• Solar Energy
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• v.12 no.1
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• pp.103-108
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• 1992

• Solar Energy
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• v.11 no.3
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• pp.89-95
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• 1991

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.67-70
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• 2009

Nesting and cutting path optimization have a great effect on the improvement of productivity in many industries such as shipbuilding, automotive, clothing, and so on. However, few researches have been carried out for the optimization of a cutting path algorithm. This study proposed a new method for cutting optimization using gravity center of cutting pieces and a genetic algorithm. The proposed method was tested for a sample plate including many different shapes of cutting pieces and compared to 2 other conventional methods. The test results showed that the new method had the shortest cutting path and the best effectiveness among the 3 methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.678-690
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• 2014

The current networks do not disclose information about a management domain due to scalability, manageability and commercial reasons. Therefore, it is very hard to calculate an optimal path to the destination. Also, due to poor information sharing, if an error occurs in the intermediate path, it is very difficult to re-search the path and find the best path. Hence, to manage each domain more efficiently, an architecture with top-level path computation node which can obtain information of separate nodes are highly needed This study aims to investigate a federation of a united network around NRN(National Research Network) that could allow resource sharing between countries and also independent resource management for each country. Considering first the aspects that can be accessed from the perspective of a national research network, ICE(Information Control Element) and GFO(Global Federation Organizer)-based architecture is designed as a top-level path computation element to support traffic engineering and applied to the multi-domain network. Then, the federation for the independent management of resources and resource information sharing among national research networks have been examined.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.9-15
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• 2009

Ant Colony System is new meta heuristic for hard combinatorial optimization problem. The original ant colony system accomplishes a pheromone updating about only the global optimal path using global updating rule. But, If the global optimal path is not searched until the end condition is satisfied, only pheromone evaporation happens to no matter how a lot of iteration accomplishment. In this paper, the length of the global optimal path does not improved within the limited iterations, we evaluates this state that fall into the local optimum and selects the next node using changed parameters in the state transition rule. This method has effectiveness of the search for a path through diversifications is enhanced by decreasing the value of parameter of the state transition rules for the select of next node, and escape from the local optima is possible. Finally, the performance of Best and Average_Best of proposed algorithm outperforms original ACS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5B
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• pp.397-404
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• 2006

As an increase in recent optical network-based IP services, GMPLS management framework becomes more important than ever before. In this paper, we propose the dynamic GMPLS path management algorithm, which can satisfy the users with their traffic engineering recovery requirements and find out the best backup service path under multiple link failures. To be more specific, we are deriving the soluble conditions of a backup path which is satisfied in a GMPLS network. In addition, through proposing the fast backup path selection algorithm, we can sufficiently satisfy a user's recovery requirement and minimally protect the suspension of the service against a link failure.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.371-377
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• 2021

This research proposes the best combination of tropospheric delay models for Korean Positioning System (KPS). The overall results are based on real observation data of Japanese Quasi-Zenith satellite system (QZSS), whose constellation is similar to the proposed constellation of KPS. The tropospheric delay models are constructed as the combinations of three types of zenith path delay (ZPD) models and four types of mapping functions (MFs). Two sets of International GNSS Service (IGS) stations with the same receiver are considered. Comparison of observation residuals reveals that the ZPD models are more influential to the measurement model rather than MFs, and that the best tropospheric delay model is the combination of GPT3 with 5 degrees grid and Vienna Mapping Function 1 (VMF1). While the bias of observation residual depends on the receivers, it still remains to be further analyzed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2154-2172
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• 2013

A centralized cognitive radio (CR) network is proposed and its system capacity is studied. The CR network is designed with power control and multi-user scheduling schemes to support best-effort traffics under peak interference power constraints. We provide an analytical framework to quantify its system capacity, taking into account various key factors such as interference constraints, density of primary users, cell radius, the number of CR users, and propagations effects. Furthermore, closed-form formulas are derived for its capacities when only path loss is considered in the channel model. Semi-analytical expressions for the capacities are also given when more realistic channel models that include path loss, shadowing, and small-scale fading are used. The accuracy of the proposed analytical framework is validated by Monte Carlo simulations. Illustrated with a practical example, the provided analytical framework is shown to be useful for the strategic planning of centralized CR networks.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.1-23
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• 2005

The shortest-paths problem is a fundamental problem in graph theory and finds diverse applications in various fields. This is why shortest path algorithms have been designed more thoroughly than any other algorithm in graph theory. A large number of optimization problems are mathematically equivalent to the problem of finding shortest paths in a graph. The shortest-path between a pair of vertices is defined as the path with shortest length between the pair of vertices. The shortest path from one vertex to another often gives the best way to route a message between the vertices. This paper presents an $O(n^2)$ time sequential algorithm and an $O(n^2/p+logn)$ time parallel algorithm on EREW PRAM model for solving all pairs shortest paths problem on circular-arc graphs, where p and n represent respectively the number of processors and the number of vertices of the circular-arc graph.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.256-262
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• 2013

This paper presents a linear path control algorithm for NeuroMate robot in a skull drilling system. For the path control inverse kinematics of the robot is analyzed and a linear interpolation algorithm is presented. A geometric approach is used for solving inverse kinematic equations for the robot. Four feasible solutions are found through the approach. The approach gives geometric insights for selecting the best solution from the feasible solutions. The presented linear interpolation algorithm computes a next position considering current velocity and remaining distance to the target position. Presented algorithm is implemented and tested in a skull drilling system.