Sub-threshold operation has received a lot of attention in limited performance applications.However, energy optimization of sub-threshold circuits should be performed with the concern of the performance limitation of such circuit. In this paper, a dual size design is proposed for energy minimization of sub-threshold CMOS circuits. The optimal downsizing factor is determined and assigned for some gates on the off-critical paths to minimize the energy at the maximum allowable performance. This assignment is performed using the proposed slack based genetic algorithm which is a heuristic-mixed evolutionary algorithm. Some gates are heuristically assigned to the original and the downsized design based on their slack time determined by static timing analysis. Other gates are subjected to the genetic algorithm to perform an optimal downsizing assignment taking into account the previous assignments. The algorithm is applied for different downsizing factors to determine the optimal dual size for low energy operation without a performance degradation. Experimental results are obtained for some ISCAS-85 benchmark circuits such as 74283, 74L85, ALU74181, and 16 bit ripple carry adder. The proposed design shows an energy per cycle saving ranged from (29.6% to 56.59%) depending on the utilization of available slack time from the off-critical paths. © School of Engineering, Taylor’s University.
Objective: The goal of this research is to load Doxorubicin (DOX) on silver nanoparticles coupled with folic acid and test their anticancer properties against breast cancer. Methods: Chitosan-Capped silver nanoparticles (CS-AgNPs) were manufactured and loaded with folic acid as well as an anticancer drug, Doxorubicin, to form CS-AgNPs-DOX-FA conjugate. AFM, FTIR, and SEM techniques were used to characterize the samples. The produced multifunctional nano-formulation served as an intrinsic drug delivery system, allowing for effective loading and targeting of chemotherapeutics on the Breast cancer (AMJ 13) cell line. Flowcytometry was used to assess therapy efficacy by measuring apoptotic induction. Results: DOX and CS-Ag
... Show MoreThe objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost, loss etc. while maintaining an acceptable system performance in terms of limits on generators real and reactive powers, line flow limits etc. The OPF solution includes an objective function. A common objective function concerns the active power generation cost. A Linear programming method is proposed to solve the OPF problem. The Linear Programming (LP) approach transforms the nonlinear optimization problem into an iterative algorithm that in each iteration solves a linear optimization problem resulting from linearization both the objective function and constrains. A computer program, written in MATLAB environme
... Show MoreThe topic of urban transformations has attracted the attention of researchers as it is one of the basic issues through which cities can be transformed towards sustainability. A specific level of transformation levels according to a philosophical concept known as a crossing. This article has relied on a specific methodology that aims to find a new approach for urban transformation based on the crossing concept. This concept derives from philosophical entrances based on the concepts of (being, process, becoming, and integration). Four levels have been for the crossing are (normal, ascending, leap, and descending). Each of these levels includes specific characteristics that distinguish it. The results showed that there is no descending
... Show MoreVehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c
... Show MoreOwing to their cost-effectiveness and the natural abundance of magnesium, magnesium-ion batteries (MIBs) were introduced as encouraging alternatives to Lithium-ion batteries. Following the successful synthesis of carbon nano-tube, its B and N doped derivatives which were doped with B and N enjoyed the attention of researchers as novel anode materials (AM) for MIBs. Here, we investigated a BC2N nano-tube (BC2NNT) as an encouraging AM for MIBs. To have a deeper understanding of the electrochemical properties, cycling stability, specific capacity (SC) and the adsorption behavior of this nano-tube, first-principles density functional theory computations were performed. By performing NMR calculations, we identified two types of non-aromatic hexa
... Show MoreFeature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
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