Increasingly, temporally-detailed graphs are of a size, variety, and update rate that exceed the capability of current computing technologies. Such datasets can be called Big Temporally-Detailed Graph (Big-TDG) Data. ...
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Increasingly, temporally-detailed graphs are of a size, variety, and update rate that exceed the capability of current computing technologies. Such datasets can be called Big Temporally-Detailed Graph (Big-TDG) Data. Examples include temporally-detailed (TD) roadmaps which provide typical travel speeds experienced on every road segment for thousands of departure-times in a typical week. Likewise, we have temporally-detailed (TD) social networks which contain a temporal trace of social interactions among the individuals in the network over a time window. Big-TDG data has transformative potential. For instance, a 2011 McKinsey Global Institute report estimates that location-aware data could save consumers hundreds of billions of dollars annually by 2020 by helping vehicles avoid traffic congestion via next-generation routing services such as eco-routing. However, Big-TDG data presents big challenges for the current computer science state of the art. First, Big-TDG data violates the cost function decomposability assumption of current conceptual models for representing and querying temporally-detailed graphs. Second, the voluminous nature of Big-TDG data can violate the stationary ranking-of-candidate-solutions assumption of dynamic programming based techniques such Dijsktra’s shortest path algorithm. This thesis proposes novel approaches to address these challenges. To address the first challenge, this thesis proposes a novel conceptual model called, "Lagrangian Xgraphs," which models non-decomposability through a series of overlapping (in space and time) relations, each representing a single atomic unit which retains the required semantics. An initial study shows that Lagrangian Xgraphs are more convenient for representing diverse temporally-detailed graph datasets and comparing candidate travel itineraries. For the second challenge, this thesis proposes a novel divide-and-conquer technique called "critical-time-point (CTP) based approach," which efficiently divides t
Background: Interpreting large-scale studies from microarrays or next-generation sequencing for further experimental testing remains one of the major challenges in quantitative biology. Combining expression with physi...
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Background: Interpreting large-scale studies from microarrays or next-generation sequencing for further experimental testing remains one of the major challenges in quantitative biology. Combining expression with physical or genetic interaction data has already been successfully applied to enhance knowledge from all types of high-throughput studies. Yet, toolboxes for navigating and understanding even small gene or protein networks are poorly developed. Results: We introduce two Cytoscape plug-ins, which support the generation and interpretation of experiment-based interaction networks. The virtual pathway explorer viPEr creates so-called focus networks by joining a list of experimentally determined genes with the interactome of a specific organism. viPEr calculates all paths between two or more user-selected nodes, or explores the neighborhood of a single selected node. Numerical values from expression studies assigned to the nodes serve to score identified paths. The pathway enrichment analysis tool PEANuT annotates networks with pathway information from various sources and calculates enriched pathways between a focus and a background network. Using time series expression data of atorvastatin treated primary hepatocytes from six patients, we demonstrate the handling and applicability of viPEr and PEANuT. Based on our investigations using viPEr and PEANuT, we suggest a role of the FoxA1/A2/A3 transcriptional network in the cellular response to atorvastatin treatment. Moreover, we find an enrichment of metabolic and cancer pathways in the Fox transcriptional network and demonstrate a patient-specific reaction to the drug. Conclusions: The Cytoscape plug-in viPEr integrates -omics data with interactome data. It supports the interpretation and navigation of large-scale datasets by creating focus networks, facilitating mechanistic predictions from -omics studies. PEANuT provides an up-front method to identify underlying biological principles by calculating enriched path
In the Switching Tower of Hanoi interpretation of Sierpinski graphs S-p(n) the P2 decision problem is to find out whether the largest moving disc has to be transferred once or twice in a shortestpath between two give...
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In the Switching Tower of Hanoi interpretation of Sierpinski graphs S-p(n) the P2 decision problem is to find out whether the largest moving disc has to be transferred once or twice in a shortestpath between two given states/vertices. We construct an essentially optimal algorithm thus extending Romik's approach for p = 3 to the general case. The algorithm makes use of three automata and the underlying theory includes a simple argument for the fact that there are at most two shortestpaths between any two vertices. The total number of pairs leading to non-unique solutions is determined and employing a Markov chain argument it is shown that the number of input pairs needed for the decision is bounded above by a number independent of n. Elementary algorithms for the length of the shortestpath(s) and the best first move/edge are also presented. (C) 2014 Elsevier B.V. All rights reserved.
The developing tourist industry proposes higher and higher demands to the intelligent tourist guide system, which can take place of the traditional artificial guide service. Functions of intelligent automatic interpre...
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ISBN:
(纸本)9781510807587
The developing tourist industry proposes higher and higher demands to the intelligent tourist guide system, which can take place of the traditional artificial guide service. Functions of intelligent automatic interpretation, real time navigation, intelligent route planning and surrounding service reminder are included in it. With rapid development of electronic information technology and computer technology as the support, this thesis combines with the shortest path algorithm and related knowledge of graph theory to design algorithm and processing scheme. Moreover, this thesis also introduces research design of intelligent tourist system as well. Thus, the function of APP on the android platform is realized.
Clifford algebra is introduced as a theoretical foundation for network topology expression and algorithm construction. Network nodes are coded with basis vectors in a vector space Rn, and the edges and k-walk routes c...
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Clifford algebra is introduced as a theoretical foundation for network topology expression and algorithm construction. Network nodes are coded with basis vectors in a vector space Rn, and the edges and k-walk routes can be expressed by 2-blades and k-blades, respectively, in the Clifford algebra Cl(n,0). The topologies among nodes, edges, and routes of networks can be directly calculated, and the network routes can be extended and traversed with oriented join products. The network algorithm construction processes based on Clifford algebra are instantiated by the single source shortest path algorithm. The experimental results on different scale random networks suggest that Clifford algebra is suited for network expression and relation computation. The Clifford algebra-based shortest path algorithm is vivid and clear in geometric meaning and has great advantage on temporal and spatial complexity. Copyright (c) 2013 John Wiley & Sons, Ltd.
This paper presents a new algorithm for computing shortestpaths in a nearly directed graph G = (V, E). The existing Dijkstra's algorithm finds the shortest distance between given two vertices. This paper proposes...
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This paper presents a new algorithm for computing shortestpaths in a nearly directed graph G = (V, E). The existing Dijkstra's algorithm finds the shortest distance between given two vertices. This paper proposes a new algorithm which proves to be better than Dijkstra's and Floyd's algorithm in certain cases. The proposed algorithm is a single source shortest path algorithm which finds the shortestpath and shortest distance from a single vertex in a graph to all other vertices in the graph.
The problem of path-finding has to be solved in transportation, city planning, commercial computer games, navigation and many other fields. How to find the shortestpath is the key point of this problem. For computer ...
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ISBN:
(纸本)9781479942848
The problem of path-finding has to be solved in transportation, city planning, commercial computer games, navigation and many other fields. How to find the shortestpath is the key point of this problem. For computer games and many other fields, since the maps are usually not very big, traditional algorithms such as Dijkstra algorithm and AStar algorithm work well. But if we want to find the shortestpath of two points in a big city or even a country, the memory and CPU resources are limited and these algorithms may result in bad performance. To solve the problem of navigation in big maps, this paper introduces and analyzes the use of Hierarchical A-Star algorithm which adds the hierarchical mechanism into traditional A-Star algorithm and save the resources of CPU and memory. For a big map such as the map of a country, to find the shortestpath of two points, we successively divide the map of the country into maps of states, cities, towns, and blocks. Then we implement A Star algorithm for each layer and recursively find the shortestpath of these two points.
A number of tactical and operational applications, such as train timetabling and dispatching, require sophisticated and computationally efficient software to optimize train schedules. An open-source train scheduling p...
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ISBN:
(纸本)9781479960781
A number of tactical and operational applications, such as train timetabling and dispatching, require sophisticated and computationally efficient software to optimize train schedules. An open-source train scheduling package, namely FastTrain has been designed and implemented to generate feasible schedules and optimality gap estimates for trains on a generic rail network with both single and double tracks. This paper describes its two major modelling components: (1) a network cumulative flow model to capture the complex safety rules of infrastructure resources, and (2) a Lagrangian relaxation solution framework which efficiently decomposes the original multi-trains complex model to a set of single train oriented subproblems. Two experimental cases based on the adapted datasets released by INFORMS RAS are conducted to demonstrate the effectiveness and efficiency of the developed algorithm under different network and data availability conditions.
The wheeled robots have become the interesting and important training kits for students to learn to integrate those skills about hardware circuit designs, firmware programming, motion control, and path planning techni...
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ISBN:
(纸本)9781479937066
The wheeled robots have become the interesting and important training kits for students to learn to integrate those skills about hardware circuit designs, firmware programming, motion control, and path planning techniques in these past days. Therefore, a novel line maze robot kit with diagonal path planning capabilities is presented as an example in this paper to help students. The robot uses a 32-bit microcontroller with floating point processing unit to 1) detect the track curve by using optical sensors, 2) use gyro sensor to correct moving angles, 3) control the linear and angular velocities of the robot, and 4) plan a diagonal path from the start to the target. Although students could learn the abovementioned topics in a special topic project, they may also design their own mechanical structures and hardware circuits to improve furthermore the performance of their robots, and they are happy to join to win prizes in related contests.
The ever-increasing density in cloud computing users, services, and data centres has led to significant increases in network traffic and the associated energy consumed by its huge infrastructure, e.g. extra servers, s...
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ISBN:
(纸本)9781479952649
The ever-increasing density in cloud computing users, services, and data centres has led to significant increases in network traffic and the associated energy consumed by its huge infrastructure, e.g. extra servers, switches, routers, which is required to respond quickly and effectively to users requests. Transferring data, via a high bandwidth connection between data centres and cloud users, consumes even larger amounts of energy than just processing and storing the data on a cloud data centre, and hence producing high carbon dioxide emissions. This power consumption is highly significant when transferring data into a data centre located relatively far from the user's geographical location. Thus, it became high-necessity to locate the lowest energy consumption route between the user and the designated data centre, while making sure the user's requirements, e.g. response time, are met. This paper proposes a high-end autonomic meta-director framework to find the most energy efficient route to the green data centre by utilising the linear programming approach. The framework is, first, formalised by the situation calculus, and then evaluated against shortest path algorithm with minimum number of nodes traversed.
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