Wireless Sensor Networks (WSNs) are applicable in numerous domains, including industrial automation where WSNs may be used for monitoring and control of industrial plants and equipment. However, the ...requirements in the industrial systems differ from the general WSN requirements. In recent years, standards have been defined by several industrial alliances. These standards are specified as frameworks with modifiable parts that can be defined based on the particular application of WSN. However, limited work has been done on defining industry-specific protocols that could be used as a part of these standards. In this survey, we discuss representative protocols that meet some of the requirements of the industrial applications. Since the industrial applications domain in itself is a vast area, we divide them into classes with similar requirements. We discuss these industrial classes, set of common requirements and various state-of-the-art WSN standards proposed to satisfy these requirements. We then present a broader view towards the WSN solution by discussing important functions like medium access control, routing, and transport in detail to give some insight into specific requirements and the classification of protocols based on certain factors. We list and discuss representative protocols for each of these functions that address requirements defined in the industrial classes. Security function is discussed in brief, mainly in relation to industrial standards. Finally, we identify unsolved challenges that are encountered during design of protocols and standards. In addition some new challenges are introduced and discussed.
The coronavirus disease 2019 (COVID‐19) pandemic has led to a significant increase in the consumption of the internet for work, leisure time activities, and has also generated substantial amounts of ...anxiety, and uncertainty, which has lead individuals to spend a lot of time surfing the internet for the latest news on developments in the COVID‐19 crisis. This ends up as scrolling or surfing through a lot of pessimistic news items. This search for information during COVID‐19 is apparently influenced by a number of cognitive biases as well as mediated by poor affect regulation skills. Thus, there is a need to address these cognitive biases and promote affect regulation strategies across health settings.
Semiconductor-based direct conversion X-ray sensors have widespread applications spanning from medical diagnosis to industrial inspection. However, current findings on X-ray detection based on ...perovskites shows high sensitivity but exhibit large leakage current and poor stability, thus, inhibiting them from commercialization. Highly stable AgBiS2 with large attenuation coefficient (μ = 3.07 g cm−2 at 70 keV), shows excellent charge conversion due to its higher atomic number (Bi, Z = 83), and density (ρ = 7.02 g cm−3) was used for X-ray detection. Here, we approach to enhance the net sensitivity of AgBiS2 by tailoring all three parameters by segregating micro/ nanocrystals of cerium oxide (CeO2) at the AgBiS2 grain boundary (GB) region. From the X-ray impinged photocurrent response, substantial GB segregation of n-CeO2 at the AgBiS2 interface leads to improved attenuation and promotes the conversion of multiple scattered X-ray photons into electrons by interacting with the adjacent grains, thus resulting in enhanced photocurrent generation. The sensitivity (S) and noise equivalent dose (NED) ratio were calculated to determine the lowest detectivity of the sensor with less generated noise signals. From these experimental findings, 10 % of n-CeO2 segregation leads to an improvement in the sensitivity of AgBiS2 to 29 μC mGy−1 cm−3.
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•X-ray sensors were fabricated with micro/ nano CeO2 segregated AgBiS2 thick films.•Multiple scattered X-ray photons at the AgBiS2 grain boundary region were effectively utilized by nano CeO2 grains, resulting in higher charge carrier generation.•X-ray impinged photocurrent measurement revealed nano CeO2:AgBiS2 presents record sensitivity 29.3 μC mGy−1 cm−3 for 7.97 mGy dose.
Lead-free magnetoelectric (ME) composites with remarkable ME coupling are required for the realization of eco-friendly multifunctional devices. This work demonstrates the ME properties of ...Ba0.85Ca0.15Zr0.1Ti0.9O3–CoFe2O4 (BCZT–CFO) core–shell composites synthesized via co-sol–gel technique. Room temperature ferroelectric and ferromagnetic characterization have shown that the samples are magnetic and ferroelectric along with an adequate magnetoelectric coupling of 12.15mV/(cmOe). The strong dependence of electric parameters on applied magnetic DC bias fields demonstrated in ferroelectric and magnetoelectric measurements provide a framework for the development of potential magnetoelectric devices. Also, the high sensitivity of magnetoelectric coupling towards the applied AC magnetic field can be used for its application in magnetoelectric sensors.
•The magnetoelectric multiferroic BCZT–CFO nanocomposite is synthesized via sol–gel route.•The XRD measurements show no phases other than BCZT and CFO.•The microstructure analysis employing TEM indicates that the majority of particles formed are having core–shell structure.•The capacitance, resistance and ferroelectric polarization are magnetically tunable.•The composite showed a high magnetoelectric response.
Bleaching and softening of the hard fiber "Coir" renders it suitable for use in the coir industry, which presently adopts various chemical treatment processes that are not eco-friendly. The present ...study aims at treatment of coir fibers with Averrhoa bilimbi for enhanced bleaching and softening. The quality of the treated fibers with respect to physical and chemical characterization viz. variation in lignin content, flexural rigidity to assess the degree of softness, light fastness, tensile strength and brightness index has been carried out. The treated fibers displayed remarkable increase in brightness index from 9.45 to 11.19. Removal of surface projections on the coir fiber upon treatment is evident from Scanning Electron Microscope images. These surface changes can be attributed to the fiber softening.
The upsurge of stemphylium blight disease noticed during recent cropping years is the prime global threat for lentil (
Lens culinaris
Medik.) production. Identification of factors that influence ...lentil yield with the help of an advanced regression model will speed up the progress of lentil crop improvement for biotic stress tolerance. In this context, an experiment was undertaken to identify the key control factors of lentil yield under stemphylium blight stress. The field experiment was laid out under alpha lattice design using fifty lentil genotypes with two replications. An advanced dimension reduction cum regression approach Partial Least Square Regression (PLSR) was employed to mitigate the effect of multi-collinearity among 23 yield-influencing traits along with traditional Stepwise Multiple Linear Regression (SMLR). The results of SMLR analysis indicated that pods per plant, number of seeds per pod, hundred seed weight, superoxide dismutase and pod yield per plant had considerable effects on seed yield per plant with the R-squared value of 0.940. The first four PLSR components were considered to be optimum which were cumulatively explained 93.10% of the total variance towards lentil seed yield. The trait pods per plant was recorded with the highest PLSR regression coefficient devoid of multi-collinearity effects among the independent yield attributing variables under stemphylium blight environment and hence concluded to be the most influencing trait towards lentil seed yield followed by seeds per pod, hundred seed weight, pod yield per plant and superoxide dismutase.
It is a challenging problem and a little-researched subject that has recently gotten increased attention in the scientific community to identify items on drone footage. The shooting height and angle ...change when using a drone because the camera's position is not fixed during the shot, in addition to the weather and lighting circumstances. Offering a hybrid deep learning model for object detection that can aid in search and rescue operations is the goal of this research. The three working stages of this unique technique are pre-processing, feature extraction, and object recognition. First, the videos are turned into image frames, and then an improved region-based convolution neural network was used to detect objects in those frames (RCNN). Consequently, improved LGBP (Local Gabor Binary Pattern) features were also recovered from those images together with traditional ResNet and SIFT (scale-invariant feature transform) features. In the object recognition phase, the proposed African Vulture Updated Honey Badger Optimization (AVUHBO) will be applied to optimize the weight parameters of hybrid neural networks such as Bi-GRU and LSTM for object recognition based on the retrieved features. This optimization model boosts the classifier's performance to produce better results. In contrast to other approaches, our suggested AVUHBO achieves higher accuracy ratings of 0.91, 0.9, 0.91, and 0.9, while SHO only manages lower accuracy ratings of 0.84, 0.85, 0.87, and 0.88. This proves that our proposed AVUHBO can provide accurate object detection. The findings of the proposed object detection methodology are then compared to those of other existing techniques.
The paper attempts to analyze the effect of transverse magnetic field on flow over a backward-facing inclined step using the open-source CFD solver OpenFOAM. The equations governing the ...two-dimensional, incompressible, laminar, electrically conducting flow are discretized and solved using the PISO algorithm. The simulations are conducted for various backward step angles (
10
∘
≤
α
≤
90
∘
) and Hartmann Numbers (
0
≤
M
≤
30
) at fixed kinematic (
Re
) and magnetic (
R
e
m
) Reynolds Numbers of 100 and 0.04 respectively. The influence of step angle and Hartmann number on the reattachment length is explored with the help of streamlines, streamwise pressure gradient, and velocity profiles.
The present work is planned to investigate the fundamental properties of the novel plant fiber extracted from the bark of Acacia nilotica L. tree. The various chemical compositions of the Acacia ...nilotica L. fiber (ANF) such as cellulose (56.46 wt. %), hemicelluloses (14.14 wt. %), lignin (8.33 wt. %) and ash content (4.95 wt. %) were identified through the chemical analysis. The maximum degradation temperature of ANF (339°C) was determined by the thermogravimetric analysis. The crystallinity index (44.82%) and crystalline size (3.21 nm) of the ANF were calculated by the X-ray diffraction analysis. The surface topography of ANF was estimated through the atomic force microscope. The density of ANF was identified as a value of 1165 kg/m3 which is comparatively lower than the other renowned fibers such as Acacia leucophloea (1385 kg/m3) and Jute (1460 kg/m3); this would be confirmed with all above characterization results that is an appropriate material to fabricate the green composites.
In the present study, the effect of deposition temperature in the range 773–973 K on structural and nanomechanical properties of lanthanum zirconate (La2Zr2O7) ceramic coatings deposited on ...Inconel-718 substrates by EB-PVD process has been investigated. X-ray diffraction and Raman spectroscopy were used to understand the structural details of lanthanum zirconate coatings. Structural studies show that the coatings have defect fluorite structure and are textured at the highest deposition temperature of 973 K. Increase in the surface roughness as a result of increased crystallite size was discussed from SEM and AFM analyses. Scratch test showed higher adhesion strength of the coating with the substrate for the film deposited at higher deposition temperature. Nanoindentation studies indicated that higher deposition temperature leads to enhanced indentation hardness and modulus of the coatings. From the nanoindentation results, resistance to plastic deformation and elastic recovery were also determined to explain the suitability of the lanthanum zirconate as a top coat material for thermal barrier coatings.
•La2Zr2O7 coatings were prepared by EBPVD as a function of deposition temperature.•Decreasing lattice parameters was explained on the basis of vacancy concentration.•Growth process was explained using Volmer-Weber model.•Improved adhesion strength for the coatings deposited at 973 K.•Coatings deposited at 973 K showed enhanced nanomechanical properties.
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