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Blended Learning Set up of the Master Programme "Analysis and Design of Social Protection Systems"
(2017)
The master's programme "Analysis and Design of Social Protection Systems" is a newly designed programme. The international Master’s programme is aimed at students who wish to deal with social security systems and who are also interested in intercultural exchange. The on-campus and online phases provide students with the opportunity to develop an international network, while facilitating the combination of studies and professional engagement.
Impact of atmospheric aerosols on photovoltaic energy production - Scenario for the Sahel zone
(2017)
Photovoltaic (PV) energy is one option to serve the rising global energy need with low environmental impact. PV is of particular interest for local energy solutions in developing countries prone to high solar insolation. In order to assess the PV potential of prospective sites, combining knowledge of the atmospheric state modulating solar radiation and the PV performance is necessary. The present study discusses the PV power as function of atmospheric aerosols in the Sahel zone for clear-sky-days. Daily yields for a polycrystalline silicon PV module are reduced by up to 48 % depending on the climatologically-relevant aerosol abundances.
We present a new interface for interactive comparisons of more than two alternative documents in the context of a generative design system that uses generative data-flow networks defined via directed acyclic graphs. To better show differences between such networks, we emphasize added, deleted, (un)changed nodes and edges. We emphasize differences in the output as well as parameters using highlighting and enable post-hoc merging of the state of a parameter across a selected set of alternatives. To minimize visual clutter, we introduce new difference visualizations for selected nodes and alternatives using additive and subtractive encodings, which improve readability and keep visual clutter low. We analyzed similarities in networks from a set of alternative designs produced by architecture students and found that the number of similarities outweighs the differences, which motivates use of subtractive encoding. We ran a user study to evaluate the two main proposed difference visualization encodings and found that they are equally effective.
Simulating eye movements for virtual humans or avatars can improve social experiences in virtual reality (VR) games, especially when wearing head mounted displays. While other researchers have already demonstrated the importance of simulating meaningful eye movements, we compare three gaze models with different levels of fidelity regarding realism: (1) a base model with static fixation and saccadic movements, (2) a proposed simulation model that extends the saccadic model with gaze shifts based on a neural network, and (3) a user's real eye movements recorded by a proprietary eye tracker. Our between-groups design study with 42 subjects evaluates impact of eye movements on social VR user experience regarding perceived quality of communication and presence. The tasks include free conversation and two guessing games in a co-located setting. Results indicate that a high quality of communication in co-located VR can be achieved without using extended gaze behavior models besides saccadic simulation. Users might have to gain more experience with VR technology before being able to notice subtle details in gaze animation. In the future, remote VR collaboration involving different tasks requires further investigation.
Populating virtual worlds with intelligent agents can drastically improve a user's sense of presence. Applying these worlds to virtual training, simulations, or (serious) games, often requires multiple agents to be simulated in real time. The process of generating believable agent behavior starts with providing a plausible perception and attention process that is both efficient and controllable. We describe a conceptual framework for synthetic perception that specifically considers the mentioned requirements: plausibility, real-time performance, and controllability. A sample implementation will focus on sensing, attention, and memory to demonstrate the framework's capabilities in a real-time game engine scenario. A combination of dynamic geometric sensing and false coloring with static saliency information is provided to exemplify the collection of environmental stimuli. The subsequent attention process handles both bottom-up processing and task-oriented, top-down factors. Behavioral results can be influenced by controlling memory and attention The example case is demonstrated and discussed alongside future extensions.
Integration of Multi-modal Cues in Synthetic Attention Processes to Drive Virtual Agent Behavior
(2017)
Service robots performing complex tasks involving people in houses or public environments are becoming more and more common, and there is a huge interest from both the research and the industrial point of view. The RoCKIn@Home challenge has been designed to compare and evaluate different approaches and solutions to tasks related to the development of domestic and service robots. RoCKIn@Home competitions have been designed and executed according to the benchmarking methodology developed during the project and received very positive feedbacks from the participating teams. Tasks and functionality benchmarks are explained in detail.
RoCKIn@Work was focused on benchmarks in the domain of industrial robots. Both task and functionality benchmarks were derived from real world applications. All of them were part of a bigger user story painting the picture of a scaled down real world factory scenario. Elements used to build the testbed were chosen from common materials in modern manufacturing environments. Networked devices, machines controllable through a central software component, were also part of the testbed and introduced a dynamic component to the task benchmarks. Strict guidelines on data logging were imposed on participating teams to ensure gathered data could be automatically evaluated. This also had the positive effect that teams were made aware of the importance of data logging, not only during a competition but also during research as useful utility in their own laboratory. Tasks and functionality benchmarks are explained in detail, starting with their use case in industry, further detailing their execution and providing information on scoring and ranking mechanisms for the specific benchmark.
Access to affordable energy - for basic needs as well as for national economic development - is a crucial concern for developing countries. Access to modern and sustainable energy services in rural areas, where the majority of the population is living in poverty, is a particularly urgent challenge, and one which has been recognized as crucial within the global development agenda.
The current dominant development model, focused on achieving macro-economic growth, gives priority to large-scale or centralized energy infrastructures for national growth or for meeting the urban demand. Rural areas of poorer countries are often at a disadvantage in terms of access to all types of services – roads, health facilities, markets, information and clean water. The high cost of providing these services in remote areas has led to new approaches being tried, based on self-help and the private sector rather than traditional government-led solutions. The missing access to electricity is primarily the reason for the poor operational environment of entrepreneurship especially in rural areas of developing countries, which poses many barriers to their development and limits their competitiveness. Energy services for household, agriculture and production serve as best examples as sectors exposed to enable entrepreneurship by productive use of renewable energy.
This paper describes the line-up, the challenges and the outcome of a development project in rural Ethiopia to support entrepreneurship based on the usage of renewable energy, in this case mainly photo-voltaic technology. In particular, this study tries to show up key features which are required to enable sustainable energy access and foster implementation challenges of developed business models in practice. Based on this experience, the paper discusses implications and lessons learned for a further development.
The non-farm sector is critical for the socio-economic development of Ghana especially the rural poor. Literature suggest that people engage in non-farm enterprises as a way out of poverty or a survival strategy, perhaps as a substitute for the landless. This paper analyses the determinants of individual participation in non-farm enterprises and the intensity of participation. The paper uses EGC/ISSER Socio-Economic Panel Survey data collected in 2009. The paper estimated the determinants of participation using a probit model and then estimated the intensity of participation using a truncated regression model. The results indicate that majority of women (about 73%) are engaged in non-farm enterprises in rural Ghana. The study found that females tended to participate more in non-farm self-employment and are less likely to participate in non-farm wage employment. The results further showed that individual characteristics such as the gender of the individual, being head of a household, being the spouse of a household head, having formal education, age of the individual, having access to credit, possessing a mobile phone, per capita landing holding and ownership of livestock influenced the participation of individuals in self-and wage employment. Results from truncated regression model for self-employed enterprises showed that having access to mobile phones, owning more livestock and electricity are important in determining the intensity of participation in self-employed enterprises. For wage-employment, being a household head, spouse of household head, having access to mobile phone and owning more livestock increased the number of days working on wage employment. Education is relevant for employment in the non-farm sector especially wage-employment. Government should play a lead role in making formal education accessible to the rural people. Deliberate policies should focus on addressing critical factors such as access to credit, mobile phone, electricity and education which are relevant for increasing participation intensity in rural enterprises.
Over the past decades, growing trends in social media, e-literacy and globalisation have led to the increased use of electrical and electronic equipment (EEE) in offices, schools, homes, hospitals and other institutions. Although, there are more efforts at introducing diversity, innovation and increased use of EEE, there had been limited effort at managing the end?of?life of these electronic devices. Evidence from previous research showed that the management of the end of life of electronic waste is highly dominated by Micro, Small and Medium Sized Enterprises (MSMEs) in the informal sector who employ more crude technology in their operations. This exploratory study therefore, sought to examine the activities of corporate bodies and MSMEs (formal and informal) in the e-waste sector in the Accra and Kumasi Metropolitan Areas in Ghana. Data was collected via questionnaires and interview from randomly selected respondents in the two metropolises. Results reveal that even though corporate institutions import a lot of electrical and electronic equipment, they do not have any policies on disposal of the e-waste generated. Thus, a high percentage of the e-waste generated is processed by the informal sector. The implications of the results are that policy makers and other stakeholders should encourage MSMEs to formalize their activities, support investment and green business development as well as funding and training for MSMEs operating in the sector.
Media development cooperation has aimed for decades at enhancing free and independent media in developing countries as well as economies in transition. Within this field of activity, the concept of media viability has gained more and more attention in recent years. This is mainly due to a proposal of UNESCO`s intergovernmental Bureau of the International Programme for the Development of Communication (IPDC). The UNESCO, in partnership with DW Akademie, has drafted a list of indicators that delineate the influencing factors of media viability for media organizations in any given country (UNESCO 2015).
As a consequence of the novelty of the media viability concept, the state of scientific research is restricted. It is frequently focused on isolated case studies without providing a scientific basis for comparison. Empirical studies and comparative analyses are limited to certain media sectors such as the print market, as well as for journalism startups and spin-offs in developed economies.
In today’s business, culture plays a vital role or to a high degree influences the attitude, perception and decision making process of an individual. Culture is an unavoidable state of rules and regulations that defines people’s daily life in a particular environment or society. There are plenty examples of business failures or stagnation or failure of joint ventures, on account of the management's inability to recognize cross-cultural challenges and tackle them appropriately.
Entrepreneurship education serves a conduit for new venture creation as it provides the knowledge and skills needed to increase the self-efficacy of individuals to start and run new businesses and to grow existing ones. This study, therefore, sought to assess the relationship between the approaches to the teaching of entrepreneur-ship and entrepreneurial intention on a cohort of 292 respondents consisting of students who have studied entrepreneurship in three selected Universities. A structured questionnaire was used to obtain data randomly from students. The canonical correlation results indicate that education for and through entrepreneurship is the best approach to promoting entrepreneurial intensity among University students, if the aim of teaching entrepreneur-ship is to promote start-up activities. The findings provide valuable insights for institutions of higher learning and policy makers in Ghana with respect to the appropriate methodologies to be adopted in the teaching of entrepreneurship in our universities.
Small and Medium Enterprises (SMEs) are engine of economy both for developed and developing countries. They play a significant role in income generation, job creation, poverty reduction and reducing income inequality. In Burundi, key stakeholders such as policy-makers as well as other international and national actors have made more effort to develop the segment of SMEs. Indeed, many start-ups have been created but are however, exposed to several challenges in their business operations. This paper aimed at investigating main critical barriers to SMEs growth and development in Burundi. The research was based upon a sample survey of small firms in Burundi and 314 small enterprises were surveyed. Rural start-ups’ critical barriers identified are mainly poor management, lack of access to market flow, lack of working capital, inadequate qualified workforce and low selling prices. On the other hand, five severe obstacles for urban SMEs identified are insecurity, access to financing, macroeconomic situation, lack of customers and unfair competition. A better understanding of all these barriers that SMEs are facing is useful to set up best strategies susceptible to increase their growth.
Culture is at the core of any social, economic and business interactions and relationships. The way people perceive the culture of others influences their decision to collaborate socially, politically and economically with them. It is therefore, imperative students appreciate the dynamics of cross-cultural interactions and collaborations, since it exposes them to a wider view of the world. In doing this, it is important they (students) are allowed to explore as much as possible with little interference by their teachers. Using the project students went through real-life experience in a self-directed enquiry. In the process, they were taught to solve problems encountered during the learning process. The focus of the intercultural communication project was to understand how people from different cultures speak, interact and perceive others’ culture. It was found students innovate if allowed to explore a certain phenomenon on their own. Furthermore, face-to-face meetings can be arranged between people in the different countries can be arranged using these Web 2.0 tools. Based on the experience from the project, it was observed that the success of a collaborative international project depends on the understanding of the crosscultural dynamics of partners. For such collaborations, it is imperative to establish personal relationships, be flexible and adaptable to situations and change as well as being swift resolving potential conflict situation.
This study sought to determine the relationship between entrepreneurial education and youth employability and economic development in Kenya. A descriptive cross sectional design was used to collect data, with the main data collection instrument being a semi structured questionnaire. The population of the study comprised the micro, small and medium scale enterprises in Nairobi, Kenya. Out of the 100 questionnaires issued, 93 were completed and returned giving a response rate of 93%. Descriptive analysis (means and standard deviations ) and inferential analysis was used to analyze the data. Regression and correlation analysis was done to test the hypotheses. It was found that several indicators of entrepreneurial education had a significantly positive influence on youth employability. For example, entrepreneurial education enhances opportunity recognition as an indicator of entrepreneurial education was statistically significantly correlated with the statement that entrepreneurship endeavor is an employment alternative as an indicator of youth employability (r = 331**, P = 0.01). Similarly, the statement that entrepreneurial education sharpens competitiveness had a significantly positive influence on the statement that entrepreneurship endevour is an employment alternative (r =.313** P = 0.01). The overall model for entrepreneurial education and youth employability had an R Square value of 0.151, and an F value of 3.086, (p = 0.013 < 0.05), indicating that the influence is significant at the 0.05 level. The study found that most indicators of youth employability had a significantly positive correlation with indicators of economic development. It was found that there was a significant positive correlation between entrepreneurial education enhances new product and service development and entrepreneurial education reduces youth unemployment (r =0.304**, P = 0.01), while entrepreneurial education enhances new product and service development also has a positive correlation with entrepreneurial education reduces youth unemployment (.304** , P = 0.01). The overall model for youth employability and economic development had an R square value of .087 and F value of 2.103, p =0.87 > 0.05, indication that although youth employability is responsible for 8.7% of economic development, the effect is not statistically significant. The implication for this is that entrepreneurial education should be encouraged as a way of enhancing entrepreneurial thinking among the youth, so that they can use this to venture into self employment. However, this study did not find a significant direct link between youth employability and economic development, and this can only be implied. We suggest increased government support for entrepreneurship training and for closer industry university collaboration and partnerships in order to accelerate economic development.
A deployment of the Vehicle-2-Vehicle communication technology according to ETSI is in preparation in Europe. Currently, a policy for a necessary Public Key Infrastructure to enrol cryptographic keys and certificates for vehicles and infrastructure component is in discussion to enable an interoperable Vehicle-2-Vehicle communication. Vehicle-2-Vehicle communication means that vehicles periodically send Cooperative Awareness Messages. These messages contain the current geographic position, driving direction, speed, acceleration, and the current time of a vehicle. To protect privacy (location privacy, “speed privacy”) of vehicles and drivers ETSI provides a specific pseudonym concept. We show that the Vehicle-2-Vehicle communication can be misused by an attacker to plot a trace of sequent Cooperative Awareness Messages and to link this trace to a specific vehicle. Such a trace is non-disputable due to the cryptographic signing of the messages. So, the periodically sending of Cooperative Awareness Messages causes privacy problems even if the pseudonym concept is applied.
The development of fully automated vehicles is becoming more and more present in the social discussion. The image of fully automated cars is determined by automobile manufacturers and placed in the context of individual traffic. In contrast to fully autonomous private cars, fully automated public transport is already operating in some cities and is to be expanded in the future. Autonomous public transport offers great potential for the development and promotion of sustainable mobility concepts. However, the user acceptance is important for the enforcement and widespread use of these technical innovations. An online study on the acceptance of fully automated public transport based on quantitative data of a sample of N = 201 is presented. The results show a high level of familiarity with the topic and a very high level of overall intention to use fully automated public transport in the future.
Universities, Entrepreneurship and Enterprise Development in Africa – Conference Proceedings 2016
(2017)
These proceedings are the outcome of the 5th annual joint conference on “Universities Entrepreneurship and Enterprise Development in Africa” between the University of Nairobi, Kenya, the University of Cape Coast, Ghana, and Bonn-Rhein-Sieg University of Applied Sciences, Germany, held on 10-11 November 2016 on Campus Sankt Augustin, Bonn-Rhein-Sieg University of Applied Sciences.
Dare – Democracy and Science
(2017)
These times are very troubled ones. Not only do wars and political unrest seem to prevail in different regions of the world, but, corruption and fraud have reached an incredible dimension, too. It seems that societies have, to a large extent, lost values in which they had formerly believed in. These issues may be the background why at the moment Corporate Social Responsibility (CSR) as a voluntary commitment is discussed in public that intensively. However, one gets the impression that this rather often seems to be superficial. Therefore, it is time to do some in-depth research to identify whether there is real substance behind these discussions or not. Latin America is a big continent with a greater number of countries which are running through difficult times as to corruption and fraud. Consequently, the author studied the policy of the central employers association Consejo Empresarial de America Latina (CEAL) with respect to the role of CSR. On the basis of statements, news and results of studies being regularly published, conclusions were drawn to which extent social and environmental aspects, along the line of ISO 26000, are playing a relevant role.
In order to avoid a too narrow view of the issue, a holistic approach concerning the generalsituation of Latin America has been selected using parameters such as economic growth, increase of population, poverty, inequality, and the global responsibility for environment. Furthermore, apart from the central organization CEAL, regional and national institutions with a specific mission for spreading and implementing CSR and two communal projects were analyzed as well. The conclusion of the paper is that there are some CSR "lighthouses" but an urgent need exists to spread the idea of CSR more intensively across the continent. Corresponding recommendations about how to increase the relevance of CSR in Latin America are given at the end of the paper.
The combination of Software-Defined Networking (SDN) and Wireless Mesh Network (WMN) is challenging due to the different natures of both concepts. SDN describes networks with homogeneous, static and centralized controlled topologies. In contrast, a WMN is characterized by a dynamic and distributed network control, and adds new challenges with respect to time-critical operation. However, SDN and WMN are both associated with decreasing the operational costs for communication networks which is especially beneficial for internet provisioning in rural areas. This work surveys the current status for Software-Defined Wireless Mesh Networking. Besides a general overview in the domain of wireless SDN, this work focuses especially on different identified aspects: representing and controlling wireless interfaces, control-plane connection and topology discovery, modulation and coding, routing and load-balancing and client handling. A complete overview of surveyed solutions, open issues and new research directions is provided with regard to each aspect.
In January 2015, German trade and industry announced to support the national animal welfare initiative "Initiative Tierwohl" (ITW) which stands for a more sustainable and animal-friendly meat production. A web content analysis shows that the ITW initiative has been widely picked up and discussed by online media and that user comments are quite heterogeneous. The current study identifies different types of consumers through factor and cluster analysis and is based on an online survey as well as face-to-face interviews. According to our results, the identified consumer groups demonstrate a rather passive comment behaviour on the internet. In fact, the internet was hardly mentioned as an information source for meat production; consumers more frequently referred to brochures, leaflets and personal contacts with sales personnel.
Argentina substantially contributes to the global organic agriculture and food sector due to its large areas of organically managed agricultural land. However, most of the organic production is foreseen for export. Overall, food supply for the domestic organic market is hardly tapped. This study investigates the current importance of organic agriculture and food production as well as its consumption within the country. The novelty of the study also lies in the observation, documentation and analysis of latest stakeholder-driven developments towards organic agriculture and food. The publication allows to make the Argentinian organic market significantly more visible for the international audience.
Food losses occur for many reasons at all stages of supply chains for fruits, vegetables and potatoes. They cause immense economic, environmental and social costs – not only in developing countries but also in developed countries. According to the European Commission, about 90 million tonnes of food are wasted annually in Europe alone. However, particularly for the early stages of supply chains for fruits, vegetables and potatoes there is still a lack of reliable data. Thus, one objective of this study is to contribute to the quantification of food losses between field and retail, where the main focus is set on potatoes, apples, carrots, strawberries and asparagus. Furthermore, neither reasons why products are removed from the supply chains nor their alternative uses are fully examined yet. This is why, the study takes a look on those issues, too. Results are based on data from an online survey among producers of fruits, vegetables and potatoes in North-Rhine Westphalia, Germany and on interviews with producers and other supply chain experts. Findings suggest that the products’ size and form, their storage capabilities and food safety issues have big impacts on food losses. Despite a small sample size, these findings are in line with recent studies.
Infection Exposure Promotes ETV6-RUNX1 Precursor B-cell Leukemia via Impaired H3K4 Demethylases
(2017)
ETV6-RUNX1 is associated with the most common subtype of childhood leukemia. As few ETV6-RUNX1 carriers develop precursor B cell acute lymphocytic leukemia (pB-ALL), the underlying genetic basis for development of full-blown leukemia remains to be identified, but the appearance of leukemia cases in time-space clusters keeps infection as a potential causal factor. Here we present in vivo genetic evidence mechanistically connecting preleukemic ETV6-RUNX1 expression in hematopoetic stem cells/peripheral cells (HSC/PC) and postnatal infections for human-like pB-ALL. In our model, ETV6-RUNX1 conferred a low risk of developing pB-ALL after exposure to common pathogens, corroborating the low incidence observed in humans. Murine preleukemic ETV6-RUNX1 pro/preB cells showed high Rag1/2 expression, known for human ETV6-RUNX1 pB-ALL. Murine and human ETV6-RUNX1 pB-ALL revealed recurrent genomic alterations, with a relevant proportion affecting genes of the lysine demethylase (KDM) family. KDM5C loss-of-function resulted in increased levels of H3K4me3, which co-precipitated with RAG2 in a human cell line model, laying the molecular basis for recombination activity. We conclude that alterations of KDM family members represent a disease-driving mechanism and an explanation for RAG off-target cleavage observed in humans. Our results explain the genetic basis for clonal evolution of an ETV6-RUNX1 preleukemic clone to pB-ALL after infection exposure and offer the possibility of novel therapeutic approaches.
In order to help journalists investigate inside large audiovisual archives, as maintained by news broadcast agencies, the multimedia data must be indexed by text-based search engies. By automatically creating a transcript through automatic speech recognition (ASR), the spoken word becomes accessible to text search, and queries for keywords are made possible. But stil, important contextual information like the identity of the speaker is not captured. Especially when gathering original footage in the political domain, the identity of the speaker can be the most important query constraint, although this name may not be prominent in the words spoken. It is thus desireable to have this information provided explicitely to the search engine. To provide this information, the archive must be an alyzed by automatic Speaker Identification (SID). While this research topic has seen substantial gains in accuracy and robustness over last years, it has not yet established itself as a helpful, large-scale tool outside the research community. This thesis sets out to establish a workflow to provide automatic speaker identification. Its application is to help journalists searching on speeches given in the German parliament (Bundestag). This is a contribution to the News-Stream 3.0 project, a BMBF funded research project that addresses accessibility of various data sources for journalists.
OpenDaylight (ODL) is a commercial, collaborative, open-source platform to accelerate the adoption and innovation of Software Defined Networking (SDN) and Network Function Visualization. This paper describes the novel ODL architecture in a simplified way to grasp a better understanding of such architecture. ODL architecture intends to foster new innovation and accelerate adoption of programming the network. The innovation of Model-Driven Service Abstraction Layer (MD-SAL) in the architecture leads to developing models for automatic management and configuration of the networks. MD-SAL provides ODL with the ability to support any protocol talking to the network elements as well as any network application. The flexibility inherent in ODL architecture could enable ODL to shape the next generation networks.
Exosomes derived from human autologous conditioned serum are nanocarriers for IL-6 and TNF-alfa
(2017)
Solid-Phase Microextraction (SPME) is a very simple and efficient, solventless sample preparation method, invented by Pawliszyn and coworkers at the University of Waterloo (Canada) in 1989. This method has been widely used in different fields of analytical chemistry since its first applications to environmental and food analysis. SPME integrates sampling, extraction, concentration and sample introduction into a single solvent-free step. The method saves preparation time, disposal costs and can improve detection limits. It has been routinely used in combination with gas chromatography (GC) and gas chromatography/mass spectrometry (GC/MS) and successfully applied to a wide variety of ompounds, especially for the extraction of volatile and semi-volatile organic compounds from environmental, biological and food samples.
Since the last twenty years, SPME in headspace (HS) mode is used as a valuable sample preparation technique for identifying degradation products in polymers and for determination of rest monomers and other light-boiling substances in polymeric materials. For more than ten years, our laboratory has been involved in projects focused on the application of HS-SPME-GC/MS for the characterization of polymeric materials from many branches of manufacturing and building industries. This book chapter describes the application examples of this technique for identifying volatile organic compounds (VOCs), additives and degradation products in industrial plastics, rubber, and packaging materials.
Emotional communication is a key element of habilitation care of persons with dementia. It is, therefore, highly preferable for assistive robots that are used to supplement human care provided to persons with dementia, to possess the ability to recognize and respond to emotions expressed by those who are being cared-for. Facial expressions are one of the key modalities through which emotions are conveyed. This work focuses on computer vision-based recognition of facial expressions of emotions conveyed by the elderly.
Although there has been much work on automatic facial expression recognition, the algorithms have been experimentally validated primarily on young faces. The facial expressions on older faces has been totally excluded. This is due to the fact that the facial expression databases that were available and that have been used in facial expression recognition research so far do not contain images of facial expressions of people above the age of 65 years. To overcome this problem, we adopt a recently published database, namely, the FACES database, which was developed to address exactly the same problem in the area of human behavioural research. The FACES database contains 2052 images of six different facial expressions, with almost identical and systematic representation of the young, middle-aged and older age-groups.
In this work, we evaluate and compare the performance of two of the existing imagebased approaches for facial expression recognition, over a broad spectrum of age ranging from 19 to 80 years. The evaluated systems use Gabor filters and uniform local binary patterns (LBP) for feature extraction, and AdaBoost.MH with multi-threshold stump learner for expression classification. We have experimentally validated the hypotheses that facial expression recognition systems trained only on young faces perform poorly on middle-aged and older faces, and that such systems confuse ageing-related facial features on neutral faces with other expressions of emotions. We also identified that, among the three age-groups, the middle-aged group provides the best generalization performance across the entire age spectrum. The performance of the systems was also compared to the performance of humans in recognizing facial expressions of emotions. Some similarities were observed, such as, difficulty in recognizing the expressions on older faces, and difficulty in recognizing the expression of sadness.
The findings of our work establish the need for developing approaches for facial expression recognition that are robust to the effects of ageing on the face. The scientific results of our work can be used as a basis to guide future research in this direction.
Population ageing and growing prevalence of disability have resulted in a growing need for personal care and assistance. The insufficient supply of personal care workers and the rising costs of long-term care have turned this phenomenon into a greater social concern. This has resulted in a growing interest in assistive technology in general, and assistive robots in particular, as a means of substituting or supplementing the care provided by humans, and as a means of increasing the independence and overall quality of life of persons with special needs. Although many assistive robots have been developed in research labs world-wide, very few are commercially available. One of the reasons for this, is the cost. One way of optimising cost is to develop solutions that address specific needs of users. As a precursor to this, it is important to identify gaps between what the users need and what the technology (assistive robots) currently provides. This information is obtained through technology mapping.
The current literature lacks a mapping between user needs and assistive robots, at the level of individual systems. The user needs are not expressed in uniform terminology across studies, which makes comparison of results difficult. In this research work, we have illustrated the technology mapping of assistive robots using the International Classification of Functioning, Disability and Health (ICF). ICF provides standard terminology for expressing user needs in detail. Expressing the assistive functions of robots also in ICF terminology facilitates communication between different stakeholders (rehabilitation professionals, robotics researchers, etc.).
We also investigated existing taxonomies for assistive robots. It was observed that there is no widely accepted taxonomy for classifying assistive robots. However, there exists an international standard, ISO 9999, which classifies commercially available assistive products. The applicability of the latest revision of ISO 9999 standard for classifying mobility assistance robots has been studied. A partial classification of assistive robots based on ISO 9999 is suggested. The taxonomy and technology mapping are illustrated with the help of four robots that have the potential to provide mobility assistance. These are the SmartCane, the SmartWalker, MAid and Care-O-bot (R) 3. SmartCane, SmartWalker and MAid provide assistance by supporting physical movement. Care-O-bot (R) 3 provides assistance by reducing the need to move.
Recent work in image captioning and scene-segmentation has shown significant results in the context of scene-understanding. However, most of these developments have not been extrapolated to research areas such as robotics. In this work we review the current state-ofthe- art models, datasets and metrics in image captioning and scenesegmentation. We introduce an anomaly detection dataset for the purpose of robotic applications, and we present a deep learning architecture that describes and classifies anomalous situations. We report a METEOR score of 16.2 and a classification accuracy of 97 %.
Smart home systems change the way we experience the home. While there are established research fields within HCI for visualizing specific use cases of a smart home, studies targeting user demands on visualizations spanning across multiple use cases are rare. Especially, individual data-related demands pose a challenge for usable visualizations. To investigate potentials of an end-user development (EUD) approach for flexibly supporting such demands, we developed a smart home system featuring both pre-defined visualizations and a visualization creation tool. To evaluate our concept, we installed our prototype in 12 households as part of a Living Lab study. Results are based on three interview studies, a design workshop and system log data. We identified eight overarching interests in home data and show how participants used pre-defined visualizations to get an overview and the creation tool to not only address specific use cases but also to answer questions by creating temporary visualizations.
Smart home systems are becoming an integral feature of the emerging home IT market. Under this general term, products mainly address issues of security, energy savings and comfort. Comprehensive systems that cover several use cases are typically operated and managed via a unified dashboard. Unfortunately, research targeting user experience (UX) design for smart home interaction that spans several use cases or covering the entire system is scarce. Furthermore, existing comprehensive and user-centered longterm studies on challenges and needs throughout phases of information collection, installation and operation of smart home systems are technologically outdated. Our 18-month Living Lab study covering 14 households equipped with smart home technology provides insights on how to design for improving smart home appropriation. This includes a stronger sensibility for household practices during setup and configuration, flexible visualizations for evolving demands and an extension of smart home beyond the location.
Advances in computer graphics enable us to create digital images of astonishing complexity and realism. However, processing resources are still a limiting factor. Hence, many costly but desirable aspects of realism are often not accounted for, including global illumination, accurate depth of field and motion blur, spectral effects, etc. especially in real‐time rendering. At the same time, there is a strong trend towards more pixels per display due to larger displays, higher pixel densities or larger fields of view. Further observable trends in current display technology include more bits per pixel (high dynamic range, wider color gamut/fidelity), increasing refresh rates (better motion depiction), and an increasing number of displayed views per pixel (stereo, multi‐view, all the way to holographic or lightfield displays). These developments cause significant unsolved technical challenges due to aspects such as limited compute power and bandwidth. Fortunately, the human visual system has certain limitations, which mean that providing the highest possible visual quality is not always necessary. In this report, we present the key research and models that exploit the limitations of perception to tackle visual quality and workload alike. Moreover, we present the open problems and promising future research targeting the question of how we can minimize the effort to compute and display only the necessary pixels while still offering a user full visual experience.
The MAP-Elites algorithm produces a set of high-performing solutions that vary according to features defined by the user. This technique to 'illuminate' the problem space through the lens of chosen features has the potential to be a powerful tool for exploring design spaces, but is limited by the need for numerous evaluations. The Surrogate-Assisted Illumination (SAIL) algorithm, introduced here, integrates approximative models and intelligent sampling of the objective function to minimize the number of evaluations required by MAP-Elites.
The ability of SAIL to efficiently produce both accurate models and diverse high-performing solutions is illustrated on a 2D airfoil design problem. The search space is divided into bins, each holding a design with a different combination of features. In each bin SAIL produces a better performing solution than MAP-Elites, and requires several orders of magnitude fewer evaluations. The CMA-ES algorithm was used to produce an optimal design in each bin: with the same number of evaluations required by CMA-ES to find a near-optimal solution in a single bin, SAIL finds solutions of similar quality in every bin.
A new method for design space exploration and optimization, Surrogate-Assisted Illumination (SAIL), is presented. Inspired by robotics techniques designed to produce diverse repertoires of behaviors for use in damage recovery, SAIL produces diverse designs that vary according to features specified by the designer. By producing high-performing designs with varied combinations of user-defined features a map of the design space is created. This map illuminates the relationship between the chosen features and performance, and can aid designers in identifying promising design concepts. SAIL is designed for use with compu-tationally expensive design problems, such as fluid or structural dynamics, and integrates approximative models and intelligent sampling of the objective function to minimize the number of function evaluations required. On a 2D airfoil optimization problem SAIL is shown to produce hundreds of diverse designs which perform competitively with those found by state-of-the-art black box optimization. Its capabilities are further illustrated in a more expensive 3D aerodynamic optimization task.
Multiple myeloma is the second most common hematological malignancy. Despite all the progress made in treating multiple myeloma, it still remains an incurable disease. Patients are left with a median survival of 4-5 years. The combined treatment of multiple myeloma with histone deacetylase inhibitors and cytokine-induced killer cells provides a promising targeted treatment option for patients. This study investigated the impact of a combined treatment compared to treatment with histone deacetylase inhibitors. The experiments revealed that a treatment with histone deacetylase (HDAC) inhibitors could reduce cell viability to 59% for KMS 18 cell line and 46% for the U-266 cell line. The combined treatment led to a decrease of cell viability to 33% for KMS 18 and 27% for the U-266 cell line, thus showing a significantly better efficacy than the single treatment.
WiFi-based Long Distance (WiLD) networks have emerged as a promising alternative approach for Internet in rural areas. The main hardware components of these networks are commercial off-the-shelf WiFi radios and directional antennas. During our experiences with real-world WiLD networks, we encountered that interference among long-distance links is a major issue even with high gain directional antennas. In this work, we are providing an in-depth analysis of these interference effects by conducting simulations in ns-3. To closely match the real-world interference effects, we implemented a module to load radiation pattern of commonly used antennas. We analyze two different interference scenarios typically present as a part of larger networks. The results show that side-lobes of directional antennas significantly influence the throughput of long-distance WiFi links depending on the orientation. This work emphasizes that the usage of simple directional antenna models needs to be considered carefully.
This study contributes to the growing body of research concerning management consultancies by linking two previously disparate fields of study: (1) the examination of the effectiveness of consulting interventions and (2) the examination of the social processes that aim to create and legitimize the insights, knowledge and capabilities of management consultancies. We propose that consulting firms accumulate social authority in the course of pre-intervention discourse processes that is reflected in their reputation and celebrity. With respect to intervention, this social authority affects change recipients’ commitment to and compliance with the requirements of change implementation. We test the proposed relationships by conducting a measured variable path analysis of 117 change initiatives in German companies that were set up and implemented with the assistance of external consultancies. Our findings indicate that a consulting firm’s levels of both celebrity and reputation affect the change recipients’ commitment to proposed change strategies and thus, indirectly affect their behavioral compliance with the explicit requirements of change implementation.
Evolutionary illumination is a recent technique that allows producing many diverse, optimal solutions in a map of manually defined features. To support the large amount of objective function evaluations, surrogate model assistance was recently introduced. Illumination models need to represent many more, diverse optimal regions than classical surrogate models. In this PhD thesis, we propose to decompose the sample set, decreasing model complexity, by hierarchically segmenting the training set according to their coordinates in feature space. An ensemble of diverse models can then be trained to serve as a surrogate to illumination.
Neuroevolution methods evolve the weights of a neural network, and in some cases the topology, but little work has been done to analyze the effect of evolving the activation functions of individual nodes on network size, an important factor when training networks with a small number of samples. In this work we extend the neuroevolution algorithm NEAT to evolve the activation function of neurons in addition to the topology and weights of the network. The size and performance of networks produced using NEAT with uniform activation in all nodes, or homogenous networks, is compared to networks which contain a mixture of activation functions, or heterogenous networks. For a number of regression and classification benchmarks it is shown that, (1) qualitatively different activation functions lead to different results in homogeneous networks, (2) the heterogeneous version of NEAT is able to select well performing activation functions, (3) the produced heterogeneous networks are significantly smaller than homogeneous networks.
While executing actions, service robots may experience external faults because of insufficient knowledge about the actions' preconditions. The possibility of encountering such faults can be minimised if symbolic and geometric precondition models are combined into a representation that specifies how and where actions should be executed. This work investigates the problem of learning such action execution models and the manner in which those models can be generalised. In particular, we develop a template-based representation of execution models, which we call delta models, and describe how symbolic template representations and geometric success probability distributions can be combined for generalising the templates beyond the problem instances on which they are created. Our experimental analysis, which is performed with two physical robot platforms, shows that delta models can describe execution-specific knowledge reliably, thus serving as a viable model for avoiding the occurrence of external faults.
From video games to mobile augmented reality, 3D interaction is everywhere. But simply choosing to use 3D input or 3D displays isn't enough: 3D user interfaces (3D UIs) must be carefully designed for optimal user experience. 3D User Interfaces: Theory and Practice, Second Edition is today's most comprehensive primary reference to building outstanding 3D UIs. Four pioneers in 3D user interface research and practice have extensively expanded and updated this book, making it today's definitive source for all things related to state-of-the-art 3D interaction.
This paper describes the security mechanisms of several wireless building automation technologies, namely ZigBee, EnOcean, ZWave, KNX, FS20, and Home-Matic. It is shown that none of the technologies provides the necessary measure ofsecurity that should be expected in building automation systems. One of the conclusions drawn is that software embedded in systems that are build for a lifetime of twenty years or more needs to be updatable.
The knowledge of Software Features (SFs) is vital for software developers and requirements specialists during all software engineering phases: to understand and derive software requirements, to plan and prioritize implementation tasks, to update documentation, or to test whether the final product correctly implements the requested SF. In most software projects, SFs are managed in conjunction with other information such as bug reports, programming tasks, or refactoring tasks with the aid of Issue Tracking Systems (ITSs). Hence ITSs contains a variety of information that is only partly related to SFs. In practice, however, the usage of ITSs to store SFs comes with two major problems: (1) ITSs are neither designed nor used as documentation systems. Therefore, the data inside an ITS is often uncategorized and SF descriptions are concealed in rather lengthy. (2) Although an SF is often requested in a single sentence, related information can be scattered among many issues. E.g. implementation tasks related to an SF are often reported in additional issues. Hence, the detection of SFs in ITSs is complicated: a manual search for the SFs implies reading, understanding and exploiting the Natural Language (NL) in many issues in detail. This is cumbersome and labor intensive, especially if related information is spread over more than one issue. This thesis investigates whether SF detection can be supported automatically. First the problem is analyzed: (i) An empirical study shows that requests for important SFs reside in ITSs, making ITSs a good tar- get for SF detection. (ii) A second study identifies characteristics of the information and related NL in issues. These characteristics repre- sent opportunities as well as challenges for the automatic detection of SFs. Based on these problem studies, the Issue Tracking Software Feature Detection Method (ITSoFD), is proposed. The method has two main components and includes an approach to preprocess issues. Both components address one of the problems associated with storing SFs in ITSs. ITSoFD is validated in three solution studies: (I) An empirical study researches how NL that describes SFs can be detected with techniques from Natural Language Processing (NLP) and Machine Learning. Issues are parsed and different characteristics of the issue and its NL are extracted. These characteristics are used to clas- sify the issue’s content and identify SF description candidates, thereby approaching problem (1). (II) An empirical study researches how issues that carry information potentially related to an SF can be detected with techniques from NLP and Information Retrieval. Characteristics of the issue’s NL are utilized to create a traceability network vii of related issues, thereby approaching problem (2). (III) An empirical study researches how NL data in issues can be preprocessed using heuristics and hierarchical clustering. Code, stack traces, and other technical information is separated from NL. Heuristics are used to identify candidates for technical information and clustering improves the heuristic’s results. The technique can be applied to support components, I. and II.
p53 is a crucial regulator of cell response to DNA damage. MDM4 and MDM2 are the two main negative regulators of p53 activity. Upon DNA damage, their constraint is released and p53 becomes activated and exerts its safeguard function by arresting cell growth or by killing excessively damaged cells. Under these conditions, increasing data suggest that MDM4 and MDM2 play novel roles. In this respect, we recently published that MDM4 exerts a positive activity towards p53 mitochondrial apoptosis. We observed that a fraction of MDM4 stably localizes at the mitochondria where upon lethal stress conditions, promotes the mitochondrial localization of p53 phosphorylated at Ser46 (p53Ser46(P)) and facilitates its binding to BCL2, cytochrome C release and apoptosis. Most importantly, we observed a correlation of MDM4 expression with cisplatin-resistance in a group of human ovarian cancers suggesting that MDM4 proapoptotic activity may have in vivo relevance. Here, we discuss about these and some new findings and compare them with previous data trying to settle some apparent contradictions. In addition, this review discusses the potential relevance of our data to the field of human cancer.
Exploring Gridmap-based Interfaces for the Remote Control of UAVs under Bandwidth Limitations
(2017)
This book constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Smart Card Research and Advanced Applications, CARDIS 2016, held in Cannes, France, in November 2016. The 15 revised full papers presented in this book were carefully reviewed and selected from 29 submissions. The focus of the conference was on all aspects of the design, development, deployment, validation, and application of smart cards or smart personal devices.
The MAP-Elites algorithm produces a set of high-performing solutions that vary according to features defined by the user. This technique has the potential to be a powerful tool for design space exploration, but is limited by the need for numerous evaluations. The Surrogate-Assisted Illumination algorithm (SAIL), introduced here, integrates approximative models and intelligent sampling of the objective function to minimize the number of evaluations required by MAP-Elites.
The ability of SAIL to efficiently produce both accurate models and diverse high performing solutions is illustrated on a 2D airfoil design problem. The search space is divided into bins, each holding a design with a different combination of features. In each bin SAIL produces a better performing solution than MAP-Elites, and requires several orders of magnitude fewer evaluations. The CMA-ES algorithm was used to produce an optimal design in each bin: with the same number of evaluations required by CMA-ES to find a near-optimal solution in a single bin, SAIL finds solutions of similar quality in every bin.
RPSL meets lightning: A model-based approach to design space exploration of robot perception systems
(2017)
Tracelets and Specifications
(2017)
In the accompanying paper [1] the authors study a model of concurrent programs in terms of events and a dependence relation, i.e., a set of arrows, between them. There also two simplifying interface models are presented; they abstract in different ways from the intricate network of internal points and arrows of program components. This report supplements [1] by presenting full proofs for the properties of the interface models, in particular, that both models exhibit homomorphic behaviour w.r.t. sequential and concurrent composition. [1] B. Möller, C.A.R. Hoare, M.E. Müller, G. Struth: A discrete geometric model of concurrent program execution. In H. Zhu, J. Bowen: Proc. UTP 16. LNCS 10134. Springer 2017, 1-25
Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit
(2017)
(1) Background: The aim of the study was to use innovative sensor technology for non-destructive determination and prediction of optimum harvest date (OHD), using sweet cherry as a model fruit, based on different ripening parameters. (2) Methods: Two cherry varieties in two growing systems viz. field and polytunnel in two years were employed. The fruit quality parameters such as fruit weight and size proved unsuitable to detect OHD alone due to their dependence on crop load, climatic conditions, cultural practices, and season. Coloration during cherry ripening was characterized by a complete decline of green chlorophyll and saturation of the red anthocyanins, and was measured with a portable sensor viz. spectrometer 3-4 weeks before expected harvest until 2 weeks after harvest. (3) Results: Expressed as green NDVI (normalized differential vegetation index) and red NAI (normalized anthocyanin index) values, NAI increased from -0.5 (unripe) to +0.7 to +0.8 in mature fruit and remained at this saturation level with overripe fruits, irrespective of variety, treatment, and year. A model was developed to predict the OHD, which coincided with when NDVI reached and exceeded zero and the first derivative of NAI asymptotically approached zero. (4) Conclusion: The use of this sensor technology appears suitable for several cherry varieties and growing systems to predict the optimum harvest date.
A plethora of architectural patterns and elements for developing service-oriented applications can be gathered from the state-of-the-art. Most of these approaches are merely applicable for single-tenant applications. However, less methodical support is provided for scenarios, in which multiple different tenants with varying requirements access the same application stack concurrently. In order to fill this gap, both novel and existing architectural patterns, architectural elements, as well as fundamental design decisions must be considered and integrated into a framework that leverages the devel- opment of multi-tenant application. This paper addresses this demand and presents the SOAdapt framework. It promotes the development of adaptable multi-tenant applications based on a service-oriented architecture that is capable of incorporating specific requirements of new tenants in a flexible manner.
Systemunterstützung für wissensintensive Geschäftsprozesse – Konzepte und Implementierungsansätze
(2017)
A trace of the execution of a concurrent object-oriented program can be displayed in two-dimensions as a diagram of a non-metric finite geometry. The actions of a programs are represented by points, its objects and threads by vertical lines, its transactions by horizontal lines, its communications and resource sharing by sloping arrows, and its partial traces by rectangular figures.
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.