Risk-sensitive control of Markov jump linear systems: Caveats and difficulties

In this technical note, we revisit the risk-sensitive optimal control problem for Markov jump linear systems (MJLSs). We first demonstrate the inherent difficulty in solving the risk-sensitive optimal control problem even if the system is linear and the cost function is quadratic. This is due to the nonlinear nature of the coupled set of Hamilton-Jacobi-Bellman (HJB) equations, stemming from the presence of the jump process. It thus follows that the standard quadratic form of the value function with a set of coupled Riccati differential equations cannot be a candidate solution to the coupled HJB equations. We subsequently show that there is no equivalence relationship between the problems of risk-sensitive control and H ^∞ control of MJLSs, which are shown to be equivalent in the absence of any jumps. Finally, we show that there does not exist a large deviation limit as well as a risk-neutral limit of the risk-sensitive optimal control problem due to the presence of a nonlinear coupling term in the HJB equations.

     

An incremental neural network for tissue segmentation in ultrasound images

This paper presents an incremental neural network (INeN) for the segmentation of tissues in ultrasound images. The performances of the INeN and the Kohonen network are investigated for ultrasound image segmentation. The elements of the feature vectors are individually formed by using discrete Fourier transform (DFT) and discrete cosine transform (DCT). The training set formed from blocks of 4x4 pixels (regions of interest, ROIs) on five different tissues designated by an expert is used for the training of the Kohonen network. The training set of the INeN is formed from randomly selected ROIs of 4x4 pixels in the image. Performances of both 2D-DFT and 2D-DCT are comparatively examined for the segmentation of ultrasound images.     

Psychosocial and health consequences of adolescent depression in Black and White young adult women.

Depression in adolescent girls may result in negative consequences in young adulthood. The Center for Epidemiologic Studies Depression Scale (CES-D) was administered to 1,727 Black and White girls ages 16 to 18 years who participated in the National Heart, Lung, and Blood Institute's Growth and Health Study. Three years later, women in the depressed groups were more likely to be current smokers, had attained a lower level of education, and reported lower self-worth relative to the nondepressed group. Body dissatisfaction, eating concerns, and loneliness were greater in the depressed groups. Relative to Black women, White women who were moderately depressed during adolescence reported more health care services utilization in young adulthood. Prevention efforts for depressed adolescents should be broadly focused to improve young adult outcomes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Application of InP Neural Network to ECG BeatClassification

This paper presents an application of a hybrid neural network structure to the classification of the electrocardiogram (ECG) beats. Three different feature extraction methods are comparatively examined: discrete cosine transform, wavelet transform and a direct method. Classification performances, training times and the numbers of nodes of Kohonen network, Restricted Coulomb Energy (RCE) network and the hybrid neural network are presented. To increase the classification performance and to decrease the number of nodes, the hybrid neural network is trained by Genetic Algorithms (GAs). Ten types of ECG beats obtained from the MIT-BIH database and from a real-time ECG measurement system are classified with a success of 98% by using the hybrid neural network structure and discrete cosine transform together.     

The effect of categorizing returned products in remanufacturing

An increasing number of companies have been implementing comprehensive recycling and remanufacturing programs. These endeavors typically involve the operation of joint manufacturing and remanufacturing systems. One of the major challenges in managing such hybrid systems is the stochastic nature of product returns. In particular, there is significant variability in the condition of the returns. This paper presents an approach for assessing the impact of quality-based categorization of returned products. Through extensive numerical studies on a continuous-time Markov chain model, we show that incorporation of returned product quality in the remanufacturing and disposal decisions can lead to significant cost savings. We find that these savings are amplified as the return quality decreases, and as the return rate increases. We also show that prioritizing higher quality returns in remanufacturing is, in general, a better strategy.     

Electrospun polymeric nanofibrous composites containing TiO2 short nanofibers

In this study, polymeric nanofibrous composites containing anatase TiO₂ short nanofibers (TiO₂-SNF) were successfully produced via electrospinning. The fabrication of the nanofibrous composite structure includes two steps. First, anatase TiO₂ nanofibers were obtained by calcination of electrospun PVP/TiO₂ nanofibers and then crushed into short nanofibers ranging from few microns in length. Second, these TiO₂-SNF were dispersed into polymer solutions and then electrospun into nanofibrous composites. We obtained nanofibers containing TiO₂-SNF from different polymer types including PMMA, PAN, PET and PC. The SEM and TEM imaging indicated that some of the TiO₂-SNF were fully covered by the polymeric matrix whereas some TiO₂-SNF were partially covered and/or stick on the surface of the fibers. The photocatalytic activity of nanofibrous composites containing TiO₂-SNF was evaluated by monitoring the photocatalytic decomposition of a model dye (rhodamine-6G) under UV irradiation.     

Efficiency of an Otto engine under alternative power optimizations

The proper optimization criterion to be chosen for the optimum design of the heat engines may differ depending on their purposes and working conditions. In this study, a comparative performance analysis is carried out for a reversible Otto cycle based on three alternative performance criteria namely maximum power (mp), maximum power density (mpd) and maximum efficient power (mep). The power density criterion is defined as the power per minimum specific volume in the cycle and the efficient power criterion is defined as multiplication of the power by the efficiency of the Otto cycle. Maximizing the efficient power gives a compromise between power and efficiency. Three different objective functions are defined and maximization of these functions is carried out under different design parameters of the Otto engine. The variations of power, power density and efficient power outputs are derived and presented with respect to the thermal efficiency of the cycle for various temperature ratios. It has been found that the design parameters at mep conditions lead to more efficient engines than that at the mp condition and the mep criterion may have a significant power advantage compared with mpd criterion. Copyright © 2009 John Wiley & Sons, Ltd.