Reviewerly/exHarmony huggingface dataset:
Why pay attention to the data security of digital media platform in the context of big data analysis？

Data security has been a topic of widespread concern.When people surf the Internet, they tend to push the same content on multiple websites.If they view a certain type of video multiple times, they will be frequently pushed similar content, and even their purchases will be "monitored."The development of big data has brought convenience to People's Daily life, but with the penetration of big data into daily life, many behaviors in daily life has also been recorded by big data.Once the information of the database is leaked and used by criminals, irreversible losses will be caused.This paper analyzes and summarizes the phenomenon of digital media platform data leakage, and multi-dimensional data protection and further guarantees data security in the future, which can better help solve the data security problems brought by the development of digital media platforms.
A Study on the Analysis of and Educational Solution for Digital Sex Crimes in Korea

With the development and spread of information and communication technology, our society is experiencing side effects of digital culture while also benefiting from various digital cultures. Representative side effects have spread significantly, including Internet addiction, copyright infringement, personal information infringement, and digital sex crimes. Digital sex crimes are very serious crimes, and we must find their causes and strongly prevent and deal with them at the social level. In this study, the causes and routes of occurrence of digital sex crimes in Korea are analyzed using statistics on digital sex crimes at the national level over the past four years. The statistical analysis results are as follows. First, the main victims of digital sex crimes are women in their teens and twenties, though the number of male victims is steadily increasing. Second, illegal filming is the most common type of digital sex crime, but it is not statistically significant. In other words, various digital sex crimes are occurring evenly. Third, the relationship between the victim and the perpetrator demonstrates the most temporary relationship, and there is no significant correlation between direct and indirect recognition with respect to the route of crime recognition. Finally, deletion by a digital platform is the highest for adult sites compared to other platforms. Based on these analysis results, this study proposes educational countermeasures to digital sex crimes, such as the need for early education to prevent digital sex crimes and the diversification of crime-reporting methods via the establishment of an educational portal site.
The Future of Data Publication in an Open Science World: Perspectives from Researchers, Journal Publishers, and Industry Professionals

As the norms of open science take hold, scholarly communication faces a moment of transition. Scholars must increasingly reckon with whether and where to publish research data. Publishers are grappling with how to integrate research data into their publication workflows and platforms. And professionals working in a range of fields need to know where they can publish and find the most up-to-date, verified public data to inform their decisions. How do researchers decide when and where to publish research data, and what value does open science bring to journal publishers and editors looking to build audiences and impact? How do their audiences seek to use data from and share data with peers? This poster explores data publication from multiple perspectives, including peer-reviewed journals, member publications in health care engineering, and over 200 interviews with big data researchers.
METODE PROFILE MATCHING UNTUK DIAGNOSA GANGGUAN PENCERNAAN PADA ANAK

Profile matching is one of the methods in the Decision Support System, but in this study the profile matching method is used for expert systems, namely for diagnosing digestive disorders in children aged 0 to 7 years, the input data is symptom data while the output is in the form of diagnosis results in the form of a percentage of types of disorders. digestion. The process of profile matching is to determine the weight of the criteria for each symptom, create a knowledge base/ideal profile, determine the weight of the gap, determine the core factor and secondary factor, calculate the gap for each input symptom with the symptoms in the knowledge base, determine the weight of each gap, calculate the core score factor and secondary factor, ranking with a weight of 60% core factor and 40% secondary factor. The results of the study show that the profile matching method can be used to create an expert system for diagnosing digestive disorders in children with an accuracy value of 82%.
Video Stream Intensity Control Technology Based on The Selection of Compression Process Parameters and Block Encoding

This paper substantiates need to coordinate bit intensity video stream and bandwidth of infocommunication systems. The negative impact inconsistency on the quality of video information services is shown. The estimation bit intensity in the process of compressing the video context and transmission in infocommunication systems is considered. A technology is being developed to control intensity video stream based on the choice of parameters for the compression process and block coding It is proposed to take into account features content of the video frame segment and the movement objects in the sequence frames. The influence of such a process on the estimation level bit intensity is investigated. A common algorithm for selecting parameters for the video stream compression process is provided.
Data-driven systems to detect physical weakening from daily routine: A pilot study on elderly over 80 years old

The use of telemonitoring solutions via wearable sensors is believed to play a major role in the prevention and therapy of physical weakening in older adults. Despite the various studies found in the literature, some elements are still not well addressed, such as the study cohort, the experimental protocol, the type of research design, as well as the relevant features in this context. To this end, the objective of this pilot study was to investigate the efficacy of data-driven systems to characterize older individuals over 80 years of age with impaired physical function, during their daily routine and under unsupervised conditions. We propose a fully automated process which extracts a set of heterogeneous time-domain features from 24-hour files of acceleration and barometric data. After being statistically tested, the most discriminant features fed a group of machine learning classifiers to distinguish frail from non-frail subjects, achieving an accuracy up to 93.51%. Our analysis, conducted over 570 days of recordings, shows that a longitudinal study is important while using the proposed features, in order to ensure a highly specific diagnosis. This work may serve as a basis for the paradigm of future monitoring systems.
Electromagnetic Signal Interference Based on Convolutional Autoencoder

At present, electromagnetic interference methods are mainly divided into traditional interference methods and intelligent interference methods. Traditional interference is currently dominated by barrage interference. Intelligent interference solves the shortcomings of barrage interference by sending out fixed-frequency and directional targeted interference waveform. However, most of the current intelligent interference methods require prior information and cannot deal with highly dynamic electromagnetic environments. Therefore, this study introduces an intelligent interference method without prior information. This study is based on a convolutional autoencoder model, which is used to extract high-order features of disturbed communication signal waveform without prior information. By covering some indistinct features and using a deconvolution network to generate similar signals to generate the best interference waveform, this method has an ideal bit error rate. The target signal is reconstructed by a convolutional autoencoder, and the optimal interference waveform is generated in the network by covering the high-order features of the input signal. Finally, the simulation is carried out using the method in this paper. In the BPSK communication system, a bit error rate of 48.7% can be achieved with a low signal-to-noise ratio. In practical engineering, the interference method in this paper can also realize covert jamming, which greatly improves the safety of jammer itself.
The Implications of IoT in the Modern Healthcare Industry post COVID-19

The healthcare industry has recently seen a massive surge in the use of the Internet of Things (IoT) during and after the COVID-19 pandemic. IoT’s main objective is to provide people with the necessities in these uncertain times. During the pandemic, the availability of IoT-based healthcare systems is crucial. Using IoT, healthcare systems are becoming more individualized, allowing for more precise patient diagnosis, treatment, and monitoring. Since the beginning of the epidemic, many researchers have worked tirelessly to find solutions to this global problem, and IoT technology has the potential to revamp the current system completely. Over 6 million people had lost their lives by the time this document was produced due to the ongoing COVID-19 epidemic. Many lives could have been saved. The problem today is that when people are too sick, they cannot call or contact an ambulance or get safely to the hospital. With new technology, perhaps a button or programming into a device, people in need can press a button on their phone or call out into a voice-enabled device to contact the ambulance or other emergency contacts that they might have. The research has found that if significant companies take this seriously, it could be a remarkable idea that could save many lives.
A Correlation Analysis-Based Mobile Core Network KPI Anomaly Detection Method via Ensemble Learning

With the development of new networks, applications in mobile communication networks, such as mobile payment and online classes, have become an indispensable part of people’s lives. The core network is one of the most important components of the mobile communication network, which is not only essential but also complex. If the core network fails, it will cause a substantial economic loss. To ensure the reliability and stability of the mobile core network, operators need to detect abnormalities in Key Performance Indicators (KPI,e.g., average response time). Datasets of KPI are usually unbalanced and have a wide range of features. Therefore, we propose a correlation analysis-based KPI anomaly detection via an ensemble learning frame. This frame first performs data augmentation on the dataset using SMOTE oversampling algorithm and uses the Pearson correlation coefficient method for feature selection, then construct an ensemble learning XGBoost-based anomaly detection method for KPI. Finally, we evaluate our scheme with the confusion matrix. The results show that our scheme obtained a high accuracy and recall rate. The training and testing dataset we collected is a KPI dataset of a Chinese operator for the first three months of 2020. It is worth noting that no relevant studies used this dataset before.
Self-Efficacy in English Listening

Self-efficacy in English listening is an essential point to exist for every English learner. This research aimed to investigate an English listening self-efficacy of a seventh-grade student in Madrasah Tsanawiyah Siratul Jannah Kubu Raya. The researcher applied qualitative study research with a case study approach. Participant observation, documentation collection, and semi-structured interviews were the instruments of the research. The seventh grade student of Madrasah Tsanawiyah Siratul Jannah Kubu Raya is the research subject and chosen by the purposive sampling. The analysis data of the research adapted descriptive analysis, data collection, data reduction, data display, conclusion, or verification. The result of the study indicated that a seventh-grade student of English listening self-efficacy is high. It was proven by the positive characteristics that the subject has; these are consistency, having a support system, and self-confidence. It can be said that the students who have good self-efficacy will act positively toward English listening skills; the students tend to have great effort into the difficult task, they know how to use different strategies to tackle the obstacles, and have good persistence in English listening. Therefore, the English learner must have high self-efficacy to improve, enhance, and endure facing the English listening learning challenge.
Developing Pop-Up Book for Teaching Vocabulary to Young Learners

This research aims to develop a Pop-Up book for teaching vocabulary to young learners, especially kindergarten level students in Darul Uloom Kindergarten. The procedures were adapted from the ADDIE model proposed by Branch and it used three phases, namely Analyze, Design, and Develop. From analyze phase, the researcher has determined the materials and the criteria of the media that should be used and appropriated by the teacher and students in learning vocabulary. The design phase was focused on the criteria of the media for children and the materials used for the media. The development phase concerned the development of the essential parts of the media. According to the assessment rubric by the teacher, the result of the score is 96,875%. It means that the Pop-Up vocabularies book is feasible to apply in teaching vocabulary to young learners
Information System Design of Online Motorcycle and Car Repair Shop Using Dijkstra Method

Now more people are using motorized vehicles. In addition, the use of technology is also increasing, people are increasingly experiencing fast-paced services. However, in the midst of busy society and online services, some services still have to be done manually, one of which is register for a motorcycle or car repair shop. There are still many people difficult to find the right, closest, and comfortable with the needs of their vehicle. With the existing problems, a vehicle service ordering system is needed that can serve the community quickly and practically, which can be accessed by many people, especially in Tangerang City. With a vehicle service ordering system for motorcycles or car repairshop, people can easily find a repair shop that is the closest to their location and can order without having to wait in long queues. The design of the system for the closest repair shop locations uses the Dijkstra method. The workings of Dijkstra's Algorithm is to create a path to one optimal node at each step. Dijkstra's algorithm has the property to find the point whose distance from the starting point is the shortest. To find out whether the system has been accepted and has met the requirements, the system is tested using the User Acceptance Test (UAT) method, and from the test results, 85.1% of users are satisfied with the system.
From Social Media to Metaverse: Evaluation of Meta Avatars Store in The Context of Avatars, Self-Presentation and Luxury Brand

Meta Corporation announced in June 2022 that it was launching the Meta Avatars Store for users who want to adorn their avatars with luxury brands such as Balenciaga, Prada, and Thom Browne, as well as a selection of free outfits available. In this context, the store's function is to allow users to shop for their avatars in social media and Metaverse environments. In this context, the research focuses on discussing the relationship between avatars, selfpresentation, and luxury brands through the example of the Meta Avatars Store. The purpose of the research, which examines the Meta Avatars Store with the case study method, is to examine the relationship between self-presentation and the elements highlighted to direct the users to luxury consumption in the promotional activities of this virtual store. According to the research findings, it is seen that making purchases for their avatars is meaningful to find their "authentic self” and “the best version of themselves” and being “unique” to make the relationships of the users more meaningful with their friends, family, or business partners.
Pembuatan Aplikasi Data Mining Untuk Memperediksi Masa Studi Mahasiswa Menggunakan Algoritma Naive Bayes

Data mining is a series of processes to obtain additional value information that is not known manually from a database. Data mining also manages experience or even mistakes in the past to improve the quality of the analysis model, one of which is the learning ability of data mining techniques, namely classification. Class is a learning task that is a new object into one of the class labels or categories on the old object that has been previously defined. This classification uses one method of data mining algorithm that is Naive Bayes.Naive Bayes algorithm works based on a certain distance between two objects by setting the value of k. The value of k is a parameter to determine the distance between the new object to the old object.By using the data mining technique, the university can obtain student academic data, namely the Achievement Index (IP) to predict the student's study period.In this data mining application consists of data testing and data training with NIM input.PHP and the database used is MySQL.The results of this data mining application this system can predict the results of the classification of student study period based on GPA 4 first semester, the average value of high school time, and grades in high school.
Utilization of Telegram application As an Information Media Face Mask Detection Result

To know the results of the face mask detection system, one must be near a computer. This problem makes it difficult to reprimand and provide face masks to violators. One of the ways to prevent the spread of the virus is to wear a mask. This study focuses on making a face mask detection system connected to a cellular device. This study aims to make obtaining information more effortless, and monitoring officers can find out from a smartphone. As a medium of communication, we use the telegram application. Smartphone users widely use this application compared to existing messaging media applications. This study uses the YoloV4 algorithm to detect face mask and JSON to send information to the telegram application. The test consists of two stages, the first stage is to determine the accuracy of the face mask detection system and the second stage is to determine the average time required until the information is sent. The two tests performed obtained 97.57% and 0.255 seconds, respectively. The test results show that the system created can solve the existing problems. The researcher can do further research by increasing the number of datasets to increase the accuracy of face mask detection.Keywords: Face Mask Detection, JSON, Telegram Application, YoloV4 Algorithm.
Implementation of JSON Parsing in Agricultural Productive Learning Applications

The learning process at SMK Negeri 1 Mootilango is still conventional, in other words that the teaching and learning process between students and teachers can only be carried out with the condition that there are meetings between students and teachers in the classroom. If a meeting between students and teachers does not occur or the teacher concerned is not present and learning time is limited by the school, then the learning process will automatically be hampered. One of the teaching methods that is currently developing is mobile learning. Mobile Learning can assist teachers in distributing their teaching materials without having to be in class by using the internet, this can maximize learning time in limited classes. In making software using the Waterfall method. The data collection method used in this research is literature study, observation and interviews or interviews with the topic to be taken. This application is designed using Java programming language software, namely Android Studio, for PHP and HTML programming languages using Sublime Lite software, and for data storage using MySQL, as well as tools for modeling using UML (Unified Modeling Language). Based on the results of the Whitebox test on one of the processes in this system, namely on the evaluation menu with balanced Cyclometic Complexity (CC) = 4 results, this system is stated to be able to run well. While the results of testing the Blackbox system can run as expected.
A Study on the Interaction between Chinese as a Foreign Language and the Construction of Chinese Culture on Campus

In the course of Chinese as a foreign language, the students' ability to understand Chinese intuitively is relatively poor.Therefore, it is necessary to construct an interactive system between teaching and cultural activities on campus, to provide cultural environment and practical space support for students' application and understanding of Chinese.Based on the current situation of Chinese Chinese as a foreign language, this study systematically analyzes the construction of the deep interaction between Chinese Chinese as a foreign language and Chinese culture on campus, taking teaching and Chinese culture on campus as two main lines, to provide an effective reference for optimizing the Chinese as a foreign language effect.
Online Learning Service Application Using Flutter Framework and Laravel

Online learning is a concept of learning that is carried out online or through the internet network. Very advanced technology in the modern era and globalization makes various activities carried out efficiently and can be done using only gadgets. Technological developments in the field of education with the use of e-learning in learning activities in schools, colleges, courses and even online communities have started to use concepts like this.&#x0D; This study uses Flutter to create applications for users and consultants in conducting online consultations on android devices. The author uses a collection of widgets that have been provided by flutter to create components in the user interface such as buttons, input text, text, icons, and others.&#x0D; In this study, we use the Laravel framework to create an admin dashboard and provide a Restful API for android applications to handle database management on the server. The author uses Laravel's features to build a fullstack application that handles requests, routing, controllers, services, models, and views.
Derivational Suffixes in Novel â€œThe One And Only Ivanâ€ Written by Katherine Applegate

A novel written by Katherine Applegate entitled The One and Only Ivan contains so many derivational suffixes. Knowing suffixes could help the English learners enrich their vocabulary knowledge significantly. For the reason above, this research is aimed at. This research uses qualitative method as the research approach that it could help much in finding out the meaning of derivational suffixes and the functions of each derivational suffix. The data of this study are in the form of words which contain English suffixes. The data is collected by downloading The One and Only Ivan novel from internet, and by reading the entire source of the data. To analyze the data, the writers use Plag theory (2002) to sort the suffixes into their categories. After that, the writers classify, and analyze the data as the procedures of data analysis. Finally, the writers take the conclusion. In this novel, there are four types of suffixes. The suffixes found are nominal suffix, adverbial suffix, adjectival suffix, and verbal suffix. The suffixes found in this novel are -ness, -ion, -ation, -ful, -er, -ance, -ence, -ment, -or, -ity, -ty, -ly, -y, -able, -ic, -ive, -en, -ful, -en. All of the suffixes may form other words class from the root word or change the meaning of the words, though not all of them are analyzed completely because of the space limitation.