Reviewerly/exHarmony huggingface dataset:
The Effects of Facebook Live-Stream Teaching on Improving Students' Dance Skills

The purpose of this study is to enhance the effect of dance skill learning, learning motivation, and physical activity class satisfaction. Moreover, the outcome of these quasi-experiments illustrate the effects of Facebook Live-stream teaching, co-regulated learning (CRL), and experience-based learning (ExBL) on improving students' learning performance. The experimental design in this study was a 2 (CRL vs. non-CRL) × 2 (ExBL vs. non-ExBL) factorial pretest/post-test design. Four classes of a course titled ‘Physical Education: Dance' at university level were chosen for this study in one semester. According to the analysis of results, conclusions of this study are that students who receive ExBL have significantly higher physical activity class satisfaction than students who do not receive ExBL. In addition, in the case of ExBL teaching, the concurrent implementation of CRL can improve students' dance skill learning more than ExBL alone.
Adversarial attack and interpretability of the deep neural network from the geometric perspective

Deep learning has achieved significant success in various engineering fields. However, its drawback has also received considerable attention recently, i.e., it suffers from poor interpretability, weak robustness and difficulty for network training, which seriously affect the security and usability of deep neural networks. Therefore adversarial attacks and interpretability become the focuses of the next generation of artificial intelligence research. In this paper, we survey recent works on them from a novel geometric perspective. We reformulate the problems in traditional deep learning models from the viewpoint of manifold theory, and summarize several strategies for possible optimization of the deep networks based on interpretability. Finally, we state several challenges on the interpretability from manifold theory and outline possible future directions.
Maps for developing information competency of sportsman students in conditions of digital transformation

The progress to "cloud-based learning" and transition to "personalized learning" occur within digital transformation of education.Within this context, the authors analyse regulatory documents and recommendations outlined by the professional, teaching, and psychological communities and making the research relevant.The research question put up in the paper is: how to plot maps for developing the information competency of students in conditions of digital transformation.Theoretical substantiation is presented for the following phenomena under study: digital transformation, mapping, individual educational path, the information competency of students.It is pointed out that mapping is the process of creating maps for reducing the unpredictability effect and solving the problem of choice, a way of visualization of the future, and a strategy of one's self-development.It is highlighted that the individual educational route is the authors' approach to self-fulfilment in the real and virtual world.They describe the approach to understanding the student information competency as the key meta-subject educational one.This competency consists of the cognitive, motivational, and activity-based components which are provided with details by students via "understanding", generating their own meanings, and enriching their subject experience.In the paper, the stages of pedagogical support and fulfilment of maps for developing the said competency are described, too: the ascertaining one, transforming, and analytical ones.The pedagogical experience of mapping is summed up which is associated with the students' plotting and fulfilling various types of maps outlined by the authors: subject maps, meta-subject (mental) maps, portfolio maps as the digital footprint, start-up maps.The total of various maps represents the databases and analytical methods of their research.For studying the former, the authors used the expert appraisal method and applied some psychological techniques.The principal research results can be summarized by the statement: in the period of digital transformation and the pandemic, maps have to be plotted for settling emotions in conditions of lockdown and uncertainty, for supporting the relevant student initiatives, and for shaping their profound unmistakable "digital footprint", which characterizes the students' high information competency development level.
Socio-Pedagogical Aspects Of Legal Culture Development In STUDENTS

The article comprehensively analyzes the scientific analysis of the socio-pedagogical aspects of improving the legal culture of students. Methodological aspects of improving the legal culture of the population, especially young people, analysis of pedagogically effective methods, forms and factors, as well as effective mechanisms to ensure the effectiveness of modern technologies to improve the legal culture of students, the formation of their legal culture. awareness and thus effective legal awareness is important to study modern technologies.
What’s Coming Next?

The need and desire for forecasts is explored, starting with the weather. A case study is made of the 2020 Primary process to select a Democratic Party presidential campaign, and how predictions were overturned by events. Predictions of doom are investigated, ranging from Malthus to the Millennium Bug. Some of the pressing threats that we face in current times are discussed in light of our incomplete understanding of uncertainty.
Data Besar Implementasi NoSQL Column Store Menggunakan Apache Accumulo Untuk Membangun Model Infrastuktur Big Data: Implementasi NoSQL Column Store Menggunakan Apache Accumulo Untuk Membangun Model Infrastuktur Big Data

As the development of the digital world and technology, making data growth becomes very fast. This fast data growth gave rise to a new phenomenon, Big Data. However, the database that has been used, namely RDBMS has limitations in managing Big Data. Therefore, in this final project a Big Data infrastructure model will be built by implementing NoSQL using a single node and multi node cluster Apache Accumulo with seven nodes. The infrastructure that has been built will be tested for performance based on the results of runtime, throughput and latency using YCSB. The test is done based on variations in data size (500MB, 1GB, 1.5GB and 2GB), variations in the number of nodes (1, 4, 5, 6 and 7 nodes) used and variations in testing time (morning, afternoon and night). Testing uses YCSB core workload, namely workload A, B, C, D, E, and F which consists of two processes, load and run. From the results of testing and analysis of data readings obtained, runtime is influenced by the throughput and latency generated. The optimal infrastructure model is a multi node cluster using 4 nodes and the optimal time is at night.
Smart Door / COVID-19 Face Mask Detection

January 27 2020, a day that will be remembered by the Indian people for a few decades, where a deadly virus peeped into a life of a young lady and till now it has been so threatening as it took up the life of 3.26 lakh people just in India. With the start of the virus government has made mandatory to wear masks when we go out in to crowded or public areas such as markets, malls, private gatherings and etc. So, it will be difficult for a person in the entrance to check whether everyone one are entering with a mask, in this paper we have designed a smart door face mask detection to check whether who are wearing or not wearing mask. By using different technologies such as Open CV, MTCNN, CNN, IFTTT, ThingSpeak we have designed this face mask detection. We use python to program the code. MTCNN using Viola- Jones algorithm detects the human faces present in the screen The Viola-Jones algorithm first detects the face on the grayscale image and then finds the location on the colored image. In this algorithm MTCNN first detects the face in grayscale image locates it and then finds this location on colored image. CNN for detecting masks in the human face is constructed using sample datasets and MobileNetV2 which acts as an object detector in our case the object is mask. ThingSpeak is an open-source Internet of things application used to display the information we get form the smart door. This deployed application can also detect when people are moving. So, with this face mask detection, as a part to stop the spread of the virus, we ensure that with this smart door we can prevent the virus from spreading and can regain our happy life.
Data Operations and an Application for Translating Russian Speech to French Text

In 2006, the French government discretely asked for an assessment of the highest accuracy means available at the time to translate Russian speech into French text. One of us was working with the Grenoble HP site at the time, and so promptly assessed the possibilities using existing speech-to-text and translation software (Nuance and Speechworks). This article describes the surprisingly circuitous route to maximum accuracy (90.3%), and in so doing provides an unexpected insight into discerning the native language of software designed for speech-to-text and translation applications.
Triangulation between Bernoulli Distribution and Laplacian Autoregressive Model to Predict Probability of Increase in Stock Price

Stocks are one of the aspects that affect the economy in the world. In the stock market, the price of a stock changes every time. Investors who are able to predict the increase in stock prices will tend to get profit, but investors who are unable to predict the increase in stock prices will tend to experience losses. This study aims to find statistical models and use them to predict the probability of an increase in the price of a stock in the stock market. The method used in this study is a literature study regarding stochastic models and selected suitable stochastic models. This study finds stochastic models and uses them to predict the probability of an increase in stock prices. The novelty in this research lies in the stochastic model triangulation. The increase in stock prices is predicted using two stochastic models, namely: Bernoulli and autoregressive. The decision on stock prediction is determined by the results of the triangulation of the two methods. The proposed method in this study has the advantage that decision making is based on more than one stochastic model. The results of this study can be applied to the financial sector, especially in the stock market.
Role of Adult Education in Conflict Resolution for Rural Development in Abia State

Adult education is a systematic and self-educating activity which aims at gaining new forms of knowledge, skills, attitudes, or values, or any form of education ( formal, informal or non-formal) given to adults based on their felt- social, economic, political and cultural needs to enable them adjust fully to life changes. From adult education perspective, conflict resolution is the process involved in facilitating the peaceful ending of disagreement and retribution among individuals which invariably leads to rural development. In Nigeria, a critical assessment of rural development shows a gross mismatch between the lines of ideal and reality in spite of numerous contributions of the government and support of organizations. Nigeria is yet to achieve the desired expectations as clamored by her citizens which is observably seen in high rate of poverty, insurgency, militancy and communal crisis. The paper examined the move towards the role of adult education in conflict resolution in achieving peace to cause rural development in Abia state as it concerns reshaping spaces in agriculture, economy, and education, fighting hunger, politics, security, health and social aspect of human endeavor. Last year, the world cost of violence was about $14.3 trillion. One can look forward to a more equal and sustainable world if there are more peaceful and inclusive societies. The researcher recommended among others that the government should engage adult education experts to design programmes that will enlighten people on the importance of peace and unity for rural development.
Private Security in Ethiopia: Key Challenges and the Ways Forward

This study sought to explore private security in Ethiopia focusing on the challenges that hindered it to provide effective security service to its clients.To this end, the study employed a qualitative research method.Data were generated from both primary and secondary sources using in-depth interviews, focus group discussion, observation, and document review.Primary data were purposively gathered from lawmakers, security service providers, law enforcement organs, and private security service users.They are identified as the major actors that have a direct relevance to the subject under investigation.Secondary data were consulted from pertinent legislations and other materials.Thematic analysis was used to analyze the data.The study found that the major challenges as regards private security are lack of comprehensive legal and policy frameworks, absence of institutional arrangements, lack of standardized training and education.Given these, the researcher, among other things, suggested strong normative frameworks, institutional arrangements, standardized training along with periodic evaluations.
Guides and Tutorials: Effective Communication 1 & 2: The CRAAP Test

This guide will help you with all your research needs in both Effective Communications 1 and 2.
Generative Adversarial Network for Multi Facial Attributes Translation

Recently, Generative Adversarial Network (GAN) based approaches are applied in facial attribute translation. However, many tasks, i.e. multi facial attributes translation and background invariance, are not well handled in the literature. In this paper, we propose a novel GAN-based method that aims to get the target image that performs better within modifying one or more facial attributes in a single model. The model generator learns multi-points by inputting a re-coded transfer vector, ensuring the single model could learn multiple attributes simultaneously. It also optimizes the cycle loss to enhance the efficiency of transferring multi attributes. Moreover, the method uses the adaptive parameter to improve the calculation method of the loss function of the residual image. The results are also compared with the StarGAN v2, which is the current state-of-the-art model to prove the effectiveness and advancedness. Experiments show that our method has a satisfactory performance in multi facial attributes translation.
Blockchain Technology and Implications for Accounting Practice

Purpose - The article discusses the possible implications of blockchain for accounting practice and what further developments are needed to create an integrated accounting system on blockchain technology. The focus is on both accounting and auditing. Approach – The article follows a structure approach by identifying characteristics of blockchain technology to discuss the implications for accounting practice. Findings - The instant verification and immutability features of blockchain systems provide for the integrity of data for both accounting and auditing purposes. However, the intensive use of blockchain for accounting information purposes depends on different and cheaper validation processes. The complexity of different accounting transactions with related estimates and uncertainty needs to be captured correctly on blockchain through use of interventions such as smart contracts without limited human invention to be successful. The so-called triple-entry accounting provides for the secure capturing of accounting information for use by different stakeholders, but currently does not change the double-entry accounting system to prepare financial statements. Confidentiality might become an issue with the real-time distribution of information among different stakeholders. Therefore, entities might opt for the use of private or consortium blockchain systems. Blockchain creates an avenue for continuous audit, but the independence of the auditor might be compromised. Value – The article identifies the possible effect of blockchain on accounting practice and what further developments are still needed to create an integrated accounting system on blockchain technology.
ODIS – Orderly Demeanor Inspection System

In the current world, time is considered an immense treasure. People never want to waste the time and schedule their day with prioritized works. The thing people fail to understand is trying to balance the time they forget to balance their mental states. For a healthy run of the body, we not only require a healthy exterior but also a fruitful interior. When our mind runs smoothly then the body reflects the same. Failing to understand this concept the people ignore their mental balance, resulting in effects such as stress, sensation to commit extreme measures, etc. This type of behavior is always dangerous to them and also to the society around them. To contain this type of sociopathic behavior, psychologists and other professionals were trying to develop a system which detects such type of behaviors. But in this paper, we propose a system that intends to cut the problem in its roots than identifying it later. The system proposed is a semi-robotic interface that interacts with the user in toil and solves their cause of distress and maintains a mental equilibrium of that particular user. The introduction of this system brings a drastic change in the society which always struggles to maintain peace and equilibrium with itself.
Risk Analysis and Assessment Toolkit

The purpose of the Risk Assessment toolkit is to depict how organizations can manage risks associated with projects, systems, applications and departments. Before an organization can use the toolkit as described here, they will need to complete the administrative side of risk management. This includes formulating policies, completing SWOT analysis on each proposed asset, project feasibility analysis and they must complete asset valuations. Once, that is completed the organization will move on to the assessment phase. In the assessment phase an organization will utilize the toolkit to discover the impact that the risk will have on their organization and they will be provided a summary of the impacts of each risk. Next, the organization will need to complete the alleviation process. In the alleviation process the organization will review what options they have, what remediation techniques they can perform, and they will continue to monitor major assets. Once an organization completes these three methods of risk management multiple times, their organization will experience significantly less risks and increased capabilities.
Satiating A User-Delineated Time Constraints While Scheduling Workflow in Cloud Environments

Cloud computing is used to achieve sustainability in terms of computing. It reduces energy and resource consumption. Most of the companies have been moving their applications to the cloud to reduce power, energy re-source, and carbon emission. Today's computing landscape is rapidly shifting toward creating applications to leverage Cloud platforms to have necessary features such as elasticity, virtualization, low cost, and pay-per-use. Cloud computing's rising demand and versatility are achieving acceptance in the research community as a means of implementing large-scale electronic systems in the format of workflows (set of tasks). One of the most important objectives of this effort is to trim down makespan which is the total period taken by the resources to complete all workflow activities. Another foremost objective of this work is to satiate all the user-delineated time constraints while scheduling workflow activities.
Impact Of Cyber Crime On The Society During Lockdown Period

The aim of this paper is to analyse the impact of cyber-crime on the society during the period of lockdown. The concept of cyber-crime and the new hacks to extract money from the citizens and how it has impacted the common people at large is explored. The result from this study shows that computer and internet is a potent platform for the criminals and how it has impacted the lives of the people in a negative way. The discussions are made from the findings and the paper addresses how the internet and computer can be utilised properly in a safe and secured way adopting various precautions and measures to secure the usage and on the other hand increasing the awareness on how not to be trapped in any kind of web by criminals in the cyber world.
Fake News Detection based on Machine Learning Algorithm with Performance Improvement

News is crucial part of our life. In everyday life current news are useful to improve information what occur all throughout the planet. So the greater part of people groups favor watching news the vast majority of the people groups by and large incline toward perusing paper promptly in the first part of the day getting a charge out of with cup of tea. In the event that news is phony that will delude people groups here and there counterfeit word used to get out reports about things or it will influence some political pioneer positions in view of phony news. So it's vital to track down the phony news. This exploration proposed a streamlined framework to identify counterfeit news, yet now daily's information on web or web-based media is expanding unfathomably and it is so chaotic to distinguish news is phony or not by looking all information and it is tedious so we use grouping procedures to arrange tremendous information. This paper proposed fake news detection system based on the classification approach such as Naive bayes (NB), Support vector machine (SVM), K Nearest Neighbor (KNN) and Decision Tree (DT).
다문화가정 학습자를 위한 한국 전통춤 교육방안-마이크로 러닝을 활용한 날뫼북춤을 중심으로-

The purpose of this research is to find ways to provide Korean traditional culture education for students from multicultural families through the development of learning models using micro-learning techniques. This research designs class models by applying multi-store models and task memory models, which serve as the theoretical background of micro-learning techniques, that leads to memory recall-memory storage-memory activation, and activate learners'' cognitive abilities to reach medium and long-term memory allowing learners to store what they have learned as work memories for longer periods of time and utilize them. To this end, this research presents teaching-learning case utilizing motion capture of Nalmoebukchum(Nalmoe Drum Dance). It is expected that Korean traditional dance education using micro-learning techniques will reduce mental difficulties that multi-cultural learners may feel while settling in Korea and enhance cultural education and social adaptation by gaining emotional stability through culture. (Youngnam Cyber University)