• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.98.3-98
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• 2002

Vision-based systems for finding road lanes have to operate robustly under a wide variety of environ-mental conditions including large amount of scene clutters. This paper presents a method for finding the lane boundaries by combining a local line extraction method and dynamic programming as a search tool. The line extractor obtains an initial position estimation of road lane boundaries from the noisy edge fragments. Dynamic programming then improves the initial approximation to an accurate configuration of lane boundaries. Input image frame is divided into a few sub-regions along the vertical direction. The local line extractor then performs to extract candidate lines of road lanes in the...

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.12
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• pp.880-884
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• 2006

In an edge-weighted(positive, negative, or zero weights are possible) tree, we want to solve the problem of finding a longest path such that the sum of the weights of the edges in tile path is non-negative. To find a longest non-negative path of a tree we present a sequential algorithm with O(n logn) time and a CREW PRAM parallel algorithm with $O(log^2n)$ time and O(n) processors. where n is the number of nodes in the tree.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.541-544
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• 2006

In a tree with each edge associated with a length and a weight (positive, negative, or zero are possible) we develop an O(nlognloglogn) time algorithm for finding a path such that its sum of weights is maximized and its sum of lengths does not exceed a given value. The previously best-known result is O($nlog^2n$), where n is the number of nodes in the tree.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.100-105
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• 1993

This paper discusses an approach to real-time path-planning of mobile robot navigating amidst multiple obstacles. Given an environment with the coordinates of known obstacles, the moving area of a mobile robot is divided into many patches of triangles with small edge length, in order to ensure a path better than those reported in the literature. After finding a minimum-distance to minimize the number of turns and total path-length by two-step path-revision and path-smmothing.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.33-43
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• 2012

Semantic web is utilized to construct advanced information service by using semantic relationships between entities. Text mining can be applied to generate semantic relationships from unstructured data resources. In this study, ontology schema guideline, ontology instance generation, disambiguation of same name by text mining and advanced historical people finding service by reasoning have been proposed. Various relationships between historical event, organization, people, which are created by domain experts, are linked to literatures of National Institute of Korean History (NIKH). It improves the effectiveness of user access and proposes advanced people finding service based on relationships. In order to distinguish between people with the same name, we compares the structure and edge, nodes of personal social network. To provide additional information, external resources including thesaurus and web are linked to all of internal related resources as well.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1315-1318
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• 2003

In this paper, a neural network based approach using a self-organizing feature map is proposed for the segmentation of X ray images. A number of algorithms based on such approaches as histogram analysis, region growing, edge detection and pixel classification have been proposed for segmentation of general images. However, few approaches have been applied to X ray image segmentation because of blur of the X ray image and vagueness of its edge, which are inherent properties of X ray images. To this end, we develop a new model based on the neural network to detect objects in a given X ray image. The new model utilizes Mumford-Shah functional incorporating with a modified adaptive SOFM. Although Mumford-Shah model is an active contour model not based on the gradient of the image for finding edges in image, it has some limitation to accurately represent object images. To avoid this criticism, we utilize an adaptive self organizing feature map developed earlier by the authors.[1] It's learning rule is derived from Mumford-Shah energy function and the boundary of blurred and vague X ray image. The evolution of the neural network is shown to well segment and represent. To demonstrate the performance of the proposed method, segmentation of an industrial part is solved and the experimental results are discussed in detail.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.5
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• pp.841-849
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• 2001

The pixel information of the object was obtained sequentially and pixels were clustered to a label by the line labeling method. Feature points were determined by finding the slope for edge pixels after selecting the fixed number of edge pixels. The slope was estimated by the least square method to reduce the detection error. Once a matching point was determined by comparing the feature information of the object and the pattern, the parameters for translation, scaling and rotation were obtained by selecting the longer line of the two which passed through the matching point from left and right sides. Finally, modified Hausdorff Distance has been used to identify the similarity between the object and the given pattern. The multi-label method was developed for recognizing the patterns with more than one label, which performs the modified Hausdorff Distance twice. Experiments have been performed to verify the performance of the proposed algorithm and method for simple target image, complex target image, simple pattern, and complex pattern as well as the partially hidden object. It was proved via experiments that the proposed image matching algorithm for recognizing the object had a good performance of matching.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.5
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• pp.415-427
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• 1987

This paper presents an experimental model-based vision system which can identify and locate objects in scenes containing multiple occluded parts. The objects are assumed to be rigid and planar parts. In any recognition system the-type of objects that might appear in the image dictates the type of knowledge that is needed to recognize the object. The data is reduced to a sequential list of points or pixels that appear on the boundary of the objects. Next the boundary of the objects is smoothed using a polygonal approximation algorithm. Recognition cosists in finding the prototype that matches model to image. Now the hidden edge is reconstructed by transition model objects into occluded objects. The best match is obtained by optimising some similarity measure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1913-1934
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• 2022

The emergence of technologies like Big data analytics, Industrial Internet of Things, Internet of Things, and applicability of these technologies in various domains leads to increased demand in the underlying execution environment. The demand may be for compute, storage, and network resources. These demands cannot be effectively catered by the conventional cloud environment, which requires an integrated environment. The task of finding an appropriate service provider is tedious for a service consumer as the number of service providers drastically increases and the services provided are heterogeneous in the specification. A service broker is essential to find the service provider for varying service consumer requests. Also, the service broker should be smart enough to make the service providers best fit for consumer requests, ensuring that both service consumer and provider are mutually beneficial. A service broker in an integrated environment named Global Manager is proposed in the paper, which can find an appropriate service provider for every varying service consumer request. The proposed Global Manager is capable of identification of parameters for service negotiation with the service providers thereby making the providers the best fit to the maximum possible extent for every consumer request. The paper describes the architecture of the proposed Global Manager, workflow through the proposed algorithms followed by the pilot implementation with sample datasets retrieved from literature and synthetic data. The experimental results are presented with a few of the future work to be carried out to make the Manager more sustainable and serviceable.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.663-668
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• 2010

In driving a car, turns such as left turns, right turns, or u-turns, make the speed of the car decrease considerably. A more straight path, therefore, is probably faster to arrive at the destination than zig-zag path with same distance. In this paper, we have newly proposed the turn heuristic to make more straight path. The path navigation algorithm with turn heuristic(called as TA* algorithm) could enhance the straightness of a path by putting the turned-edges to the turn cost. It requires higher cost to use TA* algorithm than traditional A* algorithm because the straight-edge first searching have increased the search space. We have improved the TA* algorithm into the variable TA* algorithm(called as VTA* algorithm) which adopt the turn-heuristic during the a portion of the whole path.