• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2015년도 제52차 하계학술대회논문집 23권2호
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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.

• 센서학회지
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• 제29권3호
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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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• 제22권2호
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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.

• 한국전자파학회논문지
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• 제30권3호
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• pp.236-242
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• 2019

UWB(Ultra-WideBand)는 수 GHz 이상 광대역의 매우 짧은 신호를 이용하여 고속의 송수신이 가능한 기술로서, 최근 레이다 분야에 응용되고 있다. IR(Impulse Radio)-UWB 레이다의 경우, 높은 분해능으로 모션 인식 분야에도 적용되고 있다. 따라서, 본 논문에서는 IR-UWB 레이다를 이용한 모션 인식에 관한 연구를 진행하였다. 모션에 대한 데이터를 획득하기 위해 개발 환경을 구축하고, 성능 향상을 위한 신호처리 알고리즘을 구현하였다. 그리고 신호처리 결과를 바탕으로 모션의 특징 추출과 학습을 통해 성능을 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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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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• 제15권12호
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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.

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 1997년도 춘계학술대회
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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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• 제37권4호
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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%.

• 대한수의학회지
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• 제43권2호
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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.

• 정보과학회 논문지
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• 제44권1호
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• pp.44-50
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• 2017

보행자 검출은 수년간 광범위하게 연구된 문제이며, 자율주행 자동차와 운전자 보조시스템에서 매우 중요한 역할을 차지하고 있다. 특히, 계층적 분류기[1]와 Histogram of Gradient[2]특징벡터 등 영상기반의 보행자 검출기법과 ConvNet같이 deep model을 이용하여 검출하는 기법들이 연구되었고 검출성능은 꾸준히 상승하였다. 하지만 보행자 검출은 작은 오차에도 생명과 연관된 문제를 야기할 수 있기 때문에, 자율주행 시스템의 보행자검출 오차율은 더욱 낮출 필요가 있다. 따라서 본 연구에서는 Faster R-CNN 응용 기법에 새로 개발한 데이터 학습 모델을 적용하여 보행자 검출 오류를 줄이는 기법을 제안한다. 그리고 기존에 제안된 모델들과 비교를 통해, 보행자 검출에 있어 제안된 방법의 우수성을 보이고자 한다.