• The KIPS Transactions:PartC
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• v.18C no.4
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• pp.199-206
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• 2011

Removable Storage provides the excellent portability with light weight and small size which fits in one's hand, many users have recently turned attention to the high-capacity products. However, due to the easy of portability for Removable Storage, Removable Storage are frequently lost and stolen and then many problems have been occurred such as the leaking of private information to the public. The advent of remote storage services where data is stored throughout the network, has allowed an increasing number of users to access data. The main data of many users is stored together on remote storage, but this has the problem of disclosure by an unethical administrator or attacker. To solve this problem, the encryption of data stored on the server has become necessary, and a searchable encryption system is needed for efficient retrieval of encrypted data. However, the existing searchable encryption system has the problem of low efficiency of document insert/delete operations and multi-keyword search. In this paper, an efficient searchable encryption system is proposed.

• Journal of health informatics and statistics
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• v.43 no.4
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• pp.329-335
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• 2018

Objectives: In recent years, there has been an increased need for a way to extract desired information from multiple medical literatures at once. This study was conducted to confirm the usefulness of unstructured data analysis using previously published medical literatures to search for new indications. Methods: The new indications were searched through text mining, network analysis, and topic modeling analysis using 5,057 articles of atorvastatin, a treatment for hyperlipidemia, from 1990 to 2017. Results: The extracted keywords was 273. In the frequency of text mining and network analysis, the existing indications of atorvastatin were extracted in top level. The novel indications by Term Frequency-Inverse Document Frequency (TF-IDF) were atrial fibrillation, heart failure, breast cancer, rheumatoid arthritis, combined hyperlipidemia, arrhythmias, multiple sclerosis, non-alcoholic fatty liver disease, contrast-induced acute kidney injury and prostate cancer. Conclusions: Unstructured data analysis for discovering new indications from massive medical literature is expected to be used in drug repositioning industries.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.79-92
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• 2019

The existing computer equipment management system is designed to computerize and manage equipment information that was managed only by documents in the computer room. However, the existing system focuses on computerizing the equipment arranged in the document, so there is a limit to the equipment that can be registered and it is difficult to find the necessary equipment. In addition, it caused inconvenience to confirm whether the registered equipment is currently used. In this paper, we redesign and implement the computer equipment management system to solve the problem. For this purpose, the existing computer equipment management system was thoroughly analyzed throughout, and the system is designed and implemented to improve the system by reflecting the opinions of public officials and management companies using the system. In the performance evaluation, the efficiency of the improved system is proved by comparing the number of equipment registrations and equipment search accuracy of the existing system.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.177-182
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• 2021

This study was carried out for the purpose of selecting and structuring educational content for personal information protection education in supplementary education for childcare workers. Prior research and literature data were collected and analyzed to select educational content, and a preliminary survey was conducted for 125 applicants for education. Based on the surveyed data, the educational content was structured through focus group interview. In the focus group interview analysis, the person in charge of personal information of the institution and those who have completed education participated. Group interviews and individual interviews through e-mail, etc. were conducted, and the final contents were selected after reviewing the appropriateness of the derived opinions by two educational experts. It was found that the direction of the search for personal information protection education contents should be added to the contents of practical work in each stage of information management and practice such as document writing.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.696-702
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• 2021

Informatization of early childhood education in the EU occurs in the context of the use of ICT as a means of sharing experiences, practices in the education and training of preschool children, communication, both at the national level and locally - within educational institutions, as a means of document management, search, data processing and information for the management of early childhood educational institutions, and planning activities for these institutions. This article aims to identify the features of the informatization of early childhood education in EU countries. Results. The countries of the EU have different levels of workload on the staff of early childhood education institutions, which is caused by different numbers of preschoolers and workforce. The greatest load on the staff in France due to a large number of preschoolers, which, despite the reduction, remained the highest among all the countries. By comparison, Poland's significant workload is mitigated by the size of its workforce. With almost equal numbers of staff in Poland and Germany, the countries differ significantly in the number of preschoolers. The countries also have different funding mechanisms for early childhood education, which determines the potential for digitalization. In France, total spending on early childhood education has grown the least (by 11 % between 2012 and 2018), in Poland by 51 %, in the Czech Republic by 44 %, and in Germany by 49%. In France, 100 % is funded by the government, in Poland 78 % is funded by the government, in the Czech Republic and Germany 87 % and 85 % respectively is funded by the government. The results of the survey of teachers' training in the use of ICTs and the level of specialists' readiness to use them in their studies indicate a mismatch between education and the practice of using technology. At the same time, given the high level of professional training of teachers in the use of technology in education, a low level of practice of ICT use in teaching preschool children was revealed. Teachers require professional development of ICT skills.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.2
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• pp.111-122
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• 2023

This study aims to collect Big Data related to DIY clothing, analyze the results on a year-by-year basis, understand consumers' perceptions, the status, and reality of DIY clothing. The reference period for the evaluation of DIY clothing trends was set from 2012 to 2022. The data in this study was collected and analyzed using Textom, a Big Data solution program certified as a Good Software by the Telecommunications Technology Association (TTA). For the analysis of fabric-related DIY products, the keyword was set to "DIY clothing", and for data cleansing following collection, the "Espresso K" module was employed. Also, via data collection on a year-by-year basis, a total of 11 lists were generated and the collected data was analyzed by period. The following are the findings of this study's data collection on DIY clothing. The total number of keywords collected over a period of ten years on search engines "Naver" and "Google" between January 1, 2012 and December 31, 2022 was 16,315, and data trends by period indicate a continuous upward trend. In addition, a keyword analysis was conducted to analyze TF-IDF (Term Frequency-Inverse Document Frequency), a statistical measure that reflects the importance of a word within data, and the relationship with N-gram, an analysis of the correlation concerning the relationship between words. Using these results, it was possible to evaluate the popularity and growing tendency of DIY clothing products in conjunction with the evolving social environment, as well as the desire to explore DIY trends among consumers. Therefore, this study is valuable in that it provides preliminary data for DIY clothing research by analyzing the status and reality of DIY products, and furthermore, contributes to the development and production of DIY clothing.

• Imaging Science in Dentistry
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• v.53 no.2
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• pp.137-144
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• 2023

Purpose: This study aimed to evaluate the anatomic circle around the impacted lower third molar to show, document, and correlate essential findings that should be included in the routine radiographic assessment protocol as clinically meaningful factors in overall case evaluation and treatment planning. Materials and Methods: Cone-beam computed tomographic images of impacted lower third molars were selected according to specific inclusion criteria. Impacted teeth were classified according to their position before assessment. The adjacent second molars were assessed for distal caries, distal bone loss, and root resorption. The fourth finding was the presence of a retromolar canal distal to the impaction. Communication with the dentist responsible for each case was done to determine whether these findings were detected or undetected by them before communication. Results: Statistically significant correlations were found between impaction position, distal bone loss, and detected distal caries associated with the adjacent second molar. The greatest percentage of undetected findings was found in the evaluation of distal bone status, followed by missed detection of the retromolar canal. Conclusion: The radiographic assessment protocol for impacted third molars should consider a step-by-step evaluation for second molars, and clinicians should be aware of the high prevalence of second molar affection in horizontal and mesioangular impactions. They also should search for the retromolar canal due to its associated clinical considerations.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.113-120
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• 2024

With the advancement of information and communication technology, we can easily generate various forms of data in our daily lives. To efficiently manage such a large amount of data, systematic classification into categories is essential. For effective search and navigation, data is organized into a tree-like hierarchical structure known as a category tree, which is commonly seen in news websites and Wikipedia. As a result, various techniques have been proposed to classify large volumes of documents into the terminal nodes of category trees. However, document classification methods using category trees face a problem: as the height of the tree increases, the number of terminal nodes multiplies exponentially, which increases the probability of misclassification and ultimately leads to a reduction in classification accuracy. Therefore, in this paper, we propose a new node expansion-based classification algorithm that satisfies the classification accuracy required by the application, while enabling detailed categorization. The proposed method uses a greedy approach to prioritize the expansion of nodes with high classification accuracy, thereby maximizing the overall classification accuracy of the category tree. Experimental results on real data show that the proposed technique provides improved performance over naive methods.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.1-8
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• 2020

In recent years, due to the exponential increase in internet data, many fields such as deep learning have developed, but side effects generated as commercial advertisements, such as viral marketing, have been discovered. This not only damages the essence of the internet for sharing high-quality information, but also causes problems that increase users' search times to acquire high-quality information. In this study, we define advertisement as "a text that obscures the essence of information transmission" and we propose a model for filtering information according to that definition. The proposed model consists of advertisement filtering and advertisement filtering performance improvement and is designed to continuously improve performance. We collected data for filtering advertisements and learned document classification using KorBERT. Experiments were conducted to verify the performance of this model. For data combining five topics, accuracy and precision were 89.2% and 84.3%, respectively. High performance was confirmed, even if atypical characteristics of advertisements are considered. This approach is expected to reduce wasted time and fatigue in searching for information, because our model effectively delivers high-quality information to users through a process of determining and filtering advertisement paragraphs.