Search

This paper explores the use of fuzzy difference methods in order to understand the differences between forest classes. The context for this work is provided by REDD+, which seeks to reduce the net emissions of greenhouse gases by rewarding the conservation of forests in developing countries. REDD+ requires that local inventories of forest are undertaken and payments are made on the basis of the amount of forest (and associated carbon storage). At the most basic level this involves classifying land into forest and non-forest. However, the critical issues affecting the uptake, buy-in and ultimately the success of REDD+ are the lack of universally agreed definition of forest to support REDD+ mapping activities, and where such a definition is imposed, the marginalization of local community voices and local landscape conceptualizations. This tension is at the heart of REDD+. This paper addresses these issues by linking methods to quantify changes in fuzzy land cover to the concept of data primitives, which have been previously proposed as a suitable approach to move between land cover classes with different semantics. These are applied to case study that quantifies the difference in areas for two definitions of forest derived from the GLC and FAO definitions of forest. The results show how data primitives allow divergent concepts of forest to be represented and mapped from the same data and how the fuzzy sets approach can be used to quantify the differences and non-intersections of different concepts of forest. Together these methods provide for transparent translations between alternative conceptualizations of forest, allowing for plural notions of forest to be mapped and quantified. In particular, they allow for moving from an object-based notion of forest (and land cover in general) to a field-based one, entirely avoiding the need for forest boundaries.

Airport Security is a complex and important task directly affecting airports’ operational performances and passenger comfort. As part of the EU Horizon 2020 project PASSME, passenger centric airport and airplane interiors were redesigned in order to meet passengers’ needs and reducing door-to-door travel time. This paper will describe how simulation was used to provide early feedback as part of the security design process and for evaluating the outcome while avoiding high implementation cost and without disturbing operational processes. We will also describe the new developed security design concept as well as the simulation approach with Anylogic software. The simulation output – effects of the new design concept – will be discussed at the end of the paper along with an outlook on further research opportunities.

This paper presents an architecture for Automated Valet Parking (AVP) connected to cloud-based IoT services and mobile user interfaces. The goal is to enable AVP services for automatic vehicles. From the user perspective, automatic car drop-off and pick-up are activated via smart phone application, and the user will be able to continuously monitor the vehicle status together with additional services as cleaning or recharge during the parking phase. Further, the IoT platform allows the integration of live services that will interact with automatic driving and parking. As an example, the presented AVP setup includes the operation of service drones to automatically guide a vehicle to the best parking spot. The demonstration in this paper comprises a parking car and a micro aerial vehicle (MAV) connected in real-time through the IoT platform as well as the smart phone application where the car is controlled and supervised.

To assess digital patient briefing as an alternative to conventional paper documentation. 502 patients with a planned computed tomography (CT) examination were selected for digital patient briefing using the E-ConsentPro software from Thieme Compliance on an iPad by Apple (Cupertino, California, USA). For the analysis, three age groups were formed. The time required for the patient briefing, the number of open questions as well as the time needed for discussion with physicians were determined. Student's t-test was performed to assess statistical significance. There was no significant difference between patient age and briefing time which was about 20 minutes on average. The number of open or unclear questions increased with patient age. While patients younger than 30 years of age had about 2 open questions, patients over 30 and 60 years had about 4 and 5 questions, respectively. The total time needed for discussion with physicians was less than 2 minutes on average. A significant difference in the time required for discussion with physicians could not be observed between the individual age groups. Tablet-based digital briefing allows the storage of patient documents with reasonable time and effort. Furthermore, it minimizes the risk of data loss. · Tablet-based digital patient briefing in computed tomography can be performed with reasonable time and effort.. · The time required for tablet-based patient briefing is independent of patient age.. · The cost-benefit analysis presents a significant improvement in digital patient briefing compared to the paper-based process..· Alikhani B, Hensen B, Grosser A et al. Initial Experience with Digital Patient Briefing in Computed Tomography. Fortschr Röntgenstr 2019; 191: 540 - 546.ZIEL: Die Möglichkeit der digitalen Aufklärung von Patienten wurde im Rahmen eines Pilotprojekts evaluiert. Für die vorliegende Arbeit wurden 502 konsekutive Patienten ausgewählt, die in der Computertomografie (CT) untersucht werden sollten. Die digitale Aufklärung erfolgte mit der Software E-ConsentPro der Firma Thieme Compliance auf einem iPad. Die Patienten wurden in 3 Altersgruppen unterteilt. Die Auswertung beschränkte sich auf die Ermittlung der Gesamtdauer der Patientenaufklärung, der offenen oder unklaren Fragen sowie des Zeitaufwands für ein Aufklärungsgespräch mit dem Arzt. Zur Prüfung von signifikanten Unterschieden wurde der t-Test durchgeführt. Unabhängig vom Alter bearbeiteten die Patienten den digitalen Aufklärungsbogen im Mittel ca. 20 Minuten. Die Anzahl der offenen oder unklaren, noch mit dem aufklärenden Arzt zu besprechenden Fragen nahm nicht signifikant mit dem Patientenalter zu. Während Patienten unter 30 Jahren vor dem Arztgespräch ca. 2 offene Fragen hatten, hatten Patienten über 60 Jahre ca. 5 offene Fragen. Patienten zwischen 30 und 60 Jahren hatten noch ca. 4 Fragen, die mit dem Arzt besprochen werden sollten. Die Gesamtdauer eines Aufklärungsgesprächs mit dem Arzt betrug im Mittel unter 2 Minuten. Signifikante Unterschiede im Zeitaufwand für das ärztliche Aufklärungsgespräch konnten zwischen den einzelnen Altersgruppen nicht festgestellt werden. Die Tablet-basierte digitale Aufklärung ermöglicht unabhängig vom Patientenalter und der Anzahl der offenen Fragen vor dem Arztgespräch eine mit vertretbarem Zeit- und Arbeitsaufwand zu realisierende rechtssichere Ablage der Dokumente, bei der das Risiko des Datenverlusts durch die Logistik und Archivierung von Patientenunterlagen reduziert werden kann. · Die digitale, Tablet-basierte Patientenaufklärung kann mit vertretbarem Zeit- und Arbeitsaufwand durchgeführt werden.. · Die Tablet-basierte Aufklärungsdauer ist vom Alter der Patienten unabhängig.. · Die digitale Aufklärung leistet einen wesentlichen Beitrag zur Verbesserung der Arbeitsabläufe in der Radiologie..· Alikhani B, Hensen B, Grosser A et al. Initial Experience with Digital Patient Briefing in Computed Tomography. Fortschr Röntgenstr 2019; 191: 540 – 546.

Recent debate in human geography has challenged the problematic "alternative"/"conventional" duality that characterises contemporary food provision. Within this binary, alternative food networks and initiatives (AFIs and AFNs) are positioned in opposition to more conventional, agri-capitalist modes of food production and distribution. Framing food around materially, discursively and spatially distinct, albeit relational, geographies not only reinforces this binary but also reaffirms the hegemony of agri-capitalism that alternative provision seeks to undo. Focusing on examples of artisanal and industrial bread production in the UK and the USA, this paper challenges such ontological framings. Drawing from conceptual insights into diverse economies and alternative economic spaces (e.g. Gibson-Graham, 1996:2004; Lee and Leyshon, 2003) and adopting an integrative approach to practice (Shove and Pantzar, 2005; Hand and Shove, 2007), this paper examines the practices that constitute artisanal and industrial baking. Specifically, it focuses on the ways in which embodied practices constitute the spaces of production for such foods. While acknowledging the considerable distances between the geographies that circumscribe these alternative and conventional foods, this paper argues that practices of food production narrow these distances, thereby destabilising the alternative/conventional binary. The geographies of food may mobilise an array of places, materials and ideologies, which are suggestive of two opposing systems of food provision, but practices of food production reveal an array of marginal spaces that challenge this. By reorienting critical attention onto these marginal spaces, the differences between artisanal and conventional food become blurred – and the affinities produced through normalised discourses and materialities of food are contested, resisted and disrupted. I argue these spaces are insurgent and that they come together through affinitive practices, which result in the potential for radical change within food provision.

This paper takes up the increasingly popular topic of drones — including Unmanned Aerial Vehicles (UAVs), small unmanned aerial Systems (sUAS), Remotely Piloted Aircraft (RPA) and a vast panoply of commercial drones and copters — to argue that our analysis should lie not so much on drones as objects, but as assemblages of the vertical. Drones, I argue, constitute a socio-technical assemblage of the sky and vertical space, which means that our focus should be not (only) on their technological development and capacities (although this is certainly important) but on their wider effects and affects. The latter of these include increasing algorithmic data collection and circulation. In the second part of the paper, I examine what I call "algorithmic governance" inspired by the recent governing algorithms conference at NYU but also drawing from Foucault's work on governmentality. Algorithmic governance constitutes "conduct of conduct" to modulate how "data shadows" or Deleuzian "dividuals" can be created, sold, and passed forward. My particular concern is how this takes place in a geographic register.

There are some significant differences between the health systems in German speaking Europe and Sweden: In Sweden, the number of hospitals is small, caregiving services in the hospital and ambulatory sector are integrated, health professionals with university degrees are granted extended competencies and rights incl. first line consultation and limited prescription. Education is designed to prepare for these functions and responsibilities. It started more than 30 years ago when Linköping implemented the OECD-model of Health Universities. Interprofessional teaching, common learning of the various tracks and training on real patients are constitutive elements of this novel approach. Karolinska University in Stockholm adopted the model in 1998 and gave way to a nationwide reform. A recommendation of the German Science Council regarding training of health professionals, published 2012, drew the attention of educators to this approach. The paper explains the circumstances of the consolidation of this concept. It is important to realize that overarching governance principles and measures deriving from health and education policy are of crucial importance. They evolve from evaluations of needs carried out by the regional health agencies which lead to conditional mandates and financial incentives to the education sector. Moreover, decisions taken by the national board for accreditation and quality assurance take also in account the goals set and the outcomes in education and caregiving. Outside Sweden they would be considered an inappropriate limitation of academic freedom.The paper ends with a reflection of impressions collected during a study trip and shows some lessons to be learnt from the Swedish education and practice.

Pedestrian positioning is still a challenging field of interest when not receiving any GNSS or other reference signals as it might be the case in indoor environments or tunnels. For professional applications, where it is not possible to rely on any infrastructure, a common technique is to mount Inertial Measurement Units (IMUs) on the foot or other parts of the body for positioning. IMU based techniques still suffer from the remaining drift especially when the environment is unknown and not re-visited, or when the pedestrian walks randomly in large areas. In order to overcome this problem the so called FootSLAM algorithm applied in this paper is extended to handle known locations. FootSLAM is a SLAM (Simultaneous Localization and Mapping) algorithm estimating the map of the environment while walking wearing an inertial sensor on the foot or at other locations of the body. With only few known locations the estimated FootSLAM map can be refined or corrected in the case of non-convergence in critical areas. Beside the derivation of the algorithm handling known locations in FootSLAM, the influence of different kinds of prior information on the FootSLAM algorithm is analyzed in this paper in terms of error and map quality performance.

The environmental control system of an aircraft is a complex energy intensive system and the most important non-propellant consumer of energy among all aircraft systems. Considering the highly competitive market for conventional aircraft, meaningful analysis methods for evaluation during conceptual design of ECS and effective modelling and simulation tools became more important. Hence, this paper focuses on energy and exergy analyses applied to the conventional aircraft environmental control system combined with the model-based design approach. The reported results are related to the different analysis methods for aircraft environmental control systems and cover the model-based design approach. The exergy method is applied to a model of a conventional air generation unit of a commercial aircraft. This model was developed using a model-based design framework. Within this framework, the exergy analysis was performed for four phases of a standard flight mission: Take-off, cruise, landing and taxi. The results obtained from the detailed exergy analysis show highly varying performances for the components at the different simulation cases. The exergy efficiencies range from 1% to 88%. A discussion about the special requirements for aircraft environmental control system analysis methods concludes the paper.

Current measurement techniques do not allow the visualization of the return air flow of open volumetric receivers in solar tower power plants. The reason is that the region of interest is irradiated by concentrated solar radiation and is located on top of a tower. Therefore, a novel method of measurement, the Induced Infrared Thermography (IIT) is introduced within this paper. With this method the return air can easily be observed with an infrared camera. As air has a very low emissivity in the infrared region the activity has to be induced by the addition of an infrared-active component, here carbon dioxide. The temperature of the infrared-active component has the greatest influence on the signal strength but the mole fraction of the component and the distance to the infrared camera are also important. Due to temperature restrictions, the measured signal to noise ratio is low and therefore several post-processing steps have to be conducted to visualize the return air. The most important step for the visualization is subtracting a background image. Furthermore, a video filter is employed in order to remove noise. A time series of ITT images can be used to obtain information on the velocity fields of the flow. The process, called Infrared Image Velocimetry (IRIV) here, is similar to Particle Image Velocimetry (PIV) and is applied in this paper to external fluid flows of the open volumetric receiver. As IRIV is in an early stage of development the depicted results are treated as qualitative vector fields.

The concept of innovation ecosystems gained significant importance in academic research on strategy and practice over the last years. The emergence of the Internet of Things is disrupting industries and setting the ecosystem in the focus of innovation. Even traditional analog industries, like the energy industry, are under pressure to foster and manage ecosystems during their innovation efforts. Thus, the energy industry represents an appropriate setting for examining the evolution of an innovation ecosystem under the empirical lens of controversies, which describe the challenges of the status quo and is congruent with previous research on dialectical inquiries as source of innovation dynamics. For the purpose of this paper, the Actor-network theory (ANT) is regarded as an appropriate tool since it allows researchers to analyze how actors interact due to their specific interests with each other and thus configure the ecosystem in its base. ANT further enlarges the perspective of handling actors, while it involves not only human but also non-human actors (i.e. technologies). This is a valuable and necessary feature while dealing with digital innovations such as virtual power plants (VPP). By analyzing three how distinctive typologies, their mechanisms as well as their pathways of controversies affect the innovation ecosystem of VPPs and the evolution of the technological components of the innovation, this interaction between human and non-human actors is highlighted. In consequence, our research emphasizes the significance of involving non-human actors into managerial strategies and the role they inherit for the evolution of ecosystems. Furthermore, the present research reveals that controversies are not only a moderating factor but also a constitutional one for the coevolution of the ecosystem as well as the innovation itself especially during the forming phases. With respect to recent research of the management of digital innovation, this paper contributes to a better understanding of managerial challenges associated with digital innovation and their respective ecosystems.

Whereas crowdsourcing as a topic has often been addressed in recent literature, web-based crowdworking platforms that manage the interface between crowdsourcers and crowdworkers have not received much attention so far. Furthermore, most of these platforms focus on either the management of external or internal crowds; platforms that handle both groups are rare. This paper investigates such a provider: the German company Across Systems. It uses a hybrid model, offering an individual “mini crowdworking platform” that enables the simultaneous government of external and internal crowds as well as a more traditional marketplace crowdworking platform (crossMarket) where supply and demand meet. Using a single-case study approach, the main contribution of this paper is to shed light on a model that has the potential to change the current crowdworking platform market. We show that managing both external and internal crowds on one platform can increase the acceptance, quality and speed of task completion.

This paper deals with a low to middle order finite volume/lumped capacitance thermal model of an electric machine and the correction of critical parameters. The different parts of the electric machine are divided into sub-volumes called finite volumes or lumped capacitances. From the given characteristic geometry of the electric machine, the thermal resistances to create the system matrix are calculated. The resulting non-linear equation system is solved for steady state condition for a given current density. The result is compared to experimental measurements allowing the calculation of material correction parameters included in the thermal resistances using the least square method. In a second step an experiment with time dependent current in the stator windings is done. The experiment then is simulated with the time dependent current measured in the experiment using the correction parameters found in the first step. The paper aims to present the possibility to calculate the maximum temperatures very accurately with this method.

Range accuracy of synthetic aperture radar using modern satellites has been proven in centimeter-range after consideration of geodynamic, atmospheric effects and systematic errors; it is so-called Imaging Geodesy technique. Based on this technique, we have proposed the next-generation of Synthetic Aperture Radar (SAR) products and developed operational software SAR Geodesy Processor in the previous paper. In this paper, we are concentrated on validation of processor and accuracy analysis on a global-scale. Two datasets with different spatial resolutions generated from European Centre for Medium-Range Weather Forecast are used to compensate atmospheric refraction effect in range. At the end, we apply corrections on a Sentinel interferogram by using both datasets.

As bit rates of optical interconnects increase, a large amount of complicated signal conditioning is needed to compensate for the insufficient bandwidth of current modulators. In this paper, we evaluate the reduced equalization requirements of high-bandwidth plasmonic modulators in short-reach transmission experiments. It is shown that transmission of 100 Gbit/s non-return-to-zero (NRZ) and 112 Gbit/s pulse-amplitude modulation-4 over 1 km and 2 km distance is possible without any receiver equalization. At higher bit-rates, such as 120 Gbit/s NRZ, data transmission is demonstrated over 500 m with reduced receiver equalization requirements. Transmission up to 200 Gbit/s over 1 km is also shown with more complex receiver equalization. The reduced complexity of the receiver digital signal processing is attributed to a flat frequency response of at least 108 GHz of the plasmonic modulators. All single wavelength transmissions have been performed at 1540 nm in standard single mode fiber.

International audience; Many computer vision problems such as recognition, image retrieval, and tracking require matching two images. Currently, ones try to find as reliable as possible matching techniques with a very little constraint of computational time. In this paper, we are interested in applying image matching technique into robotic problems such as Augmented Reality, Visual Servoing in which the computational time is a critical element. We propose in this paper a real time keypoint based matching method. The novelties of this method include a fast corner detector, a compact corner descriptor based on Principal Component Analysis (PCA) technique and an efficient matching with help of Approximate Nearest Neighbor (ANN) technique. We show that the method gives a very satisfying result on accuracy as well as the computational time. The matching algorithm is applied to command a robot in a visual servoing application. It works at 10-14Hz and is well robust to variations in 3D viewpoint and illumination.

This article deals with one of the most controversial topics in urban studies related to mobile capital and mobile people. At first glance this seems to be contradictory since numbers of short-term rentals have decreased dramatically due to the coronavirus (SARS-CoV-2) pandemic. However, this paper is not about numbers and statistics. Instead it discusses structural issues regarding governance and power relations which remain important topics (especially) in times of crisis. It provides insights regarding the following issues: firstly, it deconstructs different “myths” that still surround short-term rentals and Airbnb and secondly, it delineates the structural power of Airbnb as a new urban institution. This helps us to understand some of the conflicts over Airbnb and the pitfalls with current forms of regulation on the one side as well as showing the complexity and agency of short-term rentals on the other.

This paper analyses the resilience of the French territories of Saint-Martin by considering the issue of drinking and sanitary water supply system recovery in the aftermath of hurricane Irma. We understand resilience as a post-disaster recovery process (Reghezza & Rufat 2019). We address responses and coping strategies deployed by the institutions (local and national authorities, network operators, NGOs) as well as by the local communities and individuals. The fieldwork we carried out in Saint-Martin highlights the fact that the combination of institutional and inhabitants’ responses prevented a humanitarian disaster. On one hand, institutional stakeholders were able to implement effective and efficient coping strategies. On the other hand, inhabitants’ vulnerability to freshwater shortage risks was greatly reduced by an individual adaptation, built well upstream of Irma in response to local context. Our study confirms that networks are socio-technical systems embedded in a set of production and consumption practices. In this sense, drinking and sanitary water systems criticality is territorialized and individual resilience is rooted in “ordinary vulnerability”.

Conventional CMOS image sensors with a linear transfer characteristic only have a limited dynamic range (DR) of about 60–70 dB. To extend the dynamic range considerably, the already successfully demonstrated concept of a linear self-reset pixel was employed in this work. With the self-reset concept the limit of the maximum analyzable photo generated charge (Qmax⁡) during the exposure time is extended to a multiple of the saturation charge of the photo diode (Qsat) by asynchronous self-resets of the photo diode. Additionally, the remaining charge at the end of the exposure time is evaluated to increase the resolution of the opto-electronic conversion. Thus we achieved pixels with a DR of more than 120 dB combined with an improved low light sensitivity using a pinned photodiode. This paper focuses on two topics: One is the realization and opto-electronic characterization of further self-reset pixel cells for an experimental optimization of the functionality with respect to linearity and high signal-to-noise ratio. The second one is the assembly and digital readout of a cluster structure composed of 16 × 16 pixel matrix on a CMOS test chip. One constraint for later usage of the pixel cells in a high resolution (> VGA) image sensor is the required layout area of the individual circuit blocks. For the cluster structure a size of 20 × 20 µm2 for the analog part of the pixel containing the photo diode and the other analog circuit blocks, the comparator and the signal shaping, was desired. The circuit design and layout work included several variants of the pinned photo diode with floating diffusion (FD) readout node, which is also used for analog voltage storage, and different control transistors. Further for the comparator a telescopic differential amplifier with high gain was implemented as well as peripheral 10 bit counter/shift register as static and dynamic versions. Test chips have been fabricated in an advanced 0.18 µm CMOS technology for optical sensors with low leakage currents. The sensor chips have been evaluated with a specifically developed test setup which gives the flexibility to arbitrarily generate the digital and analog control signals in terms of timing and voltage levels. Based on this, the number of asynchronous self-resets could be read out from the counters of the pixel cells as coarse values. The remaining charge at the end of the integration time was digitized using a ramp analog to digital conversion and could be read out as fine values. An opto-electronic characterization with adjustable illumination from 0 lx to 13 klx was done to measure and analyze the opto-electronic conversion function (OECF) and the noise of six different self-reset pixel cells having the high-gain differential amplifier as comparator. Finally the coarse values of two implemented 16 × 16 pixel clusters could be read out as a mini camera using a lens for optical image formation.

With increasing radar activities in the automotive, industrial and private sector, there is a need to test radar sensors in their environment. A radar target simulator can help testing radar systems repeatably. In this paper, the authors present a concept of low-cost hardware for radar target simulation. The theoretical foundations are derived and analyzed. An implementation of a demonstrator operating in the 24 GHz ISM band is shown for which the dynamical range simulation was implemented in a FPGA with fast sampling ADCs and DACs. By using a FIR filtering approach a fine discretization of the range could be reached which will furthermore allow an inherent and automatic Doppler simulation by moving the target.

The dynamics of software – and thus also of its development – is an inherent part of the story of how mobilities are made and work. Building on this argument, this ethnographic study explains how navigation software development is caught in a constant culture of acceleration through commercial competition and shifting transport conditions, on the one hand, and a logic of routing and navigation based on creating the fastest route possible for its users, on the other hand. Behind this overall process of technological acceleration lies a multiplicity of forces – sometimes accelerating, but at other times slowing down, stuttering, moving in reverse, or completely coming to a halt in breakdown, shifting the pace of such technological progress. Bringing software development practice into the picture of how mobility systems work (or don’t work) allows us to understand the multiple temporal orders of speeding up and slowing down that push and pull at the fabric of our mobile infrastructures. Doing so will help us counter the popular discourse that our networked, seamless digital technologies are invincible. Based on an ethnography at ‘BerlinTech’, a large commercial navigation software company, this paper provides a multilayered understanding about the temporal forces fuelling our software driven mobility infrastructures.

Crowdfunding is now established as a valid alternative to conventional methods of financing for startups. Unfortunately, to date, research has not investigated how backers can be encouraged to support entrepreneurs beyond funding. The aim of this study is to design and evaluate certain design elements for reward-based crowdfunding platforms that can engage backers in co-creational activities for product development. The study uses a design science research (DSR) approach and the theoretical concept of psychological ownership to inform a new design and then experimentally test that design. The results suggest that the derived artifacts positively influence co-creational activities in crowdfunding and that feelings of psychological ownership play an important mediating role. The contribution of this research is threefold. First, this paper extends crowdfunding’s application potential from merely a method of financing to a method of value creation with customers for product development. Second, the study advances DSR by applying a new DSR approach that shows whether a design performs as hypothesized by theory. Third, this research allows the exploration of backers’ individual behavior as opposed to their collective behavior.

Short range inductive data transfer has become very popular in the last years with the increased interest in technologies like RFID and NFC. Additionally, wireless power transfer has been a field of intensive research and product development. In industrial applications, a combination of both is often needed to replace mechanical contacts, mainly for safety and reliability reasons, especially regarding spark prevention and maintenance reduction. In this paper, we present a compact inductive structure that can be implemented in an existing wireless energy transfer system. The structure is developed by field considerations, leading to a single structure comprising two signal ports that are decoupled from each other, but can be used to transfer a signal to a second structure of that kind with very small interference. An optimisation to achieve comparable channel characteristics is conducted by using 3-D field simulations. Subsequent measurements are conducted to verify the achieved performance.

This paper aims to analyse the intermodal practices of mobility in the bus-metro network of Rennes metropole. Intermodality being strongly linked to the use of urban public transport networks, the Rennes Metropole bus and metro network data provided by Keolis-Rennes provides a very significant part of daily intermodality. To compensate for the lack of information on destinations and correspondances in the ticketing data a reconstruction of trips was made on the basis of hypotheses provided by the literature. The research carried out in the "Mobilletic" project considerably deepened the understanding of the temporal and spatial dimensions of intermodal mobility within Rennes Metropole’s urban public transport network.daily mobility, public transport, data science, data analysis, intermodal transportation

Requirements Engineering (RE) has been aiding software-intensive development projects for quite some time now. However, today’s projects growingly demand for agile and human-centered approaches to discover and meet the often fuzzy needs of the various stakeholders involved. In that regard, Design Thinking (DT) has become one of the most promising methods to address complex problems and define innovative solutions. We see potential to combine both, the strongly human-oriented working mode of DT with the more formal, technology-driven world of RE, to develop human-centered solutions more effectively. Yet, little is known how such an integration could be realized and which concrete benefits and challenges to expect. To better understand this endeavor, we conduct a longitudinal case study to identify how DT and RE can work together in an agile development setting from the very beginning of idea conceptualization to market-ready implementation. In this paper, we summarize our research protocol and present first findings how Design Thinking can complement current RE practices through meeting known challenges encountered by the RE community of practitioners. We provide a better understanding of the multi-faceted potential of DT for RE for both, scholars and practitioners, and describe open issues and planned future steps in our study.

Character animation tools are based on a keyframing metaphor where artists pose characters at selected keyframes and the software automatically interpolates the frames inbetween. Although the quality of the interpolation is critical for achieving a fluid and engaging animation, the tools available to adjust the result of the automatic inbetweening are rudimentary and typically require manual editing of spline parameters. As a result, artists spend a tremendous amount of time posing and setting more keyframes. In this pose-centric workflow, animators use combinations of forward and inverse kinematics. While forward kinematics leads to intuitive interpolations, it does not naturally support positional constraints such as fixed contact points. Inverse kinematics can be used to fix certain points in space at keyframes, but can lead to inferior interpolations, is slow to compute, and does not allow for positional contraints at non-keyframe frames. In this paper, we address these problems by formulating the control of interpolations with positional constraints over time as a space-time optimization problem in the tangent space of the animation curves driving the controls. Our method has the key properties that it (1) allows the manipulation of positions and orientations over time, extending inverse kinematics, (2) does not add new keyframes that might conflict with an artist's preferred keyframe style, and (3) works in the space of artist editable animation curves and hence integrates seamlessly with current pipelines. We demonstrate the utility of the technique in practice via various examples and use cases.

The fusion of complementary information from co-registered multi-modal image data enables a more detailed and more robust understanding of an image scene or specific objects, and is important for several applications in the field of remote sensing. In this paper, the benefits of combining RGB, near infrared (NIR) and thermal infrared (TIR) aerial images for the task of semantic vehicle segmentation through deep neural networks are investigated. Therefore, RGB, NIR and TIR image triplets acquired by the Modular Aerial Camera System (MACS) are precisely co-registered through the application of a virtual camera system and subsequently used for the training of different neural network architectures. Various experiments were conducted to investigate the influence of the different sensor characteristics and an early or late fusion within the network on the quality of the segmentation results.

The automatic matching of corresponding regions in remote sensing imagery acquired by synthetic aperture radar (SAR) and optical sensors is a crucial pre-requesite for many data fusion endeavours such as target recognition, image registration, or 3D-reconstruction by stereogrammetry. Driven by the success of deep learning in conventional optical image matching, we have carried out extensive research with regard to deep matching for SAR-optical multi-sensor image pairs in the recent past. In this paper, we summarize the achieved findings, including different concepts based on (pseudo-)siamese convolutional neural network architectures, hard negative mining, alternative formulations of the underlying loss function, and creation of artificial images by generative adversarial networks. Based on data from state-of-the-art remote sensing missions such as TerraSAR-X, Prism, Worldview-2, and Sentinel-1/2, we show what is already possible today, while highlighting challenges to be tackled by future research endeavors.

Building semantic segmentation is a crucial task for building information modeling (BIM). Current research generally exploits terrestrial image data, which provides only limited view of a building. By contrast, oblique imagery acquired by unmanned aerial vehicle (UAV) can provide richer information of both the building and its surroundings at a larger scale. In this paper, we present a novel pipeline for building semantic segmentation from oblique UAV images using a fully convolutional neural network (FCN). To cope with the lack of UAV image annotations at facade level, we leverage existing ground-view facades databases to simulate various aerial-view images based on estimated homography, yielding abundant synthetic aerial image annotations as training data. The FCN is trained end-to-end and tested on full-tile UAV images. Experiments demonstrate that the incorporation of simulated views can significantly boost the prediction accuracy of the network on UAV images and achieve reasonable segmentation performance.

In situ measurements of cloud droplet number concentration N are limited by the sampled cloud volume. Satellite retrievals of N suffer from inherent uncertainties, spatial averaging, and retrieval problems arising from the commonly assumed strictly adiabatic vertical profiles of cloud properties. To improve retrievals of N it is suggested in this paper to use a synergetic combination of passive and active airborne remote sensing measurement, to reduce the uncertainty of N retrievals, and to bridge the gap between in situ cloud sampling and global averaging. For this purpose, spectral solar radiation measurements above shallow trade wind cumulus were combined with passive microwave and active radar and lidar observations carried out during the second Next Generation Remote Sensing for Validation Studies (NARVAL-II) campaign with the High Altitude and Long Range Research Aircraft (HALO) in August 2016. The common technique to retrieve N is refined by including combined measurements and retrievals of cloud optical thickness τ, liquid water path (LWP), cloud droplet effective radius reff, and cloud base and top altitude. Three approaches are tested and applied to synthetic measurements and two cloud scenarios observed during NARVAL-II. Using the new combined retrieval technique, errors in N due to the adiabatic assumption have been reduced significantly.

In this paper, we analyze internal crowd work as Neo-STS from an employee’s perspective. Based on qualitative interviews, we describe in our model how employees perceive empowerment through participation in internal crowd work. As our main contribution, we detail and extend existing research regarding internal crowd work, Neo-STS as well as empowerment by identifying structural antecedents that affect psychological empowerment of internal crowd workers.

This paper presents a system calibration method for a trifocal sensor, which is sensitive to different spectral bands. The trifocal camera system consists of a stereo camera, operating in the visual (VIS) spectrum and a thermal imaging camera, operating in the Long-Wave- Infrared (LWIR) spectrum. Intrinsic parameters and spatial alignment are determined simultaneously. As calibration target a passive aluminium chessboard is used. Corner detection and subsequent bundle adjustment is done on all synchronized image triplets. The remaining reprojection errors are in the sub-pixel range and enable the system to generate metric point clouds, colored with thermal intensities in real-time.

The housing question is a topic of increasing concern in a number of European cities. Rising housing costs burden many households. Since the outbreak of the global economic crisis in 2008, housing has increasingly come under spotlight of investors. Institutional and private actors invest in real estate not only in metropolitan areas but also in middle and small-sized towns. Tourism-induced demand increases the pressure on housing markets particularly in tourist-dominated cities. The manifestation of these processes varies on a small scale and is influenced by regional-local planning and politics. Based on the example of the city of Salzburg, the article shows that the housing question manifests itself strongly aside metropolises as well. Financial investments by private and institutional actors in real estate and different forms of tourism demand exacerbate the housing shortage. By linking the discussions about the effects of (mass-)tourism and financial investments on regional housing markets, this paper provides additional insights. The additional demand for (residential) space by tourism is used to increase or secure the return on investments in real estate. Financial investments in housing offer additional (problematic) potential for tourist use, such as short-term rentals. Owners benefit from both processes. Due to the prevalent power relations, planning and politics have little to counter the current challenges. © 2019 Copernicus. All rights reserved.

In this paper, we introduce the problem of cross-modal visuo-tactile object recognition with robotic active exploration. With this term, we mean that the robot observes a set of objects with visual perception, and later on, it is able to recognize such objects only with tactile exploration, without having touched any object before. Using a machine learning terminology, in our application, we have a visual training set and a tactile test set, or vice versa. To tackle this problem, we propose an approach constituted by four steps: finding a visuo-tactile common representation, defining a suitable set of features, transferring the features across the domains, and classifying the objects. We show the results of our approach using a set of 15 objects, collecting 40 visual examples and five tactile examples for each object. The proposed approach achieves an accuracy of 94.7%, which is comparable with the accuracy of the monomodal case, i.e., when using visual data both as training set and test set. Moreover, it performs well compared to the human ability, which we have roughly estimated carrying out an experiment with ten participants.

The aeroelastic behavior of wing models is nonlinear particularly in the transonic Speed range. The interaction between aerodynamic and structural forces can lead to the occurrence of Limit-Cycle Oscillations (LCOs). If in addition the wing model is flexible and backward swept, the kinematic coupling between bending and torsion makes the Situation even more complex. In the research project ‘‘Aerostabil’’ such a wing was investigated, which was equipped with pressure transducers in three sections and accelerometers. The experiments were performed in the adaptive test section of the transonic wind tunnel TWG in Göttingen. Already Dietz et al. (2003) have reported about experimental details and preliminary results. Based on these data Bendiksen (2008) studied numerically LCO-flutter behavior using a very similar, theoretical model (G-wing) and Stickan et al. (2014) used the original data as a LCO flutter test case. The influence of flexibility on the steady aerodynamics of the wing was described in Schewe & Mai (2018). In this paper now the flutter experiments with the same flexible model were analyzed systematically in the transonic range 0.84

With air transportation growing and current civil aeronautical communication systems reaching their capacity limit in high density areas, the need for new aeronautical communication technologies becomes apparent. The biggest challenge in recent years is the transition from analogue voice to digital data communication and the related trend towards an increased autonomous data processing. A promising candidate for the digital future communication infrastructure in continental areas is the terrestrial long-range L-band Digital Aeronautical Communications System (LDACS), which is currently in the process of being standardized by the International Civil Aviation Organization (ICAO). As safety and security are strongly intertwined in civil aviation, every installation of LDACS requires protection against cyber-attacks. This paper introduces a cybersecurity architecture for LDACS and proposes suitable security algorithm, which can achieve the security objectives on top of the architecture. Therefore we integrate new security functions within the existing protocol stack of LDACS. We provide an architecture for user data encryption, data integrity, authenticated key agreement, entity authentication, broadcast channel protection, and key and access management.

Summary Inverted pendulum on cart belongs to a class of highly non-linear, multivariable and complex system which is currently a keen area of interest for researchers in the field of control engineering and robotics. This paper considers stabilisation and control of inverted pendulum on cart moving on an inclined surface. The task of controlling inverted pendulum on inclined surface is much difficult as compared to that moving on horizontal surface. An offline control of the proposed system has been successfully achieved using proportional-integral-derivative (PID) and fuzzy controllers. A Matlab-Simulink model of the proposed system has been built using mathematical equations derived from Newton's second law. The study compares the proposed techniques in terms of settling time, overshoot, undershoot and steady state error. The simulation results are illustrated with the help of graphs and tables which confirms the validity of the proposed techniques.

Summary Moulded Case Circuit Breaker (MCCB) is a protective device used for low voltage protection in the range of 12–1250 A. It is having fast breaking and making ability due to special contact structure. In case of transformer it is generally placed in secondary side and in case of motor protection it is used as backup protection. The existing design is suffering from chattering of contact tip which lead to erosion and in turn affect electrical life. It also reduces interrupting/breaking capacity of MCCB. In this paper, detailed study of the factors and constraints related to repulsion threshold current ( I rp ) and consistency of magnetic release for 630 A MCCB is carried out using Finite Element tool JMAG to find out limitations and scope of design improvements in existing design. The proposed suggestion is validated by testing.

Summary Breast cancer is significant health problem diagnosed mostly in women worldwide. Therefore, early detection of breast cancer is performed with the help of digital mammography, which can reduce mortality rate. This paper presents wrapper based feature selection approach for wavelet co-occurrence feature (WCF) using Genetic Fuzzy System (GFS) in mammogram classification problem. The performance of GFS algorithm is explained using mini-MIAS database. WCF features are obtained from detail wavelet coefficients at each level of decomposition of mammogram image. At first level of decomposition, 18 features are applied to GFS algorithm, which selects 5 features with an average classification success rate of 39.64%. Subsequently, at second level it selects 9 features from 36 features and the classification success rate is improved to 56.75%. For third level, 16 features are selected from 54 features and average success rate is improved to 64.98%. Lastly, at fourth level 72 features are applied to GFS, which selects 16 features and thereby increasing average success rate to 89.47%. Hence, GFS algorithm is the effective way of obtaining optimal set of feature in breast cancer diagnosis.

Summary In this paper, we proposed superscalar pipelined inner product computation unit for signed-unsigned number operating at 16 GHz. This is designed using five stage pipelined operation with four 8 × 8 multipliers operating in parallel. Superscalar pipelined is designed to compute four 8 × 8 products in parallel in three clock cycles. In the fourth clock cycle of the pipeline operation, two inner products are computed using two adders in parallel. Fifth stage of the pipeline is designed to compute the final product by adding two inner partial products. Upon the pipeline is filled up, every clock cycle the new product of 16 × 16-bit signed unsigned number is obtained. The worst delay measured among the pipeline stage is 0.062 ns, and this delay is considered as the clock cycle period. With the delay of 0.062 ns clock cycle period, the pipeline stage can be operated with 16 GHz synchronous clock signal. Each superscalar pipeline stage is implemented using 45 nm CMOS process technology, and the comparison of results shows that the delay is decreased by 38%, area is reduced by 45% and power dissipation is saved by 32%.

Summary In deregulated rate structure, the performance evaluation of distribution system for energy efficiency includes; loss minimization, improved power quality, loadability limit, reliability and availability of supply. Energy efficiency changes with the variation in loading pattern and the load behaviour. Further, the nature of load at each node is not explicitly of any one type rather their characteristics depend upon the node voltages. In most cases, load is assumed to be constant power (real and reactive). In this paper voltage dependent practical loads are represented with composite load model and the energy efficiency performance of distribution system for practical loads is evaluated in different configurations of 33-node system.

Summary This paper presents a technique that aimed to accomplish an efficient balance between video compression using H.265 protocol and retention of 8K resolution. The study implements multi-level of optimization in the encoding process using H.265 where JPEG2000 standards play a crucial role. The study also applies a novel concept of orthogonal projection that manages pixels metadata required in every frame transition followed by motion compensation. By using multiple file formats of 30 video datasets, the outcome of the study is found to be accomplishing approximately 49% of enhancement in data quality and around 59% of improvement in video compression in comparison to the existing techniques of HEVC-based video compression.

Automotive electric components are required to pass radiated emission tests. According to CISPR-25 standard (ALSE method), an expensive anechoic chamber is needed for conducting the field emission testing. Reproducibility due to high sensitivity to chamber and setup details is poor. Alternative methods, which perform measurements without using a chamber are preferred. This paper provides an alternative pre-compliance method for predicting the fields of CISPR-25 results for frequencies below 30 MHz, based mainly on electric near-field measurements. The motivation is that common-mode current measurements or magnetic near-field measurement based methods give good field prediction above 30 MHz, but fail below 30 MHz. The proposed method applies Huygens' Principle for field prediction. The electric field distribution for the defined Huygens' surface and the equivalent currents are estimated from a small number of field measurements close to the ground plane. It is shown that the electric field can be well predicted, compared with a full-wave simulation the deviation is within 4 dB, compared with a standard antenna measurement up to 3 MHz the deviation is less than 1 dB.

Summary Cloud storage, which can be a surrogate for all physical hardware storage devices, is a term which gives a reflection of an enormous advancement in engineering ( Hung et al., 2012 ). However, there are many issues that need to be handled when accessing cloud storage on resource constrained mobile devices due to inherent limitations of mobile devices as limited storage capacity, processing power and battery backup ( Yeo et al., 2014 ). There are many multi cloud storage applications available, which handle issues faced by single cloud storage applications. In this paper, we are providing analysis of different multi cloud storage applications developed for resource constrained mobile devices to check their performance on the basis of parameters as battery consumption, CPU usage, data usage and time consumed by using mobile phone device Sony Xperia ZL (smart phone) on WiFi network. Lastly, conclusion and open research challenges in these multi cloud storage apps are discussed.

Summary In presence of environmental noise, speakers tend to emphasize their vocal effort to improve the audibility of voice. This involuntary adjustment is known as Lombard effect (LE). Due to LE the signal to noise ratio of speech increases, but at the same time the loudness, pitch and duration of phonemes changes. Hence, accuracy of automatic speech recognition systems degrades. In this paper, the effect of unsupervised equalization of Lombard effect is investigated for Hindi vowel classification task using Hindi database designed at TIFR Mumbai, India. Proposed Quantile-based Dynamic Cepstral Normalization MFCC (QCN-MFCC) along with baseline MFCC features have been used for vowel classification. Hidden Markov Model (HMM) is used as classifier. It is observed that QCN-MFCC features have given a maximum improvement of 5.97% and 5% over MFCC features for context-dependent and context-independent cases respectively. It is also observed that QCN-MFCC features have given improvement of 13% and 11.5% over MFCC features for context-dependent and context-independent classification of mid vowels.

Summary This paper presents an optimal placement methodology of energy storage to improve energy loss minimization through peak shaving in the presence of renewable distributed generation. Storage sizing is modelled by considering the load profile and desired peak shaving. This storage is suitably divided into multiple storage units and optimally allocated at multiple sites with suitable charge discharge strategy. Thus the peak shaving for maximum loss reduction is explored here. Renewable distributed generation (RDG) is modelled based on the seasonal variations of renewable resources e.g ., solar or wind and these RDGs are placed at suitable locations. A high-performance Grey Wolf Optimization (GWO) algorithm is applied to the proposed methodology. The results are compared with the well-known genetic algorithm. The proposed methodology is illustrated by various case studies on a 34-bus test system. Significant loss minimization is obtained by optimal location of multiple energy storage units through peak shaving.

Summary Cryptographic techniques are employed for minimizing security hazards to sensitive information. To make the systems more robust, cyphers or crypts being used need to be analysed for which cryptanalysts require ways to automate the process, so that cryptographic systems can be tested more efficiently. Evolutionary algorithms provide one such resort as these are capable of searching global optimal solution very quickly. Cuckoo Search (CS) Algorithm has been used effectively in cryptanalysis of conventional systems like Vigenere and Transposition cyphers. Linear Feedback Shift Register (LFSR) is a crypto primitive used extensively in design of cryptosystems. In this paper, we analyse LFSR based cryptosystem using Cuckoo Search to find correct initial states of used LFSR. Primitive polynomials of degree 11, 13, 17 and 19 are considered to analyse text crypts of length 200, 300 and 400 characters. Optimal solutions were obtained for the following CS parameters: Levy distribution parameter ( β ) = 1.5 and Alien eggs discovering probability ( p a ) = 0.25.

Summary Many mining operations produce tailings that dewater very slowly under self-weight consolidation. On way of reducing the water content of such tailings is by coagulation/flocculation processes (C/F processes). This paper describes a study using aluminium chloride and pre-hydrated aluminium salts as aluminium chlorohydrate – ACH (F1.2A, F1AM, FD15, FDM17H, F1S) and polyaluminium chloride – PACl (PAX-18) in dewatering of flotation tailing slurries, resulting from coal flotation in the coal preparation at the Paskov Mine (Czech Republic). Experiments were conducted at different temperature and mixing conditions to simulate full-scale conditions. The results point to a potentially technique for reducing the water content of tailings streams, thus increasing storage space, improving economic and environmental aspects.

Summary In this paper, we present a software tool capable of predicting the final quality of triple play services by using the most common assessment metrics. The quality of speech and video in network environment is a growing concern of all the internet service providers to carry the multimedia traffic without the excessive delays and losses, which degrade the quality of multimedia as it is perceived by the end users. Prediction mathematical model is based on results obtained from many performed testing scenarios simulating real behavior in the network. Based on the proposed model, speech or video quality is calculated with regard to policies applied for packet processing by routers and to the level of total network utilization. The application cannot only predict QoS parameters but also generate the source code of particular QoS policy setting according to the user interaction and apply the policy to the routers in the network. Contribution of the work consists of a new software tool enables network administrators and designers to improve and optimize network traffic efficiently.

Summary In recent years, the coal mine safety production situation in our country improved year by year, but severe accidents still occurred; the accidents caused great economic loss to the national economy. According to statistical analysis, almost all of the coal mine accidents will expose the hidden danger in before, most of the accidents caused due to safety management not reaching the designated position and the hidden danger management does not take any decision in time. Based on the coal mine safety management holes in our country, the coal mine macro, meso and micro safety management system was established in this paper, which includes meaning and conception of the theories of the macro, meso and micro safety management, and also includes the matching hardware equipment, in order to achieve the hidden danger's closed-loop control and dynamic early warning in the process of coal mine production.