Nonlinear evolutionary swarm intelligence of grasshopper optimization algorithm and gray wolf optimization for weight adjustment of neural network

Engineering with Computers - The advent of new data-mining techniques and, more recently, swarm-based optimization algorithms have antiquated traditional models in the field of energy performance...     

MicroPort: A general simulation platform for seaport container terminals

Seaport container terminals are essential nodes in sea cargo transportation networks. As such, the operational efficiency of container terminals in handling containers passing through them plays a critical role in a globalized world economy. Many models and algorithms have been developed to address various decision problems in container terminals to help improve operational efficiency. These decision support tools are usually used separately for specific purposes. However, the problems they are trying to tackle are often interrelated. Therefore, in this regard, an evaluation tool which can capture as many operational conditions as possible for different decision problems is necessary. This paper introduces a general simulation platform, named MicroPort, which aims to provide an integrated and flexible modeling system for evaluating the operational capability and efficiency of different designs of seaport container terminals. The software structure of MicroPort comprises three programming layers: (1) the Functions layer; (2) the Applications layer; and (3) the Extensions layer. Different layers are bound by Application Programming Interfaces (APIs). Basic functions built in the Functions layer support the Applications layer in which major operation processes can be modeled by an agent-based method. External modules and decision support tools in the Extensions layer then use APIs to adjust the system to produce suitable simulation models for specific purposes.     

Efficacy of iron fortification compared to iron supplementation among Vietnamese schoolchildren

Background  

Parents of six children are facing a trial on charges of aggravated manslaughter in the care a 5 1/2 month old infant who died suddenly and neglect of their four older children for causing them to be malnourished by feeding them all an exclusively raw foods vegan diet. Both parents declined plea bargains and plan to defend themselves in court.     

An augmented Lagrangian approach to non-convex SAO using diagonal quadratic approximations

Successful gradient-based sequential approximate optimization (SAO) algorithms in simulation-based optimization typically use convex separable approximations. Convex approximations may however not be very efficient if the true objective function and/or the constraints are concave. Using diagonal quadratic approximations, we show that non-convex approximations may indeed require significantly fewer iterations than their convex counterparts. The nonconvex subproblems are solved using an augmented Lagrangian (AL) strategy, rather than the Falk-dual, which is the norm in SAO based on convex subproblems. The results suggest that transformation of large-scale optimization problems with only a few constraints to a dual form via convexification need sometimes not be required, since this may equally well be done using an AL formulation.     

Simultaneous Imaging of Endogenous Survivin mRNA and On‐Demand Drug Release in Live Cells by Using a Mesoporous Silica Nanoquencher

The design of multifunctional drug delivery systems capable of simultaneous target detection, imaging, and therapeutics in live mammalian cells is critical for biomedical research. In this study, by using mesoporous silica nanoparticles (MSNs) chemically modified with a small‐molecule dark quencher, followed by sequential drug encapsulation, MSN capping with a dye‐labeled antisense oligonucleotide, and bioorthogonal surface modification with cell‐penetrating poly(disulfide)s, the authors have successfully developed the first mesoporous silica nanoquencher (qMSN), characterized by high drug‐loading and endocytosis‐independent cell uptake, which is able to quantitatively image endogenous survivin mRNA and release the loaded drug in a manner that depends on the survivin expression level in tumor cells. The authors further show that this novel drug delivery system may be used to minimize potential cytotoxicity encountered by many existing small‐molecule drugs in cancer therapy.     

Disturbance decoupled fault reconstruction using sliding mode observers

This paper investigates and presents conditions that guarantee disturbance decoupled fault reconstruction using sliding mode observers, which are less stringent than those of previous work, and show that disturbance reconstruction is not necessary. An aircraft model validates the ideas proposed in this paper. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Compensation of hysteresis in piezoelectric actuator with iterative learning control

This paper presents the application of iterative learning control (ILC) to compensate hysteresis in a piezoelectric actuator. The proposed controller is a hybrid of proportional-integral-differential (PID) control, whose main function is for trajectory tracking, and a chatter-based ILC, whose main function is for hysteresis compensation. Stability analysis of the proposed ILC is presented, with the PID included in the dynamic of the piezoelectric actuator. The performance of the proposed controller is analysed through simulation and verified with experiment with a piezoelectric actuator.     

SVD-based Preisach hysteresis identification and composite control of piezo actuators

In this paper, the singular value decomposition (SVD) based identification and compensation of the hysteretic phenomenon in piezo actuators are addressed using a Preisach model. First, this paper presents an SVD-based least squares algorithm and a revision approach of the identification through updating the SVD. With the identified parameters and a log of the memory curve, a Preisach-based inversion compensator is constructed which is complemented with a feedback controller to address the inevitable and residual modeling errors. Experimental results are furnished for both the identification and compensation approaches. The Preisach-based feedforward controller significantly improves the tracking performance and reduces the root-mean-square (RMS) tracking error of a PID controller by 76.7% and 89% at 1 Hz and 25 Hz, respectively. With the proposed composite controller, the percent-RMS errors at 1 Hz and 25 Hz are reduced to 0.035% and 0.31%, respectively.     

Disturbance decoupled fault reconstruction using cascaded sliding mode observers

This paper presents a disturbance decoupled fault reconstruction (DDFR) scheme using cascaded sliding mode observers (SMOs). The processed signals from a SMO are found to be the output of a fictitious system which treats the faults and disturbances as inputs; the ‘outputs’ are then fed into the next SMO. This process is repeated until the attainment of a fictitious system which satisfies the conditions that guarantee DDFR. It is found that this scheme is less restrictive and enables DDFR for a wider class of systems compared to previous work when only one or two SMOs were used. This paper also presents a systematic routine to check for the feasibility of the scheme and to calculate the required number of SMOs from the outset and also to design the DDFR scheme. A design example verifies its effectiveness.