Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support systems that significantly reduce the cost involved when moving between two locations. Therefore, in this paper, an advanced decision support system is built for identifying the best route between two locations according to various criteria such as distance, travel time, the safety of the road, and other features. The proposed model includes several stages; Google Maps downloading, preprocessing, integrating with the database, and identifying the best route by utilizing advanced algorithms of artificial intelligence. Furthermore, the Open Street Maps (OSM) database is utilized in this model and implemented using the Quantum Geographic Information Systems (QGIS) platform. One of the main merits of this model is to be faster by removing the influence of non-processed data like null values and unlinked roads on offline google maps levels. The outcomes of this proposed model display the best route which connects the source with the destination, and a table including the entire information for this route.
In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo
... Show MoreIn this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe
... Show MoreDiphenhydramine hydrochloride was determined through a newly developed turbidimetric method on a home-designed continuous-flow injection analysis (CFIA) system. The principle of the method is based on the precipitation-induced signal enhancement, using potassium hexacyanoferrate (III) as a selective precipitating agent. The CFIA manifold uses a flow-through detection cell that consists of 12 white light-emitting diodes and three solar cells placed at 0, 90 and 180 degrees in order to track cumulative light scattering over a range of angles. The systematically optimized chemical and instrumental parameters were the reagent concentration, flow rate and sample volume to attain optimal
One of the important differences between multiwavelets and scalar wavelets is that each channel in the filter bank has a vector-valued input and a vector-valued output. A scalar-valued input signal must somehow be converted into a suitable vector-valued signal. This conversion is called preprocessing. Preprocessing is a mapping process which is done by a prefilter. A postfilter just does the opposite.
The most obvious way to get two input rows from a given signal is to repeat the signal. Two rows go into the multifilter bank. This procedure is called “Repeated Row” which introduces oversampling of the data by a factor of 2.
For data compression, where one is trying to find compact transform representations for a
... Show MoreBig developments in technology have led to upset the balance of ideas, given of its own post new properties for products not provided by traditional technology, especially economic units operating within the industrial sector, and therefore it is important to develop the Iraqi industrial sector and interest to do its vital role in light Of progress technological.The research aims to Find the use of advanced manufacturing technologies that lead to customized production and quality appropriate whether they are low quality and low cost or low cost and suitable quality or high quality and high cost to win customer satisfaction.While the important conclusions is that the application of advanced manufacturing technology is not limited to techn
... Show MoreObjectives This study aimed to compare the clinical effectiveness of four aligning archwires: Superelastic Nickel-Titanium (Superelastic-NiTi), SmartArch, Copper-Nickel-Titanium (Cu-NiTi), and Speed Tubular coaxial-Nickel-Titanium (Tubular coaxial-NiTi), regarding the alignment efficiency, associated perception of pain, and possibility of inducing root resorption.
Materials and Methods This study includes two randomized clinical trials run in parallel. Patients with 5 to 9 mm of mandibular anterior teeth crowding according to Little's irregularity index (LII) who needed fixed orthodontic appliances without extraction were randomly assigned to four groups of
The impact of management control systems (MCS) on organizations performance empirical research has been the subject of numerous studies during the past decade in developed and emerging economies. In the contemporary competitive, complex and changing global business environment, firms are being challenged to adopt business models that enable them to address the strategic uncertainties and risks they face in their business environments. The main issue of this study is that management accounting researchers argue that one of the ways firms can continually rejuvenate themselves to survive and succeed in these complex and uncertain environments is to understand the role of management control systems in Formulating a b
... Show MoreIn recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS. This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP
... Show MoreHuman resources have been regarded as the most important asset for any organization because of its essential part in achieving the sustainable competitive advantage and survival. Managing human resources is very challenging and requires an effective bundle of practices that contribute to attaining the organizational goals. This study tries to confirm the importance of HRM practices in small businesses which came to play a vital role in the economies of the world, through clarifying the influence of HRM practices on the organizational performance, using a mediating variable (employees’ outcomes). Also the study attempts to highlight the key role of governmental support from view point of small businesses, through verifying the significant
... Show MoreMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
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