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This paper presents the outcomes of an exploratory field study that examined the social impact of an ICT-based suite of exergames for people with dementia and their caregivers. Qualitative data was collected over a period of 8 months, during which time we studied the daily life of 14 people with dementia and their informal and professional caregivers. We focus on the experiential aspects of the system and examine its social impact when integrated into the daily routines of both people with dementia themselves and their professional and family caregivers. Our findings indicate that relatives were able to regain leisure time, whilst people with dementia were able to recapture certain aspects of their social and daily activities that might otherwise have been lost to them. Results suggest that the system enhanced social-interaction, invigorated relationships, and improved the empowerment of people with dementia and their caregivers to face daily challenges.
Poland
(2018)
Poland belongs to the first wave of pension reformers in Central and Eastern Europe. The Polish pension reform of the late 1990s can serve as a case study for the challenges faced when implementing a radical paradigmatic pension reform towards a privatized DC scheme. This report analyses the background of the original reform, discusses its political, social and economic impact and explains the reasons for later reform reversals. The report stresses that the two re-reform waves, which took place in 2011 and 2013, were mainly driven by fiscal considerations. Since the current system maintains the DC scheme applied to both public and private tiers, the recent reversal of privatization will not improve benefit levels.
Social protection measures require sustainable financing – creating and maintaining adequate fiscal space at the national level. Good governance of social protection at all stages – planning policies, policy reforms, and implementation – requires continuous monitoring of its performance and finances, including long-term projections and simulations of cost and benefits of different social protection programs and overall social protection systems. These projections and simulations should take into account demographic trends, including demographic ageing.
New approaches in securing more sustainable urban food futures: case from Cologne-Bonn region
(2018)
ICT has traditionally been a hostile territory for women. In information societies, this implies a drastic reduction in opportunities and autonomy for women. In emergent economies, the situation is even worse due to women’s subordinate status in society and little research regarding the intersection between gender and the digital divide. Such is the case in Latin America. In light of this, the purpose of this essay is to introduce a first comprehensive review of the few studies made in Latin America, against the background of the history of women’s digital exclusion. Based on a review of literature, we identify the main causes for women’s digital exclusion in the region and talk about the prospects for development of gender policies in the BRICS countries (Brazil, Russia, India, China and South Africa). We conclude that what this group of countries may achieve in regard to gender equality, will mark the future of the world. The aim of this essay is to make a call for the creation of inter - national research networks and propose the BRICS as host for these efforts, as they combine characteristics that will make them leaders of change in vast regions.
This Business English course in entrepreneurship goes beyond communicative language instruction and offers a course designed to introduce students to innovative thinking, entrepreneurship and sustainable business practices. About 120 students in their first year are enrolled as part of the required foreign language module in Business Management (B.Sc.). Each week students learn new concepts and terminology in sustainable business practices while applying the material in a simulation task-based course using English as a lingua franca. It prepares students to work in an international context while offering online components for autonomous learning. This 12-14 week course is designed in a student-centered and blended learning format with a flipped classroom approach. Through a grant from the German Federal Ministry of Education and Research the “work&study project” will offer additional online materials by developing new educational apps to enhance autonomous language learning and making the app content available under the Creative Commons license. The research project focuses on offering new learning environments to enhance the opportunities for non-traditional students enrolled at Bonn-Rhein-Sieg University of Applied Sciences. This paper will focus on the development of the first apps and results of the first testing phase. It shows how game-based learning and elements of gamification were added for educational purposes to enhance teaching and learning processes that were already well established.
In presence of conflicting or ambiguous visual cues in complex scenes, performing 3D selection and manipulation tasks can be challenging. To improve motor planning and coordination, we explore audio-tactile cues to inform the user about the presence of objects in hand proximity, e.g., to avoid unwanted object penetrations. We do so through a novel glove-based tactile interface, enhanced by audio cues. Through two user studies, we illustrate that proximity guidance cues improve spatial awareness, hand motions, and collision avoidance behaviors, and show how proximity cues in combination with collision and friction cues can significantly improve performance.
We present a novel forearm-and-glove tactile interface that can enhance 3D interaction by guiding hand motor planning and coordination. In particular, we aim to improve hand motion and pose actions related to selection and manipulation tasks. Through our user studies, we illustrate how tactile patterns can guide the user, by triggering hand pose and motion changes, for example to grasp (select) and manipulate (move) an object. We discuss the potential and limitations of the interface, and outline future work.
Entering the work envelope of an industrial robot can lead to severe injury from collisions with moving parts of the system. Conventional safety mechanisms therefore mostly restrict access to the robot using physical barriers such as walls and fences or non-contact protective devices including light curtains and laser scanners. As none of these mechanisms applies to human-robot-collaboration (HRC), a concept in which human and machine complement one another by working hand in hand, there is a rising need for safe and reliable detection of human body parts amidst background clutter. For this application camera-based systems are typically well suited. Still, safety concerns remain, owing to possible detection failures caused by environmental occlusion, extraneous light or other adverse imaging conditions. While ultrasonic proximity sensing can provide physical diversity to the system, it does not yet allow to reliably distinguish relevant objects from background objects.This work investigates a new approach to detecting relevant objects and human body parts based on acoustic holography. The approach is experimentally validated using a low-cost application-specific ultrasonic sensor system created from micro-electromechanical systems (MEMS). The presented results show that this system far outperforms conventional proximity sensors in terms of lateral imaging resolution and thus allows for more intelligent muting processes without compromising the safety of people working close to the robot. Based upon this work, a next step could be the development of a multimodal sensor systems to safeguard workers who collaborate with robots using the described ultrasonic sensor system.
This paper documents the reversal of pension privatization and the reforms that took place in the 1990s and 2000s in Poland. The report analyses the political economy of different reform proposals, and the characteristics of the new pension system, including laws enacted, coverage, benefit adequacy, financing and contribution rates, governance and social security administration, social dialogue, positive impacts and other key issues of Poland’s pension system.
Almost unnoticed by the e-learning community, the underlying technology of the WWW is undergoing massive technological changes on all levels these days. In this paper we draw the attention to the emerging game changer and discuss the consequences for online learning. In our e-learning project "Work & Study", funded by the German Federal Ministry of Education and Research, we have experimented with several new technological approaches such as Mobile First, Responsive Design, Mobile Apps, Web Components, Client-side Components, Progressive Web Apps, Course Apps, e-books, and web sockets for real time collaboration and report about the results and consequences for online learning practice. The modular web is emerging where e-learning units are composed from and delivered by universally embeddable web components.
In this paper we propose an architecture to integrate classical planning and real autonomous mobile robots. We start by providing with a high level description of all necessary components to set the goals, generate plans and execute them on real robots and monitor the outcome of their actions. At the core of our method and to deal with execution issues we code the agent actions with automatas. We prove the flexibility of the system by testing on two different domains: industrial (Basic Transportation Test) and domestic (General Purpose Service Robot) in the context of the international RoboCup competition. Additionally we benchmark the scalability of the planning system in two domains on a set of planning problems with increasing complexity. The proposed framework is open source1 and can be easily extended.
Design and Analysis of an OFDM-Based Orthogonal Chaotic Vector Shift Keying Communication System
(2018)
We propose a new non-coherent multicarrier spread-spectrum system that combines orthogonal chaotic vector shift keying (OCVSK) and orthogonal frequency-division multiplexing (OFDM). The system enhances OCVSK by sending multiple groups of information sequences with the same orthogonal chaotic vector reference sequences over the selected subcarriers. Each group carries M information bits and is separated from other groups by orthogonal chaotic reference signals. We derive the information rate enhancement (IRE) and the energy saving enhancement (ESE) factors as well as the bit error rate theory of OFDM-OCVSK under additive white Gaussian noise and multipath Rayleigh fading channels and compare the results with conventional OCVSK systems. For large group numbers, the results show that the IRE and ESE factors approachM×100% andM/(M+1)×100%, respectively, and thus outperform OCVSK systems. The complexity analysis of the proposed scheme as compared with OFDM-DCSK shows a significant reduction in the number of complex multiplications required.
Once aberrantly activated, the Wnt/βcatenin pathway may result in uncontrolled proliferation and eventually cancer. Efforts to counter and inhibit this pathway are mainly directed against βcatenin, as it serves a role on the cytoplasm and the nucleus. In addition, speciallygenerated lymphocytes are recruited for the purpose of treating liver cancer. Peripheral blood mononuclear lymphocytes are expanded by the timely addition of interferon γ, interleukin (IL)1β, IL2 and anticluster of differentiation 3 antibody. The resulting cells are called cytokineinduced killer (CIK) cells. The present study utilised these cells and combine them with drugs inhibiting the Wnt pathway in order to examine whether this resulted in an improvement in the killing ability of CIK cells against liver cancer cells. Drugs including ethacrynic acid (EA) and ciclopirox olamine (CPX) were determined to be suitable candidates, as determined by previous studies. Drugs were administered on their own and combined with CIK cells and then a cell viability assay was performed. These results suggest that EAtreated cells demonstrated apoptosis and were significantly affected compared with untreated cells. Unlike EA, CPX killed normal and cancerous cells even at low concentrations. Subsequent to combining EA with CIK cells, the potency of killing was increased and a greater number of cells died, which proves a synergistic action. In summary, EA may be used as an antihepatocellular carcinoma drug, while CPX possesses a high toxicity to cancerous as well as to normal cells. It was proposed that EA should be integrated into present therapeutic methods for cancer.
In recent years, a variety of methods have been introduced to exploit the decrease in visual acuity of peripheral vision, known as foveated rendering. As more and more computationally involved shading is requested and display resolutions increase, maintaining low latencies is challenging when rendering in a virtual reality context. Here, foveated rendering is a promising approach for reducing the number of shaded samples. However, besides the reduction of the visual acuity, the eye is an optical system, filtering radiance through lenses. The lenses create depth-of-field (DoF) effects when accommodated to objects at varying distances. The central idea of this article is to exploit these effects as a filtering method to conceal rendering artifacts. To showcase the potential of such filters, we present a foveated rendering system, tightly integrated with a gaze-contingent DoF filter. Besides presenting benchmarks of the DoF and rendering pipeline, we carried out a perceptual study, showing that rendering quality is rated almost on par with full rendering when using DoF in our foveated mode, while shaded samples are reduced by more than 69%.
General Chair Message
(2018)
The design of an efficient digital circuit in term of low-power has become a very challenging issue. For this reason, low-power digital circuit design is a topic addressed in electrical and computer engineering curricula, but it also requires practical experiments in a laboratory. This PhD research investigates a novel approach, the low-power design laboratory system by developing a new technical and pedagogical system. The low-power design laboratory system is composed of two types of laboratories: the on-site (hands-on) laboratory and the remote laboratory. It has been developed at the Bonn-Rhine-Sieg University of Applied Sciences to teach low-power techniques in the laboratory. Additionally, this thesis contributes a suggestion on how the learning objectives can be complemented by developing a remote system in order to improve the teaching process of the low-power digital circuit design. This laboratory system enables online experiments that can be performed using physical instruments and obtaining real data via the internet. The laboratory experiments use a Field Programmable Gate Array (FPGA) as a design platform for circuit implementation by students and use image processing as an application for teaching low-power techniques.
This thesis presents the instructions for the low-power design experiments which use a top-down hierarchical design methodology. The engineering student designs his/her algorithm with a high level of abstraction and the experimental results are obtained and measured at a low level (hardware) so that more information is available to correctly estimate the power dissipation such as specification, latency, thermal effect, and technology used. Power dissipation of the digital system is influenced by specification, design, technology used, as well as operating temperature. Digital circuit designers can observe the most influential factors in power dissipation during the laboratory exercises in the on-site system and then use the remote system to supplement investigating the other factors. Furthermore, the remote system has obvious benefits such as developing learning outcomes, facilitating new teaching methods, reducing costs and maintenance, cost-saving by reducing the numbers of instructors, saving instructor time and simplifying their tasks, facilitating equipment sharing, improving reliability, and finally providing flexibility of usage the laboratories.
Influence of design of extrusion blow molding (EBM) in terms of extrusion direction set-up and draw ratio as well as process conditions (mold temperature) on storage modulus of high density polyethylene EBM containers was analyzed with dynamic mechanical analysis. All three parameters - mold temperature, flow direction and draw ratio - are statistically significant and lead to relative and absolute evaluation of storage modulus. Furthermore, flow induced changes in crystallinity was analyzed by differential scanning calorimetry. Obtained data on deformation properties can be employed for more sophisticated finite element simulations with the aim to reach more sustainable extrusion blow molding production.
3D user interfaces for virtual reality and games: 3D selection, manipulation, and spatial navigation
(2018)
In this course, we will take a detailed look at different topics in the field of 3D user interfaces (3DUIs) for Virtual Reality and Gaming. With the advent of Augmented and Virtual Reality in numerous application areas, the need and interest in more effective interfaces becomes prevalent, among others driven forward by improved technologies, increasing application complexity and user experience requirements. Within this course, we highlight key issues in the design of diverse 3DUIs by looking closely into both simple and advanced 3D selection/manipulation and spatial navigation interface design topics. These topics are highly relevant, as they form the basis for most 3DUI-driven application, yet also can cause major issues (performance, usability, experience. motion sickness) when not designed properly as they can be difficult to handle. Within this course, we build on top of a general understanding of 3DUIs to discuss typical pitfalls by looking closely at theoretical and practical aspects of selection, manipulation, and navigation and highlight guidelines for their use.
Digitisation has brought a major upheaval to the mobility sector, and in the future, self-driving cars will probably be one of the transport modes. This study extends transport and user acceptance research by analysing in greater depth how the new modes of autonomous private cars, autonomous carsharing and autonomous taxis fit into the existing traffic mix from today's perspective. It focuses on accounting for relative added value. For this purpose, user preference theory was used as a base for an online survey (n=172) on the relative added value of the new autonomous traffic modes. Results show that users see advantages in the autonomous modes for driving comfort and time utilization whereas, in comparison to conventional cars, in many other areas – especially in terms of driving pleasure and control – they see no advantages or even relative disadvantages. Compared to public transport, the autonomous modes offer added values in almost all characteristics. This analysis at the partwor th level provides a more detailed explanation for user acceptance of automated driving.
After replanting apple (Malus domestica Borkh.) on the same site severe growth suppressions, and a decline in yield and fruit quality are observed in all apple producing areas worldwide. The causes of this complex phenomenon, called apple replant disease (ARD), are only poorly understood up to now which is in part due to inconsistencies in terms and methodologies. Therefore we suggest the following definition for ARD: ARD describes a harmfully disturbed physiological and morphological reaction of apple plants to soils that faced alterations in their (micro-) biome due to the previous apple cultures. The underlying interactions likely have multiple causes that extend beyond common analytical tools in microbial ecology. They are influenced by soil properties, faunal vectors, and trophic cascades, with genotype-specific effects on plant secondary metabolism, particularly phytoalexin biosynthesis. Yet, emerging tools allow to unravel the soil and rhizosphere (micro-) biome, to characterize alterations of habitat quality, and to decipher the plant reactions. Thereby, deep insights into the reactions taking place at the root rhizosphere interface will be gained. Counteractions are suggested, taking into account that culture management should emphasize on improving soil microbial and faunal diversity as well as habitat quality rather than focus on soil disinfection.
For many different applications, current information about the bandwidth-related metrics of the utilized connection is very useful as they directly impact the performance of throughput sensitive applications such as streaming servers, IPTV and VoIP applications. In literature, several tools have been proposed to estimate major bandwidth-related metrics such as capacity, available bandwidth and achievable throughput. The vast majority of these tools fall into one of Packet Pair (PP), Variable Packet Size (VPS), Self-Loading of Periodic Streams (SLoPS) or Throughput approaches. In this study, seven popular bandwidth estimation tools including nettimer, pathrate, pathchar, pchar, clink, pathload and iperf belonging to these four well-known estimation techniques are presented and experimentally evaluated in a controlled testbed environment. Differently from the rest of studies in literature, all tools have been uniformly classified and evaluated according to an objective and sophisticated classification and evaluation scheme. The performance comparison of the tools incorporates not only the estimation accuracy but also the probing time and overhead caused.
This policy brief investigates the costs of child poverty in the Balkans, including deprivation in terms of education, health, and social mobility. It then lays out the potential of social protection, most notably in terms of building resilence and fostering development. Set against recent case studies from around the world, including Cambodia and Uganda, the brief gives policy recommendations on various critical issues including transfer schemes, transformative measures, and (alternative) care for children with disabilities.
This policy brief is part of a wider research project entitled ‘Building the Economic Case for Investments in Social Protection’. The research aims at demonstrating the potential impacts of social protection on inclusive growth. The project is a collaborative effort between the Maastricht Graduate School of Governance at the University of Maastricht and United Nations University-MERIT, NL; the Global Development Institute at the University of Manchester, UK; the School of Social Science at the University of Makerere, Uganda; and the Expanding Social Protection Programme of the Ugandan Ministry of Gender, Labour and Social Development. This project is part of the research agenda of the Knowledge Platform Inclusive Development Policies and funded by the Ministry of Foreign Affairs of the Netherlands through the NWO-WOTRO programme.
This policy brief is part of a wider research project entitled ‘Building the Economic Case for Investments in Social Protection’. The research aims at demonstrating the potential impacts of social protection on inclusive growth. The project is a collaborative effort between the Maastricht Graduate School of Governance at the University of Maastricht and United Nations University-MERIT, NL; the Global Development Institute at the University of Manchester, UK; the School of Social Science at the University of Makerere, Uganda; and the Expanding Social Protection Programme of the Ugandan Ministry of Gender, Labour and Social Development. This project is part of the research agenda of the Knowledge Platform Inclusive Development Policies and funded by the Ministry of Foreign Affairs of the Netherlands through the NWO-WOTRO programme.
Daryoush Daniel Vaziri illustrates that the use of mixed methods designs may support the induction of more subtle and complete theories about older adults’ use of technologies for the support of active and healthy aging. The results show that older adults’ social contexts and environments considerably affect their perspectives, practices and attitudes with respect to health, quality of life, well-being and technology use for active and healthy aging support. Results were collected with older adults aged 60+ as well as relevant secondary stakeholders like caregivers, policy makers or health insurance companies.
Large, high-resolution displays are highly suitable for creation of digital environments for co-located collaborative task solving. Yet, placing multiple users in a shared environment may increase the risk of interferences, thus causing mental discomfort and decreasing efficiency of the team. To mitigate interferences coordination strategies and techniques were introduced. However, in a mixed-focus collaboration scenarios users switch now and again between loosely and tightly collaboration, therefore different coordination techniques might be required depending on the current collaboration state of team members. For that, systems have to be able to recognize collaboration states as well as transitions between them to ensure a proper adjustment of the coordination strategy. Previous studies on group behavior during collaboration in front of large displays investigated solely collaborative coupling states, not transitions between them though. To address this gap, we conducted a study with 12 participant dyads in front of a tiled display and let them solve two tasks in two different conditions (focus and overview). We looked into group dynamics and categorized transitions by means of changes in proximity, verbal communication, visual attention, visual interface, and gestures. The findings can be valuable for user interface design and development of group behavior models.
Adoption of Modern Maize Varieties in India: Insights Based on Expert Elicitation Methodology
(2018)
Design optimization techniques are often used at the beginning of the design process to explore the space of possible designs. In these domains illumination algorithms, such as MAP-Elites, are promising alternatives to classic optimization algorithms because they produce diverse, high-quality solutions in a single run, instead of only a single near-optimal solution. Unfortunately, these algorithms currently require a large number of function evaluations, limiting their applicability. In this article we introduce a new illumination algorithm, Surrogate-Assisted Illumination (SAIL), that leverages surrogate modeling techniques to create a map of the design space according to user-defined features while minimizing the number of fitness evaluations. On a two-dimensional airfoil optimization problem SAIL produces hundreds of diverse but high-performing designs with several orders of magnitude fewer evaluations than MAP-Elites or CMA-ES. We demonstrate that SAIL is also capable of producing maps of high-performing designs in realistic three-dimensional aerodynamic tasks with an accurate flow simulation. Data-efficient design exploration with SAIL can help designers understand what is possible, beyond what is optimal, by considering more than pure objective-based optimization.
Telecollaborating and communicating in online contexts using English as a Lingua Franca (ELF) requires students to develop multiple literacies in addition to foreign language skills and intercultural communicative competence. This chapter looks at the intersection of technology and teaching ELF, examining mutual contributions of technologies, more specifically Web 2.0, and ELF to each other, and the challenges in designing and implementing collaboration projects across cultures. Moreover, it looks at how the development of digital competencies in ELF (DELF) can be enhanced through the implementation of Web 2.0 mediated intercultural dialogues. The detail of the research design including internet tools used, participants and tasks are also discussed. Data analysis points to a positive attitude towards telecollaboration, also providing confirmation of some of the problems identified in theoretical framework, such as different levels of personal engagement.
Shared Autonomous Vehicles: Potentials for a Sustainable Mobility and Risks of Unintended Effects
(2018)
Automated and connected cars could significantly reduce congestion and emissions through a more efficient flow of traffic and a reduction in the number of vehicles. An increase in demand for driving with autonomous vehicles is also conceivable due to higher comfort and improved quality of time using driverless cars. So far, empirical evidence supporting this hypothesis is missing. To analyze the influence of autonomous driving on mobility behavior and to uncover user preferences, which serve as an indicator for future travel mode choices, we conducted an online survey with a paired comparison of current and future travel modes with 302 German participants. The results do not confirm the hypothesis that ownership will become an outdated model in the future. Instead they suggest that private cars, whether traditional or fully automated, will remain the preferred travel mode. At the same time, carsharing will benefit from full automation more than private cars. However, findings indicate that the growth of carsharing will mainly be at the expense of public transport, showing that more effort should be placed in making public transportation more attractive if sustainable mobility is to be developed.
The increasing complexity of tasks that are required to be executed by robots demands higher reliability of robotic platforms. For this, it is crucial for robot developers to consider fault diagnosis. In this study, a general non-intrusive fault diagnosis system for robotic platforms is proposed. A mini-PC is non-intrusively attached to a robot that is used to detect and diagnose faults. The health data and diagnosis produced by the mini-PC is then standardized and transmitted to a remote-PC. A storage device is also attached to the mini-PC for data logging of health data in case of loss of communication with the remote-PC. In this study, a hybrid fault diagnosis method is compared to consistency-based diagnosis (CBD), and CBD is selected to be deployed on the system. The proposed system is modular and can be deployed on different robotic platforms with minimum setup.
Robot deployment in realistic dynamic environments is a challenging problem despite the fact that robots can be quite skilled at a large number of isolated tasks. One reason for this is that robots are rarely equipped with powerful introspection capabilities, which means that they cannot always deal with failures in a reasonable manner; in addition, manual diagnosis is often a tedious task that requires technicians to have a considerable set of robotics skills.
Robot deployment in realistic environments is challenging despite the fact that robots can be quite skilled at a large number of isolated tasks. One reason for this is that robots are rarely equipped with powerful introspection capabilities, which means that they cannot always deal with failures in an acceptable manner; in addition, manual diagnosis is often a tedious task that requires technicians to have a considerable set of robotics skills. In this paper, we discuss our ongoing efforts to address some of these problems. In particular, we (i) present our early efforts at developing a robotic black box and consider some factors that complicate its design, (ii) explain our component and system monitoring concept, and (iii) describe the necessity for remote monitoring and experimentation as well as our initial attempts at performing those. Our preliminary work opens a range of promising directions for making robots more usable and reliable in practice.
Pyrolysis–Gas Chromatography
(2018)
The methodology of analytical pyrolysis-GC/MS has been known for several years, but is seldom used in research laboratories and process control in the chemical industry. This is due to the relative difficulty of interpreting the identified pyrolysis products as well as the variety of them. This book contains full identification of several classes of polymers/copolymers and biopolymers that can be very helpful to the user. In addition, the practical applications can encourage analytical chemists and engineers to use the techniques explored in this volume.
The structure and the functions of various types of pyrolyzers and the results of the pyrolysis–gas chromatographic–mass spectrometric identification of synthetic polymers/copolymers and biopolymers at 700°C are described. Practical applications of these techniques are also included, detailing the analysis of microplastics, failure analysis in the automotive industry and solutions for technological problems.
Surrogate-assistance approaches have long been used in computationally expensive domains to improve the data-efficiency of optimization algorithms. Neuroevolution, however, has so far resisted the application of these techniques because it requires the surrogate model to make fitness predictions based on variable topologies, instead of a vector of parameters. Our main insight is that we can sidestep this problem by using kernel-based surrogate models, which require only the definition of a distance measure between individuals. Our second insight is that the well-established Neuroevolution of Augmenting Topologies (NEAT) algorithm provides a computationally efficient distance measure between dissimilar networks in the form of "compatibility distance", initially designed to maintain topological diversity. Combining these two ideas, we introduce a surrogate-assisted neuroevolution algorithm that combines NEAT and a surrogate model built using a compatibility distance kernel. We demonstrate the data-efficiency of this new algorithm on the low dimensional cart-pole swing-up problem, as well as the higher dimensional half-cheetah running task. In both tasks the surrogate-assisted variant achieves the same or better results with several times fewer function evaluations as the original NEAT.
Improving the Performance of Parallel SpMV Operations on NUMA Systems with Adaptive Load Balancing
(2018)
For a parallel Sparse Matrix Vector Multiply (SpMV) on a multiprocessor, rather simple and efficient work distributions often produce good results. In cases where this is not true, adaptive load balancing can improve the balance and performance. This paper introduces a low overhead framework for adaptive load balancing of parallel SpMV operations. It uses statistical filters to gather relevant runtime performance data and detects an imbalance situation. Three different algorithms were compared that adaptively balance the load with high quality and low overhead. Results show that for sparse matrices, where the adaptive load balancing was enabled, an average speedup of 1.15 (regarding the total execution time) could be achieved with our best algorithm over 4 different matrix formats and two different NUMA systems.
Background: Local injection of autologous conditioned serum (ACS) is a well-known therapy for inflammatory diseases (IDs). While patients’ blood is incubated to generate ACS (with subsequent centrifugation), immune cells produce high amounts of growth factors and cytokines. This include, amongst others, interleukin-1 receptor antagonist (IL-1ra), interleukins 6 and 10, tumour necrosis factor alpha (TNF-α) and transforming growth factor beta 1 (TGF-β1). The aim of this study was to analyse exosomes release into ACS as well as their cytokine cargo.
Estimation of Prediction Uncertainty for Semantic Scene Labeling Using Bayesian Approximation
(2018)
With the advancement in technology, autonomous and assisted driving are close to being reality. A key component of such systems is the understanding of the surrounding environment. This understanding about the environment can be attained by performing semantic labeling of the driving scenes. Existing deep learning based models have been developed over the years that outperform classical image processing algorithms for the task of semantic labeling. However, the existing models only produce semantic predictions and do not provide a measure of uncertainty about the predictions. Hence, this work focuses on developing a deep learning based semantic labeling model that can produce semantic predictions and their corresponding uncertainties. Autonomous driving needs a real-time operating model, however the Full Resolution Residual Network (FRRN) [4] architecture, which is found as the best performing architecture during literature search, is not able to satisfy this condition. Hence, a small network, similar to FRRN, has been developed and used in this work. Based on the work of [13], the developed network is then extended by adding dropout layers and the dropouts are used during testing to perform approximate Bayesian inference. The existing works on uncertainties, do not have quantitative metrics to evaluate the quality of uncertainties estimated by a model. Hence, the area under curve (AUC) of the receiver operating characteristic (ROC) curves is proposed and used as an evaluation metric in this work. Further, a comparative analysis about the influence of dropout layer position, drop probability and the number of samples, on the quality of uncertainty estimation is performed. Finally, based on the insights gained from the analysis, a model with optimal configuration of dropout is developed. It is then evaluated on the Cityscape dataset and shown to be outperforming the baseline model with an AUC-ROC of about 90%, while the latter having AUC-ROC of about 80%.
Persons with disabilities have much lower employment rates than the population as a whole and are at a significantly higher risk of living in poverty (OECD, 2011, pp. 50-56 and WHO, 2011, pp. 237-239). However, many of the barriers people with disabilities face, with regards to labor market reintegration, are in fact avoidable. There has for quite some time been evidence that differences in employment and wages, between disabled and non-disabled workers, can only to a limited extent be explained by differences in human capital endowments and productivity (Kidd, Sloane, & Ferko, 2000). Instead, factors such as the absence of access to education and training, and the lack of financial assistance provided are actually significant drivers of labor market exclusion (OECD, 2009, p.15; WHO, 2011, p.239).
This book is about how computer systems might be designed to serve their users rather better. It deals with how to study the natural behaviour of users to see how computer systems might best help them, and how one might also involve them in the design of computer systems that will assist them in their everyday practices.
Large, high-resolution displays demonstrated their effectiveness in lab settings for cognitively demanding tasks in single user and collaborative scenarios. The effectiveness is mostly reached through inherent displays' properties - large display real estate and high resolution - that allow for visualization of complex datasets, and support of group work and embodied interaction. To raise users' efficiency, however, more sophisticated user support in the form of advanced user interfaces might be needed. For that we need profound understanding of how large, tiled displays impact users work and behavior. We need to extract behavioral patterns for different tasks and data types. This paper reports on study results of how users, while working collaboratively, process spatially fixed items on large, tiled displays. The results revealed a recurrent pattern showing that users prefer to process documents column wise rather than row wise or erratic.
Preleukemic clones carrying BCR-ABLp190 oncogenic lesions are found in neonatal cord blood, where the majority of preleukemic carriers do not convert into precursor B-cell acute lymphoblastic leukemia (pB-ALL). However, the critical question of how these preleukemic cells transform into pB-ALL remains undefined. Here we model a BCR-ABLp190 preleukemic state and show that limiting BCR-ABLp190 expression to hematopoietic stem/progenitor cells (HS/PC) in mice (Sca1-BCR-ABLp190) causes pB-ALL at low penetrance, which resembles the human disease. pB-ALL blast cells were BCR-ABL-negative and transcriptionally similar to pro-B/pre-B cells, suggesting disease onset upon reduced Pax5 functionality. Consistent with this, double Sca1-BCR-ABLp190+Pax5+/- mice developed pB-ALL with shorter latencies, 90% incidence, and accumulation of genomic alterations in the remaining wild-type Pax5 allele. Mechanistically, the Pax5-deficient leukemic pro-B cells exhibited a metabolic switch towards increased glucose utilization and energy metabolism. Transcriptome analysis revealed that metabolic genes (IDH1, G6PC3, GAPDH, PGK1, MYC, ENO1, ACO1) were upregulated in Pax5-deficient leukemic cells, and a similar metabolic signature could be observed in human leukemia. Our studies unveil the first in vivo evidence that the combination between Sca1-BCR-ABLp190 and metabolic reprogramming imposed by reduced Pax5 expression is sufficient for pB-ALL development. These findings might help to prevent conversion of BCR-ABLp190 preleukemic cells.
Companies investing in the occupied Palestinian territories are faced with a dilemma. Undoubtedly, the creation of jobs helps to put young Palestinians to work. Experience shows that especially young males are less likely to radicalise and commit crimes when having an occupation. However, negative press coverage due to the disputed status of the territory can force companies to withdraw. CSR activities can help to demonstrate that a company has a genuine interest in its employees and community at large. Our article looks into one particular case of an Israeli company that had to withdraw their operation due to public pressure, mainly Western media. We give recommendations how such failure could have been avoided by using the right kind of CSR activities that address the needs of the Palestinians.
Transition point prediction in a multicomponent lattice Boltzmann model: Forcing scheme dependencies
(2018)
As a result of ageing societies, the prevalence of dementia, and accordingly the need of care is increasing rapidly. Here, the use of ICT-based technologies may facilitate and promote a self-sustaining life-style for people with dementia and their caregivers. The presented poster describes early findings from the project MobiAssist and outlines the ICT-based training system. The system aims to increase the physical and cognitive capabilities of people with dementia, relief the caregivers and improve wellbeing of involved parties.
Speech understanding is a fundamental feature for many applications focused on human-robot interaction. Although many techniques and several services for speech recognition and natural language understanding have been developed in the last years, specific implementation and validation on domestic service robots have not been performed. In this paper, we describe the implementation and the results of a functional benchmark for speech understanding in service robotics that has been developed and tested in the context of different robot competitions: RoboCup@Home, RoCKIn@Home and within the European Robotics League on Service Robots. Different approaches used by the teams in the competitions are presented and the evaluation results obtained in the competitions are discussed.
Dementia not only affects the cognitive capabilities, especially memory and orientation, but also physical capabilities, which are associated with a decrease of physical activities. Here, ICT can play a major role to improve health, quality of life and wellbeing in older adults suffering from dementia and related stakeholders, such as relatives, professional and informal caregivers. The aim of the presented system is to increase physical and cognitive capabilities of people with dementia and their caregivers to support them in daily life activities, reduce the strain of the caregivers and improve both their wellbeing.
For the last 20 years, solid-phase microextraction (SPME) in headspace (HS) mode has been used as a valuable sample preparation technique for identifying degradation products in polymers and the determination of residual monomers and other light-boiling substances in polymeric materials. For more than 10 years, our laboratory has been involved in projects focused on the application of HS-SPME-gas chromatography–mass spectrometry (GC–MS) for the characterization of polymeric materials from many branches of manufacturing and building industries. This article describes the application of this technique for identifying volatile organic compounds (VOCs), additives, and degradation products in industrial rubber, car labeling reflection foil, and bone cement materials. The obtained analytical results were then used for troubleshooting and remedial action of the technological processes as well as for the health protection of producers and users.