基于双端同步信息量测的小电流单相接地故障区段定位

配电网的各分段开关将各馈线分成若干区段,针对中性点不接地系统中故障无法可靠定位的问题,在分析健全区段与故障区段首末端稳态零序电流及差值特征的基础上,提出了基于双端同步信息量测的故障区段定位判据。该定位方法借助双端同步信息测量装置,与配电自动化系统一同实现。利用实时数字仿真系统仿真验证,该方法可准确定位中性点不接地系统故障区段,不受线路长短的影响,并能削弱过渡电阻的影响。

基于卡尔曼滤波算法的网络信息观测器设计

传统电力系统大多采用统一的控制和管理,对量测设备和通信设施依赖性强。一旦发生通信延时、丢包等故障,会影响系统状态监测和系统控制。因此,针对分布式电源接入的配电网系统,提出了一种基于卡尔曼滤波算法的无通信网络信息观测器,其可以实现对系统节点电压和分布式电源本地信息无通信信息观测。仿真分析结果验证了所提观测器的有效性。

古建筑彩画的二维图像信息现场量测技术数字化实践——以武当山道教建筑两仪殿壁画为例

文物建筑工程勘察是进行文保修护作业前的基础工作。目前三维激光扫描技术在2D彩画数据量测上存在局限,然而传统的2D量测工作方法也存在精度、效率、数据后处理的缺陷,该研究则提出一种现场量测结合数字化信息处理的古建筑彩画信息量测方法。该文首先针对古建筑彩画量测的工作方法缺陷进行剖析,其次再针对目前2D图像量测技术,提出适宜的信息采集方法。最后以武当山两仪殿壁画实践这项创新工程技术为例,其中也针对现场调研的病害特征进行建筑病理学分析,可作为未来有效提出工程项目修复计划的参考。

Safety assessment of platform loadout procedures based on unascertained measures

Safety assessment of offshore platforms is an urgent task. Such assessments are now focusing on the structure, maintenance, and retirement of a platform. Some methods employed have many shortcomings. For example, they cannot make the reliability adequately explicable. Therefore, a mathematical tool, the unascertained measure, was introduced. First, the basic knowledge of the unascertained sets was introduced briefly. Second, the unascertained measure was defined and credible identification was set up. The method has been introduced into the fields for safety assessment of a jacket loadout procedure. Engineering practices showed that it can complete the safety assessment systematically and scientifically without any assumption. The work should have significance in theory and practice for offshore engineering.

Considerations when using the activPAL monitor in field-based research with adult populations

Research indicates that high levels of sedentary behavior(sitting or lying with low energy expenditure) are adversely associated with health. A key factor in improving our understanding of the impact of sedentary behavior(and patterns of sedentary time accumulation) on health is the use of objective measurement tools that collect date and time-stamped activity information. One such tool is the activP AL monitor. This thigh-worn device uses accelerometer-derived information about thigh position to determine the start and end of each period spent sitting/lying, standing, and stepping, as well as stepping speed, step counts, and postural transitions. The activP AL is increasingly being used within field-based research for its ability to measure sitting/lying via posture. We summarise key issues to consider when using the activP AL in physical activity and sedentary behavior field-based research with adult populations. It is intended that the findings and discussion points be informative for researchers who are currently using activP AL monitors or are intending to use them. Pre-data collection decisions, monitor preparation and distribution, data collection considerations, and manual and automated data processing possibilities are presented using examples from current literature and experiences from 2 research groups from the UK and Australia.

Schemes for Splitting Quantum Information with Four-Particle Genuine Entangled States

We propose two schemes for splitting single- and two-qubit states by using four-particle genuine entangled state as the quantum channel. After the sender performs Bell-basis （or three-partite GHZ- basis） measurements on her particles, and the cooperators operate single-particle measurements on their particles, the state receiver can reconstruct the original state of the sender by applying the appropriate unitary operation. In particular, in the scheme for splitting two-qubit state, the receiver needs to introduce an auxiliary particle and carries out a C-NOT operation.

Practical Research of IKONOS-2 Geopositioning and Its Accuracy in Tibet of China

This paper presents the studies of the refining of IKONOS-2 RPC, the transform of the datum, the mode of the control point distribution and the method of IKONOS stereo triangulation, so that IKONOS imagery can be used to collect the precise geospatial data and produce the large scale map.The transform between the IKONOS-2 image space and the national coordinate system based on the RPC have been developed, and the results of block adjustment with various control schemes in a practical project near Himalayas have been examined and analysed. The encouraging results of high positioning accuracy have been obtained.

A Quantitative Security Metric Model for Security Controls:Secure Virtual Machine Migration Protocol as Target of Assessment

Quantitative security metrics are desirable for measuring the performance of information security controls. Security metrics help to make functional and business decisions for improving the performance and cost of the security controls. However, defining enterprise-level security metrics has already been listed as one of the hard problems in the Info Sec Research Council's hard problems list. Almost all the efforts in defining absolute security metrics for the enterprise security have not been proved fruitful. At the same time, with the maturity of the security industry, there has been a continuous emphasis from the regulatory bodies on establishing measurable security metrics. This paper addresses this need and proposes a relative security metric model that derives three quantitative security metrics named Attack Resiliency Measure(ARM), Performance Improvement Factor(PIF), and Cost/Benefit Measure(CBM) for measuring the performance of the security controls. For the effectiveness evaluation of the proposed security metrics, we took the secure virtual machine(VM) migration protocol as the target of assessment. The virtual-ization technologies are rapidly changing the landscape of the computing world. Devising security metrics for virtualized environment is even more challenging. As secure virtual machine migration is an evolving area and no standard protocol is available specifically for secure VM migration. This paper took the secure virtual machine migration protocol as the target of assessment and applied the proposed relative security metric model for measuring the Attack Resiliency Measure, Performance Improvement Factor, and Cost/Benefit Measure of the secure VM migration protocol.

Regionalization for Rice Yield Estimation by Remote Sensing in Zhejiang Province

In order to provide a scientific basis for rice yield estimation and improve the accuracy of yield estimation in Zhejiang Province, regionalization indices for rice yield estimation by remote sensing (RS) in the province were determined by considering the special features of yield estimation by RS, and based on analysis of the natural conditions of Zhejiang Province. The indices determined included rice cropping system, agroclimate, landform, surface feature structure and rice yield level, where rice planting system was considered as the main one. Then regionalization for rice yield estimation by RS was completed by spatial neighboring analysis with the Geographical information System (GIS) technology combined with using of tree algorithm. The province was divided into two regions, i. e., the single-cropping rice region which was subdivided into 3 regions including those in mountains of northwest Zhejiang, water network area of north Zhejiang and mountains of south Zhejiang, and double-cropping rice region which was subdivided into 5 regions including those on plain of north Zhejiang, coastal plains and hills of southeast Zhejiang, Jin-Qu Basin of middle Zhejiang, hills of east Zhejiang, and hills and mountains of northwest Zhejiang. This regionalization took the county borders as the region boundaries, kept the regions connective and made the administrative regions integrity and, then, could meet the requirements of rice yield estimation by RS, showing that the results were quite satisfying.

Selection of Measured Signals in the Navigation Measuring Complex

To increase accuracy of navigation parameters,a perspective measuring complex with intellectual components is developed.Conception of synthesis optimal structure of the measuring complex is realized basing on a selective method using principles of the functional systems.Selection of measured information is finished by original numeric criterion of observation level of state vector components.Prediction is realized by algorithm of self-organization that makes synthesis of the optimal complication.Therefore mechanism of self-regulation is realized and accuracy of the selective navigation complex is increased.

Measurement of Incompatible Probability in Information Retrieval:A Case Study with User Clicks

The incompatible probability represents an important non-classical phenomenon, and it describes conflicting observed marginal probabilities, which cannot be satisfied with a joint probability. First, the incompatibility of random variables was defined and discussed via the non-positive semi-definiteness of their covariance matrixes. Then, a method was proposed to verify the existence of incompatible probability for variables. A hypothesis testing was also applied to reexamine the likelihood of the observed marginal probabilities being integrated into a joint probability space, thus showing the statistical significance of incompatible probability cases. A case study with user click-through data provided the initial evidence of the incompatible probability in information retrieval (IR), particularly in user interaction. The experiments indicate that both incompatible and compatible cases can be found in IR data, and informational queries are more likely to be compatible than navigational queries. The results inspire new theoretical perspectives of modeling the complex interactions and phenomena in IR.

Logarithm Versus Square Root： Comparing Quantum Fisher Information

In classical statistics, the Fisher information is unique in the sense that it is essentially the only monotone Riemannian metric on the space of probability densities. In quantum theory, this uniqueness breaks down, and there are many natural quantum analogues of the Fisher information, among which two particular versions distinguish themselves by their intuitive and informational significance： The first has its origin in the skew information introduced by Wigner and Yanase in 1963 in the context of quantum measurement, and is defined via the square root of the density operator. The second arises from Helstrom＇s study of quantum detection in 1967, and is defined via the symmetric logarithmic derivative. The aim of this paper Js to compare these two versions of quantum Fisher information, and to establish two informational inequalities relating them.

Mining Data Correlation from Multi-Faceted Sensor Data in Internet of Things

Sensors are ubiquitous in the Internet of Things for measuring and collecting data. Analyzing these data derived from sensors is an essential task and can reveal useful latent information besides the data. Since the Internet of Things contains many sorts of sensors, the measurement data collected by these sensors are multi-type data, sometimes contai- ning temporal series information. If we separately deal with different sorts of data, we will miss useful information. This paper proposes a method to dis- cover the correlation in multi-faceted data, which contains many types of data with temporal informa- tion, and our method can simultaneously deal with multi-faceted data. We transform high-dimensional multi-faeeted data into lower-dimensional data which is set as multivariate Gaussian Graphical Models, then mine the correlation in multi-faceted data by discover the structure of the multivariate Gausslan Graphical Models. With a real data set, we verifies our method, and the experiment demonstrates that the method we propose can correctly fred out the correlation among multi-faceted meas- urement data.

RS AND GIS-BASED FOREST FIRE RISK ZONE MAPPING IN DA HINGGAN MOUNTAINS

The Da Hinggan Mountains is one of the most important forest areas in China, but forest fire there is also of high frequency. So it is completely necessary to map forest fire risk zones in order to effectively manage and protect the forest resources. Two forest farms of Tuqiang Forest Bureau (53 degrees 34'-52 degrees 15'N,124 degrees 05'-122 degrees 18'E) were chosen as typical areas in this study. Remote sensing (RS) and Geographic Information System (GIS) play a vital role and can be used effectively to obtain and combine different forest-fire-causing factors for demarcating the forest fire risk zone map. Forest fire risk zones were described by assigning subjective weights to the classes of all the coverage layers according to their sensitivity to fire, using the ARC/INFO GIS software. Four classes of forest fire risk ranging from low to extremely high were generated automatically in ARC/INFO. The results showed that about 60.33% of the study area were predicted to be upper moderate risk zones, indicating that the forest fire management task in this area is super onerous. The RS and GIS-based forest fire risk model of the study area was found to be highly compatible with the actual fire-affected sites in 1987. Therefore the forest fire risk zone map can be used for guidance of forest fire management, and as basis for fire prevention strategies.

A simple method to extract glacier length based on Digital Elevation Model and glacier boundaries for simple basin type glacier

Glacier length is a key morphological element that has many glaciological applications; however, it is often difficult to determine, especially for glaciers that cover larger spatial areas or those that exhibit frequent temporal change. In this paper, we describe a new Arc GIS-based method that can derive glacier flow lines for determining glacier length based on digital elevation model and glacier outlines. This method involves(1) extraction of the highest and lowest points on a glacier,(2) calculation of 10-m contour lines on the glacier from 10 m to 100 m height, and(3) connection of the midpoints of each contour line with the highest and the lowest points in order to create a flow line, which is subsequently smoothed. In order to assess the reliability of this method, we tested the algorithm's results against flow lines calculated using field measurements, analysing data from the Chinese Glacier Inventory, and manual interpretation. These data showed that the new automated method is effective in deriving glacier flow lines when contour lines are relatively large; in particular, when they are between 70 m and 100 m. Nonetheless, a key limitation of the algorithm is the requirement to automatically delete repeated and closed curves in the pre-treatment processes. In addition to calculating glacier flow lines for derivation of glacier length, this method also can be used to effectively determine glacier terminus change.

Orthorectification of IKONOS and Impact of Different Resolution DEM

IKONOS image has been wildly used in city planning, precision agriculture and emergence response. However, the accuracy of IKONOS Geo product is limited due to distortion caused by terrain relief. Orthorectification was performed to remove the distortion and the impact of different DEM on orthorectification were evaluated. 38 ground control points (GCPs) and 25 independent check points (ICPs) were collected. DEMs were generated from 1∶10 000 and 1∶50 000 topographic maps. Results show that RMS error at the check points is 1.554 0 m using DEM generated from 1∶10 000 topographic map, which can meet the accuracy requirement of IKONOS Precision product (1.9 m RMSE). While RMS error is 2.572 4 m using DEM generated from 1∶50 000 topographic map.

A MULTIDISCIPLINARY AND INTEGRATED STUDY OF RICE PRECISION FARMING

In terms of demands of rice farming in the southern China, the information processing system and the yield measurement system that is installed in combine harvester, are designed and completed. Now the systems have been used in demonstration site in the Experiment Base of Shanghai Precision Agriculture. Based on the idea of spatial-oriented, object-oriented, user-oriented, the Farm Geographic Information System for precision farming of rice was developed, which is characterized by intelligence and visualized. The Decision-making Management System is integrated with rice growth model, expert model for rice cultivation. The DGPS, RS, GIS and intelligence sensors and computer technique were adopted in building the artificial intelligence system for measuring grain yield that is installed in combine harvester, so the combine harvester could provide the grain yield distribution map real-timely. The environmental and economic assessment shows that the precision rice farming applied in the demonstration site will benefit the society, economy and ecology greatly.

A Learning-Based Channel Model for Synergetic Transmission Technology

It is extensively approved that Channel State Information(CSI) plays an important role for synergetic transmission and interference management. However, pilot overhead to obtain CSI with enough precision is a significant issue for wireless communication networks with massive antennas and ultra-dense cell. This paper proposes a learning- based channel model, which can estimate, refine, and manage CSI for a synergetic transmission system. It decomposes the channel impulse response into multiple paths, and uses a learning-based algorithm to estimate paths' parameters without notable degradation caused by sparse pilots. Both indoor measurement and outdoor measurement are conducted to verify the feasibility of the proposed channel model preliminarily.

An Urban Open Space Extraction Method: Combining Spectral and Geometric Characteristics

This paper introduces an advanced method based on remote sensing and Geographic Information System for urban open space extraction combining spectral and geometric characteristics. From both semantic and remote sensing perspectives, a hybrid hierarchy structure and class organization of open space are issues and mapped from one to another. Based on per-pixel and segmentation mechanism separately, two classification approaches are performed. Owing to prior of spatial aggregation and spectral contribution, the segmentation-based classification exhibits its superiority over a pixel-based classification. Finally a GIS-based post procedure is hired to eliminate some unsuitable open space components in both spatial and numerical constraints on the one hand, and separate open space some fabrics from fused remote sensing classes by defining their Shape Index on the other hand. The case study of Beer Sheva based on ASTER data proves this method is a feasible way for open space extraction.

Performance measure for image fusion considering region information

An objective performance measure for image fusion considering region information is proposed. The measure not only reflects how much the pixel level information that fused image takes from the source image, but also considers the region information between source images and fused image. The measure is meaningful and explicit. Several simulations were conducted to show that it accords well with the subjective evaluations.