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In this paper, we review a musical-noise-generation analysis of nonlinear noise reduction techniques with using higher-order statistics (HOS). Recently, an objective metric based on HOS to analyze nonlinear artifacts, i.e., musical noise, caused by nonlinear noise reduction techniques has been proposed. Such metric enables us to perform objective comparison of any nonlinear methods from the perspective of the amount of musical noise generated. Furthermore, such metric enables us to control the musical noise generated by nonlinear noise reduction techniques. In the paper, first, the mathematical principle of the analysis for the amount of musical noise based on HOS is described, and analyses and comparison examples of typical nonlinear noise reduction techniques are demonstrated. Next, it is clarified that to find a fixed point in HOS leads to no-musical noise property in noise reduction. Finally, several expansions on the theory are discussed., APSIPA ASC 2012 : Asia-Pacific Signal and Information Processing Association 2012 Annual Summit and Conference, December 3-6, 2012, Hollywood, California, USA.

This paper proposes a novel method for estimating depth from a long image sequence captured by a moving camera. Our idea for estimating a depth map is very simple; only counting interest points in images is integrated with the framework of multi-baseline stereo. Even by a simple algorithm, depth can be determined without computing similarity measures such as SSD and NCC that have been used for traditional stereo matching. Our method realizes robust depth estimation against image distortions and occlusions that are caused by camera motion. Note that, in this paper, intrinsic and extrinsic parameters of video camera are assumed to be calibrated in advance., CRV 2005 : Second Canadian Conference on Computer and Robot Vision , May 9-11, 2005 , Victoria, Canada

For accident prevention at intersections, it is useful for drivers to grasp the position of vehicles in blind spots. This can be achieved without infrastructure if some vehicles passing near the intersection capture and share live video of the intersection through inter-vehicle communications. However, such video streaming requires a congestion control mechanism. In this paper, aiming to let a driver grasp the situation at an intersection, we propose a method to select vehicles that send a video in order to generate a live bird's-eye-view video of the intersection. In our method, each vehicle at an intersection exchanges information with others, such as the sub-areas of the intersection it captures, the quality of its video, and its position and speed. Based on the exchanged information, each vehicle autonomously judges whether it should send its video or not. Through simulation with a QualNet simulator, we confirm that our method achieves a good video arrival rate and video quality sufficient for practical use., IVCS 2010 : 2nd IEEE International Intelligent Vehicular Communications System Workshop , Jan 9-12, 2010 , Las Vegas , NV, USA

In this paper, we propose a method for detecting the positions of pedestrians by cooperation of multiple cars with directional antennas to support drivers for pedestrian safety. In the method, each pedestrian carries a device which periodically transmits a beacon with a unique ID, and each car passing near the pedestrian receives the beacon by a directional antenna and measures the distance and the angle of arrival. We assume the distribution of the measurement errors to be a normal distribution, and the system calculates the existence probabilities of each pedestrian at each point. By exchanging information of the probabilities between cars, the area with high existence probability is narrowed down. In this paper, we first describe the situations where detecting positions of pedestrians greatly contribute to pedestrian safety, and then we describe the probability model used in our method, the method for calculating existence probabilities from information from multiple cars, and the protocol for exchanging the probability information between cars. We evaluated our method on QualNet simulator, and confirmed that the positions can be detected accurately enough for practical uses., GLOBECOM2008 : IEEE Global Communications Conference , Nov 30-Dec 4, 2008 , New Orleans, LA, USA

In this paper, we propose a method for cars to autonomously and cooperatively collect traffic jam statistics to estimate arrival time to destination for each car using inter-vehicle communication. In the method, the target geographical region is divided into areas, and each car measures time to pass through each area. Traffic information is collected by exchanging information between cars using inter-vehicle communication. In order to improve accuracy of estimation, we introduce several mechanisms to avoid same data to be repeatedly counted. Since wireless bandwidth usable for exchanging statistics information is limited, the proposed method includes a mechanism to categorize data, and send important data prior to other data. In order to evaluate effectiveness of the proposed method, we implemented the method on a traffic simulator NETSTREAM developed by Toyota Central R&D Labs, conducted some experiments and confirmed that the method achieves practical performance in sharing traffic jam information using inter-vehicle communication., V2VCOM2006 : Vehicle-to-Vehicle Communications , Jul 17-21, 2006 , San Jose, CA, USA

Recent theoretical advances hold that platforms comprise a second strategic dimension next to size, called identity, which describes the platform's technological and market scope. Letting go of platform size as the main criterion for platform value opens the possibility for platforms to pursue differentiation strategies with a distinct market positioning. The concept of optimal distinctiveness (OD) implies that differentiation can be optimized so that it maximizes performance. In this paper, we draw on recent OD research in and outside of the field of platforms and elaborate on the role of platform size within the distinctiveness framework. We discuss platform size and identity in the context of OD and suggest propositions for future research. The paper contributes to the management of platforms and OD in platform markets by showing how a platform's distinctiveness strategy may depend on its size. We contribute to platform management across various platform sizes and to research on OD in platform markets., Economics of Technology and Innovation

One of the major challenges in wireless networks is to quantify and evaluate the user quality of experience (QoE). Hence, network operators are continuously working towards identifying the factors that most affect the user quality of experience for better network resource management. This paper proposes an evaluation method for video features with impact on user quality of experience. The goal is to extract and sort the features that highly affect the user experience and satisfaction while watching a video. The paper contributes first in determining the video parameters as well as the network features affecting QoE. Second, a survey is conducted to obtain subjective assessment on user satisfaction where users give their experience score and comments while watching videos with different feature values. We conduct experimental measurements and record videos with different frame rate, video resolution, transmission data rate, packet loss, delay and codec types. After collecting the QoE assessments, the supervised training data set is developed and imported into Rapid-Miner data mining tool. The feature evaluation is performed first using forward elimination feature selection algorithm, and second using decision tree classification to extract and sort the features that highly affect the subjective QoE. The results showed that the video resolution had the highest impact on user QoE. In addition, the transmission data rate was correlated to packet loss and delay and had higher impact than video frame rate and codec type.

This paper presents a security management framework driven by Zero-Touch Network and Service Management (ZSM) paradigm and embedded in the High-Level Architecture (HLA) developed in the INSPIRE-5Gplus project. This project work also included design and implementation of different smart 5G security methods and techniques that are essential for achieving security management in future networks. Moreover, the paper provides a summary of lessons learned and guidelines gathered during the practical validation activities for bringing closed loop and smart security management into Beyond 5G systems. Finally we discuss the key challenges and future work needed to enable integrating closed-loop security management in future networks.

This paper introduces realizations of a reconfigurable finite-impulse-response (FIR) filter for simultaneous equalization and lowpass filtering. The proposed structures employ properties of both a variable bandwidth (VBW) filter and a variable equalizer (VE) with an adjustable coefficient using the Farrow structure, therefore they consist of weighted combinations of fixed subfilters. Design procedures using minimax optimization technique are provided. The paper includes a design example and complexity comparisons between the proposed structures of the reconfigurable lowpass equalizer (RLPE) and a common approach of using a regular FIR equalization filter requiring online redesign.

Space stems are luminous and heated spots that appear ahead of the main discharge channel. They are very common in long negative discharges, while are rarely observed in long positive discharges. Recent numerical simulations show that isolated space stems in positive discharge may exist, but these are just too tiny to be observed. This paper attempts to demonstrate the above inference through an experimental study in the laboratory. A Schlieren system with a spatial resolution of 180 mu m/ pixel was established to visualize the isolated heating segment. A series of tests were carried out in a 1.35-m rod-plane air gap under both positive and negative lightning impulse, in which the applied voltage, discharge current, direct images and Schlieren images were synchronously recorded. The occurrence probability, length, position, and direction of the isolated heating segment are analyzed according to the experimental results. Moreover, the effects of the impulse voltage (i.e., polarity, rising time, amplitude) and the electrode size on the characteristics of the isolated heating segment is introduced. At last, we explore the issue of whether the observed isolated heating segment is the space stem. Observations in this paper may provide some references to better understanding the physical mechanism of space stem formation.

With the enforcement of governmental regulations and incentives, the share of electric vehicles (EVs) in the mobility sector is on the rise, impacting significantly the grid and its operation. This paper aims to investigate and find solutions to mitigate the impacts of EV charging on Dutch residential grids, namely the impacts of voltage magnitude regulation and distribution transformer loading. This paper proposes a decentralized coordinated charging strategy with local voltage control at its essence. The proposed charging strategy effectively allocates the charging power by prioritizing users based on their current State-of-Charge (SOC) and/or Time of Departure (ToD), or the current loading on the distribution transformer. These parameters are communicated to the charge controller through an Internet-of-Things (IoT) platform. The proposed charging strategy was simulated on a real Dutch residential grid that serves 86 household users, assuming every household has its own controllable EV charger. Based on the obtained results, the proposed charging strategy has eliminated all voltage magnitude violations, reduced the loading on the distribution transformer, while also achieving a SOC that is 2.5% less than that of the uncontrolled charging strategy., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

Testing of Computation-in-Memory (CIM) designs based on emerging non-volatile memory technologies, such as resistive RAM (RRAM), is fundamentally different from testing traditional memories. Such designs allow not only for data storage (i.e., memory configuration) but also for the execution of logical and arithmetic operations (i.e., computing configuration). Therefore, not only significant design changes are needed in the memory array and/or in the peripheral circuits, but also new fault models and test approaches are needed. Moreover, RRAM-based CIM makes use of non-linear non-volatile devices making the defect modeling with traditional linear resistor inappropriate for such device defects. Hence, even the way of doing defect modeling has to change. This paper discusses a structured test development approach for RRAM-based CIM and highlights the test challenges and how testing CIM dies is different from the traditional way of testing logic and memory. Methods for defect modeling, fault modeling, and test development will be discussed. The paper demonstrates that unique faults can occur in the CIM die while in the computation configuration and that these faults cannot be detected by just testing the CIM die in the memory configuration. Moreover, it shows that testing the CIM die in the computation configuration reduces the overall test time while improving the outgoing product quality. Finally, the paper presents an outlook on the future of structured CIM test development., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Quantum & Computer Engineering, Computer Engineering

As the complexity of nanosatellite missions have increased over time, the data generated on-board nanosatellites have increased multiple folds. As a result, there is a need to downlink large amounts of data. Multiple nanosatellite missions have started using spectral efficient modulation schemes recommended in DVB.S2 and DVB.S2X to make the best use of the available spectrum. One of the main challenges in adopting higher order modulation schemes is to power-efficiently upconvert and amplify the baseband signals. All the lost efficiency in converting the DC power to the RF output is dissipated as heat and the relatively small thermal mass of nanosatellites poses thermal management challenges. As a first step to addressing the challenge of improving the power efficiency of the communication module, optimization techniques to improve the Peak to Average Power Ratio (PAPR) of the modulation schemes (16/32-APSK) are discussed in this paper. The PAPR of 16-APSK reduces by ~2 dB by incorporating filtering techniques discussed in this paper. Further, a well-known efficiency and linearity enhancement technique; Out-phasing/LINC (Linear Amplification using Non-linear Components) is discussed. As a variant of the out-phasing architecture, a novel approach is proposed using two circularly polarized antenna to transmit the constant envelope signals in opposite polarizations and signal combining is performed at the receiver. Simulations results are used to demonstrate how higher efficiencies can be achieved using the proposed architecture., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronics

This paper presents the study of a 100kW electric vehicle (EV) fast charger based on a 12-pulse rectifier cascaded with two buck-type DC-DC converters. The proposed circuit operates with a triangular current shaping method which considerably improves the current harmonics performance of the system. The studied circuit is particularly suited for high power battery charging, being relatively simple to operate, requiring a low active semiconductor count (only two active switches), and because it employs circuit technologies well-established in the high power market. Above all, this EV fast charger meets the requirements of isolation, high efficiency, high output voltage and good power quality (low THD and unity power factor). This paper describes in detail the analytical modeling of the studied circuit, including the current harmonic input filter design which meets the grid standard requirement, and the loss modeling of the semiconductors and passive elements. The modeling and simulation results of the proposed 100 kW system are presented and analyzed., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., DC systems, Energy conversion & Storage

Fast internal detection and location in Shunt Ca-pacitor Banks (SCBs) can lead to the prevention of damages to other SCBs' elements and consequently avoid undesirable performance and effects in power system operation. This paper targets the performance of phasor-based algorithms of failure detection and fault location of SCBs. Being dependent on the fundamental phasor components which usually are calculated based on the Discrete Fourier Transform (DFT), the failure detection and fault location algorithms suffer from almost one-cycle delay. This paper provides sub-cycle phasor estimation based on the least-square technique. The proposed algorithm is evaluated for different configurations of SCBs considering different fuse protection designs. The proposed method provides a criterion for relay decision-making in the case of multiple faulty phases condition. The proposed method is designed to monitor and detect consecutive failures based on the existing data of commercial relays. Performance evaluations are conducted under different circumstances namely voltage unbalance conditions and multiple internal fault locations., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

STT-MRAM has long been a promising non-volatile memory solution for the embedded application space owing to its attractive characteristics such as non-volatility, low leakage, high endurance, and scalability. However, the operating requirements for high-performance computing (HPC) and low power (LP) applications involve different challenges. This paper addresses different aspects of STT-MRAM; it will cover state-of-the-art, some new results and future challenges related to technology, design and test. While STT-MRAM devices have shown encouraging performance metrics at device-level, a key challenge has been achieving backend-of-line (BEOL) CMOS compatibility, while retaining the benefits of low power operation. Scaling demands to improve data densities have placed additional challenges in terms of addressing the impact of process-induced damage on device performance at CD < 100 nm. In addition, the paper discusses the design of reliable read mechanism considering the variability effects. Moreover, the failure of traditional fault modeling and test approaches in model STT-MRAM unique defects for appropriate test solutions is demonstrated in this paper based on silicon data., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Computer Engineering, Quantum & Computer Engineering

Co-simulation is an important tool to capture the complexity of cyber-physical energy systems. The past decade lead us from command-line simulation orchestration to higher readiness-levels in terms of applicability. The configuration and time-domain initialisation of generic co-simulation setups, however, entail a lot of manual activities, especially when simulation components are tightly coupled. This paper provides a qualitative overview on what initialisation challenges crop up and how tools like mosaik can tackle these. This is illustrated with a multi-domain co-simulation example, in which the same time loop concept is applied to resolve cyclic dependencies between simulators during initialisation. The paper provides conclusions about the applicability of same time loops for initialisation purposes and will provide directions for further research on this topic., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

This full research paper develops a framework for using comparative case studies to triangulate with quantitative survey data in engineering ethics education research.Ethics has long been recognized as crucial to responsible engineering, but the increasingly globalized environments of contemporary engineering present challenges to effective engineering ethics training. An overarching goal of our team’s larger project is to examine the effects of culture and education on ethics training in undergraduate engineering students at universities in the United States, China, and the Netherlands to assess how this training impacts students’ ethical reasoning and moral dispositions, and how this differs cross-culturally. To gauge students’ moral dispositions and ethical reasoning skills and to measure any change in these, we administer the Moral Foundations Questionnaire and the Engineering & Science Issues Test to engineering students longitudinally over four years. Because the conditions related to engineering ethics education differ widely per participating institution, interpreting and analyzing survey quantitative data will require understanding the contextual conditions of education at each institution. In this paper we ask the question what and how can case study methods contribute to longitudinal and cross-cultural ethics educational research with large data sets? To answer it, we develop conceptual and methodological foundations for the design of comparative, multi-institutional case studies to contextualize, complement, and interpret quantitative and qualitative data on ethical reasoning and moral dispositions. We develop comparative case studies to supply missing contextual information for triangulation with quantitative and qualitative data and to provide a more complete picture of the engineering ethics educational contexts, strategies, and practices at each of the participating universities. In this project, case studies provide informational and contextual, Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Ethics & Philosophy of Technology

In ongoing and consecutive conversations with persons, a social robot has to determine which aspects to remember and how to address them in the conversation. In the health domain, important aspects concern the health-related goals, the experienced progress (expressed sentiment) and the ongoing motivation to pursue them. Despite the progress in speech technology and conversational agents, most social robots lack a memory for such experience sharing. This paper presents the design and evaluation of a conversational memory for personalized behavior change support conversations on healthy nutrition via memory-based motivational rephrasing. The main hypothesis is that referring to previous sessions improves motivation and goal attainment, particularly when references vary. In addition, the paper explores how far motivational rephrasing affects user's perception of the conversational agent (the virtual Furhat). An experiment with 79 participants was conducted via Zoom, consisting of three conversation sessions. The results showed a significant increase in participants' change in motivation when multiple references to previous sessions were provided., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Interactive Intelligence

Real-time optimal path planning for robotic manipulations in task space is a very fundamental and important problem. In this paper, the problem of generating robot trajectories in an obstacle-ridden environment is formulated under an optimal control framework using Hamilton-Jacobi-Bellman (HJB) equation. The novel contribution of this paper is that a closed form HJB control solution (a necessary and sufficient condition for global optimality of a control solution with respect to a cost function) has been achieved for generating real-time optimal trajectories for a robot manipulator. In contrast with the decoupled end-effector path planning and subsequent trajectory generation, the proposed scheme can exploit sensory input for real-time trajectory generation where the end-effector path as well as the joint trajectory is recomputed online while satisfying the real-time constraints. The stability and the performance of the proposed control framework is shown theoretically via Lyapunov approach and also verified experimentally using a 6 degrees of freedom (DOF) Universal Robot (UR) 10 robot manipulator. It is shown that a significant saving in cost metrics can be obtained over similar trajectory generation approaches from the state-of-the-art with obstacle-ridden environment and also has better performance in high speed tracking applications. Warehouse applications of the proposed scheme in case of static and dynamic targets with respect to the robot manipulator is also included., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Learning & Autonomous Control

In the last decades, there has been a steady adoption of digital online platforms as learning environments applied to all levels of education. This increasing adoption forces a transition in educational resources which has further been accelerated by the recent pandemic, leading to an almost complete online-only learning environment in some cases. The aim of this paper is to outline the methodology involved in setting up a framework for mapping course-specific data based on student activity to standard learning indicators, which will serve as an input to performance prediction algorithms. The process involves systematically surveying, capturing, and categorising the vast range of data available in digital learning platforms. The data are collected from two sample courses and distilled into five dimensions represented by the generic learning indicators: prior knowledge, preparation, participation, interaction, and performance. The data is weighted based on course development and teaching member’s perspectives to account for course-wise variations. The framework established will allow portability of prediction algorithms between courses and provide a means for meaningful and directed learner formative feedback. Two courses, both bachelor-level and worth 5 European Credits (ECs), that use several online learning platforms in their teaching tools have been chosen in this study to explore the nature and range of student interaction data available, accessible, and usable in a course. The first course is Electromagnetics II at Eindhoven University of Technology, and the second course is Electronics at Delft University of Technology. Both Universities are located in the Netherlands. This work is in the scope of a broader study to use such learning indicators with predictive algorithms to provide a prognosis on individual student performance. The findings in this paper will enable the realization of student performance prediction at a very early stage in the course., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronics

Computation-In-Memory (CIM) using memristor devices provides an energy-efficient hardware implementation of arithmetic and logic operations for numerous applications, such as neuromorphic computing and database query. However, memristor-based CIM suffers from various non-idealities such as conductance drift, read disturb, wire parasitics, endurance and device degradation. These negatively impact the computation accuracy of CIM. It is therefore essential to deal with these non-idealities and fabrication imperfections in order to harness the full potential of CIM. This paper discusses the non-ideality challenges and provides potential solutions. Furthermore, the paper outlines the potential future directions for CIM architectures., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Computer Engineering, Quantum & Computer Engineering

The concept of memory disaggregation has recently been gaining traction in research. With memory disaggregation, data center compute nodes can directly access memory on adjacent nodes and are therefore able to overcome local memory restrictions, introducing a new data management paradigm for distributed computing. This paper proposes and demonstrates a memory disaggregated in-memory object store framework for big data applications by leveraging the newly introduced Thymes-isFlow memory disaggregation system. The framework extends the functionality of the pre-existing Apache Arrow Plasma object store framework to distributed systems by enabling clients to easily and efficiently produce and consume data objects across multiple compute nodes. This allows big data applications to increasingly leverage parallel processing at reduced development costs. In addition, the paper includes latency and throughput measurements that indicate only a modest performance penalty is incurred for remote disaggregated memory access as opposed to local (~6.5 vs ~5.75 GiB/s). The results can be used to guide the design of future systems that leverage memory disaggregation as well as the newly presented framework. This work is open-source and publicly accessible at https://doi.org/10.5281/zenodo.6368998., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Computer Engineering

In this paper we study the multi-robot task assignment problem with tasks that appear online and need to be serviced within a fixed time window in an uncertain environment. For example, when deployed in dynamic, human-centered environments, the team of robots may not have perfect information about the environment. Parts of the environment may temporarily become blocked and blockages may only be observed on location. While numerous variants of the Canadian Traveler Problem describe the path planning aspect of this problem, few work has been done on multi-robot task allocation (MRTA) under this type of uncertainty. In this paper, we introduce and theoretically analyze the problem of MRTA with recoverable online blockages. Based on a stochastic blockage model, we compute offline tours using the expected travel costs for the online routing problem. The cost of the offline tours is used in a greedy task assignment algorithm. In simulation experiments we highlight the performance benefits of the proposed method under various settings., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Learning & Autonomous Control

The dispatch schedule of the electrical power plant units is the result of the solution to the unit commitment optimisation problem, and it minimises the cost of production considering pre-defined technical limits. The security-constrained unit commitment problem has been defined as including the network constraints in the previously mentioned optimisation problem to obtain a feasible power system solution. The traditional security-constrained unit commitment methods are based on the DC-power flow model, where the network losses and voltage magnitudes are neglected in the problem formulation. This paper proposed a bi-stage security-constrained unit commitment with an economic dispatch (SCUCED) optimisation problem. A merit-order-based zonal day-ahead market problem is solved in the first stage to define a preliminary generation commitment. In the second stage, the SCUCED is solved based on the AC-power flow model and sensitivity factors to embed the full network representation in the optimisation problem. In this paper, the proposed method is illustrated by an application to a modified version of the IEEE 39-bus test system., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

The free energy principle from neuroscience provides a brain-inspired perception scheme through a data-driven model learning algorithm called Dynamic Expectation Maximization (DEM). This paper aims at introducing an exper-imental design to provide the first experimental confirmation of the usefulness of DEM as a state and input estimator for real robots. Through a series of quadcopter flight experiments under unmodelled wind dynamics, we prove that DEM can leverage the information from colored noise for accurate state and input estimation through the use of generalized coordinates. We demonstrate the superior performance of DEM for state es-timation under colored noise with respect to other benchmarks like State Augmentation, SMIKF and Kalman Filtering through its minimal estimation error. We demonstrate the similarities in the performance of DEM and Unknown Input Observer (UIO) for input estimation. The paper concludes by showing the influence of prior beliefs in shaping the accuracy-complexity trade-off during DEM's estimation., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Robot Dynamics, Learning & Autonomous Control

In this paper, the controllability problem of the reaction-diffusion (RD) model, or Turing model is studied. Turing model provides a valuable framework for self-organized system and has been widely used to explain to pattern formation in the real life. With the rapidly development of the biology technology, biologists are trying to control the pattern formation artificially and has achieved some progress. However, the influence that exerted on the pattern formation by the external factors, such as light and temperature, remains to be solved. In this work, The RD model is obtained following the assumptions in Turing's original paper and spatially discretized into square grids. The nodes in the outermost layer are considered as candidates for control. Controllability of the RD system with all such nodes as control is first shown. Then controllability of the RD system with minimal number of control nodes is studied. Our results show that nearly 87.5% control nodes can be saved while the system is still controllable. Numerical simulations are provided to demonstrate the effects of controlling the reaction and diffusion of the morphogens., QC 20230425

Unmanned Aerial Vehicles (UAVs) communications attracted significant research interest in recent years as a promising tool for future wireless communication systems (beyond fifth-generation (B5G)/sixth-generation (6G)) due to their numerous capabilities and broad applicability. In this paper we consider a UAV-enabled wireless communication system consisting of two ground base stations. Owing to distance, direct communication is not feasible for the ground stations. For this reason a UAV is used to travel periodically between the ground stations in order to enable communication. This communication model is widely used in single UAV architectures enabling throughput maximization and increased network security (especially in military applications). Since the performance of this communication system depends on several factors, in this paper we examine the Age of Information (AoI) performance of the system under different parameters, such as the number of packets exchanged between the ground base stations, the distance between the ground stations, the frequency that each ground station receives data packets and the SNR level since transmissions take place via an error-prone channel. Furthermore, we derive an analytical expression for the AoI considering the aforementioned parameters, and finally we provide simulation results that illustrate the impact of the network operating parameters on the age performance, considering the trade-off between the amount of data transferred through the network and the freshness of data exchanged between the terrestrial base stations., Funding Agencies|Hellenic Foundation for Research and Innovation (HFRI) [1411]

In this paper, we introduce the notion of Cooperative Perception Error Models (coPEMs) towards achieving an effective and efficient integration of V2X solutions within a virtual test environment. We focus our analysis on the occlusion problem in the (onboard) perception of Autonomous Vehicles (AV), which can manifest as misdetection errors on the occluded objects. Cooperative perception (CP) solutions based on Vehicle-to-Everything (V2X) communications aim to avoid such issues by cooperatively leveraging additional points of view for the world around the AV. This approach usually requires many sensors, mainly cameras and LiDARs, to be deployed simultaneously in the environment either as part of the road infrastructure or on other traffic vehicles. However, implementing a large number of sensor models in a virtual simulation pipeline is often prohibitively computationally expensive. Therefore, in this paper, we rely on extending Perception Error Models (PEMs) to efficiently implement such cooperative perception solutions along with the errors and uncertainties associated with them. We demonstrate the approach by comparing the safety achievable by an AV challenged with a traffic scenario where occlusion is the primary cause of a potential collision., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

Future carbon-neutral power systems impose many challenges; one of them is an advanced simulation platform that allows replicating the complex systems' actual dynamic performance. DIgEnSys-Lab is working toward proposing solutions to the most critical challenges to carbon-neutral energy systems. This paper shows preliminary results of implementing a cyber-physical testbed co-simulation real-time dedicated to analysing system frequency response. The testbed is a cyber-physical system where the physical layer is represented by two real-time simulators in a closed loop: Typhoon HIL 604 and Opal-RT OP4510. The cybernetic layer is used to model a test system and to control the real-time simulation. This paper shows the results of the system frequency response of a modified version of the P.M Anderson 9-bus system using phasor measurement units. Simulation results show the appropriate performance of the proposed testbed., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

As power systems evolve from synchronous to inverter-based generation, voltage stability plays an increasingly important role. Voltage perturbations become faster and highly variable, and as such attract the research interest in the field of short-term instability monitoring and evaluation. The digitalization of the power systems provides a higher degree of observability by making use of synchrophasor measurements. The next step of utilizing such measurements by tailoring and applying innovative analytical and data-driven solutions is, however, still at the early development stage. In this paper, a novel approach that utilizes rapid post-fault voltage deviations for short-term instability quantification is investigated. The findings indicate that the approach is intuitive and effective. Finally, the paper discusses future research directions, enabled by the presented methodology, that deal with grid resilience challenges. Particularly, those related to post-disturbance system strength evaluation, as well as the real-time short-term instability evaluation and prediction, are addressed., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

This research paper presents a method that uses measurements of voltages angles, as provided by phasor measurement units (PMU), to accurately detect the sudden disconnection of a generation unit from a power grid. Results in this research paper have demonstrated, in a practical fashion, that a multi-layer perceptron (MLP) neural network (NN) can be appropriately trained to detect and identify the sudden disconnection of a generation unit in a multi-synchronous generation unit power system. Synthetic time-series bus voltage angles considering low inertia scenarios in the IEEE 39 bus system were used to train the MLP NN. The training process is speeded up by using four GPUs hardware. The simulations results have confirmed the successful detection and identification of the generator outage., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

Power electronic converter (PEC) is a key element for the successful integration of novel technologies, PEC working as inverter at novel generation technologies are the decisive components to zero-net carbon emissions in the electricity systems. The colossal penetration of IBG tends to produce several issues in the power networks. There is a tendency to agree that the voltage source converters (VSCs) empowered with the so-called grid forming (GFR) control may provide a long-term solution for the inverter-based generation-dominated power systems. This scientific paper presents an investigation (based on numerical simulations) of the effect of the virtual impedance control mode of one grid forming control technique in the power swing of power systems. Numerical time-domain simulations on test systems are used to assess the effect of the virtual impedance (VI) control mode of the synchronverter (SynC) during a power swing. In both cases, the simulation-based investigation has shown evidence of using high and low virtual impedance in both cases, considering constant impedance and proportional over-current limitation. However, this paper concludes that further assessments are required., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

The news articles we read online can reveal a lot about us. Privacy aware groups have therefore long pushed for the use of HTTPS (encrypted end-to-end communication). In this paper, we present the design and evaluation of a lightweight framework that can (1) successfully identify individual news articles even when the articles are delivered over encrypted connections, and (2) separate between articles associated with different news websites even when the websites are delivered over the same infrastructure. Our results demonstrate that naive use of HTTPS is not enough to prevent attackers monitoring a user's connections from identifying articles that the user reads on the most popular news website. We also provide insights into what makes some websites more/less resilient to our attack, and we use Twitter data to evaluate the effectiveness of an example attack that in addition incorporates the popularity of individual news articles. We are the first to demonstrate and evaluate the practical effectiveness of this type of attack when applied on modern news websites, and our multi-website-based evaluation provides valuable insights into how websites can best protect themselves against this type of attacks. These insights are important for websites that want to help protect the privacy of their users., This paper won the best paper award at the conference.Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

One of the challenges in WiMAX networks is to increase resource and power efficiency by optimizing the downlink (DL) burst construction. This paper proposes an energy-efficient scheme that maximizes the use of resources at the base station (BS) while reducing the energy wasted caused by sending padding bits instead of useful data. This paper presents the derivation of the general optimization problem that was formulated as a nonlinear integer programming model. A simple case formulation is used to illustrate the general application. The results show an improvement in data packing that maximizes the utilization of frames, and minimizes energy wastage.

Minimizing energy consumption is an urgent and challenging problem. As in any communication system, high energy efficiency in WiMAX systems should be maintained by increasing resource efficiency. Thus, WiMAX resources should be properly utilized by optimizing the construction of downlink (DL) bursts. This paper proposes an energy-efficient scheme that maximizes the use of resources at the base station (BS) by reducing the energy wasted caused by sending padding bits instead of useful data. The problem was formulated as nonlinear integer programming model. Due to the complexity of the problem, this paper presents first the formulation of the base model for optimal DL bursts construction problem assuming the packet is represented by one burst. Then, the formulation is expanded to allow the representation of packets by several bursts. The results show an improvement in data packing that maximizes the utilization of frames, and minimizes energy wastage.

By developing sensor network technologies, researches on data stream processing and stream mining have received much attention. Stream data prediction which predicts future data pattern by analyzing tendency of past data stream is one of streammining techniques. In a sensor network deployed in the real-world such as a city, a building and a room, data stream from a certain sensor node may relate to that from other ones. It is expected to improve the accuracy on sensor data prediction by considering correlations of these sensor data streams. In this paper, we propose a method for sensor data prediction based on correlations of multiple sensor data streams. This method extracts the feature quantities from partial sequences of each data stream and classifies these sequences into multiple groups by a clustering algorithm. The classified group is a cluster that expresses a pattern from the stream. Our method uses correlations among these clusters from different kinds of data streams and correlations between the past sequences on a stream in order to predict future data pattern. This paper describes an overview of our method for sensor data prediction and reports the results of the preliminary experiment., IInternational Workshop on Ubiquitous Service Platforms (IWUSP 2010)

Feedback is ubiquitous in both biological and engineered control systems. In biology, in addition to typical feedback between plant and controller, we observe complex feedback pathways within control systems, which we call internal feedback pathways (IFPs). These IFPs are most familiar in neural systems, our primary case study, but they appear everywhere from bacterial signal transduction to the human immune system. In this paper, we describe these very different examples and introduce the concepts necessary to explain their complex IFPs - particularly the severe speed-accuracy tradeoffs that constrain hardware in biology. We also sketch some minimal theory for extremely simplified toy models that highlight the importance of diversity-enabled sweet spots (DESS) in mitigating the impact of hardware tradeoffs. Standard modern and robust control theory can offer some insights into previously cryptic IFPs in more realistic models, and the new System Level Synthesis theory expands on these insights substantially, as explored in detail in companion papers., Part of proceedings: ISBN 978-1-6654-5196-3, QC 20221116

Almost the half of mechanical energy of a human gait cycle is generated by a hip joint. Therefore, this paper discusses a rehabilitation hip exoskeleton, starting with the modeling, simulation and ending with controlling its hip joints. A MATLAB based simulation environment with the use of Simscape Multibody toolbox was utilized to design and control the robotic hip exoskeleton. More details of adding a series elastic actuators (SEA) to the hip joints with the mathematical model are presented. However, the linearised mathematical model of the entire exoskeleton was found in simulation software which establish the basic need of controlling hip joints. The trajectory tracking is commonly used of controlling rehabilitation exoskeleton and to ensure a safe and reliable motion tracking methods, two desired torque signals were tested and analysed with the optimal linear quadratic regulator (LQR). The experiments with two torque signals–representing the sit-to-stand (STS) and the walking activity, demonstrated good performance of the motion gait tracking based on torque signals of a healthy person, which is carried out in the simulation environment. Furthermore, some studies in a human robot interaction are also mentioned in this paper.

Motion sickness is known to be an important and common factor affecting passengers' ride experience. With the popularization of intelligent vehicles, the development of multi-modal interaction methods will provide a chance to solve this problem. Therefore, the detection and mitigation of motion sickness will be an important topic for the future development of intelligent vehicles. However, detecting motion sickness using physiological and subjective data obtained in an on-road driving scenario has rarely been studied in related research. This paper proposed a solution framework for the physiological-signal-based motion sickness detection in on-road driving scenarios. Then, according to the framework, an on-road driving experiment is conducted to gather real-time physiological data using wearable devices. 12 participants took part in these experiments and about 120 min of motion sickness data were generated for analysis. The feature extraction was performed to analyze and extract the important physiological features related to motion sickness in real-world scenarios. Then the features were split into several combination groups and the representative machine learning models were trained to compare the results when different combinations were input. These detection models provide reasonable and effective detection when using the limited kind of physiological data. This method proposed in this paper will benefit the application of the motion sickness detection model in real vehicles. Meanwhile, since the visual input signals are not included, the solution is privacy-protected. In the future, with this solution, vehicles will also be able to detect motion sickness levels in real-time through low-cost daily wearable devices, such as smartwatches and glasses. © 2022 IEEE.

The conventional labor-intensive chemical inventory management methods face great challenges due to the rapid increase and diverse demands of front-line researchers, lab managers, principal investigators, and authority-level central departments. This paper addresses the practical issues of chemical management and provides a new interdisciplinary and user-friendly innovative chemical inventory management system. Empowered by RFID, multi-sensing, and blockchain technologies, the digitalization of the chemicals, sensitive and dangerous substances are constructed. According to the field tests via the deployed prototype and evaluation elaborated in this paper, stakeholders can drastically reduce the amount of low-value, miscellaneous lab work, while improving the efficiencies of research activities, administration, management, and safety control in multiple specialized domains.

Brain-Machine Interface (BMI) translates paralyzed people's neural activity into control commands of the prosthesis so that their lost motor functions could be restored. The neural activities represent brain states that change continuously over time which brings the challenge to the online decoder. Reinforcement Learning (RL) has the advantage to construct the dynamic neural-kinematic mapping during the interaction. However, existing RL decoders output discrete actions as a classification problem and cannot provide continuous estimation. Previous work has combined Kalman Filter (KF) with RL for BMI, which achieves a continuous motor state estimation. However, this method adopts a neural network structure, which might get stuck in local optimum and cannot provide an efficient online update for the neural-kinematic mapping. In this paper, we propose a Cluster Kernel Reinforcement Learning-based Kalman Filter (CKRL-based KF) to avoid the local optimum problem for online neural-kinematic updating. The neural patterns are projected into Reproducing Kernel Hilbert Space (RKHS), which builds a universal approximation to guarantee the global optimum. We compare our proposed algorithm with the existing method on rat data collected during a brain control three-lever discrimination task. Our preliminary results show that the proposed method has a higher trial accuracy with lower variance across data segments, which shows its potential to improve the performance for online BMI control. Clinical Relevance— This paper provides a more stable decoding method for adaptive and continuous neural decoding. It is promising for clinical applications in BMI.

This paper presents an integrated data model based on IFC and SensorML to facilitate the post-COVID facilities management to ensure indoor thermal comfort and human health. This paper identifies the information with the reference to different industry guidelines, including WELL building Standard and Singapore BCA post-COVID regulations, and extracts necessary information for sensor description and identification. New parameters in the BIM environment are recommended in this paper to support model-based data exchange in the future. The information required is clarified with a process map depicting the information flow, and IFC MVD to provide a structured overview of the sensor requirement. Data mapping between IFC and SensorML is performed, the result indicates that missing entities and attributes can be proposed to enrich the sensor description in the IFC schema. The integration of SensorML and IFC provides better data interoperability between both schemas, improving information standardization and openness of data exchange in sensor description. © 2021 IEEE.

The paper was awarded the best paper award, Data-driven value creation is a key topic in industrial services. However, designing such services in an optimal way represents a multidimensional and complex task. In this paper, we present a design methodology based on a simultaneous maxi-mization of value creation for both the provider and the customer, allowing the identification of optimal service configurations. We apply this methodology to a use case of a manufacturer delivering services for its machines in the context of a pay-per-use business model. The approach is based on modeling the value creation separately for both provider and customer, as a function of data-driven services which may be offered in different phases of the lifecycle. The model allows finding Pareto-optimal service configurations which provide value creation optimized simultaneously for both the provider and the customer. These optimal configurations are not easy to find with simpler methods because of non-linear effects in value creation along the lifecycle.

The design and development of smart products and services with data science enabled solutions forms a core topic of the current trend of digitalisation in industry. Enabling skilled staff, employees, and students to use data science in their daily work routine of designing such products and services is a key concern of higher education institutions, including universities, company workshop providers and in further education. The scope and usage scenario of this paper is to assess software modules (‘tools’) for integrated data and analytics as service (DAaaS). The tools are usually driven by machine learning, may be deployed in cloud infrastructures, and are specifically targeted at particular needs of the industrial manufacturing, production, or supply chain sector. The paper describes existing theories and previous work, namely methods used in didactics, work done for visually designing and using machine learning algorithms (no-code / low-code tools), as well as combinations of these two topics. For tools available on the market, an extended assessment of their suitability for a set of learning scenarios and personas is discussed.

Ensuring fairness of prediction-based decision making is based on statistical group fairness criteria. Which one of these criteria is the morally most appropriate one depends on the context, and its choice requires an ethical analysis. In this paper, we present a step-by-step procedure integrating three elements: (a) a framework for the moral assessment of what fairness means in a given context, based on the recently proposed general principle of “Fair equality of chances” (FEC) (b) a mapping of the assessment's results to established statistical group fairness criteria, and (c) a method for integrating the thus-defined fairness into optimal decision making. As a second contribution, we show new applications of the FEC principle and show that, with this extension, the FEC framework covers all types of group fairness criteria: independence, separation, and sufficiency. Third, we introduce an extended version of the FEC principle, which additionally allows accounting for morally irrelevant elements of the fairness assessment and links to well-known relaxations of the fairness criteria. This paper presents a framework to develop fair decision systems in a conceptually sound way, combining the moral and the computational elements of fair prediction-based decision-making in an integrated approach. Data and code to reproduce our results are available at https://github.com/joebaumann/fair-prediction-based-decision-making.

The design and development of smart products and services with data science enabled solutions forms a core topic of the current trend of digitalisation in industry. Enabling skilled staff, employees, and students to use data science in their daily work routine of designing such products and services is a key concern of higher education institutions, including universities, company workshop providers and in further education. The scope and usage scenario of this paper is to assess software modules (‘tools’) for integrated data and analytics as service (DAaaS). The tools are usually driven by machine learning, may be deployed in cloud infrastructures, and are specifically targeted at particular needs of the industrial manufacturing, production, or supply chain sector. The paper describes existing theories and previous work, namely methods used in didactics, work done for visually designing and using machine learning algorithms (no-code / low-code tools), as well as combinations of these two topics. For tools available on the market, an extended assessment of their suitability for a set of learning scenarios and personas is discussed.

A typical approach to harvesting the excess braking energy of a railway car has been to use a storage system. However, research momentum has been growing in the direction of integrating smart loads like EV chargers into traction networks, and this can offer a more efficient and economical solution to the harvesting of braking energy. This paper examines the case study of a segment of the Amsterdam metro grid with two 350kW integrated DC opportunity chargers for charging electric buses from the traction grid. Of the charging episodes investigated, none of them broke the minimum line voltage requirements of the grid. They managed to greatly offset any additional line losses that they had caused by a successful recuperation of up to 1212kWh per day, depending on the charging duration. In all four schemes, about 22.8% of the picked-up charging energy of the buses per day came from harvesting otherwise-wasted metro braking energy., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., DC systems, Energy conversion & Storage

Social VR aims at enabling people located at different places to communicate and interact with each other in a natural way. It poses extremely strong throughput and latency requirements on the underlying communication networks. This paper investigates the potential of using cross-layer design approaches for radio access scheduling in order to realize these challenging requirements in (beyond) 5G networks. In particular, we provide an in-depth simulation study of the performance/capacity gains that can be achieved by exploiting the end-to-end latency budget and/or video frame type as cross-layer information in the scheduling decisions, and show how the benefits depend on the actual social VR scenario. This study further reveals the importance of using application-level metrics such as PSNR or SSIM rather than traditional network-level metrics like the packet drop rate in the performance assessment., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Network Architectures and Services

Soft grippers show adaptability and flexibility in grasping irregularly shaped and fragile objects. However, the soft grippers' low loading capacity and limited shaped fitting ability are the main limitations for developing large-scale applications, especially for heavy objects and objects with sharp edges. The particle jamming effect has emerged as an essential actuation method to adjust the stiffness of soft grippers and enhance the lifting force applied to heavy objects. However, in many large and more serious practical grasping applications, soft actuators are expected to show large scales and several-fold stiffness change, which is challenging to achieve the jamming effect in pneumatic or hydraulic systems. In this paper, a novel active particle jamming method is proposed for the design of a particle jamming-based soft gripper. The proposed method uses active hydrogel particles instead of vacuum pressure to achieve the jamming effect. Additionally, the bending behaviors are implemented based on the jamming effect and actuator design. The numerical model is carried out to explore the actuator behaviors, and a brief experiment case is conducted to verify the feasibility. The results indicated that the proposed actuator achieves the functionality of bending actions by swelling the hydrogel particles. The bending performance is enhanced by lowering the trigging temperature and increasing the thickness of the strain-limit layer. Additionally, there is a transition state from bending to curling when increasing the layer of particles., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport Engineering and Logistics