Notes

Figuring out CT structure top features of individual deep excess fat to judge metabolic issues along with surgery-induced weight loss results.
e., the noised signal contributed by multiply-scattered photons and the background illuminance in the frame of our approach. Moreover, this study has also revealed that the developed method is capable of getting accurate measurements and reconstructions of translucent objects when the background illumination exists, which has been considered as a challenging issue for 3D surface measurement and reconstruction of translucent objects.Autonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications [...].The use of Software-Defined Networking (SDN) in the communications of the Industrial Internet of Things (IIoT) demands more comprehensive solutions than those developed to date. The lack of an SDN solution applicable in diverse IIoT scenarios is the problem addressed in this article. The main cause of this problem is the lack of integration of a set of aspects that should be considered in a comprehensive SDN solution. To contribute to the solution of this problem, a review of the literature is conducted in this article, identifying the main requirements for industrial networks nowadays as well as their solutions through SDN. This review indicates that aspects such as security, independence of the network technology used, and network centralized management can be tackled using SDN. All the advantages of this technology can be obtained through the implementation of the same solution, considering a set of aspects proposed by the authors for the implementation of SDNs in IIoT networks. Additionally, after analyzio the development of a comprehensive solution that is not focused on the characteristics of a specific scenario and would, therefore, be applicable in limited situations.The incidence of cardiovascular diseases and cardiovascular burden (the number of deaths) are continuously rising worldwide. Heart disease leads to heart failure (HF) in affected patients. Therefore any additional aid to current medical support systems is crucial for the clinician to forecast the survival status for these patients. The collaborative use of machine learning and IoT devices has become very important in today's intelligent healthcare systems. This paper presents a Public Key Infrastructure (PKI) secured IoT enabled framework entitled Cardiac Diagnostic Feature and Demographic Identification (CDF-DI) systems with significant Models that recognize several Cardiac disease features related to HF. To achieve this goal, we used statistical and machine learning techniques to analyze the Cardiac secondary dataset. The Elevated Serum Creatinine (SC) levels and Serum Sodium (SS) could cause renal problems and are well established in HF patients. The Mann Whitney U test found that SC and SS levels affectedmmended features have possible effects on clinical practice and would be supportive aid to the existing medical support system to identify the possibility of the survival status of the heart patient. The doctor should primarily concentrate on the follow-up month, SC, EF, CPK, and platelet count for the patient's survival in the situation.Inductor-capacitor voltage controlled oscillators (LC-VCOs) are the most common type of oscillator used in sensors systems, such as transceivers for wireless sensor networks (WSNs), VCO-based reading circuits, VCO-based radar sensors, etc. This work presents a technique to reduce the LC-VCOs phase noise using a new current-shaping method based on a feedback injection mechanism with only two additional transistors. This technique consists of keeping the negative resistance seen from LC tank constant throughout the oscillation cycle, achieving a significant phase noise reduction with a very low area increase. To test this method an LC-VCO was designed, fabricated and measured on a wafer using 90 nm CMOS technology with 1.2 V supply voltage. The oscillator outputs were buffered using source followers to provide additional isolation from load variations and to boost the output power. The tank was tuned to 1.8 GHz, comprising two 1.15 nH with 1.5 turns inductors with a quality factor (Q) of 14, a 3.27 pF metal-oxide-metal capacitor, and two varactors. The measured phase noise was -112 dBc/Hz at 1 MHz offset. Including the pads, the chip area is 750 × 850 μm2.Along with the rapid development of sensing systems and wireless transmission technology, the scope of application of the IoT has substantially increased, and research and innovation that integrate artificial intelligence. This study integrated civil engineering and electrical engineering to establish a universal and modularized long-term sensing system. Aiming at positive construction in civil engineering, the campus of National Taipei University of Technology was used as the experimental site as a green campus. This paper focused on the cooling effect of the green roof and the temperature difference of the solar panel to effectively isolate the direct sunlight on the roof of the building. To achieve long-term monitoring, energy consumption must be minimized. Considering that the distance between sensor nodes in the experimental site was over dozens of feet, LoRa transmission technology was selected for data transmission. LoRa only consumes a small amount of energy during data transmission, and it can freelyy set according to the research purposes, precision requirements of the sites, and the measurement scope, thereby enabling their application in more fields.Population-scale and rapid testing for SARS-CoV-2 continues to be a priority for several parts of the world. We revisit the in vitro technology platforms for COVID-19 testing and diagnostics-molecular tests and rapid antigen tests, serology or antibody tests, and tests for the management of COVID-19 patients. Within each category of tests, we review the commercialized testing platforms, their analyzing systems, specimen collection protocols, testing methodologies, supply chain logistics, and related attributes. Our discussion is essentially focused on test products that have been granted emergency use authorization by the FDA to detect and diagnose COVID-19 infections. Different strategies for scaled-up and faster screening are covered here, such as pooled testing, screening programs, and surveillance testing. The near-term challenges lie in detecting subtle infectivity profiles, mapping the transmission dynamics of new variants, lowering the cost for testing, training a large healthcare workforce, and providing test kits for the masses. Through this review, we try to understand the feasibility of universal access to COVID-19 testing and diagnostics in the near future while being cognizant of the implicit tradeoffs during the development and distribution cycles of new testing platforms.This paper presents a metamaterial (MTM)-integrated high-gain rectenna for RF sensing and energy harvesting applications that operates at 2.45 GHz, an industry, science, medicine (ISM) band. The novel MTM superstrate approach with a three-layered integration method is firstly introduced for rectenna applications. The integrated rectenna consists of three layers, where the first layer is an MTM superstrate consisting of four-by-four MTM unit cell arrays, the second layer a patch antenna, and the third layer a rectifier circuit. By integrating the MTM superstrate on top of the patch antenna, the gain of the antenna is enhanced, owing to its beam focusing capability of the MTM superstrate. Vorinostat manufacturer This induces the increase of the captured RF power at the rectifier input, resulting in high-output DC power and high entire end-to-end efficiency. A parametric analysis is performed in order to optimize the near-zero property of the MTM unit cell. In addition, the effects of the number of MTM unit cells on the performance of strated MTM-integrated rectenna will provide new possibilities for practical energy harvesting applications with improved antenna gain and efficiency in various IoT environments.This paper proposes a Gaussian mixture model-based (GMM) bearing fault band selection (GMM-WBBS) method for signal processing. The proposed method benefits reliable feature extraction using fault frequency oriented Gaussian mixture model (GMM) window series. Selecting exclusively bearing fault frequency harmonics, it eliminates the interference of bearing normal vibrations in the lower frequencies, bearing natural frequencies, and the higher frequency contents that prove to be useful only for anomaly detection but do not provide any insight into the bearing fault location. The features are extracted from time- and frequency- domain signals that exclusively contain the bearing fault frequency harmonics. Classification is done using the Weighted KNN algorithm. The experiments performed with the data containing the vibrations recorded from artificially damaged bearings show the positive effect of utilizing the proposed GMM-WBBS signal processing to filter out the discriminative data of uncertain origin. All comparison methods retrofitted with the proposed method demonstrated classification performance improvements when provided with vibration data with suppressed bearing natural frequencies and higher frequency contents.Electrochemical impedance spectroscopy (EIS) is a powerful technique used for the analysis of interfacial properties related to bio-recognition events occurring at the electrode surface, such as antibody-antigen recognition, substrate-enzyme interaction, or whole cell capturing. Thus, EIS could be exploited in several important biomedical diagnosis and environmental applications. However, the EIS is one of the most complex electrochemical methods, therefore, this review introduced the basic concepts and the theoretical background of the impedimetric technique along with the state of the art of the impedimetric biosensors and the impact of nanomaterials on the EIS performance. The use of nanomaterials such as nanoparticles, nanotubes, nanowires, and nanocomposites provided catalytic activity, enhanced sensing elements immobilization, promoted faster electron transfer, and increased reliability and accuracy of the reported EIS sensors. Thus, the EIS was used for the effective quantitative and qualitative detections of pathogens, DNA, cancer-associated biomarkers, etc. Through this review article, intensive literature review is provided to highlight the impact of nanomaterials on enhancing the analytical features of impedimetric biosensors.Indoor air temperature belongs to the most important climatic variables in indoor climate research, affecting thermal comfort, energy balance, and air movement in buildings. This paper focuses on measurement errors when using thermocouples in indoor temperature measurements, with special attention on measurements of air temperature. We briefly discuss errors in thermocouple measurements, noting that, for temperatures restricted to indoor temperature ranges, a thermocouple Type T performs much better than stated in "standards". When thermocouples are described in the literature, industrial applications are primarily considered, involving temperatures up to several hundred degrees and with moderate demands on accuracy. In indoor applications, the temperature difference between the measuring and the reference junction is often only a few degrees. Thus, the error contribution from the thermocouple itself is almost immeasurable, while the dominant error source is in the internal reference temperature compensation in the measuring instrument.
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