• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.199-206
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• 2009

The development of broadband multimedia content, a deaf sign language sign language is being used in education. Most of the content used in sign language training for Hangul word representation of sign language is sign language videos for the show. For the first time to learn sign language, sign language users are unfamiliar with the sign language characteristics difficult to understand, difficult to express the sign is displayed. In this paper, online, learning sign language to express the sign with reference to the attributes, Semantic Logic applying the sign language of multimedia content model for video-based platform is designed to study.

• Bulletin of the Korean Mathematical Society
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• v.43 no.2
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• pp.343-352
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• 2006

A real matrix A is called a sign-central matrix if for, every matrix $\tilde{A}$ with the same sign pattern as A, the convex hull of columns of $\tilde{A}$ contains the zero vector. A sign-central matrix A is called a tight sign-central matrix if the Hadamard (entrywise) product of any two columns of A contains a negative component. A real vector x = $(x_1,{\ldots},x_n)^T$ is called stable if $\|x_1\|{\leq}\|x_2\|{\leq}{\cdots}{\leq}\|x_n\|$. A tight sign-central matrix is called a $tight^*$ sign-central matrix if each of its columns is stable. In this paper, for a matrix B, we characterize those matrices C such that [B, C] is tight ($tight^*$) sign-central. We also construct the matrix C with smallest number of columns among all matrices C such that [B, C] is $tight^*$ sign-central.

• Communications of the Korean Mathematical Society
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• v.25 no.1
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• pp.11-18
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• 2010

The work in this paper was motivated by [3], where Eschenbach and Li listed four 4 by 4 sign patterns, conjectured to be nilpotent sign patterns of nilpotence index at least 3. These sign patterns with no zero entries, called full sign patterns, are shown to be potentially nilpotent of nilpotence index 3. We also generalize these sign patterns of order 4 so that we provide classes of n by n sign patterns of nilpotence indices at least 3, if they are potentially nilpotent. Furthermore it is shown that if a full sign pattern A of order n has nilpotence index k with $2{\leq}k{\leq}n-1$, then sign pattern A has nilpotent realizations of nilpotence indices k, k + 1, $\ldots$, n. Hence, the four 4 by 4 sign patterns in [3, page 91] also allow nilpotent realizations of nilpotence index 4.

• Bulletin of the Korean Mathematical Society
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• v.56 no.2
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• pp.305-318
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• 2019

A sign pattern is a matrix whose entries belong to the set {+, -, 0}. An n-by-n sign pattern ${\mathcal{A}}$ is said to allow an eventually positive matrix or be potentially eventually positive if there exist at least one real matrix A with the same sign pattern as ${\mathcal{A}}$ and a positive integer $k_0$ such that $A^k>0$ for all $k{\geq}k_0$. Identifying the necessary and sufficient conditions for an n-by-n sign pattern to be potentially eventually positive, and classifying the n-by-n sign patterns that allow an eventually positive matrix are two open problems. In this article, we focus on the potential eventual positivity of broom sign patterns. We identify all the minimal potentially eventually positive broom sign patterns. Consequently, we classify all the potentially eventually positive broom sign patterns.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1355-1362
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• 2021

Recently, not only congenital hearing impairment, but also the number of people with hearing impairment due to acquired factors is increasing. The environment in which sign language can be learned is poor. Therefore, this study intends to present a sign language (sign language number/sign language text) evaluation system as a sign language learning assistance tool for sign language learners. Therefore, in this paper, sign language is captured as an image using OpenCV and Convolutional Neural Network (CNN). In addition, we study a system that recognizes sign language behavior using MediaPipe, converts the meaning of sign language into text-type data, and provides it to users. Through this, self-directed learning is possible so that learners who learn sign language can judge whether they are correct dez. Therefore, we develop a sign language learning assistance system that helps us learn sign language. The purpose is to propose a sign language learning assistance system as a way to support sign language learning, the main language of communication for the hearing impaired.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.325-330
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• 2022

This paper conducts the collection and experiment of datasets for deep learning research on sign language such as sign language recognition, sign language translation, and sign language segmentation for Korean sign language. There exist difficulties for deep learning research of sign language. First, it is difficult to recognize sign languages since they contain multiple modalities including hand movements, hand directions, and facial expressions. Second, it is the absence of training data to conduct deep learning research. Currently, KETI dataset is the only known dataset for Korean sign language for deep learning. Sign language datasets for deep learning research are classified into two categories: Isolated sign language and Continuous sign language. Although several foreign sign language datasets have been collected over time. they are also insufficient for deep learning research of sign language. Therefore, we attempted to collect a large-scale Korean sign language dataset and evaluate it using a baseline model named TSPNet which has the performance of SOTA in the field of sign language translation. The collected dataset consists of a total of 11,402 image and text. Our experimental result with the baseline model using the dataset shows BLEU-4 score 3.63, which would be used as a basic performance of a baseline model for Korean sign language dataset. We hope that our experience of collecting Korean sign language dataset helps facilitate further research directions on Korean sign language.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.508-524
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• 2021

Innovative translation circumstances encouraged by scientific technique have become an element that increases realization and possibility of expanding sign language translation and Korean sign language translation is facing a new challenge and opportunity. This study raises following questions and search for answers. First, when and how did Korean sign language translation appear in the course of the historical changes in Korean sign language? Second, what is the form and characteristic of translation produced as a result of Korean sign language translation? Third, what is the present condition and prospect of Korean sign language translation? Accordingly, this study examined how Korean sign language translation was formed historically and the form and characteristics of Korean sign language translation using integrated literature review method. As a result of the study, first, the form and characteristics of Korean sign language translation classified according to the historical transition process into latent phase, formation phase, and expansion phase were revealed. Second, the forms and characteristics of Korean sign language translation according to the Korean sign language corpus project and machine translation were derived. In addition, it apprehends its present condition and proposes its future prospect.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.167-177
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• 2024

This paper proposes optimization techniques for SeaSign, an isogeny-based digital signature algorithm. SeaSign combines class group actions of CSIDH with the Fiat-Shamir with abort. While CSIDH-based algorithms have regained attention due to polynomial time attacks for SIDH-based algorithms, SeaSiogn has not undergone significat optimization because of its inefficiency. In this paper, an efficient signing method for SeaSign is proposed. The proposed signing method is simple yet powerful, achived by repositioning the rejection sampling within the algorithm. Additionally, this paper presnts parameters that can provide optimal performance for the proposed algorithm. As a result, by using the original parameters of SeaSign, the proposed method is three times faster than the original SeaSign. Additonally, combining the newly suggested parameters with the signing method proposed in this paper yields a performance that is 290 times faster than the original SeaSign and 7.47 times faster than the method proposed by Decru et al.

• Structural Engineering and Mechanics
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• v.55 no.2
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• pp.365-377
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• 2015

Large-amplitude vibration of overhead sign structures can cause unfavorable psychological responses in motorists, interfere with readability of the signs, and lead to fatigue cracking in the sign structures. Field experience in Texas suggests that an overhead sign structure can vibrate excessively when supported within the span of a highway bridge instead of at a bent. This study used finite element modeling to analyze the dynamic displacement response of three hypothetical sign structures subjected to truck-passage-induced vertical oscillations recorded for the girders from four actual bridges. The modeled sign bridge structures included several span lengths based on standard design practices in Texas and were mounted on precast concrete I-girder bridges. Results revealed that resonance with bridge girder vertical vibrations can amplify the dynamic displacement of sign structures, and a specific range of frequency ratios subject to undesirable amplification was identified. Based on these findings, it is suggested that this type of sign structure be located at a bridge bent if its vertical motion frequency is within the identified range of bridge structure excitation frequencies. Several alternatives are investigated for cases where this is not possible, including increasing sign structure stiffness, reducing sign mass, and installing mechanical dampers.

• International Journal of Highway Engineering
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• v.15 no.1
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• pp.155-161
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• 2013

PURPOSES: This study is to develop a road traffic sign recognition and automatic positioning for road facility management. METHODS: In this study, we installed the GPS, IMU, DMI, camera, laser sensor on the van and surveyed the car position, fore-sight image, point cloud of traffic signs. To insert automatic position of traffic sign, the automatic traffic sign recognition S/W developed and it can log the traffic sign type and approximate position, this study suggests a methodology to transform the laser point-cloud to the map coordinate system with the 3D axis rotation algorithm. RESULTS: Result show that on a clear day, traffic sign recognition ratio is 92.98%, and on cloudy day recognition ratio is 80.58%. To insert exact traffic sign position. This study examined the point difference with the road surveying results. The result RMSE is 0.227m and average is 1.51m which is the GPS positioning error. Including these error we can insert the traffic sign position within 1.51m CONCLUSIONS: As a result of this study, we can automatically survey the traffic sign type, position data of the traffic sign position error and analysis the road safety, speed limit consistency, which can be used in traffic sign DB.