Iris segmentation in non-ideal images using graph cuts

A non-ideal iris image segmentation approach based on graph cuts is presented that uses both the appearance and eye geometry information. A texture measure based on gradients is computed to discriminate between eyelash and non-eyelash regions, combined with image intensity differences between the iris, pupil, and the background (region surrounding the iris) are utilized as cues for segmentation. The texture and intensity distributions for the various regions are learned from histogramming and explicit sampling of the pixels estimated to belong to the corresponding regions. The image is modeled as a Markov Random Field and the energy minimization is achieved via graph cuts to assign each image pixel one of the four possible labels: iris, pupil, background, and eyelash. Furthermore, the iris region is modeled as an ellipse, and the best fitting ellipse to the initial pixel based iris segmentation is computed to further refine the segmented region. As a result, the iris region mask and the parameterized iris shape form the outputs of the proposed approach that allow subsequent iris recognition steps to be performed for the segmented irises. The algorithm is unsupervised and can deal with non-ideality in the iris images due to out-of-plane rotation of the eye, iris occlusion by the eyelids and the eyelashes, multi-modal iris grayscale intensity distribution, and various illumination effects. The proposed segmentation approach is tested on several publicly available non-ideal near infra red (NIR) iris image databases. We compare both the segmentation error and the resulting recognition error with several leading techniques, demonstrating significantly improved results with the proposed technique.     

Flexible amorphous‐silicon non‐volatile memory

Abstract— The development of a flexible, rewritable, non‐volatile memory (NVM) that is implemented on a standard, low‐temperature a‐Si:H process without additional mask steps is reported. This NVM is a part of a flexible‐display system. Each NVM cell is composed of differentially configured thin‐film‐transistors (TFTs). The cell reads out one of two stable states depending on the relative threshold voltages of the differentially configured TFTs. Information is stored in each cell by increasing the threshold voltage of one differential TFT or the other, utilizing the well‐known electrical‐stress degradation intrinsic to a‐Si:H TFTs. The stored information is retained indefinitely with no applied power. A test array of individually addressable NVM cells has been successfully fabricated and tested on flexible stainless‐steel substrates. Read and write operation, as well as preliminary reliability measurements, are described. The design is readily scalable to large memory arrays.     

Optimal operation and tracking control of vapor-recompressed batch distillation

Vapor recompressed batch distillation (VRBD) is an energy-integrated configuration which works on the principle of a heat pump. Operation of such a column is challenging due to unsteady, nonlinear dynamics and strong interplay between separation and energy efficiency. In this paper, a two-step approach is proposed for optimal operation and control of such a column. Initially, an openloop optimal operation policy is generated for maximization of an overall performance index using offline optimization. To this end, three performance indices are proposed to capture interplay between separation and energy efficiency. Subsequently, a model-based output feedback controller is designed to track this optimal performance trajectory. The effectiveness of the proposed approach is demonstrated using a benzene-toluene separation case study wherein it is shown that the proposed approach helps to achieve optimal operation in the presence of operational disturbances.     

Real-time motion segmentation of sparse feature points at any speed.

We present a real-time incremental approach to motion segmentation operating on sparse feature points. In contrast to previous work, the algorithm allows for a variable number of image frames to affect the segmentation process, thus enabling an arbitrary number of objects traveling at different relative speeds to be detected. Feature points are detected and tracked throughout an image sequence, and the features are grouped using a spatially constrained expectation-maximization (EM) algorithm that models the interactions between neighboring features using the Markov assumption. The primary parameter used by the algorithm is the amount of evidence that must accumulate before features are grouped. A statistical goodness-of-fit test monitors the change in the motion parameters of a group over time in order to automatically update the reference frame. Experimental results on a number of challenging image sequences demonstrate the effectiveness and computational efficiency of the technique.     

Synthesis and compressive behavior of Cr2GeC up to 48 GPa

M_n+1AX_n compounds have gathered huge momentum because of its exciting properties. In this paper we report the synthesis of ternary layered ceramic Cr₂GeC, a 211 M_n+1AX_n compound by hot-pressing. Scanning electron microscopy and X-ray diffraction have been employed to characterize the new synthesized phase. High-pressure compressibility of Cr₂GeC were measured using diamond anvil cell and synchrotron radiation at room temperature up to 48 GPa. No phase transformation was observed in the experimental pressure range. The bulk modulus of Cr₂GeC calculated using the Birch–Murnaghan equation of state is 169 ± 3 GPa, with K′ = 3.05 ± 0.15.     

Ultrasmall Nanoplatforms as Calcium‐Responsive Contrast Agents for Magnetic Resonance Imaging

The preparation of ultrasmall and rigid platforms (USRPs) that are covalently coupled to macrocycle‐based, calcium‐responsive/smart contrast agents (SCAs), and the initial in vitro and in vivo validation of the resulting nanosized probes (SCA‐USRPs) by means of magnetic resonance imaging (MRI) is reported. The synthetic procedure is robust, allowing preparation of the SCA‐USRPs on a multigram scale. The resulting platforms display the desired MRI activity—i.e., longitudinal relaxivity increases almost twice at 7 T magnetic field strength upon saturation with Ca²⁺. Cell viability is probed with the MTT assay using HEK‐293 cells, which show good tolerance for lower contrast agent concentrations over longer periods of time. On intravenous administration of SCA‐USRPs in living mice, MRI studies indicate their rapid accumulation in the renal pelvis and parenchyma. Importantly, the MRI signal increases in both kidney compartments when CaCl₂ is also administrated. Laser‐induced breakdown spectroscopy experiments confirm accumulation of SCA‐USRPs in the renal cortex. To the best of our knowledge, these are the first studies which demonstrate calcium‐sensitive MRI signal changes in vivo. Continuing contrast agent and MRI protocol optimizations should lead to wider application of these responsive probes and development of superior functional methods for monitoring calcium‐dependent physiological and pathological processes in a dynamic manner.     

Biocompatible tumor micro-environment responsive CS-g-PNIPAAm co-polymeric nanoparticles for targeted Oxaliplatin delivery

The objective of the research study was to develop and characterize a biodegradable, thermo and pH dual responsive Oxaliplatin-loaded chitosan-graft-poly-N-isopropylacrylamide (CS-g-PNIPAAm) co-polymeric nanoparticles as a tumor-targeting drug delivery system. CS-g-PNIPAAm co-polymers were synthesized, characterized and optimized its thermo and pH responsive properties for tumor microenvironment conditions. Optimized co-polymer could be efficiently loaded with Oxaliplatin in nanoparticle form, evaluated for their morphology (TEM), particle size, zeta potential, loading efficiency and drug content. In vitro drug release study at tumor microenvironment and physiological pH and temperature conditions. The in vitro drug release was optimal at above lower critical solution temperature (LCST) and tumor microenvironment pH when compared to physiological pH & temperature. MTT assay and fluorescence microscopic study showed that drug release and cell uptake was significantly enhanced in tumor microenvironment. In conclusion, the obtained nanoparticles appeared to be of great promise in tumor targeted drug delivery of oxaliplatin.     

Adaptive recurrent nonnegative matrix factorization with phase compensation for Single-Channel speech enhancement

The speech signals are affected by the background noise distortion that is unfavorable to both the intelligibility as well as the speech quality. Most of the speech processing algorithms function with the spectral magnitude without consideration of the spectral phase by leaving them unexplored and unstructured. The proposed single channel speech enhancement model called the Adaptive Recurrent Nonnegative Matrix Factorization (AR-NMF) is designed based on the phase compensation strategy with deep learning. The two major phases considered here are the training phase and the testing phase. During the process of training, the noisy speech signal is decomposed by the Hurst exponent-based Empirical Mode Decomposition (HEMD) and is converted into the frequency domain using Short Time Fourier Transform. Further, the new AR-NMF is used for denoising, where the tuning factor is optimally generated by the optimized RNN. Here, the hidden neurons are optimized using the proposed Adaptive Attack Power-based Sail Fish Optimization (AAP-SFO) with consideration of minimizing the Mean Absolute Error between the actual value and the predicted value. Finally, this phase compensated speech signal is given to the ISTFT that results in the final denoised clean speech signal. From the analysis, the CSED of AAP-SFO-AR-NMF for the street noise is 58.24%, 57.34%, 56.72%, and 77.37% more than RNMF, esHRNR, esTSNR, and Vuvuzela respectively. The performance of the proposed deep enhancement method is extensively evaluated and compared to diverse adverse noisy environments that describe the superiority of the proposed method.

     

Improved Connection Establishment of Dynamic Traffic with Queue in WDM Optical Networks

Wireless Personal Communications - Proper route selection between source and destination $$(s-d)$$ connection leads to efficient resource utilization which leads to the availability of resources...