Recently, the widespread deployment of smart phones globally, biomedical diagnostics. Smartphone-based devices are expected to be commonly used Intelligent Health Tracking Point-of-Care (PoC) Internet of Medical Things (IoMT) applications. As a result, this paper presents a smartphone-based blood lipid data acquisition dongle for measuring blood lipid levels such as TC, HDL-C, and triglycerides (TG). Blood loss in the fingertip to manage coronary artery disease. A thin photochemical during detection. The test strip, composed of LEDs and detectors, is plugged into a small dongle where the colour switches. The intensities of the calculated reflective coefficient of the lipide determinant are indicated. The product of chromogenics. Such photochemical data acquisition data dongle was focused on smart phones. Validated and achieved a correlation coefficient above 0.843 by reference to a clinical analyzer and summed. 5.017 per unit variance coefficient (CV) for 93 blood lipid patients assessment. The photochemistry Therefore, dongle is promising for the potential treatment of IoMT chronic diseases.

The present research work explores the consequence of eco-friendly sodium bicarbonate treatment on drilling behavior of jute fiber reinforced polyester composites. The fiber surface treatment was done by immersing the jute fibers in sodium bicarbonate solution (10 wt.%) for five days at room temperature. The raw and treated jute fiber composites were produced through compression molding process. The drilling behavior was expressed in terms of delamination factor (at entry and exit) and surface finish. The response surface methodology coupled with three factors—three levels Box–Behnken Design was used to study the interactive effects of process variables (drill diameter, feed, and cutting speed) on delamination factor and surface finish. Furthermore, the significance of the developed model was examined through analysis of variance. The chip morphology of the fabricated composites was examined to assess the quality of the drilled hole. The fractography analysis of the machined surface has also been carried using scanning electron microscopy. The outcomes revealed that the sodium bicarbonate treatment of jute fiber improved the machinability of the composites.

No abstract

The proposed domino logic is developed with the combination of Current Comparison Domino (CCD) logic and Conditional High Speed Keeper (CHSK) domino logic. In order to improve the performance metrics like power, delay and noise immunity, the redesign of CHSK is proposed with the CCD. The performance improvement is based on the parasitic capacitance, which reduces on the dynamic node for robust and rapid process of the circuit. The proposed domino logic is designed with keeper and without keeper to measure the performance metrics of the circuit. The outcomes of the proposed domino logic are better when compared to the existing domino logic circuits. The simulation of the proposed CHSK based on the CCD logic circuit is carried out in Cadence Virtuoso tool. Keywords:Conditional INTRODUCTIONThe Complementary Metal Oxide Semiconductor (CMOS) technology becomes a major part in advanced process of Very Large Scale Integration (VLSI) applications. It increases the leakage current, shows improvement in scaling and enhances the sensitivity which makes the factor fluctuations as barriers of scaling technology in CMOS. As per the improvement of wireless portable systems with the speed of microprocessors and less budget on power the VLSI circuit is rapidly integrated. In the transistor technology, the supply of power simultaneously scaled down and achieves less consumption of power and faster. As well as the threshold voltage is lesser in the similar proportionate. The threshold voltage scaling in exponential provides less immune of noise and improves the sub threshold leakage current in the transistor. In the dynamic node, the dynamic capacitance and supply voltage of domino logic reduces the storage of charges. As per the synchronized factor, the technology scaling is deceased by the substantially of domino gate immunity noise. The high leakage makes the system as difficult due to parallel process of the path evaluation.The wide fan-in domino has become difficult if there is high immunity of noise and leakage. It happens due to the parallel process and the charge leakage from the node of pre-charge. In the dynamic node, the keeper transistor is prevented by employing the undesired discharging because of charge sharing and leakage current of pull down network. It processes during the phase of evaluation and progresses the robustness by upsizing between the network evaluation and transistor. Also it enhances the delay of the circuit, shows improvement in power consumption and performance. Therefore, the delay and power are considered by compromising the leakage current, upsizing the keeper and noise improvement. The keeper ratio (K) is defined as the ratio of the product of electron mobility and aspect ratio of the keeper transistor to the product of hole mobility and aspect ratio of the evaluation network.

Though artificial intelligence (AI) has been used in nuclear medicine for more than 50 years, more progress has been made in deep learning (DL) and machine learning (ML), which have driven the development of new AI abilities in the field. ANNs are used in both deep learning and machine learning in nuclear medicine. Alternatively, if 3D convolutional neural network (CNN) is used, the inputs may be the actual images that are being analyzed, rather than a set of inputs. In nuclear medicine, artificial intelligence reimagines and reengineers the field’s therapeutic and scientific capabilities. Understanding the concepts of 3D CNN and U-Net in the context of nuclear medicine provides for a deeper engagement with clinical and research applications, as well as the ability to troubleshoot problems when they emerge. Business analytics, risk assessment, quality assurance, and basic classifications are all examples of simple ML applications. General nuclear medicine, SPECT, PET, MRI, and CT may benefit from more advanced DL applications for classification, detection, localization, segmentation, quantification, and radiomic feature extraction utilizing 3D CNNs. An ANN may be used to analyze a small dataset at the same time as traditional statistical methods, as well as bigger datasets. Nuclear medicine’s clinical and research practices have been largely unaffected by the introduction of artificial intelligence (AI). Clinical and research landscapes have been fundamentally altered by the advent of 3D CNN and U-Net applications. Nuclear medicine professionals must now have at least an elementary understanding of AI principles such as neural networks (ANNs) and convolutional neural networks (CNNs).