Reviewerly/exHarmony huggingface dataset:
Direction of SMART HEALTHCARE Utilization in Korea's Non-Medical Healthcare Service Area

Purpose: In this study, it look in to the direction of smart healthcare in Korea and would like to make sure possibility of healthcare service in non-medical area. In this contents, when non healthcare provider provide med-ical healthcare service in Korean, it can be judged what to be against the medical treatment action, furthermore, through the utilization of smart healthcare, it would be helpful to identify in the broaden professional behavior and business scope. Method: This study was conducted to look over the concept of smart healthcare, the scope of utilization in the non-healthcare service area and then to recognize what the counter strategy can be moved to which way. To achieve the goal of this study, it is confirmed to be referred the bio health report which is issued from Korea Health Industry Development Institute and the non-medical care service guideline and casebook. Results: As a result of the study, first, the introduction and step-by-step factors for establishing a smart health environment that are being implemented in Korea were confirmed. Second, the concept of non-medical healthcare services and detailed classification according to provision were examined. Third, smart healthcare technology trends and usage plans in non-medical healthcare services were confirmed. Conclusion: In order Smart healthcare is grafted with social networks, and unlike the conventional passive and one-sided healthcare services, acceptance and accuracy are expanding based on big data. In addition, the active participation of users is expected to induce cooperation, creating high-quality services and providing multi-dimensional services. Therefore, in the future, it is expected that the composition of an appropriate execution program in the non-medical healthcare service area will create various values in the local community.
Gerakan meningkatkan kualitas pendidikn ekonomi dan kesehatan masyarakat

Education, Economy and Health are three important pillars in society and social life, therefore these three things deserve more attention because all three have an important role in human life in the community directly. As a form of attention and sense of responsibility from academic, students are required to play an active role through community service in improving the quality of the three important pillars with the aim that the community becomes more empowered and prosperous. In applying this activity the students actively participate in each research and activity carried out and finally students can understand and feel firsthand the conditions and conditions of the community so that they can provide several solutions that can solve existing social problems.
Physical Activity And Programming That Promotes Healthy Behaviors In College Libraries

PURPOSE: College libraries can be excellent partners for promoting physical activity and health on the college campus. College libraries are community gathering spaces and often distribute important information to the campus community. The purpose of this study was to document what type of programming promoting physical activity and healthy behaviors (PA/HB) is being offered at campus libraries. METHODS: A 15-minute online survey was developed based on the survey used by Lenstra (2017), examining programming related to PA/HB in community libraries. College librarians were invited to complete the survey by email and by postings on librarian websites. Data was analyzed using descriptive statistics and qualitative analysis. RESULTS: Forty-four college librarians completed the survey. Seventeen did not offer any programming related to PA/HB and were not included in the results. Of those campus libraries that offered PA/HB, 13 had less than 5000 students on campus, 5 had between 5000 and 15000 students, and 9 had greater than 15000 students. PA/HB that was offered included yoga (n = 10), Zumba (n = 2), walking (n = 5), bicycling (n = 1), running (n = 1), gardening (n = 2), stress and anxiety reduction (n = 24), fitness challenges (n = 3), and fitness equipment and passes to check out (n = 2). Participants in the programs included all members of the community (students, faculty, staff). The majority of the activities were offered on weekday afternoons, followed by weekday evenings and mornings. Activities were not offered as often on weekends. Librarians reported that the reasons for offering these programs included lifelong learning (n = 4), health and wellness (n = 6), community engagement (n = 11), and stress and anxiety reduction (n = 27). Most librarians reported no administrative issues associated with offering PA/HB (n = 18). CONCLUSION: College libraries offer a variety of health promotion activities, with stress and anxiety reduction being the most popular activity. Exercise and health-related academic programs should consider collaborating with campus libraries and librarians to promote health and physical activity on campus.
Lithological classification using multi-sensor data and Convolutional Neural Networks

Abstract. Deep learning has been used successfully in computer vision problems, e.g. image classification, target detection and many more. We use deep learning in conjunction with ArcGIS to implement a model with advanced convolutional neural networks (CNN) for lithological mapping in the Mount Isa region (Australia). The area is ideal for spectral remote sensing as there is only sparse vegetation and besides freely available Sentinel-2 and ASTER data, several geophysical datasets are available from exploration campaigns. By fusing the data and thus covering a wide spectral range as well as capturing geophysical properties of rocks, we aim at improving classification accuracies and support geological mapping. We also evaluate the performance of the sensors on their own compared to a joint use as the Sentinel-2 satellites are relatively new and as of now there exist only few studies for geological applications. We developed an end-to-end deep learning model using Keras and Tensorflow that consists of several convolutional, pooling and deconvolutional layers. Our model was inspired by the family of U-Net architectures, where low-level feature maps (encoders) are concatenated with high-level ones (decoders), which enables precise localization. This type of network architecture was especially designed to effectively solve pixel-wise classification problems, which is appropriate for lithological classification. We spatially resampled and fused the multi-sensor remote sensing data with different bands and geophysical data into image cubes as input for our model. Pre-processing was done in ArcGIS and the final, fine-tuned model was imported into a toolbox to be used on further scenes directly in the GIS environment. The tool classifies each pixel of the multiband imagery into different types of rocks according to a defined probability threshold. Results highlight the power of using Sentinel-2 in conjunction with ASTER data with accuracies of 75% in comparison to only 70% and 73% for ASTER or Sentinel-2 data alone. These results are similar but examining the different classes shows that there are significant improvements for classes such as dolerite or carbonate sediments that are not that widely distributed in the area. Adding geophysical datasets reduced accuracies to 60%, probably due to an order of magnitude difference in spatial resolution. In comparison, Random Forest (RF) and Support Vector Machines (SVMs) that were trained on the same data only achieve accuracies of 46 % and 36 % respectively. Most insecurity is due to labelling errors and labels with mixed lithologies. However, results show that the U-Netmodel is a powerful alternative to other classifiers for medium-resolution multispectral data.
초⋅중등 교원연수 프로그램의 효과 분석: 국제지질자원인재개발센터를 중심으로

The purpose of this study is to analyze the results of satisfaction for learning eco-system on the teacher training program conducted at the IS-Geo (International School for Geoscience Resources) which is KIGAM (Korea Institute of Geoscience and Mineral Resources), and to determine the satisfaction and educational effects of the teacher training programs on elementary and secondary teachers. And then, to suggest improvement points in the future operation of the teacher training program at the IS-Geo. Therefore, we conducted questionnaire of satisfaction for learning eco-system based on the data collected by a survey of 98 elementary and secondary teachers who participated in the teacher training program at the IS-Geo, from July 2017 to August 2018. The research results are as follows. First, the results of satisfaction for learning eco-system showed high values of 4.58 or higher in both the elementary and secondary programs, and the teacher training program conducted by the IS-Geo had a positive effect on the training participants. Second, internal factors indicating learning motivation and learning development were elementary teacher training 4.70 and secondary teacher training 4.64, and it is necessary to develop training contents and programs by classifying them into majors other than the earth science department. Third, intermediate factors indicating contents of education and learning curriculum were 4.67 for an elementary teacher training program and 4.72 for secondary teacher training program. In addition, in order to operate the teacher training program according to the purpose of science and technology culture, it is necessary to develop a teaching-learning model and to improve the quality of teaching. Fourth, external factors indicating learner support and quality of instructors were 4.83 for an elementary teacher training program and 4.72 for a secondary teacher training program. In particular, it is necessary to develop teaching materials that can be used immediately in school classes and can generate interest.
Analisis Skema Pelepasan Beban Lebih pada Trafo AntarRel Subsistem Balaraja Baru 3,4 – Duri Kosambi 1 – Lontar Ketika Kontingensi

One of the subsystems in the Java-Bali electrical system is the New Balaraja 3,4 – Duri Kosambi 1 – Lontar subsystem, which is the new configuration subsystem for 2020 operation plan, so that an analysis regarding the overload shedding scheme is needed as one of the defense schemes when contingency happened. The purpose of this study is to analyze overload shedding schemes when the contingency occurs in the New Balaraja 3,4 – Duri Kosambi 1 – Lontar. This study is conducted using qualitative method, by analyzing the condition of subsystem when contingency occurs and the stages of overload shedding on interbus transformer 3,4 New Balaraja and interbus transformer 1 Duri Kosambi using dynamic simulation on DIgSILENT 15.1.7 software. Based on the results of this research, the overload shedding scheme is divided into 4 stages, stage 1 in 2 seconds, stage 2 in 2,5 seconds, stage 3 in 3 seconds, and stage 4 in 3,5 seconds, with the total quota of the overload shedding at the moment of peak load 545 MW also at low load 417 MW, thus once contingency happens, overload shedding scheme that has been designed is able to reduce overload on interbus transformer which is still operating
THE IMPORTANCE OF DEVELOPING DIGITAL COMPETENCE OF STUDENTS IN A DIGITAL ECONOMY

Today, all the changes and realities in the life of society are rapidly changing and updated due to digital technologies that cover all areas of human activity. The modern education system must be constantly updated and improved with scientific knowledge, because the future of our  country depends on the activities of experienced professionals trained in the digital world. Experts and social scientists recognize the modern society as an information age. The new generation is significantly different from the previous ones with their deep thinking. Society receives and processes a large amount of new information and information flow every day. The receipted new information is adapted to changing circumstances, as everybody has to adapt to the news of this world. The new era requires a change of people thinking in a new way. Many discoveries and scientific researches made in the field have already laid a solid foundation in the field of education. Today, changes in the modern educational process require the use of digital technologies [1].
CONTAIN: Privacy-oriented Contact Tracing Protocols for Epidemics

Public health agencies advocate the use of contact tracing procedures to deal with pandemics such as COVID-19 to prevent the infection of a vast population. Although several mobile applications have been developed previously for contact tracing, they typically require collection of privacy-intrusive information such as GPS locations, personal data, or require infrastructures such as WiFi APs. In this paper, we introduce CONTAIN, an early proposal for privacy-sensitive contact tracing. CONTAIN is a privacy-oriented bluetooth-based mobile digital contact tracing framework that does not rely on any infrastructure-based location sensing, nor the continuous logging of personally identifiable information. The goal of CONTAIN is to allow users to determine with complete privacy if and when they have been within a short distance of someone that is infected. We identify and prove the privacy guarantees provided by CONTAIN. We also present a simulation study utilizing an empirical trace dataset which shows that users can maximize their possibility of identifying if they were near an infected user by turning on the app in more crowded settings.
Review on Hanabi Challenge for Artificial Intelligence Research

Games were relevant to research to investigate how far computers would handle complex decision-making from the early days of computing. Machine learning has made considerable strides over recent years with automated staff that attain incredible success in difficult fields such as Go, Atari and other poker variants. Like their predecessors of chess, scrutinizers and backgammon, some areas of game science have presented artificial intelligence practitioners with complex yet well-established obstacles. The researchers continue this practice by introducing the Hanabi game as a new difficulty field with new difficulties resulting from the mixture of strictly cooperative gaming with 2 to 5 players and incomplete details. They contend in particular that Hanabi puts thinking on certain agents' beliefs and motives in the forefront. This paper assumes that creating new strategies for the philosophy of learning in Hanabi, and in particular those with human partners would be crucial to progress. To facilitate further research, this paper incorporates the Hanabi Learning Environment open-source, provides a research community with an investigational foundation for assessing algorithmic developments and determines the efficiency of modern technologies.
LibGuides: Tails and Tales Make Your Own Bookmark: Felt / Cloth Bookmarks

A collection of directions, craft templates, and pictures for making your own creative bookmarks at home.
Methods of formation of natural concepts during sensory knowledge

The State Standard of Basic Secondary Education states that the purpose of basic secondary education in Ukraine is the development of natural abilities, interests, talents of students, formation of competencies, etc. The competence potential of the natural education field and the basic knowledge of students in the basics of natural sciences are scientific facts, concepts, ideas, models, laws and methodologies of scientific knowledge – the language of science, empirical and theoretical research methods and more. This is a difficult task, and its solution is necessarily associated with the formation and development of concepts. The paper characterizes the preparatory stage for the formation of natural concepts. The method of actualization of basic knowledge and sensory experience of students and motivation of educational activity to the formation of concepts is revealed. The process of concept formation goes through two main stages of cognition – sensory and logical. The emphasis is placed on the method of formation of natural concepts at the stages of sensory cognition – sensation, perception, imagination.
Analysis, Integration and Testing the Component Based Adoption Techniques During Runtime Configuration

Component based Software Engineering is the most common term nowadays in the field of software development. The CBSE approach is actually based on the principle of ‘Select and Use’ rather than ‘Design and Test’ as in traditional software development methods. Since this trend of using and ‘reusing’ components is in its developing stage, there are many advantages and problems as well that occur while use of components. Here is presented a series of papers that cover various important and integral issues in the field concerned. This paper is an introductory research on the approaches, development process, various phases and assessment available in commercialized models in CBD.
Incremental Vulnerability Detection via Back-Propagating Symbolic Execution of Insecurity Separation Logic.

We present the first compositional, incremental static analysis for detecting memory-safety and information leakage vulnerabilities in C-like programs. To do so, we develop the first under-approximate relational program logics, including Insecurity Separation Logic (InsecSL). We show how InsecSL can be automated via back-propagating symbolic execution (BPSE) to build a bottom-up, inter-procedural and incremental analysis for detecting vulnerabilities. We prove our approach sound in Isabelle/HOL and implement it in a proof-of-concept tool, Underflow, for analysing C programs, which we apply to various case studies.
ALWT based Regularizer for Improvement of Low Intensity Visual Data

Image Completion is the process of recovering corrupted image with very limited observations. It is a challenging task to achieve accurate recovery in image with minimum observations. Many researchers are proposed various methods to recover the corrupted image. Here a new Adaptive Lifting Wavelet Transform (ALWT) based Alternating Direction Method of Multipliers (ADMM) optimization technique is proposed. A spiffing image recovery is observed at 90% of missing ratio. The non-linear filters are used in ALWT to obtain the lost observations. The Image Quality Assessment (IQA) metrics are considered to evaluate the performance of proposed approach. The IQA metrics namely Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Structural Similarity (SSIM) are achieved 32.32, 33.04dB and 0.8666 respectively. Here, the Additive White Gaussian Noise (AWGN) with standard deviation 150 is considered. The Mean Absolute Reconstruction Error (MARE), MSE and PSNR values are obtained as 3.176, 12.11 and 37.31dB respectively.
VaultVote: A Ray of Hope for Transforming the Voting System of India

This paper aims to propose Block-chain based Online Voting System over traditional voting systems for fair and transparent elections. Unlike traditional voting systems, under the proposed one there is no central tallying authority. Voting is done on a proof-based mechanism and each vote is stored as a permanent, unalterable block in the block-chain encrypted by cryptographic hash.
Almost one-third elderly persons affected with anaemia â A crosssectional community based study from rural India

Introduction: A rise in elderly population is noted in India not just in absolute numbers buts also in proportion. Anaemia in elderly is associated with increased morbidity and mortality and aggravating the comorbidities. Lack of quality information in community-based elderly exists, hence, our study aimed to estimate the prevalence of anaemia among community-dwelling elderly persons and qualify the same morphologically.Methodology: Rural community-based, cross-sectional study among elderly person’s 60 years was conducted in December 2016 and May 2017 in Haryana, India. A sample size of 396 was calculated and participants were selected randomly from the health and demographic surveillance system. The pre-tested self-developed semi-structured questionnaire was administered and a capillary blood specimen was used to estimate hemoglobin using HemoCue method. WHO cutoff ’s for anaemia was used and morphology of anaemia was ascertained by examination of peripheral blood smears.Results: Prevalence of anaemia among community-dwelling elderly persons was 28.3(95% C.I. 24-32.9). Anaemia was more prevalent in elderly males (28.6, 95% CI 22.8- 35.1) than in elderly females (27.9, 95% CI 22.1-34.6). Prevalence increased with each passing decade (24.4, 31.1, and 37.2). Normocytic anaemia was most commonly found the type of anaemia morphologically (49.5%).Conclusions: Prevalence of anaemia among community-dwelling elderly is high and is of public health concern. Routine screening for anaemia as part of geriatric health care services should be incorporated
Beyond the Black Box

As algorithms have become more complex, privacy and ethics scholars have urged artificial intelligence (AI) transparency for purposes of ensuring safety and preventing discrimination. International statutes are increasingly mandating that algorithmic decision-making be explained to affected individuals when such decisions impact an individual’s legal rights, and U.S. scholars continue to call for transparency in automated decision-making. Unfortunately, modern AI technology does not function like traditional, human-designed algorithms. Due to the unavailability of alternative intellectual property (IP) protections and their often dynamically inscrutable status, algorithms created by AI are often protected under trade-secrecy status, which prohibits sharing the details of a trade secret, lest destroy the trade secret. Furthermore, dynamic inscrutability, the true “black box,” makes these algorithms secret by definition: even their creators cannot easily explain how they work. When mandated by statute, it may be tremendously difficult, expensive, and undesirable from an IP perspective to require organizations to explain their AI algorithms. Despite this challenge, it may still be possible to satisfy safety and fairness goals by instead focusing on AI system and process disclosure.This Article first explains how AI differs from historically defined software and computer code. This Article then explores the dominant scholarship calling for opening the black box and the reciprocal pushback from organizations likely to rely on trade secret protection—a natural fit for AI’s dynamically inscrutable algorithms. Finally, using a simplified information fiduciary framework, I propose an alternative for promoting disclosure while balancing organizational interests via public AI system disclosure and black-box testing.
Short paths in PU(2)

Parzanchevski--Sarnak \cite{PS} recently adapted an algorithm of Ross--Selinger \cite{RS16} for factorization of $\PU(2)$-diagonal elements to within distance $\eps$ into an efficient probabilistic algorithm for any $\PU(2)$-element, using at most $3\log_p(\nicefrac{1}{\eps^3})$ factors from certain well-chosen sets. The Clifford+$T$ gates are one such set arising from $p=2$. In that setting, we leverage recent work of Carvalho Pinto--Petit \cite{CPP} to improve this to $\frac{7}{3}\log_2(\nicefrac{1}{\eps^3})$, and implement the algorithm in Haskell.