Design and analysis of RF MEMS shunt switch for V-band applications

Microsystem Technologies - In this paper, we have designed and simulations of RF MEMS shunt switch. The electro-mechanical and electromagnetic analysis of the switch have been done using COMSOL...     

Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals

Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals; these signals can be recorded, processed and classified into different hand movements, which can be used to control other IoT devices. Classification of hand movements will be one step closer to applying these algorithms in real-life situations using EEG headsets. This paper uses different feature extraction techniques and sophisticated machine learning algorithms to classify hand movements from EEG brain signals to control prosthetic hands for amputated persons. To achieve good classification accuracy, denoising and feature extraction of EEG signals is a significant step. We saw a considerable increase in all the machine learning models when the moving average filter was applied to the raw EEG data. Feature extraction techniques like a fast fourier transform (FFT) and continuous wave transform (CWT) were used in this study; three types of features were extracted, i.e., FFT Features, CWT Coefficients and CWT scalogram images. We trained and compared different machine learning (ML) models like logistic regression, random forest, k-nearest neighbors (KNN), light gradient boosting machine (GBM) and XG boost on FFT and CWT features and deep learning (DL) models like VGG-16, DenseNet201 and ResNet50 trained on CWT scalogram images. XG Boost with FFT features gave the maximum accuracy of 88%.     

Optimization of process parameters affecting surface roughness in magnetic abrasive finishing process

Development in manufacturing technology enhances the mechanical behavior of machined parts and improves the surface finish with high precision, which conveys the progressive importance of magnetic abrasive finishing (MAF) process. In current research work, magnetic abrasive particles were used as finishing tools during the MAF process. However, these magnetic abrasives are fabricated by special techniques, i.e., the adhesive bonding-based method, the sintering method, the plasma-based method and so on. The present study explores the basic finishing characteristics of the magnetic abrasive produced by the sintering process. After the sintering process, improved quality of magnetic abrasives was obtained, where the abrasive particle sticks on the base metal matrix. The abrasive particle used is alumina powder and the magnetic particle is iron powder. Experiments were performed on Stainless Steel 202 to inspect the sound effects of several process parameters such as rotational speed, electromagnet voltage, machining gap and abrasive particle size on machining performance. Apart from that, surface roughness was also measured, which revealed the influence of the abrasive particle on the machined surface in terms of surface finish. It is observed from this study that appropriate size of magnetic abrasive particle optimizes the surface finish.     

Utility of 18 F‐FDG PET/CT scan to diagnose the etiology of fever of unknown origin in patients on dialysis

Introduction: Studies on fever of unknown origin (FUO) in patients of chronic kidney disease and end stage renal disease patients on dialysis were not many. In this study, we used 18 F‐FDG PET/CT scan whole body survey for detection of hidden infection, in patients on dialysis, labelled as FUO. Methods: In this retrospective study, 20 patients of end stage renal disease on dialysis were investigated for the cause of FUO using 18F‐FDG PET/CT scan. All these patients satisfied the definition of FUO as defined by Petersdorf and Beeson. Any focal abnormal site of increased FDG concentration detected by PET/CT, either a solitary or multiple lesions was documented and at least one of the detected abnormal sites of radio tracer concentration was further examined for histopathology. Findings: All patients were on renal replacement therapy. Of these, 18 were on hemodialysis and two were on peritoneal dialysis. 18F‐FDG PET/CT scan showed metabolically active lesions in 15 patients and metabolically quiescent in five patients. After 18F‐FDG PET/CT scan all, but one patient had a change in treatment for fever. Anti‐tuberculous treatment was given in 15 patients, antibiotics in four patients and anti‐malaria treatment in one patient. Discussion: The present study is first study of 18F‐FDG PET/CT scan in patients of end stage renal disease on dialysis with FUO. The study showed that the 18 F FDG PET/CT scan may present an opportunity to attain the diagnosis in end stage renal disease patients on dialysis with FUO.     

Green synthesis of highly stable carbon nanodots and their photocatalytic performance

The present study reports a novel, facile, biosynthesis route for the synthesis of carbon nanodots (CDs) with an approximate quantum yield of 38.5%, using Musk melon extract as a naturally derived‐precursor material. The synthesis of CDs was established by using ultraviolet–visible (UV–vis) spectroscopy, Dynamic light scattering, photoluminescence spectroscopy, X‐ray diffraction, transmission electron microscopy and Fourier transform infrared (FTIR) spectroscopy. The as‐prepared CDs possess an eminent fluorescence under UV–light (λ _ex  = 365 nm). The size range of CDs was found to be in the range of 5–10 nm. The authors further explored the use of such biosynthesised CDs as a photocatalyst material for removal of industrial dye. Degradation of methylene blue dye was performed in a photocatalytic reactor and monitored using UV–vis spectroscopy. The CDs show excellent dye degradation capability of 37.08% in 60 min and reaction rate of 0.0032 min⁻¹. This study shows that synthesised CDs are highly stable in nature, and possess potential application in wastewater treatment.Inspec keywords: carbon, nanostructured materials, nanofabrication, catalysis, photochemistry, ultraviolet spectra, visible spectra, photoluminescence, X‐ray diffraction, transmission electron microscopy, Fourier transform infrared spectra, fluorescence, dyesOther keywords: green synthesis, highly stable CD, photocatalytic performance, biosynthesis route, carbon nanodots, quantum yield, Musk melon extract, naturally derived‐precursor material, ultraviolet‐visible spectroscopy, dynamic light scattering, photoluminescence spectroscopy, X‐ray diffraction, transmission electron microscopy, Fourier transform infrared spectroscopy, FTIR spectroscopy, fluorescence, biosynthesised CD, photocatalyst material, industrial dye, methylene blue dye degradation, photocatalytic reactor, UV‐vis spectroscopy, wastewater treatment, size 5 nm to 10 nm, time 60 min     

Indium selenide microrod films: chemical bath deposition from acidic bath

Films of indium selenide was deposited onto glass and indium tin oxide coated glass substrates in acidic medium using chemical bath deposition at room temperature. Indium sulphate and sodium selenosulphate were used as precursors of In³⁺ and Se^2?, respectively. The structural, surface morphological and optical properties of the deposited films were studied. Diffractograms in structural study revealed the deposited material is In₂Se₃ films. Controlled bath conditions resulted in the evolution of the In₂Se₃ microrod-like morphology. The optical band gap of the film was found to be 1.7 eV.     

Reinterpretable Imager: Towards Variable Post‐Capture Space,Angle and Time Resolution in Photography

We describe a novel multiplexing approach to achieve tradeoffs in space, angle and time resolution in photography. We explore the problem of mapping useful subsets of time‐varying 4D lightfields in a single snapshot. Our design is based on using a dynamic mask in the aperture and a static mask close to the sensor. The key idea is to exploit scene‐specific redundancy along spatial, angular and temporal dimensions and to provide a programmable or variable resolution tradeoff among these dimensions. This allows a user to reinterpret the single captured photo as either a high spatial resolution image, a refocusable image stack or a video for different parts of the scene in post‐processing. A lightfield camera or a video camera forces a‐priori choice in space‐angle‐time resolution. We demonstrate a single prototype which provides flexible post‐capture abilities not possible using either a single‐shot lightfield camera or a multi‐frame video camera. We show several novel results including digital refocusing on objects moving in depth and capturing multiple facial expressions in a single photo.     

Influence of pH on particle size and sensing response of chemically synthesized chromium oxide nanoparticles to alcohols

Nanoparticles of chromium oxide have been synthesized by following a co-precipitation route at various pH values of the precursor solution. Structural and morphological analysis were carried out by using XRD and TEM techniques which revealed that the size of nanoparticles synthesized at pH 9 was smaller as compared to those synthesized at other pH values. The thick films of synthesized samples were deposited on alumina substrate and their sensing response to methanol, ethanol and isopropanol was investigated at different operating temperatures. It was observed that all the sensors gave optimum response at 250 °C. It has been observed that sample prepared at pH 9, being a collection of smallest particles as compared to other samples, exhibited high sensing response to alcohol vapour. Sensor response of all the samples tested was significantly higher towards isopropanol vapour than towards methanol or ethanol.In the present study the effect of particle size on intergranular activation energy has been studied as well. It was found that smaller particles possess high activation energy and exhibit higher sensing response as compared to that of larger particles. This type of study may help in the selection of particle suitable for gas sensing.     

Lévy flight artificial bee colony algorithm

Artificial bee colony (ABC) optimisation algorithm is a relatively simple and recent population-based probabilistic approach for global optimisation. The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space. In the ABC, there is a high chance to skip the true solution due to its large step sizes. In order to balance between diversity and convergence in the ABC, a Lévy flight inspired search strategy is proposed and integrated with ABC. The proposed strategy is named as Lévy Flight ABC (LFABC) has both the local and global search capability simultaneously and can be achieved by tuning the Lévy flight parameters and thus automatically tuning the step sizes. In the LFABC, new solutions are generated around the best solution and it helps to enhance the exploitation capability of ABC. Furthermore, to improve the exploration capability, the numbers of scout bees are increased. The experiments on 20 test problems of different complexities and five real-world engineering optimisation problems show that the proposed strategy outperforms the basic ABC and recent variants of ABC, namely, Gbest-guided ABC, best-so-far ABC and modified ABC in most of the experiments.