• Archives of Pharmacal Research
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• v.11 no.1
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• pp.1-6
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• 1988

The use of blue cotton for detecting polycyclic aromatic mutagens in environmental samples (foods, human excretions, river water, etc) is reviewed. Since the invention of blue cotton has its origin in studies of mutagen modulators, these studies are also briefly reviewed.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.178-183
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• 2008

Human motion analysis is researched as a new method for human-robot interaction (HRI) because it concerns with the key techniques of HRI such as motion tracking and pose recognition. To analysis human motion, extracting features of human body from sequential images plays an important role. After finding the silhouette of human body from the sequential images obtained by CCD color camera, the skeleton model is frequently used in order to represent the human motion. In this paper, using the silhouette of human body, we propose the feature extraction method based on hybrid skeleton for detecting human motion. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.233-238
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• 2004

Comer point is a very important information to a pattern recognition of image processing. And so, many researchers develope various detecting comer point algoritms. But, there are some problems to get comer points by 8 directional chain code when the degree of edge line is not integer multiplication of 45 degree. So, we propose a new algorithm which is combined with morphology and human visual conception for optimal comer points without the above defects. We get a good simulation result by this proposed algorithm Ana so, we think this algorithm is very useful to FA(factory automation} and ship's radar system to know some coastal area from its image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5436-5458
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• 2017

Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.103-109
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• 2015

This paper introduces a multi-purpose smart fusion sensor. Normally, this type of sensor can contribute to energy savings specifically related to lighting and heating/air conditioning systems by detecting individuals in an office building. If a fire occurs, the sensor can provide information regarding the presence and location of residents in the building to a management center. The system consists of four sensors: a thermopile sensor for detecting heat energy, an ultrasonic sensor for measuring the distance of objects from the sensor, a fire detection sensor, and a passive infrared sensor for detecting temperature change. The system has a wireless communication module to provide the management center with control information for lighting and heating/air conditioning systems. We have also demonstrated the usefulness of the proposed system by applying it to a real environment.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.214-216
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• 2006

Expressive face and human body gestures are among the main non-verbal communication channels in human-human interaction. Understanding human emotions through body gesture is one of the necessary skills both for humans and also for the computers to interact with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. Skin color information for tracking hand gesture is obtained from face detection region. We have revealed relationships between paricular body movements and specific emotions by using HMM(Hidden Markov Model) classifier. Performance evaluation of emotional human body recognition has experimented.

• Imaging Science in Dentistry
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• v.47 no.2
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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.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.333-340
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• 2015

In this paper, we propose a passive microwave sensor for detecting human body using microwave radiometer technologies. The proposed sensor detects human body by measuring the change of the received radiation power from fixed background object due to human body. A C-band microwave radiometer is designed and implemented. The received radiation power changes due to human body is measured by the C-band microwave radiometer, and the effectiveness of the proposed sensor is evaluated by the measurement result analysis.

• Journal of Nutrition and Health
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• v.35 no.2
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• pp.213-222
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• 2002

The alkaline comet assay has been used with increasing popularity to investigate the level of DNA damage in biomonitoring studies within the last decade in Western countries. The purpose of this study was to evaluate the usefulness of the alkaline comet assay as a biomarker of oxidative DNA damage for monitoring in the Korean population, and also to evaluate the effect of nutritional status and lifestyle factors on H2O2 induced oxidative DNA damage measured by the alkaline comet assay in human lymphocytes. The study population consisted of 61 healthy Korean male volunteers, aged 20-28. Epidemiological background data including dietary habits, smoking habits and anthropometrical measurements were collected through personal interviews. After blood collection, the comet assay in peripheral lymphocytes and plasma lipids analysis was carried out and the results analyzed. Tail moment (TM) and tail length (TL) of the comet assay were use\ulcorner to measure DNA damage in the lymphocytes of the subjects. Statistically significant (p < 0.05) positive correlations were observed between DNA damage (TM or TL) and smoking habits expressed as cigarettes smoked per day and pack years (r = 0.311 and 0.382 for TM, r = 0.294 and 0.350 for TL, respectively). There were also significant positive correlations between DNA damage parameter and waist-hip ratio. Higher plasma triglyceride levels were associated with increased damage to DNA. There were no correlations between the consumption frequencies of vegetables and DNA damage to the subjects. However, consumption frequencies of fruit and fruit juice intake were inversely associated with the TM and TL. The results indicate that die comet assay is a simple, rapid and sensitive method for detecting lymphocyte DNA damage induced by cigarette smoking. Consumption of fruit or fruit juices could potentiall modify the damaged DNA in the human peripheral lymphocytes of young Korean men.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.18-23
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• 2010

In this paper, we propose a computationally efficient method detecting the P300 wave for brain-machine interface. Electrophysiological researches have shown that the P300 wave's potential is decreased when human intention matches visual stimulation. Motivated by this fact, we can infer human intention for brain-machine interface by detecting the P300 wave's potential decrease. The P300 wave is recorded from EEG(electroencephalogram) electrodes attached on human brain skull after giving alphabetical stimulation. To detect the potential decrease in P300, firstly we statistically model the P300 wave's negative potential. Then we infer human intention based on maximum likelihood estimation. The proposed method was evaluated on the data recorded from three healthy human subjects. The method achieved an averaging accuracy of 98% from subject k, 90% from subject j and 79.8% from subject h.