Reviewerly/exHarmony huggingface dataset:
Demographic Comparison of Information Security Behavior Toward Health Information System Protection: Survey Study

Background The health information system (HIS) functions are getting wider with more diverse users. Information security in the health industry is crucial because it involves comprehensive and strategic information that might harm human life. The human factor is one of the biggest security threats to HIS. Objective This study aims to investigate the information security behavior (ISB) of HIS users using a comprehensive assessment scale suited to the information security concerns in health care. Patients are increasingly being asked to submit their own data into HIS systems. As a result, this study examines the security behavior of health workers and patients, as well as their demographic variables. Methods We used a quantitative approach using surveys of health workers and patients. We created a research instrument from 4 existing measurement scales to measure prosecurity and antisecurity behavior. We analyzed statistical differences to test the hypotheses, that is, the Kruskal-Wallis test and the Mann-Whitney test. The descriptive analysis was used to determine whether the group exhibited exemplary behavior when processing the survey results. A correlational test using the Spearman correlation coefficient was performed to establish the significance of the relationship between ISB and age as well as level of education. Results We analyzed 421 responses from the survey. According to demographic factors, the hypotheses tested for full and partial security behavior reveal substantial differences. Education levels most significantly affect security behavior differences, followed by user type, gender, and age. The health workers’ ISB is higher than that of the patients. Women are more likely than men to engage in prosecurity actions while avoiding antisecurity behaviors. The older the HIS user, the more likely it is that they will participate in prosecurity behavior and the less probable it is that they will engage in antisecurity behavior. According to this study, differences in prosecurity behavior are mostly impacted by education level. Higher education, on the other hand, does not guarantee improved ISB for HIS users. All demographic characteristics, particularly concerning user type, show discrepancies that are caused mainly by antisecurity behavior rather than prosecurity behavior. Conclusions Since patients engage in antisecurity behavior more frequently than health workers and may pose security risks, health care facilities should start to consider information security education for patients. More comprehensive research on ISB in health care facilities is required to better understand the patient’s perspective, which is currently understudied.
Study and Development of Photovoltaic Power Generation System for Hybrid Refrigeration Units Applied in Refrigerated Semi-Trailers

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;This article presents the development of a solution that uses solar energy to power refrigerated semi-trailers. The solution employs photovoltaic cells on the surfaces of the semi-trailer, combined with a battery pack, which take advantage of a significant area with solar exposure and generate sufficient electric power to supply the refrigeration unit responsible for controlling the temperature inside the climate-controlled chamber. In addition to providing energy for the refrigeration unit, the solar system can be integrated with the auxiliary traction system used in some semi-trailers, functioning as a range extender for the battery. To achieve the main objectives of this development, studies were conducted to evaluate solar radiation through simulations considering different regions of Brazil. A hardware system was also developed for energy management and to drive the refrigeration unit, combining a high-power drive system composed of filters, DC/DC converters, and transformers to match the voltage levels of the systems, with a microprocessed circuit for functional logic control. As a result, a system capable of operating the refrigeration unit using solar energy was obtained, which can reduce diesel consumption by up to 1800 liters per year.&lt;/div&gt;&lt;/div&gt;
A Qualitative Study on educational experience Korean Teachers of Korean Teaching

Objectives This study aims to qualitatively investigate the life and educational experiences of Korean language teachers and explore in-depth the topics and implications they show in common.&#x0D; Methods It is one of the qualitative research methods and the most suitable narrative method was used to explore the meaning inherent in human experience. In-depth interviews were conducted with five Korean language teachers with at least 10 years of experience using a semi-structured questionnaire to collect data. The specific data analysis was conducted by following the data analysis steps of narrative research proposed by Creswell(2013).&#x0D; Results As a result of data analysis, the main topics that appeared in educational experiences of Korean language teachers were ‘the start of the career as a Korean language teacher by chance’, ‘students are the biggest reward as a teacher’, ‘the ambiguous status of a Korean language teacher’, ‘burden about work other than education’, and ‘emotional stability gained from fellow teachers’.&#x0D; Conclusions First, the participants highly rated the value of self-realization in occupational choice. Second, learners were the ones that give the greatest reward and motivation to the participants as teachers. Third, they were pressured by the burden of work other than education, as well as concerns about their status as a Korean language teacher. Fourth, all of the participants claimed they want improved treatment for Korean language teachers. Fifth, relationships with fellow teachers had a great impact on job satisfaction.
Exploring the Changes of Early Childhood Teachers’ Experiencers on and the Meanings of Reflective Emotion Journaling

Objectives The purposes of this study were to explore the changes of teacher’s experiences writing reflective emotion journals and the meaning of it in the contexts of early childhood education and care.&#x0D; Methods In this qualitative study, nine early childhood teachers participated in a course of the graduate school during 15 weeks, and at this time they submitted 10 journals and participated in the group discussion, group interviews.&#x0D; Results Two major themes along with multiple sub-themes were identifies including: First, the teacher's emotional journal writing experience changed from ‘unfamiliarity, difficult start’ to write down with focusing on the teacher's emotions in early childhood education to ‘objectively facing one's emotions,’ ‘discovering positive emotions, savoring them’, ‘viewing the classroom space as a living world’, and ‘considering teacher emotion in detail’. Second, the meaning of the experience of writing emotional journals to teachers can be summarized as ‘the journey to get to know me’, ‘time to empathize and comfort’, ‘the process of transferring the virtuous cycle’, and ‘time of growth’.&#x0D; Conclusions In conclusion, It is expected that it will be possible to find ways to support teachers' healthy emotional experiences in the early childhood education field while awakening the importance of teacher emotions in the early childhood teacher education program and presenting directions in terms of applying the value and meaning of teachers' emotional journal writing.
Research data management and data literacies <b>Research data management and data literacies</b> , by Koltay Tibor, Kidlington, Chandos Publishing, 2021, 195 pp., $155.75(soft cover), ISBN 978-0-12-824475-3

"Research data management and data literacies." Journal of the Australian Library and Information Association, ahead-of-print(ahead-of-print), p. 1
Improving Causal Learning Scalability and Performance using Aggregates and Interventions

Smart homes are Cyber-Physical Systems (CPS) where multiple devices and controllers cooperate to achieve high-level goals. Causal knowledge on relations between system entities is essential for enabling system self-adaption to dynamic changes. As house configurations are diverse, this knowledge is difficult to obtain. In previous work, we proposed to generate Causal Bayesian Networks (CBN) as follows. Starting with considering all possible relations, we progressively discarded non-correlated variables. Next, we identified causal relations from the remaining correlations by employing “ do-operations .” The obtained CBN could then be employed for causal inference. The main challenges of this approach included “non-doable variables” and limited scalability. To address these issues, we propose three extensions: (i) early pruning weakly correlated relations to reduce the number of required do-operations, (ii) introducing aggregate variables that summarize relations between weakly coupled sub-systems, and (iii) applying the method a second time to perform indirect do interventions and handle non-doable relations. We illustrate and evaluate the efficiency of these contributions via examples from the smart home and power grid domain. Our proposal leads to a decrease in the number of operations required to learn the CBN and in an increased accuracy of the learned CBN, paving the way toward applications in large CPS.
EVALUATION OF COMPUTER SCIENCE STUDENTS' WORK ON IT PROJECTS BASED ON QUANTIZATION OF PROFESSIONAL ACTIVITY

The article examines the process of evaluating work on IT projects, which is presented systematically and multidimensionally, as a reflective and analytical toolkit. The research was conducted on the basis of the application of a system of humanitarian, psychophysiological, anthropological and informational methods and approaches, where the application of the theory of functional systems and through methodological and value understanding of pedagogical and production experiences and practices are decisive. This work updates the methodological potential of the idea of professionalization, in particular, a specialist in computer specialties, pedagogical anthropology and the theory of functional systems, including the concept of quantization of mental activity, which is interpreted as quantization of professional activity. A decisive methodological and practical-technological factor, which is a prerequisite for considering the evaluation process as a reflective and analytical toolkit, is the systematic quantization of professional activity, which is implemented on the basis of the use of the methodologies of Kanban, Agile methodologies, in particular, Scrum, "Manifesto for Agile Software Development". The research used Information technologies: Jira Software, in particular the Kanban template, Agile tools for Kanban, Agile tools for Scrum. Current strategies for quantifying professional activity when working on IT projects are: Epic; Story; Task; Sub-Task; part of the Story/Task; Bug; Sprint. Students were divided into small groups that worked on IT projects. In the process of project activity, they performed the following roles: Engineer, Scrum Master, Product Owner, Tech Lead. The evaluation presented in the specified system format is a significant component of the result-target basis of work on IT projects, and is also considered as a tool of innovative activity and a prerequisite for personal and professional development and professional communication. In further research, it is planned to develop the problems of professional activity for work on IT projects, which includes the study of motivational, value, cognitive, operational, reflective, components, as well as the use of quantization in pedagogical research on the professional training of students of computer specialties. The results of this study are planned to be applied to improve the qualifications of information technology specialists in the conditions of postgraduate education.
PERANCANGAN APLIKASI PENGECEKAN DAN PEMESANAN LAPANGAN BASKET DI JAKARTA BERBASIS ANDROID

Basketball is one of the most popular sports today. The community loves playing basketball, especially among youths.That is one of the reasons why basketball offers chances to operate a basketball court leasing company. One of the requirements for beginning a basketball court leasing company is the high level of community involvement.If the desired basketball court has already been ordered, the prospective tenant will need to find another court, according to observations made with basketball court providers and field users. Another issue is that it is still difficult for prospective basketball court users to learn about the courts that are currently available. The field supplier also has challenges; for instance, they continue to manually record orders. As a result, the best way to address the issues at hand is to develop information technology, such as an Android-based basketball court checking and booking application, which would make it simpler for potential tenants to make field reservations and access data about schedules, locations, and court prices.It is believed that the application will help field service providers and renters make the field order procedure very effective. This application's development makes use of the Android Studio program and the MySQL database.
Penerapan Model Pembelajaran Kooperatif Tipe Student Teams Achievement Division (Stad) Untuk Meningkatkan Hasil Belajar Matematika Peserta Didik Kelas 4 C MIN 2 Kota Makassar

This study examines the Implementation of Supportive Learning Design Types of Student Teams Achievement Division (STAD) in Improving Student Counting Achievement Level 4 C MIN 2 Makassar City. This type of research is quality research located at MIN 2 Makassar City Jl. Pioneer of Independence Km. 15, Daya, Biringkanaya District, Makassar City. The deployment procedures carried out were observation, questions and answers, and archiving. The product of this research shows that the aspects that trigger the decline in arithmetical achievement of students at level 4 C MIN 2 Makassar City include lack of interest, low motivation, lack of teaching aids, frequently changing textbooks, school environment, and family area. Implementation of the Supportive Learning Design Type Student Teams Achievement Division (STAD) was able to increase the arithmetic achievement of students at level 4 C MIN 2 Makassar City by 48% from what initially many students had scores above the KKM amounting to 10 people or 35% increased to 24 people or 83 %. The conclusion of this study is that the factors that trigger the decline in arithmetic achievement of students at level 4 C MIN 2 Makassar City include lack of interest, low motivation, lack of teaching aids, frequently changing textbooks, school areas, and family areas along with the implementation of supportive learning designs of Student Teams. The Achievement Division (STAD) was able to increase the arithmetic achievement of students at level 4 C MIN 2 Makassar City by 48%.
Enhancing Media Streaming in Wireless Networks using IFW-CFH Algorithm

One of the major concerns for service providers and application developer are Quality of experience (QoE), where high traffic congestion on the Internet leads to the degradation of video quality. However, the effectiveness of video transmission is minimized due to the network based on packet loss, bandwidth, and delay. Because of bandwidth limitations, the videos transmitted are obtained in low quality. Meanwhile, various outcomes such as reduction in throughput, re-buffering, or mosaic are determined in packet loss which validated the video streaming obtained in reliable or unreliable mode. Therefore this paper proposes an Improved Fuzzy Weighted queueing based Crossover Fire Hawk (IFW-CFH) algorithm for effective real-time video transmission. The objective of the IFW-CFH approach is to reduce the delay, packet loss, and bandwidth to enhance the video quality via two key mechanisms namely congestion control mechanism as well as packet scheduling mechanism. During the generation of encoded video frames, the packaged packets to the local buffer are transmitted by the scheduler using our proposed IFW-CFH algorithm. Finally, the experimentation is conducted and the results show that the proposed method minimized transmission delay, packet loss, and bandwidth by 13.8% for effective real-time video transmission compared to the existing methods.
PERANCANGAN APLIKASI PEMBELAJARAN BENCANA TSUNAMI DI INDONESIA BERBASIS WEB

The Web-Based Design of a Tsunami Disaster Monitoring Application in Indonesia aims to make it easier for users to obtain information related to Tsunami Disasters in every province in Indonesia. This application aims to provide information ranging from total cases, active cases, dead victims, survivors, missing victims and information related to the Tsunami in Indonesia. Users can see data visualization in the form of a map of Tsunami cases and the total number of survivors in Indonesia. The design of this application uses the Waterfall model System Development Life Cycle (SDLC) development methodology. The database used in this application is MySQL.&#x0D; Mapping in this application uses the Leaflet system&#x0D; which can display data and map visualization of Indonesia. The programming languages used are HTML and PHP. The test results show that this application can be understood and used to find information from the Tsunami Disaster in Indonesia.
PERANCANGAN DASHBOARD UNTUK PELAYANAN SIRKULASI DI PERPUSTAKAAN UNIVERSITAS TARUMANAGARA

This journal writing is made with the following objectives, namely to designing the Circulation Services Dashboard at the Universitas Tarumanagara Library using Microsoft Power BI, monitoring the performance evaluation directly from 3 aspects of circulation services at the Universitas Tarumanagara (UNTAR) Library based on key performance indicator (KPI), and make it easier for library managers to read all circulation service transaction data based on the dashboard.&#x0D; By using literature study method and requirements prototype method, the dashboard design is displayed in the form of the bar chart using Microsoft Power BI. The design is divided based on 3 aspects, namely adding book titles, adding book copies, and book borrowing transactions.&#x0D; Based on the results of testing by the user on the Circulation Services Dashboard at the Universitas Tarumanagara Library, it can be concluded that the dashboard can display Year Filters, Month Filters, Science Field Filters, Book Title Addition Diagrams, Book Copy Addition Diagrams, Book Borrowing Transaction Diagrams, KPI Diagram for Adding Book Titles per Year, KPI Diagram for Adding Book Copies per Year, and KPI Diagram for Book Loan Transactions per Year properly and smoothly according to the user requests.
Implementing Conversational AI to Enhance Critical Illness Communication

Artificial intelligence (AI) enhances social communication by facilitating natural language dialogue exchanges between humans and machines. Critical illness communication (CIC) is traditionally understood as dialogues between doctors and critically sick patients about their interests, aspirations, and preferences. Conversational AI uses natural language processing (NLP) models to converse in a similar manner that a clinician would, assisting in more accurate diagnosis of patients with CIC needs, encouraging data collection to improve effective in-person collective decision-making, and reducing healthcare professional paperwork burden. The overall performance of the information compiled needs to be carried out with the participation of human evaluators from the healthcare system to improve the CIC documentation. The focus of this study is to enhance the effectiveness of critical illness communication (CIC) administration in hectic practice environments. The approach strives for consistency in meaning interpretation to enable significant in-depth involvement in predictive understanding and the transformation of patients’ interests and principles into patient-centered recommendations. The proposed system’s experimental findings reinforce the use of artificial intelligence to more accurately determine CIC-eligible patients and optimize process flow by assisting with vital mundane jobs, guaranteeing that more patients with chronic conditions receive CIC on time, freeing up healthcare professionals to concentrate on complex physiological and behavioral responsibilities.
Satellite target detection algorithm for high-pressure dense channel based on deep learning

In order to improve the detection accuracy of high-voltage dense channel satellite image, a satellite target detection algorithm based on deep learning is proposed. The convolution neural network is selected to extract the feature map of high-voltage dense channel satellite image, and the extracted feature map is input into the optimized deformation convolution neural network. The value of each sampling point and the corresponding position authority of block convolution kernel are weighted by using the regular region sampling feature map. The feature map output by the convolution operation of pooling layer is used to obtain the depth features of the same dimension. The depth feature is input into the full connection layer to obtain the full connection feature of candidate target area, and the target detection in high-voltage dense channel satellite image is realized. The experimental results show that the target detection accuracy of the method is higher than 99% and the false alarm rate and false alarm rate are lower than 1.4%.
Investigating the Gap Between Single-Hop and Multi-Hop Questions in Closed-Book Question Answering via Question Decomposition

Transformer-based language models (LMs) have been shown to perform question answering (QA) competitively even when removing context and using only questions as input (called closed-book QA). Previous work that studied closed-book has mainly used simple questions that require a single reasoning step (i.e., single-hop questions). In this study, we find that using multi-hop questions requiring multiple reasoning steps drastically drops the performance. We investigate how to close this gap using two methods: fine-tuning with explicit question decomposition using three decomposition systems, or few-shot learning with chain-of-thoughts (CoT) for implicit question decomposition. We experiment on three multi-hop datasets, considering different multi-hop question types (i.e., compositional, comparison, etc.). We demonstrate when the methods fail and identify future directions that are most promising to closing the gap between single-hop and multi-hop closed-book QA. We release the code: https://github.com/talkhaldi/mh_cbqa .