• Journal of Powder Materials
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• v.16 no.1
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• pp.56-62
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• 2009

The degree of WC decomposition and hardness of thermally sprayed WC-Co coatings are important factors determining the wear resistance of the coatings. In order to minimize the degree of decomposition and to increase hardness, the effects of processing parameters of high velocity oxyfuel(HVOF) spraying on various characteristics of nanostructured WC-12Co coating have been evaluated by an experimental design method. The HVOF sprayed WC-12Co coatings consisted of various carbide phases including WC, $W_2C$ and $W_3Co_3C$, with a much reduced carbon content. The degree of WC decomposition and decarburization was affected by changing barrel length and spray distance. The hardness of WC-Co coatings was strongly related to droplet temperature at substrate, and increased with increasing fuel addition and/or decreasing spray distance. The effective control of processing parameters was discussed in detail for manufacturing a high performance WC-Co coating.

• Journal of Powder Materials
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• v.18 no.4
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• pp.340-346
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• 2011

In order to improve the weak mechanical properties of cast Mg alloys, Mg-$Zn_1Y_2$ (at%) alloy powders were synthesized using gas atomization, a typical rapid solidification process. The powders consist of fine dendrite structures less than 3 ${\mu}m$ in arm spacing. In order to fabricate a bulk form, the Mg powders were compacted using magnetic pulse compaction (MPC) under various processing parameters of pressure and temperature. The effects of the processing parameters on the microstructure and mechanical properties were systematically investigated.

• Computers and Concrete
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• v.3 no.6
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• pp.423-437
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• 2006

Stress wave propagation through concrete is simulated by finite element analysis. The concrete medium is modeled as a homogeneous material with smeared properties to investigate and establish the suitable finite element analysis method (explicit versus implicit) and analysis parameters (element size, and solution time increment) also suitable for rigorous investigation. In the next step, finite element analysis model of the medium is developed using a digital image processing technique, which distinguishes the mortar and aggregate phases of concrete. The mortar and aggregate phase topologies are, then, directly mapped to the finite element mesh to form a heterogeneous concrete model. The heterogeneous concrete model is then used to simulate wave propagation. The veracity of the model is demonstrated by evaluating the intrinsic parameters of nondestructive ultrasonic pulse velocity testing of concrete. Quantitative relationships between aggregate size and testing frequency for nondestructive testing are presented.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.761-764
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• 2000

This paper presents a Fuzzy Neural Network (FNN) system to decide whether or not the right information of lanes can be extracted from gray-level images of road scene. The decision of noisy level of input images has been required because much noises usually deteriorates the performance of feature detection based on image processing and lead to erroneous results. As input parameters to FNN, eight noisiness indexes are constructed from a cumulative distribution function (CDF) and proved the indexes being classifiers of images as the good and the bad corrupted by sources of noise by correlation analysis between input images and the indexes. Considering real-time processing and discrimination efficiency, the proposed FNN is structured by eight input parameters, three fuzzy variables and single output. We conduct much experiments and show that our system has comparable performance in terms of false-positive rates.

• Tribology and Lubricants
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• v.23 no.1
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• pp.29-36
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• 2007

It necessarily follows that wear particles are generated through a friction and wear in a mechanical moving system. The wear particles are relative to the failure and the life of machine elements directly. To analyze the wear particle, its shape characteristics were calculated quantitative values such as diameter, roundness and fractal parameters by digital image processing. In this study, the histograms of shape parameters of wear particles were used for the purpose of analyzing the distribution of wear particles in various conditions. We consider that the histogram of shape parameter can be effectively represented to study a wear mechanism.

• Journal of Welding and Joining
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• v.8 no.2
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• pp.58-69
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• 1990

In conventional arc welding, position error of the weld torch with respect to the weld seam and variation of groove dimension are induced by inaccurate fitup and fixturing. In this study, a vision system has been developed to recognize and compensate the position error and dimensional inaccuracy. The system uses a structured laser light illuminated on the weld groove and perceived by a C.C.D camera. A new algorithm to detect the edge of the reflected laser light is introduced for real time processing. The developed system was applied to arbitarary weld paths with various types of joint in arc welding process. The experimental results show that the proposed system can detect the weld groove parameters within good accuracy and yield good tracking performance.

• The Journal of the Acoustical Society of Korea
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• v.16 no.1E
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• pp.57-63
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• 1997

In this paper, we investigated performance of a vocabulary-independent speech recognizer with speaker adaptation. The vocabulary-independent speech recognizer does not require task-oriented speech databases to estimate HMM parameters, but adapts the parameters recursively by using input speech and recognition results. The recognizer has the advantage that it relieves efforts to record the speech databases and can be easily adapted to a new task and a new speaker with different recognition vocabulary without losing recognition accuracies. Experimental results showed that the vocabulary-independent speech recognizer with supervised offline speaker adaptation reduced 40% of recognition errors when 80 words from the same vocabulary as test data were used as adaptation data. The recognizer with unsupervised online speaker adaptation reduced abut 43% of recognition errors. This performance is comparable to that of a speaker-independent speech recognizer trained by a task-oriented speech database.

• Journal of Mechanical Science and Technology
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• v.20 no.5
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• pp.583-590
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• 2006

It is hard to inspect the state of lubrication of an automobile transmission visually. Thus, it is necessary to develop a new inspection method. Wear debris can be collected from the lubricants of an operating transmission of an automobile, and its morphology will be directly related to the friction condition of the interacting materials from which the wear debris originated in the lubricated transmission. In this study, wear debris in lubricating oil are extracted by membrane filter $(0.45{\mu}m)$, and the quantitative values of shape parameters of wear debris are calculated by digital image processing. These shape parameters are studied and identified by an artificial neural network algorithm. The results of the study may be applicable to the prediction and diagnosis of the operating condition of transmission gear.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.2
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• pp.37-41
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• 2014

The vector Taylor series (VTS) based method usually employs clean speech Hidden Markov Models (HMMs) when compensating speech feature vectors or adapting the parameters of trained HMMs. It is well-known that noisy speech HMMs trained by the Multi-condition TRaining (MTR) and the Multi-Model-based Speech Recognition framework (MMSR) method perform better than the clean speech HMM in noisy speech recognition. In this paper, we propose a method to use the noise-adapted HMMs in the VTS-based speech feature compensation method. We derived a novel mathematical relation between the train and the test noisy speech feature vector in the log-spectrum domain and the VTS is used to estimate the statistics of the test noisy speech. An iterative EM algorithm is used to estimate train noisy speech from the test noisy speech along with noise parameters. The proposed method was applied to the noise-adapted HMMs trained by the MTR and MMSR and could reduce the relative word error rate significantly in the noisy speech recognition experiments on the Aurora 2 database.

• Journal of Biomedical Engineering Research
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• v.17 no.2
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• pp.155-164
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• 1996

In the clinical environment, measurements of some characteristics of the skeletal muscle are currently used to assess the severity of a neuromuscular disease or in some cases to assist in making a diagnosis. But a quantitative method of evaluation has not yet been introduced satisfactorily. In this paper, the skeletal EMG(biceps muscle, masseter muscle) analysis has been processed both in the time and in the frequency domain by designing the digital signal processing system based on pentium PC and transputer (IMS 7805). The experiment have been performed in five normal subjects, and various parameters have been statistically tested and compare4 As a results, the effective parameters obtained for the evaluation of skeletal EMG electrical activity are turn analysis, MiTi, MiTa, IEMG, PDF in the time domain, and are mean frequency, median frequency, skewness, kurtosis, muscle fatigue slope in the frequency domain. The designed H/W and S/W in this study can be used effectively for the establishment of EMG data base and for clinical research.