• Journal of Advanced Marine Engineering and Technology
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• v.38 no.5
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• pp.589-601
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• 2014

Natural gas hydrate (NGH) is emerging as a new eco-friendly source of energy to replace fossil fuels in the 21st century. It is well known that the Natural Gas Hydrate contains large amount of natural gas about 170 times as much as its volume and it is easy to be stored and transported safely at about $-20^{\circ}C$ under atmospheric pressure due to so called "self-preservation effect". The option of gas transport by gas hydrate pellets carrier has been investigated and developed in various industry and academy. The natural gas hydrate pellet carrier is on major link in a potential gas hydrate process chain, starting with the extraction of natural gas from the reservoir, followed by the production of hydrate pellets and the transportation to an onshore terminal for further processing or marketing. In recent years, Korean project team supported by Korean Government has been working on the development of NGH total systems including novel NGH carrier since 2011. In order to increase the knowledge on the NGH pellet carrier developed and to understand the major hazards that could have significant impact on the safety of the vessel, this paper presents and evaluates the pros and cons of cargo holds, loading and unloading systems through the analysis of current patent technology. Based on the proven and well-known technologies as well as potential measures to mitigate sintering and minimize mechanical stress on the hydrate pellet in the self-preservation state, this study presents the conceptual and basic design for NGH carrier.

• Journal of KIISE
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• v.45 no.1
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• pp.22-29
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• 2018

Over the decades, neural networks have been successfully used in numerous applications from speech recognition to image classification. However, these neural networks cannot explain their results and one needs to know how and why a specific conclusion was drawn. Most studies focus on extracting binary rules from neural networks, which is often impractical to do, since data sets used for machine learning applications contain continuous values. To fill the gap, this paper presents an algorithm to extract logic rules from a trained neural network for data with continuous attributes. It uses hyperplane-based linear classifiers to extract rules with numeric values from trained weights between input and hidden layers and then combines these classifiers with binary rules learned from hidden and output layers to form non-linear classification rules. Experiments with different datasets show that the proposed approach can accurately extract logical rules for data with nonlinear continuous attributes.

• Journal of the Korean Society for information Management
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• v.18 no.2
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• pp.231-254
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• 2001

As contemporary thesauri have become large and complex, it is increasingly difficult to assess the intended meaning of each one of the terms. Thereby the meaning of many descriptors seems to be very similar, and it is often not possible to distinguish among them and to identify the term correctly. Purpose of this article is to induce definitions of descriptors in thesaurus by specifying the characteristics of each concept, locating it in the domain and providing clear and prescriptive information on the meaning of each descriptor in the form of a standardized terminological definition. In this study, a small prototype thesaurus using definition of term in the field of information industry in Korean Standards has been developed. In this thesaurus definitions are written for each descriptor with the help of a proposed defining model and in accordance with defining rules borrowed from the field of terminology. In addition, elements of analyzed definition have been included in the relation structure of descriptors. It is revealed that terminological definition added to thesaurus may permit extraction of separate items of information from definitions for the representation of knowledge structures and makes it easier to confine the scope of descriptors to be included in thesaurus in a given subject field.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.15-27
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• 2020

Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.557-561
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• 2014

In this work, Altair Engineering's vibroacoustic modeling approach is used to simulate the acoustic signature of a simplified automobile in a wind tunnel. The modeling approach relies on a two step procedure involving simulation and extraction of acoustic sources using a high fidelity Computational Fluid Dynamics (CFD) simulation followed by propagation of the acoustic energy within the structure and passenger compartment using a structural dynamics solver. The tools necessary to complete this process are contained within Altair's HyperWorks CAE software suite. The CFD simulations are performed using AcuSolve and the structural simulations are performed using OptiStruct. This vibroacoustics simulation methodology relies on calculation of the acoustic sources from the flow solution computed by AcuSolve. The sources are based on Lighthill's analogy and are sampled directly on the acoustic mesh. Once the acoustic sources have been computed, they are transformed into the frequency domain using a Fast Fourier Transform (FFT) with advanced sampling and are subsequently used in the structural acoustics model. Although this approach does require the CFD solver to have knowledge of the acoustic simulation domain a priori, it avoids modeling errors introduced by evaluation of the acoustic source terms using dissimilar meshes and numerical methods. The aforementioned modeling approach is demonstrated on the Hyundai Simplified Model (HSM) geometry in this work. This geometry contains flow features that are representative of the dominant noise sources in a typical automobile design; namely vortex shedding from the passenger compartment A-pillar and bluff body shedding from the side view mirrors. The geometry also contains a thick poroelastic material on the interior that acts to reduce the acoustic noise. This material is modeled using a Biot material formulation during the structural acoustic simulation. Successful prediction of the acoustic noise within the HSM geometry serves to validate the vibroacoustic modeling approach for automotive applications.

• Clinical and Experimental Reproductive Medicine
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• v.45 no.1
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• pp.48-51
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• 2018

We report the case of a 46-year-old Chinese male patient who visited our clinic complaining of infertility. Semen analysis revealed azoospermia, and azoospermia factor c region partial deletion (b1/b3) was detected using Y chromosome microdeletion analysis. Testicular sperm extraction was performed after genetic counseling. The bilateral ductus deferens and a portion of the epididymis were absent, whereas the remaining epididymis was expanded. Motile intratesticular spermatozoa were successfully extracted from the seminiferous tubule. On histopathology, nearly complete spermatogenesis was confirmed in almost every seminiferous tubule. To our knowledge, this is the first case report of b1/b3 deletion with a congenital bilateral absence of the vas deferens and almost normal spermatogenesis.

• Ocean and Polar Research
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• v.38 no.2
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• pp.129-137
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• 2016

This study aimed to isolate and characterize sulfated polysaccharides (SPs) from Iridaea cordata and evaluate their anticancer activity. SPs of the Antarctic red seaweed were obtained by $CaCl_2$ (SP1) and ethanol precipitations (SP2) following diluted acid extraction at room temperature. Yields of SP1 and SP2 were approximately 14% and 23%, respectively, of the dry weight of red seaweed. The average molecular mass of the SP1 and SP2 was estimated about $1.84{\times}10^3$ and $1.42{\times}10^3kDa$, respectively, by size-fractionation High-Performance Liquid Chromatography (HPLC). From the High-Performance Anion-Exchange Chromatography-Pulsed Amperometric Detection (HPAEC-PAD) analysis, the main monosaccharide was galactose with glucose and fucose as minor components. The sulfate content of SP2 (40.4%) was slightly higher than that of SP1 (33.8%). The FT-IR spectra also showed characteristic band of carrageenan-like sulfated polysaccharides. Taken together the SPs are thought to be carrageenan-like sulfated galactan. The polysaccharides (SPs) from I. cordata exhibited weak antitumor activity against PC-3 (prostate cancer), HeLa (cervical cancer), and HT-29 (human colon adenocarcinoma). To our knowledge, this is the first data on biological activity of the Antarctic red seaweed I. cordata.

• The Journal of Korean Association of Computer Education
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• v.12 no.6
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• pp.21-32
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• 2009

This paper proposes a method to extract a user's intention automatically and implementation of intention map that support a user can appropriate search results using a user' information need accurately. It selects user intention based on searching history obtained from previous users' same queries and extracts user intentions by using clustering algorithm and user intention extraction algorithm, extracted user intentions are represented in an intention map base on a theory of knowledge representation. For the efficiency analysis of intention map, we extracted user intentions using 2,600 search history data which provided by a current domestic commercial search engine. The experimental results using the information intention map search when using general search engines represent more than satisfaction was statistically significant.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.239-250
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• 2003

In this research, we propose a hybrid group decision support mechanism (H-GDSM) based on Fuzzy AHP (Analytic Hierarchy Process) and FCM (Fuzzy Cognitive Map). The AHP elicits a corresponding priority vector interpreting the preferred information among the decision makers. Corresponding vector was composed of the pairwise comparison values of a set of objects. Since pairwise comparison values are the judgments obtained from an appropriate semantic scale. However, AHP couldn't represent the causal relationship among information, which were used by decision makers. In contrast to AHP, FCM could represent the causal relationship among variables or information. Therefore, FCMs were successfully developed and used in several ill-structured domains, such as strategic decision-making, policy making, and simulations. Nonetheless, many researchers used subjective and voluntary inputs to simulate the FCM. As a result of subjective inputs, it couldn't avoid the rebukes of businessman. To overcome these limitations, we incorporated the Fuzzy membership functions, AHP and FCM into a H-GDSM. In contrast to current AHP methods and FCMs, the H-GDSM method developed herein could concurrently tackle the pairwise comparison involving causal relationships under a group decision-making environment. The strengths and contributions of our mechanism were 1) handling of qualitative knowledge and causal relationships, 2) extraction of objective input value to simulate the FCM, 3) multi-phase group decision support based on H-GDSM. To validate our proposed mechanism we developed a simple prototype system to support negotiation-based decisions in electronic commerce (EC).

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.13-24
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• 2017

The Sample Cohort DB supplied by the National Health Insurance Service is a valuable resource for statistical studies as well as for health and medical studies. It takes significant time and effort to extract data from this Cohort DB having a large size. As such, we introduce a database system, conveniently called the National Health Insurance Service Cohort DB Extract Tool (NICE Tool), which supports several useful operations for effectively and efficiently managing the Cohort DB. For example, researchers can extract variables and cases related with study by simply clicking a computer mouse without any prior knowledge regarding SAS DATA step or SQL. We expect that NICE Tool will facilitate the faster extraction of data and eventually lead to the active use of the Cohort DB for research purposes.