The k-Colour Shortest Path Problem is a variant of the classic Shortest Path Problem. This problem consists of finding a shortest path on a weighted edge-coloured graph, where the maximum number of different colours u...
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The k-Colour Shortest Path Problem is a variant of the classic Shortest Path Problem. This problem consists of finding a shortest path on a weighted edge-coloured graph, where the maximum number of different colours used in a feasible solution is fixed to be k. The k-CSPP has several real-world applications, particularly in network reliability. It addresses the problem of reducing the connection cost while improving the reliability of the network. In this work, we propose a heuristic approach, namely Colour-Constrained dijkstra algorithm (CCDA), which is able to produce effective solutions. We propose a graph reduction technique, namely the Graph Reduction algorithm (GRA), which removes more than 90% of the nodes and edges from the input graph. Finally, using a Mixed-Integer Linear Programming (MILP) model, we present an exact approach, namely Reduced Integer Linear Programming algorithm (RILP), that takes advantage of the heuristic CCDA and the GRA. Several tests were performed to verify the effectiveness of the proposed approaches. The computational results indicate that the produced approaches perform well, in terms of both the solution's quality and computation times.
Due to reasons of short range, long charging time, and insufficient information exchange between charging infrastructures, more attention needs to be paid to the charging problems of EVs. This work mainly focuses on d...
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Due to reasons of short range, long charging time, and insufficient information exchange between charging infrastructures, more attention needs to be paid to the charging problems of EVs. This work mainly focuses on designing an intelligent charging navigation method for EVs, building the logic framework, and internal structure framework. Then, battery SOC and energy consumption of EVs were predicted for the range, and queueing theory was used to calculate the charging queueing time. Furthermore, the historical trend method is used to predict road travel time. Finally, combined with the above data, an EV charging navigation model based on the shortest time was established and related algorithms were written to solve the model by using dijkstra algorithm and an example is given to verify the feasibility of the intelligent charging navigation for EVs. About 24 minutes' driving time and a total of 16.63 minutes were saved for the owner from charging decision to charging completion on a 50 km drive.
The Gran Sasso National Laboratory (LNGS) is, at present, the largest deep underground laboratory in operation for astroparticle physics and rare event research. The LNGS was created to carry out this research exploit...
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The Gran Sasso National Laboratory (LNGS) is, at present, the largest deep underground laboratory in operation for astroparticle physics and rare event research. The LNGS was created to carry out this research exploiting an overburden of 1,400 m of rock to reduce the flux of muons from cosmic rays. Operating an underground laboratory and its facilities implies a high level of risk. To mitigate risks at the LNGS, a crucial aspect is represented by the evacuation of people from an underground environment during emergencies. The connection between the underground facilities and the outside infrastructure is limited, and the intervention by rescue teams is complicated. This paper reports the study of an adaptive evacuation system to improve the evacuation performance in underground laboratories. The system proposed is composed of a combination of passive, dynamic, and adaptive signage that is able to adapt itself to lead the laboratory occupants to the safe location for evacuation (assembly point). The system collects information from all safety plants, and the data are processed using a customized path-finding algorithm. In the computational algorithm, the underground laboratory is represented as a grid, and the customized path-finding algorithm discovers all available paths to reach the identified evacuation assembly point.
With the wide application of Bioinspired Neural Network in the field of robot path planning, the environmental scale of robot path planning is getting larger, and the environmental resolution requirements are getting ...
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With the wide application of Bioinspired Neural Network in the field of robot path planning, the environmental scale of robot path planning is getting larger, and the environmental resolution requirements are getting higher. However, with the increase of the environment size and resolution requirement, the neuronal activity value calculation cost and the time cost of the Bioinspired Neural Network will increase sharply. Aiming at this problem, this paper proposes an improved Bioinspired Neural Network path planning method based on Scaling Terrain. Using a Multi-Scale Map method and dijkstra algorithm, the optimal path of a Coarse Scale Map is calculated. The optimal path obtained from the Coarse Scale Map is used to guide the neural network planning weights of the Fine Scale Map from the same terrain. Thus, the optimal path of the Fine Scale Map can be calculated by the improved BNN algorithm. Introducing this Multi-Scale Map Method into the Bioinspired Neural Network can greatly reduce the time cost of the Bioinspired Neural Network path planning algorithm and reduce the mathematical complexity. Simulation results in some computer integrated virtual environments further demonstrate the superiority of this method and the experimental results are encouraging.
The aim of the undertaken research was to identify the most frequently repeated accident scenarios in relation to accidents that involve scaffolding. The source of knowledge was accident documentation containing infor...
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The aim of the undertaken research was to identify the most frequently repeated accident scenarios in relation to accidents that involve scaffolding. The source of knowledge was accident documentation containing information on the circumstances of accidents, as well as their course and consequences. As part of the research, an IT Database (ITD) was developed, which involved accidents that occurred in Poland over the past five years which were related to work on scaffolding. An original graphical, mathematical and IT process model was developed in order to enable a large set of accidents involving construction scaffolding to be studied. Due to the fact that every accident proceeds according to a different scenario, a map of possible accident scenarios was developed and presented in the form of a directed graph. Graph algorithms, including the dijkstra algorithm, were used to build the IT model. Based on the information contained in the ITD, the course of the accident sequence was analysed in the proposed graph. The most probable accident scenarios, the probability of their occurrence, and the course of the critical path were determined. The obtained results constitute a starting point for estimating the occupational risk associated with working on scaffoldings.
To maintain life, charge transfer processes must be efficient to allow electrons to migrate across distances as large as 30-50 angstrom within a timescale from picoseconds to milliseconds, and the free-energy cost sho...
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To maintain life, charge transfer processes must be efficient to allow electrons to migrate across distances as large as 30-50 angstrom within a timescale from picoseconds to milliseconds, and the free-energy cost should not exceed one electron volt. By employing local ionization and local affinity energies, we calculated the pathway for electron and electron-hole transport, respectively. The pathway is then used to calculate both the driving force and the activation energy. The electronic coupling is calculated using configuration interaction procedure. When the charge acceptor is not known, as in oxidative stress, the charge transport terminals are found using Monte-Carlo simulation. These parameters were used to calculate the rate described by Marcus theory. Our approach has been elaborately explained using the famous androstane example and then applied to two proteins: electron transport in azurin protein and hole-hopping migration route from the heme center of cytochrome c peroxidase to its surface. This model gives an effective method to calculate the charge transport pathway and the free-energy profile within 0.1 eV from the experimental measurements and electronic coupling within 3 meV.
In large-scale and long-term visual SLAM, robust place recognition is essential for building a global consistent map. However, sensor viewpoints and environmental condition changes, including lighting, weather, and se...
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In large-scale and long-term visual SLAM, robust place recognition is essential for building a global consistent map. However, sensor viewpoints and environmental condition changes, including lighting, weather, and seasons, bring a huge challenge to place recognition. We propose a place recognition algorithm based on CNN features and graph model. Firstly, CNN features of images are extracted though an AlexNet network with migration characteristics, and N-nearest neighbor image descriptors of the current image descriptor are found by approximate nearest neighbor searching. Then, according to the difference between descriptors, a weighted directed acyclic graph (weighted DAG) model which describes a cost of context matching between images is established. Finally, a candidate matching sequence with minimum cost on this model is achieved by using dijkstra algorithm. Compared with SeqCNNSLAM and Fast-SeqSLAM, the experimental results demonstrate higher recognition accuracy and robustness of our algorithm.
With the rapid economic and social development of our country, the number of private cars has also increased rapidly, and at the same time, the problems of noise pollution and environmental pollution have become more ...
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With the rapid economic and social development of our country, the number of private cars has also increased rapidly, and at the same time, the problems of noise pollution and environmental pollution have become more and more prominent. As a kind of new energy vehicle, electric vehicle has quickly entered people's field of vision with its advantages of no pollution, low noise, convenient use and high energy utilization efficiency. However, wide-spread and universal adoption of electric vehicles requires a well-established infrastructure for electric vehicles, namely a network of charging facilities. Nowadays, there are still problems such as unreasonable location selection and unsound network in the setting of charging stations. It is urgent to analyze the current road network and build a reasonable charging station selection model. With the help of geographic information system, this paper analyzes and integrates the traffic hot spots and road network in Lingang area of Shanghai, and constructs a charging station site selection model with the help of charging station accessibility and charging station construction cost. The model composition is determined, and reference opinions are provided for the site selection and construction of the charging station.
作者:
Wojciech WięlawekDivision of Telecomunications
Institiute of Electronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Postal address: Akademicka 16 44-100 Gliwice Poland Phone: (048) 32 23714 95
Abstract There are edge based segmentation approaches among the set of methods utilized to image segmentation. This type of methods analyse image gradient features (like the first, the second derivative or them modifi...
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Abstract There are edge based segmentation approaches among the set of methods utilized to image segmentation. This type of methods analyse image gradient features (like the first, the second derivative or them modification). Perfect tool to image processing is wavelet transformation which enables edges detection and often gets better results. In this paper wavelet transformation advantages was utilized. This tool was used to cost map definition. Cost map is a matrix which informs how many features of boundary each pixel possess. Then this cost map definition was applied to live-wire method. The method is semi-automatic and requires user interaction rely on points specification.
This thesis paper proposes An Integratable V-X Communication-based Conventional Vehicle Fuel Optimization model for real-time traffic conditions. Before departure, the speed profile for an entire route is optimized us...
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This thesis paper proposes An Integratable V-X Communication-based Conventional Vehicle Fuel Optimization model for real-time traffic conditions. Before departure, the speed profile for an entire route is optimized using signal phase and timing (SP AT) information and location of traffic lights to provide smooth transitions at traffic signal intersections. In this study, we are going to develop ”nonstop” optimal speed model that can be integrated to existing distance based eco-driving schemes. The initial simulation is done using MATLAB to evaluate optimal speed, fuel economy, the travel time of the ”nonstop” model and the results are compared with the optimization results from distance based eco-driving scheme which uses an estimation of distribution algorithm (EDA). Further integration compatibility of ”nonstop” model with the distance based eco-driving
scheme is analyzed.
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