Electronics & Communication (ECED)

A novel approach to implement wireless active sensing framework for Structural Health Monitoring is presented using an Unmanned Aerial Vehicle as a Mobile Agent. This approach has unique features of critical activity detection, wireless power delivery and measurement and data collection options from the sensor nodes through Zigbee. The active sensing is initiated by wirelessly triggering the sensor node from UAV. UAV provides unrestricted accessibility in various applications for SHM. It carries Beagle Board payload for real-time calculations to check the health of structures. The onboard video camera provides improved analysis of Critical activities like abnormal vibration and structure tilt. It captures video of the area of interest and data measured by any sensor node network. This paper is intended to give sufficient details of the implementation of our approach.

This paper presents a carry chain design optimized for implementing multipliers along with the adder circuitry. This kind of architecture will be very useful for designs which have very large number of mathematical operations in it. The aim of the architecture is to accommodate as much logic as possible in one LUT without increasing the size of the LUT proportionately. The discussed carry chain design is compatible with both 3-input as well as 4-input LUTs. The paper ends with a comparative study of multiplier implementation on various popular FPGA architectures.

A new methodology based on the concept of figure of merit under area constraints is described for designing optimum performance differential amplifiers. First a figure of merit is introduced that includes the three performance parameters, namely, input-referred noise, differential dc gain, and unity-gain bandwidth. Expressions for these parameters have been derived analytically and finally arrived at an expression for the figure of merit. Next it is shown how these performance parameters vary with the relative allocation of the total available area between the input and load transistors. The figure of merit peaks at a certain value of relative area allocation in the range of 60% to 80% of the available area to the input transistors. The peak value of figure of merit is a function of area. However, it is independent of biasing current (and, therefore, power consumption) subject to the minimum current (and, therefore, a minimum power) required to keep all the transistors biased in the...

Boolean function manipulation is an important component of many logic synthesis algorithms including logic optimization and logic verification of combinational and sequential circuits. Digital integrated circuits, often represented as Boolean functions, can be best-manipulated graphically in the form of Binary Decision Diagrams (BDD). Reduced-ordered binary decision diagrams (ROBDDs) are data structures for representation and manipulation of Boolean functions. The variable ordering largely influences the size of the BDD, varying from linear to exponential. In this paper, an evolutionary algorithm named genetic algorithm has been proposed for minimization of shared ordered BDDs by finding the optimal input variable ordering that aims to minimize the node count using evolutionary algorithm. The proposed algorithm gives upto 73.4% less nodes for multi-input adders.

A 10‐bit pipelined analogue‐to‐digital converter (ADC) at a sampling rate of 100 MS/s utilising only metal–oxide–semiconductor (MOS) transistors is presented and designed in 1.8 V 0.18 μm standard digital complementary MOS (CMOS) n‐well technology. The internal gain of value 2 of the intermediate stages is achieved by using a charge‐pump‐based concept that avoids the use of power‐area inefficient operational amplifier. All the capacitors are realised by capacitors implemented by metal–oxide–semiconductor field‐effect transistors (MOSCAPs) that allows easy integration with any inexpensive standard digital CMOS technology, and altogether giving low area‐power‐cost solution. A low DC gain CMOS differential amplifier in source follower configuration is used and low gain effects are calibrated digitally in the background. Peak differential non‐linearity (DNL) improves from −1/+0.27 least significant bit (LSB) to −0.43/+0.57 LSB and peak integral non‐linearity (INL) is reduced from −9.56/...

The numerical simulation of lead-free all-perovskite tandem solar cell using solar capacitance one dimensional tool (SCAPS 1D) has been performed. The combination of methyl ammonium germanium halide (CH 3 NH 3 GeI 3) as wide band-gap (1.9 eV) perovskite layer and FA 0.75 MA 0.25 Sn 0.25 Ge 0.5 I 3 (FAMASnGeI 3) as a low band-gap (1.4 eV) perovskite layer is considered for the first time which shows the optimal device efficiency of 26.72%. The present work studies the effect of the different electron transport layer, perovskite absorber thickness and its defect density on photovoltaic performance. Further, the effect of front electrode work function on the device photovoltaic performance is also studied. It has been observed that the device open circuit voltage (Vo C) is significantly affected by the built-in voltage (V bi) across the perovskite layer. In addition, the effect of thickness of the perovskite absorber layers is also investigated. Moreover, the effect of defect density of the absorber layer is also explored, and it has been found that for better device performance the defect density needs to be as low as possible. Furthermore, it has been observed that the work function of the front contact plays a significant role and for the proposed device its value should not be more than 4.4 eV. The proposed all-perovskite tandem solar cell shows the remarkable photovoltaic parameters i.e., open circuit voltage (V OC) = 1.07 Volts, short circuit current density (J SC) = 28.36 mA/cm 2 , fill factor (FF) = 84.39% and efficiency (η) = 26.72%.

Diabetic Retinopathy is a dangerous eye disease and the most common cause of blindness for worldwide population. Digital color fundus images are becoming very important as they help in diagnosing Diabetic Retinopathy. With this fact new image processing techniques can be applied to improve automatic detection of diabetic retinopathy. Segmentation, feature extraction, enhancement, image classification, pattern matching are the major image processing elements in detecting eye diseases . Microaneurysms are the primary sign of DR, therefore necessary preprocessing step for a correct diagnosis to automatically detect the microaneurysms in fundus image is an algorithm. For detecting the microaneurysms in retina images this review paper aims to develop and test a new method.

This work presents a fully differential CMOS amplifier consisting of two self-biased gain boosted inverter stages, that provides an alternative to the power hungry operational amplifier. The self-biasing avoids the use of external biasing circuitry, thus reduces the die area, design efforts, and power consumption. In the present work, regulated cascode technique has been employed for gain boosting. The Miller compensation is also applied to enhance the phase margin. The circuit has been designed and simulated in 1.8 V 0.18 µm CMOS technology. The simulation results show a high DC gain of 100.7 dB, Unity-Gain Bandwidth of 107.8 MHz, and Phase Margin of 66.7<sup>o</sup> with a power dissipation of 286 μW and makes it suitable candidate for the high resolution pipelined ADCs.

SAR-ADC is best suited for low power applications where power has a trade-off with speed. Use of redundant circuitry reduces the on chip area making it cost effective. DAC is one of the components of SAR-ADC that introduces error voltage due to mismatch and consumes large power other than comparator. Low power DAC architectures have been studied and analysed. To account for capacitor mismatch issues self-calibration techniques have been discussed and analysed for 14-bit DAC implementation. All the architectures have been analysed for 100KS/s with 1.6MHz clock speed in 180nm technology with supply voltage of 1.8V. EDA tool used for design analysis is Cadence® Spectre®.

This study describes the highly-digital 4-bit 200 MS flash analogue to digital converter (ADC) whose major part can be digitally synthesised thus achieving low power, reducing the time-to-market and is scalable with technology. The comparators used in the ADC consist of complementary metal-oxide-semiconductor (CMOS)-based inverter and NAND-NOR as standard cells. The complete flash ADC is designed in 180 nm CMOS technology with 1.8 V supply with the power consumption of 4.51 mW. The signal-to-noise and distortion ratio, signal-to-noise ratio and spurious-free dynamic range are equal to 23.3, 25.2 and 30.1 dB. It provides an effective number of bits equal to 3.5. The differential non-linearity (DNL) of this ADC is ± 0.25 LSB and integral non-linearity (INL) is + 0.6 LSB.

Electrocardiogram (ECG) signal processing and analysis is becoming more and more popular as it is useful in diagnosis and prognosis of human heart and clinically automatic machine estimation is based upon it. R-peak is the most important component in ECG beat and is widely used to investigate normal and abnormal subjects (patients). From the last few decades, R-peak detection in ECG has been the most challenging topic in the biomedical research. As QRS complex has high frequency in ECG as compared to other waves (P, T, U-wave), so majority of algorithms estimate QRS complex by either filtering or suppressing the lower frequency waves, including various artifacts like baseline wander, power line interference, and electromyograph noises. This paper demonstrates a new kind of ECG denoising algorithm based on self-convolution window (SCW) concept. The SCW based on Hamming window, herein referred to as Hamming self-convolution window, is used to design a new kind of filter which possesses negligible ripples in the stop band, as compared to the conventional window-based filters. This algorithm is validated on MIT-BIH arrhythmia database and the results outperform in terms of sensitivity, positive predictivity, and error rate obtained as 99.93%, 99.95%, and 0.117%, respectively, as compared to the other well-established works. The approach has also outperformed the results of well-established window-based filters (Hamming and Kaiser) in terms of reduced false negative, false positive, and error rate.

Semisupervised text classification has become a major focus of research over the past few years. Hitherto, most of the research has been based on supervised learning, but its main drawback is the unavailability of labeled data samples in practical applications. It is still a key challenge to train the deep generative models and learn comprehensive representations without supervision. Even though continuous latent variables are employed primarily in deep latent variable models, discrete latent variables, with their enhanced understandability and better compressed representations, are effectively used by researchers. In this paper, we propose a semisupervised discrete latent variable model for multi-class text classification and text generation. The proposed model employs the concept of transfer learning for training a quantized transformer model, which is able to learn competently using fewer labeled instances. The model applies decomposed vector quantization technique to overcome problems like posterior collapse and index collapse. Shannon entropy is used for the decomposed sub-encoders, on which a variable DropConnect is applied, to retain maximum information. Moreover, gradients of the Loss function are adaptively modified during backpropagation from decoder to encoder to enhance the performance of the model. Three conventional datasets of diversified range have been used for validating the proposed model on a variable number of labeled instances. Experimental results indicate that the proposed model has surpassed the state-of-the-art models remarkably.

In this paper, we propose a new approach for performing edgepreserving image filtering. This paper deals with wavelet decomposition, local linear Stein’s unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a 6 db better PSNR and minimum Standard Deviation algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various applications, including noise reduction.

This paper presents a design methodology of a two stage fully differential telescopic operational amplifier. Similar analysis is carried out for the two stage folded cascode operational amplifier and results are compared at 180 nm technology node. Here effort is made to make the unity gain frequency and the slew rate same of both the respective two stage amplifiers. The purpose of such an effort is to carry out a comparison of various parameters viz. voltage gain, phase margin, common mode rejection ratio (CMRR), power supply rejection ratio (PSRR), output swing and power consumption. It has been observed that the two stage telescopic amplifier gives better results in terms of voltage gain, CMRR, PSRR as compared to folded cascade counterpart. Whereas the folded cascode two stage gives better results in terms of bandwidth and output swing limit. Furthermore, it is also seen that the two stage telescopic amplifier is more suitable for low power applications.

In this paper as my base paper introduces:-6 Correct detection of external defects on potatoes is the key technology in the realization of automatic potato grading and sorting station. This paper reports a novel inspection approach to external defects of potato in three potato cultivars. Adaptive Intensity Interception (AII) and Fixed Intensity Interception (FII) methods have been proposed to extract the suspect defects. Otsu segmentation combined with morphologic operation was used to remove the normal skin and background. Area threshold and black ratio threshold were used to identify defects in the suspect defects. Experiments have shown FII performed better than AII in a specific circumstance. The correct classification rate of defects, the correct recognition rate of defects and the correct inspection rate of potatoes based on FII are 92.1%, 91.4% and 100% respectively. The results showed this approach was fast, valid and convenient for defect detection on yellow-skin potatoes.

The authors investigate the performance of various diversity combining schemes in Internet of Things- Cognitive Radios (IOT-CR) system under the influence of co-channel interference limited environment. An approximate expression for probability density function (PDF) of maximum signal to interference ratio (SIR) at the receiver has been derived. By utilizing the derived PDF, closed loop expressions for Average post processing SIR, Ergodic capacity and Average bit error rate (ABER) have been derived. The proposed CR system is studied and analyzed under the impact of Peak transmit power (PTP) and Peak interference power (PIP) constraints. The achieved result shows that the Optimum combining (OC) at the receiver outperforms the traditional combining schemes in co-channel interference (CCI) scenario.

In this paper, we demonstrate the performance analysis of an underlay MIMO cognitive radios employing space time block coding at secondary's user transmitter (SU-Tx) and generalized selection combining at secondary's user receiver. The transmit power strategy enforces the SU-Tx to adapt its power to be transmitted so as to protect primary user's receiver from harmful interference in order to satisfy primary user outage constraint. We derive closed form expressions for average post processing signal to noise ratio and ergodic capacity. Moreover, approximate expression for average bit error rate is also obtained. Based on the achieved results, we show that the average post processing SNR, Ergodic Capacity and average BER improve as number of best branches to be combined increases. Finally analytical results are affirmed through Monte Carlo simulations. Keywords Cognitive radio (CR) Á Generalized selection combining (GSC) Á Space time block coding (STBC) Á Multiple-input-multiple-output (MIMO)