Showing papers by "College of Engineering, Pune published in 2012"

Sliding Mode and Inertial Delay Control Based Missile Guidance

Abstract: A novel formulation of sliding mode control (SMC) based proportional navigation (PN) guidance law is presented. Unlike conventional SMC-based guidance laws, the law presented here does not need any knowledge of bounds of target acceleration. The target acceleration is estimated using the so-called inertial delay control (IDC). Closed-loop stability for the guidance loop is established. Simulations are carried out by considering highly-maneuvering targets and constant as well as varying missile velocity and the results are presented to demonstrate the effectiveness of the proposed formulation.

Flow around six in-line square cylinders

Abstract: The flow around six in-line square cylinders has been studied numerically and experimentally for and , where is the surface-to-surface distance between two cylinders, is the size of the cylinder and is the Reynolds number The effect of spacing on the flow regimes is initially studied numerically at for which a synchronous flow regime is observed for , while quasi-periodic-I, quasi-periodic-II and chaotic regimes occur between , and , respectively These regimes have been confirmed via particle-image-velocimetry-based experiments A flow regime map is proposed as a function of spacing and Reynolds number The flow is predominantly quasi-periodic-II or chaotic at higher Reynolds numbers The quasi-periodic and chaotic nature of the flow is due to the wake interference effect of the upstream cylinders which becomes more severe at higher Reynolds numbers The appearance of flow regimes is opposite to that for a row of cylinders The Strouhal number for vortex shedding is the same for all the cylinders, especially for synchronous and quasi-periodic-I flow regimes The mean drag () experienced by the cylinders is less than that for an isolated cylinder, irrespective of the spacing The first cylinder is relatively insensitive to the presence of downstream cylinders and the is almost constant at 12 The for the second and third cylinders may be negative, with the value of increasing monotonically with spacing The changes in root mean square lift coefficient are consistent with changes in Interestingly, the instantaneous lift force can be larger than the instantaneous drag force on the cylinders These results should help improve understanding of flow around multiple bluff bodies

Heart Disease Diagnosis Using Machine Learning Algorithm

Abstract: Recent advances in computing and developments in technology have facilitated the routine collection and storage of medical data that can be used to support medical decisions. However, in most countries, there is a first need for collecting and organizing patient’s data in digitized form. Then, the collected data are to be analyzed in order for a medical decision to be drawn, whether this involves diagnosis, prediction, course of treatment, or signal and image analysis. In this paper, India centric dataset is used for Heart disease diagnosis. The correct diagnosis performance of the automatic diagnosis system is estimated by using classification accuracy, sensitivity and specificity analysis. The study shows that, the SVM with Sequential Minimization Optimization learning algorithm have better choice for medical disease diagnosis application.

Automated region-based hybrid compression for digital imaging and communications in medicine magnetic resonance imaging images for telemedicine applications

Abstract: Many classes of images contains spatial regions which are more important than other regions. Compression methods which are capable of delivering higher reconstruction quality are attractive in this situation for the important parts. For the medical images, only a small portion of the image might be diagnostically useful, but the cost of a wrong interpretation is high. Hence, Region Based Coding (RBC) technique is significant for medical image compression and transmission. Lossless compression in these `regions` and lossy compression for rest of image can helps to achieve high efficiency and performance in telemedicine applications. This paper proposes an automated, efficient and low complexity, lossless, scalable RBC for Digital Imaging and Communications in Medicine (DICOM) images. The advantages of RBC are exploited in this paper, segmenting the region into various regions of importance and subjecting varying bit-rates for optimal performance. Moreover, the combined effects of Integer Wavelet Transform (IWT) and bit-rate limiting compression technique for lesser important regions helps reconstruct the image, reversibly, up to a desired quality. The overall compression thus reaches a satisfactory level to be able to safely transmit the image in limited bandwidth over a telemedicine network and reconstruct diagnostic details for treatment, most faithfully.

An energy efficient and reliable internet of things

Abstract: Internet of Things (IoT) is innovation in the field of Communication where a number of intelligent devices are involved sharing information and making collaborative decision. IOT is going to be a market-changing force for a wide variety of real-time monitoring applications, such as E-healthcare, homes automation system, environmental monitoring and industrial automation as it is supporting to a large number of characteristics and achieving better cost efficiency. This article explores the emerging IoT in terms of the potential Energy Efficiency Reliability (EER) issues. This paper discusses the potential EER barriers with examples and suggests remedies and techniques which are helpful in propelling the development and deployment of IoT applications.

Feature Extraction and Texture Classification in MRI

Abstract: Automated MRI (Magnetic resonance Imaging) brain tumor segmentation is a difficult task due to the variance and complexity of tumors. In this paper, a statistical structure analysis based tumor segmentation scheme is presented, which focuses on the structural analysis on both tumorous and normal tissues. The basic concept is that local textures in the images can reveal the typical 'regularities' of biological structures. Thus, textural features have been extracted using co-occurrence matrix approach. By the analysis of level of correlation we can reduce the number of features to the only significant component .An artificial neural network and fuzzy c-means are used for classification. This approach is designed to investigate the differences of texture features among macroscopic lesion white matter (LWM), normal appearing white matter (NAWM) in magnetic resonance images (MRI) from patients with tumor and normal white matter (NWM).

Modelling maintenance and repair costs using stochastic point processes for life cycle costing of repairable systems

Abstract: The objective of this article is to present a methodology based on reliability and maintainability (R & M) parameters for effective implementation of life cycle costing in design and procurement of repairable systems. For this purpose, a number of life cycle cost models developed over the years have been reviewed, the important life cycle stages for repairable systems are identified and a generalised model for life cycle cost analysis is first proposed. The mathematical equations have been formulated for the life cycle stages, such as acquisition, installation and commissioning, operation, maintenance and repair and disposal. The focus is mainly on modelling the maintenance and repair costs, which are the major elements of repairable system life cycle cost. To model maintenance and repair costs, the stochastic point process approach is employed. The lifetime of repairable system is modelled using a two parameter Weibull distribution. The expected number of failures are estimated based on the assumption th...

Cloud storage architecture

Abstract: Designing storage architectures for emerging data-intensive applications presents several challenges and opportunities. Tackling these problems requires a combination of architectural optimizations to the storage devices and layers of the memory/storage hierarchy as well as hardware/software techniques to manage the flow of data between the cores and storage. As we move deeper into an era in which data is a first-class citizen in architecture design, optimizing the storage architecture will become more important. Cloud Storage Architecture is major topic in now a day because the data usage and the storage capacity are increased double year by year. So that some of the major companies are mainly concentrated on demand storage option like cloud storage. The existing cloud storage providers are mainly concentrated on performance, cost issues and multiple storage options.

Sliding mode control of active suspension systems using a disturbance observer

Abstract: In this paper a novel active suspension scheme that combines sliding mode control with a disturbance observer is proposed for a quarter car model. The disturbance observer estimates the uncertainties in the system and the unknown road disturbance acting on the unsprung mass. Two control strategies to compensate for the uncertainties and the road disturbance in order to improve the ride comfort are proposed. The stability of the suspension system and the disturbance observer is proved. The efficacy of the method is illustrated by simulation for a vehicle suspension system.

CFD Analysis for Heat Transfer Enhancement inside a Circular Tube with Half-Length Upstream and Half-Length Downstream Twisted Tape

Abstract: CFD investigation was carried out to study the heat transfer enhancement characteristics of air flow inside a circular tube with a partially decaying and partly swirl flow. Four combinations of tube with twisted-tape inserts, the half-length upstream twisted-tape condition (HLUTT), the half-length downstream twisted-tape condition (HLDTT), the full-length twisted tape (FLTT), and the plain tube (PT) with three different twist parameters (, 0.27, and 0.38) have been investigated. 3D numerical simulation was performed for an analysis of heat transfer enhancement and fluid flow for turbulent regime. The results of CFD investigations of heat transfer and friction characteristics are presented for the FLTT, HLUTT, and the HLDTT in comparison with the PT case.

Failure Prevention of Hydraulic System Based on Oil Contamination

Abstract: Oil contamination is the major source of failure and wear of hydraulic system components. As per literature survey, approximately 70 % of hydraulic system failures are caused by oil contamination. Hence, to operate the hydraulic system reliably, the hydraulic oil should be of perfect condition. This requires a proper ‘Contamination Management System’ which involves monitoring of various parameters like oil viscosity, oil temperature, contamination level etc. A study has been carried out on vehicle mounted hydraulically operated system used for articulation of heavy article, after making the platform levelled with outrigger cylinders. It is observed that by proper monitoring of contamination level, there is considerably increase in reliability, economy in operation and long service life. This also prevents the frequent failure of hydraulic system.

Implementation and analytical modelling of modified optimised link state routing protocol for network lifetime improvement

Abstract: Self-organising ad hoc networks need development of efficient routing protocols in terms of reliable routing and energy conservation. For dense ad hoc networks, optimised link state routing (OLSR) protocol is suitable owing to its multi-point relaying (MPR) feature. The authors have tried to make OLSR energy efficient by making effective neighbour selection based on residual battery energy of a node and traffic conditions that influence the drain rate of the node in the network. The authors have considered the multipath and source routing concept for route selection and a route recovery technique to tackle mobility issue efficiently. With these modifications the protocol becomes energy efficient and at the same time achieves balancing of network load. Simulation results of OLSR and the modified protocol OLSRM, show improvement in ‘Number of nodes alive’ against variation in pause time, speed and node density. In this study, the authors have tried to model the network behaviour using R software. The work also describes analytical modelling of the protocol performance in terms of energy aware metric, ‘Number of nodes alive’ with respect to simulation time as a common frame of reference. Using analytical modelling approach the authors can predict correct network behaviour for future instances.

ANN based intelligent control of Induction Motor drive with Space Vector Modulated DTC

Abstract: This paper presents the design of Direct Torque Controlled (DTC) Induction Motor drive that incorporates Artificial Neural Network (ANN) based controller. The control algorithms are employed to improve control performance, and to reduce torque and flux ripple. A new control strategy for Space Vector Modulation based DTC (SVM_DTC) using ANN to generate control vector is proposed. The paper investigates application of ANN to Conventional DTC (C_DTC) and SVM_ DTC. Simulation studies show that the intelligent control technique is able to reduce the torque and flux ripples and to improve the performance of the drive especially at low speed. Proposed ANN_SVM_DTC is less complex, requires a single ANN controller for decoupled torque and flux control, and improves the performance.

Visualizing semantic web

Abstract: Extensive volume of information spread across the web poses a major challenge for identification of relevant information. Attaching concise meaning to this information allows for effective retrieval and usage. In this paper, we propose an interactive component that extracts pertinent information from this structured data and presents it to the user through an innovative graph mechanism, namely the spring graph. Adobe Flash builder forms the base for spring graph generation, whereas deduction of desired result from semantic data is handled by Jena framework and SPARQL query language. RDF technology is used to structure information aggregated from various web sources. The current implementation reads RDF file input and visualizes it in the form of nodes of the spring graph. The solution is validated through relevant experiments that test the efficiency and proper functionality of the system. The proposed mechanism renders better quality graphs, visual output and concrete results instead of long list of documents.

Simulation and Parametric Analysis of Cryogenic Oxygen Plant for Biomass Gasification

Abstract: Cryogenic air separation plants are used for production of oxygen, nitrogen and argon with required purity and recovery.The first grade oxygen (purity over 99.99%) is required for welding, cutting, and medical applications. These plants operate at low thermodynamic efficiency with specific power consumption in a range between 0.5-0.6 kw/scmh of O2. As air gasification produces poor quality syngas, oxygen is used as gasifying agent for biomass gasification. Medium purity cryogenic air separation units (ASU) are chiefly required for gasification. Biomass gasification with oxygen as gasifying agent has great potential in applications like integrated gasification combined cycle (IGCC), chemical production and Fischer-Tropsch (F-T) products. In this work simulation of medium purity oxygen cryogenic air separation plant integrated with biomass gasifier is carried out by using Aspen plus. Such cryogenic air separation plants which produce oxygen in a range between 85-98% can be used economically for gasification. The cryogenic oxygen plant produces oxygen with purity 96.2 % mole basis with specific power consumption as 0.2435 kw/scmh of O2. The performance parameters like recovery, purity, temperature and pressure and power consumption of cryogenic air separation unit are obtained. The parameters like syngas composition and heating value also predicted in simulation of biomass gasifier. The effect of parameters (parametric analysis), like vapour fraction of the feed on pure liquid (PL) flow and condenser duty, effect of number of stages on PL and rich liquid (RL) flow and its purity and effect of oxygen flow and gasifier temperature on syngas composition is discussed.

Analysis of Arching in Soil-Passive State

Abstract: Arching involves stress transfer from yielding part of a soil to unyielding part of soil. Many authors considered arching action for active earth pressure. In this paper arching action is considered for passive earth pressure in noncohesive backfill. The backfill is assumed to move upward in a form of catenary arch due to arching. The value of θw (the angle of major principal plane) is calculated for soil-wall friction angle and soil friction angle. An expression for passive lateral stress ratio has been derived considering these angles. An illustrative example has been solved to show the effect on earth pressure distribution on retaining wall considering arching for different wall friction angles and soil friction angles. The applicability of proposed formulation is compared with model test results.

Synthesis of bis(indolyl)methanes using molten N-butylpyridinium bromide

Abstract: A simple and rapid protocol has been developed for the synthesis of bis (indolyl)methane compounds in excellent yields using molten N -butyl-pyridinium bromide as a solvent and a working catalyst for the reaction. Synthesis of bis (indolyl)methane compounds were accomplished at moderate experimental conditions of temperature and ambient pressure, also involving an electrophilic substitution reaction of indoles with several aromatic aldehydes. The derivatives were confirmed with mass and other usual spectroscopic techniques. A discussion on plausible mechanism for the reaction is also presented.

Validation of Capacitance and Equivalent Series Resistance Model of Manganese Oxide-based Aqueous Super-capacitor

Abstract: Electrical energy storage is a critical parameter in many advanced electric vehicles. Conventional batteries provide limited solution in this regard. Development of a battery compatible super-capacitor can give a good hybrid energy storage system consisting of a battery and super-capacitor. An aqueous metal oxide super-capacitor is voltage compatible with a conventional battery. Advances are required in improving both the energy and power density of this super-capacitor through a new electrode, electrolyte materials, and issues related to the construction of the device. Modeling with electrical parameters as an output and electrode/ electrolyte parameters as an input can be very effective in developing a low-cost super-capacitor. Electrode construction and material play important roles in its performance; these two aspects have been addressed in this article through a modeling approach to convert a manganese oxide-based aqueous super-capacitor into a cost-effective product. New super-capacitor st...

Relativistic ultrafast rendering using time-of-flight imaging

Abstract: We capture ultrafast movies of light in motion and synthesize physically valid visualizations. The effective exposure time for each frame is under two picoseconds (ps). Capturing a 2D video with this time resolution is highly challenging, given the low signal-to-noise ratio (SNR) associated with ultrafast exposures, as well as the absence of 2D cameras that operate at this time scale. We re-purpose modern imaging hardware to record an average of ultrafast repeatable events that are synchronized to a streak tube, and we introduce reconstruction methods to visualize propagation of light pulses through macroscopic scenes.

TIO2/Nanoclay nanocomposite for phenol degradation in sonophotocatalytic reactor

Abstract: A TiO2–nanoclay nanocomposite was used as a photocatalyst for the degradation of phenol in presence of acoustic cavitation. TiO2–nanoclay nanocomposite was synthesised in benzyl alcohol medium wherein TiO2 nanoparticles were formed between the nanoclay platelets. The synthesised product was characterised by using FTIR, XRD and TEM techniques. TEM image shows that TiO2–nanoclay nanocomposite particles were in the range of 30–40 nm. XRD gram confirms the formation of nanocomposite of TiO2 nanoclay. The effect of cavitation and TiO2–nanoclay nanocomposite photocatalyst on phenol removal was investigated. The effects of various parameters such as nanocomposite loading, initial concentration, etc., have been studied. On comparing the results obtained with that of nanocomposite without UV, it was found for an initial concentration of 500 mg/L of phenol, the TiO2–nanoclay nanocomposite exhibited higher percentage of pollutant removal (59%) and for nanoclay it was 47%. © 2011 Canadian Society for Chemical Engineering

Segmentation using region growing algorithm based on CLAHE for medical images

Abstract: As medical images are mostly fuzzy in nature, segmentation of intensity based image is the most challenging task. A novel region growing segmentation algorithm for the image segmentation to detect tumor is presented where selective median filter is used for pre-processing. For enhancement Contrast Limited Adaptive Histogram Equalization (CLAHE) method is used. It is found that in the images processed with CLAHE, lesions appear obvious to the background and the image detail is very good. It is useful for radiologists to see subtle edge information, such as speculation. Next Scale Invariant Feature transform is used to automatically find growing seeds and the seeded region growing rule for the development of regions is able to detect both strong and weak edges, which is more suitable compared to other methods.

Output feedback control of flexible link manipulator using sliding modes

Abstract: Control of flexible link manipulators poses a challenge due to flexible modes This paper presents output feedback control for positioning a tip of flexible link manipulator(FLM) using sliding modes Sliding mode observer(SMO) is designed for estimation of system states Output estimation error becomes zero in finite time due to sliding modes The SMC with SMO is designed for positioning a tip of FLM The method is validated in simulation and experiment both

Evaluation of the Permeability Behaviour of Sand-Bentonite Mixtures Through Laboratory Tests

Abstract: In recent years, when suitable impervious soils are not available for containing the waste, barriers constructed using sand-bentonite mixtures are being frequently adopted to contain the waste. This paper presents the laboratory evaluation of permeability of sand-bentonite mixtures through falling head tests performed with rigid wall permeameter and oedometer on different categories of sand-bentonite mixtures. Five different categories of sand-bentonite mixtures were formulated by varying bentonite content in increments of 5 % from 5 to 25 % by dry weight. Atterberg limits and compaction characteristics of sand-bentonite mixtures were evaluated. With an increase in bentonite content, the unconfined compressive strength of the sand-bentonite mixture was found to increase linearly and a sharp decrease in permeability was registered up to a bentonite content of 15 % and beyond this the decrease in the permeability was marginal. Permeability tests were carried out with and without prior saturation of the samples. It was found that permeability behavior of sand-bentonite mixtures was affected by the initial saturation process and type of permeability testing method.

Decision support system for dispute resolution in construction contracts

Abstract: The construction industry has been characterized by an adversarial operating environment that generates disputes and claims due to the infinite complexities of delivering a building or infrastructure project, the multiplicity of organizations and individuals involved, and the magnitude of the funds at risk. Disputes typically start with the difference of opinion regarding claims, which can escalate to conflicts that require some form of legal action. This paper highlights the need of scientific framework for understanding and administratively resolving disputes over contract clauses. Decision Support System is one such tool. An attempt has been made to develop one such system for disputes arising out of variation and deviations clause in Indian construction contracts.

Mood classification of Indian popular music

Abstract: Music has been an inherent part of human life when it comes to recreation; entertainment and much recently, even as a therapeutic medium. Music is closely related to human emotions. We often choose to listen to a song or music which best fits our mood at that instant. The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques contributing considerably to analyze and identify the relation of mood with music. We take the same inspiration forward and contribute by making an effort to build a system for automatic identification of mood underlying the audio songs by mining their spectral, temporal audio features. Our current work involves analysis of various classification algorithms in order to learn, train and test the model representing the moods of the audio songs. The focus is on the Indian popular music. The classification model was experimented using a set of 2300 distinct music clips. We have been successful to achieve a satisfactory precision of 70% to 75% in identifying the mood underlying the Indian popular music by introducing the bagging (ensemble) of random forest approach experimented over a total list of 2300 audio clips. We also propose the framework for including lyrics analysis along with audio feature analysis in order to strengthen the accuracy of predicting the mood of an audio file, implementation of which is still under experimentation.

Role of features and classifiers on accuracy of identification of musical instruments

Abstract: Selection of effective feature set and proper classifier is a challenging task in problems where machine learning techniques are used. In automatic identification of musical instruments also it is very crucial to find the right set of features and accurate classifier. In this paper, we have discussed the role of various features with different classifiers on automatic identification of musical instruments. Piano, flute, trumpet, guitar, xylophone and violin are identified using various features and classifiers. Spectral features like spectral centroid, spectral slope, spectral spread, spectral kurtosis, spectral skewness and spectral roll-off are used along with zero crossing rate, autocorrelation and Mel Frequency Cepstral Coefficients (MFCC) for this purpose. The dependence of instrument identification accuracy on these features is studied for different classifiers. Decision trees, Naive Bayes classifier, k nearest neighbour classifier, multilayer perceptron, Sequential Minimal Optimization Algorithm (SMO) and multi class classifier (metaclassifier) are used. We have obtained improved accuracy by proper selection of these features and classifier. The analysis also confirms the selection of features and classifiers as the results are better.

Performance analysis of shunt active power filter using sliding mode control strategies

Abstract: This paper presents a three-phase four-wire shunt active power filter design using two different control strategies. The control techniques analyzed and compared are: sliding mode control (SMC) and proportional-integral control (PI). Current harmonic compensation is achieved by implementation of a Instantaneous Reactive Power Theory for three phase system. The simulation results with and without the shunt active power filter in the system are presented and analyzed. The simulation results show that the SMC controller has a better performance than PI, allowing compensation of reactive power, neutral current, load unbalance and reducing the harmonic level below the limit specified in IEEE-519 standard

Congestion control in Wireless Sensor Networks by using Differed Reporting Rate

Abstract: In Wireless Sensor Networks (WSNs), there are one or more sinks or base stations and many sensor nodes distributed over wide area. Sensor nodes have restricted power. When a particular event is occurred, these sensor nodes can transmit large volume of data towards the sink. It can result in buffer overflow at the nodes. It causes packet drops and also network throughput decreases. In WSNs, congestion may lead to energy waste due to a large number of retransmissions and packet drops. Hence it shortens the lifetime of sensor nodes. So, congestion in WSNs needs to be controlled to decrease the waste of energy and also to increase the lifetime of sensor nodes. Proposed congestion control mechanisms will improve network throughput, packet delivery ratio and packet loss. Many network aspects such as reporting rate, node density, packet size etc. can affect congestion. Congestion can be controlled by using Differed Reporting Rate (DRR) algorithm.