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Objective To analyze the incidence trend and epidemiological characteristics of dengue fever in Fujian Province from 2009 to 2023, identify the high-incidence population and hotspot areas, and a scientific basis for formulating targeted prevention and control measures. Methods The surveillance data of dengue fever during 2009-2023 in Fujian Province were obtained from the National Disease Reporting Information System and analyzed using descriptive epidemiological methods, and the spatial autocorrelation analysis of dengue fever incidence at county/district levels was performed with ArcGlS 10.8. Results A total of 3 586 cases of dengue fever were reported in Fujian Province from 2009 to 2023, with an average annual incidence rate of 0.61/100 000, showing an overall increasing trend year by year (Z=18.35, P< 0.001). Among them, there were 2 362 local cases and 1 224 imported cases, with a local/imported ratio of 1.93:1 (2 362/1 224). The local cases were mainly distributed in Fuzhou, Putian, and Nanping, accounting for 87.81% (2 074/2 362). The imported cases were mainly distributed in Quanzhou, Fuzhou, and Xiamen, accounting for 72.55% (888/1 224). The local/imported ratio in Fuzhou, Nanping, and Putian was 6.20:1 (1 557/251), 3.92:1 (145/37), and 3.32:1 (372/112), respectively, all significantly higher than the provincial average level. The spatial distribution of the local cases showed a clustered pattern, with 12 hotspots of incidence, all located in the counties and districts under the jurisdiction of Fuzhou. The onset of the disease had obvious seasonality: imported cases from other countries or regions mainly occurred from July to September (accounting for 45.73%, 519/1 135), imported cases from other provinces mainly occurred from August to November (accounting for 93.25%, 83/89), and local cases mainly occurred from August to October (accounting for 97.50%, 2 303/2 362). The gender ratio for local cases was 0.88:1, and for imported cases, it was 3.04:1. The average age of onset for local cases was 48 years old (Q1=32 years old, Q3=62 years old), while the average age for imported cases was 35 years old (Q1=28 years old, Q3=44 years old). Conclusions From 2009 to 2023, the dengue fever epidemic in Fujian Province showed a continuous upward trend, with spatiotemporal clustering of incidence. Therefore, prevention and control measures should be strengthened in key areas and populations during the high-incidence season. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Environmental Science & Technology (10036504) is the property of Editorial Board of Environmental Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

【Objective】There is a large population and strong demand for vegetables in Guangdong-Hong KongMacao Greater Bay Area (hereinafter called “the Greater Bay Area”). The evolution of vegetable production pattern and its influencing factors are studied in order to provide references for the spatial layout optimization and high-quality development of vegetable industry in the Greater Bay Area.【Method】The global autocorrelation indexes of vegetable gross outputs of each year were calculated to judge the regional correlation of vegetable production by using the statistical data at counties of the Greater Bay Area from 2010 to 2020 and the administrative map of the same year. The aggregation area of vegetable production and its spatial pattern evolution in counties were analyzed by local autocorrelation index. Spatial regression model was used to analyze the socio-economic factors affecting vegetable production under spatial correlation.【Result】From 2012 to 2020, the global autocorrelation index passes the test and the value is greater than 0, indicating that the vegetable production at county level forms a positive spatial correlation pattern, and the vegetable production has a certain degree of aggregation in space and increases with inter-annual changes. Through local spatial autocorrelation test and analysis, it is found that vegetable production areas such as Longmen county, Boluo county and Huicheng district shows a high-high aggregation pattern, and gradually forms an aggregation pattern in the northeast of the Greater Bay Area over time. The high-low and low-high spatial patterns of vegetable production are gradually affected by the positive correlation of adjacent areas, and finally forms the same pattern with the surrounding areas. Through the analysis of spatial regression model, it is found that the main factors affecting vegetable production are land, economic level, labor force and agricultural technology input in 2012. After 2016, the main influencing factor is land, while the influence of other factors is not obvious or significant, indicating that the expansion of vegetable planting scale is the first factor of yield increase.【Conclusion】There is a positive spatial correlation in vegetable production in Guangdong-Hong Kong-Macao Greater Bay Area, and gradually forms an industrial core area. In the future, it is necessary to increase investment in agricultural science and technology in the core areas of vegetable production such as Boluo, Longmen, Huicheng and Conghua, to further improve the modernization level of production, continuously drive the surrounding areas to improve the comprehensive industrial benefits, and promote the high-quality development of the vegetable industry. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University (Science Edition) is the property of Journal of Zhejiang University (Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Environmental Science & Technology (10036504) is the property of Editorial Board of Environmental Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Remote Sensing for Natural Resources is the property of Remote Sensing for Natural Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Remote Sensing for Natural Resources is the property of Remote Sensing for Natural Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives：Outdoor advertisement can attract the attention of target user groups and increase brand influence, and site selection is the most important influencing factor for its effectiveness. Reasonable site selection plays a positive role in improving brand awareness and expanding the market. However, due to the difficulty in obtaining commercial data, previous studies on a macro and rough scales failed to conduct detailed analysis on the actual effects of site selection. Methods：We propose a framework to solve the above problems. Firstly, we extract feature sets from geographical attributes and commercial economic attributes and preprocess them using mathematical statistics and the geographical processing basic method. Then, by coupling of the in⁃store conversion rate with road network characteristics, point of interest (POI), and other multi⁃source spatial features, a random forest model is constructed to mine the correlation between them. Finally, the importance of each feature is quantified. Results：We choose Beijing as the study area, and build a prediction model for the in⁃store conversion rate of a home decoration brand based on this framework. The model shows a good performance (Standard R²=0.758). Then we obtain the spatial distribution and factors influencing the suitability of outdoor advertising for this home decoration brand in Beijing. The in⁃store conversion rate of the brand is high in the center and is low in the periphery of Beijing, which features the phenomena of strong spatial autocorrelation and high⁃value aggregation. Meanwhile, the in⁃store conversion rate has a significant correlation with social economy, commercial politics, and crowd activities. The location of continuous advertising exposure to the same group has a great influence on the in⁃store conversion rate. Conclusions：The fine mapping results of the model constructed in this study can quantitatively evaluate the advertising effect of each location and maximize the efficiency, which can provide a reference and theoretical basis for relevant studies on the outdoor advertisement or commercial site selection. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the precision loss problem of most low-complexity Root-MUSIC algorithms at present, a low-complexity Root-MUSIC algorithm with precision compensation ability is studied and proposed. The algorithm reconstructs the autocorrelation matrix with Toeplitz shape according to the first row of the approximate data observation matrix obtained by finite snapshots, so that the reconstructed autocorrelation matrix has Hermitian property. After decomposing the reconstructed autocorrelation matrix, the noise subspace is obtained, the noise subspace is flipped and split, a new root-finding polynomial is reconstructed, and then the DOA estimated value is obtained by the root-finding method. The algorithm proposed in this paper using Toeplitz matrix reconstruction and root polynomial reduction effectively improves the DOA estimation accuracy of the improved Root-MUSIC algorithm. And the time complexity of the improved algorithm is no higher than that of previous algorithms. Under different incident sources and sampling snapshots, the algorithm proposed in this paper also shows stronger robustness and stability. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agricultural Science & Technology (1008-0864) is the property of Journal of Agricultural Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study explored the value of MRI texture analysis in the preoperative T staging diagnosis of rectal cancer and its relationship with the degree of tumor differentiation. Seventy-two patients with rectal cancer were selected as the research objects, and MRI texture analysis was performed. The results showed that the mean value of MRI texture parameters, contrast, autocorrelation, entropy, variance, and preoperative T staging of rectal cancer were all influencing factors. The preoperative T staging AUC of each parameter in the combined diagnosis of rectal cancer was 0.951, which was significantly higher than that of a single parameter. The MRI texture parameters of patients with different tumor differentiation levels are significantly different. The mean, autocorrelation, entropy, variance and the tumor differentiation are negatively correlated, and the contrast is positively correlated with the tumor differentiation (P<0.05). The mean value of MRI texture parameters, contrast, autocorrelation, entropy, and variance are the influencing factors of preoperative T stage of rectal cancer, which can be used for the diagnosis of T stage and are related to the degree of tumor differentiation. [ABSTRACT FROM AUTHOR]

Objectives：Due to the sharp decline of global ecosystem services (ESs), there is an urgent need for correct environmental governance policies. The two problems in the current ecological environment governance in China need to be solved: (1) The lack of overall planning based on ecological function areas, (2) The shortage of in⁃depth synergy and tradeoff understanding among ESs. This study takes ecological function areas as the research units to measure the spatio temporal changes of four ESs (grain production (GP), carbon sequestration (CS), outdoor recreation (OR), and biodiversity conservation (BC)). It also explores the formation mechanism of the synergy and tradeoff among ESs and its spatially non⁃stationary response of the synergy and tradeoff to the five influencing factors of temperature, precipitation, sunshine, altitude, and urbanization. Methods: Various models and multisource data are integrated to estimate the yield distribution of ESs in Fujian Province. A difference comparison method is proposed to determine the spatial distribution of the synergy and tradeoff among ESs. The Moran􀆳s I applied is to determine the spatial autocorrelation of the synergy and tradeoff among ESs. The influencing factors are selected by principal component analysis, and the geographical weighted logistic regression (GWLR) determined the spatial response of the synergy and tradeoff to the influencing factors. Results: The main results are as follows: (1) The four ESs selected in the study (GP, CS, OR, And BC) have spatial heterogeneity. Among them, the yield distribution of GP is significantly related to the administrative region, and the highest values of BC, OR and CS appear in the ecological functional areas of biodiversity and water conservation. (2) All the Moran􀆳s I values applied are greater than 0, which means the synergy and tradeoff among ESs have significant spatial autocorrelation and are spatially clustered. (3) In space, there are synergy and tradeoff, instead of a single relationship between two ESs. (4) When the yield spatial distribution of two services is similar, such as BC and OR, the spatial distribution of synergies and tradeoffs of other services is also very similar. (5) The synergy and tradeoff among ESs showed significant responses to climate, topography, and urbanization. (6) The responses of the synergy and tradeoff among ESs to the influencing factors are spatially heterogeneous, and their positivity, negativity, and intensity varied with space. Conclusions: The diagnosis results of the model show that GWLR is superior to the global regression model in explaining the correlation of synergy and tradeoff among ESs with the influencing factors. By summarizing the law of the occurrence of synergy and tradeoff among ESs, this paper refines the existing formation mechanism of the synergy and tradeoff among ESs: In a certain area, the area proportion of supporting type of land and non⁃supporting type of land, and the degree of their support effect for each service will divide the two services into superior service and inferior service within the region. Due to the changes in land use, there are a dynamic gap between the superior service and the inferior service, and the increase in the gap may lead to tradeoff. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Unbalanced land use and multifunctionality have posed a great challenge in Liaoning Province, northeast China. There is an urgent need to conduct a multifunctional evaluation system for regional land use, particularly on zoning assessment. In this study, 22 typical indicators were selected from the three aspects of land use, including living, production, and ecology function. An entropy weighting method was applied to calculate the weights of indicators, and then to obtain the mean values of land use life, production, and ecological function in the study area in 2017. A two-dimensional graph-theoretic clustering method was used to integrate the spatial connectivity and indicator similarity between the zoning units. In a weighted connectivity vectorless map G = (V, E, D), the clustering data was achieved using a graph-theoretic minimal tree method. According to the main functional area planning, an optimal construction of each zoning district was proposed for spatial planning in county-level land. The research shows that: 1) The Pearson correlation coefficient of living function and production function was 0.343, whereas, that of production function and ecological function was -0.518. There was no significant correlation between living function and ecological function. 2) The high-value areas of living function were mainly distributed in an oblique “X” shape in the middle of Liaoning province, with low functional values on the east and west areas. There was no significant spatial autocorrelation of living function. The production function value presented a ring-shaped distribution in the center of Shenyang city, while decreased gradually from the center to the edge areas. In the production function, there was a positive and weak autocorrelation with high-high aggregation in the middle, while low-low aggregation in the east. High-value areas of ecological function were mostly distributed in the east and west areas, indicating the function value decreased gradually from the outside to the inside. In the ecological function, there was a positive and strong autocorrelation with high-high aggregation in the east, and a low-low aggregation in the middle. 3) According to the multifunctional features of land use, the study area was divided into, a) the east, the demonstration area of ecological function, b) the north, the function less coordination area, c) the south, the relatively balanced area, and d) the west, the function less development area. The east of Liaoning Province can be strengthened in the construction of public service facilities and economic development. Much attention can be paid to the development of inferior functions in the functional undercoordinated area of northern Liaoning, in order to achieve the goal of coordinated development. In the south of Liaoning, the spatial structure of land use can be optimized in the relatively balanced functional area, thereby to improve the land use function and competitiveness. In the west of Liaoning, the regional advantages can be enhanced in the underdeveloped functional areas, to gradually strengthen the function of land use. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

NPP of cropland was estimated based on MODIS data and VPM model between 2000 and 2015 in the Jianghan Plain. The spatial autocorrelation and Sen trend methods were used to analyze the spatiotemporal variations and influencing factors of cropland NPP in the study area during the 16 years. The results show that: (1) The average annual NPP of cropland in the plain increased from 2000 to 2005, decreased from 2005 to 2009, and increased from 2009 to 2015. The annual total of cropland NPP was stable from 2000 to 2015. (2) The proportions of high, medium and low yield fields were 66.03% , 27.04% and 6.93% , respectively. NPP had a strong spatial aggregation from 2000 to 2015, which showed an increasing trend year by year, and its aggregation decreased with the increase of spatial distance. The NPP is characterized by high- high aggregation and low-low aggregation in the Jianghan Plain. (3) No significant change was found in 69.5% of cropland NPP, with 1.30% of cropland NPP rising significantly and 29.20% of cropland NPP decreasing significantly in the Jianghan Plain. [ABSTRACT FROM AUTHOR]

Copyright of South China Fisheries Science is the property of South China Fisheries Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of Beijing Institute of Technology is the property of Beijing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

High importance has been put by government on the issues of water and soil erosion which are the key factors for sustainable development of agriculture in the Loess Plateau. There is a considering number of models to resolve this problem after several year’s practice. From the perspective of relationship and coupling of agricultural eco-economic system, some crisis is hidden in the process of establishing benign coupling relationship of agricultural eco-economic system. To achieve sustainable development in the area of Loess Plateau, it is necessary to build win-win situation among ecology, economy and society. In this study, we selected panel data from 16 prefecture-level cities in Shaanxi, Gansu and Ningxia Province from 2007 to 2014. On the basis of previous researches, the subjective and objective comprehensive weighting method named Analytic Hierarchy Process (AHP) and Variation Coefficient Method (CPA) were adopted to measure the weights of the evaluation indicators from the qualitative and quantitative perspectives. Based on the coupling degree model, the degree of mutual influence between the water and soil erosion management system and the ecological agriculture development system was explored from the perspective of the geomorphological features and prefecture-level cities for understanding the consistency of the system development situation as a whole. Based on the coordination degree model, the internal elements relationship between water and soil erosion management system and ecological agricultural development system was explored from the perspective of geomorphological features and prefecture-level cities for understanding the interaction relationship and coordination of every factor under different coupling stages. Using the bivariate spatial autocorrelation model, the coupling coordinative degree between the benefits of soil and water loss treatment and the level of ecological agriculture were taken as a measurement index. The index of measuring level of coupling degree of water and soil erosion control efficiency and ecological agriculture development: global and local degree Moran I indexes were calculated using Geoda software. Combined with LISA clustering analysis, in this paper, we analyzed the spatial distribution correlation of coupling degree between water and soil erosion control efficient benefits and ecological agriculture development to explore the coupling coordination state and development trend between water and soil erosion management and ecological agriculture development. Also, in this paper, we wanted to find the general laws of coupling and coordination between two subjects in order to provide scientific basis for policy development. The results indicated that the coupling level of water and soil loss erosion control benefits and the development level of ecological agriculture were generally high in the research area, but the degree of coordination was low and the development trend of coupling and coordination was slow, it presented a "low level equilibrium" state. The overall spatial agglomeration was gradually strengthened, but the two levels were severely differentiated. There was a lack of necessary “radiation hubs” between the “high-high” agglomeration areas and “low-low” agglomeration areas. New agglomeration poles were badly needed to be trained. Based on the above conclusions, we proposed the following policy recommendations: 1) maintaining the momentum of coupling development, 2) radiating development models, technology, and experience actively, 3) increasing mutual support and cooperation among regions, 4) strengthening pilot research, 5) exploring key factors that stop coordinated development from multiple perspectives, 6) breaking through the bottleneck of coordinated development, 7) cultivate new agglomeration poles, 8) increasing system resilience, and 9) easing spatial agglomeration. [ABSTRACT FROM AUTHOR]

Combined with the current research progress and shortcomings on spatial distribution characteristics and scale effects of soil properties, using a combination of variogram theory, spatial autocorrelation theory, multi-fractal theory and other methods from the aspects of the spatial variability of soil properties and the structure, the paper gradually revealed the spatial distribution characteristics of SOC (soil organic carbon) and its scale effects under 4 kinds of scales. The results showed that: Ratio of nugget to sill of SOC under 15, 25, 35 and 45 km scales were 61.78%, 42.65%, 49.98% and 39.34%, respectively, which showed a moderate spatial correlation. The spatial correlation from high to low was 45, 25, 35 and 15 km in turn. Except the 15 km scale, the spatial variability caused by random factors including representative measurement error and the micro-scale process, was less than the structure variance, namely the ratio of nugget to sill was less than 50%, the structural factors were dominant, and spatial variability from the random part showed a decreasing trend with the scale increasing. The variation function couldn't be described with discrete characteristics (i.e. spatial negative correlation), which was also impossible to make a significant test for variable range. As the separation distance increased, the Moran index decreased from full positive to negative, then the positive and negative values alternately occurred, and eventually the values turned out to be negative totally. Nearer positive correlation distance represents the spatial correlation distance, which is the first cross point of positive and negative conversion under different scales, and were 1 607, 7 520, 8 649 and 9 053 m for 15, 25, 35, and 45 km scale. With the scale increasing, the spatial correlation distance increased, and compared to the change range in the semi-variation function, it became smaller with varying degree under different scales except 15 km scale. The greater the scale, the greater the total spatial autocorrelation. The order for standardized statistic under different scales was 15 km < 45 km <35 km < 25 km, which increased firstly and then decreased with the scale. All random scale accounted for less than 5%, and on the whole each scale had good spatial structure. The multidimensional fractal parameter value under 25 km scale was the largest, indicating that the SOC content in this scale was mainly concentrated in a dense area. The magnitude of variation of Rayleigh dimension of SOC under 4 kinds of scales was consistent with that of width of multidimensional spectrum. The spatial distribution of SOC is a typical fractal dimension. Multifractal method is a tool for describing the spatial heterogeneity of SOC. It can reveal the scale variation characteristics of spatial heterogeneity of SOC. No matter what kind of scale, specific value of the measured value based on the Mkrige method agreed well with the predicted value, and the coverage ratio of specific value was above 85%. Spatial distribution characteristics of SOC were deeply revealed through combining variation function, spatial autocorrelation, multi-fractal and Mkrige method from spatial variability, spatial correlation and spatial structure in research area. The results can provide a method to the research on the spatial distribution characteristics of SOC in relatively flat agricultural region. However, due to the different combinations of artificial and natural factors, the spatial variability, correlation and structure will vary with scale change. [ABSTRACT FROM AUTHOR]

This paper studied the autocorrelation of two kinds of binary sequences with period N≡2( mod 4) and N≡0( mod4). Utilizing the correlation of balanced sequences with period N≡1( mod 4),this article obtained the distribution frequency for the autocorrelation of these binary sequences. Also the autocorrelation of these sequences only existed determined values and the frequency of these values was also determined. The results show that such sequences have good autocorrelation property and distribution frequency of the autocorrelation is determine. Therefore,these sequences can eliminate the effect of multipath,which indicates these sequences have strong potential applications in communication systems and cryptography. [ABSTRACT FROM AUTHOR]

Single channel mixed signal parameter estimation is a hot topic in wireless communication and signal processing. In this paper, two cyclic auto-correlation based time estimation methods are presented for single-channel mixed communication signals, which is based on the relationship of cyclic autocorrelation functions and signal's modulation parameters. The two different methods are designed for scenarios of unknown and known channels of both signals respectively. The methods treat both co-channel signals as desired signals. Firstly, cyclic autocorrelation function of the received mixed signal is analyzed, and then the linear equations on time delay parameters are established for the two scenarios. Secondly, the closed-form solution for time delay parameters of both co-channel signals is obtained by solving the equations, and two estimation algorithms are presented. The Cramer-Rao bound is also analyzed in this paper. Finally, computer simulation results are provided to demonstrate the performance of the proposed methods and their application conditions. [ABSTRACT FROM AUTHOR]

Higher requirement of pulse repetition frequency will be faced when synthetic aperture radar (SAR) is at a very low height. Doppler centroid will deviate from zero when the squint angle is too large, resulting in defocusing the final image. For imaging of low-height and squint-looking SAR, a pulse repetition frequency is designed properly in order to get a high resolution image and avoid the range and azimuth ambiguities and the interference of the transmitted pulses, and the problem of overlaying the azimuth spectrais solved. Goiomb sequence is optimized with cyclic algorithm, and a good autocorrelation is used to get high range resolution. After STOLT interpolation mapping, the raw data is properly processed using w-k algorithm to get agood imaging result. Simulation results show that the algorithm can solve the problem of low height and large squint SARimaging. [ABSTRACT FROM AUTHOR]

A carrier frequency estimation algorithm based on the expanded autocorrelation in additive white Gaussian noise was proposed, Through theoretical analysis, the algorithm fully excavates frequency information contained by the autocorrelation function and derives a new expanded autocorrelation and improves the frequency estimation formula based on the Yan algorithm. Compared with the existing algorithm, Numerical simulations indicate the estimation variance of the proposed algorithm is more close to the Cramer-Rao low bound (CRLB) when the sequence length is small or the SNR is low. and the calculation amount is smaller under the same estimate variance compared with the Yan algorithm when the sequence length is large or the SNR is sufficient. [ABSTRACT FROM AUTHOR]

Conventional power spectrum density (PSD) estimation method based on correlation function is obviously degraded in the impulsive noise environment, even loses efficacy under big impulsive noise. As a new localized similarity measure, correntropy is not sensitive to the impulsive noise and adapts this environment. Correntropy spectrum density (CSD) estimation method is achieved through correntropy function replacing autocorrelation function of signal. With the same SNR the CSD method is robust to the PSD method through simulation. Specially, the CSD method is also effective under big impulsive noise (α < 1.6), and the mean and variance of estimation error remain low level. [ABSTRACT FROM AUTHOR]

For the contradition of existing variable step-size adaptive algorithms between convergence speed and steady-state error, a new variable step-size least mean square(LMS) adaptive filtering algorithm is proposed. Based on a function of the class S, this new algorithm introduces a reference of adjustment factor P to perform real-time adjustments of the shape of step function, and adjusts the step according to errors autocorrelation mean value so that the convergence is faster innitially and the step changes more smoothly at steady state. The introduction of maximum likelihood weighted algorithm further suppresses the spurious peaks of adaptive filter weights. The new algorithm with maximum likelihood weighted is applied in adaptive time delay estimation experiment, and the result shows under the condition of the existing fixed parameters, the newly-proposed algorithm has faster convergence and smaller steady-state error. Meanwhile, accurate delay estimation when SNR is above -3 dB can be achieved effectively. [ABSTRACT FROM AUTHOR]

Research on the relationship between tourism development and economic growth is not only the core of tourism economics study, but also a long-term hot topic among tourism theorists. Studies on the relationship between tourism development and economic growth are voluminous, but generally they are undertaken using two approaches: theoretical analyses and empirical tests. For a long time, the impact of tourism development on economic growth has been the focus of debate throughout the history of tourism economics research. Mainstream tourism economics literatures believe that tourism development has played a significant role in promoting economic growth. However, skeptics argue that tourism development does not have long and sustainable contributions to economic growth. Thus, this article intends to explore the impact of tourism development one conomic growth in China. A literature review of overseas empirical studies shows that researchers mainly investigate the relationship between tourism development and economic growth through time-series studies and general panel data analysis. Although these researchers are consistent in defining study objects as independent observations in the traditional sense, they ignore the geospatial relevance and dependence of tourism development and economic growth. A basic preliminary judgment is that such studies neglect the spatial spillover effect of tourism development on economic growth. As a result, the findings and explanations of these traditional studies are unconvincing. The literature review indicates that little research incorporates spatial spillover effect into the research framework with regard to the impact of tourism development on economic growth. No foreign literature has touched on this topic. In response to the biased conclusion caused by the neglect of spatial correlation in traditional research, this article adopts space panel measurement, a more cutting-edge method, to analyze 30 provinces' panel data during 1999~2009 in China, and empirically test the relationship between tourism development and economic growth. Research findings indicate that tourism development shows a significant spatial autocorrelation, and remarkable spatial agglomeration features; most provinces are categorized into the high-high and low-low group; tourism development has significant promoting effect on economic growth, the traditional panel regression model overestimated this positive effect due to neglect of the spatial correlation; tourism development has significant and steady spatial spillover effect on economic growth. Tourism development has significant spatial spillover effect on economic growth. This finding indicates the importance of the cooperation to regional tourism strategic alliances. The most critical thing is to establish a market adjustment mechanism for tourism production factors, break administrative barriers, and rationally allocate resource elements. These will help to improve the positive effect of tourism development on economic growth. Second, it's important to strengthen the regional cooperation of tourism market, extend the production chain of tourism products, build complementary tourism product supply system to realize the diffusion and diversion of tourism flows, and ultimately strengthen tourism development's spatial spillover effects on economic growth through regional tourism integration. In addition, when provinces plan tourism industry or make related policies, they should have a proactive strategic vision, take full advantage of micro spillover conditions, such as tourism industry cluster, tourism enterprises' knowledge spillover, tourism routes design, tourism products promotion, tourist sharing, etc., strengthen cross- regional tourism cooperation, thereby expand the spatial spillover range of tourism development. [ABSTRACT FROM AUTHOR]

Aimed at the problems of the parameter estimation of non-periodic long-code Direct Sequence Spread Spectrum (DSSS), in this paper, a representation model for non-periodic long-code DSSS is built up, and the autocorrelation function of its delay-product is derived and analyzed. The autocorrelation function has periodic peaks, and a reciprocal of the space between two adjoining peaks is the chip-rate of pseudo-random sequence. The effect of the noise to the autocorrelation function is also analyzed, and theoretically the effect of the noise could be canceled by choosing the right delay. On the basis of these properties an estimation method of the chip rate of pseudo-random sequence of non-periodic long-code DSSS is proposed. At first, the autocorrelation is calculated after the received base signal is delayed and multiplied. Then the peak which is generated by noise is canceled. At last, the interval between two adjoining peaks is estimated and the chip rate is got. The computer simulations results show that the proposed method is effective. [ABSTRACT FROM AUTHOR]

The method of how to find the blur parameters on an image was suggested when blurring factors of high frequency vibration and uniform linear motion happen simultaneously. Blurred images with various composite motion blur parameters were synthesized and analyzed using existing algorithms. It was found that cepstral analysis was capable of discerning the motion angles accurately when the directions of two motions are different. Along the motion angle, if the autocorrelation function of derivative image exists two close extreme points with positive and negative values separately and the space between two peak points is less than 4~ 5 pixels, the image would be blurred by high frequency motion, otherwise it would be blurred by uniform linear motion. Having determined the motion angle and motion style, the quadratic radon transform is the best way to obtain the blur amplitude for high frequency vibration. As for the uniform linear motion, the autocorrelation of image derivative is the best algorithm to obtain the blur length. [ABSTRACT FROM AUTHOR]

Considering characteristics of urban land price space system, fractal feature extraction models of urban land price space system based on Moran's I index, Getis-Ord General G index and the box counting dimension principle were proposed. The experiment was carried out with residential land market data of Beijing. The results show that there are significant positive autocorrelations for residential land price space system within 3500m. Spatial autocorrelation degree of land price decreases with the increase of spatial scale. Residential land prices are clustered in space such that higher land price tends to be surrounded by higher land price neighbors and lower land price by lower land price neighbors. Further, fractal dimension of residential land price space system is between 2 and 3. The bigger fractal dimension, the more complicated land price space system. The empirical results suggest the existence of fractal features in urban land price space system. It helps us not only for knowing the land price distribution in space better, but also for exploring fractal interpolation of land price space. [ABSTRACT FROM AUTHOR]

In the CPC Central Committee's Proposals for the 12th 5-year Plan, the Chinese government has advocated the harmonious development among regions. Based on the spatial econometric analysis of the economic development of 36 regions in Northeast China from 2000 to 2010, this paper explores the evolution process of spatial economic developmental inequity in Northeast China. The findings indicate that the spatial inequity of Northeast China is closing the gap yearly and the regional dual structure of economic development is disappearing gradually. However, the spatial autocorrelation has become more and more significant. The evolution pattern of Liaoning Province is consistent with the overall situation of Northeast China while the cases of Jilin and Heilongjiang are to the contrary. [ABSTRACT FROM AUTHOR]

Based on the wavelet transform, an innovative method of calculating the turbulent integral length is presented, in which the errors of the integral length caused by the oscillating correlation of the higher frequency components are depressed. The contributions of the different wavelet components with different frequencies can be described in detail. The investigated results of the turbulent integral length at the Beijing Meterological Tower show that the integral length scales are distributed scattered and that they are postive skewed. In order to obtain the reasonable results of the integral length scales, the integral length scales of the large probability occurred are remained while the singular integral length scales are discarded. A profile formula of the integral length scales for Beijing city is proposed after the fitted expression is found and then the comparison between the proposed formula and the formulas of the integral length scales in different codes. [ABSTRACT FROM AUTHOR]

The spatial effects of both interdependence and heterogeneity are common in regional tourism growth processes, and this refers to the indirect or unintentional effects that one region's tourism industry exerts on the tourism industries of other regions. As a result, a region's tourism growth can obtain benefits from their neighbors' tourism growth through positive spillover effects. Even though the estimation research on the contributions of capital and labor on outputs in the tourism industry have received a high level of interest internationally and domestically, very few studies have considered spatial effects in theoretical tourism growth analysis and empirical tourism model specifications. The lack of research is especially obvious regarding empirical evidence on the growth of regional tourism industries in China's provinces. At present, the vast majority of empirical studies that estimate and measure tourism elasticity have been based on conditional mean estimates using the ordinary least squares (OLS) method, which ignores the role of spatial effects in model design and empirical studies of the tourism production function. As a result, estimate results of tourism elasticity coefficients lack scientificity and accuracy. As such, the conclusions obtained may not actually accurately represent growth in the tourism industry. Furthermore, policy judgments based on parameter estimation results and conclusions are often questionable. While it is pleasing to see that some studies do consider spatial effects in the tourism growth process, the aggregate production function should be homogeneous to each spatial unit in tourism research, and the parameters estimated using the OLS method are often constant parameters. As a result, it is difficult to measure regional tourism production behavior including spatial correlation and to spatially estimate the heterogeneous production function. In contrast to similar studies that include constant parameters, the present study, in its consideration of the location specificity (i. e., resource endowment, geographical position, history and culture, market location, tourism accessibility, tourism consumption level, traffic accessibility, and information technology) of China's various regions, is based on sectional average data from the Chinese provincial tourism industry from 2001 to 2009. Using a geographically weighted regression (GWR) production function model of provincial tourism in China, which includes spatial heterogeneity, this study positively estimates and studies local varying elasticity coefficients of capital and labor on tourism industrial growth. The results, based on a spatial autocorrelation analysis of global Moran's I and local indicators of spatial association ( LISA) analysis, show that there is a significantly global spatial dependency and an obvious local clustering trend for provincial tourism output. Thus, in the study of the tourism industry, we cannot ignore spatial effects, including both interdependence and heterogeneity. The globally constant parameter estimation results, with and without consideration of spatial autocorrelation in the provincial tourism production function, show that the capital investment of the elasticity coefficient is 0. 6939 and 0. 7824, and the labor input elasticity coefficients are 0. 4932 and 0. 3163, respectively, which means each factor input is in a phase of increasing returns to scale. The locally varying parameter estimation results, which consider spatial heterogeneity in the GWR models, show that the elasticity coefficients of capital investment are between 0.6905 and 0.6958, and the labor input elasticity coefficients are between 0.4859 and 0.4989. Thus, each provincial factor input is in a phase of increasing returns to scale. The GWR model can effectively estimate the regional tourism elasticity coefficients under the premise of spatial heterogeneity, which increases the differential policy implications for regional tourism development. In terms of general policy suggestions, the heterogeneity policy implication of this study is very obvious. It is not possible to achieve sustainable tourism development with a simple dependence on capital input growth. Once China's tourism enters the transformation development stage, and this is true for China's tourism development and the current mode of national economic development, the economic development pattern will rapidly transform from increasing quantity to increasing quality. To realize sustainable tourism development in China's provinces, the nation together with each province needs to promote the reform of institutions and the tourism development mechanism, and especially strengthen the reformation of tourism human resources and improve employee skills, taking into account regional heterogeneity. Furthermore, in time, the uniform nature of China's tourism development planning and tourism strategy needs to be adjusted, and tourism development strategies and travel supervision laws and regulations should be developed in accord with an area's regional character, and their regional characteristics be promulgated as soon as possible. [ABSTRACT FROM AUTHOR]

A new passive detection and location method for underwater targets based on the correlation metric of three signals received by three elements was proposed, and its advantages compared with two-element-correlation in detection performances were analyzed. The simulation was performed to verify the detection performances and time delay estimation accuracy. The simulation results show that, compared with two-element-correlation method, the modified method can improve the detection performance by 2 dB and the time delay estimation accuracy in a certain extent. [ABSTRACT FROM AUTHOR]

A new approach of automatic classification of the radar emitter signals is presented. This method is based upon the characteristics derived from instantaneous frequencies and contains three sequential steps: firstly, the instantaneous frequencies of radar emitter signals are extracted via the improved instantaneous autocorrelation algorithm; secondly, a two-times-normalizations based feature re-extraction approach is used to obtain the classification characteristic vector; finally, the kernelized fuzzy c-means clustering with validity assessment is carried out to categorize the considered signals automatically. The results of simulation experiments show that, the characteristic vector can reflect the differences of signals with different modulation types and has a good ability to resist noises. The proposed scheme of signals classification can achieve the overall success rate of above 95% , even at the signal to noise ratio of 6dB. [ABSTRACT FROM AUTHOR]

In this paper we take a spatial statistics approach to examine the Taiwan's urban-rural gap in educational attainment. The spatial autocorrelation statistics measure the degree of dependency among observations in a geo-space so that the spatial clustering association and intensity of the data at proximal locations can be analyzed. Based on the data on the subject competency test in 2007, along with the zip code of students' permanent residence, we integrate spatial statistics and Geographic Information Systems (GIS) to graphically map the clustering patterns of test scores across the 358 townships of Taiwan. In that sense, the spatial clustering index provides a better view into the spatial distribution of test performance, and highlights the magnitude of the unbalanced education development over the Taiwan region. The contributions of this paper are threefold: First, we spatially depict the urban-rural disparity in educational attainment so as to avoid artificial data division imposed by administrative districts. As a result, the problem of the aggregation bias can be eliminated. Second, our empirical finding indicates that the academic performance in a part of the townships is significantly greater than that in metropolitan areas. But contrary to common belief, test outcomes in several urban areas are not as exceptional as observed by the previous studies. Finally, the scattering of spatial outliers reveals the inherent problems and the promising solutions for improvement of educational resources allocation. [ABSTRACT FROM AUTHOR]

In view of the question that the estimation performance and the computation for two-stage autocorrelation frequency estimation algorithm (TSA algorithm) can't be taken into account, this paper proposed a new two-stage autocorrelation approach which was based on sinusoidal signal to solve it. The algorithm first bisected the observed signal to get two signals of same frequency as the source one with different phase and uncorrelated noise. Then it used the LP property of sinusoidal signal and the self-correlation function, established the parameter estimation equation and obtained the high-precision frequency estimation algorithm. Finally, it performed the Monte Carlo method to verify the effectiveness of the algorithm. The simulation results show that the new algorithm is better than the TSA algorithm as a whole, and also it has a good practicability. [ABSTRACT FROM AUTHOR]