Multi-cue based crowd segmentation

With a rough foreground region, crowd segmentation is an efficient way for human detection in dense scenarios. However, most previous work on crowd segmentation considers shape and motion cues independently. In this paper, a method to use both shape and motion cues simultaneously for crowd segmentation in dense scenarios is introduced. Some results have been shown to illustrate the improvements when multi-cue is considered. The contribution of the paper is two-fold. First, coherent motion in each individual is combined with shape cues to help segment the foreground area into individuals. Secondly, the rigid body motion in human upper-parts is observed and also used for more accurate human detection.link_to_subscribed_fulltextThe 8th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2011) held in conjunction with the 1st International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2011), Noordwijkerhout, The Netherlands, 29-31 July 2011. In Proceedings of the 8th ICINCO, 2011, v. 2, p. 173-17

Effective software design and development for the new graph architecture HPC machines.

Software applications need to change and adapt as modern architectures evolve. Nowadays advancement in chip design translates to increased parallelism. Exploiting such parallelism is a major challenge in modern software engineering. Multicore processors are about to introduce a significant change in the way we design and use fundamental data structures. In this work we describe the design and programming principles of a software library of highly concurrent scalable and nonblocking data containers. In this project we have created algorithms and data structures for handling fundamental computations in massively multithreaded contexts, and we have incorporated these into a usable library with familiar look and feel. In this work we demonstrate the first design and implementation of a wait-free hash table. Our multiprocessor data structure design allows a large number of threads to concurrently insert, remove, and retrieve information. Non-blocking designs alleviate the problems traditionally associated with the use of mutual exclusion, such as bottlenecks and thread-safety. Lock-freedom provides the ability to share data without some of the drawbacks associated with locks, however, these designs remain susceptible to starvation. Furthermore, wait-freedom provides all of the benefits of lock-free synchronization with the added assurance that every thread makes progress in a finite number of steps. This implies deadlock-freedom, livelock-freedom, starvation-freedom, freedom from priority inversion, and thread-safety. The challenges of providing the desirable progress and correctness guarantees of wait-free objects makes their design and implementation difficult. There are few wait-free data structures described in the literature. Using only standard atomic operations provided by the hardware, our design is portable; therefore, it is applicable to a variety of data-intensive applications including the domains of embedded systems and supercomputers.Our experimental evaluation shows that our hash table design outperforms the most advanced locking solution, provided by Intel's TBB library, by 22%. When compared to more traditional locking designs we show a performance improvement by a factor of 7.92. When compared to alternative non-blocking designs, our hash table demonstrates solid performance gains in a large majority of cases, typically by a factor of 3.44

Order-picking workstations for automated warehouses

The FALCON (Flexible Automated Logistic CONcept) project aims at the development of a new generation of warehouses and distribution centers with a maximum degree of automation. As part of the FALCON project, this dissertation addresses the design and analysis of (automated) workstations in warehouses with an end-of-aisle order-picking system (OPS). Methods are proposed for architecting, quantifying performance, and controlling such a system. Four main topics are discussed in this dissertation. First, a modular architecture for an end-of-aisle OPS with remotely located workstations is presented. This architecture is structured into areas and operational layers. A hierarchical decentralized control structure is applied. A case of an industrial-scale distribution center is presented to demonstrate the applicability of the proposed architecture for performance analysis using the process algebra-based simulation language $\chi$ (Chi). Additionally, it is demonstrated how the architecture allows straightforward modification of the systems configurations, design parameters, and control heuristics. Second, a method to quantify the operational performance of order-picking workstations has been developed. The method is based on an aggregate modeling representation of the workstation using the EPT (Effective Process Time) concept. A workstation is considered in which a human picker is present to process one customer order at a time while products for multiple orders arrive simultaneously at the workstation. The EPT parameters are calculated from arrival and departure times of products using a sample path equation. Two model variants have been developed, namely for workstations with FCFS (First-Come-First-Serve) and for workstations with non-FCFS processing of products and orders. Both models have been validated using data from a real, operating workstation. The results show that the proposed aggregate modeling methodology gives good accuracy in predicting product and order flow time distributions. Third, the dissertation studies the design and control of an automated, remotely located order-picking workstation that is capable of processing multiple orders simultaneously. Products for multiple orders typically arrive out-of-sequence at the workstation as they are retrieved from dispersed locations in the storage area. The design problem concerns the structuring of product/order buffer lanes and the development of a mechanism that overcomes out-of-sequence arrivals of products. The control problem concerns the picking sequence at the workstation, as throughput deteriorates when a poor picking sequence is applied. An efficient control policy has been developed. Its performance is compared to a number of other picking policies including nearest-to-the-head, nearest neighbor, and dynamic programming. Subsequently, the resulting throughput and queue length distribution are evaluated under different settings. Insights for design considerations of such a system are summarized. Finally, the dissertation reflects on the findings from the proposed methods and uses them to come up with comprehensive design principles of end-of-aisle OPS with remotely located workstations. The various issues influencing the performance of such a system are highlighted. Moreover, the contribution of each proposed method with regards to these issues is delineated

Spatially explicit assessment of roundwood and logging residues availability and costs for the EU28

Competition for woody biomass between material and energy uses is expected to further increase in the future, due to the limited availability of forest resources and increasing demand of wood for material and bioenergy. Currently, methodological approaches for modeling wood production and delivery costs from forest to industrial gates are missing. This study combines forest engineering, geographically explicit information, environmental constraints and economics in a bottom-up approach to assess cost–supply curves. The estimates are based on a multitude of wood supply systems that were assigned according to geographically explicit forestry characteristics. For each harvesting and transportation system, efficiencies were modeled according to harvesting sites and main delivery hubs. The cost–supply curves for roundwood and logging residues as estimates for current time and for the future (2030) show that there are large regional differences in the potential to increase extraction in the EU28. In most EU Member States, the costs of logging residues extraction increase exponentially already for low levels of mobilization, while extraction of roundwood can be increased to a larger extent within reasonable costs (30–40 $/m3). The large differences between countries in their harvest potential highlight the importance of spatially explicit analyses

Combining Climate Change Mitigation Scenarios with Current Forest Owner Behavior: A Scenario Study from a Region in Southern Sweden

This study investigates the need for change of current forest management approaches in a southern Swedish region within the context of future climate change mitigation through empirically derived projections, rather than forest management according to silvicultural guidelines. Scenarios indicate that climate change mitigation will increase global wood demand. This might call for adjustments of well-established management approaches. This study investigates to what extent increasing wood demands in three climate change mitigation scenarios can be satisfied with current forest management approaches of different intensities in a southern Swedish region. Forest management practices in Kronoberg County were mapped through interviews, statistics, and desk research and were translated into five different management strategies with different intensities regulating management at the property level. The consequences of current practices, as well as their intensification, were analyzed with the Heureka Planwise forest planning system in combination with a specially developed forest owner decision simulator. Projections were done over a 100-year period under three climate change mitigation scenarios developed with the Global Biosphere Management Model (GLOBIUM). Current management practices could meet scenario demands during the first 20 years. This was followed by a shortage of wood during two periods in all scenarios unless rotations were reduced. In a longer timeframe, the wood demands were projected to be easily satisfied in the less ambitious climate change mitigation scenarios. In contrast, the demand in the ambitious mitigation scenario could not be met with current management practices, not even if all owners managed their production forests at the intensive extreme of current management approaches. The climate change mitigation scenarios provide very different trajectories with respect to future drivers of forest management. Our results indicate that with less ambitious mitigation efforts, the relatively intensive practices in the study region can be softened while ambitious mitigation might push for further intensification

Impact of modelling choices on setting the reference levels for the EU forest carbon sinks: how do different assumptions affect the country-specific forest reference levels?

Background In 2018, the European Union (EU) adopted Regulation 2018/841, which sets the accounting rules for the land use, land use change and forestry (LULUCF) sector for the period 2021–2030. This regulation is part of the EU’s commitments to comply with the Paris Agreement. According to the new regulation, emissions and removals for managed forest land are to be accounted against a projected forest reference level (FRL) that is estimated by each EU Member State based on the continuation of forest management practices of the reference period 2000–2009. The aim of this study is to assess how different modelling assumptions possible under the regulation may influence the FRL estimates. Applying the interlinked G4M and WoodCarbonMonitor modelling frameworks, we estimate potential FRLs for each individual EU Member State following a set of conceptual scenarios, each reflecting different modelling assumptions that are consistent with the regulation and the technical guidance document published by the European Commission. Results The simulations of the conceptual scenarios show that differences in the underlying modelling assumptions may have a large impact on the projected FRL. Depending on the assumptions taken, the projected annual carbon sink on managed forest land in the EU varies from −319 MtCO2 to −397 MtCO2 during the first compliance period (2021–2025) and from −296 MtCO2 to −376 MtCO2 during the second compliance period (i.e. 2026–2030). These estimates can be compared with the 2017 national GHG inventories which estimated that the forest carbon sink for managed forest land was −373 MtCO2 in 2015. On an aggregated EU level, the assumptions related to climate change and the allocation of forest management practices have the largest impacts on the FRL estimates. On the other hand, assumptions concerning the starting year of the projection, stratification of managed forest land, and timing of individual management activities are found to have relatively small impacts on the FRL estimates. Conclusions We provide a first assessment of the level of uncertainty associated with the different assumptions discussed in the technical guidance document and the LULUCF regulation, and the impact of these assumptions on the country-specific FRL. The results highlight the importance of transparent documentation by the EU Member States on how their FRL has been calculated, and on the underlying assumptions. Backgroun

Radio shadowing in vehicle-to-vehicle communication at urban intersections : a measurement and simulation-based evaluation

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Surrogate-Based Optimization for Marine Ecosystem Models

Marine ecosystem models are of great importance for understanding the oceanic uptake of carbon dioxide and for projections of the marine ecosystem’s responses to climate change. The applicability of a marine ecosystem model for prognostic simulations crucially depends on its ability to resemble the actually observed physical and biogeochemical processes. An assessment of the quality of a given model is typically based on its calibration against observed quantities. This calibration or optimization process is intrinsically linked to an adjustment of typically poorly known model parameters. Straightforward calibration attempts by direct adjustment of the model parameters using conventional optimization algorithms are often tedious or even beyond the capabilities of modern computer power as they normally require a large number of simulations. This typically results in prohibitively high computational cost, particularly if already a single model evaluation involves time-consuming computer simulations. The optimization of coupled hydrodynamical marine ecosystem models simulating biogeochemical processes in the ocean is here a representative example. Computing times of hours up to several days already for a single model evaluation are not uncommon. A computationally efficient optimization of expensive simulation models can be realized using for example surrogate-based optimization. Therein, the optimization of the expensive, so-called high-fidelity (or fine) model is carried out by means of a surrogate – a fine model’s fast but yet reasonably accurate representation. This work comprises an investigation and application of surrogate-based optimization methodologies employing physics-based low-fidelity (or coarse) models. Seeking a computationally efficient calibration of marine ecosystem models serves as the fundamental aim. As a case study, two illustrative marine ecosystem models are considered. Here, coarse models obtained by a coarser temporal resolution and by a truncated model spin-up are investigated. The accuracy of these computationally cheaper coarse models is typically not sufficient to directly exploit them in the optimization loop in lieu of the fine model. I investigate suitable correction techniques to ensure that the corrected coarse model (the surrogate) provides a reliable prediction of the fine model optimum. Firstly, I focus on Aggressive Space Mapping as one of the original Space Mapping approaches. It will be shown that this optimization method allows to achieve a reasonable reduction in the optimization costs, provided that the considered coarse and fine model are sufficiently “similar”. A multiplicative response correction approach, subsequently investigated, turned out to be very suitable for the considered marine ecosystem models. A reliable surrogate can be obtained. Exploiting the latter in a surrogate-based optimization algorithm, a computationally cheap but yet accurate solution is achieved. The optimization costs can be significantly reduced compared to what is achieved by the Aggressive Space Mapping algorithm. The proposed methodologies, particularly the multiplicative response correction approach, serve as initial parts of a set of tools for a computationally efficient calibration of marine ecosystem models. The investigation of further enhancements of the presented algorithms as well as other promising approaches in the framework of surrogate-based optimization will be highly valuable

Combining Climate Change Mitigation Scenarios with Current Forest Owner Behavior: A Scenario Study from a Region in Southern Sweden

This study investigates the need for change of current forest management approaches in a southern Swedish region within the context of future climate change mitigation through empirically derived projections, rather than forest management according to silvicultural guidelines. Scenarios indicate that climate change mitigation will increase global wood demand. This might call for adjustments of well-established management approaches. This study investigates to what extent increasing wood demands in three climate change mitigation scenarios can be satisfied with current forest management approaches of different intensities in a southern Swedish region. Forest management practices in Kronoberg County were mapped through interviews, statistics, and desk research and were translated into five different management strategies with different intensities regulating management at the property level. The consequences of current practices, as well as their intensification, were analyzed with the Heureka Planwise forest planning system in combination with a specially developed forest owner decision simulator. Projections were done over a 100-year period under three climate change mitigation scenarios developed with the Global Biosphere Management Model (GLOBIUM). Current management practices could meet scenario demands during the first 20 years. This was followed by a shortage of wood during two periods in all scenarios unless rotations were reduced. In a longer timeframe, the wood demands were projected to be easily satisfied in the less ambitious climate change mitigation scenarios. In contrast, the demand in the ambitious mitigation scenario could not be met with current management practices, not even if all owners managed their production forests at the intensive extreme of current management approaches. The climate change mitigation scenarios provide very different trajectories with respect to future drivers of forest management. Our results indicate that with less ambitious mitigation efforts, the relatively intensive practices in the study region can be softened while ambitious mitigation might push for further intensification