College of Engineering, Pune

About: College of Engineering, Pune is a based out in . It is known for research contribution in the topics: Computer science & Sliding mode control. The organization has 4264 authors who have published 3492 publications receiving 19371 citations. The organization is also known as: COEP.

Nickel ferrite/polypyrrole core-shell composite as an efficient electrode material for high-performance supercapacitor

Abstract: In the present work, we report the high-performance supercapacitive behavior of NFO/PPy core–shell composite. The composite electrode was prepared by adopting simple and inexpensive in-situ chemical oxidation route in an aqueous medium containing sodium dodecyl sulfate (SDS) as a surfactant and characterized for the spectral, structural, electrical, thermal and morphological studies. The electrochemical properties were recognized by cyclic voltammetry, charge–discharge and electrochemical impedance spectroscopy. The supercapacitive performance of NFO/PPy electrode was studied in an aqueous 0.1N H2SO4 electrolyte solution. The effect of electrolyte concentration on specific capacitance and the stability of electrode were studied. The highest specific capacitance (Cs) achieved with NFO/PPy electrode was 721.66 Fg−1. The specific energy (Es), specific power (Ps) and coulomb efficiency (η%) were observed to be 51.95 Whkg−1, 6.18 kWkg−1 and 99.08% respectively. This electrode shows the outstanding electrochemical stability over 1000th continuous charging–discharging cycles and emerged as an efficient electrode material for energy storage devices as a supercapacitor.

Analysis of Speech Features for Emotion Detection: A Review

Abstract: Emotion detection of speech in human machine interaction is very important. Framework for emotion detection is essential, that includes various modules performing actions like speech to text conversion, feature extraction, feature selection and classification of those features to identify the emotions. The features used for emotion detection of speech are prosody features, spectral features and voice quality features. The classifications of features involve the training of various emotional models to perform the classification appropriately. The features selected to be classified must be salient to detect the emotions correctly. And these features should have to convey the measurable level of emotional modulation.

Improvement in k-Means Clustering Algorithm Using Data Clustering

Abstract: The set of objects having same characteristics are organized in groups and clusters of these objects reformed known as Data Clustering. It is an unsupervisedlearning technique for classification of data. K-means algorithm is widely used and famous algorithm for analysis of clusters. In this algorithm, n number of data points are divided into k clusters based on some similarity measurement criterion. K-Means Algorithm has fast speed and thus is used commonly clustering algorithm. Vector quantization, cluster analysis, feature learning aresome of the application of K-Means. However results generated using this algorithm are mainly dependant on choosing initial cluster centroids. The main short come of this algorithm is to provide appropriate number of clusters. Provision of number of clusters before applying the algorithm is highly impractical and requires deep knowledge of clustering field. In this project, we are going to propose an algorithm for improvement in the initializing the centroids for K-Means algorithm. We are going to work on numerical data sets along with the categorical datasets with the n dimensions. For similarity measurement we are going to consider the Manhattan distance,Dice distance and cosine distance. The result of this proposed algorithm will be compared with the original K-Means. Also the quality and complexity of the proposed algorithm will be checked with the existing algorithm.

Review on AMI technology for Smart Meter

Abstract: Smart Meter is an advance meter which measures electricity, gas & water consumption and gives more detailed information than a traditional meter. Implementation of AMI software into these meters will give variety of controls, facilities and features. In this work, customer service benefits such as managing demand response, flexible billing cycle, pricing structure, distributed network management, AMI standards, cost estimate and communication infrastructure of AMI with respect to Indian protocols are discussed regarding electricity measurement only.