Applied Mechanics and Materials Vols. 738-739

Abstract: This paper introduces the application of IOT technology in the communication room monitoring and asset management in Hubei electric power company, consists of the design of general construction, hierarchical structure and functions. Target for the effective management of communication room power and environment monitoring, communication resources and site operation, applying monitoring and communication features of IOT, to make fast and reasonable configuration of communication resources at benefit maximization, support for the information level of communication room operational & maintenance.

Abstract: The Hong Kong-Zhuhai-Macao Bridge (HZMB), is one of the most significant mega projects in China. It is a combination of bridges, artificial islands and an immersed tunnel with a service life of 120 years. Embedded durability monitoring system are used to obtain the real time concrete durability data of the bridge, in order to better understand the durability degradation of the bridge, and to give data support for future durability redesign,. Herein the durability monitoring system used and the selecting of the monitoring points for the HZMB is presented.

Abstract: A cloud-based security management and control platform is proposed, used in the Safe City security monitoring. The platform includes video monitoring and emergency command system. Video monitoring center, including command centers, branch centers, police center, monitoring the site, and through the client to complete audio and video viewing, playback and other services function. Emergency command system can complete handling emergencies, including tasking, information, resource scheduling, and other functions.

Abstract: As the rapid development of modern society, it's hard for traditional workflow technologies to meet the variant requirements inside an enterprise. The research focus of workflow technology has been moved to flexibly adjustable workflow models that can easily and fast adapt to business change. In terms of this point, a flexible workflow model is put forward based on the UML technology. Several UML diagrams, such as class diagram, activity diagram and sequence diagram, are introduced to illustrate both model elements and detailed working mechanism of the workflow model. In addition, the strategy of flexible adaption is proposed to deal with changes. Based on this model, a general-purpose system of project application and review is designed and implemented, which is able to adapt flexibly to the business flow changes of project applying after putting into use.

Abstract: Automatic Target Recognition (ATR) system is widely utilized in engineering. However, the performance evaluation method for an ATR system is limited. This paper resolves the problem based on the theory of Sugeno fuzzy integration. The performance metrics are firstly measured. Then, a performance evaluation model is developed. Simulation result shows that, compared to the existing technologies, the novel method can offer more objective performance conclusions for an ATR system.

Abstract: Space target detection under the background of stars is one of the key techniques in space based optical measurement. In this paper, we proposed a space target detection algorithm based on star identification. First, the centroid of stars and space target is extracted by FPGA. Then, DSP accomplish space target detection based on the centroid data. Result shows that this method have a good effect on the space target detection.

Abstract: To improve the performance of quantum-inspired evolutionary algorithms (QIEAs), a new kind of QIEAs——elite group guided QIEA (EQIEA) are proposed through introducing an elite group guidance updating approach to solve knapsack problems. In EQIEA, the elite group at each iteration is composed of a certain number of individuals with better fitness values in the current population; all the individuals in the elite group cooperate together to affect quantum-inspired gates to produce off spring. Knapsack problems, a class of well-known NP-complete combinatorial optimization problems, are used to conduct experiments. The choices of parameters in EQIEA are discussed in an empirical way. Extensive experiments show that the EQIEA outperform six variants of QIEAs recently reported in the literature in terms of the quality of solutions. This paper also analyzes the convergence of EQIEA and the six variants of QIEAs. Experimental results show that EQIEA has better convergence than the six variants of QIEAs.

Abstract: This paper presents a new gesture track recognition method based on the depth image information received from the Kinect sensor. First, a Kinect sensor is used to obtain the coordinates of a moving arm. Then, the gesture tracks corresponding to these coordinates are analyzed. Matching and recognition of gesture tracks are implemented by performing golden section search. The results show that this track-based method is highly effective in gesture recognition.

Abstract: As the geographical location of sensors is of great importance in the applications of a wireless sensor network, localization attracts significant research interest. Among the localization methods, received signal strength indicator (RSSI) localization algorithm is widely studied due to its low-cost. However, the radio signal transmission is affected by the factors of channel attenuation and noise, etc. Therefore, the actual location is impossible to estimate. To alleviate the effect of the RSSI measure errors, we proposed a novel error modified method for RSSI location algorithm based on neural network, short for RSSI-NN. First, we use the fitting parameters of the monitoring area to determine the parameters of RSSI model. Second, the distance between anchor node i and the unknown node L_i is calculated. Then, the error modified algorithm based on neural network is proposed. Finally, we can obtain the modified value of the output layer data. Simulations demonstrate that RSSI-NN achieves lower localization error compared with conventional RSSI-based localization algorithm.

Abstract: Firstly, through the principle analysis and simulation experiment, the maneuvering target tracking algorithm of curve model interacting multiple model tracking algorithm was given. Because the algorithm is simple structure and high cost efficiency, it becomes generally applicable algorithm for curve tracking model. But, the target mobility is very high in practice, Single target tracking model is no longer applicable curve tracking model. To improve the accuracy of tracking, the adaptive grid interacting multiple model (AGIMM) algorithm was given. The algorithm has two fatal weaknesses in the practical application. First, the process of maneuvering target tracking, when the model changes and gradient, the tracking precision is not high ;Second, because the changing model structure is very large model sets, the algorithm is complexity and system processing speed is very slow, which cannot be widely used. In order to improve the algorithm and its scope of application, The paper proposed the adaptive Kalman filter adaptive interacting multiple model algorithm (AKFAIMM).The algorithm introduced the parameter in the adaptive Kalman filter, and adjusted parameter in maneuvering target tracking, the parameter was adjusted Continuously in the curve motion model, it could greatly improve the tracking precision and the application of the model. Second, to improve the algorithm complexity. The paper improved on turning curve. The angular velocity estimation method replaced centripetal acceleration estimation method. The estimation method reduced the number of model set and reduced greatly of computation.