Showing papers by "College of Engineering, Pune published in 2009"

Knowledge management in education

Abstract: Institutional effectiveness, synonymous with assessment of learning, but perhaps larger is having sweeping impact on education. Education today is subject to the same pressures of the marketplace to spur innovation, improve customer service, or achieve operational excellence. Modalities of delivering learning have changed from “only game in town” to “anywhere, anytime”. Knowledge management is the process of transforming information and intellectual assets into enduring value. It connects people with the knowledge that they need to take action, when they need it. There is tremendous value to educational institutions that develop initiatives to share knowledge to achieve business objectives. If done effectively, it can lead to better decision-making capabilities, reduced “product” development cycle time (for example, curriculum development and research), improved academic and administrative services, and reduced costs. The challenge is to convert the information that currently resides in the individuals of the institution widely and easily available to any faculty member, staff person, or other constituent. This paper outlines the basic concepts of knowledge management as and considers trends, and explores how it might be applied in educational institutes and whether educational institutes are ready to embrace it. All institutions inherently store, access, and deliver knowledge in some manner. It is with KM that institutions will be better able to increase student retention and graduation rates; retain a technology workforce in the face of severe employee shortages; expand new web based offerings; work to analyze the cost effective use of technology to meet more enrollment; transform existing transaction-based systems to provide information, not just data, for management; and compete in an environment where institutions cross state and national borders to meet student needs anytime/anywhere.

Intrusion Detection System using Self Organizing Maps

Abstract: With the rapid expansion of computer usage and computer network the security of the computer system has became very important. Every day new kind of attacks are being faced by industries. Many methods have been proposed for the development of intrusion detection system using artificial intelligence technique. In this paper we will have a look at an algorithm based on neural networks that are suitable for Intrusion Detection Systems (IDS) [1] [2]. The name of this algorithm is “Self Organizing Maps” (SOM). Neural networks method is a promising technique which has been used in many classification problems. The neural network component will implement the neural approach, which is based on the assumption that each user is unique and leaves a unique footprint on a computer system when using it. If a user's footprint does not match his/her reference footprint based on normal system activities, the system administrator or security officer can be alerted to a possible security breach. At the end of the paper we will figure out the advantages and disadvantages of Self Organizing Maps and explain how it is useful for building an Intrusion Detection System.

Texture Based Palmprint Identification Using DCT Features

Abstract: In the palmprint recognition application utilizing more information other than principle lines or minutiae is much helpful. In this paper we proposed Discrete Cosine Transform (DCT) based feature vector for palmprint representation and matching and compared with DFT and Wavelet transform. Here the central part of the palmprint image of size 128x128 is resized to the size of 64x64 and divided into four non overlapping sub-images. The transform is applied on each sub-image directly without any preprocessing. By dividing the transformed sub-image into nine blocks, standard deviation is calculated for each block and such in total 36 (9x4=36) standard deviations will form the feature vector. This feature vector is used in matching stage. Total 10 images per person are taken from standard database available. Training set is prepared with the help of k images where k varies from 1 to 8. Results are checked against remaining images image in identification mode. Results are represented in terms of Genuine acceptance rate(%). In identification mode 97.5% recognition rate is obtained. The work is preliminary but recognition rate is promising and without any pre-processing.

Algorithm to Break Visual CAPTCHA

Abstract: Completely Automated Public Turing Tests to Tell Computers and Humans Apart (CAPTCHAs) are the automatic filters that are widely used these days to disallow any automated script that can perform the work of a human. CAPTCHAs are built in such a way that it is very difficult for any automated script to break them. In this paper, an approach to break text based CAPTCHAs has been proposed that first preprocesses the given CAPTCHA, segments its characters, and then recognizes the characters depending on its features. The breaking of CAPTCHA gives strength of CAPTCHA which in turn helps to develop more robust CAPTCHA The testing results shows that the algorithm successfully breaks the CAPCHA. This algorithm will be also helpful to screen reader program. The results show that it is not a trivial task to design a CAPTCHA scheme that is both usable and robust.

Natural Convection Heat Transfer From Horizontal Rectangular Inverted Notched Fin Arrays

Abstract: The variables for natural convection cooling with the help of finned surfaces are orientation and geometry. In lengthwise short array (L/H ∼5), where single chimney flow pattern is present, a stagnant zone is created at the central bottom portion of fin array channel and hence it does not contribute much in heat dissipation. Hence it is removed in the form of inverted notch at the central bottom portion of fin to modify its geometry for enhancement of heat transfer. An experimental setup is developed for studying the investigation on normal and inverted notched fin arrays (INFAs). Fin spacing, heater input, and percentage of area removed in the form of inverted notch are the parameters. For few spacing, it is verified by computational fluid dynamics analysis (Course Notes on Introduction to Commercial CFD of Tridiagonal Solutions, Pune), and the results are well matching. It is found that the average heat transfer coefficient for INFAs is nearly 30― 40% higher as compared with normal array.

Selection of Wavelets for Medical Image Compression

Abstract: Medical images carry huge and vital information. It is necessary to compress the medical images without losing its vital-ness. Wavelet transform is preferable in the field of compression because of much more information of image can be retraced by it than any other transform. There are varieties of wavelets available but always there is a question in designers mind about which type of wavelet should I select for my design? Here we have focused on the selection of wavelet for compression of medical images. Various wavelets have been used for compression and we have done quality analysis on reconstructed image. Based on results we have found out the best suitable wavelet for medial image compression.

Texture representation using autoregressive models

Abstract: Texture is a fundamental characteristic in many natural images that plays an important role in human visual perception and in turn provides information for image understanding and scene interpretation. The textured image can be modeled to describe, analyze and synthesize the texture. The model parameters capture the essential perceived qualities of texture. One of the important characteristics of texture data is the statistical dependence of the gray level at a lattice point on those of its neighbors. The spatial-interaction models characterize this statistical dependency by representing the intensity of a pixel, as a 2-D linear combination of the intensity of its neighbors and an additive noise. One way of specifying this interaction is simultaneous autoregressive (SAR) models. This is one of the most traditional methods used for modeling in the area of image processing. This paper presents the work done by the authors on parameter estimation and synthesis of textured images using Simultaneous Autoregressive (SAR) modeling. Different programs are developed in MATLAB to implement the parameter estimation and synthesis and are tested for their performance. The scope of this work includes the use of causal and noncausal methods for modeling and synthesizing natural textures. Simultaneous or spatial autoregressive models with causal and noncausal neighborhoods are used for parameter estimation and texture pattern generation. Parameter estimation is done by two different methods: The least square error (LSE) and maximum likelihood estimation (MLE). LSE method is preferred for causal models. MLE method is used for noncausal autoregressive models and it uses iterative algorithm. The synthesis procedure is based on generating a two dimensional autoregressive random field driven by a two dimensional zero mean white noise field with unit variance. Two different algorithms are used for synthesis of causal and noncausal AR models. Different image textures are synthesized using a given set of neighborhoods and parameters. Different patterns of synthetic images can be generated using various sets of parameters. A number of images from Brodatz album are tested for parameter estimation and synthesis. The synthesized image retains the pattern in the original image like vertical or horizontal streaks. An interactive graphical user interface (GUI) is developed using MATLAB that allows user to select one image from Brodatz album. The user can choose between causal or noncausal neighborhood and select number of elements in the neighborhood or choose any one set of neighborhood from different sets stored, and find out SAR model parameters by one of the methods of parameter estimation. The user can synthesize the image using these parameters. Both original and synthesized image are displayed side by side on the screen and the user can easily compare the two images. Thus the GUI offers an interactive platform for implementation of parameter estimation using different neighborhoods for the images from Brodatz album and synthesis of the image from these estimated parameters.

Hand Gesture Recognition Using Object Based Key Frame Selection

Abstract: The sign language recognition is the most popular research area involving computer vision, pattern recognition and image processing. It enhances communication capabilities of the mute person. In this paper, we present an object based key frame selection. Hausdorff distance and Euclidean distance are used for shape similarity for hand gesture recognition. We proposed the use of nonlinear time alignment model with key frame selection facility and gesture trajectory features for hand gesture recognition. Experimental results demonstrate the effectiveness of our proposed scheme for recognizing American Sign Language.

Time of Use pricing - India, a case study

Abstract: As electricity markets are liberalized, consumers become exposed to higher electricity prices and may decide to modify their demand to reduce their electricity costs. Real Time Pricing (RTP) and Time of Use pricing (TOU) function as load management tools. The magnitude variation of price (for e.g., the diurnal, weekly or seasonal) would require setting up of a model to represent consumer behavior. The model relies on the concept of demand elasticity across time, degree of consumer economic rationality and, on the supply side, on the price formulation model. A range of assumptions in respect of these matters are explored. In this paper the MSEDCL system is analyzed to check demand elasticity. It shall be done in two parts viz; (a) within the existing time slots, the TOU rates to be modified based on Cost of Unserved Energy (CUE) , (b) With the existing tariff the time slots to be varied and its implications to be analyzed based on the Cost of Service (COS) study, (c)A new tariff proposed based on COS and CUE to decide peak hour tariff.

A new approach to a sliding mode controller design for a magnetic levitation system

Abstract: The problem of precisely controlling the position of a ferromagnetic ball above the ground by levitating it against the force of gravity using an electromagnet is of interest because the magnetic levitation system is open loop unstable and highly nonlinear. We have designed a sliding mode controller based on the concept of a proportional integral switching surface for this application. Furthermore, we have compared the proportional integral sliding mode controller and a feedback linearization controller for their performance in controlling the ball position in the presence of parametric and matched uncertainties. Simulation results show that the proportional integral sliding mode controller is more effective than a feedback linearization controller.

Neuro-Wavelet based vector quantizer design for image compression

Abstract: This paper presents a novel idea of designing codebook, which is heart of vector quantization scheme based on Kohonens self organizing feature maps (SOFM) and wavelet transform. Being named as neuro wavelet generic codebook for compression of gray images, it can also be extended to the compression of color images and video frames. The code vectors are generated by evaluating the characteristics of the specific image sub samples, which are determined through rigorous mathematical operations and training the selected samples by Kohonen's SOFM artificial neural network with adjustable learning rate and initializations conditions followed by application of discrete wavelet transform. The testing of the codebook is done with variety of images and the compression performance is evaluated by using objective and subjective quality measures such as image fidelity, structural content, mean structural similarity index, universal quality index, spatial frequency measure and spectral activity measure along with PSNR. The proposed design is such that it can be implemented with less complexity and cost using VLSI techniques.

Marathi Language Speech Synthesizer Using Concatenative Synthesis Strategy (Spoken in Maharashtra, India)

Abstract: in this paper, we present the concatenative text-to-speech system and discuss the issues relevant to the development of a Marathi speech synthesizer using different choice of units: words, phonemes as a database. Quality of the synthesizer with different unit size indicates that the word synthesizer performs better than the phoneme synthesizer. The most important qualities of a speech synthesis system are naturalness and intelligibility. We synthesize the Marathi text and perform the subjective evaluations of the synthesized speech. As a result, (1) 81% of speech synthesized by the proposed method was preferred to that by the conventional method, (2) The error rate of TTS synthesizer is around 8.22%, (3) Speech synthesis runtime was reduced for proposed method. The results show the effectiveness of the proposed method.

A Scale Adaptive Tracker Using Hybrid Color Histogram Matching Scheme

Abstract: In this paper we propose a computationally efficient scale adaptive tracking method using a hybrid color histogram matching scheme. Firstly, we report an important property of the Chi-squared measure- It outperforms Bhattacharyya measure in the task of histogram matching from a few significantly similar multimodal histograms. Also, Bhattacharyya measure performs better while selecting matches from a varied dataset. We employ these results to develop a hybrid histogram matching procedure using the two measures. This method is used for a patch matching algorithm in real time tracking. We first calculate a color histogram of the target which is then compared with histograms of patches in the neighborhood in subsequent frames using this hybrid procedure to obtain the best match. We devise a systematic scale adaptive tracking method which is robust to rapid changes in the target size. It is also robust to partial occlusion of the target. Extensive experimental proof based on real life and test datasets is presented which demonstrates the excellent tracking accuracy achieved by our algorithm at real time.

Systolic architecture for integer point matrix multiplication using FPGA

Abstract: The paper presents a systolic architecture for integer point matrix multiplication algorithm using FPGA. Approach uses four processing elements that minimizes resources, reduces the routing complexity and improves Area/Speed metric.

The prisoner's dilemma with semi-synchronous updates: evidence for a first-order phase transition

Abstract: The emergence of cooperation in self-centered individuals has been a major puzzle in the study of evolutionary ethics. Reciprocal altruism is one of the explanations put forward and the prisoner's dilemma has been a paradigm in this context. The emergence of cooperation was demonstrated for the prisoner's dilemma on a lattice with synchronous update. However, the cooperation disappeared for asynchronous update and the general validity of the conclusions was questioned. Neither synchronous nor asynchronous updates are realistic for natural systems. In this paper, we make a detailed study of a more realistic system of semi-synchronous updates where pN agents are updated at every time instant. We observe a transition from an all-defector state to a mixed state as a function of p. Our studies indicate that despite it being a transition from an absorbing state, it is a first-order transition. Furthermore, we used a damage spreading technique to demonstrate that the transition in this system could be classified as a frozen–chaotic transition.

A novel line start permanent magnet synchronous motor using two-part rotor

Abstract: Line Start Permanent Magnet Synchronous Motor (LSPMSM) has been proved as an economically feasible, high efficiency alternative to an induction motor where constant speed is desirable. These motors are having the properties of an induction motor during starting and synchronous motor during steady state period. The need of line starting, calls for a cage winding in addition to permanent magnets in the rotor, which increases the complications in rotor design, and restricts the choice of rotor geometries. There is always conflict in the rotor design of this machine. This conflict is in between synchronous and asynchronous performance of the machine which in turn is a conflict between cage and magnet placement in the rotor. This paper reports an attempt in the direction of removing this conflict and optimizes both synchronous and asynchronous performances of the machine. A new two-part rotor geometry is suggested and analyzed using the dynamic model of LSPMSM prepared in Simulink.

Effective energy conservation for the agricultural sector using line start permanent magnet synchronous motors

Abstract: The growing demand for electricity in developing countries calls for a continuous increase in the installed capacity. However, with installed capacity unable to meet the pace of increase in demand, increase in efficiency of energy conversion devices is a vital requirement. The present paper considers one such energy improvement method in the form of a Line Start Permanent Magnet Synchronous Motor (LSPMSM) which is intended as a substitute for induction motors in developing countries. The economic benefits due to the utilization of such machines, their commercial viability and their life cycle costing have all been considered here. The paper also presents theoretical results obtained for various rotor configurations of the LSPMSM and practical results for the selected spoke type rotor geometry.

Mobile Forensics: An Introduction from Indian Law Enforcement Perspective

Abstract: Mobile phone proliferation in our societies is on the increase. Advances in semiconductor technologies related to mobile phones and the increase of computing power of mobile phones led to an increase of functionality of mobile phones while keeping the size of such devices small enough to fit in a pocket. This led mobile phones to become portable data carriers. This in turn increased the potential for data stored on mobile phone handsets to be used as evidence in civil or criminal cases. This paper examines the nature of some of the newer pieces of information that can become potential evidence on mobile phones. It also highlights some of the weaknesses of mobile forensic toolkits and procedures. Finally, the paper shows the need for more in depth examination of mobile phone evidence.

Resource efficient 64-bit floating point matrix multiplication algorithm using FPGA

Abstract: The paper presents a novel methodology to implement resource efficient 64-bit floating point matrix multiplication algorithm using FPGA. Approach uses systolic architecture using four processing element (PE's) that gives tradeoffs between resource utilization and execution time, results in reducing the routing complexity for dense matrix multiplication problems.

Power system switching transients analysis using multiresolution signal decomposition

Abstract: Deregulation and embedded generation are two important reasons for the recent interest in power quality. Other important reasons are the increased emission of disturbances by equipment and the increased susceptibility of equipment, production processes, and manufacturing industry to voltage disturbances. Thus it is essential to establish a real time power quality monitoring system to detect power quality disturbance. Wavelet Transform (WT) is a mathematical tool, which provides an automatic detection of Power Quality Disturbance (PQD) waveforms, especially using Daubechies family. Several types of Wavelets Network algorithms have been considered for detection of power quality problems. But both time and frequency information are available by Multi Resolution Analysis (MRA) alone. This paper presents the application of wavelet transform to detect, localize, and extract power switching disturbance. A power system switching transients have been simulated using MATLAB-7.01. The key idea underlying the approach is to decompose a given disturbance signal into other signals which represent a smoothed version and a detailed version of the original signal. The decomposition is performed using multiresolution signal decomposition techniques. The proposed technique appears to be robust for detection and localization of power quality disturbances created due to capacitor switching and load switching.

Applying micro GA concept for problems with large and rugged solution space

Abstract: Genetic Algorithms have been a very effective tool in solving highly non-linear problems in various disciplines. They are capable of finding an acceptable solution, even if number of acceptable solutions happens to be very small percentage of the total number of possible solutions. However the convergence rate may become very slow when the solution space happens to be very large and rugged. In this paper an approach based on micro-GA has been suggested for solving such class of problems. An illustrative example of applying the concept for an antenna problem is discussed.

A fragment based scale adaptive tracker with partial occlusion handling

Abstract: We propose a fragment based algorithm for efficient target tracking under significant scale variation and partial occlusion In contrast, none of the previous multiple part or fragment based algorithms are both scale adaptive and robust to partial occlusion In our algorithm, the target is divided into a number of overlapping image fragments Their color histograms are compared with those of candidate fragments within the neighborhood in subsequent frames The candidate fragments with maximum histogram similarity with the template fragments contribute towards selection of location of best match within that neighborhood Its position is further calibrated by using a localization method We implement a systematic scale adaptive tracking scheme which is robust to significant changes in the target size Extensive experimental results based on real life sequences and test datasets are presented which demonstrate the excellent tracking accuracy achieved by our algorithm at real time

Estimation of the temperature of heat sources by digital photography and image processing

Abstract: Present work proposes a novel, low cost non-contact temperature measurement technique using consumer grade digital still camera. The images of various visible heat sources are captured. Using colour image segmentation, source zones are identified. The actual temperature is measured by placing a miniature thermocouple in each zone. The colour temperature correlation is established by applying various analytical techniques. Different equations are formulated for different zones observing colour dominance in respective zone. The results indicate that the image-based measurements agree with the corresponding contact measurements within an error range of about 5%.

Speech based watermarking for digital images

Abstract: This paper presents a novel scheme of watermarking of digital images for copyright protection and authentication. In this paper we proposed a method of embedding owner's speech signal. Speech being a biometric data, the watermark signal in this method is expected to be more meaningful and has closer correlation with copyright holder. The main issue of concern here is the capacity because the speech data has large number of samples. Linear predictive coding is used to encode the audio data. Here, speech samples are imperceptibly inserted using spread spectrum technique into the mid frequency band of wavelet transform of image which makes it robust to lossy compression. Applications for such a speech-hiding scheme include copy protection, authentication and covert communication.

Response Surface Modeling and Optimization of Electro-Discharge Machining of Al/Al2O3p

Abstract: In this study, wire electrical discharge machining of aluminium matrix composites has been experimentally investigated. A metal matrix composite Al/Al2 O3p /10% has been machined at various combinations of machining parameters such as pulse on-time, off-time, wire speed and wire tension. Empirical models have been developed to predict the cutting rate, surface roughness and kerf width of the machined composite material. The models were developed by using the technique of response surface methodology. The experiments were conducted by using carefully planned response surface design matrix (central composite design). The model predictions are in good agreement with the experimental results. The R2 values of the proposed cutting rate, and kerf width models are above 0.99 and 0.98 respectively, where as it is 0.95 for the surface roughness model. The pulse on-time was found to influence cutting rate and surface finish significantly. Kerf width was significantly affected by pulse on-time, off-time, wire speed, and wire tension. In addition, a model was developed to correlate the multiple performance characteristic called as grey relational grade and the process parameters. Thus, a new combination of response surface method and grey relational analysis is proposed. The grey relational grade was significantly affected by pulse on-time and off-time time. The R2 value for the grey relational grade model was 0.94. Optimal parameter setting was determined for the multiple performance characteristic. The improvement in cutting rate was more than 100% compared to the ‘0’ level experiments, with reasonably smooth surfaces and narrow kerf width.Copyright © 2009 by ASME

Higher Dimensional Cosmological Model of the Universe with Decaying Λ Cosmology with Varying G

Abstract: In this paper we present higher dimensional cosmological model of the universe with the decaying vacuum energy density in the realm of model with a time varying gravitational constant. We have shown that our model admits the usual higher dimensional de Sitter solution and the other solutions characterized by the constant ratio between matter density and the total energy density. Our work is the generalization of the work obtained earlier by Carneiro (Proceedings of the MG10 Meeting held at Brazilian Center for Research in Physics (CBPF), Rio de Janeiro, Brazil, 20–26 July, 2003) in four dimensional space-time.

Microwave absorbing polymer composites

Abstract: The authors have synthesized the thermally stable epoxy resin modified polymer composites such as polydiphenylamine, benzidine polyvinyl alcohol, styrene polymethyl methacrylate by in situ polymerization technique. To this, the materials were modified with triethylene tetramine as hardener to obtain highly cross-linked thermosetting resins in weight percentages with AR grade epoxy resin. Then the reflection characteristics of these polymer composites, made as thin slabs was carried out by a transmission/ reflection method using a vector network analyzer R&S ZVA40, in the X and Ku-bands [8.0 to 18.0 GHz]. The microwave reflectivity properties of all these three blends were evaluated, and the epoxy modified styrene polymethyl methacrylate is found to be remarkably high upto − 50.2 dB at 14.1 GHz. The reflectivity of −10 dB or less could be obtained for a range of 7.4 GHz for the epoxy modified polydiphenylamine. The response slightly varies for all three samples. After due comparison of their response, epoxy modified polydiphenylamine and benzidine polyvinyl alcohol are deemed to be suitable as microwave absorber in the X and styrene polymethyl methacrylate is suitable in the Ku-band. The morphological features of the composites were examined using xray powder diffratogram and scanning electron microscopy.

Forbidden-minor characterization for the class of graphic element splitting matroids

Abstract: This paper is based on the element splitting operation for binary matroids that was introduced by Azadi as a natural generalization of the corresponding operation in graphs. In this paper, we consider the problem of determining precisely which graphic matroids M have the property that the element splitting operation, by every pair of elements on M yields a graphic matroid. This problem is solved by proving that there is exactly one minor-minimal matroid that does not have this property.