• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1258-1275
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• 2023

Cloud computing is a new technology that has adapted to the traditional way of service providing. Service providers are responsible for managing the allocation of resources. Selecting suitable containers and bandwidth for job scheduling has been a challenging task for the service providers. There are several existing systems that have introduced many algorithms for resource allocation. To overcome these challenges, the proposed system introduces an Optimized Task Scheduling Algorithm with Deep Learning (OTS-DL). When a job is assigned to a Cloud Service Provider (CSP), the containers are allocated automatically. The article segregates the containers as' Long-Term Container (LTC)' and 'Short-Term Container (STC)' for resource allocation. The system leverages an 'Optimized Task Scheduling Algorithm' to maximize the resource utilisation that initially inquires for micro-task and macro-task dependencies. The bottleneck task is chosen and acted upon accordingly. Further, the system initializes a 'Deep Learning' (DL) for implementing all the progressive steps of job scheduling in the cloud. Further, to overcome container attacks and errors, the system formulates a Container Convergence (Fault Tolerance) theory with high-level security. The results demonstrate that the used optimization algorithm is more effective for implementing a complete resource allocation and solving the large-scale optimization problem of resource allocation and security issues.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.307-311
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• 2010

EPCglobal Class-1 Gen-2 protocol has been proposed for UHF-band RFID systems. In Gen-2 standard, Q-algorithm was proposed to select a frame size for the next query round without estimating the number of tags. Therefore, the Q-algorithm has advantage that the reader's algorithm is simpler than other algorithms. However, it is impossible to allocate the optimized frame size. Also, the original Q-algorithm did not define an optimized parameter C for adjusting the frame size. In this paper, we propose an adaptive Q-algorithm with the different parameter $C_c$ and $C_i$ in accordance with the status of reply slot. Simulation results show that the proposed adaptive Q-algorithm outperforms the original Gen-2 Q-algorithm.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.45-50
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• 2010

EPCglobal Class-1 Gen-2 standard proposed Q-algorithm to select a frame size for the next query round. Q-algorithm calculates the frame size without estimating the number of tags. Therefore, the Q-algorithm has advantage that the reader's algorithm is simpler than other algorithms. However, it is impossible to allocate the optimized frame size. Also. the conventional Q-algorithm does not define an optimized parameter value C for adjusting the frame size. In this paper, we propose a modified Q-algorithm with the tag number estimation scheme, and evaluate the performance with computer simulations.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1008-1014
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• 2020

Aiming at the defect detection quality of denim fabric, this paper designs an improved algorithm based on the optimized Gabor filter. Firstly, we propose an improved defect detection algorithm of jean fabric based on the maximum two-dimensional image entropy and the loss evaluation function. Secondly, 24 Gabor filter banks with 4 scales and 6 directions are created and the optimal filter is selected from the filter banks by the one-dimensional image entropy algorithm and the two-dimensional image entropy algorithm respectively. Thirdly, these two optimized Gabor filters are compared to realize the common defect detection of denim fabric, such as normal texture, miss of weft, hole and oil stain. The results show that the improved algorithm has better detection effect on common defects of denim fabrics and the average detection rate is more than 91.25%.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.469-474
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• 2009

Q-algorithm is proposed at EPC global Class-1 Generation-2 RFID systems to determine the frame size of next query round. In Q-algorithm, the reader calculates the frame size without estimating the number of tags. But, it uses only the slot conditions: empty, success, or collision. Therefore, it wastes less computational cost and is simpler than other algorithms. However, the constant parameter C value, which is used for calculating the next frame size, is not optimized. In this paper, we propose the optimized C values of Q-algorithm according to the number of tags within the identification range of reader through a lot of computer simulations.

• Journal of the Optical Society of Korea
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• v.18 no.2
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• pp.118-123
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• 2014

For multi parameter optimization of Raman Fiber Amplifier (RFA), a simple genetic algorithm is presented in the scenario of a 320 channel Dense Wavelength Division Multiplexed (DWDM) system at channel spacing of 25 GHz. The large average gain (> 22 dB) is observed from optimized RFA with the optimized parameters, such as 39.6 km of Raman length with counter-propagating pumps tuned to 205.5 THz and 211.9 THz at pump powers of 234.3 mW, 677.1 mW respectively. The gain flattening filter (GFF) has also been optimized to further reduce the gain ripple across the frequency range from 190 to 197.975 THz for broadband amplification.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.442-448
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• 2014

For the first time, a novel analytical model of the net gain for a Raman-EDFA hybrid optical amplifier (HOA) is proposed and its various parameters optimized using a genetic algorithm. Our method has been shown to be robust in the simultaneous analysis of multiple parameters (Raman length, EDFA length, and pump powers) to obtain large gain. The optimized HOA is further investigated at the system level for the scenario of a 50-channel DWDM system with 0.2-nm channel spacing. With an optimized HOA, a flat gain of >17 dB is obtained over the effective ITU-T wavelength grid with a variation of less than 1.5 dB, without using any gain-flattening technique. The obtained noise figure is also the lowest value ever reported for a Raman-EDFA HOA at reduced channel spacing.

• The Journal of Korean Physical Therapy
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• v.13 no.2
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• pp.257-264
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• 2001

To take the Far-infrared(FIR) ray which is a optimized wavewlength and strength, at first, it is to be induced the characteristic algorithm and the computerized programing of FlR radiating materials. In this study, we induced that the formular of optimized FIR with physical, mathematical logic and theory, especially, Plank, Kirchhoff, Wien, Stefan-Boltzmann's logic and law. In the long run the formular was induced with mathematical integration. since we had to know the molecular wavelength. Base on the induced formular as above, we programmed the optimized FlR radiating computerized program, it would be useful to design semiconductor( VLSI) as the FlR instrument center control system.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.4
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• pp.156-161
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• 2002

This paper proposes an optimized universal motor for improving its performance using the finite element method (FEM) with the (1＋1) Evolution Strategy (ES) algorithm. To do this, various design parameters are modified, such as air gap length, shape of motor slot, pole shoe, pole width, and rotor shaft diameter. Two parameters (arc length of stator pole and thickness of pole shoe) are chosen and optimized using the program, and the optimized model is built and tested with a performance measuring system. The measured values of the model are compared with those of the initial and the optimized model to prove the algorithm. As a result, the final model improves its performance compared with those of the initial model.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.877-885
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• 2018

Various controllers such as proportional-integral-derivative (PID) controllers have been designed and optimized for load-following issues in nuclear reactors. To achieve high performance, gain tuning is of great importance in PID controllers. In this work, gains of a PID controller are optimized for power-level control of a typical pressurized water reactor using particle swarm optimization (PSO) algorithm. The point kinetic is used as a reactor power model. In PSO, the objective (cost) function defined by decision variables including overshoot, settling time, and stabilization time (stability condition) must be minimized (optimized). Stability condition is guaranteed by Lyapunov synthesis. The simulation results demonstrated good stability and high performance of the closed-loop PSO-PID controller to response power demand.