Showing 4 results for Singh
S. Singh, M. D. Upadhayay, S. Pal,
Volume 17, Issue 2 (June 2021)
Abstract
In this manuscript, higher-order Orbital Angular Momentum (OAM) modes and parameters affecting vortex in the radiation pattern have been studied. A uniform circular array resonating at 10 GHz frequency is formed using eight identical rectangular patch antennas. Three uniform circular arrays are analyzed, simulated, and fabricated for OAM modes 0, +1, and -1 respectively. The higher-order OAM modes ±2, ±3, and ±4 are simulated and their effects on radiation and phase pattern are discussed. The effect of number of antenna elements and radius of the circular array on the phase purity of higher order OAM modes is presented. The results of simulated radiation patterns and phase front are well satisfying the generation of OAM modes. The measured results show a close agreement with the simulated result.
S. V. Akram, R. Singh, A. Gehlot, A. K. Thakur,
Volume 17, Issue 4 (December 2021)
Abstract
Waste management is crucial for maintaining the hygienic environment in urban cities. The establishment of a reliable and efficient IoT system for waste management is based on integrating low power and long-range transmission protocol. Low Power Wide Area Network (LPWAN) is specially designed for the aforementioned requirement of IoT. LoRa (Long Range) is an LPWAN transmission protocol that consumes low power for long-range transmission. In this study, we are implementing long-range (LoRa) communication and cloud applications for real-time monitoring of the bins. The customized sensor node and gateway node are specifically designed for sensing the level of bins using ultrasonic sensor and communicating it to the cloud via long-range and internet protocol connectivity. Blynk and cayenne are the two cloud-based applications for storing and monitoring the sensory data receiving from the gateway node over internet protocol (IP). The customization of nodes6 and utilization of two cloud-based apps are the unique features in this study. In the future, we will implement blockchain technology in the study for enabling a waste-to-model platform.
Biswapriyo Sen, Maharishi Kashyap, Jitendra Singh Tamang, Sital Sharma, Rijhi Dey,
Volume 20, Issue 2 (June 2024)
Abstract
Cardiovascular arrhythmia is indeed one of the most prevalent cardiac issues globally. In this paper, the primary objective was to develop and evaluate an automated classification system. This system utilizes a comprehensive database of electro- cardiogram (ECG) data, with a particular focus on improving the detection of minority arrhythmia classes.
In this study, the focus was on investigating the performance of three different supervised machine learning models in the context of arrhythmia detection. These models included Support Vector Machine (SVM), Logistic Regression (LR) and Random Forest (RF). An analysis was conducted using real inter-patient electrocardiogram (ECG) records, which is a more realistic scenario in a clinical environment where ECG data comes from various patients.
The study evaluated the models’ performances based on four important metrics: accuracy, precision, recall, and f1-score. After thorough experimentation, the results highlighted that the Random Forest (RF) classifier outperformed the other methods in all of the metrics used in the experiments. This classifier achieved an impressive accuracy of 0.94, indicating its effectiveness in accurately detecting arrhythmia in diverse ECG signals collected from different patients.
Chhaya Belwal, Kunwar Singh, Shireesh Kumar Rai,
Volume 20, Issue 2 (June 2024)
Abstract
This paper introduces a floating flux-controlled meminductor emulator, implemented using two voltage differencing differential difference amplifier (VDDDA) along with a memristor and capacitor. Grounded and floating configurations are simulated with TSMC 0.18 µm level-49 BSIM3 CMOS process parameters in LTspice, showcasing the performance of the proposed circuits. The circuit features electronic tunability, allowing for the adjustment of nonlinear flux through the tuning of bias voltage. Simulation results validate the frequency-dependent current-flux dynamics of the proposed meminductor emulator. The simulation results, which involve frequency-dependent pinched hysteresis loops, transient analysis, non-volatility, and Monte Carlo analysis of the proposed meminductor, affirm the functionality and adequacy of the proposed design. A Chua’s oscillator is realized using proposed VDDDA-based meminductor as non-linear element.
