• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.05a
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• pp.243-246
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• 2005

As seen in constant reference to our modern are as the 'Information Age', our daily lives are flooded with a variety of information. Under such circumstance, efficient management and distribution of information are increasingly needed. When it comes to office environment, the role of furniture is very important because furniture must be placed in the office and it also serves as an essential component to improve work efficiency. As the importance of furniture increases, office furniture reflects diverse needs. That is to say, office furniture is used to partition space while reflecting mental and emotional state of workers in the office. At this backdrop, it can be perceived that office goes beyond a place where work is done. In order to contemplate how office and office furniture enhance work efficiency and create pleasant, delightful office environment, the study in this paper identified and examined overall color images of office, and color use and color preference in office furniture. The purposes of this study were: 1) to identify the use of and preference for color images of office 2) to analyze the color images of office furniture and understand its color use and color preference; 3) to understand the color use and color preference in office storage furniture.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.377-382
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• 2006

Advantageous features of flash memory are stimulating its exploitation in mobile and ubiquitous related devices. The hardware characteristics of flash memory however place restrictions upon this current trend. In this paper, a cleaning policy for flash memory is proposed in order to decrease the necessary penally for recycling of memory minimizing the degradation of performance at the same time. The proposed cleaning algorithm is based on partitioning of candidate memory regions, to be reclaimed as free, into a number of groups. In addition, in order to improve the balanced utilization of the entire flash memory space in terms of 'wearing-out', a free segment selection algorithm is discussed. The impact of the proposed algorithms is evaluated through a number of experiments. Moreover, the composition of the optimal configuration featuring the proposed methods is tested through experiments.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.97-114
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• 2022

Interest is increasing in electrocardiogram (ECG) signal analysis for embedded devices, creating the need to develop an algorithm suitable for a low-power, low-memory embedded device. Linear approximation of the ECG signal facilitates the detection of fiducial points by expressing the signal as a small number of vertices. However, dynamic programming, a global optimization method used for linear approximation, has the disadvantage of high complexity using memoization. In this paper, the calculation area and memory usage are improved using a linear approximated template. The proposed algorithm reduces the calculation area required for dynamic programming through local optimization around the vertices of the template. In addition, it minimizes the storage space required by expressing the time information using the error from the vertices of the template, which is more compact than the time difference between vertices. When the length of the signal is L, the number of vertices is N, and the margin tolerance is M, the spatial complexity improves from O(NL) to O(NM). In our experiment, the linear approximation processing time was 12.45 times faster, from 18.18 ms to 1.46 ms on average, for each beat. The quality distribution of the percentage root mean square difference confirms that the proposed algorithm is a stable approximation.

• Journal of the Korean housing association
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• v.25 no.6
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• pp.57-66
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• 2014

With regard to the pavilion buildings of Imcheonggak Gunjajeong and Donglakdang Gyejeong that are located within residential areas, this study focused on the construction background, the building owner's circumstances and the location environment of these buildings, and attempted to derive the architectural characteristics presented by these two pavilion buildings and, through this, to grasp the architect's intention of plan. The results of this study are as follows. With regard to Gunjajeong, it could be confirmed that, first, it is located in a propitious site and took the composition that follows the family ritual standards for the family rituals of the scholar-gentry class and opens to visitor access, and second, the floor height of the site and interior space was designed so that Munpilbong on the south and the Sarangchae on the west, and the Sadang on the east can be connected visually, and third, the authority and dignity of the head family were built through the symmetric 丁-shaped plane figure, the wide partition module, the form-centered building, and the hierarchical composition of the roof. On the other hand, with regard to Gyejeong, it could be confirmed that, first, it is located along the stream of Jagye valley that has no mountains in the front and in the back and took the composition that put the name symbolizing Taoist thoughts on the surrounding natural environment and was closed to visitor access but opens to nature, and second, with Jagye and Jagye surroundings as the main landscape, it built the concept of intended landscape that symbolizes the Taoist thoughts by giving names not only simply to the visible objects but also to surrounding rocks, and third, the asymmetric ㄱ-shaped plane composed a yard-centered space rather than emphasizing the shape, and connected the part of the plane with Jagye so as to be embodied as a personal inner self-perfecting place that closely communicates only with nature away from the mundane world.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.346-348
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• 2004

In this rarer, we introduce a new Fuzzy Polynomial Neural Networks (FPNNs)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNs based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNs-like structurenamed Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. In considering the structures of FPNN-like networks such as FPNN and FSPNN, they are almost similar. Therefore they have the same shortcomings as well as the same virtues on structural side. The proposed design procedure for networks' architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IG) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using gas furnace process dataset.

• Journal of the Korea Convergence Society
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• v.6 no.3
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• pp.51-57
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• 2015

This paper proposes an efficient method such as Extended Three Region Partitioning Method for nested loops with irregular dependences for maximizing parallelism. Our approach is based on the Convex Hull theory, and also based on minimum dependence distance tiling, the unique set oriented partitioning, and three region partitioning methods. In the proposed method, we eliminate anti dependences from the nested loop by variable renaming. After variable renaming, we present algorithm to select one or more appropriate lines among given four lines such as LMLH, RMLH, LMLT and RMLT. If only one line is selected, the method divides the iteration space into two parallel regions by the selected line. Otherwise, we present another algorithm to find a serial region. The selected lines divide the iteration space into two parallel regions as large as possible and one or less serial region as small as possible. Our proposed method gives much better speedup and extracts more parallelism than other existing three region partitioning methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.781-792
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• 2015

This paper proposes a virtual and invisible private disk (VIPDISK) technology equipped with the secure storage devices. As a software based security technology, it can create hidden partitions on any data storage device which can not be identified by the windows OS, so the program running on it, does not have any evidence of the existence of the hidden storage space. Under inactive state, it maintains an unexposed secure partition which can only be activated with a matching combination of a unique digital key and a user password to open the decryption tool. In addition, VIPDISK can store data to secure storage device with real-time encryption, it is worry-free even in the case of lost or theft. Simulation results show that VIPDISK provides a much higher level of security compared to other existing schemes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.433-436
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• 2004

In this paper, we introduce a new Fuzzy Polynomial Neural Networks (FPNNS)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNS based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNS-like structure named Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. The proposed design procedure for networks architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IC) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using the time series dataset of gas furnace process.

• Bulletin of the Korean Mathematical Society
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• v.53 no.5
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• pp.1531-1548
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• 2016

Let C[0, t] denote the space of real-valued continuous functions on [0, t] and define a random vector $Z_n:C[0,t]{\rightarrow}\mathbb{R}^n$ by $Z_n(x)=(\int_{0}^{t_1}h(s)dx(s),{\ldots},\int_{0}^{t_n}h(s)dx(s))$, where 0 < $t_1$ < ${\cdots}$ < $ t_n=t$ is a partition of [0, t] and $h{\in}L_2[0,t]$ with $h{\neq}0$ a.e. Using a simple formula for a conditional expectation on C[0, t] with $Z_n$, we evaluate a generalized analytic conditional Wiener integral of the function $G_r(x)=F(x){\Psi}(\int_{0}^{t}v_1(s)dx(s),{\ldots},\int_{0}^{t}v_r(s)dx(s))$ for F in a Banach algebra and for ${\Psi}=f+{\phi}$ which need not be bounded or continuous, where $f{\in}L_p(\mathbb{R}^r)(1{\leq}p{\leq}{\infty})$, {$v_1,{\ldots},v_r$} is an orthonormal subset of $L_2[0,t]$ and ${\phi}$ is the Fourier transform of a measure of bounded variation over $\mathbb{R}^r$. Finally we establish various change of scale transformations for the generalized analytic conditional Wiener integrals of $G_r$ with the conditioning function $Z_n$.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.477-490
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• 2006

Existing index structures need very much update cost because they repeat delete and insert operations in order to update continuously moving objects. In this paper, we propose a new index structure which reduces the update cost of continuously moving objects. The proposed index structure consists of a space partitioning index structure that stores the location of the moving objects and an auxiliary index structure that directly accesses to their current positions. In order to increase the fanout of the node, it stores not the real partitioning area but kd-tree as the information about the child node of the node. In addition, we don't traverse a whole index structure, but access the leaf nodes directly and accomplish a bottom-up update strategy for efficiently updating the positions of moving objects. We show through the various experiments that our index structure outperforms the existing index structures in terms of insertion, update and retrieval.