• 한국음향학회지
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• 제37권1호
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• pp.31-38
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• 2018

2015년 5월 제주 서남부 해역에서 실시된 SAVEX15(Shallow Water Acoustic Variability EXperiment 2015) 데이터를 기반으로 내부파가 소나의 예상탐지확률(Predictive Probability of Detection, PPD)에 미치는 영향에 대하여 분석하였다. 제주 서남부 해역은 내부파, 수중음파채널 등으로 인하여 복잡한 해수 유동이 존재하는 해역이다. 본 논문에서는 확률적인 접근 방법을 통하여 소나의 성능을 예측하였다. SAVEX15 데이터 중 11 kHz ~ 31 kHz 대역대의 LFM(Linear Frequency Modulation), MLS(Maximum Length Sequence) 신호를 데이터 처리 하여 음원과 수신기가 약 2.8 km 떨어진 지점에서의 전달손실(Transmission Loss, TL)과 소음준위(Noise Level, NL) 값을 산출하였다. TL과 NL의 확률밀도함수(Probability Density Function, PDF)를 합성곱하여 신호이득에 대한 확률밀도 함수를 구하고 음원과 수신기의 수심에 따른 예상탐지확률을 산출하였다. 솔리톤 패킷과 내부조석 등의 내부파가 존재할 때 시간에 따른 예상탐지확률의 변화를 분석한 결과 각각 다른 양상으로 예상탐지확률 값에 영향을 주는 것을 확인하였다.

• 한국음향학회지
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• 제43권3호
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• pp.285-292
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• 2024

소나 탐지확률을 계산하는 경우, 수중음향 불확정성은 표준편차가 8 dB ~ 9 dB인 정규분포를 따르는 것으로 고려되고 있다. 하지만, 소나 탐지성능은 실험해역, 해양환경 변동성에 따라 크게 변화하기 때문에 해상실험 데이터 기반의 수중음향 불확정성을 반영한 탐지성능 예측이 필요하다. 본 논문에서는 동해 천해환경에서 측정된 중주파수(2.3 kHz, 3 kHz) 소음준위와 전달손실 자료 기반의 수중음향 불확정성이 산출되었다. 해상실험 데이터 기반의 수중음향 불확정성을 반영한 예상탐지확률을 산출한 후, 이를 기존의 탐지확률 결과, 레일리 분포의 불확정성과 음으로 치우친 분포의 불확정성을 반영한 예상탐지확률 결과와 비교하였다. 결과적으로 각각의 수중음향 불확정성에 따라 탐지영역의 차이가 발생하는 것을 확인할 수 있었다.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.348-358
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• 2022

Software fault prediction is a method to compute fault in the software sections using software properties which helps to evaluate the quality of software in terms of cost and effort. Recently, several software fault detection techniques have been proposed to classifying faulty or non-faulty. However, for such a person, and most studies have shown the power of predictive errors in their own databases, the performance of the software is not consistent. In this paper, we propose a hybrid soft computing technique for SFP based on optimal feature extraction and classification (HST-SFP). First, we introduce the bat induced butterfly optimization (BBO) algorithm for optimal feature selection among multiple features which compute the most optimal features and remove unnecessary features. Second, we develop a layered recurrent neural network (L-RNN) based classifier for predict the software faults based on their features which enhance the detection accuracy. Finally, the proposed HST-SFP technique has the more effectiveness in some sophisticated technical terms that outperform databases of probability of detection, accuracy, probability of false alarms, precision, ROC, F measure and AUC.

• Asian Pacific Journal of Cancer Prevention
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• 제16권17호
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• pp.7607-7612
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• 2015

Aims: The purpose of our study was to evaluate the diagnostic performance of breast magnetic resonance imaging (MRI) in the evaluation of contralateral breast in patients with diagnosed breast cancer. A secondary objective was to determine accuracy of breast MRI in diagnosing multi-focal and multicentric lesions in the ipsilateral breast. Materials and Methods: Using a non-probability convenience sampling technique, patients with histopathologically diagnosed breast cancer with MRI of breast performed to exclude additional lesions were included. MRI findings were correlated with histopathology. In addition, follow-up imaging with mammography and ultrasound was also assessed for establishing stability of negative findings and for the detected of benign lesions. Results: Out of 157 MRI breast conducted during the period of 2008 to 2013, 49 were performed for patients with diagnosed breast cancer. The sample comprised of all females with mean age $50.7{\pm}11.0years$. The patient follow-up imaging was available for a period of 2-5 years. The sensitivity, specificity, and positive and negative predictive values of MRI in the detection of multifocal/multicenteric lesions was 85.7%, 88.8%, 60% and 96.6% respectively and for the detection of lesions in the contralateral breast were 100%, 97%, 83.3% and 100% respectively. Conclusions: Our study highlights the diagnostic performance and the added value of MRI in the detection of multifocal/multicenteric and contralateral malignant lesions. In patients with diagnosed breast cancer having dense breast parenchyma and with infiltrating lobular carcinoma as the index lesion MRI is particularly useful with excellent negative predictive value in the exclusion of additional malignant foci in the ipsilateral and contralateral breasts.

• 한국인공지능학회지
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• 제12권1호
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• pp.25-29
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• 2024

In this study, research was conducted to predict the probability of cervical cancer occurrence associated with the use of hormonal contraceptives. Cervical cancer is influenced by various environmental factors; however, the human papillomavirus (HPV) is detected in 99% of cases, making it the primary attributed cause. Additionally, although cervical cancer ranks 10th in overall female cancer incidence, it is nearly 100% preventable among known cancers. Early-stage cervical cancer typically presents no symptoms but can be detected early through regular screening. Therefore, routine tests, including cytology, should be conducted annually, as early detection significantly improves the chances of successful treatment. Thus, we employed artificial intelligence technology to forecast the likelihood of developing cervical cancer. We utilized the logistic regression algorithm, a predictive model, through Microsoft Azure. The classification model yielded an accuracy of 80.8%, a precision of 80.2%, a recall rate of 99.0%, and an F1 score of 88.6%. These results indicate that the use of hormonal contraceptives is associated with an increased risk of cervical cancer. Further development of the artificial intelligence program, as studied here, holds promise for reducing mortality rates attributable to cervical cancer.

• 지능정보연구
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• 제17권4호
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• pp.157-173
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• 2011

최근 인터넷 사용의 증가에 따라 네트워크에 연결된 시스템에 대한 악의적인 해킹과 침입이 빈번하게 발생하고 있으며, 각종 시스템을 운영하는 정부기관, 관공서, 기업 등에서는 이러한 해킹 및 침입에 의해 치명적인 타격을 입을 수 있는 상황에 놓여 있다. 이에 따라 인가되지 않았거나 비정상적인 활동들을 탐지, 식별하여 적절하게 대응하는 침입탐지 시스템에 대한 관심과 수요가 높아지고 있으며, 침입탐지 시스템의 예측성능을 개선하려는 연구 또한 활발하게 이루어지고 있다. 본 연구 역시 침입탐지 시스템의 예측성능을 개선하기 위한 새로운 지능형 침입탐지모형을 제안한다. 본 연구의 제안모형은 비교적 높은 예측력을 나타내면서 동시에 일반화 능력이 우수한 것으로 알려진 Support Vector Machine(SVM)을 기반으로, 비대칭 오류비용을 고려한 분류기준값 최적화를 함께 반영하여 침입을 효과적으로 차단할 수 있도록 설계되었다. 제안모형의 우수성을 확인하기 위해, 기존 기법인 로지스틱 회귀분석, 의사결정나무, 인공신경망과의 결과를 비교하였으며 그 결과 제안하는 SVM 모형이 다른 기법에 비해 상대적으로 우수한 성과를 보임을 확인할 수 있었다.

• 한국임상수의학회지
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• 제26권2호
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• pp.130-133
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• 2009

검사키트의 신속성과 간편성이 보편화되면서 진단목적으로 키트를 사용하는 빈도가 증가하고 있다. 그러나 대부분의 검사키트는 민감도와 특이도가 100% 완벽하지 못하기 때문에 진단검사의 특성과 이러한 특성에 영향을 미치는 요인을 이해하지 못할 경우 검사결과를 해석하는데 오류를 범하게 된다. 임상의는 검사결과 양성 혹은 음성일 때 환자가 실제로 질병에 감염되어 있을 확률이 어느 정도인지에 관심을 두기 때문에 본 연구에서는 예측도를 이용하여 유병율에 따른 결과 해석방법을 개 심장사상충 진단키트를 예로 들어 설명하였다. 문헌고찰 결과 심장사상충 진단용 키트검사의 평균 민감도와 특이도는 DiroChek 78.1-95.2%, SNAP 66.3-98.1%, Solo Step 69.5-97.5%를 보였다. 혈액학적 검사법(Modified Knott's, direct smear, capillary tube)의 민감도와 특이도는 각각 38.4-81.8%, 96.9-100%의 범위를 보여 검사법에 따라 상당한 차이를 보였다. 또한 국내 개 심장상충의 자충과 항원 유병율은 지역별로 차이가 있으며 키트검사의 예측도는 유병율에 매우 민감하다는 점을 고려하면 개 심장사상충에 대한 검사결과에 근거하여 감염확률을 추정할 때 유병율이 상이한 임상환경에서는 양성 혹은 음성결과에 대하여 신중하게 해석할 필요가 있다.

• 지능정보연구
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• 제27권3호
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• pp.57-73
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• 2021

ICT 인프라의 이상탐지를 통한 유지보수와 장애 예방이 중요해지고 있다. 장애 예방을 위해서 이상탐지에 대한 관심이 높아지고 있으며, 지금까지의 다양한 이상탐지 기법 중 최근 연구들에서는 딥러닝을 활용하고 있으며 오토인코더를 활용한 모델을 제안하고 있다. 이는 오토인코더가 다차원 다변량에 대해서도 효과적으로 처리가 가능하다는 것이다. 한편 학습 시에는 많은 컴퓨터 자원이 소모되지만 추론과정에서는 연산을 빠르게 수행할 수 있어 실시간 스트리밍 서비스가 가능하다. 본 연구에서는 기존 연구들과 달리 오토인코더에 2가지 요소를 가미하여 이상탐지의 성능을 높이고자 하였다. 먼저 다차원 데이터가 가지고 있는 속성별 특징을 최대한 부각하여 활용하기 위해 멀티모달 개념을 적용한 멀티모달 오토인코더를 적용하였다. CPU, Memory, network 등 서로 연관이 있는 지표들을 묶어 5개의 모달로 구성하여 학습 성능을 높이고자 하였다. 또한, 시계열 데이터의 특징을 데이터의 차원을 늘리지 않고 효과적으로 학습하기 위하여 조건부 오토인코더(conditional autoencoder) 구조를 활용하는 조건부 멀티모달 오토인코더(Conditional Multimodal Autoencoder, CMAE)를 제안하였다. 제안한 CAME 모델은 비교 실험을 통해 검증했으며, 기존 연구들에서 많이 활용된 오토인코더와 비교하여 AUC, Accuracy, Precision, Recall, F1-score의 성능 평가를 진행한 결과 유니모달 오토인코더(UAE)와 멀티모달 오토인코더(Multimodal Autoencoder, MAE)의 성능을 상회하는 결과를 얻어 이상탐지에 있어 효과적이라는 것을 확인하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제15권22호
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• pp.10039-10043
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• 2014

Background: In Pakistan thyroid cancer is responsible for 1.2% cases of all malignant tumors. Ultrasonography (US) is helpful in detecting cancerous thyroid nodules on basis of different features like echogenicity, margins, microcalcifications, size, shape and abnormal neck lymph nodes. We therefore aimed to calculate diagnostic accuracy of ultrasound in detection of carcinoma in thyroid nodules taking fine needle aspiration cytology as the reference standard. Materials and Methods: A cross-sectional analytical study was designed to prospectively collect data from December 2010 till December 2012 from the Department of Radiology in Aga Khan University Hospital, Karachi, Pakistan. A total of 100 patients of both genders were enrolled after informed consent via applying non-probability consecutive sampling technique. Patients referred to Radiology department of Aga Khan University to perform thyroid ultrasound followed by fine-needle aspiration cytology of thyroid nodules were included. They were excluded if proven for thyroid malignancy or if their US or FNAC was conducted outside our institution. Results: The subjects comprised 76 (76%) females and 24 males. Mean age was $41.8{\pm}SD$ 12.3 years. Sensitivity and specificity with 95%CI of ultrasound in differentiating malignant thyroid nodule from benign thyroid nodule calculated to be 91.7% (95%CI, 0.72-0.98) and 78.94% (0.68-0.87) respectively. Reported positive predictive value and negative PV were 57.9% (0.41-0.73) and 96.8% (0.88-0.99) and overall accuracy was 82%. Likelihood ratio (LR) positive was computed to be 4.3 and LR negative was 0.1. Conclusions: Ultrasonography has a high diagnostic accuracy in detecting malignancy in thyroid nodules on the basis of features like echogenicity, margins, micro calcifications and shape.

• Journal of Trauma and Injury
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• 제20권2호
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• pp.57-64
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• 2007

Purpose: Clinically, acute respiratory distress syndrome (ARDS) occurs within 72 hours after acute exposure of risk factors. Because of its high fatality rate once ARDS progresses, early detection and management are essential to reduce the mortality rate. Accordingly, studies on early changes of ARDS were started, and serum ferritin, as well the as injury severity score (ISS), which has been addressed in previous studies, thought to be an early predictive indicator for ARDSMethods: From March 2003 to March 2005, we investigated 50 trauma patients who were admitted to the intensive care unit in Dongguk University Medical Center, Gyeongju. The patients were characterized according to age, sex, ISS, onset of ARDS, time onset of ARDS, serum ferritin level (posttraumatic $1^{st}\;&\;2^{nd}$ day), amount of transfused blood, and death. Abdominal computed topography was performed as an early diagnostic tool to evaluate the onset of ARDS according to its diagnostic criteria. The serum ferritin was measured by using a $VIDAS^{(R)}$ Ferritin (bioMeriux, Marcy-1' Etoile, France) kit with an enzyme-linked fluorescent assay method. For statistical analysis, Windows SPSS 13.0 and MedCalc were used to confirm the probability of obtaining a predictive measure from the receiver operating characteristics (ROC) curve. Results: The ISS varied from 14 to 66 (mean: 33.8) whereas the onset of ARDS could be predicted with the score above 30 (sensitivity: 90.0%, specificity: 60.0%, p<0.05). On the posttraumatic $1^{st}$ day, the serum ferritin levels were measured to be from 31 mg/dL to 1,200 mg/dL (mean: 456 mg/dL), and the onset of ARDS could be predicted when the value was over 340 mg/dL (sensitivity: 80.0%, specificity: 65.0%, p<0.05). On the posttraumatic $2^{nd}$ day, the serum ferritin levels were measured to be from 73 mg/dL to 1,200 mg/dL (mean: 404 mg/dL), and the onset of ARDS could be predicted when the value was over 627 mg/dL (sensitivity: 60.0%, specificity: 92.5%, p<0.05). The serum ferritin levels and the ISS were significantly higher on the posttraumatic $1^{st}$ and $2^{nd}$ day in the ARDS group, suggesting that they are suitable indices predicting the onset of ARDS, however relationship between the serum ferritin levels and the ISS was not statistically significant. Conclusion: In this study, we discovered increasing serum ferritin levels in multiple- trauma patients on the posttraumatic $1^{st}$ & $2^{nd}$ day and concluded that both the serum ferritin level and the ISS were good predictors of ARDS. Although they do not show statistically significant relationship to each other, they can be used as independent predictive measures for ARDS. Since ARDS causes high mortality, further studies, including the types of surgery and the methods of anesthesia on a large number of patients are essential to predict the chance of ARDS earlier and to reduce the incidence of death.