• BMB Reports
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• 제46권7호
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• pp.358-363
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• 2013

In this paper, we firstly reported a C-type lectin cDNA clone of 1029 bps from the larvae of A. Pernyi (Ap-CTL) using PCR and RACE techniques. The full-length cDNA contains an open reading frame encoding 308 amino acid residues which has two different carbohydrate-recognition domains (CRDs) arranged in tandem. To investigate the biological activities in the innate immunity, recombinant Ap-CTL was expressed in E. coli with a 6-histidine at the amino-terminus (Ap-rCTL). Besides acted as a broad-spectrum recognition protein binding to a wide range of PAMPs and microorganisms, Ap-rCTL also had the ability to recognize and trigger the agglutination of bacteria and fungi. In the proPO activation assay, Ap-rCTL specifically restored the PO activity of hemolymph blocked by anti-Ap-rCTL antibody in the presence of different PAMPs or microorganisms. In summary, Ap-rCTL plays an important role in insect innate immunity as an pattern recognition protein.

• 제어로봇시스템학회논문지
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• 제18권10호
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• pp.928-933
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• 2012

In this paper, the IR and compass sensors for the underwater system were used. The walls of the water tank have been recognized and avoided treating the walls as obstacles by the bio-mimetic underwater robot. This paper is consists of two parts: 1.The hardware part for the IR and compass sensors and 2.The software part for obstacle avoidance algorithm while the bio-mimetic robot is swimming with the obstacle recognition. Firstly, the hardware part controls through the RS-485 communications between a microcontroller and the bio-mimetic underwater robot. The software part is simulated for obstacle recognition and collision avoidance based upon the data from IR and compass sensors. Actually, the bio-mimetic underwater robot recognizes where is the obstacle as well as where is the bio-mimetic robot itself while it is moving in the water. While the underwater robot is moving at a constant speed recognizing the wall of water tank as an obstacle, an obstacle avoidance algorithm is applied for the wall following swimming based upon the IR and compass sensor data. As the results of this research, it is concluded that the bio-mimetic underwater robot can follow the wall of the water tank efficiently, while it is avoiding collision to the wall.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.935-939
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• 2003

The emotion recognition is one of the most significant interface technologies which make the high level of human-machine communication possible. The central nervous system stimulated by emotional stimuli affects the autonomous nervous system like a heart, blood vessel, endocrine organs, and so on. Therefore bio-signals like HRV, ECG and EEG can reflect one' emotional state. This study investigates the correlation between emotional states and bio-signals to realize the emotion recognition. This study also covers classification of human emotional states, selection of the effective bio-signal and signal processing. The experimental results presented in this paper show possibility of the emotion recognition.

• Bulletin of the Korean Chemical Society
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• 제30권6호
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• pp.1247-1251
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• 2009

The recognition of neutral aromatic substrates by different neutral calix[4]arene receptors 1, 2, and 3 was studied by NMR spectroscopy. The stoichiometry is 1:1 in all cases as was confirmed by jobs plot. Owing to the deep cavity, 1 affords stronger binding abilities for substrate 4 and 5, while all receptors remained inert for substrates 6 and 7. The binding constants determined by $^1H$ NMR titration show that the recognition of substrate 4 by 1 gives strongest complexation ($K_a\;of\;9.8\;{\times}\;102\;M^{-1}$).

• BMB Reports
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• 제46권5호
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• pp.264-269
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• 2013

Pattern recognition receptors are known to participate in the activation of Prophenoloxidase system. In this study, a 1,3-${\beta}$-D-glucan recognition protein was detected for the first time in Antheraea pernyi larvae (Ap-${\beta}GRP$). Ap-${\beta}GRP$ was purified to 99.9% homogeneity from the hemolymph using traditional chromatographic methods. Ap-${\beta}GRP$ specifically bind 1,3-${\beta}$-D-glucan and yeast, but not E. coli or M. luteus. The 1,3-${\beta}$-D-glucan dependent phenoloxidase (PO) activity of the hemolymph inhibited by anti-Ap-${\beta}GRP$ antibody could be recovered by addition of purified Ap-${\beta}GRP$. These results demonstrate that Ap-${\beta}GRP$ acts as a biosensor of 1,3-${\beta}$-Dglucan to trigger the Prophenoloxidase system. A trace mount of 1,3-${\beta}$-D-glucan or Ap-${\beta}GRP$ alone was unable to trigger the proPO system, but they both did. Ap-${\beta}GRP$ was specifically degraded following the activation of proPO with 1,3-${\beta}$-Dglucan. These results indicate the variation in the amount of Ap-${\beta}GRP$ after specific immune challenge in A. pernyi hemolymph is an important regulation mechanism to immune response.

• 정보처리학회논문지B
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• 제11B권7호
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• pp.759-768
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• 2004

생체인식기술을 응용한 제품이 다양해지면서 상호운용성의 문제가 제기되어 국제표준화가 진행중인 BioAPl(Biometric Application Pro-gramming Interface)를 기반으로 한 생체인식 제품의 개발이 증대되고 있다. 그러나 BioAPl를 적용하여 개발된 제품에 대한 성능 측정 및 표준규격의 적합성 여부에 대한 신뢰성 있는 평가 도구가 마련되어 있지 않은 상태이다. 본 논문은 생체인식시스템이 BioAPl 규격의 요구사항 및 기준에 얼마나 만족하여 개발하였는가를 검증하기 위한 적합성시험 방법을 연구하였다. 제안된 적합성 시험기술의 첫 번째는 BioAPl명세서가 제공하는 각 함수들을 제대로 구현하였는가에 대한 확인과 사용여부를 평가하는 것이다. 이것은 응용에서 APl(Application Provider Inter-face)함수를 호출하면 프레임워크를 통해 BSP(Biometric Service Provider)를 실행하는 것으로 이때 파라미터와 선행함수의 선택이 필요하다. 두 번째는 BioAPl의 해당 테스트케이스를 분석하여 모듈관리, 핸들기능, 검증기능에 대한 시나리오를 평가하는 것이다. 실험은 BioAPl 컨소시엄에서 제공하는 샘플프로그램과 상용 지문검증시스템의 BSP를 사용하여 제안하는 적합성 평가 방법에 대한 실험을 수행하였다. 이에 따라 BioAPl를 기반으로 한 BSP들이 요구사항에 적합하게 개발되었는지를 판단할 수 있었다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제3권8호
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• pp.299-308
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• 2014

신체 동작, 얼굴 표정과 같이 아주 복잡한 생체 패턴을 인식하고 분류하는 인간의 능력을 모방한 정보처리 컴퓨팅 관련 연구가 최근 다수 등장하고 있다. 특히 컴퓨터비전 분야에서는 인간의 뛰어난 인지 능력 중 상황정보 없이 시각시퀀스에서 동작을 분류하는 기능을 통해 시공간적 패턴 코딩과 빠른 인식 방법을 이해하고자 한다. 본 연구는 비디오 시퀀스상의 동작인식에 생물학적 시각인지과정의 영향을 받은 생체 기반 컴퓨터비전 모델을 제시하였다. 제안 모델은 이미지 시퀀스에서 동작을 검출하고 시각 패턴을 판별하는 데 생체 시각처리과정의 신경망 구조 단계를 반영하였다. 실험을 통해 생체 기반 동작인식 모델이 인간 시각인지 처리의 여러 가지 속성을 고려했을 뿐 아니라 기존 동작인식시스템에 비해 시간 정합성이 뛰어나며 시간 변화에 강건한 분류 능력을 보임을 알 수 있다. 제안 모델은 지능형 로봇 에이전트와 같은 생체 기반 시각정보처리 시스템 구축에 기여할 수 있다.

• 대한금속재료학회지
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• 제46권1호
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• pp.6-12
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• 2008

Peptides with specific sequences against $LaPO_4$ and $TiO_2$ nanoparticles were discovered through peptide phage display technique as an application to biomolecular recognition of inorganic materials. Sequencing results showed that a motif consisting of serine and proline was commonly expressed in specific sequences. It was postulated that serine directly bound to nanoparticles using its terminal hydroxyl (OH) group. In this sense, oxygen atom seemed to work as a ligand to metal ions and hydrogen atom as a H-bond donor, was thought to bind to the oxygen atoms or the hydroxyl groups on particle surface. Also, it was expected that proline assists serine to make an ideal van der Waals contact between serine and nanoparticles, which optimizes the binding of peptide onto surface.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권4호
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• pp.819-833
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• 2013

Computing global features based on local features using a bio-inspired framework has shown promising performance. However, for some tough applications with large intra-class variances, a single local feature is inadequate to represent all the attributes of the images. To integrate the complementary abilities of multiple local features, in this paper we have extended the efficacy of the bio-inspired framework, HMAX, to adapt heterogeneous features for global feature extraction. Given multiple global features, we propose an approach, designated as parameterized metric learning, for high dimensional feature fusion. The fusion parameters are solved by maximizing the canonical correlation with respect to the parameters. Experimental results show that our method achieves significant improvements over the benchmark bio-inspired framework, HMAX, and other related methods on the Caltech dataset, under varying numbers of training samples and feature elements.

• Nutrition Research and Practice
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• 제13권6호
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• pp.521-528
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• 2019

BACKGROUND/OBJECTIVES: The aim of this study was to develop Korean food image detection and recognition model for use in mobile devices for accurate estimation of dietary intake. MATERIALS/METHODS: We collected food images by taking pictures or by searching web images and built an image dataset for use in training a complex recognition model for Korean food. Augmentation techniques were performed in order to increase the dataset size. The dataset for training contained more than 92,000 images categorized into 23 groups of Korean food. All images were down-sampled to a fixed resolution of $150{\times}150$ and then randomly divided into training and testing groups at a ratio of 3:1, resulting in 69,000 training images and 23,000 test images. We used a Deep Convolutional Neural Network (DCNN) for the complex recognition model and compared the results with those of other networks: AlexNet, GoogLeNet, Very Deep Convolutional Neural Network, VGG and ResNet, for large-scale image recognition. RESULTS: Our complex food recognition model, K-foodNet, had higher test accuracy (91.3%) and faster recognition time (0.4 ms) than those of the other networks. CONCLUSION: The results showed that K-foodNet achieved better performance in detecting and recognizing Korean food compared to other state-of-the-art models.