• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.29-38
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• 2011

In order to derive domain-independent heuristics from the specification of a planning problem, it is required to relax the given problem and then solve the relaxed one. In this paper, we present a new planning graph, Merged Planning Graph(MPG), and GD heuristics for solving contingent planning problems with both uncertainty about the initial state and non-deterministic action effects. The merged planning graph is an extended one to be applied to the contingent planning problems from the relaxed planning graph, which is a common means to get effective heuristics for solving the classical planning problems. In order to get heuristics for solving the contingent planning problems with sensing actions and non-deterministic actions, the new graph utilizes additionally the effect-merge relaxations of these actions as well as the traditional delete relaxations. Proceeding parallel to the forward expansion of the merged planning graph, the computation of GD heuristic excludes the unnecessary redundant cost from estimating the minimal reachability cost to achieve the overall set of goals by analyzing interdependencies among goals or subgoals. Therefore, GD heuristics have the advantage that they usually require less computation time than the overlap heuristics, but are more informative than the max and the additive heuristics. In this paper, we explain the experimental analysis to show the accuracy and the search efficiency of the GD heuristics.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.706-716
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• 2016

Because of efficient space utilization and fast key search times, B-trees have been widely accepted for the use of indexes in HDD-based DBMSs. However, when the B-ree is stored in flash memory, its costly operations of node updates may impair the performance of a DBMS. This is because the random updates in B-tree's leaf nodes could tremendously enlarge I/O costs for the garbage collecting actions of flash storage. To solve the problem, we make all the parents of leaf nodes the virtual nodes, which are not stored physically. Rather than, those nodes are dynamically generated and buffered by referring to their child nodes, at their access times during key searching. By performing node updates and tree reconstruction within a single flash block, our proposed B-tree can reduce the I/O costs for garbage collection and update operations in flash. Moreover, our scheme provides the better performance of key searches, compared with earlier flash-based B-trees. Through a mathematical performance model, we verify the performance advantages of the proposed flash B-tree.

• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.277-289
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• 2005

To overcome the long design time/high computational effort/low computational performance of phylogenetic learning featuring selection and reproduction, this paper proposes a genetic representation based on XML. Since genetic programs (GP) and genetic operations of this representation are maintained by the invocation of the built-in off-the-shelf XML parser's API, the proposed approach features significant reduced time consumption of GP design process. Handling only semantically correct GPs with standard XML schema can reduce search space and computational effort. Furthermore, computational performance can be improved by the parallelism of GP caused by the utilization of XML, which is a feasible system and wire format for migration of genetic programs in heterogeneous distributed computer environments. To verify the proposed approach, it is applied to the evolution of social behaviors of multiple agents modeling the predator-prey pursuit problem. The results show that the approach can be applied for fast development and time efficiency of GPs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2367-2372
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• 2009

Recently, Many studies have been progressing to path-finding adapted dynamic information on the Terminal Based Navigation System(TBNS). The algorithms proposed are based on $A^*$ algorithm. Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost. Path-finding with an abstract graph which expresses real road network as a simple graph is proposed for reducing dependency of heuristic and exploring cost. In this paper, two abstract graph that are different method of construction, Homogeneous Node merging($AG^H$) and Connected Node Merging($AG^C$), are implemented. In result of evaluation of performance, $AG^C$ has better performance than $AG^H$ at construction cost and the number of node access but $AG^C$ has worse performance than AGH at exploring cost.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.85-91
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• 2014

Nowadays, Dynamic lighting control and management skills are studied and used. If the system which is to manage multiple intelligent spot applied ubiquitous service technology is built with decision making and used in the complex intelligent space like a apartment then will improve energy efficiency and provide comfortability in optimal conditions. To solve this problem distributed autonomous control middleware and energy management system which process data gathering by zigbee mesh network and search proper services to save energy by the existing state of things is necessary. In paper we designed DDLEMS (Distributed Dynamic Lighting Energy Management System) that is to service duplex communication embedded by software based home server platform to provide mobile services in the smart place and support decision making about energy saving to the best use of wireless censor node and controled network, energy display devices.

• Journal of KIISE
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• v.43 no.9
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• pp.1034-1042
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• 2016

Together with machine-learning frameworks, area-based imagery registration techniques can be easily applied to diverse types of image pairs without predefined features and feature descriptors. However, feature detectors are often used to quickly identify candidate image patch pairs, limiting the applicability of these registration techniques. In this paper, we propose a ConvNet (Convolutional Network) "Dart" that provides not only the matching metric between patches, but also information about their distance, which are helpful in reducing the search space of the corresponding patch pairs. In addition, we propose a ConvNet "Fad" to identify the patches that are difficult for Dart to improve the accuracy of registration. These two networks were successfully implemented using Deep Learning with the help of a number of training instances generated from a few registered image pairs, and were successfully applied to solve a simple image registration problem, suggesting that this line of research is promising.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.245-248
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• 2009

Recently, Many studies have been progressing to path-finding with dynamic information on the Terminal Based Navigation System(TBNS). However, the most of existing algorithms are based on $A{\ast}$ algorithm. Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost in case of that there is no way determined by heuristic function or there are 2 way more which have almost same cost. In this paper, two abstract graph(AG) that are different method of construction, Homogeneous Node merging($AG^H$) and Connected Node Merging($AG^C$), are implemented. The abstract graph is a simple graph of real road network. The method of using the abstract graph is proposed for reducing dependency of heuristic and exploring cost. In result of evaluation of performance, $AG^C$ has better performance than $AG^H$ at construction cost but $AG^C$ has worse performance than $AG^H$ exploring cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5860-5876
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• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1873-1893
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• 2023

The development of lightweight, low energy and small-sized sensors incorporated with the wireless networks has brought about a phenomenal growth of Wireless Sensor Networks (WSNs) in its different fields of applications. Moreover, the routing of data is crucial in a wide number of critical applications that includes ecosystem monitoring, military and disaster management. However, the time-delay, energy imbalance and minimized network lifetime are considered as the key problems faced during the process of data transmission. Furthermore, only when the functionality of cluster head selection is available in WSNs, it is possible to improve energy and network lifetime. Besides that, the task of cluster head selection is regarded as an NP-hard optimization problem that can be effectively modelled using hybrid metaheuristic approaches. Due to this reason, an Improved Coyote Optimization Algorithm-based Clustering Technique (ICOACT) is proposed for extending the lifetime for making efficient choices for cluster heads while maintaining a consistent balance between exploitation and exploration. The issue of premature convergence and its tendency of being trapped into the local optima in the Improved Coyote Optimization Algorithm (ICOA) through the selection of center solution is used for replacing the best solution in the search space during the clustering functionality. The simulation results of the proposed ICOACT confirmed its efficiency by increasing the number of alive nodes, the total number of clusters formed with the least amount of end-to-end delay and mean packet loss rate.

• Journal of Radiation Protection and Research
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• v.30 no.1
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• pp.17-25
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• 2005

Since the safety of nuclear power plant has been becoming a big social issue the exposure dose of radiation for workers has been one of the important factors concerning the safety problem. The existing calculation methods of radiation dose used in the planning of radiation work assume that dose rate does not depend on the location within a work space thus the variation of exposure dose by different work path is not considered. In this study, a modified numerical method was presented to estimate the exposure dose during radiation work in radwaste storage considering the effects of the distance between a worker and sources. And a new numerical algorithm was suggested to search the optimal work path minimizing the exposure dose in pre-defined work space with given radiation sources. Finally, a virtual work simulation program was developed to visualize the exposure dose of radiation doting radiation works in radwaste storage and provide the capability of simulation for work planning. As a numerical example, a test radiation work was simulated under given space and two radiation sources, and the suggested optimal work path was compared with three predefined work paths. The optimal work path obtained in the study could reduce the exposure dose for the given test work. Based on the results, tile developed numerical method and simulation program could be useful tools in the planning of radiation work.