• Journal of the Korea Society for Simulation
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• v.22 no.1
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• pp.63-75
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• 2013

The School Bus Routing Problem(SBRP) seeks to plan an efficient schedule of a fleet of school buses that must pick up student from various bus stops and deliver them by satisfying various constraints; maximum capacity of the bus, maximum riding time of students, arrival time between a school's time window. By extending the existing SBRP, we consider a case study of SBRP with allowance of mixed-loading and dynamic arrivals reflecting the school bus operation of university in Korea. Our solution procedure is based on constructing the initial solution using sweep algorithm and then improving solution within the framework of the evolutionary approach known as efficient meta-heuristics. By comparing the various scenarios through the constraints relaxation for reflecting the real operational strategies, we assess the merit of our proposed procedure.

• Journal of Gifted/Talented Education
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• v.11 no.3
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• pp.131-153
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• 2001

The importance of identifying gifted children during early childhood is becoming recognized. Nonetheless, most researchers preferred to study the primary and secondary levels where children are already and more clearly demonstrating what talents they have, and where more reliable predictions of gifted may be made. Comparatively lisle work has been done in this area. When we identify giftedness during early childhood, we have to consider the potential of the young children rather than on actual achievement. Giftedness during early childhood is still developing and less stable than that of older children and this prevents us from making firm and accurate predictions based on children's actual achievement. Dynamic assessment, based on Vygotsky's concept of the zone of proximal development(ZPD), suggests a new idea in the way the gifted young children are identified. In light of dynamic assessment, for identifying the potential giftedness of young children. we need to involve measuring both unassisted and assisted performance. Dynamic assessment usually consists of a test-intervene-retest format that focuses attention on the improvement in child performance when an adult provides mediated assistance on how to master the testing task. The advantages of the dynamic assessment are as follows: First, the dynamic assessment approach can provide a useful means for assessing young gifted child who have not demonstrated high ability on traditional identification method. Second, the dynamic assessment approach can assess the learning process of young children. Third, the dynamic assessment can lead an individualized education by the early identification of young gifted children. Fourth, the dynamic assessment can be a more accurate predictor of potential by linking diagnosis and instruction. Thus, it can make us provide an educational treatment effectively for young gifted children.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.175-195
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• 1998

Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.734-741
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• 2020

This article proposes a new pedestrian avoidance algorithm for social robots that coexist and communicate with humans and do not induce stress caused by invasion of psychological safety distance(Social Distance). To redefine the pedestrian model, pedestrians are clustered according to the pedestrian's gait characteristics(straightness, speed) and a social distance is defined for each pedestrian cluster. After modeling pedestrians(obstacles) with the social distances, integrated navigation algorithm is completed by applying the newly defined pedestrian model to commercial obstacle avoidance and path planning algorithms. To show the effectiveness of the proposed algorithm, two commercial obstacle avoidance & path planning algorithms(the Dynamic Window Approach (DWA) algorithm and the Timed Elastic Bands (TEB) algorithm) are used. Four cases were experimented in applying and non-applying the new pedestrian model, respectively. Simulation results show that the proposed algorithm can significantly reduce the stress index of pedestrians without loss of traveling time.