This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as compared with matching by minimum distance, gave (94%) and (83%) score by using group (1), (gp) and features respectively, which is much better than the minimum distance. Recognition using (gp) neural network (NN) gave a (94%) and (72%) score by using group (2), (gp) and features respectively, while the minimum distance gave (11%) and (33%) scores. Time consumption through the recognition process using (NN) with (gp) is less than that minimum distance.
The present study is an attempt to throw light on the nature of the US policy regarding the Middle East region as portrayed by AI-Sabah, Al-Mashriq and Tariq Al-Shaab papers over a period of three months from 1st of July to 30th of September 2013.
In writing this study, a number of goals have been set by the researcher. These goals may include but in no way limited to the nature of the US image as carried by the above three papers, the nature of the topics tackled by them and the nature of the Arab countries which received more and extensive coverage than others.
A qualitative research approach is proposed for the study. This approach has allowed the researcher to arrive at definite answers for the possible questions rais
... Show MorePredicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be
... Show MoreThis research presents a model for surveying networks configuration which is designed and called a Computerized Integrated System for Triangulation Network Modeling (CISTNM). It focuses on the strength of figure as a concept then on estimating the relative error (RE) for the computed side (base line) triangulation element. The CISTNM can compute the maximum elevations of the highest
obstacles of the line of sight, the observational signal tower height, the contribution of each triangulation station with their intervisibility test and analysis. The model is characterized by the flexibility to select either a single figure or a combined figures network option. Each option includes three other implicit options such as: triangles, quadri
Mobile Ad hoc Networks (MANETs) is a wireless technology that plays an important role in several modern applications which include military, civil, health and real-time applications. Providing Quality of Service (QoS) for this application with network characterized by node mobility, infrastructure-less, limitation resource is a critical issue and takes greater attention. However, transport protocols effected influential on the performance of MANET application. This study provides an analysis and evaluation of the performance for TFRC, UDP and TCP transport protocols in MANET environment. In order to achieve high accuracy results, the three transport protocols are implemented and simulated with four different network topology which are 5, 10
... Show MoreThe Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr
... Show MoreLong memory analysis is one of the most active areas in econometrics and time series where various methods have been introduced to identify and estimate the long memory parameter in partially integrated time series. One of the most common models used to represent time series that have a long memory is the ARFIMA (Auto Regressive Fractional Integration Moving Average Model) which diffs are a fractional number called the fractional parameter. To analyze and determine the ARFIMA model, the fractal parameter must be estimated. There are many methods for fractional parameter estimation. In this research, the estimation methods were divided into indirect methods, where the Hurst parameter is estimated fir
... Show MoreCompressing an image and reconstructing it without degrading its original quality is one of the challenges that still exist now a day. A coding system that considers both quality and compression rate is implemented in this work. The implemented system applies a high synthetic entropy coding schema to store the compressed image at the smallest size as possible without affecting its original quality. This coding schema is applied with two transform-based techniques, one with Discrete Cosine Transform and the other with Discrete Wavelet Transform. The implemented system was tested with different standard color images and the obtained results with different evaluation metrics have been shown. A comparison was made with some previous rel
... Show MoreA Strength Pareto Evolutionary Algorithm 2 (SPEA 2) approach for solving the multi-objective Environmental / Economic Power Dispatch (EEPD) problem is presented in this paper. In the past fuel cost consumption minimization was the aim (a single objective function) of economic power dispatch problem. Since the clean air act amendments have been applied to reduce SO2 and NOX emissions from power plants, the utilities change their strategies in order to reduce pollution and atmospheric emission as well, adding emission minimization as other objective function made economic power dispatch (EPD) a multi-objective problem having conflicting objectives. SPEA2 is the improved version of SPEA with better fitness assignment, density estimation, an
... Show MoreThis study includes the direct influence of (single & multi) dose of Cold Atmospheric Plasma (CAP) on the no. of platelets for mice for different exposure time (15, 30, 60, and 120) sec. the influence of CAP on mice was measured after 1, 2, 3, 7, and 14 day from exposure.
The results obtained in this study indicate that the effect of low doses of CAP on platelets was stimulatory effect in the first few hours from exposure (1day) but the high dose was inhibitory, It was found that after two weeks of exposure that the number of platelets became normal comparable to the control one, and this indicates that plasma effect was removed after this period.
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In this study, optical fibers were designed and implemented as a chemical sensor based on surface plasmon resonance (SPR) to estimate the age of the oil used in electrical transformers. The study depends on the refractive indices of the oil. The sensor was created by embedding the center portion of the optical fiber in a resin block, followed by polishing, and tapering to create the optical fiber sensor. The tapering time was 50 min. The multi-mode optical fiber was coated with 60 nm thickness gold metal. The deposition length was 4 cm. The sensor's resonance wavelength was 415 nm. The primary sensor parameters were calculated, including sensitivity (6.25), signal-to-noise ratio (2.38), figure of merit (4.88), and accuracy (3.2)
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