Reviewerly/exHarmony huggingface dataset:
METHODS OF MUSICAL AND RHYTHMIC EDUCATION OF PRESCHOOL CHILDREN WITH VISUAL DISABILITIES BASED ON PEDAGOGICAL SYSTEM OF KARL ORFF

The article reveals the methods of musical-rhythmic education of preschool children with visual disabilities on the basis of pedagogical system by Karl Orff in the process of musical lessons in kindergarten. This method includes the development of speech, figurative thinking, coordination of movements, the development of communication skills, emotionality and creativity of children with visual disabilities. The method provides different musical quests using simple literary text, that allows children to sing along with the teacher, thereby developing their speech; literary and musical images, displayed by various attributes, which children are able to understand, and also tasks for the development of children’s spatial coordination. The method involves different kinds of tasks, such as “Songs with replacement”, in which words are replaced by defined movements, aiming to develop coordination, attention and mind, as well as creative participation of all children in the execution of the musical composition. The tone of voice of the teacher, his manner of communication with children are of great importance along with the laws of perception: a) Tell me an I forget, b) Show me and I remember, c) Put me in the process and I understand.
Upaya Peningkatan Keaktifan Siswa melalui Metode Talking Stick pada Siswa Kelas III SDN Karanggedang

This study aims to determine whether the use of the talking stick learning model can increase student activity in the third grade thematic learning at SDN Karanggedang. The design used in this research is classroom action research which is carried out in two cycles. The results of research observations carried out showed an increase from cycle to cycle. Active learning in the first cycle got 58.45% in the less active category, in the second cycle it increased by 26.05%, which amounted to 84.5% in the very active category. The achievement for the implementation of learning by applying the talking stick model in the first cycle was 73% with a good category and in the second cycle it got 88.45% with a very good category, the achievement of student activity using the talking stick model is considered successful in reaching the limit of activity given, which is 80%.
Inductive learning for product assortment graph completion

Global retailers have assortments that contain hundreds of thousands of products that can be linked by several types of relationships like style compatibility, "bought together", "watched together", etc. Graphs are a natural representation for assortments, where products are nodes and relations are edges.Relations like style compatibility are often produced by a manual process and therefore do not cover uniformly the whole graph.We propose to use inductive learning to enhance a graph encoding style compatibility of a fashion assortment, leveraging rich node information comprising textual descriptions and visual data.Then, we show how the proposed graph enhancement improves substantially the performance on transductive tasks with a minor impact on graph sparsity.
Comparison of Translation Techniques by Google Translate and U-Dictionary: How Differently Does Both Machine Translation Tools Perform in Translating?

Better translation produced by computation linguistics should be evaluated through linguistics theory. This research aims to describe translation techniques between Google Translate and U-Dictionary. The study used a qualitative research method with a descriptive design. This design was used to describe the occurrences of translation techniques in both translation machine, with the researchers serving as an instrument to compare translation techniques which is produced on machine. The data are from expository text entitled “Importance of Good Manners in Every Day Life”. The total data are 122 words/phrases which are pairs of translations, English as source language and Indonesia as target language. The result shows that Google Translate apply five of Molina &amp; Albir’s (2002) eighteen translation techniques, while U-dictionary apply seven techniques. Google Translate dominantly apply literal translation techniques (86,8%) followed by reduction translation techniques (4,9%). U-dictionary also dominantly apply literal translation techniques (75,4%), but follows with the variation translation techniques (13,1%). This study showed that both machines produced different target texts for the same source language due to different applications of techniques, with U-dictionary proven to apply more variety of translation techniques than Google Translate. The researcher hopes this study can be used as an evaluation for improving the performance of machine translations.
Research on Teaching Mode of Building Architecture Based on Digital Technology

This paper analyzes the present situation of traditional teaching of building architecture and the problems existing in the process of reform.Based on the OBE output-oriented concept and aiming at cultivating excellent engineers, relying on the Virtual simulation Experiment Center of China University of Petroleum (East China), this paper explores the digital teaching mode of building architecture course, proposes the construction and integration measures of virtual module resource base, and discusses the assessment method based on virtual simulation +BIM.This paper analyzes the effects and advantages of the curriculum reform of building architecture, and shows that digital technology plays an important role in the teaching of building architecture.
PRIVACY IN ADVANCED CRYPTOGRAPHIC PROTOCOLS: PROTOTYPICAL EXAMPLES

Cryptography is the fundamental cornerstone of cybersecurity employed for achieving data confidentiality, integrity, and authenticity. However, when cryptographic protocols are deployed for emerging applications such as cloud services or big data, the demand for security grows beyond these basic requirements. Data nowadays are being extensively stored in the cloud, users also need to trust the cloud servers/authorities that run powerful applications. Collecting user data, combined with powerful machine learning tools, can come with a huge risk of mass surveillance or undesirable data-driven strategies for making profits rather than for serving the user. Privacy, therefore, becomes more and more important, and new techniques should be developed to protect personal information and to reduce trust requirements on the authorities or the Big Tech providers. In a general sense, privacy is ``the right to be left alone'' and privacy protection allows individuals to have control over how their personal information is collected and used. In this survey, we discuss the privacy protection methods of various cryptographic protocols, in particular we review: - Privacy in electronic voting systems. This may be, perhaps, the most important real-world application where privacy plays a fundamental role. %classical authentication with group, ring signatures, anonymous credentials. - Private computation. This may be the widest domain in the new era of modern technologies with cloud computing and big data, where users delegate the storage of their data and the computation to the cloud. In such a situation, ``how can we preserve privacy?'' is one of the most important questions in cryptography nowadays. - Privacy in contact tracing. This is a typical example of a concrete study on a contemporary scenario where one should deal with the unexpected social problem but needs not pay the cost of weakening the privacy of users. Finally, we will discuss some notions which aim at reinforcing privacy by masking the type of protocol that we execute, we call it the covert cryptographic primitives and protocols.
MONITORING KINEJA DOSEN :Manfaat Dan Dampaknya Terhadap Perguruan Tinggi

Monitoring Lecturer Performance: Benefits and Impact on Higher Education, this study aims to analyze Unpam Lecturer Performance Monitoring Based on the Tri Dharma of Higher Education, to find out how the impact of Unpam Lecturer Performance Monitoring, to find out how the impact of Unpam Lecturer Performance Monitoring. This type of research is an evaluative research using qualitative methods. The informants used in the research are informants who have been determined by the researchers, namely people who are authorized to convey the information. Data were collected by means of in-depth interviews, direct observation and document review. The research instruments used were interview guides, observation sheets, and documentation sheets. The results show that the performance of Pamulang University lecturers is quite good, there are only a few findings that must be improved, such as in terms of functional positions that need to be improved, lecturer certification needs to be achieved and research on grants for higher education needs to be maximized.
THE USE OF CARD SORT STRATEGY TO IMPROVE ESP STUDENTS’ READING COMPREHENSION AT UNIVERSITAS MUHAMMADIYAH SINJAI

This study aimed at investigating the effect of the use of card sort strategy on their reading comprehension. The method employed was true experimental design with pretest-posttest control groups design. The population of this study was the first semester students of Universitas Muhammadiyah Sinjai. The sample of this research consisted of 60 Animal Husbandry students of Universitas Muhammadiyah Sinjai. The researcher used cluster random sampling which 30 Students as control group and 30 students as experimental group. Two research instruments were used to collect the data in the study, namely card sort strategy and reading achievement test. The data were analyzed by using descriptive and inferential statistics on SPSS version 20 for windows program. The result of this study showed that there was a significant difference of the students’ reading comprehension achievement between experimental group and control group. The result of hypothesis testing using ANACOVA with SPSS for windows 20 program to get significance value is 0,000. The significance value 0.000 < α= 0,05, so hypothesis was tenable. These lead to the conclusion that using card sort strategy can improve the reading comprehension.Keywords: card sort strategies, reading comprehension
FORMATION OF RUSSIAN CIVIL IDENTITY: RESULTS OF SCHOOL STUDENTS 'SURVEY

The article examines the features of the development of society in the Russian state in interaction with the education in the young generation of feelings of civic identity. Researchers pay special attention to the issue of methods and ways of educating the young generation in modern conditions of society development, working out the possible results of mastering new tasks and courses set for teachers. The pedagogical tasks for teaching history and social studies have been determined: fostering a sense of civic identity in schoolchildren, studying the traditions, cultures and values of the peoples of the Russian State; unification of the Russian society and interaction for the favorable development of the country in the future. The problem of the formation of civic position, responsibility, social culture and socialization is considered as one of the main ones. The main conclusions and recommendations are made on the basis of studying the results of the questionnaire survey of schoolchildren in grades 10-11.
Exploration on the Construction and Teaching Reform of Introduction Course of Applied Chemistry

“Introduction to Applied Chemistry” is a theoretical core course for freshmen majoring in applied chemistry. The teaching of introduction to applied chemistry is helpful for freshmen to make clear their learning direction, guide the follow-up theoretical and practical teaching activities, and help students cultivate professional interest, so as to establish professional thinking, and realize comprehensive development. In this paper, the advantages of various new teaching modes are discussed.
The Role of Artificial Intelligence in Criminal Justice System with Special Reference to Forensic Science Investigation Techniques

Artificial Intelligence (AI) is the ability of a machine or computer programme to execute human-like skills like visual perception, speech recognition, cognitive reasoning, decision making, learning from experiences, and solving difficult problems at a faster rate and with fewer errors than humans. AI is a rapidly developing field that is also being used to advance forensic science and the justice system. In today's forensic science and criminal investigation environment, experts face numerous challenges due to large amounts of data, small pieces of evidence in a chaotic and complex environment, traditional laboratory structures, and sometimes insufficient knowledge, all of which can lead to investigation failure or miscarriage of justice. Artificial intelligence (AI) is the weapon of choice for combating these difficulties, which include machine learning and deep learning. In numerous domains of forensics, neural networks and case-based reasoning are used to produce errorless, objective, and repeatable conclusions. Data analysis, Pattern recognition, Image processing, Computer vision, Data mining, Statistical analysis and probabilistic methods, Artificial olfaction, Computational and mathematical methods, Graphical modelling are just some of the ways AI is assisting almost every major field of forensic science and criminal investigation. As a result, AI is assisting forensic specialists and investigators at all levels of investigation by constructing logical evidence, 3D reconstruction of crime scenes, handling evidence properly, and analyzing it to reach logical conclusions. AI-based algorithms can sift through massive amounts of data to find risk, and they're used to detect, prevent, and even forecast future crime or criminal conduct.
Hoax Classification Corona Virus (COVID-19) News in Indonesian using the Support Vector Machine (SVM) Method

The development of information technology more widely, rapidly and quickly provide convenience to the public in access information.Internet is a container or online media makes the information hasn't been verified or proved to be true which is rapidly spreading in the community.The purpose of this study is to facilitate in determining the hoax news or facts about corona virus in Indonesia and appoint the performance text mining classification with SVM algorithm.Stages The hoax classification process is carried out with the preprocessing then weighting is carried out using TF-IDF method and classified using the support vector machine algorithm then tested by cross validation and k-folds testing.The data used in this study consisted of 535 text message containing information about facts and news text 425 contains information on hoaxes.The results obtained on testing the highest accuracy to 7 on the k-fold 9 with accuracy of 83.82%.Thus, the SVM algorithm can be used in the classification of Corona Virus Hoax news or COVID-19.
A Framework for the Image Retrieval System Based on Histogram Normalization Technique with Python

The processing of multimedia content is used for real-world computer vision in various applications, and digital images make up a large part of multimedia data. The processing of multimedia content is used for real-computer vision in various applications, and digital images make up a large part of multimedia data. Content-based Retrieval of photographs (CBIR) is a system of picture recovery which utilizes the visual highlights of a picture, for example, shading, shape and surface so as to look through the client based inquiry pictures from the huge databases. CBIR relies upon highlight extraction of a picture which are the visual highlights and these highlights are extricated naturally i.e. without human collaboration. We intend in this paper to provide a detailed overview of recent developments related to CBIR and image representation. We researched the main aspects of various models of image recovery and image representation from low-level feature extraction to recent semantict ML approaches. And, for extraction of features, HSV, image segmentation and color histogram techniques are used, which effectively gives us the main point in an image that these techniques are used to minimize complexity, expense, and energy and time consumption. Then a machine learning model is trained for similarity test and the validation and texting phases are performed accordingly which leads to better performance as. Then a machine learning model is trained for similarity testing and then the validation and texting steps are performed accordingly, resulting in improved results compared to previously performed techniques. The precision values in the proposed technique are fairly excellent.
Research on E-learning Strategies to Cultivate Middle School Students' English Autonomous Learning Ability under the Background of "Internet+"

Autonomous learning is crucial to improve students' comprehensive ability. In the era of rapid development of the Internet, E-Learning has become one of the main ways for students to learn independently. This article will discuss the development strategies of middle school students' autonomous learning ability from the development of the concept of autonomous learning, the characteristics of students' learning in E-Learning, and how teachers guide middle school students to use E-Learning correctly.
LibGuides: Library Technologies: Ethernet Cables and student laptops

The aim of this libguide is the help students with accessing the library technologies, such as the computers, printers, etc.
ON THE USE OF MULTIPLE INSTANCE LEARNING FOR DATA CLASSIFICATION

In the multiple instances learning framework, instances are arranged into bags, each bag contains several instances, the labels of each instance are not available but the label is available for each bag. Whilst in a single instance learning each instance is connected with the label that contains a single feature vector. This paper examines the distinction between these paradigms to see if it is appropriate, to cast the problem within a multiple instance framework. In single-instance learning, two datasets are applied (students’ dataset and iris dataset) using Naïve Bayes Classifier (NBC), Multilayer perceptron (MLP), Support Vector Machine (SVM), and Sequential Minimal Optimization (SMO), while SimpleMI, MIWrapper, and MIBoost in multiple instances learning. Leave One Out Cross-Validation (LOOCV), five and ten folds Cross-Validation techniques (5-CV, 10-CV) are implemented to evaluate the classification results. A comparison of the result of these techniques is made, several algorithms are found to be more effective for classification in the multiple instances learning. The suitable algorithms for the students' dataset are MIBoost with MLP for LOOCV with an accuracy of 75%, whereas SimpleMI with SMO for the iris dataset is the suitable algorithm for 10-CV with an accuracy of 99.33%.
Self-Calibrated Convolutional Neural Network for SAR Image Despeckling

Synthetic aperture radar (SAR) images are contaminated by speckle noise, which has largely limited its practical applications. Recently, convolutional neural networks (CNNs) have indicated good potential for various image processing tasks. In this paper, we propose a self-calibrated convolutional neural network for SAR image despeckling, called SAR-SCCNN. To enlarge the receptive field of the network, downsampling and dilated convolutions are employed in each self-calibrated block. Also, the contextual information from spaces with different scales is extracted and concentrated to obtain accurate despeckled images. Experiments on synthetic speckled and real SAR data are conducted to perform the subjective visual assessment of image quality and objective evaluation. Results show that our proposed method can effectively suppress speckle noise and preserve detailed features.
Expanding Students’ Vocabulary Mastery Using Pictures at Junior High School

This research aimed at finding out whether or not pictures can improve students’ vocabulary mastery. Pre-experimental design was applied in this research with one group pre-test and post-test design. The population of this research was the seventh-grade students of Junior High School 27 Makassar, academic year 2018/2019 which consisted of 3 classes. This research instrument used vocabulary test consisted of word form, word meaning, and word use as the research instrument. The result of this research showed that the application of pictures can improve students’ vocabulary mastery. It was proved by the value of the t-test 17.683 which was greater than the value of t-table 1.70 the level of significance (p)= 0.05 and degree of freedom (n-1) =27.
Meningkatkan Hasil Belajar Siswa Pada Mata Pelajaran IPS Melalui Media Gambar

Learning is a process marked by a change in a person. A teacher must be skilled in determining appropriate strategies, methods, and learning media. Lack of media and teaching aids, students find it difficult to get grades that are in accordance with the KKM. This study aims to determine the improvement of student learning outcomes in social studies subjects using image media in class V SD Negeri Kedungsono 3 is classroom action research. Data collection techniques using the method of observation, documentation and tests. The instruments used in this study were observation sheets for improving student achievement both individually and in groups, student learning independence sheets and evaluation questions. The results of this study were 33.33% in the pre-cycle, 60% in the second cycle, 100% in the third cycle. Based on the results of the research obtained, it is concluded that through the media images can increase the activity and learning outcomes of fifth grade students at SD Negeri Kedungsono 3, Bulu District, Sukoharjo Regency.
Relationship of Information Sharing in Social Media to Reinforcement of Online Social Capital during Humanitarian Crisis Response in Yemen

The internet revolution has brought about several interesting phenomena, with one of the top being the use of social media as an avenue for social development and for the contribution to the cohesion among the community members. In the present study, the focus was placed on information sharing in social media as tools used by participants in Yemeni non-profit organizations to making informed decisions when it comes to crisis response, via the development of social capital in the virtual community. The study made use of statistical method of quantitative to obtain the results. Accordingly, data was gathered by distributing 423 questionnaires to non-profit organizations managers who had participated in emergency or disaster relief tasks in Yemen. The study found that exchange of information and its management timely through social media helped to develop the social capital, which facilitated and maintain ongoing relationships and establish to social coordination, volunteerism, and social cohesion among organizations and victims for creating the social capital in crisis community.