• Communications for Statistical Applications and Methods
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• 제28권2호
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• pp.161-169
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• 2021

The two-dimensional confusion matrix used in credit assessment, biostatistics, and many other fields consists of true positive, true negative, false positive, and false negative. Their rates, such as the true positive rate (TPR), true negative rate (TNR), false positive rate, and false negative rate, can be applied to measure its accuracy. In this study, we propose the TPR-TNR plot, a graphical method that can geometrically describe and explain these rates based on the confusion matrix. The proposed TPR-TNR plot consists of two right-angled triangles. We obtain that the TPR and TNR describe the acute angles of right-angled triangles in the plot. These acute angles can be used to determine optimal thresholds corresponding to lots of accuracy measures.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.215-217
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• 2008

동영상 내용검색을 위해서 가장 많이 사용되고 있는 기술은 컷 추출에 의한 내용비교 방법이다. 그러나 컷 추출을 위해 사용되는 CHD(Color Histogram Difference)나 ECR(Edge Change Ratio)등은 영상물의 Cropping, Resizing Low bit rate등의 변화에 대해 대단히 취약하다. 본 방법은 이러한 변형에 강인하도록 상대적으로 변형이 적은 오디오정보를 이용하여 Indexing과 Searching을 수행하였다. 특히 변형에 강인한 Searching을 위해 오디오의 장면(Scene)을 검출하였고 장면을 중심으로 Time-frequency domain에서 각각의 Frequency bin. 에 대한 스펙트럴 파워를 파워임계값을 중심으로 이진화(Binary)하였다. 제안된 방법으로 Cropping, clipping, Lowbit rate, Additive Frame 등의 변형본에 대한 검색을 시도한 결과 False posit ive Error 와 True Negative Error 에 대해 각각 1%미만의 오탐지 결과를 얻었다.

• Journal of information and communication convergence engineering
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• 제7권1호
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• pp.7-12
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• 2009

The advanced computer network and Internet technology enables connectivity of computers through an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, making it vulnerable to previously unidentified attack patterns and variations in attack and increasing false negatives. Intrusion detection and prevention technologies are thus required. We proposed a network based hybrid Probe Intrusion Detection model using Fuzzy cognitive maps (PIDuF) that detects intrusion by DoS (DDoS and PDoS) attack detection using packet analysis. A DoS attack typically appears as a probe and SYN flooding attack. SYN flooding using FCM model captures and analyzes packet information to detect SYN flooding attacks. Using the result of decision module analysis, which used FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance evaluation, the "IDS Evaluation Data Set" created by MIT was used. From the simulation we obtained the max-average true positive rate of 97.064% and the max-average false negative rate of 2.936%. The true positive error rate of the PIDuF is similar to that of Bernhard's true positive error rate.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.255-260
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• 2015

Among many optimal threshold criteria from ROC curve, the closest-to-(0,1) and amended closest-to-(0,1) criteria are considered. An ROC curve that passes close to the (0,1) point indicates that two models are well classified. In this case, the ROC curve is located far from the (1,0) point. Hence we propose two criteria: the farthest-to-(1,0) and amended farthest-to-(1,0) criteria. These criteria are found to have a relationship with the KolmogorovSmirnov statistic as well as some optimal threshold criteria. Moreover, we derive that a definition for the proposed criteria with more than two dimensions and with relations to multi-dimensional optimal threshold criteria.

• 대한건축학회논문집:구조계
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• 제36권3호
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• pp.113-120
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• 2020

The purpose of this study is to compare the models of Deep Learning-based Convolution Neural Network(CNN) for concrete crack detection. The comparison models are AlexNet, GoogLeNet, VGG16, VGG19, ResNet-18, ResNet-50, ResNet-101, and SqueezeNet which won ImageNet Large Scale Visual Recognition Challenge(ILSVRC). To train, validate and test these models, we constructed 3000 training data and 12000 validation data with 256×256 pixel resolution consisting of cracked and non-cracked images, and constructed 5 test data with 4160×3120 pixel resolution consisting of concrete images with crack. In order to increase the efficiency of the training, transfer learning was performed by taking the weight from the pre-trained network supported by MATLAB. From the trained network, the validation data is classified into crack image and non-crack image, yielding True Positive (TP), True Negative (TN), False Positive (FP), False Negative (FN), and 6 performance indicators, False Negative Rate (FNR), False Positive Rate (FPR), Error Rate, Recall, Precision, Accuracy were calculated. The test image was scanned twice with a sliding window of 256×256 pixel resolution to classify the cracks, resulting in a crack map. From the comparison of the performance indicators and the crack map, it was concluded that VGG16 and VGG19 were the most suitable for detecting concrete cracks.

• Journal of Acupuncture Research
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• 제24권6호
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• pp.187-193
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• 2007

Objectives : The objectives of this study were to investigate the relationship between electrical detection of ear acupuncture points and musculoskeletal pain. Methods : 18 adults who have musculoskeletal pain without trauma factorsparticipated in this study. They answered the questionnaire and their ear acupuncture points were examined with electrical detectors. We analyzed the relationship between electrical detection of ear acupuncture points and musculoskeletal pain with concordance rate and validity. Results : Total concordance rates of the head region was 68.00%(questionnaire) 32.08%(investigation), that of vertebral region was 67.86%, 59.38%, that of both upper limbs was 86.67%, 39.69%, and that of both lower limbs was 50.00%, 23.46%. The true positive rate was 0.704, the true negative rate was 0.492, the false positive rate was 0.508, and the false negative rate was 0.296 in the validity test. In the head, two concordance rates of the temporal and occipital regions were relatively higher than those of the parietal and frontal regions. In the vertebral region, two concordance rates of the cervical and lumbar regions were relatively higher than those of the thoracic and sacrum regions. In the upper limb, two concordance rates of the shoulder and shoulder joints were relatively higher than those of the others. In the lower limb, concordance rates of investigation were relatively low at all areas. The right lower limb was relatively higher than the left in concordance rates of the questionnaire. Conclusions : The results suggest that electrical detection of ear acupuncture points can be used in the diagnosis and treatment of musculoskeletal pain.

• 한국산학기술학회논문지
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• 제10권4호
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• pp.811-817
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• 2009

IT 시스템 기반의 네트워크 환경의 급속한 발전은 지속적인 연구방향의 중요한 이슈의 결과이다. 침입시도 탐지는 관심분야의 하나인 것이다. 최근에 다양한 기술을 기반으로 하는 침입시도탐지들이 제안되고 있으나 이러한 기술은 여러 형태의 침입시도의 패턴 중에 한가지 형태 및 시스템에 적용이 가능한 것이다. 또한 새로운 형태 침입시도를 탐지하지 못하고 있다. 그러므로 새로운 형태를 인식하는 침입탐지 관련 기술이 요구되어 지고 있다. 본 연구에서는 퍼지인식도와 비정상 트래픽 분석을 이용한 네트워크 기반의 침입탐지기법(NePID)을 제안한다. 이 제안은 패킷 분석을 통하여 서비스거부공격과 유사한 침입시도를 탐지하는 것이다. 서비스거부공격은 침입시도의 형태를 나타내며 대표적인 공격으로는 syn flooding 공격이 있다 제안한 기법은 syn flooding을 탐지하기 위하여 패킷정보를 수집 및 분석한다. 또한 피지인식도와 비정상 트래픽 분석을 적용하여 판단모듈의 분석 결과를 토대로 기존의 서비스 거부 공격의 탐지 툴과의 비교분석을 하였으며 실험데이터로는 MIT Lincoln 연구실의 IDS 평가데이터 (KDD'99)를 이용하였다. 시뮬레이션 결과 최대평균 positive rate는 97.094% 탐지율과 negative rate는 2.936%을 얻었으며 이 결과치는 KDD'99의 우승자인 Bernard의 결과치와 유사한 수준의 값을 나타내었다.

• Journal of Information Processing Systems
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• 제10권2호
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• pp.314-333
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• 2014

When analyzing default predictions in real estate companies, the number of non-defaulted cases always greatly exceeds the defaulted ones, which creates the two-class imbalance problem. This lowers the ability of prediction models to distinguish the default sample. In order to avoid this sample selection bias and to improve the prediction model, this paper applies a minority sample generation approach to create new minority samples. The logistic regression, support vector machine (SVM) classification, and neural network (NN) classification use an imbalanced dataset. They were used as benchmarks with a single prediction model that used a balanced dataset corrected by the minority samples generation approach. Instead of using prediction-oriented tests and the overall accuracy, the true positive rate (TPR), the true negative rate (TNR), G-mean, and F-score are used to measure the performance of default prediction models for imbalanced dataset. In this paper, we describe an empirical experiment that used a sampling of 14 default and 315 non-default listed real estate companies in China and report that most results using single prediction models with a balanced dataset generated better results than an imbalanced dataset.

• The Journal of Asian Finance, Economics and Business
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• 제9권2호
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• pp.1-14
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• 2022

The implications of bank-specific risks and macroeconomic risks on the growth, profitability, and stability of Islamic and conventional banks are examined and compared in this article. The study also investigates whether corporate governance mitigates the effects of both bank-specific and macroeconomic risks on Islamic and conventional banks' development, profitability, and stability. For the period 2007-2019, we examined a panel data set of 22 banks in Pakistan, including both Islamic and conventional banks. We discovered considerable evidence that both bank-specific risks and macroeconomic risks have negative effects on the growth, profitability, and stability of Pakistani banks using a dynamic panel data estimator, the two-step Generalized Method of Moments (GMM) approach. Furthermore, the findings show that bank-specific and macroeconomic risks have different consequences in both types of banking. The impacts of liquidity risk, operational risk, capital risk, inflation risk, and exchange rate risk are higher for Islamic banks than for conventional banks. Conventional banks, on the other hand, are more vulnerable to credit risk and interest rate risk. Finally, the findings show that good corporate governance reduces the negative consequences of both categories of risks on bank development, profitability, and stability. This is true for Islamic and conventional banks alike.

• 한국콘텐츠학회논문지
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• 제17권11호
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• pp.50-59
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• 2017

최근 임상에서 활용하고 있는 일체형 PET-MRI의 간암 진단능력을 평가하기 위해 $2{\times}2$ 판정행렬을 이용하여 유용성을 평가하였다. 실험대상의 PET-MRI 검사 결과를 통해 간암 판정 여부 즉 비정상과 정상 판정을 받은 경우는 각각 98건, 51건 이었으며, 세포병리학적 결과가 양성과 음성 판정을 받은 경우는 각각 103건, 62건으로 나타났다. 이 중 두가지 검사에서 진양성의 경우는 95건, 위양성은 3건으로 나타났으며, 진음성은 62건, 위음성의 경우는 5건으로 분석되었다. 실험결과 PET-MRI 검사의 예민도는 95.00%, 특이도는 95.38%, 위음성률은 0.05%, 위양성률은 0.05%, 정확도는 95.15%로 분석되었다. 따라서 간암의 진단에 있어 수술 전 병기 결정이나 치료 후 재발 및 원격전이의 발견, 불분명한 원발 림프절 전이 등의 평가 등에 활용 가능성이 높을 것으로 판단되며, 특히 병리학적 검사와의 복합적 진단 및 추적검사를 통해 간암 진단을 위한 PET-MRI 임상적 유용성은 충분할 것으로 사료된다.