• 전기학회논문지
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• 제63권6호
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• pp.797-803
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• 2014

In this paper, 3D face recognition system is designed by using polynomial based on RBFNNs. In case of 2D face recognition, the recognition performance reduced by the external environmental factors such as illumination and facial pose. In order to compensate for these shortcomings of 2D face recognition, 3D face recognition. In the preprocessing part, according to the change of each position angle the obtained 3D face image shapes are changed into front image shapes through pose compensation. the depth data of face image shape by using Multiple Point Signature is extracted. Overall face depth information is obtained by using two or more reference points. The direct use of the extracted data an high-dimensional data leads to the deterioration of learning speed as well as recognition performance. We exploit principle component analysis(PCA) algorithm to conduct the dimension reduction of high-dimensional data. Parameter optimization is carried out with the aid of PSO for effective training and recognition. The proposed pattern classifier is experimented with and evaluated by using dataset obtained in IC & CI Lab.

• 전기학회논문지
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• 제64권6호
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• pp.900-911
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• 2015

In this paper, 3D face recognition model is designed by using Polynomial based RBFNN(Radial Basis Function Neural Network) and PNN(Polynomial Neural Network). Also recognition rate is performed by this model. In existing 2D face recognition model, the degradation of recognition rate may occur in external environments such as face features using a brightness of the video. So 3D face recognition is performed by using 3D scanner for improving disadvantage of 2D face recognition. In the preprocessing part, obtained 3D face images for the variation of each pose are changed as front image by using pose compensation. The depth data of face image shape is extracted by using Multiple point signature. And whole area of face depth information is obtained by using the tip of a nose as a reference point. Parameter optimization is carried out with the aid of both ABC(Artificial Bee Colony) and PSO(Particle Swarm Optimization) for effective training and recognition. Experimental data for face recognition is built up by the face images of students and researchers in IC&CI Lab of Suwon University. By using the images of 3D face extracted in IC&CI Lab. the performance of 3D face recognition is evaluated and compared according to two types of models as well as point signature method based on two kinds of depth data information.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.1373-1374
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• 2015

본 논문은 복잡한 비선형 모델링 방법인 다항식 기반 RBF 뉴럴 네트워크(Radial Basis Function Neural Network)와 벡터공간에서 임의의 비선형 경계를 찾아 두 개의 집합을 분류하는 방법으로 주어진 조건하에서 수학적으로 최적의 해를 찾는 SVM(Support Vector Machine)를 사용하여 3차원 얼굴인식 모델을 설계하고 두 모델의 3차원 얼굴 인식률을 비교한다. 3D스캐너를 통해 3차원 얼굴형상을 획득하고 획득한 영상을 전처리 과정에서 포인트 클라우드 정합과 포즈보상을 수행한다. 포즈보상 통해 정면으로 재배치한 영상을 Multiple Point Signature기법을 이용하여 얼굴의 깊이 데이터를 추출한다. 추출된 깊이 데이터를 RBFNN과 SVM의 입력패턴과 출력으로 선정하여 모델을 설계한다. 각 모델의 효율적인 학습을 위해 PCA 알고리즘을 이용하여 고차원의 패턴을 축소하여 모델을 설계하고 인식 성능을 비교 및 확인한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4534-4555
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• 2015

We propose a robust object cataloging method using multiple locally distinct heterogeneous features for aiding image retrieval. Due to challenges such as variations in object size, orientation, illumination etc. object recognition is extraordinarily challenging problem. In these circumstances, we adapt local interest point detection method which locates prototypical local components in object imageries. In each local component, we exploit heterogeneous features such as gradient-weighted orientation histogram, sum of wavelet responses, histograms using different color spaces etc. and combine these features together to describe each component divergently. A global signature is formed by adapting the concept of bag of feature model which counts frequencies of its local components with respect to words in a dictionary. The proposed method demonstrates its excellence in classifying objects in various complex backgrounds. Our proposed local feature shows classification accuracy of 98% while SURF,SIFT, BRISK and FREAK get 81%, 88%, 84% and 87% respectively.

• 한국통신학회논문지
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• 제29권8A호
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• pp.898-908
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• 2004

본 논문에서는 RACH(Random Access Channel) 구조에 적자한 WCDMA 역방향 링크 수신기용 고속 프리앰블 탐색기를 제안한다. WCDMA 시스템에서는 IS-95 시스템과 상이한 AISMA(Acquisition Indication Sense Multiple Access)방식을 적용하고 있으므로 UE에서 송신하는 RACH 프리앰블과 수신하는 AI(Acquisition indicators)의 시간 제한이 존재하며, 또한 RACH에 할당된 시그너쳐의 수가 제한적이므로 원활한 동작을 위하여 RACH 프리앰블에 대한 빠른 포착 확인이 요구된다. 본 논문에서 제안하는 프리앰블 탐색자는 2 안테나 기반의 구조로 빠른 포착(acquisition)을 위하여 radix-2 16 point FFT구조를 갖는 FHT(Fast Hadamard Transform)를 적용하였다. 본 논문의 FHT는 각 시그너쳐를 상관하는 일반적인 방식보다 최대 32배의 빠른 포착이 가능하다. 이러한 빠른 포착 능력을 기반으로 전체 프리앰블 4096칩에 대한 상관을 수행함으로써 포착 성능을 극대화하였다. 본 논문에서 제안한 프리앰블 탐색기는 WCDMA 기지국 모뎀 구현에 적용되었으며, 성능 분석은 Neyman-pearson 방식을 이용하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• Journal of Yeungnam Medical Science
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• 제39권2호
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• pp.98-107
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• 2022

Background: Stroke patients usually experience damage to multiple functions and a long rehabilitation period. Hence, there is a large volume of patient clinical information. It thus takes a long time for clinicians to identify the patient's information and essential pieces of information may be overlooked. To solve this, we stored the essential clinical information of stroke patients in a blockchain and implemented the blockchain technology using the Java programming language. Methods: We created a mini blockchain to store the medical information of patients using the Java programming language. Results: After generating a unique pair of public/private keys for identity verification, a patient's identity is verified by applying the Elliptic Curve Digital Signature Algorithm based on the generated keys. When the identity verification is complete, new medical data are stored in the transaction list and the generated transaction is verified. When verification is completed normally, the block hash value is derived using the transaction value and the hash value of the previous block. The hash value of the previous block is then stored in the generated block to interconnect the blocks. Conclusion: We demonstrated that blockchain can be used to store and deliver the patient information of stroke patients. It may be difficult to directly implement the code that we developed in the medical field, but it can serve as a starting point for the creation of a blockchain system to be used in the field.

• 생명과학회지
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• 제28권6호
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• pp.639-647
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• 2018

한국의 고급 양식대상 어종인 붉바리(Epinephelus akaara)로부터 새로운 heat shock protein (Hsp) 70을 동정하였다. 붉바리 Hsp70 (RgHsp70)의 cDNA는 RACE (rapid amplification of cDNA ends)법을 사용하였고, RgHsp70 cDNA의 전장은 2,152 bp이고, 5'-terminal untranslated region (UTR)은 105 bp, 3'-terminal UTR은 274 bp, 590개의 아미노산을 암호화하는 open reading frame (ORF)는 1,773 bp였으며, 분자무게(molecular weight)는 64.9 kDa 및 등전위값(isoelectric point, pI)은 5.2였다. 추정되는 아미노산 비교 및 계통발생학적 분석 결과, 다른 어종과 마찬가지로 Hsp70 고유의 signature를 포함하는 것을 비롯하여 높은 유사성을 나타내었으므로 RgHsp70이 Hsp70 family임을 확인할 수 있었다 RgHsp70 mRNA는 간과 두신 조직에서 높은 발현을 보였으며, 48시간 동안 수온별(21, 18, 15 및 $12^{\circ}C$) 노출 후 간 조직에서 대조구인 $21^{\circ}C$보다 $12^{\circ}C$에서 발현이 증가함을 확인하였다. 본 연구에서는, 수온이 하강함에 따라 RgHsp70 mRNA 발현에 주요한 영향을 미치는 것으로 보아, 수온변화에 따른 스트레스로 인해 발현의 변화를 나타내는 주요 스트레스성 단백질임을 확인할 수 있었다.