Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, to find the optimal solution. This method also included multiple adaptive and random variables to guarantee that the solution space was explored and used in various optimization tasks. When all criteria are considered, the results of this study show that the SSA is efficient for least-distance path allocation. The simulation findings reveal a significant improvement over the well-known particle swarm optimization (PSO) algorithm, with recycling and disposal costs decreasing by 10% to 30%.
The growing emphasis on sustainable construction has prompted interest in repurposing agricultural by-products as alternatives to conventional aggregates in asphalt mixtures. While natural sand is widely available, its use can lead to less stable, more tender mixes, which can limit various specifications. This study explores the potential of palm date seed (PDS) powder as a partial and full replacement for natural sand in asphalt concrete. A series of laboratory tests was conducted to evaluate the effect of PDS incorporation on the mechanical and durability performance of asphalt mixtures, including Marshall properties, resilient modulus, fatigue resistance, moisture susceptibility, and permanent deformation. Additionally, microstructural a
... Show MoreThe aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).
Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. The frequency domain is well suited for embedding in image, since hiding in this frequency domain coefficients is robust to many attacks. This paper proposed hiding a secret image of size equal to quarter of the cover one. Set Partitioning in Hierarchal Trees (SPIHT) codec is used to code the secret image to achieve security. The proposed method applies Discrete Multiwavelet Transform (DMWT) for cover image. The coded bit stream of the secret image is embedded in the high frequency subbands of the transformed cover one. A scaling factors ? and ? in frequency domain control the quality of the stego
... Show MoreThe software-defined network (SDN) is a new technology that separates the control plane from data plane for the network devices. One of the most significant issues in the video surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the video from the cameras. In this paper, two methods are proposed to solve this problem. The first method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).
... Show MoreContent-based image retrieval has been keenly developed in numerous fields. This provides more active management and retrieval of images than the keyword-based method. So the content based image retrieval becomes one of the liveliest researches in the past few years. In a given set of objects, the retrieval of information suggests solutions to search for those in response to a particular description. The set of objects which can be considered are documents, images, videos, or sounds. This paper proposes a method to retrieve a multi-view face from a large face database according to color and texture attributes. Some of the features used for retrieval are color attributes such as the mean, the variance, and the color image's bitmap. In add
... Show MoreCoagulation is the most important process in drinking water treatment. Alum coagulant increases the aluminum residuals, which have been linked in many studies to Alzheimer's disease. Therefore, it is very important to use it with the very optimal dose. In this paper, four sets of experiments were done to determine the relationship between raw water characteristics: turbidity, pH, alkalinity, temperature, and optimum doses of alum [ .14 O] to form a mathematical equation that could replace the need for jar test experiments. The experiments were performed under different conditions and under different seasonal circumstances. The optimal dose in every set was determined, and used to build a gene expression model (GEP). The models were co
... Show MoreThe COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
... Show MoreCobalt substituted nickel copper ferrite samples with general formula Ni0.95-xCoxCu0.05Fe2O4, where (x= 0.00, 0.01, 0.02, 0.03, 0.04 and 0.05) were prepared by solid-state reactions method at 1373 K for 4h. The samples prepared were examined by X-ray diffraction (XRD(, atomic force microscope (AFM), Fourier transform infra-red spectroscopy (FTIR) and Vickers hardness. X-ray diffraction patterns confirm the formation of a single phase of cubic spinel structure in all the prepared samples . XRD analysis showed that the increase in the cobalt concentration causes an increase in the lattice constant, bulk density (ρm) and the x-ray density (ρx), whereas porosity (p) and crystallite size (D) decrease. The Topography of the surface observed
... Show MorePAN/PMMA) with different blend ratios (80/20, 75/25,70/30,65/35, and 60/40) wt% undoped and doped with various lithium (Li) salts (LiCO3, Li2SO4H2O, and LiCl) at 20 wt %. Different techniques were employed to investigate the composition and optical properties of the prepared blend samples undoped and doped with Lithium salts like FT-IR and UV-Visible spectroscopies. The optical properties analysis declared that the energy gap increased from (4.0 eV to 4.20 eV) by increasing of PMMA ratio from 20 to 40 wt %. In contrast, the energy gap reduced and shifted toward the low energy side by adding lithium salts; the minimum energy gap value was 2 eV obtained from 65 % PAN and 35 % PMMA doped with Li2CO3. The optical constants were determ
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