• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2006년도 춘계학술대회 논문집
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• pp.429-433
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• 2006

High Temperature deformation behavior of newly developed beta-gamma TiAl alloy was investigated in this study. The optimum processing condition was investigated with the aid of Dynamic Materials Model (DMM). Processing maps representing the efficiency of power dissipation for microstructural evolution and instability were constructed utilizing the results of hot compression test at temperatures ranging from $1000^{\circ}C$ to $1200^{\circ}C$ and strain rate ranging from $10^{-4}/s$ to $10^2/s$. The Artificial Neural Network (ANN) simulation was adopted to consider the deformation heating. With the help of processing map and microstructural analysis, the optimum processing condition was presented and the role of $\beta$ phase was also discussed in this study.

• 음성과학
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• 제11권3호
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• pp.175-180
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• 2004

In case of the hearing impairment with tinnitus and increased sound sensitivity, it is known that the patients tend to appeal the psychologically oriented social handicap rather than communication disability. The audiologist who is responsible for such patients in aural rehabilitation should pay special attention to the counseling techniques including tinnitus retain therapy (TRT), ear protector, noise generator, or specific acoustic training based on close cooperation and rapport. And then the audiologist should try to lessen their reaction to the tinnitus by using a hearing aid. This therapies tries to focus not a. total approach but a treatment to lessen the severity of tinnitus. This paper as a case report that a unilateral sharply slopped sensorineural hearing impaired person with tinnitus and increased sound sensitivity by using four channel digital signal processing (DSP) hearing aid with programming increment at low level (PILL).

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.190-195
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• 2005

The hearing aid chip described in this paper is an analog & digital mixed system. The design focuses on the$\mu$DSP core. This $\mu$DSP core includes internal time delays to two inputs from front and rear microphones. The paper consists of two parts; one is the composure and signal processing algorithm of digital hearing aids and the other is Verilog HDL codes for$\mu$DSP cores. All digital modules in the design were coded and synthesized by Verilog HDL codes which were verified by Mentor Graphics and Synopsis semiconductor chip design tools.

• International Journal of Advanced Culture Technology
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• 제1권1호
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• pp.11-14
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• 2013

In this paper, we propose a prototype of the SpeechWeb application using the information selection agent. We describe its design and implementation method and illustrated the processing results with the aid of some screenshots. Proposed SpeechWeb application presents the associated contents to the user by the aid of dynamic voice-anchors. These contents are presented using the apriori algorithm, which is one of data mining techniques. The application is better than the existing user-initiative structure from the viewpoint of making the user's interesting induction. Moreover, we believe that our proposed application is effective in information retrieval through wired and wireless telephone networks.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권9호
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• pp.657-662
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• 2004

The low-power design of the digital hearing aid is indispensable to achieve the compact portable device with long battery duration. In this paper, new low-power adaptive filter structure is proposed based on distributed arithmetic(DA). By modifying the DA technique, the proposed decimation filter structure can significantly reduce the power consumption and implementation area. Through Verilog-HDL coding, cell occupation of the proposed structure is reduced to 33.49% in comparison with that of the conventional multiplier structure. Since Verilog-HDL simulation processing time of the two structures are same, it is assumed that the power consumption or implementation area is proportional to the cell occupation in the simulation.

• 로봇학회논문지
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• 제11권2호
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• pp.108-114
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• 2016

This paper presents a sensor-based cane mechanism for walking aid of the visually impaired person. We also describe an approach to decide properly the length of the specified cane mechanism. The cane mechanism has some sensors to identify the possibility of a collision between the cane user and an object and/or a person, and a signal processing unit that enables the user to recognize such a collision is attached in the mechanism. Thus, the walker using this cane can recognize in advance the possibility of such a collision in his walking process. Consequently, it is helpful for the visually impaired person to walk on a pedestrian road safely. The feature of the proposed cane mechanism and its availability have been shown through experimental works in a typical walking environment.

• Journal of Electrical Engineering and Technology
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• 제6권4호
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• pp.573-579
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• 2011

To meet the scalability and performance requirements of data analyses, which often involve voluminous data, efficient parallel or concurrent algorithms and frameworks are essential. We present a high-performance Korean morphological analyzer which employs the MapReduce framework on the graphics processing unit (GPU). MapReduce is a programming framework introduced by Google to aid the development of web search applications on a large number of central processing units (CPUs). GPUs are designed as a special-purpose co-processor. Their programming interfaces are typically formulated for graphics applications. Compared to CPUs, GPUs have greater computation power and memory bandwidth; however, GPUs are more difficult to program because of the design of their architectures. The performance of the Korean morphological analyzer using the MapReduce framework on the GPU is evaluated in comparison with the CPU-based model. The proposed Korean Morphological analyzer shows promising scalable performance on distributed computing with the GPU.

• Journal of Information Processing Systems
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• 제13권2호
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• pp.285-304
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• 2017

Big data information and pattern analysis have applications in many industrial sectors. To reduce energy consumption effectively, the eco-driving method that reduces the fuel consumption of vehicles has recently come under scrutiny. Using big data on commercial vehicles obtained from digital tachographs (DTGs), it is possible not only to aid traffic safety but also improve eco-driving. In this study, we estimate fuel consumption efficiency by processing and analyzing DTG big data for commercial vehicles using parallel processing with the MapReduce mechanism. Compared to the conventional measurement of fuel consumption using the On-Board Diagnostics II (OBD-II) device, in this paper, we use actual DTG data and OBD-II fuel consumption data to identify meaningful relationships to calculate fuel efficiency rates. Based on the driving pattern extracted from DTG data, estimating fuel consumption is possible by analyzing driving patterns obtained only from DTG big data.

• 한국정보전자통신기술학회논문지
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• 제10권1호
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• pp.102-110
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• 2017

본 논문에서는 다채널 디지털 보청기에 적용 가능한 적응 음향 궤환 제거(Adaptive Feedback Cancellation : AFC) 알고리즘을 실시간으로 구현한다. 다채널 디지털 보청기는 일반적으로 난청 보상을 위해 FFT 필터뱅크 기반 광역 동범위압축(Wide Dynamic Range Compression) 알고리즘을 사용한다. 구현한 실시간 음향 궤환 제거 알고리즘은 다채널 디지털 보청기와 동일한 FFT 필터뱅크를 사용하여 WDRC와 함께 하나의 통합된 구조를 가짐으로써 보청기 배터리 수명에 영향을 미치는 연산량 측면에서 이득을 볼 수 있었다. 구현된 음향 궤환 제거 알고리즘은 고정 및 변화하는 음향 궤환 경로를 실시간으로 추정하여 보청기 출력 신호의 품질을 향상시킴을 확인하였다. 또한 비선형적인 입, 출력에 의해 음향 궤환 제거기가 정상적으로 작동하지 못해 출력 신호의 포화가 일어날 경우 감소 이득을 적용하여 시스템의 안정성을 높이고자 하였다. 결과적으로 다양한 실제 사용 환경에서 강건하게 동작하는 알고리즘을 구현할 수 있었다. 본 알고리즘은 추후 음질 개선 알고리즘 등 다양한 기능의 추가 구현이 용이하다.

• 전기학회논문지
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• 제63권4호
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• pp.526-533
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• 2014

In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.