Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Performance analysis of secure unified communications in the VMware-based cloud

Unified communications as a service (UCaaS) can be regarded as a cost-effective model for on-demand delivery of unified communications services in the cloud. However, addressing security concerns has been seen as the biggest challenge to the adoption of IT services in the cloud. This study set up a cloud system via VMware suite to emulate hosting unified communications (UC), the integration of two or more real time communication systems, services in the cloud in a laboratory environment. An Internet Protocol Security (IPSec) gateway was also set up to support network-level security for UCaaS against possible security exposures. This study was aimed at analysis of an implementation of UCaaS over IPSec and evaluation of the latency of encrypted UC traffic while protecting that traffic. Our test results show no latency while IPSec is implemented with a G.711 audio codec. However, the performance of the G.722 audio codec with an IPSec implementation affects the overall performance of the UC server. These results give technical advice and guidance to those involved in security controls in UC security on premises as well as in the cloud.

Measurement of transit network accessibility based on access stop choice behaviour

This research improved the measurement of public transport accessibility by capturing; travellers' behaviour; diversity of public transport mode; and the subjectivity of travellers' decision in the complex transport networks. The results of this research not only highlighted the importance of considering public transport network characteristics but also, revealed the impact of public transport diversity in the modelling of public transport accessibility. The research developed a hybrid discrete choice model with a nested logit structure to treat the correlation among the public transport mode choices and, a logit correction factor to rectify the correlation among the stop choices.

Covalently bonded networks through surface-confined polymerization

The prospect of synthesizing ordered, covalently bonded structures directly on a surface has recently attracted considerable attention due to its fundamental interest and for potential applications in electronics and photonics. This prospective article focuses on efforts to synthesize and characterize epitaxial one- and two-dimensional (1D and 2D, respectively) polymeric networks on single crystal surfaces. Recent studies, mostly performed using scanning tunneling microscopy (STM), demonstrate the ability to induce polymerization based on Ullmann coupling, thermal dehalogenation and dehydration reactions. The 2D polymer networks synthesized to date have exhibited structural limitations and have been shown to form only small domains on the surface. We discuss different approaches to control 1D and 2D polymerization, with particular emphasis on the surface phenomena that are critical to the formation of larger ordered domains.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

Comparative analysis of traffic state estimation ─ Cumulative counts-based and trajectory-based methods

The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow. Since the MFD represents the area-wide network traffic performance, studies on perimeter control strategies and network-wide traffic state estimation utilising the MFD concept have been reported. Most previous works have utilised data from fixed sensors, such as inductive loops, to estimate the MFD, which can cause biased estimation in urban networks due to queue spillovers at intersections. To overcome the limitation, recent literature reports the use of trajectory data obtained from probe vehicles. However, these studies have been conducted using simulated datasets; limited works have discussed the limitations of real datasets and their impact on the variable estimation. This study compares two methods for estimating traffic state variables of signalised arterial sections: a method based on cumulative vehicle counts (CUPRITE), and one based on vehicles’ trajectory from taxi Global Positioning System (GPS) log. The comparisons reveal some characteristics of taxi trajectory data available in Brisbane, Australia. The current trajectory data have limitations in quantity (i.e., the penetration rate), due to which the traffic state variables tend to be underestimated. Nevertheless, the trajectory-based method successfully captures the features of traffic states, which suggests that the trajectories from taxis can be a good estimator for the network-wide traffic states.

The Networks of Learning in Technological Innovation : The Emergence of Collaboration Across Fields of Expertise

This study addresses four issues concerning technological product innovations. First, the nature of the very early phases or "embryonic stages" of technological innovation is addressed. Second, this study analyzes why and by what means people initiate innovation processes outside the technological community and the field of expertise of the established industry. In other words, this study addresses the initiation of innovation that occurs without the expertise of established organizations, such as technology firms, professional societies and research institutes operating in the technological field under consideration. Third, the significance of interorganizational learning processes for technological innovation is dealt with. Fourth, this consideration is supplemented by considering how network collaboration and learning change when formalized product development work and the commercialization of innovation advance. These issues are addressed through the empirical analysis of the following three product innovations: Benecol margarine, the Nordic Mobile Telephone system (NMT) and the ProWellness Diabetes Management System (PDMS). This study utilizes the theoretical insights of cultural-historical activity theory on the development of human activities and learning. Activity-theoretical conceptualizations are used in the critical assessment and advancement of the concept of networks of learning. This concept was originally proposed by the research group of organizational scientist Walter Powell. A network of learning refers to the interorganizational collaboration that pools resources, ideas and know-how without market-based or hierarchical relations. The concept of an activity system is used in defining the nodes of the networks of learning. Network collaboration and learning are analyzed with regard to the shared object of development work. According to this study, enduring dilemmas and tensions in activity explain the participants' motives for carrying out actions that lead to novel product concepts in the early phases of technological innovation. These actions comprise the initiation of development work outside the relevant fields of expertise and collaboration and learning across fields of expertise in the absence of market-based or hierarchical relations. These networks of learning are fragile and impermanent. This study suggests that the significance of networks of learning across fields of expertise becomes more and more crucial for innovation activities.

Human brain networks of auditory attention and working memory

This thesis examines brain networks involved in auditory attention and auditory working memory using measures of task performance, brain activity, and neuroanatomical connectivity. Auditory orienting and maintenance of attention were compared with visual orienting and maintenance of attention, and top-down controlled attention was compared to bottom-up triggered attention in audition. Moreover, the effects of cognitive load on performance and brain activity were studied using an auditory working memory task. Corbetta and Shulman s (2002) model of visual attention suggests that what is known as the dorsal attention system (intraparietal sulcus/superior parietal lobule, IPS/SPL and frontal eye field, FEF) is involved in the control of top-down controlled attention, whereas what is known as the ventral attention system (temporo-parietal junction, TPJ and areas of the inferior/middle frontal gyrus, IFG/MFG) is involved in bottom-up triggered attention. The present results show that top-down controlled auditory attention also activates IPS/SPL and FEF. Furthermore, in audition, TPJ and IFG/MFG were activated not only by bottom-up triggered attention, but also by top-down controlled attention. In addition, the posterior cerebellum and thalamus were activated by top-down controlled attention shifts and the ventromedial prefrontal cortex (VMPFC) was activated by to-be-ignored, but attention-catching salient changes in auditory input streams. VMPFC may be involved in the evaluation of environmental events causing the bottom-up triggered engagement of attention. Auditory working memory activated a brain network that largely overlapped with the one activated by top-down controlled attention. The present results also provide further evidence of the role of the cerebellum in cognitive processing: During auditory working memory tasks, both activity in the posterior cerebellum (the crus I/II) and reaction speed increased when the cognitive load increased. Based on the present results and earlier theories on the role of the cerebellum in cognitive processing, the function of the posterior cerebellum in cognitive tasks may be related to the optimization of response speed.

Soft Functional Materials Induced by Fibrillar Networks of Small Molecular Photochromic Gelators

Low-molecular-mass organogelators (LMOGs) based on photochromic molecules aggregate in selected solvents to form gels through various spatio-temporal interactions. The factors that control the mode of aggregation of the chromophoric core in the LMOGs during gelation, gelation-induced changes in fluorescence, the formation of stacked superstructures of extended pi-conjugated systems, and so forth are discussed with selected examples. Possible ways of generating various light-harvesting assemblies are proposed, and some unresolved questions, future challenges, and their possible solutions on this topic are presented.

The success of the diversified farm : resource-based view

Farms and rural areas have many specific valuable resources that can be used to create non-agricultural products and services. Most of the research regarding on-farm diversification has hitherto concentrated on business start-up or farm survival strategies. Resource allocation and also financial success have not been the primary focus of investigations as yet. In this study these specific topics were investigated i.e. resource allocation and also the financial success of diversified farms from a farm management perspective. The key question addressed in this dissertation, is how tangible and intangible resources of the diversified farm affect the financial success. This study’s theoretical background deals with resource-based theory, and also certain themes of the theory of learning organisation and other decision-making theories. Two datasets were utilised in this study. First, data were collected by postal survey in 2001 (n = 663). Second, data were collected in a follow-up survey in 2006 (n = 439). Data were analysed using multivariate data analyses and path analyses. The study results reveal that, diversified farms performed differently. Success and resources were linked. Professional and management skills affected other resources, and hence directly or indirectly influenced success per se. In the light of empirical analyses of this study, tangible and intangible resources owned by the diversified farm impacted on its financial success. The findings of this study underline the importance of skills and networks for entrepreneur(s). Practically speaking all respondents of this study used either agricultural resources for non-farm businesses or non-farm resources for agricultural enterprises. To share resources in this way was seen as a pragmatic opportunity recognised by farmers. One of the downsides of diversification might be the phenomenon of over-diversification, which can be defined as the situation in which a farm diversifies beyond its optimal limit. The empirical findings of this study reveal that capital and labour resource constrains did have adverse effects on financial success. The evidence indicates that farms that were capital and labour resource constrained in 2001 were still less profitable than their ‘no problems’ counterparts five years later.

Performance-based contracting for roads – Experiences of Australia and Indonesia

Many countries over the last decade, have used performance-based contracting (PBC) to manage and maintain roads. The implementation of PBC provides additional benefits for the government/public such as cost savings and improved conditions of contracted road assets. In Australia, PBC is already being implemented on all categories of roads: national, state, urban and rural. Australian PBC arrangement is designed to turn over control and responsibility for roadway system maintenance, rehabilitation, and capital improvement projects to private contractors. Contractors’ responsibilities include determination of treatment types, the design, programming and the undertaking of works needed to maintain road networks at predetermined performance levels. Indonesia initiated two PBC pilot projects in 2011, the Pantura Section Demak-Trengguli (7.68 kilometers) in Central Java Province and Section Ciasem-Pamanukan (18.5 kilometers) in West Java Province. Both sections are categorized as national roads. The contract duration for both of these projects is four years. To facilitate a possible way forward, it is proposed to conduct a study to understand Australia's experiences of advancing from pilot projects to nation-wide programs using PBC. The study focuses on the scope of contracts, bidding processes, risk allocation, and key drivers, using relevant PBC case studies from Australia. Recommendations for future PBC deployment nation-wide should be based on more research associated with risk allocation. This will include investigation of standard conditions of contract. Implications of the contract clauses for the risk management strategy to be adopted by contractors. Based on the nature of risks, some are best managed by the project owner. It is very important that all parties involved to be open to the new rules of contract and to convince themselves about the potential increased benefits of the use of PBC. The most recent states of challenging issues were explored and described.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

IP Mobility in Wireless Operator Networks

Wireless network access is gaining increased heterogeneity in terms of the types of IP capable access technologies. The access network heterogeneity is an outcome of incremental and evolutionary approach of building new infrastructure. The recent success of multi-radio terminals drives both building a new infrastructure and implicit deployment of heterogeneous access networks. Typically there is no economical reason to replace the existing infrastructure when building a new one. The gradual migration phase usually takes several years. IP-based mobility across different access networks may involve both horizontal and vertical handovers. Depending on the networking environment, the mobile terminal may be attached to the network through multiple access technologies. Consequently, the terminal may send and receive packets through multiple networks simultaneously. This dissertation addresses the introduction of IP Mobility paradigm into the existing mobile operator network infrastructure that have not originally been designed for multi-access and IP Mobility. We propose a model for the future wireless networking and roaming architecture that does not require revolutionary technology changes and can be deployed without unnecessary complexity. The model proposes a clear separation of operator roles: (i) access operator, (ii) service operator, and (iii) inter-connection and roaming provider. The separation allows each type of an operator to have their own development path and business models without artificial bindings with each other. We also propose minimum requirements for the new model. We present the state of the art of IP Mobility. We also present results of standardization efforts in IP-based wireless architectures. Finally, we present experimentation results of IP-level mobility in various wireless operator deployments.

A Decentralized Session Management Framework for Heterogeneous Ad-Hoc and Fixed Networks

Wireless technologies are continuously evolving. Second generation cellular networks have gained worldwide acceptance. Wireless LANs are commonly deployed in corporations or university campuses, and their diffusion in public hotspots is growing. Third generation cellular systems are yet to affirm everywhere; still, there is an impressive amount of research ongoing for deploying beyond 3G systems. These new wireless technologies combine the characteristics of WLAN based and cellular networks to provide increased bandwidth. The common direction where all the efforts in wireless technologies are headed is towards an IP-based communication. Telephony services have been the killer application for cellular systems; their evolution to packet-switched networks is a natural path. Effective IP telephony signaling protocols, such as the Session Initiation Protocol (SIP) and the H 323 protocol are needed to establish IP-based telephony sessions. However, IP telephony is just one service example of IP-based communication. IP-based multimedia sessions are expected to become popular and offer a wider range of communication capabilities than pure telephony. In order to conjoin the advances of the future wireless technologies with the potential of IP-based multimedia communication, the next step would be to obtain ubiquitous communication capabilities. According to this vision, people must be able to communicate also when no support from an infrastructured network is available, needed or desired. In order to achieve ubiquitous communication, end devices must integrate all the capabilities necessary for IP-based distributed and decentralized communication. Such capabilities are currently missing. For example, it is not possible to utilize native IP telephony signaling protocols in a totally decentralized way. This dissertation presents a solution for deploying the SIP protocol in a decentralized fashion without support of infrastructure servers. The proposed solution is mainly designed to fit the needs of decentralized mobile environments, and can be applied to small scale ad-hoc networks or also bigger networks with hundreds of nodes. A framework allowing discovery of SIP users in ad-hoc networks and the establishment of SIP sessions among them, in a fully distributed and secure way, is described and evaluated. Security support allows ad-hoc users to authenticate the sender of a message, and to verify the integrity of a received message. The distributed session management framework has been extended in order to achieve interoperability with the Internet, and the native Internet applications. With limited extensions to the SIP protocol, we have designed and experimentally validated a SIP gateway allowing SIP signaling between ad-hoc networks with private addressing space and native SIP applications in the Internet. The design is completed by an application level relay that permits instant messaging sessions to be established in heterogeneous environments. The resulting framework constitutes a flexible and effective approach for the pervasive deployment of real time applications.

Optimisation Problems in Wireless Sensor Networks : Local Algorithms and Local Graphs

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.