A decision support system for selective cleaning

[Abstract]

Strategisten investointienhallinta ryhmäpäätöksenteon tukisysteemien avulla

Tutkielman tavoitteena on kehittää prosessi yrityksen strategisten investointien hal-lintaan siten, että yrityksen strateginen arkkitehtuuri mukailee dynaamisten mark-kinoiden jatkuvasti muuttuvia kriittisiä menestystekijöitä. Tutkielma tarjoaa ratkai-sun strategisten investointien kohtaamaan epävarmuuteen, kompleksisuuteen ja si-säisiin konflikteihin luomalla dynaamisiin kyvykkyyksiin perustuvan prosessin, joka toteutetaan ryhmäpäätöksenteon tukisysteemien avulla asiantuntijatietoa hyö-dyntäen. Yrityksen strateginen arkkitehtuuri on mahdollista mallintaa skenaariopohjaisen strategiakartan eli kyvykkyyskartan avulla. Kyvykkyyskarttaan sisällytetyt QFD- ja AHP-mallit mahdollistavat strategisten investointien arvottamisen markkinoiden kriittisten menestystekijöiden suhteen. Dynaamisiin kyvykkyyksiin perustuvat lead user- ja skenaariosuunnitteluvaiheet mahdollistavat puolestaan joustavan investoin-tistrategian luonnin. Tutkielma osoittaa dynaamisia kyvykkyyksiä ja ryhmäpäätök-senteon tukisysteemejä hyödyntävän strategisten investointien hallintaprosessin tarjoavan ratkaisun strategisien investointipäätösten kohtaamiin haasteisiin.Ky-vykkyyskarttaan pohjautuvan strategisen arkkitehtuurin optimointimallin katsottiin olevan realistinen ja uskottava ja korostavan investointien strategisia vaikutuksia.

Integrating Group Support Systems to innovation process of a forest company

The objective of this study was to analyze the effects of Group Support Systems (GSS) to overall efficiency of innovation process. Overall efficiency was found to be a sum of meeting efficiency, product effectiveness, and learning efficiency. These components were studied in various working situations common in early stages of innovation process. In the empirical part of this study, the suitability of GSS at the forest company was assessed. The basics for this study were idea generation meetings held at LUT and results from the surveys done after the sessions. This data combined with the interviews and theoretical background was used to analyze suitability of this technology to organizational culture at the company. The results of this study are divided to theory and case level. On theory level GSS was found to be a potentially valuable tool for innovation managers, especially at the first stages of the process. On case level, GSS was found to be a suitable tool at Stora Enso for further utilization. A five step implementation proposal was built to illustrate what would be the next stages of GSS implementation, if technology was chosen for further implementation.

Reducing Cardiovascular Mortality Through Prevention and Management of Raised Blood Pressure: A World Heart Federation Roadmap.

Prospective epidemiological data have shown that blood pressure has a graded, continuous adverse effect on the risk of various forms of CVD (including stroke, myocardial infarction, heart failure, peripheral arterial disease and end-stage renal disease). 'Raised blood pressure' is frequently considered to be any systolic blood pressure greater than 115 mmHg. It accounts for 45% of all heart disease deaths and 51% of all stroke-related deaths [1], which together are the biggest causes of morbidity and mortality worldwide [2,3,4]. Annually, there are >17 million deaths due to CVD worldwide, of which 9.4 million are attributable to complications of raised blood pressure. This highlights the importance of both high-risk and population-based strategies in blood pressure management and control.

Prototype of a web-based participative decision support platform in natural hazards and risk management

This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.

Evaluation of a revision of the BSPcast decision support system for control of brown spot of pear

Control of brown spot of pear requires fungicide treatments of pear trees during the growing season. Scheduling fungicide sprays with the Brown spot of pear forecasting system (BSPcast) provides significantfungicide savings but does not increase the efficacy of disease control. Modifications in BSPcast wereintroduced in order to increase system performance. The changes consisted of: (1) the use of a daily infectionrisk (Rm≥0.2) instead of the 3-day cumulative risk (CR≥0.4) to guide the fungicide scheduling, and (2) theinclusion of the effect of relative humidity during interrupted wetness periods. Trials were performed during2 years in an experimental pear orchard in Spain. The modifications introduced did not result in increaseddisease control efficacy, compared with the original BSPcast system. In one year, no reduction in the numberof fungicide applications was obtained using the modified BSPcast system in comparison to the original system, but in the second year the number of treatments was reduced from 15 to 13. The original BSPcast model overestimated the daily infection risk in 6.5% of days with wetness periods with low relative humidity during the wetness interruption, and in these cases the modified version was more adequate

An analytic approach to distribution logistics strategic management

Logistics management is increasingly being recognised by many companies to be of critical concern. The logistics function includes directly or indirectly many of the new areas for achieving or maintaining competitive advantage that companies have been forced to develop due to increasing competitive pressures. The key to achieving a competitive advantage is to manage the logistics function strategically which involves determining the most cost effective method of providing the necessary customer service levels from the many combinations of operating procedures in the areas of transportation, warehousing, order processing and information systems, production, and inventory management. In this thesis, a comprehensive distribution logistics strategic management process is formed by integrating the periodic strategic planning process with a continuous strategic issues management process. Strategic planning is used for defining the basic objectives for a company and assuring co operation and synergy between the different functions of a company while strategic issues management is used on a continuous basis in order to deal with environmental and internal turbulence. The strategic planning subprocess consists of the following main phases: (1) situational analyses, (2) defining the vision and strategic goals for the logistics function, (3) determining objectives and strategies, (4) drawing up tactical action plans, and (5) evaluating the implementation of the plans and making the needed adjustments. The aim of the strategic issues management subprocess is to continuously scan the environment and the organisation for early identification of the issues having a significant impact on the logistics function using the following steps: (1) the identification of trends, (2) assessing the impact and urgency of the identified trends, (3) assigning priorities to the issues, and (4) planning responses to the, issues. The Analytic Hierarchy Process (AHP) is a systematic procedure for structuring any problem. AHP is based on the following three principles: decomposition, comparative judgements, and synthesis of priorities. AHP starts by decomposing a complex, multicriteria problem into a hierarchy where each level consists of a few manageable elements which are then decomposed into another set of elements. The second step is to use a measurement methodology to establish priorities among the elements within each level of the hierarchy. The third step in using AHP is to synthesise the priorities of the elements to establish the overall priorities for the decision alternatives. In this thesis, decision support systems are developed for different areas of distribution logistics strategic management by applying the Analytic Hierarchy Process. The areas covered are: (1) logistics strategic issues management, (2) planning of logistic structure, (3) warehouse site selection, (4) inventory forecasting, (5) defining logistic action and development plans, (6) choosing a distribution logistics strategy, (7) analysing and selecting transport service providers, (8) defining the logistic vision and strategic goals, (9) benchmarking logistic performance, and (10) logistic service management. The thesis demonstrates the potential of AHP as a systematic and analytic approach to distribution logistics strategic management.

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.

Corporate Social Responsibility in the Oil and Gas Industry: Environmental Management Systems as a Source of Sustainable Development

The environmental aspect of corporate social responsibility (CSR) expressed through the process of the EMS implementation in the oil and gas companies is identified as the main subject of this research. In the theoretical part, the basic attention is paid to justification of a link between CSR and environmental management. The achievement of sustainable competitive advantage as a result of environmental capital growth and inclusion of the socially responsible activities in the corporate strategy is another issue that is of special significance here. Besides, two basic forms of environmental management systems (environmental decision support systems and environmental information management systems) are explored and their role in effective stakeholder interaction is tackled. The most crucial benefits of EMS are also analyzed to underline its importance as a source of sustainable development. Further research is based on the survey of 51 sampled oil and gas companies (both publicly owned and state owned ones) originated from different countries all over the world and providing reports on sustainability issues in the open access. To analyze their approach to sustainable development, a specifically designed evaluation matrix with 37 indicators developed in accordance with the General Reporting Initiative (GRI) guidelines for non-financial reporting was prepared. Additionally, the quality of environmental information disclosure was measured on the basis of a quality – quantity matrix. According to results of research, oil and gas companies prefer implementing reactive measures to the costly and knowledge-intensive proactive techniques for elimination of the negative environmental impacts. Besides, it was identified that the environmental performance disclosure is mostly rather limited, so that the quality of non-financial reporting can be judged as quite insufficient. In spite of the fact that most of the oil and gas companies in the sample claim the EMS to be embedded currently in their structure, they often do not provide any details for the process of their implementation. As a potential for the further development of EMS, author mentions possible integration of their different forms in a single entity, extension of existing structure on the basis of consolidation of the structural and strategic precautions as well as development of a unified certification standard instead of several ones that exist today in order to enhance control on the EMS implementation.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Evaluating land-use related environmental impacts of biomass value chains for decision-support : Comparison and testing of methodologies proposed for environmental life cycle assessment

Life cycle assessment (LCA) is one of the most established quantitative tools for environmental impact assessment of products. To be able to provide support to environmentally-aware decision makers on environmental impacts of biomass value-chains, the scope of LCA methodology needs to be augmented to cover landuse related environmental impacts. This dissertation focuses on analysing and discussing potential impact assessment methods, conceptual models and environmental indicators that have been proposed to be implemented into the LCA framework for impacts of land use. The applicability of proposed indicators and impact assessment frameworks is tested from practitioners' perspective, especially focusing on forest biomass value chains. The impacts of land use on biodiversity, resource depletion, climate change and other ecosystem services is analysed and discussed and the interplay in between value choices in LCA modelling and the decision-making situations to be supported is critically discussed. It was found out that land use impact indicators are necessary in LCA in highlighting differences in impacts from distinct land use classes. However, many open questions remain on certainty of highlighting actual impacts of land use, especially regarding impacts of managed forest land use on biodiversity and ecosystem services such as water regulation and purification. The climate impact of energy use of boreal stemwood was found to be higher in the short term and lower in the long-term in comparison with fossil fuels that emit identical amount of CO2 in combustion, due to changes implied to forest C stocks. The climate impacts of energy use of boreal stemwood were found to be higher than the previous estimates suggest on forest residues and stumps. The product lifetime was found to have much higher influence on the climate impacts of woodbased value chains than the origin of stemwood either from thinnings or final fellings. Climate neutrality seems to be likely only in the case when almost all the carbon of harvested wood is stored in long-lived wooden products. In the current form, the land use impacts cannot be modelled with a high degree of certainty nor communicated with adequate level of clarity to decision makers. The academia needs to keep on improving the modelling framework, and more importantly, clearly communicate to decision-makers the limited certainty on whether land-use intensive activities can help in meeting the strict mitigation targets we are globally facing.

Gendered attitudes and family planning decision-making in Honduras

This study examines gendered attitudes and family planning in the Central American country of Honduras using a feminist perspective. Specifically, this study investigates the relationships between gendered attitudes (i.e., male oriented or non-male oriented attitudes) and who makes decisions about contraceptive use and family size among married and common-law Hondurans. This study also attempts to account for social elements such as gendered attitudes, education, economics, environment and demographics that may act to limit or enhance women's agency in reproductive decisionmaking. Furthermore, gender is examined to determine whether these relationships depend on the gender of the respondents. Two national Honduran surveys from 2001 are used in a secondary analysis, specifically muUinomial logisfic regression. Findings indicate that women reporting non-male oriented attitudes are significantly more likely to indicate that they (the wives) make the contraceptive decisions. Moreover, both men and women reporting non-male oriented attitudes are significantly more likely to indicate making contraceptive decisions together. Both of these effects remain significant when other social factors included in the analyses, though part of the effect is explained by education and economics. Similar effects are found in terms of family size decisions. Limitations and directions for future research are discussed.

KAIRON PROJECT : assessing the role of expressive arts in community-based breast cancer support systems in the Niagara Region

Research Report Written for the Canadian Breast Cancer Foundation.

Adaptive business intelligence for an open negotiation environment

Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation

Embedding Emotional Context in Recommender Systems

Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems