Evaluation of expanded gamut software solutions for spot color reproduction

Expanded gamut printing is an approach in color reproduction that expands the color gamut of conventional CMYK printing processes via the use of additional colorants, such as Orange, Green, and Violet inks. This study evaluates the ability of commercial color management software to create an accurate solution for an expanded gamut printing system. In this study, two printing processes were used, an Epson SureColor P9000 inkjet printer/proofer and an HP Indigo 7900 digital production press, both with 7-color expanded gamut ink sets. Software solutions from Alwan, CGS ORIS, ColorLogic, GMG Color, Heidelberg, and Kodak were evaluated. The systems were tested to see how well they could reproduce the colors in the entire PANTONE+ Solid Coated spot color library. It is shown that the solutions are able to reproduce 89% to 94% of the spot colors on the Epson P9000 inkjet printer and 77% to 87% of the library on the Indigo 7900, both to less than two CIEDE2000 (a typical tolerance in label and packaging work). The number of color patches in expanded gamut characterization test charts was noted, as this is still an area of proprietary, nonstandardized working practice. There are many different colorant combinations that can make the same color in expanded gamut printing. The ink build created by the different software solutions was studied, as it relates to press stability through appropriate choice of colorants. Pantone and Adobe provide everyday commercial tools for expanded color workflows. The study identified some issues with products from these companies that could confuse a less-skilled user in a busy production environment. The conclusion of the study is that expanded gamut solutions for spot color printing produce totally acceptable results for digital printing processes; expanded gamut printing is ready, here and now. The findings show that expanded gamut printing can replace cumbersome conventional spot color workflows creating considerable savings and advantages, especially for label and packaging printers.     

State estimation for high-dimensional chemical processes

The application of conventional observer designs for high-dimensional systems may not always be practical due to high computational requirements or the resulting observers being too sensitive to measurement noise. In order to address these issues, this paper presents two observer design techniques for state estimation of high-dimensional chemical processes. One technique is used for systems with inputs, whereas the other one is specifically geared towards systems that are not excited from the outside. Both of these observers are applicable to linear and with a modification to non-linear systems.The main idea behind the presented observer designs is that a reduced-order observer is implemented instead of a conventional state estimator. The motivation is that subspaces, which are close to being unobservable, cannot be correctly reconstructed in a realistic setting due to measurement noise and inaccuracies in the model. The presented approaches make use of this observation and only reconstruct the parts of the system where accurate state estimation is possible. The observer designs are illustrated on a 30-tray distillation column model. Additionally, it has been shown that the location of process measurements has a major effect on the performance of the presented reduced-order observers.     

Propagation of quasi-simple waves in a compressible rotating atmosphere

Summary A class of self-propagating linear and nonlinear travelling wave solutions for compressible rotating fluid is studied using both numerical and analytical techiques. It is shown that, in general, a three dimensional linear wave is not periodic. However, for some range of wave numbers depending on rotation, horizontally propagating waves are periodic. When the rotation is equal to , all horizontal waves are periodic. Here, is the ratio of specific heats. The analytical study is based on phase space analysis. It reveals that the quasi-simple waves are periodic only in some plane, even when the propagation is horizontal, in contrast to the case of non-rotating flows for which there is a single parameter family of periodic solutions provided the waves propagate horizontally. A classification of the singular points of the governing differential equations for quasi-simple waves is also appended.     

CNFET Based Ultra-Low-Power Schmitt Trigger SRAM for Internet of Things (IoT) Applications

Wireless Personal Communications - This paper presents Carbon Nanotube FET (CNFET) based ultra-low-power Schmitt trigger SRAM designs which can operate at voltage levels as low as 200 mV, with high...     

Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals

Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals; these signals can be recorded, processed and classified into different hand movements, which can be used to control other IoT devices. Classification of hand movements will be one step closer to applying these algorithms in real-life situations using EEG headsets. This paper uses different feature extraction techniques and sophisticated machine learning algorithms to classify hand movements from EEG brain signals to control prosthetic hands for amputated persons. To achieve good classification accuracy, denoising and feature extraction of EEG signals is a significant step. We saw a considerable increase in all the machine learning models when the moving average filter was applied to the raw EEG data. Feature extraction techniques like a fast fourier transform (FFT) and continuous wave transform (CWT) were used in this study; three types of features were extracted, i.e., FFT Features, CWT Coefficients and CWT scalogram images. We trained and compared different machine learning (ML) models like logistic regression, random forest, k-nearest neighbors (KNN), light gradient boosting machine (GBM) and XG boost on FFT and CWT features and deep learning (DL) models like VGG-16, DenseNet201 and ResNet50 trained on CWT scalogram images. XG Boost with FFT features gave the maximum accuracy of 88%.     

Enhancing the isolation between the strips of dipoles antenna at terahertz frequency with cuboid-shaped graphene layer

Wireless Networks - In this paper, the concept of mantle cloaking method uses to enhance the isolation between the two electrically close dipole antenna at low-terahertz (THz) frequencies, two...     

Premarin Reduces Neurodegeneration and Promotes Improvement of Function in an Animal Model of Spinal Cord Injury

Spinal cord injury (SCI) causes significant mortality and morbidity. Currently, no FDA-approved pharmacotherapy is available for treating SCI. Previously, low doses of estrogen (17β-estradiol, E2) were shown to improve the post-injury outcome in a rat SCI model. However, the range of associated side effects makes advocating its therapeutic use difficult. Therefore, this study aimed at investigating the therapeutic efficacy of Premarin (PRM) in SCI. PRM is an FDA-approved E2 (10%) formulation, which is used for hormone replacement therapy with minimal risk of serious side effects. The effects of PRM on SCI were examined by magnetic resonance imaging, immunofluorescent staining, and western blot analysis in a rat model. SCI animals treated with vehicle alone, PRM, E2 receptor antagonist (ICI), or PRM + ICI were graded in a blinded way for locomotor function by using the Basso–Beattie–Bresnahan (BBB) locomotor scale. PRM treatment for 7 days decreased post-SCI lesion volume and attenuated neuronal cell death, inflammation, and axonal damage. PRM also altered the balance of pro- and anti-apoptotic proteins in favor of cell survival and improved angiogenesis and microvascular growth. Increased expression of estrogen receptors (ERs) ERα and ERβ following PRM treatment and their inhibition by ER inhibitor indicated that the neuroprotection associated with PRM treatment might be E2-receptor mediated. The attenuation of glial activation with decreased inflammation and cell death, and increased angiogenesis by PRM led to improved functional outcome as determined by the BBB locomotor scale. These results suggest that PRM treatment has significant therapeutic implications for the improvement of post-SCI outcome.