Realisation of 2D analogue filters

A modified method is presented for the realisation of 2D analogue filters used for processing television images. The proposed procedure reduces the required number of integrators considerably. For Example, for the second- and third-order cases, the reduction in the number of integrators would be seven and 21, respectively.<>     

Simplified odd-even sort using multiple shift-register loops

By using anN-loop shift-register structure called a uniform ladder,N records can be sorted by a simplified adaptation of the odd-even transposition-sort algorithm to finish in (N + 1)/2 loop times (periods) using (N – 1) comparators. The sorting can be overlapped with input/output; the percentage of unoverlapped sorting times is less than 20% of the total time with a single ladder, less than 6% using two ladders, and is zero with a sufficient number of ladders.Presented at the Second International Magnetic Bubble Conference, Eindhoven, The Netherlands, August 1976.     

THE SCOPE OF DIMENSIONAL ANALYSIS IN QUALITATIVE REASONING

Dimensional analysis, traditionally used in physics and engineering to identify quantitative relationships, has recently been applied to qualitative reasoning of physical systems. We illustrate some problems of this approach. In the light of this, we reexamine the fundamentals of dimensional analysis in order to more precisely characterize its scope and limitations as a tool in qualitative reasoning. We also explore its relationship to state equation representations of physical systems. In particular, we describe its value in providing a set of constraints to reduce the ambiguity that bedevils qualitative reasoning schemes. We argue that dimensional analysis should not be seen as a substitute for knowledge about the physics but rather a supplement to other sources of knowledge.     

Fusing cluster-centric feature similarities for face recognition in video sequences

The emergence of video has presented new challenges to the problem of face recognition. Most of the existing methods are focused towards the use of either representative exemplars or image sets to summarize videos. There is little work as to how they can be combined effectively to harness their individual strengths. In this paper, we investigate a new dual-feature approach to face recognition in video sequences that unifies feature similarities derived within local appearance-based clusters. Relevant similarity matching involving exemplar points and cluster subspaces are comprehensively modeled within a Bayesian maximum-a posteriori (MAP) classification framework. An extensive performance evaluation of the proposed method on three face video datasets have demonstrated promising results.     

Effect of blockage on heat transfer from a cylinder to power law liquids

The influence of planar confining walls on the steady forced convection heat transfer from a cylinder to power-law fluids has been investigated numerically by solving the field equations using FLUENT (version 6.2). Extensive results highlighting the effects of the Reynolds number (1?Re?40), power-law index (0.2?n?1.8), Prandtl number (1?Pr?100) and the blockage ratio (β=4 and 1.6) on the average Nusselt number have been presented. For a fixed value of the blockage ratio, the heat transfer is enhanced with the increasing degree of shear-thinning behaviour of the fluid, while an opposite trend was observed in shear-thickening fluids. Due to the modifications of the flow and temperature fields close to the cylinder, the closely placed walls (i.e., decreasing value of the blockage ratio) further enhance the rate of heat transfer as the fluid behaviour changes from Newtonian to shear-thickening fluids (n>1), the opposite influence is seen with the decreasing value of the flow behaviour index (n) in shear-thinning (n<1) fluids. Finally, the functional dependence of the present numerical results on the relevant dimensionless parameters has been presented in the form of closure relationships for their easy use in a new application.     

Cyclomatrix poly(organo phosphazenes)—some aspects of synthesis,characterization and adhesive heat resistance

Structure-property relationships of a phosphazene-modified epoxy-based cyclomatrix system were studied using aromatic diamine condensates of hexachlorocyclotriphosphazene (PNCl₂)₃ and a diglycidyl ether of bisphenol-A. Synthesis and characterization of the condensates and difficulties associated with these aspects are described. Adhesive heat resistance and thermal stability are reported as functions of the “active hydrogen” content of the condensates, molar ratios of the epoxy and “active hydrogen,” and amine structures. Modification of the ? OH groups formed in the amine–epoxy reaction via cyanoethylation and transesterification was not effective in improving high-temperature adhesion. The polymer systems were stable up to 380°C in air, exhibited higher char contents at elevated temperatures, and were optically clearer when compared with the corresponding nonphosphazene systems. Presence of phosphazene rings was also helpful in lowering the cure time and temperature.     

Drag on a single fluid sphere translating in power-law liquids at moderate Reynolds numbers

A numerical investigation has been carried out to obtain the steady state drag coefficients and flow patterns of a single Newtonian fluid sphere sedimenting in power-law liquids. A finite difference method based simplified marker and cell (SMAC) algorithm has been implemented on a staggered grid arrangement to solve the continuity and momentum equations. For both phases, the convective terms have been discretized using the quadratic upstream interpolation for convective kinematics (QUICK) scheme, and diffusive and non-Newtonian terms with central differencing scheme. An exponential transformation has been applied in the radial direction for the continuous phase computational domain. In order to ensure the accuracy of the solver, extensive validation has been carried out by comparing the present results with the existing literature values for a few limiting cases. Further, in this study the effects of the Reynolds number (Re_o), internal to external fluid characteristic viscosity ratio (k) and power-law index (n_o) on the continuous phase flow field, pressure drag (C_dp), friction drag (C_df) and total drag (C_D) coefficients have been analyzed over the range of parameters: 5?Re_o?500, 0.1?k?50 and 0.6?n_o?1.6. Based on numerical results obtained in this work, a simple correlation has been proposed for the total drag coefficient, which can be used to predict the rate of sedimentation of a fluid sphere in power-law liquids.     

Applied techniques for residual oil recovery from source rocks: A review of current challenges and possible developments

Depleted fossil fuel resources have led to an investigation of other promising alternatives such as renewable and unconventional energy sources. Shale formations have limited permeability. Therefore, several extraction techniques have been applied to improve residual oil recovery and production. In this work, the techniques applied above ground to extract the organic fractions from oil/gas shale are discussed. Studies related to compositional fractionation, ultrasonic‐assisted, microwave‐assisted, supercritical fluids, and surface retorting techniques have been conducted systematically in approximately 150 scholarly articles over the past 10 years. The impacts of each technique as well as the drawbacks and challenges are highlighted in this paper. The fractionation techniques are sufficient in general; however, they are time consuming as they include several stages and use a considerable amount of solvents. Ultrasonic and microwave techniques are highly reliant on formation transparency linked to the organic fraction heterogeneous distribution. The surface retorting method, which is highly efficient with up to 90% recovery, for example, the Galoter and Paraho methods, is still dependent on shale particulate size, generates a massive amount of spent shale as waste, and is prominently emissive. Therefore, assessments that can be used to overcome existing drawbacks are considered. This can provide practical insight about these techniques to overcome limitations and concerns in terms of efficiency, cost, environmental issues, and reliability features. The work highlights the dominant extraction techniques for further development.     

An IoT-Cloud Based Intelligent Computer-Aided Diagnosis of Diabetic Retinopathy Stage Classification Using Deep Learning Approach

Diabetic retinopathy (DR) is a disease with an increasing prevalence and the major reason for blindness among working-age population. The possibility of severe vision loss can be extensively reduced by timely diagnosis and treatment. An automated screening for DR has been identified as an effective method for early DR detection, which can decrease the workload associated to manual grading as well as save diagnosis costs and time. Several studies have been carried out to develop automated detection and classification models for DR. This paper presents a new IoT and cloud-based deep learning for healthcare diagnosis of Diabetic Retinopathy (DR). The proposed model incorporates different processes namely data collection, preprocessing, segmentation, feature extraction and classification. At first, the IoT-based data collection process takes place where the patient wears a head mounted camera to capture the retinal fundus image and send to cloud server. Then, the contrast level of the input DR image gets increased in the preprocessing stage using Contrast Limited Adaptive Histogram Equalization (CLAHE) model. Next, the preprocessed image is segmented using Adaptive Spatial Kernel distance measure-based Fuzzy C-Means clustering (ASKFCM) model. Afterwards, deep Convolution Neural Network (CNN) based Inception v4 model is applied as a feature extractor and the resulting feature vectors undergo classification in line with the Gaussian Naive Bayes (GNB) model. The proposed model was tested using a benchmark DR MESSIDOR image dataset and the obtained results showcased superior performance of the proposed model over other such models compared in the study.     

Modeling analysis and fabrication of MEMS capacitive differential pressure sensor for altimeter application

This paper proposes the modeling analysis of MEMS highly sensitive Capacitive Differential Pressure Sensor (CDPS) and also the development of a fabrication process for CDPS structures for aircraft altimeter applications. Highly sensitive CDPS structure models using circular and square sandwich polyimide diaphragm membranes, with and without center boss, were adopted, whereas other studies report on silicon diaphragms. CDPS characterization was carried out to analyze the deflection sensitivity, capacitive sensitivity, stress on diaphragm membrane and the effect of temperature on capacitive sensitivity. Simulation results of square diaphragm without center boss show better characteristics than other proposed diaphragm structures. This design yields 145.8 nm/mbar and 0.574 fF/mbar of deflection and capacitive sensitivity, respectively. The maximum stress developed on the diaphragm at maximum working pressure is less than the yield stress of polyimide material by a factor of 1.77 and capacitive sensitivity deviates at ±0.00195%/°C. From the modeling analysis, square diaphragm CDPS structure yields better characteristics and hence the fabrication process for CDPS has been developed, and its fabrication process flow verified using Intellisuit virtual fab tool.