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D.C conductivity of In2O3: SnO2 thin films and manufacturing of gas sensor
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Compounds were prepared from In2O3 doped SnO2 with different doping ratio by mixing and sintering at 1000oC. Pulsed Laser Deposition PLD was used to deposit thin films of different doping ratio In2O3: SnO2 (0, 1, 3, 5, 7 and 9 % wt.) on glass and p-type wafer Si(111) substrates at ambient temperature under vacuum of 10-3 bar thickness of ~100nm. X-ray diffraction and atomic force microscopy were used to examine the structural type, grain size and morphology of the prepared thin films. The results show the structures of thin films was also polycrystalline, and the predominate peaks are identical with standard cards ITO. On the other side the prepared thin films declared a reduction of degree of crystallinity with the increase of doping ratio. Atomic Force Microscopy (AFM) measurements show the average grain size exhibit to change in non-systematic manner with the increase of doping ratio with tin oxide. The average grain size increases at doping ratios 1, 5 and 7 % from 52.48 to 79.12, 87.57, and 105.59 nm respectively and decreases at residual doping ratio. The average surface roughness increases from 0.458 to 26.8 nm with the increase of doping ratio. The gas sensing measurements of In2O3:SnO2 thin films prepared on p-Si to NO2 gas showed good sensitivity and Maximum sensitivity (50) obtained for In2O3:SnO2 prepared on p-Si at operating temperature 573 K and doping ratio 7 % and 9 %. Maximum speed of response time (8 sec) at operating temperature 573 K and doping ratio 1 %.

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Sat Sep 03 2022
Journal Name
International Journal Of Health Sciences
Bioremediation of contaminated soil with hydrocarbons discharged from liquid petroleum gas filling refineries by Burkholdaria cepatia
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Commercial, industrial, and military activity, largely in the 19th and 20th centuries, have led to  environmental pollution that can threaten human health and ecosystem function, liquid gas petroleum (LPG) products are the major sources of energy for industry and daily life that cause environmental contamination during various stages of production, transportation, refining and use. Screening of bacterial isolate by using clear zone techniques and biomass and optical density. Results revealed that isolate Burkholdaria cepatia showed a high ability for hydrocarbons biodegradation and this isolate identified depending on morphological cultural, gram stain, microscopic features, biochemical tests, and VITEK2 compact.   In this study,

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Publication Date
Wed Jun 24 2020
Journal Name
Systematic Reviews In Pharmacy
Studies on the Photostability of Polystyrene Films with New Metals Complex of 1, 2, 4-triazole-3-thione Derivate
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The new complexes including Cu(II), Co(II), Ni(II), Pt(IV), and Pd(II) metals with 4,4'-(((1E,1'E)-1,4-phenylenebis(methaneylylidene))bis(azaneylylidene))bis(5-(4-chlorophenyl)-4H-1,2,4-triazole-3-thione) have been synthesized of utilizing us polystyrene (PS) photostability. The supplement (0,5 w / v%) was for the production of polystyrene ( PS) in the form of tetrahydrofuran (THF). Polystyrene films were exposing irradiation (250 – 380 nm) absorption light intensity of 6.02 x 10-9 ein dm-3 s-1 at room temperature, through the changes that occur to each of viscosity average molecular weight (Mv), main chain scission (S), degree of polymerization (DPn), weight loss %, hydroxyl index (lOH), carbonyl index (ICo) determined the photo stabiliz

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Dispersion in a Gas Filled Hollow Core Photonic Crystal Fiber
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Hollow core photonic bandgap fibers provide a new geometry for the realization and enhancement of many nonlinear optical effects. Such fibers offer novel guidance and dispersion properties that provide an advantage over conventional fibers for various applications. Dispersion, which expresses the variation with wavelength of the guided-mode group velocity, is one of the most important properties of optical fibers. Photonic crystal fibers (PCFs) offer much larger flexibility than conventional fibers with respect to tailoring of the dispersion curve. This is partly due to the large refractive-index contrast available in the silica/air microstructures, and partly due to the possibility of making complex refractive-index structure over the fibe

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Publication Date
Sat Sep 27 2014
Journal Name
Soft Computing
Multi-objective evolutionary routing protocol for efficient coverage in mobile sensor networks
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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Data Aggregation in Wireless Sensor Networks Using Modified Voronoi Fuzzy Clustering Algorithm
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Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

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Publication Date
Tue Jan 18 2022
Journal Name
Photonic Sensors
Arsenic Detection Using Surface Plasmon Resonance Sensor With Hydrous Ferric Oxide Layer
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Abstract<p>The lethality of inorganic arsenic (As) and the threat it poses have made the development of efficient As detection systems a vital necessity. This research work demonstrates a sensing layer made of hydrous ferric oxide (Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub>) to detect As(III) and As(V) ions in a surface plasmon resonance system. The sensor conceptualizes on the strength of Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub> to absorb As ions and the interaction of plasmon resonance towards the changes occurring on the sensing layer. Detection sensitivity values for As(III) and As(V) were 1.083 °·ppb<sup>−1</sup> and 0.922 °·ppb<jats></jats></p> ... Show More
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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Refractive index sensor based on a solid-core photonic crystal fiber interferometer
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Photonic crystal fiber interferometers are widely used for sensing applications. In this work, solid core-Photonic crystal fiber based on Mach-Zehnder modal interferometer for sensing refractive index was presented. The general structure of sensor applied by splicing short lengths of PCF in both sides with conventional single mode fiber (SMF-28). To apply modal interferometer theory; collapsing technique based on fusion splicing used to excite higher order modes (LP01 and LP11). Laser diode (1550 nm) has been used as a pump light source. Where a high sensitive optical spectrum analyzer (OSA) was used to monitor and record the transmitted. The experimental work shows that the interference spectrum of Photonic crystal fiber interferometer

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Sensors
Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review
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The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages

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Publication Date
Sun Jul 01 2012
Journal Name
Applied Soft Computing
A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks
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