This article studies a comprehensive methods of edge detection and algorithms in digital images which is reflected a basic process in the field of image processing and analysis. The purpose of edge detection technique is discovering the borders that distinct diverse areas of an image, which donates to refining the understanding of the image contents and extracting structural information. The article starts by clarifying the idea of an edge and its importance in image analysis and studying the most noticeable edge detection methods utilized in this field, (e.g. Sobel, Prewitt, and Canny filters), besides other schemes based on distinguishing unexpected modifications in light intensity and color gradation. The research as well discusses the benefits and limitations of each technique, emphasizing their efficacy in addressing various kinds of images and the dares they face in complex environs. This article offers a comparative analysis of the numerous approaches utilized in edge detection, which assistances in selecting the suitable technique according to the requirements of applications, like video processing, object recognition, medical image analysis, and computer vision.
The aim of this research is to solve a real problem in the Department of Economy and Investment in the Martyrs establishment, which is the selection of the optimal project through specific criteria by experts in the same department using a combined mathematical model for the two methods of analytic hierarchy process and goal programming, where a mathematical model for goal programming was built that takes into consideration the priorities of the goal criteria by the decision-maker to reach the best solution that meets all the objectives, whose importance was determined by the hierarchical analysis process. The most important result of this research is the selection of the second pro
... Show MoreThe reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese
... Show MoreIn this paper reliable computational methods (RCMs) based on the monomial stan-dard polynomials have been executed to solve the problem of Jeffery-Hamel flow (JHF). In addition, convenient base functions, namely Bernoulli, Euler and Laguerre polynomials, have been used to enhance the reliability of the computational methods. Using such functions turns the problem into a set of solvable nonlinear algebraic system that MathematicaⓇ12 can solve. The JHF problem has been solved with the help of Improved Reliable Computational Methods (I-RCMs), and a review of the methods has been given. Also, published facts are used to make comparisons. As further evidence of the accuracy and dependability of the proposed methods, the maximum error remainder
... Show MoreIn this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.
The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the
... Show Morehis study aimed to investigate the usability of Recycled Concrete Aggregate (RCA) in warm mix asphalt (WMA) as the implementation of sustainable construction technology. Five replacement rates (0%, 25%, 50%, 75%, and 100%) were tested for the coarse fraction of virgin aggregate (VA) with 3 types of RCA: untreated RCA, HL-treated RCA, and HCL-treated RCA. Scanning electron microscopy (SEM) analyses were performed to investigate the surface morphology for both treated and untreated RCA. The optimum asphalt cement content for every substitution rate was determined using Marshall mix design method. Thereafter, asphalt concrete specimens were prepared using the optimum asphalt cement content, followed by the evaluation of their performance prope
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In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error ( λ ) in the model (SPSEM), estimated the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo
... Show Moreالوصف In this time, most researchers toward about preparation of compounds according to green chemistry. This research describes the preparation of 2-fluoro-5-(substituted benzylideneamino) benzonitrile under reflux and microwave methods. Six azomethine compounds (B1-6) were synthesized by two methods under reflux and assisted microwave with the comparison between the two methods. Reflux method was prepared of azomethine (B1-6) by reaction of 5-amino-2-fluorobenzonitrile with some aldehyde derivatives with (50–100) mL of absolute ethanol and some quantity of GAA and time is limited between (2–5) hours with a yield between (60–70) percent with recrystallization for appropriate solvents. But the microwave-assisted method was synthe
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
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