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Quality Uncertainty and Perception 1

丛书名： Contributions to Management Science

1000年

作者： Lalit Wankhade Balaji Dabade

ISBN: (数字)9783790821956

ISBN: (纸本)9783790821949;9783790828221

It has been observed that the studies of quality are pursued in various disciplines like economics, quality management, and marketing science, and are seen isolated. The treatments imparted to these studies are also different and has the backdrop of discipline in which the work has been pursued. The nature of isolation is equally seen when quality uncertainty and perceived quality were pursued separately without showing any inkling that these can be complimentary. Economist and Nobel Laureate, Akerlof (1970), wrote a seminal piece “The market for lemons: quality uncertainty and market mechanism”, where he described quality uncertainty due to information asymmetry. It refers to the fact that a party in a transaction may have more information than the other. This is information asymmetry. If the seller has more information than the buyer about the product quality, he/she may sell it, as if it is a high-quality product. In reality, it could be a low-quality product. The buyer does not have the information regarding the quality of the offered product. The market condition that led to this transaction is quality uncertainty due to information asymmetry.

关键词： Organization Business Strategy/Leadership Marketing Innovation/technology Management Operations Management engineering Economics, Organization, Logistics, Marketing

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Object Removal and Image Restoration within Subspaces by Prioritized Patch Optimization 6

Object Removal and Image Restoration within Subspaces by Pri...

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6th International Conference on Signal Processing and Communication, ICSC 2020

作者： Bonde, S.V. Borole, Rajesh P. Shri Sggs Institute of Engineering and Technology Department of Electronics and Telecom Nanded Maharashtra India

ISBN: (纸本)9781728154930

The purpose of this work is to develop a robust technique for image inpainting to restore small cracks as well as large regions those include the regions developed by object removal. The image to be restored is transformed into sub-bands by the use of DWT (Discrete Wavelet Transform). These sub-bands are reconstructed back to spatial domain to obtain the subspaces images that are at the same scale as the original image to be restored but having different resolutions. These subspace images are then subjected individually to 'prioritized exemplar approach' to fill-in different structures and textures simultaneously. We also optimize the patch size to cope up different sizes of textures, structures and varying resolution of the subspace images. These restored subspace images are superposed to obtain the final restored image. A number of images with changing complexion are used to estimate the effectiveness of the algorithm. The results shows visually plausible background where from the object is removed in variety of images with different structures and textures. The RMSE (Root Mean Squared Error) and PSNR (Peak Signal to Noise Ratio) measures are used to quantify the improvement over visual quality of the restoration. © 2020 IEEE.

关键词： Textures

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Gujrati character recognition using adaptive neuro fuzzy classifier

Gujrati character recognition using adaptive neuro fuzzy cla...

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International Conference on Electronic Systems, Signal Processing, and Computing Technologies, ICESC 2014

作者： Prasad, Jayshree Rajesh Kulkarni, Uday V. Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Department of Computer Engineering SGGS Institute of Technology Nanded India

ISBN: (纸本)9781479921027

This paper presents implementation of an Adaptive Neuro Fuzzy Classifier (ANFC) for recognition of isolated handwritten characters of Gujrati based on [2]. Authors aim to compare the performance of ANFC with weighted k-NN classifier proposed in [1] by them. Fuzzy classification is the task of partitioning a feature space into fuzzy classes. Authors exploit the method of employing adaptive networks based on [2] to solve a fuzzy classification problem. System parameters, such as the membership functions defined for each feature and the parameterized t-norms used to combine conjunctive conditions are calibrated with back propagation. Towards this aim, authors use a supervised learning procedure based on Scaled Conjugate Gradient (SCG) algorithm to update parameters in an adaptive network. Next, this architecture is deployed for the character recognition problem. From the experimental results, it is summarized that although adaptively adjusted classifier performs well as far as time complexity is concerned but fails to achieve better recognition rates than weighted k-NN. The results are discussed from the viewpoint of feature extraction methods discussed in [1] and their effectiveness on neuro fuzzy classifiers. © 2014 IEEE.

关键词： Character recognition

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Text - Independent speaker identification using hidden Markov models

Text - Independent speaker identification using hidden Marko...

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1st International Conference on Emerging Trends in engineering and technology, ICETET 2008

作者： Deshpande, Mangesh S. Holambe, Raghunath S. SRES College of Engineering Kopargaon Maharashtra India SGGS Institute of Engineering and Technology Nanded Maharashtra India

ISBN: (纸本)9780769532677

This paper presents a closed-set, text-independent speaker identification using continuous density hidden Markov model (CDHMM). Each registered speaker has a separate HMM which is trained using Baum-Welch algorithm. The system performance has been studied for different system parameters such as the number of states, number of mixture components per state and the amount of data required for training. Identification accuracy of 100% is achieved by conducting the experiments on TIMIT database. © 2008 IEEE.

关键词： Hidden Markov models

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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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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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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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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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Performance-based efficient seismic design of reinforced concrete frames with vertical irregularities

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Asian Journal of Civil engineering 2022年第3期23卷 375-389页

作者： Hashmi, Arshad K. Singh, H. Karanpal Jameel, Mohammed Patil, L.G. MGM’s College of Engineering Nanded 431605 India SGGS Institute of Engineering & Technology Nanded India King Khalid University Abha Saudi Arabia

Distribution pattern for the equivalent static lateral force in the seismic design process appears to be based on elastic approach. On the contrary, during extreme events such as seismic load, structures experience inelastic range. Consequently, the assumed lateral load distribution pattern for the seismic design does not remain applicable in the inelastic range. Thereby, some members of the structure go through extreme stress/deformations and the other experiences minor stresses/deformation. Current paper presents near optimum (i.e., efficient) design of reinforced concrete (RC) frames with structural irregularities applied to seismic excitations based on the model of uniform distribution of deformation and thereby damage. The efficient design is achieved by moving the material (i.e., steel reinforcement) from the members with minor deformation/damage to the member with extreme deformation/damage. The efficient design procedure for multiple performance objectives is demonstrated through the examples of irregular frames. The study illustrates that for same damage, efficient design requires less material (i.e., steel) than the design based on practicing code;again for the same amount of material (i.e. steel), efficient design gives less structural damage compared to the design based on practicing code. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Damage index Optimization Performance-based seismic design Uniform distribution of damage Vertical irregularities

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