Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

In recent years, the iris biometric occupies a wide interesting when talking about
biometric based systems, because it is one of the most accurate biometrics to prove
users identities, thus it is providing high security for concerned systems. This
research article is showing up an efficient method to detect the outer boundary of
the iris, using a new form of leading edge detection technique. This technique is
very useful to isolate two regions that have convergent intensity levels in gray scale
images, which represents the main issue of iris isolation, because it is difficult to
find the border that can separate between the lighter gray background (sclera) and
light gray foreground (iris texture). The proposed met

     One technique used to prepare nanoparticles material is Pulsed Laser Ablation in Liquid (PLAL), Silver Oxide nanoparticles (AgO) were prepared by using  this technique, where silver target was submerged in ultra-pure water (UPW)  at room temperature after that Nd:Yag laser which characteristics by 1064 nm wavelength, Q-switched, and 6ns pulse duration was used to irradiated silver target. This preparation method was used to study the effects of laser irradiation on Nanoparticles synthesized by used varying laser pulse energy 1000 mJ, 500 mJ, and 100 mJ, with 500 pulses each time on the particle size. Nanoparticles are characterized using XRD, SEM, AFM, and UV-Visible spectroscopy. All the structural peaks determined by the XRD

The Indian costus plasma properties are investigated including electron temperature (Te), "electron density (ne)", "plasma frequency (fp)", " Debye sphere length", and amount of Debye(Nd),  using the spectrum of optical emission technique. There are several energies used, with ranging from 300 to 600 mJ. The Boltzmann Plot is used to calculate the temperature; where as Stark's Line Broadening is used to calculate the electron density. The Indian costus was spectroscopically examined in the air with the laser  at 10 cm away from the target and the optical fiber  at 0.5 cm away. The results were obtained for an electron temperature range of (1.8-2.2) electron volts (ev) and a wavelength range of (300-600) nm. The XRF analysis reveals th

     Synthesis of sedimentologic, paleocurrent, and organic geochemistry data of the Lower Permian Ga’ara Formation from the Western Desert, western Iraq, shows good hydrocarbon potentiality and deposition by high sinuosity and mixed-load channels, likely by a meandering river system. The Ga’ara Formation includes kaolinitic mudstone beds of various colors and channelized quartzitic sandstone beds. Based on the lithofacies identification, five lithofacies associations have been recognized: channel-floor, point-bar, abandoned channel plug, crevasse splay, and interchannel flood basin. In addition, the paleocurrent analysis and sandstone percentage map indicate a variation of the paleoflow spatially and temporally with a general di

The palm vein recognition is one of the biometric systems that use for identification and verification processes since each person have unique characteristics for the veins. In this paper we can improvement palm vein recognition system have been made. The system based on centerline extraction of veins, and employs the concept of Difference-of Gaussian (DoG) Function to construct features vector. The tests results on our database showed that the identification rate is 100 % with the minimum error rate was 0.333.

      Bioinformatics is one of the computer science and biology sub-subjects concerned with the processes applied to biological data, such as gathering, processing, storing, and analyzing it. Biological data (ribonucleic acid (RNA), deoxyribonucleic acid (DNA), and protein sequences) has many applications and uses in many fields (data security, data segmentation, feature extraction, etc.). DNA sequences are used in the cryptography field, using the properties of biomolecules as the carriers of the data. Messenger RNA (mRNA) is a single strand used to make proteins containing genetic information. The information recorded from DNA also carries messages from DNA to ribosomes in the cytosol. In this paper, a new encryption technique bas

Abstract

Pneumatic processes sequence (PPS) is used widely in industrial applications. It is common to do a predetermined PPS to achieve a specific larger task within the industrial application like the PPS achieved by the pick and place industrial robot arm. This sequence may require change depending on changing the required task and usually this requires the programmer intervention to change the sequence’ sprogram, which is costly and may take long time. In this research a PLC-based PPS control system is designed and implemented, in which the PPS is programmed by demonstration. The PPS could be changed by demonstrating the new required sequence via the user by following simple series of manual steps without h

In this research, a new technique is suggested to reduce the long time required by the encoding process by using modified moment features on domain blocks. The modified moment features were used in accelerating the matching step of the Iterated Function System (IFS). The main disadvantage facing the fractal image compression (FIC) method is the over-long encoding time needed for checking all domain blocks and choosing the least error to get the best matched domain for each block of ranges. In this paper, we develop a method that can reduce the encoding time of FIC by reducing the size of the domain pool based on the moment features of domain blocks, followed by a comparison with threshold (the selected  threshold based on experience

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th