There is a growing focus on 24/7 cardiac monitoring that leverages state of the art mobile phones and commercial-off-the-shelf (COTS) wearable bio-sensors. While many signal processing techniques for mobile ECG analys...
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There is a growing focus on 24/7 cardiac monitoring that leverages state of the art mobile phones and commercial-off-the-shelf (COTS) wearable bio-sensors. While many signal processing techniques for mobile ECG analysis have been developed, these techniques tend to be computationally intensive. In this paper, we propose, develop and evaluate a resource-aware and energy-efficient time series analysis technique for real-time ECG analysis on mobile devices based on the well-known SAX (Symbolic Aggregate Approximation) representation for time series termed RA-SAX.
This paper utilizes a theoretically-grounded model of information systems change together with data from 1891 maintenance projects to test the effects that four factors have on the volatility index of application soft...
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This paper utilizes a theoretically-grounded model of information systems change together with data from 1891 maintenance projects to test the effects that four factors have on the volatility index of application software. The volatility index is a measure of the relative cost of doing maintenance on the deep structure of a system. Two factors were found to be associated with a higher volatility index, the age of the system and the size of the system. One factor was found to be associated with a lower volatility index, the use of higher-level languages of implementation. One factor was found to be unrelated to the volatility index, the time period when the change was made. Some factors may be under management control, e.g. the language of implementation, while others are usually system characteristics, e.g. system size. Knowledge of the effects of these factors could influence how researchers work with information systems and how information systems management does its work.
Requirements written in multiple languages can lead to error-proneness, inconsistency and incorrectness. In a Malaysian setting, software engineers are exposed to both Malay and English requirements. This can be a cha...
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Data classification has attracted considerable research attention in the field of computational statistics and data mining due to its wide range of applications. K Best Cluster Based Neighbour (KB-CB-N) is our novel c...
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Data classification has attracted considerable research attention in the field of computational statistics and data mining due to its wide range of applications. K Best Cluster Based Neighbour (KB-CB-N) is our novel classification technique based on the integration of three different similarity measures for cluster based classification. The basic principle is to apply unsupervised learning on the instances of each class in the dataset and then use the output as an input for the classification algorithm to find the K best neighbours of clusters from the density, gravity and distance perspectives. Clustering is applied as an initial step within each class to find the inherent in-class grouping in the dataset. Different data clustering techniques use different similarity measures. Each measure has its own strength and weakness. Thus, combining the three measures can benefit from the strength of each one and eliminate encountered problems of using an individual measure. Extensive experimental results using eight real datasets have evidenced that our new technique typically shows improved or equivalent performance over other existing state-of-the-art classification methods.
The objective behind building domain-specific visual languages (DSVLs) is to provide users with the most appropriate concepts and notations that best fit with their domain and experience. However, the existing DSVL de...
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The objective behind building domain-specific visual languages (DSVLs) is to provide users with the most appropriate concepts and notations that best fit with their domain and experience. However, the existing DSVL designers do not support integrating environment and user context information when modeling, editing or viewing DSVL models at different locations, permissions, devices, etc. In this paper, we introduce HorusCML, a context-aware DSVL designer, which supports DSVL experts in integrating necessary context details within their DSVLs. The resultant DSVLs can reflect different facets, layouts, and behaviours according to context it is used in. We show a case study on developing a context-aware data flow diagram DSVL tool using HorusCML.
A survey has been designed to seek the practical foundation of base process activities (BPAs) in the software industry and to support research in modelling the softwareengineering processes. A superset of BPAs compat...
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A survey has been designed to seek the practical foundation of base process activities (BPAs) in the software industry and to support research in modelling the softwareengineering processes. A superset of BPAs compatible with the current software process models, such as SPICE (ISO 15504), CMM, ISO 9000 and BOOTSTRAP, were identified for the construction of the questionnaires. This paper reports the survey findings on BPAs in softwareengineering processes. A summary of the current softwareengineering process techniques and practices modelled by 83 BPAs in 10 processes and three categories is given. Each BPA is benchmarked on attributes of mean importance and ratios of significance, practice and effectiveness. Based on the benchmarks, and by comparing with the current practice of the reader's organization, recommendations can be given on which specific areas need to have processes established first, and which areas should be highest priority for process improvement.
Real time logic (RTL) was introduced as a formalism for reasoning about the relative and absolute timing properties of computational tasks of discrete real-time systems. Extended real time logic (ERTL) is a formalism ...
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Extended Real Time Logic (ERTL) is proposed for the modelling and analysis of hybrid systems, taking as a basis Real Time Logic (RTL). RTL is a first order logic with uninterpreted predicates which relate events of a ...
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Activity recognition focuses on inferring current user activities by leveraging sensory data available on today's sensor rich environment. Supervised learning has been applied pervasively for activity recognition....
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ISBN:
(纸本)9781479902279
Activity recognition focuses on inferring current user activities by leveraging sensory data available on today's sensor rich environment. Supervised learning has been applied pervasively for activity recognition. Typical activity recognition techniques process sensory data based on point-by-point approaches. In this paper, we propose a novel cluster-based classification for activity recognition systems, termed StreamAR. The system incorporates incremental and active learning for mining user activities in data streams. The novel approach processes activities as clusters to build a robust classification framework. StreamAR integrates supervised, unsupervised and active learning and applies hybrid similarity measures technique for recognising activities. Extensive experimental results using real activity recognition datasets have evidenced that our new approach shows improved performance over other existing state-of-the-art learning methods.
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