based models are two types of variational segmentation methods that typically offer more robust solutions for complicated images. The primary challenge of segmenting low-contrast images with interesting visual features having piecewise smooth intensities is addressed in this project study. Whites and blacks are replaced by a plethora of grey tones in low-contrast images that have little to no tonal contrast. The difficulties posed by the two factors low contrast and piecewise smooth features are in fact well-known difficulties. Due of its potential to enhance the MS model, the Blake–Zisserman model is taken into account in this research. Similar to the MS, the model has never been explicitly solved, making it impossible to apply it exactly and directly. A convex-relaxed game formulation of the less well-known Blake–Zisserman model is applied in this study to segment images with poor contrast and heavy noise. Programming in MATLAB with a version of R2017b or higher will be used for this project. This paper suggests using segmentation to detect weak leaps and finer edges without being vulnerable to noise. By segmenting using a CRCV model, it can successfully improve photos that have undergone piecewise smoothing and low-contrast images. With the alternate direction approach of multipliers, try to solve the coupled issue using the split-Bregman variation (ADMM).
THE DEVELOPMENT OF POLY SYNCHRONOUS-BASED E-LEARNING FOR EFL CLASSES AT THE ISLAMIC UNIVERSITY

This study aims to develop e-learning and adapt the system to the needs of learning English. In addition, e-learning which can be used as asynchronous learning media can be integrated into learning media commonly used for synchronous learning also. So that all learning processes can be monitored and disciplined. In addition, the achievement of competence in learning English can be exceeded maximally. This research used the research and development (R&amp;D) method with the ADDIE model. In this method, the researcher uses a descriptive quantitative approach. The assessment instruments used were test scores, interviews, observations, and interviews. The parties involved in this research were English lecturers, students, online learning media experts, and English learning material experts.
Count Regression

This accessible and practical textbook gives students the perfect guide to the use of regression models in testing and evaluating hypotheses dealing with social relationships. A range of statistical methods suited to a wide variety of dependent variables is explained, which will allow students to read, understand, and interpret complex statistical analyses of social data. Each chapter contains example applications using relevant statistical methods in both Stata and R, giving students direct experience of applying their knowledge. A full suite of online resources - including statistical command files, datasets and results files, homework assignments, class discussion topics, PowerPoint slides, and exam questions - supports the student to work independently with the data, and the instructor to deliver the most effective possible course. This is the ideal textbook for advanced undergraduate and beginning graduate students taking courses in applied social statistics.
Retracted: Application of Image Recognition Based on Wireless Sensors in Dance Teaching System

[This retracts the article DOI: 10.1155/2022/2440263.].
Retracted: Exploration of Strategies for Organic Integration of Labor Education and Occupational Therapy for College Students

[This retracts the article DOI: 10.1155/2022/7115412.].
Retracted: Prediction Model of Ischemic Stroke Recurrence Using PSO-LSTM in Mobile Medical Monitoring System

[This retracts the article DOI: 10.1155/2022/8936103.].
Sistem Pendukung Keputusan Rekomendasi Supplier Bahan Baku Kerupuk Rambak Tapioka Terbaik Menggunakan Metode Evaluation Based On Distance From Average Solution (EDAS)

Kerupuk (Crackers ) are one of the specialties of the Indonesian people and are well-known by all social classes, from the lower to the upper middle classes. Most Indonesians consume crackers because they are delicious and can be consumed with any meal. This resulted in the proliferation of cracker manufacturers in Indonesia, not only producing a single type of cracker but also a variety of crackers whose flavor and ingredients were adapted to the palate of the Indonesian people. Crackers made from leather or Rambak crackers are well-known among the general population. Rambak crackers are not significantly distinct from other types of crackers. The difference is in the ingredients. Rambak crackers are made from various ingredients, including cow, buffalo, rabbit, chicken, fish, tapioca flour, and flour. In making these Rambak crackers, however, cowhide is typically employed. Cow leather is one of the products of the livestock sector, which, according to the Central Statistics Agency of Jember Regency, produced 11,287 pieces of leather in 2019. This demonstrates that Rambak tapioca cracker ingredients are not readily available on the market. Consequently, a Decision Support System (DSS) is a system that can provide problem-solving and communication capabilities in semi-structured and unstructured environments. Positive Distance from Average (PDA) and Negative Distance from Average (NDA) are the two distance measures used in the Evaluation Based on the Distance from Average Solution (EDAS) method. The best alternative will be the one with the highest PDA value and the lowest NDA. Based on the User Acceptance Test (UAT) results of the system, which the Wanteyan Home Industry well received, this decision support system yields 5%.