Reviewerly/exHarmony huggingface dataset:
Clean and Healthy Living Behavior Education to improve the knowledge of Elementary School Students

&#x0D; Clean and healthy living behavior is the main foundation for maintaining individual health and preventing the spread of disease. Education about clean and healthy living behaviors can be done in various ways, such as through counseling, campaigns, the development of educational materials, collaboration with health centers, training, the active role of schools, the use of social media, exemplary examples, and measurement and evaluation. Educational materials that are arranged in an attractive and easy-to-understand manner are the main instruments in this effort. Collaboration with medical personnel, involving health centers, and the active role of schools are recognized as important supporting factors. The use of social media is also integrated as an effective means of reaching a wider audience. By combining these approaches, it is hoped that people can better understand and adopt clean and healthy living behaviors in their daily lives. Evaluation of the effectiveness of educational programs needs to be done to ensure their success and impact on community knowledge and behavior.&#x0D;
RANCANG BANGUN APLIKASI E-VOTING DI SMK NURUL HUDA PETIR BERBASIS WEB DENGAN SENSOR RADIO FREQUENCY IDENTIFICATION (RFID)

Information technology is developing rapidly in all aspects of life and until now its application has created conditions conducive to community work. One of the activities that can now take advantage of information technology is e-voting in the election of the chairman and deputy chairman of the organization. SMK Nurul Huda Petir has more than 200 students. The democratic process of selecting the head of this school organization is still used manually. There will be many obstacles, namely data security risks, which will reduce learning time, and require large implementation costs. The problems that arose created an information system called e-voting. E-voting is a system for creating ballots, casting, counting, and displaying ballot results, and generating and maintaining audit trails electronically and digitally. This research aims to speed up, improve security, and reduce implementation costs in the process of election activities at Nurul Huda Petir Vocational School. The application development process-voting uses the method Waterfall with Unified Modelling Language (UML) for system design. System e-voting its build-based web with Framework Codeigniter and added an RFID sensor (Radio Frequency Identification). The results of this research found that the application of e-voting can reduce 80% of implementation costs, improve voice data security, and speed up the process of collecting and calculating voice data.
KLASIFIKASI KEMATANGAN BUAH ALPUKAT MENTEGA BERDASARKAN FITUR WARNA MENGGUNAKAN SUPPORT VECTOR MACHINE

The ripeness level of the avocado greatly affects the shelf life of the fruit and also determines the taste of the fruit. Determining the proper ripeness of a fruit will play an important role in increasing the nutritional value and ripeness of avocado affects the quality of avocado oil. Classification of fruit maturity manually has many limitations because it is influenced by human subjectivity so that the application of digital image processing needs to be used.This study aims to classify avocado fruit ripeness which is divided into three categories, namely Unripe, Ripe, and Rotten. This research is intended to facilitate the classification of ripeness in fruit through its color. This study used avocado fruit as an experimental material which was carried out using the SVM (Support Vector Machine) method. The colors of the various avocados and in different positions and conditions of light contrast are used as data to classify the types of avocados. Data collection was taken from the selected Keagle Dataset of 150 data. The data is grouped into two data sets, namely dataset-1 (120 training data and 30 test data) and dataset-2 (90 training data and 60 test data). The image will be converted to grayscale to facilitate the classification process and look for HSV (Hue, Saturation, Value) and RGB (Red, Green, Blue) values to classify the fruit. The results from dataset-1 has an accuracy rate of 86%, 90% precision, and 86% Recall, while dataset-2 has an accuracy rate of 85%, 84% precision, and 85% Recall.
SISTEM INFORMASI PENGELOLAAN TOUR DAN TRAVEL BERBASIS WEB APP PADA CV. KENKEN AGENCY

CV. Kenken is a service company in the city of Serang in managing tour and travel reservations still using the manual system. There are many problems including management of tour booking data and WEB-Based Travel On CV. Kenken Agency, still using a ledger, boking data collection and departure schedule is not well recorded, difficulties in tracking documents sent. The method used is the waterfall method, the design tool uses the UML flow map. While the implementation uses the PHP programming language and MySQL data base. With the web-based tour and travel information system on CV. Kenken Agency, is expected to overcome the problems that exist in the CV. Kenken Agency. Therefore, the recording of documents is neat, the departure schedule is well organized, the latest prices, boking and schedules are well recorded.
APPLICATION OF AUGMENTED REALITY IN MOBILE BASED HIJAIYAH LETTER RECOGNITION APPLICATIONS USING MULTIMEDIA DEVELOPMENT METHODS LIFE CYCLE

Islamic religious education is an important aspect of Muslim life, and learning Arabic and Hijaiyah letters is an integral part of Islamic education. The use of augmented reality (AR) technology in educational setting is rapidly increasing. This study aims to apply the AR concepts to the creation of mobile Hijaiyah letters using Multimedia Development Life Cycle (MDLC) methodology. The application of AR in this application allows users to interactively learn each hijaiyah letter. Through a mobile device camera, users can see hijaiyah letters that appear virtually on the device screen. The development of this application is based on the needs of users in understanding hijaiyah letters in a more attractive and interactive way. Thus, this application is expected to facilitate users, especially children, to learn hijaiyah letters more effectively.
An Evaluation of Selected Newspapers' Reporting on Hate Speeches during the 2015 Presidential Election in Nigeria

Election stakeholders in Nigeria continue to express worry over the growing trend of hate speech, particularly during the 2015 general elections. The influx of advertisements, political innuendos, and propaganda messages in some chosen individuals who were in the forefront of delivering hate speeches in Nigeria prior to the 2015 general elections increased the socio-political climate. With regard to the 2015 Nigerian presidential election, this study aims to investigate the effects of hate speech from a few media reports. Secondary data are heavily cited in this study such as textbooks, official reports and publications, Internet resources, journals, among others. As for analysing the various data gathered, content analysis was performed. This study found that hate speech coming from particular media reports contributed to electoral-related violence and mistrust among Nigerians. Consequently, the electoral process' credibility is affected. This study recommended, among other things, that election stakeholders, in particular INEC, CSOs, Elections Observers and Monitors, should also keep an eye on the media, particularly native language radio stations that utilise hate speech to fan the ember of ethnic and religious separation.
RANCANG BANGUN PERANGKAT RUMAH CERDAS PENCEGAHAN KEBAKARAN BERBASIS IOT

Various technologies, including the Internet of Things (IoT), aim to streamline system functionalities. IoT finds application in diverse sectors, notably Smart Homes, enhancing household tasks and bolstering security via internet-connected devices. This study investigates IoT's utilization in detecting different types of smoke—combustion smoke from various sources like cigarettes, paper, and gas. The trials involved testing the MQ2 sensor's efficacy in detecting smoke at varying distances. In testing this device the author conducted several trials on several types of combustion smoke, cigarette smoke, paper combustion smoke and gas. In these trials, the authors obtained several tests of distance differences in detecting smoke using the MQ2 sensor. The devices made in this study have been adjusted to the purpose of the study. The important conclusion of this study is the need to understand the specifications of the device at the beginning of the study, so as not to use 2 (two) microcontrollers
A Novel Method for Hill Cipher Encryption and Decryption Using Gaussian Integers Implemented in Banking Systems

Cryptographic tools like Hill's encryption algorithm protect digital data. In this work, we present a novel Hill cipher security method that utilizes Gaussian integers from number theory. Using these intriguing mathematical entities to disguise plaintext values dramatically boosts assault resistance and duration. This research includes a three-pass protocol for encryption and decryption without key exchange, ensuring a safe, efficient, and dependable solution. Pandas is used for efficient data processing, and Numpy for computational tasks, notably matrices. Hill cipher-based encryption and decryption can be utilized in real life. It also demonstrates how to save Pandas DataFrame data to Excel. This strategy assures progress in cryptography. Uniquely designed for banking, it emphasizes its applicability and possible influence on present financial systems.
Does digital inclusive finance promote regional green inclusive growth?

Based on the construction of theoretical foundations, this study uses panel data from 30 provinces in China from 2011 to 2021, and employs regression analysis and mediation mechanism tests to explore the relationship between digital inclusive finance and regional green inclusive growth. The findings indicate that digital inclusive finance significantly enhances the level of regional green inclusive growth, and the results remain significant after addressing endogeneity issues and conducting robustness tests. The mechanism test reveals that digital inclusive finance effectively promotes regional green inclusive growth by improving the efficiency of financial services in supporting the real economy.
Integration of ICT for Research and Administrative Work by Teacher Educators in Secondary Stage Teacher Education Institutes

The study explored the best practices by Teacher Educators in integrating ICT into Research and Administrative work. Understanding teacher educators’ use of ICT and its influence is central to determining technology’s role and effectiveness during their career. Thus, teacher educators should be assisted and encouraged to develop positive attitudes in learning and to apply ICT in their Profession. The findings showed that both young and experienced teacher educators showed readiness to use ICT in their career.
Monocular depth estimation for 2D mapping of simulated environments

This article addresses the problem of constructing maps for 2D simulated environments. An algorithm based on monocular depth estimation is proposed achieving comparable accuracy to methods utilizing expensive sensors such as RGBD cameras and LIDARs. To solve the problem, we employ a multi-stage approach. First, a neural network predicts a relative disparity map from an RGB flow provided by RGBD camera. Using depth measurements from the same camera, two parameters are estimated that connect the relative and absolute displacement maps in the form of a linear regression relation. Based on a simpler RGB camera, by applying a neural network and estimates of scaling parameters, an estimate of the absolute displacement map is formed, which allows to obtain an estimate of the depth map. Thus, a virtual scanner has been designed providing Cartographer SLAM with depth information for environment mapping. The proposed algorithm was evaluated on a ROS 2.0 simulation of a simple mobile robot. It achieves faster depth prediction compared to other depth estimation algorithms. Furthermore, maps generated by our approach demonstrated a high overlap ratio with those obtained using an ideal RGBD camera. The proposed algorithm can find applicability in crucial tasks for mobile robots, like obstacle avoidance, and path planning. Moreover, it can be used to generate accurate cost maps, enhancing safety and adaptability in mobile robot navigation.
Solving the problem of preliminary partitioning of heterogeneous data into classes in conditions of limited volume

In the context of the formation of heterogeneous data that differ significantly in nature, even of a small volume, it becomes necessary to analyze them for decision-making. This is typical for many high-tech industrial fields of human activity. The problem can be solved by bringing heterogeneous data to a single view and then dividing it into clusters. Instead of searching for a solution for each data element, it is proposed to use the division of the entire set of normalized data into clusters, and thereby simplify the process of isolating the cluster and making a decision on it. The essence of the proposed solution is the automatic grouping of objects with similar data into clusters. This allows you to reduce the amount of analyzed information by combining a lot of data and perform mathematical operations already for the cluster. When splitting, it is proposed to use the theory of fuzzy logic. The possibility of such an approach is due to the fact that different objects always have several characteristics by which they can be combined. These signs are often not obvious and are poorly formalized. A hierarchical modification of the AFC fuzzy clustering method based on the operation (max- min) of the fuzzy similarity ratio is proposed. The basic concepts and definitions of the proposed method of automatic partitioning of a set of input data, a step-by-step scheme of the corresponding cluster procedure are considered. The efficiency of the proposed method is demonstrated by the example of solving the problem of forming a traffic flow. A numerical experiment has shown that the developed algorithm allows you to automatically analyze heterogeneous data and stably divide them into classes. The application of the proposed modification allows for the preliminary partitioning of data into clusters and allows reducing the volume of analyzed data in the future. There is no need to consider the objects in each case separately.
An improved performance of RetinaNet model for hand-gun detection in custom dataset and real time surveillance video

The prevalence of armed robberies has become a significant concern in today’s world, necessitating the development of effective detection systems. While various detection devices exist in the market, they do not possess the capability to automatically detect and alarm the presence of guns during robbery activities. In order to address this issue, a deep learning-based approach using gun detection using RetinaNet model is proposed. The objective is to accurately detect guns and subsequently alert either the police station or the bank owner. RetinaNet, the core of the system, comprises three main components: the Residual Neural Network (ResNet), the Feature Pyramid Network (FPN), and the Fully Convolutional Networks (FCN). These components work together to enable real-time detection of guns without the need for human intervention. Proposed implementation uses a custom robbery detection dataset that consists of gun, no-gun and robbery activity classes. By evaluating the performance of the proposed model on our custom dataset, it is evident that the ResNet50 backbone architecture yields outperforms for the accuracy in robbery detection that reached in 0.92 of Mean Average Precision (mAP). The model effectiveness lies in its ability to accurately identify the presence of guns during robbery activities.
Computational prediction in the problem of stereo image identification

The paper examines the issues of increasing the efficiency and reliability of stereo image identification through computational prediction of the position and size of the uncertainty zone in which the desired correspondence point is known to be located. A control point is selected on one of the stereo images, for which it is necessary to find a correspondence point on the second stereo image. Based on the known parameters of the stereoscopic television system and the coordinates of the control point, using the mathematical apparatus proposed in the work, the coordinates of the boundaries of the uncertainty zone on the second stereo image are calculated. The second point of correspondence is found by the search procedure by comparing identical small areas with centers in the control point on the first stereo image and in the points of the uncertainty zone on the second; the comparison is made according to the criterion of minimum quadratic mismatch of intensities. The necessary a priori information for implementing the method is the maximum heights of the relief displayed on stereo images. The ratios of linear dimensions on a flat relief and on an image formed according to the principle of central projection were obtained. Relationships have been obtained that make it possible to obtain, by calculation, the coordinates of the correspondence points and the stereoscopic mismatch for stereo images of a flat relief. For stereo images of a volumetric relief, calculation formulas are obtained for determining the boundaries of the zone of uncertainty in the second stereo image within which the search for the point of correspondence is carried out. The correctness and performance of the obtained relationships are confirmed by computer modeling. Limiting the size of the search area by means of calculated prediction of the uncertainty zone makes it possible to reduce the computational and time costs of the search procedure. Due to this, the efficiency of identifying stereo image points increases and the likelihood of false identification decreases.
A method of storing vector data in compressed form using clustering

The development of the machine learning algorithms for information search in recent years made it possible to represent text and multimodal documents in the form of vectors. These vector representations (embeddings) preserve the semantic content of documents and allow the search to be performed as the calculation of distance between vectors. Compressing embeddings can reduce the amount of memory they occupy and improve computational efficiency. The article discusses existing methods for compressing vector representations without loss of accuracy and with loss of accuracy. A method is proposed to reduce error by clustering vector representations using lossy compression. The essence of the method is in performing the preliminary clustering of vector representations, saving the centers of each cluster, and saving the coordinate value of each vector representation relative to the center of its cluster. Then, the centers of each cluster are compressed without loss of accuracy, and the resulting shifted vector representations are compressed with loss of accuracy. To restore the original vector representations, the coordinates of the center of the corresponding cluster are added to the coordinates of the displaced representation. The proposed method was tested on the fashion-mnist-784-euclidean and NYT-256-angular datasets. A comparison has been made of compressed vector representations with loss of accuracy by reducing the bit depth with vector representations compressed using the proposed method. With a slight (around 10 %) increase in the size of the compressed data, the absolute value of the error from loss of accuracy decreased by four and two times, respectively, for the tested sets. The developed method can be applied in tasks where it is necessary to store and process vector representations of multimodal documents, for example, in the development of search engines.
Profile of ICT Literacy in Science Learning Assisted by Google-Sites for Junior High Students

Education in the era of revolution must utilize the application of ICT in science learning which can refer to 21st- century skills is ICT literacy. The purpose of this study aims to see the effect of Google sites-based science learning on the profile of ICT literacy of junior high school students. The method used is quantitative research by giving post-tests to two different classes that have implemented the learning The two classes consisted of the experiment class and the control class. The sampling technique used was cluster random sampling. The results obtained were then analyzed and discussed descriptively quantitative. The results show that the application of Google sites-based learning can affect the achievement of students' ICT literacy profile by obtaining an average score of high categories in the experiment class and medium category in the control class. Based result of study, there is a significant influence of the use of Google-sited based in science learning on ICT literacy in junior high school students
QR Code Use and Identification Problems in Tourism

The integration of technology with tourism increases its efficiency and improves the tourist experience, especially through QR codes and NFC technologies, which are already widely used. The number of research related to digitization and the sustainability of tourism is increasing, and the focus is shifting towards ICT, AR and VR. Mobile services like QR codes are crucial in tourism, improving service availability and user experience. The article analyzes the importance of QR codes and image processing in logistics and tourism. The focus is on the technological foundations, recognition, and decoding methods of QR codes, highlighting the role of artificial intelligence. The article discusses in detail the application of QR codes in tourism, along with technological challenges and development opportunities. It also presents future research directions and the potential effects of QR codes on tourism.&#x0D;
A Systematic Literature Survey on Electronic Health Record System Using Blockchain

Abstract-Compared with traditional paper-based medical records , Electronic health records (EHRs) are widely used because of their efficiency, secu- rity, and reducing data redundancy.The Electronic Health Record (EHR) system is a major technolog- ical development in healthcare that has completely changed how patient data is collected, stored, and used. Through the use of cutting-edge digital tech- nologies, the EHR system offers a safe, centralized location for all patient data. Healthcare personnel may easily access, edit, and share patient informa- tion thanks to its user-friendly interfaces, which helps them make more informed clinical decisions and provide better treatment.The system developed using the Ethereum network using Ganache. The measured approach is to store patients data and execute functions in a decentralized system using blockchain smart contracts. To further protect pa- tient privacy and adhere to privacy laws, the system places a high priority on data security and uses strong authentication and encryption mechanisms. Keywords-Blockchain, Decentralized, Ethereum, Healthcare, Smartcontacts,