Reviewerly/exHarmony huggingface dataset:
PENERAPAN MODEL PEMBELAJARAN THINK-TALK-WRITE (TTW) UNTUK MENINGKATKAN HASIL BELAJAR MATEMATIKA SISWA

The root of the research problem is that students' perceptions of mathematics tend to be negative, students' interest in learning is less because they can make money, teachers lack knowledge about learning models, so that the learning process tends to be monotonous, and student learning outcomes in mathematics are low. The type of research is Classroom Action Research (CAR), carried out in Class V UPT SPF SDN 105336 Rantau Panjang. Student learning outcomes before using the Think-Talk-Write (TTW) learning model: there were 21 students who scored in the incomplete category with an average value of 20.95. Furthermore, after using the Think-Talk-Write (TTW) learning model in the first cycle, the average student learning outcomes increased by 3 students (14.28%) in the complete category and 18 students (85.71%) in the incomplete category. In the first cycle it is considered not optimal because there are still many students who have not achieved the complete score and students look less active in learning. After making improvements, in the second cycle, student learning outcomes have increased. In the second cycle test results obtained an average of 80.95 with as many as 19 students (90.48%) in the complete category and 2 students (9.52%) in the incomplete category. The results of the observation are that the percentage of the success rate of teacher performance is 95.8%, the criteria are very good and student learning activities reach 75.9%, the criteria are sufficient. This shows that there is an increase in students' mathematics learning outcomes with the application of the Think-Talk-Write (TTW) learning model.
A Study on the Use Attributes of Watching Game: Focusing on the Relationship between Adolescent’s Motivation, Satisfaction and Intention to Use

본 연구는 청소년의 보는 게임 이용동기를 탐색하고, 이용만족 및 이용의도와의 영향 관계를 살펴보았다. 분석을 위해 청소년 274명을 대상으로 설문 조사하였다. 분석결과는 첫째, 청소년의 보는 게임 이용동기는 총 5개 요인이 추출되었으며, '정보 습득 동기', '사회관계/멀티태스킹 동기', '게이머/크리에이터 선호 동기', '도피/습관 동기', '대리만족/재미 동기'였다. 둘째, 대리만족/재미 동기는 보는 게임의 이용만족, 이용의도에 영향을 미쳤다. 셋째, 게임이용량에 따라 이용동기의 영향력에 차이가 있었다. 이 연구는 게임 시장의 활성화 요인을 탐색하고, 성인과는 다른 청소년만의 게임 이용심리를 분석했다는 점에서 연구의 의의가 있다. This study explored the motivation for adolescents to watching games and analyzed the relationship between motivation, satisfaction, and intention to use. The study surveyed 274 middle and high school students, and the results of the analysis are as follows. First, five motivations for adolescents to watching games were extracted: 'Acquire Information', 'Social Relations/Multitasking', 'Gamer/Creator Preference', 'Escape/Habit', and 'Vicarious Satisfaction/Fun'. Second, 'Vicarious Satisfaction/Fun' motivation influenced the satisfaction and the intention to use of game. Lastly, Groups based on usage showed differences in motivation. The findings could be used as data to explore the factors of adolescents's game motivation and viewed the game markets.
Logical constants in abstract frameworks and A Note on Logicality of Generalized Quantifiers

Abstract Logical Constants&#x0D; A possibility of defining logical constants within abstract logical frameworks is discussed, in relation to abstract definition of logical consequence. We propose using duals as a general method of applying the idea of invariance under replacement as a criterion for logicality.&#x0D; &#x0D; A Note on Logicality of Generalized Quantifiers&#x0D; This note follows up an earlier paper in which a possibility of defining logical constants within abstract logical frameworks was discussed, by using duals as a general method of applying the idea of invariance under replacement as a criterion for logicality. In the present note, this approach is applied to the discussion on logicality of generalized quantifiers. It is demonstrated that generalized quantifiers are logical constants by this criterion.
Generalized Intensity-Dependent Multiphoton Jaynes–Cummings Model

In this chapter, we study the Jaynes–Cummings model under multiphoton excitation and in the general case of intensity-dependent coupling strength given by an arbitrary function f. The Jaynes–Cummings theoretical model is of great interest to atomic physics, quantum optics, solid-state physics, and quantum information theory with several applications in coherent control and quantum information processing. As the initial state of the radiation mode, we consider a squeezed state, which is the most general Gaussian pure state. The time evolution of the mean photon number and the dispersions of the two quadrature components of the electromagnetic field are calculated for an arbitrary function f. The mean value of the inversion operator of the atom is also calculated for some simple forms of the function f.
Digital Certificate System for Verification of Educational Certificates Using Blockchain

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Design of Chatbot System for College Website

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
THE INFLUENCE OF SCRABBLE GAME TOWARDS VOCABULARY MASTERY FOR YOUNG LEARNERS (STUDY CASE IN AL-IRSYAD QURAN HOUSE LAPPA)

This research aims to know the influence of the application of the Scrabble game in learning English to know the increase in the vocabulary of the Al-Irsyad Quran House Lappa using the Scrabble game. The researchers use the quantitative methods, through techniques random sampling and focused on one group. The type of research is pre-experimental design. Through the application of pre-test and post-test designs. The instrument used in this research is a short objective test with a total of 10 items that have been randomized through content validity because the preparation of the instrument is adjusted to the material taught to students. Students experienced a significant increase in the vocabulary category as evidenced before the pretest, more students were included in the Enough category as many as 11 students or 44%, while in Excellent and Very good categories, there were only 2 students each who proved their vocabulary mastery was still low. After applying the Scrabble game, students experienced an increase, it can be seen in the Insufficient category that there were no more students who got a score of 60. This increased in the Excellent and Very Good categories which initially only 2 students, after the post-test the Excellent category was 11 students or (44% ) funds in the Very Good category were 7 students (28%) of 25 students.&#x0D;
Real-Time Face Mask Detection

After the breakout of the worldwide pandemic COVID-19, there arises a severe need of protection mechanisms, face mask being the primary one. According to the World Health Organization, the corona virus COVID-19 pandemic is causing a global health epidemic, and the most successful safety measure is wearing a face mask in public places. Convolutional Neural Networks (CNNs) have developed themselves as a dominant class of image recognition models. The aim of this project is to use machine learning capabilities for detecting and recognize face masks worn by people in any given video or picture or in real time. This project develops a real-time, GUI-based automatic Face detection and recognition system. It can be used as an entry management device by registering an organization's employees or students with their faces, and then recognizing individuals when they approach or leave the premises by recording their photographs with faces. The proposed methodology makes uses of Principal Component Analysis (PCA), Face Net, LBPH Face detection Algorithm and HAAR Cascade Algorithm. Based on the performance and accuracy of our model, the result of the binary classifier will be indicated showing a green rectangle superimposed around the section of the face indicating that the person at the camera is wearing a mask, or a red rectangle indicating that the person on camera is not wearing a mask along with face identification of the person. Once the Algorithm Identified the face it will send a text message to the recognized person to wear a mask and save the record.
Sewing DEI Into the Fabric of the Geosciences

AGU journals host a new living special collection on diversity, equity, and inclusion in the geosciences and invite additional contributions to grow this collection.
Scene Semantic Anomaly Detection of Multi-Sensor in Autonomous Driving

Abstract Autonomous driving is an outstanding representative of artificial intelligence, and while it has unlimited opportunities, it also faces unprecedented challenges. The potential risks of autonomous vehicles cause a significant threat to our current traffic system. Multi-sensor data in autonomous vehicles will form scene semantics. When sensors are intruded, however, discordant elements of scene semantics will appear. Anomaly detection of scene semantics can improve the robustness of intrusion detection systems for autonomous driving. In this paper, we proposed a method for scene semantic anomaly detection. We obtain the scene semantic representation by performing a semantic-level fusion of sensor data. Then, to achieve a scene semantic anomaly detection, convert abnormal semantic detection to out-of-distribution detection. To test the effectiveness of our method, we performed experiments on a publicly available dataset of autonomous driving.
Preface of the Multilingual Intelligent Information Processing Dataset

Preface of the Multilingual Intelligent Information Processing Dataset
A Study on Student’s Perception and Subject Development Direction for History Electives in the Expansion of Subject Selection Right - Focusing on the Case of D High School, a Leading High School Credit System -

In the context of rapidly changing educational environment, the Department of History is facing various difficulties. One is that students do not choose history subjects, and the other is that history departments are at a disadvantage in the curriculum organization.BR To solve the former problem, we will need to know why students don’t choose history subjects. Therefore, a survey was conducted to find out the students’ perception of the history elective subject. The subjects of the survey were 349 students in the first and second grades of D High School, a leading high school credit system. After preparing a questionnaire through a preliminary survey, the main questionnaire was conducted, and the questionnaire was divided into groups according to the learning conditions of the students.BR As a result, first, the biggest reason that students do not choose history subjects is because they perceive history subjects as too many and difficult. Second, as the number of students taking history subjects decreased due to this perception, it became disadvantageous for their grades, creating a vicious cycle in which more students did not choose history subjects. Third, although few students chose history, they thought that more students wanted to learn history and should learn it. It was confirmed that it was necessary to improve the problems while maintaining the charm of the history subject itself.BR In order to overcome the difficulties faced by the history department, the following elective subjects should be developed. First, it is necessary to deal with the contents derived from the basic contents while maintaining the original nature of the subject. Second, it should be composed of content that students want to learn and the teacher’s expertise can be demonstrated, rather than guiding students’ choices with easy and concise content.
A subset of Chinese-Mongolian and Uyghur-Chinese speech translation dataset aided by machine translation

At present, there are few public datasets for speech translation, especially those between Chinese and other low-resource languages. The development of end-to-end speech translation is limited by resources. In light of the research idea of international speech translation datasets, in this paper, we used the public speech recognition datasets (AISHELL and THUYG-20) to convert them into speech translation datasets through machine translation. After data processing, they were reviewed and verified by experts, so as to obtain high-quality speech translation datasets. The dataset includes Chinese-Mongolian speech translation dataset and Uygur-Chinese speech translation dataset, and the audio sampling rate is 16 kHz. The Chinese-Mongolian speech translation subset contains 1,919 items with a size of 238 MB. The Uygur-Chinese speech translation subset contains 3,692 samples with a size of 652 MB. This dataset can be used for the research on end-to-end speech translation, and provide data support for exploring the speech translation between Chinese and minority languages. As the dataset has been reviewed and verified by experts, it can also be combined with speech recognition dataset to study machine translation.
Demo: Automated Micro-Activity Annotations for Human Activity Recognition with Inertial Sensing

This demo presents AmicroN which automatically generates fine-grained annotations using locomotive signatures. In the backend, AmicroN exploits short-duration macro labels already present in a pre-annotated dataset. It uses zero-shot learning to identify the finer micro-activities present within a coarse-grain macro-activity label.
Penerapan Arsitektur Enterprise Berkelanjutan Untuk Perusahaan Sistem Integrator Teknologi Informasi

&lt;p&gt;&lt;strong&gt;Abstrak.&lt;/strong&gt; Keberadaan perusahaan sistem integrator teknologi informasi yang menyediakan solusi &lt;em&gt;Internet of Thing&lt;/em&gt; (IoT) semakin memegang peranan penting untuk memenuhi kebutuhan inisiatif transformasi digital yang dilakukan di pelanggan sektor swasta dan pemerintahan. Karakteristik tiap pelanggan sangatlah berbeda satu sama lainnya, sehingga diperlukan perusahaan sistem integrator yang mempunyai keunggulan dalam hal kustomisasi sistem, baik sistem &lt;em&gt;hardware&lt;/em&gt;, &lt;em&gt;software, firmware&lt;/em&gt;, dan jasanya. Tujuan penelitian ini adalah mendapatkan perencanaan arsitektur &lt;em&gt;enterprise&lt;/em&gt; perusahaan sistem integrator teknologi informasi dengan spesialisasi solusi &lt;em&gt;Internet of Thing&lt;/em&gt;, dengan menggunakan pendekatan model &lt;em&gt;canvas&lt;/em&gt; dan &lt;em&gt;framework&lt;/em&gt; TOGAF (&lt;em&gt;The Open Group Architecture Framework&lt;/em&gt;) ADM (&lt;em&gt;Architecture Develoment Method&lt;/em&gt;). Kajian arsitektur &lt;em&gt;enterprise&lt;/em&gt; dilakukan secara menyeluruh termasuk aspek bisnis, aplikasi, informasi, teknologi, manajemen perubahan, dan &lt;em&gt;opportunities and solutions&lt;/em&gt;. Hasilnya bidang bisnis ini memiliki arsitektur &lt;em&gt;enterprise&lt;/em&gt; yang berkelanjutan, dan mempunyai keunggulan kompetitif.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Kata kunci&lt;/em&gt;&lt;/strong&gt;&lt;strong&gt;&lt;em&gt;:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; Arsitektur enterprise; TOGAF; Sistem Integrator; Internet of Thing&lt;/em&gt;&lt;strong&gt;&lt;em&gt; &lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; The existence of an information technology system integrator company that provides Internet of Thing (IoT) solutions has important role to address digital transformation initiatives carried out by private sector and government customers. The characteristics of each customer are very different from each other, so a system integrator company need to do system customization, on system hardware, software, firmware, and services. The purpose of this study to obtain an enterprise architecture plan for information technology system integrator company specializing in Internet of Thing solutions, using the canvas model approach and the TOGAF (The Open Group Architecture Framework) ADM (Architecture Development Method) framework. The study of enterprise architecture is carried out thoroughly including aspects of business, applications, information, technology, change management, and opportunities &amp;amp; solutions. As a result, this business has a sustainable enterprise architecture, and has a competitive advantage.&lt;/em&gt;&lt;/p&gt;&lt;strong&gt;&lt;em&gt;Key words:&lt;/em&gt; &lt;/strong&gt;&lt;em&gt;Enterprise Architecture; TOGAF; System Integrator; Internet of Thing &lt;/em&gt;
Orchestrating Heterogeneous Applications: Motivation and State of the Art

Abstract This chapter presents the motivation for SODALITE highlighting the difficulties faced by developers of complex applications when they need to deploy such applications in execution contexts where the usage of heterogeneous resources (HPC, Cloud and Edge) coexist. An overview of the state of the art to highlight gaps and open issues is also presented.
Automated vs. Manual Case Investigation and Contact Tracing for Pandemic Surveillance: Evidence from a Stepped Wedge Cluster Randomized Trial

Background: Case investigation and contact tracing (CICT) is an important tool for communicable disease control, both to proactively interrupt chains of transmission and to collect information for situational awareness. We run the first randomized trial for COVID-19 CICT to investigate the utility of manual (i.e., call-based) vs. automated (i.e., survey-based) CICT for pandemic surveillance.Methods: Between December 15, 2021 and February 5, 2022, a stepped wedge cluster randomized trial was run in which Santa Clara County ZIP Codes progressively transitioned from manual to automated CICT. Eleven individual-level data fields on demographics and disease dynamics were observed for non-response. The data contains 106,522 positive cases across 29 ZIP Codes.Findings: Automated CICT reduced overall collected information by 29 percentage points (SE = 0.08, p < 0.01), as well as the response rate for individual fields. However, we find no evidence of differences in information loss by race or ethnicity.Interpretations: Automated CICT can serve as a useful and cost-effective alternative to manual CICT, with no substantial evidence of skewing data along racial or ethnic lines, but manual CICT improves completeness of key data for monitoring epidemiologic patterns.Funding: This research was supported in part by the Stanford Office of Community Engagement’s seed funding and Stanford’s Institute for Human-Centered Artificial Intelligence. No study sponsors were involved in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.Declaration of Interest: The authors declare no competing interest.Ethical Approval: This study examined COVID-19 case investigation and contact tracing data from existing databases used by public health jurisdictions. The Santa Clara County Public Health Department and Stanford University, Stanford, California, deemed the work public health surveillance; the Revised Common Rule deems “public health surveillance activities” not subject to IRB oversight under 45 CFR § 46. Thus, it was not submitted for IRB approval, but was subjected to privacy and compliance review by Santa Clara County
Dual-Image Reversible Information Hiding Scheme Using Staggered Turtle Shells

This paper proposed a two-image real-time and reversible data hiding method based on the staggered turtle shell concealment technology. First, the dual-turtle shells are continuously staggered on the diagonal of a reference matrix. The embedding rules are developed to conceal confidential message accordingly. The experimental results show that the time that our proposed method takes to build the reference matrix, and embed secret information is faster than other TS-based dual-image data hiding schemes. Moreover, the scheme is simple and maintains certain good performance.