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Planting forests is an effective way to improve desertification. In order to elucidate the impacts of different vegetation types on soil development and restoration of degraded lands, we compared the properties of soils at different depths in three plantation forests in the Hunsandak Sandy Land in the Chinese agro-pastoral ecotone (Ulmus pumila, Pinus sylvestris var. mongolica, and Populus simonii). The results show that all three plantation forests were able to significantly improve the soil properties, and they resulted in soil nutrient enrichment in the surface layer. As the soil depth increased, the soil became progressively poorer in nutrients, the fine particle content decreased, and the bulk density and water content increased. The orders of the fractal dimension characterization and soil improvement effects of the different tree species were as follows: U. pumila > P. sylvestris var. mongolica > P. simonii. Compared with the bare sand, the soil bulk density under the U. pumila plantation was 19% lower; the soil water content was 74% higher; the soil organic matter, total N, P, and K were 336%, 207%, 106%, and 31% higher; the available N, P, and K were 41%, 125%, and 21% higher; and the clay and silt contents were 498% and 387% higher, respectively. The ranges of the soil fractal dimension were 1.67–2.08 for the bare sandy land and 2.14–2.32 for the planted forests. The soil fractal dimension was strongly correlated with the soil physicochemical properties, especially with the soil nutrients and fine particle content, which exhibited highly significant correlations (p < 0.01), and the correlation coefficients were all greater than 0.8. Therefore, we believe that U. pumila is a suitable sand-fixing plant species in this area. In addition, the soil fractal dimension can be used as an important reference index for characterizing soil properties in sandy areas. [ABSTRACT FROM AUTHOR]

Abstract Planting forests is an effective way to improve desertification. In order to elucidate the impacts of different vegetation types on soil development and restoration of degraded lands, we compared the properties of soils at different depths in three plantation forests in the Hunsandak Sandy Land in the Chinese agro-pastoral ecotone (Ulmus pumila, Pinus sylvestris var. mongolica, and Populus simonii). The results show that all three plantation forests were able to significantly improve the soil properties, and they resulted in soil nutrient enrichment in the surface layer. As the soil depth increased, the soil became progressively poorer in nutrients, the fine particle content decreased, and the bulk density and water content increased. The orders of the fractal dimension characterization and soil improvement effects of the different tree species were as follows: U. pumila > P. sylvestris var. mongolica > P. simonii. Compared with the bare sand, the soil bulk density under the U. pumila plantation was 19% lower; the soil water content was 74% higher; the soil organic matter, total N, P, and K were 336%, 207%, 106%, and 31% higher; the available N, P, and K were 41%, 125%, and 21% higher; and the clay and silt contents were 498% and 387% higher, respectively. The ranges of the soil fractal dimension were 1.67–2.08 for the bare sandy land and 2.14–2.32 for the planted forests. The soil fractal dimension was strongly correlated with the soil physicochemical properties, especially with the soil nutrients and fine particle content, which exhibited highly significant correlations (p

It had been demonstrated that the functional brain networks of Alzheimer’s patients exhibit topological properties distinct from those of cognitively normal individuals, including small-world and clustering coefficients. To further elucidate the structural characteristics of the brain networks of Alzheimer’s patients and their differences in brain network structure with cognitively normal individuals, fractal features were introduced for comparative analysis. Experimental results demonstrated a significant difference in the minimum number of boxes and connection ratio between brain networks of Alzheimer’s patients and cognitively normal individuals at the same box-covering radius. At the brain network threshold of 0.4, the connection ratio values of cognitively normal individuals’ brain networks were distributed in the [0,1] interval, while the connection ratio values of Alzheimer’s patients’ brain networks were distributed in the (0.5,1) interval. Furthermore, the average connection ratio of Alzheimer’s patients’ brain networks was found to be higher than that of cognitively normal individuals at different thresholds. These differences in network structure provide a new reference for the diagnosis of Alzheimer’s disease.

Silty mudstone distributed in southern China subjected to wet–dry cycling exacerbates the rock deterioration, posing significant challenges to slope stability. This study aims to investigate the damage characteristics and degradation mechanisms of silty mudstone after undergoing multiple wet–dry cycles. The specimen variation was simulated in laboratory under repeated cycles and the degree of specimen degradation across various cycle numbers (N) was evaluated using a combination of geotechnical tests (uniaxial compressive and split tensile tests) and microscopic observations via Scanning Electron Microscopy. Further, the fractal feature was characterized by Box-counting Dimension method implemented in MATLAB, and the damage evolution equation was obtained based on the damage theory. The findings reveal a pronounced decline in mechanical properties and a transition from brittle to shear failure modes with an increase in N, alongside an enhancement in cross-sectional integrity post-damage. Porosity changes notably, with an increased proportion of larger pores post-erosion. The fractal dimension escalates with rising N, with the damage variable and strength degradation rate initially increasing followed by stabilizing. A developed quadratic polynomial damage model exhibits universality for silty mudstone submitted to wet–dry cycling. The degradation mechanism is identified as resulting from cement dissolution and recrystallization, mineral surface hydration, and particle softening and disintegration. [ABSTRACT FROM AUTHOR]

The pressure on coal affects the pore fracture structure, altering the seepage characteristics of fluids such as gas or water. A special pseudo-triaxial loading nuclear magnetic gripper was used for uniaxial compression testing of the coal body. The T2 map of the lignite was tested online, and MRI imaging was performed. The correlation between the pore fracture structure evolution and seepage characteristics of lignite was studied. The results show that (1) there are three stages, namely, compression, pore development, and post-peak failure, which promote the development and evolution of medium pore and macropores in lignite. (2) Under uniaxial compression, the permeability of the lignite sample shows a “V-shaped” trend, first decreasing and then increasing. When the axial pressure reaches approximately 3.0 MPa, the mutation of the MRI signal increases, and the enhancement of the MRI signal of the sample is due to the cumulative effect of mutation after aggregation. The aggregation of water image signals reflects the distribution area of pores that dominate seepage. (3) Under uniaxial compression, the pore change rate Si slightly decreased. The pore change rate Si of medium pores and macropores showed a positive correlation with axial pressure, which is consistent with the total pore change trend. The compressibility coefficient Cp of the porous pores (medium pores and macropores) and the permeability stress sensitivity coefficient Cf exhibited a linear correlation. The fractal dimension D2 and D3 values of pores in the medium and macropores scale range are close to 3, with the maximum value of D2 being 2.971. This indicates significant fractal characteristics, suggesting that medium pores are the most developed in this scale range. Researches show that that the middle pore has a greater stress sensitivity and shows obvious fractal characteristics during the load failure. The compressibility of the large pore is correlated with the permeability sensitivity, These results show can help elucidate the influence of the pores fracture structure on the seepage evolution of lignite.

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The comparative analysis of coal samples under different gas occurrence conditions systematically reveals the pore structure characteristics of coal and gas outburst coal seams. The functional relationship between R0,max and Kc was clarified using mathematical statistical methods, and the pore structure and fractal characteristics of coal and gas outburst coal seams were analyzed on the basis of modified mercury pressure data and fractal analysis. The results show that the functional relationship between R0,max and Kc is consistent with y = 1.59x−0.48, and when the mercury inlet pressure is 10~120 MPa, the coal sample is the most affected by the matrix compression effect. The average pore volume and average specific surface area of the outburst coal samples were 41.71% and 23.09%, which is greater than those of the non-outburst coal samples, respectively, and the specific surface area and pore volume provided by the outburst mining micropores were 46.24% and 81.67%, respectively. The fractal dimension, D, of the coal seam increased with the increase in metamorphism, and compared with low gas mines, the fractal dimension of coal samples in the coal and gas outburst mines was higher, the influence of the matrix compression effect was more obvious, and the heterogeneity was stronger. [ABSTRACT FROM AUTHOR]

In order to study the micro pore structure and fractal characteristics of Zhiluo Formation sandstone aquifer in Binchang Mining Area, the characterization parameters, such as pore size, perimeter, area and morphological characteristics of sandstone surface at different depths, are obtained by scanning electron microscope（ＳＥＭ）. At the same time, the fractal dimension and morphological characteristics of sandstone aquifer pore structure are deeply analyzed combined with fractal theory. The results show that the pores of the sandstone aquifer of Zhiluo Formation in Binchang Mining Area are developed and diverse, and the pore space is composed of four pore types: macropore, mesopore, small hole and micropore. The mesopores and macropores account for a large proportion of the total pore area and are the main water storage space of Zhiluo Formation sandstone aquifer. According to the pore perimeter and area extracted from sandstone samples, it is found that the fractal dimension of sandstone pores is large, the pore distribution is uneven, and the pore morphology is complex.

Copyright of Journal of Materials Science & Engineering (1673-2812) is the property of Journal of Materials Science & Engineering 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.)

Accurate extraction of cropland distribution information using remote sensing technology is a key step in the monitoring, protection, and sustainable development of black soil. To obtain precise spatial distribution of cropland, an information extraction method is developed based on a fractal algorithm integrating temporal and spatial features. The method extracts multi-seasonal fractal features from the Landsat 8 OLI remote sensing data. Its efficiency is demonstrated using black soil in Lishu County, Northeast China. First, each pixel's upper and lower fractal signals are calculated using a blanket covering method based on the Landsat 8 OLI remote sensing data in the spring, summer, and autumn seasons. The fractal characteristics of the cropland and other land-cover types are analyzed and compared. Second, the ninth lower fractal scale is selected as the feature scale to extract the spatial distribution of cropland in Lishu County. The cropland vector data, the European Space Agency (ESA) WorldCover data, and the statistical yearbook from the same period are used to assess accuracy. Finally, a comparative analysis of this study and existing products at different scales is carried out, and the point matching degree and area matching degree are evaluated. The results show that the point matching degree and the area matching degree of cropland extraction using the multi-seasonal fractal features are 90.66% and 96.21%, and 95.33% and 83.52%, respectively, which are highly consistent with the statistical data provided by the local government. The extracted accuracy of cropland is much better than that of existing products at different scales due to the contribution of the multi-seasonal fractal features. This method can be used to accurately extract cropland information to monitor changes in black soil, and it can be used to support the conservation and development of black soil in China. [ABSTRACT FROM AUTHOR]

The research on pore structure and heterogeneity of shale reservoirs has always been a hotspot in the study of unconventional reservoir characteristics. China is a country dominated by continental shale. Compared with marine shale, continental shale has lower maturity and stronger reservoir heterogeneity. In this study, Sha-4 shale in the Liaohe Western Depression was selected for low-temperature nitrogen adsorption, scanning electron microscopy and other experiments revealing the pore structure and fractal characteristics of continental low mature organic-rich shale. The fractal dimension was calculated by the FHH model and the effects of TOC and mineral composition on pore structure and fractal characteristics were discussed. The results show that the Sha-4 shale in the study area is mainly mesoporous and the main pore types are inorganic pores with relatively large pore diameters, such as intergranular pores and inter-crystalline pores. The pore morphology is very complex, mainly narrow slit and flat pore, and the pore is often filled with organic matter. The fractal dimensions D1 range from 2.58 to 2.87 and D2 range from 2.18 to 2.55, and the pore structure shows obvious dual fractal characteristics. The pore structure and fractal characteristics of shale are mainly affected by TOC and quartz due to the low degree of the thermal evolution of shale and their effects are different from those of marine shale reservoirs. The increase in TOC reduces the heterogeneity of the shale reservoir. In addition, mineral particles with strong weathering resistance and stability such as quartz can protect the pore structure of shale, improve the pore structure and reduce the reservoir heterogeneity. This study can provide support for the study of low maturity continental shale reservoir heterogeneity in the Sha-4 member of the Liaohe Western Depression. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering 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.)

A fractal realizes the quantitative characterization of complex and disordered mining fracture networks, and it is of great significance to grasp the fractal characteristics of rock movement law to guide mine production. To prevent the water-conducting fracture (WF) under the gullies from conducting the surface water body, and to realize the purpose of safe production and surface water body protection. The evolution of overburden fissures in the working face with shallow buried gulley landform and thick bedrock conditions is studied. The development height of water-conducting fracture (DHWF) is theoretically analyzed. The evolution characteristics of overlying fissures with different mining heights were observed by similarity simulation, and the observation results were analyzed by fractal theory. The results show that the main factor that determines the height of WF is mining height. The working face is mined at different mining heights, and the corresponding indexes such as the height of the WF, the area of the caving zone and the fractal dimension are related to engineering phenomena. In particular, the appearance and disappearance of the separation space correspond to the fractal dimension fluctuation phase. The safe mining technology under a gully water body, which mainly reduces mining height, is adopted, and the fissures of the working face are not connected to the surface water body after mining. [ABSTRACT FROM AUTHOR]

The quantitative evaluation of pore-fractures which links to methane storage space and transportation channels is of great significance for underground gas extraction and coalbed methane development. This study is aimed at revealing the surface roughness and structure irregularity of typical bituminous coal samples using the combination of SEM, box-counting method, and low-pressure N2 adsorption (LPN2A). Pore-fracture fractal dimension is calculated based on the SEM images, and its influencing factors involving coal maturity, tectonic deformation, coal components, and pore structure have been explored in depth. The results indicate that pore morphology varies greatly among these samples. Some wedge-shaped macopores (diameter > 50 nm) and bottle-shaped pores are identified in bituminous C coals, and macropores are the dominant pore types, while macropores only account for less than 23% of pore volume in the high-rank bituminous coals, suggesting that mesopores take a leading role in coal with rank of bituminous A. These samples have different pore-fracture fractal dimensions with D ranging from 1.28 to 1.94, and D is distributed in sequence: bituminous A > bituminous B > bituminous C. The ash content plays a vital role in structure irregularity, and it can reduce the fractal dimension due to the filling in the coal pore-fractures. However, as the increase of burial depth and tectonic deformation, a large proportion of macropores and fractures are transformed into smaller pores including mesopores and micropores, leading to the growing surface heterogeneity. This work is expected to provide a better understanding of complex surface characteristics in coal. [ABSTRACT FROM AUTHOR]

Mixed forests play a key role in the environmental restoration of desert ecosystems and in order to address the improvement of soil properties by different mixed vegetation types. We selected four typical mixed vegetation types (including: Populus alba var. pyramidalis × Caragana korshinskii, P. pyramidalis × Hedysarum mongdicum, P. pyramidalis × Hedysarum scoparium and Hedysarum scoparium × Salix cheilophila) that have been restored for 22 years and the moving sandy land in the transition zone between the desert and the Yellow River in northern China. We compared the differences in soil properties using a total of 45 soil samples from the 0–30 cm soil layer (10 cm units). We found that revegetation had a significant positive effect on fine particles, soil nutrients, soil bulk density (SBD), and soil fractal dimension (D) values. Soil D values under different types of vegetation range from 2.16 to 2.37. Soil nutrients and fractal dimension showed highly significant or stronger negative correlations with SBD and sand and highly significant or stronger positive correlations with clay and silt. The construction of P. pyramidalis × C. korshinskii improved the soil texture better than other vegetation restoration types. Compared to the mobile sandy land, organic carbon (SOC), available phosphorus (AP), available potassium (AK), alkaline hydrolysis nitrogen (AN), total nitrogen (TN), total potassium (TK), clay, and silt increased by 161%, 238%, 139%, 30%, 125%, 69%, 208%, and 441% respectively. As mentioned above, P. pyramidalis × C. korshinskii is a suitable type of mixed vegetation restoration for the area. In addition, establishing vegetation with high nitrogen fixation rates in desert ecosystems tolerant to drought and aeolian conditions is beneficial in reversing the trend of desertification. This research will suggest vegetation building strategies for controlling desertification. [ABSTRACT FROM AUTHOR]

The three bipyridine‐proline chiral ligands (Z) with different structural units as highly active species were successfully introduced on Zn‐modified bimodal mesoporous silicas (BMMs). The representative heterogeneous catalysts (ZZnBMMs‐n) containing different molar ratios of Z/Zn (5, 20, 50, 100, 200%) were prepared, and their catalytic performances were evaluated in the asymmetric aldol reactions between p‐nitrobenzaldehyde and cyclohexanone, showing the satisfactory activities (yields) and good stereoselectivity (dr and ee). Meanwhile, their microstructural features and physicochemical properties were characterized by various methods. Particularly, the fractal evolution, the pair distance distribution function, and the Porod plots of the ZZnBMMs catalysts were demonstrated by SAXS analysis. The results revealed that the interfacial layer thickness and their mass fractal (Dm) value gradually increased with the enhanced molar ratios of Z/Zn, along with the decrease of pore size and densification of volume, suggesting the successful Z‐grafting into the mesoporous channels of Zn‐modified matrixes. The essential relationships between the fractal features and their catalytic performance (yield, dr and ee) were explored, showing the larger the Dm values, the better catalytic performance. Besides, the uniform distributions of Zn and S elements in ZZnBMMs catalysts and the formation of enamine‐imine intermediates during the asymmetric aldol reactions were confirmed. [ABSTRACT FROM AUTHOR]

In order to study the evolution and subsidence law of the overlying rock separation fracture under the mining of thick loose bed and thin bedrock, combined with the geological conditions of 1302 face of the first mining face of Shandong Guotun Coal Mine, the fractal characteristics of the overlying rock fracture network and subsidence in the mining process are studied by using the method of similar material simulation test and fractal. The research results show that: the evolution characteristics of overburden fractures have good self-similarity and fractal characteristics; as the working face advances, the fractal dimension of the overburden fracture network increases slowly and steadily during the early and mid-jumping periods. There are four layers in the whole mining process, and the location and size of the layers show a certain regularity; under the action of thick loose layer, the thin bedrock layer can still form a stable and strong bearing structure; the settlement of overburden in goaf and fractal dimension of fracture network show a nonlinear relation of approximately bifold line.

Accurate extraction of cropland distribution information using remote sensing technology is a key step in the monitoring, protection, and sustainable development of black soil. To obtain precise spatial distribution of cropland, an information extraction method is developed based on a fractal algorithm integrating temporal and spatial features. The method extracts multi-seasonal fractal features from the Landsat 8 OLI remote sensing data. Its efficiency is demonstrated using black soil in Lishu County, Northeast China. First, each pixel’s upper and lower fractal signals are calculated using a blanket covering method based on the Landsat 8 OLI remote sensing data in the spring, summer, and autumn seasons. The fractal characteristics of the cropland and other land-cover types are analyzed and compared. Second, the ninth lower fractal scale is selected as the feature scale to extract the spatial distribution of cropland in Lishu County. The cropland vector data, the European Space Agency (ESA) WorldCover data, and the statistical yearbook from the same period are used to assess accuracy. Finally, a comparative analysis of this study and existing products at different scales is carried out, and the point matching degree and area matching degree are evaluated. The results show that the point matching degree and the area matching degree of cropland extraction using the multi-seasonal fractal features are 90.66% and 96.21%, and 95.33% and 83.52%, respectively, which are highly consistent with the statistical data provided by the local government. The extracted accuracy of cropland is much better than that of existing products at different scales due to the contribution of the multi-seasonal fractal features. This method can be used to accurately extract cropland information to monitor changes in black soil, and it can be used to support the conservation and development of black soil in China.

The research on pore structure and heterogeneity of shale reservoirs has always been a hotspot in the study of unconventional reservoir characteristics. China is a country dominated by continental shale. Compared with marine shale, continental shale has lower maturity and stronger reservoir heterogeneity. In this study, Sha-4 shale in the Liaohe Western Depression was selected for low-temperature nitrogen adsorption, scanning electron microscopy and other experiments revealing the pore structure and fractal characteristics of continental low mature organic-rich shale. The fractal dimension was calculated by the FHH model and the effects of TOC and mineral composition on pore structure and fractal characteristics were discussed. The results show that the Sha-4 shale in the study area is mainly mesoporous and the main pore types are inorganic pores with relatively large pore diameters, such as intergranular pores and inter-crystalline pores. The pore morphology is very complex, mainly narrow slit and flat pore, and the pore is often filled with organic matter. The fractal dimensions D1 range from 2.58 to 2.87 and D2 range from 2.18 to 2.55, and the pore structure shows obvious dual fractal characteristics. The pore structure and fractal characteristics of shale are mainly affected by TOC and quartz due to the low degree of the thermal evolution of shale and their effects are different from those of marine shale reservoirs. The increase in TOC reduces the heterogeneity of the shale reservoir. In addition, mineral particles with strong weathering resistance and stability such as quartz can protect the pore structure of shale, improve the pore structure and reduce the reservoir heterogeneity. This study can provide support for the study of low maturity continental shale reservoir heterogeneity in the Sha-4 member of the Liaohe Western Depression.

Many of the previous investigations predicted wind speed by directly using wind speed data, which rarely considered physical characteristics of wind speed and was difficult to improve prediction accuracy further. Therefore, a novel self-adaptive wind speed prediction model considering atmospheric motion and fractal feature is developed in this paper. Lorenz-Stenflo (LS) equation is employed to describe the disturbances and chaos effect caused by atmospheric motion on wind speed. One-dimension LS motion series obtained by LS equation is adopted to improve the decomposition effect of wind speed by ensemble empirical mode decomposition (EEMD). The fractal feature of wind speed series is primitively adopted to determine the key parameter in LS equation. Then back propagation (BP) neural network model optimized by genetic algorithm (GA), as a fundamental prediction model, is used for prediction. Eight groups of wind speed series on different time scales from two wind farms are tested and evaluated. The proposed model effectively overcomes the disturbances of atmospheric motion and achieves promising prediction accuracy. Meanwhile, the criterion based on fractal feature ensures accurate selection of the key parameter in atmospheric motion equation according to different features of sampled wind data.

A fractal realizes the quantitative characterization of complex and disordered mining fracture networks, and it is of great significance to grasp the fractal characteristics of rock movement law to guide mine production. To prevent the water-conducting fracture (WF) under the gullies from conducting the surface water body, and to realize the purpose of safe production and surface water body protection. The evolution of overburden fissures in the working face with shallow buried gulley landform and thick bedrock conditions is studied. The development height of water-conducting fracture (DHWF) is theoretically analyzed. The evolution characteristics of overlying fissures with different mining heights were observed by similarity simulation, and the observation results were analyzed by fractal theory. The results show that the main factor that determines the height of WF is mining height. The working face is mined at different mining heights, and the corresponding indexes such as the height of the WF, the area of the caving zone and the fractal dimension are related to engineering phenomena. In particular, the appearance and disappearance of the separation space correspond to the fractal dimension fluctuation phase. The safe mining technology under a gully water body, which mainly reduces mining height, is adopted, and the fissures of the working face are not connected to the surface water body after mining.

Gearboxes are an important part of the mechanical drives element that provides the several applications like automotive industry, wind turbine industry and power plant industry, etc. The condition monitoring of the gearbox reduces its operational cost, maintenance cost and avoid hazardous losses. The features selected for the health status of the gearbox has important parameter to calculate classification accuracy. In the current study the intrinsic time-scale decomposition (ITD) and tunable Q-factor wavelet transform (TQWT) are used to diagnose the faults in the gear. The ITD method decomposed the input signal into the baseline signal with instantaneous parameters of signal and sequence of the proper rotation components (PRCs). The PRC of higher kurtosis value is the input signal for TQWT. The TQWT is a discrete wavelet transform and decomposed the vibration signals of the gearbox into sub-bands. The feature vector is calculated for each subband of the TQWT. The proposed approach is analyzed by the classification accuracy of the feature vector. The recommended method is evaluated using experimental data of 2009 PHM Data of gearbox under various health conditions. The SVM and KNN methods are investigated that the improved classification accuracy with ITD-TQWT model are 97.9% and 96.9% respectively. [ABSTRACT FROM AUTHOR]

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Heritage sites are vulnerable to damage due to social, anthropological and environmental factors. Major Earthquakes are followed by damage to cultural heritage buildings. The assessment of such building damage is a critical problem. Earth Observation data, owing to its property of being non-contact, cost effective, synoptic view and high repeatability, has a significant role to play in estimation of damage in the earthquake affected areas. Currently, several and varied types of remote sensing data have become available, and therefore, appropriate methods for rapid assessment and analysis of the data need to be developed. Rapid damage assessment is critical to minimize loss in terms of life and property. In case of cultural monuments, rapid assessment can minimize damage and help in the conservation of monument. This research focuses on evolving a robust method for rapid identification and extraction of damaged heritage building structures, especially those affected by disasters such as earthquakes. In this study, we propose to examine the utility of advance texture algorithms such as Gabor, fractal and semi-variogram for rapid damage detection in heritage building structures. The methodology attempts to automatically highlight damaged portions of the structure through a knowledge driven rule set. The technique was able to extract the damaged area from the heritage building structure with the use of high-resolution space borne data. It is observed that feature extraction algorithms based on fractal and variogram provide better results than the Gabor based textures and are very useful in the case of high-resolution satellite imagery. Both the methods are able to extract damaged features in both shadowed and non-shadowed regions of the image. Hence the problems posed by shadowed dead grounds on EO data can be effectively resolved. However, it is also observed that the advance texture feature extraction algorithms are useful only in case of high-spatial resolution dataset and has limited use for rapid damage assessment from medium and low resolution datasets. [ABSTRACT FROM AUTHOR]

Automatic detection of fabric defects is an important process in the textile industry, which is required to locate and classify microdefects from a large fabric image. We propose a learning-based system for automatic detection of microfabric defects. A segmentation algorithm based on fractal and gray features is applied to extract microdefect regions. Gabor fractal network is designed to further improve identification ability of this approach. The proposed network achieves superior performance in terms of detection accuracy with a much smaller model size. The best testing accuracy rates on dark line, hole, broken yarn, and dirt are 96.9%, 98.0%, 92.9%, and 98.8%, respectively. Experimental results demonstrate the effectiveness of the proposed scheme in defect detection for microfabrics. The proposed system has great potential for automatic detection of microfabric defects. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing 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.)

Abstract To investigate the adsorption capacity and fractal features of coal-measure shales and understand the influence of shale properties on the adsorption capacity and fractal features, a series of experiments were conducted on fifteen shale samples from Shanxi-Taiyuan Formations in the Yushe-Wuxiang Block, South-Central Qinshui Basin. The results indicate that organic and clay minerals are the two adsorption carriers for coal-measure shales, Langmuir volume (V L) of shales increases as the total organic matter (TOC) content or clay minerals content increases. Additionally, there is a negative correlation between V L and quartz content. As vitrinite reflectance (R o %) increases, V L has an evolutionary path of first increasing and then decreasing, the maximum value is reached at near R o = 2.1%. Furthermore, V L increases as specific surface area (SSA) increases or average pore diameter (APD) decreases. The coal-measure shales exhibit double fractal features. The fractal dimension of pore surface (D 1) and fractal dimension of pore structure (D 2) vary from 2.4899 to 2.6272 and 2.7318–2.840, respectively. The fractal dimensions show an increasing trend as SSA increases. As pore volume increases, D 1 presents a slight increasing trend while D 2 shows a decreasing trend. And fractal dimensions increase as APD decreases. The relationships of TOC with D 1 and D 2 are opposite. Clay minerals are the determining factor of the fractal dimensions as the fractal dimensions (D 1 and D 2) show an increasing trend as clay minerals content increases. An increase in quartz content or organic matter maturity will greatly reduce the heterogeneity of shales. As for non-clay minerals, the fractal dimensions (D 1 and D 2) show an increasing trend as pyrite content increases, while D 1 increases and D 2 decreases as carbonate mineral content increases. Regarding the composition of clay minerals, D 1 increases as the mixed layers of illite/smectite (I/S) and illite contents increase or kaolinite and chlorite contents increase, while D 2 is opposite. Shales with higher fractal dimensions develop stronger adsorption capacity while shales with higher D 1 and lower D 2 develop lower Langmuir pressure (P L). Highlights • TOC shows positive correlation with D 2 but negative correlation with D 1. • Clay minerals is positively correlated with D 1 and D 2 due to its complex structure. • The lower quartz content and OM maturity in shales, the greater D 1 and D 2 values. • V L increases as D 1 and D 2 increase, P L increases as D 1 increases or D 2 decreases. [ABSTRACT FROM AUTHOR]

Abstract Impervious surfaces (IS) constitute a quantifiable metric for urbanization and ecological environmental assessment. This study estimated the IS in the subtropical coastal area of Xiamen, southeastern China, from TM/OLI images obtained in 1994, 2000, 2004, 2010, and 2015. Two-dimension box-counting and two-dimension multifractal box-counting method were employed to quantitatively characterize the fractal and multifractal features of the spatial patterns of the IS. Results suggest that the spatial patterns observed during the study period are typical fractal structures with scale invariance, and the fractal dimension reveals the spatio-temporal complexity. Increasing the pixel binarization threshold decreases the spatial complexity of the IS pattern. The increasing dimension values over time show that the IS patterns become more complex and the spatial distribution becomes more clustered from 1994 to 2015. The two-dimension multifractal approach can transform an irregular IS pattern into a compact form and amplify small differences between different data series. The results revealed multifractality in the five study years, which varied throughout the study period, but the probability distribution shows a slightly decreasing trend. The probability of a given pixel having a high IS-fraction is consistently high in the study area, as indicated by the positive ratio between the regions where the probability measure appears most concentrated and most sparse. Highlights • Two-dimensional fractal nature is found in impervious surface spatial patterns. • The box-counting dimensions describe how the fraction values fill in the study area. • Two-dimensional multifractality is found in impervious surface spatial patterns. • Multifractal parameters show how heterogeneity of impervious surface patterns vary. [ABSTRACT FROM AUTHOR]

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Tree precise classification and identification of forest species is a core issue of forestry resource monitoring and ecological effect assessment. In this paper, an independent tree species classification method based on fractal features of terrestrial laser point cloud is proposed. Firstly, the terrestrial laser point cloud data of an independent tree is preprocessed to obtain terrestrial point clouds of independent tree canopy. Secondly, the multi-scale box-counting dimension calculation algorithm of independent tree canopy dense terrestrial laser point cloud is proposed. Furthermore, a robust box-counting algorithm is proposed to improve the stability and accuracy of fractal dimension expression of independent tree point cloud, which implementing gross error elimination based on Random Sample Consensus. Finally, the fractal dimension of a dense terrestrial laser point cloud of independent trees is used to classify different types of independent tree species. Experiments on nine independent trees of three types show that the fractal dimension can be stabilized under large density variations, proving that the fractal features of terrestrial laser point cloud can stably express tree species characteristics, and can be used for accurate classification and recognition of forest species.

A new nano-soil stabilizer (N-MBER, Nanometer Material Becoming Earth into Rock) material was developed in this research by using the high activity and ultrafine properties of nano-SiO2 (NS), which were able to improve the properties of cement-based soil stabilizer and had broad application prospects. The results showed that (1) the strength of N-MBER obeyed a compound function relation with curing period and additive amount of NS. The relationship between strength and curing period obeyed an exponential function when the additive amount was constant. The strength and additive amount were a power function when the curing period was fixed. The compressive strength of N-MBER increased by more than 15% compared with MBER at day 28 of the curing period, and 50% compared with grade 32.5 cement. (2) The pozzolanic catalytic activity of NS significantly increased the amount of calcium silicate hydrate gel (C−S−H) in the N-MBER colloid. NS was also able to make the distribution of the network structure of colloidal space more uniform and improved the fractal dimension of particles by 0.05. The above results provide theoretical data for exploring the mechanism of soil stabilizer strength growth and for promoting the application of solid waste utilization.

The fractal is an important feature of many real complex networks. According to the definition of the Hausdorff dimension, the minimum number of boxes that can be used to cover complex networks is an important factor for revealing the fractal feature of self-similar complex networks. The calculation of the minimum number of boxes is an NP (Non-deterministic Polynomial)-hard problem. In this paper, a heuristic algorithm, named the Max-Min ant colony algorithm, is introduced to approximate the minimum number of boxes. The pheromone-updating rules and heuristic rules are redefined to improve the performance of the algorithm. The experimental results show that, for Escherichia coli networks, the number of boxes was significantly decreased compared to the box-covering greedy algorithm, especially when the box size is small. [ABSTRACT FROM AUTHOR]

The initial particle size distributions (PSDs) and cyclic loading effects for the confined comminution tests are studied by using discrete element method (DEM). Three typical PSDs, i.e. the uniform, bimodal and fractal, respectively, are used to explore the general correlations from microscopic quantities to macroscopic quantities during the loading-unloading-reloading procedure. For the initial bimodal packing, it cannot easily generate an ultimate fractal packing. And for the initial uniform and fractal packings, the ultimate fractal dimension of PSD would gradually increase during the reloading procedure. Moreover, the coordination distribution of particles (CNP) is insensitive with the initial PSDs and cyclic loadings. Furthermore, the fractal analysis of the network of force chains is also studied by the box method to evaluate the fractal features of force chains from the general, strong and weak perspectives. Additionally, a new descriptor for interpreting the relationship between the force chains and the composed particles ( C FC ) is proposed to evaluate the packing geometrical topologies and force chains. It can be used to evaluate the inter-particle structure feature of the granular assemblies. It is interesting to find that C FC is gradually increased with the increasing loading stress, and reaches a peak value in the unloading stage for the same stress state and decreases with the increasing number intensity of force chains. [ABSTRACT FROM AUTHOR]

Radar Target Recognition (RTR) is one of the most important needs of modern and future airborne surveillance radars, and it is still one of the key technologies of radar. The majority of present algorithms are based on wide-band radar signal, which not only needs high performance radar system and high target Signal-to-Noise Ratio (SNR), but also is sensitive to angle between radar and target. Low-Resolution Airborne Surveillance Radar (LRASR) in downward-looking mode, slow flying aircraft and ground moving truck have similar Doppler velocity and Radar Cross Section (RCS), leading to the problem that LRASR air/ground moving targets can not be distinguished, which also disturbs detection, tracking, and classification of low altitude slow flying aircraft to solve these issues, an algorithm based on narrowband fractal feature and phase modulation feature is presented for LRASR air/ground moving targets classification. Real measured data is applied to verify the algorithm, the classification results validate the proposed method, helicopters and truck can be well classified, the average discrimination rate is more than 89% when SNR ≥ 15 dB.

Target classification is particularly important in modern and future airborne radar. Nowadays, most investigations of radar target classification are based on wideband radar signals, which have higher requirements for SNR and radar systems, and are sensitive to the angles. Modern airborne radars require narrowband tracking and target classification; hence, an algorithm based on the narrowband fractal features and the amplitude modulation of a two-dimensional distribution is presented. Experimental data and Support Vector Machine (SVM) are used to verify the algorithm, and the classification results validate the proposed method, which show that jet aircrafts, propeller aircrafts, and helicopters can be classified with an average discrimination rate greater than 92%.

Copyright of Journal of Central China Normal University is the property of Huazhong Normal 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.)

This paper proposes a novel patient-specific real-time automatic epileptic seizure onset detection, using both scalp and intracranial electroencephalogram (EEG). The proposed technique obtains harmonic multiresolution and self-similarity-based fractal features from EEG for robust seizure onset detection. A fast wavelet decomposition method, known as harmonic wavelet packet transform (HWPT), is computed based on Fourier transform to achieve higher frequency resolutions without recursive calculations. Similarly, fractal dimension (FD) estimates are obtained to capture self-similar repetitive patterns in the EEG signal. Both FD and HWPT energy features across all EEG channels at each epoch are organized following the spatial information due to electrode placement on the skull. The final feature vector combines feature configurations of each epoch within the specified moving window to reflect the temporal information of EEG. Finally, relevance vector machine is used to classify the feature vectors due to its efficiency in classifying sparse, yet high-dimensional data sets. The algorithm is evaluated using two publicly available long-term scalp EEG (data set A) and short-term intracranial and scalp EEG (data set B) databases. The proposed algorithm is effective in seizure onset detection with 96% sensitivity, 0.1 per hour median false detection rate, and 1.89 s average detection latency, respectively. Results obtained from analyzing the short-term data offer 99.8% classification accuracy. These results demonstrate that the proposed method is effective with both short- and long-term EEG signal analyzes recorded with either scalp or intracranial modes, respectively. Finally, the use of less computationally intensive feature extraction techniques enables faster seizure onset detection when compared with similar techniques in the literature, indicating potential usage in real-time applications. [ABSTRACT FROM PUBLISHER]

Evaluation of tight sandstone reservoir, including space types, storage capacity, and heterogeneity, provides a basis for the selection of favorable areas for tight gas and oil. Therefore, a variety of research methods, such as rate-controlled mercury injection, fractal theory, and observation of thin sections and SEM (scanning electron microscope) images, were integrated to explore these parameters. With the decrease of porosity and permeability, tight sandstones can be classified into three types: pore-dominated, pore-throat, and throat-dominated. The reservoir spaces of the three types of tight sandstones gradually evolve from micro-to nano-scale. The micro-scale spaces in pore-dominated and pore-throat type samples are primarily made up of intergranular and mixed pores and are characterized by a two-segment fractal feature, while the throat-dominated samples are mainly composed of intergranular pores with a one-segment fractal feature. The nano-scale reservoir spaces in the three types of tight sandstones also display similar two- and one-segment fractal characteristics, and are mainly composed of intragranular honeycombed dissolution pores, authigenic mineral intercrystalline pores, and throats in pore-dominated and pore-throat tight sandstones. However, the authigenic mineral intercrystalline pores constitute the main nano-scale spaces in throat-dominated tight sandstones. With the tight sandstones from pore-dominated through pore-throat to throat-dominated types, the fractal dimensions of micro-scale spaces increase gradually, but in nano-scale spaces the fractal dimensions decrease, which indicating that the heterogeneity of micro-scale spaces is gradually enhanced whereas that of the nano-scale spaces is gradually weakened. Because of differences in reservoir space types and heterogeneity, the enrichment and distribution of tight gas and oil changes with the distance between the reservoir layers and the source rocks. The tight reservoirs dominated by nano-scale spaces are also incorporated into the exploration and development goals in areas adjacent to source rocks. However, in areas located far from source rocks, the tight reservoirs dominated by micro-scale spaces should be the preferred targets for tight gas and oil. [ABSTRACT FROM AUTHOR]

Microseismic (MS) technology has been widely adopted for monitoring coal and rock dynamic disasters. Insights into MS wave characteristics contribute to the accurate prediction of these disasters. In this study, MS wave characteristics were analysed from three aspects: the signal spectra, wavelet packet energy and fractal features. It is shown that prior to the rock burst, the MS wave main frequency decreased following a power law, the amplitude linearly increased, the wavelet packet energy tended to become concentrated on the low frequency bands, and the correlation dimension decreased. When the rock burst occurred, the MS wave main frequency, wavelet packet energy and correlation dimension declined to their lowest levels. Meanwhile, the amplitude rose to a maximum. Therefore, the MS wave characteristics in this study were found to effectively identify and extract precursor information of value for predicting rock dynamic disasters. [ABSTRACT FROM PUBLISHER]

Fractal represents a special feature of nature and functional objects. However, fractal based computing can be applied to many research domains because of its fixed property resisted deformation, variable parameters and many unpredictable changes. Theoretical research and practical application of fractal based computing have been hotspots for 30 years and will be continued. There are many pending issues awaiting solutions in this domain, thus this thematic issue containing 14 papers publishes the state-of-the-art developments in theorem and application of fractal based computing, including mathematical analysis and novel engineering applications. The topics contain fractal and multifractal features in application and solution of nonlinear odes and equation. [ABSTRACT FROM AUTHOR]

There exist some problems when the fractal feature method is applied to identify thruster faults for autonomous underwater vehicles (AUVs). Sometimes it could not identify the thruster fault, or the identification error is large, even the identification results are not consistent for the repeated experiments. The paper analyzes the reasons resulting in these above problems according to the experiments on AUV prototype with thruster faults. On the basis of these analyses, in order to overcome the above deficiency, an improved fractal feature integrated with wavelet decomposition identification method is proposed for AUV with thruster fault. Different from the fractal feature method where the signal extraction and fault identification are completed in the time domain, the paper makes use of the time-domain and frequent-domain information to identify thruster faults. In the paper, the thruster fault could be mapped multisource and described redundantly by the fault feature matrix constructed based on the time-domain and frequent-domain information. In the process of identification, different from the fractal feature method where the fault is identified based on fault identification model, the fault sample bank is built at first in the paper, and then pattern recognition is achieved by calculating the relative coefficients between the constructed fault feature matrix and the elements in the fault sample bank. Finally, the online pool experiments are performed on an AUV prototype, and the effectiveness of the proposed method is demonstrated in comparison with the fractal feature method. [ABSTRACT FROM AUTHOR]

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Copyright of Jianzhu Cailiao Xuebao: Journal of Building Materials is the property of Journal of Building Materials 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.)