• Journal of IKEEE
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• v.20 no.3
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• pp.251-259
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• 2016

This paper describes that how to enhance the robustness of semiconductor TRM(Transmitter and Receiver Module) through the bias sequencing and tuning the switching time. Previous circuit designs focused on improving the MDS(Minimum Detection Signal) performance. Because TRM has critical problem which transmission output signal leak into receiver by it's compact design. Under this condition, TRM was frequently broken down within the MTBF(Mean Time Between Failure). This study proposes the bias sequencing and tuning the switching time to improve above problem. At first, we collected major failure symptom and infer it's cause. Second, we demonstrated it's effect by derive the improvement method and apply it to our system. And finally we can convinced that the proposed method clear the frequent failure problem with its lack of isolation.

• Korean Journal of Food Science and Technology
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• v.46 no.5
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• pp.538-543
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• 2014

A sandwich enzyme-linked immunosorbent assay method (sELISA) for detecting the presence of shrimp in processed foods was developed using rabbit polyclonal antibodies against tropomyosin produced by black tiger prawns (shrimp). Based on the standard curve derived using this method, the detection range of shrimp was determined to be $1-100{\mu}g/mL$. The cross-reactivity of these antibodies toward black tiger prawns, fleshy prawns, cocktail prawns, lobster, and blue crab was 100, 73, 155, 18, and 0%, respectively. When shrimp was heated for 10 min, the mean assay recovery of tropomyosin was 121-221% at $70-100^{\circ}C$ and 7.8% at $121^{\circ}C$. When shrimp was added to cream soup, weaning food, sausage, fish paste, and sauce, the mean assay recovery was 397, 639, 168, 234, and 0%, respectively. In sample tests involving 14 commercial items, the coincidence ratio of assay results and reference was 79%.

• Journal of Internet Computing and Services
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• v.16 no.4
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• pp.51-59
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• 2015

JavaScript is a popular technique for activating static HTML. JavaScript has drawn more attention following the introduction of HTML5 Standard. In proportion to JavaScript's growing importance, attacks (ex. DDos, Information leak using its function) become more dangerous. Since these attacks do not create a trail, whether the JavaScript code is malicious or not must be decided. The real attack action is completed while the browser runs the JavaScript code. For these reasons, there is a need for a real-time classification and determination technique for malicious JavaScript. This paper proposes the Analysis Engine for detecting malicious JavaScript by adopting the requirements above. The analysis engine performs static analysis using signature-based detection and dynamic analysis using behavior-based detection. Static analysis can detect malicious JavaScript code, whereas dynamic analysis can detect the action of the JavaScript code.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.7-14
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• 2012

We frequently confront with cars interfering into our lane on the ramp. We suffered from serious traffic congestion due to the interfering cars. But the police enforcement has not done actively because it's hard to enforce. In this study, we have evaluated the systems to enforce cutting-in cars through the field test. Generally, the image processing method depends on the weather. To overcome this limitation we proposed a new algorithm combined with section detection method. In the filed test we concluded the results as follows. Whereas the violation detection rate of the general image processing was 58.2%, a new algorithm proposed by this study was 74.5%. And, an error rate enforcing vehicles that do not violate was 0.0%. Also, we can use the existing facilities, such as street light because of compact and lightweight systems which are integrated camera with controller. Therefore, we concluded that it is possible to enforce the interfering Cars using vehicle enforcement systems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.4
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• pp.421-429
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• 1999

It is estimated that, in the twenty-first century, 70％ of global citizens will live in urban areas. This accelerated urbanization will require a greater need for the building DEM and orthoimagery along with Geographic Information System for urban management. The building DEM requires the detection of outlines showing building shapes. To do this, automatic and semiautomatic building extractions are usually used. However, in cases where automatic extraction is performed directly from the aerial images, accurate building outline extraction is very difficult because of shadow, roof color, and neighboring trees making it hard to discern building roofs. To overcome this problem semiautomatic building extraction was suggested in this paper. When a roof texture was homogeneous, building outline detection was performed by mouse-clicking on a part of the roof. To construct the building outlines when the texture was not homogeneous, a computer program was developed to search out corner points by clicking spots near corner points. The building DEM was generated by taking into account building outlines and heights calculated by image matching.

• Korean Journal of Veterinary Service
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• v.36 no.2
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• pp.79-86
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• 2013

Mycobacterium (M.) bovis, a member of the M. tuberculosis complex (MTC), is a re-emerging, zoonotic agent of bovine tuberculosis whose prevalence probably depends on variations in direct exposure to cattle and ingestion of raw milk. Accurate species differentiation of M. bovis and M. tuberculosis is needed to distinguish between human and zoonotic tuberculosis. This study successfully developed a loop-mediated isothermal amplification (LAMP) assay for rapid detection and differentiation of M. bovis and M. tuberculosis, however showed negative reactions in eight non-tuberculous mycobacteria (NTM) samples and ten other bacterial species. Sensitivity of this assay for detection of genomic M. bovis DNA was 10 $fg/{\mu}l$. And this assay successfully detected M. bovis in bovine clinical specimens. In conclusion, the LAMP assay is a simple and powerful tool for rapid detection of M. bovis in both pure bacterial culture and in clinical samples.

• Imaging Science in Dentistry
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• v.33 no.1
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• pp.27-33
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• 2003

Purpose : The purpose of this experiment was to evaluate the diagnostic ability of a CCD-based digital system (CDX-2000HQ) in the detection of incipient dental caries. Materials and Methods : 93 extracted human teeth with sound proximal surfaces and interproximal artificial cavities were radiographed using 4 imaging methods. Automatically processed No.2 Insight film (Eastman Kodak Co., U.S.A.) was used for conventional radiography, scanned images of conventional radiograms for indirect digital radiography were used. For the direct digital radiography, the CDX-2000HQ CCD system (Biomedisys Co. Korea) was used. The subtraction images were made from two direct digital images by Sunny program in the CDX-2000HQ system. Two radiologists and three endodontists examined the presence of lesions using a five-point confidence scale and compared the diagnostic ability by ROC (Receiver Operating Characteristic) analysis and one way ANOV A test. Results: The mean ROC areas of conventional radiography, indirect digital radiography, direct digital radiography, and digital subtraction radiography were 0.9093, 0.9102, 0.9184, and 0.9056, respectively. The diagnostic ability of direct digital radiography was better than the other imaging modalities, but there were no statistical differences among these imaging modalities (p > 0.05). Coclusion : These results indicate that new CCD-based digital systems (CDX-2000HQ) have the potential to serve as an alternative to conventional radiography in the detection of incipient dental caries.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.55-63
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• 2011

This paper describes new moving target detection technique combining two algorithms to detect targets and reject clutters in video frame images for surveillance system: One obtains the region of moving target using phase correlation method using $N{\times}M$ sub-block images in frequency domain. The other uses adaptive threshold using learning weight for extracting target candidates in subtracted image. The block region with moving target can be obtained using the characteristics that the highest value of phase correlation depends on the movement of largest image in block. This technique can be used in camera motion environment calculating and compensating camera movement using FFT phase correlation between input video frame images. The experimental results show that the proposed algorithm accurately detects target(s) with a low false alarm rate in variety environment using the receiver operating characteristics (ROC) curve.

• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.173-183
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• 2009

We present a real-time monitoring system for detecting anomalous network events using the entropy. The entropy accounts for the effects of disorder in the system. When an abnormal factor arises to agitate the current system the entropy must show an abrupt change. In this paper we deliberately model the Internet to measure the entropy. Packets flowing between these two networks may incur to sustain the current value. In the proposed system we keep track of the value of entropy in time to pinpoint the sudden changes in the value. The time-series data of entropy are transformed into the two-dimensional domains to help visually inspect the activities on the network. We examine the system using network traffic traces containing notorious worms and DoS attacks on the testbed. Furthermore, we compare our proposed system of time series forecasting method, such as EWMA, holt-winters, and PCA in terms of sensitive. The result suggests that our approach be able to detect anomalies with the fairly high accuracy. Our contributions are two folds: (1) highly sensitive detection of anomalies and (2) visualization of network activities to alert anomalies.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3710-3717
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• 1999

For the development of unmanned autonomous vehicle, it is essential to detect obstacles, especially vehicles, in the forward direction of navigation. In order to reliably exclude regions that do not contain obstacles and save a considerable amount of computational effort, it is often necessary to confine computation only to ROI(region of interest)s. A ROI is usually chosen as the interior region of the lane. We propose a computationally simple and efficient method for the detection of lanes based on Hough transform and quadratic curve fitting. The proposed method first employs Hough transform to get approximate locations of lanes, and then applies quadratic curve fitting to the locations computed by Hough transform. We have experimented the proposed method on real outdoor road scene. Experimental results show that our method gives accurate detection of straight and curve lanes, and is computationally very efficient.