Flexible pavement layer moduli determination : an adaptive artificial neural network approach

The estimation of pavement layer moduli through the use of an artificial neural network is a new concept which provides a less strenuous strategy for backcalculation procedures. Artificial Neural Networks are biologically inspired models of the human nervous system. They are specifically designed to carry out a mapping characteristic. This study demonstrates how an artificial neural network uses non-destructive pavement test data in determining flexible pavement layer moduli. The input parameters include plate loadings, corresponding sensor deflections, temperature of pavement surface, pavement layer thicknesses and independently deduced pavement layer moduli.

Simulation and analysis of network traffic for efficient and reliable information transfer

With the growing commercial importance of the Internet and the development of new real-time, connection-oriented services like IP-telephony and electronic commerce resilience is becoming a key issue in the design of TP-based networks. Two emerging technologies, which can accomplish the task of efficient information transfer, are Multiprotocol Label Switching (MPLS) and Differentiated Services. A main benefit of MPLS is the ability to introduce traffic-engineering concepts due to its connection-oriented characteristic. With MPLS it is possible to assign different paths for packets through the network. Differentiated services divides traffic into different classes and treat them differently, especially when there is a shortage of network resources. In this thesis, a framework was proposed to integrate the above two technologies and its performance in providing load balancing and improving QoS was evaluated. Simulation and analysis of this framework demonstrated that the combination of MPLS and Differentiated services is a powerful tool for QoS provisioning in IP networks.

Cooperative routing for collision minimization in wireless sensor networks

Cooperative communication has gained much interest due to its ability to exploit the broadcasting nature of the wireless medium to mitigate multipath fading. There has been considerable amount of research on how cooperative transmission can improve the performance of the network by focusing on the physical layer issues. During the past few years, the researchers have started to take into consideration cooperative transmission in routing and there has been a growing interest in designing and evaluating cooperative routing protocols. Most of the existing cooperative routing algorithms are designed to reduce the energy consumption; however, packet collision minimization using cooperative routing has not been addressed yet. This dissertation presents an optimization framework to minimize collision probability using cooperative routing in wireless sensor networks. More specifically, we develop a mathematical model and formulate the problem as a large-scale Mixed Integer Non-Linear Programming problem. We also propose a solution based on the branch and bound algorithm augmented with reducing the search space (branch and bound space reduction). The proposed strategy builds up the optimal routes from each source to the sink node by providing the best set of hops in each route, the best set of relays, and the optimal power allocation for the cooperative transmission links. To reduce the computational complexity, we propose two near optimal cooperative routing algorithms. In the first near optimal algorithm, we solve the problem by decoupling the optimal power allocation scheme from optimal route selection. Therefore, the problem is formulated by an Integer Non-Linear Programming, which is solved using a branch and bound space reduced method. In the second near optimal algorithm, the cooperative routing problem is solved by decoupling the transmission power and the relay node se- lection from the route selection. After solving the routing problems, the power allocation is applied in the selected route. Simulation results show the algorithms can significantly reduce the collision probability compared with existing cooperative routing schemes.

Important factors in predicting mortality outcome from stroke : findings from the Anglia Stroke Clinical Network Evaluation Study

The Anglia Stroke Clinical Network Evaluation Study (ASCNES) is funded by the National Institute for Health Research (NIHR) Research for Patient Benefit Programme (PB-PG-1208-18240). This paper presents independent research funded by the NIHR under its Research for Patient Benefit (RfPB) programme (Grant Reference Number PB-PG-1208-18240). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. EAW receives funding support from the NIHR Biomedical Research Centre award to Cambridge

« Utilisation des services de santé chez les personnes âgées : association avec la maladie chronique et l’incapacité »

Diverses publications soulignent l'augmentation de l'espérance de vie et avec elle, le vieillissement mondial de la population. Ce processus se poursuivra à l'avenir, ainsi que son influence sur l’incidence et la prévalence de l'incapacité. Chez les personnes âgées, l’incapacité, les maladies chroniques et leur association constituent un sujet important dans le domaine de la santé publique en raison de l'effet qu'ils ont sur la demande des services de santé. Le but de ce mémoire est d’examiner quelle est la contribution respective des maladies chroniques et de l'incapacité dans l'utilisation des services de santé chez les personnes âgées et de leur interaction. Il s’agit de savoir si l'association entre la maladie chronique et l'utilisation des services de santé est modifiée par l’incapacité prenant en compte les caractéristiques de l'individu et son environnement. Ce travail est basé sur le modèle comportemental proposé par Andersen et Newman et le modèle du processus d’incapacité de Verbrugge et Jette. Pour répondre à l’objectif, nous utilisons les données du projet de recherche “ FRéLE ” (Fragilité, une étude longitudinale de ses expressions), réalisé durant la période 2010 -2013 auprès d’un échantillon de 1643 personnes âgées vivant dans la communauté au Québec. L’incapacité est évaluée à l’aide de deux indicateurs : les AVQ et les AVD. Les maladies chroniques sont mesurées par l’indice fonctionnel de comorbidité (IFC). La dépression est évaluée selon les critères de l’échelle de dépression gériatrique (EDG). L’état cognitif est mesuré par l'évaluation cognitive de Montréal (MoCA). Les facteurs de prédisposition comportent l’âge, le sexe, l’ethnicité et le niveau scolaire. Les facteurs facilitateurs incluent le revenu et le réseau social, ce dernier étant mesure par la présence ou non d’une personne de soutien et son lien avec la personne âgée. Divers modèles de régression sont adoptés pour identifier les facteurs statistiquement significatifs du modèle comportemental d’Andersen et Newman et du modèle du processus d’incapacité de Verbrugge et Jette. Nos résultats ont montré que, si le rôle des prédicteurs de l’utilisation varie en fonction du type de services de santé utilisé, l’utilisation s’accroît principalement avec le nombre de maladies chroniques. En ce qui concerne l’interaction entre la maladie chronique et l’incapacité, nos résultats ont révélé que l’interaction n’est statistiquement significative pour aucun des services analysés. Compte tenu de la diversité et les besoins de la population âgée, caractérisée par une prévalence élevée de maladies chroniques et d'incapacités, l’étude des facteurs impliqués dans l'utilisation des services de santé sera utile pour la mise en œuvre d’une offre de services, plus conforme aux besoins de cette population

Structural and agentic analysis of supply-chains: a social network analysis approach

This research adds to a body of work exploring the role of Social Network Analysis (SNA) in the study of both relational and structural characteristics of supply chain networks. Two contrasting network cases (food enterprises and digital-based enterprises) are chosen in order to elicit structural differences in business networks subject to divergences in local embeddedness and the relative materiality of the goods and services produced. Our analysis and findings draw out differences in network structure as evidenced by metrics of network centralization and cohesion, the presence of components and other sub-groupings, and the position of central actors. We relate these structural features both to the nature of the networks and to the (qualitative) experiences of the actors themselves. We find, in particular, the role of customers as co-creators of knowledge (for the Food network), the central role of infrastructure and services (for the Digital network), the importance of ICT as a source of codified knowledge inputs, along with the continuing importance of geographical proximity for the development and transfer of tacit knowledge and for incremental learning.

Forces of agglomeration and dispersal in rural business networks: a social network analysis

Two concepts in rural economic development policy have been the focus of much research and policy action: the identification and support of clusters or networks of firms and the availability and adoption by rural businesses of Information and Communication Technologies (ICT). From a theoretical viewpoint these policies are based on two contrasting models, with clustering seen as a process of economic agglomeration, and ICT-mediated communication as a means of facilitating economic dispersion. The study’s conceptual framework is based on four interrelated elements: location, interaction, knowledge, and advantage, together with the concept of networks which is employed as an operationally and theoretically unifying concept. The research questions are developed in four successive categories: Policy, Theory, Networks, and Method. The questions are approached using a study of two contrasting groups of rural small businesses in West Cork, Ireland: (a) Speciality Foods, and (b) firms in Digital Products and Services. The study combines Social Network Analysis (SNA) with Qualitative Thematic Analysis, using data collected from semi-structured interviews with 58 owners or managers of these businesses. Data comprise relational network data on the firms’ connections to suppliers, customers, allies and competitors, together with linked qualitative data on how the firms established connections, and how tacit and codified knowledge was sourced and utilised. The research finds that the key characteristics identified in the cluster literature are evident in the sample of Speciality Food businesses, in relation to flows of tacit knowledge, social embedding, and the development of forms of social capital. In particular the research identified the presence of two distinct forms of collective social capital in this network, termed “community” and “reputation”. By contrast the sample of Digital Products and Services businesses does not have the form of a cluster, but matches more closely to dispersive models, or “chain” structures. Much of the economic and social structure of this set of firms is best explained in terms of “project organisation”, and by the operation of an individual rather than collective form of “reputation”. The rural setting in which these firms are located has resulted in their being service-centric, and consequently they rely on ICT-mediated communication in order to exchange tacit knowledge “at a distance”. It is this factor, rather than inputs of codified knowledge, that most strongly influences their operation and their need for availability and adoption of high quality communication technologies. Thus the findings have applicability in relation to theory in Economic Geography and to policy and practice in Rural Development. In addition the research contributes to methodological questions in SNA, and to methodological questions about the combination or mixing of quantitative and qualitative methods.

« Utilisation des services de santé chez les personnes âgées : association avec la maladie chronique et l’incapacité »

Diverses publications soulignent l'augmentation de l'espérance de vie et avec elle, le vieillissement mondial de la population. Ce processus se poursuivra à l'avenir, ainsi que son influence sur l’incidence et la prévalence de l'incapacité. Chez les personnes âgées, l’incapacité, les maladies chroniques et leur association constituent un sujet important dans le domaine de la santé publique en raison de l'effet qu'ils ont sur la demande des services de santé. Le but de ce mémoire est d’examiner quelle est la contribution respective des maladies chroniques et de l'incapacité dans l'utilisation des services de santé chez les personnes âgées et de leur interaction. Il s’agit de savoir si l'association entre la maladie chronique et l'utilisation des services de santé est modifiée par l’incapacité prenant en compte les caractéristiques de l'individu et son environnement. Ce travail est basé sur le modèle comportemental proposé par Andersen et Newman et le modèle du processus d’incapacité de Verbrugge et Jette. Pour répondre à l’objectif, nous utilisons les données du projet de recherche “ FRéLE ” (Fragilité, une étude longitudinale de ses expressions), réalisé durant la période 2010 -2013 auprès d’un échantillon de 1643 personnes âgées vivant dans la communauté au Québec. L’incapacité est évaluée à l’aide de deux indicateurs : les AVQ et les AVD. Les maladies chroniques sont mesurées par l’indice fonctionnel de comorbidité (IFC). La dépression est évaluée selon les critères de l’échelle de dépression gériatrique (EDG). L’état cognitif est mesuré par l'évaluation cognitive de Montréal (MoCA). Les facteurs de prédisposition comportent l’âge, le sexe, l’ethnicité et le niveau scolaire. Les facteurs facilitateurs incluent le revenu et le réseau social, ce dernier étant mesure par la présence ou non d’une personne de soutien et son lien avec la personne âgée. Divers modèles de régression sont adoptés pour identifier les facteurs statistiquement significatifs du modèle comportemental d’Andersen et Newman et du modèle du processus d’incapacité de Verbrugge et Jette. Nos résultats ont montré que, si le rôle des prédicteurs de l’utilisation varie en fonction du type de services de santé utilisé, l’utilisation s’accroît principalement avec le nombre de maladies chroniques. En ce qui concerne l’interaction entre la maladie chronique et l’incapacité, nos résultats ont révélé que l’interaction n’est statistiquement significative pour aucun des services analysés. Compte tenu de la diversité et les besoins de la population âgée, caractérisée par une prévalence élevée de maladies chroniques et d'incapacités, l’étude des facteurs impliqués dans l'utilisation des services de santé sera utile pour la mise en œuvre d’une offre de services, plus conforme aux besoins de cette population

Mining the Online Social Network Data: Influence, Summarization, and Organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Vertical Handoff Target Selection in a Heterogeneous Wireless Network Using Fuzzy ELECTRE

Global connectivity is on the verge of becoming a reality to provide high-speed, high-quality, and reliable communication channels for mobile devices at anytime, anywhere in the world. In a heterogeneous wireless environment, one of the key ingredients to provide efficient and ubiquitous computing with guaranteed quality and continuity of service is the design of intelligent handoff algorithms. Traditional single-metric handoff decision algorithms, such as Received Signal Strength (RSS), are not efficient and intelligent enough to minimize the number of unnecessary handoffs, decision delays, call-dropping and blocking probabilities. This research presents a novel approach for of a Multi Attribute Decision Making (MADM) model based on an integrated fuzzy approach for target network selection.

Acceleration and visualization of Dynamic Network Optimization

With the emerging prevalence of smart phones and 4G LTE networks, the demand for faster-better-cheaper mobile services anytime and anywhere is ever growing. The Dynamic Network Optimization (DNO) concept emerged as a solution that optimally and continuously tunes the network settings, in response to varying network conditions and subscriber needs. Yet, the DNO realization is still at infancy, largely hindered by the bottleneck of the lengthy optimization runtime. This paper presents the design and prototype of a novel cloud based parallel solution that further enhances the scalability of our prior work on various parallel solutions that accelerate network optimization algorithms. The solution aims to satisfy the high performance required by DNO, preliminarily on a sub-hourly basis. The paper subsequently visualizes a design and a full cycle of a DNO system. A set of potential solutions to large network and real-time DNO are also proposed. Overall, this work creates a breakthrough towards the realization of DNO.

Task sharing within a managed clinical network to improve child health in Malawi

BACKGROUND: Eighty per cent of Malawi's 8 million children live in rural areas, and there is an extensive tiered health system infrastructure from village health clinics to district hospitals which refers patients to one of the four central hospitals. The clinics and district hospitals are staffed by nurses, non-physician clinicians and recently qualified doctors. There are 16 paediatric specialists working in two of the four central hospitals which serve the urban population as well as accepting referrals from district hospitals. In order to provide expert paediatric care as close to home as possible, we describe our plan to task share within a managed clinical network and our hypothesis that this will improve paediatric care and child health.

PRESENTATION OF THE HYPOTHESIS: Managed clinical networks have been found to improve equity of care in rural districts and to ensure that the correct care is provided as close to home as possible. A network for paediatric care in Malawi with mentoring of non-physician clinicians based in a district hospital by paediatricians based at the central hospitals will establish and sustain clinical referral pathways in both directions. Ultimately, the plan envisages four managed paediatric clinical networks, each radiating from one of Malawi's four central hospitals and covering the entire country. This model of task sharing within four hub-and-spoke networks may facilitate wider dissemination of scarce expertise and improve child healthcare in Malawi close to the child's home.

TESTING THE HYPOTHESIS: Funding has been secured to train sufficient personnel to staff all central and district hospitals in Malawi with teams of paediatric specialists in the central hospitals and specialist non-physician clinicians in each government district hospital. The hypothesis will be tested using a natural experiment model. Data routinely collected by the Ministry of Health will be corroborated at the district. This will include case fatality rates for common childhood illness, perinatal mortality and process indicators. Data from different districts will be compared at baseline and annually until 2020 as the specialists of both cadres take up posts.

IMPLICATIONS OF THE HYPOTHESIS: If a managed clinical network improves child healthcare in Malawi, it may be a potential model for the other countries in sub-Saharan Africa with similar cadres in their healthcare system and face similar challenges in terms of scarcity of specialists.

A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks

Localization is one of the key technologies in Wireless Sensor Networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints on cost and power consumption make it infeasible to equip each sensor node in the network with a Global Position System (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use mobile anchor nodes (MANs), which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. A considerable body of research has addressed the Mobile Anchor Node Assisted Localization (MANAL) problem. However to the best of our knowledge, no updated surveys on MAAL reflecting recent advances in the field have been presented in the past few years. This survey presents a review of the most successful MANAL algorithms, focusing on the achievements made in the past decade, and aims to become a starting point for researchers who are initiating their endeavors in MANAL research field. In addition, we seek to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful advances in this research field.

Feature Study on a Programmable Network Traffic Classifier

Monitoring and tracking of IP traffic flows are essential for network services (i.e. packet forwarding). Packet header lookup is the main part of flow identification by determining the predefined matching action for each incoming flow. In this paper, an improved header lookup and flow rule update solution is investigated. A detailed study of several well-known lookup algorithms reveals that searching individual packet header field and combining the results achieve high lookup speed and flexibility. The proposed hybrid lookup architecture is comprised of various lookup algorithms, which are selected based on the user applications and system requirements.

A secure authentication and key management scheme for Wireless Sensors Network

In recent years, the adaptation of Wireless Sensor Networks (WSNs) to application areas requiring mobility increased the security threats against confidentiality, integrity and privacy of the information as well as against their connectivity. Since, key management plays an important role in securing both information and connectivity, a proper authentication and key management scheme is required in mobility enabled applications where the authentication of a node with the network is a critical issue. In this paper, we present an authentication and key management scheme supporting node mobility in a heterogeneous WSN that consists of several low capabilities sensor nodes and few high capabilities sensor nodes. We analyze our proposed solution by using MATLAB (analytically) and by simulation (OMNET++ simulator) to show that it has less memory requirement and has good network connectivity and resilience against attacks compared to some existing schemes. We also propose two levels of secure authentication methods for the mobile sensor nodes for secure authentication and key establishment.