• Imaging Science in Dentistry
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• 제47권2호
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• pp.99-107
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• 2017

Purpose: Erosions and osteophytes are radiographic characteristics that are found in different stages of temporomandibular joint (TMJ) osteoarthritis. This study assessed the effectiveness of digital subtraction radiography (DSR) in diagnosing simulated osteophytes and erosions in the TMJ. Materials and Methods: Five intact, dry human skulls were used to assess the effectiveness of DSR in detecting osteophytes. Four cortical bone chips of varying thicknesses (0.5 mm, 1.0 mm, 1.5 mm, and 2.0 mm) were placed at the medial, central, and lateral aspects of the condyle anterior surface. Two defects of varying depth (1.0 mm and 1.5 mm) were created on the lateral, central, and medial poles of the condyles of 2 skulls to simulate erosions. Panoramic images of the condyles were acquired before and after artificially creating the changes. Digital subtraction was performed with Emago dental image archiving software. Five observers familiar with the interpretation of TMJ radiographs evaluated the images. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of the imaging methods. Results: The area under the ROC curve (Az) value for the overall diagnostic accuracy of DSR in detecting osteophytic changes was 0.931. The Az value for the overall diagnostic accuracy of panoramic imaging was 0.695. The accuracy of DSR in detecting erosive changes was 0.854 and 0.696 for panoramic imaging. DSR was remarkably more accurate than panoramic imaging in detecting simulated osteophytic and erosive changes. Conclusion: The accuracy of panoramic imaging in detecting degenerative changes was significantly lower than the accuracy of DSR (P<.05). DSR improved the accuracy of detection using panoramic images.

• 한국정밀공학회지
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• 제24권8호통권197호
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• pp.41-49
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• 2007

In this paper, we proposed a new ultrasonic distance measurement system with high accuracy and long range. To improve accuracy and enlarge range, the time of flight of ultrasonic is calculated by the period detecting method. In the proposed ultrasonic distance measurement system, the ultrasonic transmitter and receiver are separated but synchronized by RF(Radio frequency) module. The experiment has been implemented from short distance 1m to maximum available distance 30m. And the period detecting method is compared with the conventional threshold level method. Experimental results show the accuracy and range of the distance measurement are improved by this period detecting method.

• 디지털산업정보학회논문지
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• 제18권4호
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• pp.31-40
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• 2022

YOLOv4 can be used for detecting parking vehicles in order to check a vehicle in out-door parking space. YOLOv4 has 9 anchor boxes in each of 13x13 grid cells for detecting a bounding box of object. Because anchor boxes are allocated based on each cell, there can be existed small observational error for detecting real objects due to the distance between neighboring cells. In this paper, we proposed YOLOv4 grid cell shift algorithm for improving the out-door parking vehicle detection accuracy. In order to get more chance for trying to object detection by reducing the errors between anchor boxes and real objects, grid cells over image can be shifted to vertical, horizontal or diagonal directions after YOLOv4 basic detection process. The experimental results show that a combined algorithm of a custom trained YOLOv4 and a cell shift algorithm has 96.6% detection accuracy compare to 94.6% of a custom trained YOLOv4 only for out door parking vehicle images.

• Asian Pacific Journal of Cancer Prevention
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• 제15권18호
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• pp.7719-7724
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• 2014

Background: Lymph node metastasis is believed to be a dependent negative prognostic factor of esophageal cancer. To explore detection methods with high sensitivity and accuracy for metastases to regional and distant lymph nodes in the clinic is of great significance. This study focused on clinical application of FDG PET/CT and contrast-enhanced multiple-slice helical computed tomography (MSCT) in lymph node staging of esophageal cancer. Materials and Methods: One hundred and fifteen cases were examined with enhanced 64-slice-MSCT scan, and FDG PET/CT imaging was conducted for neck, chest and upper abdomen within one week. The primary lesion, location and numbers of metastatic lymph nodes were observed. Surgery was performed within one week after FDG PET/CT detection. All resected lesions were confirmed histopathologically as the gold standard. Comparative analysis of the sensitivity, specificity, and accuracy based on FDG PET/CT and MSCT was conducted. Results: There were 946 lymph node groups resected during surgery from 115 patients, and 221 were confirmed to have metastasis pathologically. The sensitivity, specificity, accuracy of FDG PET/CT in detecting lymph node metastasis were 74.7%, 97.2% and 92.0%, while with MSCT they were 64.7%, 96.4%, and 89.0%, respectively. A significance difference was observed in sensitivity (p=0.030), but not the others (p>0.05). The accuracy of FDG PET/CT in detecting regional lymph node with or without metastasis were 91.9%, as compared to 89.4% for MSCT, while FDG PET/CT and MSCT values for detecting distant lymph node with or without metastasis were 94.4% and 94.7%. No significant difference was observed for either regional or distant lymph node metastasis. Additionally, for detecting para-esophageal lymph nodes metastasis, the sensitivity of FDG PET/CT was 72%, compared with 54.7% for MSCT (p=0.029). Conclusions: FDG PET/CT is more sensitive than MSCT in detecting lymph node metastasis, especially for para-esophageal lymph nodes in esophageal cancer cases, although no significant difference was observed between FDG PET/CT and MSCT in detecting both regional and distant lymph node metastasis. However, enhanced MSCT was found to be of great value in distinguishing false negative metastatic lymph nodes from FDG PET/CT. The combination of FDG PET/CT with MSCT should improve the accuracy in lymph node metastasis staging of esophageal cancer.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제5권7호
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• pp.345-350
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• 2016

본 논문에서는 트위터를 활용하여 이벤트를 실시간으로 탐지하는 시스템에서의 재난 키워드 필터링과 지명 검출 기법을 제안한다. 스마트폰의 보급이 SNS의 빠른 확산을 이끌었고, 최근 SNS를 활용하여 다양한 연구들이 진행되고 있다. SNS 중에서 트위터는 140자의 단문으로 작성되어 빠르게 확산되는 특성을 가지고 있다. 따라서 트윗 사용자들이 작성하는 트윗은 하나의 센서 역할을 수행할 수 있다. 이러한 특성들을 이용하여 발생한 이벤트를 탐지하는 연구가 진행되었다. 그러나 최근 개인 정보 유출 사례가 증가해 자신의 위치 정보를 공개하기 꺼려함에 따라 재난이 발생한 지역을 파악하는데 어려움이 있다. 또한 맞춤법을 따르지 않은 게시글의 내용을 분석하는 과정에서 정확성과 관련된 문제가 발생한다. 따라서 이벤트 발생 탐지 과정에 재난 관련 키워드 필터링과 지명 검출 기법이 추가적으로 적용되어야 한다. 본 논문에서는 재난 관련 키워드 필터링의 적용과 두 가지 지명 검출 기법을 제안한다. 지명을 검출하는 두 가지 기법은 지명 단어에서 발생되는 노이즈를 제거하는 지명 노이즈 제거 기법과 랜드 마크를 이용하여 지명 단어를 확정하는 지명 확정 기법이다. 재난 관련 키워드와 두 지명 검출 기법을 적용한 결과 기존 시스템의 정확도 49%에서 지명노이즈 제거기법은 78%, 지명확정기법은 89%로 향상되었다.

• 한국정밀공학회지
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• 제34권3호
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• pp.179-184
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• 2017

Recently, traffic accidents and damage on the highway have increased because of overloaded vehicles. The existing overload-detecting system has a low accuracy rate. An overload-detecting system using a weigh-in-motion (WIM) system has been developed to solve this problem. The WIM system can be used to detect overloaded vehicles by measuring the weight of the vehicles. The WIM system is divided into high-speed and low-speed types. The inaccuracy rate in the low-speed WIM system results mainly from the low response rate of the sensor when the velocity is moving at more than 20 km/h. In this study, a low-speed overload-detecting pad with a hydraulic structure using a WIM system was developed to make the system more accurate. The structural and formal analysis was carried out by using a finite element method (FEM) in order to analyze the structural stability and the extrusion velocity of the system. In addition, a static load test was performed to confirm the linearity and accuracy of the pad.

• 대한세포병리학회지
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• 제17권1호
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• pp.1-17
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• 2006

Urine cytology is the most useful technique for detecting either primary or recurrent neoplasms in the urinary tract. Although urine cytology is the traditional method of detecting these neoplasms, its diagnostic accuracy has been underevaluated because of low sensitivity. The cytologic interpretation of urinary samples is not an easy task, even with some expertise in this area, for many reasons. In low-grade urothelial carcinoma, no reliable or reproducible diagnostic cytologic criteria can be provided because of the lack of obvious cytologic features of malignancy, which is one of the main factors lowering its diagnostic accuracy. Many diagnostic markers have been developed recently to enhance its diagnostic yield, but the results have not been satisfactory. However, urine cytology plays a role in detecting high-grade urothelial carcinoma or its precursor lesions. It still shows higher specificity than any of the newly developed urine markers. Understanding the nature of urine samples and the nature of neoplasms of the urinary tract, recognizing their cytologic features fully, and using cytologic findings under appropriate conditions in conjunction with a detailed clinical history would make urine cytology a very valuable diagnostic tool.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.56-62
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• 2021

The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3515-3538
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• 2015

Data accuracy can be increased by detecting and removing the incorrect data generated in wireless sensor networks. By increasing the data accuracy, network lifetime can be increased parallel. Network lifetime or operational time is the time during which WSN is able to fulfill its tasks by using microcontroller with on-chip memory radio transceivers, albeit distributed sensor nodes send summary of their data to their cluster heads, which reduce energy consumption gradually. In this paper a powerful algorithm using proactive fuzzy system is proposed and it is a mixture of fuzzy logic with comparative correlation techniques that ensure high data accuracy by detecting incorrect data in distributed wireless sensor networks. This proposed system is implemented in two phases there, the first phase creates input space partitioning by using robust fuzzy c means clustering and the second phase detects incorrect data and removes it completely. Experimental result makes transparent of combined correlated fuzzy system (CCFS) which detects faulty readings with greater accuracy (99.21%) than the existing one (98.33%) along with low false alarm rate.

• Investigative Magnetic Resonance Imaging
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• 제22권4호
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• pp.229-239
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• 2018

Purpose: To assess the diagnostic performance in detecting rotator cuff tears at 3T of non-arthrographic shoulder magnetic resonance imaging (MRI) using 3D isotropic turbo spin-echo (TSE-SPACE) sequence as compared with 2D sequences. Materials and Methods: Seventy-four patients who were arthroscopically confirmed to have underwent non-arthrographic shoulder MRI with 2D sequences and TSE-SPACE were included. Three independent readers retrospectively scored supraspinatus and infraspinatus tendon (SST-IST) and subscapularis tendon (SCT) tears on 2D sequences and TSE-SPACE. Results: The mean sensitivity, specificity, and accuracy of the three readers were 95%, 100%, and 95% on TSE-SPACE and 99%, 93%, and 98% on 2D sequences for detecting SST-IST tears, respectively, whereas those were 87%, 49%, and 68% on TSESPACE and 88%, 66%, and 77% on 2D sequences for detecting SCT tears, respectively. There was no statistical difference between the two sequences, except for in the specificity of one reader for detecting SCT tears. The mean AUCs of the three readers on TSE-SPACE and 2D sequences were 0.96 and 0.98 for detecting SST-IST tears, respectively, which were not significantly different, while those were 0.71 and 0.82 for detecting SCT tears, respectively, which were significantly different (P < 0.05). Conclusion: TSE-SPACE may have accuracy and reliability comparable to conventional 2D sequences for SST-IST tears at non-arthrographic 3T shoulder MRI, whereas TSE-SPACE was less reliable than conventional 2D sequences for detecting SCT tears.