• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.1-10
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• 2024

In the era of big data, the growth of e-commerce transactions brings forth both opportunities and risks, including the threat of data theft and fraud. To address these challenges, an automated real-time fraud detection system leveraging machine learning was developed. Four algorithms (Decision Tree, Naïve Bayes, XGBoost, and Neural Network) underwent comparison using a dataset from a clothing website that encompassed both legitimate and fraudulent transactions. The dataset exhibited an imbalance, with 9.3% representing fraud and 90.07% legitimate transactions. Performance evaluation metrics, including Recall, Precision, F1 Score, and AUC ROC, were employed to assess the effectiveness of each algorithm. XGBoost emerged as the top-performing model, achieving an impressive accuracy score of 95.85%. The proposed system proves to be a robust defense mechanism against fraudulent activities in e-commerce, thereby enhancing security and instilling trust in online transactions.

• Annual Conference of KIPS
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• 2024.05a
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• pp.621-622
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• 2024

본 논문은 Exemplar Transformer를 활용하여 단일 프로세서 환경에서 동작하는 시각적 객체 추적(Visual Object Tracking) 모델인 ETTrack(Exemplar Transformer Track)을 리눅스(우분투 20.04) 운영체제를 사용하는 임베디드 시스템 라떼판다 알파(LattePanda Alpha)에 탑재하였다. 데스크톱 프로세서인 Intel i7-8700와 라떼판다 알파의 Intel m3-8100y에서의 객체 추적 성능과 속도를 AUC(Area Under the ROC Curve)와 FPS를 통해서 비교평가하였다. 평가 결과 기존 트랜스포머 기반 추적 모델(TransT)과 유사한 성능, 3 FPS 빠른 추적 속도를 나타내는 것을 구현 증명하였다.

• Journal of the Korean Society of Radiology
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• v.85 no.1
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• pp.184-196
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• 2024

Purpose We investigated potentially promising imaging findings and their combinations in the evaluation of cognitive decline. Materials and Methods This retrospective study included 138 patients with subjective cognitive impairments, who underwent brain MRI. We classified the same group of patients into Alzheimer's disease (AD) and non-AD groups, based on the neuropsychiatric evaluation. We analyzed imaging findings, including white matter hyperintensity (WMH) and cerebral microbleeds (CMBs), using the Kruskal-Wallis test for group comparison, and receiver operating characteristic (ROC) curve analysis for assessing the diagnostic performance of imaging findings. Results CMBs in the lobar or deep locations demonstrated higher prevalence in the patients with AD compared to those in the non-AD group. The presence of lobar CMBs combined with periventricular WMH (area under the ROC curve [AUC] = 0.702 [95% confidence interval: 0.599-0.806], p < 0.001) showed the highest performance in differentiation of AD from non-AD group. Conclusion Combinations of imaging findings can serve as useful additive diagnostic tools in the assessment of cognitive decline.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.253-262
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• 2021

Objective: To determine whether the values of hepatic apparent diffusion coefficient (ADC) can differentiate biliary atresia (BA) from non-BA or be correlated with the grade of hepatic fibrosis in infants with cholestasis. Materials and Methods: This retrospective cohort study included infants who received liver MRI examinations to evaluate cholestasis from July 2009 to October 2017. Liver ADC, ADC ratio of liver/spleen, aspartate aminotransferase to platelet ratio index (APRI), and spleen size were compared between the BA and non-BA groups. The diagnostic performances of all parameters for significant fibrosis (F3-4) were obtained by receiver-operating characteristics (ROCs) curve analysis. Results: Altogether, 227 infants (98 males and 129 females, mean age = 57.2 ± 36.3 days) including 125 BA patients were analyzed. The absolute ADC difference between two reviewers was 0.10 mm²/s for both liver and spleen. Liver ADC value was specific (80.4%) and ADC ratio was sensitive (88.0%) for the diagnosis of BA with comparable performance. There were 33 patients with F0, 15 with F1, 71 with F2, 35 with F3, and 11 with F4. All four parameters of APRI (τ = 0.296), spleen size (τ = 0.312), liver ADC (τ = -0.206), and ADC ratio (τ = -0.288) showed significant correlation with fibrosis grade (all, p < 0.001). The cutoff values for significant fibrosis (F3-4) were 0.783 for APRI (area under the ROC curve [AUC], 0.721), 5.9 cm for spleen size (AUC, 0.719), 1.044 x 10^-3 mm²/s for liver ADC (AUC, 0.673), and 1.22 for ADC ratio (AUC, 0.651). Conclusion: Liver ADC values and ADC ratio of liver/spleen showed limited additional diagnostic performance for differentiating BA from non-BA and predicting significant hepatic fibrosis in infants with cholestasis.

• Economic and Environmental Geology
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• v.46 no.4
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• pp.301-312
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• 2013

Landslides are caused by complex interaction among a large number of interrelated factors such as topography, geology, forest and soils. In this study, a comparative study was carried out using fuzzy relationship method and artificial neural network to evaluate landslide susceptibility. For landslide susceptibility mapping, maps of the landslide occurrence locations, slope angle, aspect, curvature, lithology, soil drainage, soil depth, soil texture, forest type, forest age, forest diameter and forest density were constructed from the spatial data sets. In fuzzy relation analysis, the membership values for each category of thematic layers have been determined using the cosine amplitude method. Then the integration of different thematic layers to produce landslide susceptibility map was performed by Cartesian product operation. In artificial neural network analysis, the relative weight values for causative factors were determined by back propagation algorithm. Landslide susceptibility maps prepared by two approaches were validated by ROC(Receiver Operating Characteristic) curve and AUC(Area Under the Curve). Based on the validation results, both approaches show excellent performance to predict the landslide susceptibility but the performance of the artificial neural network was superior in this study area.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.617-629
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• 2020

In order to overcome the limitations of the rule-based intrusion detection system due to changes in Internet computing environments, the emergence of new services, and creativity of attackers, network anomaly detection (NAD) using machine learning and deep learning technologies has received much attention. Most of these existing machine learning and deep learning technologies for NAD use supervised learning methods to learn a set of training data set labeled 'normal' and 'attack'. This paper presents the feasibility of the unsupervised learning AutoEncoder(AE) to NAD from data sets collecting of secured network traffic without labeled responses. To verify the performance of the proposed AE mode, we present the experimental results in terms of accuracy, precision, recall, f1-score, and ROC AUC value on the NSL-KDD training and test data sets. In particular, we model a reference AE through the deep analysis of diverse AEs varying hyper-parameters such as the number of layers as well as considering the regularization and denoising effects. The reference model shows the f1-scores 90.4% and 89% of binary classification on the KDDTest+ and KDDTest-21 test data sets based on the threshold of the 82-th percentile of the AE reconstruction error of the training data set.

• Journal of Microbiology and Biotechnology
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• v.24 no.8
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• pp.1044-1050
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• 2014

Since there is no consensus about the most reliable assays to detect invasive aspergillosis from samples obtained by minimally invasive or noninvasive methods, we compared the efficacy of an enzyme-linked immunosorbent assay (ELISA) for galactomannan (GM) detection and quantitative real-time PCR assay (qRT-PCR) for the diagnosis of invasive pulmonary aspergillosis. Neutropenic, male Sprague-Dawley rats (specific pathogen free; 8 weeks old; weight, $200{\pm}20g$) were immunosuppressed with cyclophosphamide and infected with Aspergillus fumigatus intratracheally. Tissue and whole blood samples were harvested on days 1, 3, 5, and 7 post-infection and examined with GM ELISA and qRT-PCR. The A. fumigatus DNA detection sequence was detected in the following number of samples from 12 immunosuppressed, infected rats examined on the scheduled days: day 1 (0/12), day 3 (0/12), day 5 (6/12), and day 7 (8/12) post-infection. The sensitivity and specificity of the qRT-PCR assay was 29.2% and 100%, respectively. Receiver operating characteristic curve (ROC) analysis indicated a Ct (cycle threshold) cut-off value of 15.35, and the area under the curve (AUC) was 0.627. The GM assay detected antigen in sera obtained on day 1 (5/12), day 3 (9/12), day 5 (12/12), and day 7 (12/12) post-infection, and thus had a sensitivity of 79.2% and a specificity of 100%. The ROC of the GM assay indicated that the optimal Ct cut-off value was 1.40 (AUC, 0.919). The GM assay was more sensitive than the qRT-PCR assay in diagnosing invasive pulmonary aspergillosis in rats.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.1-11
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• 2019

With the development of remote sensing sensor technology, it has become possible to acquire satellite images with various spectral information. In particular, since the hyperspectral image is composed of continuous and narrow spectral wavelength, it can be effectively used in various fields such as land cover classification, target detection, and environment monitoring. Change detection techniques using remote sensing data are generally performed through differences of data with same dimensions. Therefore, it has a disadvantage that it is difficult to apply to heterogeneous sensors having different dimensions. In this study, we have developed a change detection method applicable to hyperspectral image and high spat ial resolution satellite image with different dimensions, and confirmed the applicability of the change detection method between heterogeneous images. For the application of the change detection method, the dimension of hyperspectral image was reduced by using correlation analysis and principal component analysis, and the change detection algorithm used CVA. The ROC curve and the AUC were calculated using the reference data for the evaluation of change detection performance. Experimental results show that the change detection performance is higher when using the image generated by adequate dimensionality reduction than the case using the original hyperspectral image.

• Journal of the Korean Society of Radiology
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• v.11 no.4
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• pp.205-212
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• 2017

Chronic diffuse hepatopathy is one of the important clinical tasks to reduce mortality and morbidity due to liver cirrhosis, liver failure, and liver cancer. The purpose of this study was to evaluate the criteria for predicting liver and chronic liver disease using Fibroscan based on ultrasound diagnosis. Serum and liver stiffness measurement(kPa) were analyzed in 280 patients and cut-off values of liver stiffness measurement for predicting fatty liver and chronic diffuse hepatopathy were determined using ROC curve analysis. Bilirubin and PT(prothrombin time) were not related to disease prediction(p=0.243, p=0.115). Serum glucose and triglyceride levels were significantly higher in the liver (p<0.05). The cut-off value for predicting chronic diffuse hepatopathy was determined as 10.3 kPa(AUC 0.98, sensitivity 94.94%, specificity 94.93%) in the order of control group, fatty liver and chronic diffuse hepatopathy. Therefore, it will be used as a primary tool for the diagnosis of chronic liver disease patients with quantitative evaluation.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.18 no.3
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• pp.187-192
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• 2015

Purpose: Measurement of serum ceruloplasmin level is the first step in screening for Wilson's disease (WD). Despite the rarity of WD in the general population, ceruloplasmin levels are routinely measured through hepatitis screening in both adults and children. Herein, we evaluated the diagnostic value of ceruloplasmin for the diagnosis of WD among children with hepatitis. Methods: We retrospectively reviewed data on serum ceruloplasmin levels measured as a serologic marker for patients with hepatitis at Asan Medical Center (Seoul, Korea) between from January 2004 to November 2013. The diagnosis of WD was confirmed by the identification of pathogenic variants in the ATP7B gene. To determine the diagnostic accuracy of ceruloplasmin, receiver operation characteristic (ROC) curves were constructed and the area under curve (AUC) were calculated. Results: Measurements of serum ceruloplasmin were performed in 2,834 children who had hepatitis. Among these, 181 (6.4%) children were diagnosed with WD. The sensitivity, specificity, and accuracy of a ceruloplasmin level of <20 mg/dL in the discrimination of WD were 93.4%, 84.2%, and 84.8%, respectively. In this study, 418 (14.7%) false-positive cases and 12 (0.4%) false-negative cases were noted. Using a ROC curve, a ceruloplasmin level of ${\leq}16.6mg/dL$ showed the highest AUC value (0.956) with a sensitivity of 91.2%, a specificity of 94.9%, and an accuracy of 94.7%. Conclusion: The measurement of serum ceruloplasmin was frequently used for the screening of WD in children, despite a low positive rate. The diagnostic value of ceruloplasmin may be strengthened by adopting a new lower cut-off level.