Right ventricle extraction by low level and model-based algorithm

In this paper we present an algorithm as the combination of a low level morphological operation and model based Global Circular Shortest Path scheme to explore the segmentation of the Right Ventricle. Traditional morphological operations were employed to obtain the region of interest, and adjust it to generate a mask. The image cropped by the mask is then partitioned into a few overlapping regions. Global Circular Shortest Path algorithm is then applied to extract the contour from each partition. The final step is to re-assemble the partitions to create the whole contour. The technique is deemed quite reliable and robust, as this is illustrated by a very good agreement between the extracted contour and the expert manual drawing output.

Comparing transport emissions and impacts for energy recovery from domestic waste (EfW): centralised and distributed disposal options for two UK Counties

Many local authorities (LAs) are currently working to reduce both greenhouse gas emissions and the amount of municipal solid waste (MSW) sent to landfill. The recovery of energy from waste (EfW) can assist in meeting both of these objectives. The choice of an EfW policy combines spatial and non-spatial decisions which may be handled using Multi-Criteria Analysis (MCA) and Geographic Information Systems (GIS). This paper addresses the impact of transporting MSW to EfW facilities, analysed as part of a larger decision support system designed to make an overall policy assessment of centralised (large-scale) and distributed (local-scale) approaches. Custom-written ArcMap extensions are used to compare centralised versus distributed approaches, using shortest-path routing based on expected road speed. Results are intersected with 1-kilometre grids and census geographies for meaningful maps of cumulative impact. Case studies are described for two counties in the United Kingdom (UK); Cornwall and Warwickshire. For both case study areas, centralised scenarios generate more traffic, fuel costs and emitted carbon per tonne of MSW processed.

Enabling long journeys in electric vehicles:design and demonstration of an infrastructure location model

This research develops a methodology and model formulation which suggests locations for rapid chargers to help assist infrastructure development and enable greater battery electric vehicle (BEV) usage. The model considers the likely travel patterns of BEVs and their subsequent charging demands across a large road network, where no prior candidate site information is required. Using a GIS-based methodology, polygons are constructed which represent the charging demand zones for particular routes across a real-world road network. The use of polygons allows the maximum number of charging combinations to be considered whilst limiting the input intensity needed for the model. Further polygons are added to represent deviation possibilities, meaning that placement of charge points away from the shortest path is possible, given a penalty function. A validation of the model is carried out by assessing the expected demand at current rapid charging locations and comparing to recorded empirical usage data. Results suggest that the developed model provides a good approximation to real world observations, and that for the provision of charging, location matters. The model is also implemented where no prior candidate site information is required. As such, locations are chosen based on the weighted overlay between several different routes where BEV journeys may be expected. In doing so many locations, or types of locations, could be compared against one another and then analysed in relation to siting practicalities, such as cost, land permission and infrastructure availability. Results show that efficient facility location, given numerous siting possibilities across a large road network can be achieved. Slight improvements to the standard greedy adding technique are made by adding combination weightings which aim to reward important long distance routes that require more than one charge to complete.

Trajectory privacy preservation in mobile Wireless Sensor Networks

In recent years, there has been an enormous growth of location-aware devices, such as GPS embedded cell phones, mobile sensors and radio-frequency identification tags. The age of combining sensing, processing and communication in one device, gives rise to a vast number of applications leading to endless possibilities and a realization of mobile Wireless Sensor Network (mWSN) applications. As computing, sensing and communication become more ubiquitous, trajectory privacy becomes a critical piece of information and an important factor for commercial success. While on the move, sensor nodes continuously transmit data streams of sensed values and spatiotemporal information, known as ``trajectory information". If adversaries can intercept this information, they can monitor the trajectory path and capture the location of the source node. ^ This research stems from the recognition that the wide applicability of mWSNs will remain elusive unless a trajectory privacy preservation mechanism is developed. The outcome seeks to lay a firm foundation in the field of trajectory privacy preservation in mWSNs against external and internal trajectory privacy attacks. First, to prevent external attacks, we particularly investigated a context-based trajectory privacy-aware routing protocol to prevent the eavesdropping attack. Traditional shortest-path oriented routing algorithms give adversaries the possibility to locate the target node in a certain area. We designed the novel privacy-aware routing phase and utilized the trajectory dissimilarity between mobile nodes to mislead adversaries about the location where the message started its journey. Second, to detect internal attacks, we developed a software-based attestation solution to detect compromised nodes. We created the dynamic attestation node chain among neighboring nodes to examine the memory checksum of suspicious nodes. The computation time for memory traversal had been improved compared to the previous work. Finally, we revisited the trust issue in trajectory privacy preservation mechanism designs. We used Bayesian game theory to model and analyze cooperative, selfish and malicious nodes' behaviors in trajectory privacy preservation activities.^

Graph analysis of verbal fluency test discriminate between patients with Alzheimer’s disease, Mild Cognitive Impairment and normal elderly controls

Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment – subtypes amnestic(aMCI) and amnestic multiple domain (a+mdMCI) - and patients with Alzheimer’s disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGAs). The individuals were compared when divided in three (NC – MCI – AD) and four (NC – aMCI – a+mdMCI – AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.

Graph analysis of verbal fluency test discriminate between patients with Alzheimer’s disease, Mild Cognitive Impairment and normal elderly controls

Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment – subtypes amnestic(aMCI) and amnestic multiple domain (a+mdMCI) - and patients with Alzheimer’s disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGAs). The individuals were compared when divided in three (NC – MCI – AD) and four (NC – aMCI – a+mdMCI – AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.

Protocolo de roteamento para redes oportunistas utilizando otimização por enxame de partículas

In this research work, a new routing protocol for Opportunistic Networks is presented. The proposed protocol is called PSONET (PSO for Opportunistic Networks) since the proposal uses a hybrid system composed of a Particle Swarm Optimization algorithm (PSO). The main motivation for using the PSO is to take advantage of its search based on individuals and their learning adaptation. The PSONET uses the Particle Swarm Optimization technique to drive the network traffic through of a good subset of forwarders messages. The PSONET analyzes network communication conditions, detecting whether each node has sparse or dense connections and thus make better decisions about routing messages. The PSONET protocol is compared with the Epidemic and PROPHET protocols in three different scenarios of mobility: a mobility model based in activities, which simulates the everyday life of people in their work activities, leisure and rest; a mobility model based on a community of people, which simulates a group of people in their communities, which eventually will contact other people who may or may not be part of your community, to exchange information; and a random mobility pattern, which simulates a scenario divided into communities where people choose a destination at random, and based on the restriction map, move to this destination using the shortest path. The simulation results, obtained through The ONE simulator, show that in scenarios where the mobility model based on a community of people and also where the mobility model is random, the PSONET protocol achieves a higher messages delivery rate and a lower replication messages compared with the Epidemic and PROPHET protocols.

Trajectory Privacy Preservation in Mobile Wireless Sensor Networks

In recent years, there has been an enormous growth of location-aware devices, such as GPS embedded cell phones, mobile sensors and radio-frequency identification tags. The age of combining sensing, processing and communication in one device, gives rise to a vast number of applications leading to endless possibilities and a realization of mobile Wireless Sensor Network (mWSN) applications. As computing, sensing and communication become more ubiquitous, trajectory privacy becomes a critical piece of information and an important factor for commercial success. While on the move, sensor nodes continuously transmit data streams of sensed values and spatiotemporal information, known as ``trajectory information". If adversaries can intercept this information, they can monitor the trajectory path and capture the location of the source node. This research stems from the recognition that the wide applicability of mWSNs will remain elusive unless a trajectory privacy preservation mechanism is developed. The outcome seeks to lay a firm foundation in the field of trajectory privacy preservation in mWSNs against external and internal trajectory privacy attacks. First, to prevent external attacks, we particularly investigated a context-based trajectory privacy-aware routing protocol to prevent the eavesdropping attack. Traditional shortest-path oriented routing algorithms give adversaries the possibility to locate the target node in a certain area. We designed the novel privacy-aware routing phase and utilized the trajectory dissimilarity between mobile nodes to mislead adversaries about the location where the message started its journey. Second, to detect internal attacks, we developed a software-based attestation solution to detect compromised nodes. We created the dynamic attestation node chain among neighboring nodes to examine the memory checksum of suspicious nodes. The computation time for memory traversal had been improved compared to the previous work. Finally, we revisited the trust issue in trajectory privacy preservation mechanism designs. We used Bayesian game theory to model and analyze cooperative, selfish and malicious nodes' behaviors in trajectory privacy preservation activities.

Simulation of URLLC slicing with resource reconfiguration in 5G networks

This thesis seeks to analyse the performance of dynamic slice provisioning in a 5G metro network with the low latency and reliability guaranties. This elaborate highlight the comparison in terms of performance of two versions of a simulator developed in Python based on different models: the Exhaustive research model and Shortest Path First Fit (SPFF) model. It further presents the differences between the dedicated path protection and the shared path protection. This analysis is made through several simulations at different network conditions by varying networks resources and observing the network performances while comparing the 2 models mentioned above. A reconfiguration procedure was implemented on backup resources in the shortest path first fit in order to improve its performance with respect to the exhaustive research which is more optimised. Subsequently, several triggering events was implemented, for the reconfiguration. And a comparison is made between these different triggering events in terms blocking probability, bandwidth at link, capacity at each node, primary and backup bandwidth per slice and backup capacity per slice.

Studio e implementazione di algoritmi per il tracciamento ottimo di satellite LEO da stazioni di terra di tipo radioamatoriale

Questo elaborato di tesi ha l’obbiettivo di studiare le limitazioni delle stazioni di terra nel tracciamento di satelliti in orbita LEO, investigare possibili soluzioni ed implementare queste soluzioni all’interno della Ground Station AMGS di Forlì per verificarne l’efficacia. A questo scopo, dopo un’attenta revisione della letteratura sono stati identificati due promettenti algoritmi descritti nei paper: “Trajectory optimisation to minimise antenna pointing error” di P. S. Crawford , R. J. H. Brush e “An optimal antenna motion generation using shortest path planning” di Moon-Jin Jeon , Dong-Soo Kwon. Questi algoritmi sono stati implementi in Python 3, al fine di inglobarli all’interno del software di tracking al momento in uso nella GS di Forlì, ovvero AMGS Orbit Predictor. All’interno di questo elaborato sono anche riportati i risultati dei test conseguiti e una valutazione dettagliata di questi ultimi.

Cutting path as a rural postman problem

The Rural Postman Problem (RPP) is a particular Arc Routing Problem (ARP) which consists of determining a minimum cost circuit on a graph so that a given subset of required edges is traversed. The RPP is an NP-hard problem with significant real-life applications. This paper introduces an original approach based on Memetic Algorithms - the MARP algorithm - to solve the RPP and, also deals with an interesting Industrial Application, which focuses on the path optimization for component cutting operations. Memetic Algorithms are a class of Metaheuristics which may be seen as a population strategy that involves cooperation and competition processes between population elements and integrates “social knowledge”, using a local search procedure. The MARP algorithm is tested with different groups of instances and the results are compared with those gathered from other publications. MARP is also used in the context of various real-life applications.

Path dependence and Britain’s "coal wagon problem"

This article explores the nature and impact of path dependence in British rail coal haulage before 1939. It examines the factors which locked Britain's railways into a system of small coal wagons with highly fragmented ownership, the cost penalties of this system, and the reasons that attempts at modernization were unsuccessful. The analysis highlights the importance of decentralized ownership of a highly durable installed base of complementary infrastructure. Technical and institutional interrelatedness blocked incremental modernization, while the political requirement to compensate private wagon owners for the loss of their wagon stock made wholesale rationalization financially unattractive.

GRASP heuristic with path-relinking for the multi-plant capacitated lot sizing problem

This paper addresses the independent multi-plant, multi-period, and multi-item capacitated lot sizing problem where transfers between the plants are allowed. This is an NP-hard combinatorial optimization problem and few solution methods have been proposed to solve it. We develop a GRASP (Greedy Randomized Adaptive Search Procedure) heuristic as well as a path-relinking intensification procedure to find cost-effective solutions for this problem. In addition, the proposed heuristics is used to solve some instances of the capacitated lot sizing problem with parallel machines. The results of the computational tests show that the proposed heuristics outperform other heuristics previously described in the literature. The results are confirmed by statistical tests. (C) 2009 Elsevier B.V. All rights reserved.

GRASP with evolutionary path-relinking for the capacitated arc routing problem

The Capacitated Arc Routing Problem (CARP) is a well-known NP-hard combinatorial optimization problem where, given an undirected graph, the objective is to find a minimum cost set of tours servicing a subset of required edges under vehicle capacity constraints. There are numerous applications for the CARP, such as street sweeping, garbage collection, mail delivery, school bus routing, and meter reading. A Greedy Randomized Adaptive Search Procedure (GRASP) with Path-Relinking (PR) is proposed and compared with other successful CARP metaheuristics. Some features of this GRASP with PR are (i) reactive parameter tuning, where the parameter value is stochastically selected biased in favor of those values which historically produced the best solutions in average; (ii) a statistical filter, which discard initial solutions if they are unlikely to improve the incumbent best solution; (iii) infeasible local search, where high-quality solutions, though infeasible, are used to explore the feasible/infeasible boundaries of the solution space; (iv) evolutionary PR, a recent trend where the pool of elite solutions is progressively improved by successive relinking of pairs of elite solutions. Computational tests were conducted using a set of 81 instances, and results reveal that the GRASP is very competitive, achieving the best overall deviation from lower bounds and the highest number of best solutions found. © 2011 Elsevier Ltd. All rights reserved.