Estimation of bit error rate in 2×2 and 4×4 multi-input multi-output-orthogonal frequency division multiplexing systems

Multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems with multiple input antennas and multiple output antennas in dynamic environments face the challenge of channel estimation. To overcome this challenge and to improve the performance and signal-to-noise ratio, in this paper we used the Kalman filter for the correct estimation of the signal in dynamic environments. To obtain the original signal at the receiver end bit error rate factor plays a major role. If the signal to noise ratio is high and the bit error rate is low then signal strength is high, the signal received at the receiver end is almost similar to the ith transmitted signal. The dynamic tracking characteristic of Kalman filter is used to establish a dynamic space-time codeword and a collection of orthogonal pilot sequences to prevent interference among transmissions in this paper. Using the simulation, the Kalman filter method can be compared to the other channel estimation method presented in this paper that can track time-varying channels rapidly

Waste Moringa oleifera seed pods as green sorbent for efficient removal of toxic aquatic pollutants

© 2018 Elsevier Ltd In the present study, biosorption of chromium (Cr(VI)) ions and Naphthol blue black (NBB) dye using Moringa oleifera seed pods powder (MPP) as green biosorbent was investigated. Three different sizes of MPP viz. fine fraction (\u3c53 \u3eμm), coarse fraction (\u3e250 μm) and mixed fraction were investigated. The biosorbent was characterized by pHzpc, Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM) in order to get an insight of the surface charge, functional groups, and morphology of the biosorbent, respectively. The biosorption studies were conducted with Cr(VI) and NBB dye and different parameters, such as solution pH, contact time, initial concentration of the pollutant, adsorbent dosage and co-existing ions were examined. Experimental results revealed that the maximum removal of Cr(VI) and NBB dye was observed at pH 1 and 2, respectively and the equilibrium was achieved in ca. 180 min. The removal efficiency of Cr(VI) by fine, mixed and coarse fraction was 91.8, 74.9, 52.6%, respectively, whereas for NBB dye, the removal efficiency for the same fractions was 97.5, 33.6, 18.9%, respectively. The removal efficiency of Cr(VI) and NBB dye was influenced in the presence of competing ions. The biosorption isotherm and kinetic data were best correlated with Langmuir isotherm and pseudo-second order kinetic model, respectively. Column studies were also conducted with MPP by studying different flow rates and adsorbates concentrations to check the practical applicability of MPP in removing target metal and dye pollutants

Growth of CuS Nanostructures by Hydrothermal Route and Its Optical Properties

CuS nanostructures have been successfully synthesized by hydrothermal route using copper nitrate and sodium thiosulphate as copper and sulfur precursors. Investigations were done to probe the effect of cationic surfactant, namely, Cetyltrimethylammonium bromide (CTAB) on the morphology of the products. A further study has been done to know the effect of reaction time on the morphology of CuS nanostructures. The FE-SEM results showed that the CuS products synthesized in CTAB were hexagonal plates and the samples prepared without CTAB were nanoplate like morphology of sizes about 40–80 nm. Presence of nanoplate-like structure of size about 40–80 nm was observed for the sample without CTAB. The synthesized CuS nanostructures were characterized by X-ray diffraction (XRD), FE-SEM, DRS-UV-Vis spectroscopy, and FT-IR spectroscopy. A possible growth mechanism has been elucidated for the growth of CuS nanostructures

Оцінка виготовлення пристроїв від FET до CFET: огляд

Напівпровідникова промисловість розвивається з кожним днем, щоб задовольнити потреби суспільства. З розвитком технологій щільність транзисторів в мікросхемі зростає, щоб підвищити продуктивність, зберігаючи при цьому розмір. Завдяки мініатюризації транзисторів за останні десятиліття, технічний прогрес не стоїть на місці. Інтенсивне масштабування планарного MOSFET перервало еру нанорозмірних приладів через значні ускладнення, пов'язані зі збільшенням паразитної ємності, підпороговим струмом витоку, більш тонкими оксидами затвора, що спонукало дослідників розробити та впровадити нові пристрої з підвищеною ефективністю при низьких параметрах потужності та зменшеними короткоканальними ефектами (SCEs). У цій оглядовій статті було досліджено та проаналізовано нещодавній технологічний попит на польові транзистори (FETs) з декількома затворами. Пристрої з декількома затворами демонструють кращі характеристики, ніж звичайні FETs через їх крутий підпороговий схил, менший струм витоку та відмінні електростатичні властивості навіть при нанометровій довжині каналу. Польові транзистори з потрійним затвором (TG FETs) і польові транзистори з горизонтальним розташуванням каналів та круговим затвором (GAA FETs) додатково покращують керування затвором у каналі. Використовуючи технологію з декількома затворами на основі FinFET, контроль затвора над каналом може бути покращено разом із зменшенням паразитних ємностей. Щоб вивчити переривання у дослідженнях, проблеми технологій FinFET також були розглянуті разом із впровадженням нових пристроїв. Нанолисти та розгалужені листи добре вирішують ці проблеми, оскільки структури затворів накладаються одна на одну, щоб сформувати структуру з декількома затворами, яка підтримує покращений контроль затвора над каналом, тоді як CFET вводить 3D масштабування шляхом "складання" nFET поверх pFET, використовуючи всі можливості масштабування пристрою в 3D просторі.Semiconductor industry is advancing day by day to meet the needs of society. As technology grows, the transistor density in an IC increases to augment the performance keeping down the size. Due to the miniaturization of transistors over the past decades, technological progress is in great demand. Vigorous scaling of a planar MOSFET has outaged its nanoscale era due to significant complications associated with increased parasitic capacitance, subthreshold leakage current, thinner gate oxides, which led the researchers to develop and innovate new devices with improved efficiency at low power parameters and reduced short channel effects (SCEs). In this review article, recent technological demand for FETs with multiple gates has been explored and reviewed with advancements. Devices with multiple gates show better performance than conventional FETs due to their steep subthreshold slope, lower leakage current and excellent electrostatic properties even in nanometer regime channel lengths. A triple gate FET and a gate all around FET further improve gate control over the channel. Using FinFET based multi-gate technology, gate control over the channel charge could be increased along with a reduction in parasitic capacitances. To explore the discontinuity of research, the challenges of FinFET technologies have also been addressed along with the introduction of emerging devices. Nanosheets and forksheets address these problems well, as gate structures are stacked on top of each other to form a multiple gate structure that supports enhanced gate control over the channel, whereas C-FET introduces 3D scaling by „folding‟ the nFET on top of the pFET by exploiting the full edge possibilities of device scaling in 3D

Static Hand Gesture Recognition Using Novel Convolutional Neural Network and Support Vector Machine

Hand tracking and identification through visual means pose a challenging problem. To simplify the identification of hand gestures, some systems have incorporated position markers or colored bands, which are not ideal for controlling robots due to their inconvenience. The motion recognition problem can be solved by combining object identification, recognition, and tracking using image processing techniques. A wide variety of target detection and recognition image processing methods are available. This paper proposes novel CNN-based methods to create a user-free hand gesture detection system. The use of synthetic techniques is recommended to improve recognition accuracy. The proposed method offers several advantages over existing methods, including higher accuracy and real-time hand gesture recognition suitable for sign language recognition and human-computer interaction. The CNN automatically extracts high-level characteristics from the source picture, and the SVM is used to classify these features. This study employed a CNN to automatically extract traits from raw EMG images, which is different from conventional feature extractors. The SVM classifier then determines which hand gestures are being made. Our tests demonstrate that the proposed strategy achieves superior accuracy compared to using only CNN

Simulation and Analysis of Piezoelectric Energy Harvester with Various Proof-Mass Geometries

This paper aims to generate electricity, by decreasing fossil fuels consumption and conserving electricity for further use.  In this project, the method is to produce pollution-free electricity using the technique i.e. piezoelectric effect technique. By applying mechanical stress electric charge is generated known as the piezoelectric effect.  A sufficient amount of energy is produced as it can reduce the damage of pollution caused by power plants. So to make the use of moving vehicles on road, power generated helps the environment last longer.  Different shape, proof mass geometries are analyzed and plotted a graph between frequency versus voltage and electrical energy. Among them, it is identified that stacked cylindrical block has a good Voltage of 2.04mV (milliVolts = 10-3V) and Energy of 21.2fJ (femtoJoule = 10-15J). &nbsp

Detection of Depression Using Machine Learning Algorithms

Online media outlets such as Facebook, Twitter, and Instagram have forever altered our reality. People are now more connected than ever before, and they have developed such a sophisticated identity. According to ongoing research, there is a link between excessive usage of social media and depression. A mood illness is known as depression. It's defined as sadness, loss, or anger that interferes with a person's day-to-day activity. For different people, depression expresses itself in a number of ways. It might cause disturbances in your daily routine, resulting in missed time and lower productivity. It can also affect relationships as well as some chronic conditions. It has evolved into a serious disease in our generation, with the number of those affected increasing by the day. Some people, on the other hand, can confess that they are depressed, while others are utterly ignorant. On the other hand, the great majority Social media has evolved into a "diary," allowing them to share their mental condition

Removal of cationic and anionic heavy metals from water by 1D and 2D-carbon structures decorated with magnetic nanoparticles

Abstract In this study, cobalt ferrites (C) decorated onto 2D material (porous graphene (PG)) and 1D material (carbon nanofibers (CNF)), denoted as PG-C and CNF-C nanocomposites, respectively, were synthesized using solvothermal process. The prepared nanocomposites were studied as magnetic adsorbents for the removal of lead (cationic) and chromium(VI) (anionic) metal ions. The structural and chemical analysis of synthesized nanocomposites was conducted using different characterization techniques including Brunauer–Emmett–Teller (BET) analysis, field emission-scanning electron microscopy (FE-SEM), Fourier-transform infrared spectroscopy (FTIR), high resolution-transmission electron microscopy (HR-TEM), vibrating sample magnetometer (VSM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). Batch mode adsorption studies were conducted with the prepared nanocomposites to examine their maximum adsorption potential for lead and chromate ions. Performance parameters (time, pH, adsorbent dosage and initial ion concentrations) effecting the adsorption capacity of the nanocomposites were optimized. Different kinetic and isotherm models were examined to elucidate the adsorption process. Synthesized nanocomposites exhibited significant potential for the studied metal ions that can be further examined at pilot scale for the removal of metal ions from contaminated water

Face Mask Detection Using LabView

Rapid worldwide spread of Corona virus Disease 2019 (COVID 19) has resulted in a global pandemic. In present scenario due to covid-19, the mask has been an important part of our live for our safety as well as for the others safety so there is a need for efficient face mask detection applications in crowded areas like shopping malls, Public transportation etc. To ensure safety of the people in the surroundings. Face Mask Detection using NI LabVIEW. In this project a real-time system is developed to detect whether the person is wearing a mask or not by acquiring a real-time image of him through a Camera. The main challenges in detecting the mask are there are masks with various colors and patterns and secondly the background, light intensity are also the factors that affect the result. So, all these factors should be taken into consideration while developing the system in real-time. This system used for this application consists of vision development module. Vision development module helps to develop applications for machine vision and image processing applications we can use it with LabVIEW for real- time systems. A camera with good pixel quality is used for image acquisition. The captured image is of RGB format, it is difficult to analyze the image in this format, so it undergoes color plane extraction in this only a single plane of the image is considered which separates the mask from surroundings and results in a grey scale image for further processing. The image later is compared to a custom-made template dataset using pattern matching algorithm from vision assistant which helps to detect the mask region. overlaying techniques are used to highlight the mask region which shows that the person is wearing the mask