• Proceedings of the IEEK Conference
• /
• summer
• /
• pp.400-404
• /
• 2004

There are many methods to find solutions for Integer Programming problems (IPs) such as the Branch-Bound philosophy or the Cutting Plane algorithm. However, most of them have a problem that is the explosion of sets in the computing process. In addition, GA is known as a heuristic search algorithm for solutions of optimization problems. It is started from a random initial guess solution and attempting to find one that is the best under some criteria and conditions. The paper will study an artificial intelligent method to solve IPs by using Genetic Algorithms (GAs). The original solution of this was presented in the papers of Fabricio Olivetti de Francaand and Kimmo Nieminen [2003]. However, both have several limitations which causes could be operations in GAs. The paper proposes a method to upgrade these operations and computational results are also shown to support these upgrades.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.10 no.2
• /
• pp.180-187
• /
• 2007

In this paper, we propose an automatic method which combines two or more images acquired by camera on the air-vehicle into a larger image mosaics. The shift, scaling, rotation factors between two images can be calculated by using the correspondences between the points of the images. In order to estimate these factors, we find the relative positions of two images with respect to each other by using the SIFT descriptor and the RANSAC algorithm. After estimating the factors, the images can be merged into a single image mosaic by warping the target image. To avoid seams when mosaics are constructed from overlapped images, we apply the average gray level value of points within a overlapped zone. We have tested our proposed method on various image sets and have confirmed that our method produced good result subjectively.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.39 no.5
• /
• pp.527-537
• /
• 1990

This paper describes an intelligent control-based job scheduler, named ESIJOBS, for flexible manufacturing system. In order to construct rulebase of this system, traditional rules of job scheduling in FMS are examined and evaluated. This result and the repetitional simulations with graphic monitoring system are used to form the rulebase of ESIJOBS, which is composed of three parts:six part selection rules, four machine center selection rules, and twenty-one metarules. Appropriate scheduling rule sets are selected by this rulebase and manufacturing system status. The performances of all simulations are affected by random breakdowns of major FMS components during each simulation. Six criteria are used to evaluate the performance of each scheduling. The two modes of ESIJOBS are simulated and compared with combinational 24 rule-set simulations. In this comparison ESIJOBS dominated the other rule-set simulations and showed the most excellent performance particularly in three criteria.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.8
• /
• pp.500-505
• /
• 2003

In this paper, the method to register multiple sets of skull CT images to absolute coordinate system is proposed. Contrary to correspondence paired mapping of previous techniques, four anatomical landmark points, three coplanar points and one non-coplanar point, compose three principal axes simple and unique for efficient registration by means of rigid body transformation. Throughout the numerical simulation with added random noises, the error performances in terms of different rotation and rounding-off of landmark points, and incorrect localization of anatomical landmark and target points are quantitatively analyzed to generalize the proposed technique. Experiments using real skull CT images demonstrate the feasibility for an efficient use in clinical practice.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.3
• /
• pp.677-684
• /
• 2014

Support vector quantile regression (SVQR) is capable of providing more complete description of the linear and nonlinear relationships among random variables. To improve the estimation performance of SVQR we propose to use SVQR ensemble with bagging (bootstrap aggregating), in which SVQRs are trained independently using the training data sets sampled randomly via a bootstrap method. Then, they are aggregated to obtain the estimator of the quantile regression function using the penalized objective function composed of check functions. Experimental results are then presented, which illustrate the performance of SVQR ensemble with bagging.

• Communications of the Korean Mathematical Society
• /
• v.9 no.4
• /
• pp.961-973
• /
• 1994

A stochastics process $X = {X(t) : t \in T}$, with an index set T, is said to be infinitely divisible (ID) if its finite dimensional distributions are all ID. An ID process X is said to be a stochastic integral process if $X = {X(t) : t \in T} =^D {\int f_td\Lambda : t \in T}$ where $f : T \times S \to R$ is a deterministic function and $\Lambda$ is an ID random measure on a $\delta$-ring S of subsets of an arbitrary non-empty set S with the property; there exists an increasing sequence ${S_n}$ of sets in S with $U_n S_n = S$. Here $=^D$ denotes equality in all finite dimensional distributions.

• Journal of Information Processing Systems
• /
• v.13 no.1
• /
• pp.68-82
• /
• 2017

Nowadays, geographic information system (GIS) is developed and implemented in many areas. A huge volume of vector map data has been accessed unlawfully by hackers, pirates, or unauthorized users. For this reason, we need the methods that help to protect GIS data for storage, multimedia applications, and transmission. In our paper, a selective encryption method is presented based on vertex randomization and hybrid transform in the GIS vector map. In the proposed algorithm, polylines and polygons are focused as the targets for encryption. Objects are classified in each layer, and all coordinates of the significant objects are encrypted by the key sets generated by using chaotic map before changing them in DWT, DFT domain. Experimental results verify the high efficiency visualization by low complexity, high security performance by random processes.

• Parasites, Hosts and Diseases
• /
• v.45 no.4
• /
• pp.283-285
• /
• 2007

To examine the expressed gene profile during encystation of Acanthamoeba castellanii Castellani, we used differentially expressed gene (DGE) screening by RT-PCR with 20 sets of random primers. From this analysis, we found that approximately 16 genes showed up regulation during encystation. We chose 6 genes, which had relatively higher expression levels, for further investigation. Based on homology search in database, DEG2 showed 55% of similarity with xylose isomerase, DEG9 showed 37% of similarity with Na P-type ATPase, and DEG14 showed 77% of similarity with subtilisin-like serine proteinase. DEG3 and DEG26 were identified as hypothetical proteins and DEG25 exhibited no significant similarity to any known protein. Encystation of Acanthamoeba has been suggested to be a process to resist adverse environmental or nutritional conditions. Further characterization studies of these genes may provide us with more information on the encystation mechanism of Acanthamoeba.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.5095-5111
• /
• 2016

The Probability Hypothesis Density (PHD) filter is a suboptimal approximation and tractable alternative to the multi-target Bayesian filter based on random finite sets. However, the PHD filter fails to track newborn targets when the target birth intensity is unknown prior to tracking. In this paper, a dual detection-guided newborn target intensity PHD algorithm is developed to solve the problem, where two schemes, namely, a newborn target intensity estimation scheme and improved measurement-driven scheme, are proposed. First, the newborn target intensity estimation scheme, consisting of the Dirichlet distribution with the negative exponent parameter and target velocity feature, is used to recursively estimate the target birth intensity. Then, an improved measurement-driven scheme is introduced to reduce the errors of the estimated number of targets and computational load. Simulation results demonstrate that the proposed algorithm can achieve good performance in terms of target states, target number and computational load when the newborn target intensity is not predefined in multi-target tracking systems.

• Bulletin of the Korean Chemical Society
• /
• v.19 no.12
• /
• pp.1326-1333
• /
• 1998

The study of coupled relaxation for methyl spin system in 2,6-dichlorotoluene was performed on the basis of the magnetization mode formalism. Using five initial perturbing pulse sequences, eight experimntal data sets were obtained, which were fitted with theoretical expressions with nine spectral density parameters. The same experiment was carried out at both 50.3 MHz and 125.6 MHz in carbon frequency. The measured spectral densities at both fields are similar in the exception of that related with carbon random field term. Furthermore, from the dipolar spectral density, the physical values may be extracted depending on the model of molecular reorientation. For example, it was assumed that the molecular framework undergoes asymmetric diffusive rotational process and methyl group reorients by either diffusive rotation about its symmetry axis or jump among internal rotational potential minima.