• Journal of Information Technology and Architecture
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• v.9 no.3
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• pp.233-241
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• 2012

Architecture framework (AF) is a guideline to define components needed to develop and operate enterprise architecture (EA), and to define relationships among the components. There are many architecture frameworks to operate EA of governments and businesses such as Zachman framework, DoDAF, TOGAF, FEAF, and TEAF. DoDAF is the most representative AF to support the development of the EA in the military domain. DoDAF is composed of eight viewpoints and 40 views that are affiliated with the viewpoints. To develop an AF for a specific goal, system architects decide a set of views. Furthermore, they determine data that are needed for a view modeling. However, views and data in DoDAF are structurally inter-related explicitly and/or implicitly. So, developing an AF for a specific goal is going to be a project to be carried out over a long haul. To reduce the burden of its development, in this paper, we develop ONT-SAF (Ontology for DoDAF) that can infer inter-relationships like referential and transitive relationships and the sequences among the views. Furthermore, to promote reusability and consistency of the views and the data within an AF, we adopt the view-data separation strategy. ONT-DAT contains classes like 'viewpoint', 'view', 'data', 'expression method', and 'reference model', and 11 properties including 'hasView.' To prove the effectiveness of ONT-SAF, we perform a case study.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.6
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• pp.503-513
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• 2005

With the recognition of the importance of computational approach for protein-protein interaction prediction, many techniques have been developed to computationally predict protein-protein interactions. However, few techniques are actually implemented and announced in service form for general users to readily access and use the techniques. In this paper, we design and implement a protein interaction prediction service system based on the domain combination based protein-protein interaction prediction technique, which is known to show superior accuracy to other conventional computational protein-protein interaction prediction methods. In the prediction accuracy test of the method, high sensitivity($77\%$) and specificity($95\%$) are achieved for test protein pairs containing common domains with teaming sets of proteins in a Yeast. The stability of the method is also manifested through the testing over DIP CORE, HMS-PCI, and TAP data. Performance, openness and flexibility are the major design goals and they are achieved by adopting parallel execution techniques, web Services standards, and layered architecture respectively. In this paper, several representative user interfaces of the system are also introduced with comprehensive usage guides.

• Journal of Life Science
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• v.17 no.12
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• pp.1610-1615
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• 2007

Genus Sorbus is a long lived woody species that is primarily distributed throughout Asia and Europe. This species is regarded as very important herbal medicines in Korea and China. Sorbus commixta is primarily distributed throughout Europe. We evaluated a representative sample of the four taxa with nuclear ribosomal DNA internal transcribed spacer sequences (ITS) to estimate genetic relationships within genus. Aligned nucleotide sequences of the length of ITS1 were nearly constant within genus Sorbus varying from 219 in S. aucuparia to 218 in the rest species. Especially, the 5.8S subunit of all taxa of Sorbus was found to constant of 165 bp nucleotides. However, aligned nucleotide sequences of the length of ITS2 vary from 240 in S. sambucifolia var. pseudogrcilisto 245 in S. aucuparia. Total alignment length is 629 positions, of which 35 are parsimony-informative, 32 variable but parsimony-uninformative, and 552 constant characters. The base furtherance showed the difference to the by a total taxon: an average A and T are 17.7% and G and C are 30.4%, 34.2%, respectively. All the four taxa beginning with conserved base paired triplets emerging from single strand regions (domain I). Noteworthy, in the RNA secondary structure proposed for the three Korean Sorbus taxa RNA transcript ITS2, which shows a remarkedly well-conserved folding (domain II). When compared to the European Sorbus (S. aucuparia) of ITS2. ITS analysis may be useful in germ-plasm classification several taxa of genus Sorbus.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.307-332
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• 2022

One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.483-494
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• 2023

Measurement of the physical properties of rocks or minerals is an important factor in determining the distribution of the underground medium as well as mineral resource investigations. Resistivity and induced polarization, which are widely used in Korea, are methods for measuring electrical properties, which are representative properties of obtaining subsurface information. In order to precisely analyze the exploration data obtained from various sites, it is important to accurately measure the material properties. Electrical properties of rock is measured using two-electrode or four-electrode method. Compared to the four-electrode method, the two-electrode method is generally used because it is very easy to contact the sample and the electrode, but there is a problem in that the impedance of the electrode and the sample is measured together. In this study, the time-domain the induced polarization effects were measured using the 2-electrode method and the 4-electrode method for artificial samples mixed with graphite and cement having induced polarization characteristics, and the results were compared. Although the 4-electrode method has difficulties in installing potential electrodes, it was confirmed that it is effective in measuring electrical properties because it can reduce the problem caused by the impedance of potential electrodes compared to the 2-electrode method.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.235-243
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• 2007

Hepatocellular carcinoma is significant worldwide public health problem with an estimated annually mortality of 1,000,000 people. Radiofrequency (RF) ablation is an interventional technique that in recent years has come to be used for treatment of the hepatocellualr carcinoma, by destructing tumor tissues in high temperatures. Numerous studies have been attempted to prove excellence of RF ablation and to improve its efficiency by various methods. However, the attempts are sometimes paradox to advantages of a minimum invasive characteristic and an operative simplicity in RF ablation. The aim of the current study is, therefore, to suggest an improved RF ablation technique by identifying an optimum RF pattern, which is one of important factors capable of controlling the extent of high temperature region in lossless of the advantages of RF ablation. Three-dimensional finite element (FE) model was developed and validated comparing with the results reported by literature. Four representative Rf patterns (sine, square, exponential, and simulated RF waves), which were corresponding to currents fed during simulated RF ablation, were investigated. Following parameters for each RF pattern were analyzed to identify which is the most optimum in eliminating effectively tumor tissues. 1) maximum temperature, 2) a degree of alteration of maximum temperature in a constant time range (30-40 second), 3) a domain of temperature over $47^{\circ}C$ isothermal temperature (IT), and 4) a domain inducing over 63% cell damage. Here, heat transfer characteristics within the tissues were determined by Bioheat Governing Equation. Developed FE model showed 90-95% accuracy approximately in prediction of maximum temperature and domain of interests achieved during RF ablation. Maximum temperatures for sine, square, exponential, and simulated RF waves were $69.0^{\circ}C,\;66.9^{\circ}C,\;65.4^{\circ}C,\;and\;51.8^{\circ}C$, respectively. While the maximum temperatures were decreased in the constant time range, average time intervals for sine, square, exponential, and simulated RE waves were $0.49{\pm}0.14,\;1.00{\pm}0.00,\;1.65{\pm}0.02,\;and\;1.66{\pm}0.02$ seconds, respectively. Average magnitudes of the decreased maximum temperatures in the time range were $0.45{\pm}0.15^{\circ}C$ for sine wave, $1.93{\pm}0.02^{\circ}C$ for square wave, $2.94{\pm}0.05^{\circ}C$ for exponential wave, and $1.53{\pm}0.06^{\circ}C$ for simulated RF wave. Volumes of temperature domain over $47^{\circ}C$ IT for sine, square, exponential, and simulated RF waves were 1480mm3, 1440mm3, 1380mm3, and 395mm3, respectively. Volumes inducing over 63% cell damage for sine, square, exponential, and simulated RF waves were 114mm3, 62mm3, 17mm3, and 0mm3, respectively. These results support that applying sine wave during RF ablation may be generally the most optimum in destructing effectively tumor tissues, compared with other RF patterns.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.99-120
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• 2010

Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.

• Animal cells and systems
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• v.15 no.4
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• pp.310-314
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• 2011

The Banna miniature pig (BNMP) is a representative miniature pig breed in China. Even though BNMP dwarfism is obvious, its underlying causative mutations remain unknown. In this study, the BNMP and Large White pig (LWP) serum growth hormone (GH) and insulin-like growth factor (IGF-1) levels were detected by ELISA and compared. BNMP serum IGF-1 levels were significantly lower than LWP levels (P<0.05). The miniature condition may arise from mutations in the GH and GH receptor (GHR) genes. Therefore, GH and GHR cDNA from the BNMP were cloned into a pMD18-T vector by RT-PCR using the total RNA obtained from the BNMP's pituitary and liver tissues. Sequencing results indicated that the open reading frame of the BNMP GH gene is composed of a 26-residue signal peptide and a 191-residue mature peptide. The coding sequence of the BNMP GHR gene contained 639 amino acids, including a signal peptide that is 18 amino acids long. Two amino acid substitutions, A09V and R22Q, were found in the signal peptide of the GH gene. Additionally, the S104P mutation was found in the BNMP's mature GH protein. Four mutations in the cytoplasmic domain of GHR may influence the downstream signal transduction of GHR, which needs further experimental evidence.

• Journal of Korea Water Resources Association
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• v.50 no.4
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• pp.233-239
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• 2017

In this study, we analyzed typhoon affecting Korean Peninsula and runoff characteristic changes according to the typhoon based on Sumjin river dam, a representative multi-purpose dam. We quantified typhoon flow by applying the typhoon domain, and will provide base data for climate change adaptation and counterstrategy through correlation analysis of the change of typhoon statistical data and Indicators of Hydrologic Alterations (IHA). Korean Peninsula impact typhoon has a great effect on the scale of peak flow and the change of occurrence time. The occurrence frequency and duration of the peak flow were analyzed to be relatively unrelated to the typhoon affected by the Korean peninsula. These changes were also confirmed in the correlation analysis results. Correlation coefficient between the peak flow (0.41) and peak flow occurrence time (correlation coefficient = 0.83) was positively correlated with the Korean peninsula influenced typhoon.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.1
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• pp.48-60
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• 2007

Palpation of the pulse has been used in Korean traditional medicine since ancient times to assess physical health. Pulse wave contour may be obtained by measuring arterial pressure or blood volume change of skin. The latter is called as Photoplethysmography(PPG) or digital volume pulse(DVP). The PPG signal is measured by a device comprising an infrared light sourece and a photodetector. Although less widely used, this technique deserves further consideration because of its simplicity and ease of use. The contour of the PPG is formed as a result of a complex interaction between the left ventricle and the systemic circulation. It usually exhibits an early systolic peak and an early diastolic peak. the first peak is formed mainly by pressure trasmitted along a direct path from the left ventricle to the finger. The second peak is formed in part by pressure transmitted along the aorta and large arteries to sites of impedance mismatch in the lower body. The contour of the PPG is sensitive to changes in arterial tone and is influenced by ageing and large artery stiffness. Measurements taken directly from the PPG or from its second derivative can be used to assess these properties. In some mathematical approaches, the extraction of periodic components using frequency analysis was tried to analysis of the PPG. But we don't understand yet what kind of factor in the cardiovascular system or human body is related with the respective specific Fourier components of PPG. This review describes the background to measurement principles, representative contour, contour analysis and frequency domain analysis of PPG, and current and future.