Reviewerly/exHarmony huggingface dataset:
Teacher Perception of Implementation Learning Management System: CCR with Android Opensource

The purpose of this research is mapping teacher perception on learning management system as second opinion in pandemic era. The methodology of research divided into three parts, namely preparation, action, and evaluation. The first step is preparation, include prepare to train the teacher to use CCR and android application opensourse. The second step is action, this section is most important in this research because in this section the teachers were practicing with CCR and android application within the teaching activities in online learning. After those steps, the final is evaluation, the teachers were evaluated using likert scale of the implementation of CCR and android open sourse. The result of this research is most of the teachers feel easy in accessing CCR and android opensource application.
Software Defect Prediction using Machine Learning Algorithms: Current State of the Art

One of the essential exploratory fields in the software quality field is software defect prediction. Software engineering involves many ways to predict software quality assurance topics such as test effort prediction, cost prevention, error prediction, reusability prediction, prediction for safety, and consistency prediction. Though most of these predictive methods remain in the initial stage, and more study is in the forecast, many academicians and industry people have begun to work on new projects in this field.  Mechanisms to increase the efficiency of the assurance activities and allocate resources more effectively are becoming more efficient with Software Defect Prediction (SDP). In this article, the state of the art in software defects with Machine Learning algorithms is discussed.Keywords- Software Defect Prediction, Machine Learning Algorithms, Static Metrics, Dynamic Metrics, Object-Oriented Metrics, SVM, Random Forest, Decision Tree
A realizability semantics for inductive formal topologies, Church's Thesis and Axiom of Choice.

We present a Kleene realizability semantics for the intensional level of the Minimalist Foundation, for short mtt, extended with inductively generated formal topologies, Church's thesis and axiom of choice. This semantics is an extension of the one used to show consistency of the intensional level of the Minimalist Foundation with the axiom of choice and formal Church's thesis in previous work. A main novelty here is that such a semantics is formalized in a constructive theory represented by Aczel's constructive set theory CZF extended with the regular extension axiom.
Women Safety Application using Machine Learning

Crime against women these days has become a problem of every nation around the globe. Many countries are trying to curb this problem. Preventive measures are taken to reduce the increasing number of cases of crime against women. A large amount of data set is generated annually on the basis of reporting of crime. This data can prove to be very useful in analyzing and predicting crime and help us prevent the crime to some extent. Crime analysis is an area of vital importance in the police department. Study of crime data can help us analyze crime patterns, inter-related clues & important hidden relations between the crimes. For prevention of crime, further using data mining techniques data can be predicted and visualized in various forms in order to provide better understanding of crime patterns. The safest route prediction system will check for all the possible alternatives for reaching particular destination and based crime analysis the route with minimum crime rates will be selected and will be provided to user. Machine learning algorithms are used to generate the risk score of a path based upon average risk score of nearby clusters/regions. The Public safety can be ensured bydeveloping such a kind of system.We are looking forward to developing the safest route prediction using crime analysis.This system is the backbone used to implement this women safety application which enables a greater level of safe experience for them along with these several emergency handlers are also integrated in this application.
Decoding China’s COVID-19 ‘Virus Exceptionalism’: Community-based Digital Contact Tracing in Wuhan

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Compression Analysis Using Coiflets, Haar Wavelet, and SVD Methods

The image problem lies in the amount of storage space required, to save memory as little as possible image compression is required.The image compression technique is a technique used to represent an image by reducing the quality of the original image but still retaining the information inside.This study compares the best compression method between Coiflets, Haar wavelets, and SVD with JPG image material.The comparison process has done by calculating the compression ratio (CR), Space Saving (SS), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Peak Signal to Noise Ratio (PSNR).The results obtained prove that the SVD method has the highest compression ratio of 3.25 while in the case of Space Saving (SS) the Coiflets method gives the best performance with a value of 73.Measurement in terms of MSE and RMSE is the best for the Coiflets method because it has an average value.-The smallest average among all methods is 0.02395 and 0.111383.provides the best performance in maintaining compression quality.The best PSNR based image quality assessment is the Coiflets method with the highest PSNR average of 63.02 dB.Overall, the Coiflets, Haar wavelet, and SVD compression methods used for JPG images can reduce file size and preserve image information and quality.
'The New-Normal of Talent &amp;amp; Knowledge Management – A Framework Towards Virtual Learning – Post- COVID-19'

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BankBot: Contactless Machine Learning Chatbot for Communication during COVID-19 in Bank

This paper presents the development of a Contactless Chatbot which can be used in banks to solve/guide general queries of customer who are visiting the bank on day to day basis and thus the concept of “social distancing” between the customers is enforced and the bank employee can achieve to a large extent relief via the Chatbots . Contactless Chatbots is a intelligent system that understand user’s natural language queries and responds accordingly in a conversation. The paper presents an efficient machine learning Chatbot which takes data from Banks of Mumbai and provides accurate answers to user’s query and can guide customers in a meaningful manner during and after covid-2019 situation. The Contactless Chatbot is developed keeping the cosine algorithm as our base, An article will be downloaded through the specified URL, after which tokenization is performed using TF-IDF vector, followed by lemmatization and vectorization to get a similarity score from which our machine learns and provides the most efficient results to the user. Additionally, we also use a dictionary to remove all punctuations in the article, and to get the similarity score in the user’s query and according to the similarity score the response will be generated by the Chatbot. The detailed explanation about the algorithm is presented under the Methodology section of this paper. The main aim of this paper is to provide a solution to banks so that there is a contactless communication between the employees of the bank and the customers which would be very beneficial during these pandemic times. The Chatbot proposed in this paper has the capability to replace the “May I Help You?” desk which is present in every bank just at the entrance, It will also be a major boon in the current Covid-19 situation, fostering minimum or no human to human interaction.
Research on the recognition of students’ classroom learning state based on facial expressions

Abstract The learning state of students in the classroom can not only affect the learning effect of students, but also reflect the teaching quality of teachers. In this paper, a new image database of classroom learning state is established according to students’ learning state in real classroom environment, and an improved ResNeSt network model based on spatial attention mechanism is proposed. In this method, spatial attention mechanism is introduced into the ResNeSt network, which is complementary to the channel attention thought of the original network, so as to improve the recognition accuracy of learning state images. Using this method to identify students’ classroom learning state can provide a basis for teaching administrators to evaluate teachers’ teaching quality, as well as provide guidance for teachers to better adjust teaching models and teaching methods, and improve teaching efficiency.
Speaking skills development in ESL E-learning educational environment

The article focuses on the peculiarities of teaching speaking in E-learning educational environment, which today is a must for organizing educational process of high quality. The material to analyze is based on the on-line part of the course "Foreign language practice (English)", worked out for the students of Bachelor’s Program "Pedagogical Education (double major) and Second Foreign language " (5 years, full time) of Kazan Federal University. The status of foreign language teachers has always been high as they play an important role in fostering cross-cultural communication, in promoting tolerance and bridging nations and countries. It is up to teachers to make students understand the essence of successful communication that lies in respecting the diversity of cultures, peoples, nations, and languages. In this respect being culturally competent is of great importance (MINGAZOVA; MELLO; GAFIYATOVA, 2017). The course "Foreign language practice (English)" is located on the platform edu.kpfu.ru. Special attention is paid to the implementation of a communicative approach when teaching speaking, considering the individual educational trajectory of the student or the study group. In addition, the research gives the gist of the theoretical analysis and the results of the experimental testing of the teaching speaking approaches, the effectiveness of the methods used when forming speaking skills of the students. Thus, we could state that when teaching speaking in E-learning educational environment, it is necessary to conduct preparatory stages in the form of studying and training new vocabulary online, which leads to the possibility to give more time to group forms of work during face-to-face classes. The groundwork and analysis of the selected factual material indicate that, teaching speaking can be effectively carried out online, if certain requirements are met, such as the use of a communicative approach, the proper organization of individual and group work, high self-discipline and motivation of the student and the teacher. The use of E-learning educational environment can improve the quality of training speaking skills in higher educational institution.
Visual Analysis Of Children Books Illustration As a Psychiatric Therapy

One of the most acute urban problems is the emergence of psychiatric problems caused by the acceleration of daily routine. These psychiatric problems not only suffered by adults, but also children. These children generally have a problem called B.L.A.S.T. (Bored, Lonely, Angry-Afraid, Sad, Tired). To overcome this problem, there are a number of ways, including reading. Since 1802, Benjamin Rush, the father of United States psychiatry, recommends reading as part of therapy for patients with mental disorders. This therapy also applies for children by adding more illustrations wihin the books. This study analyzed three illustrated books that read by children in Indonesia from ages 7-13 years. The Illustrations analyzed by Roland Barthes's semiotic approach, to get conclusions regarding how illustration have a positive psychiatric therapy impact on children. The finding and results based on semiotic approach that, books mentioned above have the potential to overcome of B.L.A.S.T. because it contains two functions, education and entertainment. This assumption supported by theoritical view of psychologist Jean Piaget, things that educate and entertain are two important elements as a therapy for many kinds of psychiatric problems.Keywords: Children, Illustration, Psychology,Semiotics, B.L.A.S.T
Target tracking based on standard hedging and feature fusion for robot

Purpose Visual tracking technology enables industrial robots interacting with human beings intelligently. However, due to the complexity of the tracking problem, the accuracy of visual target tracking still has great space for improvement. This paper aims to propose an accurate visual target tracking method based on standard hedging and feature fusion. Design/methodology/approach For this study, the authors first learn the discriminative information between targets and similar objects in the histogram of oriented gradients by feature optimization method, and then use standard hedging algorithms to dynamically balance the weights between different feature optimization components. Moreover, they penalize the filter coefficients by incorporating spatial regularization coefficient and extend the Kernelized Correlation Filter for robust tracking. Finally, a model update mechanism to improve the effectiveness of the tracking is proposed. Findings Extensive experimental results demonstrate the superior performance of the proposed method comparing to the state-of-the-art tracking methods. Originality/value Improvements to existing visual target tracking algorithms are achieved through feature fusion and standard hedging algorithms to further improve the tracking accuracy of robots on targets in reality.
Speech and Kinova Arm-Based Interactive System with Person Tracking

This paper presents the integrated module of speech, person detection, and an assistive robotic arm. This whole project is developed in Linux Ubuntu 16.04 using robot operating system (ROS) platform in which the kinetic version is used. Speech to text and text to speech code is developed using Google API. Person detection is performed using lidar using a Kalman filter and global nearest neighbor data association algorithms. Assistive robotic arm package of Kinova Jaco is used. An external microphone is used to record the voice of a person, and RPLiDAR is used to detect, track persons, and to predict estimated 3D coordinates of a person in real time. This is an autonomous model with no manual control by any other persons, it is also a fixed system where both lidar and Kinova arm base are fixed to a table, and it can work efficiently when a person is at a distance below the 1.2 m to both lidar and arm.
QUANTIFICATION OF SPACIOUSNESS OF INTERIORS CONSIDERING LIGHTING AND VISUAL ENVIRONMENT (PART 1) : VERIFICATION OF SPACIOUSNESS EVALUATION USING VIRTUAL REALITY WITH HEAD MOUNTED DISPLAY IN CLOSED INTERIOR SPACES

While improvements in the energy-saving performance of buildings are required, productivity improvements and health management are also getting more necessary due to work style reforms. This trend demands the development of new methods which enable us to quantitatively assess the physiological and psychological quality of the built environment from the design stage. In terms of the light and visual environment, spaciousness is one of the factors that affect the comfort, intellectual productivity, and health of users of interiors.
Machine Learning - A New Trend in Web User Behavior Analysis

Many disciplines, including political economy, linguistics, psychology, social science, and marketing and engineering science, have studied human behavior.As a result, machine learning could be a broad theoretical framework with a wide range of applications, especially in the analysis of internet user browsing behavior.-Aben E. NLANR PMA knowledge, 2010.For testing and calibrating their theoretical models, the aforementioned disciplines used surveys and experimental sampling.The internet logs dealings that store and register each visitor's action on an internet website are the most important sources of information in terms of internet user browsing behavior.Such files may contain incalculable registers, based on the traffic of a web site, and represent a valuable source of human behavior data.This paper examines the rise of machine learning as a trend in analyzing online user behavior, as well as some novel approaches such as knowledge collection and preparation, understanding human behavior, characterization of information analysis in human behavior, internet application, and global application for defining what internet users are looking for in a computing machine..
Multichannel Attendance Management System using QR Code and Location

With the advent of technologies and multiple options available, it’s very essential to rethink and optimize the current manual process by utilizing technologies, like web, mobile together. At present mobile phones play a vital role in our day-to-day life, and it also became a mode of identity. Using the mobile and its geo tagging feature we can precisely locate and validate once presence. The inbuilt ability of mobile can be very well leveraged to modernize the current manual attendance system. QR Code scanning is one of such features of mobile phones that enables them to quickly capture and process the data. Smartphones can be used to speed up the process of taking attendance. This project ‘Multichannel Attendance Management system using QR Code and Location’ focuses on simplifying &amp; solving the problem of manual process of taking attendance. The project proposes a system that is based on using a QR code. QR stands for ‘Quick Response’. They can be read quickly by a cell phone. It stores information such as the lecture number, date, name of the professor, etc, which is used in this proposed system.
The Security Issue of ICS: The Use of IT Infrastructure

With the trend of Industry 4.0, the communication established by Ethernet is becoming more and more common in the Industrial Control System (ICS), and it brings not only pros but also cons like vulnerabilities from information technology.Furthermore, most devices in the ICS are not ready for cyberattacks, and it opens up opportunities for attackers.We generalized a procedure of attacking an Ethernet-enabled ICS and implemented it to the real industrial system we obtained.The procedure gets the information and access of the devices in the ICS, like identifying the manufacturer of Programmable Logic Controllers (PLCs) and overwriting the configuration of PLCs.
Constructing an Intelligent Navigation System for Autonomous Mobile Robot Based on Deep Reinforcement Learning

Motion planning plays an essential role in motion control for autonomous mobile robots (ARMs). When the information about the operating environment and robot's position obtained from a simultaneous localization and mapping (SLAM) system, a navigation system guarantees that the robot can autonomously and safely move to the desired position in the virtual environments and simultaneously avoid any collisions. This paper presents an intelligent navigation system in unknown 2D environments based on deep reinforcement learning (DRL). Our work was constructed base on the Robot Operating System (ROS). The proposed method's efficiency and accuracy are shown in Gazebo's simulation results and the physical robot's actual results.
Cascade-Based Pedestrian Detector Using Edge and Pattern Features

Pedestrian detection plays a significant role in computer vision applications and has been a popular research topic. In this paper, a new pedestrian detector is proposed with a combination of the edge-based histogram of oriented gradient features and pattern-based dense local difference binary features. An important requirement in a pedestrian detector is computational speed. Cascade-based classifiers provide a good trade-off between accuracy and speed. This work uses a cascade of boosted classifiers to enhance the detection speed. To further boost the speed, the histogram of oriented gradients is computed using integral images. The proposed system is evaluated in terms of computational speed as well as precision versus recall and miss-rate versus FPPW/FPPI. The performance is also compared with similar existing pedestrian detectors.
The Enlightenment of the Educational Concept of "Whole Language" on Early Reading Education

Teaching in childhood is very important and can have a great impact on different stages of education. If a good foundation is laid through some special educational methods in childhood, it will greatly promote future learning. Based on the educational concept of the whole language and combined with the current status of early childhood education, this article puts forward a study on the enlightenment of the educational concept of "whole language" to early childhood reading education. This research uses children aged 6-10 as the research object, based on the overall language teaching theory, using current textbooks, trying to apply the overall language teaching theory in the early reading education, and exploring the teaching of the overall language teaching theory in the teaching of English writing in junior high schools The construction of the model combines writing with listening, speaking, reading, and writing to improve children's early reading ability, enrich reading teaching methods, and improve the quality of writing English teaching. This research has certain practical guidance and guidance for early children's reading education Reference meaning. Experimental research results show that it is feasible to use the holistic language teaching method to guide children's early reading ability, to use the whole to make up for the lack of children's reading environment, to stimulate interest in learning, to cultivate language comprehension, and to obtain new life experiences. The use of overall teaching in early childhood reading environment education can not only help children improve their early independent reading ability, but also increase children's interest in reading and stimulate students' initiative and creativity.