OpenStreetMap (OSM) represents the most common example of online volunteered mapping applications. Most of these platforms are open source spatial data collected by non-experts volunteers using different data collection methods. OSM project aims to provide a free digital map for all the world. The heterogeneity in data collection methods made OSM project databases accuracy is unreliable and must be dealt with caution for any engineering application. This study aims to assess the horizontal positional accuracy of three spatial data sources are OSM road network database, high-resolution Satellite Image (SI), and high-resolution Aerial Photo (AP) of Baghdad city with respect to an analogue formal road network dataset obtained from the Mayoralty of Baghdad (MB). The methodology of, U.S. National Standard Spatial Data Accuracy (NSSDA) was applied to measure the degree of agreement between each data source and the formal dataset (MB) in terms of horizontal positional accuracy by computing RMSE and NSSDA values. The study concluded that each of the three data sources does not agree with the MB dataset in both study sites AL-Aadhamiyah and AL-Kadhumiyah in terms of positional accuracy.
Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved. In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)
... Show MoreThe petroleum industry, which is one of the pillars of the national economy, has the potential to generate vast wealth and employment possibilities. The transportation of petroleum products is complicated and changeable because of the hazards caused by the corrosion consequences. Hazardous chemical leaks caused by natural disasters may harm the environment, resulting in significant economic losses. It significantly threatens the aim for sustainable development. When a result, determining the likelihood of leakage and the potential for environmental harm, it becomes a top priority for decision-makers as they develop maintenance plans. This study aims to provide an in-depth understanding of the risks associated with oil and gas pipeli
... Show MoreThe behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u
... Show MoreInfrared photoconductive detectors working in the far-infrared region and room temperature were fabricated. The detectors were fabricated using three types of carbon nanotubes (CNTs); MWCNTs, COOH-MWCNTs, and short-MWCNTs. The carbon nontubes suspension is deposited by dip coating and drop–casting techniques to prepare thin films of CNTs. These films were deposited on porous silicon (PSi) substrates of n-type Si. The I-V characteristics and the figures of merit of the fabricated detectors were measured at a forward bias voltage of 3 and 5 volts as well as at dark and under illumination by IR radiation from a CO2 laser of 10.6 μm wavelengths and power of 2.2 W. The responsivity and figures of merit of the photoconductive detector
... Show MoreBackground; Perforated duodenal ulcer (PDU) is a common surgical emergency that is associated with high mortality and morbidity. Early diagnosis and prompt surgical treatment is required to prevent grave complications.
Objective; The study was designed to evaluate the diagnostic accuracy of different radiological investigations in the diagnosis of perforated duodenal ulcer.
Methods; A prospective study of 185 pts with PDU at al kindy teaching hospital, Baghdad, Iraq from June 2008- august 2010. patients were examined clinically and investigated by blood test, chest x ray, plain X ray of the abdomen. Ultrasonography (U/S) and CT scanning done for those patients with negative X- ray finding. Resuscitation by intravenous fluid and ant
Background: Menstrual problems with all manifestations ranging from life-threatening bleeding to amen- orrhea are considered patterns of abnormal uterine bleeding (AUB), which is until now a popular reason for referral to the gynaecologic clinic and requires a special diagnostic tool. Objective: To assess the accuracy of hysteroscopy in diagnosing endometrial pathologies and to compare it with sonographic and histopathologic reports. Patients and Methods: A prospective study conducted in the Baghdad Teaching Hospital on 60 Iraqi females having varying complaints from abnormal uterine bleeding in pre- and post-menopausal women, infertility, and chronic pelvic pain with normal or abnormal ultrasound findings. Office hysteroscopy was done and
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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