• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.389-390
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• 2019

Tensor decomposition, proven to be an efficient data processing method, can be used to provide data-driven services. we propose a novel datadriven mutation strategy for parent individuals selection, namely tensor-based DE with parapatric and cross-generation(TPCDE).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.383-403
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• 2021

With the development of mobile edge computing (MEC), some late-model application technologies, such as self-driving, augmented reality (AR) and traffic perception, emerge as the times require. Nevertheless, the high-latency and low-reliability of the traditional cloud computing solutions are difficult to meet the requirement of growing smart cars (SCs) with computing-intensive applications. Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency. To solve this problem with effect, we propose a context-aware offloading strategy based on differential evolution algorithm (DE) by considering vehicle mobility, roadside units (RSUs) coverage, vehicle priority. On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. Simulation results demonstrate that the practical performance of the context-aware vehicular task offloading (CAVTO) optimization scheme could reduce the system delay significantly.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.293-303
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• 2016

Analysis of bargaining games utilizing evolutionary computation in recent years has dealt with important issues in the field of game theory. In this paper, we investigated interaction and coevolution process among heterogeneous artificial agents using evolutionary computation in the bargaining game. We present three kinds of evolving-strategic agents participating in the bargaining games; genetic algorithms (GA), particle swarm optimization (PSO) and differential evolution (DE). The co-evolutionary processes among three kinds of artificial agents which are GA-agent, PSO-agent, and DE-agent are tested to observe which EC-agent shows the best performance in the bargaining game. The simulation results show that a PSO-agent is better than a GA-agent and a DE-agent, and that a GA-agent is better than a DE-agent with respect to co-evolution in bargaining game. In order to understand why a PSO-agent is the best among three kinds of artificial agents in the bargaining game, we observed the strategies of artificial agents after completion of game. The results indicated that the PSO-agent evolves in direction of the strategy to gain as much as possible at the risk of gaining no property upon failure of the transaction, while the GA-agent and the DE-agent evolve in direction of the strategy to accomplish the transaction regardless of the quantity.

• Steel and Composite Structures
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• v.51 no.4
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• pp.363-375
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• 2024

Within the optimization field, addressing the intricate posed by fluidic pressure loads on functionally graded structures with frequency-related designs is a kind of complex design challenges. This paper thus introduces an innovative density-based topology optimization strategy for frequency-constraint functionally graded structures incorporating Darcy's law and a drainage term. It ensures consistent treatment of design-dependent fluidic pressure loads to frequency-related structures that dynamically adjust their direction and location throughout the design evolution. The porosity of each finite element, coupled with its drainage term, is intricately linked to its density variable through a Heaviside function, ensuring a seamless transition between solid and void phases. A design-specific pressure field is established by employing Darcy's law, and the associated partial differential equation is solved using finite element analysis. Subsequently, this pressure field is utilized to ascertain consistent nodal loads, enabling an efficient evaluation of load sensitivities through the adjoint-variable method. Moreover, this novel approach incorporates load-dependent structures, frequency constraints, functionally graded material models, and polygonal meshes, expanding its applicability and flexibility to a broader range of engineering scenarios. The proposed methodology's effectiveness and robustness are demonstrated through numerical examples, including fluidic pressure-loaded frequency-constraint structures undergoing small deformations, where compliance is minimized for structures optimized within specified resource constraints.

• Smart Structures and Systems
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• v.31 no.4
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• pp.421-436
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• 2023

This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.

• Korean journal of applied entomology
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• v.22 no.2 s.55
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• pp.52-66
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• 1983

The brown planthopper, N. lugens (Stal), has become a serious pest of rice in tropical Asia during the last decade. At high pest density, its feeding damage causes 'hopperburn' or complete wilting and drying of the rice plant. It also transmits grassy and ragged stunt virus diseases. The estimated losses caused by the pest in tropical Asia exceed $US\$300$ millions. While cultivation of resistant rice varieties has proved to be highly effective against the pest, their long-term stability is threatened because of the evolution of prolific biotypes which can destroy these varieties. At present, identification of biotypes is based principally on the differential reactions of host rice varieties to the pest and on host-mediated behavioral and physiological responses of the pest. Recent findings of morphological differences in adult rostrum, legs, and antennae, body parts that possess receptors for host plant location and discrimination, and cytological differences in N. lugens populations maintained as stock cultures strongly complement other biotype studies. So far, three N. lugens biotypes have been identified in the Philippines. Biotype I can survive on and damage varieties that do not carry and genes for resistance, while Biotype 2 survives on resistant varieties carrying Bph 1 gene and Biotype 3 on varieties carrying gene bph 2. However, none of these biotypes can survive on varieties with genes Bph 3 or bph 4. Several varieties which are resistant in the Philippines are susceptible in India and Sri Lanka as the South Asian biotypes of N. lugens are more virulent than Southeast Asian biotypes. To monitor the pest biotypes in different geographical regions and to identify new sources of resistance, an International Brown Planthopper Nursery has been established in many cooperating countries. The evolution of biotypes is an exceedingly complex process which is governed by the interactions of genetic and biological factors of the pest populations and the genetic makeup of the cultivated varieties. While the strategy for sequential release of varieties with major resistance genes has been fairly successful so far, the monegenic resistance of these varieties makes them vulnerable to the development of the pest biotypes. Therefore, present breeding endeavors envisage utilizing both major and minor resistance genes for effective control of the pest.