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There is severe clinical vitamin A deficiency (VAD) prevalence among Ghanaians and many African countries. Foodbased diets has been suggested as a more sustainable approach to solving the VAD situation in Africa. In this study, A participatory action research between orange flesh sweet potato farmers, gari processors within central region and academia was adopted to develop gari containing provitamin A beta-carotene. Gari is a major staple for Ghanaians and people in the West African subregion due to its affordability and swelling capacity. It is mainly eaten raw with water, sugar, groundnut and milk as gari-soakings or with hot water to prepare gelatinized food called gari-kai in Ghana or “eba” among Nigerians. However, gari is limited in provitamin A carotenoids. Orange fleshed sweet potato (OFSP) is known to contain large amount of vitamin A precursor. Therefore, addition of OFSP to gari would have the potential to fight the high prevalence rate of vitamin A deficiency amongst less developed regions of Africa. To develop this, different proportions of orange fleshed sweet potatoes (OFSP) was used to substitute cassava mash and fermented spontaneously to produce composite gari - a gritty-crispy ready-to-eat food product. Both the amount of OFSP and the fermentation duration caused significant increases in the β-carotene content of the composite gari. OFSP addition reduced the luminance while roasting made the composite gari yellower when compared with the cake used. Addition of OFSP negatively affected the swelling capacity of the gari although not significant. The taste, texture, flavour and the overall preferences for the composite gari decreased due to the addition of the OFSP but fermentation duration (FD) improved them. The sample with 10% OFSP and FD of 1.81 days was found to produce the optimal gari. One-portion of the optimal gari would contribute to 34.75, 23.2, 23.2, 27, 17 and 16% of vitamin A requirements amongst children, adolescent, adult males, adult females, pregnant women and lactating mothers respectively. The study demonstrated that partial substitution of cassava with OFSP for gari production would have the potential to fight the high prevalence rate of vitamin A deficiency amongst less developed regions of Africa while involvement of farmers and processors prior to the design of research phase enhanced the adoption of intervention strategies.
An essential measure of autonomy in assistive service robots is adaptivity to the various contexts of human-oriented tasks, which are subject to subtle variations in task parameters that determine optimal behaviour. In this work, we propose an apprenticeship learning approach to achieving context-aware action generalization on the task of robot-to-human object hand-over. The procedure combines learning from demonstration and reinforcement learning: a robot first imitates a demonstrator’s execution of the task and then learns contextualized variants of the demonstrated action through experience. We use dynamic movement primitives as compact motion representations, and a model-based C-REPS algorithm for learning policies that can specify hand-over position, conditioned on context variables. Policies are learned using simulated task executions, before transferring them to the robot and evaluating emergent behaviours. We additionally conduct a user study involving participants assuming different postures and receiving an object from a robot, which executes hand-overs by either imitating a demonstrated motion, or adapting its motion to hand-over positions suggested by the learned policy. The results confirm the hypothesized improvements in the robot’s perceived behaviour when it is context-aware and adaptive, and provide useful insights that can inform future developments.
ICT integration by universities teaching professionals is emerging as a major concern, this study demonstrate the need to address the integration problem by encouraging existing metrics use in indexing ICT integration as an ICT governance strategy. Quality of integration depends on quality indexing which also depend on quality of existing metrics and their use. Considering the role that University Information Technology Teaching Professionals’ (UITTPs) continuous improvement indexing can offer, towards autonomic governance of the continuous emerging ICTs in the university teaching, this study examined extent in use of existing ICT integration metrics to index ICT integration by the UITTPs. Six metrics for ICT integration were investigated; time, workshop course content relevance, technical malfunctions, support conditions, support services, and motivation and commitment to student learning and staff professional development metrics. Descriptive survey design was used in which interviews were conducted to UITTPs in three (3) public and three (3) private purposively selected universities in Kenya. The findings were analyzed descriptively and inferentially using Kendall’s correlation of concordance and tested using Chi-square on the extent of concordance and presented with help of frequency tables, figures and percentages. The findings revealed that all the metrics are rarely used for indexing ICT integration (32.8%), and most UITTPs were in discordance on this level of all the six metrics use except for support condition. This implied that the use of metrics for indexing integration has not been formalized across the Kenyan universities. Universities need to be encouraged to identify suitable metrics, formalize them and improve their frequency in use. Secondly, socio based metrics such as content relevance are used more frequently for indexing integration as compared to Technical metrics, socio-technical metrics balance therefore need to be emphasized by the universities management when determining and using metrics for indexing ICT integration.
Cancer is one of the leading causes of death worldwide [183], with lung tumors being the most frequent cause of cancer deaths in men as well as one of the most common cancers diagnosed in woman [40]. As symptoms often arise in advanced stages, an early diagnosis is especially important to ensure the best and earliest possible treatment. In order to achieve this, Computed Tomography (CT) scans are frequently used for tumor detection and diagnosis. We will present examples of publicly available CT image data of lung cancer patients and discuss possible methods to realize an automatic system for automated cancer diagnosis. We will also look at the recent SPIE-AAPM Lung CT Challenge [10] data set in detail and describe possible methods and challenges for image segmentation and classification based on this data set.
With trainings and research oriented towards sustainable development since 2006 (Water and Sanitation, Infrastructure, Renewable Energies and Energy Processes), Foundation 2iE is positioning itself as a reference institute that trains innovative engineers-entrepreneurs for the needs and challenges of Africa’s development. Center of Excellence of the UEMOA and the World Bank, CSR is at the heart of the Strategy of the institute which aims to be a showcase in this field in Africa.
The role of tourism entrepreneurship in rural development continues to be a subject of interest and debate among academia and practitioners. Theoretically, it is anticipated that tourism entrepreneurship will lead to livelihood diversification, enhancement and ultimately a revitalization of the rural economy. While tourism is posited as an accessible entrepreneurship pathway, there is a dearth of information regarding rural dwellers’ actual experiences with it, especially within the Ghanaian context. Using a case study approach and qualitative data from Wli; a rural tourism destination in Ghana, this paper delves into the opportunities and concerns associated with tourism entrepreneurship in rural areas. Data was obtained between November and December 2016 from 27 persons who were either tourism enterprise owners or employees. Findings from the study showed that entrepreneurial activities centred on the provision of accommodation, food and beverage, souvenir and guiding services. The nature of the activities enabled easy transfer of existing skills and knowledge. Further, entry into tourism entrepreneurship was perceived to be easy by the majority of study participants. These findings confirm the potential for tourism to be employed in boosting entrepreneurial activities in rural areas. Nevertheless, there were concerns regarding access to credit, institutional support, unhealthy competitions, low incomes, unguaranteed pensions, and seasonality and skewness of demand. These concerns threatened the growth and sustainability of tourism entrepreneurship within the community. From a policy perspective, there is a need for institutional recognition and support for tourism entrepreneurial intentions and activities in rural areas. Practice-wise, credit facilities need to be designed specifically for tourism-related rural enterprises. Further, periodic skills and knowledge augmentation programmes must be initiated to help expand the skill sets for the rural entrepreneurs. Finally, there is a need for the formation of traderelated networks to provide a platform for knowledge and experience sharing among the entrepreneurs.
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.
Robust Indoor Localization Using Optimal Fusion Filter For Sensors And Map Layout Information
(2014)
This paper presents the b-it-bots RoboCup@Work team and its current hardware and functional architecture for the KUKA youBot robot.We describe the underlying software framework and the developed capabilities required for operating in industrial environments including features such as reliable and precise navigation, flexible manipulation and robust object recognition.
Despite perfect functioning of its internal components, a robot can be unsuccessful in performing its tasks because of unforeseen situations. These situations occur when the behavior of the objects in the robot’s environment deviates from its expected values. For robots, such deviations are exhibited in the form of unknown external faults which prohibit them from performing their tasks successfully. In this work we propose to use naive physics knowledge to reason about such faults in the robotics domain. We propose an approach that uses naive physics concepts to find information about the situations which result in a detected unknown fault. The naive physics knowledge is represented by the physical properties of objects which are formalized in a logical framework. The proposed approach applies a qualitative version of physical laws to these properties for reasoning about the detected fault. By interpreting the reasoning results the robot finds the information about the situations which can cause the fault. We apply the proposed approach to the scenarios in which a robot performs manipulation tasks of picking and placing objects. Results of this application show that naive physics holds great promise for reasoning about unknown ex- ternal faults in robotics.
Sind kleinere und mittlere Unternehmen (KMU) bereits auf die Digitale Transformation vorbereitet?
(2018)
Eine von den Autoren durchgeführte Untersuchung konnte deutliche Indizien dafür ausmachen, dass viele kleinere und mittlere Unternehmen (KMU) aktuell noch keine ausreichende Reife zur Digitalen Transformation haben. Zur Lösung des Problems wird vorgeschlagen, ein agiles IT-Management-Konzept zu entwickeln, um den IT-Bereich dynamisch und ohne formalen Ballast des klassischen IT-Managements zu steuern.
Mergers and acquisitions take place all over the world and in many industries, typically motivated by corporate politics. While IT management is often not involved in the decision-making, it has to solve a wide range of problems in the post-merger phase. Indeed, merging two or more companies implies not only merging their core businesses, but also creating a new and efficiently integrated IT organisation from the individual ones, since persistence of the current IT organisations usually does not make sense. In addition, corporate management frequently imposes constraints, e.g., cost reductions, on the IT infrastructure. The principal critical success factor when merging IT organisations is the uninterrupted operation of the IT business, because a service gap is neither acceptable for in-house functional departments nor for external customers. Therefore, the IT rebuilding phase has to focus on IT services that facilitate the processes of functional departments, support processes, and processes of customers and suppliers, so that any transformation work is transparent to internal and external customers. In this article we describe a real-world but anonymous case study. Our goals are to highlight the points important for merging IT organisations, and to help decision-makers, particularly in the areas of IT organisation and IT personnel. We focus on the arising organisational and non-technical issues from a management perspective, i.e., the CIO's view, and provide checklists intended to help IT managers to address the most pressing issues. To assist CIOs surviving in the post merger phase, we give check lists for merging IT organisations, check lists for merging IT human resources, check lists for IT budgets and reporting, and assess activities in a merger scenario. IT hardware, software and IT infrastructure as well as running IT projects are not considered in this paper.
Während sich die unternehmerische Arbeitswelt immer mehr in Richtung Agilität verschiebt, verharrt das IT-Controlling noch in alten, klassischen Strukturen. Diese Arbeit untersucht die Fragestellung, ob und inwieweit agile Ansätze im IT-Controlling eingesetzt werden können. Dieser Beitrag ist eine modifizierte Version des in der Zeitschrift „HMD Praxis der Wirtschaftsinformatik“ (https://link.springer.com/article/10.1365/s40702-022-00837-0) erschienenen Artikels „Agiles IT-Controlling“.
IT performance measurement is often associated by chief executive officers with IT cost cutting although IT protects business processes from increasing IT costs. IT cost cutting only endangers the company’s efficiency. This opinion discriminates those who do IT performance measurement in companies as a bean-counter. The present paper describes an integrated reference model for IT performance measurement based on a life cycle model and a performance oriented framework. The presented model was created from a practical point of view. It is designed lank compared with other known concepts and is very appropriate for small and medium enterprises (SME).
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.
Die digitale Transformation verändert die internationale Kooperation der Hochschulen massiv. Über die Möglichkeiten der virtuellen Mobilität hinaus entstehen neue Themenfelder, die internationale Lern- und Lehrerlebnisse mit digitaler Unterstützung verändern, ergänzen oder neu ermöglichen. Dazu sind im Bereich der Förderung der Internationalisierung (DAAD, Erasmus+, BMBF u.a.) Projekte und Förderformate entstanden, die Digitalisierung und Internationalisierung kombinieren und die neuen Themenstellungen adressieren, z.B. didaktische Formate, administrative Prozesse (auch im Kontext OZG und DSGVO), virtuelle und hybride Mobilität, internationale Projekt- und Teamformate sowie schlussendlich auch Inhalte, die internationale, interkulturelle und interdisziplinäre Kompetenzen mit digitalen Kompetenzen verbinden. Der vorgeschlagene Workshop soll entsprechende Projekte zusammenbringen und die Themen strukturieren, um einen Überblick der Entwicklungen zu schaffen und somit einen Beitrag zur Definition des Themenfelds „Digitalisierung & Internationalisierung“ zu leisten.
The need for innovation around the control functions of inverters is great. PV inverters were initially expected to be passive followers of the grid and to disconnect as soon as abnormal conditions happened. Since future power systems will be dominated by generation and storage resources interfaced through inverters these converters must move from following to forming and sustaining the grid. As “digital natives” PV inverters can also play an important role in the digitalisation of distribution networks. In this short review we identified a large potential to make the PV inverter the smart local hub in a distributed energy system. At the micro level, costs and coordination can be improved with bidirectional inverters between the AC grid and PV production, stationary storage, car chargers and DC loads. At the macro level the distributed nature of PV generation means that the same devices will support both to the local distribution network and to the global stability of the grid. Much success has been obtained in the former. The later remains a challenge, in particular in terms of scaling. Yet there is some urgency in researching and demonstrating such solutions. And while digitalisation offers promise in all control aspects it also raises significant cybersecurity concerns.
In 1991 the researchers at the center for the Learning Sciences of Carnegie Mellon University were confronted with the confusing question of “where is AI” from the users, who were interacting with AI but did not realize it. Three decades of research and we are still facing the same issue with the AItechnology users. In the lack of users’ awareness and mutual understanding of AI-enabled systems between designers and users, informal theories of the users about how a system works (“Folk theories”) become inevitable but can lead to misconceptions and ineffective interactions. To shape appropriate mental models of AI-based systems, explainable AI has been suggested by AI practitioners. However, a profound understanding of the current users’ perception of AI is still missing. In this study, we introduce the term “Perceived AI” as “AI defined from the perspective of its users”. We then present our preliminary results from deep-interviews with 50 AItechnology users, which provide a framework for our future research approach towards a better understanding of PAI and users’ folk theories.
For most people, using their body to authenticate their identity is an integral part of daily life. From our fingerprints to our facial features, our physical characteristics store the information that identifies us as "us." This biometric information is becoming increasingly vital to the way we access and use technology. As more and more platform operators struggle with traffic from malicious bots on their servers, the burden of proof is on users, only this time they have to prove their very humanity and there is no court or jury to judge, but an invisible algorithmic system. In this paper, we critique the invisibilization of artificial intelligence policing. We argue that this practice obfuscates the underlying process of biometric verification. As a result, the new "invisible" tests leave no room for the user to question whether the process of questioning is even fair or ethical. We challenge this thesis by offering a juxtaposition with the science fiction imagining of the Turing test in Blade Runner to reevaluate the ethical grounds for reverse Turing tests, and we urge the research community to pursue alternative routes of bot identification that are more transparent and responsive.
Technological objects present themselves as necessary, only to become obsolete faster than ever before. This phenomenon has led to a population that experiences a plethora of technological objects and interfaces as they age, which become associated with certain stages of life and disappear thereafter. Noting the expanding body of literature within HCI about appropriation, our work pinpoints an area that needs more attention, “outdated technologies.” In other words, we assert that design practices can profit as much from imaginaries of the future as they can from reassessing artefacts from the past in a critical way. In a two-week fieldwork with 37 HCI students, we gathered an international collection of nostalgic devices from 14 different countries to investigate what memories people still have of older technologies and the ways in which these memories reveal normative and accidental use of technological objects. We found that participants primarily remembered older technologies with positive connotations and shared memories of how they had adapted and appropriated these technologies, rather than normative uses. We refer to this phenomenon as nostalgic reminiscence. In the future, we would like to develop this concept further by discussing how nostalgic reminiscence can be operationalized to stimulate speculative design in the present.
When dialogues with voice assistants (VAs) fall apart, users often become confused or even frustrated. To address these issues and related privacy concerns, Amazon recently introduced a feature allowing Alexa users to inquire about why it behaved in a certain way. But how do users perceive this new feature? In this paper, we present preliminary results from research conducted as part of a three-year project involving 33 German households. This project utilized interviews, fieldwork, and co-design workshops to identify common unexpected behaviors of VAs, as well as users’ needs and expectations for explanations. Our findings show that, contrary to its intended purpose, the new feature actually exacerbates user confusion and frustration instead of clarifying Alexa's behavior. We argue that such voice interactions should be characterized as explanatory dialogs that account for VA’s unexpected behavior by providing interpretable information and prompting users to take action to improve their current and future interactions.
In the fermentation process sugars are transformed into lactic acid. pH meters have traditionally been used for fermentation process monitoring based on acidity. More recently, near infrared (NIR) spectroscopy has proven to provide an accurate and non-invasive method to detect when the transformation of sugars into lactic acid is finished. The fermentation process when sugars are transformed into lactic acid. This research proposes the use of simplified NIR spectroscopy using multispectral optical sensors as a simpler and less expensive measure to end the fermentation process. The NIR spectrum of milk and yogurt is compared to find and extract features that can be used to design a simple sensor to monitor the yogurt fermentation process. Multispectral images in four selected wavebands within the NIR spectrum are captured and show different spectral remission characteristics for milk, yogurt and water, which support the selection of these wavebands for milk and yogurt classification.
Das Kernanliegen des Datenschutzes ist es, natürliche Personen vor nachteiligen Effekten der Speicherung und Verarbeitung der sie betreffenden Daten zu schützen. Aber viele Personen scheinen gar nicht geschützt werden zu wollen. Im Gegenteil, viele Endanwender willigen “freiwillig“ – bewusst oder unbewusst – in eine umfassende Verarbeitung ihrer personenbezogenen Daten ein. Warum tun Menschen dies? Es werden verschiedene Ursachen diskutiert (beispielsweise in [79]), hierzu gehören Uninformiertheit, mangelnde Sensibilität, das Gefühl der Hilflosigkeit, mangelnde Zahlungsbereitschaft und mangelnde Alternativen. Auch wenn dies in Einzelfällen zutrifft, so gibt es oft sehr wohl datenschutzfreundliche Alternativen. Beispielsweise existiert zu WhatsApp (als Instant Messaging App) die Alternative Threema. Threema gilt als EU-DS-GVO-konform und funktional durchaus mit WhatsApp vergleichbar [62]. Allerdings ist inzwischen die aktuelle Netzwerkgröße ein entscheidendes Auswahlkriterium: Im Januar 2018 hatte Threema 4,5 Millionen Nutzer [172], WhatsApp dagegen 1,5 Milliarden [171]. Dies ist ein Indiz dafür, dass WhatsApp sich quasi zum De-facto-Standard entwickelt hat und es für die einzelne Person nur schwer möglich ist, viele andere “zum Wechsel auf ein anderes Produkt zu bewegen. [. . . ] Bei Diensten mit Nutzerzahlen im Milliardenbereich kann von ’Freiwilligkeit’ nur noch bedingt gesprochen werden.“ [9]
Introduction: After cellulose, lignin represents the most abundant biopolymer on earth that accounts for up to 18-35 % by weight of lignocellulose biomass. Today, it is a by-product of the paper and pulping industry. Although lignin is available in huge amounts, mainly in form of so called black liquor produced via Kraft-pulping, processes for the valorization of lignin are still limited [1]. Due to its hyperbranched polyphenol-like structure, lignin gained increasing interest as biobased building block for polymer synthesis [2]. The present work is focused on extraction and purification of lignin from industrial black liquor and synthesis of lignin-based polyurethanes.
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.
LiDAR-based Indoor Localization with Optimal Particle Filters using Surface Normal Constraints
(2023)
Over the years, entrepreneurship has proven to be one of the key roles towards development. The cycle of business start-ups and growth are linked to the socio-economic benefits of the global world at large. With a growing world population of over 7billion people, the existence of universities (both public &private) as well as enterprises has increased globally in the 21st century. The mission and purpose behind Universities, Entrepreneurship and Enterprises thrive on development in the areas of capacity building, skill acquisition, training and knowledge amongst others. Africa alone has a population of over 1.2billion people with about 650 recognized universities and over 140,000 registered businesses (enterprises) in Ghana alone. A case study in Ghana reveals three key drivers towards entrepreneurship and the role university education has played in various business establishments. The drivers are problem statements, resources and research findings. Some of these notions to business include the management of risk, research findings and customer relationship. These are major features that need critical attention and play a role in business and entrepreneurship in Africa. A major success in business and entrepreneurship is the utilization of the human resource population and the lifeline support given to households in terms of income, while a barrier being the limited access to credit support from the financial companies at the inception stages. In conclusion, this conference should develop a practical book guide on business start-ups and entrepreneurship knowledge to be used at the various universities in Africa to enhance development.
The transport of carbon dioxide through pipelines is one of the important components of Carbon dioxide Capture and Storage (CCS) systems that are currently being developed. If high flow rates are desired a transportation in the liquid or supercritical phase is to be preferred. For technical reasons, the transport must stay in that phase, without transitioning to the gaseous state. In this paper, a numerical simulation of the stationary process of carbon dioxide transport with impurities and phase transitions is considered. We use the Homogeneous Equilibrium Model (HEM) and the GERG-2008 thermodynamic equation of state to describe the transport parameters. The algorithms used allow to solve scenarios of carbon dioxide transport in the liquid or supercritical phase, with the detection of approaching the phase transition region. Convergence of the solution algorithms is analyzed in connection with fast and abrupt changes of the equation of state and the enthalpy function in the region of phase transitions.
This study sought to examine the relationship between the components of SMEs social capital and firm performance. Using the social capital theory and the resource-based view as the theoretical foundations and census, 1,532 SMEs were selected in the Accra Metropolis for the study. Empirical results from 717 SMEs, utilising the hierarchical linear regression model, revealed that owner/manger’s network relationships are beneficial to the firm depending on when the relationships are closed or opened. Moreover, the study found that social capital has a significant impact on the sales and market performance of small and medium-sized enterprises. The results also brought to the fore the fact that most social networks of SME entrepreneurs are family, friends and relatives, which most times can only be used for expressive purposes and not for instrumental gain. The practical implications of the results are also discussed.
Nowadays, we input text not only on stationary devices, but also on handheld devices while walking, driving, or commuting. Text entry on the move, which we term as nomadic text entry, is generally slower. This is partially due to the need for users to move their visual focus from the device to their surroundings for navigational purposes and back. To investigate if better feedback about users' surroundings on the device can improve performance, we present a number of new and existing feedback systems: textual, visual, textual & visual, and textual & visual via translucent keyboard. Experimental comparisons between the conventional and these techniques established that increased ambient awareness for mobile users enhances nomadic text entry performance. Results showed that the textual and the textual & visual via translucent keyboard conditions increased text entry speed by 14% and 11%, respectively, and reduced the error rate by 13% compared to the regular technique. The two methods also significantly reduced the number of collisions with obstacles.
Emotion and gender recognition from facial features are important properties of human empathy. Robots should also have these capabilities. For this purpose we have designed special convolutional modules that allow a model to recognize emotions and gender with a considerable lower number of parameters, enabling real-time evaluation on a constrained platform. We report accuracies of 96% in the IMDB gender dataset and 66% in the FER-2013 emotion dataset, while requiring a computation time of less than 0.008 seconds on a Core i7 CPU. All our code, demos and pre-trained architectures have been released under an open-source license in our repository at https://github.com/oarriaga/face classification.
Ghanaian tertiary graduates' perception of entrepreneurship education on employment opportunities
(2017)
This study focuses on whether entrepreneurship education increases entrepreneurial interest in students to set up new businesses. Entrepreneurship is a core course taken in the third year by all students of Ho Technical University. Out of the 1329 population of level 300 students of the 2016/2017 academic year, data were collected by convenience sampling from 325 (217 males and 108 females) with mean age of 24.75 years from 14 departments of four faculties. The students responded to 43-survey items derived from reviewed literature on a 5-Point Likert-Scale. It is concluded that more than 84% of the respondents agreed that entrepreneurship education informed students about entrepreneurship through the acquisition of practical skills, knowledge about acquisition of personal orientation, knowledge about business management principles and the availability of entrepreneurial support agencies. This shows that the students are highly confident of setting up their own businesses through the knowledge acquired. The study therefore has important implications for policy makers, management of tertiary institutions, students and educational evaluators on how to ensure that tertiary graduates set up entrepreneurship ventures in order to partially solve the unemployment problem in Ghana.
We present a model checking algorithm for ∀CTL (and full CTL) which uses an iterative abstraction refinement strategy.
It terminates at least for all transition systems M that have a finite simulation or bisimulation quotient. In contrast to other abstraction refinement algorithms, we always work with abstract models whose sizes depend only on the length of the formula θ (but not on the size of the system, which might be infinite).
The goal of this work is to develop an integration framework for a robotic software system which enables robotic learning by experimentation within a distributed and heterogeneous setting. To meet this challenge, the authors specified, defined, developed, implemented and tested a component-based architecture called XPERSIF. The architecture comprises loosely-coupled, autonomous components that offer services through their well-defined interfaces and form a service-oriented architecture. The Ice middleware is used in the communication layer. Additionally, the successful integration of the XPERSim simulator into the system has enabled simultaneous quasi-realtime observation of the simulation by numerous, distributed users.
Adapting plans to changes in the environment by finding alternatives and taking advantage of opportunities is a common human behavior. The need for such behavior is often rooted in the uncertainty produced by our incomplete knowledge of the environment. While several existing planning approaches deal with such issues, artificial agents still lack the robustness that humans display in accomplishing their tasks. In this work, we address this brittleness by combining Hierarchical Task Network planning, Description Logics, and the notions of affordances and conceptual similarity. The approach allows a domestic service robot to find ways to get a job done by making substitutions. We show how knowledge is modeled, how the reasoning process is used to create a constrained planning problem, and how the system handles cases where plan generation fails due to missing/unavailable objects. The results of the evaluation for two tasks in a domestic service domain show the viability of the approach in finding and making the appropriate goal transformations.
In this paper, we present XPERSim, a 3D simulator built on top of open source components that enables users to quickly and easily construct an accurate and photo-realistic simulation for robots of arbitrary morphology and their environments. While many existing robot simulators provide a good dynamics simulation, they often lack the high quality visualization that is now possible with general-purpose hardware. XPERSim achieves such visualization by using the Object-Oriented Graphics Rendering Engine 3D (Ogre) engine to render the simulation whose dynamics are calculated using the Open Dynamics Engine (ODE). Through XPERSim’s integration into a component-based software integration framework used for robotic learning by experimentation, XPERSIF, and the use of the scene-oriented nature of the Ogre engine, the simulation is distributed to numerous users that include researchers and robotic components, thus enabling simultaneous, quasi-realtime observation of the multiple-camera simulations.
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.
For years, the common logic that underpinned entrepreneurship was to find a niche within in a market/sector and then solidify business practice to achieve success in the market segment. The dawn of technologically-based disruptive enterprises, such as Uber and Air B&B, coupled with the nearing Fourth Industrial revolution seriously call into question the conventional business logic. In this article, the projected impact of these forces on African entrepreneurs is explored. We look at the role of government, business and education systems to prepare for the impact of the Fourth Industrial revolution. Specific focus is placed on the need for entrepreneurial skills and training to prepare for the impact of the Fourth Industrial revolution. We also explore the importance of innovation, both in terms of products and processes to mitigate against the impact of these forces.
Small, Medium and Micro Enterprises (SMMEs) are widely recognised as playing a pivotal role in economic development and job creation. This is particularly so in Africa, where SMMEs are responsible for 80% of all formal jobs. While this is recognised by various African continental and national developments plans, the nefarious practice of late payment, by especially governments, not only stunt the growth of SMMEs, but often-time leads to business failure. This article investigates the impact of late payment, with a specific focus on South Africa and touches on international good practice that may be employed to address this phenomenon.
ProtSTonKGs: A Sophisticated Transformer Trained on Protein Sequences, Text, and Knowledge Graphs
(2022)
While most approaches individually exploit unstructured data from the biomedical literature or structured data from biomedical knowledge graphs, their union can better exploit the advantages of such approaches, ultimately improving representations of biology. Using multimodal transformers for such purposes can improve performance on context dependent classication tasks, as demonstrated by our previous model, the Sophisticated Transformer Trained on Biomedical Text and Knowledge Graphs (STonKGs). In this work, we introduce ProtSTonKGs, a transformer aimed at learning all-encompassing representations of protein-protein interactions. ProtSTonKGs presents an extension to our previous work by adding textual protein descriptions and amino acid sequences (i.e., structural information) to the text- and knowledge graph-based input sequence used in STonKGs. We benchmark ProtSTonKGs against STonKGs, resulting in improved F1 scores by up to 0.066 (i.e., from 0.204 to 0.270) in several tasks such as predicting protein interactions in several contexts. Our work demonstrates how multimodal transformers can be used to integrate heterogeneous sources of information, paving the foundation for future approaches that use multiple modalities for biomedical applications.
In this paper, modeling of piston and generic type gas compressors for a globally convergent algorithm for solving stationary gas transport problems is carried out. A theoretical analysis of the simulation stability, its practical implementation and verification of convergence on a realistic gas network have been carried out. The relevance of the paper for the topics of the conference is defined by a significance of gas transport networks as an advanced application of simulation and modeling, including the development of novel mathematical and numerical algorithms and methods.
Solving transport network problems can be complicated by non-linear effects. In the particular case of gas transport networks, the most complex non-linear elements are compressors and their drives. They are described by a system of equations, composed of a piecewise linear ‘free’ model for the control logic and a non-linear ‘advanced’ model for calibrated characteristics of the compressor. For all element equations, certain stability criteria must be fulfilled, providing the absence of folds in associated system mapping. In this paper, we consider a transformation (warping) of a system from the space of calibration parameters to the space of transport variables, satisfying these criteria. The algorithm drastically improves stability of the network solver. Numerous tests on realistic networks show that nearly 100% convergence rate of the solver is achieved with this approach.
In this paper, an analysis of the error ellipsoid in the space of solutions of stationary gas transport problems is carried out. For this purpose, a Principal Component Analysis of the solution set has been performed. The presence of unstable directions is shown associated with the marginal fulfillment of the resistivity conditions for the equations of compressors and other control elements in gas networks. Practically, the instabilities occur when multiple compressors or regulators try to control pressures or flows in the same part of the network. Such problems can occur, in particular, when the compressors or regulators reach their working limits. Possible ways of resolving instabilities are considered.
The formulation of transport network problems is represented as a translation between two domain specific languages: from a network description language, used by network simulation community, to a problem description language, understood by generic non-linear solvers. A universal algorithm for this translation is developed, an estimation of its computational complexity given, and an efficient application of the algorithm demonstrated on a number of realistic examples. Typically, for a large gas transport network with about 10K elements the translation and solution of non-linear system together require less than 1 sec on the common hardware. The translation procedure incorporates several preprocessing filters, in particular, topological cleaning filters, which accelerate the solution procedure by factor 8.
The paper presents the topological reduction method applied to gas transport networks, using contraction of series, parallel and tree-like subgraphs. The contraction operations are implemented for pipe elements, described by quadratic friction law. This allows significant reduction of the graphs and acceleration of solution procedure for stationary network problems. The algorithm has been tested on several realistic network examples. The possible extensions of the method to different friction laws and other elements are discussed.
Target meaning representations for semantic parsing tasks are often based on programming or query languages, such as SQL, and can be formalized by a context-free grammar. Assuming a priori knowledge of the target domain, such grammars can be exploited to enforce syntactical constraints when predicting logical forms. To that end, we assess how syntactical parsers can be integrated into modern encoder-decoder frameworks. Specifically, we implement an attentional SEQ2SEQ model that uses an LR parser to maintain syntactically valid sequences throughout the decoding procedure. Compared to other approaches to grammar-guided decoding that modify the underlying neural network architecture or attempt to derive full parse trees, our approach is conceptually simpler, adds less computational overhead during inference and integrates seamlessly with current SEQ2SEQ frameworks. We present preliminary evaluation results against a recurrent SEQ2SEQ baseline on GEOQUERY and ATIS and demonstrate improved performance while enforcing grammatical constraints.
Mobile technologies have evolved into the means of gaining access to information for learning. Its application in higher education is still a novel concept, particularly in underdeveloped countries. This study is aimed at exploring the views of doctoral students regarding their learning experiences with mobile technologies. Student focus group interviews of 24 doctoral students from 3 different academic institutions were interviewed. The participants’ responses were recorded, transcribed, and analyzed to make conclusions. According to the findings of this study, mobile devices play an important part in the learning experiences of doctoral students. The participating students engaged in collaborative learning using mobile technologies. Given the benefits of adopting mobile technologies for learning activities, academic institutions should focus on teaching faculty members to use this to involve students in their learning process. The implications of this study call for the continued advancement of mobile technologies to facilitate effective learning experience for the multitude of mobile learners in developing countries. Another implication is that academic institutions with collaboration with libraries should see the need to develop user friendly mobile app that is linked to the library management system. Such an application would allow the students to optimally use their smartphones and tablets to search the library’s resources from their mobile devices. Training should be offered to the teaching faculty members to come to terms with the benefits of mobile technologies for learning activities.
Photovoltaic (PV) power data are a valuable but as yet under-utilised resource that could be used to characterise global irradiance with unprecedented spatio-temporal resolution. The resulting knowledge of atmospheric conditions can then be fed back into weather models and will ultimately serve to improve forecasts of PV power itself. This provides a data-driven alternative to statistical methods that use post-processing to overcome inconsistencies between ground-based irradiance measurements and the corresponding predictions of regional weather models (see for instance Frank et al., 2018). This work reports first results from an algorithm developed to infer global horizontal irradiance as well as atmospheric optical properties such as aerosol or cloud optical depth from PV power measurements.
Incoming solar radiation is an important driver of our climate and weather. Several studies (see for instance Frank et al. 2018) have revealed discrepancies between ground-based irradiance measurements and the predictions of regional weather models. In the realm of electricity generation, accurate forecasts of solar photovoltaic (PV)energy yield are becoming indispensable for cost-effective grid operation: in Germany there are 1.6 million PVsystems installed, with a nominal power of 46 GW (Bundesverband Solarwirtschaft 2019). The proliferation of PV systems provides a unique opportunity to characterise global irradiance with unprecedented spatiotemporalresolution, which in turn will allow for highly resolved PV power forecasts.
In view of the rapid growth of solar power installations worldwide, accurate forecasts of photovoltaic (PV) power generation are becoming increasingly indispensable for the overall stability of the electricity grid. In the context of household energy storage systems, PV power forecasts contribute towards intelligent energy management and control of PV-battery systems, in particular so that self-sufficiency and battery lifetime are maximised. Typical battery control algorithms require day-ahead forecasts of PV power generation, and in most cases a combination of statistical methods and numerical weather prediction (NWP) models are employed. The latter are however often inaccurate, both due to deficiencies in model physics as well as an insufficient description of irradiance variability.
The rapid increase in solar photovoltaic (PV) installations worldwide has resulted in the electricity grid becoming increasingly dependent on atmospheric conditions, thus requiring more accurate forecasts of incoming solar irradiance. In this context, measured data from PV systems are a valuable source of information about the optical properties of the atmosphere, in particular the cloud optical depth (COD). This work reports first results from an inversion algorithm developed to infer global, direct and diffuse irradiance as well as atmospheric optical properties from PV power measurements, with the goal of assimilating this information into numerical weather prediction (NWP) models.
The electricity grid of the future will be built on renewable energy sources, which are highly variable and dependent on atmospheric conditions. In power grids with an increasingly high penetration of solar photovoltaics (PV), an accurate knowledge of the incoming solar irradiance is indispensable for grid operation and planning, and reliable irradiance forecasts are thus invaluable for energy system operators. In order to better characterise shortwave solar radiation in time and space, data from PV systems themselves can be used, since the measured power provides information about both irradiance and the optical properties of the atmosphere, in particular the cloud optical depth (COD). Indeed, in the European context with highly variable cloud cover, the cloud fraction and COD are important parameters in determining the irradiance, whereas aerosol effects are only of secondary importance.