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Bhubaneshwar, India

Sahoo S.,KIIT University | Mohanty S.,OUAT | Sahoo T.,OEC
Souvenir of the 2014 IEEE International Advance Computing Conference, IACC 2014 | Year: 2014

This paper introduces a method of preference analysis based on electroencephalogram (EEG) analysis of prefrontal cortex activity. The proposed method applies the relationship between EEG activity and the Egogram. The EEG senses a single point and records readings by means of a dry-type sensor and a number of electrodes. The EEG analysis adapts the feature mining and the clustering on EEG patterns using a self-organizing map (SOM). EEG activity of the prefrontal cortex displays individual difference. To take the individual difference into account, we construct a feature vector for input modality of the SOM. The input vector for the SOM consists of the extracted EEG feature vector and a human character vector, which is the human character quantified through the ego analysis using psychological testing. In preprocessing, we extract the EEG feature vector by calculating the time average on each frequency band: θ, low- β, and high- β. To prove the effectiveness of the proposed method, we perform experiments using real EEG data. These results show that the accuracy rate of the EEG pattern classification is higher than it was before improvement of the input vector. © 2014 IEEE.


Panda S.,VSSUT | Baliarsingh A.K.,OEC | Mahapatra S.,KIIT University | Swain S.C.,KIIT University
Mechanical Systems and Signal Processing | Year: 2015

This paper proposes to use gravitational search algorithm (GSA) to design a supplementary sub-synchronous damping controller for the static synchronous series compensator (SSSC) device to damp the torsional oscillations. The IEEE second benchmark model (SBM) which is a series compensated ac system is considered in this study for design and analysis purpose. The design problem is formulated as an optimization problem and GSA is employed to search for the optimal controller parameters. The dynamic performance of the system under study is evaluated at various levels of series compensation with different types of disturbances. Fast Fourier Transform (FFT) analysis and robustness analysis against operating point changes and system uncertainties are also investigated. For specific system studied in the paper, the superiority of the GSA optimization technique over genetic algorithm (GA) optimization technique is also shown by comparing the simulation results and various performance indexes. © 2015 Elsevier Ltd.


Mohanty A.,Templecity Institute of Technology and Engineering | Mohanty P.P.,OSME Keonjhar | Mohanty S.,OEC
International Review on Modelling and Simulations | Year: 2013

The paper presents a comparison study of Transient Stability and Reactive Power Compensation Issues in a Wind Diesel Hybrid System with different FACTS Controllers. A Small signal model of the Hybrid System is taken with the use of Fuzzy Logic based PI Controller to compensate the Reactive power generated in an Isolated Wind Diesel hybrid system. Detailed analysis of the system is undertaken with varying loading conditions. Linearised small signal models of SVC, STATCOM and UPFC are taken to study the transient stability analysis of the proposed system with IEEE type 1 Excitation System. A Self tuned Fuzzy PI Controller is implemented to tune the parameters of KP and Ki of the Hybrid System which undergoes through Voltage Instability due to sudden change in load. Simulation result shows that the proposed controller attains steady state value with less time. © 2013 Praise Worthy Prize S.r.l. -All rights reserved.


Chakravarty S.,OEC | Mohapatra P.,IIT
2015 IEEE Power, Communication and Information Technology Conference, PCITC 2015 - Proceedings | Year: 2015

Classification plays an important role in various fields such as science, engineering, medicine and business. This paper proposes a cuckoo search based hybrid model i.e. Functional Link Neural Fuzzy Network named as CSFLNFN for classification of multi-class datasets. Both FLANN, as an efficient computational technique and fuzzy logic, as a basis of much inference system are combined to take the advantages from both the techniques. These two techniques are supplementary to each other in a way that one is helping other to overcome their limitations. The proposed CSFLNFN model uses FLANN to the consequent part of the fuzzy rules. The parameters of the models are optimized by the evolutionary algorithm, Cuckoo Search (CS). The CSFLNFN model is evaluated with one medical dataset, dermatology and three other frequently used multi-class datasets, wine, glass and iris. Further, to get more classification accuracy, Principal Component Analysis (PCA) has been used to extract the features from the datasets. Performance of the model is measured by number of measures like confusion matrix, accuracy, sensitivity, specificity, F-score, gmean and area under the receiver operating characteristic (ROC) curve. In this study, a comparison has been made between results before and after features extraction and it is seen that the classification accuracy increases with extracted features from the datasets. However the results demonstrate the superiority of the CSFLNFN compare to other models including CSMLP, CSFLANN, Naïve Bayesian and K-Nearest Neighbor irrespective of the feature extraction. © 2015 IEEE.


Photocleavage of H O into clean and storable H fuel by photoelectrochemical (PEC) cell is a vital part of the sustainable hydrogen economy. However, thus far one of the limitations confronted by PEC cell to preferable performance is the insufficient behavior of photoanode for water oxidation half-reaction. One of the strategies to elevate the photoanode performance is integrating with an oxygen evolution catalyst (OEC) to remove the bottleneck of the water oxidation kinetics. Herein, an ultrafine cobalt iron oxide (CIO) nanocrystalline is reported as a novel OEC for photoelectrochemical water splitting. The CIO evenly distributing on the surface of hematite nanorod arrays not only greatly facilitates the surface hole injection, but also promotes the charge separation along with passivating the surface states. Such combined effects of CIO finally lead to an impressive 1.71 fold enhancement on the photocurrent density at 1.23 V and ≈170 mV negative shift of onset potential, even overwhelms the commonly utilized Co-Pi. Along with its excellent long-term stability, the CIO possesses a great potential application in PEC water splitting devices.

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