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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.
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.
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.
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.
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.
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 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.
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.
Synthesis of Substituted Hydroxyapatite for Application in Bone Tissue Engineering and Drug Delivery
(2019)
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.
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.
Estimating the impact of successful completion of vocational education on employment outcomes
(2019)
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.