• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.509-517
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• 2001

Full-search algorithm requires large amount of computation which causes time delay or very complex hardware architecture for real time implementation. In this paper, we propose a fast motion estimator based on bit-plane matching, which reduce the computational complexity and the hardware cost. In the proposed motion estimator, the conventional motion estimation algorithms are applied to the binary images directly extracted from the video sequence. Furthermore, in the proposed VLSI motion estimator, we employ a Pair of processing cores that calculate the motion vector continuously By controlling the data flow in a systolic fashion using the internal shift registers in the processing cores, we avoid using SRAM (local memory) so that we remove the time overhead for accessing the local memory and adopt lower-cost fabrication technology. We modeled and tested the proposed motion estimator in VHDL, and then synthesized the whole system which has been integrated in a 0.6-$\mu$m triple-metal CMOS chip of size 8.15 X 10.84$\textrm{mm}^2$.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.171-179
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• 2005

This paper presents the algorithm using fuzzy inference that preestimates each link speed changed by different kinds of road situations. The elements we are considered are time zone, rainfall probability information and lane control information. This paper is consists of three parts. First of all we set up the fuzzy variables, and preestimate link speed changed by various road situations. For this process, we build the membership functions for each fuzzy variable and establish the fuzzy inference relations to find how fuzzy variables influence on link speed. Second, using backtracking method, we search the shortest route influenced by link speed changed by fuzzy inference. Third, we apply this algorithm to hypothetical network and find the shortest path. As a result, it is shown that this algorithm choose appropriate roundabout path according to the changing road situations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5015-5022
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• 2010

Most of the existing pattern mining techniques are capable of searching patterns according to the continuous change of the spatial information of an object but there is no constraint on the spatial information that must be included in the extracted pattern. Thus, the existing techniques are not applicable to the optimal path search between specific nodes or path prediction considering the nodes that a moving object is required to round during a unit time. In this paper, the precision of the path search according to the spatial hierarchy is analyzed using the Spatial-Temporal Optimal Moving Pattern(with Frequency & Weight) (STOPM(FW)) algorithm which searches for the optimal moving path by considering the most frequent pattern and other weighted factors such as time and cost. The result of analysis shows that the database retrieval time is minimized through the reduction of retrieval range applying with the spatial constraints. Also, the optimal moving pattern is efficiently obtained by considering whether the moving pattern is included in each hierarchical spatial scope of the spatial hierarchy or not.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.1-14
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• 2000

The berth and crane scheduling problem in a container terminal encompasses the whole process of assigning berth to each ship, determining the duration of berthing, assigning container cranes to each ship, and determining the specific start and end time of each crane service, for all the ships scheduled to be arriving at the terminal during a certain scheduling horizon. This problem is basically a constraint satisfaction problem in which cranes and berths should be assigned in such a way that all the spatial and temporal constraints are satisfied without any interference. However, it is also an optimization problem because the requested arrival and departure time should be met for as many of the scheduled ships as possible, while the operation cost of the terminal should be minimized. In this paper, we present an effective and efficient approach to solving this type of problem, which combines constrain satisfaction search and heuristic repair. We first employ a constraint satisfaction search to find a feasib1e solution. Then, the feasible solution is modified to a more optimal one by iteratively applying our heuristic repair operations within the framework of constraint satisfaction search. Experimental results with a real data from Pusan East Container Terminal showed that our approach can derive a schedule of satisfactory quality in a very short time.

• Journal of KIISE:Information Networking
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• v.37 no.1
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• pp.35-41
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• 2010

Since the ad-hoc network allow nodes to communicate each other without infrastructure system and predefined configuration, it comes into the spotlight that is suitable to ubiquitous society. In ad-hoc network, route recovery mechanism is considered important. Normally route recovery is needed to solve the link failure problem because there is no route maintaining system like a router in ad-hoc networks. In this paper we propose BS-AODV(Bidirectional Searching-AODV) route recovery method. The proposed method is a local repair method that can be applied in all of the network area. Unlike a limited local repair method in AODV. the proposed method adopts the bidirectional searching method where the upstream/downstream nodes can send the route maintenance messages. Restricting the flooding of route request messages, the proposed scheme attempts to minimize the costs of local repair, the performance of the proposed scheme is evaluated through the simulations. In two scenarios which variate the node numbers and node speed, the comparison among the proposed scheme, AODV and AOMDV is shown in terms of the control traffic and data delivery ratio.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.767-773
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• 2014

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and there have been various systems which have been recently studied. For a successful economic ship routing system, it is needed to properly control an engine power or change a geographical path considering weather forecast. An optimal geographical path is difficult to be determined, though, because it is a minimal dynamic-cost path search problem where the actual fuel consumption is dynamically variable by the weather condition when the ship will pass the area. In this paper, we propose an geographical path-search algorithm based on evolutionary strategy to efficiently search a good quality solution out of tremendous candidate solutions. We tested our approach with the shortest path-based sailing method over seven testing routes and observed that the former reduced the estimated fuel consumption than the latter by 1.82% on average and the maximum 2.49% with little difference of estimated time of arrival. In particular, we observed that our method can find a path to avoid bad weather through a case analysis.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.320-330
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• 2004

Query languages for XML use paths in a data graph to represent queries. Actually, paths in a data graph are used as a basic constructor of an XML query. User can write more expressive Queries by using Patterns (e.g. regular expressions) for paths. There are many identical paths in a data graph because of the feature of semi-structured data. Current researches for indexing XML utilize identical paths in a data graph, but such an index can grow larger than source data graph and cannot guarantee efficient access path. In this paper we propose a partitioning technique that can partition all the paths in a data graph. We develop an index graph that can find appropriate partitions for a path query efficiently. The size of our index graph can be adjusted regardless of the source data. So, we can significantly improve the cost for index graph traversals. In the performance study, we show our index much faster than other graph based indexes.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.487-495
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• 2023

Ammonia is either a crucial resource of fertilizer production for solving the food problem of mankind or an important energy source as both an eco-friendly hydrogen carrier and a carbon-free fuel. Therefore, nowadays ammonia synthesis and decomposition become promising. Then, a catalyst is required to effectively perform the ammonia synthesis and decomposition. In order to design high-performing as well as cheap novel catalysts for ammonia synthesis and decomposition, it is necessary to test huge amount of catalyst candidates, but it is inevitably time-consuming and expensive to search and analyze using only traditional approaches. Recently, new methods using machine learning which is one of the core technologies of the 4th industrial revolution that can quickly and accurately search high-performance catalysts has been emerging. In this paper, we investigate reaction mechanisms of ammonia synthesis and decomposition, and we described recent research and prospects of machine learning-driven methods that can efficiently find high-performing and economical catalysts for ammonia synthesis and decomposition.

• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.2797-2806
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• 2000

Recently, DDSs(Distributed Database Systems) have been implemented on V AN(V alue Added Network) as we know the amazing expansion of information network. DDS can yield significant cost and response time advantages over centralized systems for geographically distributed organizations. However, inappropriate design can result in high cost and poor response time to maintain the database at each site. In a DDS design, the main problem is how to select proper computer and how to allocate data fragment into a proper site. In this paper, we address DDS design problem of selecting the proper class of computers and the allocating data files on VAN. Also, the formulated model includes two objectives, the waited response time and the investment cost to include their relationship. Specially, the formulation of waited response time is based on M/M/1 queueing system to evaluate more precisely. GA(Genetic Algorithm), a kind of heuristic search method, is developed to search an optimal solution in the proposed design model and we show the simulation result to examine the algorithm performance.

• Information Systems Review
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• v.16 no.1
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• pp.37-50
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• 2014

Conventional case-based reasoning (CBR) does not perform efficiently for high volume dataset because of case-retrieval time. In order to overcome this problem, some previous researches suggest clustering a case-base into several small groups, and retrieve neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performances than the conventional CBR. This paper suggests a new hybrid case-based reasoning method which dynamically composing a searching pool for each target case. This method is applied to diagnose for the heart disease dataset. The results show that the suggested hybrid method produces statistically the same level of predictive performances with using significantly less computational cost than the CBR method and also outperforms the basic clustering-CBR (C-CBR) method.