• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.317-318
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• 2022

최근 인공지능 기술이 발전함에 따라 자율주행, 첨단 운전자 지원 시스템과 같은 기술들이 개발되고 있다. 이런 기술들은 교통사고를 예방하여 사망률 등을 감소시키고, 운전자의 편의성을 향상시킨다. 본 논문에서는 자율주행과 첨단 운전자 지원 시스템에서 사용할 수 있는 기술들을 개발하고, 이를 RC카에 적용하여 구현하였고, 인공트랙에서 실험하여 평가하였다. 딥러닝 기반 실시간 객체 인식 및 Opencv 를 이용한 차선 인식기술을 통해 차선을 인식하여 이탈하지 않고 주행하며 표지판 등 객체를 인식하여 상황에 따른 대응으로 모터를 제어하는 기술을 개발하고 인공트랙을 자율주행하는 RC카를 구현하고 실험하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.35-45
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• 2013

A autonomous vehicle requires improved and robust perception systems than conventional perception systems of intelligent vehicles. In particular, single sensor based perception systems have been widely studied by using cameras and laser radar sensors which are the most representative sensors for perception by providing object information such as distance information and object features. The distance information of the laser radar sensor is used for road environment perception of road structures, vehicles, and pedestrians. The image information of the camera is used for visual recognition such as lanes, crosswalks, and traffic signs. However, single sensor based perception systems suffer from false positives and true negatives which are caused by sensor limitations and road environments. Accordingly, information fusion systems are essentially required to ensure the robustness and stability of perception systems in harsh environments. This paper describes a perception system for autonomous vehicles, which performs information fusion to recognize road environments. Particularly, vision and laser radar sensors are fused together to detect lanes, crosswalks, and obstacles. The proposed perception system was validated on various roads and environmental conditions with an autonomous vehicle.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.2
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• pp.119-129
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• 2019

Objectives : The purpose of this study was to examine cognitive and psychological characteristics of patients who visited psychiatric outpatient clinic with military service suitability issues. Methods : Since January, 2017 to September, 2018, patients were recruited from the department of psychiatry of university hospital. Participants were diagnosed using DSM-5 criteria by board certified psychiatrists. And each of participants tested with K-WAIS-IV, K-SCL-95 by clinical psychologist. The data were analyzed using SPSS 18.0. Results : The results indicated 24.6% of the patients have significantly low level of intellectual functioning. and 10.8% of the patients have borderline level of intellectual functioning, and 26.3% of them were below average. The results of psychological characteristics showed patients have cautious and potentially dangerous level of depression, anxiety, agoraphobia, and suicidal idea. And PTSD subscale's mean score was above problematic level. Next, we divided patients into two groups based on question of whether the patient is eligible to serve in the military service or not arises from recruitment process or army training center. But two group didn't differ significantly. And for further analyses, we also divided patients into two groups based on if they got single psychiatric diagnosis or more than one psychiatric diagnosis. Conclusions : The results indicated that group which has coexisting psychiatric disorders were more depressed, had higher level of anger and aggression, and had more serious levels of suicidal ideas than single psychiatric diagnosis group. The implications and limitations were discussed along with some suggestions for the future studies.

• Korean Journal of Biological Psychiatry
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• v.13 no.2
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• pp.70-81
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• 2006

Objective : The purpose of this study was to investigate the differences of the cognitive performance, emotional and behavioral problems among the attention-deficit/hyperactivity disorder(ADHD) groups that show the difference between visual and auditory attention. Method : Using 'ADHD Diagnostic System(ADS)', visual attention and auditory attention of 98 children diagnosed as ADHD were measured. According to the omission and commission error of ADS, they were divided into three groups ; 1) the group whose each visual omission and commission error scores were higher than each auditory omission and commission error scores(VV group), 2) the group whose each auditory omission and commission error scores were higher than each visual omission and commission error scores(AA group), 3) the group that was the rest of VV and AA group(M group). And the results of both the subscales of Korean Educational Development Institute-Wechsler Intelligence Scale for Children(KEDI-WISC) and the subscales of Korean Child Behavior Checklist(K-CBCL) among three groups were compared. Finally, the correlation between the visual omission, visual commission, auditory omission, auditory commission error and the results of KEDI-WISC, K-CBCL were investigated. Results : The results were as follows ; 1) In 98 ADHD children, the number of VV group(N=56) was higher than that of AA (N=10) and M group (N=32). 2) All mean scores of the subscales of KEDI-WISC of VV group were higher than those of M and AA group. The score of verbal IQ(p=.039) of VV group was significantly higher than that of AA group and the scores of block design(p=.015), Kaufman's factor 2(p=.045), performance IQ(p=.004) were significantly higher than those of M group. The score of full IQ(p=.004) were significantly higher than that of M and AA group. 3) The mean scores of all K-CBCL subscales of VV group were higher than those of M and AA group, except the score of Somatic complaint subscale. The score of Social subscale(p=.041) of VV group was significantly higher than that of AA group. The score of Withdrawn subscale(p=.021) of AA group was significantly higher than that of VV group. 4) There were no significant correlation between the scores of visual omission/commission error and those of each subscale of KEDI-WISC. But, there were many significant correlations between the scores of auditory omission/commission error and those of each subscale of KEDI-WISC. 5) There were significant correlation between the score of the visual omission error and that of Thought problem subscale(r=.205, p=.043) of K-CBCL. There were significant correlation between the scores of the auditory omission error and those of Social subscale(r=-.319, p=.001), Social problems subscale(r=.206, p=.042), Thought problem subscale(r=.235, p=.021). Finally, there were significant correlation between the scores of auditory commission error and those of Social subscale(r=-.241, p=.017), Thought problem subscale(r=.235, p=.020). Conclusion : The ADHD children whose auditory attention ability were higher than visual attention ability had relatively better cognitive performance and less emotional/behavioral problems than the others. The more comprehensive experiment will be needed about the cognitive performance, emotion and behavior problems of the ADHD children showing the difference between visual and auditory attention.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4773-4779
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• 2012

In this paper we propose two types of reconfigurable 3-D beam steering antenna for intelligent or smart antenna system. Proposed antennas are composed of triangular(structure1.) or circuler(structure2.) loop structure and bended dipole antenna structure. This antenna can steer beam pattern of 6 direction at xy-plane state (0, 1, 2) and xz-plane state (3, 4, 5) by 4 switch motion with one antenna element. Antenna structure1. is symmetric equilibrium structures based on feeding point. There is no grounding point. As a result, designed antenna's gain is similar to dipole antenna. Also, As unbalanced structure by using CPWG in the form of a semicircular, structure2. is enhanced directivity. The operation frequency of antenna are 2.5 GHz(Structure1.) and 2.55 GHz(Structure2.), maximum gain is 1.04 ~ 2.06 dBi(Structure1. : Omni-directional beam), 1.6 ~ 4 dBi(structure2. : Directional beam). The overall HPBW is about over $160^{\circ}$ in the both of the xy-plane and xz-plane at structure1. and over $125^{\circ}$ at structure2.

• Journal of Science Education
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• v.39 no.3
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• pp.418-433
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• 2015

In this study, we investigated the cognitive characteristics of low science achieving middle school students in K-WISC-IV, and compared the results with high science achieving and achieving students. The results showed us that high science achieving students scored higher than counterparts in FSIQ. Low science achieving students scored lower than high science achieving and achieving students in VCI. Especially low science achieving students scored lower than two groups in subtest SI. The low level of abstraction in low science achieving students is due to the lack of scientific reasoning ability. Therefore subtest SI is considered as highly discriminating test for low science achieving group. Low levels in verbal comprehension, abstraction and reasoning ability are the major factors in poor school performance. High science achieving students scored more than achieving and low achieving students in WMI. Because the working memory is involved in scientific reasoning problem solving process, it is believed to play an important role in science achieved.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.210-218
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• 2002

This paper proposes an efficient separation method of the composite images by using independent component analysis(ICA) based on neural networks of the approximate learning algorithm. The Proposed learning algorithm is the fixed point(FP) algorithm based on Secant method which can be approximately computed by only the values of function for estimating the root of objective function for optimizing entropy. The secant method is an alternative of the Newton method which is essential to differentiate the function for estimating the root. It can achieve a superior property of the FP algorithm for ICA due to simplify the composite computation of differential process. The proposed algorithm has been applied to the composite signals and image generated by random mixing matrix in the 4 signal of 500-sample and the 10 images of $512{\times}512-pixel$, respectively The simulation results show that the proposed algorithm has better performance of the learning speed and the separation than those using the conventional algorithm based method. It also solved the training performances depending on initial points setting and the nonrealistic learning time for separating the large size image by using the conventional algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.133-142
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• 2021

With the recent advancements of deep learning, companies such as smart home, healthcare, and intelligent transportation systems are utilizing its functionality to provide high-quality services for vehicle detection, emergency situation detection, and controlling energy consumption. To provide reliable services in such sensitive systems, deep learning models are required to have high accuracy. In order to develop a deep learning model for analyzing previously mentioned services, developers should utilize the state of the art deep learning models that have already been verified for higher accuracy. The developers can verify the accuracy of the referenced model by validating the model on the dataset. For this validation, the developer needs structural information to document and apply deep learning models, including metadata such as learning dataset, network architecture, and development environments. In this paper, we propose a description language that represents the network architecture of the deep learning model along with its metadata that are necessary to develop a deep learning model. Through the proposed description language, developers can easily verify the accuracy of the referenced deep learning model. Our experiments demonstrate the application scenario of a deep learning description document that focuses on the license plate recognition for the detection of illegally parked vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.2
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• pp.12-22
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• 2010

The variable message sign(VMS) is a facility to smoothen traffic flows and enable safe passing by providing real-time necessary information on roads, weather, transportation, and traffic regulations. The VMS also solves a feeling of uneasiness and gives a sense of psychological security by providing information to drivers. However, the VMS has a strong character of being a non-market product but a public product, so it has not normally been evaluated for its value. This research has evaluated a value of satisfaction level for traffic information users, using a contingent valuation method(CVM). As a result of evaluating the value of satisfaction level for users through division into an urban roadway and an urban highway for the cities where an intelligent transportation system(ITS) has been established, the urban highway had a value of 96.7 won/system and the urban roadway had a value of 76.3 won/system.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.28 no.2
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• pp.141-148
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• 2017

Objectives: The current study examined the effect of birth weight on the relationship between age and IQ of children, who were born preterm with very low birth weight (VLBW) or extremely low birth weight (ELBW). Methods: The study subjects were 82 children, aged between 3-5 years, who visited the neonatal intensive care unit of a university hospital located in Seoul. The children had been born prematurely with VLBW or ELBW. Their IQ was tested using the performed Korean-Wechsler Preschool and Primary Scale of Intelligence fourth edition. Results: A hierarchical regression analysis showed a significant interaction effect of birth weight and age on Full Scale IQ (FSIQ); the effect of age on FSIQ differed according to birth weight. For the group with VLBW, FSIQ was more likely to be higher with increasing age. Conversely, for the group with ELBW, FSIQ remained low regardless of the age level. In addition, birth weight and age had a significant interaction effect on the Visual Spatial Index. Birth weight had a significant main effect on Verbal Comprehension Index. Conclusion: This research suggested the possibility of predicting the cognitive developmental of premature children, by highlighting the fact that prematurely born children, with VLBW/ELBW, have different cognitive developmental trajectories.