• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.377-385
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• 2015

This paper proposes a novel forward vehicle tracking algorithm based on the WMIL(Weighted Multiple Instance Learning) equipped with a particle filter. In the proposed algorithm Haar-like features are used to train a vehicle object detector to be tracked and the location of the object are obtained from the recognition result. In order to combine both the WMIL to construct the vehicle detector and the particle filter, the proposed algorithm updates the object location by executing the propagation, observation, estimation, and selection processes involved in particle filter instead of finding the credence map in the search area for every frame. The proposed algorithm inevitably increases the computation time because of the particle filter, but the tracking accuracy was highly improved compared to Ababoost, MIL(Multiple Instance Learning) and MIL-based ones so that the position error was 4.5 pixels in average for the videos of national high-way, express high-way, tunnel and urban paved road scene.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.53-63
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• 2008

In this paper, we propose the regional travel time measurement algorithm using the sequence pattern matching to the type of vehicles between the origin of the region and the end of the region, that could be able to overcome the limit of conventional method such as Probe Car Method or AVI Method by License Plate Recognition. This algorithm recognizes the vehicles as a sequence group with a definite length, and measures the regional travel time by searching the sequence of the origin which is the most highly similar to the sequence of the end. According to the assumption of similarity cost function, there are proposed three types of algorithm, and it will be able to estimate the average travel time that is the most adequate to the information providing period by eliminating the abnormal value caused by inflow and outflow of vehicles. In the result of computer simulation by the length of region, the number of passing cars, the length of sequence, and the average maximum error rate are measured within 3.46%, which means that this algorithm is verified for its superior performance.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1593-1601
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• 2017

In a big data platform, association rule mining applications could bring some benefits. For instance, in a agricultural big data platform, the association rule mining application could recommend specific products for farmers to grow, which could increase income. The key process of the association rule mining is the frequent itemsets mining, which finds sets of products accompanying together frequently. Former researches about this issue, e.g. Apriori, are not satisfying enough because huge possible sets can cause memory to be overloaded. In order to deal with it, SON algorithm has been proposed, which divides the considered set into many smaller ones and handles them sequently. But in a single machine, SON algorithm cause heavy time consuming. In this paper, we present a method to find association rules in our Hadoop based big data platform, by parallelling SON algorithm. The entire process of association rule mining including pre-processing, SON algorithm based frequent itemset mining, and association rule finding is implemented on Hadoop based big data platform. Through the experiment with real dataset, it is conformed that the proposed method outperforms a brute force method.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.247-258
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• 2004

Recently, there have been researches on storage and retrieval technique of moving objects, which are highly concerned by user in database application area such as video databases, spatio-temporal databases, and mobile databases. In this paper, we propose a new signature-based indexing scheme which supports similar sub-trajectory retrieval at well as good retrieval performance on moving objects trajectories. Our signature-based indexing scheme is classified into concatenated signature-based indexing scheme for similar sub-trajectory retrieval, entitled CISR scheme and superimposed signature-based indexing scheme for similar sub-trajectory retrieval, entitled SISR scheme according to generation method of trajectory signature based on trajectory data of moving object. Our indexing scheme can improve retrieval performance by reducing a large number of disk access on data file because it first scans all signatures and does filtering before accessing the data file. In addition, we can encourage retrieval efficiency by appling k-warping algorithm to measure the similarity between query trajectory and data trajectory. Final]y, we evaluate the performance on sequential scan method(SeqScan), CISR scheme, and SISR scheme in terms of data insertion time, retrieval time, and storage overhead. We show from our experimental results that both CISR scheme and SISR scheme are better than sequential scan in terms of retrieval performance and SISR scheme is especially superior to the CISR scheme.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1601-1614
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• 2008

The number of web service users has been increased rapidly as existing services are changed into the web-based internet applications. Therefore, it is necessary for us to use web log pre-processing technique to detect attacks on diverse web service transactions and it is also possible to extract web mining information. However, existing mechanisms did not provide efficient pre-processing procedures for a huge volume of web log data. In this paper, we proposed both a field based parsing and a high-speed log indexing mechanism based on the suggested B-tree Index Vector structure for performance enhancement. In experiments, the proposed mechanism provides an efficient web log pre-processing and search functions with a session classification. Therefore it is useful to enhance web attack detection function.

• Journal of the Korea Computer Graphics Society
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• v.20 no.2
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• pp.25-32
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• 2014

We present an example-based approach to synthesizing physically simulated Rube Goldberg machines in which a series of rigid body elements are sequentially triggered and driven along the causal chain. Given a set of elements, our goal is to automatically instantiate and arrange those elements to meet the user-specified requirements including the start and end positions, and the boundary of movement. To do so, we first sample small-scale machines consisting of only a few elements randomly, and represent the connectivity between every pair of components as a graph structure. Searching over possible paths in this graph solves our problem by finding a path that can be unrolled to satisfy the given requirements, and then assembling components sequentially along the solution path. In order to ensure that the machine works precisely in a physically simulated environment, we finally elaborate the layout of assembled components by a simple greedy algorithm. We demonstrate the usefulness of our approach by displaying a large diversity of Rube Goldberg machines built with only five kinds of elements.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.10
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• pp.53-60
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• 2009

Due to increased integration density and reduced threshold voltages, leakage current reduction becomes important in the semiconductor IC design for low power consumption. In a combinational logic circuit, the leakage current in the standby state depends on the values of the input. In this research, we developed a new input vector control method to minimize the leakage power. A new efficient algorithm is developed to find the minimal leakage vector. It can reduce the leakage current by 15.7% from the average leakage current and by 6.7% from the results of simulated evolution method during standby or idle states for a set of benchmark circuits. The minimal leakage input vector, with idle input signal, can also reduce the leakage current by 6.8% from the average leakage current and by 3.2% from the results of simulated evolution method for sequential circuits.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.291-305
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• 2013

Collective traffic data (BPS, PPS etc.) for detection against the distributed denial of service attack on network is the time sequencing big data. The algorithm to detect the change point in the big data should be accurate and exceed in detection time and detection capability. In this work, the sliding window and discretization method is used to detect the change point in the big data, and propose five nonparametric test statistics using empirical distribution functions and ranks. With various distribution functions and their parameters, the detection time and capability including the detection delay time and the detection ratio for five test methods are explored and discussed via monte carlo simulation and illustrative examples.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.17-29
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• 2010

A container terminal productivity is maximized by a minimized time for processing containers. So, we have been elevated the container terminal productivity through an improvement of computing system, but there are a limitation because of problems for transportation management and method. A Y/T(Yard Tractor), which is a representative transportation, is able to do only one process, loading or unloading, at one time. So if the Y/T can do loading and unloading step by step at a same time, the processing time would be shortened. In this paper, we proposed an effective operating process of Y/T(Yard Tractor) Multi-Cycle System by applying RTLS(Real Time Location System) to Y/T(Yard Tractor) in order to improve the process of loading and unloading at the container terminal. For this, we described Multi-Cycle System. This system consists of a real time location of Y/T based on RTLS, an indicating of Y/T location in real time with GIS technology, and an algorithm(Dijkstra's algorithm) of the shortest distance. And we used the system in container terminal process and could improve the container terminal productivity. As the result of simulation for the proposed system in this paper, we could verify that 9% of driving distance was reduced compared with the existing rate and 19% of driving distance was reduced compared with the maximum rate. Consequently, we could find out the container performance is maximized.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.115-126
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• 2012

Mashups have become very popular over the last few years, and their use also varies for IT convergency services. In spite of their popularity, there are several challenging issues when combining Open APIs into mashups, First, since portal sites may have a large number of APIs available for mashups, manually searching and finding compatible APIs can be a tedious and time-consuming task. Second, none of the existing portal sites provides a way to leverage semantic techniques that have been developed to assist users in locating and integrating APIs like those seen in traditional SOAP-based web services. Third, although suitable APIs have been discovered, the integration of these APIs is required for in-depth programming knowledge. To solve these issues, we first show that existing techniques and algorithms used for finding and matching SOAP-based web services can be reused, with only minor changes. Next, we show how the characteristics of APIs can be syntactically defined and semantically described, and how to use the syntactic and semantic descriptions to aid the easy discovery and composition of Open APIs. Finally, we propose a goal-directed interactive approach for the dynamic composition of APIs, where the final mashup is gradually generated by a forward chaining of APIs. At each step, a new API is added to the composition.