Reviewerly/exHarmony huggingface dataset:
TEXT RECOGNITION

The Optical Character Recognition (OCR) is one of the automatic identification techniques that fulfil the automation needs in various applications.A machine can read the information present in natural scenes or other materials in any form with OCR.The typed and printed character recognition is uncomplicated due to its well-defined size and shape.Recognition of text from images is an important process in the present scenario.Nowadays there is a great surge in storing the information found in the paper document in digital format.This helps in preserving the information, easy storage and also permits retrieval of information as and when required.The various stages of text recognition are: pre-processing, segmentation, feature extraction, classification and post processing.The pre-processing step involves a number of operations the most significant being converting colour image into a binary image thus separating the text from the background.Text recognition is of utmost importance in several applications.This paper discusses the text recognition module and also presents the various applications of text recognition from images.Related work is also examined in this paper.
IMAGE AND TEXT ENCRYPTED DATA WITH AUTHORIZED DEDUPLICATION IN THE CLOUD

Role re-encryption is used to avoid privacy data leakage and also to avoid deduplication in a secure role reencryption system (SRRS).And also, checks for proof of ownership to identify whether the user is an authorized user or not.This is for efficiency.The role re-encryption method is to share the access key for the corresponding authorized user for accessing the particular file without the leakage of private data.In our project, we are using both the avoidance of text and digital images.For example, we have personal images on our mobile, handheld devices, and the desktop, etc., So, as these images have to keep secure and so we are using encryption to increase high security.The text file is also important for users nowadays.It has to keep secure in a cloud server.Digital images have to be protected over communication, however, generally, personal identification details like copies of pan cards, Passports, ATMs, etc. to store none's pc.
Exploring the Relationship Between Teacher Professional Capital and Self-Efficacy: Based on the Interaction Effect of Generation

Purpose: The study examines how human capital and social capital among teachers' professional capital are related to three types of teacher self-efficacy (student participation, instruction, and class management), and investigates to what extent the relationships vary between millennials and non-millennials generations. Methods: Using the TALIS 2018 data, which provides a nationally representative sample of middle school teachers in South Korea, we conducted a linear regression analysis with the school fixed effect model. Results: The results show that even after controlling both individual and school characteristics, teachers' human capital and social capital were positively related to all three types of teacher self-efficacy. Next, the interaction effect between generation and professional capital is significant only for instruction self-efficacy. The millennials were more strongly related to human capital, and the non-millennials were more strongly associated with social capital when it comes to instruction self-efficacy. Conclusion: Based on the results, this study proposes accumulating teachers' human capital, supporting professional collaborative activities to revitalize social capital, and considering the distinctive characteristics of the millennials.
VIRUS DESTROYER GAME FOR EDUKATING HEALTH PROTOCOL AND LEARNING MEDIA OF VIRUS DURING COVID-19 PANDEMIC

At the end of 2019, the world was shocked by the spread of the Corona Virus that causes Corona Virus Disease (COVID-19). The Covid-19 pandemic has changed all aspects of life, one of which is the world of education. The government's stay at home policy changes learning to online-based distance learning. So that students cannot be separated from the use of smartphones. Therefore, learning media is needed for education on health protocols and interesting virus-based material on smartphones. The purpose of this study is to provide media that interesting to the public for the prevention of COVID-19 and to provide learning media about Viruses in Biology subjects. This research is developmental research, with research stages covering game development, game algorithms, and game testing. The data were analyzed descriptively quantitatively using the Guttman Scale and Likert Scale. The results showed that the Virus Destroyer Game received a positive response from respondents with a percentage of 83.9% and included a very feasible virus learning media according to the validation results with a percentage of 90.83%. The conclusion of this research is that, the Virus Destroyer Game which was developed, received a positive response as an educational media for preventing COVID-19 and also feasible to be a viral KD learning media. The implication of this research is that students better understand the importance of implementing health protocols to break the spread of Covid-19 in a fun way. &#x0D; Keywords: game education, health protocol, Virus Destroyer Game
Performance Analysis of Hardware Implementations of Reverse Conversion from the Residue Number System

The Residue Number System (RNS) is a non-positional number system that allows parallel computations without transfers between digits. However, some operations in RNS require knowledge of the positional characteristic of a number. Among these operations is the conversion from RNS to the positional number system. The methods of reverse conversion for general form moduli based on the Chinese remainder theorem and the mixed-radix conversion are considered, as well as the optimized methods for special form moduli. In this paper, a method is proposed that develops the authors’ ideas based on the modified mixed-radix conversion and reference points. The modified method based on the mixed-radix conversion in this case makes it possible to replace the operation of finding the residue of division by a large modulo with the sequential calculation of the residue. The method of reference points allows to reduce the size of the stored information compared to the use of ROM to store all the residues of RNS. The application of this approach makes it possible to find a balance between the speed of the calculation and the hardware used, by varying the number of moduli of one method and the other.
Design &amp; Build Banknote Nominal Identification Tools for Visual Impairment Using Convolutional Neural Network Algorithm and Tensorflow with Android Based

The buying and selling transactions that we usually do in our daily lives are difficult for people with visual impairment because it is difficult to distinguish the denomination of rupiah banknotes because of the limitation of sight, so it becomes one of the problems. This research focused on making a voice-based rupiah banknote nominal detection tool, using convolutional neural network algorithms in machine learning as the core of this system. This tool was also equipped with a voice-based android application to monitor the remaining money used when making buying and selling transactions-testing the tool used real test data of 20 images per class, producing an accuracy of 83%, as evidenced by Confusion matrix calculations.
REVEALING EXPRESSIONS OF HAPPINESS AND SADNESS IN STUDENTS’S ESSAYS BY GRADE 3rd AND 5th ELEMENTARY SCHOOL STUDENTS

Psycholinguistics study is a study that focuses on language acquisition, both normal language acquisition (children in general), and language acquisition for children with special needs. Each person's language acquisition goes through a different process. The acquisition of the language is obtained from several factors that support the individual. This is evidenced by several other supporting factors such as environmental factors, age, intelligence, education, talent, demand, and others. This study will try to focus on the study of language acquisition taken from the essays of 3rd and 5th grade elementary school students. By using the theme “My Hope”, the researcher took two samples of student essays by partitioning two essays from 3rd grade elementary school students and two essays from 5th grade students as a form of comparison. The four essays obtained will later be compared how they express their expressions of happiness and sadness in their essays. The results of this study indicate that not all students who experience homeschooling do not have skills in processing written language. Likewise with they levels. A high level does not necessarily indicate that the student is able to process written language well. This research is a type of qualitative descriptive research. This research consists of three stages, namely the stage of data collection, data analysis, and exposure of the results of data analysis. The data collection technique carried out in this study consisted of one stage, namely the analysis of students' thinking processes through tests. The data analysis technique in this study used the analysis of morphological and syntactic elements that were adjusted to age and level (class). This analysis is used to determine the emergence of an element that is a reflection of the child's competence or is a new competence that they get.
EXPLORING THE PRESERVICE TEACHERS’PERCEPTION TOWARD THE USE OF DUOLINGO IN TEACHING VOCABULARY TO YOUNG LEARNERS

The purpose of doing research is to have the investigation on the students’ belief when Duo lingo application is applied in the class of vocabulary and to describe the justification of the advantages using the Duo lingo to empower the vocabulary enrichment. The students of English Study Program in State Islamic College as Pre Service –teachers have participated in this study. The data were collected by the questionnaire distribution and the interview methods. The data analysis uses the qualitative description. The result of the study exposes the facts that the respondents agree the Duo lingo can facilitate the vocabulary learning achievement. The medium labelled Duo lingo makes the students easy and interesting in learning the English word knowledge. The interview with the sample of informants suggests the testimony that the young learners can use the app overtime as far as they want. They are free to set or make up the schedule of lesson session. One more meaningful thing found in the application is that the English is spoken by the native speaker. By performing the English of the native speaker can be a model or master for the students. They get the chance to exercise repeating the word or the sentence spoken by the native speaker correctly.
Understanding and Trends of a Transformer Deep Learning Model in the Liberal Arts Education

대학에서의 교양교육은 학생들에게 다양한 분야의 학문에 관한 기초 지식을 쌓게 한다. 대학 교양교육에서는 비 IT 계열 학생들에게도 4차 산업혁명을 선도할 수 있는 기초교육이 진행되어야 한다. 4차 산업혁명의 핵심기술 중에서 관심이 급증하고 있는 인공지능 기술의 종류와 활용에 대한 기초 이해가 필요하다. 본 논문은 인공지능 기술이 적용되는 다양한 분야에 응용되고 있으며, 주요 응용 분야 중 하나인 자연어 처리(NLP, Natural Language Processing)를 위한 딥러닝 트랜스포머 모델에 관한 이해와 동향을 분석 한다. 이를 기반으로 추후 대학 교양교육 과정에서 다양한 전공의 학생들이 트랜스포머 모델을 활용하여 자연어 처리를 통한 예측, 분류, 분석, 감지 등으로 활용하는 기초 지식을 학습이 가능할 것으로 기대된다.In university, the liberal arts education enables students to build basic knowledge about various domains. The liberal arts education should be provided basic lectures that can lead the 4th industrial revolution even to non-IT students. Among the core technologies of the 4th industrial revolution, it is necessary to have a basic understanding of the types and applications of artifical intelligence studies, which are rapidly gaining interest. In this paper, we describe understands and trends of a transformer model born from NLP(Natural Language Processing) researches and applied to various domains.
Current Status and Direction of Korean History Education in University Education

4차 산업혁명 시대에는 인문학적 소양을 갖춘 융복합 인재를 요구하기 때문에 인문학의 중요성이 강조된다. 특히 역사교육은 과거의 사실 중심에서 비판적 사고력과 역사적 상상력 함양을 위한 학습으로 전환이 필요하다. 또한 한국사 교육은 특수성과 보편성의 조화, 창의성을 키워줄 수 있는 교양교육이 되어야 할 것이다. 아울러 교수자와 학습자간의 소통을 바탕으로 한 학생주도의 체험․ 참여형 교육으로 변화가 필요하다. 교양 한국사의 올바른 방향은 첫째, 전공준비 단계를 넘어 문제해결능력 향상과 현재의 정치, 경제, 사회의 비판적‧통찰적 역사인식을 배양시켜야한다. 둘째 1980년대 이후의 자주,민주,통일의 민족주의를 기반으로 하는 역사관에서 더 나아가 인문소양과 시민 역량을 함양시키는 민주시민, 평화 까지 연계된 교육을 할 필요가 있다. 셋째 각 대학별 역사교육과정에서 학교교육이념만이 아니라 시대적 요청과 학생들의 관심이 적절하게 반영되는 교과목을 편성해야 한다. 넷째 4차 산업혁명시대에 교수자 중심의 강의형 방식과 함께 논쟁점 중심의 토론수업, 영상역사학 기반의 수업, 스마트기술을 활용한 체험학습, 현장학습 등 다양한 역사교육이 이뤄져야 한다.In the era of the 4th Industrial Revolution, the importance of humanities is emphasized because convergence and complex talents with humanities skills are required. In particular, history education needs to shift from the focus of facts in the past to learning to cultivate critical thinking and historical imagination. In addition, Korean history education should be a liberal arts education that can foster harmony between specificity and universality and creativity. In addition, it is necessary to change to student-led experience and participatory education based on communication between instructors and learners. The correct direction of liberal arts Korean history is, first, to improve problem-solving skills beyond the major preparation stage and foster critical and insightful historical perceptions of current politics, economy, and society. Second, it is necessary to go further from the historical perspective based on independence, democracy, and unification since the 1980s to provide education linked to democratic citizens and peace that fosters humanities and civic capabilities. Third, in the history curriculum of each university, it is necessary to organize subjects that properly reflect not only the concept of school education but also the requests of the times and the interests of interest. Fourth, in the era of the 4th Industrial Revolution, various history education should be conducted, including controversial discussion classes, video history-based classes, hands-on learning using smart technology, and field trips.
Kahoot! Sebagai Inovasi Evaluasi Hasil Belajar Siswa Yang Efektif Dan Menyenangkan

Student learning outcomes became an important part of decisions making about planning and implementing future learning. In general, the evaluation tools put the students under stress and lead to failure to achieve minimum graduation competencies. Kahoot! is one of the applications that can be used as an innovation in evaluation of student learning outcomes. The purpose of this study is to analyze the effectiveness and level of student acceptance of Kahoot! as a platform for evaluating Economics subject learning outcomes at SMA Negeri 1 Gemuh class X IPS. Respondents involved in the study were students of class X IPS 1 as the experimental class and class X IPS 2 as the control class, each class totaling of 30 students, at SMA N 1 Gemuh, Kendal Regency, Central Java. Data were taken through tests and in-depth interviews. The test result data were analyzed descriptively quantitatively. Analysis of interview data using an interactive model, namely data reduction, data display, and drawing conclusions. The results showed that the Kahoot! effective as a platform for evaluating economic learning outcomes. Kahoot app! is an innovation in evaluating learning outcomes that are more enjoyable.
Peningkatan aktivitas belajar mata pelajaran Ilmu Pengetahuan Sosial melalui model pembelajaran Talking Chips di kelas I Madrasah Ibtidaiyah

This research is based on the fact that social studies learning in class I, MI Bilingual Roudlotul Jannah, Prambon, tends for students to be inactive during learning. So, this impacts learning activities in social studies learning in the classroom that has not been fully implemented properly. This study aimed to increase learning activities through the application of the talk chips model in social studies learning. The research subjects in this study were 32 bilingual students of class 1 MI Roudlotul Jannah Prambon, Sidoarjo. This research is a type of classroom action research that consists of 2 cycles. Data collection techniques used in this study are observation and documentation—data relating to assessing student learning activities. The results of learning mastery are 36%, then increase in the first cycle to 75%, and in the second cycle, there is an increase until the mastery of learning activities reaches 93%. So, it can be concluded that the chip speaking model can improve learning activities.
The development of Flashcard media to improve students’ English vocabulary in English lessons at MIS Nurul Hidayah Medan

This study aims to determine how to develop appropriate and effective flashcards and to find out whether flashcards can improve students' English vocabulary. The developed media is flashcards. The subjects in this study were fourth-grade students of SD MIS Nurul Hidayah Medan. This type of research was R &amp; D research using a 4-D model. Finding out the feasibility of the media is obtained from an expert validator. Meanwhile, finding out the effectiveness of the media is obtained by testing the media. The trial was carried out twice. The trial was conducted on fourth-grade students consisting of 30 students. Based on the conclusion of the expert, it was stated that the flashcard is worthwhile and effective. While based on the results of the students’ assessment test on the flashcard showed that there was an increase in students' English vocabulary in the first and second trials. Thus, it can be concluded that the development of flashcard as media is feasible and effective for students to use in the teaching and learning process.
Assamese Speech-based Vocabulary Identification System using Convolutional Neural Network

Though the machine learning techniques were being used in Assamese Language Automatic Speech Recognition (ALASR) system over the last five years, but the applications of Convolutional Neural Network (CNN) are very limited in ALASR.The present study introduces a Convolutional Neural Network (CNN) enabled ALASR system for the Assamese language by collecting 35 isolated words in five different prime emotions as Normal, Angry, Happy, Sad, and Fear from five native male and five native female speakers.During the experiment, the Mel Frequency Cepstral Coefficient (MFCCs), Spectral Centroid (SC), zero-crossing rate (ZCR), Chroma Frequencies (CF), spectral roll-off (SRO), and intensity are extracted and analyzed using CNN with convolution layers and max-pooling layers.To examine the consequences, other model such as Feed Forward Artificial Neural Network (FFANN) is likewise applied in ALASR.The evaluating results of CNN with an accuracy of 98.4 % outperformed the ANN accuracy of 86.4 %.
A Decentralized Coordination Algorithm for Patrolling and Target Tracking in Internet of Robotic Things using Dynamic Waypoints and Self-triggered Communication

The Internet of Robotic Things (IoRT) deals with autonomous objects such as robots and sensors together.It can be used for efficient patrolling and target tracking; however, mobile sensors (robots) must coordinate to decide their optimal actions.This paper proposes a decentralized coordination strategy that can enable multiple robots to perform both patrolling and target tracking in the deployed scenario.The basic idea is that the whole site is divided into local zones, and a single robot is deployed in each zone.All robots are logically divided into two groups, namely category C1 and category C2 robots.A dynamic waypoint generation algorithm is proposed to assist category C1 robots in the perimeter patrol.It produces the waypoints such that certain locations can be prioritized and intruders cannot predict the patrolling trajectory.Category C2 robots are responsible for area patrolling within the zone.Here, we also propose a strategy such that the places with a high probability of unusual acts can be visited frequently.We use the distributed Extended Kalman filter (EKF) to estimate and predict the position of the targets.Each robot has a self-triggered communication mechanism to share the necessary information with the neighbors, such as the estimated position of the intruder, EKF parameters, asking for help, etc.We have also developed an Internet of Thing (IoT) based web application to monitor and control the robots.In this app, robots subscribe to the server for necessary information and commands and publish their position, patrolled area, intruders' position, battery status, etc., to the server for real-time monitoring and control.The proposed solution is validated through simulations in the Robot Operating System (ROS) and Gazebo.The results show the patrolling and target tracking performance using idleness and error in the target's estimated position, respectively, as metric.
7P Predicting lymph node metastasis and molecular subtype from pathology united with genomics in breast cancer with multitask deep learning

In early-stage of breast cancer, the analysis of lymph node metastasis(LNM) and molecular subtypes is conductive to clinical diagnosis and treatment decision-making. Here we proposed a new Deep learning network architecture, called DeepCALM, Conducted with Attention mechanism to united genomics and pathology, that can simultaneously predict LNM and Molecular subtypes.
A study on developing integrated risk assessment tool for juvenile probationers

The current study attempts to investigate the predictive validities of the risk assessment tools that are currently being used in juvenile probation and parole in Korea. Since 2016, MOJ(Ministry of Justice) has used the JDRAI-S and JDRAI-D for a different purpose; JDRAI-S has been in use for the purpose of risk classification of juvenile delinquents while JDRAI-D has been utilized for case planning of juvenile probationers and parolees. With the two risk assessment tools being rolled out, concerns have been expressed over the predictive validity of the tools among the practitioners. More importantly, Probation officers have expressed the need to integrate the two different tools into a single, integrated risk assessment tool. Against this backdrop, the current study examines the predictive validities of JDRAI-S and JDRAI-D, and also investigates the possibility that a new tool could be constructed and demonstrate a good level of predictive validity. The results of the current study show that the two current risk assessment tools fail to demonstrate adequate levels of predictive validity. A series of ROC analyses showed that JDRAI-S has the value of AUC .64 and JDRAI-D has the value of AUC .61. Specially the predictive validity of JDRAI-D has posed a serious concern, because many items included in JDRAI-D have been shown not to be associated with recidivism. The second part of the study shows promising results. The newly constructed risk assessment tool, named as JDRAI-Ⅱ, demonstrates a very good level of predictive validity with the value of AUC .73. In addition, the sub factors of JDRAI-Ⅱ also show a good level of consistency and validity. At the end of the study, the authors provide some useful tips for future research and practices.