• Journal of Mechanical Science and Technology
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• v.15 no.8
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• pp.1097-1107
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• 2001

In this paper, the wall following navigation algorithm of the mobile robot using a mono vision system is described. The key points of the mobile robot navigation system are effective acquisition of the environmental information and fast recognition of the robot position. Also, from this information, the mobile robot should be appropriately controlled to follow a desired path. For the recognition of the relative position and orientation of the robot to the wall, the features of the corridor structure are extracted using the mono vision system, then the relative position, the offset distance and steering angle of the robot from the wall, is derived for a simple corridor geometry. For the alleviation of the computation burden of the image processing, the Kalman filter is used to reduce search region in the image space for line detection. Next, the robot is controlled by this information to follow the desired path. The wall following control scheme by the PD control scheme is composed of two control parts, the approaching control and the orientation control, and each control is performed by steering and forward-driving motion of the robot. To verify the effectiveness of the proposed algorithm, the real time navigation experiments are performed. Through the result of the experiments, the effectiveness and flexibility of the suggested algorithm are verified in comparison with a pure encoder-guided mobile robot navigation system.

• Journal of the Korean Home Economics Association
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• v.42 no.8
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• pp.77-93
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• 2004

This study examined the factors affecting allowance management and buying behaviors and their interrelationship. The data were collected from fourth, fifth and sixth grade students of elementary students in Kimhae-city by a self-administered questionnaire. Frequency distributions, Cronbach's Alpha, Pearson's correlation analysis, regression analyses, and path analysis were analyzed by SPSS Windows. According to the regression model for the allowance management behaviors, the significant variables were the child's sex, term of receiving allowances, recognition of the allowance amount before receipt, parents' guidance before using allowances, parent-child communication about consumption, and parents' mediation of mass media. On the other hand, in the regression model for the buying behaviors, the satisfaction of the allowance amount, parents' guidance before using allowances, the amount of watching TV, parent-child communication about consumption, and allowance management behaviors were significant. The path model showed the child's sex, term of receiving allowances, recognition of the allowance amount before receipt, and parents' mediation of mass media indirectly affected the buying behaviors. In addition, the satisfaction of the allowance amount and the amount of watching 1V directly affected the buying behaviors. Moreover, parents' guidance before using allowances and parent-child communication about consumption had a direct effect and an indirect effect through the allowance management behaviors on the buying behaviors. Finally, the allowance management behaviors showed a strong positive effect on the buying behaviors.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.246-257
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• 2010

Autonomous guided robot navigation which consists of following unknown paths and avoiding unknown obstacles has been a fundamental technique for unmanned robots in outdoor environments. The unknown path following requires techniques such as path recognition, path planning, and robot pose estimation. In this paper, we propose a novel sensor fusion system for autonomous guided robot navigation in outdoor environments. The proposed system consists of three monocular cameras and an array of nine infrared range sensors. The two cameras equipped on the robot's right and left sides are used to recognize unknown paths and estimate relative robot pose on these paths through bayesian sensor fusion method, and the other camera equipped at the front of the robot is used to recognize abrupt curves and unknown obstacles. The infrared range sensor array is used to improve the robustness of obstacle avoidance. The forward camera and the infrared range sensor array are fused through rule-based method for obstacle avoidance. Experiments in outdoor environments show the mobile robot with the proposed sensor fusion system performed successfully real-time autonomous guided navigation.

• Journal of Families and Better Life
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• v.9 no.2
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• pp.1-18
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• 1991

The purpose of this study is to find out influential variables related to Home Management Ability of urban home makers. This study focuses on the following aspects; 1) to find out which variables of sociodemographic variables (ie. home maker's age, level of education-husband, wife, job-husband, wife, income, duration of marriage), of psychological variables (ie. degree of resourcefulness recognition, degree of stress recognition, degree of life level recognition) have significant effects on home management ability. 2) to find out which variables of sociodemographic variables have significant effects on degree of resourcefulness recognition, of stress recognition, and of life level recognition. 3) to identify the influence of significant variables related to home management ability. Data was analyzed by frequency. percentage, mean , F-test, t-test, Duncan's multiple range test. regression analysis , path analysis pearson's r. x2-test. Major findings are as follows; 1) The level of education (husband , wife)and occupation of husband were variables to have influences on home management ability. 2) a. The level of education (husband, wife) and income were variable to have influences on degree of resourcefulness recognition. b. The employment of home makers. income, and the form of family were variables to have influences on degree of stress recognition. c. The level of education (husband, wife) occupation of husband , income , and duration of marriage were variables to have influences on degree of life level recognition. 3) There were significant relationships between home management ability and degree of resourcefulness recognition and of stress recognition (r=0.13, r=-0.12, p<.05). a. The higher degree of resourcefulness recognition, the higher home management ability (x2=11.17. df=4. p<.05) b. The higher degree of stress recognition, the lower home n=management ability (x2=14.64. df=4. p<.01) 4) The education level of homemakers (β =0.15) and income (β=0.12) were variables to have indirect influences on home management ability through the medium of the degree of resourcefulness recognition (β =0.13) 5) The employment of home makers (β=-0.17) was a variable to have indirect influence on home management ability through the medium of the degree of stress recognition(β=-0.12) 6) the education level of husband (β=0.16) and income (β=0.32) were variables to have direct influence on degree of life level recognition. 7) The degree of life level recognition (β=0.13) and education level of home makers (β=0.17) were variables to have indirect influences on home management ability through the medium of the degree of resourcefulness recognition (β=0.13) 8)The degree of life level recognition (β=-0.22) the employment of home makers(β=-0.17) and the from of family(β=-0.10) were variables to have indirect influences on home management ability through the medium of the degree of stress recognition.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1E
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• pp.11-19
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• 1994

Hidden Markov Models (HMM's) with explicit state duration density (HMM/SD) can represent the time-varying characteristics of speech signals more accurately. However, such an advantage is reduced in relatively smooth state duration densities or ling bounded duration. To solve this problem, we propose HMM's with global path constraint (HMM/GPC) where the transition between states occur only within prescribed time slots. HMM/GPC explicitly limits state durations and accurately describes the temproal structure of speech simply and efficiently. HMM's formed by combining HMM/GPC with HMM/SD are also presented (HMM/SD+GPC) and performances are compared. HMM/GPC can be implemented with slight modifications to the conventional Viterbi algorithm. HMM/GPC and HMM/SD_GPC not only show superior performance than the conventional HMM and HMM/SD but also require much less computation. In the speaket independent isolated word recognition experiments, the minimum recognition eror rate of HMM/GPC(1.6%) is 1.1% lower than the conventional HMM's and the required computation decreased about 57%.

• Journal of the Korean Home Economics Association
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• v.35 no.1
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• pp.429-442
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• 1997

This study present s and tests a casual model of cohesion adaptability the level of stress recognition coping starategies and quality of life for employed wives and unemployed wives. For the data set 205 employed wives and 200 unemployed wives living in Pusan were chosen. The data were analyzed using M, SD, t-test multiple regression and path analysis. The findings of this study are as follows; First There level of stress recognition and quality of life are higher for employes wives than unemployed wives. Cohesion is higher for employed wives. Whereas adaptability is higher for unemployed wives than employed wives. Employes wives are greater use of coping starategies than unemployed wives. Second For employes wives adaptability the level of stress recognition and coping starategies have significant direct effect on quality of life. Besides wife's level of education age of the youngest child working hours employment motivation and cohesion have significant indirect effect on quality of life. For unemployed wives cohesion adaptability and level of stress recognition have signficant direct effect on quality of life. Besides wife's level of education number of children religion and husband's housework participation are indirectly associated with quality of life. From these results the proposed model is generally supported by the data.

• Journal of Family Resource Management and Policy Review
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• v.1 no.2
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• pp.1-15
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• 1997

The purpose of this study is to investigate (1)the level of the urban housewives’behavior and satisfaction of wedding, (2)the influential factors related to the two dependent variables above mentioned. So that provides some fundamental materials to improve the level of sound wedding culture and the whole home living. The subjects were 356 housewives, in April, 1997, Seoul. The data obtained were analyzed by Mean, Pearson’s correlation, Stepwise Multiple Regression and Path Analysis. The major findings were as follows: 1) The general tendency of the housewives’wedding behavior and satisfaction was reasonable. 2) According to the background variables(ie: marital form, the existence of job, the recognition degree of her husband’s family’s living standards, the recognition degree of her parents’home’s living standards, the perception of marital transactions), the housewives’wedding behavior was significantly different. 3) According to (1)the background variables(ie: communication frequency in household, self-acceptance, the adequacy of household income, educational level), (2)intermediated variable(ie: articles essential to a marriage), the housewives’wedding satisfaction was significantly different. 4) The indirect variable of the positive influence for housewives’satisfaction of wedding was marital form, the existence of job. the indirect variable of the negative influence for housewives’satisfaction of wedding was the recognition degree of her husband’s family’s living standards, the recognition degree of her parents’home’s living standards, the perception of marital transfactions.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.1027-1032
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• 1994

This paper introduces a interword modeling and a Viterbi search method for continuous speech recognition. We also describe a development of a real-time voice dialing system which can recognize around one hundred words and continuous digits in speaker independent mode. For continuous digit recognition, between-word units have been proposed to provide a more precise representation of word junctures. The best path in HMM is found by the Viterbi search algorithm, from which digit sequences are recognized. The simulation results show that a interword modeling using the context-dependent between-word units provide better recognition rates than a pause modeling using the context-independent pause unit. The voice dialing system is implemented on a DSP board with a telephone interface plugged in an IBM PC AT/486.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.114-120
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• 2000

Burr is an unavoidable and undesirable by-product of most metal cutting or shearing operations. This burr must be removed to improve the fit of machined parts and safety of workers, to improve the effectiveness of finishing operations. Despite the full or partial automation of FMC or FMS, deburring operations to obtain workpiece with fine surface quality are difficult to be automated since the occurrence and condition of burr are not constant. This study focused on developing a software for deburring automation, which includes automatic recognition of parts, generation of deburring tool path and NC code, by analyzing the IGES format file which contains information of part geometry. The successful performance of developed software was demonstrated by computer simulation and deburring experiment using miniature end brush. And, this research can provide a basis for further advanced studies for automated deburring applications.