Compared with the large number of disabled population, medical resource is scarce and partially distributed. With the development of Internet and information technology, more and more services can be provided through ...
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Because of the extensive amount of waste water that is discharged during its processes, conventional carpet printing is a big polluting industry. In this paper, we propose a new digital carpet printing method based on...
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Because of the extensive amount of waste water that is discharged during its processes, conventional carpet printing is a big polluting industry. In this paper, we propose a new digital carpet printing method based on traditional textile-printing technology. Our method aims to remove limitations in carpet design and eliminate industry pollution. A series of measures are performed to raise the permeability of acid inks. In addition, a new ink control method is employed to compensate for penetrated color inks. This results in carpet production processes that not only take advantage of digital textile printers, but also satisfy the requirements of carpet production.
Compared with the large number of disabled population,medical resource is scarce and partially *** the development of Internet and information technology,more and more services can be provided through the network,not ...
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Compared with the large number of disabled population,medical resource is scarce and partially *** the development of Internet and information technology,more and more services can be provided through the network,not restricted by *** this context,this paper developed a P2 P instant communication system based on the WebRTC technology and realized a remote rehabilitation guidance *** goal of this system is to make sure that a user can receive remote rehabilitation guidance scheme through computer or mobile *** system has no need to install additional software and *** open web rehabilitation guidance can be realized through a browser only.
In multi-hop wireless ad-hoc networks, packet delivery delay is one of the most important performance metrics. While a lot of research efforts have been spent on measuring and optimizing the end-to-end delay performan...
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In multi-hop wireless ad-hoc networks, packet delivery delay is one of the most important performance metrics. While a lot of research efforts have been spent on measuring and optimizing the end-to-end delay performance, there usually lack accurate and lightweight methods for decomposing the end-to-end delay into the per-hop delay for each packet. Knowledge on the per-hop per-packet delay can greatly improve the network visibility and facilitate network measurement and management. In this paper, we propose Domo, a passive, lightweight and accurate delay tomography approach to decomposing the packet end-to-end delay into each hop. The basic idea is to formulate the problem into a set of optimization problems by carefully considering the constraints among various timing quantities. At the network side, Domo attaches a small overhead to each packet for constructing constraints of the optimization problems. At the PC side, Domo employs semi-definite relaxation and several other methods to efficiently solve the optimization problems. We implement Domo and evaluate its performance extensively using large-scale simulations. Results show that Domo significantly outperforms two existing methods, nearly tripling the accuracy of the state-of-the-art.
To enable sustainable service innovation, services are often subject to changes and variations. In particular, service evolution creates problems in invocation if the service users cannot be notified timely. Therefore...
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Detecting and diagnosing anomalies in networked embedded systems like sensor networks is a very difficult task, due to the variable workloads and severe resource constraints. We notice that most node-level debugging t...
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Detecting and diagnosing anomalies in networked embedded systems like sensor networks is a very difficult task, due to the variable workloads and severe resource constraints. We notice that most node-level debugging tools can provide detailed program information inside the node but fail to detect when and where a problem occurs in the network. On the other hand, most network-level diagnosis tools can effectively detect a problem from the network but fail to narrow down the problem within the node because they lack detailed program information. To close the gap, we propose D2, a new anomaly detection and diagnosis method by combining program profiling and symptom mining. D2 employs binary instrumentation to perform lightweight function count profiling. Based on the statistics, D2 uses PCA (Principal Component Analysis) based approach for automatically detecting network anomalies. Compared to previous methods, D2 is able to point programmers closer to the most likely causes by a novel approach combining statistical tests and program call graph analysis. We implement our method based on TinyOS 2.1.1 and evaluate its effectiveness by case studies in the development of a working sensor network. Results show that our method is effective for detecting and diagnosing problems in real-world sensor network systems, and at the same time, incurs an acceptable overhead.
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