An evolutionary lion optimization algorithm‐based image compression technique for biomedical applications

Recently, medical image compression becomes essential to effectively handle large amounts of medical data for storage and communication purposes. Vector quantization (VQ) is a popular image compression technique, and the commonly used VQ model is Linde–Buzo–Gray (LBG) that constructs a local optimal codebook to compress images. The codebook construction was considered as an optimization problem, and a bioinspired algorithm was employed to solve it. This article proposed a VQ codebook construction approach called the L2‐LBG method utilizing the Lion optimization algorithm (LOA) and Lempel Ziv Markov chain Algorithm (LZMA). Once LOA constructed the codebook, LZMA was applied to compress the index table and further increase the compression performance of the LOA. A set of experimentation has been carried out using the benchmark medical images, and a comparative analysis was conducted with Cuckoo Search‐based LBG (CS‐LBG), Firefly‐based LBG (FF‐LBG) and JPEG2000. The compression efficiency of the presented model was validated in terms of compression ratio (CR), compression factor (CF), bit rate, and peak signal to noise ratio (PSNR). The proposed L2‐LBG method obtained a higher CR of 0.3425375 and PSNR value of 52.62459 compared to CS‐LBG, FA‐LBG, and JPEG2000 methods. The experimental values revealed that the L2‐LBG process yielded effective compression performance with a better‐quality reconstructed image.     

Real-time integrated production-scheduling and maintenance-planning in a flexible job shop with machine deterioration and condition-based maintenance

The introduction of modern technologies in manufacturing is contributing to the emergence of smart (and data-driven) manufacturing systems, known as Industry 4.0. The benefits of adopting such technologies can be fully utilized by presenting optimization models in every step of the decision-making process. This includes the optimization of maintenance plans and production schedules, which are two essential aspects of any manufacturing process. In this paper, we consider the real-time joint optimization of maintenance planning and production scheduling in smart manufacturing systems. We have considered a flexible job shop production layout and addressed several issues that usually take place in practice. The addressed issues are: new job arrivals, unexpected due date changes, machine degradation, random breakdowns, minimal repairs, and condition-based maintenance (CBM). We have proposed a real-time optimization-based system that utilizes a modified hybrid genetic algorithm, an integrated proactive-reactive optimization model, and hybrid rescheduling policies. A set of modified benchmark problems is used to test the proposed system by comparing its performance to several other optimization algorithms and methods used in practice. The results show the superiority of the proposed system for solving the problem under study. The results also emphasize the importance of the quality of the generated baseline plans (i.e., initial integrated plans), the use of hybrid rescheduling policies, and the importance of rescheduling times (i.e., reaction times) for cost savings.     

基于SPOT-5多光谱影像的矿区塌塘水体提取方法研究

针对基于遥感影像的水体提取方法存在水体提取不完整和误提的现象,提出了一种基于SPOT-5多光谱影像的矿区塌塘水体提取方法。在利用波段合成增加一个可用波段的基础上对已有的水体提取方法进行适当的改进,并基于决策树分类器和改进后的方法进行矿区水体的四级提取,保证了水体提取的完整性,同时减少了误提率;最后利用实测数据对水体提取的精度进行了评定。试验结果表明,基于决策树分类器的水体提取方法具有较高的精度,能满足矿区实际应用的需要。     

隐极无刷双馈电动机的研究

针对无刷双馈电动机的转子磁场转换效率决定了其工作效率的问题,提出了一种隐极无刷双馈电动机隐极转子结构的优化设计方案。对作用较小的隐极转子进行优化设计,即将它们的槽型更改为半开口槽,不断改变它们的长宽比;利用有限元软件ANSYS分析不同长宽比转子结构的隐极无刷双馈电动机,获得其功率绕组励磁与控制绕组励磁分布;利用Matlab软件分解转子磁动势,获得转子磁动势的谐波含量,从而确定最有效谐波含量。实验结果表明,在设定隐极转子的长宽比分别为10、13、15、17、20的情况下,隐极无刷电动机在15倍长宽比转子结构时的能量转换效果最好。     

煤矿井下高压降尘供水系统监控装置的研制

根据煤矿井下高压降尘系统对供水的要求,研制了一种基于PIC18F4580单片机的井下高压降尘供水系统监控装置,介绍了该装置的硬件和软件设计。该装置可实时监测水箱水位、压力、运行状态,并可将这些保护状态信息通过CAN总线接口和转换单元并入煤矿监测监控网,实现远程监测。实验结果表明,该监控装置达到了设计要求,能保证高压降尘供水系统的实时监测与安全运行。     

矿用柴油机车中新型无源液位传感器设计

针对目前矿用柴油机车液位传感器无法动态调整水箱剩余水位的报警高度、可靠性较差等问题,提出一种新型无源液位传感器的设计方案。该液位传感器采用干簧管和电阻阵列等无源器件,实现了对水箱水位高度的连续监测,并可设置报警深度,可靠性和耐高温性能较好。     

空间遥感TDICCD相机振动补偿的优化设计

为了降低振动对空间遥感TDICCD相机的影响,提高成像质量,提出了被动补偿和主动补偿相结合的振动补偿方法;分析了振动对TDICCD相机MTF的影响,指出了当振动量小于一定数值时,通过优化设置积分级数可以同时满足系统对信噪比和调制传递函数的要求,提出了小振动时积分级数被动补偿和大振动时压电陶瓷主动补偿相结合的补偿方法;数值计算结果表明,在系统的信噪比要求为100倍,振动导致的调制传递函数大于0.95的前提下,当振动量不大于0.0136μm时,可采用被动补偿的方法对振动进行补偿,否则采用主动补偿。     

多目标优化策略在精馏过程中的应用研究

针对精馏塔自由度多,能耗大,扰动复杂多变,控制和优化要求高等特点,提出了一种基于动态矩阵控制(DMC)的二层多目标优化控制策略。在实现精馏过程控制目标的前提下,设计了二层优化指标,可在有多余自由度的情况下,进行二层控制和优化,实现精馏过程质量控制目标和经济运行优化。通过对Shell多侧线精馏过程的仿真研究,验证了二层多目标优化控制策略的有效性。与DMC控制相比,二层多目标优化控制策略可以明显改善精馏塔运行的经济性,实现增加收益的目标。     

基于蚁群优化的WSN能耗均衡链状路由协议

为了从路由技术的角度解决无线传感器网络的能耗问题,综合蚁群优化算法和PEGASIS协议的思想提出了ACO-PEGASIS路由协议;该协议采用蚁群优化算法构建通信链,解决了PEGASIS协议中由于贪婪算法的局部性产生的相邻节点间的长链问题;并在成链过程中综合考虑节点间距离、节点剩余能量等因子,以均衡全网的能量消耗;同时根据距离和能量因素选取链头节点并采用一定措施降低链头重选次数;仿真结果表明,与PEGASIS协议相比,该协议更加有效地均衡了全网的能量消耗,延长了网络的生存周期。     

Reduced order model predictive control for constrained discrete‐time linear systems

A reduced order model predictive control (MPC) is discussed for constrained discrete‐time linear systems. By employing a decomposition method for finite‐horizon linear systems, an MPC law is obtained from a reduced order optimization problem. The decomposition enables us to construct pairs of initial state and control sequence which have large influence on system responses, and it also characterizes the standard LQ control. The MPC law is obtained based on a combination of the LQ control and dominant input sequences over the prediction horizon. The proposed MPC method is illustrated with numerical examples. Copyright © 2011 John Wiley & Sons, Ltd.