An energy efficient vertical handover decision algorithm

As wireless communications evolve towards heterogeneousnetworks, mobile terminals have been enabled tohandover seamlessly from one network to another. At the sametime, the continuous increase in the terminal power consumptionhas resulted in an ever-decreasing battery lifetime. To that end,the network selection is expected to play a key role on howto minimize the energy consumption, and thus to extend theterminal lifetime. Hitherto, terminals select the network thatprovides the highest received power. However, it has been provedthat this solution does not provide the highest energy efficiency.Thus, this paper proposes an energy efficient vertical handoveralgorithm that selects the most energy efficient network thatminimizes the uplink power consumption. The performance of theproposed algorithm is evaluated through extensive simulationsand it is shown to achieve high energy efficiency gains comparedto the conventional approach.

Group preference structures in AHP–group decision making

This paper presents a procedure that allows us to determine the preference structures(PS) associated to each of the different groups of actors that can be identified in a groupdecision making problem with a large number of individuals. To that end, it makesuse of the Analytic Hierarchy Process (AHP) (Saaty, 1980) as the technique to solvediscrete multicriteria decision making problems. This technique permits the resolutionof multicriteria, multienvironment and multiactor problems in which subjective aspectsand uncertainty have been incorporated into the model, constructing ratio scales correspondingto the priorities relative to the elements being compared, normalised in adistributive manner (wi = 1). On the basis of the individuals’ priorities we identifydifferent clusters for the decision makers and, for each of these, the associated preferencestructure using, to that end, tools analogous to those of Multidimensional Scaling.The resulting PS will be employed to extract knowledge for the subsequent negotiationprocesses and, should it be necessary, to determine the relative importance of thealternatives being compared using anyone of the existing procedures

Theoretical background for market emergence framework : Case: Electricity Distribution Industry

Both the competitive environment and the internal structure of an industrial organization are typically included in the processes which describe the strategic management processes of the firm, but less attention has been paid to the interdependence between these views. Therefore, this research focuses on explaining the particular conditions of an industry change, which lead managers to realign the firm in respect of its environment for generating competitive advantage. The research question that directs the development of the theoretical framework is: Why do firms outsource some of their functions? The three general stages of the analysis are related to the following research topics: (i) understanding forces that shape the industry, (ii) estimating the impacts of transforming customer preferences, rivalry, and changing capability bases on the relevance of existing assets and activities, and emergence of new business models, and (iii) developing optional structures for future value chains and understanding general boundaries for market emergence. The defined research setting contributes to the managerial research questions “Why do firms reorganize their value chains?”, “Why and how are decisions made?” Combining Transaction Cost Economics (TCE) and Resource-Based View (RBV) within an integrated framework makes it possible to evaluate the two dimensions of a company’s resources, namely the strategic value and transferability. The final decision of restructuring will be made based on an analysis of the actual business potential of the outsourcing, where benefits and risks are evaluated. The firm focuses on the risk of opportunism, hold-up problems, pricing, and opportunities to reach a complete contract, and finally on the direct benefits and risks for financial performance. The supplier analyzes the business potential of an activity outside the specific customer, the amount of customer-specific investments, the service provider’s competitive position, abilities to revenue gains in generic segments, and long-term dependence on the customer.

Medical students' knowledge about end-of-life decision-making

The influence of medical students' knowledge concerning end-of-life care, considering ethical theories and clinical practice, remains controversial. We aimed to investigate medical students' knowledge of bioethical concepts related to moral kinds of death (euthanasia, disthanasia, and orthothanasia) and to analyze the influence of their clinical experience on practicing such approaches in a tertiary hospital in the state of São Paulo, Brazil. We interviewed 180 medical students [distributed in Group 1 (G1) - first to third- year students, and Group 2 (G2) - fourth to sixth-year students] to evaluate the influence of the course on "medical ethics" on ethical theories and clinical practice, using a closed questionnaire. The course on "medical ethics" did not distinguish the groups (P=0.704) in relation to bioethical concepts. Neologisms such as "cacothanasia" and "idiothanasia" were incorrectly viewed as bioethical concepts by 28% of the interviewees. Moreover, 45.3% of the sample considered health care professionals incapable of managing terminally ill patients, especially G2 (29%) as compared to G1 (16.5%, P=0.031). The concept of euthanasia was accepted by 41% of sample, as compared to 98.2% for orthothanasia. Among medical students that accepted ways to abbreviate life (22.9%), 30.1% belonged to G1, and only 16.1% to G2 (P=0.049). These medical students were unfamiliar with common bioethical concepts. Moreover, they considered healthcare professionals incapable of managing terminally ill patients. The ethical ideal of the "good death" reflects better acceptance of orthothanasia by medical students, suggesting a tendency to apply it in their future clinical practice.

Analysis on firm innovation boundaries

Innovation has been widely recognized as an important driver of firm competitiveness, and the firm’s internal research and development (R&D) activities are often considered to have a critical role in innovation activities. Internal R&D is, however, not the source of innovation as firms may tap into knowledge necessary for innovation also through various types of sourcing agreements or by collaborating with other organizations. The objective of this study is to analyze the way firms go about organizing efficiently their innovation boundaries. Within this context, the analysis is focused, firstly, on the relation between innovation boundaries and firm innovation performance and, secondly, on the factors explaining innovation boundary organization. The innovation literature recognizes that the sources of innovation depend on the nature of technology but does not offer a sufficient tool for analyzing innovation boundary options and their efficiency. Thus, this study suggests incorporating insights from transaction cost economics (TCE) complemented with dynamic governance costs and benefits into the analysis. The thesis consists of two parts. The first part introduces the background of the study, research objectives, an overview of the empirical studies, and the general conclusions of the study. The second part is formed of five publications. The overall results firstly indicate that although the relation between firm innovation boundary options is partly industry sector-specific, the firm level search strategies and knowledge transfer capabilities are important for innovation performance independently of the sector. Secondly, the results show that the attributes suggested by TCE alone do not offer a sufficient explanation of innovation boundary selection, especially under conditions of high levels of (radical) uncertainty. Based on the results, the dynamic governance cost and benefit framework complements the static TCE when firm innovation boundaries are scrutinized.

Russian market entry decision for an e-business company, the case Ampparit Inc.

The aim of the study was to examine foreign operation methods and suggest the entry mode for the Russian E-business market. Ampparit Inc. was chosen as a case company, as it operates in the e-commerce B2B type of the business by providing Witpik - media monitoring service. The concept of foreign operation method was clarified with a specific focus on Russian market peculiarities and E-business. The main focuses of the present work were to figure out the most applicable entry mode for the Russian market in case of e-business company and factors affecting the decision about entry, including risks, barriers and other aspects.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

MCMC Analysis for Optimization of Stochastic Models

In any decision making under uncertainties, the goal is mostly to minimize the expected cost. The minimization of cost under uncertainties is usually done by optimization. For simple models, the optimization can easily be done using deterministic methods.However, many models practically contain some complex and varying parameters that can not easily be taken into account using usual deterministic methods of optimization. Thus, it is very important to look for other methods that can be used to get insight into such models. MCMC method is one of the practical methods that can be used for optimization of stochastic models under uncertainty. This method is based on simulation that provides a general methodology which can be applied in nonlinear and non-Gaussian state models. MCMC method is very important for practical applications because it is a uni ed estimation procedure which simultaneously estimates both parameters and state variables. MCMC computes the distribution of the state variables and parameters of the given data measurements. MCMC method is faster in terms of computing time when compared to other optimization methods. This thesis discusses the use of Markov chain Monte Carlo (MCMC) methods for optimization of Stochastic models under uncertainties .The thesis begins with a short discussion about Bayesian Inference, MCMC and Stochastic optimization methods. Then an example is given of how MCMC can be applied for maximizing production at a minimum cost in a chemical reaction process. It is observed that this method performs better in optimizing the given cost function with a very high certainty.

Ambivalent self-understanding? : change, language and boundaries in the Shetland Islands (1970–present)

Avhandlingen berör språkets roll på Shetlandsöarna från år 1970 till idag och shetländarnas självbild som shetländare och skottar. Öarna, som ligger i Storbritanniens nordligaste del, beskrivs ofta som kulturellt annorlunda och unika. Även om shetländarna uppfattar sig själva som annorlunda, har utomstående betraktare tidvis tonat ner, tidvis betonat öarnas kulturella särdrag. Shetlandsöarna utgör ett intressant undersökningsobjekt, eftersom shetländarnas uppfattningar om sig själva som en särskild grupp har genomgått en förändring under de fyra senaste årtiondena. Den ekonomiska högkonjunktur som var en konsekvens av oljefynden i Nordsjön och 1990-talets politiska förändringar på öarna och i Skottland har båda påverkat de sätt på vilka Shetland beskrivs och förstås. I den förändrade samhällssituationen tvingades shetländarna omvärdera sin relation till det skotska fastlandet. Man var också tvungen att hitta nya svar på frågan vilka shetländarna är och på vilka sätt man borde värna om den verkliga eller föreställda kulturella autonomin. Avhandlingens syfte var att undersöka och analysera de sätt på vilka de samhälleliga förändringarna har påverkat shetländarnas självförståelse, särskilt de uppfattningar som är kopplade till språket. Undersökningen visar att många av dagens uppfattningar om en kulturell särart kan spåras till slutet av 1800-talet och tiden efter andra världskriget. Som avhandlingen visar har språkhistorien spelat en viktig roll i den process i vilken shetländarna har särskilt sig som en separat grupp. Språkets betydelse kan förstås korrekt endast om man i stället för att betrakta shetländarna som en etnisk grupp betraktar Shetlandsöarna som en relativt sett autonom beslutför region. I detta fall fungerar dialekten som en symbol för regional samhörighet.

A decision support system for cost determination in grain storage facility operations

Many research works have being carried out on analyzing grain storage facility costs; however a few of them had taken into account the analysis of factors associated to all pre-processing and storage steps. The objective of this work was to develop a decision support system for determining the grain storage facility costs and utilization fees in grain storage facilities. The data of a CONAB storage facility located in Ponta Grossa - PR, Brazil, was used as input of the system developed to analyze its specific characteristics, such as amount of product received and stored throughout the year, hourly capacity of drying, cleaning, and receiving, and dispatch. By applying the decision support system, it was observed that the reception and expedition costs were exponentially reduced as the turnover rate of the storage increased. The cleaning and drying costs increased linearly with grain initial moisture. The storage cost increased exponentially as the occupancy rate of the storage facility decreased.