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At the end of the battlefield, the efficient networking among combat resources to ensure the real-time and reliable transmission of information is one of the keys to forming information superiority. Network resources will become scarcer in contested environments. According to the mission characteristics and differentiated needs, making full use of the limited network resource to guarantee task is the focus of network attention. Therefore how to optimize the use of limited network resources based on the characteristics of tasks becomes a very important issue. According to the research results in tactical data link and civil mobile communication many researchers have contributed, we compare the representative mission-driven networking technologies and analyze their integral development.

Plant leaves can be used to effectively detect plant diseases. However, the number of images of unhealthy leaves collected from various plants is usually unbalanced. It is difficult to detect diseases using such an unbalanced dataset. We used DoubleGAN (a double generative adversarial network) to generate images of unhealthy plant leaves to balance such datasets. We proposed using DoubleGAN to generate high-resolution images of unhealthy leaves using fewer samples. DoubleGAN is divided into two stages. In stage 1, we used healthy leaves and unhealthy leaves as inputs. First, the healthy leaf images were used as inputs for the WGAN (Wasserstein generative adversarial network) to obtain the pretrained model. Then, unhealthy leaves were used for the pretrained model to generate 64*64 pixel images of unhealthy leaves. In stage 2, a superresolution generative adversarial network (SRGAN) was used to obtain corresponding 256*256 pixel images to expand the unbalanced dataset. Finally, compared with images generated by DCGAN (Deep convolution generative adversarial network). The dataset expanded with DoubleGAN, the generated images are clearer than DCGAN, and the accuracy of plant species and disease recognition reached 99.80 and 99.53 percent, respectively. The recognition results are better than those from the original dataset.

To investigate the effect of Irbesartan on the changes of myocardial advanced glycation end products and their receptor (AGEs-RAGE), and matrix metalloproteinases (MMPs) systems in rat type 2 diabetes myocardial fibrosis model. All male Sprague-Dwaley rats were randomly divided into four groups: control (CON), high glucose and high-caloric diet (HC), type 2 diabetes (T2DM) and Irbesartan + T2DM (Ir+T2DM) groups. At 12th week, the fasting blood glucose (FBG) and fasting serum insulin (FINS) levels, insulin resistance index (IRI), insulin sensitivity index (ISI), body weight (BW), the ratio of heart weight/body weight (H/B), left ventricular weight index (LVWI), and cardiac col I, col III contents, plasma MMP-2, MMP-9 levels were evaluated. The protein expressions of col I, AGE, RAGE, MMP-2, MMP-14, and TIMP-2 were analyzed by Western blot. In the T2DM group, FBG, H/B, LVWI, IRI were increased ( P Impact statement There are about 425 million diabetes patients (20–79 years) in the world according to the International Diabetes Federation Diabetes Atlas – 8th Edition. The cardiovascular complication is one of the major causes of death in diabetes patients. Myocardial fibrosis is one of the serious pathological changes, so investigating the pathogenesis of myocardial fibrosis has the significant value. Our study aims to investigate the effect of Irbesartan (the angiotensin II receptor antagonist) on the changes of AGE-RAGE system and MMP family components, and analyzes the potential mechanisms in type 2 diabetes-induced myocardial fibrosis. Our results provide the theoretical base for better understanding the pathogenesis in type 2 diabetes-induced myocardial complication. It is useful for clinicians to select the effective therapeutic measures for treatment of type 2 diabetes-induced organ fibrosis.

To better implement the interconnections among micro-grids, renewable energy and traditional grid, a novel power router topology is proposed in this paper. It enjoys the advantages of bidirectional power flow, plug-and-play and a general AC and DC port. The power router consists of a converter, a filter and a standard information interface. The converter’s topology has various choices according to the power level of the system. The output filter switches between LC filter and LCL filter according to the converter’s operation mode. The standard information interface grants the power router the ability of plug-and-play. The filter is designed to give the best transient response. Simulation results are presented in this paper to prove the effectiveness and feasibility of the proposed power router topology.

In order to improve the fault detection accuracy for rolling bearings, an automated fault diagnosis system is presented based on lifting wavelet packet transform (LWPT), sample entropy (SampEn), and classifier ensemble. Bearing vibration signals are firstly decomposed into different frequency subbands through a three-level LWPT, resulting in a total of 8 frequency-band signals throughout the third layers of the LWPT decomposition tree. The SampEns of all the 8 components are then calculated as feature vectors. Such a feature extraction paradigm is expected to depict complexity, irregularity, and nonstationarity of bearing vibrations. Moreover, a novel classifier ensemble is proposed to alleviate the effect of initial parameters on the performance of member classifiers and to improve classification effectiveness. Experiments were conducted on electric motor bearings considering various set of fault categories and fault severity levels. Experimental results demonstrate the proposed diagnosis system can effectively improve bearing fault recognition accuracy and stability in comparison with diagnosis methods based on a single classifier.

This paper proposes an intelligent medicine box which can be used to provide safe medication to the elderly who are living alone. The design is based on STM32F103 micro-controller and other intelligent control components. The basic working principle is analyzed as well as the hardware structure. The proposed medicine box is full-automation, high-intelligent and multi-functional which can effectively avoid the health and safety risks caused by the memory declination of the old people.

This paper presents a method for measuring the plasma parameters of a Hall thruster plume based on image diagnostics. A digital camera obtains the plume image, and the RGB (red, green, blue) data extracted from the plume image are related to the light intensity information of different spectral lines. A photographic method for obtaining the electron temperature distribution in the Hall thruster plume is established by using RGB data based on the collisional-radiative (CR) model. The results from this photographic method were compared with published results from measurements made with a Langmuir probe and simulated results. The trends of the electron temperature distribution were similar to those results. The limitations and application of the photographic method, which could ensure that it is suitable for diagnosing the plasma parameters of the in-orbit Hall thruster plume, are also discussed.

With the deepening of social informatization, almost every aspect of the key industries of national economy is reflected on the internet, such as industrial structure, industrial distribution, industrial-scale, industrial development, industrial policies and so on. How to use these massive free industrial data on the internet effectively becomes more and more important for industrial rule exploration and industrial policy formulation. Industry is a concept between microeconomic cells and macroscopical economy units. If each microeconomic cell is viewed as a node in networks, then the whole national economy constitutes a complex network, and further, a specific industry is a community of this complex network. In this paper, we propose the concept of internet based industry community and two discovery algorithms, and then apply them to industry survey. The case study on fishing industry shows that internet based industry community can offer constructive information in tasks such as comparative analysis of domestic and foreign industries and hot events tracking.

The robust vibration control of a flexible beam has been investigated by using control scheme. The finite element method and experimental modal test are applied to obtain the model of a beam with piezoelectric actuators and strain gage transducer. Taking into account the uncertain disturbance and measurement noise, the augmented closed-loop system with output weighting is presented by selecting the correct weighting function according to the model of flexible beam. The experimental tests are performed by using dSPACE DS1103. The experimental results show the proposed controller can suppress the effect of external disturbance on output strains and the vibration response of the flexible beam.