• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.258-261
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• 2015

본 논문에서는 주행 중에 보행자의 인식 및 추적을 위해서 차량에서 촬영된 영상정보를 이용하여 주변의 보행자를 찾고, 사고 위험성이 있는 보행자를 인식하기 위해서 보행자 파악 및 보행자와의 거리를 측정하기 위한 연구를 하고자 한다. 본 논문에서는 차량에 정착된 카메라를 통한 보행자 인식 기술에 대해 연구 하였다. 제안한 방법은 보행자 인식 단계에서 Cascasde HOG, Haar-like 알고리즘을 적용하였고, 추적 단계에서 칼만 필터와 클러스터링 기법을 결합하여 실시간으로 보행자를 인식 및 추적하였다.

• Journal of Sensor Science and Technology
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• v.29 no.3
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• pp.194-200
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• 2020

Human detection is an important aspect in many video-based sensing and monitoring systems. Studies have been actively conducted for the automatic detection of humans in camera images, and various methods have been proposed. However, there are still problems in terms of performance and computational cost. In this paper, we describe a method for efficient human detection in the field of view of a camera, which may be static or moving, through multiple processing steps. A detection line is designated at the position where a human appears first in a sensing area, and only the one-dimensional gray pixel values of the line are monitored. If any noticeable change occurs in the detection line, corner detection and optical flow computation are performed in the vicinity of the detection line to confirm the change. When significant changes are observed in the corner numbers and optical flow vectors, the final determination of human presence in the monitoring area is performed using the Histograms of Oriented Gradients method and a Support Vector Machine. The proposed method requires processing only specific small areas of two consecutive gray images. Furthermore, this method enables operation not only in a static condition with a fixed camera, but also in a dynamic condition such as an operation using a camera attached to a moving vehicle.

• Archives of Pharmacal Research
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• v.22 no.2
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• pp.137-142
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• 1999

Anti-ulcer activity of newly synthesized acylquinoline derivatives was investigated. For the in vitro screening, the effects of compounds on gastric $H^{+}/K^{+}$ ATPase isolated from hog and rabbit were examined. Among them, AU-090, AU-091, AU-254, AU-413 and AU-466 exhibited good in vitro activity on both enzymes. To correlate the in vitro activity with in vivo action, the effects of the compounds on the basal gastric acid secretion were studied. Some derivatives showed considerable anti-secretory activities, and AU-413 was selected for further studies. AU-413 protected gastric damage induced by either ethanol or NaOH dose dependently when given orally. $ED_{50}$ values of 12 mg/kg, p.o. (ethanol) and 41 mg/kg, p.o. (NaOH) were obtained. In addition, histamine-stimulated gastric secretion was reduced upon AU-413 administration. Taken together, newly synthesized acylquinoline derivatives, especially AU-413, is worthy of further investigation to be developed as an anti-ulcer agent.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.3
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• pp.236-242
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• 2019

Ultra-wideband(UWB) is a technology that can transmit and receive signals at high speeds using a very short signal of wideband of several GHz, and has been recently used in the field of radar technology. Impulse radio(IR)-UWB radar is used in the field of motion recognition with high resolution. In this work, we studied motion recognition using IR-UWB radar. We constructed a development environment to acquire data about motion and implemented a signal processing algorithm for performance enhancement. Based on the signal processing result, the performance was verified through feature extraction and learning of motion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6000-6017
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• 2018

This paper presents a new descriptor, named Histograms of Prominent Edge Directions (HPED), for the recognition of facial expressions in a person-independent environment. In this paper, we raise the issue of sampling error in generating the code-histogram from spatial regions of the face image, as observed in the existing descriptors. HPED describes facial appearance changes based on the statistical distribution of the top two prominent edge directions (i.e., primary and secondary direction) captured over small spatial regions of the face. Compared to existing descriptors, HPED uses a smaller number of code-bins to describe the spatial regions, which helps avoid sampling error despite having fewer samples while preserving the valuable spatial information. In contrast to the existing Histogram of Oriented Gradients (HOG) that uses the histogram of the primary edge direction (i.e., gradient orientation) only, we additionally consider the histogram of the secondary edge direction, which provides more meaningful shape information related to the local texture. Experiments on popular facial expression datasets demonstrate the superior performance of the proposed HPED against existing descriptors in a person-independent environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4456-4475
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• 2021

The system for re-identifying persons is used to find and verify the persons crossing through different spots using various cameras. Much research has been done to re-identify the person by utilising features with deep-learned or hand-crafted information. Deep learning techniques segregate and analyse the features of their layers in various forms, and the output is complex feature vectors. This paper proposes a distinctive framework called Integrated Level Feature Pattern (ILFP) framework, which integrates local and global features. A new deep learning architecture named modified XceptionNet (m-XceptionNet) is also proposed in this work, which extracts the global features effectively with lesser complexity. The proposed framework gives better performance in Rank1 metric for Market1501 (96.15%), CUHK03 (82.29%) and the newly created NEC01 (96.66%) datasets than the existing works. The mean Average Precision (mAP) calculated using the proposed framework gives 92%, 85% and 98%, respectively, for the same datasets.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1997.04a
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• pp.100-100
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• 1997

To treat peptic ulcer diseases, many potent proton pump inhibitors have been developed for suppressing the gastric acid secretion in clinical patients. However, most of these agents have common irreversible mechanisms against H$\^$+/, K$\^$+/-ATPase which might be the cause of hypergastrinemia and ECL cell hyperplasia. Therefore, the development of new reversible inhibitors is prompted. In this study, we investigated the inhibitory mechanism of a newly synthesized proton pump inhibitor, YJA20379-8 using lyophilized hog gastric microsomes. YJA20379-8 inhibited K$\^$+/-stimulated H$\^$+/K$\^$+/-ATPase activity uncompetitively with respect to K$\^$+/, and in the other hand, showed competitive inhibitory pattern with ATP, respectively. From these data, we suggest that YJA20379-8 may be a proton pump inhibitor with a new inhibitory mechanism.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.271-278
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• 2012

Worldwide trends in animal welfare have resulted in an increased interest in individual management of sows housed in groups within hog barns. Estrus detection has been shown to be one of the greatest determinants of sow productivity. Purpose: We conducted this study to develop a method that can automatically detect the estrus state of a sow by selecting optimal texture parameters from images of a sow's pudendum and by optimizing the number of neurons in the hidden layer of an artificial neural network. Methods: Texture parameters were analyzed according to changes in a sow's pudendum in estrus such as mucus secretion and expansion. Of the texture parameters, eight gray level co-occurrence matrix (GLCM) parameters were used for image analysis. The image states were classified into ten grades for each GLCM parameter, and an artificial neural network was formed using the values for each grade as inputs to discriminate the estrus state of sows. The number of hidden layer neurons in the artificial neural network is an important parameter in neural network design. Therefore, we determined the optimal number of hidden layer units using a trial and error method while increasing the number of neurons. Results: Fifteen hidden layers were determined to be optimal for use in the artificial neural network designed in this study. Thirty images of 10 sows were used for learning, and then 30 different images of 10 sows were used for verification. Conclusions: For learning, the back propagation neural network (BPN) algorithm was used to successful estimate six texture parameters (homogeneity, angular second moment, energy, maximum probability, entropy, and GLCM correlation). Based on the verification results, homogeneity was determined to be the most important texture parameter, and resulted in an estrus detection rate of 70%.

• Korean Journal of Veterinary Research
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• v.43 no.2
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• pp.263-270
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• 2003

The objective of the present study was to investigate the use of fluid released from muscle samples as an alternative to serum for ELISA to detect classical swine fever(CSF) virus antibodies in slaughter pigs. The optimal correspondence between serum 1:20 OD values and muscle fluid OD values was achieved at a muscle fluid dilution of 1:2. Significant correlation was found between serum and neck muscle ELISA ($r_s=0.880$, p<0.0001, ${\kappa}=0.82$; specificity of 97.0% and sensitivity 90.6%). The semimembranous muscle showed similar correlation in CSF ELISA($r_s=0.877$, p<0.0001, ${\kappa}=0.75$; specificity of 94.1% and sensitivity 89.1%). High correlation was obtained between serum and mesenteric lymph node in the CSF ELISA ($r_s=0.937$, p<0.0001, ${\kappa}=0.87$; specificity of 97.1% and sensitivity 93.0%). Measmement agreement between serum ELISA and muscle fluid ELISA was calculated and expressed as limits of agreement. The correspondence of ELISA of serum and muscle fluid indicated limits of agreement. Above 95% of all muscle fluid values were distributed within this limits of agreement. Among the samples used for ELISA for detecting CSFV antibodies, mesenteric lymph node had the most correlation and agreement with serum ELISA. F-test for comparison of variances showed no significant difference between the serum and muscle fluid. In conclusion, muscle fluid is a useful postmortem alternative to serum to detect CSFV antibodies.

• Journal of KIISE
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• v.44 no.1
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• pp.44-50
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• 2017

Pedestrian detection, an important component of autonomous driving and driving assistant system, has been extensively studied for many years. In particular, image based pedestrian detection methods such as Hierarchical classifier or HOG and, deep models such as ConvNet are well studied. The evaluation score has increased by the various methods. However, pedestrian detection requires high sensitivity to errors, since small error can lead to life or death problems. Consequently, further reduction in pedestrian detection error rate of autonomous systems is required. We proposed a new method to detect pedestrians and reduce the error rate by using the Faster R-CNN with new developed pedestrian training data sets. Finally, we compared the proposed method with the previous models, in order to show the improvement of our method.