Reviewerly/exHarmony huggingface dataset:
SISTEM INFORMASI PENDAFTARAN CALON TENAGA KERJA INDONESIA (TKI) PADA KANTOR CABANG PT. PUTRA JABUNG PERKASA

The development of Information Technology is very fast, has a positive impact on all current information services, in particular the delivery of information to the PT Putra Jabung Perkarsa branch office, especially the submission of information on the registration of prospective Indonesian Migrant Workers (TKI), where the registration process for prospective TKI is currently still using forms in the form of paper manually, while the enthusiasts to become TKI are currently increasing, but are constrained by the long registration process that requires a long queue time, people who are interested in becoming TKI must come to the location to register to become TKI by bringing complete data, then carry out manual filling of forms, employees of PT.Putra Jabung Perkasa process the applicant's files manually and provide recommendations to the prospective migrant workers in accordance with the objectives agreed upon by each prospective TKI. Seeing the above problems, the authors are interested in designing an information system to make it easier for programmers to build a registration system for future migrant workers, as for the system design that will be proposed, namely in terms of departure schedules, testimonials, checking TKI salaries, searching and storing data, will be structured and stored in a structured manner with the aim that at any time the data is needed it can easily be seen and used.
Domain Ontology Based Similarity and Analysis in Higher Education

Text Re-use is a process of creating documents using existing ones. Text reuse is a common fact and rises, For example, copying text from different sites or re-using text in free blogs. Submitting someone else’s work as your own, Cutting and pasting from sources without documenting, Media “borrowing” without documentation, Web publishing without permission of creators, Providing false documentation or data etc. Detecting text re-use has been studies in range of tasks and many applications. It is traditionally detected by computing similarity between contents as source text and possibly re-used text. Text similarity methods have been proposed for calculating similarity based on surface level or semantic features. But it is difficult to detect the similarity of text on concept bases. Conceptual similarity is silent problematic. Semantic based text re-use and its detection are receiving attention within the research community, where parts of certain source text has been re-used by using similar words or phrases. Ontology is explicit formal specifications of the terms in the domain and relations among them. Use of Ontologies for information extraction is common in information retrieval domain. These are limitedly used for concept mapping and extraction as well. To deal with cases of text re-use in which the text documents has been paraphrased. A DOBS (Domain Ontology Based Similarity) is proposed for detection of conceptual or topical similarity between two documents.
Scene classification using a combination of aerial and ground images

lt is undeniable that aerial images can provide useful information for a large variety of tasks, such as disaster relief, and urban planning. But, since these images only see the Earth from one point of view, some applications may benefit from complementary information provided by other perspective views of the scene, such as ground-level images. Despite a large number of public image repositories for both georeferenced photos and aerial images (such as Google Maps, and Street View), there is a lack of public datasets that allow studies that exploit the complementarity of aerial+ground imagery. Given this, we present two new publicly available datasets named AiRound and CV-BrCT. Using both, we tackled the scene classification task in 2 different scenarios. The first one has a fully-paired image set, while the second has missing samples. In both situations, we used deep learning and feature fusion algorithms. To handle missing samples, we proposed a content-based image retrieval framework.
Discovering 3D Parts From Image Collections

Reasoning 3D shapes from 2D images is an essential yet challenging task, especially when only single-view images are at our disposal. While an object can have a complicated shape, individual parts are usually close to geometric primitives and thus are easier to model. Furthermore, parts provide a mid-level representation that is robust to appearance variations across objects in a particular category. In this work, we tackle the problem of 3D part discovery from only 2D image collections. Instead of relying on manually annotated parts for supervision, we propose a self-supervised approach, latent part discovery (LPD). Our key insight is to learn a novel part shape prior that allows each part to fit an object shape faithfully while constrained to have simple geometry. Extensive experiments on the synthetic ShapeNet, PartNet, and real-world Pascal 3D+ datasets show that our method discovers consistent object parts and achieves favorable reconstruction accuracy compared to the existing methods with the same level of supervision.
KEMAMPUAN MENULIS TEKS PERSUASI OLEH SISWA KELAS VIII-5 SMP NEGERI 4 MEDAN TAHUN AJARAN 2019/2020

The results showed that the ability to write persuasive texts based on the aspect of issue recognition an average score of 71.7%, a series of arguments an average score of 74.16%, a statement of invitation an average score of 64.16%, reaffirmation an average score of 49 .6%, technical words score an average of 80.8%, and argumentative conjunctions score an average of 65.8%. So, the results show that grade VIII-5 students of SMP Negeri 4 Medan are categorized as sufficient in writing persuasive texts with the total average score of 66 and is in the sufficient category
An Investigation of EFL Students’ Anxiety towards Online English Learning in Paragraph based Writing Subject

This study aims to investigate the students’ anxiety related to the online English learning in writing subject as well as the factors that contribute anxiety during online learning, and exploring the students’ anxiety strategies in overcoming their anxiety for this study. One of private university in Cirebon was chosen as the site for this study. This study employed qualitative study with a case study design. Students’ anxiety from fourth semester in academic year 2019/2020 was chosen as the participant of this study. The data were collected through interview and questionnaire. This study discovered that students’ anxiety related to the English online learning is situation-specific anxiety, and the factors that contribute anxiety which can be group into four categories: being not familiar with the situation in, incompetence in learning, less English proficiency, no match with expectation. This study also identifies four category strategies employed by students’ anxiety: positive thinking, keep calm and enjoy it, self-confidence, and preparation. The findings of this study provide experiences for students about anxiety that can arise during online learning in unsupportive situation.&#x0D; Keywords: Anxiety; Types of Anxiety; Online Learning, Writing Skill; Paragraph Based Writing.
An Improved Method for Picking Up Microseismical P Waves for Earthquake Monitoring by Communication Signal

Accurate pickup of microseismic P waves when they arrive is a key link in microseismic monitoring and the basis and prerequisite for realizing microseismic source positioning. Based on the STA/LTA algorithm, an improved P wave arrival time picking algorithm is proposed. First, use STA/LTA to pick up the time ti of the same signal based on four different feature functions, use the minimum value min(ti) and maximum value max(ti) as the reference, and expand forward and backward by L/10 according to the signal length L. The sampling points form the pick-up time window M, and the AIC algorithm is used to pick up the accurate first arrival time of the signal under the pick-up time window M. Taking manual picking results as the benchmark, and comparing and analyzing the results of automatic picking using the AIC algorithm, the experimental results show that the improved algorithm improves the accuracy of picking up microseismic signals with high signal-to-noise ratio by 4% (the error within ±3ms is accurate picking) The accuracy of low signal-to-noise ratio signal pickup is increased by 16% (the error is within ±10ms for accurate pickup).
중국 대학의 창업교육이 예비창업자들의 창업효능감, 기업가정신 및 창업의지에 미치는 영향 -사천(四川)대학 학부생들을 중심으로-

Recently, to decrease high youth unemployment rate and promote sustained economic growth through creating new jobs in China. Various types of entrepreneurship education have been taking place in Chinese university due to governmental policy support and the number of entrepreneurship education in Chinese university has increased in quantity and the interest in realistic entrepreneurship education and improvement measures has been increasing.In this context, this study is to learn if and how entrepreneurship education carrying out in Chinese university influence entrepreneurial self-efficacy, entrepreneurship and entrepreneurial intention of potential entrepreneur in many ways.For this purpose, a research model and hypotheses are developed based on the relevant literature reviews. Data have been collected from university students who have completed entrepreneurship education in China and the empirical findings were tested by structural equation modeling analysis.The empirical findings are as follows: First, entrepreneurship education has not a positive effect on entrepreneurial intention, but a positive effect on entrepreneurial self-efficacy and entrepreneurship. Second, flow entrepreneurial self-efficacy has a positive effect on entrepreneurship. Third, entrepreneurial self-efficacy and entrepreneurship have a positive effect on entrepreneurial intention respectively. Finally, entrepreneurial self-efficacy and entrepreneurship have a mediating effect on the relationship between entrepreneurship education and entrepreneurial intention.Based on the results, this study a few significant implications having meaningful to Chinese entrepreneurship education, is expected to have contribution to the successful promoting entrepreneurial intention of potential entrepreneur in China.
Hybrid Technique on Image Clustering

Face recognition using FLD for extracting high dimensional images is introduced in this paper. The main purpose is to work on removing bugs and noise from the images and extract the facial expression applied on face descriptor. FLD is selected for increasing the discrimination information [17]. The main points of this paper give the brief knowledge about the face recognition and face clustering. Its shows how biometric terms help the local and global features for extracting information from database. Finding better solutions to deal with noise in face recognition is a challenging task [18]. We also performed some comparative analysis on various face recognition techniques. The main motive of this paper is to increase the recognition rate of the images and provide good efficiency. This method defines how the features and facial expression are extracted and all noise and bugs are eliminated to make a separate individual cluster of same known faces.
Penyembunyian Pesan Pada File Audio Menerapkan Metode Chineseremainder Theorem

Information which is the result of processing from data has a different value for each person. Often information becomes very valuable and not everyone is allowed to know it, but there are always parties who try to find out information in ways that are not supposed to even intend to destroy it. There are several methods in steganography, one of which is a method to hide secret messages (text or images) in other files containing text, images, and even audio without showing any real or visible changes in the quality and structure of the original file. . These methods include invisible ink, microdots, word management, digital signatures, hidden paths and wide spectrum communications. Chineses Reminder Theorem (CRT) is a concept based on congruent relationships. However, in contrast to congruence in general, this concept is based on a simultaneous congruence relationship. Simultaneous congruence refers to several congruent relationships that have a relationship with one another, and this relationship is related to the same variable value but with different modules. This theory is an ancient theory that is often used in cryptographic applications.
Special Aspects of Motivating Young People to Learn: Redistribution of Demand from Higher to Secondary Vocational Education [Особенности Мотивации Молодежи К Обучению: Перераспределение Спроса С Высшего На Среднее Профессиональное Образование]

The main factor influencing the professional personal identity of young people is the financial situation of their Households. Worsening financial situation of households forces a large part of 9th and 11th class graduates to continue their studies in the system of secondary vocational education (SVE) in order to quickly enter the labor market.
전복류(Genus Haliotis)의 분류를 위한 단일염기변이 기반 기계학습분석

Climate change is affecting the evolutionary trajectories of individual species and ecological communities, partly through the creation of new species groups. As population shift geographically and temporally as a result of climate change, reproductive interactions between previously isolated species are inevitable and it could potentially lead to invasion, speciation, or even extinction. Four species of abalone, genus Haliotis are present along the Korean coast-line and these species are important for commercial and fisheries resources management. In this study, genetic mark-ers for fisheries resources management were discovered based on genomic information, as part of the management of endemic species in response to climate change. Two thousand one hundred and sixty one single nucleotide poly-morphisms (SNPs) were discovered using genotyping-by-sequencing (GBS) method. Forty-one SNPs were selected based on their features for species classification. Machine learning analysis using these SNPs makes it possible to differentiate four Haliotis species and hybrids. In conclusion, the proposed machine learning method has potentials for species classification of the genus Haliotis. Our results will provide valuable data for biodiversity conservation and management of abalone population in Korea.
Hubungan Kemandirian Belajar Daring dengan Hasil Belajar IPS Siswa Kelas V SD Gugus V

The study is a correlational study that aims to determine whether or not there is a relationship between online learning independence and social studies learning outcomes for V th grade students of SD Cluster V East Tanete Riattang District Bone Regency. The population in this study were all V grade students of SD Cluster V East Tanete Riattang District, Bone Regency, while the number of samples in this study was 74 students. Data collection is done by providing questionnaires and documentation. The data analysis technique used in this research is descriptive statistical analysis and inferential statistical analysis. Based on descriptive statistical analysis data obtained online learning independence with an average of 110,42 and a percentage of 69,17% in the good category, and students social studies learning outcomes with an average of 78,53 and a percentage of 78,88% in the good category. The results of inferential statistical analysis obtained tcount ≥ ttable at the 5% significance level. Thus H 0 is rejected and H 1 is accepted. The conclusion in this study is that there is a significant relationship between learning independence and social studies learning outcomes for V th grade students of SD Cluster V East Tanete Riattang District Bone Regency.
Abandonment Behavior Detection Using Ganerative Advesarial Networks

Abandoned luggage items in public areas will be a potential threat caused by bombs or biological warfare. We present a method for real-time automatic detection of abandoned luggage in video captured by surveillance cameras. Most works for abandoned objects detection use a preliminary step to detect foreground regions or objects, and use various techniques including deep learning to distinguish between abandoned luggage items and other objects. These object detection-based methods require direct learning of characteristics of different types of objects. However, it is difficult to detect a new type of unlearned object, and there is insufficient detection of the instantaneous situation in which an object is abandoned. In order to solve these problems, we propose reconstruction-based anomaly detection to identify unusual patterns that do not conform to expected behavior such as abandoning objects. The approach is comprised of two stages - first, static object detection based on YOLOv4 and second, abandoned luggage recognition based on anomaly detection using Ganerative Advesarial Networks (GAN). We demonstrate the proposed GAN-based anomaly detection for abandonment behavior by performing experiments on Abnormal Event CCTV Video Dataset.
Exploring the Practice of Madani Super Camp (MSC) to Foster English Speaking Skill

This study was located at Madani Super Camp (MSC).  This research was conducted for the purpose of Exploring the Practice of Madani Super Camp (MS) to foster English Speaking Skill. This study employed descriptive qualitative method. The data were collected from observation, interview and documentation. The findings of this study revealed the learning outcomes, the activities to promote speaking skill, the activities to enrich the vocabularies and the learning assessment of the MSC program. The learning outcomes were based on the students' entrance level of English.  The activities to promote speaking skill included English day program, role play (through daily conversation, daily expression and morning puzzle), simulation (English speech, English contest, art show and master ceremony), storytelling and reporting. The activities to enrich the vocabularies were morning vocabularies, memorizing vocabularies and phrase, pamphlet and listening. The students' progress were assed through pair dialogue performance, and other mode of spoken test. Based on the findings of this study we suggest that the MSC should vary the speaking activities. It is also important to make the more specific learning outcomes for different level, so that the tutors could prepare the lesson more easily. Furthermore, the assessment should be integrated with that of international standard to ensure the test credibility.
Correction to: Conditional Action and Quantum Versions of Maxwell’s Demon

The article “Conditional Action and Quantum Versions of Maxwell’s Demon”, written by Heinz‑Jurgen Schmidt, was originally published electronically on the publisher’s internet portal on 30 September 2020 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 17 September 2021 to © The Author(s) 2020 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0 . The original article has been corrected.
On the Issue of Teaching Creative Writing to the Primary School Students

The purpose of the article is to determine the importance of teaching creative writing to younger schoolchildren. The urgency of the problem of teaching creative writing in the native Chuvash language is due to the need for the formation of text competencies in younger schoolchildren, the lack of formation of their native writing skills, especially creative writing. Material and methods of research. The main research methods were the study of literature, the analysis of teachers 'difficulties and errors in the students' works. A brief history of the issue is considered: the ideas of developing creative writing skills among foreign researchers: the most successful start of learning creative writing is 4-5 years old (M. Montessori), the need to believe in the creative abilities of a child (S. Frenet); leading domestic teachers: every child is born a potential writer (L. N. Tolstoy), the experiments of V. A. Sukhomlinsky and Sh. Amonashvili on composing fairy tales and stories by students, I. Ya. Yakovleva on teaching creative writing to students of the Chuvash Simbirsk school; the main provisions of the Chuvash linguodidacts: the support of written creativity on the development of oral speech (M. Ya. Sirotkin), on the observation of objects, phenomena (F. T. Timofeev), the need to study the structure and content of the text from the first grade (V. E. Efimov, I. V. Drozdov, L. P. Sergeev), the need to work on composing miniature texts in the native language lessons (D. S. Filippova). The main problems in teaching creative writing in the Chuvash primary school are highlighted. The assumption is made about the effectiveness of planning within the hours allocated to the native language, creative writing lessons. The results of the study. The purpose and tasks, features of the organization of creative writing lessons in grades 2-4 of Chuvash schools are described: it is recommended to conduct one lesson every two weeks, the main goal is the formation of a comprehensively developed language personality. The main directions, methods and forms of work: work on the content, structure of the text; on language tools, editing. It is concluded that the idea and provisions of the methods are accepted by teachers, and the lessons of creative writing are introduced into the practice of the Chuvash primary school.
SmartBark: An Automated Dog Barking Detection and Monitoring System using AI and Deep Learning

Dogs have the tendency to bark at loud noises that they perceive as an intruder or a threat, and the hostile barking can often last up to hours depending on the duration of such noise. These barking sessions are unnecessary and negatively impact the quality of life of the others in your community, causing annoyance to your neighbors [1]. Having the rights to file noise complaints to the Home Owners Association, potentially resulting in fines or even the removal of the pet [2]. In this paper, we will discuss the development of an algorithm that takes in audio inputs through a microphone, then processes the audio and identifies that the audio clip is dog barks through machine learning, and ultimately sends the notification to the user. By implementing our application to the everyday life of dog owners, it allows them to accurately determine the status of their dog in real-time with minimal false reports.