The designed crawler scheduling system is a JEE application based on Quartz scheduling framework that sends crawler tasks to the crawler control system automatically or manually at regular intervals. The crawler contr...
The designed crawler scheduling system is a JEE application based on Quartz scheduling framework that sends crawler tasks to the crawler control system automatically or manually at regular intervals. The crawler control system visually manages and controls the shipping crawlers. The HttpCilent-centric crawler system crawls the shipping website. The message queue ActiveMQ is used as a message middleware for the crawler control system and the crawler system to achieve asynchronous communication and reduce coupling. In this system, front-end frameworks such as Bootstrap, AngularJS, and SweetAlert are used to implement a visual scheduling system and data visualization system. Change the crawler deployment environment by deploying containers through Docker. Add Selenium dynamic page processing for shipping website. Adding message queues and MongoDB database data storage. By adopting a series of techniques and designing, testing and quality assurance of the system, we aim to make the crawler more stable and efficient, and to achieve security, stability and ease of maintenance of the system.
In the contemporary phase of big data, data visualization is one of the challenging segment of the discovery process. For a classifier, the primary goal is to identify the hidden levels of big data. The performance of...
In the contemporary phase of big data, data visualization is one of the challenging segment of the discovery process. For a classifier, the primary goal is to identify the hidden levels of big data. The performance of classifiers depends on the feature space, number of classes and size of the data. To improve the reliability, efficiency and accuracy of the classifiers, new algorithms are required for analysis. This paper enables classification and visualization of information on diseases using a Deep Learning based Convolution Neural Network classifier. For feature selection and handling massive data in analysis of multivariate data is performed using particle swarm optimization (PSO) and principal component analysis (PCA) techniques. Real-world datasets are utilized for demonstration of the proposed learning algorithm. Deep learning classifiers are scientifically higher and offers better performance when compared to other classifiers according to the comparative study.
The objective of this work is to show how advanced optimization tools can be used for hydraulic turbine design, taking the example of a Francis runner design (new or refurbishment project). The public test case consid...
The objective of this work is to show how advanced optimization tools can be used for hydraulic turbine design, taking the example of a Francis runner design (new or refurbishment project). The public test case considered corresponds to a R&D turbine model of specific speed Ns = 0.5, originally developed at the Hydraulic Machinery Laboratory (LMH) of École Polytechnique Fédérale de Lausanne (EPFL). Firstly, a standard Computational Fluid Dynamics (CFD) process is used to predict performances, in the form of efficiency and cavitation behaviour. It features structured mesh for distributor (stay vane and guide vane), runner and draft tube. Automatic scripts are created to run computations for several guide vane openings and rotation speeds, covering the whole range of operating conditions, and allowing to obtain numerical hill charts of efficiency and minimum pressure to predict the occurrence of cavitation. Secondly, some operating points are purposefully selected for the optimization and objectives are defined to maximize efficiency while constraints are set for preventing cavitation. To continue with, a parametric blade model is defined: 3D blade shape is obtained from blade to blade sections and a stacking law. Sections are defined by camber and thickness. Finally, a Surrogate Based optimization (SBO) with Evolutionary Algorithm (EA) is used for searching a global optimum. Design of Experiment (DOE) techniques are employed to efficiently define a database. Dynamic monitoring, data-mining and visualization tools are used; including Leave-One-Out (LOO), Analysis of Variance (ANOVA) and Self-Organizing Maps (SOM), with the objective of facilitating surrogate reliability assessment and a comprehensive understanding of key factors of the problem studied. This methodology is tested iteratively with the Francis Runner Hydraulic design: a first optimization is run, analysed and used to define a second optimization that shows increased benefits in particular for Best Effici
Dual-energy (DE) for quantitative material discrimination has emerged as a promising application of microCT to increase contrast discrimination in preclinical studies. Here we present a protocol designed to optimize D...
Dual-energy (DE) for quantitative material discrimination has emerged as a promising application of microCT to increase contrast discrimination in preclinical studies. Here we present a protocol designed to optimize DE image subtraction for contrast enhanced studies in rodents, employing iodine-based contrast medium (CM). Our investigation used an Albira ARS commercial unit, not specifically designed for quantitative CT tasks. DE subtraction was divided into stages that were independently analyzed: acquisition, volume reconstruction, image registration and image weighting. The DE radiological techniques (low- and high- energy) had been previously optimized to enhance the visualization of iodine-based CM. An independent reconstruction was needed to guarantee linearity between iodine intensity and its concentration for high energy acquisition; it also reduced structured noise occasionally produced by the microCT reconstruction software over uniform regions and improved bone visualization. Image registration was optimized combining an affine transformation with a non-linear transformation determined with the Free-Form Deformation algorithm. Two subtraction weight factors were determined: one that maximized the contrast-to-noise ratio (CNR) of iodine mixed with soft-tissue-equivalent resin and another that minimized CNR between bone-like rods and soft-tissue-equivalent material. A pilot test of the optimized protocol was performed on a rat injected with a continuous flow of CM.
Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning scie...
Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin’s rule for decision making formulated in London 1772, he called “Prudential Algebra” with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.
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