Applied Mechanics and Materials Vols. 644-650

Abstract: In the three-order polynomial phase signal, HAF can be used to reduce phase order to achieve the phase parameter estimation. The loss of signal to noise ratio in the order reduction processing is serious. In order to reduce the SNR loss, this paper uses CPF to reduce phase order. It requiers two one-dimensional searches to estimate the rate of acceleration and acceleration. The estimated motion parameters are used to compensate the target echo doppler and doppler spectrum expansion can be suppressed. This paper proposes a new maneuvering target detection algorithm with low non-linearity. The algorithm makes use of the cubic phase function (CPF) to estimate target motion parameters and reduce the number of phase order. Simulation demonstrates the effectiveness of the proposed algorithm and the adaptability to low signal noise ratio.

Abstract: Intent recognition is an important problem to address in order to enhance the capabilities of battlefield surveillance systems. It is concerned with finding a priori defined template that possibly are instantiated in the present flow of battle events. Intent recognition requires that many sub problems are solved. For instance, we need to establish which actions are interesting, how to represent these actions, and inferable events and states that can be used for representing them. In this paper we discuss current research efforts and goals concerning template-based intent recognition. We provide a categorization of approaches for intent recognition together with a formalization of the template-based intent recognition problem. We discuss this formalization in the light of an air-ground striking scenario. Finally, we conclude that intent recognition is an important problem to look into for enhancing the overall situation awareness of decision makers.

Abstract: Brinell hardness block plays a vital role in detecting the material mechanics properties in scientific research and production. In this paper, the uncertainty evaluation is described for the measuring results of low scale Brinell Hardness bock based on the propose of low scale Brinell hardness block calibration process, which has certain reference and guiding significance for further improving the calibration level of Brinell hardness.

Abstract: The fault in power system cannot be completely avoided. In this paper, we developed a method to resolve fault localization problems in power system. Though the data acquisition process has been highly automated, the process of assimilating and analyzing data still lags behind. Raw data must be transformed into knowledge in order to help users decide how to respond to the event and implement the necessary actions. A promising technique for substation event analysis using rough set theory is described in this paper. It interprets the data and outputs meaningful and concise information, which improves the performance of a data analysis system and help with the knowledge acquisition process. A substation model was developed to generate various fault scenarios for our case studies to evaluate the performance of the rough set algorithm. The results show that it works well and efficiently with the overwhelming data.

Abstract: Infrastructure changes in the environment have had a huge impact for the growth of crops. For real-time monitoring facilities environment, increase crop yield, the paper takes Jilin agricultural facilities, for example, introduced the greenhouses, sheds and other crops growing environmental monitoring network structures, technical methods of data acquisition and wireless transmission of real-time early warning information dissemination. This method realizes the different sensors compatible protocols and networking technology, the remote server through the unified management of data, enabling real-time alert when data anomalies. Application of the technology, which enables remote monitoring and early warning function effectively solve Jilin agricultural facilities centralized management, improve the level of facility agriculture park management and the ability to deal with abnormal.

Abstract: For the outstanding problems of traditional vehicle foundation braking performance testing systems’ such as lacking of test & analysis methods, inflexible and not easy to carry, a multi-channel Vehicle foundation break performance testing system based on CompactRIO embedded platform and LabVIEW was developed. The system design concept and concrete implementation of the key technologies such as parallel acquisition and data transmission, large data processing and time-frequency noise reduction were all introduces in detail. Actual break test experiment shows the effectiveness and reliability of the system.

Abstract: In order to narrow the range of suspects and clear direction of investigation quickly, a smart stride characteristics test system was designed and development. The system design concept and concrete implementation of the key technologies such as image mosaic, PCA-based stride characteristics extraction and membership test were all introduced in detail. Actual stride characteristics test experiments show the effectiveness of the system.

Abstract: With mobile platform development there are more and more Android-based image processing applications. The principles of four kinds of edge detection algorithms are analyzed in this paper and such algorithms are realized by adopting JNI technology based on android platform. At last the effect and efficiency of such algorithms are also compared and summarized.

Abstract: A portable test system of aeronautic electronic equipment used for UAV is researched and designed in this paper, according to the computer test and control technology. The structure of hardware and software of test system is explained in detail. The system can meet the needs that UAV units test for these devices quickly and efficiently under field-war conditions. The application results indicate that the precision of this test system is up to the demand of UAV weapon system.

Abstract: With the development of network technology and the popularity of network applications, network server attack number and severity are significantly increased; attack alarm data is mostly produced by duplicate and invalid. Classic attribute-oriented induction (Attribute-Oriented Induction, AOI) algorithm is used for conceptual clustering can greatly improve the processing of these data workload, but does not seem to be very effective in actual work. This paper makes a detailed discussion on how to improve the algorithm.With the development of network technology, the number of attacks on web services and severity increased significantly, so intrusion detection system (IDS) has been applied to the field of network security. However, IDS protects network, at the same time also brings a new problem: IDS will produce a lot of alarm data, and most of these alarm data are duplicate and invalid. According to the characteristics of the data, effective dealing with distributed IDS has brought a lot of alarm data, and how to eliminate duplicate or invalid data becomes a realistic problem which is urgent to be solved. Although using classic attribute-oriented Induction (AOI) for conceptual clustering algorithm can greatly improve the processing of these data workload, the algorithm have not achieved the result of simple data processing on computer processing, thus how to improve the algorithm is a urgent subject of work efficiency.