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Multi-objective optimisation of thickness and strain distribution for automotive component in forming process

International Journal of Computational Intelligence Studies 2020年第1-2期9卷 172-184页

作者： Kakandikar, Ganesh Nandedkar, Vilas School of Mechanical Engineering Dr. V.D. Karad MIT World Peace University Pune India SGGS Institute of Engineering and Technology Nanded India

Automotive manufacturing industry has emerged as one of the important facet of economy boost in developing countries like India. Globalisation, with invited competition, is demanding best quality products from manufacturer. Most of the parts of automotive, which contribute to safety and aesthetics, i.e., body parts are manufactured from sheet metal. Metal forming is complex, strain distribution process in formed part from flat blank involving range of processes from simple bending to deep drawing. Ideally the volume of the blank and formed component must remain constant, but decrease/increase in thickness of sheet metal is observed along with strains in major and minor direction. This results in various failures as wrinkling and fracture. The paper presents innovative methodology to distribute uniformly the thickness, preventing thinning/thickening. Multi-objective optimisation problem has been framed with two contradictory objectives as thinning and thickening correlating the process variables. Petrol tank cover, automotive component has been selected for study and numerical experimentation, from Vishwadeep Enterprises, Pune. Multi-objective genetic algorithm [MOGA] has been applied for process optimisation. The results obtained are encouraging and avoids thinning/thickening and results in uniform distribution of thickness in all sections of petrol tank cover. © 2020 Inderscience Enterprises Ltd.

关键词： Sheet metal

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Biomedical image coding using dual tree discrete wavelet transform and noise shaping algorithm

Biomedical image coding using dual tree discrete wavelet tra...

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IEEE Conference on Open Systems

作者： Talbar, Sanjay N. Deshmane, Anil K. SGGS Institute of Engineering and Technology Nanded 431605 India TCT's College of Engineering Osmanabad India

ISBN: (纸本)9781424490554

The main objective of the proposed work is to explore the application of 2-D dual tree discrete wavelet transform (DDWT) which is directional and redundant over the critically sampled transform like discrete wavelet transform (DWT) for image coding. In this paper biomédical image coding is investigated with DDWTs along with iterative projection based noise shaping (IP-NS) algorithm. The noise shaping is one of sparsifying method for DDWT coefficients used to modify large coefficients to compensate for the loss of small coefficients, without substantially changing the original image. We compared results with various biomédical images using DWT, DDWT with noise shaping algorithm. Proposed scheme of noise shaping with DDWT significantly improve the performance in terms of PSNR. © 2010 IEEE.

关键词： Image coding

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Statistical analysis of RR series variability in spinal cord injured persons

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Journal of Medical engineering and technology 2012年第3期36卷 180-184页

作者： Patil, A.G. Chile, R.H. Hamde, S.T. Shri Bhagubhai Mafatlal Polytechnic Vile Parle West Mumbai India Department of Instrumentation SGGS Institute of Engineering and Technology Vishnupuri Nanded India

Disabled persons with spinal cord injury are prone to cardiovascular dysfunction and an increased risk of cardiovascular disease. Rehabilitation of the disabled person is a critical task as it involves multiple therapies. Physical exercise is an important component of rehabilitation, and depends on cardiovascular health. Reduced RR variability is a marker of poor cardiac health. Time domain RR variability analysis of 38 normal healthy subjects and 20 spinal cord injured subjects has been carried out and compared. In this study, RR intervals were recorded in three different modes or positions: supine, sitting and five-second rhythm respiration. At a time of 150 s RR interval data were acquired in each mode and analysed. Statistical parameters (mean, HR, STD, NN50 and pNN50) were calculated. It was observed that most of the indices were significantly and substantially altered in spinal cord injured persons. © 2012 Informa UK, Ltd.

关键词： Time domain analysis

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Isolated word recognition using normalized teager energy cepstral features

Isolated word recognition using normalized teager energy cep...

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International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2009

作者： Nehe, Navnath S. Holambe, Raghunath S. Pravara Rural Engineering College Loni Maharashtra India SGGS Institute of Engineering and Technology Nanded Maharashtra India

ISBN: (纸本)9780769539157

A robust feature extraction technique using Teager Energy Operator (TEO) for Isolated Word Recognition (IWR) has been proposed in this paper. A feature extraction algorithm is motivated by the enhanced discrimination capability TEO that estimates the true energy of the source of a resonance. The robustness is further added using Cepstral Mean Normalization (CMN) on the estimated features. The robust features are computed from the speech signal of a given frame through a series of steps. First, the short time spectrum of each frame of speech signal is calculated. Second, the frame spectrum is passed through a Mel scaled triangular filter bank. Then, the average of absolute values of sequence obtained after applying TEO on each filter output is estimated. Finally, the cepstral coefficients are extracted by applying discrete cosine transform on the estimated averages. These coefficients are further normalized using CMN to get the final features denoted as Normalized Teager Energy Coefficient (NTEC) features. The effectiveness of this technique has been tested on TI-20 isolated word database in presence of white noise. The experimental results show the superiority of the proposed technique over conventional MFCC, Spectral Subtraction (SS) and CMN methods. © 2009 IEEE.

关键词： Discrete cosine transforms

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MRIP: A heuristic approach for packet classification using multistage refinement on IP packet header

MRIP: A heuristic approach for packet classification using m...

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International Conference on Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies, ICN/ICONS/MCL'06

作者： Wash, S.J. Sontakke, T.R. Department of IT Army Institute of Technology Dighi Hills Pune MS India SGGS Institute of Engineering and Technology Nanded MS India

ISBN: (纸本)0769525520

The router classifies the packets to determine which flow they belong to or decide where to forward them and what service they supposed to receive. A packet classification on multiple fields is one of the best known techniques used so far in the network devices such as router and firewalls. The speedy classification on multiple fields of IP packet header is mathematically complicated and expensive to implement. In this paper, we present an algorithmic framework for solving the packet classification problem that minimizes memory usage, while preserving the average search time. The MRIP is a packet classification technique using Multistage Refinement on IP Packet header fields similar to Recursive Flow Control (RFC), the previously well known algorithm. As a result of simulation, the MRIP has been recognized to be very efficient as compared to other techniques. © 2006 IEEE.

关键词： Packet networks

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The Design of Multiuser BGN Encryption with Customized Multiple Pollard’s Lambda Search Instances to Solve ECDLP in Finite Time

The Design of Multiuser BGN Encryption with Customized Multi...

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International Conference on Artificial Intelligence and Data engineering, AIDE 2019

作者： Javheri, Santosh Kulkarni, Uday JSPM’s Rajarshi Shahu College of Engineering Pune India SGGS Institute of Engineering and Technology Nanded India

ISBN: (纸本)9789811535130

Data privacy breach is an important concern for data owners, in today’s online world. Data science applications, smart city applications and smart grid applications generate precious knowledge through analyzing user’s data. But many a times, it is experienced by the users that their sensitive personal data is exposed by these applications, without their consent. Due to the serious issues of data privacy preservation problems, public cloud-based data centers have failed in achieving popularity in third-party computation. To solve this privacy preservation problem, data can be collected and uploaded in unidentifiable format, such a way that meaningful computation can be performed easily. Homomorphic encryption is one of the favorite techniques, wherein direct computation on encrypted data is permitted and its results are equivalent to their plaintext format. BGN ‘doubly’ homomorphic encryption can execute infinite additions and single multiplication over encrypted data values at a time. BGN is based on the elliptic curve. Constant size of ciphertext is an attractive feature of BGN encryption. User has to solve elliptic curve discrete logarithm problem (ECDLP) to receive the desired results of addition and multiplication in plaintext format. Solving ECDLP is most time-consuming operation. Hence, BGN encryption can be used in small message space only. Customize Pollard’s lambda method can increase the message space of BGN encryption and solve the problem. Multiple instances of Pollard’s lambda attack can be executed with different range of intervals to solve ECDLP in finite time. This customization will make narrow search intervals to Pollard’s lambda to solve even 78-bit ECDLP for 88-bit prime field in finite times. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Geometry

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Class-Specific Fuzzy Hypersphere Neural Network

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Procedia Computer Science 2018年 143卷 285-294页

作者： A.B. Kulkarni S.V. Bonde U.V. Kulkarni SGGS Institute of Engineering and Technology Nanded-413601 India Department of EXTC SGGS Institute of Engineering and Technology Nanded-413601 India Department of CSE SGGS Institute of Engineering and Technology Nanded-413601 India

A new Fuzzy Hypersphere Neural Network (FHNN) classifier is proposed in the framework of Radial Basis Function Neural Network (RBFNN) for which two class specific fuzzy clustering algorithms are suggested for the creation of fuzzy set hyperspheres (FSHs) in the hidden layer and the traditional least mean square (LMS) algorithm used to determine the weights between hidden to output layer is avoided by assigning the appropriate binary weights during training. The FHNN classifier utilizes FSH as pattern cluster and classes are represented by union of FSHs. The proposed fuzzy clustering algorithms are developed on the basis of inter-class and intra-class fuzzy membership metrics with maximum coverage of data points to create the FSHs in the hidden layer of FHNN. The weights between hidden to output layer of FHNN are adapted simultaneously during the creation of FSHs in the hidden layer. Unlike RBFNN and other similar models, the learning is: fast, independent of tuning parameters, formulates precise centroids and widths or radii of the FSHs, leading to 100% training accuracy on any training set. The learning rule 1 proposed for the FHNN is insusceptible to the order of data presentation and always results in identical clusters showing good data visualization, while the learning rule 2 eradicates the overlap between inter-class FSHs. The performance of FHNN is compared with the RBFNNs using twelve benchmark data sets. The empirical findings demonstrate that the FHNN is highly efficient classifier.

关键词： Fuzzy membership function fuzzy hypersphere neural network fuzzy set hypersphere Radial basis function neural network

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Robust speaker identification in babble noise 11

Robust speaker identification in babble noise

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Proceedings of the International Conference & Workshop on Emerging Trends in technology

作者： Deshpande, M.S. Holambe, R.S. Department of E and TC Engineering SRES College of Engineering Kopargaon India Department of Instrumentation Engineering SGGS Institute of Engineering and Technology Nanded India

ISBN: (纸本)9781450304498

Performance of speaker recognition systems strongly degrades in the presence of background noise, like the babble noise. Speech babble is one of the most challenging noise interference due to its speaker/speech like characteristics. In contrast to existing works, the aim is to improve noise robustness focusing on the features only. To derive robust features, amplitude modulation - frequency modulation (AM-FM) based speaker model is proposed which combines the speech production and perception mechanism. The performance is evaluated using clean speech corpus from TIMIT database combined with babble noise from the NOISEX-92 database. Experimental results show that the proposed features significantly improve the performance over the conventional Mel frequency cepstral coefficient (MFCC) features under mismatched training and testing environments. Copyright © 2011 ACM.

关键词： Amplitude modulation

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Evapotranspiration studies for vishnupuri irrigation project

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ISH Journal of Hydraulic engineering 2005年第2期11卷 132-145页

作者： Waikar, M.L. Dhoot, S.A. Department of Civil and Water Management Engineering SGGS Institute of Engineering and Technology Nanded M.S. 431 605 Vishnupuri United States

Knowledge of the exact amount of water required by different crops in a given set of climatic conditions of region is of great help for planning of irrigation schemes, irrigation scheduling and also for mid term planning in case of mid season drought. The objective of the present study is to identify a suitable method for estimating reference evapotranspiration, ET_o and its effect on irrigation water requirement for the typical location of Shri Shankarraoji Chavan Vishnupuri Irrigation Project canal, Nanded in the Marathwada region of Maharashtra State. In department level irrigation planning of canal for the present case study, FAO modified Penman method has been used for estimation of ET_o. As this method was found to frequently overestimate ET_o, FAO has recommended the use of Penman-Monteith method which is now generally considered as the standard method. Further interrelationship among frequently used methods for estimation of ET_o is developed with modified Penman method and FAO Penman-Monteith method from the available climatic data. It is found that FAO Penman-Monteith method gives average 32.15% lower value of ET than that by modified Penman method. In the absence of adequate climatic data for Penman- Monteith method, modified Penman method has been found to be more suitable than other methods. © 2005 Taylor & Francis Group, LLC.

关键词： Penman Monteith Method Reference evapotranspiration Regression

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Design of decentralized controllers for MIMO processes

Design of decentralized controllers for MIMO processes

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作者： Lengare, M.J. Chile, R.H. Waghmare, L.M. Department of Instrumentation Engineering Ramrao Adik Institute of Technology Navi Mumbai 400706 India Department of Instrumentation Engineering SGGS Institute of Engineering and Technology Nanded 431606 India

In this paper, the design of decentralized PID controller for interactive and delay time processes is proposed. Direct controller synthesis approach is used to obtain parameters of the multi-loop controllers. A detuning factor for each loop is specified based on the closed-loop time constant. Then appropriate controller settings are determined using the Maclaurin series expansion and the model of the process. The success of the proposed algorithm is based on the detuning parameter thus the selection of the desired closed-loop time constant is an important factor. The proposed method has no limitations regarding systems weak or strong interactions, multiple delays, and its operating behaviors such as monotonic or oscillatory. The proposed algorithm is simpler and improved performance of various processes are achieved as compared to some of the prevalent techniques. Simulation examples demonstrate the usefulness of the proposed method. © 2011 Elsevier Ltd. All rights reserved.

关键词： Controllers

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