A tunable band pass filter based on fiber Bragg grating sensor using an in-fiber Mach-Zender interferometer with dual micro-cavities is presented. The micro-cavity was formed by splicing together a conventional single-mode fiber and a solid core photonic crystal fiber (SCPCF) with simple arc discharge technique. Different parameters such as arc power, length of the SCPCF and the overlap gap between samples were considered to control the fabrication process. The ellipsoidal air-cavity between the two fibers forms Fabry-Perot cavity. The diffraction loss was very low due to short cavity length. Ellipsoidal shape micro-cavities were experimentally achieved parallel to the propagation axis having dimensions of (24.92 – 62.32) μm of width and (3.82 – 18.2) μm of length. The maximum tunability 0.73nm was achieved at minimum length of (SCPCF) in the range (1545.673-1545.546) nm. A micro- cavity with width and length as high as 62.32 um and 18.3 um have higher sensitivity 0.31 nm/cm than temperature sensitivities of 18 pm/°C.
In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform
Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The
... Show MoreImage fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM,
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The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model
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Starting from 4, - Dimercaptobiphenyl, a variety of phenolic Schiff bases (methylolic, etheric, epoxy) derivatives have been synthesized. All proposed structure were supported by FTIR, 1H-NMR, 13C-NMR Elemental analysis all analysis were performed in center of consultation in Jordan Universty.
Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM
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Iraqi provinces suffer many of the environmental problems, appear explained these problems in the city of Basra, Basra, the largest province and is among Iraq's provinces in the annexation of oil fields, which is experiencing an oil production operations of large, it suffers from the burning of gas associated with oil extraction resulting in the emission severe gas process including toxic hydrogen sulfide gas (h2S) and oxides of carbon, sulfur and nitrogen in addition to the release of toxic metal elements such as mercury, arsenic, vanadium, which caused the man many serious diseases. , And perhaps one of the most important of these problems are worsening air quality and increasing cases of air pollution and the deterioration of the qual
... Show MoreBackground:Â Various fluids in the oral environment can affect the surface roughness of resin composites. This in vitro study was conducted to determine the influence of the mouth rinses on surface roughness of two methacrylate-based resin (nanofilled and packable composite) and siloraine-based resin composites.
Materials and methods: Disc-shaped specimens (12 mm in diameter and 2mm in height) were prepared from three types of composi
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The aim of this work is to enhance the mechanical properties of the glass ionomer cement GIC (dental materials) by adding Zirconium Oxide ZrO2 in both micro and nano particles. GIC were mixed with (3, 5 and 7) wt% of both ZrO2 micro and nanoparticles separately. Compressive strength (CS), biaxial flexural strength (BFS), Vickers Microhardness (VH) and wear rate losses (WR) were investigated. The maximum compression strength was 122.31 MPa with 5 wt. % ZrO2 micro particle, while 3wt% nanoparticles give highest Microhardness and biaxial flexural strength of 88.8 VHN and 35.79 MPa respectively. The minimum wear rate losses were 3.776µg/m with 7 wt. % ZrO2 nanoparticle. GIC-contai
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NiO nanoparticle synthesis by chemical method and characterized by XRD with crystal size 11.72
nm and grain size 13 nm from FESEM image also NiO micro used ,two NiO as an additive to evaluate the
possibility of producing photodegradable polymers, the practical application of solid-phase photocatalytic
degradation of polyvinyl chloride (PVC- NiO composite films) was investigated. PVC has a negative impact
on the environment since its polymer degrades slowly, yet it has a wide range of industrial applications and
the amount used shows no evidence of diminishing use. Thus, a synthesis of modified PVC- NiO micro and
nano has been studied with 0, 50, 100, 150, 200, 250, and 300 (hours) as irradiation time a
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