• IE interfaces
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• v.13 no.4
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• pp.639-645
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• 2000

Virtual manufacturing systems that perform production activities ahead of real production in virtual world can reduce time and cost to develop, design, plan, and manage new products. In this paper, a virtual manufacturing system is constructed as a tool to support decision making by using VRML and Java. The basic structure of the virtual manufacturing system and the operation models are also presented. The developed system helps any related persons to share design and manufacturing information, and to perform their tasks collaboratively through Internet. The other function of the system is to monitor operation status in real time.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.159-166
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• 2010

Trip distribution is to connect travel demand for each OD pair based on travel cost, trip production and attraction derived from trip generation step. In real world the travel cost is a function of travel demand, but existing models could not fully consider such functional relation between travel cost and demand, which leads to an equilibrium in trip distribution model. This paper proves the equilibrium trip distribution by using gravity model. In order to obtain such equilibrium this paper also presents a solution algorithm based on fixed point theorem. The algorithm will be tested with an example and confirmed the equilibrium solution of trip distribution.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.129-140
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• 2006

Quantity Flexibility contract coordinates individually motivated supplier and buyer to the systemwide optimal outcome by effectively allocating the costs of market demand uncertainty. The main feature of the contract is to couple the buyer's commitment to purchase no less than a certain percentage below the forecast with the supplier's guarantee to deliver up to a certain percentage above. In this paper we refine the previous models by adding some realistic features including the upper and lower limits of the purchase. We also incorporate purchase and canceling costs in a cost function to reflect the real world contracting process more accurately. To obtain the solution of the model, we derive a condition for extreme points using the Leibniz's rule and construct an algorithm for finding the optimal solution of the model. Several examples illustrating the algorithm show that the approach is valid and efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1922-1940
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• 2019

IP address lookup is a function to determine nexthop for a given destination IP address. It takes an important role in modern routers because of its computation time and increasing Internet traffic. TCAM-based IP lookup approaches can exploit the capability of parallel searching but have a limitation of its size due to latency, power consumption, updatability, and cost. On the other hand, multibit trie-based approaches use SRAM which has relatively low power consumption and cost. They reduce the number of memory accesses required for each lookup, but it still needs several accesses. Moreover, the memory efficiency and updatability are proportional to the number of memory accesses. In this paper, we propose a novel architecture using an Indexed Multibit Trie (IMT) which is based on combined TCAM and SRAM. In the proposed architecture, each lookup takes at most two memory accesses. We present how the IMT is constructed so as to be memory-efficient and fast updatable. Experiment results with real-world forwarding tables show that our scheme achieves good memory efficiency as well as fast updatability.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.69-78
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• 2007

In real world, the project managers handle conflicting goals that govern the use of resources within the stipulated time and budget with required quality and safety. These conflicting goals are required to be optimized simultaneously by the project managers in the framework of fuzzy aspiration levels. The fuzzy linear programming model proposed herein helps project managers to minimize total project costs, completion time, and crashing costs considering indirect costs, contractual penalty costs etc by practically charging them in terms of direct cost of the project. A case study of bituminous pavement under construction is considered to demonstrate the feasibility of applying the proposed model for optimization of project parameters. Consequently, the proposed model yields an efficient compromise solution and the decision maker's overall degree of satisfaction with multiple fuzzy goal values. Additionally, the proposed model provides a systematic decision-making framework, enabling decision maker to interactively modify the fuzzy data and model parameters until a satisfactory solution is obtained. The significant characteristics that differentiate the proposed model with other models include, flexible decision-making process, multiple objective functions, and wide-ranging decision information.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.207-210
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• 2005

Ubiquitous computing is one of the key technology areas in the "Project on Development of Ubiquitous computing and network technology" promoted by the Ministry of Science and Technology as a frontier business of the $21^{st}$ century in Korea, which is based on the new concept merging physical space and computer-based cyber space. With recent advances in Micro Electro Mechanical System (MEMS) technology, low cost and low-power consumption wireless micro sensor nodes have been available. Using these smart sensor nodes, there are many activities to monitor real world, for example, habitat monitoring, earthquake monitoring and so on. In this paper, we introduce web-based real environment monitoring system incorporating wireless sensor nodes. It collects sensing data produced by some wireless sensor nodes and stores them into a database system to analyze. Our environment monitoring system is composed of a networked camera and environmental sensor nodes, which are called Mica2 and developed by University of California at Berkeley. We have modified and ported network protocols over TinyOS and developed a monitoring application program using the MTS310 and MTS420 sensors that are able to observe temperature, relative humidity, light and accelerator. The sensed data can be accessed user-friendly because our environment monitoring system supports web-based user interface. Moreover, in this system, we can setup threshold values so the system supports a function to inform some anomalous events to administrators. Especially, the system shows two useful pre-processed data as a kind of practical uses: a discomfort index and a septicity index. To make both index values, the system restores related data from the database system and calculates them according to each equation relatively. We can do enormous works using wireless sensor technologies, but just environment monitoring. In this paper, we show just one of the plentiful applications using sensor technologies.

• Journal of the Korean Magnetics Society
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• v.8 no.3
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• pp.169-177
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• 1998

In the case of an induction motor efficiency optimal design for electric vehicle which is a real world problem, several different designs are almost equal in terms of efficiency. But these designs may have the differences in terms of other characteristics such as power factor, temperature rise, material cost, and ease of manufacture. Therefore it is necessary that an optimization routine suggests various possible solution alternatives and a designer selects optimal solution among them using other characteristics, his experience and judgment. In this paper new niching genetic algorithm and the rating function method to select the optimal point among possible optimal solution alternatives are presented.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.305-318
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• 2023

The complexity of software products led many manufacturers to stitch open-source software for composing a product. Using open-source help reduce the development cost, but the difference in the different development life cycles makes it difficult to keep the product up-to-date. For this reason, even the patches for known vulnerabilities are not adopted quickly enough, leaving the entire product under threat. Existing studies propose to use binary differentiation techniques to determine if a product is left vulnerable against a particular vulnerability. Despite their effectiveness in finding real-world vulnerabilities, they often fail to locate the evidence of a vulnerability if it is a small function that usually is inlined at compile time. This work presents our tool FunRank which is designed to identify the short functions. Our experiments using synthesized and real-world software products show that FunRank can identify the short, inlined functions that suggest that the program is left vulnerable to a particular vulnerability.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.77-86
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• 2000

The shortest path problem is one of the mathematical Programming models that can be conveniently solved through the use of networks. The common shortest Path Problem is to minimize a single objective function such as distance, time or cost between two specified nodes in a transportation network. The sing1e objective model is not sufficient to reflect any Practical Problem with multiple conflicting objectives in the real world applications. In this paper, we consider the shortest Path Problem under multiple objective environment. Wile the shortest path problem with single objective is solvable in Polynomial time, the shortest Path Problem with multiple objectives is NP-complete. A genetic a1gorithm approach is developed to deal with this Problem. The results of the experimental investigation of the effectiveness of the algorithm are also Presented.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.1-2
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• 1994

With the prevalence of computers in modern organizations, simulation is receiving more atention as an effectvie decision -making tool. Simualtion is a computer-based numerical technique which uses mathmatical and logical models to approximate the behaviror of a real-world system. However, iptimization of synamic stochastic systems often defy analytical and algorithmic soluions. Although a simulation approach is often free fo the liminting assumption s of mathematical modeling, cost and time consiceration s make simulation the henayst's last resort. Therefore, whenever possible, analytical and algorithmica solutions are favored over simulation. This paper discussed the issues and procedrues for using simulation as a tool for optimization of stochastic complex systems that are dmodeled by computer simulation . Its emphasis is mostly on issues that are speicific to simulation optimization instead of consentrating on the general optimizationand mathematical programming techniques . A simulation optimization problem is an optimization problem where the objective function. constraints, or both are response that can only be evauated by computer simulation. As such, these functions are only implicit functions of decision parameters of the system, and often stochastic in nature as well. Most of optimization techniqes can be classified as single or multiple-resoneses techniques . The optimization of single response functins has been researched extensively and consists of many techniques. In the single response category, these strategies are gradient based search techniques, stochastic approximate techniques, response surface techniques, and heuristic search techniques. In the multiple response categroy, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphica techniqes, direct search techniques, constrained optimization techniques, unconstrained optimization techniques, and goal programming techniques. The choice of theprocedreu to employ in simulation optimization depends on the analyst and the problem to be solved. For many practival and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computersimulation is one of the most effective means of studying such complex systems. In this paper, after discussion of simulation optmization techniques, the applications of above techniques will be presented in the modeling process of many flexible manufacturing systems.