Evaluation of knowledge management performance: An organic approach

Knowledge management (KM) strategy is the planned or actual coordination of a firm's major goals and learning in time; this coordination continually co-aligns the firm's knowledge-based resources with the environment. Based on the organic perspective of strategy, a KM performance evaluation approach should be able to 1) review the knowledge governance mechanisms and learning routines that underpin the KM strategy, as well as the performance outcomes driven by the strategy, and 2) predict the evolution of performance drivers and outcomes into the future to facilitate strategic planning. This study combined a survey study and a system dynamics (SD) simulation to demonstrate the transformation from a mechanistic to an organic perspective on KM strategy and performance evaluation. The survey study was conducted based on a sample of 143 construction contractors and used structural equation modeling (SEM) techniques to develop a KM performance index for reviewing the key elements that underpin KM strategy. The SD simulation predicted the development of KM strategy configurations and the evolution of KM performance over time. The organic KM performance evaluation approach demonstrated by this study has significant potential to improve the alignment of KM strategy within an increasingly dynamic business environment.

A cellular automata model to investigate immune cell–tumor cell interactions in growing tumors in two spatial dimensions

We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.

On food security and alternative food networks: Understanding and performing food security in the context of urban bias

This paper offers one explanation for the institutional basis of food insecurity in Australia, and argues that while alternative food networks and the food sovereignty movement perform a valuable function in building forms of social solidarity between urban consumers and rural producers, they currently make only a minor contribution to Australia’s food and nutrition security. The paper begins by identifying two key drivers of food security: household incomes (on the demand side) and nutrition-sensitive, ‘fair food’ agriculture (on the supply side). We focus on this second driver and argue that healthy populations require an agricultural sector that delivers dietary diversity via a fair and sustainable food system. In order to understand why nutrition-sensitive, fair food agriculture is not flourishing in Australia we introduce the development economics theory of urban bias. According to this theory, governments support capital intensive rather than labour intensive agriculture in order to deliver cheap food alongside the transfer of public revenues gained from rural agriculture to urban infrastructure, where the majority of the voting public resides. We chart the unfolding of the Urban Bias across the twentieth century and its consolidation through neo-liberal orthodoxy, and argue that agricultural policies do little to sustain, let alone revitalize, rural and regional Australia. We conclude that by observing food system dynamics through a re-spatialized lens, Urban Bias Theory is valuable in highlighting rural–urban socio-economic and political economy tensions, particularly regarding food system sustainability. It also sheds light on the cultural economy tensions for alternative food networks as they move beyond niche markets to simultaneously support urban food security and sustainable rural livelihoods.

Correction factors for dynamic state estimation of aggregated generators

This paper presents an approach for dynamic state estimation of aggregated generators by introducing a new correction factor for equivalent inter-area power flows. The spread of generators from the center of inertia of each area is summarized by the correction term α on the equivalent power flow between the areas and is applied to the identification and estimation process. A nonlinear time varying Kalman filter is applied to estimate the equivalent angles and velocities of coherent areas by reducing the effect of local modes on the estimated states. The approach is simulated on two test systems and the results show the effect of the correction factor and the performance of the state estimation by estimating the inter-area dynamics of the system.

The ozone transfer between atmosphere and vegetation. A study on Scots pine in the field

Ozone (O3) is a reactive gas present in the troposphere in the range of parts per billion (ppb), i.e. molecules of O3 in 109 molecules of air. Its strong oxidative capacity makes it a key element in tropospheric chemistry and a threat to the integrity of materials, including living organisms. Knowledge and control of O3 levels are an issue in relation to indoor air quality, building material endurance, respiratory human disorders, and plant performance. Ozone is also a greenhouse gas and its abundance is relevant to global warming. The interaction of the lower troposphere with vegetated landscapes results in O3 being removed from the atmosphere by reactions that lead to the oxidation of plant-related components. Details on the rate and pattern of removal on different landscapes as well as the ultimate mechanisms by which this occurs are not fully resolved. This thesis analysed the controlling processes of the transfer of ozone at the air-plant interface. Improvement in the knowledge of these processes benefits the prediction of both atmospheric removal of O3 and its impact on vegetation. This study was based on the measurement and analysis of multi-year field measurements of O3 flux to Scots pine (Pinus sylvestris L.) foliage with a shoot-scale gas-exchange enclosure system. In addition, the analyses made use of simultaneous CO2 and H2O exchange, canopy-scale O3, CO2 and H2O exchange, foliage surface wetness, and environmental variables. All data was gathered at the SMEAR measuring station (southern Finland). Enclosure gas-exchange techniques such as those commonly used for the measure of CO2 and water vapour can be applied to the measure of ozone gas-exchange in the field. Through analysis of the system dynamics the occurring disturbances and noise can be identified. In the system used in this study, the possible artefacts arising from the ozone reactivity towards the system materials in combination with low background concentrations need to be taken into account. The main artefact was the loss of ozone towards the chamber walls, which was found to be very variable. The level of wall-loss was obtained from simultaneous and continuous measurements, and was included in the formulation of the mass balance of O3 concentration inside the chamber. The analysis of the field measurements in this study show that the flux of ozone to the Scots pine foliage is generated in about equal proportions by stomatal and non-stomatal controlled processes. Deposition towards foliage and forest is sustained also during night and winter when stomatal gas-exchange is low or absent. The non-stomatal portion of the flux was analysed further. The pattern of flux in time was found to be an overlap of the patterns of biological activity and presence of wetness in the environment. This was seen to occur both at the shoot and canopy scale. The presence of wetness enhanced the flux not only in the presence of liquid droplets but also during existence of a moisture film on the plant surfaces. The existence of these films and their relation to the ozone sinks was determined by simultaneous measurements of leaf surface wetness and ozone flux. The results seem to suggest ozone would be reacting at the foliage surface and the reaction rate would be mediated by the presence of surface wetness. Alternative mechanisms were discussed, including nocturnal stomatal aperture and emission of reactive volatile compounds. The prediction of the total flux could thus be based on a combination of a model of stomatal behaviour and a model of water absorption on the foliage surfaces. The concepts behind the division of stomatal and non-stomatal sinks were reconsidered. This study showed that it is theoretically possible that a sink located before or near the stomatal aperture prevents or diminishes the diffusion of ozone towards the intercellular air space of the mesophyll. This obstacle to stomatal diffusion happens only under certain conditions, which include a very low presence of reaction sites in the mesophyll, an extremely strong sink located on the outer surfaces or stomatal pore. The relevance, or existence, of this process in natural conditions would need to be assessed further. Potentially strong reactions were considered, including dissolved sulphate, volatile organic compounds, and apoplastic ascorbic acid. Information on the location and the relative abundance of these compounds would be valuable. The highest total flux towards the foliage and forest happens when both the plant activity and ambient moisture are high. The highest uptake into the interior of the foliage happens at large stomatal apertures, provided that scavenging reactions located near the stomatal pore are weak or non-existent. The discussion covers the methodological developments of this study, the relevance of the different controlling factors of ozone flux, the partition amongst its component, and the possible mechanisms of non-stomatal uptake.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters I. Algorithm

The simultaneous state and parameter estimation problem for a linear discrete-time system with unknown noise statistics is treated as a large-scale optimization problem. The a posterioriprobability density function is maximized directly with respect to the states and parameters subject to the constraint of the system dynamics. The resulting optimization problem is too large for any of the standard non-linear programming techniques and hence an hierarchical optimization approach is proposed. It turns out that the states can be computed at the first levelfor given noise and system parameters. These, in turn, are to be modified at the second level.The states are to be computed from a large system of linear equations and two solution methods are considered for solving these equations, limiting the horizon to a suitable length. The resulting algorithm is a filter-smoother, suitable for off-line as well as on-line state estimation for given noise and system parameters. The second level problem is split up into two, one for modifying the noise statistics and the other for modifying the system parameters. An adaptive relaxation technique is proposed for modifying the noise statistics and a modified Gauss-Newton technique is used to adjust the system parameters.

Uncertainty based online planning for UAV target finding in cluttered and GPS-denied environments

There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge due to the occlusion of GPS systems signal, the presence of obstacles and constraints in the space in which a UAV operates. An additional challenge is presented when a target whose location is unknown must be found within a confined space. In this paper we present a UAV navigation and target finding mission, modelled as a Partially Observable Markov Decision Process (POMDP) using a state-of-the-art online solver in a real scenario using a low cost commercial multi rotor UAV and a modular system architecture running under the Robotic Operative System (ROS). Using POMDP has several advantages to conventional approaches as they take into account uncertainties in sensor information. We present a framework for testing the mission with simulation tests and real flight tests in which we model the system dynamics and motion and perception uncertainties. The system uses a quad-copter aircraft with an board downwards looking camera without the need of GPS systems while avoiding obstacles within a confined area. Results indicate that the system has 100% success rate in simulation and 80% rate during flight test for finding targets located at different locations.

Managing uncertainty to improve the cost performance of complex infrastructure projects

There has been a recent spate of high profile infrastructure cost overruns in Australia and internationally. This is just the tip of a longer-term and more deeply-seated problem with initial budget estimating practice, well recognised in both academic research and industry reviews: the problem of uncertainty. A case study of the Sydney Opera House is used to identify and illustrate the key causal factors and system dynamics of cost overruns. It is conventionally the role of risk management to deal with such uncertainty, but the type and extent of the uncertainty involved in complex projects is shown to render established risk management techniques ineffective. This paper considers a radical advance on current budget estimating practice which involves a particular approach to statistical modelling complemented by explicit training in estimating practice. The statistical modelling approach combines the probability management techniques of Savage, which operate on actual distributions of values rather than flawed representations of distributions, and the data pooling technique of Skitmore, where the size of the reference set is optimised. Estimating training employs particular calibration development methods pioneered by Hubbard, which reduce the bias of experts caused by over-confidence and improve the consistency of subjective decision-making. A new framework for initial budget estimating practice is developed based on the combined statistical and training methods, with each technique being explained and discussed.

Vitrification, relaxation and free volume in glycerol-water binary liquid mixture:Spin probe ESR studies

Glass transition and relaxation of the glycerol-water (G-W) binary mixture system have been studied over the glycerol concentration range of 5-85 mol% by using the highly sensitive technique of electron spin resonance (ESR). For the water rich mixture the glass transition,sensed by the dissolved spin probe, arises from the vitrified mesoscopic portion of the binary system. The concentration dependence of the glass transition temperature manifests a closely related molecular level cooperativity in the system. A drastic change in the mesoscopic structure of the system at the critical concentration of 40 mol is confirmed by an estimation of the spin probe effective volume in a temperature range where the tracer reorientation is strongly coupled to the system dynamics.

A Nonlinear Approach for Re-entry Guidance of Reusable Launch Vehicles Using Model Predictive Static Programming

A nonlinear suboptimal guidance scheme is developed for the reentry phase of the reusable launch vehicles. A recently developed methodology, named as model predictive static programming (MPSP), is implemented which combines the philosophies of nonlinear model predictive control theory and approximate dynamic programming. This technique provides a finite time nonlinear suboptimal guidance law which leads to a rapid solution of the guidance history update. It does not have to suffer from computational difficulties and can be implemented online. The system dynamics is propagated through the flight corridor to the end of the reentry phase considering energy as independent variable and angle of attack as the active control variable. All the terminal constraints are satisfied. Among the path constraints, the normal load is found to be very constrictive. Hence, an extra effort has been made to keep the normal load within a specified limit and monitoring its sensitivity to the perturbation.

Korkeakoulupolitiikan dynamiikat Suomessa

The study scrutinizes the dynamics of the Finnish higher education political system. Dynamics is understood as the regularity of interaction between actors. By actors is meant the central institutions in the system. The theoretical framework of the study draws on earlier research in political science and higher education political studies. The theoretical model for analysis is built on agenda-setting theories. The theoretical model separates two dimensions of dynamics, namely the political situation and political possibilities. A political situation can be either favourable or contradictory to change. If the institutional framework within the higher education system is not compatible with the external factors of the system, the political situation is contradictory to change. To change the situation into a favourable one, one needs either to change the institutional structure or wait for external factors to change. Then again, the political possibilities can be either settled or politicized. Politicization means that new possibilities for action are found. Settled possibilities refer to routine actions performed according to old practices. The research tasks based on the theoretical model are: 1. To empirically analyse the political situation and the possibilities from the actors point of view. 2. To theoretically construct and empirically test a model for analysis of dynamics in the Finnish higher education politics. The research material consists of 25 thematic interviews with key persons in the higher education political system in 2008. In addition, there are also documents from different actors since the 1980s and statistical data. The material is analysed in four phases. In the first phase the emphasis is on trying to understand the interviewees and actors points of view. In the second phase the different types of research material are related to each other. In the third phase the findings are related to the theoretical model, which is constructed over the course of the analysis. In the fourth phase the interpretation is tested. The research distinguishes three historical periods in the Finnish higher education system and focuses on the last one. This is the era of the complex system beginning in the 1980s 1990s. Based on the interviews, four policy threads are identified and analysed in their historical context. Each of the policy threads represents one of the four possible dynamics identified in the theoretical model. The research policy thread functions according to reform dynamics. A coalition of innovation politics is able to use the politicized possibilities due to the political situation created by the conception of the national innovation system. The regional policy thread is in a gridlock dynamics. The combination of a political system based on provincial representation, a regional higher education institutional framework and outside pressure to streamline the higher education structure created a contradictory political situation. Because of this situation, the politicized possibilities in the so-called "regional development plan" do not have much effect. In the international policy thread, a consensual change dynamics is found. Through changes in the institutional framework, the higher education political system is moulded into a favourable situation. However, the possibilities are settled: a pragmatic national gaze prevailed. A dynamics of friction is found in the governance policy thread. A political situation where political-strategic and budgetary decision-making are separated is not favourable for change. In addition, as governance policy functions according to settled possibilities, the situation seems unchangeable. There are five central findings. First, the dynamics are different depending on the policy thread under scrutiny. Second, the settled possibilities in a policy thread seemed to influence other threads the most. Third, dynamics are much related to changes external to the higher education political system, the changing positions of the actors in different policy threads and the unexpected nature of the dynamics. Fourth, it is fruitful to analyse the dynamics with the theoretical model. Fifth, but only hypothetically and thus left for further research, it seems that the Finnish higher education politics is reactive and weak at politicization.

Monte-Carlo estimation of time-dependent statistical characteristics of random dynamical systems

The problem of estimating the time-dependent statistical characteristics of a random dynamical system is studied under two different settings. In the first, the system dynamics is governed by a differential equation parameterized by a random parameter, while in the second, this is governed by a differential equation with an underlying parameter sequence characterized by a continuous time Markov chain. We propose, for the first time in the literature, stochastic approximation algorithms for estimating various time-dependent process characteristics of the system. In particular, we provide efficient estimators for quantities such as the mean, variance and distribution of the process at any given time as well as the joint distribution and the autocorrelation coefficient at different times. A novel aspect of our approach is that we assume that information on the parameter model (i.e., its distribution in the first case and transition probabilities of the Markov chain in the second) is not available in either case. This is unlike most other work in the literature that assumes availability of such information. Also, most of the prior work in the literature is geared towards analyzing the steady-state system behavior of the random dynamical system while our focus is on analyzing the time-dependent statistical characteristics which are in general difficult to obtain. We prove the almost sure convergence of our stochastic approximation scheme in each case to the true value of the quantity being estimated. We provide a general class of strongly consistent estimators for the aforementioned statistical quantities with regular sample average estimators being a specific instance of these. We also present an application of the proposed scheme on a widely used model in population biology. Numerical experiments in this framework show that the time-dependent process characteristics as obtained using our algorithm in each case exhibit excellent agreement with exact results. (C) 2010 Elsevier Inc. All rights reserved.

An optimal dynamic inversion approach for controlling a class of one-dimensional nonlinear distributed parameter systems

Combining the principles of dynamic inversion and optimization theory, a new approach is presented for stable control of a class of one-dimensional nonlinear distributed parameter systems, assuming the availability a continuous actuator in the spatial domain. Unlike the existing approximate-then-design and design-then-approximate techniques, here there is no need of any approximation either of the system dynamics or of the resulting controller. Rather, the control synthesis approach is fairly straight-forward and simple. The controller formulation has more elegance because we can prove the convergence of the controller to its steady state value. To demonstrate the potential of the proposed technique, a real-life temperature control problem for a heat transfer application is solved. It has been demonstrated that a desired temperature profile can be achieved starting from any arbitrary initial temperature profile.

Common underlying steering curves for motorcycles in steady turns

We study the steady turn behaviours of some light motorcycle models on circular paths, using the commercial software package ADAMS-Motorcycle. Steering torque and steering angle are obtained for several path radii and a range of steady forward speeds. For path radii much greater than motorcycle wheelbase, and for all motorcycle parameters including tyre parameters held fixed, dimensional analysis can predict the asymptotic behaviour of steering torque and angle. In particular, steering torque is a function purely of lateral acceleration plus another such function divided by path radius. Of these, the first function is numerically determined, while the second is approximated by an analytically determined constant. Similarly, the steering angle is a function purely of lateral acceleration, plus another such function divided by path radius. Of these, the first is determined numerically while the second is determined analytically. Both predictions are verified through ADAMS simulations for various tyre and geometric parameters. In summary, steady circular motions of a given motorcycle with given tyre parameters can be approximately characterised by just one curve for steering torque and one for steering angle.

Synchronizing and Damping Torques Analysis of Nonlinear Voltage Regulators

This paper makes an attempt to assess the benefits of replacing a conventional generator excitation system (AVR + PSS) with a nonlinear voltage regulator using the concepts of synchronizing and damping torque components in a single machine infinite bus (SMIB) system. In recent years, there has been considerable interest in designing nonlinear excitation controllers, which are expected to give better dynamic performance over a wider range of system and operating conditions. The performance of these controllers is often justified by simulation studies on few test cases which may not adequately represent the diverse operating conditions of a typical power system. The performance of two such nonlinear controllers which are designed based on feedback linearization and include automatic voltage regulation with good dynamic performance have been analyzed using an SMIB model. Linearizing the nonlinear control laws along with the SMIB system equations, a Heffron Phillip's type of a model has been derived. Concepts of synchronizing and damping torque components have been used to show that such controllers can impair the small signal stability under certain operating conditions. This paper shows the possibility of negative damping contribution due to nonlinear voltage regulators and gives a new insight on understanding the physical impact of complex nonlinear control laws on power system dynamics.