• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1656-1666
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• 1999

The more complex and large digital circuits become, the more important delay test becomes which guarantees that circuits operate in time. In this paper, the proposed algorithm is developed, which enable the fast indirect implication for efficient test pattern generation in sequential circuits of standard scan environment. Static learning algorithm enables application of a new implication value using contrapositive proposition. The static learning procedure found structurally, analyzes the gate structure in the preprocessing phase and store the information of learning occurrence so that it can be used in the test pattern generation procedure if it satisfies the implication condition. If there exists a signal line which include all paths from some particular primary inputs, it is a partitioning point. If paths passing that point have the same partial path from primary input to the signal or from the signal to primary output, they will need the same primary input values which separated by the partitioning point. In this paper test pattern generation can be more effective by using this partitioning technique. Finally, an efficient delay fault test pattern generator using indirect implication is developed and the effectiveness of these algorithms is demonstrated by experiments.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.413-420
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• 2006

Most vendors of digital signal processors (DSPs) support a Harvard architecture, which has two or more memory buses, one for program and one or more for data and allow the processor to access multiple words of data from memory in a single instruction cycle. We already addressed how to efficiently assign data to multi-memory banks in our previous work. This paper reports on our recent attempt to optimize run-time memory. The run-time environment for dual data memory banks (DBMBs) requires two run-time stacks to control activation records located in two memory banks corresponding to calling procedures. However, activation records of two memory banks for a procedure are able to have different size. As a consequence, dual run-time stacks can be unbalanced whenever a procedure is called. This unbalance between two memory banks causes that usage of one memory bank can exceed the extent of on-chip memory area although there is free area in the other memory bank. We attempt balancing dual run-time slacks to enhance efficiently utilization of on-chip memory in this paper. The experimental results have revealed that although our algorithm is relatively quite simple, it still can utilize run-time memories efficiently; thus enabling our compiler to run extremely fast, yet minimizing the usage of un-time memory in the target code.

• Journal of Internet Computing and Services
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• v.5 no.1
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• pp.67-84
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• 2004

Real-time database systems (RTDBS) are database systems whose transactions are associated with timing constraints such as deadlines. Therefore transaction needs to be completed by a certain deadline. Besides meeting timing constraints, a RTDBS needs to observe data consistency constraints as well. That is to say, unlike a conventional database system, whose main objective is to provide fast average response time, RTDBS may be evaluated based on how often transactions miss their deadline, the average lateness or tardiness of late transactions, the cost incurred in transactions missing their deadlines. Therefore, in RTDBS, transactions should be scheduled according to their criticalness and tightness of their deadlines, even If this means sacrificing fairness and system throughput, And It always must guarantee preceding process of the transaction with the higher priority. In this paper, we propose an efficient real-time scheduling algorithm (Multi-level EFDF) that alleviates problems of the existing real-time scheduling algorithms, a real-time concurrency control algorithm(2PL-FT) for firm and soft real-time transactions. And we compare the proposed 2PL F[ with AVCC in terms of the restarting ratio and the deadline missing ratio of transactions. We show through experiments that our algorithms achieve good performance over the other existing methods proposed earlier.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.1
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• pp.27-35
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.1-11
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• 2015

Recently, NAND flash memories are used for storage devices because of fast access speed and low-power. However, applications of FTL on low power computing devices lead to heavy workloads which result in a memory requirement and an implementation overhead. Consequently, studies of B+-Tree on embedded devices without the FTL have been proposed. The studies of B+-Tree are optimized for performance of inserting and updating records, considering to disadvantages of the NAND flash memory that it can not support in-place update. However, if a general garbage collection method is applied to the previous studies of B+-Tree, a performance of the B+-Tree is reduced, because it generates a rearrangement of the B+-Tree by changing of page positions on the NAND flash memory. Therefor, we propose a novel garbage collection method which can apply to the B+-Tree based on the NAND flash memory without the FTL. The proposed garbage collection method does not generate a rearrangement of the B+-Tree by using a block information table and a proxy block. We implemented the B+-Tree and ${\mu}$-Tree with the proposed garbage collection on physical devices with the NAND flash memory. In experiment results, the proposed garbage collection scheme compared to greedy algorithm garbage collection scheme increased the number of inserted keys by up to about 73% on B+-Tree and decreased elapsed time of garbage collection by up to about 39% on ${\mu}$-Tree.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.105-113
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• 2009

The interpretation of observed waveform characteristics identified in refraction and wide-angle reflection data increases confidence in the crustal structure model obtained. When calculating traveltimes and raypaths, wavefront methods on a regular grid based on graph theory are robust even with complicated structures, but basically compute only first arrivals. In this paper, we develop new algorithms to compute traveltimes and raypaths not only for first arrivals, but also for fast and later reflection arrivals, later refraction arrivals, and converted waves between P and S, using the modified wavefront method based on slowness network nodes mapped on a multi-layer model. Using the new algorithm, we can interpret reflected arrivals, Pg-later arrivals, strong arrivals appearing behind Pn, triplicated Moho reflected arrivals (PmP) to obtain the shape of the Moho, and phases involving conversion between P and S. Using two models of an ocean-continent transition zone and an oceanic ridge or seamount, we show the usefulness of this algorithm, which is confirmed by synthetic seismograms using the 2D Finite Difference Method (2D-FDM). Characteristics of arrivals and raypaths of the two models differ from each other in that using only first-arrival traveltime data for crustal structure analysis involves risk of erroneous interpretation in the ocean-continent transition zone, or the region around a ridge or seamount.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.481-484
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• 2013

Many people today are interested in Machine to Machine (M2M) as the new-generation growth engine of mobile communications service providers in Korea. Its use and application are broadening to various areas and the number of devices used for it is increasing to increase the number of information transmitted for each object. When the traffic reaches its limit while each set of data is transmitted from the devices divided into each group through the mobile network, M2M communications service might not be processed smoothly. This study used the Knapsack Problem algorithm to create a virtual simulator for a smooth M2M service when the mobile network used for the M2M communications reaches its limit. The virtual simulator applies smooth processing of services from the M2M communications that should be processed first to other subsequent services when data comes to each group of devices. As the M2M technology develops to make many objects more compact in size, it would help with smoother processing of M2M services for the mobile network with fast-increasing traffic.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.34-43
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• 2002

Since traditional static metadata set like Dublin Core has static metadata attributes about bibliography information, integration of metadata for various metadata, problems about standard and extension of metadata must be considered for applying it to new environment. Specially, as event-driven metadata write method included the notion of e-commerce come out for interoperability in digital libraries, traditional metadata management which cannot distinguish between different kinds of update operations to new extension of metadata set occurs unsuitable waiting of update operation. So, improvement is needed about it. In this paper, we show whether alleviative transaction consistency can be applied to digital library or not. Also it would divide newer metadata into static metadata attribute connected in read operation within user read-only transaction and dynamic metadata attribute in update operation within dynamic(e-commerce) update transactions. We propose newer metadata management algorithm considered in classfication of metadata attributes and dynamic update transaction. Using two version for minimal maintenance cost and ARU(Appended Refresh Unit) for dynamic update transaction, to minimize conflict between read and write operations shows fast response time and high recency ratio. As a result of the performance evaluation, we show our algorithm is proved to be better than other algorithms in newer metadata environments.

• Geophysics and Geophysical Exploration
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• v.2 no.4
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• pp.167-173
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• 1999

Since the resolution of the 2-D hole-to-hole seismic traveltime tomography is affected by the limited ray transmission angle, various methods were used to improve the resolution. Linear traveltime interpolation(LTI) ray tracing method was chosen for forward-modeling method. Inversion results using the LTI method were compared with those using the other ray tracing methods. As an inversion algorithm, SIRT method was used. In the iterative non-linear inversion method, the cost of ray tracing is quite expensive. To reduce the cost, each raypath was stored and the inversion was performed from this information. Using the proposed method, fast convergence was achieved. Inversion results are likely to be affected by the initial velocity guess, especially when the ray transmission angle was limited. To provide a good initial guess for the inversion, generalized regression neural network(GRNN) method was used. When the transmitted raypath angle is not limited or the geological model is very complex, the inversion results are not affected by initial velocity model very much. Since the raypath angles, however, are limited in most geophysical tomographic problems, the enhancement of resolution in tomography can be achieved by providing a proper initial velocity model by another inversion algorithm such as GRNN.