• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1669-1679
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• 1996

In this paper, we address the problem of how to replace huffers in multimedia database systems with time-varying skewed data access. The access pattern in the multimedia database system to support audio-on-demand and video-on-demand services is generally skewed with a few popular objects. In addition the access pattem of the skewed objects has a time-varying property. In such situations, our analysis indicates that conventional LRU(least Recently Used) and LFU(Least Frequently Used) schemes for buffer replacement algorithm(ABRN:Adaptive Buffer Replacement using Neural suited. We propose a new buffer replacement algorithm(ABRN:Adaptive Buffer Replacement using Neural Networks)using a neural network for multimedia database systems with time-varying skewed data access. The major role of our neural network classifies multimedia objects into two classes:a hot set frequently accessed with great popularity and a cold set randomly accessed with low populsrity. For the classification, the inter-arrival time values of sample objects are employed to train the neural network.Our algorithm partitions buffers into two regions to combine the best roperties of LRU and LFU.One region, which contains the 핫셋 objects, is managed by LFU replacement and the other region , which contains the cold set objects , is managed by LRUreplacement.We performed simulation experiments in an actual environment with time-varying skewed data accsee to compare our algorithm to LRU, LFU, and LRU-k which is a variation of LRU. Simulation resuults indicate that our proposed algorthm provides better performance as compared to the other algorithms. Good performance of the neural network-based replacement scheme means that this new approach can be also suited as an alternative to the existing page replacement and prefetching algorithms in virtual memory systems.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4835-4855
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• 2015

TV white space (TVWS) is showing promise to become the first widespread practical application of cognitive technology. In fact, regulators worldwide are beginning to allow access to the TV band for secondary users, on the provision that they access the geolocation database. Device-to-device (D2D) can improve the spectrum efficiency, but large-scale D2D communications that underlie TVWS may generate undesirable interference to TV receivers and cause severe mutual interference. In this paper, we use an established geolocation database to investigate the power allocation problem, in order to maximize the total sum throughput of D2D links in TVWS while guaranteeing the quality-of-service (QoS) requirement for both D2D links and TV receivers. Firstly, we formulate an optimization problem based on the system model, which is nonconvex and intractable. Secondly, we use an effective approach to convert the original problem into a series of convex problems and we solve these problems using interior point methods that have polynomial computational complexity. Additionally, we propose an iterative algorithm based on the barrier method to locate the optimal solution. Simulation results show that the proposed algorithm has strong performance with high approximation accuracy for both small and large dimensional problems, and it is superior to both the active set algorithm and genetic algorithm.

• The KIPS Transactions:PartD
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• v.17D no.6
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• pp.405-414
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• 2010

A rule is defined as a case to determine the target values according to combination of various Business factors. The information system is used to represent enterprise's business, which includes and implements the amount of these rules to Rule-Based System. A Rule-Based System can be constructed by using the rules engine method or Relational Database technology. Because the rules engine method has some disadvantages, the Rule-Based System is mostly developed with Relational Database technology. When business scales become larger and more complex, a large number of various rule cases must be operated in system, and processing these rule cases requires additional time, overhead and storage space, and the speed of execution slows down. To solve these problems, we propose a simplification algorithm that converts a large amount of rule cases to simplification rule cases with same effects. The proposed algorithm is applied to hypothetical business rule data and a large number of simplification experiments and tests are conducted. The final results proved that the number of rows can be reduced to some extent. The proposed algorithm can be used to simplify business rule data for improving performance of the Rule-Based System implemented with the Relational Database.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.185-192
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• 1998

A new algorithm is proposed in this paper which efficiently performs join in the temporal database. The main idea is to sort the smaller relation and to partition the larger relation, and the proposed algorithm reduces the cost of sorting the larger relation. To show the usefulness of the algorithm, the cost is analyzed with respect to the number of accesses to secondary storage and compared with that of Sort-Merge algorithm. Through the comparisons, we present and verify the conditions under which the proposed algorithm always outperforms the Sort-Merge algorithm. The comparisons show that the proposed algorithm achieves 10∼30% gain under those conditions.

• Journal of Welding and Joining
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• v.31 no.5
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• pp.35-40
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• 2013

In this paper, we propose the Tangible Virtual Reality Representation Method to using haptic device and feature to morphology of created bead from Flux Cored Arc Welding. The virtual reality was started to rising for reduce to consumable materials and welding training risk. And, we will expected maximize virtual reality from virtual welding training. In this paper proposed method is get the database to changing the input factor such as work angle, travelling angle, speed, CTWD. And, it is visualization to bead from extract to optimal morphological feature information to using the Neural Network algorithm. The database was building without error to extract data from automatic robot welder. Also, the Neural Network algorithm was set a dataset of the highest accuracy from verification process in many times. The bead was created in virtual reality from extract to morphological feature information. We were implementation to final shape of bead and overlapped in process by time to using bead generation algorithm and calibration algorithm for generate to same bead shape to real database in process of generating bead. The best advantage of virtual welding training, it can be get the many data to training evaluation. In this paper, we were representation bead to similar shape from generated bead to Flux Cored Arc Welding. Therefore, we were reduce the gap to virtual welding training and real welding training. In addition, we were confirmed be able to maximize the performance of education from more effective evaluation system.

• The Journal of Information Technology and Database
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• v.6 no.2
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• pp.19-28
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• 1999

Digital image and video libraries require new algorithms for the automated extraction and indexing of salient image features. Eigen values of an image provide one important cue for the discrimination of image content. In this paper we propose a new approach for automated content extraction that allows efficient database searching using eigen values. The algorithm automatically extracts eigen values from the image matrix represented by the covariance matrix for the image. We demonstrate that the eigen values representing shape information and the skewness of its distribution representing complexity provide good performance in image query response time while providing effective discriminability. We present the eigen value extraction and indexing techniques. We test the proposed algorithm of searching by eigen value and its skewness on a database of 100 images.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.331-336
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• 2005

Post translational modifications (PTMs) discovery is an important problem in proteomic. In the past, people discover PTMs by Tandem Mass Spectrometer based on ‘bottom-up’ strategy. However, such strategy suffers from the problem of failing to discover all PTMs. Recently, due to the improvement in proteomic technology, Taylor et al. proposed a database software to discover PTMs with ‘topdown’ strategy by FTMS, which avoids the disadvantages of ‘bottom-up’ approach. However, their proposed algorithm runs in exponential time, requires a database of proteins, and needs prior knowledge about PTM sites. In this paper, a new algorithm is proposed which can work without a protein database and can identify modifications in polynomial time. Besides, no prior knowledge about PTM sites is needed.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.6
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• pp.183-193
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• 2003

Most construction works on the soft ground adopt instrumentation to manage settlement and stability of the embankment. The rapid progress of the information technologies and the digital data acquisition on the soft ground instrumentation has led to the fast-growing amount of data. Although valuable information about the behaviour of the soft ground may be hiding behind the data, most of the data are used restrictedly only for the management of settlement and stability. One of the critical issues on soft ground instrumentation is the long-term settlement prediction. Some observational settlement analysis methods are used for this purpose. But the reliability of the analysis results is remained in vague. The knowledge could be discovered from a large volume of experiences on the observational settlement analysis. In this article, we present a database to store settlement records and data mining procedure. A large volume of knowledge about observational settlement prediction were collected from the database by applying the filtering algorithm and knowledge discovery algorithm. Statistical analysis revealed that the reliability of observational settlement analysis depends on stay duration and estimated degree of consolidation.

• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.291-294
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• 1995

본논문은 POW algorithm과 알고리즘을 통해 수행된 결과인 large scale word recognizer를 위한 POW set에 대하여 설명하겠다. Large scale word recognizer를 위한 speech database를 구축하기 위해서는 모든 가능한 phonological phenomenon이 POW set에 포함 되어얗 ks다. 또한 POW set의 음운 현상들의 분포는 추출하고자 하는 모집단의 음운현상들의 분포와 유사해야 한다. 위와 같은 목적으로 다음과 같이 3가지 성질을 갖는 POW set을 추출하기 위한 새로운 algorithm을 제안한다. 1. 모집단에서 발생하는 모든 음운현상을 포함해야 한다. 2, 최소한의 단어 집합으로 구성되어야 한다. 3. POW set과 모집단의 음운현상의 분포가 유사해야 한다. 우리는 약 300만 어절의 한국어 text corpus로부터 5천 단어의 고빈도 어절을 추출하고 이로부터 한국어 POW set을 추출하였다.