Photonic Side-Channel Analysis of Arbiter PUFs

As intended by its name, physically unclonable functions (PUFs) are considered as an ultimate solution to deal with insecure storage, hardware counterfeiting, and many other security problems. However, many different successful attacks have already revealed vulnerabilities of certain digital intrinsic PUFs. This paper demonstrates that legacy arbiter PUF and its popular extended versions (i.e., feed-forward and XOR-enhanced) can be completely and linearly characterized by means of photonic emission analysis. Our experimental setup is capable of measuring every PUF internal delay with a resolution of 6 ps. Due to this resolution, we indeed require only the theoretical minimum number of linear independent equations (i.e., physical measurements) to directly solve the underlying inhomogeneous linear system. Moreover, it is not required to know the actual PUF responses for our physical delay extraction. We present our practical results for an arbiter PUF implementation on a complex programmable logic device manufactured with a 180 nm process. Finally, we give an insight into photonic emission analysis of arbiter PUF on smaller chip architectures by performing experiments on a field programmable gate array manufactured with a 60 nm process.     

Phase Behavior and Micro-Structure of Fat–Oil Mixtures: Engineering the Shape of Fat Clusters

The mechanical properties of fat–oil mixtures are dictated by the morphology of the fat crystal network, which in turn is strongly affected by the processing conditions. In this work the effect of uniform (linear) cooling rates on the size and shape of tribehenin (fat) clusters in isopropyl myristate (oil) was studied. The state of the fat–oil mixtures was comprehensively analyzed by establishing pseudo‐phase diagrams via visual observations, brightfield and polarization microscopy at various cooling rates and fat concentrations. The microstructure of the constituent fat clusters undergo a shape transition from bundles of needles at low cooling rates to spherical clusters at high cooling rates. The network structures formed with these different shaped fat clusters were examined using rheology. At a given cooling rate, the storage modulus (G?) of fat–oil mixtures versus fat concentration followed a power law relationship. For a given fat concentration, the fat crystal networks comprising of bundles of needles showed higher G? values as compared to fat networks made of spherical clusters. While the fractal dimension of networks cooled at different cooling rates varied over a small range of 2.78–2.86, considerable change in the pre‐exponential factor (γ) was observed. The results show the critical importance of processing conditions on the shape and size of fat clusters and its impact on the rheological properties of the fat crystal network.     

Signal and noise transfer in spatiotemporal quantum-based imaging systems

Fourier-based transfer theory is extended into the temporal domain to describe both spatial and temporal noise processes in quantum-based medical imaging systems. Lag is represented as a temporal scatter in which the release of image quanta is delayed according to a probability density function. Expressions describing transfer of the spatiotemporal Wiener noise power spectrum through quantum gain and scatter processes are derived. Lag introduces noise correlations in the temporal domain in proportion to the correlated noise component only. The effect of lag is therefore dependent on both spatial and temporal physical processes. A simple model of a fluoroscopic system shows that image noise is reduced by a factor that is similar to Wagner's information bandwidth integral, which depends on the temporal modulation transfer function.     

Dynamic tank in series modeling of direct internal reforming SOFC

A dynamic tank in series reactor model of a direct internally reforming solid oxide fuel cell is presented and validated using experimental data as well as a computational fluid dynamics (CFD) model for the spatial profiles. The effect of the flow distribution pattern at the inlet manifold on the cell performance is studied with this model. The tank in series reactor model provides a reasonable understanding of the spatio‐temporal distribution of the key parameters at a much lesser computational cost when compared to CFD methods. The predicted V–I curves agree well with the experimental data at different inlet flows and temperatures, with a difference of less than ±1.5%. In addition, comparison of the steady‐state results with two‐dimensional contours from a CFD model demonstrates the success of the adopted approach of adjusting the flow distribution pattern at the inlet boundaries of different continuous stirred tank reactor compartments. The spatial variation of the temperature of the PEN structure is captured along with the distributions of the current density and the anode activation over‐potential that strongly related to the temperature as well as the species molar fractions. It is found that, under the influence of the flow distribution pattern and reaction rates, the dynamic responses to step changes in voltage (from 0.819 to 0.84 V), fuel flow (15%) and temperature changes (30 °C), on anode side and on cathode side, highly depend on the spatial locations in the cell. In general, the inlet points attain steady state rapidly compared to other regions. Copyright © 2017 John Wiley & Sons, Ltd.     

A TinyOS-enabled MICA2-based wireless neural interface

Existing approaches used to develop compact low-power multichannel wireless neural recording systems range from creating custom-integrated circuits to assembling commercial-off-the-shelf (COTS) PC-based components. Custom-integrated-circuit designs yield extremely compact and low-power devices at the expense of high development and upgrade costs and turn-around times, while assembling COTS-PC-technology yields high performance at the expense of large system size and increased power consumption. To achieve a balance between implementing an ultra-compact custom-fabricated neural transceiver and assembling COTS-PC-technology, an overlay of a neural interface upon the TinyOS-based MICA2 platform is described. The system amplifies, digitally encodes, and transmits neural signals real-time at a rate of 9.6 kbps, while consuming less than 66 mW of power. The neural signals are received and forwarded to a client PC over a serial connection. This data rate can be divided for recording on up to 6 channels, with a resolution of 8 bits/sample. This work demonstrates the strengths and limitations of the TinyOS-based sensor technology as a foundation for chronic remote biological monitoring applications and, thus, provides an opportunity to create a system that can leverage from the frequent networking and communications advancements being made by the global TinyOS-development community.     

Recent advances in γ‐aminobutyric acid (GABA) properties in pulses: an overview

Beans, peas, and lentils are all types of pulses that are extensively used as foods around the world due to their beneficial effects on human health including their low glycaemic index, cholesterol lowering effects, ability to decrease the risk of heart diseases and their protective effects against some cancers. These health benefits are a result of their components such as bioactive proteins, dietary fibre, slowly digested starches, minerals and vitamins, and bioactive compounds. Among these bioactive compounds, γ‐aminobutyric acid (GABA), a non‐proteinogenic amino acid with numerous reported health benefits (e.g. anti‐diabetic and hypotensive effects, depression and anxiety reduction) is of particular interest. GABA is primarily synthesised in plant tissues by the decarboxylation of l ‐glutamic acid in the presence of glutamate decarboxylase (GAD). It is widely reported that during various processes including enzymatic treatment, gaseous treatment (e.g. with carbon dioxide), and fermentation (with lactic acid bacteria), GABA content increases in the plant matrix. The objective of this review paper is to highlight the current state of knowledge on the occurrence of GABA in pulses with special focus on mechanisms by which GABA levels are increased and the analytical extraction and estimation methods for this bioactive phytochemical. © 2017 Society of Chemical Industry     

Quantification of Mildew Damage in Soft Red Winter Wheat Based on Spectral Characteristics of Bulk Samples: A Comparison of Visible-Near-Infrared Imaging and Near-Infrared Spectroscopy

Mildew growth on wheat kernels reduces grain quality due to gray discoloration of kernels that has negative impact on the resulting flour color. Higher levels of mildew damage equate to lower levels of quality. In this study, grain spectra in the 400–1,000 (visible-shortwave-near-infrared) and 1,000–2,500-nm (near-infrared) wavelength ranges were investigated for their ability to quantify mildew damage in Soft Red Winter (SRW) wheat grown in eastern Canada. For each wavelength range, partial least squares (PLS) regression models were developed for various commonly used data pre-treatments. Spectra in the 400–1,000-nm region with a mean-centering pre-treatment were optimal for quantification of mildew damage in SRW wheat. A PLS model using this approach predicted mildew damage in an independent test sample set accurately achieving a root-mean-squared-error of 0.69 and ratio-performance-deviation of 3.84 with the classification accuracy of 96 % for predictions within ±1 level against the trained inspectors’ visual assessment of mildew damage scored on a nine-level scale.     

Analog to digital converter for high density neural signal recording front-end in 90 nm

High-fidelity recording of neural signals requires varying levels of signal gain to capture low-amplitude single-unit activity in the presence of high-amplitude population activity. A floating-point approach has been used to widen the dynamic range of analog-to-digital converters (ADC) designed for this application. In this paper we present an ADC, designed for multi-channel, portable neural signal recording systems. To achieve low power consumption, small die area and wide dynamic range, an ADC based on a time-based algorithm, combined with a floating-point pipelined structure has been designed and simulated. A conventional variable-gain amplifier (VGA) stage has been eliminated in favor of a reference-current in a time-based ADC architecture. The 12-b pipelined time-based floating-point ADC has been designed with a 7-b mantissa and an exponent that provides an additional 5 bits of dynamic range. The mantissa is determined by a uniform 7-b pipelined time-based analog to digital converter. The ADC chip was designed and simulated in a 90 nm CMOS process, which occupies an active area of 360 μm × 550 μm, and consumes 7.8 μW at 1.2 V in full-scale conversion.     

Computer Vision System (CVS) for In-Line Monitoring of Visual Texture Kinetics During Shrimp (Penaeus Spp.) Drying

In this study, the effects of drying medium temperature and velocity were surveyed on the image texture features of shrimp (Penaeus spp.) batches in a dryer equipped with a perpendicular dual-view computer vision system (CVS). This was carried out by applying an innovative rotation- and scale-invariant image texture processing approach with the capability of eliminating the effects of sample shrinkage on the visual textural features. Moreover, the variations in image texture parameters were investigated with moisture ratio, color, and geometrical characteristics of the shrimp samples. Drying experiments were conducted at hot air drying (HAD) temperatures of 50–90°C and superheated steam drying (SSD) temperatures of 110–120°C with drying medium velocities of 1–2 m/s. Several configurations of a multilayer perceptron artificial neural network (MLP-ANN) were also used to predict the moisture ratio and the geometrical characteristics of the shrimp batch using the image texture parameters. Generally, the image texture features were significantly affected by drying medium temperatures (p < 0.01), and the effects of drying medium velocities on the textural properties were nonsignificant (p > 0.05). Additionally, the higher drying temperatures generated products with uniform and regular texture patterns. The SSD produced samples with somewhat nonuniform and irregular texture patterns compared with HAD at 90°C. Finally, selected MLP-ANN topologies successfully predicted the moisture ratio and the geometrical characteristics of the shrimp batch using the textural properties with correlation coefficients higher than 0.99.