Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

Multi-criteria logistics distribution network design using SAS/OR

This paper explores the use of the optimization procedures in SAS/OR software with application to the contemporary logistics distribution network design using an integrated multiple criteria decision making approach. Unlike the traditional optimization techniques, the proposed approach, combining analytic hierarchy process (AHP) and goal programming (GP), considers both quantitative and qualitative factors. In the integrated approach, AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, a GP model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. To facilitate the use of integrated multiple criteria decision making approach by SAS users, an ORMCDM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear programming models based on the selected GP model. An example is given to illustrate how one could use the code to design the logistics distribution network.

Network lifetime maximization with cross-layer design in wireless sensor networks

This paper investigates a cross-layer design approach for minimizing energy consumption and maximizing network lifetime (NL) of a multiple-source and single-sink (MSSS) WSN with energy constraints. The optimization problem for MSSS WSN can be formulated as a mixed integer convex optimization problem with the adoption of time division multiple access (TDMA) in medium access control (MAC) layer, and it becomes a convex problem by relaxing the integer constraint on time slots. Impacts of data rate, link access and routing are jointly taken into account in the optimization problem formulation. Both linear and planar network topologies are considered for NL maximization (NLM). With linear MSSS and planar single-source and single-sink (SSSS) topologies, we successfully use Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expressions of the optimal NL when all nodes are exhausted simultaneously. The problem for planar MSSS topology is more complicated, and a decomposition and combination (D&C) approach is proposed to compute suboptimal solutions. An analytical expression of the suboptimal NL is derived for a small scale planar network. To deal with larger scale planar network, an iterative algorithm is proposed for the D&C approach. Numerical results show that the upper-bounds of the network lifetime obtained by our proposed optimization models are tight. Important insights into the NL and benefits of cross-layer design for WSN NLM are obtained.

Practical network coding for two way relay channels in LTE networks

In this paper, the implementation aspects and constraints of the simplest network coding (NC) schemes for a two-way relay channel (TWRC) composed of a user equipment (mobile terminal), an LTE relay station (RS) and an LTE base station (eNB) are considered in order to assess the usefulness of the NC in more realistic scenarios. The information exchange rate gain (IERG), the energy reduction gain (ERG) and the resource utilization gain (RUG) of the NC schemes with and without subcarrier division duplexing (SDD) are obtained by computer simulations. The usefulness of the NC schemes are evaluated for varying traffic load levels, the geographical distances between the nodes, the RS transmit powers, and the maximum numbers of retransmissions. Simulation results show that the NC schemes with and without SDD, have the throughput gains 0.5% and 25%, the ERGs 7 - 12% and 16 - 25%, and the RUGs 0.5 - 3.2%, respectively. It is found that the NC can provide performance gains also for the users at the cell edge. Furthermore, the ERGs of the NC increase with the transmit power of the relay while the ERGs of the NC remain the same even when the maximum number of retransmissions is reduced.

Network optimisation - A statistical physics perspective

Inference and optimisation of real-value edge variables in sparse graphs are studied using the tree based Bethe approximation optimisation algorithms. Equilibrium states of general energy functions involving a large set of real edge-variables that interact at the network nodes are obtained for networks in various cases. These include different cost functions, connectivity values, constraints on the edge bandwidth and the case of multiclass optimisation.

Development of local homeland security networks in the state of Florida: A social network analysis approach

How do local homeland security organizations respond to catastrophic events such as hurricanes and acts of terrorism? Among the most important aspects of this response are these organizations ability to adapt to the uncertain nature of these "focusing events" (Birkland 1997). They are often behind the curve, seeing response as a linear process, when in fact it is a complex, multifaceted process that requires understanding the interactions between the fiscal pressures facing local governments, the institutional pressures of working within a new regulatory framework and the political pressures of bringing together different levels of government with different perspectives and agendas. ^ This dissertation has focused on tracing the factors affecting the individuals and institutions planning, preparing, responding and recovering from natural and man-made disasters. Using social network analysis, my study analyzes the interactions between the individuals and institutions that respond to these "focusing events." In practice, it is the combination of budgetary, institutional, and political pressures or constraints interacting with each other which resembles a Complex Adaptive System (CAS). ^ To investigate this system, my study evaluates the evolution of two separate sets of organizations composed of first responders (Fire Chiefs, Emergency Management Coordinators) and community volunteers organized in the state of Florida over the last fifteen years. Using a social network analysis approach, my dissertation analyzes the interactions between Citizen Corps Councils (CCCs) and Community Emergency Response Teams (CERTs) in the state of Florida from 1996–2011. It is the pattern of interconnections that occur over time that are the focus of this study. ^ The social network analysis revealed an increase in the amount and density of connections between these organizations over the last fifteen years. The analysis also exposed the underlying patterns in these connections; that as the networks became more complex they also became more decentralized though not in any uniform manner. The present study brings to light a story of how communities have adapted to the ever changing circumstances that are sine qua non of natural and man-made disasters.^

Basic measurements of radiation from the Baseline Surface Radiation Network (BSRN) in the years 1992 to 2012, reference list of 6378 datasets

In the framework of the global energy balance, the radiative energy exchanges between Sun, Earth and space are now accurately quantified from new satellite missions. Much less is known about the magnitude of the energy flows within the climate system and at the Earth surface, which cannot be directly measured by satellites. In addition to satellite observations, here we make extensive use of the growing number of surface observations to constrain the global energy balance not only from space, but also from the surface. We combine these observations with the latest modeling efforts performed for the 5th IPCC assessment report to infer best estimates for the global mean surface radiative components. Our analyses favor global mean downward surface solar and thermal radiation values near 185 and 342 Wm**-2, respectively, which are most compatible with surface observations. Combined with an estimated surface absorbed solar radiation and thermal emission of 161 Wm**-2 and 397 Wm**-2, respectively, this leaves 106 Wm**-2 of surface net radiation available for distribution amongst the non-radiative surface energy balance components. The climate models overestimate the downward solar and underestimate the downward thermal radiation, thereby simulating nevertheless an adequate global mean surface net radiation by error compensation. This also suggests that, globally, the simulated surface sensible and latent heat fluxes, around 20 and 85 Wm**-2 on average, state realistic values. The findings of this study are compiled into a new global energy balance diagram, which may be able to reconcile currently disputed inconsistencies between energy and water cycle estimates.

Position measurements at five permanent GPS stations in the Bavarian Alps as part of the Geodetic Alpine Integrated Network (GAIN) of the ALPS-GPSQUAKENET project

In the frame of the transnational ALPS-GPSQUAKENET project, a component of the Alpine Space Programme of the European Community Initiative Programme (CIP) INTERREG III B, the Deutsches Geodätisches Forschungsinstitut (DGFI) in Munich, Germany, installed in 2005 five continuously operating permanent GPS stations located along the northern Alps boundary in Bavaria. The main objective of the ALPS-GPSQUAKENET project was to build-up a high-performance transnational space geodetic network of Global Positioning System (GPS) receivers in the Alpine region (the so-called Geodetic Alpine Integrated Network, GAIN). Data from this network allows for studying crustal deformations in near real-time to monitor Earthquake hazard and improve natural disaster prevention. The five GPS stations operatied by DGFI are mounted on concrete pillars attached to solid rock. The names of the stations are (from west to east) Hochgrat (HGRA), Breitenberg (BREI), Fahrenberg (FAHR), Hochries (HRIE) and Wartsteinkopf (WART). The provided data series start from October 7, 2005. Data are stored with a temporal spacing of 15 seconds in daily RINEX files.

R-ArcticNet, A Regional Hydrographic Data Network for the Pan-Arctic Region (ISO-image of CD-ROM)

We describe the contemporary hydrography of the pan-Arctic land area draining into the Arctic Ocean, northern Bering Sea, and Hudson Bay on the basis of observational records of river discharge and computed runoff. The Regional Arctic Hydrographic Network data set, R-ArcticNET, is presented, which is based on 3754 recording stations drawn from Russian, Canadian, European, and U.S. archives. R-ArcticNET represents the single largest data compendium of observed discharge in the Arctic. Approximately 73% of the nonglaciated area of the pan-Arctic is monitored by at least one river discharge gage giving a mean gage density of 168 gages per 106 km2. Average annual runoff is 212 mm yr?1 with approximately 60% of the river discharge occurring from April to July. Gridded runoff surfaces are generated for the gaged portion of the pan-Arctic region to investigate global change signals. Siberia and Alaska showed increases in winter runoff during the 1980s relative to the 1960s and 1970s during annual and seasonal periods. These changes are consistent with observations of change in the climatology of the region. Western Canada experienced decreased spring and summer runoff.

Exploring the relationship between women’s empowerment and the internet in China: potentials and constraints

This thesis reports on an exploratory study of the relationship between the Internet and women’s empowerment in China. The theoretical framework of the study combines feminist theorisations of power – the core concept of empowerment – with insights from sociological perspectives on power and gender, as well as collective action theory. This allows for the conceptualisation of women’s empowerment as a dynamic process that is shaped by a set of communicative practices. Focusing on female Chinese bloggers and women’s groups of different organisational types, this study aims to explore the respective ways in which these two types of women actors use the Internet with a view to examining whether, and the extent to which it enables them to generate a sense of empowerment. The empirical data mainly derives from interviews with female bloggers and with staff members from different women’s groups, as well as from a features analysis and social network analysis of the sampled blogs and official websites of studied groups. Overall, the findings suggest that the opportunities offered by the Internet for women’s empowerment through awareness-raising, social interactions, and the organising of collective action, are limited. For female bloggers, their activities do not translate the new communicative practices afforded by the Internet into concrete action to bring about changes in their everyday life. On the contrary, blogs become an alternative platform to discipline their behaviours and to reinforce patriarchal gendered norms. Moreover, the research finds that the promise of empowerment is further undermined by the pervasive commercialisation of the Internet and state control. For women’s groups, contextual factors prevent them from fully realising the potential of the Internet for increasing their organisational visibility, promoting public awareness about gender issues, building a sense of the collective, campaigning, or networking. The major barriers in these processes are state control, a lack of resources, online censorship, and at times, competition from commercial sites. In this respect, the Internet does not play a significant role in forming a collective to challenge existing unjust power relations.

Opportunities and constraints of transhumant small ruminant production in the Chinese Altay Mountains

This PhD thesis focuses on current livelihoods of agro-pastoral livestock keepers, their animal nutrition, herd and rangeland management strategies. It thereby aims to contribute to sustainable rangeland management, livestock production and household income in Qinghe county of the Chinese Altay Mountain region, located in Xinjiang Uyghur Autonomous Region, PR China. In its first part the study characterizes the socio-economic situation and agricultural practices of agro-pastoralists through structured household interviews. The second part provides insights into the grazing behaviour and feed intake of small ruminants on seasonal pastures in this region, and into the quantitative and qualitative biomass offer on natural rangelands. The third part analyses the reproductive performance and annual growth of the local sheep and goat herds, and, by modelling improved feeding and culling strategies, tests herd management options that potentially improve the monetary output per female herd animal without increasing the pressure onto natural rangelands. Taken together, the results of the study suggest that, despite an increase and intensification of cropping and vegetable gardening in the region of Qinghe, livestock rearing is still the major livelihood strategy both in terms of prevalence and relative importance. However, livestock keeping is challenged by low biomass production on rangelands, due to the combined impact of high climate variability and highly localized grazing pressure on the seasonal pastures. Though government regulations try to tackle the latter aspect, their implementation is sometimes difficult. Alternatives to strict regulation of grazing periods and animal numbers on seasonal pastures are, in the case of goats, more rigorous culling strategies and, in the case of sheep and goats, strategic supplementation of the animals in the winter and spring season. However, for the latter strategy to become economically viable, an improvement of live animal and meat marketing options and an investment in local meat processing facilities that add value to the carcasses is needed. As the regional cities grow rapidly, the potential market to absorb diverse and good quality meat products is there, along with the road network connecting Qinghe county to the regional capital. Such governmental measures will not only create new job opportunities in the region but also benefit the cash income of pastoralists in this westernmost region of China.

Modeling the Network of Dutch and Flemish Print Production, 1550-1750

The production of artistic prints in the sixteenth- and seventeenth-century Netherlands was an inherently social process. Turning out prints at any reasonable scale depended on the fluid coordination between designers, platecutters, and publishers; roles that, by the sixteenth century, were considered distinguished enough to merit distinct credits engraved on the plates themselves: invenit, fecit/sculpsit, and excudit. While any one designer, plate cutter, and publisher could potentially exercise a great deal of influence over the production of a single print, their individual decisions (Whom to select as an engraver? What subjects to create for a print design? What market to sell to?) would have been variously constrained or encouraged by their position in this larger network (Who do they already know? And who, in turn, do their contacts know?) This dissertation addresses the impact of these constraints and affordances through the novel application of computational social network analysis to major databases of surviving prints from this period. This approach is used to evaluate several questions about trends in early modern print production practices that have not been satisfactorily addressed by traditional literature based on case studies alone: Did the social capital demanded by print production result in centralized, or distributed production of prints? When, and to what extent, did printmakers and publishers in the Low countries favor international versus domestic collaborators? And were printmakers under the same pressure as painters to specialize in particular artistic genres? This dissertation ultimately suggests how simple professional incentives endemic to the practice of printmaking may, at large scales, have resulted in quite complex patterns of collaboration and production. The framework of network analysis surfaces the role of certain printmakers who tend to be neglected in aesthetically-focused histories of art. This approach also highlights important issues concerning art historians’ balancing of individual influence versus the impact of longue durée trends. Finally, this dissertation also raises questions about the current limitations and future possibilities of combining computational methods with cultural heritage datasets in the pursuit of historical research.

Credible Commitments and Post-Conflict Refugee Return: A Statistical and Network Analysis

I examine determinants of refugee return after conflicts. I argue that institutional constraints placed on the executive provide a credible commitment that signals to refugees that the conditions required for durable return will be created. This results in increased return flows for refugees. Further, when credible commitments are stronger in the country of origin than in the country of asylum, the level of return increases. Finally, I find that specific commitments made to refugees in the peace agreement do not lead to increased return because they are not credible without institutional constraints. Using data on returnees that has only recently been made available, along with network analysis and an original coding of the provisions in refugee agreements, statistical results are found to support this theory. An examination of cases in Djibouti, Sierra Leone, and Liberia provides additional support for this argument.

Network Development with Bicycle Lanes

Bicycling as an active mode of transport can offer great individual and societal benefits. Allocating space for bicycle facilities is the key to promoting cycling as bicyclists perceive better safety and convenience in separate bikeways. In this thesis, a method is proposed for optimizing the selection and scheduling of capacity enhancements in road networks while also optimizing the allocation of road space to bicycle lanes. The goal is to determine what fraction of the available space should be allocated to bicycles, as the network evolves, in order to minimize the present value of the total cost of the system cost. The allocation method is combined with a genetic algorithm to select and schedule road expansion projects under certain budget constraints.

Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.