Mobile Edge Computing Servers Deployment with Improved Genetic Algorithm in Cellular Internet of Things

Mobile edge computing(MEC)provides services to devices and reduces latency in cellular internet of things(IoT)networks.However,the challenging problem is how to deploy MEC servers economically and efficiently.This paper investigates the deployment problem of MEC servers of the real-world road network by employing an improved genetic algorithm(GA)scheme.We first use the threshold-based K-means algorithm to form vehicle clusters according to their locations.We then select base stations(BSs)based on clustering center coordinates as the deployment locations set for potential MEC servers.We further select BSs using a combined simulated annealing(SA)algorithm and GA to minimize the deployment cost.The simulation results show that the improved GA deploys MEC servers effectively.In addition,the proposed algorithm outperforms GA and SA algorithms in terms of convergence speed and solution quality.

Improved adaptive genetic algorithm based RFID positioning

The existing active tag-based radio frequency identi-fication(RFID)localization techniques show low accuracy in practical applications.To address such problems,we propose a chaotic adaptive genetic algorithm to align the passive tag ar-rays.We use chaotic sequences to generate the intersection points,the weakest single point intersection is used to ensure the convergence accuracy of the algorithm while avoiding the optimization jitter problem.Meanwhile,to avoid the problem of slow convergence and immature convergence of the algorithm caused by the weakening of individual competition at a later stage,we use adaptive rate of change to improve the optimiza-tion efficiency.In addition,to remove signal noise and outliers,we preprocess the data using Gaussian filtering.Experimental results demonstrate that the proposed algorithm achieves high-er localization accuracy and improves the convergence speed.

Advances in the Study of Protein Quality Traits and Main Influencing Factors of Wheat in China

Wheat, the third major grain crop in China, is an important source of hu- man proteins. Wheat quality and yield has a direct impact on the development of agricultural economy and food industry. Investigating and improving protein quality of wheat has become a key to solving the contradiction. This paper reviewed the exist- ing literature published at home and abroad, analyzed the present situation and ex- isting problems of wheat protein quality in China, summarized the latest research progress about genetic models, main influencing factors, and correlations between protein quality traits and other traits, discussed current issues in the improvement of wheat protein quality, and proposed suggestions for breeding high-quality wheat, aiming at providing theoretical basis for genetic improvement, planting structure ad- justment and efficient production of high-quality wheat.

Effects of acquiring FSC forest management certification for Japanese enterprises using SmartWood Audits

We explore the organizational, environmental, and economic effects of sustainable forest management （FM） certification by Smart- Wood （SW）, one of the certification bodies accredited by the Forest Stewardship Council （FSC） to carry out certification in Japan. We closely investigated three enterprises： the Yusuhara Forest Owners＇ Cooperative, Yamanashi Prefectural Forest, and Ryujin-mura Forest Owners＇ Coopera- tive. Interviews with representatives of these entities provided crucial empirical information regarding the influence of certification on envi- ronmental assessment, rare-species protection, landscape-management planning, management objectives, and forest supervision. Attainment of FM status improved environmental awareness and engendered positive changes in assessing and managing forests and other natural resources but simultaneously imposed heavier economic costs.

An Improved Gas-Kinetic Scheme for Multimaterial Flows

The efficiency of recently developed gas-kinetic scheme for multimaterial flows is increased through the adoption of a new iteration method in the kinetic non-mixing Riemann solver and an interface sharpening reconstruction method at a cell interface.The iteration method is used to determine the velocity of fluid interface,based on the force balance between both sides due to the incidence and bounce back of particles at the interface.An improved Aitken method is proposed with a simple hybrid of the modified Aitken method(Aitken-Chen)and the Steffensen method.Numerical tests validate its efficiency with significantly less calls to the function not only for the average number but also for the maximum.The new reconstruction is based on the tangent of hyperbola for interface capturing(THINC)but applied only to the volume fraction,which is very simple to be implemented under the stratified frame-work and capable of resolving fluid interface in mixture.Furthermore,the directional splitting is adopted rather than the previous quasi-one-dimensional method.Typical numerical tests,including several watergas shock tube flows,and the shock-water cylinder interaction flow show that the improved gas-kinetic scheme can capture fluid interfaces much sharper,while preserving the advantages of the original one.

ON NEW STRATEGIES TO CONTROL THE ACCURACY OF WENO ALGORITHM CLOSE TO DISCONTINUITIES Ⅱ:CELL AVERAGES AND MULTIRESOLUTION

This paper is the second part of the article and is devoted to the construction and analysis of new non-linear optimal weights for WENO interpolation capable of rising the order of accuracy close to discontinuities for data discretized in the cell averages.Thus,now we are interested in analyze the capabilities of the new algorithm when working with functions belonging to the subspace L1\L2 and that,consequently,are piecewise smooth and can present jump discontinuities.The new non-linear optimal weights are redesigned in a way that leads to optimal theoretical accuracy close to the discontinuities and at smooth zones.We will present the new algorithm for the approximation case and we will analyze its accuracy.Then we will explain how to use the new algorithm in multiresolution applications for univariate and bivariate functions.The numerical results confirm the theoretical proofs presented.