Peak ground acceleration (PGA) is one of the critical factors that affect the determination of earthquake intensity. PGA is generally utilized to describe ground motion in a particular zone and is able to efficiently predict the parameters of site ground motion for the design of engineering structures. Therefore, novel models are developed to forecast PGA in the case of the Iraqi database, which utilizes the particle swarm optimization (PSO) approach. A data set of 187 historical ground-motion recordings in Iraq’s tectonic regions was used to build the explicit proposed models. The proposed PGA models relate to different seismic parameters, including the magnitude of the earthquake (Mw), average shear-wave velocity (VS30), focal depth (FD), and nearest epicenter distance (REPi) to a seismic station. The derived PGA models are remarkably simple and straightforward and can be used reliably for pre-design purposes. The proposed PGA models (i.e., models I and II) obtained via the explicit formula produced using the PSO method are highly correlated to the actual PGA records owing to low coefficients of variation (CoV) of approximately 2.12% and 2.06%, and mean values (i.e., close to 1.0) of approximately 1.005 and 1.004. Lastly, high-frequency, low absolute relative error (ARE), which is below 5%, is recorded for the proposed models, thereby showing an acceptable error distribution.
This paper involved the registration of 1,936 cases of infection of the Leishmania tropica parasite observed at hospitals and health centers in Ramadi, Fallujah, Baghdadi, and Hit during 2017. The results revealed that the highest rates of infection were found in Ramadi and Fallujah. The 1-10 years age group recorded the highest rate at 35.5%. There was no significant difference (p ≥ 0.05) between the sexes. December and January saw the highest rate of infection, where the rate in rural townships was found to be 65.5%, higher than in urban regions which saw a rate of 34.4%. Facial lesions were the most prominent area of infection, recorded at a rate of 41.3%. The study also included an examination of 180 rodents (94 mice and 86 black r
... 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 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 MoreAn 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
... Show MoreIn 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
In this paper, an adaptive medical image watermarking technique is proposed based on wavelet transform and properties of human visual system in order to maintain the authentication of medical images. Watermark embedding process is carried out by transforming the medical image into wavelet domain and then adaptive thresholding is computed to determine the suitable locations to hide the watermark in the image coefficients. The watermark data is embedded in the coefficients that are less sensitive into the human visual system in order to achieve the fidelity of medical image. Experimental results show that the degradation by embedding the watermark is too small to be visualized. Also, the proposed adaptive watermarking technique can preserv
... Show MoreEnergy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the
... Show MoreA total of 533 specimens were collected in survey of Brachyceran species from different regions of Iraq during February to November 2014 .This study was reported 16 species belonging to 13 genera and 7 families, the results showed that Dicranosepsis Duda, 1926 (Family; Sepsidae) is recorded the genus for the first time in Iraq.