Face relighting using discriminative 2D spherical spaces for face recognition

As part of the face recognition task in a robust security system, we propose a novel approach for the illumination recovery of faces with cast shadows and specularities. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients by using the face spherical spaces properties. First, an illumination training database is generated by computing the properties of the spherical spaces out of face albedo and normal values estimated from 2D training images. The training database is then discriminately divided into two directions in terms of the illumination quality and light direction of each image. Based on the generated multi-level illumination discriminative training space, we analyze the target face pixels and compare them with the appropriate training subspace using pre-generated tiles. When designing the framework, practical real-time processing speed and small image size were considered. In contrast to other approaches, our technique requires neither 3D face models nor restricted illumination conditions for the training process. Furthermore, the proposed approach uses one single face image to estimate the face albedo and face spherical spaces. In this work, we also provide the results of a series of experiments performed on publicly available databases to show the significant improvements in the face recognition rates.     

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.     

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.     

Enhancement of the neural network modeling accuracy using a submodeling decomposition-based technique, application in gas sensor

This paper presents an algorithm based on the use of artificial neural networks (ANNs) in order to reduce the processing time and to improve the accuracy in ANN modeling, which can be accomplished with a division of the model to submodels by input subintervals. We apply this method with a gas sensor aiming to accurately control the small gas leaks, thus decreasing the risk of false alarms and missed detections. The sensor model accurately, especially in small concentrations, expresses the nonlinear character of the response and the dependence on temperature and relative humidity in addition to the gas nature dependency. The corrector linearizes and compensates the sensor’s responses. The results obtained show the effectiveness of the proposed technique.     

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.     

An optimization model for storage yard management in transshipment hubs

This paper studies a yard storage allocation problem in a transshipment hub where there is a great number of loading and unloading activities. The primary challenge is to efficiently shift containers between the vessels and the storage area so that reshuffling and traffic congestion is minimized. In particular, to reduce reshuffling, a consignment strategy is used. This strategy groups unloaded containers according to their destination vessel. To reduce traffic congestion, a new workload balancing protocol is proposed. A mixed integer-programming model is then formulated to determine the minimum number of yard cranes to deploy and the location where unloaded containers should be stored. The model is solved using CPLEX. Due to the size and complexity of this model two heuristics are also developed. The first is a sequential method while the second is a column generation method. A bound is developed that allows the quality of the solution to be judged. Lastly, a numerical investigation is provided and demonstrates that the algorithms perform adequately on most cases considered.