• Diabetes and Metabolism Journal
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• v.42 no.6
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• pp.519-528
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• 2018

Background: Clinical manifestations of diabetic peripheral neuropathy (DPN) vary along the course of nerve damage. Nerve conduction studies (NCS) have been suggested as a way to confirm diagnoses of DPN, but the results have limited utility for evaluating clinical phenotypes. The current perception threshold (CPT) is a complementary method for diagnosing DPN and assessing DPN symptoms. We compared NCS variables according to clinical phenotypes determined by CPT measurements. Methods: We retrospectively enrolled patients with type 2 diabetes mellitus who underwent both NCS and CPT tests using a neurometer. CPT grades were used to determine the clinical phenotypes of DPN: normoesthesia (0 to 1.66), hyperesthesia (1.67 to 6.62), and hypoesthesia/anesthesia (6.63 to 12.0). The Michigan Neuropathy Screening Instrument (MNSI) was used to determine a subjective symptom score. DPN was diagnosed based on both patient symptoms (MNSI score ${\geq}3$) and abnormal NCS results. Results: A total of 202 patients (117 men and 85 women) were included in the final analysis. The average age was 62.6 years, and 71 patients (35.1%) were diagnosed with DPN. The CPT variables correlated with MNSI scores and NCS variables in patients with diabetes. Linear regression analyses indicated that hypoesthesia was associated with significantly lower summed velocities and sural amplitudes and velocities, and higher summed latencies, than normoesthesia. Sural amplitude was significantly lower in patients with hyperesthesia than in patients with normoesthesia. Conclusion: NCS variables differed among patients with diabetes according to clinical phenotypes based on CPT and decreased sural nerve velocities was associated with hyperesthesia.

• Explosives and Blasting
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• v.39 no.3
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• pp.1-14
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• 2021

Rockburst is a sudden and violent failure of rock. During the failure process, excess energy is liberated as seismic energy, which in turn causes the surrounding rock mass to vibrate. The level of the ground vibration can reach a magnitude of over 4.5 in the Richter local scale. Thus, a rockburst can cause not only injury to persons, but also damage to both underground workings and surface structures. In this paper the source mechanism of rockburst is analyzed based mainly on the two reports of the Canadian Rockburst Research Program (CRRP). A simplified LS-DYNA modeling is also performed to identify the tensile failure patterns occurring in the remaining rock mass right after blasting in mine stope. The configuration of the simplified model will probably be useful in small-scale laboratory tests for investigating the source mechanism of rockburst.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.33-39
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• 2019

As cyber attack methods are becoming more intelligent, incidents such as security breaches and international crimes are increasing. In order to predict and respond to these cyber attacks, the characteristics, methods, and types of attack techniques should be identified. To this end, many security companies are publishing security intelligence reports to quickly identify various attack patterns and prevent further damage. However, the reports that each company distributes are not structured, yet, the number of published intelligence reports are ever-increasing. In this paper, we propose a method to extract structured data from unstructured security intelligence reports. We also propose an automatic intelligence report analysis system that divides a large volume of reports into sub-groups based on their topics, making the report analysis process more effective and efficient.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.153-172
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• 2018

Overloading of Commercial vehicles have been an important area of transportation as one of the main causes of pavement damage, bridge collapse, severe traffic accident, etc. In this study, we analyzed the effects of overweight prevention by analyzing overweight driving patterns and using weight sensors. First, we analyzed relevant literatures of overweight and surveyed the commercial weight sensors. Then we chose the typical type of overweight vehicles based of overweight enforcement data analysis. MEMs inclinometer weight sensor were installed to 10 test vehicles and data was collected by weight sensors and gps in real time. As a result of gross vehicle weight and axle weight analysis, it was found weight sensor could decrease overweight rate. However, since the number of samples of test vehicles is insufficient to represent the whole commercial vehicle, further studies are deemed possible through the extension test.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.6
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• pp.505-513
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• 2018

Main engine failures in ship operations can lead to a major damage in terms of the vessel itself and the financial cost. In this respect, monitoring of a vessel's main engine condition is crucial in ensuring the vessel's performance and reducing the maintenance cost. The collection of a huge amount of vessel operational data in the maritime industry has never been easier with the advent of advanced data collection technologies. Real-time monitoring of the condition of a vessel's main engine has a potential to create significant value in maritime industry. This study presents a case study on the establishment of upper control limit to detect vessel's main engine failures using multivariate control chart. The case study uses sample data of an ocean-going vessel operated by a major marine services company in Korea, collected in the period of 2016.05-2016.07. This study first reviews various main engine-related variables that are considered to affect the condition of the main engine, and then attempts to detect abnormalities and their patterns via multivariate control charts. This study is expected to help to enhance the vessel's availability and provide a basis for a condition-based maintenance that can support proactive management of vessel's main engine in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.791-800
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• 2017

For fires in ship accommodation areas, if it is possible to predict the pattern in which fire will spread and suggest proper countermeasures according to a situation using a fire simulation tool, fire damage may be reduced. However, fire simulations have a practical limit: a significant amount of time is required to analyze the results due to the size of the computational domain and the number of grids. Therefore, in this study, applicable grid size for fire simulations to predict fire patterns in ship accommodation areas was analyzed, and a generation method was conducted to predict fire behavior in real time. As a result, a value within 0.25[m] was judged appropriate as an applicable grid size for ship accommodation areas. Also, in comparison with studies using a single mesh generation method, the visibility value was similar, within 4.3 %, as was the temperature value, within 8.3 %, when a multi mesh generation method was used, showing a decline of 80 % in analysis time. Therefore, it was confirmed that composing a grid using multi mesh was effective for reducing analysis time.

• BMB Reports
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• v.52 no.6
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• pp.373-378
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• 2019

The nucleotide-binding and oligomerization domain (NOD) is an innate pattern recognition receptor that recognizes pathogen- and damage-associated molecular patterns. The 29-kDa amino-terminal fibronectin fragment (29-kDa FN-f) is a matrix degradation product found in the synovial fluids of patients with osteoarthritis (OA). We investigated whether NOD2 was involved in 29-kDa FN-f-induced pro-catabolic gene expression in human chondrocytes. The expression of mRNA and protein was measured using quantitative real-time polymerase chain reaction (qrt-PCR) and Western blot analysis. Small interfering RNAs were used for knockdown of NOD2 and toll-like receptor 2 (TLR-2). An immunoprecipitation assay was performed to examine protein interactions. The NOD2 levels in human OA cartilage were much higher than in normal cartilage. NOD1 and NOD2 expression, as well as pro-inflammatory cytokines, including interleukin-1beta (IL-$1{\beta}$) and tumor necrosis factor-alpha (TNF-${\alpha}$), were upregulated by 29-kDa FN-f in human chondrocytes. NOD2 silencing showed that NOD2 was involved in the 29-kDa FN-f-induced expression of TLR-2. Expressions of IL-6, IL-8, matrix metalloproteinase (MMP)-1, -3, and -13 were also suppressed by TLR-2 knockdown. Furthermore, NOD2 and TLR-2 knockdown data demonstrated that both NOD2 and TLR-2 modulated the expressions of their adaptors, receptorinteracting protein 2 (RIP2) and myeloid differentiation 88, in 29-kDa FN-f-treated chondrocytes. 29-kDa FN-f enhanced the interaction of NOD2, RIP2 and transforming growth factor beta-activated kinase 1 (TAK1), an indispensable signaling intermediate in the TLR-2 signaling pathway, and activated nuclear factor-${\kappa}B$ (NF-${\kappa}B$), subsequently leading to increased expressions of pro-inflammatory cytokines and cartilage-degrading enzymes. These results demonstrate that 29-kDa FN-f modulated pro-catabolic responses via cross-regulation of NOD2 and TLR-2 signaling pathways.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.369-380
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• 2019

When a extreme loading such as blast is applied to prestressed concrete (PSC) structures and infrastructures for an instantaneous time, serious property damages and human casualties occur. However, a existing design procedure for PSC structures such as prestressed containment vessel (PCCV) and gas storage tank do not consider a protective design for extreme internal blast scenario. Particularly, an internal blast is much more dangerous than that of external blast. Therefore, verification of the internal blast loading is required. In this paper, the internal blast resistance capacity of PSC member is evaluated by performing internal blast tests on RC and bi-directional PSC scaled down specimens. The applied internal blast loads were 22.68, 27.22, and 31.75 kg (50, 60, and 70 lbs) ANFO explosive charge at 1,000 mm standoff distance. The data acquisitions include blast pressure, deflection, strain, crack patterns, and prestressing force. The test results showed that it is possible to predict the damage area to the structure when internal blast loading occurs in PCCV structures.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.97-105
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• 2008

The various mutations of the malicious codes are fast generated on the network. Also the behaviors of them become intelligent and the damage becomes larger step by step. In this paper, we suggest the method to select the useful measures for the detection of the codes. The method has the advantage of shortening the detection time by using header data without payloads and uses connection data that are composed of TCP/IP packets, and much information of each connection makes use of the measures. A naive estimator is applied to the probability distribution that are calculated by the histogram estimator to select the specific measures among 80 measures for the useful detection. The useful measures are then selected by using relative entropy. This method solves the problem that is to misclassify the measure values. We present the usefulness of the proposed method through the result of the detection experiment using the detection patterns based on the selected measures.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.1
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• pp.55-63
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• 2006

Recently, there is much abnormal traffic driven by several worms, such as Nimda, Code Red, SQL Stammer, and so on, making badly severe damage to networks. Meanwhile, diverse prevention schemes for defeating abnormal traffic have been studied in the academic and commercial worlds. In this paper, we present the structure of a stepwise intrusion prevention system that is designed with the feature of putting limitation on the network bandwidth of each network traffic and dropping abnormal traffic, and then compare the proposed scheme with a pre-existing scheme, which is a True/False based an anomaly prevention scheme for several worm-patterns. There are two criteria for comparison of the schemes, which are Normal Traffic Rate (NTR) and False Positive Rate (FPR). Assuming that the abnormal traffic rate of a specific network is $\beta$ during a predefined time window, it is known that the average NTR of our stepwise intrusion prevention scheme increases by the factor of (1+$\beta$)/2 than that of True/False based anomaly prevention scheme and the average FPR of our scheme decrease by the factor of (1+$\beta$)/2.