Influence of High-k Passivation Layer on Gate Field Plate AlGaN/GaN/AlGaN Double Heterojunction HEMT

Silicon - In this work, we have analysed the influence of passivation material such as Silicon dioxide (SiO2), Silicon Nitride (Si3N4), Aluminium oxide (Al2O3), Hafnium Silicon Oxide (HfSiO4),...     

Review: Heart Diseases Detection by Machine Learning Classification Algorithms

Most human deaths are caused by heart diseases. Such diseases cannot be efficiently detected for the lack of specialized knowledge and experience. Data science is important in healthcare sector for the role it plays in bulk data processing. Machine learning (ML) also plays a significant part in disease prediction and decision-making in medical care industry. This study reviews and evaluates the ML approaches applied in heart disease detection. The primary goal is to find mathematically effective ML algorithm to predict heart diseases more accurately. Various ML approaches including Logistic Regression, Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), t-Distributed Stochastic Neighbor Embedding (t-SNE), Nave Bayes, and Random Forest were utilized to process heart disease dataset and extract the unknown patterns of heart disease detection. An analysis was conducted on their performance to examine the effecacy and efficiency. The results show that Random Forest out-performed other ML algorithms with an accuracy of 97%.     

Effect of Oxygen Flow Rate on Structural,Electrical and Optical Properties of Zinc Aluminum Oxide Thin Films Deposited by DC Magnetron Sputtering

Semiconductors - Zinc Aluminum Oxide thin films were deposited on glass substrates by reactive DC magnetron sputtering method by varying oxygen flow rates from 1 to 4 sccm. Glancing angle X-ray...     

Multi-level image thresholding using Otsu and chaotic bat algorithm

Multi-level thresholding is a helpful tool for several image segmentation applications. Evaluating the optimal thresholds can be applied using a widely adopted extensive scheme called Otsu’s thresholding. In the current work, bi-level and multi-level threshold procedures are proposed based on their histogram using Otsu’s between-class variance and a novel chaotic bat algorithm (CBA). Maximization of between-class variance function in Otsu technique is used as the objective function to obtain the optimum thresholds for the considered grayscale images. The proposed procedure is applied on a standard test images set of sizes (512 × 512) and (481 × 321). Further, the proposed approach performance is compared with heuristic procedures, such as particle swarm optimization, bacterial foraging optimization, firefly algorithm and bat algorithm. The evaluation assessment between the proposed and existing algorithms is conceded using evaluation metrics, namely root-mean-square error, peak signal to noise ratio, structural similarity index, objective function, and CPU time/iteration number of the optimization-based search. The results established that the proposed CBA provided better outcome for maximum number cases compared to its alternatives. Therefore, it can be applied in complex image processing such as automatic target recognition.

     

Provable secure lightweight hyper elliptic curve‐based communication system for wireless sensor networks

It is widely believed that hyper elliptic curve cryptosystems (HECCs) are not attractive for wireless sensor network because of their complexity compared with systems based on lower genera, especially elliptic curves. Our contribution shows that for low cost security applications HECs cryptosystems can outperform elliptic curve cryptosystems. The aim of this paper is to propose a discrete logarithm problem‐based lightweight secure communication system using HEC. We propose this for different genus curves over varied prime fields performing a full scale study of their adaptability to various types of constrained networks. Also, we propose to evaluate the performance of the protocol for computational times with respect to different genus for main operations like Jacobian, Divisor identifications, key generation, signature generation/verification, message encryption, and decryption by changing the size of the field. A formal security model was established based on the hardness of HEC‐Decision Diffie‐Hellman (HEC‐DDH). Finally, a comparative analysis with ECC‐based cryptosystems was made, and satisfactory results were obtained.     

Switching Transient Analysis and Characterization of an E-Mode B-Doped GaN-Capped AlGaN DH-HEMT with a Freewheeling Schottky Barrier Diode (SBD)

Journal of Electronic Materials - This paper presents a systematic study of Al0.23Ga0.77N/GaN/AlxGa1?xN double-heterojunction high-electron-mobility transistors (DH-HEMTs) with a boron-doped...     

Particle swarm optimized multiple regression linear model for data classification

This paper presents a new data classification method based on particle swarm optimization (PSO) techniques. The paper discusses the building of a classifier model based on multiple regression linear approach. The coefficients of multiple regression linear models (MRLMs) are estimated using least square estimation technique and PSO techniques for percentage of correct classification performance comparisons. The mathematical models are developed for many real world datasets collected from UCI machine repository. The mathematical models give the user an insight into how the attributes are interrelated to predict the class membership. The proposed approach is illustrated on many real data sets for classification purposes. The comparison results on the illustrative examples show that the PSO based approach is superior to traditional least square approach in classifying multi-class data sets.     

Optical investigations on Tb3+ doped l-Histidine hydrochloride mono hydrate single crystals grown by low temperature solution techniques

The potential nonlinear optical material of Terbium (Tb³⁺) ion doped l-Histidine hydrochloride monohydrate (LHHC) single crystals were successfully grown. Tb³⁺:LHHC crystals of 7 mm × 5 mm × 3 mm and 59 mm length and 15 mm diameter have been grown by the slow solvent evaporation and Sankaranarayanan-Ramasamy (SR) techniques respectively. The grown crystals were characterized by single crystal X-ray diffraction analysis to confirm the crystalline structure and morphology. High resolution X-ray diffraction (HRXRD) studies revealed that the SR grown sample shows relatively good crystalline nature with 9″ full-width at half-maximum (FWHM) for the diffraction curve. Functional groups were identified by Fourier transform infra-red spectroscopy (FTIR). The optical transparency and band gaps of grown crystals were measured by UV–Vis spectroscopy. Thermogravimetric and differential thermal analysis (TG/DTA) studies reveal that the crystal was thermally stable up to 155 °C in SR grown crystal. Surface morphology of the growth plane was observed using scanning electron microscopy (SEM). The incorporation of Tb ion was estimated by EDAX. The frequency-dependent dielectric properties of the crystals were carried out for different temperatures. Vickers hardness study carried out on (1 0 0) face at room temperature shows increased hardness of the SR method grown crystal. Second harmonic generation efficiency of SEST and SR grown crystals are 3.2 and 3.5 times greater than that of pure KDP. The Photoluminescence (PL) studies of Tb³⁺ ions result from the radiative intra-configurational f-f transitions that occur from the ⁵D₄ excited state to the ⁷F_j (j = 6, 5, 4, 3) ground states. The decay curve of the ⁵D₄ level of emission was observed with a long life time of 319.2041 μs for the SR grown Tb³⁺:LHHC crystal.