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In the actual work of reconnaissance sonar, without any prior information, an adaptive threshold selection method based on power spectrum entropy is proposed in this paper in order to solve this problem that is poor adaptability of pulse signal detection method. By using the difference between the power spectrum entropy of pulse signal and background noise, the background noise change is to find out. And the detection threshold value is dynamically adjusted, so as to realize that the detection threshold automatically changes with the background change. In this paper, the detection threshold, detection probability and false alarm probability of this method are deduced theoretically under the background of Gaussian white noise. The steps of automatic threshold selection under non-Gaussian background are presented. Through simulation analysis and sea trial data verification, the adaptability and practicability of this method are proved.

In digital sonar system, cross-spectral orientation method is closer for Cramer-Rao lower bound, which is more simple and widely used than other high resolution algorithms. This work introduces a cross-spectral orientation method based on coprime array. In order to show the advantage of the proposed algorithm, the performance is compared with that of the linear.

How to extract useful and key information from the original big wave data with large volume and low information density and establish a wave climate datasets is still in a blank status, which is also urgently needed in the ocean navigation, deep sea development, marine resource development, offshore construction, and disaster prevention and mitigation, etc. Based on the ERA-interim wave data for 1979–2018 and ERA-40 wave reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF), this study adopts the climate statistical analysis methods to establish the first open and public wave climate dataset for the Maritime Silk Road, systematically including the prevailing wave direction and significant wave height (SWH), wave period, swell index (SI), rough sea occurrence, wave direction occurrence, co-occurrence of wave height and wave direction, co-occurrence of wave height and wave period, and extreme wave height. It is hoped that the results can provide a data support for the safe and efficient deployment of marine development and construction.

The target of buildings’ energy efficient is to facilitate a comfortable environment for occupants while maintaining minimal energy consumption. Occupant behaviors pay a large impact in influencing the energy consumption. Time-aware occupancy detection could give information support for intelligent building energy management. In this paper several building occupancy detection methods, which are based on the temporal analysis of historical data, are proposed for providing different size of prediction window occupancy detection. Each proposed approaches are evaluated against accurate real-life data collected from a building. Experiments have been conducted using actual occupancy data under six different time horizons can be used to perform time-aware occupancy states prediction. The experimental results show that Stochastic Gradient Descent (SGD) and Gaussian mixture models-Hidden Markov Model (GMM-HMM) outperforms the other methods for the evaluation. With proposed more accurate time-aware occupancy prediction algorithms, we hope to develop more energy-efficient HVAC(Heating, Ventilation, and Air Conditioning) scheduling systems in order to save energy consumption.

Electrocardiogram (ECG) diagnosis is based on the waveform, duration and amplitude of characteristic wave, which are required to have a high accuracy for ECG signal reconstruction. As an effective nonlinear signal processing method, empirical mode decomposition (EMD) has been widely used for diagnosing and reconstructing the ECG signal, but there are two problems arising here. One is the mode mixing, and the other is that the mode components used in reconstruction are identified by experience. Therefore, the method of reconstruction is not adaptive and universal, and reconstructed ECG signal loses accuracy. Firstly, we propose an improved EMD method, which is called integral mean mode decomposition (IMMD). The analysis of 5000 samples of Gaussian white noise shows that IMMD has better multi-resolution analysis ability than EMD, and it can effectively alleviate mode mixing consequently. Secondly, based on the inherent physical characteristics of ECG signal, cardiac cycle or heart rate (HR), it has practical physical significance to identify the mode components used in ECG signal reconstruction. The cardiac cycle feature acts as the intrinsic mode function (IMF) component through two modes. 1) For the low-order IMF that belongs to the ECG signal, the cardiac cycle feature acts as the amplitude modulation. The envelope of the IMF component has the characteristics of the cardiac cycle, and the frequency corresponding to the maximum amplitude in the spectrum of the envelope is equal to HR. 2) For the high-order IMF that belongs to the ECG signal, the cardiac cycle feature acts as frequency modulation. Those IMF components have the harmonic characteristics of periodic heartbeats, and the maximum amplitude in the spectrum corresponds to an integral multiple of HR (usually 1－3 times). The noise attributed to IMF component cannot show the above two cardiac cycle characteristics. Thus the proposed method is adaptive and universal. The 47 ECG signals with baseline drift and muscle artifact noise are tested. The results show that the proposed method is more effective than the variational mode decomposition (VMD), Haar wavelet with soft threshold, ensemble empirical mode decomposition (EEMD) and EMD. Among the 47 correlation coefficients between reconstructed and original ECG signals, the proposed method has 31 better than VMD, 33 better than Haar wavelet, 42 better than EEMD and 45 better than EMD. The mean of 47 correlation coefficients from the proposed method is 0.8904, and the variance is 0.0071, which shows that the proposed method has good performance and stability.

TV logo is one of the important symbols of TV station. Nowadays TV logo recognition has been widely used in various fields, such as video analysis, video surveillance, video management and so on. According to TV logo's characteristics, a TV logo detection and recognition algorithm based on SURF feature and bag-of-visual-words model is proposed in this paper. First, obtain binary logo images by using the automatic image segmentation method based on Otsu in the region of interest, and then execute AND operation with original images, thereby completing the logo extraction. Second, extract logo images' SURF features, and then use k-means clustering algorithm to construct a visual dictionary, and ultimately use support vector machine (SVM) to complete logo recognition. Experimental results show that the proposed method has high recognition accuracy, strong anti-interference ability and good practicality.

Several models of measuring case similarity in CBR systems are deeply explored. We also discuss the case matching process, and present three matching functions. Finally, we illustrate the significance of the models in CBR(Case Based Reasoning) systems implementation.

Educating and training outstanding engineers involves the government, the institution of higher learning and enterprises. The chief problems of implementing “A Plan for Educating and Training Outstanding Engineers (PETOE)” are how to build an guarantee evaluation index system and determine the guarantee index weight and interaction among indexes. In this paper, the method of Analytic Network Process (ANP) were adopted, eleven indexes, such as the policy, capital and teachers involved in implementing guarantee were analyzed, the guarantee Model and supermatrix of implementing PETOE Based on ANP were built, the SD software was used to find out the convergence state of the associated supermatrix, the stable limit supermatrix, the index weights were calculated and their total sequences of affecting indexes was sorted. The results show that the guarantee model of implementing PETOE based on ANP is reasonable.

The third party logistics-hub (3PL-HUB) is a model of logistics direct delivery stations, and an advanced logistics organization mode. And it can integrate supply-side resources and promote the supply chain coordination. Logistics information system plays a key role for successful implementation of 3PL-HUB. The main objective of the paper is to solve the existing data collection problems in logistics systems, such as lag, inaccuracy, and unreal-time tracking. According to 3PL-HUB and combined with the VPN-based internet, wireless communication and mobile barcode scanning technology, this paper established a mobile logistics management integrated architecture of auto parts, and proposed the business processes based on 3PL-HUB, and constructed the logistics management architecture for auto parts, and some key technologies are studied, such as standardization technology, data synchronization, and PDA development, Finally, through an example, the feasibility and practicality of this system are verified.

In order to response the increased competition, improve the correctness and timeliness of decision-making, enterprises need to make efficient data analysis techniques and methods used in competitive intelligence system. XML combines with Web data mining technology can effectively solve many problems faced by web data mining, significantly improve the efficiency and effect of collection and analysis of competitive intelligence system of enterprise. Then help enterprises win the competitive advantage. Based on the analysis of the existed problems of data mining under web environment, this paper brief introduces competitive intelligence system, XML and web data mining technology, focused on the specific application and the process of realization of XML and web data mining technology in competitive intelligence system. Due to the study of this paper, it will provide a reference for the construction and implementation of competitive intelligence system of enterprise based on XML and web data mining technology.

Facing the rapid development of collaborative design and manufacturing and networked manufacturing, standardization has become one of the important measures which enhance the core competitiveness of enterprises. Focusing on these problems in the process of standardization strategy of the small and medium enterprises (SMEs), such as poor management, weak technical strength and slow standardization progresses, this paper adopted SWOT analysis method, information technology and UML modeling language, proposed the positioning, objectives and measures of standardization strategy, regarded informationization as the basis of standardization strategy, and developed the standard management information system. This system put into application successfully, and its feasibility was verified.

The third-party logistics enterprise direct delivery station is the new model of the collaborative operation in supply chain, the dynamic performance evaluation of supplier is one of the important problems of supplier management. This paper proposed the evaluation system of supplier based on 3PL-HUB direct delivery station, established the supplier expected profit function, and analyzed the strong correlation between purchase price, inventory costs, extension punishments, quality deductions and promise delivery time. As well as it presented the calculation methods of supplier performance evaluation through using the multiplication of utility theory. Finally this paper proved the validity and feasibility of model by an example. And the model was verified by the implementation cases in enterprises. This calculation method is simple, practical and strong maneuverability.

Some measures to preventing the faults of the voltage transformers was introduced. In this paper we lay emphasis on analysis the advantages and questions of the anti-resonance voltage transformer and search the optimum way to improve their characteristics. The optimization results. was proven by the dynamic analog test.