Assessing uncertainty in pollutant build-up and wash-off processes

Assessing build-up and wash-off process uncertainty is important for accurate interpretation of model outcomes to facilitate informed decision making for developing effective stormwater pollution mitigation strategies. Uncertainty inherent to pollutant build-up and wash-off processes influences the variations in pollutant loads entrained in stormwater runoff from urban catchments. However, build-up and wash-off predictions from stormwater quality models do not adequately represent such variations due to poor characterisation of the variability of these processes in mathematical models. The changes to the mathematical form of current models with the incorporation of process variability, facilitates accounting for process uncertainty without significantly affecting the model prediction performance. Moreover, the investigation of uncertainty propagation from build-up to wash-off confirmed that uncertainty in build-up process significantly influences wash-off process uncertainty. Specifically, the behaviour of particles <150µm during build-up primarily influences uncertainty propagation, resulting in appreciable variations in the pollutant load and composition during a wash-off event.

Communicative and Anticipatory Decision-making Supported by Bayesian Networks

The purpose of this research is to draw up a clear construction of an anticipatory communicative decision-making process and a successful implementation of a Bayesian application that can be used as an anticipatory communicative decision-making support system. This study is a decision-oriented and constructive research project, and it includes examples of simulated situations. As a basis for further methodological discussion about different approaches to management research, in this research, a decision-oriented approach is used, which is based on mathematics and logic, and it is intended to develop problem solving methods. The approach is theoretical and characteristic of normative management science research. Also, the approach of this study is constructive. An essential part of the constructive approach is to tie the problem to its solution with theoretical knowledge. Firstly, the basic definitions and behaviours of an anticipatory management and managerial communication are provided. These descriptions include discussions of the research environment and formed management processes. These issues define and explain the background to further research. Secondly, it is processed to managerial communication and anticipatory decision-making based on preparation, problem solution, and solution search, which are also related to risk management analysis. After that, a solution to the decision-making support application is formed, using four different Bayesian methods, as follows: the Bayesian network, the influence diagram, the qualitative probabilistic network, and the time critical dynamic network. The purpose of the discussion is not to discuss different theories but to explain the theories which are being implemented. Finally, an application of Bayesian networks to the research problem is presented. The usefulness of the prepared model in examining a problem and the represented results of research is shown. The theoretical contribution includes definitions and a model of anticipatory decision-making. The main theoretical contribution of this study has been to develop a process for anticipatory decision-making that includes management with communication, problem-solving, and the improvement of knowledge. The practical contribution includes a Bayesian Decision Support Model, which is based on Bayesian influenced diagrams. The main contributions of this research are two developed processes, one for anticipatory decision-making, and the other to produce a model of a Bayesian network for anticipatory decision-making. In summary, this research contributes to decision-making support by being one of the few publicly available academic descriptions of the anticipatory decision support system, by representing a Bayesian model that is grounded on firm theoretical discussion, by publishing algorithms suitable for decision-making support, and by defining the idea of anticipatory decision-making for a parallel version. Finally, according to the results of research, an analysis of anticipatory management for planned decision-making is presented, which is based on observation of environment, analysis of weak signals, and alternatives to creative problem solving and communication.

From Creative Ideas to New Emerging Ventures: Entrepreneurial Processes among Finnish Design Entrepreneurs

This study focuses on self-employed industrial designers and how they emerge new venture ideas. More specifically, this study strives to determine what design entrepreneurs do when they create new venture ideas, how venture ideas are nurtured into being, and how the processes are organized to bring such ideas to the market in the given industrial context. In contemporary times when the concern for the creative class is peaking, the research and business communities need more insight of the kind that this study provides, namely how professionals may contribute to their entrepreneurial processes and other agents’ business processes. On the one hand, the interviews underlying this study suggest that design entrepreneurs may act as reactive service providers who are appointed by producers or marketing parties to generate product-related ideas on their behalf. On the other hand, the interviews suggest that proactive behaviour that aims on generating own venture ideas, may force design entrepreneurs to take considerable responsibility in organizing their entrepreneurial processes. Another option is that they strive to bring venture ideas to the market in collaboration, or by passing these to other agents’ product development processes. Design entrepreneurs’ venture ideas typically emerge from design related starting points and observations. Product developers are mainly engaged with creating their own ideas, whereas service providers refer mainly to the development of other agents’ venture ideas. In contrast with design entrepreneurs, external actors commonly emphasize customer demand as their primary source for new venture ideas, as well as development of these in close interaction with available means of production and marketing. Consequently, design entrepreneurs need to address market demand since without sales their venture ideas may as well be classified as art. In case, they want to experiment with creative ideas, then there should be another source of income to support this typically uncertain and extensive process. Currently, it appears like a lot of good venture ideas and resources are being wasted, when venture ideas do not suite available production or business procedures. Sufficient communication between design entrepreneurs and other agents would assist all parties in developing production efficient and distributable venture ideas. Overall, the findings suggest that design entrepreneurs are often involved simultaneously in several processes that aim at emerging new product related ventures. Consequently, design entrepreneurship is conceptualized in this study as a dual process. This implies that design entrepreneurs can simultaneously be in charge of their entrepreneurial processes, as they operate as resources in other agents’ business processes. The interconnection between activities and agents suggests that these kinds of processes tend to be both complex and multifaceted to their nature.

Time Dimension in Consumers’ Image Construction Processes: Introducing Image Heritage and Image-in-use

This paper focuses on the time dimension in consumers’ image construction processes. Two new concepts are introduced to cover past consumer experiences about the company – image heritage, and the present image construction process - image-in-use. Image heritage and image-in-use captures the dynamic, relational, social, and contextual features of corporate image construction processes. Qualitative data from a retailing context were collected and analysed following a grounded theory approach. The study demonstrates that consumers’ corporate images have long roots in past experiences. Understanding consumers’ image heritage provides opportunities for understanding how consumers might interpret management initiatives and branding activities in the present.

Investigating online reading with eye tracking and EEG : The influence of text format, reading task and parafoveal stimuli on reading processes

Research on reading has been successful in revealing how attention guides eye movements when people read single sentences or text paragraphs in simplified and strictly controlled experimental conditions. However, less is known about reading processes in more naturalistic and applied settings, such as reading Web pages. This thesis investigates online reading processes by recording participants eye movements. The thesis consists of four experimental studies that examine how location of stimuli presented outside the currently fixated region (Study I and III), text format (Study II), animation and abrupt onset of online advertisements (Study III), and phase of an online information search task (Study IV) affect written language processing. Furthermore, the studies investigate how the goal of the reading task affects attention allocation during reading by comparing reading for comprehension with free browsing, and by varying the difficulty of an information search task. The results show that text format affects the reading process, that is, vertical text (word/line) is read at a slower rate than a standard horizontal text, and the mean fixation durations are longer for vertical text than for horizontal text. Furthermore, animated online ads and abrupt ad onsets capture online readers attention and direct their gaze toward the ads, and distract the reading process. Compared to a reading-for-comprehension task, online ads are attended to more in a free browsing task. Moreover, in both tasks abrupt ad onsets result in rather immediate fixations toward the ads. This effect is enhanced when the ad is presented in the proximity of the text being read. In addition, the reading processes vary when Web users proceed in online information search tasks, for example when they are searching for a specific keyword, looking for an answer to a question, or trying to find a subjectively most interesting topic. A scanning type of behavior is typical at the beginning of the tasks, after which participants tend to switch to a more careful reading state before finishing the tasks in the states referred to as decision states. Furthermore, the results also provided evidence that left-to-right readers extract more parafoveal information to the right of the fixated word than to the left, suggesting that learning biases attentional orienting towards the reading direction.

The Role of Electronic Word of Mouth in Shaping Consumer Attitudes

The purpose of this research was to investigate the role of electronic word of mouth (eWOM) in shaping consumer attitudes towards various products and services with concentration on the consumer attitude change. eWOM has long been proven to play an important role in influencing consumer attitudes and has been researched from a variety of perspectives. This study attempts to look deeper into the process of consumer attitude change by applying as the central theory of the study the Elaboration Likelihood Model of Persuasion by Petty and Cacioppo. In the processes of examining the background academic and empirical research the Internet and Web 2.0 are closely depicted in order to understand how throughout the past centuries technology allowed the rise of various mediums where consumers can not only share their opinions online about products and services but also communicate with other consumers. Manuel Castel’s Internet Galaxy, Gildin’s, Carl and Noland’s, Hennig-Thurau, Gwinner, Walsh and Gremler’s researches on eWOM are the central works that helped to shape both the theoretical and empirical parts of this study. The mixed method approach was chosen as a research method for this study. An online survey was conducted via the Surveymonkey.com platform and eight qualitative in-depth interviews were conducted. The results of the study show that central route queues as text quality and text argumentativeness are more prominent among the research subjects and the peripheral route queues: source credibility and source expertise did not show considerable significance. Also more experience and participation consumers have with user-rating websites and applications more inclined they are to elaborate on the central route cues and are more likely to search for opinions that they consider rational and credible. Also these respondents are less inclined to search for ratings that confirm their existing beliefs about products or services. Less experience/participation they have about eWOM more likely they are to search for reviews confirmatory to their own.

Speedup Macroblock Mode Decision in H.264/SVC Encoding Using Cost-Sensitive Learning

In this paper we present a novel macroblock mode decision algorithm to speedup H.264/SVC Intra frame encoding. We replace the complex mode-decision calculations by a classifier which has been trained specifically to minimize the reduction in RD performance. This results in a significant speedup in encoding. The results show that machine learning has a great potential and can reduce the complexity substantially with negligible impact on quality. The results show that the proposed method reduces encoding time to about 70% in base layer and up to 50% in enhancement layer of the reference implementation with a negligible loss in quality.

Role of Management Decision Variables in Determining Technology Progress and Technical Efficiency in Indian Electronic Industry

This paper analyses the influence of management on Technical Efficiency Change (TEC) and Technological Progress (TP) in the communication equipment and consumer electronics sub-sectors of Indian hardware electronics industry. Each sub-sector comprises 13 sample firms for two time periods.The primary objective is to determine the relative contribution of TP and TEC to TFP Growth (TFPG) and to establish the influence of firm specific operational management decision variables on these two components. The study finds that both the sub-sectors have strived and achieved steady TP but not TEC in the period of economic liberalisation to cope with the intensifying competition. The management decisions with respect to asset and profit utilization, vertical integration, among others, improved TP and TE in the sub-sectors. However, R&D investments and technology imports proved costly for TFP indicating inadequate efforts and/or poor resource utilisation by the management. Management was found to be complacent in terms of improving or developing their own technology as indicated by their higher dependence on import of raw materials and no influence of R&D on TP.

Optimal Control of Markov Processes with Age-Dependent Transition Rates

We study optimal control of Markov processes with age-dependent transition rates. The control policy is chosen continuously over time based on the state of the process and its age. We study infinite horizon discounted cost and infinite horizon average cost problems. Our approach is via the construction of an equivalent semi-Markov decision process. We characterise the value function and optimal controls for both discounted and average cost cases.

Wild Ungulate Decision-Making and the Role of Tiny Refuges in Human-Dominated Landscapes

Wildlife conservation in human-dominated landscapes requires that we understand how animals, when making habitat-use decisions, obtain diverse and dynamically occurring resources while avoiding risks, induced by both natural predators and anthropogenic threats. Little is known about the underlying processes that enable wild animals to persist in densely populated human-dominated landscapes, particularly in developing countries. In a complex, semi-arid, fragmented, human-dominated agricultural landscape, we analyzed the habitat-use of blackbuck, a large herbivore endemic to the Indian sub-continent. We hypothesized that blackbuck would show flexible habitat-use behaviour and be risk averse when resource quality in the landscape is high, and less sensitive to risk otherwise. Overall, blackbuck appeared to be strongly influenced by human activity and they offset risks by using small protected patches (similar to 3 km(2)) when they could afford to do so. Blackbuck habitat use varied dynamically corresponding with seasonally-changing levels of resources and risks, with protected habitats registering maximum use. The findings show that human activities can strongly influence and perhaps limit ungulate habitat-use and behaviour, but spatial heterogeneity in risk, particularly the presence of refuges, can allow ungulates to persist in landscapes with high human and livestock densities.

Product aesthetics: representing designer intent and consumer response

This thesis reports on the development of a conceptual framework for product aesthetics. By adopting the theoretical perspective that products are a medium of communication between designers and consumers, the nature of consumer response and designer intent is explored. By integrating a range of disparate literature within a single coherent framework, the varieties of consumer response to product visual form are illustrated. To investigate the ways in which designers intend to evoke these responses, a qualitative research study was undertaken. This primarily involved interviews with industrial designers and consumer investigators. Analysis of these interviews led to the development of a conceptual framework for designer intent which both mirrors, and integrates with, that produced for consumer response. By representing processes beyond design that are influential in determining product form, a broader contextual framework is presented within which product aesthetics is situated. In concluding the thesis, applications for this framework are discussed and future research directions are proposed.

Evaluating governance and participatory processes in Natura 2000: lessons learned and guidance for future prospects

In recent years, participatory approaches have been incorporated in decision-making processes as a way to strengthen the bonds between diverse areas of knowledge and social actors in natural resources management and environmental governance. Despite the favourable context, this paradigm shift is still in an early stage within the development of the Natura 2000 in the European Union, the largest network of protected areas in the world. To enhance the full scope of participatory approaches in this context, this article: (i) briefly reviews the role of participatory approaches in environmental governance, (ii) develops a common framework to evaluate such participatory processes in protected area management, (iii) applies this framework to a real case study, and (iv) based on the lessons learned, provides guidance to improve the future governance of Natura 2000 sites.

Evaluating Governance and Participatory Processes in Natura 2000: Lessons Learned and Guidance for Future Prospects

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Neural and computational representations of decision variables

These studies explore how, where, and when representations of variables critical to decision-making are represented in the brain. In order to produce a decision, humans must first determine the relevant stimuli, actions, and possible outcomes before applying an algorithm that will select an action from those available. When choosing amongst alternative stimuli, the framework of value-based decision-making proposes that values are assigned to the stimuli and that these values are then compared in an abstract “value space” in order to produce a decision. Despite much progress, in particular regarding the pinpointing of ventromedial prefrontal cortex (vmPFC) as a region that encodes the value, many basic questions remain. In Chapter 2, I show that distributed BOLD signaling in vmPFC represents the value of stimuli under consideration in a manner that is independent of the type of stimulus it is. Thus the open question of whether value is represented in abstraction, a key tenet of value-based decision-making, is confirmed. However, I also show that stimulus-dependent value representations are also present in the brain during decision-making and suggest a potential neural pathway for stimulus-to-value transformations that integrates these two results.

More broadly speaking, there is both neural and behavioral evidence that two distinct control systems are at work during action selection. These two systems compose the “goal-directed system”, which selects actions based on an internal model of the environment, and the “habitual” system, which generates responses based on antecedent stimuli only. Computational characterizations of these two systems imply that they have different informational requirements in terms of input stimuli, actions, and possible outcomes. Associative learning theory predicts that the habitual system should utilize stimulus and action information only, while goal-directed behavior requires that outcomes as well as stimuli and actions be processed. In Chapter 3, I test whether areas of the brain hypothesized to be involved in habitual versus goal-directed control represent the corresponding theorized variables.

The question of whether one or both of these neural systems drives Pavlovian conditioning is less well-studied. Chapter 4 describes an experiment in which subjects were scanned while engaged in a Pavlovian task with a simple non-trivial structure. After comparing a variety of model-based and model-free learning algorithms (thought to underpin goal-directed and habitual decision-making, respectively), it was found that subjects’ reaction times were better explained by a model-based system. In addition, neural signaling of precision, a variable based on a representation of a world model, was found in the amygdala. These data indicate that the influence of model-based representations of the environment can extend even to the most basic learning processes.

Knowledge of the state of hidden variables in an environment is required for optimal inference regarding the abstract decision structure of a given environment and therefore can be crucial to decision-making in a wide range of situations. Inferring the state of an abstract variable requires the generation and manipulation of an internal representation of beliefs over the values of the hidden variable. In Chapter 5, I describe behavioral and neural results regarding the learning strategies employed by human subjects in a hierarchical state-estimation task. In particular, a comprehensive model fit and comparison process pointed to the use of "belief thresholding". This implies that subjects tended to eliminate low-probability hypotheses regarding the state of the environment from their internal model and ceased to update the corresponding variables. Thus, in concert with incremental Bayesian learning, humans explicitly manipulate their internal model of the generative process during hierarchical inference consistent with a serial hypothesis testing strategy.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.