Dissolution of Dynamic Electronic Institutions, a first approach: Relevant factors and causes

In the context of the digital business ecosystems, small organizations cooperate between them in order to achieve common goals or offer new services for expanding their markets. There are different approaches for these cooperation models such as virtual enterprises, virtual organizations or dynamic electronic institutions which in their lifecycle have in common a dissolution phase. However this phase has not been studied deeply in the current literature and it lacks formalization. In this paper a first approach for achieving and managing the dissolution phase is proposed, as well as a CBR process in order to support it in a multi-agent system

Profitability, uncertainty and multi-product firm product proliferation: The Spanish car industry

This article studies how product introduction decisions relate to profitability and uncertainty in the context of multi-product firms and product differentiation. These two features, common to many modern industries, have not received much attention in the literature as compared to the classical problem of firm entry, even if the determinants of firm and product entry are quite different. The theoretical predictions about the sign of the impact of uncertainty on product entry are not conclusive. Therefore, an econometric model relating firms’ product introduction decisions with profitability and profit uncertainty is proposed. Firm’s estimated profits are obtained from a structural model of product demand and supply, and uncertainty is proxied by profits’ variance. The empirical analysis is carried out using data on the Spanish car industry for the period 1990-2000. The results show a positive relationship between product introduction and profitability, and a negative one with respect to profit variability. Interestingly, the degree of uncertainty appears to be a driving force of entry stronger than profitability, suggesting that the product proliferation process in the Spanish car market may have been mainly a consequence of lower uncertainty rather than the result of having a more profitable market

The generation and re-generation of social capital and enterprises in multi-stakeholders social cooperative enterprises: a system dynamic approach

Theories on social capital and on social entrepreneurship have mainly highlighted the attitude of social capital to generate enterprises and to foster good relations between third sector organizations and the public sector. This paper considers the social capital in a specific third sector enterprise; here, multi-stakeholder social cooperatives are seen, at the same time, as social capital results, creators and incubators. In the particular enterprises that identify themselves as community social enterprises, social capital, both as organizational and relational capital, is fundamental: SCEs arise from but also produce and disseminate social capital. This paper aims to improve the building of relational social capital and the refining of helpful relations drawn from other arenas, where they were created and from where they are sometimes transferred to other realities, where their role is carried on further (often working in non-profit, horizontally and vertically arranged groups, where they share resources and relations). To represent this perspective, we use a qualitative system dynamic approach in which social capital is measured using proxies. Cooperation of volunteers, customers, community leaders and third sector local organizations is fundamental to establish trust relations between public local authorities and cooperatives. These relations help the latter to maintain long-term contracts with local authorities as providers of social services and enable them to add innovation to their services, by developing experiences and management models and maintaining an interchange with civil servants regarding these matters. The long-term relations and the organizational relations linking SCEs and public organizations help to create and to renovate social capital. Thus, multi-stakeholder cooperatives originated via social capital developed in third sector organizations produce new social capital within the cooperatives themselves and between different cooperatives (entrepreneurial components of the third sector) and the public sector. In their entrepreneurial life, cooperatives have to contrast the "working drift," as a result of which only workers remain as members of the cooperative, while other stakeholders leave the organization. Those who are not workers in the cooperative are (stake)holders with "weak ties," who are nevertheless fundamental in making a worker's cooperative an authentic social multi-stakeholders cooperative. To maintain multi-stakeholder governance and the relations with third sector and civil society, social cooperatives have to reinforce participation and dialogue with civil society through ongoing efforts to include people that provide social proposals. We try to represent these processes in a system dynamic model applied to local cooperatives, measuring the social capital created by the social cooperative through proxies, such as number of volunteers and strong cooperation with public institutions. Using a reverse-engineering approach, we can individuate the determinants of the creation of social capital and thereby give support to governance that creates social capital.

Adaption of Courses and Learning Environment to the User Context in dotLRN

The explosive growth of Internet during the last years has been reflected in the ever-increasing amount of the diversity and heterogeneity of user preferences, types and features of devices and access networks. Usually the heterogeneity in the context of the users which request Web contents is not taken into account by the servers that deliver them implying that these contents will not always suit their needs. In the particular case of e-learning platforms this issue is especially critical due to the fact that it puts at stake the knowledge acquired by their users. In the following paper we present a system that aims to provide the dotLRN e-learning platform with the capability to adapt to its users context. By integrating dotLRN with a multi-agent hypermedia system, online courses being undertaken by students as well as their learning environment are adapted in real time

Socio-economic benefits of using space technologies to monitor and respond to earthquakes

Earthquakes represent a major hazard for populations around the world, causing frequent loss of life,human suffering and enormous damage to homes, other buildings and infrastructure. The Technology Resources forEarthquake Monitoring and Response (TREMOR) Team of 36 space professionals analysed this problem over thecourse of the International Space University Summer Session Program and published their recommendations in the formof a report. The TREMOR Team proposes a series of space- and ground-based systems to provide improved capabilityto manage earthquakes. The first proposed system is a prototype earthquake early-warning system that improves theexisting knowledge of earthquake precursors and addresses the potential of these phenomena. Thus, the system willat first enable the definitive assessment of whether reliable earthquake early warning is possible through precursormonitoring. Should the answer be affirmative, the system itself would then form the basis of an operational earlywarningsystem. To achieve these goals, the authors propose a multi-variable approach in which the system will combine,integrate and process precursor data from space- and ground-based seismic monitoring systems (already existing andnew proposed systems) and data from a variety of related sources (e.g. historical databases, space weather data, faultmaps). The second proposed system, the prototype earthquake simulation and response system, coordinates the maincomponents of the response phase to reduce the time delays of response operations, increase the level of precisionin the data collected, facilitate communication amongst teams, enhance rescue and aid capabilities and so forth. It isbased in part on an earthquake simulator that will provide pre-event (if early warning is proven feasible) and post-eventdamage assessment and detailed data of the affected areas to corresponding disaster management actors by means of ageographic information system (GIS) interface. This is coupled with proposed mobile satellite communication hubs toprovide links between response teams. Business- and policy-based implementation strategies for these proposals, suchas the establishment of a non-governmental organisation to develop and operate the systems, are included.

Determination of hydraulic properties of a tropical soil of Hawaii using column experiments and inverse modeling

A method for determining soil hydraulic properties of a weathered tropical soil (Oxisol) using a medium-sized column with undisturbed soil is presented. The method was used to determine fitting parameters of the water retention curve and hydraulic conductivity functions of a soil column in support of a pesticide leaching study. The soil column was extracted from a continuously-used research plot in Central Oahu (Hawaii, USA) and its internal structure was examined by computed tomography. The experiment was based on tension infiltration into the soil column with free outflow at the lower end. Water flow through the soil core was mathematically modeled using a computer code that numerically solves the one-dimensional Richards equation. Measured soil hydraulic parameters were used for direct simulation, and the retention and soil hydraulic parameters were estimated by inverse modeling. The inverse modeling produced very good agreement between model outputs and measured flux and pressure head data for the relatively homogeneous column. The moisture content at a given pressure from the retention curve measured directly in small soil samples was lower than that obtained through parameter optimization based on experiments using a medium-sized undisturbed soil column.

Computer simulation study of liquid lithium at 470 and 843 K

Both structural and dynamical properties of 7Li at 470 and 843 K are studied by molecular dynamics simulation and the results are comapred with the available experimental data. Two effective interatomic potentials are used, i.e., a potential derived from the Ashcroft pseudopotential [Phys. Lett. 23, 48 (1966)] and a recently proposed potential deduced from the neutral pseudoatom method [J. Phys.: Condens. Matter 5, 4283 (1993)]. Although the shape of the two potential functions is very different, the majority of the properties calculated from them are very similar. The differences among the results using the two interaction models are carefully discussed.

Volume-targeted and whole-heart coronary magnetic resonance angiography using an intravascular contrast agent.

PURPOSE: To compare volume-targeted and whole-heart coronary magnetic resonance angiography (MRA) after the administration of an intravascular contrast agent. MATERIALS AND METHODS: Six healthy adult subjects underwent a navigator-gated and -corrected (NAV) free breathing volume-targeted cardiac-triggered inversion recovery (IR) 3D steady-state free precession (SSFP) coronary MRA sequence (t-CMRA) (spatial resolution = 1 x 1 x 3 mm(3)) and high spatial resolution IR 3D SSFP whole-heart coronary MRA (WH-CMRA) (spatial resolution = 1 x 1 x 2 mm(3)) after the administration of an intravascular contrast agent B-22956. Subjective and objective image quality parameters including maximal visible vessel length, vessel sharpness, and visibility of coronary side branches were evaluated for both t-CMRA and WH-CMRA. RESULTS: No significant differences (P = NS) in image quality were observed between contrast-enhanced t-CMRA and WH-CMRA. However, using an intravascular contrast agent, significantly longer vessel segments were measured on WH-CMRA vs. t-CMRA (right coronary artery [RCA] 13.5 +/- 0.7 cm vs. 12.5 +/- 0.2 cm; P < 0.05; and left circumflex coronary artery [LCX] 11.9 +/- 2.2 cm vs. 6.9 +/- 2.4 cm; P < 0.05). Significantly more side branches (13.3 +/- 1.2 vs. 8.7 +/- 1.2; P < 0.05) were visible for the left anterior descending coronary artery (LAD) on WH-CMRA vs. t-CMRA. Scanning time and navigator efficiency were similar for both techniques (t-CMRA: 6.05 min; 49% vs. WH-CMRA: 5.51 min; 54%, both P = NS). CONCLUSION: Both WH-CMRA and t-CMRA using SSFP are useful techniques for coronary MRA after the injection of an intravascular blood-pool agent. However, the vessel conspicuity for high spatial resolution WH-CMRA is not inferior to t-CMRA, while visible vessel length and the number of visible smaller-diameter vessels and side-branches are improved.

Optimization and Management of Materials in Earthwork Construction, TR-501, 2010

As a result of forensic investigations of problems across Iowa, a research study was developed aimed at providing solutions to identified problems through better management and optimization of the available pavement geotechnical materials and through ground improvement, soil reinforcement, and other soil treatment techniques. The overall goal was worked out through simple laboratory experiments, such as particle size analysis, plasticity tests, compaction tests, permeability tests, and strength tests. A review of the problems suggested three areas of study: pavement cracking due to improper management of pavement geotechnical materials, permeability of mixed-subgrade soils, and settlement of soil above the pipe due to improper compaction of the backfill. This resulted in the following three areas of study: (1) The optimization and management of earthwork materials through general soil mixing of various select and unsuitable soils and a specific example of optimization of materials in earthwork construction by soil mixing; (2) An investigation of the saturated permeability of compacted glacial till in relation to validation and prediction with the Enhanced Integrated Climatic Model (EICM); and (3) A field investigation and numerical modeling of culvert settlement. For each area of study, a literature review was conducted, research data were collected and analyzed, and important findings and conclusions were drawn. It was found that optimum mixtures of select and unsuitable soils can be defined that allow the use of unsuitable materials in embankment and subgrade locations. An improved model of saturated hydraulic conductivity was proposed for use with glacial soils from Iowa. The use of proper trench backfill compaction or the use of flowable mortar will reduce the potential for developing a bump above culverts.

Sistema de presa de decisions distribuït

DDM is a framework that combines intelligent agents and artificial intelligence traditional algorithms such as classifiers. The central idea of this project is to create a multi-agent system that allows to compare different views into a single one.

Selective catalytic reduction of nitrogen oxides with ammonia in forced unsteady state reactors - Case based reasoning and mathematical model simulation reasoning

The application of forced unsteady-state reactors in case of selective catalytic reduction of nitrogen oxides (NOx) with ammonia (NH3) is sustained by the fact that favorable temperature and composition distributions which cannot be achieved in any steady-state regime can be obtained by means of unsteady-state operations. In a normal way of operation the low exothermicity of the selective catalytic reduction (SCR) reaction (usually carried out in the range of 280-350°C) is not enough to maintain by itself the chemical reaction. A normal mode of operation usually requires supply of supplementary heat increasing in this way the overall process operation cost. Through forced unsteady-state operation, the main advantage that can be obtained when exothermic reactions take place is the possibility of trapping, beside the ammonia, the moving heat wave inside the catalytic bed. The unsteady state-operation enables the exploitation of the thermal storage capacity of the catalyticbed. The catalytic bed acts as a regenerative heat exchanger allowing auto-thermal behaviour when the adiabatic temperature rise is low. Finding the optimum reactor configuration, employing the most suitable operation model and identifying the reactor behavior are highly important steps in order to configure a proper device for industrial applications. The Reverse Flow Reactor (RFR) - a forced unsteady state reactor - corresponds to the above mentioned characteristics and may be employed as an efficient device for the treatment of dilute pollutant mixtures. As a main disadvantage, beside its advantages, the RFR presents the 'wash out' phenomena. This phenomenon represents emissions of unconverted reactants at every switch of the flow direction. As a consequence our attention was focused on finding an alternative reactor configuration for RFR which is not affected by the incontrollable emissions of unconverted reactants. In this respect the Reactor Network (RN) was investigated. Its configuration consists of several reactors connected in a closed sequence, simulating a moving bed by changing the reactants feeding position. In the RN the flow direction is maintained in the same way ensuring uniformcatalyst exploitation and in the same time the 'wash out' phenomena is annulated. The simulated moving bed (SMB) can operate in transient mode giving practically constant exit concentration and high conversion levels. The main advantage of the reactor network operation is emphasizedby the possibility to obtain auto-thermal behavior with nearly uniformcatalyst utilization. However, the reactor network presents only a small range of switching times which allow to reach and to maintain an ignited state. Even so a proper study of the complex behavior of the RN may give the necessary information to overcome all the difficulties that can appear in the RN operation. The unsteady-state reactors complexity arises from the fact that these reactor types are characterized by short contact times and complex interaction between heat and mass transportphenomena. Such complex interactions can give rise to a remarkable complex dynamic behavior characterized by a set of spatial-temporal patterns, chaotic changes in concentration and traveling waves of heat or chemical reactivity. The main efforts of the current research studies concern the improvement of contact modalities between reactants, the possibility of thermal wave storage inside the reactor and the improvement of the kinetic activity of the catalyst used. Paying attention to the above mentioned aspects is important when higher activity even at low feeding temperatures and low emissions of unconverted reactants are the main operation concerns. Also, the prediction of the reactor pseudo or steady-state performance (regarding the conversion, selectivity and thermal behavior) and the dynamicreactor response during exploitation are important aspects in finding the optimal control strategy for the forced unsteady state catalytic tubular reactors. The design of an adapted reactor requires knowledge about the influence of its operating conditions on the overall process performance and a precise evaluation of the operating parameters rage for which a sustained dynamic behavior is obtained. An apriori estimation of the system parameters result in diminution of the computational efforts. Usually the convergence of unsteady state reactor systems requires integration over hundreds of cycles depending on the initial guess of the parameter values. The investigation of various operation models and thermal transfer strategies give reliable means to obtain recuperative and regenerative devices which are capable to maintain an auto-thermal behavior in case of low exothermic reactions. In the present research work a gradual analysis of the SCR of NOx with ammonia process in forced unsteady-state reactors was realized. The investigation covers the presentationof the general problematic related to the effect of noxious emissions in the environment, the analysis of the suitable catalysts types for the process, the mathematical analysis approach for modeling and finding the system solutions and the experimental investigation of the device found to be more suitable for the present process. In order to gain information about the forced unsteady state reactor design, operation, important system parameters and their values, mathematical description, mathematicalmethod for solving systems of partial differential equations and other specific aspects, in a fast and easy way, and a case based reasoning (CBR) approach has been used. This approach, using the experience of past similarproblems and their adapted solutions, may provide a method for gaining informations and solutions for new problems related to the forced unsteady state reactors technology. As a consequence a CBR system was implemented and a corresponding tool was developed. Further on, grooving up the hypothesis of isothermal operation, the investigation by means of numerical simulation of the feasibility of the SCR of NOx with ammonia in the RFRand in the RN with variable feeding position was realized. The hypothesis of non-isothermal operation was taken into account because in our opinion ifa commercial catalyst is considered, is not possible to modify the chemical activity and its adsorptive capacity to improve the operation butis possible to change the operation regime. In order to identify the most suitable device for the unsteady state reduction of NOx with ammonia, considering the perspective of recuperative and regenerative devices, a comparative analysis of the above mentioned two devices performance was realized. The assumption of isothermal conditions in the beginningof the forced unsteadystate investigation allowed the simplification of the analysis enabling to focus on the impact of the conditions and mode of operation on the dynamic features caused by the trapping of one reactant in the reactor, without considering the impact of thermal effect on overall reactor performance. The non-isothermal system approach has been investigated in order to point out the important influence of the thermal effect on overall reactor performance, studying the possibility of RFR and RN utilization as recuperative and regenerative devices and the possibility of achieving a sustained auto-thermal behavior in case of lowexothermic reaction of SCR of NOx with ammonia and low temperature gasfeeding. Beside the influence of the thermal effect, the influence of the principal operating parameters, as switching time, inlet flow rate and initial catalyst temperature have been stressed. This analysis is important not only because it allows a comparison between the two devices and optimisation of the operation, but also the switching time is the main operating parameter. An appropriate choice of this parameter enables the fulfilment of the process constraints. The level of the conversions achieved, the more uniform temperature profiles, the uniformity ofcatalyst exploitation and the much simpler mode of operation imposed the RN as a much more suitable device for SCR of NOx with ammonia, in usual operation and also in the perspective of control strategy implementation. Theoretical simplified models have also been proposed in order to describe the forced unsteady state reactors performance and to estimate their internal temperature and concentration profiles. The general idea was to extend the study of catalytic reactor dynamics taking into account the perspectives that haven't been analyzed yet. The experimental investigation ofRN revealed a good agreement between the data obtained by model simulation and the ones obtained experimentally.

Real-Time Simulation of Mobile and Industrial Machines Using the Multibody Simulation Approach

This thesis introduces a real-time simulation environment based on the multibody simulation approach. The environment consists of components that are used in conventional product development, including computer aided drawing, visualization, dynamic simulation and finite element software architecture, data transfer and haptics. These components are combined to perform as a coupled system on one platform. The environment is used to simulate mobile and industrial machines at different stages of a product life time. Consequently, the demands of the simulated scenarios vary. In this thesis, a real-time simulation environment based on the multibody approach is used to study a reel mechanism of a paper machine and a gantry crane. These case systems are used to demonstrate the usability of the real-time simulation environment for fault detection purposes and in the context of a training simulator. In order to describe the dynamical performance of a mobile or industrial machine, the nonlinear equations of motion must be defined. In this thesis, the dynamical behaviour of machines is modelled using the multibody simulation approach. A multibody system may consist of rigid and flexible bodies which are joined using kinematic joint constraints while force components are used to describe the actuators. The strength of multibody dynamics relies upon its ability to describe nonlinearities arising from wearing of the components, friction, large rotations or contact forces in a systematic manner. For this reason, the interfaces between subsystems such as mechanics, hydraulics and control systems of the mechatronic machine can be defined and analyzed in a straightforward manner.

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.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Optimization of hydrogen plant efficiency

The purpose of this master’s thesis was to study ways to increase the operating cost-efficiency of the hydrogen production process by optimizing the process parameters while, at the same time, maintaining plant reliability and safety. The literature part reviewed other hydrogen production and purification processes as well as raw material alternatives for hydrogen production. The experimental part of the master’s thesis was conducted at Solvay Chemicals Finland Oy’s hydrogen plant in spring 2012. It was performed by changing the process parameters, first, one by one, aiming for a more efficient process with clean product gas and lower natural gas consumption. The values of the process parameters were tested based on the information from the literature, process simulation and experiences of previous similar processes. The studied parameters were reformer outlet temperature, shift converter inlet temperature and steam/carbon ratio. The results show that the optimal process conditions are a lower steam/carbon ratio and reformer outlet temperature than the current values of 3.0 and 798 °C. An increase/decrease in the shift conversion inlet temperature does not affect natural gas consumption, but it has an effect on minimizing the process steam overload.