• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2188-2195
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• 1999

This paper proposes a new call admission control scheme utilizing an inverse fuzzy vector quantizer(IFVQ) and neuralnet, which combines benefits of IFVQ and flexibilities of FCM(Fuzzy-C-Means) arithmetics, to decide whether a requested call not to be trained in learning phase to be connected or not. The system generates the estimated traffic pattern for the cell stream of a new call, using feasible/infeasible patterns in codebook, fuzzy membership values that represent the degree to which each pattern of codebook matches input pattern, and FCM arithmetics. The input to the NN is the vector consisted of traffic parameters which are the means and variances of the number of cells arriving in decision as to whether to accept or reject a new call depends on whether the NN is used for decision threshold(+0.5). This method is a new technique for call admission control using the membership values as traffic parameter which declared to CAC at the call set up stage, and this is valid for a very general traffic model in which the calls of a stream can belong to an unlimited number of traffic classes. Through the simulations, it is founded the performance of the suggested method outperforms compared to the conventional NN method.

• Journal for History of Mathematics
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• v.22 no.3
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• pp.45-60
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• 2009

Mathematical thinking can be symbolized by the external signs, and these signs determine in reverse the form of mathematical thinking. Each symbol - a symbol in algebra, a symbol in analysis, and a diagram which verifies syllogism - reflects the diverse characteristic of cogitation in mathematics and perfirms a heuristic function.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.283-290
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• 1998

A solution method is presented to solve the eigenproblem arising in tile dynamic analysis of non-proportional damping systems with symmetric matrices. The method is based on tile use of Lanczos method to generate a Krylov subspace of trial vectors, witch is then used to reduce a large eigenvalue problem to a much smaller one. The method retains the η order quadratic eigenproblem, without the need to the method of matrix augmentation traditionally used to cast the problem as a linear eigenproblem of order 2n. In the process, the method preserves tile sparseness and symmetry of the system matrices and does not invoke complex arithmetics, therefore, making it very economical for use in solving large problems. Numerical results are presented to demonstrate the efficiency and accuracy of the method.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.1985-1996
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• 1998

A parallelising algorithm for partitioning and mapping methods of matrix/vector multiplication into linear processor array/VLW simulator is presented in this paper. First we discuss the mapping methods for input matrix or vector into the arbitrarily size of processor arrays. Then, we show partitioning the algorithmss of the large size of computational problem into the size of the processor array. We execute the algorithm on VLIW simuhator and show to effectiviness of algorithm. The result which we achived better parallelising performance on our VLIW simulator dsign than on linear processor array.

• Journal of Sensor Science and Technology
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• v.30 no.5
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• pp.290-294
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• 2021

Experts have designed popular and successful model architectures, which, however, were not the optimal option for different scenarios. Despite the remarkable performances achieved by deep neural networks, manually designed networks for classification tasks are the backbone of object detection. One major challenge is the ImageNet pre-training of the search space representation; moreover, the searched network incurs huge computational cost. Therefore, to overcome the obstacle of the pre-training process, we introduce a network adaptation technique using a pre-trained backbone model tested on ImageNet. The adaptation method can efficiently adapt the manually designed network on ImageNet to the new object-detection task. Neural architecture search (NAS) is adopted to adapt the architecture of the network. The adaptation is conducted on the MobileNetV2 network. The proposed NAS is tested using SSDLite detector. The results demonstrate increased performance compared to existing network architecture in terms of search cost, total number of adder arithmetics (Madds), and mean Average Precision(mAP). The total computational cost of the proposed NAS is much less than that of the State Of The Art (SOTA) NAS method.

• Annual Conference of KIPS
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• 2024.05a
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• pp.404-407
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• 2024

동형암호는 주목받는 차세대 프라이버시 보존 기술이며, 이를 활용한 신경망 연산 연구들이 많이 수행되고 있다. 여러 체계들 중 TFHE는 비산술 연산을 직접 연산할 수 있으나 다른 체계들보다 매우 느리다는 단점이 있다. 본 연구는 정확도 하락을 최소화하며 성능 개선을 통해 다른 체계인 CKKS보다 빠른 TFHE기반 CNN 연산이 가능하도록 하는 TFHE 비산술 연산의 양자화 기술을 소개한다.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1351-1362
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• 1992

Qualitative models in model-based expert system needs modeling paradigm which provides intelligent control of modeling assumptions and extracts robust inferences without quantitative information about the system to be modeled. Qualitative reasoning methodologies has proved the property of the completeness but not the soundness to the corresponding quantitative model. We propose new methodology of qualitative reasoning by introducing the concept of Centroid-Oriented Composite Interval to improve the soundness problem. Arithmetic operations and equivalence classes were composed using this definition. Qualitative simulation results were compared to Kuipers's results and the improvements in the soundness problem is verified.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.6
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• pp.313-319
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• 2019

Finite field operations have played an important role in error correcting codes and cryptosystems. Recently, the necessity of efficient computation processing is increasing for security in cyber physics systems. Therefore, efficient implementation of finite field arithmetics is more urgently needed. These operations include addition, multiplication, division and inversion. Addition is very simple and can be implemented with XOR operation. The others are somewhat more complicated than addition. Among these operations, multiplication is the most important, since time-consuming operations, such as exponentiation, division, and computing multiplicative inverse, can be performed through iterative multiplications. In this paper, we propose a multiplexer based parallel computation algorithm that performs Montgomery multiplication over finite field using redundant basis. Then we propose an efficient multiplexer based semi-systolic multiplier over finite field using redundant basis. The proposed multiplier has less area-time (AT) complexity than related multipliers. In detail, the AT complexity of the proposed multiplier is improved by approximately 19% and 65% compared to the multipliers of Kim-Han and Choi-Lee, respectively. Therefore, our multiplier is suitable for VLSI implementation and can be easily applied as the basic building block for various applications.

• Journal for History of Mathematics
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• v.20 no.4
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• pp.153-174
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• 2007

The concept of Function is not just a single concept but an integrated concept that includes various mathematic topics such as arithmetics, geometry and so on. Therefore, the concept of function is the basic principal underlying mathematics. Moreover, we should think of function as conceptual expedient for understanding the phenomena in the variously changing real world. Therefore in this article, I would like to consider the concept of an integrated function through historical investigation. Especially, from the middle ages to the 19th century, representation which related to the function has been evolved, and therefore, I will consider function as an integrated concept through changing the concept of function.

• Journal of Educational Research in Mathematics
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• v.18 no.1
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• pp.51-62
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• 2008

In the 7th-curriculum, only basic arithmetics of complex numbers have been taught. They are taught formally like literal manipulations. This paper analyzes mathematically essential relations between algebra of complex numbers and plane geometry. Historical analysis is also performed to find effective methods of teaching complex numbers in school mathematics. As a result, we can integrates this analysis with school mathematics by help of Viete's operations on right triangles. We conclude that teaching geometric interpretation of complex numbers is possible in school mathematics.