• Tunnel and Underground Space
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• v.32 no.5
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• pp.285-297
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• 2022

We report results of Extended Leak-Off Test (XLOT) conducted in a large diameter borehole, which is drilled for installation of deep borehole geophysical monitoring system to monitor micro-earthquakes and fault behavior of major fault zones in the southeastern Korean Peninsula. The borehole was planned to secure a final diameter of 200 mm (or more) at a depth of ~1 km, with 12" diameter wellbore to intermediate depths, and 7-7/8" (~200 mm) to the bottom hole depth. We drilled first the 12" borehole to approximately 504 m deep and installed American Petroleum Institute standard 8-5/8" casing, then annulus between the casing and bedrock was fully cemented. XLOT was carried out for several purposes such as confirming casing and cementing integrity, measuring rock stress states. To that end, we drilled additional 4 m long open hole interval to directly inject water and pressurize into the rock mass using the upper API casings. During the XLOT, flow rates and interval pressures were recorded in real time. Based on the logs we tried to analyze hydraulic conductivity of the test interval.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.759-768
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• 2004

Recently the biometric recognition technology is intensively studied and the standardization of the technology has been highly demanded for its commercialization. Currently many blometric recognition products are being developed based on the BioAPl(Biometric Application Program-ming Interface) specification. However, the reliable testing tools (or scenarios) to evaluate performance and conformance of the products are not shown yet. In this paper, a conformance testing method is presented, which verifies a biometric recognition system to meet the requirements of the BioAPl standard. Two different testing procedures are used in the proposed method. The first procedure evaluates that each functions offered in the BioAPl specification are correctly implemented and that the functions are actually used in the system. Through the Procedure, a BSP(Biometric Service Provider) system is executed on the framework of the BioAPl functions. It requires selection of parameters and prece-dent functions that should be executed first. The second procedure evaluates the abilities of module management, handling operations and ver-ification process by the analysis of the test cases. It tests the correctness of the system operation when a testing scenario is given. The proposed testing method is applied on a fingerprint verification BSP using the sample BSP provided by the BioAPl consortium. The experimental results shows the benefits of the proposed testing method.

• Mycobiology
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• v.47 no.4
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• pp.449-456
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• 2019

Invasive fungal infections caused by Cyberlindnera fabianii have recently increased. However, biochemical kits such as API 20 C AUX and Vitek-2C have misidentified this species as other Candida spp. such as C. pelliculosa or C. utilis due to no information of Cy. fabianii in yeast database. During our 2016-2017 surveys, eleven isolates of Cy. fabianii were obtained in International St. Mary's Hospital in Korea. Here, we describe its morphological and molecular characteristics and tested its antifungal susceptibility against nine antifungal agents. The sequences of the ITS region and the D1/D2 region of LSU revealed 100% identity with the sequences of Cy. fabianii. In comparison with the results from MALDI-TOF mass spectrometry, we found that Cy. fabianii can be distinguished from other species. In antifungal susceptibility test, voriconazole and echinocandins exhibited good antifungal activities against the majority of Cy. fabianii isolates despite the absence of standard criteria.

• Food Science of Animal Resources
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• v.28 no.5
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• pp.637-644
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• 2008

Four different extraction and purification methods were evaluated to determine the heterocyclic amines (HCAs) in fried pork patties. Pork patties were cooked in the teflon-coated electric frying pan at $230^{\circ}C$ for 8 min per side. HCAs in the fried pork patties were extracted and purified using four different solid-phase extraction (SPE) methods and quantitated by LC-MS (API-ESI). Recovery of four different extraction and purification methods was evaluated by comparing the HCAs amounts quantified by the standard addition method. Validation of extraction and purification methods for fried pork patties was determined to establish accurate sample preparation. The recoveries of HCAs from different SPE methods were calculated. The recovery yields were 15.7-68.7% (Polar amine group) and 25.0-74.7% (less-polar amine group) in method A. Method D provided recovery yields ranging from 14.1% to 68.7% in polar amine groups and from 3.0% to 72.3% in less-polar amine groups, respectively. Modified procedures of Method A and D were the most suitable extraction and purification method for HCAs analysis from fried pork patties.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.554-557
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• 2016

Recently, supercomputer has been increasingly adopted as a computing environment for scientific simulation as well as education, healthcare and national defence. Especially, supercomputing system with heterogeneous computing resources is gaining resurgence of interest as a next-generation problem solving environment, allowing theoretical and/or experimental research in various fields to be free of time and spatial limits. However, traditional supercomputing services have only been handled through a simple form of command-line based console, which leads to the critical limit of accessibility and usability of heterogeneous computing resources. To address this problem, in this paper, we provide the design and implementation of web-based HPC (High Performance Computing) job management framework for computational scientific simulation. The proposed framework has highly extensible design principles, providing the abstraction interfaces of job scheduler (as well as bundle scheduler plug-ins for LoadLeveler, Sun Grid Engine, OpenPBS scheduler) in order to easily incorporate the broad spectrum of heterogeneous computing resources such as cluster, computing cloud and grid. We also present the detailed specification of HTTP standard based RESTful endpoints, which manage simulation job's life-cycles such as job creation, submission, control and status monitoring, etc., enabling various 3rd-party applications to be newly created on top of the proposed framework.

• Journal of the Korea Society for Simulation
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• v.26 no.2
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• pp.1-8
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• 2017

High Level Architecture(HLA) is a specification for interoperation among heterogeneous simulators which are executed in a distributed environment. HLA originally allows many federates to join in a federation using a single RTI(Run-Time Infrastructure). As the target systems become more complex, the need for the interoperation of federations, performed in a RTI-RTI interoperation environment, has been growing. It can be performed by the confederation interface with the agents, which subrogate the API calls and callbacks of each federation. The existing studies have assumed that the object models of each federation are based on same HLA standard and their object descriptions are equal. Because the existing federations are usually not under this assumption, this paper proposes the integration process of object models for the federation interoperation environment. To integrate the object models for the interoperation of federations, this process resolves the differences of HLA standards, provides conversion process between objects with different descriptions and excludes the security objects. We expect that this process enhances the reusability and effectiveness of interoperation of federations in various domains.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.2
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• pp.151-160
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• 2017

Growing demand and rapid development of the synthetic fiber rope in mooring system have taken place since it has been used in deep water platform lately. Unlike a chain mooring, synthetic fiber rope composed of lightweight materials such as Polyester(polyethylene terephthalate), HMPE(high modulus polyethylene) and Aramid(aromatic polyamide). Non-linear stiffness and another failure mode are distinct characteristics of synthetic fiber rope when compared to mooring chain. When these ropes are exposed to environmental load for a long time, the length of rope will be increased permanently. This is called 'the creep phenomenon'. Due to the phenomenon, The initial characteristics of mooring systems would be changed because the length and stiffness of the rope have been changed as time goes on. The changed characteristics of fiber rope cause different mooring tension and vessel offset compared to the initial design condition. Commercial mooring analysis software that widely used in industries is unable to take into account this phenomenon automatically. Even though the American Petroleum Institute (API) or other classification rules present some standard or criteria with respect to length and stiffness of a mooring line, simulation guide considers the mechanical properties that is not mentioned in such rules. In this paper, the effect of creep phenomenon in the fiber rope mooring system under specific environment condition is investigated. Desiged mooring system for a Mobile Offshore Drilling Unit(MODU) with HMPE rope which has the highest creep is analyzed in a time domain in order to investigate the effects creep phenomenon to vessel offset and mooring tension. We have developed a new procedure to an analysis of mooring system reflecting the creep phenomenon and it is validated through a time domain simulation using non-linear mooring analysis software, OrcaFlex. The result shows that the creep phenomenon should be considered in analysis procedure because it affects the length and stiffness of synthetic fiber rope in case of high water temperature and permanent mooring system.

• Food Science of Animal Resources
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• v.23 no.3
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• pp.269-277
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• 2003

This study was carried out to evaluate the safety of Korean human milk. The microorganisms were identified from human milk of 149 healthy mothers by two collection methods, hand and pump expression. The means of total bacterial counts were 2.33x10$^4$ cfu/mL on the samples collected by the pump expression and 7.83xl0$^3$ cfu/mL on those collected by the hand expression. Therefore, the total bacterial counts of pump expression samples was 9.80xl0$^2$∼3.06x10$^4$ cfu/mL more than that of hand expression samples. The coliform counts of pump expression was 9.36xl0$^3$∼8.57xl0$^4$ cfu/mL more than that of hand expression. However, there was any significant differences of the lactic acid bacterial counts between the two samples collected by each methods. 100 strains of 5 patterns of total bacterial counts were isolated based on the morphology of colony in the standard plate count agar. 13 species were identified among the isolated strains. The dominant species in Korean human milk were Staphylococcus which 7 subspecies identified(81% in the rate of total bacteria, 1.07x10$^4$ cfu/mL). Other species identified were Micrococcus, Bacillus, Providencia, Pseudomonas, Yersinia and Acinetobacter. 36 strains of 6 patterns of lactic acid bacterial counts were isolated based on morphology of colony in the BCP agar. 7 species were identified among the isolated strains. The dominant species of lactic acid bacteria in Korean human milk were Lactobacillus brevis(50.9% in the rate of lactic acid bacteria, 4.72xl0$^4$ cfu/mL). Others species identified(49.1% lactic acid bacteria) were Lactobacillus curvatus, Lactobacillus delbrueckii subsp. lactis, Lactobacillus acidophilus, Leuconostic lactis and Streptococcus salivarius subsp. thermophilus.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.367-376
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• 2007

In this paper, we introduce an application-specific and adaptive power management technique for portable systems that support dynamic voltage scaling (DVS). We exploit both the idle time of multitasking systems running soft real-time tasks as well as memory- or CPU-bound code regions. Detailed power and execution time profiles guide an adaptive power manager (APM) that is linked to the operating system. A post-pass optimizer marks candidate regions for DVS by inserting calls to the APM. At runtime, the APM monitors the CPU's performance counters to dynamically determine the affinity of the each marked region. for each region, the APM computes the optimal voltage and frequency setting in terms of energy consumption and switches the CPU to that setting during the execution of the region. Idle time is exploited by monitoring system idle time and switching to the energy-wise most economical setting without prolonging execution. We show that our method is most effective for periodic workloads such as video or audio decoding. We have implemented our method in a multitasking operating system (Microsoft Windows CE) running on an Intel XScale-processor. We achieved up to 9% of total system power savings over the standard power management policy that puts the CPU in a low Power mode during idle periods.