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This work presents the preliminary research towards developing an adaptive tool for fault detection and diagnosis of distributed robotic systems, using explainable machine learning methods. Autonomous robots are complex systems that require high reliability in order to operate in different environments. Even more so, when considering distributed robotic systems, the task of fault detection and diagnosis becomes exponentially difficult.
To diagnose systems, models representing the behaviour under investigation need to be developed, and with distributed robotic systems generating large amount of data, machine learning becomes an attractive method of modelling especially because of its high performance. However, with current day methods such as artificial neural networks (ANNs), the issue of explainability arises where learnt models lack the ability to give explainable reasons behind their decisions.
This paper presents current trends in methods for data collection from distributed systems, inductive logic programming (ILP); an explainable machine learning method, and fault detection and diagnosis.
Risk-based authentication (RBA) is an adaptive security measure to strengthen password-based authentication. RBA monitors additional implicit features during password entry such as device or geolocation information, and requests additional authentication factors if a certain risk level is detected. RBA is recommended by the NIST digital identity guidelines, is used by several large online services, and offers protection against security risks such as password database leaks, credential stuffing, insecure passwords and large-scale guessing attacks. Despite its relevance, the procedures used by RBA-instrumented online services are currently not disclosed. Consequently, there is little scientific research about RBA, slowing down progress and deeper understanding, making it harder for end users to understand the security provided by the services they use and trust, and hindering the widespread adoption of RBA.
In this paper, with a series of studies on eight popular online services, we (i) analyze which features and combinations/classifiers are used and are useful in practical instances, (ii) develop a framework and a methodology to measure RBA in the wild, and (iii) survey and discuss the differences in the user interface for RBA. Following this, our work provides a first deeper understanding of practical RBA deployments and helps fostering further research in this direction.
Kenya, like all other developing countries in the world, is faced with the task of working strategically towards the achievement of the Sustained Development Goals (SDGs) 2030. These goals whose due date of accomplishment coincides with those of the national development blueprint, namely, the Kenya Vision 2030, have become a major focus of attention in the country. Conferences, workshops, and seminars are organized throughout the country on regular bases by joint multiplicity of organizations to address modalities of ensuring a timely achievement of SDGs in the country. Universities either individually or jointly are working towards this same target. More specifically, there are great areas of concern or priority areas that the country is focusing on as a strategic focus towards the achievement of the Kenya Vision 2030 and SDGs 2030. These strategic areas of focus have been isolated and declared by the President of the Republic of Kenya, His Excellency Uhuru Kenyatta, as the country’s “big four priority areas”, namely, affordable housing, affordable health care, food security, and manufacturing as a grandiose effort towards achievement of the SDGs, Kenya Vision 2030 as well as job and wealth creation. Similarly, Mount Kenya University’s top management established the Graduate Enterprise Academy (GEA) in 2013 under the direct Patronage of the university’s Founder with the primary aim of assisting graduates to be job and wealth creators rather than being job seekers. So far, over twenty start-ups are running throughout the country under Graduate Enterprise Academy (GEA). Incidentally, although the Graduate Enterprise Academy’s diverse areas of focus extend beyond the President of Kenya’s “Big Four” to include ICT and creative arts, among others, there are justifiable cases to indicate that GEA’s activities are also in support of the national “Big Four” agenda. This paper gives an exposition of different start-ups under MKU’s Graduate Enterprise Academy and are show-cased as evidence of MKU’s support towards the achievement of the national “Big Four” agenda. The paper covers a part of an ongoing program through desk-top analyses of reports, with an objective of show-casing MKU’s contribution to the national agenda through the Graduate Enterprise Academy for possible scale - up.
Die Globalisierung führt zu immer komplexeren, für die Einzelnen kaum nachvollziehbaren Wertschöpfungsketten in der Lebensmittelindustrie. Zugleich eröffnet die Digitalisierung neue Möglichkeiten, Informationen entlang der Kette zu sammeln, und so mehr Transparenz und Vertrauen für den Verbraucherbeziehungsweise die Verbraucherin zu schaffen. Jedoch finden Verbraucherinformations-Apps wie fTRACE bisher nur eine geringe Verbreitung. Daher haben wir in einer qualitativen Studie mit 16 Teilnehmer/-innen Bedürfnisse und Nutzungshürden von Verbraucher/-innen im Zusammenhang mit Verbraucherinformations-Apps analysiert. Es zeigt sich, dass das Vertrauen in die Informationen, sowie der einfache Zugang dazu für Verbraucher/-innen zentral sind. Durch die gut sichtbare Bereitstellung der Informationen am Point-of-Sale, sowie der automatisierten Informationsversorgung z. B. mittels digitaler Kassenzettel in Kombination mit weiteren Verbraucher-Services kann die Bekanntheit und Akzeptanz von Rückverfolgbarkeitssystemen weiter gesteigert werden.
Stakeholder-Analyse zum Einsatz IIoT-basierter Frischeinformationen in der Lebensmittelindustrie
(2019)
Eine Herausforderung bei der Implementierung des industriellen Internet of Things (IIoT) besteht darin, Mehrwerte in Wertschöpfungsketten zu identifizieren, um darauf aufbauend Lösungen nutzerzentriert zu gestalten. Dieser Beitrag stellt das Forschungsprojekt FreshIndex vor, bei dem diese Herausforderung durch eine Kombination aus Stakeholder-Analyse und User-Centered-Design-Methoden adressiert wurde. Ziel des Projekts ist es, eine IIoT-basierte Lösung zum Monitoring der Kühlkette in der Lebensmittelindustrie zu entwickeln. Hierzu ist es wichtig zu wissen, welche Nutzer/-innen mit den Daten in Berührung kommen und welche Erfahrungen, Fähigkeiten, Anforderungen und Wünsche sie mitbringen. Die Berücksichtigung dieser Aspekte ist relevant für den Erfolg der Konzeption, Implementierung und des Betriebs eines IIoT-Systems. So können nützliche und handhabbare Produktideen generiert und Anwendungen gestaltet werden, die von Mitarbeiter/-innen und Konsument/-innen angenommen werden. IIoT schließt somit die lokale Verwendbarkeit von Daten entlang der Wertschöpfungskette ein und beschränkt sich nicht auf zentrale Verfügbarkeit von Daten.
The design of self-driving cars is one of the most exciting and ambitious challenges of our days and every day, new research work is published. In order to give an orientation, this article will present an overview of various methods used to study the human side of autonomous driving. Simplifying roughly, you can distinguish between design science-oriented methods (such as Research through Design, Wizard of Oz or driving simulator ) and behavioral science methods (such as survey, interview, and observation). We show how these methods are adopted in the context of autonomous driving research and dis-cuss their strengths and weaknesses. Due to the complexity of the topic, we will show that mixed method approaches will be suitable to explore the impact of autonomous driving on different levels: the individual, the social interaction and society.
The alternative use of travel time is one of the widely discussed benefits of driverless cars. We therefore conducted 14 co-design sessions to examine how people manage their time, to determine how they perceive the value of time in driverless cars and to derive design implications. Our findings suggest that driverless mobility will affect both people’s use of travel time as well as their time management in general. The participants repeatedly stated the desire of completing tasks while traveling to save time for activities that are normally neglected in their everyday life. Using travel time efficiently requires using car space efficiently, too. We found out that the design concept of tiny houses could serve as common design pattern to deal with the limited space within cars and support diverse needs.
Towards self-explaining social robots. Verbal explanation strategies for a needs-based architecture
(2019)
In order to establish long-term relationships with users, social companion robots and their behaviors need to be comprehensible. Purely reactive behavior such as answering questions or following commands can be readily interpreted by users. However, the robot's proactive behaviors, included in order to increase liveliness and improve the user experience, often raise a need for explanation. In this paper, we provide a concept to produce accessible “why-explanations” for the goal-directed behavior an autonomous, lively robot might produce. To this end we present an architecture that provides reasons for behaviors in terms of comprehensible needs and strategies of the robot, and we propose a model for generating different kinds of explanations.
Namibia’s hunting industry is increasingly threatened by animal rightists and opponent groups whose adversarial mindset is mostly based on emotion orientated information. The fatal consequences if closing hunting tourism in a country like Namibia are expounded in this study by critically investigating the input of well-regulated hunting tourism towards conservation in Namibia. Different factors have to be taken into consideration, regarding the country’s attributes that differ significantly from other countries and their methods to achieve successful conservation management strategies. By conducting an in-depth interview with Mr. Volker Grellmann and by obtaining secondary data from local authorities and organizations, the current research investigates how well-regulated hunting tourism in Namibia is an important part of biodiversity conservation. The results outline that hunting tourism is crucial for the value of wildlife and yields for wildlife to have a greater benefit than livestock and crop farming in Namibia. Likewise, the country takes care of their valuable natural recourse. As a result, natural habitats are induced, and subsequently a steeply growing number of wildlife was recorded over the last 50 years in Namibia. Among others hunting tourism favors the development of rural areas and yields incentives to fight poaching and the illegal trade of wild animal products.
Energy Profiles of the Ring Puckering of Cyclopentane, Methylcyclopentane and Ethylcyclopentane
(2019)
Application developers constitute an important part of a digital platform’s ecosystem. Knowledge about psychological processes that drive developer behavior in platform ecosystems is scarce. We build on the lead userness construct which comprises two dimensions, trend leadership and high expected benefits from a solution, to explain how developers’ innovative work behavior (IWB) is stimulated. We employ an efficiencyoriented and a social-political perspective to investigate the relationship between lead userness and IWB. The efficiency-oriented view resonates well with the expected benefit dimension of lead userness, while the social-political view might be interpreted as a reflection of trend leadership. Using structural equation modeling, we test our model with a sample of over 400 developers from three platform ecosystems. We find that lead userness is indirectly associated with IWB and the performance-enhancing view to be the stronger predictor of IWB. Finally, we unravel differences between paid and unpaid app developers in platform ecosystems.
Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews ofstatic scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path traced results, but with a greatly reduced computational complexity allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.
Tell Your Robot What To Do: Evaluation of Natural Language Models for Robot Command Processing
(2019)
The use of natural language to indicate robot tasks is a convenient way to command robots. As a result, several models and approaches capable of understanding robot commands have been developed, which however complicates the choice of a suitable model for a given scenario. In this work, we present a comparative analysis and benchmarking of four natural language understanding models - Mbot, Rasa, LU4R, and ECG. We particularly evaluate the performance of the models to understand domestic service robot commands by recognizing the actions and any complementary information in them in three use cases: the RoboCup@Home General Purpose Service Robot (GPSR) category 1 contest, GPSR category 2, and hospital logistics in the context of the ROPOD project.
Digital transformation in Higher Education and Science is a mission-critical demand to prepare educational institutions for their future competition on the international market. In many cases, the digitization goes along with the search for and acquisition of new software. For easily exchangeable software, wrong product decisions, in the worst case, lead to calculable financial losses. However, if a planned software requires a lot of technological adjustments and is to be applied as central component of a business- and/or security-critical environment, wrong decisions during the software acquisition process might lead to hardly calculable damage. Questions arising are how to decide for a product and how many resources should be invested for the acquisition process.
We planned to apply a commercial Business Support System, which should replace the currently used in-house developed software. Our goals were the increase of our university’s level of data security, to ease the interaction between stakeholders, to eliminate media discontinuities, to improve the process management and transparency, and to reduce the execution time of automated processes. Alongside with the introduction of the electronic case file, our agenda stipulates the digitization (and automation) of administrative university processes, especially, but not limited to, the student self-service and the administrative student life cycle. Usual tools and practices, commonly applied to (simple) software acquisition, failed in our scenario.
With the case study introduced in this paper, we address all persons, involved within software acquisition processes: From our experiences, we strongly recommend to place greater value on an exhaustively completed acquisition process, than on short-termed economic advantages.
The Learning Culture Survey (LCS) is a questionnaire-based research, investigating students’ perceptions of and expectations towards Higher Education (HE). The aim of this survey is to improve our understanding about the sources of cultural conflicts in educational scenarios. This understanding, shell help us to predict potential conflict situations and develop supportive measures.
After three years of development, the LCS was initialized in 2010 in South Korea and Germany. During the following years, the investigations were extended to further countries. The results, on the one hand, provided insights about the cultural context of HE in general and on the other hand, about specific (national / regional) characteristics of learners in HE. Most issues targeted with the questionnaire were directly linked to value systems. Thus, we expected from the beginning that the collected data would keep valid over longer periods of time. However, we had no evidence regarding the actual persistence of learning culture. For a study, designed to being implemented on a global scope and providing input for further applications, persistence is a basic condition to justify related investigations.
To answer the question on persistence, we repeated the LCS in our university every four years, between 2010 to 2018/19. Besides a small number of slight changes, explainable out of their situational context, the overall results kept consistent over the investigated years. In this paper, after an introduction of the LCS’ concept, setting and its general results from the past years, we present the insights from our most recently finalized longitudinal study on learning culture.
This paper stresses the importance of entrepreneurship education towards enhancing sustainable development in Kenya. The problems facing the country ranging from high rate of poverty, youth and graduate unemployment; overdependence on foreign goods and technology.
This paper therefore argues that entrepreneurship education will equip the students with the skills with which to not only be self-reliant, but to become wealth creators. The intervention level of entrepreneurship education has been at tertiary institutions and universities. This paper argues that attitudes and values are acquired at formative stage in life. Based on literature review of the models that have been used and yielded positive results, this paper proposes an innovative approach to the teaching of entrepreneurship education that is inclusive of pre-school, primary, secondary, tertiary and university levels. This paper explores the “Mully Model of Applied Entrepreneurship Teaching” as a case study, using interviews, surveys and reviewing relevant MCF data. The organization’s success factors within the Kenyan context are discussed.
The paper also recommended that educational programs at all levels of education should be made relevant to provide the youth the needed entrepreneurial skills. Further, it recommends that experiential learning methodologies be emphasized in the delivery of entrepreneurship education.
Quantifying Interference in WiLD Networks using Topography Data and Realistic Antenna Patterns
(2019)
Avoiding possible interference is a key aspect to maximize the performance in Wi-Fi based Long Distance networks. In this paper we quantify self-induced interference based on data derived from our testbed and match the findings against simulations. By enhancing current simulation models with two key elements we significantly reduce the deviation between testbed and simulation: the usage of detailed antenna patterns compared to the cone model and propagation modeling enhanced by license-free topography data. Based on the gathered data we discuss several possible optimization approaches such as physical separation of local radios, tuning the sensitivity of the transmitter and using centralized compared to distributed channel assignment algorithms. While our testbed is based on 5 GHz Wi-Fi, we briefly discuss the possible impact of our results to other frequency bands.
Beyond HCI and CSCW: Challenges and Useful Practices Towards a Human-Centred Vision of AI and IA
(2019)
This research was conducted to determine the relationship between entrepreneurship educations, venture intention on venture creation among entrepreneurial graduate in Kenya focusing on selected universities in Kenya. The study was grounded on the economic entrepreneurship theory, an attitude-based view on entrepreneurship education and resource-based theory. This research embraced a cross-sectional descriptive survey design. Study population was 2500 student taking entrepreneurship course in various universities of whom a sample of 345 students was chosen using purposive and simple random sampling technique. The study used both primary and secondary data. Statistical Package for Social Sciences (SPSS Version 21) was used to analyse quantitative date. The findings of the study revealed that entrepreneurial education had a noteworthy influence on venture creation (r= 0. 512, p = .001<0.05, t= 10.904) increase in entrepreneurial education would lead to significant increase in venture creation. The study revealed that entrepreneurial training has significance influence in venture creation among graduate as indicated by β1=-0.670, p=0.002<0.05, t= 10.304. Study established that increase in entrepreneurial orientation would lead to increase in venture creation among graduates by a factor of 0.519 with P value of 0.002 (r =0.519, P=0.03< 0.05). The research conclusion was that entrepreneurial knowledge acquisition, entrepreneurial training and entrepreneurial orientation combined have important and positive relationship with venture creation among the graduates.
The link between universities and the industry has been of concern both locally as well as globally for a long time, for the obvious reason that it is perceived to enhance organizational performance. The gap between universities and the industry has been widening in developing countries leading to lost opportunities for joint research, product development and job creation. Marketing and entrepreneurship could play a pivotal role in reversing the weakened linkages by building mutual relationship and strengthening bonds between universities and industry. This study sought to examine the role of marketing and entrepreneurship as important tools for enhancing the university industry linkages. The study sought to determine the aspects of marketing and entrepreneurship that have the highest influence on enhancing the university industry linkages. It considered the nexus of entrepreneurship and marketing exemplified by the attributes of innovativeness, creativity, risk taking; proactive orientation and value creation as crucial for creating, nurturing and developing sustained linkages between universities and industry. The study targeted 150 small and medium sized enterprises in Nairobi City County, out of which 143 responded, giving a response rate of 95 %. Data was collected using structured questionnaire administered to managers of small and medium sized enterprises engaged in manufacturing, retail, banking and hospitals. Survey data collected from small and medium enterprises will be analyzed through descriptive statistics including mean scores and standard deviation. We will test our hypothesis through regression analysis. The study found that marketing practices especially those focused on the product, promotion and distribution were key in enhancing University industry linkage. With regards to entrepreneurial orientation, risk taking, and creativity indicators were found to be more important than innovation in enhancing university-industry linkages.
Data-Driven Robot Fault Detection and Diagnosis Using Generative Models: A Modified SFDD Algorithm
(2019)
This paper presents a modification of the data-driven sensor-based fault detection and diagnosis (SFDD) algorithm for online robot monitoring. Our version of the algorithm uses a collection of generative models, in particular restricted Boltzmann machines, each of which represents the distribution of sliding window correlations between a pair of correlated measurements. We use such models in a residual generation scheme, where high residuals generate conflict sets that are then used in a subsequent diagnosis step. As a proof of concept, the framework is evaluated on a mobile logistics robot for the problem of recognising disconnected wheels, such that the evaluation demonstrates the feasibility of the framework (on the faulty data set, the models obtained 88.6% precision and 75.6% recall rates), but also shows that the monitoring results are influenced by the choice of distribution model and the model parameters as a whole.
When developing robot functionalities, finite state machines are commonly used due to their straightforward semantics and simple implementation. State machines are also a natural implementation choice when designing robot experiments, as they generally lead to reproducible program execution. In practice, the implementation of state machines can lead to significant code repetition and may necessitate unnecessary code interaction when reparameterisation is required. In this paper, we present a small Python library that allows state machines to be specified, configured, and dynamically created using a minimal domain-specific language. We illustrate the use of the library in three different use cases - scenario definition in the context of the RoboCup@Home competition, experiment design in the context of the ROPOD project, as well as specification transfer between robots.
For robots acting - and failing - in everyday environments, a predictable behaviour representation is important so that it can be utilised for failure analysis, recovery, and subsequent improvement. Learning from demonstration combined with dynamic motion primitives is one commonly used technique for creating models that are easy to analyse and interpret; however, mobile manipulators complicate such models since they need the ability to synchronise arm and base motions for performing purposeful tasks. In this paper, we analyse dynamic motion primitives in the context of a mobile manipulator - a Toyota Human Support Robot (HSR)- and introduce a small extension of dynamic motion primitives that makes it possible to perform whole body motion with a mobile manipulator. We then present an extensive set of experiments in which our robot was grasping various everyday objects in a domestic environment, where a sequence of object detection, pose estimation, and manipulation was required for successfully completing the task. Our experiments demonstrate the feasibility of the proposed whole body motion framework for everyday object manipulation, but also illustrate the necessity for highly adaptive manipulation strategies that make better use of a robot's perceptual capabilities.
Opportunities for Sustainable Mobility: Re-thinking Eco-feedback from a Citizen's Perspective
(2019)
In developed nations, a growing emphasis is being placed on the promotion of sustainable behaviours amongst individuals, or ‘citizen-consumers’. In HCI, various eco-feedback tools have been designed as persuasive instruments, with a strong normative appeal geared to encouraging citizens to conduct a more sustainable mobility. However, many critiques have been formulated regarding this ‘paternalistic’ stance. In this paper, we switched the perspective from a designer’s to a citizen’s point of view and explored how people would use eco-feedback tools to support sustainable mobility in their city. In the study, we conducted 14 interviews with citizens who had used eco-feedback previously. The findings indicate new starting points that could inform future eco-feedback tools. These encompass: (1) better information regarding how sustainable mobility is measured and monitored; (2) respect for individual mobility situations and preferences; and (3) the scope for participation and the sharing of responsibility between citizens and municipal city services.
Background & Objective: Due to the policy goals for sustainable energy production, renewable energy plants such as photovoltaics are increasingly in use. The energy production from solar radiation depends strongly on atmospheric conditions. As the weather mostly changes, electrical power generation fluctuates, making technical planning and control of power grids to a complex problem. Due to used materials (semiconductors e.g. silicon, gallium arsenide, cadmium telluride) the photovoltaic cells are spectrally selective. It means that only radiation of certain wavelengths converts into electrical energy. A material property called spectral response characterizes a certain degree of conversion of solar radiation into the electric current for each wavelength of solar light.
Innovation has been touted to be the central catalyst of entrepreneurship. This view has dominated research in start-ups as well as small and medium enterprises. Therefore, the relationship between innovation and firm performance has been a subject of interest to many researchers and policy makers. Through a longitudinal approach, this study investigated the influence of product innovation on the performance of Haco Tiger Brands, a medium sized fast-moving consumer goods (FMCG) company in Kenya’s East Africa market. The study looked at the product innovation activities within the company for a period of 7 years for a total of 35 products across the five major brand categories of the company. Using a secondary data capture form, data on sales revenues for both the company and innovated products for the past 7 years was obtained. Data on the innovated products launch time and type of innovation was also obtained. Using time series and linear regression analysis, the results indicate that the total company sales revenues less innovation grew at a slower rate of 50% as compared to growth when product innovation sales revenues were included in the total company sales revenues accounting for a faster sales growth rate of 76%. The influence of product innovation on performance was statistically significant (p<0.05) accounting for 92.19% variation in performance. These findings provide irrefutable empirical basis that product innovations have significant revenue growth rates, hence the need for managers of medium sized companies to invest in research and development to sustain product innovation and spur growth. The results sit well within theory and other empirical studies with additional contribution to methodology. Based on the study limitations, further areas for research have been suggested.
Bisherige Versuche der HCI-Community die Lebensmittelverschwendung oder den CO2-Fußabdruck zu reduzieren, basierten meist auf Persuasive Design Ansätzen. Diese werden jedoch kritisiert, die Alltagswelten und Konsumpraktiken für eine Langzeitwirkung nur unzureichend zu berücksichtigen. Das Problem aufgreifend, untersucht dieser Beitrag die Rolle (digitaler) Medien im Übergang zu einer veganen Ernährungspraktik. Hierfür wurden semi-strukturierte Interviews mit 9 VeganerInnen geführt und vor dem Hintergrund der Praxistheorie analysiert. Die Ergebnisse deuten dabei auf eine intensive Nutzung (digitaler) Medien, insbesondere in der frühen Phase der Änderung der Konsumpraktik. Statt Gamification oder Persuasive Design, zeigt sich Mediennutzung in Form von Irritation, Informationsbereitstellung zur Ausbildung eines vegan-spezifischen Konsumwissens sowie als Vermittler zwischen Gleichgesinnten.
In the field of service robots, dealing with faults is crucial to promote user acceptance. In this context, this work focuses on some specific faults which arise from the interaction of a robot with its real world environment due to insufficient knowledge for action execution.
In our previous work [1], we have shown that such missing knowledge can be obtained through learning by experimentation. The combination of symbolic and geometric models allows us to represent action execution knowledge effectively. However we did not propose a suitable representation of the symbolic model.
In this work we investigate such symbolic representation and evaluate its learning capability. The experimental analysis is performed on four use cases using four different learning paradigms. As a result, the symbolic representation together with the most suitable learning paradigm are identified.
We present a novel, multilayer interaction approach that enables state transitions between spatially above-screen and 2D on-screen feedback layers. This approach supports the exploration of haptic features that are hard to simulate using rigid 2D screens. We accomplish this by adding a haptic layer above the screen that can be actuated and interacted with (pressed on) while the user interacts with on-screen content using pen input. The haptic layer provides variable firmness and contour feedback, while its membrane functionality affords additional tactile cues like texture feedback. Through two user studies, we look at how users can use the layer in haptic exploration tasks, showing that users can discriminate well between different firmness levels, and can perceive object contour characteristics. Demonstrated also through an art application, the results show the potential of multilayer feedback to extend on-screen feedback with additional widget, tool and surface properties, and for user guidance.
Pan-African University (PAU) is an initiative of the African Union Commission (AUC) that started in 2008 with the objective to promote higher education, science and technology on the African continent at a high academic level. The Pan-African University Institute of Water and Energy Sciences (including Climate Change) (PAUWES) is one of the five hubs of the Pan African University (PAU) and hosted at the University of Tlemcen in Algeria. PAUWES offers graduate students access to leading academic research and the latest theoretical and hands-on training in areas vital to the future of Africa’s development in water, energy and the challenge of climate change.
While universities are mandated to teach, research and do community outreach, studies reveal that typical university communities live in relative isolation where research is more basic than applied. This study focused on; 1) determining how WWE could be fostered through linkages between universities and external agencies (communities, public and private sectors); 2) establishing how universities’ resources could be optimized to promote research and capacity building for WWE. The dimensions of WWE studied were; 1) Technical & Business Models; 2) Capacity building; and 3) institutional frameworks. Baseline studies were conducted in which qualitative and quantitative data was collected through questionnaires, interviews, documents analysis. Experimentations were carried out whereby Laboratory tests on Bio-methane Potential (BMP) for different biomass types was conducted. A complete chain of briquettes production and consumption has been successfully piloted at St Kizito High School in Namugongo, near Kampala. The 20,000 kg of briquettes produced (from municipal bio-waste) by students monthly are used to cook in three schools whose total population is 2000 students. With an average net profit of $ 3000, the project makes business sense even in absence of social-benefit accounting. Based on start-up capital of $ 12,250, the payback period on investment is 14.7 months. Bio-char (from carbonized waste) and briquette-ash are used as organic fertilizers and biocide in vegetable gardens at the schools. New pathways for municipal waste management based on stakeholder engagement and entrepreneurship are demonstrated; departing from the conventional waste collection and disposal models. This circular enterprise which enhances Food, Agriculture, Biodiversity, Land-use and Energy (FABLE) nexus will scale-up to incorporate non-student communities (youths/women), private waste-collectors and entrepreneurs. The application of entrepreneurial models for engaging students in green enterprises integrates technological, social, economic and governance dimensions for promoting municipal sanitation, environment; energy and food security.
The aim of the descriptive study is to gain an understanding of the perceived level of fairness in their experience of security screening relation to their satisfaction. The context of the study was a major aviation hub in East Africa. The target population was all departing international passengers. Primary data was collected using a self-administered questionnaire. The respondents were selected using convenience sampling of passengers who had just completed the final security check at the departure area of the airport. A total of 251 usable responses were collected from a target of 384 respondents giving a response rate of 65 percent.
The findings contribute to the existing body of knowledge on the relationship between the perceptions of fairness of security procedures and their influence on satisfaction. One way between groups analysis of variance (ANOVA) was conducted to test for statistical significance. A Cronbach’s alpha of 88.7 was computed demonstrating a high level of internal consistency of the survey instrument. The adequacy of security procedures, level of communication provided before and during the screening process, consistency and fairness were found to have a significant relationship to the level of satisfaction reported by passengers. The findings suggest that there are significant differences between groups’ perception of different elements security procedures.
The implications of the study are twofold. The study was cross sectional and indeed was impacted by significant changes in security procedures at the airport at the time of the study. A longitudinal survey may further mitigate the impact of the variances of responses and support a robust contribution to the development of a theoretical model of airport passenger satisfaction. Airport managers could use the results of this study as inputs to enhance the design of screening procedures in modern hubs to enhance the passenger experience to drive revenue growth.
Due to the policy goals for sustainable energy production, renewable energy plants such as photovoltaics are increasingly in use. The energy production from solar radiation depends strongly on atmospheric conditions. As the weather mostly changes, electrical power generation fluctuates, making technical planning and control of power grids to a complex problem.
Surrogate models are used to reduce the burden of expensive-to-evaluate objective functions in optimization. By creating models which map genomes to objective values, these models can estimate the performance of unknown inputs, and so be used in place of expensive objective functions. Evolutionary techniques such as genetic programming or neuroevolution commonly alter the structure of the genome itself. A lack of consistency in the genotype is a fatal blow to data-driven modeling techniques: interpolation between points is impossible without a common input space. However, while the dimensionality of genotypes may differ across individuals, in many domains, such as controllers or classifiers, the dimensionality of the input and output remains constant. In this work we leverage this insight to embed differing neural networks into the same input space. To judge the difference between the behavior of two neural networks, we give them both the same input sequence, and examine the difference in output. This difference, the phenotypic distance, can then be used to situate these networks into a common input space, allowing us to produce surrogate models which can predict the performance of neural networks regardless of topology. In a robotic navigation task, we show that models trained using this phenotypic embedding perform as well or better as those trained on the weight values of a fixed topology neural network. We establish such phenotypic surrogate models as a promising and flexible approach which enables surrogate modeling even for representations that undergo structural changes.
The initial phase in real world engineering optimization and design is a process of discovery in which not all requirements can be made in advance, or are hard to formalize. Quality diversity algorithms, which produce a variety of high performing solutions, provide a unique chance to support engineers and designers in the search for what is possible and high performing. In this work we begin to answer the question how a user can interact with quality diversity and turn it into an interactive innovation aid. By modeling a user's selection it can be determined whether the optimization is drifting away from the user's preferences. The optimization is then constrained by adding a penalty to the objective function. We present an interactive quality diversity algorithm that can take into account the user's selection. The approach is evaluated in a new multimodal optimization benchmark that allows various optimization tasks to be performed. The user selection drift of the approach is compared to a state of the art alternative on both a planning and a neuroevolution control task, thereby showing its limits and possibilities.
The Potential of Sustainable Antimicrobial Additives for Food Packaging from Native Plants in Benin
(2019)
Renewable energies play an increasingly important role for energy production in Europe. Unlike coal or gas powerplants, solar energy production is highly variable in space and time. This is due to the strong variability of cloudsand their influence on the surface solar irradiance. Especially in regions with large contribution from photovoltaicpower production, the intermittent energy feed-in to the power grid can be a risk for grid stability. Therefore goodforecasts of temporal and spatial variability of surface irradiance are necessary to be able to properly regulate thepower supply.
Are quality diversity algorithms better at generating stepping stones than objective-based search?
(2019)
The route to the solution of complex design problems often lies through intermediate "stepping stones" which bear little resemblance to the final solution. By greedily following the path of greatest fitness improvement, objective-based search overlooks and discards stepping stones which might be critical to solving the problem. Here, we hypothesize that Quality Diversity (QD) algorithms are a better way to generate stepping stones than objective-based search: by maintaining a large set of solutions which are of high-quality, but phenotypically different, these algorithms collect promising stepping stones while protecting them in their own "ecological niche". To demonstrate the capabilities of QD we revisit the challenge of recreating images produced by user-driven evolution, a classic challenge which spurred work in novelty search and illustrated the limits of objective-based search. We show that QD far outperforms objective-based search in matching user-evolved images. Further, our results suggest some intriguing possibilities for leveraging the diversity of solutions created by QD.
Verschiedene intelligente Heimautomatisierungsgeräte wie Lampen, Schlösser und Thermostate verbreiten sich rasant im privaten Umfeld. Ein typisches Kommunikationsprotokoll für diese Geräteklasse ist Bluetooth Low Energy (BLE). In dieser Arbeit wird eine strukturierte Sicherheitsanalyse für BLE vorgestellt. Die beschriebene Vorgehensweise kategorisiert bekannte Angriffsvektoren und beschreibt einen möglichen Aufbau für eine Analyse. Im Zuge dieser Arbeit wurden einige sicherheitsrelevante Probleme aufgedeckt, die es Angreifern ermöglichen die Geräte vollständig zu übernehmen. Es zeigte sich, dass im Standard vorgesehene Sicherheitsfunktionen wie Verschlüsselung und Integritätsprüfungen häufig gar nicht oder fehlerhaft implementiert sind.
More and more devices will be connected to the internet [3]. Many devicesare part of the so-called Internet of Things (IoT) which contains many low-powerdevices often powered by a battery. These devices mainly communicate with the manufacturers back-end and deliver personal data and secrets like passwords.
Estimating the impact of successful completion of vocational education on employment outcomes
(2019)
Destination Development for Entrepreneurial Tourism in Lake Bosomtwe and Kintampo falls (Ghana)
(2019)
The tourism industry is one of the world’s largest industries (direct, indirect and induced Africa has the potential with its cultural and natural resources to outpace other regions in attracting valuable tourism dollars. The main aim of the study is to improve visitor experience on the two tourist sites. To do this it is necessary to explore the elements and success factors of Tourism Destination Development and using these as a checklist to identify the strength and weaknesses of the selected Tourist Destinations in Ghana West Africa. The rationale behind the study is to outline the crucial Destination Management (DM) criteria of all aspect that contribute to boost ultimate visitor experience, articulating the roles of the different stakeholders and identifying clear actions for effective Tourism Development in Ghana. The interview technique was employed to collect data from staff and management of the selected destinations. Data was analyzed for themes related to elements, success factors and challenges of destination development and new ideas for development was also solicited. It was revealed that some of the elements that feature for tourists’ attraction are good hotels, high hygiene and sanitation standards, good food and activities of amusements. Competency gaps identified suggest collaboration with academia to secure a high level of knowledge through research in this present world of dynamism. Some of the critical success factors found are: systematic provision of cultural events, advance knowledge of agents and tour operators and quality leisure and recreation. It is recommended that product and service development should be a joint idea of all stakeholders. The research team therefore, have plans underway to proceed on the second phase of the project: that is to gather resources together to make lake Bosomtwe and Kintampo falls sites attractive to tourists.
It is shown that the electrochemical kinetics of alkaline methanol oxidation can be reduced by setting certain fast reactions contained in it to a steady state. As a result, the underlying system of Ordinary Differential Equations (ODE) is transformed to a system of Differential-Algebraic Equations (DAE). We measure the precision characteristics of such transformation and discuss the consequences of the obtained model reduction.
Synthesis of Substituted Hydroxyapatite for Application in Bone Tissue Engineering and Drug Delivery
(2019)
Trust is the lubricant of the sharing economy, especially in peer-to-peer carsharing where you leave a valuable good to a stranger in the hope of getting it backunscathed. Central mechanisms for handling this information gap nowadays are ratings and reviews of other users. The rising of connected car technology opens new possibilities to increase trust by collecting and providing e.g. driving behavior data. At the same time, this means an intrusion into the privacy of the user. Therefore, in this work we explore technological approaches that allow building trust without violating the privacy of individuals. We evaluate to what extent blockchain technology and smart contracts are suitable technologies to meet these challengesby setting upa prototype implementation of a block-chain-based carsharing approach. In this context, we present our research approachand evaluate the prototype in terms of trust and privacy.
In Sensor-based Fault Detection and Diagnosis (SFDD) methods, spatial and temporal dependencies among the sensor signals can be modeled to detect faults in the sensors, if the defined dependencies change over time. In this work, we model Granger causal relationships between pairs of sensor data streams to detect changes in their dependencies. We compare the method on simulated signals with the Pearson correlation, and show that the method elegantly handles noise and lags in the signals and provides appreciable dependency detection. We further evaluate the method using sensor data from a mobile robot by injecting both internal and external faults during operation of the robot. The results show that the method is able to detect changes in the system when faults are injected, but is also prone to detecting false positives. This suggests that this method can be used as a weak detection of faults, but other methods, such as the use of a structural model, are required to reliably detect and diagnose faults.