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The Study on Remote Sensing Data Classification Using Bayesian Network
遥感数据的贝叶斯网络分类研究

Dai Qin,Ma Jian-wen,Li Qi-qing,Chen-Xue,Feng Chun,
戴 芹
,马建文,李启青,陈 雪,冯春

电子与信息学报 , 2005,
Abstract: Because of the complexity in satellite remote sensing imaging system,some uncertainties or mixed spectrum information are contained in the data.By using maximal likelihood classification to process remote sensing data,the result accuracy of the classification is affected.In order to improve the accuracy of the classification,prior knowledge is needed to modify the probability.Bayesian network is composed of directed acyclic graph and probability chart;it can modify the prior probability density dynamically and improve the accuracy of classification.In this paper,a technical procedure is demonstrated that using Bayesian network to process the remote sensing data,the classification results prove that Bayesian network has solid mathematics base and can be a new effective methods for remote sensing data processing.
Integrating Local and Global Error Statistics for Multi-Scale RBF Network Training: An Assessment on Remote Sensing Data  [PDF]
Giorgos Mountrakis, Wei Zhuang
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0040093
Abstract: Background This study discusses the theoretical underpinnings of a novel multi-scale radial basis function (MSRBF) neural network along with its application to classification and regression tasks in remote sensing. The novelty of the proposed MSRBF network relies on the integration of both local and global error statistics in the node selection process. Methodology and Principal Findings The method was tested on a binary classification task, detection of impervious surfaces using a Landsat satellite image, and a regression problem, simulation of waveform LiDAR data. In the classification scenario, results indicate that the MSRBF is superior to existing radial basis function and back propagation neural networks in terms of obtained classification accuracy and training-testing consistency, especially for smaller datasets. The latter is especially important as reference data acquisition is always an issue in remote sensing applications. In the regression case, MSRBF provided improved accuracy and consistency when contrasted with a multi kernel RBF network. Conclusion and Significance Results highlight the potential of a novel training methodology that is not restricted to a specific algorithmic type, therefore significantly advancing machine learning algorithms for classification and regression tasks. The MSRBF is expected to find numerous applications within and outside the remote sensing field.
Artificial neural network model for identifying taxi gross emitter from remote sensing data of vehicle emission
ZENG Jun,GUO Hua-fang,HU Yue-ming,
ZENG Jun
,GUO Hua-fang,HU Yue-ming

环境科学学报(英文版) , 2007,
Abstract: Vehicle emission has been the major source of air pollution in urban areas in the past two decades. This article proposes an artificial neural network model for identifying the taxi gross emitters based on the remote sensing data. After carrying out the field test in Guangzhou and analyzing various factors from the emission data, the artificial neural network modeling was proved to be an advisable method of identifying the gross emitters. On the basis of the principal component analysis and the selection of algorithm and architecture, the Back-Propagation neural network model with 8-17-1 architecture was established as the optimal approach for this purpose. It gave a percentage of hits of 93%. Our previous research result and the result from aggression analysis were compared, and they provided respectively the percentage of hits of 81.63% and 75%. This comparison demonstrates the potentiality and validity of the proposed method in the identification of taxi gross emitters.
Research on Storage Security of Dynamic Distributed Diskless Network Based on PXE
基于PXE技术的动态分布式无盘网络存储安全研究

HUANG Guan-li,JIN Yan,GOU Chuan-jing,WANG Ping,
黄冠利
,金岩,勾传静,王萍

计算机科学 , 2010,
Abstract: PXE(Pre-boot Execution Environment)技术因其强大的兼容性与易维护性在互联网的发展中作用越来越高,但是将PXE技术用于提高数据安全的研究却相对不够.在分析当前网络数据安全的现状及特点基础上,提出了将无盘网络及动态分布式数据存储技术应用于已有PXE网络系统中的方案,并对其主要构造进行了设计与研究.新的系统降低了数据泄漏风险,提高了网络数据的安全性及可靠性.该方案经济可行,大大降低了网络安全维护成本,并随着成果的普及与应用,将会带来更大的经济效益.
Effect of wind speed on aerosol optical depth over remote oceans, based on data from the Maritime Aerosol Network
A. Smirnov, A. M. Sayer, B. N. Holben, N. C. Hsu, S. M. Sakerin, A. Macke, N. B. Nelson, Y. Courcoux, T. J. Smyth, P. Croot, P. K. Quinn, J. Sciare, S. K. Gulev, S. Piketh, R. Losno, S. Kinne,V. F. Radionov
Atmospheric Measurement Techniques (AMT) & Discussions (AMTD) , 2012,
Abstract: The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (~0.004–0.005), even for strong winds over 10 m s 1. The relationships show significant scatter (correlation coefficients typically in the range 0.3–0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used.
Effect of wind speed on aerosol optical depth over remote oceans, based on data from the Maritime Aerosol Network
A. Smirnov,A. M. Sayer,B. N. Holben,N. C. Hsu
Atmospheric Measurement Techniques Discussions , 2011, DOI: 10.5194/amtd-4-7185-2011
Abstract: The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (~0.004–0.005), even for strong winds over 10 m s 1. The relationships show significant scatter (correlation coefficients typically in the range 0.3–0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used.
Improved Smartphone Application for Remote Access by Network Administrators  [PDF]
Ekwonwune Emmanuel Nwabueze, Etim Emmanuel Okon
Journal of Information Security (JIS) , 2019, DOI: 10.4236/jis.2019.104014
Abstract: This research attempts the implementation of an improved smartphone application for remote system administration. The work was motivated by the inability of network administrators to access their virtual servers from a remote location without worrying about the security implications, inaccurate and unreliable reports from a third party whenever he is out of town. The cloud server can be monitored and administered because various task such as creating users, manage users (grant access, block or delete users), restart server and shutdown server can be handled by the remote system administrator. This will involve of securing the system with a one-way hashing of encrypted password and a device ID for only whitelisted devices to be granted access. It will be observed that remote access for system administration can be implemented using a smartphone app based on a Point-to-Point Protocol and also reveal the advantages of PPP protocol, therefore making the enormous responsibilities of a remote system administrator much easier to accomplish.
Network Performance and Quality of Experience of Remote Access Laboratories  [cached]
Alexander A. Kist,Andrew D Maxwell
International Journal of Online Engineering (iJOE) , 2012, DOI: 10.3991/ijoe.v8i4.2276
Abstract: Remote Access Laboratories (RAL) have become important learning and teaching tools. This paper presents a performance study that targets a specific remote access architecture implemented within a universities operational environment. This particular RAL system provides globally authenticated and arbitrated remote access to virtualized computers as well as computer controlled hardware experiments. This paper presents system performance results that have been obtained utilizing both a set of automated and human subject tests. Principle objectives of the study were: To gain a better understanding of the nature of network traffic caused by experimental activity usage; to obtain an indication of user expectations of activity performance; and to develop a measure to predict Quality of Experience, based on easily measurable Quality of Service parameters. The study emulates network layer variation of access-bandwidth and round-trip-time of typical usage scenarios and contrasts against user perception results that allow classifying expected user performance. It demonstrates that failure rate is excellent measure of usability, and that round-trip-time predominantly affects user experience. Thin-client and remote desktop architectures are popular to separate the location of users and the actual data processing and use similar structures, hence results of this study to be applied in these application areas as well.
A Processing Method For Remote sensing imagery data based on bayesian network model
基于贝叶斯网络模型的遥感图像数据处理技术

Li Qiqing,Ma Jianwen,Hasi Bagan,Han Xiuzhen,Liu Zhili,
李启青
,马建文,哈斯巴干,韩秀珍,刘志丽

电子与信息学报 , 2003,
Abstract: Bayesian network is a new inference and express method of uncertain knowledge. It is proposed an inference and express technique for remote sensing imagery data which has complexity and uncertainty based on Bayesian Network Model(BNM). In the paper, the LU data, TSP and LST/Albedo data of AVHRR time-sequence imagery which get from the project of China-Japan Asian dust storm in 2002 are used to analyze the dust storm and at the same time BNM is used to describe the knowledge and information inference. The satisfied results are given in the paper with the method.
MONITORING LOCAL AREA NETWORK USING REMOTE METHOD INVOCATION  [PDF]
Harsh Mittal,Manoj Jain,Latha Banda
International Journal of Computer Science and Mobile Computing , 2013,
Abstract: The project aim is to secure the network or a LAN by implementing such a software which isenable to carry out operations which are capable to monitor whole of the network ,sitting on one chair byviewing remote desktop ,passing messages to remote system and is also able to shut down the system byperforming remote aborting operations . This software is purely developed in JAVA RMI (REMOTEMETHOD INVOCATION). This project is to provide the maximum details about the network to theadministrator on their screen without knowing them their users. The administrator can view the static imageof client’s desktop and then he/she could sends warning message to the user to stop that operationimmediately. Even than if client do not stops than administrator has the facility to abort the system remotelyor restart the system whatever necessary he thinks.
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