Web service based spatial forest information system using an open source software approach

For technical and other reasons there is a dilemma that data providers cannot find an appropriate way to redistribute spatial forest data and data users who need spatial data cannot access and integrate available forest resources information. To overcome this dilemma, this paper proposed a spatial forest information system based on Web service using an open source software approach. With Web service based architecture, the system can enable interoperability, integrate Web services from other application servers, reuse codes, and shorten the development time and cost. At the same time, it is possible to extend the local system to a regional or national spatial forest information system. The growth of Open Source Software （OSS） provides an alternative choice to proprietary software for operating systems, web servers, Web-based GIS applications and database management systems. Using open source software to develop spatial forest information systems can greatly reduce the cost while providing high performance and sharing spatial forest information. We chose open source software to build a prototype system for Xixia County, Henan Province, China. By integrating OSS packages Deegree and UMN MapServer which are compliant to the OGC open specifications, the prototype system enables users to access spatial forest information and travelling information of Xixia County which come from two different data servers via a standard Web browser and promotes spatial forest information sharing.

Strategic information perception methods and practices in the open source intelligence

Open source intelligence is one of the most important public data sources for strategic information analysis. One of the primary and core issues of strategic information research is information perception,so this paper mainly expounds the perception method for strategic information perception in the open source intelligence environment as well as the framework and basic process of information perception. This paper argues that in order to match the information perception result with the information depiction result,it conducts practical exploration for the results of information acquisition,perception,depiction and analysis. This paper introduces and develops a monitoring platform for information perception. The results show that the method proposed in this paper is feasible.

The Combination Operator of Information Sources by a New Expressive Matrix

The multi-sensors fusion refers to the synergistic combination of sensory data from multiple sensors to provide more accurate and reliable information. The potential benefits of the Fusion are multi-sensors’ redundancy and extra information acquired. The fusion of redundant information can reduce the overall uncertainty and thus helps to provide information specified more precisely. Several sensors providing redundant information can also be used to increase reliability in the case of error, omission or failure of sensors. The combination operators are exponential and are more complex in terms of calculation;the Dempster-Shafer operator is exponential for more than three (3) information sources?[1] [2]. Our work focuses on the definition of another formulation of this operation, and puts it in a matrix form to illuminate the computational complexity, more precision guaranty and a minimal execution time. We propose to use each information source in a form of a matrix, which contains 0 value in lines that do not contain the masses (m(Ai) = 0) or once m(Ai) is not null (m(Ai) ≠ 0). The use of this expressed matrix attempts to ameliorate Dempster-Shafer operator via initialing either a criterion or criteria sources’ solution, increasing the efficiency of the Dempster-Shafer operator and facilitates the combination among the sources. We evaluate our approach by conducting a case study for showing the effectiveness of this matrix.

Farmers’ Access to Agricultural Information Sources: Evidences from Rural Pakistan

The current study was conducted to probe farmers’ accessible agricultural information sources in rural areas of Pakistan. For this purpose a random sample of 160 households from four districts of the Punjab province of Pakistan was selected. Data were collected using validated and expert reviewed questionnaire with the help of interview method. The results revealed that majority of farmers (47.5%) ranked neighbor-friends-relatives as first source of information while 31.9% of farmers ranked this source as second and 33.7% farmers’ ranked it as third major source. With contrast to this very less farmers (10%) ranked agricultural extension staff as first information source. Keeping in view the study results, the performance of extension staff is not encouraging;therefore government should plan and launch a policy to foster performance of public agricultural extension system to fulfill the advanced technological needs of farmers to flourish sustainable agriculture and rural development.

Follow the Open Source Road： Contemplating the Ethics of the New Information Ecology

The evolutionary complexity of modem media systems represents an area of research that would benefit from further description and debate. In order to better understand the challenges and considerations associated with the new, constantly changing media ecology, a more holistic worldview must be catapulted to the forefront of the collective discussion. To that effect, the following essay examines the open source software movement from the philosophical perspective of Tibetan Buddhism. Using the principles of interconnectedness, impermanence, and the illusory nature of self and reality, all fundamental elements of Buddhist philosophy, this discussion provides a renewed framework for exploring the ethical implications of open sourcing. A review of Buddhist teachings, coupled with literature from foundational media theorists such as Neil Postman and Marshall and Eric McLuhan, will set the stage for contemplating the ethics of the modem information ecology, epitomized by the collaborative spirit and community connections of open source software.

Information Sources Consulted by Women in African Countries to Manage Menopausal Symptoms:A Systematic Review and Meta-Analysis

Background: Despite an abundance of information regarding menopausal women in western society, African menopausal women have been overlooked in menopausal research, particularly, where they find information regarding menopause. Since inadequate health-related knowledge on menopause negatively affects the understanding of and coping with menopause and related symptoms, it is important to determine where women in Africa obtain their information about menopause. Aim: To conduct a systematic review to identify and analyse information sources consulted by menopausal women in the African region regarding the management of menopausal symptoms. Method: PubMed, Embase (OVID), Google Scholar, Medline (OVID), Medline in Process (OVID), Scopus, https://www.africabib.org/, African Index Medicus;http://indexmedicus.afro.who. int/,and African Journals Online (AJOL) were searched for publications from January 2000 to April 2017. Fourteen studies met the eligibility criteria. Twelve were quantitative while two were qualitative. Studies were independently appraised by two researchers using checklists from the Centre for Evidence-Based Management. Results: Meta-analysis explored the prevalence of different information sources reported with friends being the highest (44%, 95% CI: [0.35, 0.54]) followed by relatives (35%, 95% CI: [0.22, 0.50]) with medical providers being sources of information for only 30% of participants (95% CI: [0.15, 0.50]). Conclusion: Information regarding menopause among African women emanated primarily from friends and relatives, suggesting that women perceive menopause as a natural process whereby information is the best gleaned from informal sources. However, health care should aim to increase public awareness of menopause education and strengthen efforts to provide accurate, timely and helpful information for women and their friends and families.

Information-Driven Collaborative Processing for Diffusive Source Estimation in Wireless Sensor Networks

This paper discusses an accurate distributed algorithm for diffusive source localization while maintaining the low energy consumption of sensor nodes in wireless sensor networks. In this algorithm, the sensor selection scheme based on the information utility measure is used. To update the estimation in each selected node, a neighborhood radius equal to the communication range of the sensor nodes is defined and all sensors located in the neighborhood circle, whose radius is equal to the neighborhood radius and the selected node is its centre, collaborate their information. To decrease the energy consumption, the neighborhood radius is reduced gradually based on the error covariance value of the estimation. In addition, this paper includes a new method for the initial point calculation which is important in the recursive methods used for distributed algorithms in wireless sensor networks. Numerical examples are used to study the performance of the algorithms. Simulation results show the accuracy of the new algorithm becomes better while its energy consumption is low enough.

MEIC-global-CO_(2):A new global CO_(2)emission inventory with highly-resolved source category and sub-country information

CO_(2)emission inventory provides fundamental data for climate research and emission mitigation.Currently,most global CO_(2)emission inventories were developed with energy statistics from International Energy Agency(IEA)and were available at country level with limited source categories.Here,as the first step toward a high-resolution and dynamic updated global CO_(2)emission database,we developed a data-driven approach to construct seamless and highly-resolved energy consumption data cubes for 208 countries/territories,797 sub-country administrative divisions in 29 countries,42 fuel types,and 52 sectors,with the fusion of activity data from 24 international statistics and 65 regional/local statistics.Global CO_(2)emissions from fossil fuel combustion and cement production in 1970–2021 were then estimated with highly-resolved source category(1,484 of total)and sub-country information(797 of total).Specifically,73%of global CO_(2)emissions in 2021 were estimated with sub-country information,providing considerably improved spatial resolution for global CO_(2)emission accounting.With the support of detailed information,the dynamics of global CO_(2)emissions across sectors and fuel types were presented,representing the evolution of global economy and progress of climate mitigation.Remarkable differences of sectoral contribution were found across sub-country administrative divisions within a given country,revealing the uneven distribution of energy and economic structure among different regions.Our estimates were generally consistent with existing databases at aggregated level for global total or large emitters,while large discrepancies were observed for middle and small emitters.Our database,named the Multiresolution Emission Inventory model for Climate and air pollution research(MEIC)is publicly available through http://meicmodel.org.cn with highly-resolved information and timely update,which provides an independent carbon emission accounting data source for climate research.

Optimization of sensor deployment sequences for hazardous gas leakage monitoring and source term estimation

Nowadays, chemical safety has attracted considerable attention, and chemical gas leakage monitoring and source term estimation(STE) have become hot spots. However, few studies have focused on sensor layouts in scenarios with multiple potential leakage sources and wind conditions, and studies on the risk information(RI) detection and prioritization order of sensors have not been performed. In this work, the monitoring area of a chemical factory is divided into multiple rectangles with a uniform mesh. The RI value of each grid node is calculated on the basis of the occurrence probability and normalized concentrations of each leakage scenario. A high RI value indicates that a sensor at a grid node has a high chance of detecting gas concentrations in different leakage scenarios. This situation is beneficial for leakage monitoring and STE. The methods of similarity redundancy detection and the maximization of sensor RI detection are applied to determine the sequence of sensor locations. This study reveals that the RI detection of the optimal sensor layout with eight sensors exceeds that of the typical layout with 12 sensors. In addition, STE with the optimized placement sequence of the sensor layout is numerically simulated. The statistical results of each scenario with various numbers of sensors reveal that STE is affected by sensor number and scenarios(leakage locations and winds). In most scenarios, appropriate STE results can be retained under the optimal sensor layout even with four sensors. Eight or more sensors are advised to improve the performance of STE in all scenarios. Moreover, the reliability of the STE results in each scenario can be known in advance with a specific number of sensors. Such information thus provides a reference for emergency rescue.

Degenerate polarization entangled photon source based on a single Ti-diffusion lithium niobate waveguide in a polarization Sagnac interferometer

Combining a Ti-diffusion periodically poled lithium niobate(PPLN)waveguide with a Sagnac interferometer,two opposite directions type-II spontaneous parametric down conversions(SPDC)occur coherently and yield a high brightness,high stability polarization entanglement source.The source produces degenerate photon pairs at 1540.4 nm with a brightness of B=(1.36±0.03)×10^(6) pairs/(s·nm·m W).We perform quantum state tomography to reconstruct the density matrix of the output state and obtain a fidelity of F=0.983±0.001.The high brightness and phase stability of our waveguide source enable a wide range of quantum information experiments operating at a low pump power as well as hold the advantage in mass production which can promote the practical applications of quantum technologies.

Identify information sources with different start times in complex networks based on sparse observers

The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial moments.Although there are many research results of multi-source identification,the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains unresolved.In this study,we provide the backward spread tree theorem and source centrality theorem,and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start times.The proposed algorithm does not require prior knowledge of the number of sources,however,it can estimate both the initial spread moment and the spread duration.The core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear programming.Extensive experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and efficiency.Furthermore,we find that our method maintains robustness irrespective of the number of sources and the average degree of network.Compared with classical and state-of-the art source identification methods,our method generally improves the AUROC value by 0.1 to 0.2.

Estimation of ammonia nitrogen load from nonpoint sources in the Xitiao River catchment, China

Ammonia nitrogen (NH4+-N) is one of the three main forms of total nitrogen (TN). Most studies have estimated the load of TN from nonpoint sources instead of one specific form. The relationship between land use and concentrations of NH4+-N in runoff was analyzed using the hydraulic analysis functions of a Geographic Information Systems (GIS), and the annual loads of NH4+-N in the Xitiao River catchment were estimated according to model results. The results suggested that the calculated annual loads of NH4+-N...

Application of particle swarm optimization blind source separation technology in fault diagnosis of gearbox

Blind source separation (BBS) technology was applied to vibration signal processing of gearbox for separating different fault vibration sources and enhancing fault information. An improved BSS algorithm based on particle swarm optimization (PSO) was proposed. It can change the traditional fault-enhancing thought based on de-noising. And it can also solve the practical difficult problem of fault location and low fault diagnosis rate in early stage. It was applied to the vibration signal of gearbox under three working states. The result proves that the BSS greatly enhances fault information and supplies technological method for diagnosis of weak fault.

New Individual Identification Method of Radiation Source Signal Based on Entropy Feature and SVM

In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly,based on the theory of multi-resolution wavelet analysis,the wavelet power spectrum of noncooperative signal can be gotten. Secondly,according to the information entropy theory,the wavelet power spectrum entropy is defined in this paper. Therefore,the database of signal's wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally,the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual's identification rate in low SNR,when the SNR is greater than 4 dB,the identification rate can reach 100%. Under unstable SNR conditions,when the range of SNR is between 0 dB and 24 dB,the average identification rate is more than 92. 67%. Therefore,this method has a great application value in the complex electromagnetic environment.

Source extension based on ε-entropy

It is known by entropy theory that image is a source correlated with a certain characteristic of probability. The entropy rate of the source and ε- entropy (rate-distortion function theory) are the information content to identify the characteristics of video images, and hence are essentially related with video image compression. They are fundamental theories of great significance to image compression, though impossible to be directly turned into a compression method. Based on the entropy theory and the image compression theory, by the application of the rate-distortion feature mathematical model and Lagrange multipliers to some theoretical problems in the H.264 standard, this paper presents a new the algorithm model of coding rate-distortion. This model is introduced into complete test on the capability of the test model of JM61e (JUT Test Model). The result shows that the speed of coding increases without significant reduction of the rate-distortion performance of the coder.

SPATIAL ANALYSIS OF SOIL EROSION AND NON-POINT SOURCE POLLUTION BASED ON GIS IN ERLONG LAKE WATERSHED, JILIN PROVINCE

Data collection, factor composition, nappe analysis and integrative simulation of natural geographical factors in Erlong Lake watershed have been carried out based on GIS. The risk areas where non-point source pollution may occur were compartmentalized and assessed, and the total soil erosion and the runoffs of N and P with rainfall in this valley were worked out by experiment and GIS mapping. The study indicated that the main type of soil erosion was moderate (erosion modulus is 1000-2500t/(km(2).a)) at present, and the intense erosion areas are located in dry land with variable slope east of the lake and the middle-south parts of steep slope mountainous region (erosion modulus is more than 5000t/(km(2).a)). Though the area is small, it should be paid attention to. The trend of non-point source pollution (NSP) of nitrogen and phosphorus loss was corresponded with the soil erosion. Spatial distribution and the reasons of the distribution difference have been presented and it was emphasized that the human activities among the influence factors was the most important. It surely offers a scientific basis to control and prevent non-point source pollution in the watershed.

Quantitative information measurement and application for machine component classification codes

Information embodied in machine component classification codes has internal relation with the probability distribu- tion of the code symbol. This paper presents a model considering codes as information source based on Shannon’s information theory. Using information entropy, it preserves the mathematical form and quantitatively measures the information amount of a symbol and a bit in the machine component classification coding system. It also gets the maximum value of information amount and the corresponding coding scheme when the category of symbols is fixed. Samples are given to show how to evaluate the information amount of component codes and how to optimize a coding system.

Optimization of Well Position and Sampling Frequency for Groundwater Monitoring and Inverse Identification of Contamination Source Conditions Using Bayes’Theorem

Coupling Bayes’Theorem with a two-dimensional(2D)groundwater solute advection-diffusion transport equation allows an inverse model to be established to identify a set of contamination source parameters including source intensity(M),release location(0 X,0 Y)and release time(0 T),based on monitoring well data.To address the issues of insufficient monitoring wells or weak correlation between monitoring data and model parameters,a monitoring well design optimization approach was developed based on the Bayesian formula and information entropy.To demonstrate how the model works,an exemplar problem with an instantaneous release of a contaminant in a confined groundwater aquifer was employed.The information entropy of the model parameters posterior distribution was used as a criterion to evaluate the monitoring data quantity index.The optimal monitoring well position and monitoring frequency were solved by the two-step Monte Carlo method and differential evolution algorithm given a known well monitoring locations and monitoring events.Based on the optimized monitoring well position and sampling frequency,the contamination source was identified by an improved Metropolis algorithm using the Latin hypercube sampling approach.The case study results show that the following parameters were obtained:1)the optimal monitoring well position(D)is at(445,200);and 2)the optimal monitoring frequency(Δt)is 7,providing that the monitoring events is set as 5 times.Employing the optimized monitoring well position and frequency,the mean errors of inverse modeling results in source parameters(M,X0,Y0,T0)were 9.20%,0.25%,0.0061%,and 0.33%,respectively.The optimized monitoring well position and sampling frequency canIt was also learnt that the improved Metropolis-Hastings algorithm(a Markov chain Monte Carlo method)can make the inverse modeling result independent of the initial sampling points and achieves an overall optimization,which significantly improved the accuracy and numerical stability of the inverse modeling results.

Risk Prevention and Control for Agricultural Non-Point Source Pollution Based on the Process of Pressure-Transformation-Absorption in Chongqing, China

According to China’s second national survey of pollution sources, the contribution of agricultural non-point sources(ANS) to water pollution is still high. Risk prevention and control are the main means to control costs and improve the efficiency of ANS, but most studies directly take pollution load as the risk standard, leading to a considerable misjudgment of the actual pollution risk. To objectively reflect the risk of agricultural non-point source pollution(ANSP) in Chongqing, China, we investigated the influences of initial source input, intermediate transformation, and terminal absorption of pollutants via literature research and the Delphi method and built a PTA(pressure kinetic energy, transformation kinetic energy, and absorption kinetic energy) model that covers 12 factors, with the support of geographical information system(GIS) technology. The terrain factor calculation results and the calculation results of other factors were optimized by Python tools to reduce human error and workload. Via centroid migration analysis and Kernel density analysis, the risk level, spatial aggregation degree, and key prevention and control regions could be accurately determined. There was a positive correlation between the water quality of the rivers in Chongqing and the risk assessment results of different periods, indirectly reflecting the reliability of the assessment results by the proposed model. There was an obvious tendency for the low-risk regions transforming into high-risk regions. The proportion of high-risk regions and extremely high-risk regions increased from 17.82% and 16.63%in 2000 to 18.10% and 16.76% in 2015, respectively. And the risk level in the main urban areas was significantly higher than that in the southeastern and northeastern areas of Chongqing. The centroids of all grades of risky areas presented a successive distribution from west to east, and the centroids of high-risk and extremely high-risk regions shifted eastward. From 2000 to 2015, the centroids of highrisk and extremely high-risk regions moved 4.63 km(1.68°) and 4.48 km(12.08°) east by north, respectively. The kernel density analysis results showed that the high-risk regions were mainly concentrated in the main urban areas and that the distribution of agglomeration areas overall displayed a transition trend from contiguous distribution to decentralized concentration. The risk levels of the regions with a high proportion of cultivated land and artificial surface were significantly increased, and the occupation of cultivated land in the process of urbanization promoted the movement of the centroids of high-risk and extremely high-risk regions. The identification of key areas for risk prevention and control provides data scientific basis for the development of prevention and control strategies.

Design and Application of the Automatic Monitoring System for Wastewater Source in Shandong Province

In order to realize real-time online monitoring of the wastewater source enterprises,manage and issue monitoring information,this paper comprehensively uses automatic control,embedded data acquisition and transmission,distributed computing and data processing,geographic information system,etc.to develop automatic monitoring system of the wastewater source in Shandong Province.This system incorporates automatic monitoring information acquisition,transmission and daily work as an organic whole.The system realizes not only the continuous online monitoring of wastewater source enterprise,but also the deep excavation and utilization on monitoring information.It provides scientific and objective basis for energy saving,consumption reduction,carbon emission reduction,total amount control and other environmental management works,and meets the requirements of environmental management and related departments to wastewater source management.