• Convergence Security Journal
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• v.11 no.1
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• pp.71-77
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• 2011

NCW(Network Centric- Warfare) encompasses the concept to use computer data processing and network linkage communications techniques, share information and furthermore, enhance the effectiveness of computer-operating systems. As IT(Information & Technology) have become developed in the recent years, the existing warfare system-centered conventional protocol is not use any longer. Instead, network-based NCW is being widely-available, today. Under this changing computer environment, it becomes important to establish algorithm and build the stable communication systems. Tools to identify malign node factors through Wireless Ad-hoc network cause a tremendous error to analyze and use paths of even benign node factors misreported to prove false without testing or indentifying such factors to an adequate level. These things can become an obstacle in the process of creating the optimum network distribution environment. In this regard, this thesis is designed to test and identify paths of benign node factors and then, present techniques to transmit data through the most significant open short path, with the tool of MP-SAR Protocol, security path search provider, in Ad-hoc NCW environment. Such techniques functions to identify and test unnecessary paths of node factors, and thus, such technique users can give an easy access to benign paths of node factors.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.174-179
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• 2015

Failure Mode and Effects Analysis (FMEA) has been used by Dynamic Positioning (DP) system for risk and reliability analysis. However, there are limitations associated with its implementation in offshore project. 1) since the failure data measured from the SCADA system is missing or unreliable, assessments of Severity, Occurrence, Detection are based on expert's knowledge; 2) it is not easy for experts to precisely evaluate the three risk factors. The risk factors are often expressed in a linguistic way. 3) the relative importance among three risk factors are rarely even considered. To solve these problems and improve the effectiveness of the traditional FMEA, we suggest a Fuzzy-FMEA method for risk and failure mode analysis in Dynamic Positioning System of offshore. The information gathered from DP FMEA report and DP FMEA Proving Trials is expressed using fuzzy linguistic terms. The proposed method is applied to an offshore Dynamic Positioning system, and the results are compared with traditional FMEA.

• Microbiology and Biotechnology Letters
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• v.31 no.4
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• pp.377-382
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• 2003

Purification of methioninase resulted in a yield of 69%, and SDS-PAGE analysis of the purified product revealed a single band of approximately 43 kDa in molecular weight. in vitro experiments with cancer cells incubated in methionine-free media demonstrated an increase in $^{11}$ C-methionine uptake to 25.8$\pm$1.1% at 6 hr, 31.8$\pm$0.8% at 24 hr, and 62.2$\pm$0.6% at 48hr, compared to controls. Treatment of the cancer cells with purified methioninase showed no decrease in survival after a 2 hr incubation with 0.01 U/ml, but survival of RR1022 cells decreased 30% after 24 to 48 hr incubation. SKOV-3 cells showed a 5% and 14% decrease in survival with 0.1 and 1 U/ml methioninase after 24 hr. After 48hr survival decreased 15% and 24% with 0.1 and 1 U/ml methioninase. Measurements of $^{11}$ C-methionine uptake in RR1022 cells demonstrated no change at 2 hr, but a 13.7$\pm$4.7% and 40.7$\pm$2.6% increase in uptake at 24 and 48 hr, respectively. SKOV-3 cells also showed no change at 2 hr, but had a 17.7$\pm$7.2% and 38.9$\pm$4.9% increase in $^{11}$ C-methionine uptake after 24 hr and 48 hr treatment with methioninase, respectively. $^{11}$ C-methionine PET imaging revealed clear visualization of both the tumors and contralateral infectious lesions. Administration of rMET appeared to result in a slight increase in tumor:nontumor contrast on $^{11}$ C-methionine PET images. Injection of purified methioninase also produced PET images where tumor uptake was higher than that of infectious lesions.

• Journal of KIISE:Software and Applications
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• v.33 no.7
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• pp.605-614
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• 2006

The success of a software development project can be determined by the use of QCD. And as a software's size and complexity increase, the importance of early quality assurance rises. Therefore, more effort should be given to prevention, as opposed to correction. In order to provide a framework for the prevention of defects, defect detection activities such as peer review and testing, along with analysis of previous defects, is required. This entails a systematization and use of quality data from previous development efforts. FMEA, which is utilized for system safety assurance, can be applied as a means of software defect prevention. SW-FMEA (Software Failure Mode Effect Analysis) attempts to prevent defects by predicting likely defects. Presently, it has been applied to requirement analysis and design. SW-FMEA utilizes measured data from development activities, and can be used for defect prevention on both the development and management sides, for example, in planning, analysis, design, peer reviews, testing, risk management, and so forth. This research discusses about related methodology and proposes defect prevention model based on SW-FMEA. Proposed model is extended SW-FMEA that focuses on system analysis and design. The model not only supports verification and validation effectively, but is useful for reducing defect detection.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.6
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• pp.1149-1158
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• 2000

A radioisotope tracer experiment was carried out in the submerged fixed bioreactor of a dye wastewater treatment facility to evaluate the flow behaviors in the 6 compartments of the reactor and to find any possible factors which may affect to the efficiency of the process. Approximately 20mCi of $^{131}I$ was injected into the system as a tracer and 8 radiation detectors were placed in the 6 compartments and at the inlet and the outlet of the system to measure the change of the tracer concentration with time. Using the Perfect Mixers in Series Model the measured data were analyzed to calculate the mean residence time and the characteristic parameters of the flow in the system. The mean residence time of the system was calculated as 17 hours which is 76% of the designed MRT(22.3hr). Among the 6 compartments, the first compartment doesn't show the characteristic of perfect mixer, whereas, the other 5 compartments are working as perfect mixers. The output response of the first compartment is fit well with the simulated output of a model which consists of a perfect mixer with an exchange volume. It indicates that a quarter of the tank volume is working as a dead volume or an exchange volume. From the measured residence time distributions in each compartment, the appropriate sampling times after the change of operational condition of the electron beam accelerator were evaluated.

• Analytical Science and Technology
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• v.28 no.4
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• pp.260-269
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• 2015

The protective effects of extract powder of Angelica gigas on the degeneration of the articular cartilage in rats was investigated with monosodium iodoacetate (MIA)-induced osteoarthritis, The treatment of high concentration (50 μg/mL) of Angelica gigas effectively inhibited nitric oxide (NO) production induced by interleukin-1α (IL-1α) without any cytotoxicity. Specifically, mRNA and protein expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) were dose dependently reduced by extract powder of Angelica gigas. Importantly, mRNA expression in articular cartilage of inflammatory cytokines, tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and interleukin-6 (IL-6) were clearly reduced. The inflammatory cytokines in blood were also reduced as well. These results suggested that the protective effects on the degeneration of the articular cartilage was derived from the inhibitory effects of mRNA and protein expression of tested inflammatory cytokines which is linked to prevent the degradation of proteoglycan (PG), the main matrix content in articular cartilage. Meanwhile, the 2 hrs incubation of decursin, a major compound of extract powder in rat whole blood rapidely converted decursin into decursinol which shows string anti-inflammatory activity. The coverted decursinol was detected after 8 hrs in whole blood by LC-MS/MS. Conclusively, the inhibitory effects of inflammatory cytokines production in osteoarthritis may be derived from the production of decursinol, which performs against inflammatroy cytokines like TNF-α, IL-1β, and IL-6.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.1
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• pp.9-18
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• 2018

Recently, the use of image stitching technology has been increasing as the number of contents based on virtual reality increases. Image Stitching is a method for matching multiple images to produce a high resolution image and a wide field of view image. The image stitching is used in various fields beyond the limitation of images generated from one camera. Image Stitching detects feature points and corresponding points to match multiple images, and calculates the homography among images using the RANSAC algorithm. Generally, corresponding points are needed for calculating conversion relation. However, the corresponding points include various types of noise that can be caused by false assumptions or errors about the conversion relationship. This noise is an obstacle to accurately predict the conversion relation. Therefore, RANSAC algorithm is used to construct an accurate conversion relationship from the outliers that interfere with the prediction of the model parameters because matching methods can usually occur incorrect correspondence points. In this paper, we propose an algorithm that extracts more accurate inliers and computes accurate transformation relations by using correspondence point relation information used in RANSAC algorithm. The correspondence point relation information uses distance ratio between corresponding points used in image matching. This paper aims to reduce the processing time while maintaining the same performance as RANSAC.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.739-752
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• 2002

Recently, to utilize the limited bandwidth effectively, the concept of partial response (PR) signaling has widely been adopted in both the high-speed data transmission and high-density digital recording/playback systems such as digital microwave, digital subscriber loops, hard disk drives, digital VCR's and digital versatile recordable disks and so on. This paper is concerned with adaptive equalization of partial response channels particularly for the magnetic recording channels. Specifically we study how the PR channel equalizers work for different choices of desired or reference signals used for adjusting the equalizer weights. In doing so, we consider three different configurations that are actually implemented in the commercial products mentioned above. First of all, we show how to compute the theoretical values of the optimum Wiener solutions derived by minimizing the mean-squared error (MSE) at the equalizer output. Noting that this equalizer MSE measure cannot be used to fairly compare the three configurations, we propose to use the data MSE that is computer just before the final detector for the underlying PR system. We also express the data MSE in terms of the channel impulse response values, source data power and additive noise power, thereby making it possible to compare the performance of the configurations under study. The results of extensive computer simulation indicate that our theoretical derivation is correct with high precision. Comparing the three configurations, it also turns out that one of the three configurations needs to be further improved in performance although it has an apparent advantage over the others in terms of memory size when implemented using RAM's for the decision feedback part.

• Journal of Food Hygiene and Safety
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• v.19 no.1
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• pp.49-54
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• 2004

The prevention of infectious disease from contaminated foods is very important in public health. Quantitative microbial risk assessment has been used in advance countries to achieve the safety of public health against hazardous microbial causing contaminated foods. This study was conducted to estimate maximum edible time without producing enterotoxin from Staphylococcus aureus in Kimbap selling at different domestic store using Food MicroModel and monitoring data and to compute maximum edible time by temperature with 99th percentile safety probability based on only restaurant data. For estimating maximum edible time, model operation conditions like reaching time at 2 ${\times}$ 10$^{7}$ , which enterotoxin was known as producing point from S. aureus, temperature of 28∼3$0^{\circ}C$, pH 5.2, NaCl 0.22%, aw(water activity) 0.99, and intaking one serving size of 171g in Kimbap were considered. Estimated maximum edible times by regarding outdoor temperature in summer were 3.9∼4.6 hrs in restaurant, 6.7∼7.9 hrs in department store and 7.4∼8.7 hrs in convenient store. Based on restaurant data, estimated maximum edible times with 99th percentile safety probability by temperature were 1.9 hrs in 3$0^{\circ}C$ and 17.7 hrs in 15$^{\circ}C$.

• Smart Media Journal
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• v.10 no.3
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• pp.31-38
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• 2021

It is hard to predict when and where a fall accident will happen. Also, if rapid follow-up measures on it are not performed, a fall accident leads to a threat of life, so studies that can automatically detect a fall accident have become necessary. Among automatic fall-accident detection techniques, a fall detection scheme using an IMU (inertial measurement unit) sensor attached to a wrist is difficult to detect a fall accident due to its movement, but it is recognized as a technique that is easy to wear and has excellent accessibility. To overcome the difficulty in obtaining fall data, this study proposes an algorithm that efficiently learns less data through machine learning such as KNN (k-nearest neighbors) and SVM (support vector machine). In addition, to improve the performance of these mathematical classifiers, this study utilized feature data aquired in the frequency space. The proposed algorithm analyzed the effect by diversifying the parameters of the model and the parameters of the frequency feature extractor through experiments using standard datasets. The proposed algorithm could adequately cope with a realistic problem that fall data are difficult to obtain. Because it is lighter than other classifiers, this algorithm was also easy to implement in small embedded systems where SIMD (single instruction multiple data) processing devices were difficult to mount.