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(2021)
Social protection is for many international organizations a state’s affair.1 While the state definitely plays an important role, the state is by far not the only actor and there is no predefined institutional arrangement of how social protection should be implemented. An exclusive focus on the state would therefore be short-sighted when assessing and comparing the performance of social protection systems. It is hence important to understand the mix of actors involved, the type of contribution they can make to social protection and their modes of cooperation. This contribution will therefore first sketch out the role and interplay of the main actors in social protection and then challenge some of the common assumptions made around how roles are best allocated in the social protection system concerning the providers of informal social protection, the private sector, civil society organizations (CSO) as well as international actors.
This thesis work presents the implementation and validation of image processing problems in hardware to estimate the performance and precision gain. It compares the implementation for the addressed problem on a Field Programmable Gate Array (FPGA) with a software implementation for a General Purpose Processor (GPP) architecture. For both solutions the implementation costs for their development is an important aspect in the validation. The analysis of the flexibility and extendability that can be achieved by a modular implementation for the FPGA design was another major aspect. This work is based upon approaches from previous work, which included the detection of Binary Large OBjects (BLOBs) in static images and continuous video streams [13, 15]. One addressed problem of this work is the tracking of the detected BLOBs in continuous image material. This has been implemented for the FPGA platform and the GPP architecture. Both approaches have been compared with respect to performance and precision. This research project is motivated by the MI6 project of the Computer Vision research group, which is located at the Bonn-Rhein-Sieg University of Applied Sciences. The intent of the MI6 project is the tracking of a user in an immersive environment. The proposed solution is to attach a light emitting device to the user for tracking the created light dots on the projection surface of the immersive environment. Having the center points of those light dots would allow the estimation of the user’s position and orientation. One major issue that makes Computer Vision problems computationally expensive is the high amount of data that has to be processed in real-time. Therefore, one major target for the implementation was to get a processing speed of more than 30 frames per second. This would allow the system to realize feedback to the user in a response time which is faster than the human visual perception. One problem that comes with the idea of using a light emitting device to represent the user, is the precision error. Dependent on the resolution of the tracked projection surface of the immersive environment, a pixel might have a size in cm2. Having a precision error of only a few pixels, might lead to an offset in the estimated user’s position of several cm. In this research work the development and validation of a detection and tracking system for BLOBs on a Cyclone II FPGA from Altera has been realized. The system supports different input devices for the image acquisition and can perform detection and tracking for five to eight BLOBs. A further extension of the design has been evaluated and is possible with some constraints. Additional modules for compressing the image data based on run-length encoding and sub-pixel precision for the computed BLOB center-points have been designed. For the comparison of the FPGA approach for BLOB tracking a similar implementation in software using a multi-threaded approach has been realized. The system can transmit the detection or tracking results on two available communication interfaces, USB and RS232. The analysis of the hardware solution showed a similar precision for the BLOB detection and tracking as the software approach. One problem is the strong increase of the allocated resources when extending the system to process more BLOBs. With one of the applied target platforms, the DE2-70 board from Altera, the BLOB detection could be extended to process up to thirty BLOBs. The implementation of the tracking approach in hardware required much more effort than the software solution. The design of high level problems in hardware for this case are more expensive than the software implementation. The search and match steps in the tracking approach could be realized more efficiently and reliably in software. The additional pre-processing modules for sub-pixel precision and run-length-encoding helped to increase the system’s performance and precision.
The introduction of new steering conceptsSteer-by-Wire (SBW) gives possibility to replace theconventional steering wheel by an alternative userinterface such as a sidestick. In SBW system the sidestickcan be used as user input element instead of a steeringwheel. The implementation of sidestick in the Human-Machine-Interface (HMI) allows combiningthe conventional steering consisting of a steeringwheel, an accelerator and a brake pedal into a singleelement. Also the implementation of the sidestickcreates new, interesting and flexible design optionswhich can be used to transform the driver’s spatialenvironment. This article describes an active sidestickfor a vehicle which has been developed, integrated andtested in accordance of haptic, ergonomic and safetyrelevant requirements. The control strategies used forthe active attenuators of the sidestick have beeninvestigated and optimised using a Simulink model.
We developed a scene text recognition system with active vision capabilities, namely: auto-focus, adaptive aperture control and auto-zoom. Our localization system is able to delimit text regions in images with complex backgrounds, and is based on an attentional cascade, asymmetric adaboost, decision trees and Gaussian mixture models. We think that text could become a valuable source of semantic information for robots, and we aim to raise interest in it within the robotics community. Moreover, thanks to the robot’s pan-tilt-zoom camera and to the active vision behaviors, the robot can use its affordances to overcome hindrances to the performance of the perceptual task. Detrimental conditions, such as poor illumination, blur, low resolution, etc. are very hard to deal with once an image has been captured and can often be prevented. We evaluated the localization algorithm on a public dataset and one of our own with encouraging results. Furthermore, we offer an interesting experiment in active vision, which makes us consider that active sensing in general should be considered early on when addressing complex perceptual problems in embodied agents.
The detection of human skin in images is a very desirable feature for applications such as biometric face recognition, which is becoming more frequently used for, e.g., automated border or access control. However, distinguishing real skin from other materials based on imagery captured in the visual spectrum alone and in spite of varying skin types and lighting conditions can be dicult and unreliable. Therefore, spoofing attacks with facial disguises or masks are still a serious problem for state of the art face recognition algorithms. This dissertation presents a novel approach for reliable skin detection based on spectral remission properties in the short-wave infrared (SWIR) spectrum and proposes a cross-modal method that enhances existing solutions for face verification to ensure the authenticity of a face even in the presence of partial disguises or masks. Furthermore, it presents a reference design and the necessary building blocks for an active multispectral camera system that implements this approach, as well as an in-depth evaluation. The system acquires four-band multispectral images within T = 50ms. Using a machine-learning-based classifier, it achieves unprecedented skin detection accuracy, even in the presence of skin-like materials used for spoofing attacks. Paired with a commercial face recognition software, the system successfully rejected all evaluated attempts to counterfeit a foreign face.
At present, data publication is one of the most dynamic topics in e-Research. While the fundamental problems of electronic text publication have been solved in the past decade, standards for the external and internal organisation of data repositories are advanced in some research disciplines but underdeveloped in others. We discuss the differences between an electronic text publication and a data publication and the challenges that result from these differences for the data publication process. We place the data publication process in the context of the human knowledge spiral and discuss key factors for the successful acquisition of research data from the point of view of a data repository. For the relevant activities of the publication process, we list some of the measures and best practices of successful data repositories.
Herein we report an update to ACPYPE, a Python3 tool that now properly converts AMBER to GROMACS topologies for force fields that utilize nondefault and nonuniform 1–4 electrostatic and nonbonded scaling factors or negative dihedral force constants. Prior to this work, ACPYPE only converted AMBER topologies that used uniform, default 1–4 scaling factors and positive dihedral force constants. We demonstrate that the updated ACPYPE accurately transfers the GLYCAM06 force field from AMBER to GROMACS topology files, which employs non-uniform 1–4 scaling factors as well as negative dihedral force constants. Validation was performed using β-d-GlcNAc through gas-phase analysis of dihedral energy curves and probability density functions. The updated ACPYPE retains all of its original functionality, but now allows the simulation of complex glycomolecular systems in GROMACS using AMBER-originated force fields. ACPYPE is available for download at https://github.com/alanwilter/acpype.
Users should always play a central role in the development of (software) solutions. The human-centered design (HCD) process in the ISO 9241-210 standard proposes a procedure for systematically involving users. However, due to its abstraction level, the HCD process provides little guidance for how it should be implemented in practice. In this chapter, we propose three concrete practical methods that enable the reader to develop usable security and privacy (USP) solutions using the HCD process. This chapter equips the reader with the procedural knowledge and recommendations to: (1) derive mental models with regard to security and privacy, (2) analyze USP needs and privacy-related requirements, and (3) collect user characteristics on privacy and structure them by user group profiles and into privacy personas. Together, these approaches help to design measures for a user-friendly implementation of security and privacy measures based on a firm understanding of the key stakeholders.
This article concerns with the accessibility of Business process modelling tools (BPMo tools) and business process modelling languages (BPMo languages). Therefore the reader will be introduced to business process management and the authors' motivation behind this inquiry. Afterwards, the paper will reflect problems when applying inaccessible BPMo tools. To illustrate these problems the authors distinguish between two different categories of issues and provide practical examples. Finally the article will present three approaches to improve the accessibility of BPMo tools and BPMo languages.
Abstract Classical ballet requires dancers to exercise significant muscle control and strength both while stationary and when moving. Following the Royal Academy of Dance (RAD) syllabus, 8 male and 27 female dancers (aged 20.2 + 1.9 yr) in a full-time university undergraduate dance training program were asked to stand in first position for 10 seconds and then perform 10 repeats of a demi-plié exercise to a counted rhythm. Accelerometer records from the wrist, sacrum, knee and ankle were compared with the numerical scores from a professional dance instructor. The sacrum mounted sensor detected lateral tilts of the torso in dances with lower scores (Spearman’s rank correlation coefficient r = -0.64, p < 0.005). The 5RMS6 acceleration amplitude of wrist mounted sensor was linearly correlated to the movement scores (Spearman’s rank correlation coefficient r = 0.63, p < 0.005). The application of sacrum and wrist mounted sensors for biofeedback during dance training is a realistic, low cost option.
Reversible logic synthesis is an emerging research topic with different application areas like low-power CMOS design, quantum- and optical computing. The key motivation behind reversible logic synthesis is the optimization of the heat dissipation problem current architectures show, by reducing it to theoretically zero [2].
This report presents the implementation and evaluation of a computer vision task on a Field Programmable Gate Array (FPGA). As an experimental approach for an application-specific image-processing problem it provides reliable results to measure gained performance and precision compared with similar solutions on General Purpose Processor (GPP) architectures.
The project addresses the problem of detecting Binary Large OBjects (BLOBs) in a continuous video stream. For this problem a number of different solutions exist. But most of these are realized on GPP platforms, where resolution and processing speed define the performance barrier. With the opportunity of parallelization and performance abilities like in hardware, the application of FPGAs become interesting. This work belongs to the MI6 project from the Computer Vision research group of the University of Applied Sciences Bonn-Rhein-Sieg. It address the detection of the users position and orientation in relation to the virtual environment in an Immersion Square.
The goal is to develop a light emitting device, that points from the user towards the point of interest on the projection screen. The projected light dots are used to represent the user in the virtual environment. By detecting the light dots with video cameras, the idea is to interface the position and orientation of the relative position of the user interface. Fort that the laser dots need to be arranged in a unique pattern, which requires at least five points.[29] For a reliable estimation a robust computation of the BLOB's center-points is necessary.
This project has covered the development of a BLOB detection system on a FPGA platform. It detects binary spatially extended objects in a continuous video stream and computes their center points. The results are displayed to the user and where validated for their ground truth. The evaluation compares precision and performance gain against similar approaches on GPP platforms.
This report presents the implementation and evaluation of a computer vision problem on a Field Programmable Gate Array (FPGA). This work is based upon [5] where the feasibility of application specific image processing algorithms on a FPGA platform have been evaluated by experimental approaches. The results and conclusions of that previous work builds the starting point for the work, described in this report. The project results show considerable improvement of previous implementations in processing performance and precision. Different algorithms for detecting Binary Large OBjects (BLOBs) more precisely have been implemented. In addition, the set of input devices for acquiring image data has been extended by a Charge-Coupled Device (CCD) camera. The main goal of the designed system is to detect BLOBs in continuous video image material and compute their center points.
This work belongs to the MI6 project from the Computer Vision research group of the University of Applied Sciences Bonn-Rhein-Sieg1 . The intent is the invention of a passive tracking device for an immersive environment to improve user interaction and system usability. Therefore the detection of the users position and orientation in relation to the projection surface is required. For a reliable estimation a robust and fast computation of the BLOB's center-points is necessary. This project has covered the development of a BLOB detection system on an Altera DE2 Development and Education Board with a Cyclone II FPGA. It detects binary spatially extended objects in image material and computes their center points. Two different sources have been applied to provide image material for the processing. First, an analog composite video input, which can be attached to any compatible video device. Second, a five megapixel CCD camera, which is attached to the DE2 board. The results are transmitted on the serial interface of the DE2 board to a PC for validation of their ground truth and further processing. The evaluation compares precision and performance gain dependent on the applied computation methods and the input device, which is providing the image material.