• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2907-2915
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• 2018

Journal of the Korean Data Analysis Society founded in 1998 has played the role of a major application journal. In this study, we checked the objective of this journal by checking the abstracts for 10 years. Abstract data was crawled from the online journal site (kdas.jems.or.kr) and analyzed by topic model. As a result, we found 18 topics from 2680 abstracts that had several contents, for example, nursing, marketing, economics, regression, factor analysis, data mining and statistical inferences. Topic1 (regression) is most frequent with 460 documents and we found the usefulness of regression in the applied science area. We confirmed the significant 10 association rules using by Fisher's exact test. Also, for exploring the trend of topics, we conducted the topic analysis for two periods which are 2006-2011 period and 2012-2016 period. We found that the control study was more frequent than survey study over time and regression and factor analysis were frequent regardless of time.

• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1393-1403
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• 1999

공간 데이타베이스 시스템을 통하여 공유되는 공간 데이타는 무결성이 적절하게 유지되지 않는 한 전체 응용 시스템의 행위를 예측할 수 없게 되므로 데이타의 무결성 확인 및 유지는 필수적이다. 특히 공공 GIS에 저장된 공간 데이타는 토지 이용도 평가, 도시 계획, 자원 관리, 시설물 관리, 안전 관리, 국방 등 국가 전체 및 지역의 중요한 정책 결정을 위한 다양한 응용 시스템들에 의해 이용되므로 적절한 공간 객체의 무결성 확인이 더욱 더 필요하다. 본 논문에서는 능동(active) DBMS의 능동 규칙(active rule) 기법을 이용하여 공간 객체의 무결성 확인을 지원하기 위한 규칙 관리 시스템을 제시한다. 능동 규칙을 이용한 공간 객체의 무결성 확인은 응용 프로그래머를 무결성 확인에 대한 부담으로부터 자유롭게 할 수 있다. 본 시스템은 특정 DBMS에 종속되지 않는 독립적인 외부 시스템으로 존재하며, 능동 규칙 관리기, 규칙 베이스, 그리고 활성규칙 생성기의 3 부분으로 구성된다. 사용자가 공간 데이타베이스 응용 프로그램을 통해 공간 객체를 조작하고자 할 때, 본 시스템은 데이타베이스 트랜잭션을 단위로 조작되는 모든 공간 객체의 무결성 확인을 위해 응용 프로그램에 삽입될 무결성 제약조건 규칙들을 효율적으로 관리하는 역할을 한다.Abstract It is necessary that the integrity of spatial data shared through the spatial database system is validated and appropriately maintained, otherwise the activity of whole application system is unpredictable. Specially, the integrity of spatial data stored in public GIS has to be validated, because those data are used by various applications which make a decision on an important policy of the region and/or whole nation such as evaluation of land use, city planning, resource management, facility management, risk management/safety supervision, national defense. In this paper, we propose rule management system to support validating the integrity of spatial object, using the technique of active rule technique from active DBMS. Validating data integrity using active rules allows database application programmer to be free from a burden on validation of the data integrity. This system is an independent, external system that is not subject to specific DBMS and consists of three parts, which are the active rule manager, the rule base, and the triggered rule generator. When an user tries to manipulate spatial objects through a spatial database application program, this system serves to efficiently manage integrity rules to be inserted into the application program to validate the integrity constraints of all the spatial objects manipulated by database transactions.

• Journal of Preventive Medicine and Public Health
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• v.41 no.2
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• pp.92-99
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• 2008

Objectives : Effective cancer prevention and control measures can only be done when dependable data on the cancer incidence is available. The Seoul Cancer Registry (SCR) was founded to provide valid, comparable and representative cancer incidence data for Koreans. We aimed to compare the cancer incidence in the first (1993-1997) and second term (1998-2002) of the SCR, and we analyzed the annual incidence trend during that 10 years. Methods : The SCR detects potential cancer cases through the Korean Central Cancer Registry (KCCR) data, the health insurance claims, the individual hospital's discharge records and the death certificates. About 87% of the SCR data is registered through the KCCR. The rest of the data is registered by SCR registrars who visit about $70{\sim}80$ mid-sized hospitals in Seoul to review and abstract the medical records of the potential cancer patients. Results: The total number of new cancer cases was higher in $1998{\sim}2002$ than in $1993{\sim}1997$ by 20.6% for men and 18.4% for women, respectively. The age-standardized rate (ASR) of total cancer per 100,000 increased 1% (from 295.4 to 298.3) for men and 5.1% (from 181.5 to 190.7) for women, between the two periods. The commonest cancer sites during 1998-2002 for men were stomach, liver, bronchus/lung, colorectum, bladder and prostate, and the commonest cancer sites for women were breast, stomach, colorectum, cervix uteri, thyroid and bronchus/lung. Compared with the ASRs in 1993, the ASRs in 2002 increased for colorectum (58.4% for men, 27.1% for women), prostate (81.5%), breast (58.3% for women), thyroid (141% for women), and bronchus/lung (15.4% for women). The ASRs for stomach (-18.7% for men, -20.7% for women) and uterine cervix cancer (-39.7%) had decreased. Conclusions : The cancer incidence is increasing in Seoul, Korea, especially for the colorectum and prostate for men, and for the breast, colorectum, bronchus/lung and thyroid for women.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1270-1281
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• 1999

피라미드 기법 1 은 d-차원의 공간을 2d개의 피라미드들로 분할하는 특별한 공간 분할 방식을 이용하여 고차원 데이타를 효율적으로 색인할 수 있는 새로운 색인 방법으로 제안되었다. 피라미드 기법은 고차원 사각형 형태의 영역 질의에는 효율적이나, 유사성 검색에 많이 사용되는 고차원 구형태의 영역 질의에는 비효율적인 면이 존재한다. 본 논문에서는 고차원 데이타를 많이 사용하는 유사성 검색에 효율적인 새로운 색인 기법으로 구형 피라미드 기법을 제안한다. 구형 피라미드 기법은 먼저 d-차원의 공간을 2d개의 구형 피라미드로 분할하고, 각 단일 구형 피라미드를 다시 구형태의 조각으로 분할하는 특별한 공간 분할 방법에 기반하고 있다. 이러한 공간 분할 방식은 피라미드 기법과 마찬가지로 d-차원 공간을 1-차원 공간으로 변환할 수 있다. 따라서, 변환된 1-차원 데이타를 다루기 위하여 B+-트리를 사용할 수 있다. 본 논문에서는 이렇게 분할된 공간에서 고차원 구형태의 영역 질의를 효율적으로 처리할 수 있는 알고리즘을 제안한다. 마지막으로, 인위적 데이타와 실제 데이타를 사용한 다양한 실험을 통하여 구형 피라미드 기법이 구형태의 영역 질의를 처리하는데 있어서 기존의 피라미드 기법보다 효율적임을 보인다.Abstract The Pyramid-Technique 1 was proposed as a new indexing method for high- dimensional data spaces using a special partitioning strategy that divides d-dimensional space into 2d pyramids. It is efficient for hypercube range query, but is not efficient for hypersphere range query which is frequently used in similarity search. In this paper, we propose the Spherical Pyramid-Technique, an efficient indexing method for similarity search in high-dimensional space. The Spherical Pyramid-Technique is based on a special partitioning strategy, which is to divide the d-dimensional data space first into 2d spherical pyramids, and then cut the single spherical pyramid into several spherical slices. This partition provides a transformation of d-dimensional space into 1-dimensional space as the Pyramid-Technique does. Thus, we are able to use a B+-tree to manage the transformed 1-dimensional data. We also propose the algorithm of processing hypersphere range query on the space partitioned by this partitioning strategy. Finally, we show that the Spherical Pyramid-Technique clearly outperforms the Pyramid-Technique in processing hypersphere range queries through various experiments using synthetic and real data.

• Design Convergence Study
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• v.16 no.6
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• pp.169-184
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• 2017

There is a lot of needs that are not expressed as much as the expressed needs in familiar products and services that are used in daily life such as a smartphone. Finding the 'Inconveniences in familiar use' make it possible to create opportunities for value expanding in the existing products and service area. There are a lot of related works, which have studied the definition of hidden needs and the methods to find it. But, they are making it difficult to address the hidden needs in the cases of familiar use due to focus on the new product or service developing typically. In this study, we try to redefine the hidden needs in the daily familiarity and approach it in the new way to find out. Because of the users' unability to express what they want and the complexity of needs which can not be explained clearly, we can not approach it as the quantitative issue. For this reason, the basic data type selected as the user behavior data excluding all description is the screen-shot of the smartphone. We try to apply the integrated rules and patterns to the individual data using the qualitative coding techniques to overcome the limitations of qualitative analysis based on unstructured data. From this process, We can not only extract meaningful clues which can make to understand the hidden needs but also identify the possibility as a way to discover hidden needs through the review of relevance to actual market trends. The process of finding hidden needs is not easy to systemize in itself, but we expect the possibility to be conducted a reference frame for finding hidden needs of other further studies.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.375-382
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• 2008

A protein's subcellular localization is considered an essential part of the description of its associated biomolecular phenomena. As the volume of biomolecular reports has increased, there has been a great deal of research on text mining to detect protein subcellular localization information in documents. It has been argued that linguistic information, especially syntactic information, is useful for identifying the subcellular localizations of proteins of interest. However, previous systems for detecting protein subcellular localization information used only shallow syntactic parsers, and showed poor performance. Thus, there remains a need to use a full syntactic parser and to apply deep linguistic knowledge to the analysis of text for protein subcellular localization information. In addition, we have attempted to use semantic information from the WordNet thesaurus. To improve performance in detecting protein subcellular localization information, this paper proposes a three-step method based on a full syntactic dependency parser and WordNet thesaurus. In the first step, we constructed syntactic dependency paths from each protein to its location candidate, and then converted the syntactic dependency paths into dependency trees. In the second step, we retrieved root information of the syntactic dependency trees. In the final step, we extracted syn-semantic patterns of protein subtrees and location subtrees. From the root and subtree nodes, we extracted syntactic category and syntactic direction as syntactic information, and synset offset of the WordNet thesaurus as semantic information. According to the root information and syn-semantic patterns of subtrees from the training data, we extracted (protein, localization) pairs from the test sentences. Even with no biomolecular knowledge, our method showed reasonable performance in experimental results using Medline abstract data. Our proposed method gave an F-measure of 74.53% for training data and 58.90% for test data, significantly outperforming previous methods, by 12-25%.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.555-563
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• 2016

Science and technology contents (research papers, patents, reports) are the most common reference material for researchers involved in research and development in the fields of science and technology. Based on various search elements (title, abstract, keyword, year of publication, name of journal, name of author, publisher, etc.), many services are available for users to search science and technology contents and bibliographic information owned by libraries. Authority data on organization name can be useful as an element for author identification and as an element to search for results produced by specific organizations. However, organization name is not taken into account by current search services for domestic academic information and bibliographic records. This study analyzes organization name data contained in the metadata of science and technology contents, which are the basis of the establishment of authority data, and proposes a method and system based on string containment and exact string matching.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.73-82
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• 2019

In order to build a smart factory, building a CPPS (Cyber Physical Product System) is an important system that must be accompanied. Through the CPPS, it is the reality of smart factories to move physical factories to a digital-based cyber world and to intelligently and autonomously monitor and control them. But The existing CPPS architectures present only an abstract modeling architecture, and the research that applied the OPC UA Framework (Open Platform Communication Unified Architecture), an international standard for data exchange in the smart factory, as the basic system of CPPS It was insufficient. Therefore, it is possible to implement CPPS that can include both cloud and IoT by collecting field data distributed by CPPS architecture applicable to actual factories and concentrating data processing in a centralized In this study, we implemented CPPS architecture through central OPC UA Server based on OPC UA conforming to central processing OPC UA Framework, and how CPPS logical process and data processing process are automatically generated through OPC UA modeling processing We have proposed the CPPS architecture including the model factory and implemented the model factory to study its performance and usability.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.59-70
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• 2021

With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context information that expresses the state of situations. However, these datasets is mostly unstructured and have difficulty in processing with simple approaches. Therefore, providing context-aware services using the datasets should be managed in simplified method. One of examples that should be considered as the unstructured datasets is a deep learning application. Processes in deep learning applications have a strong coupling in a way of abstracting dataset from the acquisition to analysis phases, it has less flexible when the target analysis model or applications are modified in functional scalability. Therefore, an abstraction model that separates the phases and process the unstructured dataset for analysis is proposed. The proposed abstraction utilizes a description name Analysis Model Description Language(AMDL) to deploy the analysis phases by each fat client is a specifically designed instance for resource-oriented tasks in edge computing environments how to handle different analysis applications and its factors using the AMDL and Fat client profiles. The experiment shows functional scalability through examples of AMDL and Fat client profiles targeting a vehicle image recognition model for vehicle access control notification service, and conducts process-by-process monitoring for collection-preprocessing-analysis of unstructured data.

• Knowledge Management Research
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• v.23 no.3
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• pp.129-152
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• 2022

As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.