• Journal of the Korean Mathematical Society
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• v.49 no.5
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• pp.1065-1082
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• 2012

In this paper we first investigate the existence of the generalized Fourier-Feynman transform of the functional F given by $$F(x)={\hat{\nu}}((e_1,x)^{\sim},{\ldots},(e_n,x)^{\sim})$$, where $(e,x)^{\sim}$ denotes the Paley-Wiener-Zygmund stochastic integral with $x$ in a very general function space $C_{a,b}[0,T]$ and $\hat{\nu}$ is the Fourier transform of complex measure ${\nu}$ on $B({\mathbb{R}}^n)$ with finite total variation. We then define two sequential transforms. Finally, we establish that the one is to identify the generalized Fourier-Feynman transform and the another transform acts like an inverse generalized Fourier-Feynman transform.

• Journal of the Korean Mathematical Society
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• v.51 no.6
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• pp.1321-1322
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• 2014

• Journal of KIISE
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• v.42 no.4
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• pp.483-486
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• 2015

Security systems that use face recognition are vulnerable to spoofing attacks where unauthorized individuals use a photo or video of authorized users. In this work, we propose a method to detect a face spoofing attack with a video of an authorized person. The proposed method uses three sequential frames in the video to extract features by using Fourier Transform and Dense-SIFT filter. Then, classification is completed with a Support Vector Machine (SVM). Experimental results with a database of 200 valid and 200 spoof video clips showed 99% detection accuracy. The proposed method uses simplified features that require fewer memory and computational overhead while showing a high spoofing detection accuracy.

• Journal of KIISE
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• v.42 no.3
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• pp.289-294
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• 2015

The consensus problem is finding a representative string, called a consensus, of a given set S of k strings. Circular strings are different from linear strings in that the last symbol precedes the first symbol. Given a set S of circular strings of length n over an alphabet ${\Sigma}$, we first present an $O({\mid}{\Sigma}{\mid}nlogn)$ time parallel algorithm for finding a consensus of S minimizing both radius and distance sum when k=3 using O(n) threads. Then we present an $O({\mid}{\Sigma}{\mid}n^2logn)$ time parallel algorithm for finding a consensus of S minimizing distance sum when k=4 using O(n) threads. Finally, we compare execution times of our algorithms implemented using CUDA with corresponding sequential algorithms.

• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1542-1552
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• 1999

자료 병렬성이란 자료 집합의 원소들에 대하여 동일한 작업을 동시에 수행하므로써 얻어지는 병렬성을 말한다. 함수형 언어에서 자료 집합에 대한 반복 수행은 재귀적 자료형에 대한 재귀 함수에 의하여 표현된다. 본 논문에서는 이러한 재귀 함수를 자료 병렬 프로그램으로 변환하기 위한 병렬화 방법을 제시한다. 생성되는 병렬 프로그램의 병렬 수행 구조로는 일반적인 형태의 재귀적 자료형에 대하여 정의되는 다형적인 자료 병렬 연산을 사용하여 트리, 리스트 등과 같은 일반적인 재귀적 자료 집합에 대한 자료 병렬 수행이 가능하도록 하였다. 재귀 함수의 병렬화를 위해서는, 함수를 이루는 각각의 계산들의 병렬성을 재귀 호출에 의해 존재하는 의존성에 기반하여 분류하고, 이에 기반하여 각각의 계산들에 대한 적절한 자료 병렬 연산을 사용하는 병렬 프로그램을 생성하였다.Abstract Data parallelism is obtained by applying the same operations to each element of a data collection. In functional languages, iterative computations on data collections are expressed by recursions on recursive data structures. We propose a parallelization method for data-parallel implementation of such recursive functions. We employ polytypic data-parallel primitives to represent the parallel execution structure of the object programs, which enables data parallel execution with general recursive data structures, such as trees and lists. To transform sequential programs to their parallelized versions, we propose a method to classify the types of parallelism in subexpressions, based on the dependencies of the recursive calls, and generate the data-parallel programs using data-parallel primitives appropriately.

• ETRI Journal
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• v.46 no.4
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• pp.648-659
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• 2024

Author verification is challenging because of the diversity in writing styles. We propose an enhanced handwriting verification method that combines handcrafted and automatically extracted features. The method uses a genetic algorithm to reduce the dimensionality of the feature set. We consider offline Bangla handwriting content and evaluate the proposed method using handcrafted features with a simple logistic regression, radial basis function network, and sequential minimal optimization as well as automatically extracted features using a convolutional neural network. The handcrafted features outperform the automatically extracted ones, achieving an average verification accuracy of 94.54% for 100 writers. The handcrafted features include Radon transform, histogram of oriented gradients, local phase quantization, and local binary patterns from interwriter and intrawriter content. The genetic algorithm reduces the feature dimensionality and selects salient features using a support vector machine. The top five experimental results are obtained from the optimal feature set selected using a consensus strategy. Comparisons with other methods and features confirm the satisfactory results.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.395-406
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• 2006

This study was carried out to offer the systematical and scientific method of regional environment conservation by deciding the rank using fuzzy theory, and try to find the methodology to accurately accomplished the regional environment assessment for sound land conservation. The results were as follows. To transform the Likert's scale granted to assessment indicators into the type of triangular fuzzy number (a, b, c), there was conversion to each minimum (a), median (b), and maximum (c) in applying membership function. We used the center of gravity and eigenvalue leading to the rank. In the sequential analysis of rank-based test of assessment indicators by triangular fuzzy number, the result proclaimed that ranking of the indicators was, in the biotic field, in the order of 'dominance', 'sociality', 'coverage' and in the abiotic one, 'soil pH', 'T-N', 'soil property', and in the qualitative one, 'impact rating class', 'hemeroby degree', 'land use pattern', and in the functional one, 'protection of water resource', 'offer of recreation', 'protection of soil erosion'. Therefore, there was a difference between subjective rank from human and the rank from triangular fuzzy number. In other words, the scientific rank decision would be not so much being subjective and biased as dealing with human thoughts mathematically by triangular fuzzy number.

• Fisheries and Aquatic Sciences
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• v.25 no.4
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• pp.189-201
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• 2022

Jellyfish is an emerging aquaculture species, farmed for Oriental cuisines and nutraceutical ingredients. This study aimed to examine antioxidative and antimicrobial potentials of various fractions of the jellyfish, Acromitus hardenbergi. The bell and oral arms of the jellyfish were sequentially extracted with petroleum ether (PE), dichloromethane (DCM), chloroform (CHCl₃), methanol (MeOH), and water (H₂O) to extract its bioactive in an increasing polarity gradient. Test fractions were assayed for antiradical activities using electron spin resonance spectrometry, β-carotene-linoleate model and Folin-Ciocalteu assay; and antimicrobial activity against 2 Gram-negative bacteria, 4 Gram-positive bacteria and 2 fungal species using the disc diffusion assay. All fractions were also subjected to Fourier Transform Infrared (FTIR) analysis to identify types of functional groups present. It was found that the hydrophilic extracts (H₂O fractions) possessed the most effective radical scavenging activity (p < 0.05) while the lipophilic extracts (PE fractions) the most active antimicrobial activity, especially against Gram-positive bacteria (p < 0.05). Total oxidation substrates content was found to be highest in the PE fractions of jellyfish bell and oral arms (p < 0.05). FTIR data showed that the H₂O and MeOH fractions contains similar functional groups including -OH, -C=O, -N-H and -S=O groups, while the PE, DCM, and CHCl₃ fractions, the -CH₃, -COOH groups. This study showed that A. hardenbergi contains antioxidants and antimicrobials, thereby supporting the traditional claim of the jellyfish as an anti-aging and health-promoting functional food. Bioassay-guided fractionation approach serves as a critical milestone for the strategic screening, purification, and elucidation of therapeutically significant actives from jellyfish.