Energy Estimation Tool Research Articles

Designing Collagen-Binding Peptide with Enhanced Properties Using Hydropathic Free Energy Predictions.

Collagen is fundamental to a vast diversity of health functions and potential therapeutics. Short peptides targeting collagen are attractive for designing modular systems for site-specific delivery of bioactive agents. Characterization of peptide-protein binding involves a larger number of potential interactions that require screening methods to target physiological conditions. We build a hydropathy-based free energy estimation tool which allows quick evaluation of peptides binding to collagen. Previous studies showed that pH plays a significant role in collagen structure and stability. Our design tool enables probing peptides for their collagen-binding property across multiple pH conditions. We explored binding features of currently known collagen-binding peptides, collagen type I alpha chain 2 sense peptide (TKKTLRT) and decorin LRR-10 (LRELHLNNN). Based on these analyzes, we engineered a collagen-binding peptide with enhanced properties across a large pH range in contrast to LRR-10 pH dependence. To validate our predictions, we used a quantum-dots-based binding assay to compare the coverage of the peptides on type I collagen. The predicted peptide resulted in improved collagen binding. Hydropathy of the peptide-protein pair is a promising approach to finding compatible pairings with minimal use of computational resources, and our method allows for quick evaluation of peptides for binding to other proteins. Overall, the free-energy-based tool provides an alternative computational screening approach that impacts protein interaction search methods.

A novel efficient coplanar QCA full adder and full subtractor design

ABSTRACT Quantum-dot Cellular Automata (QCA) nanotechnology is an alternative technology with high speed, high density and low power for designing nanoscale circuits. A novel design of Full Adder-Subtractor based on full subtractor using single layer is proposed. The proposed architecture has a major advantage in terms of complexity, area, latency, and power consumption as compared to previous designs. The proposed QCA full subtractor showed higher performance concerning area with a reduction of 66%, and complexity with a reduction of 51% over best existing circuit designs. However, the proposed design of full Adder-Subtractor achieved a reduction of 74% in area, with 70% improvement in complexity, 33% reduction in latency by using two clock phases, and 95% improvement in cost needed over the best reported circuits using single-layer design. Total cell area and cost for the Full Adder-Subtractor were 0.01 μm2 and 0.07, respectively. Results showed that power consumption for the novel design was minimal. Therefore, the suggested Full Adder-Subtractor provides 86% less total energy consumption for 0.5Ek tunnelling energy level. These designs were tested and simulated using the freely known QCA Designer tool version 2.0.3. The energy dissipation result was realised by using the QCAPro energy estimation tool.

Comparative Weibull distribution methods for reliable global solar irradiance assessment in France areas

This paper investigates the Weibull distribution analysis for an accuracy global solar irradiance assessment considering period measurements based on several and grouping years. The problem study in this paper is to find a global solar irradiance model in order to provide accurate estimation of PV energy output allowing better sizing of PV installation. The aim is to select the best Weibull fit procedure for obtaining reliable global solar irradiance from sun that incident in a place during time periods to estimate its yearly energy generation from PV plant. Comparisons are carried out between Graphic, Moments and Maximum Likelihood methods with two different databases (real data on-site measurements and SODA website database). These comparisons are made on global solar irradiance frequency distributions and annual solar irradiance assessment for different French locations. The originality of the paper is that the obtained results prove that the Maximum Likelihood method fits better with the global solar irradiance distribution while the Moment method provides an annual solar irradiance prediction. Thereby, we exploit the obtained results from the Moment method to achieve a more accurate solar energy forecasting model. This resulting model can be implemented for providing one solar energy estimation tool for PV plant sites.

Alpha particles energy estimation from track diameter development in a CR-39 detector

The slight nonlinearity in temporal development of tracks diameter in CR-39 nuclear track detectors is examined with the aim of attempting to find if such nonlinearity can be directly related to the charged particle energy. Narrowly spaced etching time-diameter experimental data for alpha particles at five energy values and for one additional energy value etched at five different temperatures are obtained. Initial results show good indication that measuring such time-diameter relationship can form a useful energy estimation tool. Good consistency with other independent published results is obtained.

An XML-based machining energy estimation tool from process plans

Excessive energy consumption has become a worldwide issue in today’s manufacturing industry. Software tools for estimating manufacturing energy consumption that could later be used to integrate with CAD/CAM systems are in demand. This research develops software tools for estimating manufacturing energy consumption in machining operations based on manufacturing process plans. This study first reviews literature and background in related areas and then presents the method to calculate manufacturing energy in machining operations. eXtended Markup Language (XML) has been adopted as the knowledge representation language for machining process plans and forms one of the inputs for energy estimation. Since XML plays an important role in estimating machining energy, this article introduces XML validation and parsing. The method is demonstrated via case studies for machining energy estimation in machining operations. The method will assist users who have little knowledge about energy computations to estimate energy consumption during the manufacturing phase. Such energy estimation can be used to redesign the part and assemblies, leading to products with reduced machining energy.

An Accurate Instruction-Level Energy Estimation Model and Tool for Embedded Systems

Estimating the energy consumption of applications is a key aspect in optimizing embedded systems energy consumption. This paper proposes a simple yet accurate instruction-level energy estimation model for embedded systems. As a case study, the model parameters were determined for a commonly used ARM7TDMI-based microcontroller. The total energy includes the energy consumption of the processor core, Flash memory, memory controller, and SRAM. The model parameters are instructions opcode, number of shift operations, register bank bit flips, instructions weight and their Hamming distance, and different types of memory accesses. Also, the effect of pipeline stalls have been considered. In order to validate the proposed model, a physical hardware platform equipped with energy measurement capabilities was developed. We have conducted experiments on several embedded applications from MiBench benchmark suite and the results show less than 6% error in the energy consumption estimation. We have also developed an energy profiler tool for the systems that use ARM7TDMI processors by embedding the model parameters in an instruction-level profiler from the SimpleScalar toolset which provides valuable information and guidelines for software energy optimization.

Web-based energy exploration tool for embedded systems

We describe a Web-based energy estimation tool for embedded systems. An interesting feature of this tool is that it performs real-time cycle-accurate energy measurements on a hardware prototype of the processor. The authors describe the various steps involved in using the tool and present case studies to illustrate its utility.