• Journal of Institute of Control, Robotics and Systems
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• v.12 no.9
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• pp.935-944
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• 2006

EMG pattern recognition is essential for the control of a multifunction myoelectric hand. The main goal of this study is to develop an efficient feature projection method for EMC pattern recognition. To this end, we propose a linear supervised feature projection that utilizes linear discriminant analysis (LDA). We first perform wavelet packet transform (WPT) to extract the feature vector from four channel EMC signals. For dimensionality reduction and clustering of the WPT features, the LDA incorporates class information into the learning procedure, and finds a linear matrix to maximize the class separability for the projected features. Finally, the multilayer perceptron classifies the LDA-reduced features into nine hand motions. To evaluate the performance of LDA for the WPT features, we compare LDA with three other feature projection methods. From a visualization and quantitative comparison, we show that LDA has better performance for the class separability, and the LDA-projected features improve the classification accuracy with a short processing time. We implemented a real-time pattern recognition system for a multifunction myoelectric hand. In experiment, we show that the proposed method achieves 97.2% recognition accuracy, and that all processes, including the generation of control commands for myoelectric hand, are completed within 97 msec. These results confirm that our method is applicable to real-time EMG pattern recognition far myoelectric hand control.

• Transactions of Materials Processing
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• v.31 no.5
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• pp.281-289
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• 2022

Presently, 3D printers manufactured by material extrusion are economical and easy to use, so they are being used in various fields. However, this study conducted a tensile test on the infill pattern and density of the PLA+ material, due to the limitations of long printing time as well as low mechanical strength. The infill area for the infill density change was measured, using a vision-measuring machine for four infill patterns (concentric, zigzag, honeycomb, and cross) in which the nozzle path was the same for each layer. The tensile strength/weight[MPa/g] and tensile strength/printing time[MPa/min] of the tensile specimens were analyzed. In this study, efficient infill density and patterns are suggested, for cost reduction and productivity improvement. Consequently, it was confirmed that the infill area and infill percentage of the four patterns, were not constant according to the infill pattern. And the tensile strength of the infill density 40% of the honeycomb pattern and infill density 20% of the cross pattern, tended to highly consider the weight and printing time. Honeycomb and cross patterns could reduce the weight of the tensile specimen by 19.11%, 28.07%, as well as the printing time by 29.56%, 52.25%. Tensile strength was high in the order of concentric, zigzag, honeycomb, and cross patterns, considering the weight and printing time.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.55-75
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• 2010

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

• Proceedings of the Korean Nuclear Society Conference
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• 1999.10a
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• pp.194-194
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• 1999

• Journal of Korea Foundry Society
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• v.43 no.2
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• pp.95-101
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• 2023

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.345-348
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• 2008

Recently, in Weld Processing field, unmanned and automatic system construction has experienced the rapid growth, and diverse signal processing has been employed in order to translate the exact weld pattern. It this paper, We will suggest the effective neural network which can deride the weld quality in arc weld and monitoring system in real time. In addition, We will present the pre-processing for selecting the study data, and the method to evaluate the wave of weld more precisely and accurately through known Neural Network.

• Proceedings of the KIEE Conference
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• 1999.07d
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• pp.1876-1878
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• 1999

Developed was a 5kW-class polymer electrolyte membrane fuel cell(PEMFC) system comprised of fuel cell stack, fuel processing, thermal and water management subsystems and ancillary equipments. Several large single cells have been fabricated with different gas flow field patterns and paths, and the gas flow field pattern for the stack has been determined based on the single cell performance of thin film membrane electrode assembly (MEA). The PEMFC stack was consisted of 100 cells with an electrode area of $300cm^2$, having serpentine flow pattern. Fuel processing was developed including an autothermal methanol reformer and two preferential CO oxidation reactors. The fuel processing was combined to PEMFC operation system consisted of air compressor and thermal and water management subsystems. The PEMFC stack showed performance of 5kW under the supply of $H_2$ and air, but its performance was lowered to 3.5kW under the supply of reformed gas.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.385-399
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• 2017

Nowadays, with the development of signal processing technique, the protection to the integrity and authenticity of images has become a topic of great concern. A blind image authentication technology with high tamper detection accuracy for different common attacks is urgently needed. In this paper, an improved fragile watermarking method based on local binary pattern (LBP) is presented for blind tamper location in images. In this method, a binary watermark is generated by LBP operator which is often utilized in face identification and texture analysis. In order to guarantee the safety of the proposed algorithm, Arnold transform and logistic map are used to scramble the authentication watermark. Then, the least significant bits (LSBs) of original pixels are substituted by the encrypted watermark. Since the authentication data is constructed from the image itself, no original image is needed in tamper detection. The LBP map of watermarked image is compared to the extracted authentication data to determine whether it is tampered or not. In comparison with other state-of-the-art schemes, various experiments prove that the proposed algorithm achieves better performance in forgery detection and location for baleful attacks.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.7
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• pp.106-111
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• 1989

A new EMG signal processing algorithm for SMUAP pattern classification is proposed. It checks the combination and regularity of ISI using a spike counter as a decision making routine, and performs SMUAP waveform alignment in frequency domain and selects spikes through FIR filtering. As a result, with the EMG signals recorded during 5 seconds at 10-50% MVC force level, the SMUAP ranged from five to nine units were classified and identification rate is greater than 55 percent using a concentric needle electrode. In the IBM PC/AT the processing time typically required 2 minutes.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.691-700
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• 2017

This paper describes the design and implementation of automatic braille converter based on image processing for a person who is visually impaired. The conversion algorithm based on the image processing converts the input image obtained by the web-cam to binary image, and then calculates the cross-correlation with the stored character pattern image by labeling the character area and converts the character pattern image into the corresponding braille. The computer simulations showed that the proposed algorithm showed 95% and 91% conversion success rates for numerals and alphabets printed on A5 paper. The prototype test implemented by the servo motor using Arduino confirmed 89%, conversion performance. Therefore, we confirmed the feasibility of the automatic braille transducer.