Reviewerly/exHarmony huggingface dataset:
Event-based White Blood Cell Classification from Nailfold Capillaries

Detecting absorption gaps in a nailfold capillary can be used to quantify an estimation of white blood cells (WBCs). Previously, the absorption gaps in a nailfold capillary were usually measured using a standard camera on a fingernail. However, difficulties arise due to low visibility of the gap, the small size of the capillaries, the high speed of WBC movement, and the lack of contrast between the capillary and its environment/background. To address these issues, an event-based WBC image is utilized as input data to detect WBC existence in the nailfold. Specifically, we utilize a dynamic vision sensor (DVS) camera, which can detect a change in luminance on a pixel basis and can produce a stream of asynchronous event output at a microsecond temporal resolution. With the event-based WBC dataset, we conduct a classification task using three different machine learning algorithms: k-nearest neighbors, the decision tree, and random forest. The best result is from random forest with 75.51% accuracy. Based on our evaluation, event-based WBC classification is a promising new approach to detecting WBC presence in nailfold capillaries.
Texts and ‘Minjung’ by Shin Chae-ho in the 1920s

The word ‘Minjung’, which was vigorously presented in the Declaration of the Korean Revolution(1923), was never used in the general discussion of the Joseon History(1924). As a result of processing the two texts using the text mining method and analyzing the lexical network based on them, there was a clear difference in the text structure between the Revolutionary Declaration and the General Discussion as well as the usage of “Minjung”.BRFour main texts from the late 1910s to the late 1920s were added to the analysis target. As a result, it was confirmed that there was a close correlation between the use of ‘Miniung’ and the text genre in movement writing (Revolutionary Declaration, The Declaration) and novel writing (Dream Sky, Dragon and Dragon). On the other hand, in academic writing (General Discussion, Introductions), neither the text-oriented binary opposition structure nor the use of “minjung” were observed.BRFinally, in Shin Chae-ho’s thought in the 1920s, ‘Minjung’ was not an indicator of the renewal of nationalism or acceptance of anarchism, but a boundary and threshold that revealed differences by genre of text.
Big Data Backup Deduplication : A Survey

The massive explosion in the field of data such as images, video, audio, and text has caused significant problems in data storage and retrieval. Companies and organizations spend a lot of money to store and manage data. Therefore, there is an urgent need for efficient technologies to deal with this massive amount of data. One of the essential techniques to eliminate redundant data is data deduplication and data reduction. The best technique used for this purpose is data deduplication. Data deduplication decreases bandwidth, hard disc drive utilization, and backup costs by removing redundant data. This paper focuses on studying the literature of several research papers related to data deduplication for various techniques that several researchers have proposed. It summarized multiple concepts and techniques related to deduplication and methods used to improve storage. The data deduplication processes were examined in detail, including data chunking, hashing, indexing, and writing. Also, this study discussed the most critical problems faced by the data deduplication algorithm.
Comparison of Characteristics of Technical Barriers to Trade by region according to Overseas Expansion of Companies: Focusing on the Fishery Industry

The purpose of this study was to investigate the characteristics of each country’s Technical Barriers to Trade(TBT) notification according to each region as the TBTrelated regulations in the fisheries became more sensitive. The research data used the overseas overseas technical regulation information system of the Korean Agency for Technology and Standards and includes 201 notices affecting Korea. The study areas were Africa, Asia, Europe, North America, Latin America. As the analysis method, the text mining technique was applied, and there are word frequency and N-gram. As a result, the commonly extracted words include aquatic products production, processing, and packaging, as well as compliance with standards and technical regulations. By region, developing countries in Africa, Asia, Latin America showed formal regulations such as additional certification and an increase in required documents. Conversely, developed countries such as Europe and North America showed word connectivity related to practical regulations such as environmental protection and hygiene. Korea is in a position to respond to both practical and formal regulations at the same time. Therefore, it should be possible to evade regulations on technical barriers to trade through technical support such as Korea's fisheries standards to host countries.
A study on the Influence of the Self-Directed Learning of Post-adolescents on the Career Adaptability : mediating effect of the self-efficacy of career decision

This article aims to verify the mediating effect of the self-efficacy of career decision in the relationship between self-directed learning and career adaptability of post-adolescents. The subjects of the study for analysis were 316 university students in Daegu and Gyeongbuk. The results of the study show. First, post-adolescents the self-directed learning and its sub-variables including learning motivation, learning strategy, self-awareness in order has a meaningful effect on the career adaptability. Second, post-adolescents the self-directed learning and its sub-variables including learning strategy, self-awareness, learning motivation in order has a meaningful effect on the self-efficacy of career decision. Third, post-adolescents the self-efficacy of career decisions and its sub-variables including goal selection, job information, future plans in order has a meaningful effect on the career adaptability. Fourth, the analysis result of the correlation between the self-directed learning and the self-efficacy of career decision shows that the self-directed learning and the career adaptability and the self-efficacy of career decision have a meaningful positive correlation with each other. And, the results of multiple regression analysis and Sobel Test show that the self-efficacy of career decision has a meaningful partial mediating effect in the relationship between the self-directed learning and the career adaptability.
Confluence Framework: Proving Confluence with CONFident

This paper describes CONFident, a tool which is able to automatically prove and disprove confluence of variants of rewrite systems: term rewriting systems, conditional term rewriting systems (using join, oriented, or semi-equational semantics), and context-sensitive term rewriting systems. We introduce a new proof framework to generate proof trees by combining different techniques for proving confluence (including modular decompositions, checking joinability of (conditional) critical pairs, transformations, etc.). We also use external tools for proving termination and operational termination (mu-term), or feasibility (infChecker) and deducibility (Prover9).
Topology-Preserved Human Reconstruction with Details

Due to the high diversity and complexity of body shapes, it is challenging to directly estimate the human geometry from a single image with the various clothing styles. Most of model-based approaches are limited to predict the shape and pose of a minimally clothed body with over-smoothing surface. While capturing the fine detailed geometries, the model-free methods are lack of the fixed mesh topology. To address these issues, we propose a novel topology-preserved human reconstruction approach by bridging the gap between model-based and model-free human reconstruction. We present an end-to-end neural network that simultaneously predicts the pixel-aligned implicit surface and an explicit mesh model built by graph convolutional neural network. Experiments on DeepHuman and our collected dataset showed that our approach is effective. The code will be made publicly available.
A study on ethical management of South Korean Airlines

The purpose of this paper is to study the ethical management of South Korean Airlines. The importance of ethical management for sustainable management of firms has been gradually growing. Ethical management is divided into internal ethics and external ethics. Earnings management is known to represent internal ethics, while CSR is known to represent external ethics. Earnings management is measured by discretionary accruals, and CSR is measured by charitable contribution expenditures. The results of the analyses indicated that South Korean airlines' discretionary accruals were large while their charitable contribution expenditures were small. South Korean airlines can be regarded to practise more earnings management while conducting fewer charitable contributions. South Korean airlines are judged to be unethical both internally and externally. This paper is meaningful in that it verified the ethical management of airlines that emerged as a matter of national interest in South Korea in recent years.
Ecommerce based on Cloud Computing: The Art of State

The emergence of several computing paradigms, the most recent cloud computing, has resulted from significant technological advances in the information and communication technologies (ICT) sector in the last decades, with the most significant improvements in internet services and virtualization techniques. Individuals and businesses may access various cloud services and solutions from some big cloud service providers worldwide. As a result, more businesses are migrating to the cloud, causing the cloud services industry to expand. Organizations can profit from cloud technology in various ways, but there are also dangers and issues connected with this phrase. Cloud computing is a way to improve Ecommerce by making it easier for people to buy and sell things. This paper explains the concept and features of cloud computing and how cloud computing can help Ecommerce.
Extended Abstract: Human-AI Teaming: Cases and Considerations for Professional Communicators

Increasingly, professional communication is being produced by machines—that is, artificial intelligence (AI)-based systems that either assist human writers or that produce writing mostly on their own. As writing machines become more advanced, human professional communicators will be called on to partner with these machines as collaborators in various roles. This panel—consisting of three papers presented by five authors—considers some of the implications extending from this technology development: How is professional communication changing because of human-machine teaming (HMT)? What new skills and literacies will be required—from machines as well as humans—as we increasingly partner with machines to create professional communications?
The Physical Cause of Planetary Perihelion Precession

According to the revised gravitation formula, the gravitational force on planets in the solar system is mainly provided by the sun, and only when the planet is far enough from the sun to treat the sun as a particle, the gravitational force on the planet coincides well with Newton's gravitational formula. The closer the planet is to the sun, the more the gravitational force on the planet deviates from (greater than) the value calculated by Newton's universal gravitation formula. The precession of the planet's perihelion is due to this property of gravity.
Determining the Most Effective Machine Learning Techniques for Detecting Phishing Websites

Consumer tastes have moved away from conventional shopping and toward electronic commerce due to the Internet’s fast growth. Rather than conducting bank or shop robberies, today’s criminals use a range of sophisticated cyber methods to track down their victims. Attackers have developed new ways of deceiving customers, such as phishing, using fake websites to gather sensitive information such as account IDs, usernames, and passwords. The semantic-based nature of the assaults, which mainly leverage the vulnerabilities of computer users, makes establishing the authenticity of a web page more difficult. Machine learning (ML) is a typical data analysis technique that has shown promising results in the battle against phishing. The article examines the applicability of machine learning methods for identifying phishing attempts and their advantages and disadvantages. Specifically, a variety of machine learning methods have been explored to find appropriate anti-Phishing technology solutions. More significantly, we used a wide range of machine learning methods to test real-world phishing datasets and against several criteria. To detect phishing websites, six different machine learning classification methods are employed. The Random Forest classifier had the most outstanding possible accuracy of 97.17% in this research, while the Gradient Boost Classifier had the highest achievable accuracy of 94.75%. The Decision Tree classifier has a provisioning accuracy of 94.69%. In contrast, Logistic Regression has a provisioning accuracy of 92.76%, KNN has a provisioning accuracy of 60.45%, and SVM has 56.04%. We showed that KNN has trouble detecting phishing sites since it hasn’t been updated in terms of accuracy. Decision trees are almost similar to Gradient Boosting in terms of performance.
GyanSagAR 1.0: An AR Tool for K-12 Educational Assistance

With the slowly shifting dynamics of education from simple textbook recitals to practical experiments, video lectures, and interactive classrooms, Education and learning domain is slowly adopting the miracles of technology to make this process exciting and enjoyable for students at all levels. While these solutions may have been the best alternative to the old school teaching and learning method, the COVID-19 pandemic brought a colossal change to this system. Keeping this in mind, we have applied the concept of Augmented reality in education and developed a tool- GyanSagAR 1.0 for K-12 educational assistance. Our tool currently supports common STEM subjects such as physics, chemistry, mathematics, and biology which will help students to visualize various concepts. The user interface is designed keeping accessibility and ease of usage in mind. It has many advantages- it's a complete learning package that will enrich the user experience and will promote open-ended learning in students.
Genesis – an Architectural Pattern for Federated PLM

Abstract Product Lifecycle Management (PLM) is a key capability for any organization developing and/or maintaining complex systems. This paper presents a modular architectural pattern for realizing a federated PLM capability from integrating multiple engineering discipline specific development environments. This open the possibility for replacement of individual environments, while maintaining the overall development system landscape. Thus, providing a desired flexibility in adapting to future organizational challenges at comparatively low cost.
Intelligent Traffic Monitoring System

The increased popularity of private automobile has result in more congested urban traffic. As a result, traffic has become one of the most serious issues in major cities throughout the globe. Congestion and accidents are two major traffic challenges, both of which have resulted in significant time loss, property damage, and pollution. This project entails the development and deployment of a computer vision and image processing-based intelligent and automated traffic control system. This technology recognizes the number of cars on each route and assigns an optimal amount of waiting time based on the the amount more cars on every route. This system is entirely automated and may be used to replace the traditional, dynamically regulated transportation system with a fixed-time transportation system. The planned method has the potential to significantly reduce traffic congestion in congested cities via preserving it considerable number of person time that would otherwise be wasted waiting on congested highways. This research focuses, low-cost image analysis, and load balancing.
Factors influencing the perception of corruption (a multilevel analysis in Africa)

Many developing countries suffer high levels of corruption, which contributes to the divergence in economic development between more developed and developing countries. Corruption perceptions play a key role in forming a culture that is more or less tolerant of corruption, which contributes to its persistence. Individuals who have high perception of corruption believe that bribes must be paid. Customers will be more likely to accept a bribe if they believe many people pay bribes. The importance of this research is that it contributes to the micro-level research tradition by providing a deeper understanding of the factors that influence corruption perception. What factors influence the perception of corruption? I conducted an empirical analysis using 2017 Afrobarometer survey data, focusing on 34 democratic African countries. The study finds that those who are relatively poor are more likely to have a high perception of corruption and develop an unfavorable view of corruption than those with high income. The study also provides the potential mechanisms involved in the perception of corruption, finding that individuals with high access to information through the media, and higher education have a higher perception of corruption.
Novel no-reference multi-dimensional perceptual similarity metric

Enormous progress has been made in the domain of determining image quality. However, even the recently proposed deep learning based perceptual quality metrics and the classical structural similarity metric (SSIM) are not designed to operate in the absence of a good quality reference image. Many of the image acquisition processes, especially in medical imaging, would immensely benefit from a metric that can indicate if the quality of an image is improving or worsening based on adaptation of the acquisition parameters. In this work, we propose a novel multi-dimensional no-reference perceptual similarity metric that can compute the quality of a given image without a reference pristine quality image by combining no-reference image quality metric (PIQUE) and perceptual similarity. The dimensions of quality currently explored are in the axis of noise, blur, and contrast. Our experiments demonstrate that our proposed novel no-reference perceptual similarity metric correlates very well with the quality of an image in a multi-dimensional sense.
Cross-Modal Transfer Learning Methods for Alzheimer's Disease Diagnosis

In this paper we propose cross-modal transfer learning for Alzheimer's disease detection. We use positron emission tomography (PET) and magnetic resonance imaging (MRI) brain scans from ADNI to train convolutional neural networks (CNNs) on one modality and fine-tune it on the other modality. We start by showing that cross-modal transfer learning approaches outperform CNNs trained from scratch on a single modality. We then show that cross-modal transfer-learning also outperforms multimodal approaches using the same data.
Natural Language Semantic Answering: Application to Medicinal Plants and Coronavirus

This paper describes PryRe (Preguntas y Respuestas) {Questions and answers}, a question answering system that receives as input a question in Spanish and returns the answer. An information retrieval algorithm identifies the meaning of the question using its semantic properties. To do this, it is necessary to implement natural language processing modules. PryRe identifies the question using a triplet R (C, V), where R is the relation or link, C is the concept or main idea, and V is the value of the concept. For example, in the question: ¿Cuál es la hierba que mejora la digestion? {What is the herb that improves digestion?}, the answer is Manzanilla {Chamomile}. To obtain this response, a process of query analysis and design is executed. The analysis consists of identifying the answer, we call this process the semantic identification of the question. The PryRe algorithms are explained in detail. The tests have been carried out with some sources on herbalism [15] and on 2019-nCoV [14] in an Ontology; they show an acceptable accuracy of 83%. Resources used in this work are (1) the OM notation, which is used to describe ontologies, and (2) the deductive capability of PryRe. PryRe consults this ontology to answer the questions using cases that are described in its algorithm.
Using Support Vector Machine for Classification and Feature Extraction of Spam in Email

We provide an overview of recent and successful content-based e-mail spam filtering algorithms in this article. Our main focus is on spam filters based on machine learning and variants influenced by them. We report on significant ideas, methodologies, key endeavors, and the field's current state-of-the-art. The initial interpretation of previous work demonstrates the fundamentals of spam filtering and feature engineering in e-mail. We finish by looking at approaches, procedures, and evaluation standards, as well as exploring intriguing offshoots of recent breakthroughs and proposing directions of future research.
General English Learning Education from the Viewpoint of Training for Interpreters

Each discipline or science has its own research object.Only with a clear research object can researchers and scholars effectively carry out targeted cognition and practical activities, and only then can they understand the targeted cognition and problems arising from practical activities and carry out research and summarize.Pedagogy is a subject whose research objects are educational activities.While education is not a natural existence, but an extremely complex social existence.It is a social activity system constructed for people to cultivate people.Pedagogy takes the educational activities of cultivating people as the research object.It is a discipline that studies educational phenomena and problems, reveals the essence of education, the laws of education, and explores the value of education and the art of education.In recent years, with the continuous improvement of China's comprehensive national strength and the rapid development of economy and technology, English, especially interpreting has received more and more attention.This research aims to find out how to explore the unresolved problems that are worthwhile in a large number of interpreting studies with the development of the times, and propose effective solutions, in the hope of inspiring and providing new ideas for interpreting research.
Oral Communication in Advertising Copy: Reviews and Implication

There is a natural contradictory tendency in consumers towards advertising.They tend to ignore or actively avoid the messages conveyed through advertisements.However, when the proposed messages in advertisements are communicated in oral form, they may be able to bypass consumers' mental barriers and work effectively.The origin of texts is inseparable from oral language, which has been an essential tool of communication since ancient times.In the current age of "secondary orality" where media platforms are highly developed, oral expression is still critical.For example, in the process of advertising, when text information is transformed into oral expression especially with certain rhythms, rhymes or a fixed mode, consumers are more likely to precisely understand the message.For the brands, they can produce advertisements that not only correspond to their core values but also better create a friendly image.However, oral communication in advertising also has its limitations for regionality and variabilit.