Reviewerly/exHarmony huggingface dataset:
A Novel Scheme for Improving Accuracy of KNN Classification Algorithm Based on the New Weighting Technique and Stepwise Feature Selection

K nearest neighbor algorithm is one of the most frequently used techniques in data mining for its integrity and performance. Though the KNN algorithm is highly effective in many cases, it has some essential deficiencies, which affects the classification accuracy of the algorithm. First, the effectiveness of the algorithm is affected by redundant and irrelevant features. Furthermore, this algorithm does not consider the differences between samples, which led the algorithm to have inaccurate predictions. In this paper, we proposed a novel scheme for improving the accuracy of the KNN classification algorithm based on the new weighting technique and stepwise feature selection. First, we used a stepwise feature selection method to eliminate irrelevant features and select highly correlated features with the class category. Then a new weighting method was proposed to give authority value to each sample in train dataset based on neighbor categories and Euclidean distances. This weighting approach gives a higher preference to samples that have neighbors with close Euclidean distance while they are in the same category, which can effectively increase the classification accuracy of the algorithm. We evaluated the accuracy rate of the proposed method and analyzed it with the traditional KNN algorithm and some similar works with the use of five real-world UCI datasets. The experiment results determined that the proposed scheme (denoted by WAD-KNN) performed better than the traditional KNN algorithm and considered approaches with the improvement of approximately 10% accuracy.
PEE Based Reversible Watermarking Algorithm for Authentication and Security of Medical Images

This paper proposes an added security feature for medical image application with Prediction Error Expansion (PEE) based Reversible Watermarking (RW) technique. The key (Private) acts as security parameter and the authentication is accomplished through watermarking. This algorithm can be implemented for security of medical images like USG, MRI, CT scan and x-ray. The patient details, diagnosis summary or some other information can be embedded in the above-mentioned medical images to provide security. Doctors or any authorized person can decode the image using private key and identify the feature. The implementation is done in MATLAB and the results are validated. The results obtained are encouraging for the proposed medical image security application.
The Research on Data Acquisition and Analysis Platform for Lathe Machine based on Stream Computing

Abstract Manufacturing industry is the main body of national economy, the foundation of building a country, the tool of rejuvenating a country and the foundation of a strong country. Lathe machine is the basis of manufacturing industry, which determines the level of intelligent manufacturing industry. This paper uses the real-time processing characteristics of stream computing to build a data acquisition and analysis platform for lathe machine. This platform monitors the efficiency of the equipment in real time, improve the utilization rate of the equipment, and improve the processing efficiency. The platform collects data in real time, analyses the data, and tracks the efficiency and process of the process, which is of great significance to optimize the process and improve production management.
Listening Skills Teaching Practice at Secondary Level: Gondar Secondary Schools in Focus

The objective of this study was to assess the exercise of teaching listening skill at general secondary schools found in Gondar city. Thus, adopting descriptive survey design, a total of 115(male=90 &amp; female=25) English language teacher who taught grade 9 students participated in the study. The study used both quantitative and qualitative data. The quantitative data were collected through structured questionnaire whereas the semi-structured interview was used to collect the qualitative data. Data analysis was undertaken using quantitative and qualitative techniques. Quantitatively, frequency and percentage were used whereas thematic analysis was used for analyzing the qualitative data. Findings show that the majority of English language teachers use the bottom-up approach during the teaching of the listening skill. Findings also show that English language teachers failed to properly and fully implement the pre, while and post listening activities. Findings also show that teachers’ emphasis on grammar, teachers’ preference to explanation and demonstration than to create students listening opportunities, teachers’ preference to teacher-centered approach, teachers’ reluctance to provide students opportunities to exercise listening were some of the challenges facing the class room exercise of teaching the listening skill. Finally, it is recommended that English language teachers should clearly understand and properly exercise the pre, while and post-listening activities in the process of teaching the listening skills. Moreover, practical in-service trainings on how to teach listening skill should be given to teachers&#x0D;
The challenge of data-driven requirements elicitation techniques : Systematic Literature Review a Controlled Experiment

Background. Nowadays, Requirements Engineering(RE) focuses not only the pri- mary stakeholders but also large scale data, which comes from an amount of cus- tomers’ operations and feedback. For ins ...
Word Embedding by Unlinking Head and Tail Entities in Crime Classification Model

Word embedding is one of the natural language processing. It is designed to represent the entities and relations with vectors or matrix to make knowledge graph model. Recently many related models and methods were proposed, such as translational methods, deep learning based methods, multiplicative approaches. We proposed an embedding method by unlink the relation of head and tail entity representation when these two are the same entity. By doing so, it can free the relation space thus can have more representations. By comparing some typical word embedding algorithms and methods, we found there are tradeoff problem to deal with between algorithm’s simplicity and expressiveness. After optimizing the parameter of our proposed embedding method, we test this embedding on the HMN model, a model used to generate auto-judge system in the law area. We carefully replaced the encoder part of the model using our embedding strategy, and tested the modified HMN model on real legal data set. The result showed our embedding method has some privileges on performance.
Simple and fast derandomization from very hard functions: Eliminating randomness at almost no cost.

Extending the classical “hardness-to-randomness” line-of-works, Doron, Moshkovitz, Oh, and Zuckerman (FOCS 2020) recently proved that derandomization with near-quadratic time overhead is possible, under the assumption that there exists a function in DTIME[2n] that cannot be computed by randomized SVN circuits of size 2(1−є)· n for a small є. In this work we extend their inquiry and answer several open questions that arose from their work. For a time function T(n), consider the following assumption: Non-uniformly secure one-way functions exist, and for δ=δ(є) and k=kT(є) there exists a problem in DTIME[2k· n] that is hard for algorithms that run in time 2(k−δ)· n and use 2(1−δ)· n bits of advice. Under this assumption, we show that: 1. (Worst-case derandomization.) Probabilistic algorithms that run in time T(n) can be deterministically simulated in time n· T(n)1+є. 2. (Average-case derandomization.) For polynomial time functions T(n)=poly(n), we can improve the derandomization time to nє· T(n) if we allow the derandomization to succeed only on average, rather than in the worst-case. 3. (Conditional optimality.) For worst-case derandomization, the multiplicative time overhead of n is essentially optimal, conditioned on a counting version of the non-deterministic strong exponential-time hypothesis (i.e., on #NSETH). Lastly, we present an alternative proof for the result of Doron, Moshkovitz, Oh, and Zuckerman that is simpler and more versatile. In fact, we show how to simplify the analysis not only of their construction, but of any construction that “extracts randomness from a pseudoentropic string”.
An Investigation on the Effectiveness of OpenCV and OpenFace Libraries for Facial Recognition Application

The complexity and applicability of facial recognition in the growing domains of security and authentication, payment, advertising and health care have accelerated the research and development of this niche in the artificial intelligence (AI) field. A facial recognition system utilizes technologies to recognize a human face through mapping of distinct facial features from raw data such as photography and video to information of known faces stored in the database. Recognizing faces in real-world images is a challenging task. Generally, a facial recognition system involves multiple processes such as facial detection, feature extraction, face matching and confidence scoring in which various techniques and algorithms are available in the form of libraries and frameworks. In this paper, an investigation is conducted using two pipelines to identify the effectiveness of two prevalent open-source libraries, OpenCV and OpenFace, on real-time face recognition system. In the OpenCV pipeline, Viola –Jones algorithm is chosen for face detection, while feature extraction is conducted using local binary pattern histogram (LBPH). Face detection is performed using dlib, while feature extraction is conducted using deep learning algorithm in the OpenFace pipeline. Performance measures of both pipelines are evaluated using Labelled Faces in the Wild (LFW) as a benchmark data set. In addition, a locally populated data set consisting of images of personnel who are given access to the office door system is used to experiment on the applicability of these pipelines on real streaming data. OpenFace achieved an AUROC of 0.98, while OpenCV scored 0.94. Both experiments inferred that facial recognition system with OpenFace pipeline outperforms OpenCV in all aspects of performance measures. Further development demonstrates the successful implementation of OpenFace pipeline to a functional prototype in replacing the manual door access control.
Healing the Digital Divide During the COVID-19 Pandemic

The COVID-19 pandemic has exposed the digital divide and inequalities among learners and compelled the need to reimagine how teachers and educators teach and support student learning no matter where they live or to what tools they have access [ ]they have not been able to participate to the same degree as their more privileged classmates Start With the Learners Teachers should begin with the following assumptions about their learners: * they may know much less about technology than the instructor;* they may have limited bandwidth and/or limited data on their phones;and * they do not own tech equipment like cameras, printers, and scanners [ ]learners may not have unlimited time to engage in coursework since they may have to share technology resources in their households There are also topicbased online resources for language learners (e g , Center for Language Study, 2020), reading (e g , PBS Teachers Lounge, 2020), and mathematics (e g , National Council of Teachers of Mathematics, 2020)
THE ROLE OF PEDAGOGICAL JOURNALS IN THE DEVELOPMENT OF MULTI-ETHNIC EDUCATION AND SCHOOLING IN SUBCARPATHIAN RUS

The article analyzes the role of pedagogical journals in the development of multiethnic education and schooling in Subcarpathian Rus (1919–1939). It has been proved that the pedagogical periodicals during the period under study were mainly initiated by the school department of the Civil Administration of Subcarpathian Rus, the Teachers’ Association of Subcarpathian Rus, the Pedagogical Society of Subcarpathian Rus, the Ukrainophile pedagogical society “Teacher Community”. It has been found out that the educational guidelines of publications depended not only on the state policy, but also on the ideology of public organizations that financed a particular journal as well as n the position of the chief editors. The pedagogical journals Uchitel, Narodnaya Shkola, Podkarpatska Rus, Uchitelskii Holos, Nasha Shkola, Venochek dlia podcarpatskih detok, Nash rodnyy kray, Pcholka raised educational problems, fulfilling this important informative function, promoting the humanistic, moral, spiritual, multi-ethnic and democratic values of education. Almost every journal contained rubrics on the conditions and criteria of multicultural, national-patriotic, spiritual, and physical education. The articles discussed specific issues of education and upbringing, educational and methodological principles of education, a chronicle of the cultural and educational development of the region, etc. The specificity of educational journals in Subcarpathian Rus was their multilingualism: the overwhelming majority of articles were published in two or three languages – Rusinian, Czech and Hungarian, which made them accessible to a wide range of readers, facilitated the dialogue of cultures between representatives of different ethnic groups in the region.
Improved Collaborative Filtering Algorithm Based on Stacked Denoising AutoEncoders

With the rapid development of the mobile Internet, the increasing user data has brought about serious information overload. Recommendation system is a more effective solution to information overload. Collaborative filtering is one of the most widely used methods in recommendation systems. The traditional collaborative filtering algorithm performs the recommendation in terms of the rating matrix to calculate the similarity. While in most applications, the ratings of the users for the item is sparse, which leads to the issues of low recommendation accuracy and cold start. In addition, traditional collaborative filtering is based on the user’s historical behavior neglecting auxiliary information of users and items. For new users, it is impossible to accurately predict the preferences. In this paper, the Stacked Denoising AutoEncoder is integrated into collaborative filtering. The ratings and auxiliary information are taken as input, and two Stacked Denoising AutoEncoder are explored to learn the implicit representation of users and items respectively. Thus the similarity between users and items can be calculated to make score prediction. In addition, the weight factor is introduced to control the proportion of the two score predictions to improve the sparsity of collaborative filtering. Experiments are done on the MovieLens dataset, where the accuracy of the proposed algorithm is proved to be significantly improved compared with several mainstream algorithms.
A practical approach on non-regular sampling and universal demosaicing of raw image sensor data

Non-regular sampling is a well-known method to avoid aliasing in digital images. However, the vast majority of single sensor cameras use regular organized color filter arrays (CFAs), that require an optical-lowpass filter (OLPF) and sophisticated demosaicing algorithms to suppress sampling errors. In this paper a variety of non-regular sampling patterns are evaluated, and a new universal demosaicing algorithm based on the frequency selective reconstruction is presented. By simulating such sensors it is shown that images acquired with non-regular CFAs and no OLPF can lead to a similar image quality compared to their filtered and regular sampled counterparts. The MATLAB source code and results are available at: http://github. com/PhilippBackes/dFSR
비판적 미디어 리터러시 신장을 위한 한국어 교육 원리 연구 -중국인 학습자들의 미디어 텍스트 반응 양상을 사례로-

Through this research, it is intended to improve the critical media literacy of the Chinese by designing this educational scheme. In recent years, research on improving the media literacy of Chinese people has become increasingly important in response to the low media quality of Chinese people. To this end, firstly in this study the concept and extension of media literacy are examined, and secondly the relationship between media literacy and critical thinking is examined, based on that the concept of critical media literacy is redefined. At the same time, the new forms of literary works in the media age are identified. Using this as a contact, the two concepts of media literature and critical thinking have been re-linked. Through the discussion of the above concepts and relationships, the educational principles of critical media literacy are reorganized.To be more specifically, in this study, it is focused on the various media forms of Yoon Dong-Ju’s poetry and a educational scheme is designed aiming at improving Chinese media literacy. In this scheme the understanding process and appearance of Chinese learners are investigated. And hopefully through this scheme to grasp the process of Chinese learners’ understanding of diversified media texts and critical understanding of these media texts. Finally, through the above investigation, a critical media literacy teaching program suitable for Chinese people was designed. I hope this study can be used as a reference basis for future media literacy research, and also a new perspective and a way of thinking for Chinese students is provided by using Korean literary works as a medium. And it facilities the students to re-examine their media literacy, critically understand various media texts, and make their own critical value judgments in line with social values and ethical attitude.(Seoul National University)
A public key cryptosystem based on lattice matrices

In this paper, we have developed a public key cryptosystem by using large abelian group of general linear group over bounded distributive lattice. We have defined automorphisms on lattice matrices by the definition lattice automorphisms. We have replaced the exponentiation by conjugation automorphisms, which are mainly used to define the public and private keys and which allows the calculations to be fast and effective. We also talk about different security aspects against known attacks and it is shown that the cryptosystem is highly secure. We have given the proposed scheme with counter example.
PENGARUH KECERDASAN EMOSIONAL TERHADAP PERILAKU MENYIMPANG REMAJA DI DESA SILAM KECAMATAN KUOK KABUPATEN KAMPAR

This study discusses emotional intelligence for adolescents in Silam Village, Kuok Subdistrict, Kampar District. The purpose of this study was to study how emotional intelligence on families in Silam Village, Kuok District, Kampar District. The type of research used is descriptive quantitative research. The population subjects were 250 teenagers in Silam Village and a sample of 71 adolescent Cluster Random Sampling. The technique of collecting data using a questionnaire with a Likert scale. The data analysis technique in this study was carried out by simple linear regression analysis, and the processing in this study used the SPSS version 17.0 (Statistical Products and Services Solution) program for windows. The results showed a significant influence between emotional intelligence on adolescent behavior in the Silam Village, Kuok Subdistrict, Kampar District. Based on the hypothesis test (Significant Test), the Probability value of α is 0.05 ig sig (0.05 ≥ 0.00) which means Ha is accepted and Ho is rejected. Thus it can be denied that emotional intelligence is approved of adolescent behavior.
SOME PROBLEMS OF EDUCATION

In post-Soviet countries, reform of the education system has been launched. However, not all actions passed the necessary expert assessment. The reform can lead to a further stratification of the population, to a decrease in the teacher’s live communication with teachers, and weakening of educational work. The increased introduction of electronic technology in the educational process will have a negative impact on the health of students
Tackling Interactional Challenges in Social Robots: A Multimodal Conversation Analytic Approach

The field of social robotics has grown considerably in recent years and social and collaborative robots have entered the consumer market. However, communicative aspects such as timing of utterances ...
Application of Computer Virtual Reality Technology in College Sports Training

Abstract With the continuous development of social science and technology, the application of computers is more and more extensive. The application of computer "virtual reality" (hereinafter referred to as VR) technology in college physical education (hereinafter referred to as PE) training can enrich the content of PE classroom teaching, update classroom teaching methods, and improve the quality and efficiency of PE training teaching. However, in the process of practical application, there are still some problems to be solved.
DevelopmentofStudentWorksheets(LKPD)Basedon theScientificApproachonTheme8,ProudoftheAreaILiveinfor Class IV SDN 13 Surau Gadang Students

DEVELOPMENTOFSTUDENTWORKSHEETS(LKPD)BASEDONASYNTHIFICAPPROACHTHEME8MYPROUDOFMYAREAFORCLASSIVSTUDENTSOFSDNEGERI13SURAUGADANGABSTRACTThis study aims to produce StudentWorksheets (LKPD)based on ascientificapproachtogradeIVSDNegeri13SurauGadangstudentswhomeet valid criteria.This type of research is development research(ResearchandDevelopment).Thedevelopmentresearchmodelusedisthe4-Ddevelopmentmodel,whichconsistsofthestagesofdefine,design,developanddisseminate.Inthisstudy,ithasonlyreachedthedevelopingstagedueto timeconstraintsand theongoing Covid-19 outbreak.Theresearchinstrumentwasavalidationsheet.Inthevalidationprocess,thequestionnairevalidatorconsistedof5materialexperts,1designexpertand1linguist.IntheLKPDpracticum process,thequestionnairevalidatorconsisted of1 teacherand 6 students in the environmentwhere theresearcherslived.Basedontheresultsofthevalidationcarriedoutfromthematerialaspect,itwasobtainedanassessmentof82.89%,from thedesign aspectofthe assessmentof83.85%,the linguisticaspectwasassessedat94.16%.TheresultingLKPD wascategorizedasvalidbythevalidatorwithatotalaveragevalueof86.96%.Thepracticalityresultsfromtheaspectofteacherresponseobtained anassessmentof97.5%,andfrom theaspectofstudentresponseobtainedanassessmentof90.83%.Theresulting LKPD wascategorized asverypracticalbyteachersandstudentswithatotalaveragescoreof94.16%.ThusitcanbeconcludedthattheresultingLKPDbasedonascientificapproachforgradeIVSDcanbeusedasalearningresourceorteachingmaterialforbothstudentsandteachers.Keywords:Development,LKPD,Scientif
한국어 교재의 피동사 목록 선정과 제시

This study suggested the selection criteria for lists of passive verbs in ‘-i/hi/li/gi-’ passive units in Korean language textbooks, based on the passive verb lists appropriate for the criteria by stage proposed in this study. In addition, this study conducted a comparative analysis of the lists of this study with the lists of passive verbs included in passive units. As a result, a variety of teaching-learning problems were identified, including a simultaneous presentation of multiple passive verbs of diverging characteristics in the passive unit. In order to solve this problem, this study argues that the similarities, differences, and characteristics of passive verb sentences composed of the passive verbs must be considered when selecting and presenting passive verbs. In addition, as the selection criteria for passive verbs, the infinitive form and its characteristics of a passive verb are utilized. Also, by emphasizing the existence of agent subject realization, passive verbs of passive verb sentences where an agent subject is realized with ‘-ege’ are presented first, followed by passive verbs of passive verb sentences where an agent subject is not realized with ‘-ege’. As such, educational measures should group together passive verbs with commonality in sentence structures for presentation and explain common sentence structures in creating a passive verb sentence with passive verbs of the pertinent group. A textbook that presents explicit rules as such will help students develop a clear and better understanding of the goal of grammar for passive verbs. (Soongsil University)