Hybrid Convolutional Neural Network for Plant Diseases Prediction

Plant diseases prediction is the essential technique to prevent the yield loss and gain high production of agricultural products.The monitoring of plant health continuously and detecting the diseases is a significant for sustainable agri-culture.Manual system to monitor the diseases in plant is time consuming and report a lot of errors.There is high demand for technology to detect the plant dis-eases automatically.Recently image processing approach and deep learning approach are highly invited in detection of plant diseases.The diseases like late blight,bacterial spots,spots on Septoria leaf and yellow leaf curved are widely found in plants.These are the main reasons to affects the plants life and yield.To identify the diseases earliest,our research presents the hybrid method by com-bining the region based convolutional neural network(RCNN)and region based fully convolutional networks(RFCN)for classifying the diseases.First the leaf images of plants are collected and preprocessed to remove noisy data in image.Further data normalization,augmentation and removal of background noises are done.The images are divided as testing and training,training images are fed as input to deep learning architecture.First,we identify the region of interest(RoI)by using selective search.In every region,feature of convolutional neural network(CNN)is extracted independently for further classification.The plants such as tomato,potato and bell pepper are taken for this experiment.The plant input image is analyzed and classify as healthy plant or unhealthy plant.If the image is detected as unhealthy,then type of diseases the plant is affected will be displayed.Our proposed technique achieves 98.5%of accuracy in predicting the plant diseases.

Visual-simulation region proposal and generative adversarial network based ground military target recognition

Ground military target recognition plays a crucial role in unmanned equipment and grasping the battlefield dynamics for military applications, but is disturbed by low-resolution and noisyrepresentation. In this paper, a recognition method, involving a novel visual attention mechanismbased Gabor region proposal sub-network(Gabor RPN) and improved refinement generative adversarial sub-network(GAN), is proposed. Novel central-peripheral rivalry 3D color Gabor filters are proposed to simulate retinal structures and taken as feature extraction convolutional kernels in low-level layer to improve the recognition accuracy and framework training efficiency in Gabor RPN. Improved refinement GAN is used to solve the problem of blurry target classification, involving a generator to directly generate large high-resolution images from small blurry ones and a discriminator to distinguish not only real images vs. fake images but also the class of targets. A special recognition dataset for ground military target, named Ground Military Target Dataset(GMTD), is constructed. Experiments performed on the GMTD dataset effectively demonstrate that our method can achieve better energy-saving and recognition results when low-resolution and noisy-representation targets are involved, thus ensuring this algorithm a good engineering application prospect.

Comparing of Aviation Network Structure of Mid-south,Northwest and Southwest of China Based on Hierarchical Index Model

In order to compare the aviation network of mid-south,northwest and southwest of China to reveal the structure similarity and difference for providing quantitative evidence to construct regional aviation network and improve its structure,hierarchical index model of regional aviation network was established through dividing the aviation network into layers to research its structure characters.Data matrixes were defined to record the basic state of regional aviation network.Index matrixes were constructed to describe the quantitative features of regional aviation network.On the basis of these indexes,several structure indexes of all layers of aviation network were calculated to show the structure features of aviation network,such as ratio of passenger volume within the region with across the region,share rate of passenger volume among layers,ratio of average number of airline for each airport,ratio of average passenger volume for each airline and ratio of airline rate.According to the statistical data,similar structure of share rate of passenger volume among layers and average passenger volume for each airline in their regional aviation network was found after calculating.But on the side of ratio of passenger volume within the region with across the region,ratio of average number of airlines for each airport and ratio of airline rate were different.

PLANNING DESIGN OF COMPUTER REGION NETWORK

In this paper, authors describe the characters and the present situation of computer region network, Moreover, authors put forward the method to plan and de sign ration ally the computer regional network system depending on the actual situa tion, in order to share the resources of software and hardware resources of the net work in best way and get higher efficiency of information management.

Analysis of datum-instability effect on calculated results of data from Longmen Mountain regional gravity network

A statistical correlation method is used to study the effect of instability of the calculation datum （ used in traditional method of indirect adjustment） on calculated gravity results, using data recorded by Longmen Mountain regional gravity network during 1996 -2007. The result shows that when this effect is corrected, anomalous gravity changes before the 2008 Wenchuan Ms8. 0 earthquake become obvious and characteristically distinctive. Thus the datum-stability problem must be considered when processing and analyzing data recorded by a regional gravity network.

Study on Coordinated Development of Regions Based on the Construction of Enterprise Value Network

Under the background of constructing harmonious economic society, how to realize the coordinated development of regions in the course of region integration is a key problem. According to the relevant theory of enterprise gene reconfiguration and enterprise value network construction, we analyzed the problems in the merging course between the value network construction and region economic growth. Finally, we put forward the basic path of coordinated development of regions.

GRAPH-THEORETIC ALGORITHM FOR SPECTRUM ALLOCATION IN IEEE 802.22 WIRELESS MESH NETWORK

The IEEE 802.22 standard based on wireless Cognitive Radio (CR) is an optimal solution to resolve the inefficient spectrum utility problem. In this paper, we focus on the spectrum allocation in IEEE 802.22 mesh networks and propose a new graph-theory algorithm. The algorithm aims at two objectives: one is the sum of the allocated channel bandwidth is maximum, and the other is the number of users can be active simultaneity is maximum. In this proposed algorithm, the topology of network was modeled as a general graph and could be transformed into a weighted complete bipartite-graph by three processes. The simulations show that the presented algorithm can improve the performance of spectrum allocation.

Wireless Regional Area Networks and Cognitive Radio 2

IEEE has set up in October 2004 the IEEE802.22 Working Group-Wireless Regional Area Network (WRAN) Task Force to work out air interface standard based on Cognitive Radio (CR) technologies. The standard includes Physical Layer (PHY) and Media Access Control (MAC), utilizig the vacant spectrum bands already allocated to broadcast TV without interference.. The WRAN employs CR technologies to sense and estimate the television signals and use the technologies of dynamic spectrum management to find and then allocate vacant spectrums. The CR technologies are representing one of the major trends for future wireless communications. This article on WRANs and CR technologies will be divided into two issues. In this issue, WRANs and IEEE 802.22, CR technologies are introduced. And the second part in the next issue will analyze the applications of CR technologies.

Wireless Regional Area Networks and Cognitive Radio(1)

IEEE has set up in October 2004 the IEEE802.22 Working Group—Wireless Regional Area Network (WRAN) Task Force to work out air interface standard based on Cognitive Radio (CR) technologies. The standard includes Physical Layer (PHY) and Media Access Control (MAC),to use the already allocated fallow spectrums to broadcast TV in a non-interference way. The WRAN employs CR technologies to sense and estimate the television frequencies and use the technologies of dynamic spectrum management to find and then allocate idle spectrums. The CR technologies are representing one of the major trends for future wireless communications. This article on WRANs and CR technologies will be divided into two issues. In this issue,WRANs and IEEE 802.22,CR technologies are introduced. And the second part in the next issue will analyze the applications of CR technologies.

WTO与江苏区域创新网络建设

This article analyzes the challenge for Jiangsu technical innovation caused by entrance into WTO. On the basis of it, this article puts forward some suggestions about how to establish a technical innovation network in Jiangsu having distinguished features, and regards it as one of important countermeasures for improving independent technical innovation ability in Jiangsu and meeting challenge.

Bottom-Up or Top-Down： Which Is the Best Approach to Improve CSR and Sustainability in Local Contexts？ Reflections From Italian Experiences

This paper reflects on the theme of sustainability and territorial social responsibility, which, in this context, is defined as a pathway promoted by a plurality of public and private actors, for- and non-profit, who find that social cohesion and the relationships that are cultivated in the place from which these diverse ＂protagonists＂ come, are the drivers in the construction of shared territorial governance. The efficacy of such processes in the local context （communal, provincial, and regional） is predicated on the culture and on the values that the diverse, networked stakeholders-actors accumulate in their territory （meso level）. In developing this theme, the paper is divided into several parts. The first part describes the theoretical context, which is illustrated by an enumeration of experiences realized at the local level in Italy. We then focus our analysis on the experience of territorial govemance promoted in the Marches Region. This project was selected as a case study, because it is emblematic of the Italian context; the territory is characterized by the diffuse presence of small businesses in the soeio-economic fabric and by the proactive role of the local government. The case allows us to evaluate this paper＇s fundamental proposition, that the policies of the European Commission [EC] and the Government of Italy for promoting Corporate Social Responsibility and sustainability are not concretely effective when they are not fostered by regional authorities together with local private actors. Furthermore, public initiatives, to be effective, should take into consideration the influence of local culture, the social milieu, and economic factors shaping the environment in which public-private networks arise.

Horizontal crustal movement in Chinese mainland from 1999 to 2001

The paper introduces the horizontal crustal movement obtained from GPS observations in the regional networks (including the basic network and the fiducial network) of the Crustal Movement Observation Network of China (CMONOC) carried out in 1999 and 2001. This paper is characterized by the acquisition of the horizontal dis- placement velocities during the period from 1999 to 2001 at the observation stations in the regional networks with datum definition of a group of stable stations with small mutual displacements in east China. Based on the most detailed map of horizontal crustal movement in Chinese mainland, the division of blocks, their displacements and deformations are studied. An approach to analysis of the intensity of the horizontal crustal deformation is proposed. The general characteristics of the recent horizontal crustal movement in Chinese mainland and that before the Kunlunshan earthquake of M=8.1 on November 14, 2001 are analyzed.

Knowledge and Social Capital： Drivers for Sustainable Local Growth

This paper presents a knowledge resources perspective for territorial competitiveness and sustainability. The latter is defined as a pathway promoted by a plurality of public and private actors, in the for-profit and non-profit sectors, who find that relationships and social cohesion are the drivers for the construction of shared territorial governance. This study integrates an extensive literature review with data from longitudinal empirical research. Authors have adopted the methodology of qualitative research-based case study. In particular, this paper focused the analysis on a project of territorial governance promoted in the Marches region of Italy. This region was selected as a case study, because it is emblematic of the Italian context; the territory is characterized by small businesses diffused throughout the socio-economic fabric and by the proactive role taken by local governments. The perspective offers a powerful instrument for raising awareness of the gaps that local policymakers should address through their initiatives in the knowledge economy.

Assessment of the sources and transformations of nitrogen in a plain river network region using a stable isotope approach

The great spatial and temporal variability in hydrological conditions and nitrogen（N）processing introduces large uncertainties to the identification of N sources and quantifying N cycles in plain river network regions. By combining isotopic data with chemical and hydrologic measurements, we determined the relative importance of N sources and biogeochemical N processes in the Taige River in the East Plain Region of China. The river was polluted more seriously by anthropogenic inputs in winter than in summer. Manure and urban sewage effluent were the main nitrate（NO-3） sources, with the nitrification of N-containing organic materials serving as another important source of NO-3. In the downstream, with minor variations in hydrological conditions, nitrification played a more important role than assimilation for the decreasing ammonium（NH＋4-N） concentrations.The N isotopic enrichment factors（ε） during NH＋4utilization ranged from- 13.88‰ in March to- 29.00‰ in July. The ratio of the increase in δ^18O and δ^15N of river NO-3in the downstream was 1.04 in January and 0.92 in March. This ratio indicated that NO-3assimilation by phytoplankton was responsible for the increasing δ^15N and δ^18O values of NO-3in winter. The relationships between δ^15N of particulate organic nitrogen and isotopic compositions of dissolved inorganic nitrogen indicated that the phytoplankton in the Taige River probably utilized NH＋4preferentially and mainly in summer, while in winter, NO-3assimilation by phytoplankton was dominant.

Understanding spatial structures and organizational patterns of city networks in China: A highway passenger flow perspective

The use of multi-perspective and multi-scalar city networks has gradually developed into a range of critical approaches to understand spatial interactions and linkages. In particular, road linkages represent key characteristics of spatial dependence and distance decay, and are of great significance in depicting spatial relationships at the regional scale. Therefore, based on highway passenger flow data between prefecture-level administrative units, this paper attempted to identify the functional structures and regional impacts of city networks in China, and to further explore the spatial organization patterns of the existing functional regions, aiming to deepen our understanding of city network structures and to provide new cognitive perspectives for ongoing research. The research results lead to four key conclusions. First, city networks that are based on highway flows exhibit strong spatial dependence and hierarchical characteristics, to a large extent spatially coupled with the distributions of major megaregions in China. These phenomena are a reflection of spatial relationships at regional scales as well as core-periphery structure. Second, 19 communities that belong to an important type of spatial configuration are identified through community detection algorithm, and we suggest they are correspondingly urban economic regions within urban China. Their spatial metaphors include the administrative region economy, spatial spillover effects of megaregions, and core-periphery structure. Third, each community possesses a specific city network system and exhibits strong spatial dependence and various spatial organization patterns. Regional patterns have emerged as the result of multi-level, dynamic, and networked characteristics. Fourth, adopting a morphology-based perspective, the regional city network systems can be basically divided into monocentric, dual-nuclei, polycentric, and low-level equilibration spatial structures, while most are developing monocentrically.

Directly Modulated 10 Gb/s Signal Transmission over 320 km of Negative Dispersion Fiber for Regional Metro Network

We demonstrate the transmission of directly modulated 10-Gb/s WDM signals over 320 km of negative dispersion fiber (dispersion: -2.5 ps/km/nm @1550 nm) without dispersion compensation. The results indicate that a regional metro WDM network could be implemented cost-effectively by using the proposed negative dispersion fiber and direct modulated lasers.

GEO and IGSO joint precise orbit determination

Experiments and analyses are carried out for GEO and joint GEO/IGSO precise orbit determination using data recorded by China's regional tracking network.Results show that joint GEO/IGSO orbit determination effectively solves the problem of poor observation geometry for GEO satellites.The laser radial evaluation thus confirms that precision is as good as less than 0.1 m.In the case of joint orbit determination,solving the empirical acceleration can reduce errors introduced by the imprecise solar radiation pressure model used for Chinese satellites.This method also improves the accuracy of orbit prediction in the radial direction.The ephemeris accuracy is thus improved and the ephemeris can provide a better service to users with navigation and positioning requirements.

Marine target detection based on Marine-Faster R-CNN for navigation radar plane position indicator images

As a classic deep learning target detection algorithm,Faster R-CNN(region convolutional neural network)has been widely used in high-resolution synthetic aperture radar(SAR)and inverse SAR(ISAR)image detection.However,for most common low-resolution radar plane position indicator(PPI)images,it is difficult to achieve good performance.In this paper,taking navigation radar PPI images as an example,a marine target detection method based on the Marine-Faster R-CNN algorithm is proposed in the case of complex background(e.g.,sea clutter)and target characteristics.The method performs feature extraction and target recognition on PPI images generated by radar echoes with the convolutional neural network(CNN).First,to improve the accuracy of detecting marine targets and reduce the false alarm rate,Faster R-CNN was optimized as the Marine-Faster R-CNN in five respects:new backbone network,anchor size,dense target detection,data sample balance,and scale normalization.Then,JRC(Japan Radio Co.,Ltd.)navigation radar was used to collect echo data under different conditions to build a marine target dataset.Finally,comparisons with the classic Faster R-CNN method and the constant false alarm rate(CFAR)algorithm proved that the proposed method is more accurate and robust,has stronger generalization ability,and can be applied to the detection of marine targets for navigation radar.Its performance was tested with datasets from different observation conditions(sea states,radar parameters,and different targets).