The presentation of management information on screens and paper is aimed at the initiation of control actions in order to bring about predefinied goals. The terms and concepts used in this control information can be interptreted in different ways. It is of vital importance that adequate definitions for these terms and concepts are provided, because of the area of tension betrween those that control and those being controlled. The creation of a common conceptual framework and the maintenance of concepts and definitions can be supported by the construction of an organization-specific lexicon and the use of modern IT tools.
The purpose of the research was the development of a questionnaire that can measure the behaviour of groups of students (for instance departments' cohorts) in Personal Information Management (PIM). Variables for the questionnaire were derived from the international literature on PIM. The questionnaire has been tested out on 79 students (last year before graduation) from four different departments of the Academy of ICT&Media at The Hague University of Applied Sciences. The students' responses were checked on consistency, item non response, desirability bias and information value of the results. All these criteria indicated that the questionnaire is an adequate tool for the assessment of PIM at an institutional level. The results that have been found for the four departments have not yet been discussed with the managers of the Academy and those of the individual departments. [De hier gepubliceerde versie is het 'accepted paper' van het origineel dat is gepubliceerd op www.springerlink.com . De officiële publicatie kan worden gedownload op http://www.springerlink.com/content/n0h3k71u85024xnt/]
For the integrated implementation of Business Process Management and supporting information systems many methods are available. Most of these methods, however, apply a one-size fits all approach and do not take into account the specific situation of the organization in which an information system is to be implemented. These situational factors, however, strongly determine the success of any implementation project. In this paper a method is provided that establishes situational factors of and their influence on implementation methods. The provided method enables a more successful implementation project, because the project team can create a more suitable implementation method for business process management system implementation projects.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
Family Dairy Tech Sustainable and affordable stable management systems for family dairy farms in India. An example of Dutch technology that is useful to an ?emerging economy?. Summary Problem The demand for dairy products in India is increasing. Small and medium-sized family farmers want to capitalize on this development and the Indian government wants to support them. Dutch companies offer knowledge and a wide range of products and services to improve dairy housing systems and better milk quality, in which India is interested. However, the Dutch technology is sophisticated and expensive. For a successful entry into this market, entrepreneurs have to develop affordable and robust (?frugal?) systems and products adapted to the Indian climate and market conditions. The external question is therefore: ?How can Dutch companies specialised on dairy housing systems adapt their products and offer these on the Indian market to contribute to sustainable and profitable local dairy farming??. Goal Since 2011, VHL University of Applied Sciences (VHL) is collaborating with a college and an agricultural information center Krishi Vigyan Kendra (KVK), Baramati, Pune district, Maharashtra State India. In this region many small-scale dairy farmers are active. Within this project, KVK wants to support farmers to scale up their farm form one or a few cows up to 15 to 100 cows, with a better milk quality. In this innovative project, VHL and Saxion Universities of Applied Sciences, in collaboration with KVK and several Dutch companies want to develop integrated solutions for the growing number of dairy farms in the State of Maharashtra, India. The research questions are: 1. "How can, by smart combinations of existing and new technologies, the cow-varieties and milk- and stable-management systems in Baramati, India, for family farmers be optimized in an affordable and sustainable way?" 2. "What are potential markets in India for Dutch companies in the field of stable management and which innovative business models can support entering this market?" Results The intended results are: 1. A design of an integral stable management system for small and medium-sized dairy farms in India, composed of modified Dutch technologies. 2. A cattle improvement programme for robust cows that are adapted to the conditions of Maharashtra. 3. An advice to Dutch entrepreneurs how to develop their market position in India for their technologies. 4. An advice to Indian family farmers how they can increase their margins in a sustainable way by employing innovative technologies.
