• Tribology and Lubricants
• /
• v.24 no.1
• /
• pp.34-43
• /
• 2008

In this paper, an actively controlled aerostatic bearing is studied to overcome the defects of air bearing such as low stiffness and damping coefficients. The actively controlled aerostatic bearing is composed of aerostatic bearings, non-contact type of displacement sensors, piezoelectric actuators and controllers. The cylindrical capacitance sensor (CCS) is used as the displacement sensor. The reason for using CCS instead of the commercial gap sensor is that it can give us the pure error motion of the spindle because it removes the roundness error or the geometric errors in the spindle. The controller is designed by the state space equation and quadratic optimal control theory. The characteristic data of the actively controlled aerostatic bearing system in the frequency domain are presented and the stiffness and damping coefficients of the bearing are mentioned. This paper shows the possibility to reduce the motion error up to 6000 rpm.

• MALSORI
• /
• no.25_26
• /
• pp.38-51
• /
• 1993

Korean phonology has not recognised metrical foot as a phonological unit to account for certain phonological processes. This paper, however, suggests that an optional h-deletion process in Korean should require the notion of metrical foot as an independent phonological domain. The previous analyses rely on the notion of speech speed to explain optional h-deletion : i. e. an intervocalic h is deleted in fast speech, but in slow speech it remains. This paper claims that the notion of speech speed should be reinterpreted in terms of metrical foot : i.e. foot-internal t is deleted, but foot-initial h remains. Such analysis provides evidence that metrical foot constitutes a phonological unit in Korean phonology. With the notion of metrical foot, it enables us to achieve more detailed and accurate analysis of the optional h-deletion process in Korean.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.3
• /
• pp.462-478
• /
• 1994

Conventional hypermedia systems provide a simple data model based on nodes and link, and give us the limited capability in information retrieval such as browsing and navigating following the links. In this paper, we design and implement a hypermedia system (AHEAD) with enhanced data modeling and querying capability, which are strongly supported in object-oriented database technology. The AHEAD makes it possible to model the accurate data semantics and relationships in application domain, to represent useful information related to nodes and links, and to define the structure and manipulation operations of multimedia data. It also support the various querying capabilities by using modeling information.

• Strategy21
• /
• s.43
• /
• pp.57-88
• /
• 2018

Security situations are fundamentally and rapidly changing on the Korean Peninsula. Above all, as North Korea(NK) is heightening its nuclear and missile capabilities, Republic of Korea(ROK) is facing an existential threat. At the same time, as China's economic, diplomatic and military power is quickly rising, the balance of power is shifting and strategic competition between the Unite States(US) and China is accelerating in the Asia-Pacific region. Under the pressure of development of these situations, ROK seems to face allegedly the most serious crisis in its national security since the end of the Korean War. In the current grim geopolitical situation, maritime security may become the most difficult security challenge for ROK in the years to come. The purpose of this paper is to compare major changes in maritime security affairs of the ROK during last twenty years from 1998 until now(2018). 1998 was when this journal 『Strategy 21』 was published for the first time by the Korea Institute for Maritime Strategy. Then, this paper tries to identify challenges and risks with which this country has to deal for its survival and prosperity, and to propose some recommendations for the government, the Navy, and the Coast Guard as they are responsible for the maritime security of the country. The recommendations of this paper are as follows: strengthen ROK-US alliance and expand security cooperation with regional powers in support of the maintenance of the current security order in the region; building-up of maritime security capacity in preparation for crisis on the maritime domain with the navy targeting to acquire 'a non-nuclear, balance-of-terror capability, to improve interoperability with the Coast Guard based on 'a national fleet,' and to actively pursue innovation in naval science and technology. Finally, this paper proposes that naval capability the country needs in another twenty years depends on how effectively and rigorously the navy put its utmost efforts towards building 'a strongest navy' today.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.4
• /
• pp.15-31
• /
• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.6
• /
• pp.765-777
• /
• 2002

For the battlefield analysis, it is required to get correct information about the identification and moving status of target enemy units. However, it is difficult for us to collect all of the information perfectly, because of the technology of communications, jamming, and tactics. Therefore, we need a reasoning function that predicts and analyzes future moving status for target units by using collected moving information and domain knowledge. Especially. since the moving units have characteristics of moving objects, which change their position and shape over time, they require functions to manage and predict locations of moving objects. Therefore, in this paper, we propose a location prediction system of moving units for battlefield analysis. The proposed system not only predicts unknown units, unidentified units, and main strike directions to application domain for battlefield analysis, but also estimates the past or future locations of moving objects not stored in a database.

• Journal of Information Technology Application
• /
• v.2 no.1
• /
• pp.1-24
• /
• 2000

Project management in the Construction field inherently has more uncertainty and more risks relative to ones from other area. This is the very reason for why project management is recognized as the important task to construction companies. For getting better performance in the project management, we need a system that keeps the consistencies in a automatic or semi-automatic manner through the project management stages like as project definition stage, project planning stage, project design and implementation stage. But since the early stages such as definition and planning stages has many unstructured features and also are dependent to unique expertise or experience of a specific company, we have difficulty providing systematic support for the task of these stages. This kind of problem becomes harder to solve especially in the plant construction domain that is our target domain. Therefore, in this paper, we propose and also implement a systematic approach to resolve the problem mentioned for the early project management stages in the plant construction domain. The results of our approach can be used not only for the purpose of the early project management stages but also can be used automatically as an input to commercial project management tools for the middle project management stages. Because of doing in this way, the construction project can be consistently managed from the definition to implementation stage in a seamless manner. For achieving this purpose, we adopt knowledge based inference, CBR, and neural network as major methodologies and we also applied our approach to two real world cases, power plant and drainage treatment plant cases from a leading construction company in Korea. Since these two application cases showed us very successful results, we can say our approach was validated successfully to the plant construction area. Finally, we believe our approach will contribute to many project management problems from more broader construction area.

• Journal of Computing Science and Engineering
• /
• v.2 no.2
• /
• pp.109-136
• /
• 2008

In this survey paper, we discuss biomedical ontologies and major text mining techniques applied to biomedicine and healthcare. Biomedical ontologies such as UMLS are currently being adopted in text mining approaches because they provide domain knowledge for text mining approaches. In addition, biomedical ontologies enable us to resolve many linguistic problems when text mining approaches handle biomedical literature. As the first example of text mining, document clustering is surveyed. Because a document set is normally multiple topic, text mining approaches use document clustering as a preprocessing step to group similar documents. Additionally, document clustering is able to inform the biomedical literature searches required for the practice of evidence-based medicine. We introduce Swanson's UnDiscovered Public Knowledge (UDPK) model to generate biomedical hypotheses from biomedical literature such as MEDLINE by discovering novel connections among logically-related biomedical concepts. Another important area of text mining is document classification. Document classification is a valuable tool for biomedical tasks that involve large amounts of text. We survey well-known classification techniques in biomedicine. As the last example of text mining in biomedicine and healthcare, we survey information extraction. Information extraction is the process of scanning text for information relevant to some interest, including extracting entities, relations, and events. We also address techniques and issues of evaluating text mining applications in biomedicine and healthcare.

• Ocean and Polar Research
• /
• v.41 no.3
• /
• pp.169-181
• /
• 2019

The purpose of this study is to develop geochemical tracers to identify a specific source desert of mineral dust in China using the published data. In addition, we tested the applicability of these tracers to wet-deposits and soil samples collected in Jeju, Korea. Because of similarity in trace elemental compositions of mineral dust from the major arid regions in China, such as Taklimakan, West Ordos (Badain Jaran), East Ordos (Mu Us and Hobq), East Northern China (Horqin), West Northern China (Gurbantunggut), and Chinese Loess Plateau, there has been limited to the use of geochemical data for source identification. Here we propose the four (4) plots using combination of seven (7) geochemical variables as a source indicator to distinguish one from other source regions in China: $\frac{Y}{Tb_N}$ vs. $\frac{Th}{{\Sigma}REE_N}$, $\(\frac{La}{Gd}\)_N$ vs. $\frac{Y}{{\Sigma}REE_N}$, $\frac{Th}{Tb_N}$ vs. $\frac{Y}{Nd_N}$, and $\frac{Th}{Tb_N}$ vs. $\(\frac{Ce}{Ce}\)_N^*$, where $_N$ and $\(\frac{Ce}{Ce}\)_N^*$ stand for values normalized to Post-Archean Average Shale composition and Ce anomaly, respectively. Mineral dusts from aforementioned six major deserts are distinguished one from the others by the combined use of these variables. Jeju rock and soil samples form a separate domain from Chinese mineral dusts in all four plots. In contrast, most of Jeju dust samples were comparable with the West Ordos desert (Badain Jaran) domain, indicative of strong influence of Badain Jaran dust in Jeju in spring season when the mineral dust was collected. A weak positive Ce anomaly in Jeju samples implies minimal local contribution. Our study suggests that the combination of $\frac{Y}{Tb_N}$ vs. $\frac{Th}{{\Sigma}REE_N}$, $\(\frac{La}{Gd}\)_N$ vs. $\frac{Y}{{\Sigma}REE_N}$, $\frac{Th}{Tb_N}$ vs. $\frac{Y}{Nd_N}$, and $\frac{Th}{Tb_N}$ vs. $\(\frac{Ce}{Ce}\)_N^*$ can be used to identify a specific source region of mineral dust in China as well as Jeju mineral particles.

• Asian Journal of Atmospheric Environment
• /
• v.7 no.1
• /
• pp.25-37
• /
• 2013

Open biomass burning (excluding biofuels) is an important contributor to air pollution in the Asian region. Estimation of emissions from fires, however, has been problematic, primarily because of uncertainty in the size and location of sources and in their temporal and spatial variability. Hence, more comprehensive tools to estimate wildfire emissions and that can characterize their temporal and spatial variability are needed. Furthermore, an emission processing system that can generate speciated, gridded, and temporally allocated emissions is needed to support air-quality modeling studies over Asia. For these reasons, a biomass-burning emissions modeling system based on satellite imagery was developed to better account for the spatial and temporal distributions of emissions. The BlueSky Framework, which was developed by the USDA Forest Service and US EPA, was used to develop the Asian biomass-burning emissions modeling system. The sub-models used for this study were the Fuel Characteristic Classification System (FCCS), CONSUME, and the Emissions Production Model (EPM). Our domain covers not only Asia but also Siberia and part of central Asia to assess the large boreal fires in the region. The MODIS fire products and vegetation map were used in this study. Using the developed modeling system, biomass-burning emissions were estimated during April and July 2008, and the results were compared with previous studies. Our results show good to fair agreement with those of GFEDv3 for most regions, ranging from 9.7 % in East Asia to 52% in Siberia. The SMOKE modeling system was combined with this system to generate three-dimensional model-ready emissions employing the fire-plume rise algorithm. This study suggests a practicable and maintainable methodology for supporting Asian air-quality modeling studies and to help understand the impact of air-pollutant emissions on Asian air quality.