The present study utilized motor imaginary-based brain-computer interface technology combined with rehabilitation training in 20 stroke patients. Results from the Berg Balance Scale and the Holden Walking Classificati...
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The present study utilized motor imaginary-based brain-computer interface technology combined with rehabilitation training in 20 stroke patients. Results from the Berg Balance Scale and the Holden Walking Classification were significantly greater at 4 weeks after treatment (P 〈 0.01), which suggested that motor imaginary-based brain-computer interface technology improved balance and walking in stroke patients.
Decision power is very important in group decision making, which effects the final decision making result. When there exists uncertainty in group decision making, it is easy for an expert to express his/her preference...
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security assessment of Thermal Power Plants (TPPs) is one of the important means to guarantee the safety of production in thermal power production enterprises. Essentially, the evaluation of power plant systems relies...
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In this paper, we propose a distributed angle estimation method for wireless sensor network localization with multipath fading. The multiple antenna system is equipped at the anchor and the angle of departure (AOD) ca...
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In this paper, we propose a distributed angle estimation method for wireless sensor network localization with multipath fading. The multiple antenna system is equipped at the anchor and the angle of departure (AOD) can be estimated individually at each sensor node with single antenna system. Further, we exploit the space diversity to improve the estimation performance by deploying multiple parallel arrays at the anchor. Analysis and simulations demonstrate the effectiveness of our method.
The general threshold broadcast encryption is not suitable for the networks with the constraints of computation and energy. In this paper, two constructions of the proper threshold broadcast encryption to these networ...
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Noise is an omnipresent phenomenon. It obscures the real behavior of dynamical system. Lots of methods are proposed to remove the noise contaminating time series. However, almost all the methods consider the noise red...
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Noise is an omnipresent phenomenon. It obscures the real behavior of dynamical system. Lots of methods are proposed to remove the noise contaminating time series. However, almost all the methods consider the noise reduction in the phase space and often sharp points are kept. Different with these methods, this paper proposes a method directly on the time series itself, considering the gauss noise feature and the smoothness of the real data, uses curve-fitting way to eliminate the sharp points. The numeral results verify the effectiveness of our method.
In a Wireless Sensor Networks (WSN), there are normally one or several sensor nodes working as Access Points (AP), which are able to provide a relay for other sensors to an external Internet connection. Since WSNs are...
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In a Wireless Sensor Networks (WSN), there are normally one or several sensor nodes working as Access Points (AP), which are able to provide a relay for other sensors to an external Internet connection. Since WSNs are resource constrained, the selection of APs is very crucial in economizing power usage. In this paper, we study the optimal selection of APs to maximize the WSN lifetime. This issue is closely related to routing protocols in WSN. We propose a new adaptive multi-path routing protocol to reduce the energy consumption and guarantee QoS requirements with respect to transmission delay. In this paper, we formulate the issues we mentioned above as a non-linear NP-hard optimization problem. Due to the high computation complexity of this problem, we proposed two polynomial-time approximation algorithms to optimally select APs in the WSN that based on the framework in. Combining with our new adaptive multi-path routing protocol, our preliminary simulation results show that our schemes can save more than 20% energy compared with the existing APs selection schemes with single path routing protocols.
Replica management method has been widely used in distributed file system to improve parallelism and reliability. Traditional replica management method is synchronous replication management (SRM) which updates replica...
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Replica management method has been widely used in distributed file system to improve parallelism and reliability. Traditional replica management method is synchronous replication management (SRM) which updates replicas synchronously. Because of synchronous updating, it is difficult to provide high throughput and low access latency. If the system achieves SRM in the memory hierarchy, it will take a lot of memory space. In order to improve write performance, we design a Two Layered Replica Management Method (TLRMM) based on memory and disk. It can be used for disk-based or memory-based data storage system. TLRMM maintains 3 replicas for every chunk and store one in memory. Using asynchronous update, it can improve the system's I/O performance significantly. We integrated TLRMM in Carrier which is a distributed file system designed by Tsinghua University, and use version number to ensure replica consistency. Furthermore, in order to ensure the reliability of Carrier, we design a replica recovery strategy to solve the failure of single point. We have implemented and evaluated the integrated prototype system. The experimental results show that TLRMM can deliver high performance on distributed file system. Compared with SRM, write throughput of TLRMM increased by a factor of 1.62~2.05, without read performance degradation.
Rough set theory, proposed by Pawlak, has been proved to be a mathematical tool to deal with vagueness and uncertainty in intelligent information processing. In this paper, we propose the concept of knowledge granulat...
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Rough set theory, proposed by Pawlak, has been proved to be a mathematical tool to deal with vagueness and uncertainty in intelligent information processing. In this paper, we propose the concept of knowledge granulation in interval-valued informationsystems, and discuss some important properties. From these properties, it can be shown that the proposed knowledge granulation provides important approaches to measuring the discernibility of different knowledge. It may be helpful for rule evaluation and knowledge discovery in interval-valued informationsystems.
Online Social Networks (OSNs) are becoming immensely popular nowadays, and they change the ways people think and live. In this paper, we propose a novel reputation system which allows users to find potential connectio...
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Online Social Networks (OSNs) are becoming immensely popular nowadays, and they change the ways people think and live. In this paper, we propose a novel reputation system which allows users to find potential connections between unfamiliar people based on the most updated friend list of each user in OSNs. To some extent, our scheme provides a way to judge people in OSNs without real interactions, but based on the existing overall attitudes on particular people. Moreover, our scheme can protect the confidentially of the potential relationships in which no one is able to acquire the detailed connections between two end nodes. Contrary to those which publish each individual's reputation online, we treat the reputation value in our system as a private issue that has been carefully guaranteed.
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