• International Journal of Contents
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• 제2권3호
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• pp.27-32
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• 2006

We present an effective algorithm for automatic tracing of retinal vessel structure and vascular landmark extraction of bifurcations and ending points. In this paper we deal with vascular patterns from RGB images for personal identification. Vessel tracing algorithms are of interest in a variety of biometric and medical application such as personal identification, biometrics, and ophthalmic disorders like vessel change detection. However eye surface vasculature tracing in RGB images has many problems which are subject to improper illumination, glare, fade-out, shadow and artifacts arising from reflection, refraction, and dispersion. The proposed algorithm on vascular tracing employs multi-stage processing of ten-layers as followings: Image Acquisition, Image Enhancement by gray scale retinal image enhancement, reducing background artifact and illuminations and removing interlacing minute characteristics of vessels, Vascular Structure Extraction by connecting broken vessels, extracting vascular structure using eight directional information, and extracting retinal vascular structure, and Vascular Landmark Extraction by extracting bifurcations and ending points. The results of automatic retinal vessel extraction using jive different thresholds applied 34 eye images are presented. The results of vasculature tracing algorithm shows that the suggested algorithm can obtain not only robust and accurate vessel tracing but also vascular landmarks according to thresholds.

• 전자공학회논문지B
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• 제33B권11호
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• pp.83-96
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• 1996

On PR-IV magnetic recording systems, the maximum likelihood sequence detection (MLSD) method is optimum. But it has the problem of the complexity of the structure. The three level detection (TLD) method can be used, which has simpler structure than MLSD, but requires almost twice of power to achieve the same probbility of error as MLSD does. Therefore a new detection method (error controlled detection: ECD) is proposed which has much simpler structure than MLSD and gives much better performance than TLD. The simulation resutls show that the performance of ECD is better than that of TLD by approximaterly 0.5~1.3dB both in linear and nonlinear channels.

• Smart Structures and Systems
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• 제16권3호
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• pp.435-457
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• 2015

The most widely known form of multifunctional aircraft structure is smart structures for structural health monitoring (SHM). The aim is to provide automated systems whose purposes are to identify and to characterize possible damage within structures by using a network of actuators and sensors. Unfortunately, environmental and operational variability render many of the proposed damage detection methods difficult to successfully be applied. In this paper, an original robust damage detection approach using output-only vibration data is proposed. It is based on independent component analysis and matrix perturbation analysis, where an analytical threshold is proposed to get rid of statistical assumptions usually performed in damage detection approach. The effectiveness of the proposed SHM method is demonstrated numerically using finite element simulations and experimentally through a conformal load-bearing antenna structure and composite plates instrumented with piezoelectric ceramic materials.

• Smart Structures and Systems
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• 제18권6호
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• pp.1233-1250
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• 2016

Cracks in plate-like structures are some of the main reasons for destruction of the entire structure. In this study, a novel two-stage methodology is proposed for damage detection of flexural plates using an optimized artificial neural network. In the first stage, location of damages in plates is investigated using curvature-moment and curvature-moment derivative concepts. After detecting the damaged areas, the equations for damage severity detection are solved via Bat Algorithm (BA). In the second stage, in order to efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, multiple damage location assurance criterion index based on the frequency change vector of structures are evaluated using properly trained cascade feed-forward neural network (CFNN) as a surrogate model. In order to achieve the most generalized neural network as a surrogate model, its structure is optimized using binary version of BA. To validate this proposed solution method, two examples are presented. The results indicate that after determining the damage location based on curvature-moment derivative concept, the proposed solution method for damage severity detection leads to significant reduction of computational time compared with direct finite element method. Furthermore, integrating BA with the efficient approximation mechanism of finite element model, maintains the acceptable accuracy of damage severity detection.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.989-997
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• 2018

Massive event stream brings us great challenges in its volume, velocity, variety, value and veracity. Picking up some valuable information from it often faces with long detection time, high memory consumption and low detection efficiency. Aiming to solve the problems above, an efficient complex event detection method based on NFA_HTS (Nondeterministic Finite Automaton_Hash Table Structure) is proposed in this paper. The achievement of this paper lies that we successfully use NFA_HTS to realize the detection of complex event from massive RFID event stream. Specially, in our scheme, after using NFA to capture the related RFID primitive events, we use HTS to store and process the large matched results, as a result, our scheme can effectively solve the problems above existed in current methods by reducing lots of search, storage and computation operations on the basis of taking advantage of the quick classification and storage technologies of hash table structure. The simulation results show that our proposed NFA_HTS scheme in this paper outperforms some general processing methods in reducing detection time, lowering memory consumption and improving event throughput.

• 센서학회지
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• 제19권6호
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• pp.403-420
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• 2010

Nano and micro structure-based biosensors are promising tool for label-free detection of biomolecular interactions with great accuracy. This review gives a brief survey on nano and micro platforms to sense a variety of analytes such as DNA, proteins and viruses. Among incredible nano and micro structure for bio-analytical applications, the scope of this paper will be limited to micro and nano resonators and nanowire field-effect transistors. Nanomechanical motion of the resonators transducers biological information to readable signals. They are commonly combined with an optical, capacitive or piezo-resistive detection systems. Binding of target molecule to the modified surface of nanowire modulates the current of the nanowire through electrical field-effect. Both detection methods have advantages of label-free, real-time and high sensitive detection. These structures can be extended to fabricate array-type sensors for multiplexed detection and high-throughput analysis. The biosensors based on these structures will be applied to lab-on-a-chip platforms and point-of-care diagnostics. Basic concepts including detection mechanisms and trends in their fields will be covered in this review.

• 한국공작기계학회논문집
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• 제14권4호
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• pp.49-54
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• 2005

Measuring defects on the inside and on the surface of a steel structure is very important technology in order to predict the life span of the structure. In particular, a place with a high probability that it may contain defects is a welded part and it is very important to check defects in the part, absence/presence of non-uniform substances, its shape, and the location. Many non-destructive tests can be applied, but the ultrasonic flow detection test is widely used with some advantages. The ultrasonic flow detection test, however, cannot be applied when there is a problem by a contact medium between PZT and a specimen, in case of a small and complicated shape or a moving object or when the specimen is hot. In this study, to solve the problems of the contact ultrasonic flow detection test, the non-contact ultrasonic flow detection test for sending/receiving ultrasonic waves using lasers was described. I intended to develop a non-destructive detection system applying the laser application ultrasonic test to a steel structure by detecting the defects inside of and on the surface of the specimen.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 추계공동학술대회
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• pp.239-254
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• 2006

In mold structure machining, tool interference is a phenomenon which results from a collision between a blade of tool and a workpiece. Also tool collision is a phenomenon which results from a collision of holder with the object to be machined. These phenomena not only cause damages to mold and tool but also increase machining time and cost. To detect a collision of a tool to mold structure, first of all, the mold structure and a tool must be defined with famous geometric models such CSG, B-rep, and Voxel. A tool is defined as a combination of the blade, the shank, and the holder. This thesis reviews various collision detection algorithms using z-map and computer 3D graphic collision detection algorithms for the tool in machining a mold structure.

• Smart Structures and Systems
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• 제23권4호
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• pp.393-403
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• 2019

Applying more features gives us better accuracy in modeling; however, increasing the inputs causes the curse of dimensions. In this paper, a new structure has been proposed for fault detecting and identifying (FDI) of high-dimensional systems. This structure consist of two structure. The first part includes Auto-Encoders (AE) as Deep Neural Networks (DNNs) to produce feature engineering process and summarize the features. The second part consists of the Local Model Networks (LMNs) with LOcally LInear MOdel Tree (LOLIMOT) algorithm to model outputs (multiple models). The fault detection is based on these multiple models. Hence the residuals generated by comparing the system output and multiple models have been used to alarm the faults. To show the effectiveness of the proposed structure, it is tested on single-shaft industrial gas turbine prototype model. Finally, a brief comparison between the simulated results and several related works is presented and the well performance of the proposed structure has been illustrated.

• 대한전자공학회논문지SD
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• 제49권7호
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• pp.30-38
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• 2012

본 논문은 mmWave OFDM-기반 WPAN 시스템을 위한 패킷 검출과 주파수 옵셋 추정 및 보정 구조를 제안하고 성능 분석 결과를 보여준다. 패킷 검출 블록은 반복된 훈련 심볼의 자기상관 관계를 이용하고 상관된 값이 일정 문턱 값을 넘을 때 패킷 시작점을 검출하는데 사용된다. 적용한 자기상관 알고리즘 구조는 기존의 패킷검출에 사용한 알고리즘에 비해 간단하게 하드웨어를 구현 할 수 있다. 주파수 옵셋 추정 구조는 기존구조와는 다른 위상 천이 처리 블록, 하드웨어 사이즈를 줄여주는 내부비트 줄임 블록 및 look-up table의 사이즈를 줄인 주파수 옵셋 조정 블록을 설계하였다. 추정된 주파수 옵셋 값은 설계한 보정 블록을 통해 수신 신호를 보정함으로써 주파수 옵셋에 대한 영향을 줄일 수 있다. 설계 검증툴을 이용한 성능 분석 결과 제안된 구조는 하드웨어 구현복잡도가 감소함을 보여 주었고 기존구조에 비하여 게이트수가 감소함을 보였다. 따라서 제안된 구조는 OFDM-기반 WPAN 시스템의 초기 동기화 과정에 적용 될 수 있고 고속 저전력 WPAN칩에 사용 될 수 있다.