• The Korean Journal of Cytopathology
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• v.7 no.2
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• pp.111-121
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• 1996

Fine needle aspiration cytology(FNAC) is preferred because of simplicity, safety, and reliability in the evaluation of patients with thyroid nodule or hyperplasia. However, there are a few limitations such as false-negative or false-positive cases and non-diagnostic material. To evaluate the usefulness of FNAC in thyroid lesions, we reviewed 704 FNAC cases of thyroid nodules from 1988 to 1994 at Soonchunhyang University Hospital. The results are as follows. 1. Among 704 FNAC cases of thyroid gland, 571(81.1%) cases were benign, 12(1.7%) were suspicious, 71(10.1%) were malignancy, and 50(7.1%) were material insufficiency. The cytologic diagnoses of the benign lesions included 168 cases of follicular neoplasm, 139 cases of adenomatous goiter, 162 cases of follicular lesion such as follicular neoplasm or adenomatous goiter, 61 cases of Hashimoto's thyroiditis, 13 cases of subacute thyroiditis, and 28 cases of colloidal nodule or benign nodule. The malignant lesions included 68 cases of papillary carcinona, two medullary carcinomas and a case of metastatic colon cancer. 2. The average number of cytologic smear slides was $4.12{\pm}1.81$ in material insufficiency and $5.63{\pm}1.79$ in diagnostic cases. This difference was statistically significant(p<0.00001). 3. Histological assessment of 150 cases revealed 2 false negative and 1 false positive cases. The false negative cases were a case of marked sclerosis in papillary carcinoma and an occult case of papillary carcinoma. The false positive case resulted from pseudo-ground glass nuclei due to marked dry artifact. 4. Comparison between the FNAC and the histologic diagnosis revealed that FNAC had a sensitivity of 93.5%, a specificity of 99.2%, a false negative rate of 6.6%, a false positive rate of 0.8%, and an overall diagnostic accuracy of 98.0%. Therefore, FNAC of thyroid gland is a very reliable diagnostic method with excellent accuracy rate.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.419-432
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• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

• Journal of IKEEE
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• v.9 no.2 s.17
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• pp.108-114
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• 2005

While E-mail has become an important way of communications in IT societies, it creates various social problems due to increase of spam mails. Even though many organizations and corperations have been doing researches to develop spam mail blocking technologies, more cost and system complexities are required because of varieties of blocking technologies. In case of adopting spam blocking technologies, system reliability largely relies on the False-positive error rate with the order of employing spam blocking filters. In this paper, a False-positive mail recovery technique based on privacy information is proposed and implemented in order to improve the reliability of spam locking filters. Through the implemented prototype, recovery procedure for False-positive mails is verified and the results are summarized and analyzed.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.609-616
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• 2005

Signature-based Intrusion Detection has many false positive and many difficulties to detect new and changed attacks. Alpha-cut is introduced which reduces false positive with a combination of signature-based IDS and machine learning-based IDS in prior paper [1]. This research is a study of a succession of Alpha-cut, and we introduce Beta-rick in which attacks can be detected but cannot be detected in single signature-based detection. Alpha-cut is a way of increasing detection accuracy for the signature based IDS, Beta-pick is a way which decreases the case of treating attack as normality. For Alpha-cut and Beta-pick we use XIBL as a learning algorithm and also show the difference of result of Sd.5. To describe the value of proposed method we apply Alpha-cut and Beta-pick to signature-based IDS and show the decrease of false alarms.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.703-706
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• 2004

나선형 CT 혈관촬영에서 획득한 영상의 분석를 통해서 폐색전증이 의심되는 부위를 자동으로 검출하는 방법으로, 연구 대상은 20명의 환자를 대상으로 분석하였으며 CT 검사 후 방사선과 의사가 정상소견을 받은 환자 5명과 폐색전증이 있는 판독소견을 가진 15명을 대상으로 비교 분석하였다. CT 검사하는 동안에 조영제를 투입하면, 폐색전증이 발생한 부위는 조영제 양과 분포가 불균등하여 명암값이 낮게 검출된다. 검출방법으로는 전처리 작업으로 폐영역만을 분할하고, 분할된 폐영역에서 혈관을 찾기 위해 모폴로지기법를 적용하여 세선화(thinning) 작업을 진행한다. 다음 공정으로는 경계선을 찾아 local watershed를 적용하여 혈관을 검출하고, 검출된 혈관내에서 원형모델을 적용하여 모폴로지(morphology)을 통해 국소 부위의 미세한 농도변화를 인지하여 색전이 발생한 영역을 자동검출하였다. 본 논문의 자동검출시스템에서는 색전증이 있는 경우에 true positive의 발생빈도는 case 당 4.5개가 검출되었다. 정상인의 경우에도 혈류의 흐름, 혈류의 분기점, 노이즈로 인한 false positive의 빈도는 case 당 2.6개가 발생하여 전체적으로 false positive는 5.2개가 검출되었다. 본 논문은 false positive의 비율이 높게 검출되었지만 폐영역 CT 검사의 컴퓨터지원진단시스템(computer aided diagnosis)의 향후 연구과제에 방향을 제시할 수 있을 것이라 사료된다.

• Journal of Chest Surgery
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• v.1 no.1
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• pp.75-80
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• 1968

This is a case report of traumatic arterial injuries with false aneurysm & arterio-venous fistula treated surgically at National Medical Center. 3 cases were A-V fistula and 2 cases only false aneurysm. Physiological disturbance were produced by only arteriovenous fistula; In one case ulceration of mid. 1/3 tibia due to diminished arterial flow and in 2 cases left ventricular hypertrophy, in which cases Bramhan`s sign were positive. Removing out the fistulous lesions and aneurysm, all of the arterial continuities has been reconstructed by means of end to end anastomosis, Dacron graft and vein graft, veins were managed by ligations of both ends in two cases and end to end anostomosis in one case. Immediate post operative results were good, and two cases were followed for 10 months.

• The Korean Journal of Cytopathology
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• v.1 no.1
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• pp.51-59
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• 1990

Fine needle aspiration biopsy cytology (FNA) for diagnosis of a variety of breast tumors has been proven to be a simple, safe, and cost saving diagnostic methodology with high accuracy. Cytologic specimens from 1,029 fine needle aspirations of the breast during last 3-year period were reviewed and subsequent biopsies from 107 breast lesions were reevaluated for cytohistological correlation. FNA had a sensitivity of 81.6% and a specificity of 98.3%. One oui of 107 cases biopsied revealed a false positive result (0.9%) and the case was due to misinterpretation of apocrine metaplastic cells in necrotic backgound as malignant cells. A false negative rate was 8.4% (9 of 107 cases biopsied). Six of 9 false negative cases were resulted from insufficient aspirates for diagnosis, and remaining three of 9 false negative cases revealed extensive necrosis with no or scanty viable cells on smears. The results indicate that for reducing false positive and false negative rates of FNA, an experienced cytopathologist and a proficient aspirator are of great importance.

• Journal of the Korean Institute of Gas
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• v.16 no.6
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• pp.107-114
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• 2012

Fire detection system is used for detection and alarm-generation of danger in case of fire. Most fire detection systems being used these days often malfunction from false positive and false negative errors. To improve detection reliability, an integrated fire detection algorithm using multi-senor information of heat, smoke and carbon monoxide detectors is suggested, then built and tested using the LabVIEW environment. Simulated using sensor measurement data offered by National Institute of Standards and Technology (NIST), possibility of reducing false positive and false negative errors is verified.

• Journal of Gastric Cancer
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• v.6 no.4
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• pp.291-294
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• 2006

F-18 FDG-PET/CT could be used to evaluate the surveillance of recurrent stomach cancer, but some cases reported as false-positives. The authors found an activated charcoal granuloma from intraperitoneal chemotherapy by using a curative resection and mitomycin C for stomach cancer. A mass behind the right colon that showed on CT 6 months after an operation in a 46-year-old male patient had no progression in size, but 36 months after the operation, an increase was seen on F-18 FDG-PET/CT, and a metastatic tumor was suspected. The tumor was resected by an explorative laparotomy and was diagnosed as being an activated charcoal granuloma based on the histologic finding. Based on this case, we should be reminded of the possibility of a false-positive on analysis of F-18 FDG-PET/CT caused by an activated charcoal granuloma in a patient who has intraperitoneal chemotherapy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1284-1297
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• 2019

The network environment is presently becoming very increased. Accordingly, the study of traffic classification for network management is becoming difficult. Automatic signature extraction system is a hot topic in the field of traffic classification research. However, existing automatic payload signature generation systems suffer problems such as semi-automatic system, generating of disposable signatures, generating of false-positive signatures and signatures are not kept up to date. Therefore, we provide a fully automatic signature update system that automatically performs all the processes, such as traffic collection, signature generation, signature management and signature verification. The step of traffic collection automatically collects ground-truth traffic through the traffic measurement agent (TMA) and traffic management server (TMS). The step of signature management removes unnecessary signatures. The step of signature generation generates new signatures. Finally, the step of signature verification removes the false-positive signatures. The proposed system can solve the problems of existing systems. The result of this system to a campus network showed that, in the case of four applications, high recall values and low false-positive rates can be maintained.