Abstract: Reflection optical fibre Humidity sensor is presented in this work, which is based on no core fibre prepared by splicing a segment of no core fibre (NCF) at different lengths 1-6 cm with fixed diameter 125 µm and a single mode fibre (SMF). The range of humidity inside the chamber is controlled from 30% to 90% RH at temperature ~ 30 °С. The experimental result shows that the resonant wavelength dip shift decreases linearly with an increment of RH% and the sensitivity of the sensor increased linearly with an increasing in the length of NCF. However, a high sensitivity 716.07pm/RH% is obtained at length 5cm with good stability and reputability.  Furthermore, the sensor is shif

   In this research we studied  the structural and optical properties of (CdTe) thin films which have been prepared  by thermal evaporation deposition method on the glass substrate at R.T with thickness (450  25) nm., as  a function of doping  ratio with copper element  in (1,3,5) % rate .The structure  measurement  by X-ray diffraction (XRD) analyses shows that the single phase of (CdTe) with polycrystalline structure with a preferred orientation [111].   The optical  measurement shows that the (CdTe) films have a direct energy gap, and they decrease with the increase of doping ratio reaching to 5% . The optical constants are investigated and calculated, such as absorpti

Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we eva

This work is aimed to design a system which is able to diagnose two types of tumors in a human brain (benign and malignant), using curvelet transform and probabilistic neural network. Our proposed method follows an approach in which the stages are preprocessing using Gaussian filter, segmentation using fuzzy c-means and feature extraction using curvelet transform. These features are trained and tested the probabilistic neural network. Curvelet transform is to extract the feature of MRI images. The proposed screening technique has successfully detected the brain cancer from MRI images of an almost 100% recognition rate accuracy.

   In this work, thin films of undoped and Al-doped CdO with (0.5, 1 and 2) wt.%  were prepared by using thermal vacuum evaporation on glass substrate at room  temperature. The optical absorption coefficient (α) of the films was determined from transmittance spectra in the range of wavelength (400-1100) nm. The spectral transmission and the optical energy band gap decrease from 75% and 2.24 eV to 20%  and 2.1 eV respectively depending upon the Al content in the films, also our studies include the calculation of  the optical constants (refractive index, extinction coefficient, real and imaginary part of dielectric constant) as a function of photon energy.  It is evaluated that the optical band gap of

CdSe thin films were deposited on glass sudstrate by thermal evaporation method with thickness of (300±25%) nm with deposition rate (2±0.1) nm/s and at substrate temperature at (R.T.). XRD analysis reveals that the structure of pure thin films are Hexagonal and polycrystalline with preferential orientation (002). In this research ,we study the effect of doping with (1,2,3)% Aluminum on optical energy gap of (CdSe) thin film . The absorption was studied by using (UV - Visible 1800 spectra photometer ) within the wavelength (300-1100) nm absorption coefficient was calculated as a function of incident photon energy for identify type of electronic transitions it is found that the type of transition is direct , and we calculated the opt

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In this study, optical fibers were designed and implemented as a chemical sensor based on surface plasmon resonance (SPR) to estimate the age of the oil used in electrical transformers. The study depends on the refractive indices of the oil. The sensor was created by embedding the center portion of the optical fiber in a resin block, followed by polishing, and tapering to create the optical fiber sensor. The tapering time was 50 min. The multi-mode optical fiber was coated with 60 nm thickness gold metal. The deposition length was 4 cm. The sensor's resonance wavelength was 415 nm. The primary sensor parameters were calculated, including sensitivity (6.25), signal-to-noise ratio (2.38), figure of merit (4.88), and accuracy (3.2)

Under aerobic and anaerobic conditions, two laboratory-scale reactors were operated. Each reactor
was packed with 8.5 kg of shredded synthetic solid waste (less than 5 cm) that was prepared according to an
average composition of domestic solid waste in the city of Kirkuk. Using an air compressor, aerobic
conditions were created in the aerobic reactor. This study shows that the aerobic reactor was more efficient in
COD and BOD5 removal which were 97.88% and 91.25% while in case of anaerobic reactor, they were
66.53%and 19.11%, respectively.

 Zinc oxide (ZnO) transparent thin films with different oxygen flow rates (0.5, 1.0, and 1.5)Litter/min. were prepared by thermal evaporation technique on glass substrate at a temperature of 200℃ with rate (10±2)nm sec-1,  The crystallinity and structure of these films were analyzed  by X-ray diffraction (XRD). It exhibits a polycrystalline hexagonal wurtzite structure and the preferred orientation along (002) plane. The Optical properties of ZnO were determined through the optical transmission method using ulta violet–Visible spectrophotometer with in wave length (300-1100)nm. The optical transmittance of the ZnO films increases from 75% to 85% with increase flow rate of O2, and the optical band gap of ZnO

Ground-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl