College of Engineering, Pune

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

Hydrothermal synthesis of mesoporous NiMnO3 nanostructures for supercapacitor application: Effect of electrolyte

Abstract: In recent days, energy storage devices like supercapacitors are gaining increasing interest. However, the real challenge of getting high specific capacitance with significant mechanical stability and high energy density at an affordable cost for the supercapacitors based on mixed transition metal oxides continues. Herein, mesoporous NiMnO3 (NMO) nanostructures have been prepared by the hydrothermal method. Electrochemical performance of the NMO Nickel foam (NF) electrode is investigated by cyclic voltammetry at various scan rates of 5–100 mVs−1, galvanostatic charge-discharge at various current densities of 3–5 mAcm−2, and electrochemical impedance spectroscopy over a frequency range of 100 Hz to 100 kHz in 1 M KOH, 1 M NaOH, and 1 M Na2SO4 electrolytes. The NMO NF working electrode displayed a high specific capacitance of 435 Fg−1 at a scan rate of 5 mVs−1 and 100% cyclic stability for 2000 cycles, in 1 M KOH electrolyte. The determined values of specific energy, specific power, and coulombic efficiency for NMO- NF electrodes are 11.13 Whkg−1, 198.52 Wkg−1, and 98.1%, respectively.

Hand Gesture Recognition System for Numbers Using Thresholding

Abstract: An efficient human computer interaction is assuming utmost importance in our daily lives. Human beings can communicate mainly by vision and sound. Human can recognize the meaningful expressions of motion using hand gesture. Hand Gesture is the most important to exchange ideas, messages, thoughts etc among deaf and dumb people. This paper discusses a simple recognition algorithm that recognizes the numbers from 0 to 10 using thresholding. The overall algorithm has three main steps: image capture, apply threshold and recognizing the number. The assumption is made that user must wear color hand gloves.

Autonomous Cars: Technical Challenges and a Solution to Blind Spot

Abstract: Automotive industry is progressing forward toward the future, where the role of driver is becoming smaller and leading to become ideally driverless Designing a fully driverless car (DC) or self-driving car is a most challenging automation project, since we are trying to automate complex processing and decision-making of driving a heavy and fast-moving vehicle in public There are many scenarios where self-driving cars are not able to perform like human drivers There are a lot of technical, non-technical, ethical and moral challenges to be addressed Furthermore, two recent accidents caused by self-driving cars of Uber [1] and Tesla [2] have raised a concern toward the readiness and safety of using these cars Therefore, it is necessary to address these challenges and issues of DC’s In this paper, we have surveyed various technical challenges and scenarios where DCs are still facing issues We have also addressed an issue of blind spots and proposed a systematic solution to tackle the issue Before self-driving cars go live on road, we have to overcome these challenges and work on technology barriers so that we can make the DCs safe and trustworthy

On the decadal predictability of the frequency of flood events across the U.S. Midwest

Abstract: Skillful predictions of the frequency of flood events over long lead times (e.g., from one to ten years ahead) are essential for governments and institutions making near‐term flood risk plans. However, little is known about current flood prediction capabilities over annual to decadal time scales. Here we address this knowledge gap at 286 U.S. Geological Survey gaging stations across the U.S. Midwest using precipitation and temperature decadal predictions from the Coupled Model Intercomparison Project (CMIP) phase 5 models. We use the 1‐ to 10‐year predictions of precipitation and temperature as inputs to statistical models that have significant skill in reproducing inter‐annual and decadal changes in the observed frequency of flood events. Our results indicate that the limited skill of basin‐averaged precipitation predictions suppresses the skill of flood event frequency predictions, even at the shortest lead time, but downscaling and bias correction improves predictions across all lead times and especially in spring.