• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4788-4813
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• 2019

In this paper, we introduce concepts of optimal and near optimal secret data hiding schemes. We present a new digital image steganography approach based on the Galois field $GF(p^m)$ using graph and automata to design the data hiding scheme of the general form ($k,N,{\lfloor}{\log}_2p^{mn}{\rfloor}$) for binary, gray and palette images with the given assumptions, where k, m, n, N are positive integers and p is prime, show the sufficient conditions for the existence and prove the existence of some optimal and near optimal secret data hiding schemes. These results are derived from the concept of the maximal secret data ratio of embedded bits, the module approach and the fastest optimal parity assignment method proposed by Huy et al. in 2011 and 2013. An application of the schemes to the process of hiding a finite sequence of secret data in an image is also considered. Security analyses and experimental results confirm that our approach can create steganographic schemes which achieve high efficiency in embedding capacity, visual quality, speed as well as security, which are key properties of steganography.

• Corrosion Science and Technology
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• v.23 no.2
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• pp.93-103
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• 2024

In the present work, a phase-field model for dendritic solidification is applied to hot-dip ZnAlMg coatings to elucidate the morphology of zinc dendrites and the solute segregation leading to the formation of eutectics. These aspects define the microstructure that conditions the corrosion resistance and the mechanical behaviour of the coating. Along with modelling phase transformation and solute diffusion, the implemented model is partially coupled with the tracking of crystal orientation in solid grains, thus allowing the effects of surface tension anisotropy to be considered in multi-dendrite simulations. For this purpose, the composition of a hot-dip ZnAlMg coating is assimilated to a dilute pseudo-binary system. 1D and 2D simulations of isothermal solidification are performed in a finite element solver by introducing nuclei as initial conditions. The results are qualitatively consistent with existing analytical solutions for growth velocity and concentration profiles, but the spatial domain of the simulations is limited by the required mesh refinement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.736-743
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• 2020

Modular multiplication is one of the most important arithmetic operations in public-key cryptography such as elliptic curve cryptography (ECC) and RSA, and the performance of modular multiplier is a key factor influencing the performance of public-key cryptographic hardware. An efficient hardware implementation of word-based Montgomery modular multiplication algorithm is described in this paper. Our modular multiplier was designed to support eleven field sizes for prime field GF(p) and binary field GF(2k) as defined by SEC2 standard for ECC, making it suitable for lightweight hardware implementations of ECC processors. The proposed architecture employs pipeline scheme between the partial product generation and addition operation and the modular reduction operation to reduce the clock cycles required to compute modular multiplication by 50%. The hardware operation of our modular multiplier was demonstrated by FPGA verification. When synthesized with a 65-nm CMOS cell library, it was realized with 33,635 gate equivalents, and the maximum operating clock frequency was estimated at 147 MHz.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1407-1413
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• 2006

The field of medical images has been digitalized as the development of computer and the digitalization of the medical instruments. As a result it causes a lot of problems such as an illegal copy related to medical images and property right of the medical images. Therefore, digital watermarking is used for discrimination whether the data are modified or not. It is also used to protect both the property right of medical images and the private life of many patients. The proposed theories, the Non-blind and the Blind method, have two problems. One is needed an original image and the other is using a gaussian watermarking. This paper proposes the new Blind Watermarking using binary images in order to easily recognize the results of watermark. This algorism is described that an watermark of a binary image is wavelet-transformed, and then a transformed watermark is inserted in medium-band of frequency domains of original image by the Circular Input method. This method don't have any loss when image didn't have any attack. As a result Watermark can be perfectly extracted by using this algorithm. And Maximam PSNR value is improved 3.35dB. This algorithm will be improved by using gray level image and color image.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.354-359
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• 2013

In this paper, we suggested the method for implementation of unsupervised nonlinear classification using Binary Harmony Search (BHS) algorithm, which is known as a optimization algorithm. Various algorithms have been suggested for classification of feature vectors from the process of machine learning for pattern recognition or EEG signal analysis processing. Supervised learning based support vector machine or fuzzy c-mean (FCM) based on unsupervised learning have been used for classification in the field. However, conventional methods were hard to apply nonlinear dataset classification or required prior information for supervised learning. We solved this problems with proposed classification method using heuristic approach which took the minimal Euclidean distance between vectors, then we assumed them as same class and the others were another class. For the comparison, we used FCM, self-organizing map (SOM) based on artificial neural network (ANN). KEEL machine learning datset was used for simulation. We concluded that proposed method was superior than other algorithms.

• Journal of the Korea Institute of Building Construction
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• v.11 no.3
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• pp.238-246
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• 2011

Choosing the best-performance materials is a crucial task for the successful completion of a project in the construction field. In general, the process of material selection is performed through the use of information by a highly experienced expert and the purchasing agent, without the assistance of logical decision-making techniques. For this reason, the construction field has considered various artificial intelligence (AI) techniques to support decision systems as their own selection method. This study proposes the application of a systematic and efficient support vector machine (SVM) model to select optimal exterior materials. The dataset of the study is 120 completed construction projects in South Korea. A total of 8 input determinants were identified and verified from the literature review and interviews with experts. Using data classification and normalization, these 120 sets were divided into 3 groups, and then 5 binary classification models were constructed in a one-against-all (OAA) multi classification method. The SVM model, based on the kernel radical basis function, yielded a prediction accuracy rate of 87.5%. This study indicates that the SVM model appears to be feasible as a decision support system for selecting an optimal construction method.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.205-214
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• 2015

In this paper, we propose a new approach to learning a discriminative model for figure/ground segmentation by incorporating the bag-of-features and conditional random field (CRF) techniques. We advocate the use of image patches instead of superpixels as the basic processing unit. The latter has a homogeneous appearance and adheres to object boundaries, while an image patch often contains more discriminative information (e.g., local image structure) to distinguish its categories. We use pixel-level sparse coding to represent an image patch. With the proposed feature representation, the unary classifier achieves a considerable binary segmentation performance. Further, we integrate unary and pairwise potentials into the CRF model to refine the segmentation results. The pairwise potentials include color and texture potentials with neighborhood interactions, and an edge potential. High segmentation accuracy is demonstrated on three benchmark datasets: the Weizmann horse dataset, the VOC2006 cow dataset, and the MSRC multiclass dataset. Extensive experiments show that the proposed approach performs favorably against the state-of-the-art approaches.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.166-172
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• 2018

A pseudo-random sequence generated by using a primitive polynomial, trace function, and Legendre symbol has been researched in our previous work. Our previous sequence has some interesting features such as period, autocorrelation, and linear complexity. A pseudo-random sequence widely used in cryptography. However, from the aspect of the practical use in cryptographic systems sequence needs to generate swiftly. Our previous sequence generated by utilizing a primitive polynomial, however, finding a primitive polynomial requires high calculating cost when the degree or the characteristic is large. It’s a shortcoming of our previous work. The main contribution of this work is to find some relation between the generated sequence and irreducible polynomials. The purpose of this relationship is to generate the same sequence without utilizing a primitive polynomial. From the experimental observation, it is found that there are (p - 1)/2 kinds of polynomial, which generates the same sequence. In addition, some of these polynomials are non-primitive polynomial. In this paper, these relationships between the sequence and the polynomials are shown by some examples. Furthermore, these relationships are proven theoretically also.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.87-99
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• 2015

In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs) and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle $A^*$ algorithm ($FAA^*$), an advanced $A^*$ algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV.

• ETRI Journal
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• v.31 no.2
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• pp.129-139
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• 2009

This paper provides an efficient algorithm for computing the ${\eta}_T$ pairing on supersingular elliptic curves over fields of characteristic two. In the proposed algorithm, we deploy a modified multiplication in $F_{2^{4n}}$ using the Vandermonde matrix. For F, G ${\in}$ $F_{2^{4n}}$ the proposed multiplication method computes ${\beta}{\cdot}F{\cdot}G$ instead of $F{\cdot}G$ with some ${\beta}$ ${\in}$ $F^*_{2n}$ because ${\beta}$ is eliminated by the final exponentiation of the ${\eta}_T$ pairing computation. The proposed multiplication method asymptotically requires only 7 multiplications in $F_{2^n}$ as n ${\rightarrow}$ ${\infty}$, while the cost of the previously fastest Karatsuba method is 9 multiplications in $F_{2^n}$. Consequently, the cost of the ${\eta}_T$ pairing computation is reduced by 14.3%.