The marine electric field observation technology is widely used in the military field such as subsea oil and gas hydrate exploration as well as the electric field detection of warship. To achieve low noise detection o...
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ISBN:
(纸本)9781315737515;9781138027053
The marine electric field observation technology is widely used in the military field such as subsea oil and gas hydrate exploration as well as the electric field detection of warship. To achieve low noise detection of weak seafloor electric signals, one of its key technologies is the low noise marine electric field sensor. For a group of electrolysis technology developed electrodes, in order to detect whether they meet the expected targets, it is necessary to carry out a comparison test for its various techniques. Our test gives an evaluation mainly on signal conversion capability, difference potential stability and self-noise of the electric field sensor. Through establishing a series of test solutions, the original test results of different electrodes were gotten. The analyzed results show that the electrode fully achieve the expected goals, it also proves the effectiveness of the test solution.
Real-time location systems (RTLS) for persons and objects are gaining high interest for consumer and industrial applications. Information about position allows the creation of intelligent context, which enables a grea...
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ISBN:
(纸本)9781479909599
Real-time location systems (RTLS) for persons and objects are gaining high interest for consumer and industrial applications. Information about position allows the creation of intelligent context, which enables a great variety of value-added or even new services. There is no one localization technology that fits all application scenarios. But the unique aspects of ultra-wide band (UWB) make it a very promising technology to realize diverse kinds of ranging and positioning systems, especially in the very harsh industrial environments. In this paper, a research project on 3D positioning using UWB technology is presented along with the project objectives and expected outcomes. The project is funded by the National Science, Technology and Innovation Plan (NSTIP) in Saudi Arabia, and is being performed at Umm Al-Qura University. The research work contributes to the field of wireless communications and wireless sensor networks (WCWSN), which is an initiative of the narrowed focus of the Electronics, Communications and Photonics (ECP) program that was selected based on the specific needs and objectives of Saudi Arabia and was also included in the research priorities of the NPSTI. The major aspects of the ECP program in addition to description of achieved project work are provided.
In the field of wireless sensor networks, missing data has been an issue of widespread concern. In this paper, an improved algorithm based on different data types, is proposed. Missing data is estimated by a new algor...
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ISBN:
(纸本)9781849199704
In the field of wireless sensor networks, missing data has been an issue of widespread concern. In this paper, an improved algorithm based on different data types, is proposed. Missing data is estimated by a new algorithm ,which is based on a variety of data types. Data, which is dynamic and transitional, is a correlative of missing data. And the multiple linear regression model is used to solve the problem of missing data whose type of value is different from the others. The proposed algorithm can not only ensures the normal data transmission, but also improves the traditional methods in dealing with the problem of the incompleteness of multiple data. Furthermore, the proposed algorithm avoids the limitations of the traditional methods for estimating real-time data.
In Wireless sensor and Actuator Networks (WSANs) sensor and actuator devices are connected through radio links to perform tasks in many different contexts. Conventionally, applications for WSANs are developed using tr...
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In recent years, industrial wireless sensor network is one of the important applications in Internet of Things. Routing technology plays a vital role in the industrial networks. The design of routing protocol that det...
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High-rise commercial and residential buildings are very common in today's modern cities and are subject to fires and gas leaks. When such buildings collapse, however, it is imperative that methods for the rescue a...
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The issues exist in the traditional environmental monitoring system for the campus, such as high costs, inflexibility deployment of instrument and so on. There are various kinds of solutions that make use of wireless ...
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ISBN:
(纸本)9781849199704
The issues exist in the traditional environmental monitoring system for the campus, such as high costs, inflexibility deployment of instrument and so on. There are various kinds of solutions that make use of wireless sensor networks (WSNs) for environmental monitoring. However, they are not the most appropriate solution for the environmental monitoring in the campus because of longer than desired development cycles. In this paper, it proposes WSNs prototype for environmental monitoring in the campus based on Arduino open source platform. The design of system is described in detail, which includes sensor nodes, sink nodes and the server. The experiment shows that the system is reasonable and feasible, it can realize timely collection, and works stable during data processing.
The problem of monitoring a network by placing a minimum number of sensor devices in the system is modelled as the vertex covering problem (VCP) in graphs. A set S of vertices of a graph G = (V, E) is called a vertex ...
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A Wireless sensor Network consists of sensor nodes distributed over the region that communicate among them through the wireless medium. Wireless sensor Network must be managed automatically with minimum number of huma...
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People engage in routine behaviors. Automatic routine discovery goes beyond low-level activity recognition such as sitting or standing and analyzes human behaviors at a higher level (e. g., commuting to work). With re...
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ISBN:
(纸本)9781479934454
People engage in routine behaviors. Automatic routine discovery goes beyond low-level activity recognition such as sitting or standing and analyzes human behaviors at a higher level (e. g., commuting to work). With recent developments in ubiquitous sensortechnologies, it becomes easier to acquire a massive amount of sensor data. One main line of research is to mine human routines from sensor data using parametric topic models such as latent Dirichlet allocation. The main shortcoming of parametric models is that it assumes a fixed, pre-specified parameter regardless of the data. Choosing an appropriate parameter usually requires an inefficient trial-and-error model selection process. Furthermore, it is even more difficult to find optimal parameter values in advance for personalized applications. In this paper, we present a novel nonparametric framework for human routine discovery that can infer high-level routines without knowing the number of latent topics beforehand. Our approach is evaluated on public datasets in two routine domains: a 34-daily-activity dataset and a transportation mode dataset. Experimental results show that our nonparametric framework can automatically learn the appropriate model parameters from sensor data without any form of model selection procedure and can outperform traditional parametric approaches for human routine discovery tasks.
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