113,278 research outputs found
Integration of decision support systems to improve decision support performance
Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes
Identifying Agile Requirements Engineering Patterns in Industry
Agile Software Development (ASD) is gaining in popularity in today´s business world. Industry is adopting agile methodologies both to accelerate value delivery and to enhance the ability to deal with changing requirements. However, ASD has a great impact on how Requirements Engineering (RE) is carried out in agile environments. The integration of Human-Centered Design (HCD) plays an important role due to the focus on user and stakeholder involvement. To this end, we aim to introduce agile RE patterns as main objective of this paper. On the one hand, we will describe our pattern mining process based on empirical research in literature and industry. On the other hand, we will discuss our results and provide two examples of agile RE patterns. In sum, the pattern mining process identifies 41 agile RE patterns. The accumulated knowledge will be shared by means of a web application.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Economía y Competitividad TIN2015-71938-RED
Efficient Opportunistic Sensing using Mobile Collaborative Platform MOSDEN
Mobile devices are rapidly becoming the primary computing device in people's
lives. Application delivery platforms like Google Play, Apple App Store have
transformed mobile phones into intelligent computing devices by the means of
applications that can be downloaded and installed instantly. Many of these
applications take advantage of the plethora of sensors installed on the mobile
device to deliver enhanced user experience. The sensors on the smartphone
provide the opportunity to develop innovative mobile opportunistic sensing
applications in many sectors including healthcare, environmental monitoring and
transportation. In this paper, we present a collaborative mobile sensing
framework namely Mobile Sensor Data EngiNe (MOSDEN) that can operate on
smartphones capturing and sharing sensed data between multiple distributed
applications and users. MOSDEN follows a component-based design philosophy
promoting reuse for easy and quick opportunistic sensing application
deployments. MOSDEN separates the application-specific processing from the
sensing, storing and sharing. MOSDEN is scalable and requires minimal
development effort from the application developer. We have implemented our
framework on Android-based mobile platforms and evaluate its performance to
validate the feasibility and efficiency of MOSDEN to operate collaboratively in
mobile opportunistic sensing applications. Experimental outcomes and lessons
learnt conclude the paper
Distributed Management of Massive Data: an Efficient Fine-Grain Data Access Scheme
This paper addresses the problem of efficiently storing and accessing massive
data blocks in a large-scale distributed environment, while providing efficient
fine-grain access to data subsets. This issue is crucial in the context of
applications in the field of databases, data mining and multimedia. We propose
a data sharing service based on distributed, RAM-based storage of data, while
leveraging a DHT-based, natively parallel metadata management scheme. As
opposed to the most commonly used grid storage infrastructures that provide
mechanisms for explicit data localization and transfer, we provide a
transparent access model, where data are accessed through global identifiers.
Our proposal has been validated through a prototype implementation whose
preliminary evaluation provides promising results
The future of technology enhanced active learning – a roadmap
The notion of active learning refers to the active involvement of learner in the learning process,
capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap,
the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a
best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap
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