362 research outputs found

    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

    An electro-mechanical contact formulation for DRY/WET electrode-scalp interfaces in an EEG headset

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    The process of generating an initial prototype for a new dry electrode wearable EEG headset system design can be time and resource intensive. The ability to predict the mechanical and electrical characteristics of this recording device could lead to major cost savings in this process. Since the skin surface roughness has a deep impact on the decrease of brain electric contact conductance (or the increase of the contact impedance) when electrode with bristles contact scalp skin, the estimation of electric conductance across rough dry and wet boundaries is a challenging task in the designing optimization of the wearable EEG headset system. In this contribution, the contact mechanism to predict the electrical impedance of scalp skin pressed against the electrode is considered as the electrical connection by the mechanical contact. With this, we have extended the Pohrt and Popov model by including the effects of conductive gel. An experiment is developed and carried-out to validate the interfacial contact impedance model

    Research Findings on Empirical Evaluation of Requirements Specifications Approaches

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    Numerous software requirements specification (SRS) approaches have been proposed in software engineering. However, there has been little empirical evaluation of the use of these approaches in specific contexts. This paper describes the results of a mapping study, a key instrument of the evidence-based paradigm, in an effort to understand what aspects of SRS are evaluated, in which context, and by using which research method. On the basis of 46 identified and categorized primary studies, we found that understandability is the most commonly evaluated aspect of SRS, experiments are the most commonly used research method, and the academic environment is where most empirical evaluation takes place

    Discovering Strategies to Improve Business Value in Outsourcing Projects

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    This paper deals with the problem of leveraging client business value in a software development outsourcing relationship. We have observed software development projects from two different Dutch IT outsourcing companies and studied the approach they apply in their (successful) projects. The results show that they create a role dedicated to facilitate communication. This arrangement has the potential to put team members in a better position to communicate, facilitating the transfer of information supporting the rationale behind design decisions. Teams are thus better equipped to anticipate change and to react faster in solving everyday problems. This paper describes our observations and the practical implications we expect, such as the improvement of re-buy intention on the client's side

    Sharing e-Health information through ontological layering

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    e-Health information, including patient clinical and demographic data, is very often dispersed across various environments, which either generate them or retrieve them from different sources. Healthcare professionals often need related e-health information in order to obtain a more comprehensive picture of a patient's health status. There are many obstacles to retrieving information and data from heterogeneous sources. In this paper we show that our ontological layering helps in (a) classifying requests imposed by healthcare professionals when retrieving e-health information from heterogeneous sources and (b) resolving semantic heterogeneities across repositories and composing an adequate answer to issued requests. We use a layered software architectural model based on Generic ontology for Context-aware, Interoperable and Data sharing (Go- CID) software applications, applicable to e-Health environments. Ontological layering and reasoning have been demonstrated with semantic web technologies

    Analyzing the Impact of Airborne Particulate Matter on Urban Contamination with the Help of Hybrid Neural Networks

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    In this study, particulate matter (PM), total suspended particulate (TSP), PM10, and PM2.5 fractions) concentrations were recorded in various cities from south of Romania to build the corresponding time series for various intervals. First, the time series of each pollutant were used as inputs in various configurations of feed-forward neural networks (FANN) to find the most suitable network architecture to the PM specificity. The outputs were evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), and Pearson correlation coefficient (r) between observed series and output series. Second, each time series was decomposed using Daubechies wavelets of third order into its corresponding components. Each decomposed component of a PM time series was used as input in the optimal feed-forward neural networks (FANN) architecture established in the first step. The output of each component was re-included to form the modeled series of the original pollutant time series

    How to Build a Patient-Specific Hybrid Simulator for Orthopaedic Open Surgery: Benefits and Limits of Mixed-Reality Using the Microsoft HoloLens

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    Orthopaedic simulators are popular in innovative surgical training programs, where trainees gain procedural experience in a safe and controlled environment. Recent studies suggest that an ideal simulator should combine haptic, visual, and audio technology to create an immersive training environment. This article explores the potentialities of mixed-reality using the HoloLens to develop a hybrid training system for orthopaedic open surgery. Hip arthroplasty, one of the most common orthopaedic procedures, was chosen as a benchmark to evaluate the proposed system. Patient-specific anatomical 3D models were extracted from a patient computed tomography to implement the virtual content and to fabricate the physical components of the simulator. Rapid prototyping was used to create synthetic bones. The Vuforia SDK was utilized to register virtual and physical contents. The Unity3D game engine was employed to develop the software allowing interactions with the virtual content using head movements, gestures, and voice commands. Quantitative tests were performed to estimate the accuracy of the system by evaluating the perceived position of augmented reality targets. Mean and maximum errors matched the requirements of the target application. Qualitative tests were carried out to evaluate workload and usability of the HoloLens for our orthopaedic simulator, considering visual and audio perception and interaction and ergonomics issues. The perceived overall workload was low, and the self-assessed performance was considered satisfactory. Visual and audio perception and gesture and voice interactions obtained a positive feedback. Postural discomfort and visual fatigue obtained a nonnegative evaluation for a simulation session of 40 minutes. These results encourage using mixed-reality to implement a hybrid simulator for orthopaedic open surgery. An optimal design of the simulation tasks and equipment setup is required to minimize the user discomfort. Future works will include Face Validity, Content Validity, and Construct Validity to complete the assessment of the hip arthroplasty simulator
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