Reviewerly/exHarmony huggingface dataset:
IDENTIFIKASI COVID-19 BERDASARKAN CITRA X-RAY PARU-PARU MENGGUNAKAN METODE LOCAL BINARY PATTERN DAN RANDOM FOREST

Covid-19 is a phenomenon that can’t be forgotten by the world. At the end of 2019 in Wuhan, China SarsCov-2 virus was discovered until the World Health Organization declared Covid-19 as pandemic on March 9, 2020. The rapid development and transmission of this virus was overwhelmed. One way to find out someone is positive for Covid-19 is by looking at the X-Ray results of their lungs. The X-Ray results will be analyzed to determine the state of a person's lungs. The method used in this study consists of feature extraction method using Local Binary Pattern (LBP) and classification method using Random Forest. This study uses training data and test data of X-Ray images of the lungs which are divided into three classes that is normal lungs, positive for Covid-19, and Pneumonia. Based on the results of tests that have been carried out using 1,200 images divided into 900 training data and 300 test data, the system can identify Covid-19 based on X-Ray images of the lungs and classify them into three classes. The highest accuracy results obtained 85.67% using variations of image resizing= 200x200 pixel, radius of LBP= 8, and the number of trees in Random Forest=200.
Grand Challenges in Visual Analytics Applications

In the past two decades, research in visual analytics (VA) applications has made tremendous progress, not just in terms of scientific contributions, but also in real-world impact across wide-ranging domains including bioinformatics, urban analytics, and explainable AI. Despite these success stories, questions on the rigor and value of VA application research have emerged as a grand challenge. This article outlines a research and development agenda for making VA application research more rigorous and impactful. We first analyze the characteristics of VA application research and explain how they cause the rigor and value problem. Next, we propose a research ecosystem for improving scientific value, and rigor and outline an agenda with 12 open challenges spanning four areas, including foundation, methodology, application, and community. We encourage discussions, debates, and innovative efforts toward more rigorous and impactful VA research.
Confusion Region Mining for Crowd Counting

Existing works mainly focus on crowd and ignore the confusion regions which contain extremely similar appearance to crowd in the background, while crowd counting needs to face these two sides at the same time. To address this issue, we propose a novel end-to-end trainable confusion region discriminating and erasing network called CDENet. Specifically, CDENet is composed of two modules of confusion region mining module (CRM) and guided erasing module (GEM). CRM consists of basic density estimation (BDE) network, confusion region aware bridge and confusion region discriminating network. The BDE network first generates a primary density map, and then the confusion region aware bridge excavates the confusion regions by comparing the primary prediction result with the ground-truth density map. Finally, the confusion region discriminating network learns the difference of feature representations in confusion regions and crowds. Furthermore, GEM gives the refined density map by erasing the confusion regions. We evaluate the proposed method on four crowd counting benchmarks, including ShanghaiTech Part_A, ShanghaiTech Part_B, UCF_CC_50, and UCF-QNRF, and our CDENet achieves superior performance compared with the state-of-the-arts.
Leading Managing Transformation to Digital University in Indonesian Context

This research aims to analyze the management of digital transformation in the context of Indonesian universities. The explanatory research was employed, utilizing a survey questionnaire administered to a randomly selected sample of 302 individuals comprising members of the ICT alignment team, change team, staff, and lecturers within the PTS environment in the LLDIKTI IV area, Banten &amp; West Java provinces. The data analysis in this study employed covariance-based structural equation modeling (SEM) procedures. Findings from this research indicate that achieving a radical transformation from traditional campus settings to digitalization, while adopting an incremental approach towards a smart university necessitates effective leadership and cultural support. A leadership coalition capable of institutionalizing new values, which subsequently become norms and guide the organizational culture, empowers members and fosters motivation for change oversight and participation. Ultimately, successful change management towards a smart university relies on leadership and culture, collectively institutionalized as a shared mental program, thereby shaping the meaningful trajectory towards a smart university.
Digitalisation of Teaching Materials for Toba Batak Ethnic Decorative Variety with Procreate Media Based on p-Books and e-Books

This research aims to develop teaching materials in the form of digitalisation of Toba Batak Ethnic Decorative Variety with p-book and e-book-based procreate media that are valid, practical, and effective in the Fine Arts Department. This research method uses research and development with the 4-D development model (Four-D Models), namely define, design, develop, and disseminate. This research instrument uses a questionnaire with a Likert scale, while the data analysis technique consists of analysing the validity, practicality and effectiveness of teaching materials. The results of this study indicate that: a) p-book and e-book-based teaching materials with the title of the book/module/teaching material "Gorga Batak Toba", with the acquisition of a category that is quite valid with an average score of 78%, b) teaching materials are quite practical to be used by students in the North Sumatra Ethnic Decorative Variety Course (RHESU) with a score of 77%, and c) teaching materials fall into an effective category where students from four categories such as reading teaching materials, asking questions, answering questions, and completing assignments given by lecturers, can be observed in the learning process and student learning outcomes are 83.26%. So, from the scores and test results of the research results above, it can be said that the teaching materials are quite valid, quite practical, and effective to be applied in learning the North Sumatra Ethnic Decorative Variety Course (RHESU) at the Department of Fine Arts, Faculty of Language and Arts, Universitas Negeri Medan.
Development of p-Book and e-Book Based Modules in Batik Creation in Fine Arts Department

This study aims to develop p-book and e-book-based modules that are valid, practical, and effective in the Archipelago Ornament Course and the Batik Craft Course in the Fine Arts Department. This research method used research and development with the 4-D development model (Four-D Models), namely: define, design, develop, and disseminate. The research instrument used a questionnaire with a Likert scale, while the data analysis technique consisted of validity data analysis, practicality data analysis, and effectiveness test data analysis. The results of this study indicated that: a) the validity value of the module was 79.25%, and the module was a pretty valid category; b) the value of the practicality of the module by students was 85.33%, and the module was included in the practical category in the learning process, and c) the average value of student activity (reading modules, asking questions, answering questions, and completing assignments) observed in the learning process and student learning outcomes was 82.81% which can be category as very active students and modules were category as effective. It showed that p-book and e-book-based modules were quite valid, practical, and effective in the learning process in the Archipelago Ornament Course and the Batik Craft Course in the Fine Arts Department, Faculty of Languages and Arts, Universitas Negeri Medan.
Can’t Believe It Went by So Fast

This autobiographical sketch starts with my arrival as a PhD student at UCLA in 1965. It focuses on the most prominent line of my intellectual development, from work in Priorean tense logic for my dissertation and essays intended to fit within the framework of Montague Grammar to the discourse-oriented framework of Discourse Representation Theory (DRT) and eventually to the unequivocally cognitive approach of Mental State Discourse Representation Theory (MSDRT), which is the core of my present view and work. Expected final online publication date for the Annual Review of Linguistics, Volume 10 is January 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
ОЦІНЮВАННЯ БЕЗПЕКИ ІНФОРМАЦІЙНО-КЕРУЮЧИХ СИСТЕМ РОЗУМНИХ БУДИНКІВ З ВИКОРИСТАННЯМ ДЕРЕВ АНАЛІЗУ АТАК

The information and control system of smart building is considered as a set of subsystems including building automation system (BAS). BAS security and availability during its life cycle are assessed using the technique Attack Tree Analysis (ATA), and Failure Modes and Effects Analysis (FMECA). The FMECA is applied at the initial stage of analysis to assess criticality of BAS hardware/software failures and failed connections between components on the different levels of system design. Modification of FMECA is IMECA allowing to analyze modes and effects of attacks/intrusions. The ATA is applied to investigate any intrusions into the BAS by analyzing system probability of a failure caused by faults and vulnerabilities during operation time. The ATA is applied for different BAS subsystems and results of analysis are combined.
The Story of AWS Glue

AWS Glue is Amazon's serverless data integration cloud service that makes it simple and cost effective to extract, clean, enrich, load, and organize data. Originally launched in August 2017, AWS Glue began as an extract-transform-load (ETL) service designed to relieve developers and data engineers of the undifferentiated heavy lifting needed to load databases, data warehouses, and build data lakes on Amazon S3. Since then, it has evolved to serve a larger audience including ETL specialists and data scientists, and includes a broader suite of data integration capabilities. Today, hundreds of thousands of customers use AWS Glue every month. In this paper, we describe the use cases and challenges cloud customers face in preparing data for analytics and the tenets we chose to drive Glue's design. We chose early on to focus on ease-of-use, scale, and extensibility. At its core, Glue offers serverless Apache Spark and Python engines backed by a purpose-built resource manager for fast startup and auto-scaling. In Spark, it offers a new data structure --- DynamicFrames --- for manipulating messy schema-free semi-structured data such as event logs, a variety of transformations and tooling to simplify data preparation, and a new shuffle plugin to offload to cloud storage. It also includes a Hivemetastore compatible Data Catalog with Glue crawlers to build and manage metadata, e.g. for data lakes on Amazon S3. Finally, Glue Studio is its visual interface for authoring Spark and Python-based ETL jobs. We describe the innovations that differentiate AWS Glue and drive its popularity and how it has evolved over the years.
Cornet: Learning Spreadsheet Formatting Rules by Example

Data management and analysis tasks are often carried out using spreadsheet software. A popular feature in most spreadsheet platforms is the ability to define data-dependent formatting rules. These rules can express actions such as "color red all entries in a column that are negative" or "bold all rows not containing error or failure". Unfortunately, users who want to exercise this functionality need to manually write these conditional formatting (CF) rules. We introduce Cornet, a system that automatically learns such conditional formatting rules from user examples. Cornet takes inspiration from inductive program synthesis and combines symbolic rule enumeration, based on semi-supervised clustering and iterative decision tree learning, with a neural ranker to produce accurate conditional formatting rules. In this demonstration, we show Cornet in action as a simple add-in to Microsoft's Excel. After the user provides one or two formatted cells as examples, Cornet generates formatting rule suggestions for the user to apply to the spreadsheet.
Developing a Risk Management System with an Optimistic Predictive Approach and Business Decision-Making

Risk Management is an important task that helps to monitor the business application to eliminate the political, financial, cultural, and social consequences. The organization's risk decision is affected by several characteristics, such as lack of accountability and risk decision-making. The difficulties are resolved by applying the Machine-Learning related Business Decision Making Approach (ML-BDMA). The created framework helps to reduce the difficulties in decision-making while managing the organization's risk. The Business Decision Making process works along with the Optimistic Predictive Techniques (OPT) that are used to identify the risk which leads to attaining the business objective. This process categorizes the risk according to the qualitative characteristics of business data. The system's effectiveness was evaluated using the experimental result in which the system ensures a 98.93% performance rate, 92.25% reliability rate, 93.47% authenticity rate, 91.11% risk management rate, and 97.77% development rate while making a business decision.
Intelligent Wireless Sensor Networks for Healthcare: Bridging Biomedical Clothing to the IoT Future

The science of achieving a healthy mind, body, and spirit through objectives and activities is known as personal health (PH). We must be aware of our mental, bodily, and social well-being. The term hygiene refers to a wide variety of healthy behaviours. Individuals' healthcare costs and quality of life increased by avoiding or reducing the long-term effects of the disease through knowledge and skills. Biomedical apparel includes sutures, vascular grafts, and biodegradable clothes (BC). Biomedical clothing is anything implanted or incorporated into the human body and used near tissue, blood, or cells. Quick, dependable, and energy-efficient connectivity between wireless sensor networks is necessary (WSNs). Physical layers, media access control, networking layers, and control requirements must be co-designed. For those with lesser means, health insurance will increase in cost. There are difficulties with privacy and cyber security, a higher chance of malpractice claims, and increased time and financial expenditures for doctors and patients. In this study, wireless sensor networks-based personal health biomedical clothing (PH-BC-WSN) was utilized to increase access to high-quality healthcare, increase food production through precision agriculture, and raise the standard of human resources. More effective healthcare and medical asset monitoring systems can be developed thanks to the Internet of Things. Eavesdropping on medical data, modification, fabrication of warnings, denial of service, user tracking and location, physical interference with equipment, and electromagnetic threats were extensively discussed. The article gives several instances of current technology, discusses design challenges including energy efficiency, security, and scalability, provides various demonstrations of current technology, and provides a complete analysis of all the advantages and disadvantages. Despite their many benefits, body sensor networks have several significant obstacles and unresolved research problems, which are described along with some potential answers. As a result, the experimental findings demonstrate that PH-BC-WSN enhances accuracy and reduces response time in inpatient health monitoring.
Pengaruh Metode Role Playing Terhadap Keterampilan Berbicara Siswa Kelas V SD Negeri 37 Pekanbaru

This study aims to determine the effect of the role playing method on speaking skills of fifth grade students at SD Negeri 37 Pekanbaru. This type of research is quantitative research using pre-experimental design methods. The research design used in this study is the one group pretest posttest design. The subject of this study were students of class V B at SD Negeri 37 Pekanbaru with a total of 23 students. The data collection technique used in this research is using an oral test through the initial test technique (pretest) and the final test (posttest). the results of this study show that students speaking skills have increased. The average pretest score obtained was 40,86 then given treatment eith the role playing methode after being given posttest further treatment, the average posttest score increassed to 64,13 and obtained an increase (gain) of 0,38 with moderate criteria. Based on the result of the research and data analysis, it can be concluded that the role playing method has an effect on the speaking skills of fifth frade students at SD Negeri 37 Pekanbaru. Based on the result of the t_table that has been carried out, a significance of 8.21 is greater than t_table 2.08 it can be concluded that H_o is rejected and H_a is accepted.
Binocular measurement method for a continuous casting slab based on the one-dimensional probabilistic Hough transform and local sub-pixel sifting

Due to the low measurement accuracy of the continuous casting slab model caused by difficulty in detecting ideal corners, a binocular measurement method based on the one-dimensional probabilistic Hough transform and local sub-pixel sifting is proposed. First, the one-dimensional probabilistic Hough transform based on inclination angle voting and the Freeman chain code is used to detect the line segments of the exterior outline. Next, sub-pixel points are extracted in each region of interest (ROI) by using Zernike moments, and sifted in the overlapping area of adjacent ROIs. Then the orthogonal total least squares (TLS) method is applied to fitting sub-pixel edges. Finally, after the key points are matched, three-dimensional localization and measurement are completed according to the binocular vision measurement principle. The experimental results show that the minimum relative error and average relative error of length reach 0.3401% and 0.3945%, respectively, satisfying the measurement requirement. Compared with scale-invariant feature transform (SIFT) and the oriented FAST and rotated BRIEF (ORB), the measurement error of the proposed algorithm is reduced by 80.01% and 74.63%, respectively. Compared with another edge fitting method based on k-means clustering and least squares fitting, its measurement error is reduced by 34.11%, and the time consumption is shortened by 39.07%, verifying its excellent performance in accuracy and efficiency.
Influence of Social Media and Parental Upbringing on Drug Abuse among Students in Tertiary Institution in Delta State

This study investigated, social media and parental upbringing on drug abuse among Tertiary institution students in Delta State. Two (2) research questions and two (2) null hypothesis was raised to guide the study. The study adopted the correlational research design. The population of this study comprised the entire students in the three colleges of education in Delta State. federal college of Education Asaba, College of Education Warri and College of Education mosogar. sample size was six hundred (600), that is to say 200 students from each college of education, this was done through simple random sampling techniques giving a total sample of 600, Instruments use for this study was, social media, parental upbringing and drug abuse scale (SMPUDAS). The total number of all the variables are 76.29%, content validity while its construct validity ranged between 0.52 to 0.99. The reliability index for, social media scale has alpha=0.89 P ? 0.5 level of significance, parental upbringing scale has alpha =0.96, and drug abuse scale has alpha =0.97 P ? 0.5 level of significance. correlation and coefficient was use to answer research questions while correlation , and Regression analysis were employed to test the hypotheses at .05 level of significance. The result showed that all the variables has a relationship with drug abuse among the tertiary school students in colleges of education in Delta State. Based on the findings, recommendations were made that, Parental upbringing and monitoring should be done both in school and at home, Parent should monitor the type of things their children watches or type of information their children asses at the social media, Students should always seek the help of a professional counsellor and a therapist for modification of behavior
MODEL OF ADAPTIVE LEARNING OF THE STEM EDUCATION SYSTEM

The article discusses an adaptive learning model that is able to provide each student with assistance to achieve the optimal level of intellectual development in accordance with his natural abilities and inclinations in the STEM education system. The main advantages of the adaptive learning model are considered. The problem of adaptive learning in modern educational systems is studied. It was determined that the planning and organization of the educational process, the selection of types of tasks, their levels of complexity, the sequence of material submission, the implementation of various types of control, the determination of evaluation criteria for each type of task belong to the methodological aspects of adaptive learning in the STEM system. The technical aspects include: an algorithm that offers to move to a new level if most of the tasks are performed correctly or to return to the previous level taking into account the mistakes made while performing the tasks; an algorithm for forming a number of tasks according to the student’s level of knowledge; evaluation of his educational achievements.
Analysis and Design of Digital Marketing Information System for Building Material Store

The manual nature of Material Store such as Toko Bangunan Berkat Rezeki's current business operations is one of the hurdles it encounters in marketing. This study intends to build a marketing information system for the products and services of Toko Bangunan Berkat Rezeki utilizing the 4P marketing mix idea (product, price, place, and promotion). The framework for application design is design thinking, which includes empathy, defining, ideating, prototyping, and test phases. Business owners, employees, and customer's requirements are identified during the empathize phase. In addition, at the designated stage, each system user's business operational difficulties are ranked according to a scale of importance. At the ideate stage, the outcomes of selecting and organizing problems and wants of system users based on priority scales are used to create flows and authorities according to their respective functions. At the prototype stage, the application interface is designed based on the demands and rules of system users and follows the 4P marketing mix concept. In the testing phase, test the login procedure for each user and the procedures for adding, saving, viewing, updating, and removing data. The findings of this study indicate that information on products, product prices, and product promotions may be handled by a website-based marketing information system, such that place is no longer synonymous with a physical store but rather an intangible one. Consequently, Toko Bangunan Berkat Rezeki can employ a website-based marketing information system to enhance sales volume and expand its market reach.