• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.191-194
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• 2001

We consider a postal transportation planning in the transportation network of the form of hub and spoke. Given mail sorting centers and an exchange center, available vehicles and amount of mails to be transported between mail sorting centers, postal transportation planning is to make a transportation plan without violating various restrictions. The objective is to minimize the total transportation cost. To solve the problem, a tabu search algorithm is Proposed. The algorithm is composed of a route construction procedure and a route improvement procedure to improve a solution obtained by the route construction procedure using a tabu search. Computational results show that the proposed algorithm can solve practically sized problems within a reasonable time and the quality of the solution is acceptable.

• BMB Reports
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• v.54 no.5
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• pp.246-252
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• 2021

The Golgi complex plays a central role in protein secretion by regulating cargo sorting and trafficking. As these processes are of functional importance to cell polarity, motility, growth, and division, there is considerable interest in achieving a comprehensive understanding of Golgi complex biology. However, the unique stack structure of this organelle has been a major hurdle to our understanding of how proteins are secreted through the Golgi apparatus. Herein, we summarize available relevant research to gain an understanding of protein secretion via the Golgi complex. This includes the molecular mechanisms of intra-Golgi trafficking and cargo export in the trans-Golgi network. Moreover, we review recent insights on signaling pathways regulated by the Golgi complex and their physiological significance.

• Journal of Korea Multimedia Society
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• v.17 no.6
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• pp.716-724
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• 2014

The pancake graph is node symmetric and is utilized on the data sorting algorithm. We propose a new half pancake graph that improve pancake graph's network cost. The half pancake degree is approximately half of pancakes degree and diameter is 3n+4. The pancake graph's network cost is $O(1.64n^2)$ and half pancake's is $O(1.5n^2)$. Additionally half pancake graph is sub graph of pancake graph. As this result, The several algorithms developed in pancake graph has the advantage of leverage on the pancake by adding constant cost.

• Journal of Korea Multimedia Society
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• v.17 no.6
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• pp.725-732
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• 2014

The Pancake graph is node symmetric and useful interconnection network in the field of data sorting algorithm. The Half Pancake graph is a new interconnection network that reduces the degree of the Pancake graph by approximately half and improves the network cost of the Pancake graph. In this paper, we analyze topological properties of the Half Pancake graph $HP_n$. Fist, we prove that $HP_n$ has maximally fault tolerance and recursive scalability. In addition, we show that in $HP_n$, there are isomorphic graphs of low-dimensional $HP_n$. Also, we propose that the Bubblesort $B_n$ can be embedded into Half Pancake $HP_n$ with dilation 5, expansion 1. These results mean that various algorithms designed for the Pancake graph and the Bubble sort graph can be executed on $HP_n$ efficiently.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.170-177
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• 2000

Sorting cut roses according to quality is very essential to increase the value of the product. Many factors are involved in determining the grade of cut roses: length, thickness, and straightness of stem, color and maturity of bud, and extra. Among these factors, the stem straightness and bud maturity are considered to be difficult to set proper classification criteria. In this study, a prototype machine and an analysis procedure were developed to grade cut roses according to stem straightness and bud maturity by utilizing color image processing and neural network. The test results indicated 15.8% classification error for stem straightness and 10.0% for bud maturity.

• Journal of Biosystems Engineering
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• v.19 no.2
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• pp.124-137
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• 1994

Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.5C
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• pp.435-444
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• 2002

In this paper, a novel packet scheduling algorithm, so-called the CSL algorithm is discussed, whereby the firewall property as well as the deterministic delay bound guarantee are supported in session level. Lots of simulation studies validate those properties of the CSL algorithm. The CSL algorithm is distingushable from the well- known EDD scheme in terms of the firewall property. Regarding the implementation complexity, the CSL algorithm turns out to be of 0(1) besides the sorting overhead. Owing to the maintained generic fair queueing structure in the CSL algorithm, a various fair queueing schemes can be applied with minor modification. For the TCP/IP network which is vulnerable to the misbehaving traffic sources, the firewall property of the CSL algorithm is quite useful for the advanced quality of services.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.513-520
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• 2000

An integrated grader which measures soluble solid content, color and weight of fresh apples was developed by NAMRI. The prototype grader consists of the near infrared spectroscopy and machine vision system. Image processing system and an algorithm to evaluate color were developed to speed up the color evaluation of apples. To avoid the light glare and specular reflection, an half-spherical illumination chamber was designed and fabricated to detect the color images of spherical-shaped apples more precisely. A color revision model based on neural network was developed. Near-infrared(NIR) spectroscopy system using NIR reflectance method developed by Lee et al(1998) of NAMRI was used to evaluate soluble solid content. In order to observe the performance of the grader, tests were conducted on conditions that there are 3 classes in weight sorting, 4 classes in combination of color and soluble solid content, and thus 12 classes in combined sorting. The average accuracy in weight, color and soluble solid content is more than about 90 % with the capacity of 3 fruits per second.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.12
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• pp.1250-1260
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• 2014

In this paper, a novel resource scheduling, which is used for hub network based long distance airborne tactical communication, is proposed. Recently, some countries of the world has concentrated on developing data rate and networking performance of CDL, striving to keep pace with modern warfare, which is changed into NCW. And our government has also developed the next generation high capacity CDL. In hub network, a typical communication structure of CDL, hybrid FDMA/TDMA can be considered to exchange high rate data among multiple UAVs simultaneously, within limited bandwidth. However, due to different RTT and traffic size of UAV, idle time resource and unnecessary packet transmission delay can occur. And these losses can reduce entire efficiency of hub network in long distance communication. Therefore, in this paper, we propose RTT and data traffic size based UAV scheduling, which selects time/frequency resource of UAVs by using iterative sorting algorithm. The simulation results verified that the proposed scheme improves data rate and packet delay performance in low complexity.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.4
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• pp.750-769
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• 2015

The geometry of engineering systems affects their performances. For this reason, the shape of engineering systems needs to be optimized in the initial design stage. However, engineering system design problems consist of multi-objective optimization and the performance analysis using commercial code or numerical analysis is generally time-consuming. To solve these problems, many engineers perform the optimization using the approximation model (response surface). The Response Surface Method (RSM) is generally used to predict the system performance in engineering research field, but RSM presents some prediction errors for highly nonlinear systems. The major objective of this research is to establish an optimal design method for multi-objective problems and confirm its applicability. The proposed process is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the approximation model is generated using the Backpropagation Artificial Neural Network (BPANN) which is considered as Neuro-Response Surface Method (NRSM). The optimization is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II). Through case studies of marine system and ship structure (substructure of floating offshore wind turbine considering hydrodynamics performances and bulk carrier bottom stiffened panels considering structure performance), we have confirmed the applicability of the proposed method for multi-objective side constraint optimization problems.