Monitoring water quality in reservoirs with IRS-1A-LISS-I

An attempt has been made to quantify the relationship between the variation in IRS-IA-LISS-I (Indian Remote Sensing Satellite-1A Linear Imaging Self-Scanning System) radiance data and field measured change in secchi disc depth. Secchi disc depth was measured for 47 predetermined sampling locations on reservoir surface water. At extinction depth (secchi depth), water samples were collected from all the sampling locations. Suspended sediments of eight locations representing various reaches of the reservoir were selected for mineralogical, particle size and optical properties analysis. The LISS-I radiance value in band 1 (0.45–0.52µm) band 2 (0-52–0.59 µm) and band 3 (0.62–0.68 µm) were used in a regression analysis. The absorption infrared band 4 (0.77–0.86 µm) was not included in the analysis. In these, the dependable variable was secchi depth (SD) and the LISS-I-radiance data was the estimator variable. Forty-seven data sets of 20 October 1988 from Tawa reservoir surface water were used to obtain an estimator equation for SD. The verification of the estimator equation was tested by applying it to a data set of 21 measurements of 28 September 1988 for this reservoir. The coefficient of correlation between observed and estimated values for the 28 September 1988 data set wasr=0.92 for SD, indicating that the equation could accurately predict the water clarity (SD) for this reservoir on new occasions from IRS-IA-LISS-I spectral data. It is shown that mineral composition and optical properties of suspended sediments influence the reflected radiance of water quality. It is concluded that IRS-IA-LISS-I data provide a useful means of mapping water quality in reservoir.     

Artificial intelligence techniques and their application in oil and gas industry

Artificial Intelligence Review - Data are being continuously generated from various operational steps in the oil and gas industry. The recordings of these data and their proper utilization have...     

Intrusion Detection System in Wireless Sensor Network Using Conditional Generative Adversarial Network

Wireless communication networks have much data to sense, process, and transmit. It tends to develop a security mechanism to care for these needs for such modern-day systems. An intrusion detection system (IDS) is a solution that has recently gained the researcher’s attention with the application of deep learning techniques in IDS. In this paper, we propose an IDS model that uses a deep learning algorithm, conditional generative adversarial network (CGAN), enabling unsupervised learning in the model and adding an eXtreme gradient boosting (XGBoost) classifier for faster comparison and visualization of results. The proposed method can reduce the need to deploy extra sensors to generate fake data to fool the intruder 1.2–2.6%, as the proposed system generates this fake data. The parameters were selected to give optimal results to our model without significant alterations and complications. The model learns from its dataset samples with the multiple-layer network for a refined training process. We aimed that the proposed model could improve the accuracy and thus, decrease the false detection rate and obtain good precision in the cases of both the datasets, NSL-KDD and the CICIDS2017, which can be used as a detector for cyber intrusions. The false alarm rate of the proposed model decreases by about 1.827%.

     

The synthesis of pixelated metamaterial cross polarizer using binary wind driven optimization algorithm

Microsystem Technologies - In this paper synthesis of two wideband Metamaterial Cross Polarizer (MCPs) is proposed. The synthesis of proposed MCPs is done by using Binary Wind Driven Optimization...     

A Comparative Investigation of Optical and Structural Properties of Cu-Doped CdO-Derived Nanostructures

In this report, we studied various structural and optical properties of pure and copper-doped cadmium oxide (CdO) thin films. Nanostructured Cu-doped CdO films were deposited using sol–gel spin-coating technique. The structural and morphological changes have been observed by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and atomic force microscopy (AFM) studies. The optical and electrical properties of the pure and Cu-doped CdO thin films were studied by UV–vis spectroscopy and four-point probe method, respectively. The XRD peaks show the formation of nanocrystalline CdO with cubic face-centered crystal structure. The band gaps of the as deposited films were found in the range of 2.32–2.73 eV, while after doping, it decreases due to structural deformation. The electrical resitivity was found to decrease approximately ～10 in Cu-doped CdO thin films.     

Simulation of driver fatigue monitoring via blink rate detection,using 65 nm CMOS technology

This paper proposes a system to detect and measure blink rate to determine fatigue levels. The method involved analysing specific frames to determine that a blink occurred, and then monitoring the time between successive blinks. The program was simulated in python using a Raspberry Pi Zero and a standard USB camera. For the blink rate detection block, a gate level schematic was implemented in Cadence software using 65 nm CMOS technology. The design was based around an asynchronous 6-bit based edge counter which was designed using D-flip-flops. The simulation calculated the average blink rate and compared this to the most recent blink rate. The outcome would determine if an alarm signal should be sent to the alarm. The system consumed 130 μA from a 1.2 V power supply.     

Microsegregation of oxygen in Zr-2.5Nb alloy materials

Oxygen partitioning between the primary-a andβ phases during heating at an(α + β) temperature was investigated in a Zr-2.5Nb alloy containing about 1100 ppm (wt) oxygen. Standard pressure tubes used in CANDU reactors have been produced from this material by hot extrusion of billets after preheating in the (α + β) temperature range. Secondary ion mass spectroscopy (SIMS) was found most suitable for oxygen mapping and for determining quantitatively the extent of preferential oxygen enrichment of primary-a grains in pressure tube samples previously subjected to experimental preheat treatments at an (α +β) temperature of 870° for different soak times up to 24 hours. For the (α α β)-treated materials, the oxygen concentration in the primary-a grains increased with soak time, reaching up to about 8 times the concentration in the primary-β matrix region. Samples from two standard pressure tubes with different fracture toughness properties were also examined. Signi-ficant differences between these tubes were found in their primary-α grain size and in the levels of oxygen enrichment of the a grains, which could provide an explanation for the difference in the toughness of these tubes.     

New Organic Nonlinear Optical Polyene Crystals and Their Unusual Phase Transitions

A series of new nonlinear optical chromophores based on configurationally locked polyenes (CLPs) with chiral pyrrolidine donors are synthesized. All CLP derivatives exhibit high thermal stability with decomposition temperatures T_d at least > 270 °C. Acentric single crystals of enantiopure D ‐ and L ‐prolinol‐based chromophores with a monoclinic space group P2₁ exhibit a macroscopic second‐order nonlinearity that is twice as large than that of analogous dimethylamino‐based crystal. This is attributed to a strong hydrogen‐bonded polar polymer‐like chain built by these molecules, which is aligned along the polar crystallographic b‐axis. Five α‐phase CLP crystals with different donors grown from solution exhibit a reversible or irreversible thermally induced structural phase transition to a β‐phase. These phase transitions are unusual, changing the crystal symmetry from higher to lower at increasing temperatures, for example, from centrosymmetric to non‐centrosymmetric, enhancing their macroscopic second‐order nonlinear optical properties.     

An Integrating Wide Dynamic-Range Image Sensor With a Logarithmic Response

An integrating CMOS image sensor with a wide dynamic range is described. The dynamic range of these pixels is controlled by a user-defined reference voltage that creates a photocurrent-dependent effective integration time. The operation of these pixels and a method of obtaining a well-controlled logarithmic response are both described. Furthermore, described are the results of two alternative methods of correcting the fixed pattern noise in these pixels and measurements of the temporal noise from individual pixels. These results show that with these pixels, it is possible to match the contrast sensitivity of the human visual system.