Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

The reaction oisolated and characterized by elemental analysis (C,H,N) , 1H-NMR, mass spectra and Fourier transform (Ft-IR). The reaction of the (L-AZD) with: [VO(II), Cr(III), Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II)], has been investigated and was isolated as tri nuclear cluster and characterized by: Ft-IR, U. v- Visible, electrical conductivity, magnetic susceptibilities at 25 Co, atomic absorption and molar ratio. Spectroscopic evidence showed that the binding of metal ions were through azide and carbonyl moieties resulting in a six- coordinating metal ions in [Cr (III), Mn (II), Co (II) and Ni (II)]. The Vo (II), Cu (II), Zn (II), Cd (II) and Hg (II) were coordinated through azide group only forming square pyramidal

The preparation and spectral characterization of complexes for Co(II), Ni(II), Cu(II), Cd(II), Zn(II) and Hg(II) ions with new organic heterocyclic azo imidazole dye as ligand 2-[(2`-cyano phenyl) azo ]-4,5-diphenyl imidazole ) (2-CyBAI) were prepared by reacting a dizonium salt solution of 2-cyano aniline with 4,5-diphenyl imidazole in alkaline ethanolic solution .These complexes were characterized spectroscopically by infrared and electronic spectra along with elemental analysis‚ molar conductance and magnetic susceptibility measurements. The data show that the ligand behaves a bidantate and coordinates to the metal ion via nitrogen atom of azo and with imidazole N3 atom. Octahedral environment is suggested for all metal complex

New bidentate Schiff base ligand (L) namely [(Z)-3-(2-oxoindolin-3ylildeneamino)benzoic acid] type (NO) was prepared via condensation of  isatin and 3-amino benzoic acid in ethanol as a solvent in existence of drops of (glac. CH3COOH). The new ligand (L) was characterized base on elemental microanalysis, FT-IR, UV-Vis, 1H-NMR spectra along with melting point. Ligand complexes in general formula [M(L)2Cl2]. H2O, where: MII = Co, Cu, Cd, and Hg; L= C15H10 N2O3 were synthesized and identified by FT-IR, UV-Vis, 1H-NMR (for Cd complex only) spectra, atomic absorption, chloride content along with molar conductivity and magnetic susceptibility. It was found that the ligand behaves as bidentate on complexation via (N) atom of imine group an

The synthesis of [1,2-diaminoethane-N,N'-bis(2-butylidine-3- onedioxime)] [II2L] and its cobalt(II), nickel(II), copper(II), palladium(II), platinum(II, IV), zinc(II), cadmium(II) and mercury(II) complexes is reported. The compounds were characterised by elemental analyses, spectroscopic methods [I.R, UV-Vis, ('H NMR. and EI mass for H2L)], molar conductivities, magnetic moments. I.R. spectra show that (H2L) behaves as a neutral or mononegative ligand depending on the nature of the metal ions. The molar conductance of the complexes in (DMSO) is commensurate with their ionic character. On the basis of the above measurements, a square planar geometry is proposed for NOD, Pd(II), and Pt(II) complexes, and an octahedr-al structure with trans

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video str

Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to enhance efficiency and maximize the output power of PV module, regardless the variation of temperature, irradiation, and the electrical characteristics of the load. A new MPPT system has been presented in this research, consisting of a synchronous DC-DC step-down Buck converter controlled by an Arduino microcontroller based unit. The MPPT process with Perturb and Observe method is performed with a DC-DC converter circuit to overcome the problem of voltage mismatch between the PV modules and the loads. The proposing system has high efficiency, lower cost and can be easily modified to handle more energy sources. The test results indicate that the u