• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2470-2478
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• 1999

In this paper, algorithm is proposed to forecast line utilization using SNMP MIB-II. We calculate line utilization using SNMP MIB-II on TCP/IP based Internet and suggest a method for forecasting a line utilization on the basis of past line utilization. We use a MA model taking difference transform among ARIMA methods. A system for orecasting is proposed. To show availability of this algorithm, some results are shown and analyzed about routers on real environments. We get a future line utilization using this algorithm and compare it ot real data. Correct results are obtained in case of being few data deviating from mean value. This algorithm for forecasting line utilization can give effect to line c-apacity plan for a manager by forecasting the future status of TCP/IP network. This will also help a network management of decision making of performance upgrade.

• Journal of IKEEE
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• v.5 no.1 s.8
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• pp.43-51
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• 2001

As the density of memories increases, unwanted interference between cells and coupling noise between bit-lines are increased. And testing high-density memories for a high degree of fault coverage can require either a relatively large number of test vectors or a significant amount of additional test circuitry. So far, conventional test algorithms have focused on faults between neighborhood cells, not neighborhood bit-lines. In this paper, a new test algorithm for neighborhood bit-line sensitive faults (NBLSFs) based on the NPSFs(Neighborhood Pattern Sensitive Faults) is proposed. And the proposed algorithm does not require any additional circuit. Instead of the conventional five-cell or nine-cell physical neighborhood layouts to test memory cells, a three-cell layout which is minimum size for NBLSFs detection is used. Furthermore, to consider faults by maximum coupling noise by neighborhood bit-lines, we added refresh operation after write operation in the test procedure(i.e.,$write{\rightarrow}\;refresh{\rightarrow}\;read$). Also, we show that the proposed algorithm can detect stuck-at faults, transition faults, coupling faults, conventional pattern sensitive faults, and neighborhood bit-line sensitive faults.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.70-74
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• 2018

In order to ensure the flow of goods available and more flexible, reduce labor costs, many factories and industrial zones around the world are gradually moving to use automated solutions. One of them is to use Automated guided vehicles (AGV). Currently, there are a line tracing method as an AGV operating method, and a method of estimating the current position of the AGV and matching with a factory map and knowing the moving direction of the AGV. In this paper, we propose ceiling Light and guided line based moving direction estimation algorithm using multi-camera on the AGV in smart factory that can operate stable AGV by compensating the disadvantages of existing AGV operation method. The proposed algorithm is able to estimate its position and direction using a general - purpose camera instead of a sensor. Based on this, it can correct its movement error and estimate its own movement path.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1729-1742
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• 2017

In designing System Protection Schemes (SPSs) in power systems, protecting transmission network against extreme undesired conditions becomes a significant challenge in mitigating the transmission line overloading. This paper presents an intelligent Special Protection and Control Scheme (SPCS) using of Differential Evolution with Adaptive Mutation (DEAM) approach to obtain the optimum generation rescheduling to solve the transmission line overloading problem in system contingency conditions. DEAM algorithm employs the attraction-repulsion idea that is applied in the electromagnetism-like algorithm to support the mutation process of the conventional Differential Evolution (DE) algorithm. Different N-1 contingency conditions under base and increase load demand are considered in this paper. Simulation results have been compared with those acquired from Genetic Algorithm (GA) application. Minimum severity index has been considered as the objective function. The final results show that the presented DEAM method offers better performance than GA in terms of faster convergence and less generation fuel cost. IEEE 30-bus test system has been used to prove the effectiveness and robustness of the proposed algorithm.

• KSBB Journal
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• v.4 no.3
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• pp.203-207
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• 1989

Software for the on-line feedback control of such variables as DO and temperature was developed and tested successfully for a real fermentation system. Several aspects like Pl, PID, DSC, and DDC were incorporated into the algorithm. Any kind of on-line computer control system can be successfully implemented without much difficulty.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.16-28
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• 2004

A seam-line determination algorithm is proposed to determine image border-line in mosaicing using the transformation of gray value differences and dynamic programming. Since visually good border-line is the one along which pixel differences are as small as possible, it can be determined in association with an optimal path finding algorithm. A well-known effective optimal path finding algorithm is the Dynamic Programming (DP). Direct application of the dynamic programming to the seam-line determination causes the distance effect, in which seam-line is affected by its length as well as the gray value difference. In this paper, an adaptive cost transform algorithm with which the distance effect is suppressed is proposed in order to utilize the dynamic programming on the transformed pixel difference space. Also, a figure of merit which is the summation of fixed number of the biggest pixel difference on the seam-line (SFBPD) is suggested as an evaluation measure of seamlines. The performance of the proposed algorithm has been tested in both quantitively and visually on various kinds of images.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.716-721
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• 1990

It is one of the essential task to determine the absolute location of mobile robot during its navigation. In this paper we propose an algorithm to calculate the distance and orientation of camera from landmark through the visual image of stripe typed landmark. Exact closed form solution of camera location is obtained with the correspondences from vertical line on mark plane to the intersection point of projected line with horizontal axis of image plane. It needs only one line image information, so that location determination can be processed in real time.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.66-76
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• 2002

Automated welding and soldering are an important manufacturing issue in order to lower the cost, increase the quality, and avoid labor problems. An off-line programming, OLP, is one of the powerful methods to solve this kind of diversity problem. Unless an OLP system is ready for the path optimization in welding and soldering, the waste of time and cost is unavoidable due to inefficient paths in welding and soldering processes. Therefore, this study attempts to obtain path optimization using a genetic algorithm based on artificial intelligences. The problem of welding path optimization is defined as a conventional TSP (traveling salesman problem), but still paths have to go through welding lines. An improved genetic algorithm was suggested and the problem was formulated as a TSP problem considering the both end points of each welding line read from database files, and then the transit problem of welding line was solved using the improved suggested genetic algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.65-77
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• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

• Journal of environmental and Sanitary engineering
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• v.21 no.4 s.62
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• pp.61-76
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• 2006

A Line Density algorithm was developed to quantify the sea surface temperature distribution using NOAA Sea Surface Temperature(SST) data and Geographic Information Systems(GIS), In addition, a GIS based automation model was designed to extract the Line Density Indices were determined by applying K-means Cluster. SST data in terms of March to May obtained on the coastal area of the Uljin from 2001 to 2004 in spring were used to make two data sets of average sea water temperature map in terms of year as well as month. From the result it was formed that water temperature gradient in April was the strongest among the other months, In particular very strog formation of oceanic front as well as temperature gradients were observed in front of the coastal area around Wonduk and Jukbyeon countries. Because those coastal area is a confront zone of two cold and a warm. It is expected that the development of a Line Density Algorithm would contribute to quantify of the SST for the research of Sea Surface Front(SSF) related to marine life management and the sea environmental conservation.