• ETRI Journal
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• v.25 no.3
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• pp.179-186
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• 2003

Using biometrics to verify a person's identity has several advantages over the present practices of personal identification numbers (PINs) and passwords. At the same time, improvements in VLSI technology have recently led to the introduction of smart cards with 32-bit RISC processors. To gain maximum security in verification systems using biometrics, verification as well as storage of the biometric pattern must be done in the smart card. However, because of the limited resources (processing power and memory space) of the smart card, integrating biometrics into it is still an open challenge. In this paper, we propose a fingerprint verification algorithm using a multi-resolution accumulator array that can be executed in restricted environments such as the smart card. We first evaluate both the number of instructions executed and the memory requirement for each step of a typical fingerprint verification algorithm. We then develop a memory-efficient algorithm for the most memory-consuming step (alignment) using a multi-resolution accumulator array. Our experimental results show that the proposed algorithm can reduce the required memory space by a factor of 40 and can be executed in real time in resource-constrained environments without significantly degrading accuracy.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1849-1857
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• 1999

We proposed the RPA (Recursive Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. This algorithm recursively partitions the pattern space until each hyperrectangle contains only those patterns of the same class, then it computes the average values of patterns in each hyperrectangle to extract a representative. Also we have used the mutual information between the features and classes as weights for features to improve the classification performance. The proposed algorithm used 30~90% of memory space that is needed in the k-NN (k-Nearest Neighbors) classifier, and showed a comparable classification performance to the k-NN. Also, by reducing the number of stored patterns, it showed an excellent result in terms of classification time when we compare it to the k-NN.

• Journal of the Korean Home Economics Association
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• v.42 no.9
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• pp.99-109
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• 2004

In residential spaces, sanitary zones are where the most basic needs of human beings are met and are used by all members of the family. A high level of privacy is therefore required in their use. This research studies the current state of sanitary zones in collective houses and in detached houses from a comparative perspective first, and then analyses the satisfaction and dissatisfaction requirement levels of dwellers of each house in comparison so as to provide data to formulate a new design for sanitary zones that is suitable for each dwelling house. The results of this research are as follows. (1) The questionnaire respondents were mostly in their 30s and 40s (99.1% in total), and lived in a nuclear family system (87.7%). (2) The number of sanitary zones was found to be more than 2 in 62% of collective houses and in 60.7% of detached houses, which leads us to conclude that non-dwelling spaces are increasing in both types of houses. (3) Of the housing facilities,13% of collective houses and 9% of detached houses were equipped with a bidet. Both percentages are very low but it needs to be noted that the percentage is relatively high in collective houses. In safety facilities, the ratio of houses furnished with safety handlers for the aged was very low in both types of houses. (4) The residents of collective houses showed high levels of dissatisfaction with regard to the problems of storage space and steam production, while residents of detached houses expressed high levels of dissatisfaction with regard to the heating system, colors of finishing materials, size, dampness, steam production, and storage space.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.313-318
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• 1998

Electro-Optical Camera(EOC) is the main payload of Korea Multi-Purpose SATellite(KOMPSAT) with the mission of cartography to build up a digital map of Korean territory including Digital Terrain Elevation Map(DTEM). This instrument which comprises EOC Sensor Assembly and EOC Electronics Assembly produces the panchromatic images of 6.6 m GSD with a swath wider than 17 km by push-broom scanning and spacecraft body pointing in a visible range of wavelength, 510 ~ 730 nm. The high resolution panchromatic image is to be collected for 2 minutes during 98 minutes of orbit cycle covering about 800 km along ground track, over the mission lifetime of 3 years with the functions of programmable rain/offset and on-board image data storage. The image of 8 bit digitization, which is collected by a full reflective type F8.3 triplet without obscuration, is to be transmitted to Ground Station at a rate less than 25 Mbps. EOC was elaborated to have the performance which meets or surpasses its requirements of design phase. The spectral response the modulation transfer function, and the uniformity of all the 2592 pixel of CCD of EOC are illustrated as they were measured for the convenience of end-user. The spectral response was measured with respect to each gain setup of EOC and this is expected to give the capability of generating more accurate panchromatic image to the EOC data users. The modulation transfer function of EOC was measured as greater than 16% at Nyquist frequency over the entire field of view which exceeds its requirement of larger than 10%, The uniformity that shows the relative response of each pixel of CCD was measured at every pixel of the Focal Plane Array of EOC and is illustrated for the data processing.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.143-151
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• 2017

The generalized Hough transform(GHough) can be used effectively for detecting and extracting an arbitrary-shaped 2-D model in an input image. However, the main drawbacks of the GHough are both heavy computation and an excessive storage requirement. Thus, most of the researches so far have focused on reducing both the time and space requirement of the GHough. But it is still not clear how well their improved algorithms will perform under various noise in an input image. Thus, this paper proposes a new framework that can measure the performance of the GHough quantitatively. For this purpose, we view the GHough as a detector in signal detection theory and the ROC curve will be used to specify the performance of the GHough. Finally, we show that we can evaluate the GHough under various noise conditions in an input image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1157-1177
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• 2014

Convertible authenticated encryption (CAE) schemes enable the signer to send a confidential message and its corresponding signature to the designated recipient. The recipient can also convert the signature into a conventional one which can be verified by anyone. Integrating the properties of self-certified public key systems, this paper presents efficient and computationally indistinguishable self-certified CAE schemes for strengthening the security of E-Commerce applications. Additionally, we also adapt the proposed schemes to elliptic curve systems for facilitating the applications of limited computing power and insufficient storage space. The proposed schemes are secure against known existential active attacks, satisfy the semantic security requirement, and have the following advantages: (i) No extra certificate is required since the tasks of authenticating the public key and verifying the signature can be simultaneously carried out within one step, which helps reducing computation efforts and communication overheads. (ii) In case of a later dispute, the recipient can convert the signature into an ordinary one for the public arbitration. (iii) The signature conversion can be solely performed by the recipient without additional computation efforts or communication overheads. (iv) The recipient of the signature can prove himself, if needed, to anyone that he is actually the designated recipient.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.87-94
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• 2004

The feature subset selection is used as a preprocessing step of a teaming algorithm. If collected data are irrelevant or redundant information, we can improve the performance of learning by removing these data before creating of the learning model. The feature subset selection can also reduce the search space and the storage requirement. This paper proposed a new feature subset selection algorithm that is using the heuristic function based on entropy to evaluate the performance of the abstracted feature subset and feature selection. The ACS algorithm was used as a search method. We could decrease a size of learning model and unnecessary calculating time by reducing the dimension of the feature that was used for learning.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1516-1522
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• 2007

We had proposed the FPA(Fixed Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. The algorithm worked not bad in many area, but it lead to some overhead for memory usage and lengthy computation in the multi classes area. We propose an Repetitive FPA algorithm which repetitively partitioning pattern space in the multi classes area. Our proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.824-830
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• 2003

RPA (Recursive Partition Averaging) method was proposed in order to improve the storage requirement and classification rate of the Memory Based Reasoning. That algorithm worked well in many areas, however, the major drawbacks of RPA are it's pattern averaging mechanism. We propose an adaptive OHC algorithm which uses the FPD(Feature-based Population Densimeter) to increase the classification rate of RPA. The proposed algorithm required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the RPA. Also, by reducing the number of stored patterns, it showed a excellent results in terms of classification when we compare it to the k-NN.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.1
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• pp.77-87
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• 2015

For a floating offshore plant such as FPSO(Floating, Production, Storage, and Off-loading unit), various equipment should be installed in the restricted space, as compared with an onshore plant. The requirement for an optimal layout method of the plant has been increased in these days. Thus, a layout method of the floating offshore plant was proposed in this study. For this, an optimization problem for layout design was mathematically formulated, and then an optimization algorithm based on the genetic algorithm was implemented with C++ language in order to solve it. Finally, the proposed method was applied to an example of FPSO topsides. As a result, it was shown that the proposed method can be applied to layout design of the floating offshore plant such as FPSO.