Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3 rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM) in M technique which has the highest values of energy (En) and compression ratio (CR) and least values of bit per pixel (bpp), time (T) and rate distortion (R (D)). Also the values of the compression parameters of the color image are nearly the same as the average values of the compression parameters of the three bands of the same image.
Abstract: Narrow laser pulses have been essential sources in optical communication system. High data rate optical communication network system demands compressed laser source with unique optical property. In this work using pulsed duration (9) ns, peak power 1.2297mW, full width half maximum (FWHM) 286 pm, and wavelength center 1546.7 nm as compression laser source. Mach Zehnder interferometer (MZI) is built by considering two ways. First, polarization maintaining fiber (PMF) with 10 cm length is used to connect between laser source and fiber brag grating analysis (FBGA). Second, Nested Mach Zehnder interferometer (NMZI) was designed by using three PMFs with 10 cm length. These three Fibers are splicing to sing
... Show MoreA number of compression schemes were put forward to achieve high compression factors with high image quality at a low computational time. In this paper, a combined transform coding scheme is proposed which is based on discrete wavelet (DWT) and discrete cosine (DCT) transforms with an added new enhancement method, which is the sliding run length encoding (SRLE) technique, to further improve compression. The advantages of the wavelet and the discrete cosine transforms were utilized to encode the image. This first step involves transforming the color components of the image from RGB to YUV planes to acquire the advantage of the existing spectral correlation and consequently gaining more compression. DWT is then applied to the Y, U and V col
... Show MoreA cantilever beam is made from composite material which is consist of (matrix: polyester) and (particles: Silicon-Carbide) with different volume fraction of particles. A force is applied at the free end of beam with different values. The experimental maximum deflection of beam which occurs at the point of the applied load is recorded. The deflection and slope of beam are analyzed by using FEM modeling. MATLAB paltform is built to assemble the equations, vector and matrix of FEM and solving the unknown variables (deflection and slope) at each node. Also ANSYS platform is used to modeling beam in finite element and solve the problem. The numerical methods are used to compare the results with the theoretical and experimental data. A good ag
... Show MoreFiber reinforced polymer composite is an important material for structural application. The diversified application of FRP composite has taken center of attraction for interdisciplinary research. However, improvements on mechanical properties of this class of materials are still under research for different applications. In this paper we have modified the epoxy matrix by Al2O3, SiO2 and TiO2 nano particles in glass fiber/epoxy composite to improve the mechanical and physical properties. The composites are fabricated by hand lay-up method. It is observed that mechanical properties like flexural strength, hardness are more in case of SiO2 modified epoxy composite compare to other nano
... Show MoreCassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
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