• Journal of Breast Disease
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• v.6 no.2
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• pp.52-59
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• 2018

Purpose: This study aimed to determine whether clinicopathological factors are potentially associated with successful breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NAC) and develop a nomogram for predicting successful BCS candidates, focusing on those who are diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative tumors during the pre-NAC period. Methods: The training cohort included 239 patients with an HR-positive, HER2-negative tumor (${\geq}3cm$), and all of these patients had received NAC. Patients were excluded if they met any of the following criteria: diffuse, suspicious, malignant microcalcification (extent >4 cm); multicentric or multifocal breast cancer; inflammatory breast cancer; distant metastases at the time of diagnosis; excisional biopsy prior to NAC; and bilateral breast cancer. Multivariate logistic regression analysis was conducted to evaluate the possible predictors of BCS eligibility after NAC, and the regression model was used to develop the predicting nomogram. This nomogram was built using the training cohort (n=239) and was later validated with an independent validation cohort (n=123). Results: Small tumor size (p<0.001) at initial diagnosis, long distance from the nipple (p=0.002), high body mass index (p=0.001), and weak positivity for progesterone receptor (p=0.037) were found to be four independent predictors of an increased probability of BCS after NAC; further, these variables were used as covariates in developing the nomogram. For the training and validation cohorts, the areas under the receiver operating characteristic curve were 0.833 and 0.786, respectively; these values demonstrate the potential predictive power of this nomogram. Conclusion: This study established a new nomogram to predict successful BCS in patients with HR-positive, HER2-negative breast cancer. Given that chemotherapy is an option with unreliable outcomes for this subtype, this nomogram may be used to select patients for NAC followed by successful BCS.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.619-630
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• 2018

The purpose of this study is to investigate the existence of faults and intrusive rocks in the volcanic rock mass of Ulleung-do using magnetic anomalies. The magnetic survey data show that basaltic (mafic) rocks have high magnetic anomalies and that trachytic (felsic) rocks have low magnetic anomalies, implying that the anomaly distributions can be used to distinguish between different volcanic rock types that may be covered by regolith (such as alluvial and colluvial deposits) and other sedimentary layers. Our results show that basaltic rocks are not present within the Nari caldera. However, outside the caldera, the occurrence of high magnetic anomaly values of >$1,000{\gamma}$ is presumed to reflect the existence of basaltic craters or volcanic vents that formed prior to the eruption of the trachytic rocks. In particular, the area with anomaly values of >$1,000{\gamma}$ in the vicinity of Namyang-ri, southwest of Ulleung-do, is interpreted as having a high probability of hosting a crater and vent originating from mafic volcanism.

• Korean Journal of Food Science and Technology
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• v.52 no.6
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• pp.661-669
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• 2020

Samgak-Kimbap is a popular ready-to-eat (RTE) food at convenience stores, in Korea. Although Samgak-Kimbap is distributed through the cold chain supply system, inappropriate temperature storage conditions prior to consumption are a cause of concern. The objective of this study was to evaluate the risk of Staphylococcus aureus growth in Samgak-Kimbap in the retail market. The prevalence and contamination levels of S. aureus in Samgak-Kimbap (n=170) were monitored, and the predictive growth model of a five-strain cocktail of enterotoxin-producing S. aureus (SEA, SEB, SEC, SED, and SEE) was developed in Samgak-Kimbap as a function of temperature (4, 10, 11, 20, 25, and 37℃). We could not observe the growth of S. aureus and enterotoxin-producing S. aureus in Samgak-Kimbap at temperatures below 10℃. The probability of illness with S. aureus per serving of Samgak-Kimbap was 1.44×10-10 per day. The most influential factor in increasing the risk of foodborne illnesses was the contamination level of S. aureus in Samgak-Kimbap.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.132-144
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• 2023

Recently, the frequency and intensity of heat waves due to the increase in climate change temperature are increasing. Therefore, this study tried to compare the evaluation process and evaluation results of the heat wave disaster evaluation, which is the government's analysis of the heat wave disaster vulnerability and the risk evaluation method recently emphasized by the IPCC. The analysis of climate change disaster vulnerability is evaluated based on manuals and guidelines prepared by the government. Risk evaluation can be evaluated as the product of the possibility of a disaster and its impact, and it is evaluated using the Markov chain Monte Carlo simulation based on Bayesian estimation method, which uses prior information to infer posterior probability. As a result of the analysis, the two evaluation results for Busan Metropolitan City differed slightly in the spatial distribution of areas vulnerable to heat waves. In order to properly evaluate disaster vulnerable areas due to climate change, the process and results of climate change disaster vulnerability analysis and risk assessment must be reviewed, and consider each methodology and countermeasures must be prepared.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.75-89
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• 2006

This paper presents a practical and realistic Life-Cycle Cost (LCC) optimum design methodology of steel bridges considering time effect of bridge reliability under environmental stressors such as corrosion and heavy truck traffics. The LCC functions considered in the LCC optimization consist of initial cost, expected life-cycle maintenance cost and expected life-cycle rehabilitation costs including repair/replacement costs, loss of contents or fatality and injury losses, road user costs, and indirect socio-economic losses. For the assessment of the life-cycle rehabilitation costs, the annual probability of failure which depends upon the prior and updated load and resistance histories should be accounted for. For the purpose, Nowak live load model and a modified corrosion propagation model considering corrosion initiation, corrosion rate, and repainting effect are adopted in this study. The proposed methodology is applied to the LCC optimum design problem of an actual steel box girder bridge with 3 continuous spans (40 m+50 m+40 m=130 m), and various sensitivity analyses of types of steel, local corrosion environments, average daily traffic volume, and discount rates are performed to investigate the effects of various design parameters and conditions on the LCC-effectiveness. From the numerical investigation, it has been observed that local corrosion environments and the number of truck traffics significantly influence the LCC-effective optimum design of steel bridges, and thus realized that these conditions should be considered as crucial parameters for the optimum LCC-effective design.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.74-80
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• 2023

This study examines the characteristics of architectural review opinions as unstructured data, focusing on the most challenging risk for developers of small and medium-sized apartment projects in response to the increasing number of single-person households in Korea. Using multidimensional analysis methods, the study analyzes the review opinions of 25 projects in B City. Correspondence analysis and MDS (Multidimensional Scale) analysis show that, consistent with prior research, the keywords related to 'structure' and 'planning' dominate architectural review opinions in B City. While the MDS model's stress is very poor at 34.4%, correspondence analysis reveals that this is due to the characteristics of unstructured data in architectural reviews. In addition, the non-structured data analyzed in this study, such as architectural review opinions, exhibited a probability distribution with low kurtosis and high skewness, as they involved various combinations and occurrences of data depending on the discretion of the review committee members and the specific formats of different local governments. This often led to the emergence of keywords that differed significantly from commonly mentioned terms. Although the study has some limitations, it provides a foundation for future detailed analysis by identifying the characteristics of architectural review opinions as unstructured data.

• The Journal of Engineering Geology
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• v.33 no.3
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• pp.389-401
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• 2023

Climate, weather, insolation (solar radiation), and solar energy in major cities of Tajikistan were investigated prior to construction of infrastructure for the Dushanbe Solar Station. In Dushanbe city there was a 70% probability of sunny days from May 16 to October 23, a period of 5.2 months. August had the most sunny days of in the year, with 99% probability of a sunny, the cloudiest month was February with a 41% chance of being sunny. In major cities of the Sughd and Gorno-Badakhshan states, the average number of cloudy days per month was ~3.3, with Dzhauz having 53 day and Fedchnko Glacier 79 days. For the 18 major cities of Tajikistan, the average annual total solar radiation was 2,429 W/m², and the average monthly solar radiation was 202 W/m². The city with the lowest annual total and monthly average solar radiation was Shartuz in Sughd state, with values ~2.7% less than the national average. The cities with the highest annual total and monthly average solar radiation were Khorog and Jirgatol in Gorno-Badakhshan state, with values ~10% above the national average. The daily average incident shortwave solar energy in the cities Dushanbe, Karakul, and Jirgatol was ~7.8 kWh per 2.4 m² during summer (May-August), and 2.7 kWh during winter (November-February), or ~35% that of summer.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2575-2583
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• 1998

The productionof the highly relible softwae systems and theirs performance evaluation hae become important interests in the software industry. The software evaluation has been mainly carried out in ternns of both reliability and performance of software system. Software reliability is the probability that no software error occurs for a fixed time interval during software testing phase. These theoretical software reliability models are sometimes unsuitable for the practical testing phase in which a software error at a certain testing stage occurs by causes of the imperfect debugging, abnornal software correction, and so on. Such a certatin software testing stage needs to be considered as an outlying stage. And we can assume that the software reliability does not improve by means of muisance factor in this outlying testing stage. In this paper, we discuss Bavesian software reliability growth modeling and estimation procedure in the presence of an imidentitied outlying software testing stage by the modification of Jehnski Moranda. Also we derive the Bayes estimaters of the software reliability panmeters by the assumption of prior information under the squared error los function. In addition, we evaluate the proposed software reliability growth model with an unidentified outlying stage in an exchangeable model according to the values of nuisance paramether using the accuracy, bias, trend, noise metries as the quantilative evaluation criteria through the compater simulation.

• IMMUNE NETWORK
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• v.3 no.4
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• pp.287-294
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• 2003

Background: In kidney transplantation, donor specific transfusion may induce tolerance as a result of some immune regulatory cells against the graft. In organ transplantation, the immune state arises from a relationship between the immunocompromised graft and the immunocompetent host. However, a reverse immunological situation exists between the graft and the host in hematopoietic stem cell transplantation (HSCT). In addition, early IL-2 injections after an allogeneic murine HSCT have been shown to prevent lethal graft versus host disease (GVHD) due to CD4+ cells. We investigated the induction of the regulatory CD4+CD25+ cells after a transfusion of irradiated recipient cells with IL-2 into a donor. Methods: The splenocytes (SP) were obtained from 6 week-old BALB/c mice ($H-2^d$) and irradiated as a single cell suspension. The donor mice (C3H/He, $H-2^k$) received $5{\times}10^6$ irradiated SP, and 5,000 IU IL-2 injected intraperitoneally on the day prior to HSCT. The CD4+CD25+ cell populations in SP treated C3H/He were analyzed. In order to determine the in vivo effect of CD4+CD25+ cells, the lethally irradiated BALB/c were transplanted with $1{\times}10^7$ donor BM and $5{\times}10^6$ CD4+CD25+ cells. The other recipient mice received either $1{\times}10^7$ donor BM with $5{\times}10^6$ CD4+ CD25- cells or the untreated SP. The survival and GVHD was assessed daily by a clinical scoring system. Results: In the MLR assay, BALB/c SP was used as a stimulator with C3H/He SP, as a responder, with or without treatment. The inhibition of proliferation was $30.0{\pm}13%$ compared to the control. In addition, the MLR with either the CD4+CD25+ or CD4+CD25- cells, which were isolated by MidiMacs, from the C3H/He SP treated with the recipient SP and IL-2 was evaluated. The donor SP treated with the recipient cells and IL-2 contained more CD4+CD25+ cells ($5.4{\pm}1.5%$) than the untreated mice SP ($1.4{\pm}0.3%$)(P<0.01). There was a profound inhibition in the CD4+CD25+ cells ($61.1{\pm}6.1%$), but a marked proliferation in the CD4+CD25- cells ($129.8{\pm}65.2%$). Mice in the CD4+CD25+ group showed low GVHD scores and a slow progression from the post-HSCT day 4 to day 9, but those in the control and CD4+CD25- groups had a high score and rapid progression (P<0.001). The probability of survival was 83.3% in the CD4+CD25+ group until post-HSC day 35 and all mice in the control and CD4+CD25- groups died on post-HSCT day 8 or 9 (P=0.0105). Conclusion: Donor graft engineering with irradiated recipient SP and IL-2 (recipient specific transfusion) can induce abundant regulatory CD4+CD25+ cells to prevent GVHD.