The electronic and optical properties of silicon-doped tetragonal hafnium dioxide (t-HfO2) have been investigated by using the meta-generalized gradient approximation (MGGA-TB09 + c) approach within the framework of density functional theory (DFT). Silicon (Si) is assumed to be the most effective dopant among all other investigated dopants to support the t-HfO2 phase as well as it improves the required properties of high-k gate dielectric oxides. The unique characteristics of this material are closely associated with the inclusion of dopants within the supercell. The primary objective of this study is to examine and compare various features distinguished by their doping percentages of Si as 0%, 6.25%, 12.50%, and 18.75% respectively. Ground state features such as lattice parameters and volume are computed and compared to existing experimental and theoretical data. A comprehensive theoretical investigation of bandgap, and dielectric properties is also computed here. This analysis not only yielded an experimental bandgap of the material as 5.83 eV but also revealed a notable reduction in the bandgap of Si-doped crystal structures. Further, the optical properties are also computed which reveals a visible isotropic spectrum phenomenon, that is attributed to the inherent electronic configuration of the Si dopant. A significant increase in the static dielectric constant is seen for the Si-doped structures, accompanied by a shift in the absorption spectra at a specific wavelength, which enables optical absorption within the visible range. The experimental results demonstrated a simultaneous rise in the real component of the refractive index and a significant enhancement in optical conductivity. These findings indicate that Si-doped t-HfO2 can be a promising material for applications as negative capacitance field effect transistors and in future-generation memory devices.

The electronic and optical properties of Si-doped t-HfO2 have been investigated using the MGGA-TB09+c method within the DFT framework. Silicon is considered the most efficient dopant among all examined dopants for stabilizing the t-HfO2 phase. This work primarily aims to investigate the optoelectronic properties of t-HfO2 with 6.25, 12.50, and 18.75

This paper introduces a novel reduced reference image quality assessment technique called “MULF RR-IQA.” The technique is based on the assumption that the marginal distribution of wavelet coefficients within each subband can be accurately modeled by a Gaussian distribution. In our proposed method, we first extract features, including the marginal distributions of neighboring coefficients and entropy in the wavelet domain. These extracted features are then combined, and the image quality is predicted using a similarity measure. We validate the performance of the proposed approach on the widely recognized LIVE Image database, demonstrating a strong correlation between the human evaluations and the objective scores obtained from the proposed method.

Here, the investigation of various properties of the rarest studied phase (Brookite) of titanium dioxide (TiO _2 ) is done. We have found these properties using two distinct approaches, namely the self-consistent Orthogonalized Linear Combination of Atomic Orbitals (OLCAO) with Generalized Gradient Approximation (GGA) and Meta-GGA (MGGA) under the framework of Density Functional Theory (DFT). Considering the optimal c value, the bandgap value is calculated using the MGGA approach. MGGA calculations are much closer to the experimental value than the GGA approach. However, the optical properties obtained using MGGA are lower than the GGA approach, especially the dielectric constant and refractive index. Absorption for brookite TiO _2 was observed in the U.V. region using both methods. E.M. spectrum shifted to a lower value by MGGA. A comparison of the two methods reveals that MGGA provides a more comprehensive description of the optical characteristics and electronic structure than GGA. Investigation done here is helpful to find applicability of brookite TiO _2 in Solar Cells.

Diverse applications in today's digital era have a high demand for low-power, faster, and high-performance arithmetic circuits. In a multiplier, the power is the costliest part of carrying out partial products. A compressor type of adder is used for faster operation and has lesser power consumption. In this paper, a low-power, energy-efficient 4:2 compressor design has been presented. The proposed design is based on multi-threshold logic. A capacitive network has been used at the input side instead of resistors for better circuit operations. The CNFET-based network is used to design the same. Powers, delay, PDP, and EDP of the proposed design have been computed. It is observed that with 32nm CNFET technology it shows a maximum improvement in PDP and EDP of 69% and 70%, respectively. Moreover, extensive performance analyses against power supply, channel length, temperature, load, and operating frequency have been presented. Finally, the proposed compressor is applied to design Wallace's multiplier which shows that it outperforms all other designs considered in this study. This indicates that the proposed compressor is quite useful for low-power VLSI circuits and systems applications.

Density functional theory (DFT) calculations are carried out on pure and doped rutile TiO _2 . The bandgap (E _g ) for pristine, S-doped, Fe-doped, and Fe/S co-doped materials is direct, with values of 2.98 eV, 2.18 eV, 1.58 eV, and 1.40 eV. The effective mass of charge carriers (m*) and ratio of effective masses of holes to effective masses of electrons (R) are also investigated, and it is discovered that Fe/S co-doped materials have the lowest charge carrier recombination rate. The Fe/S co-doped material has the highest ε (ω ) . α (ω ) of doped materials shifted into the visible range. Due to the high dopant concentration in Fe and Fe/S-doped cases, the E _g is lowered to a relatively small value; hence, only pristine and S-doped materials are verified as electron transport layer (ETL). A solar cell device analysis employing pure and S-doped rutile TiO _2 as ETL is completed using DFT-derived parameters in SCAPS-1D modeling software for the first time. For the optimized solar cells, current–voltage (IV) characteristics, quantum efficiency (QE), capacitance-voltage (CV) characteristics, and capacitance-frequency (Cf) characteristics are provided. The aim of the present study is to improve efficiency of perovskite solar cell by doping as well as to improve accuracy of simulation by applying DFT extracted parameters as input. From the analysis, improvement is found in efficiency of doped TiO _2 compared to un-doped TiO _2 . The efficiency of the PSC with S-doped ETL is 1.418

The effect of silver (Ag) and gold (Au) doping at a concentration of 8.33% on the electronic and optical properties of the LiNbO3 crystal was theoretically analyzed using density functional theory (DFT). The results showed that LiNbO3 exhibits a non-magnetic semiconductor property, which is consistent with experimental evidence described in the literature. Ag and Au doping at a concentration of 8.33% had no impact on the semiconductor behavior. However, a significant decrease in band gap energy was found when compared to pure LiNbO3. The results of this study show that LiNbO3 can be successfully used in a variety of technical fields, including spintronic. This can pave the way for additional studies and research into these materials.

Gate-all-around Tunnel Field Effect Transistors (GAA-TFETs) have been designed with the objective to reduce leakage current and to maintain high Ion/Ioff ratio. In this chapter, the influence of dielectric pocket's inclusion to GAA-TFET is investigated on its various performance parameters. Based on the results obtained through simulation, it is found that am bipolarity and OFF-state leakage conduction get notably reduced in GAA-TFET when dielectric pocket (DP) of any dielectric material either high and low-k is included to GAA-TFET. In a way, the ambipolarity is found to be minimum in GAA-TFET with high-k DP when it is compared with the rest of the two structures. Moreover, it is also observed that this reduction in OFF-state leakage and ambipolarity is obtained without getting ON-state characteristics like subthreshold swing and ION deteriorated. To achieve improved performance parameters, important dimensions of dielectric pockets like thickness and length have been optimized and found to be4 and 30 nm, respectively. The impact of DP's k-valueon various analog/HF parameters in DP-GAA-TFET is also analyzed in this work and found that GAA-TFET with low-k DP may offersuperior HF performances than those of GAA-TFET without DP and with high-k DP.

The electronic and optical properties of pure and Ag-Au co-doped lithium niobate crystals are calculated by using density functional theory (DFT). The obtained results indicate that lithium niobate exhibits a non-magnetic semiconducting nature. The co-doping percentage of 8.33% did not change the semiconducting nature of the crystal. However, a significant reduction in the band gap was found in the co-doped structure. For both pure and co-doped structures, the optical properties including dielectric function, refractive index, extinction coefficient, and reflectivity were calculated and thoroughly examined.

The effect of lanthanum (La) and Scandium (Sc) doping on the structural, electronic, and optical properties of cubic hafnium oxide (c-HfO2) has been thoroughly investigated using density functional theory (DFT). The spin-polarized calculations have been performed using the MGGA-TB09 + c exchange–correlation functional. In this study, 6.25

This paper describes a newly-created image database termed as the NITS-IQA database for image quality assessment (IQA). In spite of recently developed IQA databases, which contain a collection of a huge number of images and type of distortions, there is still a lack of new distortion and use of real natural images taken by the camera. The NITS-IQA database contains total 414 images, including 405 distorted images (nine types of distortion with five levels in each of the distortion type) and nine original images. In this paper, a detailed step by step description of the database development along with the procedure of the subjective test experiment is explained. The subjective test experiment is carried out in order to obtain the individual opinion score of the quality of the images presented before them. The mean opinion score (MOS) is obtained from the individual opinion score. In this paper, the Pearson, Spearman and Kendall rank correlation between a state-of-the-art IQA technique and the MOS are analyzed and presented.

Structural and optoelectronic properties of monoclinic hafnium dioxide (m-HfO2) are explored and studied using density functional theory (DFT). For the computation, OLCAO-MGGA-TB09+c exchange-correlation has been used. The electronic properties such as band diagram and both densities of state (DOS) are analyzed in depth. The bandgap value obtained using MGGA-TB09+c exchange-correlation is 5.73 eV. In addition, we analyzed the different optical properties such as dielectric function, refractive index, extinction coefficient, reflectivity, optical conductivity, energy loss function, and absorption coefficient of the m-HfO2 compound and observed that the results so obtained greatly matches with previously reported computational and experimental data. It is found that the MGGA-TB09 technique gives good results on all properties compared to existing computational work.

Multilevel thresholding is widely used in brain magnetic resonance (MR) image segmentation. In this article, a multilevel thresholding-based brain MR image segmentation technique is proposed. The image is first filtered using anisotropic diffusion. Then multilevel thresholding based on particle swarm optimization (PSO) is performed on the filtered image to get the final segmented image. Otsu function is used to select the thresholds. The proposed technique is compared with standard PSO and bacterial foraging optimization (BFO) based multilevel thresholding techniques. The objective image quality metrics such as Peak Signal to Noise Ratio (PSNR) and Mean Structural SIMilarity (MSSIM) index are used to evaluate the quality of the segmented images. The experimental results suggest that the proposed technique gives significantly better-quality image segmentation compared to the other techniques when applied to T2-weitghted brain MR images.

This paper presents a method of classifying five varieties of Basmati rice grains (including a non-Basmati rice) using three different types of features namely, the morphological, color and texture. The classification process has been carried out on two different kinds of images of rice. One type of image where rice grains are scattered and isolated whereas, in other case, bulk rice grain images are taken. From the isolated rice images, only the morphological features were extracted. Again, from the bulk rice images, color and texture features were extracted. Two classification methods, namely, the SVM and BPNN classifiers have been adopted here to classify the rice grains. It is seen that the Color and Texture features give better results compared to morphological features alone. From the experimental results, it can be observed that the maximum accuracy achieved is 96.4% with BPNN classifier.

In 1928, Lilienfeld filed a patent on a device named as "device for controlling current", which was later called as metal-oxide semiconductor field-effect transistor (MOSFET). In 1965, Gordon E. Moore published a paper entitled "Cramming More Components onto Integrated Circuits" in Electronics magazine. Scaling of MOSFETs may be defined as the process of reducing the device dimensions and interconnecting wires in such a manner that the functionality of integrated circuits (ICs) does not change. In Spin FETs, the gate is used to regulate the spin direction of charge carriers with the help of Rashba spin–orbit interaction, whereas in spin-MOSFETs, the gate works exactly the same as in conventional MOS devices to switch on/off the current in the channel. In contrast to classical mechanics, particles, such as electrons and holes, are treated as a wave function in quantum mechanics, which penetrate through the potential barrier rather than terminating on a finite potential barrier as considered in classical mechanics.

IoT-based smart home automation has drawn massive attention these days and is of great interest to the research communities in the last few decades. The main goal of any home automation system is to reduce the cost, increase comfort in life and achieve a reliable system. With a vast growth in embedded systems, the cost of various automation devices has been reduced, and by implementing IoT, the communication between users and appliances has become easy. With this backdrop, a smart home automation system is developed here with the use of embedded systems and IoT, a user-friendly Wi-Fi integrating ESP8266 and Raspberry pi modules. This system consists of inbuilt Wi-Fi technology for wireless communication and to control various appliances like fans, lamps, televisions, etc. This system uses an L298N Motor Driver and 4-channel relay modules for switching AC and DC home appliances. The proposed system is operated with an Android based application known as "Blynk" which provides an easy-to-use GUI for the user. Blynk IoT is a visual programming platform that establishes a direct wireless connection between user and controller. As the application is an open-source platform, there is an increase in demand for the Blynk application. Many sensors can be connected to establish a real-time application.

In this paper sensor fusion methodology along with odometry and motion estimation for autonomous vehicles (AVs) using Light Detection and Ranging (LiDAR) and camera is explored. Since during bad weather conditions, dim light or night time the sensor may not give very good readings, odometry can used in such situations. Odometry gives an estimation of change in position of given vehicle using data from sensors. The study also examines the impact of Extended Kalman Filter (EKF) to reduce error in position estimate of the vehicle both before and after using odometry through a KITTI data-set on vehicle motion.

On pure and metal, non-metal, co-doped rutile TiO2, DFT simula- tions are performed. For the stability study of doped materials, the defect formation energies of non-metal (S), metal (Fe), and metal and non-metal (Fe/S) co-doped materials are determined. A Ti- rich environment is preferable over an O-rich environment. With values of 2.98 eV, 2.18 eV, 1.58 eV, and 1.40 eV, the bandgap for pristine, S-doped, Fe-doped, and Fe/S co-doped materials is found to be direct. The effective masses (m*) and ratios (R) of charge carriers are also examined, and it is discovered that Fe/S co-doped material has the lowest charge carrier recombination rate. The maximum static dielectric constant is found in the Fe/S co-doped material. Doped material’s absorption spectra shifted into the vis- ible region. Additionally, using SCAPS-1D simulation software, a complete solar cell device study using these materials as ETL is performed for the first time. The absorber layer and the ETL settings have been tweaked to perfection. Current-voltage (IV) characteristics, quantum efficiency (QE), capacitance-voltage (CV) characteristics, and capacitance-frequency (Cf) character- istics are provided for optimize solar cells.When the smallest degree of defect for each layer is taken into account, the solar cell with Fe/S co-doped ETL has the highest efficiency of 34.27%.

This paper presents classification of five different types of milled rice grain using various texture feature extraction models. Four different gray level based texture features extraction techniques are discussed in this work. The classification task is performed using an adaptive threshold back propagation neural network. The above four texture feature extraction techniques are compared with that of the proposed gray-level-size-zone matrix based rotation invariant texture model. The classification outcome of the proposed texture features extraction model is also validated through publicly available texture dataset from Brodatz’s database. Results show that classification task based on the proposed texture model is able to achieve higher accuracy both in rice and standard data as compare to other four different texture features extraction techniques discussed in this work. Results also show that back propagation neural network provides better accuracy of 99.4% when compared with other statistical classifiers presented in this work.