Traditional volumetric asphalt mix design methods do not directly evaluate cracking and rutting resistance, which may result in mixtures with inadequate field performance despite satisfying conventional volumetric requirements. Balanced Mix Design (BMD) has been introduced to address this limitation by incorporating performance testing. However, it remains unclear whether additive modification alone can recover mixtures that do not satisfy BMD criteria, or whether volumetric redesign (binder content optimization) is necessary. Therefore, this study investigated the effectiveness of additive modification before and after BMD redesign using IDEAL-CT and IDEAL-RT performance indices. Three additive systems were evaluated: SBS polymer,

Surface runoff is considered one of the most significant water resources in arid and semi-arid environments. Estimating the volume of surface runoff through the application of Geographic Information Systems (GIS), along with maps detailing the geomorphological and geological characteristics of the Wadi Haran basin, is an essential process. This estimation is supported by mathematical equations based on the Soil Conservation Service Curve Number method (SCS-CN), which is among the most widely used approaches for calculating runoff volume. The study area, Wadi Haran basin, covers approximately 1,895 km². The Curve Number (CN) was found to be 92, with runoff volume (QV) values ranging between 582.71 m³ and 12.85 m³. The total surfa

This study tackles a fourth-order inverse problem involving a cantilever beam with nonlocal conditions to simultaneously calculate the beam’s displacement and an unknown time-dependent coefficient. A finite difference approach is suggested to discretize the hyperbolic fourth-order equation. A stability analysis for the proposed scheme is also provided. The indirect problem is the minimization of the misfit function. The goal of the minimization algorithm is to reduce the gap between the measured (noisy) data and the numerical computed solution provided by the model. To achieve stable results, Tikhonov’s regularization technique is employed, and two numerical test examples are shown to illustrate the suggested scheme's reliabilit

This work aims to find a solution to the problem under investigation and to study non-local boundary-value problems for rectangular domains and two-dimensional thirdorder partial differential equations (PDEs). A finite-difference method combined with the trapezoidal rule is used to solve problems. The numerical results were determined to be steady and accurate.

Hsieh-Wildenthal (HW) and G-matrix PF1, (GXPF1) interactions for 40Ca and 48Ca, respectively. The 40Ca was considered to be consisted of 32S as a core and 1d3/21f7/2 subshells as a model space. The 48Ca was considered to be consisted of 40Ca as a core and 1f7/22p3/21f5/2 2p1/2 subshells as a model space. The obtained one body-density matrix elements (OBDME) for both interactions for the studied Coulomb transitions:  For 40Ca, the three non-normal parity transitions (C3): ,  and  and one C5 transitions,  .  For 48Ca, the two C2 transitions:  and  and one C4 transitions  were used in parallel with the transformed harmonic-oscillator basis to compute charge density, elastic electron scattering differential cross-section and ela

Congestion management features operate to control congestion once it occurs. One way that network elements handle an overflow of arriving traffic is to use a queuing algorithm to sort the traffic, and then determine some methods of prioritizing it onto an output link. Each queuing algorithm was designed to solve a specific network traffic problem and has a particular effect on the network performance. The work presented in this thesis deals with important issue that is the quality of service (QoS) techniques, which can be integrated to enhance the operation of the network. The quality of service is the collective effect on service performance, which determines the degree of satisfaction of a user of the service. In this thesis, packet sched

Path planning in autonomous robotic systems (ARS) is challenging, especially in dynamic or uncertain environments. Many classical methods are computationally expensive and lack adaptability to real-world scenarios. In order to improve the overall path-planning capabilities of robots; this paper introduces a new smart robotic navigation system which uses Software Defined Network (SDN) and Multi-Spike Elman Neural Network (MS-ENN). The introduced system includes an innovative way to encode temporal information using multiple spikes which can capture much greater amounts of detail about changing environmental characteristics than conventional artificial neural networks. Additionally, it includes a spiking wave-front planner (SWP) to pr

This study was conducted on the possibility of manufacturing kids’ foods fortified by legumes. Three raw materials of boiled vegetables (carrots, potatoes and zucchini) were used, one of the pre-boiled legumes was added to the mixture, which included chickpeas, lentils, mung, soybean, fenugreek, by the percentage of 5% and 10%. The results of the chemical analysis showed no statistically significant differences (P <0.05) between the coefficients of moisture, ash and fiber. However, the ash ratio increased from 0.76 to 0.88% and fiber from 0.43 to 0.87%. As for protein and fat, A8 coefficient (add 10% soybean bean) recorded highest ratio of 2.54 and 0.71% respectively, the results of the analysis of mineral elements showed that the A8 coef

The current study aimed to detect artificial fraud in chemical additives (formalin, hydrogen peroxide) and to detect thickeners (starch) in imported and local dairy products and to determine their suitability for human consumption due to the high demand for their consumption by members of society, 20 samples of products were collected The local and imported milk in the Iraqi markets of the city of Baghdad consisted of 10 samples of yoghurt and 10 samples of cream. The tests were carried out, which were the detection of chemicals and additive thickeners such as formalin, hydrogen peroxide and starch, respectively, as well as the examination of the microbial load, which included the detection of colon bacteria, yeasts and molds, and the resul

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification. Different

تتميز اللغات باصواتها التي تميزها من غيرها, ولكل لغة اصواتها التي تختلف نوعا وكما , يبدو ان هناك اصواتا تتشابه في اغلب اللغات تلك هي الاصوات الصائتة او الصوائت (الالف والواو والياء) والاصوات المائعة او السائلة وما يطلق عليه (Liquids) وهي الاصوات المتوسطة بين الشدة والرخاوة , يضاف الى هاتين المجموعتين صوت اللغة , الصوت الشائع في اغلب اللغات , وقد علل سبب هذا الشيوع الى انه الصوت الاساس لصيحات الانفعال التلقائية عند ا

Transformers are a specific category of neural network design. Transformers often depend on extensive pre-training on a large scale and exhibit a notable degree of computational complexity. The disadvantage of using this method is a significant increase in computational complexity, which necessitates a significant commitment of time and computing resources in order to successfully work with these models. Transformer networks possess the desirable benefit of extracting distant characteristics effectively via their self-attention mechanism. In this paper, the Global Self-Attention Transformer module is applied to tackle these issues. The model is based on a segmentation problem called Brain-GS that works as a mechanism and encompasses

مثل اللغة العربية، إلى جانب اللغات الشقيقة لها، لهجات الخضوع العربي، والتي لا يمكن عزلها أو إنكارها. لهذه الوحدة خصائصها ومميزاتها الخاصة. هذه الخصائص والصفات جعلتنا ننظر إلى موضوع يقع بين اللغة العربية واللهجات العربية القريبة. تستخدم اللغة العربية واللغات الشقيقة لها للدعوة، من أجل توطيد النداء، معرفة محاضر وغرض استخدام أداة دون غيرها من الأدوات. استند هذا البحث إلى مقدمة وموضوعين مسبوقين بمقدمة ومتبوع

The elastic and inelastic longitudinal electron scattering form factors in of chromium isotopes (50,52Cr) isotopes were studied using the radial wave functions of a transformed harmonic oscillator potential in the local scale transformation technique. Occupation numbers from configuration mixing using the Hsieh-Wildenthal (HW) method for 50,52Cr were considered in parallel with those obtained using the adjusted occupation numbers. For shell interactions, the model space for HW interaction is restricted to the 1d3/2 and 1f7/2 subshells. The charge density distributions in the ground state and differential electron scattering cross-sections were computed. The inelastic form factors were studied by including core polarization using the

Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

—Fundus images play an essential role in ophthalmic diagnostics for the detection of many eye illnesses. The experiment begins with a thorough image preprocessing. technique, which includes clipping the circular borders, scaling the image, enhancing the contrast, removing noise, and augmenting the data. The new combined block applies to extracting distinctive deep feature representations, which help to detect the first shape of the edges of each lesion. It is namely the Attention Block and the Conv-Deconv UNET model. The attention block is subsequently implemented in order to augment the robustness and quality of feature depictions derived from a pair of DR images. The Dual Attention Block for the backbone, which is supplement

Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

This paper suggests a novel optimal inverse Radial Basis Function (RBF) neural network model for the control of Twin Rotor Aerodynamic Systems (TRAS), such as Multi-Input–Multi-Output (MIMO) systems with high nonlinearity and coupling effects between channels. After analyzing and linearizing the dynamic model, TRAS is decoupled into two Single Input Single Output (SISO) systems, thereby creating vertical (pitch model) and horizontal (yaw model) systems. The relationship between the output angle of each subsystem and the input voltage is modeled using the inverse RBF neural network. The weights, biases, centers and widths of the Gaussian function are unknown parameters of the proposed inverse neural model, and they are obtained usi

This paper considers the nonlinear homogeneous fractional Burger's equation as a type of nonlinear fractional partial differential equations (FPDE). Our goal in this paper is to show that an initial value problem (IVP) can be modified with a second initial condition when (α ∈ ( 1,2 ]) as the velocity of the movement, and the obtained solution agrees with the nature of the wave with space and time for the problem. The Caputo fractional derivative is used in all the fractional derivatives. Also, the algorithm of the Laplace transform decomposition method (LTDM) for fractional PDEs is presented. The approximate solution converges to the exact solution in Theorem 1. Also, a numerical simulation is made to confirm the theoretical resu

Let P be a right R-module, where R is a ring with identity. In the present research, a class of modules is described similar to H-μ-supplemented and μ-lifting modules. A module P is called principally H-μ-supplemented if there is a summand L of P such that pR is μ-equivalent to L for every p in P. Additionally, we present an extension of supplemented modules. A module P is considered to be principally μ-supplemented if, for every p in P, pR has a μ-supplement in P. A number of characteristics of these modules are shown, and it is demonstrated that both the Pμ-H-supplemented and Pμ-supplemented modules include the class of principally μ-lifting modules.

In this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those methods is

Today's smart engineering systems are often faced with situations that are structurally uncertain, informationally incomplete, and non-probabilistically ambiguous, especially for electrical systems. ARDL models are limited in applications in complex computational environments where the uncertainty is due to vagueness, not randomness, and assume the exact parametric representation of the models and the structure of the stochastic uncertainty. This study proposes a new soft-computing paradigm using Fuzzy Autoregressive Distributed Lag (FARDL) models and compares the performance of the Linear Programming (LP) and Quadratic Programming (QP) estimation algorithms using large-scale parallel Monte Carlo simulations to overcome these drawba

The fiscal position of governments in rentier economies depends heavily on oil revenues. The relationship between oil prices and the budget surplus or deficit is often nonlinear and characterized by complex temporal dependencies, which may limit the predictive capability of conventional econometric models. Accordingly, this study aims to forecast the Iraqi budget surplus and deficit and compare the predictive performance of the ARDL, NARDL, LSTM, 1D-CNN, and hybrid 1D-CNN-LSTM models using oil prices as the primary predictive variable. The hybrid model integrates the feature-extraction capability of One-Dimensional Convolutional Neural Networks (1D-CNN) with the ability of Long Short-Term Memory (LSTM) networks to capture long-term