For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

Ankylosing spondylitis is a complex debilitating disease because its pathogenesis is not clear. This study aims at detecting some pathogenesis factors that lead to induce the disease. Chlamydia pneumoniae is one of these pathogenesis factors which acts as a triggering factor for the disease. The study groups included forty Iraqi Ankylosing spondylitis patients and forty healthy persons as a control group. Immunological and molecular examinations were done to detect Chlamydia. pneumoniae in AS group. The immunological results were performed by Enzyme-Linked Immunosorbent Assay (ELISA) to detect anti-IgG and anti-IgM antibodies of C. pneumoniae revealed that five of forty AS patients' samples (12.5%) were positive for anti-IgG and IgM C. pneu

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

In this study, sawdust as a cheap method and abundant raw material was utilized to produce active carbon (SDAC). Physiochemical activation was utilized where potassium hydroxide   used as a chemical activating agent and carbon dioxide was used as a physical activating agent. Taguchi method of experimental design was used to find the optimum conditions of SDAC production. The produced SDAC was characterized using SEM to investigate surface morphology and BET to estimate the specific surface area. SDAC was used in aqueous lead ions adsorption. Adsorption process was modeled statistically and represented by an empirical model. The highest specific surface area of SDAC was 688.3 m2/gm. Langmuir and Freundlich isotherms were used to

Background: In this work, a fingerprint powder was used to reveal latent fingerprints from different surfaces. This powder was derived from the Date fronds as activated carbon. Methods: In preparing the activated carbon, three parameters were studied: activation time, activation temperature, and impregnation ratio. Fourier Transform Infrared Spectroscopy (FTIR) was used to characterize the prepared Date frond activated carbon (DFAC) as well as the raw material (Date frond plant). Brunauer-Emmett-Teller (BET) was used to measure the specific surface area of DFAC. The surface shape and the element composition of the prepared powder were investigated using (SEM-EDS) analysis. A Central Composite Design (CCD) was employed to determine th

The aim of this paper, study the effect of carbon nanotubes on the electrical properties of polyvinylchloride. Samples of polyvinylchloride carbon nanotubes composite prepared by using hot press technique. The weight percentages of carbon nanotubes are 0,5,10 and 20wt.%. Results showed that the D.C electrical conductivity increases with increasing of the weight percentages of carbon nanotubes. Also, the D.C electrical conductivity changed with increase temperature for different concentrations of carbon nanotubes. The activation energy of D.C electrical conductivity is decreased with increasing of carbon nanotubes concentration.