Reviewerly/exHarmony huggingface dataset:
Machine Learning Service Recommendation Based on Accuracy Related QoS Attributes

&lt;p&gt;Machine Learning (ML) is a topic of interest in computer science. Amazon AWS, Google Cloud and Microsoft Azure are examples of cloud platforms that provide ML services. Analysts can easily analyze data using online ML services, and most of the model processing is done using cloud services to provide fast and reliable results. Many of these services offer similar functionalities, and the challenge is how to select the best service for the data. Traditional approaches for service-selection depend only on general understanding of the service functionality. A better way is to consider both functional and non-functional requirements. Functional requirements determine overall behaviour of a service. Non-functional requirements establish how relevant a service is to the user’s query and refer to the Quality of Service (QoS) attribute. QoS- based service-selection has been studied in the service computing community for some time. However, characteristics of the input dataset are not usually considered in the selection process even though they might affect the QoS values of the service. In this dissertation, we investigate the impact of adding dataset features and other side information on the performance of QoS prediction and service recommendation. We focus on ML services since their QoS values are potentially highly dependent on the dataset.&lt;/p&gt; &lt;p&gt;We propose two approaches for ML service recommendation and compare their performances. The first approach uses factorization for web service recommendation. We identify latent features of the datasets and the services and then recommend services by exploiting these latent variables. The second approach uses neural networks to identify latent features. We also integrate two sets of side information (dataset and service) in both approaches, and study the effect of these added features. In the experiment, we test our system using the real QoS data of 24 classification models running on 390 datasets downloaded from OpenML. In both implementations, models with side information outperform the basic model. To guarantee the best performance for our model, adding side information is necessary, which increases the predictive accuracy by 5% to 25%. Thus, we recommend integrating the side information in recommender systems, specifically including dataset features when recommending ML services. &lt;/p&gt;
Integrated and Deep Learning Based Social Surveillance System: A Novel Approach

In industry and research, big data applications are gaining a lot of traction and space. Surveillance videos contribute significantly to big unlabelled data. The aim of visual surveillance is to understand and determine object behaviour. It includes static and moving object detection, as well as video tracking to comprehend scene events. Object detection algorithms may be used to identify items in any video scene. Any video surveillance system faces a significant challenge in detecting moving objects and differentiating between objects with the same shapes or features. The primary goal of this work is to provide an integrated framework for a quick overview of video analysis utilizing deep learning algorithms to detect suspicious activity. In greater applications, the detection method is utilized to determine the region where items are available and the form of objects in each frame. This video analysis also aids in the attainment of security. Security may be characterized in a variety of ways, such as identifying theft or violation of covid protocols. The obtained results are encouraging and superior to existing solutions with 97% accuracy.
Improving critical thinking skills of high school students through the implementation of mobile-based game applications

This study aimed to identify the effectiveness of Android-based mobile games in helping high school students improve their critical thinking skills. A quantitative research method was used through a quasi-experimental design with pre-test and post-test in both control and experimental classes. Data collection techniques comprised test techniques and the use of tools to obtain data about the critical thinking skills of high school students. The data was then analyzed quantitatively by t-test and n-gain scores. A total of 58 high school students studying the sociology subject participated in this study. The findings show that the use of mobile game-based learning products has a major impact on improving students' critical thinking skills. In addition, based on the findings of this study, it was evident that mobile game-based learning applied to sociology learning was included in the "efficient" category in influencing and enhancing students' critical thinking skills in an effort to build 21st century competence in high school students. Therefore, this research implied that teachers can start utilizing mobile game-based learning products as a medium for learning sociology in high school.
VULNERABILITIES OF MOBILE APPLICATIONS USED IN DISTANCE LEARNING ENVIRONMENT

E-Learning means learning through electronic resources.This is usually done on the Internet, where students can access materials online at any time.Nowadays, more and more students are enrolling in online courses to learn, due to the comfort of their homes and the desire to learn at their own pace, turning to various platforms that provide educational materials.Thus, mobile learning platforms, used in the university environment, bring benefits to students, although they cannot fully replace traditional education.The Internet presents many opportunities and beneficial ways of learning.In this material, we present the concept of distance education and how it is used.We present different software tools intended for mobile devices used in the education environment, and especially in the distance education process, and we analyze the vulnerabilities that have appeared for these mobile applications from the point of view of the data managed by these applications.The vulnerabilities are searched in CVE MITRE -Common Vulnerabilities and Exposures.For each mobile application, we centralize the vulnerabilities identified and we will create a statistical analysis using Common Vulnerability Scoring System -CVSS.In this way, we will create a ranking of the most vulnerable mobile applications used in distance learning.We believe that such an analysis is important for a growing technology because this technology development must be linked to certain security standards.Existing vulnerabilities already identified for the solutions used must be provided and analyzed so that there is no danger that these vulnerabilities are present in the solutions used.
Virtual Currencies and Intrapreneurial Coordination

Managers of conglomerates or companies with multiple business units are, like central planners in socialist countries, unable to perform economic calculation. These units exchange goods and services internally based on transfer prices, not market prices, and it is hard to ascertain the value contributed by management, which is often hired and rewarded based on political considerations. Innovation is also often unwelcome, as it may challenge privileges of executive management. Until 2016, conglomerates lacked the technology to benefit from economic calculation. In this paper, I propose that a blockchain platform supporting an internal virtual currency enables economic calculation inside conglomerates, unlocking productivity and supporting intrapreneurship.
A Novel Two-Factor Authentication Scheme for Increased Security in Accessing the Moodle E-Learning Platform

Moodle is a platform designed for universal learning to support pedagogical interactions and educational activities. The information technology (IT) administrator uses standard authentication methods for students logging into the Moodle platform. The need for two-factor authentication has grown as institutions, governments, and individuals realize that passwords are not secure enough to protect user accounts in their current technical format. The classic connection methods have vulnerabilities, and account passwords are easy to crack. Analyzing these aspects, the goal is to create a new safe and reliable alternative to the traditional authentication methods in e-learning platforms. The proposed solution introduces a new authentication factor using digital certificates stored on physical devices or the cloud to address the evolving authentication and security challenges effectively. The absence of this authentication within the Moodle ecosystem has imparted a sense of urgency for its implementation. With the innovative authentication scheme, the users have gained confidence, are satisfied with the new solution, and have not reported security breaches. The result is increased security, data protection, and better account management.
Development of Multicultural Education: Tasks, Tools and Project Solutions

The methodological model of multicultural education in the country has been developed and substantiated in the article, which is able to ensure timely identification of current problems of multicultural education and innovative ideas for their solution, planning, and implementation of effective measures for the development of multicultural education in accordance with existing objective needs and opportunities. The study was carried out due to the fact that global factors of population formation create a multicultural environment, which forms the conditions of multicultural education. The study suggests that achieving the goals of multicultural education should be through a synthesis of educational principles, methodology, tools of system-targeted approach to management and activity approach to building personality-oriented education, and ensuring the integration of management resources at regional, municipal, and educational institutions.
Android-Based Application for Real-Time Indonesian Sign Language Recognition Using Convolutional Neural Network

Individuals with hearing or speech impairments face challenges in communicating with others, requiring special techniques to express their thoughts and feelings. Sign language is an alternative way to communicate using a specific pattern of hand gestures to deliver messages instead of verbal speaking (oral communication). Unfortunately, most people do not know how to use and read sign language. Because of its complexity and many types of sign language worldwide, only well-trained personnel could use it as a communication medium. This research provides a solution in the form of a machine-learning Android-based application designed to recognize sign language captured by a smartphone camera and translate it into Latin characters. The recognition accommodates Convolutional Neural Network (CNN), one of the popular deep learning algorithms. This application recognizes 26 characters of Indonesian Sign Language (Bahasa Isyarat Indonesia/BISINDO) alphabets using MobileNetV3 architecture. To build the data model, dataset images were collected from 5 different models demonstrating 26 BISINDO characters in various lighting, background, and hand gesture position. These dataset images were also generated using image augmentation process to achieve the randomness by adjusting the image rotation, noise, and brightness. Based on the testing result using 6,240 dataset images, the application has 75.38% accuracy in recognizing Indonesian Sign Language alphabets.
Using the Podcast Contents to Help EFL Students in Improving Their Grammar and Pronunciation

The study aims to determine how the teacher uses podcast resources to improve the students' grammar and pronunciation learning. Many EFL students struggle to use good grammar and practice pronunciation. By addressing their weaknesses, they needed to hone their public speaking abilities. To accomplish this, twelve college students joined a treatment program that used podcasts to address this problem. The teacher created a social media group to facilitate the teaching and learning process and to improve the learning of the online course materials. After finishing it, he instructed students on how to study grammar while bilingual. The students finished the lecture and the assignment in both languages. The teacher posted a URL on a forum to help the students more naturally understand grammar usage. The students click on, and a podcast page appears on their screen. To hear the speaker's voice, they push the play button. They read the transcript as they listened to the voice. They concentrated on getting the transcript done. The corresponding grammatical content was looked for in each line of the text. The words and phrases related to the grammar being studied were highlighted. they visualized uploading their work. The instructor then requested that the students read the transcript aloud for recording and upload. The teacher then evaluated all of the uploaded work in order to offer comments. The information was acquired by keeping an eye on the teaching-learning process. The conclusion was then reached after qualitative analysis. According to the study, podcasts can improve pronunciation and structure learning. The teachers can use the findings to teach connected disciplines. The other researchers can also complete the further related work.
Exploring Blockchain-Based Applications for Digital Copyright Protection

This article provides a comprehensive review of the current landscape of digital copyright protection and the challenges it faces, particularly in the areas of registration and rights confirmation, authorized transactions, and monitoring and enforcement.It also explores the potential of blockchain technology as a solution to these challenges and analyzes the perspectives and strategies proposed by scholars.The review identifies three main research dimensions: a holistic approach to digital copyright protection, specific field perspectives, and technological advancements.Furthermore, the review highlights the importance of interdisciplinary collaboration and comprehensive exploration to further advance digital copyright protection.The findings emphasize the need to strengthen user education on copyright protection, balance the interests of creators and users, and continue evaluating the feasibility and effectiveness of blockchain technology in practical digital copyright protection scenarios.
ANALISIS MANFAAT PENGIMPLEMENTASIAN BASIS DATA DI DALAM LINGKUNGAN SEKOLAH

The aim of this study to provide the importance of the benefits of databases in schools today, because in this sophisticated era, database needs are needed to make it easier to make reports, retrieve and store data that was originally made manually which is time consuming and prone to data errors. . With the application of a database system, everything can be done easily and quickly, and the resulting data will be accurate. The research method used is a qualitative method by observing and recording reality through observation, interviews, and documentation. The results of the study show that the benefits of using databases in schools today are the quality of the data and information accessed according to what is input, and the most important benefit is classifying data and information so that it is easier for teachers to understand, anticipating the occurrence of data similarities or data instability. Helping the process of saving, accessing, editing, and deleting data, Protecting databases for schools to shorten processing time and get significant results
PENERAPAN DATA WAREHOUSE PADA PT. TELKOM YOGYAKARTA

Data warehouse (Warehouse data) is expected to empower mining information to recognize the design in the information, for example when planning procedures that can build agreement and benefit the organization. which method used in Internetsearching research or are called search based strategies online (web), is an information retrieval system through web-based media such as the internet or other network media that provide online facilities. Objective This research is to make it easier for the officers of PT. Telkom Yogyakarta to collect information about accessible products or materials. Result of research the recording and search procedures used by warehouse staff were not effective because it is still being carried out physically, and when the stock taking is carried out, the material is available are often not the same as the results obtained. So with them use a data warehouse system to collect all data carefully and accurate.
ANALISIS SISTEM INFORMASI AKUNTANSI SIKLUS PENGGAJIAN PADA USAHA MEBEL AYU

The purpose of this study was to analyze the accounting information system of the payroll cycle process in the Ayu Furniture industry. Data collected by interview, observation and documentation techniques. Observation and documentation techniques are directly carried out at the research location in the Ayu Furniture industry. Analysis carried out by the method (PIECES) Performance, Information, Economy, Control, and Efficiency. The research approach uses descriptive qualitative, namely by describing the payroll accounting information system that exists in the company which includes activities in the payroll system, related functions, documents used, accounting records used, network procedures that make up the system and internal control system. The results showed that the payroll process in the Ayu Furniture industry uses a manual system, this can lead to potential fraud or negligence at the stage of attendance and submission of employee salaries, although the system has been running smoothly and effectively in terms of service, performance, information and economy.
Implementation of Simple and Efficient Picture Caption Generator

Image captioning or picture captioning has become one of the most widely used technologies in applications that generate and provide captions for specific photographs. All these things are done with the help of deep neural networks. It identifies the specific objects in an image and their attributes and relationships. The purpose of this research is to find different things in a photograph, figure out their relationships, and write captions. The proposed system is implemented on dataset Flickr8k along with python. The input images are pre-processed and then features from images are extracted using CNN. To translate the features and objects extracted by CNN to a natural sentence in English LSTM is utilized in the implementation. Different types of images are tested with the proposed system. The results are presented with the generated image captions. The results presented shows the accuracy of the system. The presented method has potentials for such applications where image captioning is essential.
Review on E-Health Privacy and Security through ECC, SHA-256, and Multi-Authority Approaches

The rapid digitization of healthcare services has led to the proliferation of electronic health (E-Health) systems, providing convenience and improved patient care. However, the increasing use of E-Health platforms also raises concerns about the privacy and security of sensitive medical information. This review paper explores the challenges surrounding E-Health privacy and security and presents a comprehensive approach to addressing these concerns through the implementation of Elliptic Curve Cryptography (ECC), Secure Hash Algorithm 256 (SHA-256), and multi-authority schemes. The synergistic application of these cryptographic techniques not only fortifies the protection of patient data but also establishes a robust framework for secure data sharing and management in E-Health systems.
Information Fusion and Metallogenic Prognosis of Gold Deposits in the Qixia Area, Northern Shandong Province, China

Analyzing and fusing information layers of exploratory parameters is a critical step for enhancing the accuracy of identifying mineral potential zones during the reconnaissance stage of mineral exploration. The Qixia area in Shandong Province is characterized by intricate geological structures and abundant mineral resources. Numerous gold polymetallic deposits have been discovered in this region, highlighting the potential for discovering more such deposits in the ore concentration zone and its adjacent areas. In this study, we focus on the Qixia area and employ the box dimension method to analyze the fractal dimension of fault structures. We investigate the relationship between orebody occurrence and fault incidence within the mining region. Furthermore, we combine fractal analysis with Fry analysis to comprehensively predict the metallogenic potential in the area. This study reveals the fractal dimension values of fault structures, demonstrating that fault structures govern the distribution of ore bodies, with NE and NW fault structures being the primary ore-hosting features. Based on thorough analysis, we hypothesize that gold deposits in this area are generally distributed along the northeastern direction. By considering mineral distribution characteristics, this study identifies five potential metallogenic prospect areas within the study region. Capitalizing on advancements in information technology and big data, digital geology has gained prominence in prospecting and prediction. To this end, we construct a multi-information comprehensive prospecting model based on the structure-geochemical anomaly-mineralization alteration, employing the convolutional neural network (CNN) model for quantitative estimation of regional gold mineral resources. The findings validate the CNN model’s robust prediction performance in this area, leading to the determination of five prediction prospects. We observe a notable congruence between the two methods, offering significant insights for subsequent exploration endeavors in the region.
Raw data: the evolution of FAIR data and crystallography.

Scientific data in chemistry has come a long way in the last few decades. Originally entangled into scientific articles in the form of tables of numbers or diagrams, it was (partially) disentangled into supporting information when journals became electronic in the late 1990s.[1] The next phase was the introduction of data repositories in the early naughties.
Introduction

Abstract In string theory, the term “brane” is used for certain extended objects. As is typical of string theory, there are many different ways of seeing or defining these objects, depending on one’s preferred point of view.
RACISM IN TONI MORRISON’S THE BLUEST EYE

The purpose of this study is to reveal the form of racism and its impact on the mental health of African American in Toni Morrison's The Bluest Eye. The design of this study is qualitative research because the data that support this research are collected from books, journals, articles, and internet. The researchers use two kinds of data collection, namely the primary source that is the novel itself and the secondary sources are books, articles, the internet, and journals. The approach needed in research is mimetic approach, because this topic is related to the environment and as a reflection of human life. The author right to see racism in historical background of the novel. In analysing the data, researchers use three techniques called data reducing, data display, and conclusion. Researchers have read the novel and then decided the topic. From the amount of data collected from various sources researchers use text or jotting to compares, contrasts, and sorts the required data, from the notes written by the researchers, then can categorize the relevant data. The results of the analysis are racism experienced by African Americans in the form of rejection, insults and violence. Racism in the novel is not only practiced by white people but also among black people. Racism can cause victims to hate themselves, and hate others. By the story of the novel and the result of the analysis, researchers find that this impact is particularly vulnerable to children and women.