Reviewerly/exHarmony huggingface dataset:
CEAZA mega board: an open-source data logger for scientists

&lt;p&gt;Over the last decade many researchers have taken advantage of the technology boom related to the launch of the Arduino platform to make their own datalogging devices. Many of these developments ended with the first functional prototypes in which multiple electronic boards are mixed by wiring/soldering and then used in datalogging activities. In this study we present a new, simple, robust, and expandable datalogger board based on maker’s community integrations. Our datalogger board extends previous work in this area as we designed an Arduino Mega 2560 derivative integrated board that is compatible with existing developments but was also designed and implemented considering requirements such as low power consumption, expandability, and integration. Different tests were made so reliability in low temperatures and low energy needs are satisfied. Is expected that the scientific community can add this board to their tool set, as this board solves the energy problem and present an easy transition from handmade logger integrations.&lt;/p&gt;
머신러닝을 활용한 대학생 핵심역량 지표 예측 모형 개발연구

Objectives The purpose of this study was to present implications for the development and operation of the core competency-based curriculum by predicting the core competency of college students.&#x0D; Methods The panel data of the D-CODA result panel data for the past 3 years (2019-2021) of D-University students located in the Busan area were analyzed. Machine learning prediction models such as multiple linear regression analysis (LR), random forest (RF), and support vector machine (SVM), were used to predict core competencies.&#x0D; Results The following research results were derived from the study. First, the optimal prediction model for each core competency is as follows. Professional competency was shown in the RF (random forest) model, personality competency in SVM (support vector machine), creative competency in the RF (random forest) model, challenge competency and glocal (global and local) competency in the SVM (support vector machine) model, and communication competency in the LR (multi-linear regression analysis) model. Second, in the analysis of competencies, it was found that professional competency contributes to the prediction of professional competency, and both personality competency and communication competency to that of personality competency. Third, in the model analysis to predict the overall core competency index, the optimal predictive model was found to be the RF (random forest) model which showed the least error. Fourth, in the prediction of key competency indicators in 2022, it is predicted that expertise, personality, creativity, and challenging competency will improve.&#x0D; Conclusions This study revealed that the analysis using accumulated core competency data and machine learning is useful in predicting and discriminating the core competency of college students. This study is meaningful in that it suggests the importance of periodic core competency index management at the university level and provides the basis for designing a core competency-based curriculum.&#x0D;
Integrating New Media in the Undergraduate Students’ Education

As a novel teaching method, new media teaching has become one of the teaching methods in universities and colleges. By analyzing the advantages and feasibility of the new media teaching methods, this paper demonstrates that new media teaching method is a more suitable method for English teaching. Further, material selection, and how to avoid problems in the process of using this method in the teaching was also analyzed.
Overview of Android Application “PostIT”

An Application is usually a programmed for a handheld mobile that is guided by computer Programming. Many applications are built for commercial purposes. Designing of the latest electronic technology can be controlled using an App for android mobile. We are developing an android application for the Professional Photographers and Photo lovers. In which we use several features for development offered by android. The user of our application can upload pictures clicked from their device on our app. An Internet-based photo-sharing application and service that allows users to share pictures on the users of the application. Our application lets registered users upload photos clicked by them on our app. A “Global Feed” tab is present in our app which allows a person to see pictures &amp; images uploaded by another user around him. Also, we have “Explore", a tab inside the app that displays popular photos, photos taken at nearby locations, and search. The main aim of our app is to let the people to share photos and images clicked by them. We have made app for users that our new to internet photo sharing apps. Our app is simple and easy to use. We have given basic features on our app like, Share, Comment. The users of the applications can see each other's photo and can like, comment, and share them to other users. A user must register on our app to gain access to our application. Then the user has to Login on our app. A user can upload generous size photos on our app.
Soccer Action video Classification using Deep Learning

Abstract: This paper proposes a deep learning approach for the classification of different soccer actions like Goal, Yellow Card and Soccer Juggling from an input soccer video. The approach used for the same included a Hybrid model which consisted of VGG16 CNN model and Bidirectional Long short-term memory (Bi-LSTM) a Recurrent Neural Network (RNN) model. Our approach involved manually annotating approximately 400 soccer clips from 3 action classes for training. Using the VGG16 model to extract the features from the frames of these clips and then training the bi-LSTM on the features obtained. Bi-LSTM being useful in predicting input sequence problems like videos. Keywords: Soccer Videos, Convolution Neural Networks (CNNs), Recurrent Neural Network (RNN), Bidirectional Long shortterm memory (Bi-LSTM)
Application of CQI for the realization of competency-based education and it’s effects: Focusing on the case of D University

Objectives The purpose of this study is to analyze the effect of the Continuous Quality Improvement report on competency education in universities.&#x0D; Methods This study was conducted by analyzing the contents of the CQI report prepared for each of the seven common liberal arts subjects opened at University D, and comparing the results of the student's competency diagnosis conducted before and after the application of the CQI report.&#x0D; Results As a result of the study, it was found that the level of awareness among professors about the CQI report has been steadily improving, and as a result, the narrative content of the report has been greatly improved. Also, it was found that the students' competency scores increased significantly after CQI application compared to before, and the number of competencies that showed an increase in scores also increased.&#x0D; Conclusions It turns out that the CQI report is an effective tool in promoting competency-based education in universities. The CQI report can be a tool to help improve the curriculum in major subjects as well as common liberal arts subjects, the subject of this study.&#x0D;
The Effect of the Early Childhood Teachers’ Educational Beliefs and Teacher Competencies on the Degree of Young Children’s Experience in the 2019 Revised Nuri Curriculum Education Contents

Objectives The purpose of this study was to examine the effect of early childhood teachers’ educational beliefs and teacher competencies on the degree of young children’s experience in the 2019 Nuri curriculum education contents.&#x0D; Methods For data collection, 302 early childhood teachers in Gyeongnam province were surveyed by questionnaires about teachers’ educational beliefs, teacher competency, and the degree of young children’s experience in the 2019 Nuri curriculum education contents from 2 Feb. 2022 to 26. For data analysis, descriptive statistics, Cronbach’s α, and hierarchical regression analysis were used by SPSS 25.0.&#x0D; Results First, early childhood teachers' educational beliefs were high in maturationism, low in activism, and high in teacher competency, and the degree of young children’s experience in the 2019 revised Nuri curriculum education contents was high. Second, there was a significant positive correlation among the teachers’ educational beliefs, teacher competencies, and the degree of young children’s experience in the 2019 Nuri curriculum education contents. Third, teachers’ educational beliefs and teacher competencies were found to influence on the degree of young children’s experience in the 2019 Nuri curriculum education contents.&#x0D; Conclusions This results suggest that in order to enhance the degree of young children’s experience in the 2019 Nuri curriculum education contents, teache
Smart Attendance System Using QR-Code, Finger Print and Face Recognition

Smartphones now play an important role in our daily lives. It has made life simpler and easier for everyone with various social, commercial, problem-solving, educational, and marketing apps... etc., and in light of the need for social distancing following Covid-19, we have designed a system that addresses the problem of student and employee attendance in various institutions. They were utilizing a paper-based approach to keep track of their attendance. The suggested system is an Internet of Things (IoT)-based attendance system that makes use of the IEEE 2413 Standard for an Architectural Framework for the Internet of Things (IoT) (Face recognition - Fingerprint - QR code). Our system may be used in two sorts of organizations: the first is for businesses, where attendance is recorded using one of two characteristics (Face recognition or fingerprint), and the system is also designed to manage employee working hours. The second system is for educational institutions, and it is responsible for managing and analyzing all students' attendance. For pupils to take attendance, a (Face recognition& QR code) will be provided. The professor is in charge of determining whether or not all of the pupils in the group or class are present. To authenticate their attendance and exit, users will only need their smartphones.
Green Cloud Computing (GCC), Applications, Challenges and Future Research Directions

Cloud computing is a rapidly evolving field of communication and information technology, posing new environmental issues.Because cloud computing technologies are scalable, stable, and trustworthy, and provide great performance at a cheap cost, they have a wide range of application fields.The cloud computing revolution is reshaping modern networking and presenting both economic and technological benefits, as well as potential environmental protection prospects.These technologies have the potential to boost energy efficiency while also lowering carbon emissions and e-waste.These characteristics have the potential to turn cloud computing into green cloud computing.The main achievements of green cloud computing are reviewed in this survey.First, a brief introduction to cloud computing is provided.Following that, recent studies and advancements are discussed, with environmental issues being addressed especially.Finally, future research prospects for green cloud computing are discussed, as well as open issues.
An Exploration of College Students’ Perceptions on a Learner-led Questioning Activity: based on General English Classes

Objectives This study aims to explore the meaning of college students' experience on the leaner-led questioning activity performed in general English classes.&#x0D; Methods Purposeful sampling which is a technique widely used to a qualitative research was used and in-depth interviews were conducted for the data collection. And a phenomenological method was used for data analysis.&#x0D; Results The essential theme clusters were derived, that is, qualitative change in learning habits, improvement of learning ability, overcoming the limitations of non-face-to-face classes, and transformation from immaturity to maturity. And the contents of the main themes were as follows. First, participants focused on lectures more than usual and engaged in various learning activities on their own. Second, they were able to recognized and supplement the shortcomings and their led questioning activity helped them to improve their knowledge retention and to expand their knowledge. Third, they perceived that there are active interactions between teacher and students and they became more and more active learners. Fourth, they could further develop their question quality by trial and error.&#x0D; Conclusions It was found that learner-led questioning activity helped students to have high willingness to their learning and to improve their long-term knowledge retention as well as to expand their knowledge and to increase their level of academic performance. Although participants had difficulty on generating their own questions, their level of question quality was higher and higher for teachers to teach students to create their own questions. Consequently, this study shows that learner led questioning activity contribute to teachers' practice of Constructivist education and teachers need to encourage students to ask more questions maximizing their learning in the classroom.&#x0D;
Social psychology of the crowd in the works of foreign scientists of the late 19th - early 20th century

The article examines the ideas about the socio-psychological characteristics of the crowd described in the works of foreign scientists of the late 19th - early 20th century, analyzes the works on this topic by S. Sighele, G. Le Bon, G. Tarde, O. Cabanes and L. Nass. In the course of the study, a generalized picture of the views of these specialists on the phenomenology of large social groups was obtained. In general, it is recognized that the crowd is impulsive, unstable, irresponsible, susceptible to suggestions, gullible, intolerant and conservative. The behavior of an individual in a group differs from his behavior outside it, and the average intelligence of the crowd is generally lower than the individual. Of particular interest in the works under consideration is the criminal crowd, in which all the features of large social groups are expressed to an extreme degree. Its features are the susceptibility to imitation and suggestion, large numbers, moral intoxication, actualization of instinct and the specific, mostly marginal composition of the crowd. The merging of individuals into a crowd occurs with the help of a community of ideas and beliefs, through suggestion and imitation. The results obtained in the course of the study can be used both in social and political psychology and in historical science, where the scope of their application is outlined by the boundaries of mass phenomena of the past, present and future.
A SURVEY REPORT ON PROJECTOMATE

The Agile Development approach to systems development is the new fundamental for developers. Twelve Principles supporting the Agile Manifesto were elaborated in support. Hence the team always has to look towards identifying and proposing appropriate reference disciplines which are manifest in the Agile Development Universe of Discourse. The Manifesto evokes some reference disciplines to support its various aspects. Why is it desirable and necessary to search for such reference disciplines? The answer is Alternative Software Development and Project Management approaches, such as Software Prototyping and Rapid Development and now including Agile Development, all seemed based on pragmatic experience and have been designed mostly by consultants and practitioners. While this is not in any way to denigrate or deprecate them, it is felt that support for these approaches needs to also come from other disciplines, such as management studies, leadership studies, and the like to give Agile Development a more solid theoretical and intellectual basis.
KEMA: Knowledge-Graph Embedding Using Modular Arithmetic

Knowledge graph is a knowledge representation technique that helps representing entities and relations in a machine understandable way.This promising trend suffers from the problem of incompleteness that was best solved by link prediction.Indeed, link prediction is the most successful method for understanding the structure of the large knowledge graphs.Knowledge graph embedding KGE is one of the best link prediction methods.Its effectiveness is mainly affected by the accuracy of learning representations of entities and relations.In this paper, we propose a new knowledge graph embedding model called KEMA ( Knowledge-graph Embedding using Modular Arithmetic).KEMA has the ability to represent simple and complex relations in an efficient way.Consequently, this allows our model to outperform the majority of the existing models.Mainly, KEMA depends on representing the relations in a knowledge graph by modular arithmetic operations applied between entities.Experimental results on multiple benchmark knowledge graphs verify the accurate representation, low complexity and scalability of KEMA.
File Storage using Cloud and Cryptography Technologies

In this era cloud computing is employed in various fields like industry, military, college, etc. for various services and storage of big amount of information. Data stored during this cloud will be accessed or retrieved on the users request without direct access to the server computer. But the foremost concern regarding storage of knowledge online that's on the cloud is that the Security of the information. Many different approaches have also been proposed to produce data protection within the cloud, like AES, BlowFish, and RC6, but Existing systems often fail when only a specific type of encoding is utilised, either AES or RC6 reckoning on a consumer requirement. As when there are encrypted the keys are leaked thus making the info to be accessed by anyone. So we've proposed hybrid cryptography because the solution for this problem. So when the user uploads the info, it is divided into three sections, the primary is encrypted with AES, the second is completed with DES and eventually the third section is completed with RSA.
Designing an Emergency Information System for an Emergency Information System for Catastrophic Natural Situations

Natural disasters have brought about irreparable damage to humans, human activity, society, and the economy, and their effects will probably be increased in the future due to climate change. However, the extent of a natural disaster could be diminished if both individuals and authorities are informed of an impending emergency situation. Therefore, the research interest has been directed into developing robust Emergency Information Systems. This paper demonstrates the way a specific Emergency Information System could be designed to deliver alert messages. The system was designed on the base of the DRM standards and was put into action in the region of Vigla, an area located in Symi, one of the Dodecanese islands. The coverage test proved that the system operates well in remote areas that are characterized by rough geographic terrain.
Temperature Dependence of Current-Voltage Characteristics of Ionic Liquid Type Intelligent Connection Device

The temperature dependence of intelligent connection (IConnect) devices in which ionic liquid (IL) plays an important role in a memristive function is presented in this study. The appropriate choice of IL and dissolved metal ion species can control the volatility of IL-IConnect devices. The temperature dependence of IL-IConnect device was strong, although the change in the current-voltage characteristics was reversible in response to temperature variations. The device’s potential as a physical reservoir-computing device is studied. (Keywords: Ionic Liquids (IL), Intelligent Connection (IConnect) Device, IL-Reservoir device)
IMPLEMENTATION ANALYSIS OF SERVICES BASED ON SOCIAL INCLUSION IN THE COMMUNITY OF THE REPUBLIK GUBUK

Abstract: This study aims to analyze the form of implementation of social inclusion-based services in the Republic Gubuk Community which is an association of Gubuk Baca in the Jabung area, Malang Regency. The research was conducted using a descriptive qualitative data analysis approach. data sources used primary and secondary data sources obtained through interviews, observation, and literature review. The results of the research show that the activities that are part of the program at the Gubuk Republik Community are a form of social inclusion-based library service which is in line with the concept of social inclusion-based library services developed by Utami and Prasetyo which describes several aspects, namely reading huts as facilitators in developing growth potential. economy, reading huts as a vehicle for problem-solving, reading huts as a center for community activities, and reading huts play an active role in the literacy movement through various activities such as BUMI Gubuk (Hut-Owned Enterprise), teaching thug, People's Campus, mobile library movement, and others. etc.
URL’S Phishing Detection Based on Machine Learning Approach

Phishing detection is a challenging problem, and many different solutions are proposed in a market as a blacklist, rule-based detection, anomaly-based detection etc. Phishing Websites are duplicate webpages created to mimic real websites in-order to deceive people to get their personal information. Because of the adaptability of their tactics with little cost detecting and identifying phishing websites is really a obscure and dynamic problem.
LFU-Net: A Lightweight U-Net with Full Skip Connections for Medical Image Segmentation

Background: In the series of improved versions of U-Net, while the segmentation accuracy continues to improve, the number of parameters does not change, which makes the hardware required for training expensive, thus affecting the speed of training convergence. Objective: The objective of this study is to propose a lightweight U-Net to balance the relationship between the parameters and the segmentation accuracy. Methods: A lightweight U-Net with full skip connections and deep supervision (LFU-Net) was proposed. The full skip connections include skip connections from shallow encoders, deep decoders, and sub-networks, while the deep supervision learns hierarchical representations from full-resolution feature representations in outputs of sub-networks. The key lightweight design is that the number of output channels is based on 8 rather than 64 or 32. Its pruning scheme was designed to further reduce parameters. The code is available at: https://github.com/dengdy22/U-Nets. Results: For the ISBI LiTS 2017 Challenge validation dataset, the LFU-Net with no pruning received a Dice value of 0.9699, which achieved equal or better performance with a mere about 1% of the parameters of existing networks. For the BraTS 2018 validation dataset, its Dice values were 0.8726, 0.9363, 0.8699 and 0.8116 on average, WT, TC and ET, respectively, and its Hausdorff95 distances values were 3.9514, 4.3960, 3.0607 and 4.3975, respectively, which was not inferior to the existing networks and showed that it can achieve balanced recognition of each region. Conclusion: LFU-Net can be used as a lightweight and effective method in the segmentation tasks of two and multiple classification medical imaging datasets.