It has been demonstrated in a number of robotic areas how the use of virtual fixtures improves task performance both in terms of execution time and overall precision, [1]. However, the fixtures are typically inflexible, resulting in a degraded performance in cases of unexpected obstacles or incorrect fixture models. In this paper, we propose the use of adaptive virtual fixtures that enable us to cope with the above problems. A teleoperative or human machine collaborative setting is assumed with the core idea of dividing the task, that the operator is executing, into several subtasks. The operator may remain in each of these subtasks as long as necessary and switch freely between them. Hence, rather than executing a predefined plan, the operator has the ability to avoid unforeseen obstacles and deviate from the model. In our system, the probability that the user is following a certain trajectory (subtask) is estimated and used to automatically adjusts the compliance. Thus, an on-line decision of how to fixture the movement is provided.

Acquiring, representing and modeling human skins is one of the key research areas in teleoperation, programming. by-demonstration and human-machine collaborative settings. One of the common approaches is to divide the task that the operator is executing into several subtasks in order to provide manageable modeling. In this paper we consider the use of a Layered Hidden Markov Model (LHMM) to model human skills. We evaluate a gestem classifier that classifies motions into basic action-primitives, or gestems. The gestem classifiers are then used in a LHMM to model a simulated teleoperated task. We investigate the online and offline classilication performance with respect to noise, number of gestems, type of HAIM and the available number of training sequences. We also apply the LHMM to data recorded during the execution of a trajectory-tracking task in 2D and 3D with a robotic manipulator in order to give qualitative as well as quantitative results for the proposed approach. The results indicate that the LHMM is suitable for modeling teleoperative trajectory-tracking tasks and that the difference in classification performance between one and multi dimensional HMMs for gestem classification is small. It can also be seen that the LHMM is robust w.r.t misclassifications in the underlying gestem classifiers.

Acquiring, representing and modelling human skills is one of the key research areas in teleoperation, programming-by-demonstration and human-machine collaborative settings. The problems are challenging mainly because of the lack of a general mathematical model to describe human skills. One of the common approaches is to divide the task that the operator is executing into several subtasks or low-level subsystems in order to provide manageable modelling. In this paper we consider the use of a Layered Hidden Markov Model (LHMM) to model human skills. We evaluate a gesteme classifier that classifies motions into basic action-primitives, or gestemes. The gesteme classifiers are then used in a LHMM to model a teleoperated task. The proposed methodology uses three different HMM models at the gesteme level: one-dimensional HMM, multi-dimensional HMM and multidimensional HMM with Fourier transform. The online and off-line classification performance of these three models is evaluated with respect to the number of gestemes, the influence of the number of training samples, the effect of noise and the effect of the number of observation symbols. We also apply the LHMM to data recorded during the execution of a trajectory tracking task in 2D and 3D with a mobile manipulator in order to provide qualitative as well as quantitative results for the proposed approach. The results indicate that the LHMM is suitable for modelling teleoperative trajectory-tracking tasks and that the difference in classification performance between one and multidimensional HMMs for gesteme classification is small. It can also be seen that the LHMM is robust with respect to misclassifications in the underlying gesteme classifiers.

This paper presents our ongoing research in the design of a versatile service robot capable of operating in a home or office environment. Ideas presented here cover architectural issues and possible applications for such a robot system with focus on tasks requiring constrained end-effector motions. Two key components of such system is a path planner and a reactive behavior capable of force relaxation and path adaptation. These components are presented in detail along with an overview of the software architecture they fit into.

One of the main challenges in the field of robotics is to make robots ubiquitous. To intelligently interact with the world, such robots need to understand the environment and situations around them and react appropriately, they need context-awareness. But how to equip robots with capabilities of gathering and interpreting the necessary information for novel tasks through interaction with the environment and by providing some minimal knowledge in advance? This has been a longterm question and one of the main drives in the field of cognitive system development. The main idea behind the work presented in this paper is that the robot should, like a human infant, learn about objects by interacting with them, forming representations of the objects and their categories that are grounded in its embodiment. For this purpose, we study an early learning of object grasping process where the agent, based on a set of innate reflexes and knowledge about its embodiment. We stress out that this is not the work on grasping, it is a system that interacts with the environment based on relations of 3D visual features generated trough a stereo vision system. We show how geometry, appearance and spatial relations between the features can guide early reactive grasping which can later on be used in a more purposive manner when interacting with the environment.

The design of a software environment, SimDB, for molecular dynamics simulation and analysis is presented as an example of virtual laboratories enabled by high-speed networks connecting substantial computing and storage resources with more modest local compuation and visualization resources available to research groups. SimDB includes large-scale, dynamic, distributed data repositories. The simulated data sets, trajectories, are usually interpreted through reduced data sets, processed data sets, calculated by analysis functions. Both trajectory data and processed data are saved, but in differnt data bases, with processed data bases having several smaller objects for each trajectory. A browser based user interface with a well defined API allows for a wide array of analysis functions. Analysis functions are executed only if the requested analysis result is not available. The ability to incorporate user defined functions is a critical feature of SimDB.

This paper extends the recently developed Model-Aided Visual-Inertial Fusion (MA-VIF) technique for quadrotor Micro Air Vehicles (MAV) to deal with wind disturbances. The wind effects are explicitly modelled in the quadrotor dynamic equations excluding the unobservable wind velocity component. This is achieved by a nonlinear observability of the dynamic system with wind effects. We show that using the developed model, the vehicle pose and two components of the wind velocity vector can be simultaneously estimated with a monocular camera and an inertial measurement unit. We also show that the MA-VIF is reasonably tolerant to wind disturbances, even without explicit modelling of wind effects and explain the reasons for this behaviour. Experimental results using a Vicon motion capture system are presented to demonstrate the effectiveness of the proposed method and validate our claims.

This chapter provides an overview of energy demand issues in the field of ICT with a focus on the history of measuring, modelling and regulating ICT electricity consumption and the resulting methodological challenges. While the energy efficiency of ICT hardware has been dramatically improving and will continue to improve for some decades, the overall energy used for ICT is still increasing. The growing demand for ICT devices and services outpaces the efficiency gains of individual devices. Worldwide per capita ICT electricity consumption exceeded 100 kWh/year in 2007 (a value which roughly doubles if entertainment equipment is included) and is further increasing. Methodological challenges include issues of data collection and modelling ICT devices and services, assessing the entire life cycle of ICT devices and infrastructures, accounting for embedded ICT, and assessing the effect of software on ICT energy consumption.

Dalton is a molecular electronic structure program featuring common methods of computational chemistry that are based on pure quantum mechanics (QM) as well as hybrid quantum mechanics/molecular mechanics (QM/MM). It is specialized and has a leading position in calculation of molecular properties with a large world-wide user community (over 2000 licenses issued). In this paper, we present a performance characterization and optimization of Dalton. We also propose a solution to avoid the master/worker design of Dalton to become a performance bottleneck for larger process numbers. With these improvements we obtain speedups of 4x, increasing the parallel efficiency of the code and being able to run in it in a much bigger number of cores.

Dalton is a molecular electronic structure program featuring common methods of computational chemistry that are based on pure quantum mechanics (QM) as well as hybrid quantum mechanics/molecular mechanics (QM/MM). It is specialized and has a leading position in calculation of molecular properties with a large world-wide user community (over 2000 licenses issued). In this paper, we present a characterization and performance optimization of Dalton that increases the scalability and parallel efficiency of the application. We also propose asolution that helps to avoid the master/worker design of Daltonto become a performance bottleneck for larger process numbers and increase the parallel efficiency.

In environmental systems analysis tools such as cost-benefit analysis (CBA), life-cycle assessment (LCA) and Environmental Management Systems (EMS), weighting is often used to aggregate results and compare different alternatives. There are several weighting sets available, but so far there is no set that consistently use monetary values based on actual or hypothetical market valuation of environmental degradation and depletion. In this paper, we develop a weighting set where the values are based on willingness-to-pay estimates for environmental quality, and market values for resource depletion. The weighting set is applied to three case studies and the outcome is compared with the outcomes from three other weighting sets. Ecotax02, Ecoindicator99 and EPS2000. We find that the different sets give different results in many cases. The reason for this is partly that they are based on different values and thus should give different results. However, the differences can also be explained by data gaps and different methodological choices. If weighting sets are used, it is also important to use several to reduce the risk of overlooking important impacts due to data gaps. It is also interesting to note that though Ecovalue08 and Ecotax02 give different absolute values, the results are very similar in relative terms. Thus the political and the individual willingness-to-pay estimates yield a similar ranking of the impacts.

In environmental systems analysis tools like Life Cycle Assessment, strategic environmental assessment, cost benefit analysis and environmental management systems, results need to be presented in a comprehensible way to make alternatives easily comparable. One way of doing this is to aggregate results to a manageable set by using weighting methods.. In this paper, we explore how weighting methods are used in some selected Environmental Systems Analysis Tools (ESATs), and suggest possible developments of their use. We examine the differences in current use patterns, discuss the reasons for and implications of such differences, and investigate whether observed differences in use are necessary. The result of our survey shows that weighting and valuation is broadly used in the examined ESATs. The use of weighting/valuation methods is different in different tools, but these differences are not always related to the application; rather, they are related to traditions and views on valuation and weighting. Also, although the requirements on the weights/values may differ between tools, there are intersections where they coincide. Monetary weights, using either endpoint or midpoint methods, are found to be useful in all the selected tools. Furthermore, the inventory shows that that there is a common need for generic sets of weights. There is a need for further research focusing on the development of consistent value sets derived with a wide range of methods. In parallel to the development of weighting methods it is important with critical evaluations of the weighting sets with regard to scientific quality, consistency and data gaps.

The aim of this thesis is to assess potential environmental impacts of electronic media distribution and consumption—from a life cycle perspective—as compared to those of print media.

The thesis consists of a cover essay and two papers appended at the end of the thesis. The cover essay summarizes the papers and puts them in context. The main objectives of the thesis are twofold: to assess potential environmental impacts of production and consumption of tablet editions of magazines from a life cycle perspective (Paper I), and to compare potential environmental impacts of a magazine’s print edition with that of its tablet edition (Paper II).

The thesis examines the following specific research questions: (1) What are the main environmental impacts of print and tablet editions? (2) Which activities are giving rise to the main environmental impacts of the print and tablet editions? (3) What are the key factors influencing these impacts? (4) What are major data gaps and uncertainties?

Based on the present assessment, it is clear that for the print magazine, pulp and paper production is the principal cause of most of the potential environmental impacts. For this reason, the use of recycled paper, rather than virgin fiber, in newsprint production may considerably offset environmental impacts.

For the tablet edition, the content production dominates the potential environmental impacts when readers are few. This appears to be the case in an emerging state of the magazine, but with distribution of more media products to smaller groups of people, this may persist for “mature” products as well. As the number of tablet readers grows, more of the environmental impact of the is due to manufacturing of the device and electronic distribution. However, content production may still be a major factor, depending on the specific environmental impacts studied.

The production and consumption of information and communication technology (ICT) products and services continue to grow worldwide. This trend is accompanied by a corresponding increase in electricity use by ICT, as well as direct environmental impacts of the technology. Yet a more complicated picture of ICT’s effects is emerging. Positive indirect effects on environmental sustainability can be seen in substitution and optimization (enabling effects), and negative indirect effects can be seen in additional demand due to efficiency improvements (rebound effects).

A variety of methods can be employed to model and assess these direct and indirect effects of ICT on environmental sustainability. This doctoral thesis explores methods of modeling and assessing environmental effects of ICT, including electronic media. In a series of five studies, three methods were at times applied in case studies and at others analyzed theoretically. These methods include life cycle assessment (LCA) and complex systems modeling approaches, including System Dynamics (SD) and agent-based (AB) modeling.

The first two studies employ the LCA approach in a case study of an ICT application, namely, the tablet edition of a Swedish design magazine. The use of tablets has skyrocketed in recent years, and this phenomenon has been little studied to date. Potential environmental impacts of the magazine’s tablet edition were assessed and compared with those of the print edition. The tablet edition’s emerging version (which is marked by a low number of readers and low reading time per copy) resulted in higher potential environmental impacts per reader than did the print edition. However, the mature tablet edition (with a higher number of readers and greater reading time per copy) yielded lower impacts per reader in half the ten impact categories assessed.

While previous studies of electronic media have reported that the main life-cycle contributor to environmental impacts is the use phase (which includes operational electricity use as well as the manufacture of the electronic device), the present study did not support those findings in all scenarios studied in this thesis. Rather, this study found that the number of readers played an important role in determining which life-cycle phase had the greatest impacts. For the emerging version, with few readers, content production was the leading driver of environmental impacts. For the mature version, with a higher number of readers, electronic storage and distribution were the major contributors to environmental impacts. Only when there were many readers but low overall use of the tablet device was the use phase the main contributor to environmental impacts of the tablet edition of the magazine.

The third study goes beyond direct effects at product- and service-level LCAs, revisiting an SD simulation study originally conducted in 2002 to model indirect environmental effects of ICT in 15 European countries for the period 2000-2020. In the current study, three scenarios of the 2002 study were validated in light of new empirical data from the period 2000–2012. A new scenario was developed to revisit the quantitative and qualitative results of the original study. The results showed, inter alia, that ICT has a stimulating influence on total passenger transport, for it makes it more cost- and time-efficient (rebound effects).

The modeling mechanism used to represent this rebound effect is further investigated in the fourth study, which discusses the feedback loops used to model two types of rebound effects in passenger transport (direct economic rebound and time rebound). Finally, the role of systems thinking and modeling in conceptualizing and communicating the dynamics of rebound effects is examined.

The aim of the fifth study was to explore the power of systems modeling and simulation to represent nonlinearities of the complex and dynamic systems examined elsewhere in this thesis. That study reviews previous studies that have compared the SD and AB approaches and models, summarizing their purpose, methodology, and results, based on certain criteria for choosing between SD and AB approaches. The transformation procedure used to develop an AB model for purposes of comparison with an SD model is also explored.

In conclusion, first-order or direct environmental effects of ICT production, use, and disposal can be assessed employing an LCA method. This method can also be used to assess second-order or enabling effects by comparing ICT applications with conventional alternatives. However, the assessment of enabling effects can benefit from systems modeling methods, which are able to formally describe the drivers of change, as well as the dynamics of complex social, technical, and environmental systems associated with ICT applications. Such systems methods can also be used to model third-order or rebound effects of efficiency improvements by ICT.

This chapter revisits a System Dynamics model developed in 2002 with the aim of exploring the future impacts of Information and Communication Technology (ICT) on environmental sustainability in the EU, which then consisted of 15 countries. The time horizon of the study was 20 years (2000–2020). We analyze the results in light of empirical data that is now available for 2000–2012. None of the three scenarios that were developed by experts to specify the external factors needed to run the model were realistic from today’s point of view. If the model is re-run with more realistic input data for the first half of the simulation period, however, the main results regarding the impact of ICT remain qualitatively the same; they seem to be relatively robust implications of the causal system structure, as it is represented in the model. Overall, the impacts of ICT for mitigating greenhouse gas emissions and other environmental burdens for 2020 tend to be slightly stronger if the simulation is based on the empirical data now available.

The induction of demand by increasing the efficiency of a production or consumption process is known as the rebound effect. Feedback loops in System Dynamics can be used to conceptualize the structure of this complex phenomenon and also for communicating model-based insights. In passenger transport, the rebound effect can be induced through increased cost efficiency (direct economic rebound) and/or increase in speed (time rebound). In this paper we review and compare two models on environmental effects of passenger transport—including a model on the role of information and communication technology. We highlight the feedback mechanisms used to deal with the rebound effect (price, efficiency, and time rebound).

This report serves as supplementary material to the book chapter “Modeling the Effects of ICT on Environmental Sustainability: Revisiting a System Dynamics Model Developed for the European Commission” (Achachlouei and Hilty 2015) published in the book “ICT Innovations for Sustainability” (Hilty and Aebischer 2015). The current report was referred to in the book chapter whenever the data to be presented exceeded the space provided for the book chapter.

Systems modeling and simulation methods such as System Dynamics (SD) and agent-based (AB) modeling have been used to foster a better understanding of the dynamics and complexity of natural, technical, and social systems. System Dynamics provides an aggregate-level perspective, highlighting thinking in feedback loops and employing differential equations to model the causal relations in a system, exploring the system's dynamics by numerically solving the equations. Agent-based modeling, in a bottom-up method, focuses on constituent units (agents) and their interactions to explore the emerging behavior at a system level by means of simulation. Comparing these modeling methods can help us understand their strengths and weaknesses in order to choose the right approach for a given modeling problem. It may also support the analysis of a given system to build multiple models using the different approaches and comparing them, in particular to treat fundamental uncertainties in systems modeling and simulation. In this paper, we review the existing studies comparing the SD and AB approaches and models, investigating the aims, methodology, and results of such comparative studies. We also highlight lessons learned for future model comparisons by examining how the corresponding SD and AB models are built for the purpose of comparison. A procedure for transforming System Dynamics models into agent-based models is presented and discussed using examples from the literature.

Processes leading to an increase of demand for a resource as a consequence of increasing the efficiency of using this resource in production or consumption are known as (direct) rebound effects. Rebound effects at micro and macro levels tend to offset the reduction in resource consumption enabled by progress in efficiency. Systems thinking and modeling instruments such as causal loop diagrams and System Dynamics can be used to conceptualize the structure of this complex phenomenon and also to communicate model-based insights. In passenger transport, the rebound effect can be invoked by increased cost efficiency (direct economic rebound) and/or increase in speed (time rebound). In this paper we review and compare two existing models on passenger transport—including a model on the role of information and communication technology—with regard to the feedback loops used to conceptualize rebound effects.

Information and communication technology (ICT), in competition with traditional applications, is providingnew ways to access media content. Similar to print media, ICT-based media has environmental benefits andburdens alike. The overall goal of the present study is to assess the potential environmental impacts”’from a lifecycle perspective”’of a print magazine with its electronic version read on tablets. Important goals are to identifywhich activities give rise to the main impacts, in both print and tablet editions, and to identify the key factorsinfluencing the overall environmental impacts, in both editions. Moreover, data gaps and uncertainties areaddressed.The methodology used in the study is life cycle assessment (LCA). The environmental impacts assessedinclude climate change, cumulative energy/exergy demand, metal depletion, photochemical oxidant formation,particulate matter formation, terrestrial acidification, freshwater/marine eutrophication and fossil depletion.The results indicate that it is hard to compare print and tablet editions of a magazine due to difficulties indefining the function, and that different functional units indicate different preferences in terms of environmentalimpacts. Also, differences between emerging (low number of readers and low reading time per copy) andmature (high number of readers and higher reading time per copy) tablet versions leads to various results in thecomparison between print and tablet versions.The studied tablet version in its emerging stage gives rise to higher potential environmental impacts per readerthan the print version; however with an assumed mature tablet version the impacts are generally lower perreader. This illustrates clearly the importance of the number of readers to spread the environmental impactsover.

The rapid development of information and communications technology (ICT) is providing new ways to access media content. Electronic media are sometimes more advantageous from an environmental perspective than paper-based media solutions, but ICT-based media can also bring environmental burdens. This study compared the potential environmental impacts in a life cycle perspective of a print edition of a magazine and that of its electronic edition read on a tablet device. Important objectives were to identify activities giving rise to the main environmental impacts for both the print and tablet editions, determine the key factors influencing these impacts, and address data gaps and uncertainties. A detailed assessment of the tablet edition is provided in a previous article (part 1), whereas this article compares it with the print edition. The methodology used was life cycle assessment and the environmental impacts assessed included climate change, cumulative energy/exergy demand, metal depletion, photochemical oxidant formation, particulate matter formation, terrestrial acidification, freshwater eutrophication, marine eutrophication, and fossil depletion. Use of different functional units to compare the print and tablet editions of the magazine resulted in different relative environmental impacts. In addition, emerging (low number of readers and low reading time per copy) and mature (higher number of readers and higher reading time per copy) tablet editions yielded varying results. The emerging tablet edition resulted in higher potential environmental impacts per reader than the print edition, but the mature tablet edition yielded lower impacts per reader in half the impact categories assessed. This illustrates the importance of spreading the environmental impacts over a large number of readers. The electricity mix used in product system processes did not greatly affect the results of tablet/print comparisons, but overall number of readers for the tablet edition, number of readers per copy for the print edition, file size, and degree of use of the tablet device proved crucial for the comparison results.

Shifts from print media to electronic media may be regarded as apossibility for promoting sustainability. However, the benefits ofelectronic media are not unquestioned. Previous studies on theenvironmental impacts of print and electronic media have shownthat there is no easy answer. Contributing to this field of research,the present study sought to assess the climate change impact ofthe tablet edition of a magazine using a life cycle perspective.Results showed that with few readers the emerging tablet versionhad a higher potential climate change impact per reader than themature tablet version, although the latter had a substantiallylonger reading time per copy. The contribution of contentproduction, electronic distribution, reading on tablet and wastetreatment of tablet to the impact was analysed. The sensitivityanalysis of electricity mix indicated that this was an importantfactor that clearly influenced the overall results.

Information and communication technology (ICT) is providing new ways to access media content. ICT has environmental benefits and burdens. The overall goal of the present study was to assess the environmental impacts of production and consumption of magazines read on tablets from a life cycle perspective. Important goals were to identify the activities giving rise to the main impacts and the key factors influencing the overall environmental impacts. Data gaps and uncertainties were also addressed. The results are compared against those for the print edition of the magazine in a separate article (part 2). The methodology used in the study was life cycle assessment. The environmental impacts assessed included climate change, cumulative energy/exergy demand, metal depletion, photochemical oxidant formation, particulate matter formation, terrestrial acidification, freshwater/marine eutrophication, fossil depletion, human toxicity, and ecotoxicity. The results indicate that content production can be the major contributor to environmental impacts if readers are few (as for the emerging version of the magazine studied). Assuming more readers (more mature version) or a larger file size for the tablet magazine, electronic storage and distribution may be the major contributor. Thus, in contrast to previous studies on electronic media, which reported a dominant impact of the use phase, this study found a higher impact for content production (emerging version) and electronic storage and distribution (mature version). However, with inefficient, low overall use of the tablet with a mature version of the tablet magazine, the greatest impact was shown to come from the reading activity (i.e., the use phase). In conclusion, the relative impacts of the tablet magazine would decrease considerably with high numbers of readers, their efficient use of the tablet (i.e., for many purposes over a long life of the device), and a smaller magazine file.

Purpose

Lithium-ion (Li-ion) battery packs recovered from end-of-life electric vehicles (EV) present potential technological, economic and environmental opportunities for improving energy systems and material efficiency. Battery packs can be reused in stationary applications as part of a “smart grid”, for example to provide energy storage systems (ESS) for load leveling, residential or commercial power. Previous work on EV battery reuse has demonstrated technical viability and shown energy efficiency benefits in energy storage systems modeled under commercial scenarios. The current analysis performs a life cycle assessment (LCA) study on a Li-ion battery pack used in an EV and then reused in a stationary ESS.

Methods

A complex functional unit is used to combine energy delivered by the battery pack from the mobility function and the stationary ESS. Various scenarios of cascaded “EV mobility plus reuse in stationary clean electric power scenarios” are contrasted with “conventional system mobility with internal combustion engine vehicles plus natural gas peaking power.” Eight years are assumed for first use; with 10 years for reuse in the stationary application. Operational scenarios and environmental data are based on real time-of-day and time-of-year power use. Additional data from LCA databases are utilized. Ontario, Canada, is used as the geographic baseline; analysis includes sensitivity to the electricity mix and battery degradation. Seven environmental categories are assessed using ReCiPe.

Results and discussion

Results indicate that the manufacturing phase of the Li-ion battery will still dominate environmental impacts across the extended life cycle of the pack (first use in vehicle plus reuse in stationary application). For most impact categories, the cascaded use system appears significantly beneficial compared to the conventional system. By consuming clean energy sources for both use and reuse, global and local environmental stress reductions can be supported. Greenhouse gas advantages of vehicle electrification can be doubled by extending the life of the EV batteries, and enabling better use of off-peak low-cost clean electricity or intermittent renewable capacity. However, questions remain concerning implications of long-duration use of raw material resources employed before potential recycling.

Conclusions

Li-ion battery packs present opportunities for powering both mobility and stationary applications in the necessary transition to cleaner energy. Battery state-of-health is a considerable determinant in the life cycle performance of a Li-ion battery pack. The use of a complex functional unit was demonstrated in studying a component system with multiple uses in a cascaded application.

In grids, delegation is a key facility that can be used to authenticate and authorize requests on behalf of disconnected users. In current grid systems,delegation is either performed dynamically, in an unrestricted manner, or by a secure but static method. Unfortunately, the former compromises security and the latter cannot satisfy the requirements of dynamic grid application execution. Therefore, development of a delegation framework that enables a restricted and flexible delegation mechanism becomes increasingly urgent as grids are adopted by new communities and grow in size. The main barriers in development of such a mechanism are the requirements for dynamic execution of grid applications, which make it difficult to anticipate required access rights for completing tasks in advance.

Another significant architectural requirement in grids is federated security and trust. A considerable barrier to achieving this is cross-organizational authentication and identification. Organizations participating in Virtual Organizations (VOs) may use different security infrastructures that implement different protocols for authentication and identification; thus, there exists a need to provide an architectural mechanism for lightweight, rapid and interoperable translation of security credentials from an original format to a format understandable by recipients.

This thesis contributes the development of a delegation framework that utilizes a mechanism for determining and acquiring only required rights and credentials for completing a task, when they are needed. This is what we call an on-demand delegation framework that realizes a bottom-up delegation model and provides a just-in-time acquisition of rights for restricted and dynamic delegation.

In this thesis, we further contribute the development of a credential mapping mechanism using off-the-shelf standards and technologies. This mechanism provides support for an on-the-fly exchange of different types of security credentials used by the security mechanisms of existing grids.

Delegation is a key facility in dynamic, distributed and collaborative environments like e rids and enables an effective use of a wide range of dynamic applications. Traditional delegation frameworks approach a top-down model of delegation for delegating rights from a superior to a subordinate in advance before a delegate starts off a delegated task. However, a top-down model of delegation cannot meet all the requirements of dynamic execution of distributed applications, as in such environments. required access rights for completing a task cannot easily be anticipated in advance. Delegating fewer rights than required for completing a task may cause the task execution to fail while delegating more rights than needed may threaten abuse by malicious parties. It is therefore reasonable and more robust to utilize a mechanism that allows determining and acquiring only required rights and credentials for completing a task, when they are needed. This is what we call an on-demand delegation framework, which realizes a bottom-up delegation model and provides a just-in-time acquisition of rights for a restricted and dynamic delegation. In this paper we elaborate the concept of bottom-up delegation and describe how an on-demand delegation framework can leverage workflows to meet the requirements of the least privileges principle. We also discuss the vital need for dynamic and adaptive scientific workflows to support an on-demand delegation framework. We present three different models or bottom-up delegation, which cover a wide range or usage scenarios in Grids and dynamic collaborative environments. Using a standard RBAC authorization model and a graph-based workflow model (DAG), we define and analyze a formal model of our proposed bottom-up delegation approach.

Performing delegation in large scale, dynamic and distributed environments with large numbers of shared resources is more challenging than inside local administrative domains. In dynamic environments like Grids, on one hand, delegating a restricted set of rights reduces exposure to attack but also limits the flexibility and dynamism of the application; on the other hand, delegating all rights provides maximum flexibility but increases exposure. This issue has not yet been adequately addressed by current Grid security mechanisms and is becoming a very challenging and crucial issue for future Grid development. Therefore, providing an effective delegation mechanism which meets the requirements of the least privilege principle is becoming an essential need. Furthermore, we are witnessing a phenomenal increase in the automation of organizational tasks and decision making, as well as the computerization of information related services, requiring automated delegation mechanisms. In order to meet these requirements we introduce an Active Delegation Framework which extends our previous work on on-demand delegation, making it context-aware. The framework provides a just-in-time, restricted and dynamic delegation mechanism for Grids. In this paper we describe the development of this framework and its implementation and integration with the Globus Toolkit.

Grids are intended to enable cross-organizationalinteractions which makes Grid security a challenging and nontrivialissue. In Grids, delegation is a key facility that canbe used to authenticate and authorize requests on behalf ofdisconnected users. In current Grid systems there is a tradeoffbetween flexibility and security in the context of delegation.Applications must choose between limited or full delegation: onone hand, delegating a restricted set of rights reduces exposure toattack but also limits the flexibility/dynamism of the application;on the other hand, delegating all rights provides maximumflexibility but increases exposure. In this paper, we propose anon-demand restricted delegation mechanism, aimed at addressingthe shortcomings of current delegation mechanisms by providingrestricted delegation in a flexible fashion as needed for Grid applications.This mechanism provides an ontology-based solutionfor tackling one the most challenging issues in security systems,which is the principle of least privileges. It utilizes a callbackmechanism, which allows on-demand provisioning of delegatedcredentials in addition to observing, screening, and auditingdelegated rights at runtime. This mechanism provides supportfor generating delegation credentials with a very limited andwell-defined range of capabilities or policies, where a delegatoris able to grant a delegatee a set of restricted and limited rights,implicitly or explicitly.

Manual management of public key credentials can be a significant and often off-putting obstacle to Grid use, particularly for casual users. We describe the Portal-based User Registration Service (PURSE), a set of tools for automating user registration, credential creation, and credential management tasks. PURSE provides the system developer with a set of customizable components, suitable for integration with portals, that can be used to address the full lifecycle of Grid credential management. We describe the PURSE design and its use in portals for two systems, the Earth System Grid data access system and the Swegrid computational Grid. In both cases, the user is entirely freed from the need to create or manage public key credentials, thus simplifying the Grid experience and reducing opportunities for error. We argue that this capturing of common use cases in a reusable ‘solution’ can be a model for how Grid ease-of-use can be addressed in other domains as well.

Grids are becoming economically viable and productive tools. They provide a way of utilizing a vast array of linked resources such as computing systems, databases and services online within Virtual Organizations (VO). However, today's Grid architectures are not capable of supporting dynamic, agile federation across multiple administrative domains and the main barrier, which hinders dynamic federation over short time scales is security. Federating security and trust is one of the most significant architectural issues in Grids. Existing relevant standards and specifications can be used to federate security services, but do not directly address the dynamic extension of business trust relationships into the digital domain. In this paper we describe an experiment which highlights those challenging architectural issues and forms the basis of an approach that combines a dynamic trust federation and a dynamic authorization mechanism for addressing dynamic security trust federation in Grids. The experiment made with the prototype described in this paper is used in the NextGRID(1) project to define the requirements of next generation Grid architectures adapted to business application needs.

Federating security and trust is one of the most significant architectural requirements in grids. In this regard, one challenging issue is the cross-organizational authentication and identification. Organizations participated in Virtual Organizations (VOs) may use different security infrastructures that implement different authentication and identification protocols. Thus, arises an architectural need to provide a mechanism for a lightweight, rapid and interoperable translation of security credentials from an original format to a format understandable by recipients. In this paper, we describe the development and the implementation of an architecture for credential mapping in grids using off-the-shelf technologies and standard specifications. Our open-source implementation of this architecture provides support for an on-the-fly exchange for different types of security credentials used by diverse grid security infrastructures'.

This paper presents work on using prosody in the output of spoken dialogue systems to resolve possible structural ambiguity of output utterances. An algorithm is proposed to discover ambiguous parses of an utterance and to add prosodic disambiguation events to deliver the intended structure. By conducting a pilot experiment, the automatic prosodic grouping applied to ambiguous sentences shows the ability to deliver the intended interpretation of the sentences.

This study aims at automatically classifying levels of acoustic prominence on a dataset of 200 Swedish sentences of read speech by one male native speaker. Each word in the sentences was categorized by four speech experts into one of three groups depending on the level of prominence perceived. Six acoustic features at a syllable level and seven features at a word level were used. Two machine learning algorithms, namely Support Vector Machines (SVM) and memory based Learning (MBL) were trained to classify the sentences into their respective classes. The MBL gave an average word level accuracy of 69.08% and the SVM gave an average accuracy of 65.17 % on the test set. These values were comparable with the average accuracy of the human annotators with respect to the average annotations. In this study, word duration was found to be the most important feature required for classifying prominence in Swedish read speech

This work presents the development of a real-time framework for the research of Multimodal Feedback of Robots/Talking Agents in the context of Human Robot Interaction (HRI) and Human Computer Interaction (HCI). For evaluating the framework, a Multimodal corpus is built (ENTERFACE_STEAD), and a study on the important multimodal features was done for building an active Robot/Agent listener of a storytelling experience with Humans. The experiments show that even when building the same reactive behavior models for Robot and Talking Agents, the interpretation and the realization of the behavior communicated is different due to the different communicative channels Robots/Agents offer be it physical but less-human-like in Robots, and virtual but more expressive and human-like in Talking agents.

This study reports experimental results on the effect of visual prominence, presented as gestures, on speech intelligibility. 30 acoustically vocoded sentences, permutated into different gestural conditions were presented audio-visually to 12 subjects. The analysis of correct word recognition shows a significant increase in intelligibility when focally-accented (prominent) words are supplemented with head-nods or with eye-brow raise gestures. The paper also examines coupling other acoustic phenomena to brow-raise gestures. As a result, the paper introduces new evidence on the ability of the non-verbal movements in the visual modality to support audio-visual speech perception.

Auditory prominence is defined as when an acoustic segment is made salient in its context. Prominence is one of the prosodic functions that has been shown to be strongly correlated with facial movements. In this work, we investigate the effects of facial prominence cues, in terms of gestures, when synthesized on animated talking heads. In the first study, a speech intelligibility experiment is conducted, speech quality is acoustically degraded and the fundamental frequency is removed from the signal, then the speech is presented to 12 subjects through a lip synchronized talking head carrying head-nods and eyebrows raise gestures, which are synchronized with the auditory prominence. The experiment shows that presenting prominence as facial gestures significantly increases speech intelligibility compared to when these gestures are randomly added to speech. We also present a follow-up study examining the perception of the behavior of the talking heads when gestures are added over pitch accents. Using eye-gaze tracking technology and questionnaires on 10 moderately hearing impaired subjects, the results of the gaze data show that users look at the face in a similar fashion to when they look at a natural face when gestures are coupled with pitch accents opposed to when the face carries no gestures. From the questionnaires, the results also show that these gestures significantly increase the naturalness and the understanding of the talking head.

In this paper, we present new results and comparisons of the real-time lips synchronized talking head SynFace on different Swedish databases and bandwidth. The work involves training SynFace on narrow-band telephone speech from the Swedish SpeechDat, and on the narrow-band and wide-band Speecon corpus. Auditory perceptual tests are getting established for SynFace as an audio visual hearing support for the hearing-impaired. Preliminary results show high recognition accuracy compared to other languages.

SynFace is a lip-synchronized talking agent which is optimized as a visual reading support for the hearing impaired. In this paper wepresent the large scale hearing impaired user studies carried out for three languages in the Hearing at Home project. The user tests focuson measuring the gain in Speech Reception Threshold in Noise and the effort scaling when using SynFace by hearing impaired people, where groups of hearing impaired subjects with different impairment levels from mild to severe and cochlear implants are tested. Preliminaryanalysis of the results does not show significant gain in SRT or in effort scaling. But looking at large cross-subject variability in both tests, it isclear that many subjects benefit from SynFace especially with speech with stereo babble.

In this paper we present recent results on the development of the SynFace lip synchronized talking head towards multilinguality, varying signal conditions and noise robustness in the Hearing at Home project. We then describe the large scale hearing impaired user studies carried out for three languages. The user tests focus on measuring the gain in Speech Reception Threshold in Noise when using SynFace, and on measuring the effort scaling when using SynFace by hearing impaired people. Preliminary analysis of the results does not show significant gain in SRT or in effort scaling. But looking at inter-subject variability, it is clear that many subjects benefit from SynFace especially with speech with stereo babble noise.

Lip synchronization is the process of generating natural lip movements from a speech signal. In this work we address the lip-sync problem using an automatic phone recognizer that generates a phone lattice carrying posterior probabilities. The acoustic feature vector contains the posterior probabilities of all the phones over a time window centered at the current time point. Hence this representation characterizes the phone recognition output including the confusion patterns caused by its limited accuracy. A 3D face model with varying texture is computed by analyzing a video recording of the speaker using a 3D morphable model. Training a neural network using 30 000 data vectors from an audiovisual recording in Dutch resulted in a very good simulation of the face on independent data sets of the same or of a different speaker.

The assessment of hemodynamics based on medical image data represents an attractive means in order to enhance diagnostic imaging capabilities, to evaluate clinical outcomes of therapies focusing on the patient's vascular system, as well as to guide minimally invasive interventional procedures in the catheter lab. We present a first evaluation along with comparisons of algorithmic approaches towards the quantitative determination of blood flow based on 2D angiography image data.

The qualitative structure of objects and their spatial distribution,to a large extent, define an indoor human environmentscene. This paper presents an approach forindoor scene similarity measurement based on the spatialcharacteristics and arrangement of the objects inthe scene. For this purpose, two main sets of spatialfeatures are computed, from single objects and objectpairs. A Gaussian Mixture Model is applied both onthe single object features and the object pair features, tolearn object class models and relationships of the objectpairs, respectively. Given an unknown scene, the objectclasses are predicted using the probabilistic frameworkon the learned object class models. From the predictedobject classes, object pair features are extracted. A fi-nal scene similarity score is obtained using the learnedprobabilistic models of object pair relationships. Ourmethod is tested on a real world 3D database of deskscenes, using a leave-one-out cross-validation framework.To evaluate the effect of varying conditions on thescene similarity score, we apply our method on mockscenes, generated by removing objects of different categoriesin the test scenes.

We propose a black-box approach to performance analysis of grid middleware and present the architecture of a non-invasive platform-independent evaluation tool that quantifies the effects of the overhead imposed by grid middleware on both the throughput of the system and on the turnaround times of grid applications. This approach is a step towards producing a middleware independent, comparable, reproducible and fair performance! analysis of grid middlewares. The result of such performance analysis can be used by system administrators to tune the system configuration and by developers to find the bottlenecks and problems in their design and implementation of the system. It can also be used to devise more optimized usage patterns. As a proof of concept, we describe the implementation details of the evaluation tool for UNICORE 5 and demonstrate the result of initial experiments.

This paper deals with a multimodal annotation scheme dedicated to the study of gestures in interpersonal communication, with particular regard to the role played by multimodal expressions for feedback, turn management and sequencing. The scheme has been developed under the framework of the MUMIN network and tested on the analysis of multimodal behaviour in short video clips in Swedish, Finnish and Danish. The preliminary results obtained in these studies show that the reliability of the categories defined in the scheme is acceptable, and that the scheme as a whole constitutes a versatile analysis tool for the study of multimodal communication behaviour.

We propose a method that allows for dexterousmanipulation of an object by exploiting contact with an externalsurface. The technique requires a compliant grasp, enablingthe motion of the object in the robot hand while allowingfor significant contact forces to be present on the externalsurface. We show that under this type of grasp it is possibleto estimate and control the pose of the object with respect tothe surface, leveraging the trade-off between force control andmanipulative dexterity. The method is independent of the objectgeometry, relying only on the assumptions of type of grasp andthe existence of a contact with a known surface. Furthermore,by adapting the estimated grasp compliance, the method canhandle unmodelled effects. The approach is demonstrated andevaluated with experiments on object pose regulation andpivoting against a rigid surface, where a mechanical springprovides the required compliance.

We propose a method that allows for dexterous manipulation of an object by exploiting contact with an external surface. The technique requires a compliant grasp, enabling the motion of the object in the robot hand while allowing for significant contact forces to be present on the external surface. We show that under this type of grasp it is possible to estimate and control the pose of the object with respect to the surface, leveraging the trade-off between force control and manipulative dexterity. The method is independent of the object geometry, relying only on the assumptions of type of grasp and the existence of a contact with a known surface. Furthermore, by adapting the estimated grasp compliance, the method can handle unmodelled effects. The approach is demonstrated and evaluated with experiments on object pose regulation and pivoting against a rigid surface, where a mechanical spring provides the required compliance.

Robotic assembly in unstructured environments is a challenging task, due to the added uncertainties. These can be mitigated through the employment of assembly systems, which offer a modular approach to the assembly problem via the conjunction of primitives. In this paper, we use a dual-arm manipulator in order to execute a folding assembly primitive. When executing a folding primitive, two parts are brought into rigid contact and posteriorly translated and rotated. A switched controller is employed in order to ensure that the relative motion of the parts follows the desired model, while regulating the contact forces. The control is complemented with an estimator based on a Kalman filter, which tracks the contact point between parts based on force and torque measurements. Experimental results are provided, and the effectiveness of the control and contact point estimation is shown.

Robots are operating for longer times and collecting much more data than just a few years ago. In this setting we are interested in exploring ways of modeling the environment, segmenting out areas of interest and keeping track of the segmentations over time, with the purpose of building 4D models (i.e. space and time) of the relevant parts of the environment.

Our approach relies on repeatedly observing the environment and creating local maps at specific locations. The first question we address is how to choose where to build these local maps. Traditionally, an operator defines a set of waypoints on a pre-built map of the environment which the robot visits autonomously. Instead, we propose a method to automatically extract semantically meaningful regions from a point cloud representation of the environment. The resulting segmentation is purely geometric, and in the context of mobile robots operating in human environments, the semantic label associated with each segment (i.e. kitchen, office) can be of interest for a variety of applications. We therefore also look at how to obtain per-pixel semantic labels given the geometric segmentation, by fusing probabilistic distributions over scene and object types in a Conditional Random Field.

For most robotic systems, the elements of interest in the environment are the ones which exhibit some dynamic properties (such as people, chairs, cups, etc.), and the ability to detect and segment such elements provides a very useful initial segmentation of the scene. We propose a method to iteratively build a static map from observations of the same scene acquired at different points in time. Dynamic elements are obtained by computing the difference between the static map and new observations. We address the problem of clustering together dynamic elements which correspond to the same physical object, observed at different points in time and in significantly different circumstances. To address some of the inherent limitations in the sensors used, we autonomously plan, navigate around and obtain additional views of the segmented dynamic elements. We look at methods of fusing the additional data and we show that both a combined point cloud model and a fused mesh representation can be used to more robustly recognize the dynamic object in future observations. In the case of the mesh representation, we also show how a Convolutional Neural Network can be trained for recognition by using mesh renderings.

Finally, we present a number of methods to analyse the data acquired by the mobile robot autonomously and over extended time periods. First, we look at how the dynamic segmentations can be used to derive a probabilistic prior which can be used in the mapping process to further improve and reinforce the segmentation accuracy. We also investigate how to leverage spatial-temporal constraints in order to cluster dynamic elements observed at different points in time and under different circumstances. We show that by making a few simple assumptions we can increase the clustering accuracy even when the object appearance varies significantly between observations. The result of the clustering is a spatial-temporal footprint of the dynamic object, defining an area where the object is likely to be observed spatially as well as a set of time stamps corresponding to when the object was previously observed. Using this data, predictive models can be created and used to infer future times when the object is more likely to be observed. In an object search scenario, this model can be used to decrease the search time when looking for specific objects.

We present a system for creating object models from RGB-D views acquired autonomously by a mobile robot. We create high-quality textured meshes of the objects by approximating the underlying geometry with a Poisson surface. Our system employs two optimization steps, first registering the views spatially based on image features, and second aligning the RGB images to maximize photometric consistency with respect to the reconstructed mesh. We show that the resulting models can be used robustly for recognition by training a Convolutional Neural Network (CNN) on images rendered from the reconstructed meshes. We perform experiments on data collected autonomously by a mobile robot both in controlled and uncontrolled scenarios. We compare quantitatively and qualitatively to previous work to validate our approach.

We present a system for creating object modelsfrom RGB-D views acquired autonomously by a mobile robot.We create high-quality textured meshes of the objects byapproximating the underlying geometry with a Poisson surface.Our system employs two optimization steps, first registering theviews spatially based on image features, and second aligningthe RGB images to maximize photometric consistency withrespect to the reconstructed mesh. We show that the resultingmodels can be used robustly for recognition by training aConvolutional Neural Network (CNN) on images rendered fromthe reconstructed meshes. We perform experiments on datacollected autonomously by a mobile robot both in controlledand uncontrolled scenarios. We compare quantitatively andqualitatively to previous work to validate our approach.