Reconstruction of cylinder pressure for SI engine using recurrent neural network

Model predictive control (MPC) frequently uses online identification to overcome model mismatch. However, repeated online identification does not suit the real-time controller, due to its heavy computational burden. This work presents a computationally efficient constrained MPC scheme using nonlinear prediction and online linearization based on neural models for controlling air–fuel ratio of spark ignition engine to its stoichiometric value. The neural model for AFR identification has been trained offline. The model mismatch is taken care of by incorporating a PID feedback correction scheme. Quadratic programming using active set method has been applied for nonlinear optimization. The control scheme has been tested on mean value engine model simulations. It has been shown that neural predictive control with online linearization using PID feedback correction gives satisfactory performance and also adapts to the change in engine systems very quickly.     

Analysis of ENVISAT ASAR data for forest parameter retrieval and forest type classification—a case study over deciduous forests of central India

The present paper gives an account of potential of Environment Satellite‐Advanced Synthetic Aperture Radar (ENVISAT‐ASAR) C‐band data in forest parameter retrieval and forest type classification over deciduous forests of Tadoba Andhari Tiger Reserve (TATR), central India. Ground data on phyto‐sociology and Leaf Area Index (LAI) over the study area was collected in 23 sampling points (20m×20m) over the study area. Phyto‐sociological data collected over the study area was used to compute plot‐wise biometric parameters like basal area, volume, stem density and dominant height. ENVISAT ASAR data covering the study area, pertaining to 24 November 2005, has been geo‐referenced and digital number (DN) values were converted to radar backscatter values. Regression analysis between backscatter and the retrieved biometric variables has been done to explain the relationships between SAR backscatter and forest parameters. Analysis showed a significant correlation between backscatter and biometric parameters and backscatter values typically increased with increase in basal area, volume, stem density and dominant height. The scatter observed between ASAR backscatter and stem density, basal area and dominant height suggested limitation of C‐band data in estimating biometric variables in heterogeneous forest systems. Further, ASAR data was used in conjunction with Indian Remote sensing Satellite (IRS‐P6)—Linear Imaging Self Scanner (LISS) III data of 16 October 2004 to classify the study area into different land use/land cover (LU/LC) classes. Various texture and adaptive filters were applied on ASAR image to reduce speckle noise and enhance image features. An attempt is made to merge ASAR image with LISS‐III to enhance feature discrimination. Training sets corresponding to the ground data have been used to derive confusion matrices for the ASAR and LISS‐III images. Results suggested better discrimination of vegetation types in the merged data suggesting the possible use of ASAR data in forest type discrimination.     

A robust image encryption algorithm resistant to attacks using DNA and chaotic logistic maps

An image encryption technique using DNA (Deoxyribonucleic acid) operations and chaotic maps has been proposed in this paper. Firstly, the input image is DNA encoded and a mask is generated by using 1D chaotic map. This mask is added with the DNA encoded image using DNA addition. Intermediate result is DNA complemented with the help of a complement matrix produced by two 1D chaotic maps. Finally, the resultant matrix is permuted using 2D chaotic map followed by DNA decoding to get the cipher image. Proposed technique is totally invertible and it can resist known plain text attack, statistical attacks and differential attacks.     

Layout and Component Size Optimization of Sewer Network Using Spanning Tree and Modified PSO Algorithm

In the paper, a new method is introduced for optimally solve the problem of the layout and component size determination of sewer network. Simultaneously Layout and component size optimization of sewer network problem consists of many hydraulic constraints which are generally nonlinear and discrete; which creates a challenge even to the modern heuristic search methods. An algorithm generation of a predefined number of spanning trees is introduced to generate a predefined number of sewer layouts of a base sewer network in order of increasing length. These generated layouts are sorted in ascending order of total cumulative flow and sorted layouts are individually optimized for sewer components sizing. It has been found that the optimal sewer layout for total system optimization is one where the total cumulative flow has the minimal value. The modified particle swarm optimization (MPSO) algorithm has been used to optimally determine the component sizes of the selected layouts. The proposed method is applied to the Sudarshanpura sewer network (situated in Jaipur, India) design problem. The results are presented for optimal cost vs cumulative flow of the layouts. Further results of MPSO has been compared with the original PSO algorithm.     

Concentration profile of glass fiber bundles in epoxy‐based gradient composites during centrifugation

The short fiber bundles separated from the machining waste of a printed circuit board (PCB) manufacturing plant were used in preparing functionally graded composites using polysulfide‐modified epoxy resin. The graded material was developed using centrifugation technique. The centrifugation time was varied to obtain different gradient profiles. The concentration profile was then compared with the theoretical HD model (Hashmi‐Dwivedi model), which was modified to accommodate the changes in the shape of suspending particles. A shape factor was introduced in terminal velocity estimation. The simulated results are in agreement with the experimental trends. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Storage space estimation for videos using fading channels

In this paper, we propose a model for estimating the buffer storage for providing continuous delivery of the video data to users. The model incorporates the jitter delay, which is a switching delay between two consecutive video segments being transmitted through a logical channel. The jitter delay is assumed to be Rayleigh distributed as it characterizes the channel fading.     

Influence of wood flour loading on tribological behavior of epoxy composites

A series of wood flour (WF) filled epoxy composites consisting of five samples were prepared by varying the concentration of WF in step of 10 wt%. These samples were characterized for its wear behavior in abrasive and sliding wear modes to study the influence of WF. It was observed that specific wear rate (k₀) of all the composites decreased with increasing load in sliding wear mode. Specific wear rate was of the order of 10⁻¹⁰ m³/Nm in abrasive wear mode and ∼10⁻¹⁴ m³/Nm in sliding wear mode. Composite containing 40 wt% WF exhibited the lowest specific wear rate in abrasive wear mode. While composite containing 20 wt% WF exhibited lowest specific wear rate in sliding wear mode. This was attributed to the fact that in abrasive wear mode, the wear debris consisting of mainly WF particles was maximum for 10 wt% composite and minimum for 40 wt% composite. In sliding wear mode, the exposed WF particles caused maximum roughening of steel counterface in the case of composite containing higher concentration of WF particles. Hence, they exhibited a higher value of specific wear rate. POLYM. COMPOS., 2008. © 2008 Society of Plastics Engineers