• Journal of Multimedia Information System
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• v.5 no.1
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• pp.15-20
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• 2018

There are a lot of problems in the face detection area. One of them is detecting faces by facial features and reducing number of the false negatives and positions. This paper is directed to solve this problem by the proposed triangle method. Also, this paper explans cascades, Haar-like features, AdaBoost, HOG. We propose a scheme using 12-net, 24-net, 48-net to scan images and improve efficiency. Using triangle method for frontal pose, B and B1 methods for other poses in neural networks are proposed.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.837-839
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• 2001

This paper presents dynamic characteristic of a 2 phase hybrid stepping motor which includes pull-out torque with constant voltage drive and one step response. In order to analyze this characteristics, vector diagram of a synchronous motor and torque-voltage equation are used. Analytic results are good agreement with experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.763-768
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• 1994

A hierarchical Petri- net is utilized in supervising an automated vehicle system, The supervisory system is supported by computer networking in order to facilitate necessary processing, and consists of control flow level and computer allocation level so that a designer and an operator can easily build and/or access to each level. There are two modes of utilizing Petri net here in this paper. One is to employ it in designing the control system, in order to optimally allocate computers in every stage of processing. The other is for supervision of the system in operation, in order for the operator to be in a easy-to-comprehend environment of operation. The effect of these two modes of utilizing Petri net is examined.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2E
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• pp.49-55
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• 2003

The modified neural net pattern recognition equations were attempted to apply to speech recognition. The proposed method has a dynamic process of self-organization that has been proved to be successful in recognizing a depth perception in stereoscopic vision. This study has shown that the process has also been useful in recognizing human speech. In the processing, input vocal signals are first compared with standard models to measure similarities that are then given to a process of self-organization in neural net equations. The competitive and cooperative processes are conducted among neighboring input similarities, so that only one winner neuron is finally detected. In a comparative study, it showed that the proposed neural networks outperformed the conventional HMM speech recognizer under the same conditions.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.7-13
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• 1998

This paper presents a methodology for determining machining conditions in Electric Discharge Wire-Cut. Unification of two phase neural network approach with an automatic generation of machining parameters is designed. The first phase neural network, which is 1 to M backward-mapping neural net, produces approximate machining conditions. Using approximate conditions, all possible conditions are newly created by the proposed automatic generation procedure. The second phase neural net, which is a M to 1 forward-mapping neural net, determines the best one among the generated candidates. Simulation results with ANN are given to verify that the presenting methodology could apply for determining machining parameters in Electric Discharge Wire-Cut.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.220-228
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• 1996

This paper presents a extended stochastic Petri net (ESPN) model for CTN(Circulated Token with No duration) service in the data link layer of IEC/ISA fieldbus. It is assumed that a station on the fieldbus has a specified minimum token holding time, a finite capacity buffer, and one transmitter queue with the highest priority. The mean transmission (or service) time at a station and the mean token rotation time for the symmetric fieldbus system atr derived using the presented SPN model and the moment generating function. These performance measures are represented in terms of the minimum token holding time, the number of stations, the arrival rate of messages, and the mean length of messages. The presented performance measure are validated by computer simulations.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.4
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• pp.219-225
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• 2016

Visual object tracking is one of the key tasks in computer vision. Robust trackers should address challenging issues such as fast motion, deformation, occlusion and so on. In this paper, we therefore propose a visual object tracking method that exploits inter-frame correlations of convolutional feature maps in Convolutional Neural Net (ConvNet). The proposed method predicts the location of a target by considering inter-frame spatial correlation between target location proposals in the present frame and its location in the previous frame. The experimental results show that the proposed algorithm outperforms the state-of-the-art work especially in hard-to-track sequences.

• Journal of Computing Science and Engineering
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• v.7 no.1
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• pp.44-52
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• 2013

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.962-969
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• 2000

Quality that character of energy is the same at every state in case of equal working fluid and net concept of material flow was applied to thermoeconomics about energy system, and we could naturally explain the suitable degree about this concept, also thermoecomic equations about general power plant was easily deduced. And deduced equations exactly corresponded with principle of thermoeconomics that overall input cost flow rate equal overall output cost flow rate. This equations is applied to gas turbine cogeneration power plant as one example and found the product unit cost. Also this product cost comparison could been naturally explained.

• Near Infrared Analysis
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• v.1 no.2
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• pp.1-8
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• 2000

Using the net analyte signal, hybrid linear analysis was proposed to predict chemical concentration. In this paper, we select a sample from training set and apply orthogonal signal correction to obtain an improved pseudo unit spectrum for hybrid least analysis. using the mean spectrum of a calibration training set, we first show the calibration by hybrid least analysis is effective to the prediction of not only chemical concentrations but also physical property variables. Then, a pseudo unit spectrum from a training set is also tested with and without orthogonal signal correction. We use two data sets, one including five chemical concentrations and the other including ten physical property variables, to compare the performance of partial least squares and modified hybrid least analysis calibration methods. The results show that the hybrid least analysis with a selected training spectrum instead of well-measured pure spectrum still gives good performances, which is a little better than partial least squares.