Feasibility of biosorbent of England bamboo plant origin was tested for removal of priority metal ions such as Cu and Zn from aqueous solutions in single metal state. Batch single metal state experiments were performed to determine the effect of dosage (0.5, 1 and 1.5 g), pH (3, 4, 4.5, 5 and 6), mixing speed (90, 111, 131, 156 and 170 rpm), temperature (20, 25, 30 and 35 °C) and metal ion concentration (10, 50, 70, 90 and 100 mg/L) on the ability of dried biomass to remove metal from solutions which were investigated. Dried powder of bamboo removed (for single metal state) about 74 % Cu and 69% Zn and maximum uptake of Cu and Zn was 7.39 mg/g and 6.96 mg/g respectively, from 100 mg/L of synthetic metal solution in 120 min. of contact time at pH 4.5 and 25°C with continuous stirring at 170 rpm. Experimental results have been analyzed using Langmuir and Freundlich isotherms. Both equilibrium sorption isotherms were found to represent well the measured sorption data, but Freundlich isotherm was better than Langmuir isotherm. The effect of time was studied and the rate of removal of Cu (II) and Zn (II) ions from aqueous solution by bamboo plant was found. The rates of sorption of copper and zinc were rapid initially within 5-15 minutes and reached a maximum in about 60 minutes.
In this study, a fast block matching search algorithm based on blocks' descriptors and multilevel blocks filtering is introduced. The used descriptors are the mean and a set of centralized low order moments. Hierarchal filtering and MAE similarity measure were adopted to nominate the best similar blocks lay within the pool of neighbor blocks. As next step to blocks nomination the similarity of the mean and moments is used to classify the nominated blocks and put them in one of three sub-pools, each one represents certain nomination priority level (i.e., most, less & least level). The main reason of the introducing nomination and classification steps is a significant reduction in the number of matching instances of the pixels belong to the c
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No-fines concrete is an advanced pavement material known for its strong drainage capabilities, making it a widely used rigid road surface. With growing demand for reduced cement content due to industrial advancements, researchers have explored epoxy resin as a partial or total cement replacement. This study examines the mechanical properties of no-fines concrete with varying epoxy replacement levels and applies KENSLAB analysis for pavement thickness design. Seven concrete mixes were prepared with epoxy replacing cement at 100%, 95%, 75%, 55%, 35%, and 15%. Mechanical tests, including compressive strength, flexural strength, modulus of elasticity, bulk density, water absorption, and durability (wet-dry), were conducted after 7 and 2
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<span>Digital audio is required to transmit large sizes of audio information through the most common communication systems; in turn this leads to more challenges in both storage and archieving. In this paper, an efficient audio compressive scheme is proposed, it depends on combined transform coding scheme; it is consist of i) bi-orthogonal (tab 9/7) wavelet transform to decompose the audio signal into low & multi high sub-bands, ii) then the produced sub-bands passed through DCT to de-correlate the signal, iii) the product of the combined transform stage is passed through progressive hierarchical quantization, then traditional run-length encoding (RLE), iv) and finally LZW coding to generate the output mate bitstream.
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This paper proposes a hybrid learning-based navigation framework that integrates classical path planning with a spiking neural network model to achieve scalable and computationally efficient robot navigation in grid - based environments. Optimal reference trajectories are generated using the Spiking Wavefront Planner (SWP) over occupancy maps derived from the KITTI Odometry dataset. These expert paths are employed to train a Super Elman Spiking Neural Network (SE-SNN) using the e-prop learning rule to capture sequential navigation decisions. The framework is evaluated across map sizes ranging from 100×100 to 400×400 and compared with classical planners such as A* and D* Lite. Results show that the proposed SWP-SE-SNN model reduces plannin
... Show MoreOptical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using M
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