One common heavy metal that is extremely harmful to the kidneys, reproductive system, and nervous system of humans is lead (Pb). This study aimed to investigate the effectiveness of a novel nanocomposite adsorbent, synthesised from polypyrrole, zinc oxide, and nickel (PPy/ZnO-NiO), in eliminating Pb(II) ions from a waterbased solution. This adsorbent offers excellent metal selectivity, environmental stability, ease of manufacture, and reusability. Several techniques, namely XRD, FTIR, TGA, SEM, TEM, EDX, and BET, were employed to characterize the synthesised nanocomposite adsorbent. The study examined the impact of multiple factors influencing the adsorption process, including pH, temperature, contact period, metal ion concentration, and ad

YY Lazim, NAB Azizan, 2nd International Conference on Innovation and Entrepreneurship, 2014

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

Nanoferrite materials have been synthesized by sol-gel auto combustion method. The effect of doping different percentages of Y₂O₃ (0.34 µm) on the physical and mechanical properties of selected mixed ferrite [(Li_2.5Fe_0.5) 0.9(Co₄Fe₂O₄) _0.1] by adding 10% Cobalt ferrite was studied. Physical properties (i.e. .density, porosity and water absorption) were affected by the doping, where the density increased about 32% at 6 wt% Y₂O₃, while porosity has a drastically decreased about 80% at 6% Y₂O₃ and has a correlation effect on the mechanical properties(Splitting  tensile strength and Vicker

When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

In this paper, Nordhaus-Gaddum type relations on open support independence number of some derived graphs of path related graphs under addition and multiplication are studied.

Rationing is a commonly used solution for shortages of resources and goods that are vital for the citizens of a country. This paper identifies some common approaches and policies used in rationing as well asrisks that associated to suggesta system for rationing fuelwhichcan work efficiently. Subsequently, addressing all possible security risks and their solutions. The system should theoretically be applicable in emergency situations, requiring less than three months to implement at a low cost and minimal changes to infrastructure.

The dielectric constant of most polymers is very low; the addition of TiO2 particles into the polymers provides an attractive and promising way to reach a high dielectric constant. Polymer-based materials with a high dielectric constant show great potential for energy storage applications. Four samples were prepared, one of them was polyurethane (PU) and the other were PU with different weight percent (wt %) of TiO2 (0.1, 0.2, 0.3) powder AFM test was used to distinguish the nanoparticles. The result shows that the most shape of these nanoparticles are spherical and the roughness average is 0.798 nm. The dielectric properties were measured for all samples before and after the exposure to the UV radiation. The result illustrates that the