An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to change its affiliation with other clusters based on a deep learning modified Element-wise Attention Gate. The modified Element-wise Attention Gate has the ability to handle the buffer capacity in all the network, thereby enriching the Quality of Service. A deep learning modified training algorithm is proposed to learn the artificial intelligent system allowing the neurons to have greater concentration ability. The simulation results demonstrate that the Root Mean Square error is minimized by 37.14% when using modified Element-wise Attention Gate when compared with a Deep Learning Recurrent Neural Network. Also, the Quality of Service of the network is improved, for example, the network lifetime is enhanced by 12.7% more than with Deep Learning Recurrent Neural Network.
The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when
... Show MoreIn this paper, tunable optical band-pass filters based on Polarization Maintaining Fiber –Mach Zehnder Interferometer presented. Tunability of the band-pass filter implemented by applying different mechanical forces N on the micro-cavities splicing regions (MCSRs). The micro-cavity formed by using three variable-lengths of single-mode polarization-maintaining fiber with (8, 16, 24) cm lengths, splice between two segments of (SMF-28) with (26, 13) cm lengths, using the fusion splicing technique. Ellipsoidal shape micro-cavities experimentally achieved parallel to the propagation axis having dimensions between (12-24) μm of width and (4-12) μm of length. A micro-cavity with width and length as high as 24 μm and 12 μ
... Show MoreThe internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat
... Show MoreThe multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA).
... Show MoreThe performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD). In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc
... Show MoreLED is an ultra-lightweight block cipher that is mainly used in devices with limited resources. Currently, the software and hardware structure of this cipher utilize a complex logic operation to generate a sequence of random numbers called round constant and this causes the algorithm to slow down and record low throughput. To improve the speed and throughput of the original algorithm, the Fast Lightweight Encryption Device (FLED) has been proposed in this paper. The key size of the currently existing LED algorithm is in 64-bit & 128-bit but this article focused mainly on the 64-bit key (block size=64-bit). In the proposed FLED design, complex operations have been replaced by LFSR left feedback technology to make the algorithm perform more e
... Show MoreBaghdad city has been faced numerous issues related to freshwater environment deteriorations due to many reasons, mainly was the discharge of wastewater without adequate treatment. Al- Rustamiya Wastewater Treatment Plant (WWTP) have been constructed among many plants in Baghdad city to reduce the amount of wastewater discharged into natural environment and its subsequent adverse effects. This study was conducted to evaluate the performance of the plant which consist of a conventional activated sludge (CAS) and sequencing batch reactors (SBR) systems as secondary treatment units and its ability to meet Iraqi specifications. A reliability level determination and analysis also were conducted to find the plant's stability and its capabi
... Show MoreThis study designed to prepare ultrafine apixaban (APX) o/w nanoemulsion (NE) based gel with droplet size below 50 nm as a good method for transdermal APX delivery without using permeation enhancer, alternatively, the formulation components itself act as permeation enhancer. APX, a potent oral anticoagulant drug that selectively and directly inhibit coagulation factor Xa, was selected as a good candidate for transdermal delivery as it displays poor water solubility (0.028 mg/mL) and low bioavailability (50%). APX-NE gel was prepared using triacetin, triton-x-100 and carbitol as oil phase, surfactant and cosurfactant respectively, while Carbopol 940 used as a gelling agent. Ex vivo permeation of APX-NE gel through human stratum c
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