• Structural Monitoring and Maintenance
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• v.5 no.1
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• pp.67-78
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• 2018

The stability of cutting slope influences the safety of railway operation, and how to identify the stability of the slope quickly and determine the rational monitoring plan is a pressing problem at present. In this study, the attribute recognition model of risk assessment for high cutting slope stability in the heavy haul railway is established based on attribute mathematics theory, followed by the consequent monitoring scheme design. Firstly, based on comprehensive analysis on the risk factors of heavy haul railway loess slope, collapsibility, tectonic feature, slope shape, rainfall, vegetation conditions, train speed are selected as the indexes of the risk assessment, and the grading criteria of each index is established. Meanwhile, the weights of the assessment indexes are determined by AHP judgment matrix. Secondly, The attribute measurement functions are given to compute attribute measurement of single index and synthetic attribute, and the attribute recognition model was used to assess the risk of a typical heavy haul railway loess slope, Finally, according to the risk assessment results, the monitoring content and method of this loess slope were determined to avoid geological disasters and ensure the security of the railway infrastructure. This attribute identification- risk assessment- monitoring design mode could provide an effective way for the risk assessment and control of heavy haul railway in the loess plateau.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5738-5743
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• 2014

This paper evaluated an electric wheelchair control algorithm by slope recognition on uneven terrain. Nowadays, the population using wheelchair has been increasing rapidly due to increases in the elderly population. On the other hand, most wheelchairs are directly controlled by the user without any device capable of securing the safety of the user. This causes difficulties in wheelchair control from the influence of gravity on the slope. This paper proposes a vehicle control algorithm that can move a wheelchair similar to moving on a plane. At that time, sensors are not used to recognize the degree of the slope. All processes were verified by simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2831-2838
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• 2014

This paper proposes the off-line handwritten flowchart symbol recognition algorithm by type and strength of a cross region of the straight line strokes that is extracted based the normalized dominant slope vectors. In the proposed algorithm, first of all, a connector symbol which consisted only curves is recognized by the special features, and the other symbols with straight line strokes are recognized by type and strength of a cross region, and that is extracted by extension of minimum bounding rectangle of the clusters of the normalized dominant slope vectors, and the straight line strokes of the symbols is extracted by the normalized dominant slope vectors. To confirm the validity of the proposed algorithm, the experiments are conducted for 10 different kinds of flowchart symbols that mainly used for computer program, and the number of symbols is 198. Experiment results were obtained the recognition rate of 99.5%, and the flowchart symbols is recognized correctly robust to variations, and then the proposed algorithm were found very effective for off-line handwritten flowchart symbol recognition.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.161-169
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• 1997

A variety of learning methods are used for neural networks. Among them, the backpropagation algorithm is most widely used in such image processing, speech recognition, and pattern recognition. Despite its popularity for these application, its main problem is associated with the running time, namely, too much time is spent for the learning. This paper suggests a method which maximize the convergence speed of the learning. Such reduction in e learning time of the backpropagation algorithm is possible through an adaptive adjusting of the slope of the activation function depending on total errors, which is named as the variable slope algorithm. Moreover experimental results using this variable slope algorithm is compared against conventional backpropagation algorithm and other variations; which shows an improvement in the performance over pervious algorithms.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.471-480
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• 2008

The deaf can not recognize useful sound informations such as alarm, doorbell, siren, car horn, and phone ring etc., because they have the hearing impairment. To solve this problems, portable hearing assistive devices which have suitable environment sound recognition methods are needed. In this paper, the DTW algorithm for sound recognition system with new active slope weighting constraint method was proposed. The environment sound recognition methods consist of three processes. First process is extraction of start point and end point using frequency and amplitude of sound. Second process is extraction of features and third process is classification of features for given segments. As a result of the experiment, the recognition rate of the proposed method is over 90%. And, the recognition rate of the proposed method increased about 20% than the conventional algorithm. Therefore if there are developed portable assistive devices which use developed method to recognize environment sound for hearing-impaired persons, they could be more convenient in life.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.525-533
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• 2003

In this paper we introduce some existing preprocessing algorithm for character recognition and consider feature extraction method for the recognition of low resolution document. Image recognition of low resolution document including fax images can be frequently misclassified due to the blurring effect, slope effect, noise and so on. In order to overcome these difficulties in the character recognition we considered a mesh feature extraction and contour direction code feature. System for automatic character recognition were suggested.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.158-164
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• 2002

This paper proposes the optimization of ultrasonic signal recognition in ferrite carbon steel weld zone using neural networks. For these purposes, the ultrasonic signals for defects as porosity, incomplete penetration and slag inclusion in the weld zone are acquired in the type of time series data. And then their applications evaluated feature extraction based on the time-frequency-attractor domain(peak to peak, rise time, rise slope, fall time, fall slope, pulse duration, power spectrum, and bandwidth) and attractor characteristics (fractal dimension and attractor quadrant) etc. The proposed neural networks system in this study can enhances performance of ultrasonic signal recognition.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.957-965
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• 2008

Recently, slope stability analysis in current design criteria is criticized for its unrealistic assumption of groundwater table and slope stability analysis incorporating seepage analysis considering rainfall is gaining a recognition as an alternative. However, a reasonable method for determining the rainfall used in the seepage analysis has not yet been established. Rainfall input for seepage analysis is a time series of rainfall and is similar to the hyetograph which is usually obtained from hydrology. In this paper a method to obtain the hyetograph from the intensity-duration-frequency is proposed. The resulting hyetograph can be used in the in the slope design stage. Also some considerations for practical application of slope stability analysis considering the rainfall is included.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.960-967
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• 2013

Shape recognition of solder ball bumps in a BGA (Ball Grid Array) is an important issue in flip chip bonding technology. In particular, the semiconductor industry has required faster and more accurate inspection of micron-size solder bumps in flip chip bonding as the density of balls has increased dramatically. The difficulty of this issue comes from specular reflection on the metal ball. Shape recognition of a metal ball is a very realproblem for computer vision systems. Specular reflection of the metal ball appears, disappears, or changes its image abruptly due to tiny movementson behalf of the viewer. This paper presents a practical shape recognition method for three dimensional (3-D) inspection of a BGA using a 5-step ring illumination device. When the ring light illuminates the balls, distinctive specularity images of the balls, which are referred to as "iso-slope contours" in this paper, are shown. By using a mathematical reflectance model, we can drive the 3-D shape information of the ball in aquantitative manner. The experimental results show the usefulness of the method for industrial application in terms of time and accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.2
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• pp.87-95
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• 2003

Dynamic Programming Matching (DPM) is a mathematical optimization technique for sequentially structured problems, which has, over the years, played a major role in providing primary algorithms in pattern recognition fields. Most practical applications of this method in signature verification have been based on the practical implementational version proposed by Sakoe and Chiba [9], and il usually applied as a case of slope constraint p = 0. We found, in this case, a modified version of DPM by applying a heuristic (forward seeking) implementation is more efficient, offering significantly reduced processing complexity as well as slightly improved verification performance.