Reviewerly/exHarmony huggingface dataset:
An Analysis on International Trade Relation between Korea and China using Text Mining and SNA after Covid 19

The objective of this study is to analyze international trade relation between Korea and China using text mining and SNA(Social Network Analysis) for the three Covid 19 years from 2019 to 2021. For the analysis, text mining analysis was conducted through keywords ‘China Export’ and ‘China Import’. And then, key issues were analyzed by using keyword frequency analysis. Finally, we analyzed centrality tests such as the degree centrality, eigenvector centrality, and the convergence of iteration correlation (CONCOR) using the social network analysis. As a result, Korea seems to show the most interest in internal and external trade risks in relation to Chinese imports and exports as it is highly dependent on China.
Education of Aristocratic Women in the Late Joseon Dynasty Found from Yeojachohak and Gyujungyoram of the Kawai Collection

Kim Jong-su’s Yeojachohak(1797) and the Korean manuscript Gyujungyoram, housed in the Kawai Collection of Kyoto University, Japan, is a comprehensive instruction book for aristocratic women, showing the characteristics and significance of women’s education in the late Joseon Dynasty. First, this study confirmed that the source of the manuscript Yeojachohak and assumed that it was transcribed in 1843 by a person not from the Uiseong Kim family. Second, according to the manuscript, the social refinement required of aristocratic women in the late Joseon Dynasty was information about the eight provinces of Joseon, the structure of central and regional bureaucracies, the Gwageo(highest level state) examination, and the development process of faction politics. Third, genealogy education and the reinforcement of paternal order were essential to yangban women’s education in the late Joseon Dynasty. Thus, women’s education in the late Joseon Dynasty consisted of Confucian gender norms that women must perform in everyday life, knowledge acquisition as social refinement, and genealogy education for self-awareness as daughter.
Why Should Middle School Students Learn ‘Jungdong Haengsung(征東行省)’? -Locating the Learning Elements in the Context of the 2015 History Curriculum-

In the 2015 revised curriculum for middle school history, the minor subject [Mongol Interference and Reform] dealing with Goryeo-Mongol relations consists of four [learning elements]: Jungdong Haengsung, Kwon Moon-sejok(權門世族), King Gongmin’s Reform, and Shinjin Sadaebu(新進士大夫). They have a relationship centering on 〈Reform of King Gongmin〉, and 〈Jungdong Haengsung〉 is a learning element representing the Mongol empire’s ‘interference’ and is the subject of 〈Reform of King Gongmin〉.BR However, in addition to Jungdong Haengsung, there are about 10 cases of the Mongol empire’s ‘interference’ in textbook and many other than Jungdong Haengsung were nominated as [learning elements] representing the Mongol empire’s interference in the curriculum revision process. Two factors are believed to have contributed to the fact that 〈Jungdong Haengsung〉 was finally selected as a [learning elements] representing the Mongol empire’s ‘interference’ after competing with other cases.BR One is that the content of ‘political interference’ represented by Jungdong Haengsung is more suitable in light of the ‘achievement standards’ with the main content of understanding the changes in political forces starting with the reform of King Gongmin. The other is that Jungdong Haengsung can reveal the groundbreaking of King Gongmin’s Reform and has the constancy to maximize such groundbreaking.BR The learning element 〈Jungdong Haengsung〉 does not have completeness and suitability in itself, but is a learning element that is established through the role of supplementing and highlighting its meaning by belonging to another learning element, 〈Reform of King Gongmin〉, whichoccupies an important position in the textbook narrative.
A Comparative Analysis of High School East Asian History Textbooks in Korea and Taiwan

In this paper, I analyzed the high school East Asian History Textbooks in Korea and Taiwan. The textbooks used for comparison are East Asian History(2019) published by Chunjae Education Inc., History2(2020) published by Nani Book Enterprise co.(Nani ver.) and the Sanmin Book Co.(Sanmin ver.)BR In terms of narrative, East Asian History focused on the history of Korea, China, and Japan, while History2 arranged not only China, Korea, and Japan but also Vietnam and Southeast Asia. In terms of content, both East Asian History and History2 emphasized the common elements of East Asian Cultural Area. East Asian History and History2(Nani ver.) critically accepted Nishijima’s ‘East Asian World Theory’, but History2(Sanmin ver.) did not. In the description of the modern era, East Asian History emphasized on the Japanese imperialist invasion and the anti-Japanese national movement. History2(Nani ver.) emphasized Vietnam’s anti-imperialist national movement and the development of the East Asian socialist regimes. But History2(Sanmin ver.) emphasized the colonial rule of Japanese imperialism rather than the anti-imperialist national movement.
Non-Invasive Sensor-Based Multi-Output Networks for Predicting Multiple Blood Components Levels

In healthcare industries, non-invasive sensor technology has played an important role in gathering biometric information without blood sampling for each patient. Existing studies have attempted to predict blood component levels based on non-invasive sensor coupled with machine learning models. However, they focused on constructing a single output model that predicts only one blood component level. In this study, we propose a multi-output predictive model that can predict the multiple blood components levels simultaneously based on non-invasive impedance sensor data. Results show that our method improves predictive performance compared to the single output models. Furthermore, we use Shapley additive explanation to identify important sensor variables that achieve efficient sensor design reducing the cost of data collection. To the best of our knowledge, this study is the first attempt to use non-invasive impedance sensor data to predict multiple blood components levels.
MFAS: Multimodal Fusion Architecture Search

We tackle the problem of finding good architectures for multimodal classification problems. We propose a novel and generic search space that spans a large number of possible fusion architectures. In order to find an optimal architecture for a given dataset in the proposed search space, we leverage an efficient sequential model-based exploration approach that is tailored for the problem. We demonstrate the value of posing multimodal fusion as a neural architecture search problem by extensive experimentation on a toy dataset and two other real multimodal datasets. We discover fusion architectures that exhibit state-of-the-art performance for problems with different domain and dataset size, including the NTU RGB+D dataset, the largest multi-modal action recognition dataset available.
Comparing slopes: analysis of covariance

A useful variation on analysis of variance is analysis of covariance, ANCOVA. With ANCOVA, we can compare the slopes and elevations of two or more lines, the x-axis being a range of numbers. In comparison, with analysis of variance, all the independent variables are categorical. While comparing slopes and elevations is useful in itself, ANCOVA can also be used to reduce variation, and thus increase power, and to reduce the effect of a confound. While all this might sound technical, ANCOVA can be a real eye-opener. ANCOVA lets us isolate independent variables from each other, which can sometimes allow us to exclude variables as potential causes of a phenomenon.
Cloud Service Provider Selection Using Fuzzy Data Envelopment Analysis Based on SMI Attributes

A variety of business firms are moving towards the cloud after realizing the benefits and success of using cloud technology. With multiple cloud service providers having different features, selecting the best or ranking them becomes a tedious task. There are several multi-criteria decision-making models (MCDM) trying to handle the selection of the best cloud service provider problem. A significant amount of research focused on MCDM models using quality of service (QoS) characteristics, but not much research has been conducted to address the fuzziness inherent in data. Therefore, a suitable model for choosing suitable cloud service providers is proposed in this work to address this data fuzziness. The SMI attributes recommended by CSMIC, approved by ISO, are considered as the evaluation criteria for the evaluation of cloud service providers. In this research work, fuzzy DEA is used to compute the efficiency values of cloud service providers and modified Chen and Klein method is used to arrive at the final ranking of cloud service providers(CSPs).
A Holographic Future: Exploring the Capabilities of the Looking Glass Holographic Display

&lt;p&gt;&lt;em&gt;"&lt;/em&gt;&lt;em&gt;ME: “Hey SIRI. What do you look like?”&lt;/em&gt;&lt;/p&gt; &lt;p&gt;When I was completing my master’s degree, I pondered this question a lot. If SIRI or any AI had a face, what would it look like? &lt;/p&gt; &lt;p&gt;&lt;em&gt;SIRI: “I imagine I probably look like colourful sound waves.”&lt;/em&gt;&lt;/p&gt; &lt;p&gt;I believe that the future of artificial intelligence (AI) will have a face—or, more accurately, many faces. But, rather than a device or the company that makes it determining what an AI looks like (inevitably giving us 3D variations on an old Winamp visualizer), appearances will be determined and customized by individual users—and will be every bit as varied as the live human beings interacting with them. &lt;/p&gt; &lt;p&gt;In 2018, I demonstrated this idea in front of a class by creating the illusion of myself as an AI hologram. The set-up was simple—just a hacked CD jewel case and a cellphone video of my face, shot in a dark room with blue light—but the effect was convincing enough to capture the attention of my entire class, almost as if nothing else mattered but me and what I was presenting—as though I were the Wizard of Oz. &lt;/p&gt; &lt;p&gt;This experience made me realize just how useful holograms (or the illusion of them) could be in helping increase engagement and combat distractions in a classroom. &lt;/p&gt; &lt;p&gt;As is often the case, my curiosity eventually led me through the Looking Glass." --from the introduction&lt;/p&gt;
CLEAR: Causal Explanations from Attention in Neural Recommenders

We present CLEAR, a method for learning session-specific causal graphs, in the possible presence of latent confounders, from attention in pre-trained attention-based recommenders. These causal graphs describe user behavior, within the context captured by attention, and can provide a counterfactual explanation for a recommendation. In essence, these causal graphs allow answering "why" questions uniquely for any specific session. Using empirical evaluations we show that, compared to naively using attention weights to explain input-output relations, counterfactual explanations found by CLEAR are shorter and an alternative recommendation is ranked higher in the original top-k recommendations.
Raspberry Pi, A Sustainable Internet Connectivity Solution for Master Craftsmen: A Case Study of Kenya Technical Trainers College

The current educational disruption brought on by the Covid-19 epidemic has prompted a slew of investments and the usage of educational technologies for blended and virtual Learning. Despite the importance of online learning for emergency remote learning in most educational institutions, internet limitations in the country has remained a concern, making learning difficult. In response to this, KTTC in collaboration with COL, identified a Raspberry Pi technology to help and mitigate the internet issue. A study was done to ascertain this claim. A thousand trainees from five county regions in Kenya were chosen to undertake courses in master craftsmen. The courses were blended, that meant that trainers would take the trainees in face to face sessions and KTTC would provide internet connectivity through the use of Raspberry Pi to the training shades. A Raspberry Pi, would provide sufficient internet to 30 trainees sited at a distance of 70 meters from each other without the need to simulate existing internet connectivity. The study showed that it is possible to provide cheap internet to remote areas of a given region, hence enhancing the blended approaches to training. This case study recommends the implementation of Raspberry Pi use in sustainable internet provision. It further allows more research to be done to ascertain its findings.
Modern &amp; Resilient Cybersecurity The Need for Principles, Collaboration, Innovation, Education &amp; the Occasional Application of Power

For many years, the ITindustry have discussed how best to address the growing concern about data & IT security. In recent years the discussions have moved into both the board room 1 of most companies, into governments and also grown to be a concern of many citizens/individuals. Hacking has become a global enterprise. Companies, countries, and individuals are routinely targeted by nation states and shady corporations and not a week goes by without news of some terrible cybercrime, data breach or threat to the digital part of our modern lives. Mobile devices and digital services proliferate, and businesses, public services as well as most individuals have become ever more connected and dependent on the digital tools and this way of life. We have all become accustomed to the convenience and speed of these solutions, and while the benefits are naturally the driver for the digitization, it is obvious that it also opens the door, to more cyber risk.
An Efficient Phishing Website Detection Plugin Service for Existing Web Browsers Using Random Forest Classifier

An efficient phishing website detection plugin service was developed using machine learning technique based on the prevalent phishing threat while using existing web browsers in critical online transactions. The study gathered useful information from 27 published articles and dataset consisting of 11,000 data points with 30 features downloaded from phishtank. A unique architectural framework for detecting phishing websites was designed using random forest machine learning classifier based the aim and objectives of the study. The model was trained with 90% (9,900) of the dataset and tested with 10% (1,100) using Python programming language for better efficiency. Microsoft Visual Studio Code, Jupiter Notebook, Anaconda Integrated Development Environment, HTML/CSS and JavaScript was used in developing the frontend of the model for easy integration into existing web browsers. The proposed model was also modeled using use-case and sequence diagrams to test its internal functionalities. The result revealed that the proposed model had an accuracy of 0.96, error rate of 0.04, precision of 0.97, recall value of 0.99 and f1-score of 0.98 which far outperform other models developed based on literatures. Future recommendations should focus on improved security features, more phishing adaptive learning properties, and so on, so that it can be reasonably applied to other web browsers in accurately detecting real-world phishing situations using advanced algorithms such as hybridized machine learning and deep learning techniques.
Medication Alert - an Android Application

This is an android application software that alerts users with an automatic alarming system for medication and dosages. Most of the time patients cannot remember the exact time when they need to take the medicine. This app will alert patients about the time of medication, description of medicine, before-after meals, and so on. The alarm can be set with different types of pictures with the name of the medicines to overcome any kind of difficulty in reading. To develop this project, an incremental development strategy is followed to support customer requirements. Android Studio IDE, Java, and XML tools will be used for the implementation of the project. The system focuses on easy navigation and a good user interface. Many systems have been developed where new hardware and data storage is required but, in our work, we have made an attempt to develop a system that is economical, time-saving, and supports medication adherence.
Strategies for Education Quality Management

The quality of education is the main objective of the policies of the different levels of government – national, regional, local and institutional. In the article, based on the areas of quality and their characteristics according to the state educational inspection standard, variants of strategies relevant to achieving this main goal are summarized as a vision for the development of institutions, part of the system of preschool and school education. Other specific strategies are also offered, according to the state of quality in the institution and the measures to increase it. Needs for developing long-term plans are identified and practices for integrated approaches to achieving quality education are analyzed. Attention is paid to the role of cooperation in school organizations, the commitment and motivation of pedagogical teams to achieve institutional goals. In this regard, emphasis is placed on the integrated interaction between the participants in the educational process when choosing an appropriate strategy or a set of strategies depending on the conditions of the institutions' functioning and the achieved results of the activity. Attention is paid to the role of the survey of the satisfaction of teachers, parents and students with the quality of the educational service and the participation of interested parties in quality assurance as a basis for the effectiveness of the development strategies of the institutions.
Priority Analysis for Consumers’ Purchasing Factors of Seafood Online Using AHP Method

Purpose The purpose of this study to explore factors consumers prioritize when purchasing seafood online. The originality of the study lies on adopting AHP-based approach in analyzing prioritized purchasing factors of seafood online. Design/methodology/approach A survey was conducted targeting Korean consumers who have purchased seafood online. AHP method was applied to rank factors consumers prioritize before making decision. Findings First, product’s factor ranked first among other high level factors including delivery service, seller, online platform. Second, sanitation, taste, country of origin ranked first, second, third respectively, within product’s factors. Third, safe delivery, timeliness, information accuracy ranked first, second, third respectively, within delivery factors. Fourth, consumer reviews, consumer response ability, promotion ranked first, second, third within seller factors. Fifth, Personal information management system, credibility, user-friendliness ranked first, second, third, within online platform factors. Research implications or Originality To activate seafood online market, it is crucial to assure consumers that the seafood is well managed in a sanitary way from the production site to table. Existing government programs such as seafood traceability system, HACCP, and cold-chain infrastructure needs improvement. Due to highly perishable characteristic of seafood , delivery factors matter when purchasing online. Online platforms needs to continue to improve delivery service. Seafood products are mostly not branded and without objective information about their properties. Creating quality classification and seafood brands are likely to help consumers chose seafood online.
Discussion on the Practical Use of Police Technology R&amp;D: Focusing on the Perception of Technology by Field Police Officers

This study is a pre-study for the survey on the demand for commercialization of police technology, and aims to grasp the perception of the current technology of field police officers. Specifically, the current status, utilization, satisfaction, problem, improvement direction, and technology and equipment desired to be introduced by field police officers under the classification system for each technology target were analyzed. As for the analysis data, preliminary survey data of the demand survey for the 「2022 Police Technology Commercialization Project and FGI data of 15 on-site police officers were used. As a result of the analysis, it was found that the holding status was held by the affiliated functions/institution from at least 4.0% to a maximum of 55.2% by the middle classification of security science and technology. It was confirmed that the average score of utilization and satisfaction were higher than 5points in all middle categories (7point scale). However, in the case of introduction recognition, a relatively low number was reported, with a minimum of 3.2% to a maximum of 15.5% for each division. In this study, policy suggestions for the direction of commercialization of police technology were presented through these results and opinions of field police officers derived from FGI.
일본 경찰조직의 운영실태와 시사점에 관한 연구

Many police scholars in the West describe Japan as one of the world's most secure countries because its police system is run mainly by citizens. Japan has a low crime rate and its police system has a unique structure in which national and municipal police coexist. And the Japanese police are successfully carrying out crime prevention activities in such an organization. The Japanese police system is a combination of a centralized police system controlled by the state and a decentralized police system controlled by the prefecture. Though it is not well organized like a centralized police system, it is better organized than a decentralized police system. Even if prefectural control and impact are not as large as the decentralized police system, they can be said to be greater than the centralized police system. The Japanese police are receiving a lot of favorable reviews in terms of system and operation, but they also have many problems. In this study, the organizational structure of the Japanese police is analyzed to examine the characteristics that appear due to the dual structure, and to find implications for the Korean police system.