• Current Optics and Photonics
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• v.1 no.3
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• pp.196-202
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• 2017

Corona discharge is always a sign of failure processes of high-voltage electrical apparatus, including those utilized in electric railway systems. Solar-blind ultraviolet (UV) cameras are effective tools for corona inspection. In this work, we present an automatic railway corona-discharge detection system based on solar-blind ultraviolet detection. The UV camera, mounted on top of a train, inspects the electrical apparatus, including transmission lines and insulators, along the railway during fast cruising of the train. An algorithm based on the Hough transform is proposed for distinguishing the emitting objects (corona discharge) from the noise. The detection system can report the suspected corona discharge in real time during fast cruises. An experiment was carried out during a routine inspection of railway apparatus in Xinjiang Province, China. Several corona-discharge points were found along the railway. The false-alarm rate was controlled to less than one time per hour during this inspection.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.9-18
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• 2013

In this paper, we design and implement an intelligent system for finding objects with RFID(Radio Frequency IDentification) tag in which an mobile robot can do. The system we developed is a learning system of artificial neural network that uses RSSI(Received Signal Strength Indicator) value as input and absolute coordination value as target. Although a passive RFID is used for location estimation, we consider an active RFID for expansion of recognition distance. We design the proposed system and construct the environment for indoor location estimation. The designed system is implemented with software and the result related learning is shown at test bed. We show various experiment results with similar environment of real one from earning data generation to real time location estimation. The accuracy of location estimation is verified by simulating the proposed method with allowable error. We prepare local test bed for indoor experiments and build a mobile robot that can find the objects user want.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.107-119
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• 1999

There is no authentic solution in a face detection problem though it is an important part of pattern recognition and has many diverse application fields. The reason is that there are many unpredictable deformations due to facial expressions, view point, rotation, scale, gender, age, etc. To overcome these problems, we propose an algorithm based on feature-based method, which is well known to be robust to these deformations. We detect a face by calculating a similarity between the formation of real face feature and candidate feature formation which consists of eyebrow, eye, nose, and mouth. In this paper, we use a steerable filter instead of general derivative edge detector in order to get more accurate feature components. We applied deformable template to verify the detected face, which overcome the weak point of feature-based method. Considering the low detection rate because of face detection method using whole input images, we design an adaptive skin-color filter which can be applicable to a diverse skin color, minimizing target area and processing time.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.43-50
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• 2011

The scope of the problems that could be solved by monitoring and the improvement of the recognition time is directly correlated to the performance of the management function of the business process. However, the current event-managing monitoring system and the real-time advanced alarming business monitoring system decided whether to apply warnings or not by assuming a fixed environment and showing expressions based on the design rules. Therefore, there is a limit for distinguishing the range of occurrence and the level of severity in regard to the new external problems occurring in a complicated environment. Such problems cannot be abstracted. In this paper, evaluation model of business process contextual situations using goal scenario is suggested to provide constant services through the current monitoring process in regard to the service demands of the new scenario which occurs outside. The new demands based on the outside situation are analyzed according to the target scenario for the process activities. Also, a similar process model is found and identified by combining similarity and interrelationship. The process can be stopped in advance or adjusted to the wanted direction.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.431-439
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• 2013

The purpose of this study is to analyze the apartment investment performance including the risk and to verify the presence or absence of regional characteristics. This study made an analysis on the apartment investment performance by dividing it into long and short-term basis. Data collection period is 10 years from 2002 to 2012 and target area includes Gangnam and Gangbuk (southern and northern area of Seoul) and 6 metropolitan cities. For evaluating the investment performance, this study used the earning rate of 5 year 1st class national housing bond as the risk-free rate of return and 1~2 year interest rate of fixed deposit for calculating lease profit. The results of study are as follows, Treynor's Index was used in long investment performance evaluation because of regional characters non-existing in Seoul and Incheon whereas Jensen's Index was used in evaluating because of regional characters existing in 5 metropolitan cities. And Jensen's Index was used in short-term evaluation of all districts as existing regional characters in all districts. Short-term performance considering regional characteristics yielded different results of simple evaluation. Therefore, in case of simple rate of return to evaluate the performance, the recognition of that can be distorted.

• Nutrition Research and Practice
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• v.8 no.4
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• pp.377-385
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• 2014

BACKGROUND/OBJECTIVES: Abundant consumption of seaweeds in the diet is epidemiologically linked to the reduction in risk of developing cancer. In larger cases, however, identification of particular seaweeds that are accountable for these effects is still lacking, hindering the recognition of competent dietary-based chemo preventive approaches. The aim of this research was to establish the antiproliferative potency and angiosuppressive mode of action of Stoechospermum marginatum seaweed methanolic extract using various experimental models. MATERIALS/METHODS: Among the 15 seaweeds screened for antiproliferative activity against Ehrlich ascites tumor (EAT) cell line, Stoechospermum marginatum extract (SME) was found to be the most promising. Therefore, it was further investigated for its anti-proliferative activity in-vitro against choriocarcinoma (BeWo) and non-transformed Human embryonic kidney (HEK 293) cells, and for its anti-migratory/tube formation activity against HUVEC cells in-vitro. Subsequently, the angiosuppressive activity of S. marginatum was established by inhibition of angiogenesis in in-vivo (peritoneal angiogenesis and chorioallantoic membrane assay) and ex-vivo (rat cornea assay) models. RESULTS: Most brown seaweed extracts inhibited the proliferation of EAT cells, while green and red seaweed extracts were much less effective. According to the results, SME selectively inhibited proliferation of BeWo cells in-vitro in a dose-dependent manner, but had a lesser effect on HEK 293 cells. SME also suppressed the migration and tube formation of HUVEC cells in-vitro. In addition, SME was able to suppress VEGF-induced angiogenesis in the chorio allantoic membrane, rat cornea, and tumor induced angiogenesis in the peritoneum of EAT bearing mice. A decrease in the microvessel density count and CD31 antigen staining of treated mice peritoneum provided further evidence of its angiosuppressive activity. CONCLUSIONS: Altogether, the data underline that VEGF mediated angiogenesis is the target for the angiosuppressive action of SME and could potentially be useful in cancer prevention or treatment involving stimulated angiogenesis.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.272-277
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• 2010

AR(Augmented Reality) needs medium between real and virtual, world, and recognition techniques are necessary to track an object continuously. Optical tracking using marker is mainly used, but it takes time and is inconvenient to attach marker onto the target objects. Therefore, many researchers try to develop markerless tracking techniques nowaday. In this paper, we extract features and 3D position from 3D objects and suggest realtime tracking based on these features and positions, which do not use just coplanar features and 2D position. We extract features using SURF, get rotation matrix and translation vector of 3D object using POSIT with these features and track the object in real time. If the extracted features are nor enough and it fail to track the object, then new features are extracted and re-matched to recover the tracking. Also, we get rotation in matrix and translation vector of 3D object using POSIT and track the object in real time.

• Journal of Advanced Navigation Technology
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• v.24 no.1
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• pp.47-52
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• 2020

Direction of arrival (DoA) estimation is a scheme of estimating the directions of targets by analyzing signals generated or reflected from the targets and is used in various fields. Artificial neural networks (ANN) is a field of machine learning that mimics the neural network of living organisms. They show good performance in pattern recognition. Although researches has been using ANNs to estimate the DoAs, there are limitationsin dealing with variations of the signal-to-noise ratio (SNR) of the target signals. In this paper, we propose a three-stage ANN algorithm for DoA estimation. The proposed algorithm can minimize the performance reduction by applying the model trained in a single SNR environment to various environments through a 'noise reduction process'. Furthermore, the scheme reduces the difficulty in learning and maintains efficiency in estimation, by employing a process of DoA shift. We compare the performance of the proposed algorithm with Cramer-Rao bound (CRB) and the performances of existing subspace-based algorithms and show that the proposed scheme exhibits better performance than other schemes in some severe environments such as low SNR environments or situations in which targets are located very close to each other.

• Korean Journal of Cognitive Science
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• v.10 no.3
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• pp.1-15
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• 1999

Based on known physiological and psychophysical results, a neural network model for visual selection, called FeaureGate is proposed. The model consists of a hierarchy of spatial maps. and the flow of information from each level of the hierarchy to the next is controlled by attentional gates. The gates are jointly controlled by a bottom-up system favoring locations with unique features. and a top-down mechanism favoring locations with features designated as target features. The present study focuses on the top-down mechanism of the FeatureGate model that produces results similar to Moran and Desimone's (1985), which many current models have failed to explain, The FeatureGate model allows a consistent interpretation of many different experimental results in visual attention. including parallel feature searches and serial conjunction searches. attentional gradients triggered by cuing, feature-driven spatial selection, split a attention, inhibition of distractor locations, and flanking inhibition. This framework can be extended to produce a model of shape recognition using upper-level units that respond to configurations of features.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.470-477
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• 2009

Modular reconfigurable robots with physical docking capability easily adapt to a new environment and many studies are necessary for the modular robots. In this paper, we propose a vision-based fuzzy autonomous docking controller for the modular docking robots. A modular docking robot platform which performs real-time image processing is designed and color-based object recognition method is implemented on the embedded system. The docking robot can navigate to a subgoal near a target robot while avoiding obstacles. Both a fuzzy obstacle avoidance controller and a fuzzy navigation controller for subgoal tracking are designed. We propose an autonomous docking controller using the fuzzy obstacle avoidance and navigation controllers, absolute distance information and direction informations of robots from PSD sensors and a compass sensor. We verify the proposed docking control method by docking experiments of the developed modular robots in the various environments with different distances and directions between robots.