Healthcare information management systems (HIMS) are critical in day-to-day management of large healthcare institutions to provide timely and accurate patient/diagnosis/treatment information, to improve the quality of...
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ISBN:
(纸本)1891706241
Healthcare information management systems (HIMS) are critical in day-to-day management of large healthcare institutions to provide timely and accurate patient/diagnosis/treatment information, to improve the quality of service and to lower the costs. Poor implementation of such systems may cause critical failures, such as inaccurate patient records, wrong treatments. It is necessary to prioritize software quality and process management activities during implementation of HIMS. We have worked with a medium size enterprise, which has a HIMS product, to build an in-house Issue Tracking and Project Management Tool. Using this tool, we have managed to a) collect customer requests automatically, b) plan the projects, c) implement software processes, and d) manage the projects in terms of bug tracking, version control and reporting. We have observed that software development effort per a given task has decreased by 82%. Improvements in the quality of service in HIMS have led to increase in customer satisfaction.
This paper describes gait identification using cumulants of accelerometer data. Accelerometer data of three different walking speeds for each subject (normal, slow and fast) was acquired by a cell phone placed on the ...
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ISBN:
(纸本)9789604741359
This paper describes gait identification using cumulants of accelerometer data. Accelerometer data of three different walking speeds for each subject (normal, slow and fast) was acquired by a cell phone placed on the person's hip. Data analysis was based on gait cycles that were detected first. Cumulants of order from 1 to 4 with lags from 0 to 10 for second, third and fourth order cumulants were calculated from the cycles and used as feature vectors for classification which was accomplished by support vector machines (SVM). Six healthy young subjects participated in the experiment. According to their gait classification the average recognition rate was 93.1%. A similarity measure for discerning different walking types of the same subject was also introduced using principal component analysis (PCA).
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used to map the input space into a high dim...
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ISBN:
(纸本)9781615671090
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used to map the input space into a high dimensional feature space. However, it can perform rather poorly when there are too many dimensions (e.g. for gene expression data) or when there is a lot of noise. In this paper, we investigate the suitability of using a new feature weighting scheme for SVM kernel functions, based on receiver operating characteristics (ROC). This strategy is clean, simple and surprisingly effective. We experimentally demonstrate that it can significantly and substantially boost classification performance, across a range of datasets.
In the last decade, moving horizon estimation (MHE) has emerged as a powerful technique for tackling the problem of estimating the state of a dynamic system in the presence of nonlinearities and disturbances. MHE is b...
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ISBN:
(纸本)9781424477456
In the last decade, moving horizon estimation (MHE) has emerged as a powerful technique for tackling the problem of estimating the state of a dynamic system in the presence of nonlinearities and disturbances. MHE is based on the idea of minimizing an estimation cost function defined on a sliding window composed of a finite number of time stages. The cost function is usually made up of two contributions: a prediction error computed on a recent batch of inputs and outputs;an arrival cost that serves the purpose of summarizing the past data. However, the diffusion of such techniques has been hampered by: i) the difficulty in choosing the arrival cost so as to ensure stability of the overall estimation scheme;ii) the request of an adequate computational effort on line. In this paper, both problems are addressed and possible solutions are proposed. First, by means of a novel stability analysis, it is constructively shown that under very general observability conditions a quadratic arrival cost is sufficient to ensure the stability of the estimation error provided that the weight matrix is adequately chosen. Second, a novel approximate MHE algorithm is proposed that is based on nonlinear programming sensitivity calculations. The approximate MHE algorithm has the same stability properties of the optimal one which make the overall approach suitable to be applied in real settings. Preliminary simulation results confirm the effectiveness of proposed method.
The proprietary nature of existing Content Delivery Networks (CDNs) means they are closed and do not naturally cooperate. A CDN is expected to provide high performance Internet content delivery through global coverage...
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The proprietary nature of existing Content Delivery Networks (CDNs) means they are closed and do not naturally cooperate. A CDN is expected to provide high performance Internet content delivery through global coverage, which might be an obstacle for new CDN providers, as well as affecting commercial viability of existing ones. Finding ways for distinct CDNs to coordinate and cooperate with other CDNs is necessary to achieve better overall service, as perceived by end-users, at lower cost. In this paper, we present an architecture to support peering arrangements between CDNs, based on a Virtual Organization (VO) model. Our approach promotes peering among providers, while upholding user perceived performance. This is achieved through proper policy management of negotiated Service Level Agreements (SLAs) between peers. We also present a Quality of Service (QoS)-driven performance modeling approach for peering CDNs in order to predict the user perceived performance. We show that peering between CDNs upholds user perceived performance by satisfying the target QoS. The methodology presented in this paper provides CDNs a way to dynamically distribute user requests to other peers according to different request-redirection policies. The model-based approach helps an overloaded CDN to return to a normal state by offloading excess requests to the peers. It also assists in making concrete QoS guarantee for a CDN provider. Our approach endeavors to achieve scalability and resource sharing among CDNs through effective peering in a user transparent manner, thus evolving past the current landscape where non-cooperative and distinct CDNs exist.
While supersampling is an essential element for high quality rendering, high sampling rates, routinely employed in offline rendering, are still considered quite burdensome for real-time ray tracing. In this paper, we ...
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Cloud resource providers in a market face dynamic and unpredictable consumer behavior. The way, how prices are set in a dynamic environment, can influence the demand behavior of price sensitive customers. A Cloud reso...
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Event log is the important starting point of any process analysis technique. Existent business process analysis techniques are applied mainly to manual or simulated logs, considering mainly information about control p...
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