Two-agent cooperative search using game models with endurance-time constraints

In this article, the problem of two Unmanned Aerial Vehicles (UAVs) cooperatively searching an unknown region is addressed. The search region is discretized into hexagonal cells and each cell is assumed to possess an uncertainty value. The UAVs have to cooperatively search these cells taking limited endurance, sensor and communication range constraints into account. Due to limited endurance, the UAVs need to return to the base station for refuelling and also need to select a base station when multiple base stations are present. This article proposes a route planning algorithm that takes endurance time constraints into account and uses game theoretical strategies to reduce the uncertainty. The route planning algorithm selects only those cells that ensure the agent will return to any one of the available bases. A set of paths are formed using these cells which the game theoretical strategies use to select a path that yields maximum uncertainty reduction. We explore non-cooperative Nash, cooperative and security strategies from game theory to enhance the search effectiveness. Monte-Carlo simulations are carried out which show the superiority of the game theoretical strategies over greedy strategy for different look ahead step length paths. Within the game theoretical strategies, non-cooperative Nash and cooperative strategy perform similarly in an ideal case, but Nash strategy performs better than the cooperative strategy when the perceived information is different. We also propose a heuristic based on partitioning of the search space into sectors to reduce computational overhead without performance degradation.

Inference on Cointegration in Vector Autoregressive Models (summary section only)

In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

Managing Project Business Development: an Inter-Organizational and Intra-Organizational Perspective (summary section only)

The driving force behind this study is the gap between the reality of the firms engaged in project business and the available studies covering project management and business process development. Previous studies show that project-based organizations were ‘immature’ in terms of the project-management ‘maturity model’, as few firms were found to be optimizing processes. Even within those, very little attention was paid to combine inter-organizational and intra-organizational perspectives. In this study an effort is made to elaborate some thoughts and views on project management, which interrelate firms’ external and internal activities. In line with the integration, the dissertation uses an approach to the management of project-business interdependencies in the networks of actors, activities and resources. Firstly, the study develops an understanding for inter-organizational perspectives by exploring the complementarities of process activities in the basic development of project business. It presents a framework that is elaborated on the basis of the reciprocal interactions of activities within and outside the organization—thus providing a coherent basis for continuous business-process improvement. In addition, the study presents new tools that can be used to develop project-business processes in each of its functional areas. The research demonstrates how project-business activities can be optimized using the right resources at the right time with the right actors and the right actions. The selected five articles included in this dissertation explain the basic framework for the development of project business. Each paper covers various aspects of inter-organizational and intra-organizational perspectives for project management. The study develops a valuable and procedural model for business-process improvement using the Delphi method that can be used not only in academia but also as a guide for practitioners that takes them through a series of well-defined steps when making informed, consistent and efficient changes to their business processes.

Estimation of signals in colored non gaussian noise based on Gaussian Mixture models

Non-Gaussianity of signals/noise often results in significant performance degradation for systems, which are designed using the Gaussian assumption. So non-Gaussian signals/noise require a different modelling and processing approach. In this paper, we discuss a new Bayesian estimation technique for non-Gaussian signals corrupted by colored non Gaussian noise. The method is based on using zero mean finite Gaussian Mixture Models (GMMs) for signal and noise. The estimation is done using an adaptive non-causal nonlinear filtering technique. The method involves deriving an estimator in terms of the GMM parameters, which are in turn estimated using the EM algorithm. The proposed filter is of finite length and offers computational feasibility. The simulations show that the proposed method gives a significant improvement compared to the linear filter for a wide variety of noise conditions, including impulsive noise. We also claim that the estimation of signal using the correlation with past and future samples leads to reduced mean squared error as compared to signal estimation based on past samples only.

Hedging Options with Different Time Units in the Pricing Models

This study examined the effects of the Greeks of the options and the trading results of delta hedging strategies, with three different time units or option-pricing models. These time units were calendar time, trading time and continuous time using discrete approximation (CTDA) time. The CTDA time model is a pricing model, that among others accounts for intraday and weekend, patterns in volatility. For the CTDA time model some additional theta measures, which were believed to be usable in trading, were developed. The study appears to verify that there were differences in the Greeks with different time units. It also revealed that these differences influence the delta hedging of options or portfolios. Although it is difficult to say anything about which is the most usable of the different time models, as this much depends on the traders view of the passing of time, different market conditions and different portfolios, the CTDA time model can be viewed as an attractive alternative.

An Empirical Comparison of Linear and Nonlinear Volatility Models for Nordic Stock Returns

This paper examines how volatility in financial markets can preferable be modeled. The examination investigates how good the models for the volatility, both linear and nonlinear, are in absorbing skewness and kurtosis. The examination is done on the Nordic stock markets, including Finland, Sweden, Norway and Denmark. Different linear and nonlinear models are applied, and the results indicates that a linear model can almost always be used for modeling the series under investigation, even though nonlinear models performs slightly better in some cases. These results indicate that the markets under study are exposed to asymmetric patterns only to a certain degree. Negative shocks generally have a more prominent effect on the markets, but these effects are not really strong. However, in terms of absorbing skewness and kurtosis, nonlinear models outperform linear ones.

Evaluating Option Pricing Models

This study evaluates three different time units in option pricing: trading time, calendar time and continuous time using discrete approximations (CTDA). The CTDA-time model partitions the trading day into 30-minute intervals, where each interval is given a weight corresponding to the historical volatility in the respective interval. Furthermore, the non-trading volatility, both overnight and weekend volatility, is included in the first interval of the trading day in the CTDA model. The three models are tested on market prices. The results indicate that the trading-time model gives the best fit to market prices in line with the results of previous studies, but contrary to expectations under non-arbitrage option pricing. Under non-arbitrage pricing, the option premium should reflect the cost of hedging the expected volatility during the option’s remaining life. The study concludes that the historical patterns in volatility are not fully accounted for by the market, rather the market prices options closer to trading time.

Stochastic models of IEEE 802.11e wireless net works with multimedia applications

We provide a survey of some of our recent results ([9], [13], [4], [6], [7]) on the analytical performance modeling of IEEE 802.11 wireless local area networks (WLANs). We first present extensions of the decoupling approach of Bianchi ([1]) to the saturation analysis of IEEE 802.11e networks with multiple traffic classes. We have found that even when analysing WLANs with unsaturated nodes the following state dependent service model works well: when a certain set of nodes is nonempty, their channel attempt behaviour is obtained from the corresponding fixed point analysis of the saturated system. We will present our experiences in using this approximation to model multimedia traffic over an IEEE 802.11e network using the enhanced DCF channel access (EDCA) mechanism. We have found that we can model TCP controlled file transfers, VoIP packet telephony, and streaming video in the IEEE802.11e setting by this simple approximation.

Constructing Stability in Software Product Development during Organizational Restructurings

We all have fresh in our memory what happened to the IT sector only a few years ago when the IT-bubble burst. The upswing of productivity in this sector slowed down, investors lost large investments, many found themselves looking for a new job, and countless dreams fell apart. Product developers in the IT sector have experienced a large number of organizational restructurings since the IT boom, including rapid growth, downsizing processes, and structural reforms. Organizational restructurings seem to be a complex and continuous phenomenon people in this sector have to deal with. How do software product developers retrospectively construct their work in relation to organizational restructurings? How do organizational restructurings bring about specific social processes in product development? This working paper focuses on these questions. The overall aim is to develop an understanding of how software product developers construct their work during organizational restructurings. The theoretical frame of reference is based on a social constructionist approach and discourse analysis. This approach offers more or less radical and critical alternatives to mainstream organizational theory. Writings from this perspective attempt to investigate and understand sociocultural processes by which various realities are created. Therefore these studies aim at showing how people participate in constituting the social world (Gergen & Thatchenkery, 1996); knowledge of the world is seen to be constructed between people in daily interaction, in which language plays a central role. This means that interaction, especially the ways of talking and writing about product development during organizational restructurings, become the target of concern. This study consists of 25 in-depth interviews following a pilot study based on 57 semi-structured interviews. In this working paper I analyze 9 in-depth interviews. The interviews were conducted in eight IT firms. The analysis explores how discourses are constructed and function, as well as the consequences that follow from different discourses. The analysis shows that even though the product developers have experienced many organizational restructurings, some of which have been far-reaching, their accounts build strongly on a stability discourse. According to this discourse product development is, perhaps surprisingly, not influenced to a great extent by organizational restructurings. This does not mean that product development is static. According to the social constructionist approach, product development is constantly being reproduced and maintained in ongoing processes. In other words stable effects are also ongoing achievements and these are of particular interest in this study. The product developers maintain rather than change the product development through ongoing processes of construction, even when they experience continuous extensive organizational restructurings. The discourse of stability exists alongside other discourses, some which contradict each other. Together they direct product development and generate meanings. The product developers consequently take an active role in the construction of their work during organizational restructurings. When doing this they also negotiate credible positions for themselves

Organizational Measures Taken against Workplace Bullying: The Case of Finnish Municipalities

Although workplace bullying and other inappropriate treatment in the workplace have received growing attention, especially in Northern Europe, in the past few decades, little research has so far been conducted about the prevention of and intervention in such phenomena. This paper provides a review of different organizational measures typically recommended for preventing and intervening in workplace bullying and other forms of inappropriate treatment in the workplace. These measures include anti-bullying policies, training and information, appropriate job designs, active monitoring, and early intervention. As for intervention, both informal and formal strategies are discussed. Furthermore, the paper reports findings from a study among Finnish municipalities on the extent to which these measures are actually used in Finland, a country that has fairly recently introduced anti-bullying legislation.

Construction and use of linear regression models for processor performance analysis

Processor architects have a challenging task of evaluating a large design space consisting of several interacting parameters and optimizations. In order to assist architects in making crucial design decisions, we build linear regression models that relate Processor performance to micro-architecture parameters, using simulation based experiments. We obtain good approximate models using an iterative process in which Akaike's information criteria is used to extract a good linear model from a small set of simulations, and limited further simulation is guided by the model using D-optimal experimental designs. The iterative process is repeated until desired error bounds are achieved. We used this procedure to establish the relationship of the CPI performance response to 26 key micro-architectural parameters using a detailed cycle-by-cycle superscalar processor simulator The resulting models provide a significance ordering on all micro-architectural parameters and their interactions, and explain the performance variations of micro-architectural techniques.

On the momentum balance in linear-combination models for the transition zone

The momentum balance of the linear-combination integral model for the transition zone is investigated for constant pressure flows. The imbalance is found to be small enough to be negligible for all practical purposes. [S0889-504X(00)00703-0].

Prediction of inplane damping from deterministic and stochastic models

This paper reviews computational reliability, computer algebra, stochastic stability and rotating frame turbulence (RFT) in the context of predicting the blade inplane mode stability, a mode which is at best weakly damped. Computational reliability can be built into routine Floquet analysis involving trim analysis and eigenanalysis, and a highly portable special purpose processor restricted to rotorcraft dynamics analysis is found to be more economical than a multipurpose processor. While the RFT effects are dominant in turbulence modeling, the finding that turbulence stabilizes the inplane mode is based on the assumption that turbulence is white noise.