• Journal of the Korean Data and Information Science Society
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• 제18권3호
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• pp.619-628
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• 2007

This study is devoted to suggesting the norm of detection abnormal users who are inferior to the other users in the recommender system compared with estimation accuracy. To select the abnormal users, we propose the pre-filtering method by using the preference ratings to the item rated by users. In this study, the experimental result shows the possibility of detecting the abnormal users before the process of preference estimation through the prediction algorithm. And It will be possible to improve the performance of the recommender system by using this detecting norm.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2118-2126
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• 2017

The large-scale power system blackouts have indicated that conventional protection relays that based on local signals cannot fit for modern power grids with complicated setting or heavily loaded-flow transfer. In order to accurately detect various faulted lines and improve the fault-tolerance of wide-area protection, a novel multi-section weighed fault matching and detecting algorithm is proposed. The real protection vector (RPV) and expected section protection vectors (ESPVs) for five fault sections are constructed respectively. The function of multi-section weighed fault matching is established to calculate the section fault matching degrees between RPV and five ESPVs. Then the fault degree of protected line based on five section fault degrees can be obtained. Two fault detecting criterions are given to support the higher accuracy rate of detecting fault. With the enumerating method, the simulation tests illustrate the correctness and fault-tolerance of proposed algorithm. It can reach the target of 100% accuracy rate under 5 bits error of wide-area protections. The influence factors of fault-tolerance are analyzed, which include the choosing of wide-area protections, as well as the topological structures of power grid and fault threshold.

• 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.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• 제44권1호
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• pp.18-24
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• 2018

Objectives: Foreign bodies (FBs) account for 3.8% of all pathologies of the head and neck region, and approximately one third of them are missed on initial examination. Thus, FBs represent diagnostic challenges to maxillofacial surgeons, rendering it necessary to employ an appropriate imaging modality in suspected cases. Materials and Methods: In this cross-sectional study, five different materials, including wood, metal, glass, tooth and stone, were prepared in three sizes (0.5, 1, and 2 mm) and placed in three locations (soft tissue, air-filled space and bone surface) within a sheep's head (one day after death) and scanned by panoramic radiography, cone-beam computed tomography (CBCT), and ultrasonography (US) devices. The images were reviewed, and accuracy of the detection modalities was recorded. The data were analyzed statistically using the Kruskal-Wallis, Mann-Whitney U-test, Friedman, Wilcoxon signed-rank and kappa tests (P<0.05). Results: CBCT was more accurate in detection of FBs than panoramic radiography and US (P<0.001). Metal was the most visible FB in all of modalities. US was the most accurate technique for detecting wooden materials, and CBCT was the best modality for detecting all other materials, regardless of size or location (P<0.05). The detection accuracy of US was greater in soft tissue, while both CBCT and panoramic radiography had minimal accuracy in detection of FBs in soft tissue. Conclusion: CBCT was the most accurate detection modality for all the sizes, locations and compositions of FBs, except for the wooden materials. Therefore, we recommend CBCT as the gold standard of imaging for detecting FBs in the maxillofacial region.

• Journal of Gynecologic Oncology
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• 제29권6호
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• pp.98.1-98.13
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• 2018

Objective: We describe a systematic review and meta-analysis of the performance of ${18}F$-fluorodeoxyglucose ($^{18}F-FDG$) positron emission tomography/computed tomography (PET/CT) for detecting metastasis in ovarian cancer. Methods: MEDLINE and Embase were searched for diagnostic accuracy studies that used $^{18}F-FDG$ PET or PET/CT for pre-treatment staging, using surgical findings as the reference standard. Sensitivities and specificities were pooled and plotted in a hierarchic summary receiver operating characteristic plot. Potential causes of heterogeneity were explored through sensitivity analyses. Results: Eight studies with 594 patients were included. The overall pooled sensitivity and specificity for metastasis were 0.72 (95% confidence interval [CI]=0.61-0.81) and 0.93 (95% CI=0.85-0.97), respectively. There was considerable heterogeneity in sensitivity ($I^2=97.57%$) and specificity ($I^2=96.74%$). In sensitivity analyses, studies that used laparotomy as the reference standard showed significantly higher sensitivity and specificity (0.77; 95% CI=0.67-0.87 and 0.96; 95% CI=0.92-0.99, respectively) than those including diagnostic laparoscopy (0.62; 95% CI=0.46-0.77 and 0.84; 95% CI=0.69-0.99, respectively). Higher specificity was shown in studies that confirmed surgical findings by pathologic evaluation (0.95; 95% CI=0.90-0.99) than in a study without pathologic confirmation (0.69; 95% CI=0.24-1.00). Studies with a lower prevalence of the FDG-avid subtype showed higher specificity (0.97; 95% CI=0.94-1.00) than those with a greater prevalence (0.89; 95% CI=0.80-0.97). Conclusion: Pre-treatment $^{18}F-FDG$ PET/CT shows moderate sensitivity and high specificity for detecting metastasis in ovarian cancer. With its low false-positive rate, it can help select surgical approaches or alternative treatment options.

• 대한두경부종양학회지
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• 제4권1호
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• pp.5-11
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• 1988

CT examination has been used in the preoperative examination of patients with head and neck cancer. The accuracy of CT in detecting nodal metastases has not been well established. We studied 35 patients (41 neck specimens) with head and neck cancer who underwent neck dissection. Surgical pathologic findings were compared with preoperative CT scan to establish the diagnostic accuracy for cervical lymph node metastases. The results of physical examination, CT scans of neck and histologic examinations were compared each other. The overall diagnostic accuracy of CT was 83.3%. Comparison with clinical accuracy shows the CT scan to be superior to the clinical examination in spite of careful physical examination, particularly in detecting occult metastases.

• 대한임베디드공학회논문지
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• 제13권6호
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.

• Imaging Science in Dentistry
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• 제45권3호
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• pp.153-158
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• 2015

Purpose: The purpose of this study was to evaluate and compare the efficacy of cone-beam computed tomography (CBCT) and digital intraoral radiography in diagnosing simulated small external root resorption cavities. Materials and Methods: Cavities were drilled in 159 roots using a small spherical bur at different root levels and on all surfaces. The teeth were imaged both with intraoral digital radiography using image plates and with CBCT. Two sets of intraoral images were acquired per tooth: orthogonal (PA) which was the conventional periapical radiograph and mesioangulated (SET). Four readers were asked to rate their confidence level in detecting and locating the lesions. Receiver operating characteristic (ROC) analysis was performed to assess the accuracy of each modality in detecting the presence of lesions, the affected surface, and the affected level. Analysis of variation was used to compare the results and kappa analysis was used to evaluate interobserver agreement. Results: A significant difference in the area under the ROC curves was found among the three modalities (P=0.0002), with CBCT (0.81) having a significantly higher value than PA (0.71) or SET (0.71). PA was slightly more accurate than SET, but the difference was not statistically significant. CBCT was also superior in locating the affected surface and level. Conclusion: CBCT has already proven its superiority in detecting multiple dental conditions, and this study shows it to likewise be superior in detecting and locating incipient external root resorption.

• 전기학회논문지
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• 제56권5호
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• pp.876-883
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• 2007

The magnetic flux leakage(MFL) type nondestructive testing(NDT) method is widely used to detect corrosion, defects and mechanical deformation of the underground gas pipelines. The object pipeline is magnetically saturated by the magnetic system with permanent magnet and yokes. Hall sensors detect the leakage fields in the region of the defect. The defects are sometimes occurred in group. The accuracy of the detecting signals in this defect cluster become lowered because of the complexity of the defect cluster. In this paper, the effects of the multi -defects are analyzed. The detecting signals are computed by 3-dimensional finite element method and compared with real measurement. The results say that, rather than the size of the defects, the effects of the relative position of the multi-defects are very important on the detecting signals.

• Journal of Multimedia Information System
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• 제4권1호
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• pp.33-38
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• 2017

This article suggests a new algorithm for detecting two-wheelers on the road that have various shapes according to viewpoints. Because of complicated shapes, it is more difficult than detecting a human. In general, the Histograms of Oriented Gradients(HOG) feature is well known as a useful method of detecting a standing human. We propose a method of detecting a human on a two-wheelers using the spatial relocation of HOG (Histogram of Oriented Gradients) features. And this paper adapted the contrast method which is generally using in the image process to improve the detection rate. Our experimental results show that a two-wheelers detection system based on proposed approach leads to higher detection accuracy, less computation, and similar detection time than traditional features.