• Journal of the Korean Operations Research and Management Science Society
• /
• v.21 no.3
• /
• pp.197-214
• /
• 1996

Financial analysis of stock data usually involves extensive computation of large amount of time series data sets. To handle the large size of the data sets and complexity of the analyses, database management systems have been increasingly adaopted for efficient management of stock data. Specially, relational database management system is employed more widely due to its simplistic data management approach. However, the normalized two-dimensional tables and the structured query language of the relational system turn out to be less effective than expected in accommodating time series stock data as well as the various computational operations. This paper explores a new data management approach to stock data management on the basis of an object-oriented database management system (ODBMS), and proposes a data model supporting times series data storage and incorporating a set of financial analysis functions. In terms of functional stock data analysis, it specially focuses on a primitive set of operations such as variance of stock data. In accomplishing this, we first point out the problems of a relational approach to the management of stock data and show the strength of the ODBMS. We secondly propose an object model delineating the structural relationships among objects used in the stock data management and behavioral operations involved in the financial analysis. A prototype system is developed using a commercial ODBMS.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.2
• /
• pp.56-64
• /
• 1998

Multi-layered perceptrons that are a nonlinear neural network model, have been widely used for various applications mainly thanks to good function approximation capability for nonlinear fuctions. However, for digital hardware implementation of the multi-layere perceptrons, the quantization scheme using "look-up tables (LUTs)" is commonly employed to handle nonlinear signmoid activation functions in the neworks, and thus requires large amount of storage to prevent unacceptable quantization errors. This paper is concerned with a new effective methodology for digital hardware implementation of multi-layered perceptrons, and proposes a "piecewise affine approximation" method in which input domain is divided into (small number of) sub-intervals and nonlinear sigmoid function is linearly approximated within each sub-interval. Using the proposed method, we develop an expression and an error backpropagation type learning algorithm for a multi-layered perceptron, and compare the performance with the quantization method through Monte Carlo simulations on XOR problems. Simulation results show that, in terms of learning convergece, the proposed method with a small number of sub-intervals significantly outperforms the quantization method with a very large storage requirement. We expect from these results that the proposed method can be utilized in digital system implementation to significantly reduce the storage requirement, quantization error, and learning time of the quantization method.quantization method.

• Wind and Structures
• /
• v.12 no.6
• /
• pp.505-517
• /
• 2009

Synchronous wind-induced pressures, measured in wind-tunnel tests on model buildings instrumented with hundreds of pressure taps, are an invaluable resource for designing safe buildings efficiently. They enable a much more detailed, accurate representation of the forces and moments that drive engineering design than conventional tables and graphs do. However, the very large volumes of data that such tests typically generate pose a challenge to their widespread use in practice. This paper explains how a wavelet representation for the time series of pressure measurements acquired at each tap can be used to compress the data drastically while preserving those features that are most influential for design, and also how it enables incremental data transmission, adaptable to the accuracy needs of each particular application. The loss incurred in such compression is tunable and known. Compression rates as high as 90% induce distortions that are statistically indistinguishable from the intrinsic variability of wind-tunnel testing, which we gauge based on an unusually large collection of replicated tests done under the same wind-tunnel conditions.

• The Korean Journal of Applied Statistics
• /
• v.26 no.4
• /
• pp.595-610
• /
• 2013

Testing of order-restricted alternative hypothesis in $2{\times}k$ contingency tables can be applied to various fields of medicine, sociology, and business administration. Most testing methods have been developed based on a large sample theory. In the case of a small sample size or unbalanced sample size, the Type I error rate of the testing method (based on a large sample theory) is very different from the target point of 5%. In this paper, the exact testing method is introduced in regards to the testing of an order-restricted alternative hypothesis in categorical data (particularly if a small sample size or extreme unbalanced data). Power and exact p-value are calculated, respectively.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.10
• /
• pp.3272-3279
• /
• 2000

In this paper, we propose two fast VQ coclebook search algorithms efficient to the Wavelet/ VQ coding schemes. It is well known that the probability having large values in wavelet coefficient blocks is very low. In order to apply this property to codebook search, the index tables of the reordered codebook in each wavelet subband ae used. The exil condition in PDE can be satisfied in an earlystage by comparing the large coefficients of the codeword with their corresponding elements of input vector using the index tbles. As a result, search time can be reduced.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2599-2613
• /
• 2015

Multi-index hashing (MIH) is the state-of-the-art method for indexing binary codes, as it di-vides long codes into substrings and builds multiple hash tables. However, MIH is based on the dataset codes uniform distribution assumption, and will lose efficiency in dealing with non-uniformly distributed codes. Besides, there are lots of results sharing the same Hamming distance to a query, which makes the distance measure ambiguous. In this paper, we propose a data-oriented multi-index hashing method (DOMIH). We first compute the covariance ma-trix of bits and learn adaptive projection vector for each binary substring. Instead of using substrings as direct indices into hash tables, we project them with corresponding projection vectors to generate new indices. With adaptive projection, the indices in each hash table are near uniformly distributed. Then with covariance matrix, we propose a ranking method for the binary codes. By assigning different bit-level weights to different bits, the returned bina-ry codes are ranked at a finer-grained binary code level. Experiments conducted on reference large scale datasets show that compared to MIH the time performance of DOMIH can be improved by 36.9%-87.4%, and the search accuracy can be improved by 22.2%. To pinpoint the potential of DOMIH, we further use near-duplicate image retrieval as examples to show the applications and the good performance of our method.

• The KIPS Transactions:PartD
• /
• v.14D no.6
• /
• pp.597-604
• /
• 2007

Stream data is a continuous flow of information that mostly arrives as the form of an infinite rapid stream. Recently researchers show a great deal of interests in analyzing such data to obtain value added information. Here, we propose an efficient cube computation algorithm for multidimensional analysis of stream data. The fact that stream data arrives in an unsorted fashion and aggregation results can only be obtained after the last data item has been read. cube computation requires a tremendous amount of memory. In order to resolve such difficulties, we compute user selected aggregation fables only, and use a combination of an way and AVL trees as a temporary storage for aggregation tables. The proposed cube computation algorithm works even when main memory is not large enough to store all the aggregation tables during the computation. We showed that the proposed algorithm is practically fast enough by theoretical analysis and performance evaluation.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.2
• /
• pp.197-204
• /
• 2014

This paper investigates a design of optimization database structure layout of Message Oriented Analysis and Management Tool (MOMAT) for naval combat systems (NCS). The NCS is composed of heterogeneous and large-scale component such as communication service and data distribution servcies (DDS). Each components are massively made the data as components. To manage the messages, MOMAT is developed. Typical modeling tool have problems that low performance due to duplicate database tables. An efficient design that one of the database optimization is proposed to solve the problems in this paper. It reduces the number of tables and improves application response and processing time. Experiment results shows that an availability of proposed method in MOMAT and decrease of both amount of data from client node to server and sever load.

• Journal of Digital Contents Society
• /
• v.11 no.1
• /
• pp.91-97
• /
• 2010

Flash memory has been used by many digital devices for data storage, exploiting the advantages of non-volatility, low power, stability, and so on, with the help of high integrity, large capacity, and low price. As the fast growing popularity of flash memory, the density of it increases so significantly that its entire address mapping table becomes too big to be stored in SRAM. This paper proposes the associated page address cache with an efficient table management scheme for hybrid flash translation layer mapping. For this purpose, all tables are integrated into a map block containing entire physical page tables. Simulation results show that the proposed scheme can save the extra memory areas and decrease the searching time with less 2.5% of miss ratio on PC workload and can decrease the write overhead by performing write operation 33% out of total writes requested.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2009.10a
• /
• pp.185-189
• /
• 2009

It is very important to control the vibration transmitted from external utilities and the transient response due to the internal sources for the precision equipment, which is very sensitive to the vibration environment. The anti-vibration tables that use air springs have been widely used due to their excellent isolation performance, but the systems with high flexibility have the critical problem of large transient response by the impulsive force of the moving mass in operation of the equipment. In this paper, the hybrid vibration control system is proposed, which is combined the air springs with the semi-active MR dampers in order to satisfy the performances of isolation and vibration reduction simutaneously.