Particle Swarm Optimization (PSO) system based on the distributed architecture over multiple sub-swarms is very efficient for static multi-objective optimization, but has not been considered for solving dynamic multi-...
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Particle Swarm Optimization (PSO) system based on the distributed architecture over multiple sub-swarms is very efficient for static multi-objective optimization, but has not been considered for solving dynamic multi-objective problems (DMOPs). Tracking the most effective solutions over time and ensuring good exploitation and exploration are the main challenges of solving DMOP. This study proposes a Dynamic Pareto bi-level Multi-Objective Particle Swarm Optimization (DPb-MOPSO) algorithm including two parallel optimization levels. At the first level, all solutions are managed in a single search space. When a dynamic change is successfully detected in the objective values, the Pareto ranking operator is used to enable a multiple sub-swarm’ subdivisions and processing which drives the second level of enhanced exploitation. A dynamic handling strategy based on random detectors is used to track the changes of the objective function due to time-varying parameters. A response strategy consisting in re-evaluate all unimproved solutions and replacing them with newly generated ones is also implemented. The DPb-MOPSO system is tested on a set of DMOPs with different types of time-varying Pareto Optimal Set (POS) and Pareto Optimal Front (POF). Inverted generational distance (IGD), mean inverted generational distance (MIGD), and hypervolume difference (HVD) metrics are used to assess the DPb-MOPSO performances. Quantitative results are analyzed using Friedman's analysis of variance, while stability is analyzed using Lyapunov's theorem. The DPb-MOPSO is more robust than several dynamic multi-objective evolutionary algorithms in solving 21 complex problems over a range of changes in both the POS and POF. On IGD and HVD, DPb-MOPSO can solve 8/13 and 7/13 of the 13 UDF and ZJZ functions with moderate changes. DPb-MOPSO is able to resolve 4/8 FDA and DMOP benchmarks with severe changes to the MIGD, and 5/8 with moderate changes. DPb-MOPSO assumes 4/8 of the solving function on IGD
We initiate the study of computational complexity of graph coverings, aka locally bijective graph homomorphisms, for graphs with semi-edges. The notion of graph covering is a discretization of coverings between surfac...
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The Plasmodium parasite, which causes malaria is transmitted by Anopheles mosquitoes, and remains a major development barrier in Africa. This is particularly true considering the conducive environment that promotes th...
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Spectral imaging is a broad term that refers to the use of a spectroscopy technique to analyze sample surfaces, collecting and representing spatially referenced signals. Depending on the technique utilized, it allows ...
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Spectral imaging is a broad term that refers to the use of a spectroscopy technique to analyze sample surfaces, collecting and representing spatially referenced signals. Depending on the technique utilized, it allows the user to reveal features and properties of objects that are invisible to the human eye, such as chemical or molecular composition. However, the interpretability and interaction with the results are often limited to screen visualization of two-dimensional representations. To surpass such limitations, augmented reality emerges as a promising technology, assisted by recent developments in the integration of spectral imaging datasets onto three-dimensional models. Building on this context, this work explores the integration of spectral imaging with augmented reality, aiming to create an immersive toolset to increase the interpretability and interactivity of the results of spectral imaging analysis. The procedure follows a two-step approach, starting from the integration of spectral maps onto a three-dimensional models, and proceeding with the development of an interactive interface to allow immersive visualization and interaction with the results. The approach and tool developed present the opportunity for a user-centric extension of reality, enabling more intuitive and comprehensive analyses with the potential to drive advancements in various research domains.
The diagnosis of many diseases involves invasive detection methods, which are both painful and stressing for patients. In the last decades, the ever-growing development in electronic nose (E-Nose) technology made them...
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ISBN:
(数字)9781665467315
ISBN:
(纸本)9781665467322
The diagnosis of many diseases involves invasive detection methods, which are both painful and stressing for patients. In the last decades, the ever-growing development in electronic nose (E-Nose) technology made them great candidates for non-invasive disease detection methods. Such devices mimic the human olfactory system through a set of sensors which produce signals that can be associated with diseases. Recently, a class of low-cost and innovative ionogel sensors, developed by our group demonstrated their full applicability in E-Nose systems, opening a new and promising approach to the field. However, the operation of such sensor needs a background calibration phase which relies on the correct characterization and parameterization of the corresponding electrical sensor *** paper proposes a model characterization methodology based on a set of frequency responses acquisitions of the sensor, under several humidity conditions. To obtain a flexible acquisition tool capable of acquiring accurate results, an analog front-end (AFE) circuit to interface with the interdigitated electrode (IDE) sensors is presented. Such AFE circuit is fully implemented using a programmable system-on-a-chip (PSoC), helping to reduce system size and cost. Lastly, a comparison between the electrical model and data acquired with the proposed system is presented.
The liver is one of the most critical metabolic organs in vertebrates due to its vital functions in the human body, such as detoxification of the blood from waste products and medications. Liver diseases due to liver ...
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With no associated devices, device-free localization (DFL) uses wireless sensor networks to find a target. DFL has created comprehensive applications, smart cities and the Internet of Things (IoT), among other things....
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Due to a successful commitment to developing an international education offer, the number of foreign students enrolled in studies at Riga Technical University (RTU) is increasing significantly every year. In this pape...
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According to the classical theory of Brownian motion, the mean-squared displacement of diffusing particles evolves linearly with time, whereas the distribution of their displacements is Gaussian. However, recent exper...
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According to the classical theory of Brownian motion, the mean-squared displacement of diffusing particles evolves linearly with time, whereas the distribution of their displacements is Gaussian. However, recent experiments on mesoscopic particle systems have discovered Brownian yet non-Gaussian regimes where diffusion coexists with an exponential tail in the distribution of displacements. Here we show that, contrary to the present theoretical understanding, the length scale λ associated with this exponential distribution does not necessarily scale in a diffusive way. Simulations of Lennard-Jones systems reveal a behavior λ∼t1/3 in three dimensions and λ∼t1/2 in two dimensions. We propose a scaling theory based on the idea of hopping motion to explain this result. In contrast, simulations of a tetrahedral gelling system, where particles interact by a nonisotropic potential, yield a temperature-dependent scaling of λ. We interpret this behavior in terms of an intermittent hopping motion. Our findings link the Brownian yet non-Gaussian phenomenon with generic features of glassy dynamics and open new experimental perspectives on the class of molecular and supramolecular systems whose dynamics is ruled by rare events.
In human, the abnormality in lung causes a severe respiratory problem and breathing difficulties. Tuberculosis (TB) is one of the common lung abnormality caused due a bacterium named Mycobacterium tuberculosis. TB inf...
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