Elasto-Thermodiffusive Response in a Spherically Isotropic Hollow Sphere

The present work deals with the investigation of elasto-thermo diffusion interactions inside a spherically isotropic hollow sphere in the context of linear theory of generalized thermoelastic diffusion based on Green and Lindsay theory. The inner and outer boundaries of the body are free from stresses and are subjected to a time-dependent thermal shock and also the chemical shock. Laplace transform techniques are used to write the basic equations in the form of a vector matrix differential equations, which is then solved by the eigenvalue approach. The inversion of the transformed solution is carried out by applying the method of Bellman. The stress, temperature, mass concentration and chemical potential are computed and presented graphically. A comparative study of diffusive medium and thermoelastic medium is carried out, and it was seen that the effect of diffusion is significant on the stresses. A comparison of spherically isotropic body with isotropic body has also been presented, and a significant difference is observed.     

数据库垄断的成因及对策分析

学术数据库市场被少数几个出版商掌握，新的数据库商难以加入到竞争中来，因此导致了学术数据库市场的垄断问题。本文通过叙述学术数据库垄断的四个问题，即数据库定价的不合理、数据库许可权的滥用、经营者集中和数据库用户受限，提出通过开放获取、图书馆联合与立法保护来应对数据库市场的垄断问题。     

具有双通道数据包丢失的Delta算子系统故障检测

研究同时存在双通道数据包丢失和时变时延的Delta算子网络控制系统（NCSs）故障检测问题.假定数据包丢失发生在控制器到执行器、传感器至控制器的数据传输过程中，并且利用两个相互独立的伯努利随机变量描述是否发生丢包.将上述的NCSs建模为网络切换系统，提出任意切换律下故障检测滤波器的设计方法.利用线性矩阵不等式（LMIs）方法、Lyapunov-Krasovskii泛函和平均驻留时间等得出所考虑的网络切换系统具备指数均方稳定性的充分条件.证明了所用的网络切换系统满足H_∞性能，并推导出了滤波器参数的显式表达.数值仿真结果验证了所提方法的有效性.     

Electrodeposition of amorphous Ni–P layers,thermal treatment and corrosion behaviour

The investigation reported comprises an experimental study of the thermal and corrosion properties of electrodeposited nickel-phosphorus amorphous alloy layers. The structure of the species was determined by means of X-ray diffraction spectroscopy. Samples with hypo- and hyper-eutectic compositions were synthesised out of modified classical and customised electrolytic solutions on copper substrates. The composition of the samples was determined via energy dispersive spectroscopy. A short review of the development of the composition of existing plating baths for Ni–P electrodeposition has also been presented. Thermal treatment of the samples has been carried out to crystallise the amorphous structure and to compare the thermal and the corrosion properties of the species with both types of structure. Differential thermal measurements were used to examine the thermal effects in the Ni–P samples obtained. The corrosion parameters of initial as-plated and thermally treated binary Ni–P alloy coatings were determined from Tafel plot analysis.     

基于变异测试的错误定位研究进展

随着软件规模和复杂度的不断提高，软件的质量问题成为了关注的焦点，如何高效地找出软件中的错误成为一个亟需解决的问题。错误定位是软件质量保证的重要途径之一，近年来已经成为软件工程中一个非常重要的研究课题。基于变异测试的错误定位通过比较原程序和对应变异体的差异来计算每条语句的怀疑度，再由怀疑度大小进行排序，程序员根据排序逐个检查找出错误语句。汇总近7年（2012-2018）国内外的基于变异测试的错误定位技术的研究成果，介绍了错误定位的基本方法，介绍基于变异测试的错误定位思想，从变异算子、变异体及等价变异体3个方面对已有的研究工作进行分类归纳和总结，探讨了基于变异测试的错误定位未来可能的研究方向、机遇和挑战。     

OTS在环氧氯丙烷装置中的应用

研究了操作员仿真培训系统(OTS)在环氧氯丙烷装置中的具体应用。介绍了OTS的基本概念及软硬件组成,对环氧氯丙烷工艺流程进行分析并研究了OTS系统的使用流程,总结了研究的成果在实际生产中所带来的经济和社会效益。     

注塑机料筒温度调控和计算机仿真研究

利用模糊控制和比例积分微分(PID)控制相结合的手段对注塑机料筒温度进行了控制,同时以Matlab 6.0软件为仿真平台,对料筒温度控制进行了模拟仿真研究。实验发现,在注塑机料筒升温过程中利用CHR整定的PID控制手段和模糊控制手段,恒温过程中利用人工整定的PID控制手段,可保证快速的料筒升温响应速率和稳定的保温过程。通过实际注塑实验对该仿真结果进行了验证,在十组实验中,料筒温度误差不超过2%,产品翘曲变形量不超过0.059 mm。     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

A novel hybridized metaheuristic technique in enhancing the diagnosis of cross-sectional dent damaged offshore platform members

Offshore jacket platforms are widely used for oil and gas extraction as well as transportation in shallow to moderate water depth. Tubular cross-sectional elements are used to construct offshore platforms. Tubular cross sections impart higher resistance against hydrodynamic forces and have high torsional rigidity. During operation, the members can be partially or fully damaged due to lateral impacts. The lateral impacts can be due to ship collisions or through the impact of falling objects. The impact forces can weaken some members that influence the overall performance of the platform. This demonstrates an urgent need to develop a framework that can accurately forecast dent depth as well as dent angle of the affected members. This study investigates the use of an adaptive metaheuristics algorithm to provide automatic detection of denting damage in an offshore structure. The damage information includes dent depth and the dent angle. A model is developed in combination with the percentage of the dent depth of the damaged member and is used to assess the performance of the method. It demonstrates that small changes in stiffness of individual damaged bracing members are detectable from measurements of global structural motion.     

Modified transform-based gamma correction for MRI tumor image denoising and segmentation by optimized histon-based elephant herding algorithm

Medical image processing is typically performed to diagnose a patient's brain tumor prior to surgery. In this study, a technique in denoising and segmentation was developed to improve medical image processing. The proposed approach employs multiple modules. In the first module, the noisy brain tumor image is transformed into multiple low- and high-pass tetrolet coefficients. In the second module, multiple low-pass tetrolet coefficients are applied through a modified transform-based gamma correction method. Generalized cross-validation is used on multiple high-pass tetrolet coefficients to obtain the best threshold value. In the third module, all enhanced coefficients are applied to the partial differential equation method. In the final module, the denoised image is applied to Atanassov's intuitionistic fuzzy set histon-based fuzzy clustering method with centroid optimization using an elephant herding method. Accordingly, the tumor part is segmented from the nontumor part in the magnetic resonance imaging brain images. The method was assessed in terms of peak signal-to-noise ratio, mean square error, specificity, sensitivity, and accuracy. The experimental results showed that the suggested method is superior to traditional methods.