6,992 research outputs found

    Wearable learning tools

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    In life people must learn whenever and wherever they experience something new. Until recently computing technology could not support such a notion, the constraints of size, power and cost kept computers under the classroom table, in the office or in the home. Recent advances in miniaturization have led to a growing field of research in ‘wearable’ computing. This paper looks at how such technologies can enhance computer‐mediated communications, with a focus upon collaborative working for learning. An experimental system, MetaPark, is discussed, which explores communications, data retrieval and recording, and navigation techniques within and across real and virtual environments. In order to realize the MetaPark concept, an underlying network architecture is described that supports the required communication model between static and mobile users. This infrastructure, the MUON framework, is offered as a solution to provide a seamless service that tracks user location, interfaces to contextual awareness agents, and provides transparent network service switching

    Context Mining with Machine Learning Approach: Understanding, Sensing, Categorizing, and Analyzing Context Parameters

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    Context is a vital concept in various fields, such as linguistics, psychology, and computer science. It refers to the background, environment, or situation in which an event, action, or idea occurs or exists. Categorization of context involves grouping contexts into different types or classes based on shared characteristics. Physical context, social context, cultural context, temporal context, and cognitive context are a few categories under which context can be divided. Each type of context plays a significant role in shaping our understanding and interpretation of events or actions. Understanding and categorizing context is essential for many applications, such as natural language processing, human-computer interaction, and communication studies, as it provides valuable information for interpretation, prediction, and decision-making. In this paper, we will provide an overview of the concept of context and its categorization, highlighting the importance of context in various fields and applications. We will discuss each type of context and provide examples of how they are used in different fields. Finally, we will conclude by emphasizing the significance of understanding and categorizing context for interpretation, prediction, and decision-making

    M-health review: joining up healthcare in a wireless world

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    In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

    Context Aware Adaptable Applications - A global approach

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    Actual applications (mostly component based) requirements cannot be expressed without a ubiquitous and mobile part for end-users as well as for M2M applications (Machine to Machine). Such an evolution implies context management in order to evaluate the consequences of the mobility and corresponding mechanisms to adapt or to be adapted to the new environment. Applications are then qualified as context aware applications. This first part of this paper presents an overview of context and its management by application adaptation. This part starts by a definition and proposes a model for the context. It also presents various techniques to adapt applications to the context: from self-adaptation to supervised approached. The second part is an overview of architectures for adaptable applications. It focuses on platforms based solutions and shows information flows between application, platform and context. Finally it makes a synthesis proposition with a platform for adaptable context-aware applications called Kalimucho. Then we present implementations tools for software components and a dataflow models in order to implement the Kalimucho platform

    Location Based Reminder System: L-Minder System

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    A reminder plays an important role in every day life for everyone. People use various methods to remind themselves about daily tasks, events, meetings and etc. For example they use to-do list, stick notes, and date-time reminders in mobile phone. This research focuses on the development of location based reminder, a method of reminding people deployed on mobile phones. It implements the concept of context-aware in ubiquitous and is supported by location detection by GSMtechnologies. The project, L-Minder, will be an upgraded version of the existing time and date based reminder because of the location awareness and context awareness. The reminder will remind the users about the daily tasks, events, meetings and etc based on the desired location at which these events or tasks needed to be performed. Intensive research and literature review had been done in order to obtain as much useful information data to develop the project. Surveys had been done over a specific group of users to obtain dataon preferences, dislikes and other important information regarding the development of the system. The project will solve many problems that arise from both time and date based reminder and the existing location based reminders in the market

    Data Mining in Ubiquitous Healthcare

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