• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1373-1391
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• 2022

We investigate mobile multiple-input multiple-output (MIMO) molecular communication via diffusion (MCvD) system which is consisted of two source nodes, two destination nodes and one relay node in the mobile three-dimensional channel. First, the combinations of decode-and-forward (DF) relaying protocol and network coding (NC) scheme are implemented at relay node. The adaptive thresholds at relay node and destination nodes can be obtained by maximum a posteriori (MAP) probability detection method. Then the mathematical expressions of the average bit error probability (BEP) of this mobile MIMO MCvD system based on DF and NC scheme are derived. Furthermore, in order to minimize the average BEP, we establish the optimization problem with optimization variables which include the ratio of the number of emitted molecules at two source nodes and the initial position of relay node. We put forward an iterative scheme based on block coordinate descent algorithm which can be used to solve the optimization problem and get optimal values of the optimization variables simultaneously. Finally, the numerical results reveal that the proposed iterative method has good convergence behavior. The average BEP performance of this system can be improved by performing the joint optimizations.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.8
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• pp.421-431
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• 2004

This paper presents adaptive execution techniques that determine whether parallelized loops are executed in parallel or sequentially in order to maximize performance. The adaptation and performance estimation algorithms are implemented in a compiler preprocessor. The preprocessor inserts code that automatically determines at compile-time or at run-time the way the parallelized loops are executed. Using a set of standard numerical applications written in Fortran77 and running them with our techniques on a distributed shared memory multiprocessor machine (SGI Origin2000), we obtain the performance of our techniques, on average, 26%, 20%, 16%, and 10% faster than the original parallel program on 32, 16, 8, and 4 processors, respectively. One of the applications runs even more than twice faster than its original parallel version on 32 processors.

• Journal of Computing Science and Engineering
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• v.6 no.1
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• pp.26-38
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• 2012

Java has been increasingly used in programming for real-time systems. However, some of Java's features such as automatic memory management and dynamic compilation are harmful to time predictability. If these problems are not solved properly then it can fundamentally limit the usage of Java for real-time systems, especially for hard real-time systems that require very high time predictability. In this paper, we propose to exploit multicore computing in order to reduce the timing unpredictability that is caused by dynamic compilation and adaptive optimization. Our goal is to retain high performance comparable to that of traditional dynamic compilation, while at the same time, obtain better time predictability for Java virtual machine (JVM). We have studied pre-compilation techniques to utilize another core more efficiently, preoptimization on another core (PoAC) scheme to replace the adaptive optimization system (AOS) in Jikes JVM and the counter based optimization (CBO). Our evaluation reveals that the proposed approaches are able to attain high performance while greatly reducing the variation of the execution time for Java applications.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.1
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• pp.49-55
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• 2020

Studies on the optimizations of machining processes use two different methods. The first is feed control in real-time by spindle load in a machine tool. The second is feed scheduling in NC code control by material removal rate using a CAD/CAM system. Each approach possesses its respective merits and issues compared to the other. That is, each method can be complementary to the other. The purpose of the study is to improve the productivity of the bulkhead, an aircraft Duralumin structure. In this paper, acceleration or deceleration of cutting tool by spindle load data is achieved using adaptive feed control macro programming in a machine tool.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.736-741
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• 2009

In this paper, adaptive optimizations of precoder codebook to channel conditions is proposed for a multiuser multiple-input multiple-output (MIMO) system with split linear array and limited feedback. We propose adaptive method for constructing a precoder codebook by coloring the random vector quantization codebook at each link by using limited long-term feedback information on transmit correlation matrix of each link. It is shown that the proposed multiuser MIMO codebook design scheme outperforms existing multiuser MIMO codebook design schemes for various channel conditions in terms of the average sum throughput of multiuser MIMO systems using zero-forcing maximum eigenmode transmission and limited feedback.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.6
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• pp.730-740
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• 2018

Hydrofoil is the direct component to generate thrust for underwater glider. It is significant to improve propulsion efficiency of hydrofoil. This study optimizes the shape of a hydrofoil using Free-Form Deformation (FFD) parametric approach and Surrogate-based Optimization (SBO) algorithm. FFD approach performs a volume outside the hydrofoil and the position changes of control points in the volume parameterize hydrofoil's geometric shape. SBO with adaptive parallel sampling method is regarded as a promising approach for CFD-based optimization. Combination of existing sampling methods is being widely used recently. This paper chooses several well-known methods for combination. Investigations are implemented to figure out how many and which methods should be included and the best combination strategy is provided. As the hydrofoil can be stretched from airfoil, the optimizations are carried out on a 2D airfoil and a 3D hydrofoil, respectively. The lift-drag ratios are compared among optimized and original hydrofoils. Results show that both lift-drag-ratios of optimized hydrofoils improve more than 90%. Besides, this paper preliminarily explores the optimization of hydrofoil with root-tip-ratio. Results show that optimizing 3D hydrofoil directly achieves slightly better results than 2D airfoil.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.204-208
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• 2018

Comparison of different optimizer performance in photovoltaic power modeling using artificial neural deep learning techniques is described in this paper. Six different deep learning optimizers are tested for Long-Short-Term Memory networks in this study. The optimizers are namely Adam, Stochastic Gradient Descent, Root Mean Square Propagation, Adaptive Gradient, and some variants such as Adamax and Nadam. For comparing the optimization techniques, high and low fluctuated photovoltaic power output are examined and the power output is real data obtained from the site at Mokpo university. Using Python Keras version, we have developed the prediction program for the performance evaluation of the optimizations. The prediction error results of each optimizer in both high and low power cases shows that the Adam has better performance compared to the other optimizers.

• Smart Structures and Systems
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• v.31 no.3
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• pp.283-299
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• 2023

Structural stability of floating platforms has long since been a crucial issue in the field of marine engineering. Excessive motions would not only deteriorate the operating conditions but also seriously impact the safety, service life, and production efficiency. In recent decades, several control devices have been proposed to reduce unwanted motions, and an attractive one is the tuned heave plate (THP). However, the THP system may reduce or even lose its effectiveness when it is mistuned due to the shift of dominant wave frequency. In the present study, a novel adaptive tuned heave plate (ATHP) is proposed based on inerter by adjusting its inertance, which allows to overcome the limitation of the conventional THP and realize adaptations to the dominant wave frequencies in real time. Specifically, the analytical model of a representative semisubmersible platform (SSP) equipped with an ATHP is created, and the equations of motion are formulated accordingly. Two optimization strategies (i.e., J₁ and J₂ optimizations) are developed to determine the optimum design parameters of ATHP. The control effectiveness of the optimized ATHP is then examined in the frequency domain by comparing to those without control and controlled by the conventional THP. Moreover, parametric analyses are systematically performed to evaluate the influences of the pre-specified frequency ratio, damping ratio, heave plate sizes, peak periods and wave heights on the performance of ATHP. Furthermore, a Simulink model is also developed to examine the control performance of ATHP in the time domain. It is demonstrated that the proposed ATHP could adaptively adjust the optimum inertance-to-mass ratio by tracking the dominant wave frequencies in real time, and the proposed system shows better control performance than the conventional THP.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3150-3163
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• 2023

To improve the performance of blanket: maximizing the tritium breeding rate (TBR) for tritium self-sufficiency, and minimizing the Dose of backplate for radiation protection, most previous studies are based on manual corrections to adjust the blanket structure to achieve optimization design, but it is difficult to find an optimal structure and tends to be trapped by local optimizations as it involves multiphysics field design, which is also inefficient and time-consuming process. The artificial intelligence (AI) maybe is a potential method for the optimization design of the blanket. So, this paper aims to develop an intelligent optimization method based on an improved multi-objective NSGA-III algorithm and an adaptive BP neural network to solve these problems mentioned above. This method has been applied on optimizing the radial arrangement of a conceptual design of CFETR HCSB blanket. Finally, a series of optimal radial arrangements are obtained under the constraints that the temperature of each component of the blanket does not exceed the limit and the radial length remains unchanged, the efficiency of the blanket optimization design is significantly improved. This study will provide a clue and inspiration for the application of artificial intelligence technology in the optimization design of blanket.

• Journal of the Korea Computer Graphics Society
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• v.15 no.3
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• pp.19-26
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• 2009

In this paper, a new adaptive vertex clustering using a KD-tree is presented for 3D mesh partitioning. A vertex clustering is used to divide a huge 3D mesh into several partitions for various mesh processing. An octree-based clustering and K-means clustering are currently leading techniques. However, the octree-based methods practice uniform space divisions and so each partitioned mesh has non-uniformly distributed number of vertices and the difference in its size. The K-means clustering produces uniformly partitioned meshes but takes much time due to many repetitions and optimizations. Therefore, we propose to use a KD-tree to efficiently partition meshes with uniform number of vertices. The bounding box region of the given mesh is adaptively subdivided according to the number of vertices included and dynamically determined axis. As a result, the partitioned meshes have a property of compactness with uniformly distributed vertices.