This research explores the preparation of polypyrrole (PPy) using chemical oxidation and its enhancement with graphene oxide (GO) for optical sensor applications. PPy was synthesized by polymerizing pyrrole monomers with ferric chloride (Fe2Cl3) as the oxidant. The resulting PPy was then combined with GO to form a composite material, aiming to improve its electrical and optical properties. Polypyrrole nanofibers were obtained and after adding graphene oxide, the sensitivity increased. Characterization techniques including UV-Vis spectroscopy, DC conductivity measurements, Field Emission Scanning Electron Microscopy (FESEM) and response of photocurrent analysis were employed. The incorporation of GO into PPy resulted in a significant reducti

Electrochemical method was used to prepare carbon quantum dots (CQDs). Size of matter was nature when evaluate via X-ray diffraction (XRD). A distinct peak at 2θ equal to 31.6° and three other small peaks at 38.28°, 56.41° and 66.12° were observed. The measures of Fourier Transform Infrared Spectroscopy (FTIR) showed the bonds in the transmittance spectrum are manufactured with carbon nanostructures in view. The first peaks are the O–H stretching vibration bands at (3417 and 2922) cm−1, (C–O–H at 1400, and 1317) cm−1, (C–H), (C=C), (C–O–H), (C=O), and (C–O) bonds at 2850, 1668, 1101, and 1026 cm−1 sequentially. The transmission electron microscopy (TEM) results presented that the spherical CQDs are in shape and on a

The light-based life in the universe, including the human derived concepts and meanings of the fear of darkness and evil, comfort and goodness of light, became constitute bilateral haunted man to this day in various concepts of life.Therefore reflect the light form artistic aesthetic in visual arts such arts Fine Photography and the other until the emergence of art cinema, as the use of lighting in cinema has produced high-energy in the composition of its values expressive and symbolic, where it became dark and light are the space visually moving the vehicles media kit for many within the work structure artwork. The research is divided into five chapters, the first chapter (the methodological framework) that included an introduction the

A chemical optical fiber sensor based on surface plasmon resonance (SPR) was developed and implemented using multimode plastic optical fiber. The sensor is used to detect and measure the refractive index and concentration of various chemical materials (Urea, Ammonia, Formaldehyde and Sulfuric acid) as well as to evaluate the performance parameters such as sensitivity, signal to noise ratio, resolution and figure of merit. It  was noticed that the value of the sensitivity of the optical fiber-based SPR sensor, with 60nm and 10 mm long, Aluminum(Al) and Gold (Au) metals film exposed sensing region, was 4.4 μm, while the SNR was 0.20, figure of merit was 20 and resolution 0.00045. In this work a multimode

In this work, MWCNT in the epoxy can be prepared at room temperature and thickness (1mm) at different concentration of CNTs powder. Optical properties of multi-walled carbon nanotubes (CNTs) reinforced epoxy have been measured in the range of (300-800)nm. The electronic transition in pure epoxy and CNT/epoxy indicated direct allowed transition. Also, it is found that the energy gap of epoxy is 4.1eV and this value decreased within range of (4.1-3.5)eV when the concentration of CNT powder increased from (0.001-0.1)% respectively.
The optical constants which include (the refractive index (n), the extinction coefficient (k), real (ε1) and imaginarily (ε2) part of dielectric constant calculated in the of (300-800)nm at different concent

CuInSe2 (CIS)thin films have been prepared by use vacuum thermal evaporation technique, of 750 nm thickness, with rate of deposition 1.8±0.1 nm/sec on glass substrate at room temperature and pressure (10-5) mbar. Heat treatment has been carried out in the range (400-600) K for all samples. The optical properties of the CIS thin films are been studied such as (absorption coefficient, refractive index, extinction coefficient, real and imaginary dielectric constant)by determined using Measurement absorption and transmission spectra. Results showed that through the optical constants we can made to control it is wide applications as an optoelectronic devices and photovoltaic applications.

Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi

The effect of α-particle irradiation on the optical absorption in nuclear track detectors (LR115) has been studied. These detectors have been irradiated with different doses. The optical absorption has been measured using the ultraviolet-visible (UV-1100) spectroscopy, that irradiation results in shifting the peaks of the optical absorption. The values of Urbach energy have been calculated from the position of steady-state optical band gap energy, for a standard sample which was unirradiated with indirect influence, has been found 1.9 eV  whereas its value after irradiation 1.98 eV. In case of the direct influence, it is found to be, respectively, before irradiation 1.98 eV and after irradiation 2.05 eV. From these results, we can

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope