PulsatioMech: An Open-Source MATLAB Toolbox for Seismocardiography Signal Processing
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This paper summarizes and presents PulsatioMech: an open-source MATLAB toolbox for seismocardiography (SCG) signal processing. The toolbox may be found here: https://github.com/nzavanelli/SCG_master_toolbox PulsatioMech is currently under development as a common tool to promote new studies and discoveries in the use of cardiac mechanical signal for wearable health monitoring. This toolbox is designed to assist users in analyzing SCG signals without the need to devote significant effort into signal processing and coding tasks. Simultaneously, it provides a uniform basis to assess the reproducibility of works based on this toolbox, including those cited here [1-6]. The referenced works contain a great deal more detail regarding the specific algorithms implemented here, whereas this paper will present a short overview of the PulsatioMech Toolbox.Keywords:
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Taking the small gear pump for example,aiming at the minimum volume,this design creates a structure optimum-design model,based on its requests and characteristics.Afterwards,the optimum results were figured out by making use of the optimum toolbox of MATLAB.The results prove that it is more convenient to solve the optimum questions by using optimum toolbox of MATLAB than traditional methods.
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In this paper we present a new toolbox that is developed for perceptual computing (PerC). This toolbox provides all requirements to implement PerC applications on different platforms and hence will promote perceptual computers in various domains. We will demonstrate the effectiveness of the developed procedures and will also describe an example of implementing a perceptual computer with the proposed toolbox.
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By sorting and improving the GA toolbox designed by university of Sheffield based on MATLAB,a new simple and reliable computing framework based on MATLAB is presented in this paper.A typical test function is chosen for detecting the improved toolbox.The experimental resets show the improved toolbox has good performance on function optimization.
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Based on the charge materials database,a optimal charging system by using C~(++)Builder(BCB) software has been developed.the least cost charging has been obtained by using the optimal toolbox function in Matlab.A compared example was alse provided.
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Visually recognising a traversed route - regardless of whether seen during the day or night, in clear or inclement conditions, or in summer or winter - is an important capability for navigating robots. Since SeqSLAM was introduced in 2012, a large body of work has followed exploring how robotic systems can use the algorithm to meet the challenges posed by navigation in changing environmental conditions. The following paper describes OpenSeqSLAM2.0, a fully open source toolbox for visual place recognition under changing conditions. Beyond the benefits of open access to the source code, OpenSeqSLAM2.0 provides a number of tools to facilitate exploration of the visual place recognition problem and interactive parameter tuning. Using the new open source platform, it is shown for the first time how comprehensive parameter characterisations provide new insights into many of the system components previously presented in ad hoc ways and provide users with a guide to what system component options should be used under what circumstances and why.
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This chapter contains sections titled: Understanding Toolbox Administering Toolbox Configuring Toolbox Alternatives to Toolbox Summary
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This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning.
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Visually recognising a traversed route - regardless of whether seen during the day or night, in clear or inclement conditions, or in summer or winter - is an important capability for navigating robots. Since SeqSLAM was introduced in 2012, a large body of work has followed exploring how robotic systems can use the algorithm to meet the challenges posed by navigation in changing environmental conditions. The following paper describes OpenSeqSLAM2.0, a fully open-source toolbox for visual place recognition under changing conditions. Beyond the benefits of open access to the source code, OpenSeqSLAM2.0 provides a number of tools to facilitate exploration of the visual place recognition problem and interactive parameter tuning. Using the new open source platform, it is shown for the first time how comprehensive parameter characterisations provide new insights into many of the system components previously presented in ad hoc ways and provide users with a guide to what system component options should be used under what circumstances and why.
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