There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

A review on carbon nanotubes and graphene as fillers in reinforced polymer nanocomposites

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well as solve challenging machine learning problems The promise of the technology is to create a brain-like ability to learn and adapt, but the technical challenges are significant, starting with an accurate neuroscience model of how the brain works, to finding materials and engineering breakthroughs to build devices to support these models, to creating a programming framework so the systems can learn, to creating applications with brain-like capabilities In this work, we provide a comprehensive survey of the research and motivations for neuromorphic computing over its history We begin with a 35-year review of the motivations and drivers of neuromorphic computing, then look at the major research areas of the field, which we define as neuro-inspired models, algorithms and learning approaches, hardware and devices, supporting systems, and finally applications We conclude with a broad discussion on the major research topics that need to be addressed in the coming years to see the promise of neuromorphic computing fulfilled The goals of this work are to provide an exhaustive review of the research conducted in neuromorphic computing since the inception of the term, and to motivate further work by illuminating gaps in the field where new research is needed

A Survey of Neuromorphic Computing and Neural Networks in Hardware.

http://ieeexplore.ieee.org/iel5/5/31324/01456901.pdf

Microelectronic circuits

We have reviewed the humidity sensors based on ceramic materials. We first discuss the operating principle of ceramic humidity sensors. This is followed by a section on the relationship between the conduction mechanism and microstructure characteristics of the sensing elements of ceramic humidity sensors. This part of the review is also focused on the methods for optimization of the microstructure of ceramic porous elements. The next section summarizes the information on the materials used for the ceramic humidity sensors fabrication and effect of dopants or hybrid compositions on the sensing ceramic-based materials. Then we analyze state-of-the-art techniques for producing ceramic sensors. The key research and technological challenges in the field are discussed at the end of the review. The review is based on 424 references published during from 1998–2013.

Recent trends of ceramic humidity sensors development: A review

In this work, Dissolved gas Analysis (DGA) has been implemented using softcomputing models namely fuzzy logic and Adaptive Neuro fuzzy inference system (ANFIS). DGA has developed as an effective tool for the identification of transformer incipient faults. A number of standards and procedures have evolved over the years making DGA more reliable and user friendly. A comparative study of the two models has been developed based on their ability to circumvent the limitations of the IEC 599 standard, Rogers ratio method and Doernenburg’s method. The models have been tested using a reported fault database for their diagnostic capability. Results presented in this paper clearly indicate the superiority of the ANFIS model over the fuzzy system. The ANFIS model presents a reliable system with relative high degree accuracy. ANFIS model being very simple to develop can obviate the limitations of conventional methods of transformer fault diagnosis using DGA.

A comprehensive comparative study of DGA based transformer fault diagnosis using fuzzy logic and ANFIS models

We have investigated the effects of chemical treatment on Single Wall Carbon Nanotube (SWCNT) before and after being modified with HNO3/H2SO4 by Raman, FTIR and UV-Vis-NIR spectroscopy. The results show successful carboxylation of the CNT sidewalls as observed from FTIR and UV-Vis-NIR spectroscopy. This successful functionalization is achieved in 6-8 hrs of refluxing. We also report changes in the first and second order Raman spectra of SWNTs functionalized with oxygenated groups. During the experiment, we observe some important Raman features: Radial breathing mode (RBM), Tangential mode (G-band), and Disordered mode (D-band); which are affected due to the chemical oxidation of carbon nanotubes. We found that the ratio of D- to the G-band intensity (Id/Ig), increase after functionalization and the RBM mode in acid treated SWCNTs is almost disappeared.

https://file.scirp.org/pdf/JMP20110600009_11044356.pdf

Spectroscopic Investigation of Modified Single Wall Carbon Nanotube (SWCNT)

Present work deals with the development of a low cost moisture sensor for measuring moisture in the range of 2.5–25 ppm using nanoporous thin film of alumina (γ-Al 2 O 3 ). Thin film of γ-Al 2 O 3 prepared by low cost and simple sol–gel method offers very high surface to volume ratio with distribution of micro pores for moisture detection. Pore morphologies of the film have been studied by FESEM, AFM, XRD and BET methods. To form a capacitive sensor, the porous film of 3–6 μm thickness was dip-coated in between two parallel gold electrodes. The characteristic of the sensors have been examined by Agilent 4294 A impedance analyzer for the frequency range of 1–20 kHz. The characteristics of the sensor can be used for making trace moisture sensor for commercial applications. The capacitance change with moisture is almost linear with 1.05% nonlinearity and 0.33% hysteresis.

A novel sol–gel thin film porous alumina based capacitive sensor for measuring trace moisture in the range of 2.5–25 ppm

A course on the emerging topic “Smart Sensors and Internet of Things (IoT)” has been designed, developed, and delivered from 21st March 2016 to 31st March 2016 in the Department of Electrical Engineering, Jamia Millia Islamia (Central University), New Delhi-110025, India. This course was organized under a program initiated by the Government of India, entitled “Global Initiative of Academic Networks” for higher education. The basic objective is to bring the internationally and nationally acclaimed scientists on a single platform to motivate young minds of India so that India’s scientific and technological capacity reach global excellence. The course was designed to develop the technical skills for the students, the researchers, the engineers, and the faculties, who desire to address some of the issues faced by the people around the world in the fields of smart sensors and IoTs with applications in smart homes, smart cities, smart grids, smart environment, smart transport, and so on. The assessment of the course by the participants shows extreme usefulness of it.

Tarikul Islam

Papers

A comprehensive comparative study of DGA based transformer fault diagnosis using fuzzy logic and ANFIS models

Spectroscopic Investigation of Modified Single Wall Carbon Nanotube (SWCNT)

A novel sol–gel thin film porous alumina based capacitive sensor for measuring trace moisture in the range of 2.5–25 ppm

Smart Sensors and Internet of Things: A Postgraduate Paper

Temperature compensation of piezoresistive micro-machined porous silicon pressure sensor by ANN