• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2006.05a
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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.

• Speech Sciences
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• v.11 no.3
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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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• 2005.06a
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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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• v.1 no.1
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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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.9
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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.

• The Journal of Korea Robotics Society
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• v.11 no.2
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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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• v.6 no.4
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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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• v.13 no.2
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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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.102-110
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• 2017

In this paper, we have implemented an real-time adaptive feedback cancellation(AFC) algorithm that can be applied to multi-channel digital hearing aid. Multichannel digital hearing aid typically use the FFT filterbank based Wide Dynamic Range Compression(WDRC) algorithm to compensate for hearing loss. The implemented real-time acoustic feedback cancellation algorithm has one integrated structure using the same FFT filter bank with WDRC, which can be beneficial in terms of computation affecting the hearing aid battery life. In addition, when the AFC fails to operate due to nonlinear input and output, the reduction gain is applied to improve robustness in practical environment. The implemented algorithm can be further improved by adding various signal processing algorithm such as speech enhancement.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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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.