• 대한두경부종양학회지
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• 제15권2호
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• pp.189-193
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• 1999

Objectives: Fine needle aspiration cytology(FNAC) is a well established preoperative diagnostic procedure in the thyroid nodules. However, diagnostic accuracy of FNAC varies according to the size and the structural characteristics of thyroid nodule. We performed the ultrasound guided FNAC(US-guided FNAC) for impalpable thyroid nodule, and estimated the sampling accuracy rate through a comparison study between the cytologic diagnosis and the final histologic diagnosis of the postoperative specimens in order to determine clinical efficacy of the US-guided FNAC. Materials and Methods: We evaluated 117 patients underwent US-guided FNAC from January 1997 to December 1998. These patients had 129 thyroid nodules to need cytologic examination. Whereas the nodules were so no graphically classified into cystic, solid, and mixed type according to echo pattern, the aspirated thyroid specimens were classified into benign, malignant, suspicious, and insufficient. Results: Positive sampling for diagnositc examination was achieved in 75 nodules(58.1%), and US-guided FNAC in our study showed the accuracy rate of 95.2%, false positivity rate of 0%, and false negativity rate of 5.5%. Conclusions: US-guided FNAC is a powerful techniques for evaluating cytologic characterics and allowing a reliable diagnositc result in the impalpable thyroid nodule. However, the experienced technique is recommanded in order to obtain the sufficient samples for reliable results.

• Communications for Statistical Applications and Methods
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• 제13권3호
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• pp.787-794
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• 2006

In group testing, the test unit consists of a group of individuals and each group is tested to classify units from a population as infected or non-infected or estimate the infection rate. If the test group is infected, one or more individuals in the group are presumed to be infected. It is assumed in group testing that classification of group as positive or negative is without error. But, the possibility of false negatives as a result of dilution effects happens often in practice, specially in many clinical researches. In this paper, dilution effect models in group testing are discussed and estimation methods of infection rate are proposed when a dilution effect exists.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3797-3822
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• 2020

The inspection of cracks on the surface of tunnel linings is a common method of evaluate the condition of the tunnel. In particular, determining the thickness and shape of a crack is important because it indicates the external forces applied to the tunnel and the current condition of the concrete structure. Recently, several automatic crack detection methods have been proposed to identify cracks using captured tunnel lining images. These methods apply an image-segmentation mechanism with well-annotated datasets. However, generating the ground truths requires many resources, and the small proportion of cracks in the images cause a class-imbalance problem. A weakly annotated dataset is generated to reduce resource consumption and avoid the class-imbalance problem. However, the use of the dataset results in a large number of false positives and requires post-processing for accurate crack detection. To overcome these issues, we propose a crack detection method using a ternary classifier. The proposed method significantly reduces the false positive rate, and the performance (as measured by the F1 score) is improved by 0.33 compared to previous methods. These results demonstrate the effectiveness of the proposed method.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권11호
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• pp.912-919
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• 2009

본 논문에서는 이차원 텐서보팅과 에지 기반 방법을 이용하여 자연영상에서 문자를 검출하는 새로운 방법을 제시한다. 텍스트의 문자들은 보통 연속적인 완만한 곡선 상에 배열되어 있고 서로 가깝게 위치하며, 이러한 특성은 텐서보팅에 의하여 효과적으로 검출될 수 있다. 이차원 텐서보팅은 토큰의 연속성을 curve saliency 로 산출하며 이러한 특성은 다양한 영상해석에 사용된다. 먼저 에지 검출을 이용하여 영상 내의 텍스트 영역이 위치할 가능성이 있는 텍스트 후보영역을 찾고 이러한 후보영역의 연속성을 텐서보팅에 의해 검증하여 잡음영역을 제거하고 텍스트 영역만을 구분한다. 실험 결과, 제안된 방법은 복잡한 자연영상에서 효과적으로 텍스트 영역을 검출함을 확인하였다.

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 2006년도 하계학술대회
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• pp.365-369
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• 2006

Multiple Message Authentication Codes can be represented by one of the Short MAC, Bloom Filter or Compressed Bloom Filler to reduce communication overheads. However, this will inevitably increase false positive rate (fpr) which is a false authentication probability of adversarial messages in trade-off of communication efficiency. While the simple short MAC scheme has the lowest fpr, one cannot choose arbitrary authenticator size. Bloom filter, randomized data structure often used for membership queries, can represent multiple MACs more flexibly with slightly higher fpr. Furthermore, compressed Bloom filter has the same fpr with the short MAC while maintaining its flexibility. Through our detailed analysis, we show that pros and cons of the three schemes are scenario specific. Therefore one can choose appropriate scheme under given parameters to achieve both communication efficiency and security based on our results.

• Journal of Chest Surgery
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• 제26권3호
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• pp.209-213
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• 1993

The pathogenesis of the primary spontaneous pneumothorax is the rupture of subpleural bleb or bullae and subsequent sudden collapse of the affected lung. Mostly, the bullae or blebs are present bilaterally, but detecting the number, size, and location of the causating foci by plain chest film is quite difficult . We have performed chest CT scans for detecting the bullous lesions in 33 cases of primary spontaneous pneumothorax, and compared the results with surgical findings.1. Seventy-four blebs were identified in the chest CT scan, and 100 blebs or bullae were detected surgically [ Sensitivity was 0.74 ].2. Diagnosis rate was 80% [40/50] at right upper lobe, 75.7% [28/37] at left upper lobe, 55.6% at right lower lobe, and 25.0% at left lower lobe, respectively.3. Blebs or bullae smaller than 1 cm of its diameter were detected by 57.1% [24/42] of sensitivity, and in the cases of size larger than 1 cm, it revealed 86.2% [50/58] of sensitivity respectively.4. Of the 45 cases, 7 cases were false negative [15.6%], most of these were ruptured or small size [< 0.5 cm]. 5. One case was false positive, which was irregular adhesion at the apex of the lung.6. We could detect blebs or bullae with preoperative CT scans in 84.4% [38/45] of total patients. In conclusion, chest CT scan is a very advantageous diagnostic tool for proper management and preventing recurrence of primary spontaneous pneumothorax patient.

• 한국컴퓨터정보학회논문지
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• 제17권5호
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• pp.33-40
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• 2012

본 논문은 HTTP Outbound Traffic의 감시를 통해 다양한 웹 공격의 침입 경로에 대응하고, 학습 효율성을 높여 변종 또는 새로운 기법을 이용한 비정상 행위에 대한 오탐을 낮춘 기법을 제안한다. 제안 기법은 HMM(Hidden Markov Model)을 적용하여 HTML 문서속의 태그와 자바스크립트의 학습을 통한 정상 행위 모델을 생성한 후, HTTP Outbound Traffic속의 정보를 정상 행위 모델과 비교하여 웹 공격을 탐지한다. 실제 침입된 환경에서의 검증 분석을 통해, 제안기법이 웹 공격에 대해 0.0001%의 오탐율과 96%의 우수한 탐지능력을 보임을 제시한다.

• 디지털산업정보학회논문지
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• 제13권3호
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• pp.19-25
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• 2017

Nowadays, networked computer systems play an increasingly important role in our society and its economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason computer security has become an essential concern for network administrators. Recently, a number of Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. Therefore, probe detection has become a major security protection technology to detection potential attacks. Probe detection needs to take into account a variety of factors ant the relationship between the various factors to reduce false negative & positive error. It is necessary to develop new technology of probe detection that can find new pattern of probe. In this paper, we propose an hybrid probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) in dynamic environment such as Cloud and IoT. Also, in order to verify the proposed method, experiments about measuring detection rate in dynamic environments and possibility of countermeasure against intrusion were performed. From experimental results, decrease of false detection and the possibilities of countermeasures against intrusions were confirmed.

• International Journal of Advanced Culture Technology
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• 제9권4호
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• pp.260-267
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• 2021

In this paper, we intend to use a new mixed model of YoloV5 and DeepSort. For fire detection, we want to increase the accuracy by automatically extracting the characteristics of the flame in the image from the training data and using it. In addition, the high false alarm rate, which is a problem of fire detection, is to be solved by using this new mixed model. To confirm the results of this paper, we tested indoors and outdoors, respectively. Looking at the indoor test results, the accuracy of YoloV5 was 75% at 253Frame and 77% at 527Frame, and the YoloV5+DeepSort model showed the same accuracy at 75% at 253 frames and 77% at 527 frames. However, it was confirmed that the smoke and fire detection errors that appeared in YoloV5 disappeared. In addition, as a result of outdoor testing, the YoloV5 model had an accuracy of 75% in detecting fire, but an error in detecting a human face as smoke appeared. However, as a result of applying the YoloV5+DeepSort model, it appeared the same as YoloV5 with an accuracy of 75%, but it was confirmed that the false positive phenomenon disappeared.

• 한국콘텐츠학회논문지
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• 제9권4호
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• pp.1-11
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• 2009

최근 인터넷에 유통되는 유해영상이 급증하면서 이들을 자동으로 차단하는 컴퓨터비전 기술의 연구가 활발히 이루어지고 있다. 본 논문에서는 피부색상을 이용한 유해영상 분류도구를 연구 및 개발한다. 제안하는 분류도구는 2단계로 구성되며, 1단계에서는 피부색 분류기를 이용하여 입력영상에서 피부색 영역을 검출하고, 2단계에서는 영역특징 분류기를 이용하여 앞서 검출된 피부색 영역의 비율과 위치 특징을 무해 또는 유해로 분류한다. 피부색 분류기는 히스토그램 모델에 기반하여 무해영상과 유해영상의 RGB 값으로 학습되며, 영역특징 분류기는 SVM(Support Vector Machine)에 기반하여 영상의 29개 지역의 피부색 비율로 학습된다. 실험결과 제안하는 분류기는 92.80%의 검출율(Detection Rate)과 6.73%의 양성오류율(False Positive Rate)을 나타내었다.