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International Conference on Signal Processing and Integrated Networks (SPIN)

作者： Rajeev Kumar Aruna Malik Samayveer Singh Satish Chand Division of Computer Engineering Netaji Subhas Institute of Technology New Delhi India Department of Computer Science and Engineering National Institute of Technology Jalandhar Punjab India

ISBN: (纸本)9781467391986

In this paper, we propose a high capacity text steganography method using Huffman compression. The forward email platform is used to hide the secret data. We make use of the number of characters used in email id to indicate the hidden secret data bits. So, to make optimal utilization of number of characters in email ids, the characters added to the email id to indicate the secret data bits are taken from the processed secret data. Hence, the hiding capacity is further increased. The new characters are appended just before the `@' symbol of email ids. Experimental results show that our method performs better than the some important existing methods in terms of hiding capacity.

关键词： Electronic mail Media Data mining Security Signal processing Mathematical model computers

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Analysis of model order reduction based on Mikhailov criterion

Analysis of model order reduction based on Mikhailov criteri...

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International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Anuj Rawat Shyama Kant Jha Department of Instrumentation Control Engineering Netaji Subhas Institute of Technology New Delhi

Prodigious applications concerning control processes utilize vigorous systems for simulation purpose. The burgeoning requirements for further precise and broad depiction of reasonable phenomena lead to higher order vital systems which intern entails an increased computational effort. Hence, an approximation in terms of Reduced Order Model of these extensive systems becomes essential for a cost efficient simulation. This paper presents a new model algorithm for order reduction, which is based on proposed Mikhailov criterion. The efficacy of the new order reduction algorithm is demonstrated by truncating higher-order SISO an Automatic Voltage Regulator system. The simulation grades show the suitability of the projected algorithm.

关键词： Mathematical model Voltage control Regulators Reduced order systems Computational modeling Approximation algorithms Algorithm design and analysis

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Ontology based framework for detecting ambiguities in software requirements specification

Ontology based framework for detecting ambiguities in softwa...

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： M P S Bhatia Akshi Kumar Rohit Beniwal Division of Computer Engineering Netaji Subhas Institute Of Technology Delhi India Department of Computer Engineering Delhi Technological University DTU Delhi India

ISBN: (纸本)9781467394178

Research in recent years has shown integration amongst the prominent & dynamic areas of software engineering and semantic web technologies. Prolifically published studies have explored the advantages of applying semantic web techniques to the field of software engineering. The motivation to further probe opportunities available in this collaborated field is ample with many issues and challenges. Among such issues, one is to detect ambiguities in Software Requirements Specification using ontology. This research paper presents a framework and discusses the implementation approach to resolve this issue.

关键词： Ontologies Software Software engineering Semantics Pragmatics computers Semantic Web

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Ontology based framework for reverse engineering of conventional softwares

Ontology based framework for reverse engineering of conventi...

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International Conference on Computing for Sustainable Global Development (INDIACom)

ISBN: (纸本)9781467394178

In contemporary years, integration among research areas of semantic web technologies and software engineering took place due to the reason of developers being present at different virtual, cultural, and geographical locations. Due to this amalgamation, a new collaborated field has emerged known as Semantic Web Enabled Software engineering. This field presents researchers ample opportunities to probe issues and challenges, which are originated due to their amalgamation. Among such issues, one is the reverse engineering of conventional softwares using ontologies. This research paper presents a framework and discusses the implementation approach to resolve to the above issue.

关键词： Ontologies Reverse engineering Maintenance engineering Software engineering Resource description framework Software systems

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Generalized Regression Neural Network Based Wind Speed Prediction Model for Western Region of India

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Procedia computer Science 2016年 93卷 26-32页

作者： Gaurav Kumar Hasmat Malik Electrical Engineering Department Indian Institute of Technology Delhi 110016 India ICE Division Netaji Subhas Institute of Technology Delhi 110078 India

With the growing demand of power generated by wind energy, prediction of wind speed has become an important region for research. In this paper, wind speed is predicted using Generalized Regression Neural Network (GRNN) and Multi-layer perceptron (MLP) in 67 cities of India. The input variables used are: Longitude, Latitude, daily solar radiation- horizontal, air temperature, relative humidity, earth temperature, elevation, cooling degree-days, heating degree-days, atmospheric pressure. The MSE of the two models are compared and found that GRNN gives better result than MLP. The accuracy of GRNN and MLP are 99.99% and 97.974% for training phase and 98.85% and 95.23% for testing phase respectively.

关键词： wind speed prediction GRNN MLP ANN

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Proximal Support Vector Machine (PSVM) Based Imbalance Fault Diagnosis of Wind Turbine Using Generator Current Signals

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Energy Procedia 2016年 90卷 593-603页

作者： Hasmat Malik Sukumar Mishra Department of Electrical Engineering Indian Institute of Technology Delhi 110016 India Instrumentation and Control Engineering Division Netaji Subhas Institute of Technology Delhi 110078 India

This paper presents an intelligent diagnosis technique for wind turbine imbalance fault identification based on generator current signals. For this aim, Proximal Support Vector (PSVM), which is powerful algorithm for classification problems that needs small training time in solving nonlinear problems and applicable to high dimension applications, is employed. The complete dynamics of a permanent magnet synchronous generator (PMSG) based wind-turbine (WTG) model are imitated in an amalgamated domain of Simulink, FAST and TurbSim under six distinct conditions, i.e., aerodynamic asymmetry, rotor furl imbalance, tail furl imbalance, blade imbalance, nacelle-yaw imbalance and normal operating scenarios. The simulation results in time domain of the PMSG stator current are decomposed into the Intrinsic Mode Functions (IMFs) using EMD method, which are utilized as input variable in PSVM. The analyzed results proclaim the effectiveness of the proposed approach to identify the healthy condition from imbalance faults in WTG. The presented work renders initial results that are helpful for online condition monitoring and health assessment of WTG.

关键词： Wind turbine fault diagnosis proximal support vector machine empirical mode decomposition FAST

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A Gaussian Shuffled Differential Evolution approach to Economic Load Dispatch Problem with valve point effect

A Gaussian Shuffled Differential Evolution approach to Econo...

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International Conference on Computing, Communication and Automation

作者： NANDAN KUMAR NAVIN RAJNEESH SHARMA Research Scholar Department of Instrumentation and control Engineering Netaji Subhas Institute of Technology New Delhi India Associate Professor Department of Instrumentation and control Engineering Netaji Subhas Institute of Technology New Delhi India

ISBN: (纸本)9781509016679

This paper proposes a Gaussian shuffled differential evolution (GSDE) for economic load dispatch problem. Proposed technique employs hybrid shuffled differential evolution with Gaussian mutation operator to blend differential evolution with shuffled frog leaping algorithm. Our approach uses shuffled Gaussian mutation operator for avoiding local optima during optimization and prevents prematurisation of convergence. Gaussian differential mutation operator imparts superior convergence efficiency and accuracy to the solution. We validate the effectiveness and superiority of GSDE by simulation on three diverse test system involving 13, 20 and 40 power generating units and compare performance against shuffled differential evolution, and with other recent techniques. Results demonstrate that proposed Gaussian shuffled differential evolution technique leads to faster and accurate solution to the economic load dispatch problem.

关键词： economic load dispatch gaussian shuffled differential evolution stochastic optimization evolutionary computation

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Modeling and control of one-link robotic manipulator using neural network based PID controller

Modeling and control of one-link robotic manipulator using n...

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Rajesh Kumar Smriti Srivastava J. R.P Gupta Department of Instrumentation and Control Engineering Netaji Subhas Institute of Technology Dwarka New Delhi

ISBN: (纸本)9781509020300

The dynamics of one-link robotic manipulator is complex and non linear and hence, cannot be easily controlled by conventional PID controller. The severity of the problem further increases when the plant's mathematical model is unknown or partially known which makes the use of PID control more difficult because it requires the dynamics of the system for tuning its parameters. Even if the dynamics are known, the parameters of PID controller are required to be retuned when external disturbance signals and/or parameter variations occurs in the system. In this paper, the PID controller is implemented using a multilayer feed forward neural network (MLFFNN) for the desired trajectory tracking control of one-link robotic manipulator (plant). To make the controller adaptive, the dynamics of plant is assumed to be unknown and hence, a separate multilayer feed forward neural network identification model is used which will approximate the plant's dynamics and operate simultaneously with the controller. The other benefits of using an identification model is that it can adjust its own parameters to reflect the effects of the disturbance signal and parameter variations on the system and provides this information to the controller which then makes necessary adjustment to its output to compensate these effects. Simulation results shows that MLFFNN based PID controller is able to control the plant and provides the desired trajectory in the presence of parameter variations and disturbance signal.

关键词： Manipulator dynamics Mathematical model Neurons Trajectory Informatics

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Time series prediction using focused time lagged radial basis function network

Time series prediction using focused time lagged radial basi...

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International Conference on Information technology (InCITe) - The Next Generation IT Summit on the Theme - Internet of Things: Connect your Worlds

作者： Rajesh Kumar Smriti Srivastava J. R. P. Gupta Department of Instrumentation and Control Engineering Netaji Subhas Institute of Technology Dwarka New Delhi

ISBN: (纸本)9781509026135

In this paper temporal processing of time series function has been done using radial basis function network. Radial basis function network structure is actually static but it has been converted into dynamic one using memory component. Proposed dynamic radial basis function network is called as focused time lagged radial basis function network (FTLRBFN). In a time series function, output at any given instant of time depends on the past values of the inputs. This feature is exploited while implementing the FTLRBFN. Back propagation algorithm based on gradient descent principle is used to adjust the parameters of radial basis function network. The proposed FTLRBFN is also implemented to simulate the complex time series function. The results so obtained show that FTLRBFN is effective in approximating any complex time series function. Comparison in terms of average mean square error is also made when multi layer feed forward neural network (MLFFNN) is used in the proposed scheme. It is found that the proposed scheme with radial basis function network has given less average mean square error as compared to that obtained with MLFFNN in the scheme.

关键词： Time series analysis Training Radial basis function networks Delay lines Mean square error methods Neurons Forecasting

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Investigation of launch power and regenerator placement trade-off in MLR optical networks

Investigation of launch power and regenerator placement trad...

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International Conference on Fibre Optics and Photonics, Photonics 2016

作者： Iyer, Sridhar Singh, Shree Prakash Department of ECE Jain College of Engineering T S. Nagar Hunchanatti Cross- Machhe Belagavi590014 India Division of ECE Netaji Subhas Institute of Technology Sector-3 Dwarka New Delhi110078 India

We investigate the trade-off between regenerator placement and launch power in MLR network. Results demonstrate optimal combination of launch powers providing the best design and network cost primarily being controlle... 详细信息

ISBN: (纸本)9781943580224

关键词： Regenerators

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