Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Photonic Crystal Fiber Interferometers (PCFIs) are widely used for sensing applications. This work presents the fabrication and the characterization of a relative humidity sensor based on a polymer-coated photonic crystal fiber that operates in a Mach- Zehnder Interferometer (MZI) transmission mode. The fabrication of the sensor involved splicing a short (1 cm) length of Photonic Crystal Fiber (PCF) between two single-mode fibers (SMF). It was then coated with a layer of agarose solution. Experimental results showed that a high humidity sensitivity of 29.37 pm/%RH was achieved within a measurement range of 27–95%RH. The sensor also showed good repeatability, small size, measurement accuracy and wide humidity range. The RH sensitivity o

In the present study, a low cost adsorbent is developed from the naturally available sawdust
which is biodegradable. The removal capacity of chromium(VI) from the synthetically prepared
industrial effluent of electroplating and tannery industrial is obtained.
Two modes of operation are used, batch mode and fixed bed mode. In batch experiment the
effect of Sawdust dose (4- 24g/L) with constant initial chromium(VI) concentration of 50 mg/L and
constant particle size less than1.8 mm were studied.
Batch kinetics experiments showed that the adsorption rate of chromium(VI) ion by Sawdust
was rapid and reached equilibrium within 120 min. The three models (Freundlich, Langmuir and
Freundlich-Langmuir) were fitted to exper

This review investigates the practice and influence of chatbots and ChatGPT as employable tools in writing for scientific academic purposes. A primary collection of 150 articles was gathered from academic databases, but it was systematically chosen and refined to include 30 studies that focused on the use of ChatGPT and chatbot technology in academic writing contexts. Chatbots and ChatGPT in writing enhancement, support for student learning at higher education institutions, scientific and medical writing, and the evolution of research and academic publishing are some of the topics covered in the reviewed literature. The review finds these tools helpful, with their greatest advantages being in areas such as structuring writings, gram

S a mples of compact magnesia and alumina were evaporated
using CO2-laser .The
Processed powders were characterized by electron microscopy
and both scanning and transmission electron microscope. The results
indicated that the particle size for both powders have reduced largely
to 0.003 nm and 0.07 nm for MgO and Al2O3, with increasing in
shape sphericity.

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

The Present study investigated the drought in Iraq, by using the rainfall data which obtained from 39 meteorological stations for the past 30 years (1980-2010). The drought coefficient calculated on basis of the standard precipitation index (SPI) and then characteristics of drought magnitude, duration and intensity were analyzed. The correlation and regression between magnitude and duration of drought were obtained according the (SPI) index. The result shows that drought magnitude values were greater in the northeast region of Iraq.