Department of Electrical Engineering

&ldquo;IIT Jodhpur is committed to impart quality education to facilitate the creation of qualified, competent and responsible human resources to meet the emerging technological challenges of the world. It is working towards creating an equitable learning platform that is positive, accessible and effective in the face of the modern societal and scientific advancements.

Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

The existing power system utilizes communication infrastructure for fast and reliable transfer of control and protection inputs. This dependency of a power system on communication infrastructure for critical applications makes it vulnerable to cyber attacks. Cyber-induced outages trigger both randomized and intentional switchings in a power system producing relatively similar dynamics as natural events making their classification difficult. This article proposes a principal component analysis (PCA) assisted sequential deep learning approach for online classification of cyber outages and natural events in a power system. This article provides objective-driven models for false setting injection (FSI) and false command injection (FCI) type attacks. The proposed classification method uses PCA to deduce truncated z-score sequences [or principal test sequences (PTSs)] capturing distinct spatio-temporal progression patterns of natural disturbances and cyber outages. The PTSs in the training sets are shuffled and sampled using a stratified random sampling technique and classified using an ensemble long short-term memory network. The proposed method is tested for simulation examples of FSI and FCI attacks in the standard IEEE118-bus test system, where it showed improved accuracy and time performance.

IEEE Systems Journal

PCA-LSTM Learning Networks With Markov Chain Models for Online Classification of Cyber-Induced Outages in Power System

The continuously fluctuating energy output and varying power demands in the renewable energy systems have led to the degradation of power quality. This work presents a model predictive based control for a solar PV system integrated to the grid for optimal management and control of the power transfer. The double stage three-phase configuration is controlled using model predictive control (MPC) strategy, which considers the power converters' switching states to predict the next control variable. The control uses a modified-dual second-order generalized-integrator for estimation of the power requirements based on the continuously varying system parameters. The PCC voltages assist and the ride through operation are performed based on the drops in voltage levels and optimum switching state is selected based on the minimization of the cost function to deliver the required active and reactive powers to the grid. The performance of the controller is validated through simulation and is also shown using hardware implementation. The IEEE-519 standard is followed throughout and a comparative analysis shows the remarkable performance of the presented grid controller. © 1986-2012 IEEE.

World University root node

IEEE Transactions on Energy Conversion

An MPC Based Algorithm for a Multipurpose Grid Integrated Solar PV System with Enhanced Power Quality and PCC Voltage Assist

A compressive acquisition technique for on-array image compression is proposed in this paper. It capitalizes on representation ability of accumulated spatial gradients of the acquired scene. The local variations inferred from strength of the accumulated gradients are used as cues to vary number of samples read through the image sensor readout. Such sampling enables the reconstruction using traditional interpolation techniques with desired quality. The proposed method is first verified using MATLAB simulations, where on an average, a compression of 87% is achieved, for a threshold of 40 intensity levels. The images are reconstructed using nearest neighbour interpolation (NNI) method which results in a mean peak signal to noise ratio (PSNR) value of 29.09 dB. The reconstructed images are further enhanced using deep convolutional neural network, which improves the PSNR to 32.46 dB. The biggest advantage of the proposed technique is low-complex hardware design. As a proof of concept, a hardware implementation of the technique is performed using discrete components. Pixel intensity values of standard images are converted into analog voltages using a data acquisition system and mapped in the input voltage range of 1.5 V -5.5 V. For a threshold of 3.8 V, the compression of 81% - 83% is observed for the considered images. The proposed technique is simple and effective, and is suitable for low-power complementary metal oxide semiconductor (CMOS) image sensors. © 1991-2012 IEEE.

Department of Computer Science & Engineering

IEEE Transactions on Circuits and Systems for Video Technology

On-Array Compressive Acquisition in CMOS Image Sensors Using Accumulated Spatial Gradients

We present highly time-resolved (30 to 120 min) measurements of size-fractionated (PM10 and PM2.5) elements in two cities in Asia (Delhi and Beijing) and Europe (Krakow and London). For most elements, the mean concentrations in PM10 and PM2.5 are higher in the Asian cities (up to 24 and 28 times, respectively) than in Krakow and often higher in Delhi than in Beijing. Among European cities, Krakow shows higher elemental concentrations (up to 20 and 27 times, respectively) than London. Hourly maximum concentrations of Pb and Zn reach up to 1 μg m-3 in Delhi, substantially higher than at the other sites. The enrichment factor of an element together with the size distribution allows for a rough classification of elements by major source. We define five groups: (1) dust emissions, (2) non-exhaust traffic emissions, (3) solid fuel combustion, (4) mixed traffic/industrial emissions, and (5) industrial/coal/waste burning emissions, with the last group exhibiting the most site-To-site variability. We demonstrate that the high time resolution and size-segregated elemental dataset can be a powerful tool to assess aerosol composition and sources in urban environments. Our results highlight the need to consider the size distributions of toxic elements, diurnal patterns of targeted emissions, and local vs. regional effects in formulating effective environmental policies to protect public health.. © 2021 Mary Ann Liebert Inc.. All rights reserved.

Department of Civil & Infrastructure Engineering

Fulltext

Atmospheric Chemistry and Physics

Highly time-resolved measurements of element concentrations in PM10 and PM2.5: Comparison of Delhi, Beijing, London, and Krakow

Modern data-driven applications pose stringent requirements of high bandwidth, ultra-low-latency, low-powered, and scalable interconnections among switches and routers in data-centers. To address these demands, electronic switching is not a viable choice due to bandwidth and computing bottlenecks. Thus, researchers explored effective optical switch design principles for next-generation data-centers. In optical switches, data aggregates in the form of optical bursts (OB) at ultra-high speeds. In the case of OB contention, solutions are proposed by researchers to store OB as recirculating patterns in fiber delay lines (FDL) with induced optical delay. However, due to variable burst length, it is not possible to measure slot delay length, thus storage of contending bursts is not possible at intermediate core switches. Motivated from the aforementioned discussions, in this paper, we propose a switch design DbOBS, that is capable to store variable OB during contention slots. DbOBS estimates mean burst length, and possible deviation from mean length to minimize burst loss. The considered switch design is validated through parameters like-burst length estimation, over-reservation, and waiting time. For network-layer simulations, poison arrivals of data bursts are considered as packetized units. The packets are sent through Monte-Carlo arrivals and burst loss probability (BLP) is estimated at various input load conditions and buffer sizes. DbOBS achieves a BLP in order of 10(-4) at load approximate to 0.8, and buffer-size of 50, and burst length of L = 5, that outperforms the traditional switch designs.

OPTICAL AND QUANTUM ELECTRONICS

DbOBS: dual buffered switch for variable optical bursts in future datacenters

This article presents a fault identification technique that makes use of the empirical mode decomposition of three-phase current signals of a distribution network. The current signals measured at the substation bus over a moving window are decomposed to obtain the first-level intrinsic mode function and residue. The standard deviation of the first-level residue is calculated as a fault index for each phase and compared with a threshold to detect and categorize the type of fault. A ground fault index based on the average value of the first-level residue of the neutral current is proposed to discriminate the phase-phase and phase-phase-ground faults. The proposed algorithm has been successfully tested on the IEEE 13 bus and 34 bus distribution systems in the presence of the solar photovoltaic power plant by varying the type of fault, fault incidence angle, and fault location in the presence of noise. The selectivity of the proposed algorithm has been established by testing the algorithm with nonfaulty transients such as transformer excitation and deexcitation, feeder energization and deenergization, load switching, capacitor switching, and also those associated with distributed generation (DG) penetration like islanding and tripping of DG. Subsequently, the residue-based features are fed to a decision tree to locate the faults on the distribution system. Thus, the proposed algorithm has been successful in detecting, classifying, and locating faults with DG penetration in the presence of noise within half cycle by utilizing only current signals. © 1972-2012 IEEE.

IEEE Transactions on Industry Applications

An EMD and Decision Tree-Based Protection Algorithm for the Solar PV Integrated Radial Distribution System

This article presents an analytical approach to determine jitter for a CMOS inverter in the presence of power supply noise (PSN). The deviation in the transition edge of the output signal from its ideal timing is modeled accurately for each transition. A power series method is used to solve differential equations for different regions of transistors during output transition. The PSN has been expressed in Taylor series expression, aids to derive closed-form equation for time interval error (TIE). The obtained results from the proposed methodology closely match with electronic design automation (EDA) simulator results and verified on 40 nm Taiwan Semiconductor Manufacturing Company (TSMC) and 28 nm United Microelectronics Corporation (UMC) foundries, demonstrating accurate modeling of jitter. IEEE

IEEE Transactions on Electron Devices

Device Parameter-Based Analytical Modeling of Power Supply Induced Jitter in CMOS Inverters

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92–2.59, <0.0001), use of public transport (1.79, 1.43–2.24, <0.0001), not smoking (1.52, 1.16–1.99, 0.0257), non-vegetarian diet (1.67, 1.41–1.99, <0.0001), and B blood group (1.36, 1.15–1.61, 0.001). © Naushin et al.

eLife

Insights from a pan India sero-epidemiological survey (Phenome-india cohort) for SARS-CoV2

This paper introduces the characterization of AZ-P4620 photoresist as a sacrificial layer for Radio Frequency MEMS (Micro-Electro-Mechanical System) switches. The surface micromachining process is opted for the fabrication of RF MEMS switches, which includes a suspended structure. Initially, a thick photoresist is coated and patterned, to be utilized as a sacrificial layer and then the structural layer is deposited on it. For proper connectivity of the structural layer, edge coverage is required. This photoresist is optimized at different post-baking temperatures. We investigated that slope angles decrease with an increase in post bake temperature. Using the optimized recipe, the RF MEMS switch is fabricated and characterized successfully. The measured isolation, pull-in voltage, and insertion loss, are − 30 dB, 23 V, and − 0.2 dB, respectively at 18 GHz frequency. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Microsystem Technologies

Sacrificial layer optimization for RF MEMS switches

The role of indium trioxide (In2O3) decorated Si nanowires (SiNWs) based resistive sensor for selective detection of ethanol vapors at near room temperature has been successfully demonstrated. SiNWs samples were synthesized using metal assisted chemical etching technique and these were decorated by a thin film of indium followed by annealing. The sensing response was captured by measuring the change in resistance of the sensing layer using a Cr-Au inter-digitated-electrode (IDE) structure formed on top of the sensing layers. All sensors were tested for ethanol, acetone, iso-propanol (IPA), xylene, benzene and toluene vapours in the wide concentration range of 5-500 ppm and at different temperatures. Sensors based on SiNWs alone had displayed higher response towards acetone vapours whereas after heterojunction formation with In2O3, significant sensitivity to ethanol was depicted. In2O3 decorated SiNWs resulted in significant enhancement of the sensor response% towards ethanol at near room temperature. Minimum detection of ethanol at 50 ppm and 10 ppm was portrayed by SiNWs and In2O3/SiNWs based sensors respectively. It was concluded that sensing behaviour was a consequence of combinatory effect produced by the presence of both SiNWs and In2O3. A simple explanation with device schematic and band diagrams of the material are proposed to describe the sensing mechanism. This study demonstrates the significance of surface treatment of SiNWs and the role of heterostructures for tuning the sensing properties and development of wafer scalable sensors. © 2001-2012 IEEE.