• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.987-992
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• 2002

In an attempt to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands the user to have knowledge about the underlying problem. Moreover, in solving multiobjective problems, designers may be interested in a set of Pareto-optimal points, instead of a single point. In this paper, pareto-based Continuous Evolutionary Algorithms for Multiobjective Optimization problems having continuous search space are introduced. This algorithm is based on Continuous Evolutionary Algorithms to solve single objective optimization problems with a continuous function and continuous search space efficiently. For multiobjective optimization, a progressive reproduction operator and a niche-formation method fur fitness sharing and a storing process for elitism are implemented in the algorithm. The operator and the niche formulation allow the solution set to be distributed widely over the Pareto-optimal tradeoff surface. Finally, the validity of this method has been demonstrated through a numerical example.

• Journal of KIISE
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• v.41 no.12
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• pp.1152-1159
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• 2014

In this paper, we presents a system to ensure the safety of residents through appropriate action or alarm in case the residents occurs an emergency situation and abnormal activity. We collect and analysis real-time data of living environment of the residents using video and sensor. The existing system have been determined by using only the sensor data it have several problems. Our system attach camera to solve the existing system problem. We use weighted difference image and motion vector. The existing system, it takes about 48 hours to determine that an abnormal activity occurs. However, our system takes less than 1 hour.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1531-1536
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• 2011

We propose an automatic swearword filter system for online game chatting by using Support Vector Machines(SVM). We collected chatting sentences from online games and tagged them as normal sentences or swearword included sentences. We use n-gram syllables and lexical-part of speech (POS) tags of a word as features and select useful features by chi square statistics. Each selected feature is represented as binary weight and used in training SVM. SVM classifies each chatting sentence as swearword included one or not. In experiment, we acquired overall 90.4% of F1 accuracy.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.59-69
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• 2006

Bluetooth is reputed as a wireless networking technology supplying ad-hoc networks between digital devices. In particular, Bluetooth scatternet is an essential part of dynamic ad-hoc networks. Yet, there have not been sufficient researches performed on scatternet environment. This paper proposes a scatternet reformation algorithm for ad-hoc networks for instances where some nodes enter or leave the scatternet. The proposed algorithm is a general algorithm that can be applied to many types of Bluetooth scatternet regardless of the topology. The proposed algorithm is made for two reformation cases, i.e., nodes leaving and nodes entering. For the reformation when nodes leave a scatternet, the recovery node vector (RNV) algorithm is proposed. It has short reformation setup delay because the process involves a single page process (not including inquiry process). For the reformation when nodes enter a scatternet, the entry node algorithm is proposed. This is a simple and easily implementable algorithm. In this paper, real hardware experiments are carried out to evaluate the algorithm's performance where the reformation setup delay, the reformation setup probability and the data transfer rate are measured. The proposed algorithm has shown improvement in the reformation setup delay and probability.

• Journal of Sericultural and Entomological Science
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• v.38 no.2
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• pp.144-149
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• 1996

To develope the baculovirus expression vector system (BEVS) using Spodoptera exigua nuclear polyhedrosis virus (SeNPV), we characterized the polyhedrin of SeNPV. The SeNPV polyhedra was irregular and composed of the major protein molecular weight of 30 kDa determined by electronmicroscopy and SDS-AGE analysis, respectively. The nucleotid suquences of 876 bases including the coding region of polyhedrin gene was determined and it was revealed that the polyhedrin gene is located within Xho I 3.0Kb and Nco I 6.0 Kb by Southern blot analysis, respectively. Also, the Xho I 3.0 Kb and the Nco I 6.0 Kb fragments were cloned and restriction enzyme map of these clones were determined.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.163-170
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• 2011

This study proposed the composition of a new long-code MMSE detector using the pilot channel that demonstrated the most excellent performance under Rayleigh fading in the previous studies. It analyzed and explained how to maintain the stability of the weight vector(introduction to the course of radio waves) in the receiver. In the operation of the receiver system to remove radio interference, the signal vector distortion received in the channel where fading was present achieved good results by compensating for signal errors. When there was distortion, the response characteristics of the received signals were superior to the common matching filter according to the computer simulation. The long-code MMSE receiver proposed in the study was able to prolong the cycle by $16{\times}T_b$ in the fading environment to fulfill the satisfaction.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.216-221
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• 2003

Emotions recognition is a topic on which little research has been done to date. This paper proposes a new method that can recognize the human s emotion from facial image by using eigenspace. To do so, first, we get the face image by using the skin color from the original color image acquired by CCD color camera. Second, we get the vector image which is projected the obtained face image into eigenspace. And then, we propose the method for finding out each person s identification and emotion from the weight of vector image. Finally, we show the practical application possibility of the proposed method through the experiment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.303-309
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• 2012

Energy expenditure values were estimated based on the voice signals and body activities. Voice signals and body activities were obtained using PVDF contact vibration sensor and 3-axis accelerometer, respectively. Vibration caused by voices, activity signals, and actual energy consumption were acquired using data acquisition system and gas analyzer. With the use of power values from the voice signals and weight as independent variables, R-square of 0.918 appeared to show the highest value. For activity outputs, use of signal vector magnitude, body mass index, height, and age as independent variables revealed to provide the highest correlation with actual energy expenditure. Estimation of energy expenditure based on voice and activity provides more accurate results than based on activity only.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1446-1452
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• 2014

Existing LDA uses the transform matrix that maximizes distance between classes. So we have to convert from an image to one-dimensional vector as training vector. However, in 2D-LDA, we can directly use two-dimensional image itself as training matrix, so that the classification performance can be enhanced about 20% comparing LDA, since the training matrix preserves the spatial information of two-dimensional image. However 2D-LDA uses same calculation schema for transformation matrix and therefore both LDA and 2D-LDA has the heteroscedastic problem which means that the class classification cannot obtain beneficial information of spatial distances of class clusters since LDA uses only data correlation-based covariance matrix of the training data without any reference to distances between classes. In this paper, we propose a new method to apply training matrix of 2D-LDA by using WPS-LDA idea that calculates the reciprocal of distance between classes and apply this weight to between class scatter matrix. The experimental result shows that the discriminating power of proposed 2D-LDA with weighted between class scatter has been improved up to 2% than original 2D-LDA. This method has good performance, especially when the distance between two classes is very close and the dimension of projection axis is low.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.4
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• pp.82-90
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• 2009

Pneumatic cylinder is one of the low cost actuation sources which have been applied in industrial and prosthetic application since it has a high power/weight ratio, a high-tension force and a long durability However, the control problems of pneumatic systems, oscillatory motion and compliance, have prevented their widespread use in advanced robotics. To overcome these shortcomings, a number of newer pneumatic actuators have been developed such as McKibben Muscle, Rubber Actuator and Pneumatic Artificial Muscle (PAM) Manipulators. In this paper, one solution for position control of a robot arm, which is driven by two pneumatic artificial muscles, is presented. However, some limitations still exist, such as a deterioration of the performance of transient response due to the changes in the external load of the robot arm. To overcome this problem, a switching algorithm of the control parameter using a learning vector quantization neural network (LVQNN) is proposed in this paper. This estimates the external load of the pneumatic artificial muscle manipulator. The effectiveness of the proposed control algorithm is demonstrated through experiments with different external working loads.