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In this paper, we proposed a registration method by combining the morphological component analysis (MCA) and scale-invariant feature transform (SIFT) algorithm. This method uses the perception dictionaries, and combines the Basis-Pursuit algorithm and the Total-Variation regularization scheme to extract the cartoon part containing basic geometrical information from the original image, and is stable and unsusceptible to noise interference. Then a smaller number of the distinctive key points will be obtained by using the SIFT algorithm based on the cartoon part of the original image. Matching the key points by the constrained Euclidean distance, we will obtain a more correct and robust matching result. The experimental results show that the geometrical transform parameters inferred by the matched key points based on MCA+SIFT registration method are more exact than the ones based on the direct SIFT algorithm.

An adaptive tensor voting algorithm combined with texture spectrum is proposed. The image texture spectrum is used to get the adaptive scale parameter of voting field. Then the texture information modifies both the attenuation coefficient and the attenuation field so that we can use this algorithm to create more significant and correct structures in the original image according to the human visual perception. At the same time, the proposed method can improve the edge extraction quality, which includes decreasing the flocculent region efficiently and making image clear. In the experiment for extracting pavement cracks, the original pavement image is processed by the proposed method which is combined with the significant curve feature threshold procedure, and the resulted image displays the faint crack signals submerged in the complicated background efficiently and clearly.

INTRODUCTION: Based on reports, infection with Mycobacterium tuberculosis is believed to induce the development of antibodies that are considered to be biological indicators for the diagnosis of some other diseases. However, conflicting results have been published regarding the presence of antineutrophil cytoplasmic antibodies (ANCAs) in patients with tuberculosis. We aim to study the seroprevalence of ANCA in a population of Chinese patients with tuberculosis, which may lead to the misdiagnosis of vasculitic disorders. METHODS: The study was conducted from January 2016 to May 2017 to evaluate the presence of ANCA in 103 Chinese patients using indirect immunofluorescent assay. An enzyme-linked immunosorbent assay was performed for anti-myeloperoxidase (MPO) and anti-proteinase 3 (PR3) detection. RESULTS: Perinuclear ANCA (p-ANCA) was detected in 4.8% (5/103) of patients, whereas cytoplasmic ANCA (c-ANCA) was not detected; 1.9% (2/103) of patients with tuberculosis was positive for anti-MPO antibodies, and none had anti-PR3 antibodies. Both anti-MPO-positive patients were diagnosed with ANCA-associated vasculitides. CONCLUSIONS: ANCA positivity may be more related to vasculitis and immunological disorders than to a M. tuberculosis infection. Therefore, to improve diagnostic accuracy, patients with M. tuberculosis who are ANCA positive should be investigated for concurrent diseases, including the effects of drugs. Therefore, even in tuberculosis epidemic area, ANCA seropositivity, detected by ELISA, is still more suggestive of ANCA-associated vasculitides.

Wireless transmission of electric power efficiently in itself is a challenge, even more in a seawater environment. This paper focuses on methodology and apparatus for such an environment. Through design and experimentation, a structure was devised, which could transmit electric power efficiently. A system parameter was changed to optimize transmission efficiency and structure. A comparison test with different parameters was performed. The results were normalized in reference to that in the air. In the latter case, efficiency up to 90% could be achieved. The present work reveals that the efficiency of wireless power transmission in the sea water is lower than that in the air. The best structure's efficiency could be up to ~90% of that in the air. The efficiency has a strong dependency on the structure.

The car engine failures in the course of time and place have many possibilities. The engine fault diagnosis system developed in .NET platform. The core of the system make use of noise wavelet energy features and non-linear support vector machine classification. After the experiment, the system has fairly good results.

Engine is a core component. It’s performance is important to the production safety, it will affect production efficiency. At the conclusion of other types of fault diagnosis method, proposed the engine fault diagnosis technology is based on SVM and noise analysis and do some pilot studies. The method can be used to early diagnosis, and can quickly and easily find fault.

Due to the different structure of the machine parts, machine vibrations sent audio signal have different frequency. The early defect, audio signal can be analyzed well by wavelet packet transform. After wavelet packet decomposition and reconstruction, Audio signal noise reduced. And then through high and low frequency decomposition, we can constitute the energy characteristics. The experiment shows: the extracted features have good structure.

Traditional laser ranging system has a poor phase measuring accuracy, low anti-jamming capability and time-consuming measurement. A multi-frequency modulation laser range finder method is proposed in this paper. System uses phase detection algorithm to calculate the sine of ranging phase for noisy environments, and the angle is calculated by Coordinate Rotation Digital Computer(CORDIC) angle solver algorithm. When the sampling frequency is 500MHz, the word length is 16-bits, the SNR is 12dB, the measurement range is 100m, the phase difference resolution is higher than 0.0213°, and the distance accuracy is 0.10mm. Experiments proved that the system can meet the need of high-accuracy and low computational complexity.

In order to keep sustainable excellent, the corporation must constantly innovate on creating market values, that is the open innovation of business model. The open business model means enterprise knowledge resources will be shared and transferred, the corporation has to use a variety of ways to manage intellectual property to match the open business model. Based on these, this paper expounds the natures and necessities of business model and the open business model. Also we analyze the mutual influences of the intellectual property rights and open business mode, and put forward to connect intellectual property rights and open business model and build open business model based on intellectual property rights(IPR). Finally we give a successful case analysis, and hope this paper can have certain significances on the innovation of corporation business model.

To realize multiple false targets deception jamming against stepped-frequency ISAR, a method of synthesizing multi-false-targets signal for countering stepped-frequency ISAR is proposed, and the scheme of the image synthesizer to produce multi-false-targets signal against stepped-frequency ISAR is given in this paper. The multi-false-targets signal synthesis theory and system architecture of the image synthesizer is firstly described in detail, furthermore, it is illuminated using the synthesis process of two and three false targets. Then, the simulations to synthesize multiple false targets have been done, and the multiple false targets deception jamming against stepped-frequency is accomplished. The simulation results show that multiple false targets are produced successfully, and this method is effective and feasible.

Anew model for the economic selection of combines and other self-propelled machines is based on engine power as the dependent variable. New sub-models for timeliness costs, labor costs, and price functions improve the selection of a fleet of machines. The annual area of operation and the maximum size of machine available are the most significant input data for fleet operations.