• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.75-85
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• 2010

This paper presents a robust 3D model hashing based on object feature vector for 3D content authentication. The proposed 3D model hashing selects the feature objects with highest area in a 3D model with various objects and groups the distances of the normalized vertices in the feature objects. Then we permute groups in each objects by using a permutation key and generate the final binary hash through the binary process with the group coefficients and a random key. Therefore, the hash robustness can be improved by the group coefficient from the distance distribution of vertices in each object group and th hash uniqueness can be improved by the binary process with a permutation key and a random key. From experimental results, we verified that the proposed hashing has both the robustness against various mesh and geometric editing and the uniqueness.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.861-869
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• 2003

The rapid growth of multimedia network systems has caused overflowing illegal copies of digital contents. Among digital contents, watermarking technique can be used to protect ownership about the image. Copyright protection involves the authentication of image ownership and the identification of illegal copies of image. In this paper, a new digital watermarking technique using HVS and adaptive scale factor based on the wavelet transform is proposed to use the binary image watermark. The original image is decomposed by 3-level wavelet transform. It is embedded to baseband and high frequency band. The embedding in the baseband is considered robustness, the embedding in the high frequency band is concerned about HVS and invisibility. The watermarking of a visually recognizable binary image used the HVS and random permutation to protect the copyright. From the experimental results, we confirm that the proposed technique is strong to various attacks such as joint photographic experts ground(JPEG) compression, cropping, collusion, and inversion of lines.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.11-18
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• 2005

In this paper, we proposed a video watermarking algerian based on wavelet transform using statistical characteristic of video according to the energy distribution and the spread spectrum technique. In the proposed method, the original video is splitted by spatial difference metric and classified into the motion region and the motionless region according to the motion degree. The motion region is decomposed into 3-levels using 3D DWT and the motionless region is decomposed into 2-levels using 2D DWT The baseband of the wavelet-decomposed image is not utilized because of the image quality. So that the standard deviation of the highest subband coefficients except for the baseband is used to determine the threshold. Binary video watermarks preprocessed by the random permutation and the spread spectrum technique are embedded into selected coefficients. In computer experiments, the proposed algorithm was found to be more invisible and robust than the conventional algorithms.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.149-160
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• 2017

In hypothesis testing, the interpretation of a statistic obtained from the data analysis relies on a probabilistic distribution of the statistic constructed according to several statistical theories. For instance, the statistical significance of a mean difference between experimental conditions is determined according to a probabilistic distribution of the mean differences (e.g., Student's t) constructed under several theoretical assumptions for population characteristics. The present study explored the logic and advantages of random-resampling approach for analyzing event-related potentials (ERPs) where a hypothesis is tested according to the distribution of empirical statistics that is constructed based on randomly resampled dataset of real measures rather than a theoretical distribution of the statistics. To motivate ERP researchers' understanding of the random-resampling approach, the present study further introduced a specific example of data analyses where a random-permutation procedure was applied according to the random-resampling principle, as well as discussing several cautions ahead of its practical application to ERP data analyses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1653-1660
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• 2010

The user information stored in database have been leaked frequently. To protect information against malevolent manager on the inside or outside aggressor, it is one of the most efficient way to encrypt information and store to database. It is better to destruct information than not to use encrypted information stored in database. The encrypted database search system is developed variously, and used widely in many fields. In this paper, we implemented the scheme that can search encrypted document without exposing user's information to the untrusted server in mobile device. We compared and analyzed the result embodied with DES, AES, and ARIA based on symmetric key by searching time.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2493-2500
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• 1997

We propose a new key management scheme for multiuser group which is classified as hierarchical structure (sometimes it is called a multilevel security hierarchy) in the symmetric key cryptosystem. The proposed scheme is based on the trapdoor one-way permutations which are generated by the pseudo-random permutation algorithm, and it is avaliable for multilevel hierarchical structure composed of a totally ordered set and a partially ordered set, since it has advantage for time and storage from an implemental point of view. Moreover, we obtain a performance analysis by comparing with the other scheme, and show that the proposed scheme is very efficient for computing time of key generation and memory size of key storage.

• Geomechanics and Engineering
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• v.36 no.4
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• pp.381-390
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• 2024

The introduction of bio-based materials has been recommended in the geotechnical engineering field to reduce environmental pollutants such as heavy metals and greenhouse gases. However, bio-treated soil methods face limitations in field application due to short research periods and insufficient verification of engineering performance, especially when compared to conventional materials like cement. Therefore, this study aimed to develop a machine learning model for predicting the unconfined compressive strength, a representative soil property, of biopolymer-based soil treatment (BPST). Four machine learning algorithms were compared to determine a suitable model, including linear regression (LR), support vector regression (SVR), random forest (RF), and neural network (NN). Except for LR, the SVR, RF, and NN algorithms exhibited high predictive performance with an R² value of 0.98 or higher. The permutation feature importance technique was used to identify the main factors affecting the strength enhancement of BPST. The results indicated that the unconfined compressive strength of BPST is affected by mean particle size, followed by biopolymer content and water content. With a reliable prediction model, the proposed model can present guidelines prior to laboratory testing and field application, thereby saving a significant amount of time and money.

• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.223-238
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• 1994

A random vector $\b{X} = (X_1,\cdots,X_n)$ is weakly associated if and only if for every pair of partitions $\b{X}_1 = (X_{\pi(1)},\cdots,X_{\pi(k)}), \b{X}_2 = (X_{\pi(k+1),\cdots,X_{\pi(n)})$ of $\b{X}, P(\b{X}_1 \in A, \b{X}_2 \in B) \geq P(\b{X}_1 \in A)\b{P}(\b{X}_2 \in B)$ whenever A and B are open upper sets and $\pi$ is a permutation of ${1,\cdots,n}$. In this paper, we develop notions of weak positive dependence, which are weaker than a positive version of negative association (weak association) but stronger than positive orthant dependence by arguments similar to those of Shaked. We also illustrate some concepts of a particular interest. Various properties and interrelationships are derived.

• Industrial Engineering and Management Systems
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• v.10 no.3
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• pp.203-208
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• 2011

Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

• Journal of the Korean Mathematical Society
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• v.36 no.4
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• pp.649-662
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• 1999

A random vector =(X1,…, Xn) is conditionally weakly associated if and only if for every pair of partitions 1=(X$\pi$(k+1),…,X$\pi$(k)), 2=(X$\pi$(k+1),…,X$\pi$(n)) of P(1$\in$A│2$\in$B, $\theta$$\in$I) $\geq$P$\in$A│$\theta$$\in$I whenever A and B are open upper sets and $\pi$ is any permutation of {1,…,n}. In this note we develop some concepts of conditional positive dependence, which are weaker than conditional weak association but stronger than conditional positive orthant dependence, by requiring the above inequality to hold only for some upper sets and applying the arguments in Shaked (1982).