Reviewerly/exHarmony huggingface dataset:
The use of big data technology to support the transformation of public content management towards knowledge management

Big Data technology is a phenomenon and many organisations are trying to integrate it into their business processes to obtain added value as well as support business processes. Big Data can be used in various ways, one of which is public communication management. Along with the growing dissemination of public issues on social media and others’ internet content, the Ministry of Communication and Information made it easier for various stakeholders to handle public issues and internet content by utilising Big Data technology. In addition, after the process of handling public issue, the knowledge management concept, which is integrated with big data, will help turn information into useful knowledge. The research was carried out with a qualitative method and described the use of huge amounts of information from big data technology on Big Data machines to monitor negative internet content. The results of this study show the use of Big Data and Knowledge Management technology in dealing with internet content and public issue circulating on the internet, in particular to support the public policy-making process.
Global Citizenship of University Students : Types and Determinants

본 연구의 목적은 대학생의 세계시민성의 유형 및 결정요인을 밝히고, 이를 통해 대학생세계시민교육에 대한 시사점을 얻는 데 있다. 이를 위해 수도권 소재 대학생 439명을 대상으로 전문리서치기관의 온라인 설문조사를 진행하였다. 자료분석은 SPSS ver. 25.0을 사용하여 군집분석 및 다항 로지스틱 회귀분석회귀분석을 실시하였다. 분석 결과 대학생의세계시민성은 ‘성숙한 세계시민성 유형(27.1%)’, ‘실천 지향적 세계시민성 유형’(32.8%), ‘지식 태도 지향적 세계시민성 유형’(23%), ‘미숙한 세계시민성 유형’(17.1%)의 4가지유형으로 도출되었다. 대학생의 세계시민성 유형별 결정요인을 분석한 결과 개인적 요인에서는 성별, 대중매체 및 소셜미디어의 글로벌이슈 접촉, 사회적 유대감, 자기효능감이, 가정요인에서는 부모지지가, 학교 요인에서는 학교환경이 유형별로 유의한 영향을 미치는 것으로 나타났다. 이러한 연구결과에 기반하여 대학생의 세계시민성교육의 설계 및 운영 방향에대한 시사점을 논하였다.The purpose of this study is to deduce implications of global citizenship education in universities by surveying the types and determinants of global citizenship among university students. In this study, an online survey was conducted over 439 students from the capital area. The survey data was analyzed with multinomial logistic regression model and K-means clustering using SPSS (Version 25.0). As a result, the students were categorized into 4 types: ‘mature global citizenship(27.1%) , ‘behavioral-oriented global citizenship’(32.8%) , ‘knowledge and skill-oriented global citizenship (23%) and ‘immature global citizenship’(17.1%)]. To add, the main factors that determines the types of global citizenship includes: gender, self-efficacy, media/SNS exposure to global issues, social connectedness, parental support, and school environment. Based on our analysis, we discuss a direction for the global citizenship education program, in terms of design and operation.
NATURAL LANGUAGE PROCESSING METHODS FOR CONCEPT MAP MINING: THE CASE FOR ENGLISH, KAZAKH AND RUSSIAN TEXTS

Concept maps are used for knowledge visualization via representing an input text or domain at the conceptual level.Concept maps reflect the systemic relations between key concepts of a text/ domain and thereby contribute to a deeper understanding of text/domain ideas, save time spent on reading and analysis.However, the process of concept maps construction is laborious and time consuming.Currently, there is a lot of research on the idea of automatic generation concept map from natural language texts.The problem has a high practical value, but in theoretical terms, methods for its solution are mainly language-dependent.Such methods require high-quality annotated linguistic resources, which is a serious problem for low-resource languages like Kazakh.In this work, we analyze the issues related to language-dependent approaches and present our experimental work on automatic generating concept maps from English, Kazakh and Russian texts.We use a well-known language-dependent method called ReVerb which was originally developed for English, and on the example of this method we explore the issues that we have encountered in the case of Kazakh and Russian languages.
High-dimensional temporal-mode decoding with a multi-output quantum pulse gate

We demonstrate a multi-output quantum pulse gate that sorts temporal modes (or their superpositions) at telecommunication wavelengths into separate output channels. This device will prove beneficial for high-dimensional quantum information processing in the time-frequency domain.
Peer review declaration

All papers published in this volume of Journal of Physics: Conference Serieshave been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind • Conference submission management system: easychair.org • Number of submissions received: 575 • Number of submissions sent for review: 461 • Number of submissions accepted: 83 • Acceptance Rate (Number of Submissions Accepted/Number of Submissions Received X 100): 14.43 % • Average number of reviews per paper: 02 • Total number of reviewers involved: 123 • Any additional info on review process: Step 1. Each of selected paper will be reviewed by two/three professional experts in the related subject area. Step 2. Review Reports received from the experts will be judged by one of the editors either Review Reports are logical or not? Step 3. If not logical, then editor can assign new reviewer or can also judge at his/her own. Step 4. If logical, then Review Reports will be sent to authors to modify the manuscript accordingly. Step 5. Authors will be required to revise their papers according to the points raised. Step 6. Revised version will then be evaluated by the editor for the incorporation of the points raised by the reviewers. Step 7. Then the editor will send the revised manuscript to the reviewers again for reevaluation. Step 8. If the reviewers approve the revise version of the manuscript, then will be accepted for publication • Contact person for queries: Dr C Kishor Kumar Reddy Associate Professor Stanley College of Engineering &amp; Technology for Women Abids, Hyderabad, India - 500001 Email : ckishorkumar@stanley.edu.in
Minimization of Contacts with Students During Covid-19 in an Automatic and Transparent Assessment Process of Exams Organized with Personalized Thesis Randomly Generated Via Microsoft Word

The authors are teachers in different universities in Tirana, Albania.We all like our profession and are very dedicated to teaching.There are two main reasons why we started working on this project: For many years in Albania entering the university as a student has been arranged through a competition process.This process is similarly like organizing exams with considerable numbers of students.Every faculty used to organize its own test
POSA288 Virtual Reality and Gaming Technology in Clinical Research: Past Trends and Future Prospects

Digital therapeutics (DTx) is a category of regulated software designed to improve health outcomes via the delivery of evidence-based behavioral or physical therapy to treat or prevent disease. Virtual reality (VR) and video games (VG) represent new modalities with the potential to increase patient engagement for the delivery of DTx. This research aims to characterize how these technologies have been studied. Clinicaltrials.gov was searched for studies containing “(video game OR gaming OR game OR virtual reality AND NOT board OR ball)” registered up to and including 03-Jun-2021. Technology type (VR or VG) was determined based on study title, intervention and outcome. 3,041 studies were returned, of which 1,398 studies were excluded primarily due to inability to determine technology type. 1,643 studies were analyzed (VR=1,000 [60.1%], VG=643 [30.9%]) of which 67.3% were registered in the last 5 years. 82.3% of studies were non-industry and non-government funded. In terms of study design, 94.1% of studies were interventional and the most common interventional model was the randomized, parallel groups design (60.1% [VR 61.1%, VG 59.7%]). Most studies investigated the treatment effects (47.3% [VR 52.9%, VG 38.7%]), followed by 11% of the overall sample investigating preventative effects (VR 5.3%, VG 19.9%). The median sample size across all studies was n=57 (IQR=30-100). CONCLUSION: Most (>70%) of the clinical research on VR and VG has been small interventional (<100 subjects) studies investigating treatment effects of these technologies. These findings point to a paucity of large studies (≥1000 subjects) on these technologies (<2.3%). DTx could be considered well suited to decentralized (DcT) study approaches, which could enable larger, more robust trials. The ability to apply such approaches to study VR and VG presents an exciting opportunity to advance the development these technologies in real-world settings.
Waveguide-Based Spontaneous Parametric Downconversion Sources of Polarization-Entangled Photon Pairs

We present waveguide-based SPDC sources for producing both degenerate and highly nondegenerate polarization-entangled photon pairs. We measure entanglement metrics of up to 99% through optimization of both temporal and spectral overlap.
3D optical components made by additive manufacturing for casting complex patterns of light

We report on the design, fabrication by 3D printing and soft molding, and characterization of magic windows , which are 3D optical components capable of generating structured light patterns by refraction of an incident beam.
Improved sample efficiency by episodic memory hit ratio deep Q-networks

Deep Reinforcement Learning (DRL) has achieved great success in making decisions on some complex tasks.Unfortunately, existing DRL algorithms are usually sample inefficient in that they require a huge amount of interactions with the environment to gain a desirable performance.Recently, Episodic Memory Deep Q-Networks (EMDQN) substantially improves the sample efficiency by episodic memory.However, rewards in episodic memory are delayed because they are obtained after the agent interacts with the environment in a multi-step trial and error manner, which means that EMDQN is sample inefficient to some extent.In this paper, we propose a new algorithm, Episodic Memory Hit Ratio DQN (EMHR-DQN), to improve sample efficiency by reward shaping.Inspired by reward shaping methods, we design a new reward shaping function Episodic Memory Hit Ration (EMHR) to provide additional rewards for the retrieval result of episodic memory.In this way, our method can modify rewards in episodic memory and provide useful supervision for the training of the agent.Experimental results verify the superiority of our method.
A Comparative Tunings Chart

In Experimental Musical Instruments' February 1989 issue, the authors published a sound spectrum chart, laying out values for frequency, pitch name, and wavelength, over the entire audible range. Tunings from diverse music cultures, historical European scale systems, and scales created by contemporary composers and theorists are represented on the chart. To help demarcate the tonal territory, horizontal reference lines cross the entire chart at heights corresponding to certain basic just intervals: the major second 9:8, the major third 5:4, the perfect fourth 4:3, the perfect fifth 3:2, and the major 6th 5:3. The ratios appearing on the chart give the frequency of the given scale degree over the frequency of the starting tone of the tuning, reduced to the simplest terms. On the chart, the blue tonalities appear, inevitably, primarily as a series of gradations.
DESIGN OF PRIVATE CLOUD STORAGE USING SECURITY METHODS IDS AND IPS

Cloud computing is a form of technological progress that has developed along with the times, this has spurred the increasing use of the internet. By usingtechnology internet that is able to implement server a virtual, which has the aim of building a cloud computing server at the District Communications and Information Office. Padang Pariaman uses the Operating System (OS) Proxmox VE (Virtual Environment) 6.4. Cloud computing is able to provide storage services that can be used simultaneously. The results of this study produce a cloud computing server that implements a security system with themethods ids (intrusion detection system) and ips (intrusion prevention system)that are able to process data(storagestorage), use software simultaneously in the network, and use infrastructure within the scope of this research.network cloud computing at the District Communications and Information Office. Padang Pariaman using aservice model private cloud
Review of Tusting, McCulloch, Bhatt, Hamilton &amp; Barton (2019): Academics writing: The dynamics of knowledge creation

Abstract This article reviews Academics writing: The dynamics of knowledge creation 9780815385905$ 128.00$ 37.56$ 37.56
Slate Rock Mines: from formation to Extraction

Slate rock has been analyzed for more than 170 years and was among the first geological features to be used in a number of countries such as Spain, France, Wales, North America and Brazil. Early observations recognized the importance of slate into th
Visual Tracking Detection and Movement Identification by Using Eye-Tracker for E-sports Player

E-sports has been included in the official sport in November 2017, but in various world competitions, Korean players always perform particularly well, which makes people want to know whether Korean players have introduced scientific training (Gu in Expert Syst Appl 130:293–305, 2019 [1]). This research hopes to find out the differences in eye movement interactions during the players’ operation of the game, and find out the differences between the player’s viewing position and the game consciousness during the game through eye tracking (Cho in Int J Med Informatics 129:366–373, 2019 [2]) technology. This research mainly uses multiplayer online battle arena games as the experimental platform. From the game process and game videos, we compare the eye movements of novices and experienced players. In this study, by wearing an eye tracker, and using eye tracking technology to capture eye movement paths, collect eye movement areas of interest, and analyze the heat map, data comparison and analysis of data differences. This study is mainly divided into two categories, namely 1. The difference in viewing positions of players with different degrees of the same movie, and 2. The difference in viewing positions of players with different degrees in actual game operations. Through the above two experimental results, it can be found that there is a significant difference between the novice and veteran eye movements.
RECORD THE TRANSCRIPT OF STUDENT ACTIVITY IN HIGHER EDUCATION BASED ON BLOCKCHAIN TECHNOLOGY

Apart from the core competency, learning in the organization also brings students opportunities to improve their soft skills.Good soft skills can help students when working in a company with many people.Students can get soft skills by participating in various non-academic activities such as new student orientation, Student organization, seminar, and workshop.For every non-academic activity participated by students, they will get points and recorded in Student Academic Transcript (SAT).SAT is an integral part of a diploma certificate.The research method used in this research is a user-centered design to build an education value chain model for recording student activity transcripts based on blockchain technology.Blockchain technology is used to ensure data validity, reliability, and integrity for all student non-academic activities.
Temporal Minimal-World Query Answering over Sparse ABoxes

Abstract Ontology-mediated query answering is a popular paradigm for enriching answers to user queries with background knowledge. For querying the absence of information, however, there exist only few ontology-based approaches. Moreover, these proposals conflate the closed-domain and closed-world assumption and, therefore, are not suited to deal with the anonymous objects that are common in ontological reasoning. Many real-world applications, like processing electronic health records, also contain a temporal dimension and require efficient reasoning algorithms. Moreover, since medical data are not recorded on a regular basis, reasoners must deal with sparse data with potentially large temporal gaps. Our contribution consists of two main parts: In the first part, we introduce a new closed-world semantics for answering conjunctive queries (CQs) with negation over ontologies formulated in the description logic $${\mathcal E}{\mathcal L}{{\mathcal H}_ \bot }$$ , which is based on the minimal canonical model. We propose a rewriting strategy for dealing with negated query atoms, which shows that query answering is possible in polynomial time in data complexity. In the second part, we extend this minimal-world semantics for answering metric temporal CQs with negation over the lightweight temporal logic and obtain similar rewritability and complexity results.
Guidance and Counseling Record Management System

The developed Record Management System for Guidance and Counseling Center of the Nueva Ecija University of Science and Technology aimed to provide software application that will manage the recordof student and provides fast and easy access of personal information of students. The functions focused in adding and updating students’ information/profile by using the application. The user can produce a printed copy of the record of student. The development of the Record Management System underwent the phases for System Development Life Cycle (SDLC) such as: Stage 1 –Planning; Stage 2 –Analysis; Stage 3 –Design; Stage 4 –Coding; Stage 5 –Testing; Stage 6-Implementation; and Stage 7 –Maintenance.The system took three months to be developed was accomplished using Visual Basic 2017 programming language and Microsoft SQl Server 2017 database. Record Management Systemhas been strongly accepted by the respondents based on their assessment on these five criteria: functionality, usability, efficiency, portability,and security. The suggestions given by the group of respondents may be considered for future enhancement of the system.
Development of Indian Spoken Language Identification System for Two Languages using MFCC Feature with Deep Neural Network

Language is the ability to communicate with any person. Approximate number of spoken languages are 6500 in the world. Different regions in a world have different languages spoken. Spoken language recognition is the process to identify the language spoken in a speech sample. Most of the spoken language identification is done on languages other than Indian. There are many applications to recognize a speech like spoken language translation in which the fundamental step is to recognize the language of the speaker. This system is specifically made to identify two Indian languages. The speech data of various news channels is used that is available online. The Mel Frequency Cepstral Coefficients (MFCC) feature is used to collect features from the speech sample because it provides a particular identity to the different classes of audio. The identification is done by using MFCC feature in the Deep Neural Network. The objective of this work is to improve the accuracy of the classification model. It is done by making changes in several layers of the Deep Neural Network.
BEHAVIORAL PROGRAMMING WITH A SUBSET OF NATURAL LANGUAGE: AN EVALUATION STUDY

We consider the idea of behavioral programming by writing controlled natural language requirements, which are then compiled directly into executable code.Our motivation is to bridge the gap between system requirements and a final system.We claim that formal structured natural language requirements can serve as the means and the end to programming the behavior of reactive systems, if one utilizes a fully executable language that supports story-like sentences, such as live sequence charts (LSC).We use natural language processing methods combined with user interaction in order to understand English requirements, and translate them into LSCs, disambiguating and clarifying intentions with the user when necessary.We test a multi-modal user interface we term show & tell, where natural language is interspersed with play-in, and model-based co-reference resolution.Our approach is domain general and builds the underlying model of the system leading to direct execution.The paper presents novel evaluation studies that show its potential as an effective tool for natural language programming of reactive system behavior.
Teaching Method of Folk Music Appreciation in the Music Appreciation Course for International Students in China

North China University of Water Conservancy and Hydropower has resumed the recruitment of international students since 2016.There are currently 370 enrolled students, including 295 undergraduates, 55 masters, and 20 doctors.There are 29 graduates.According to the number of registered foreign students in the province, the school is now ranked fourth in the province.The countries of origin for enrolled international students are mainly Morocco, Pakistan, Uzbekistan, Kyrgyzstan, Russia, Zambia, Bangladesh, Zimbabwe, Tanzania, Ethiopia, Indonesia, Belarus, Peru, Mongolia, Ukraine and other 23 "Belt and Road" routes nation.The author mainly used the three well-known musical instruments of Hulusi, Guzheng and Erhu to enter the classroom of international students as examples: in the 2020 autumn semester "China Overview" course, 2 hours of folk music appreciation related content was opened for international students; in the spring semester of 2021 The business Chinese major "Music Appreciation" offers 4 hours of folk music appreciation.
Modeling of Binary Logistic Regression in the Event of Childhood Diarrhea in Indonesia

Logistic regression or logit regression is a statistical technique used to create predictive modeling. To determine the logistic regression equation that will be used to predict the value of the dependent variable, parameter estimates must be sought in the logistic regression model, one of the methods in this study uses the maximum likelihood method. The 2017 Indonesian Demographic and Health Survey (IDHS) collected various information, including about toddler diarrhea. Therefore, the logistic regression method is the right method to use in this condition, considering that the diarrhea data collected in the IDHS are categorical data. In this study, the variables influencing toddler diarrhea werechild age, birth size (average),exclusive breastfeeding, maternal age, maternal education (high school), wealth index (top), and latrine facilities The results of the logistic regression analysis showed that the variable with the highest risk figure for reducing the diarrhea rate was wealth index (top) (OR=1,438).