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Academic literature on the topic 'Improved Accumulation Area Ratio method'
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Journal articles on the topic "Improved Accumulation Area Ratio method"
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Yang, Shengying, Huibin Qin, Xiaolin Liang, and Thomas Gulliver. "An Improved Unauthorized Unmanned Aerial Vehicle Detection Algorithm Using Radiofrequency-Based Statistical Fingerprint Analysis." Sensors 19, no. 2 (2019): 274. http://dx.doi.org/10.3390/s19020274.
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Unmanned aerial vehicles (UAVs) are now readily available worldwide and users can easily fly them remotely using smart controllers. This has created the problem of keeping unauthorized UAVs away from private or sensitive areas where they can be a personal or public threat. This paper proposes an improved radio frequency (RF)-based method to detect UAVs. The clutter (interference) is eliminated using a background filtering method. Then singular value decomposition (SVD) and average filtering are used to reduce the noise and improve the signal to noise ratio (SNR). Spectrum accumulation (SA) and statistical fingerprint analysis (SFA) are employed to provide two frequency estimates. These estimates are used to determine if a UAV is present in the detection environment. The data size is reduced using a region of interest (ROI), and this improves the system efficiency and improves azimuth estimation accuracy. Detection results are obtained using real UAV RF signals obtained experimentally which show that the proposed method is more effective than other well-known detection algorithms. The recognition rate with this method is close to 100% within a distance of 2.4 km and greater than 90% within a distance of 3 km. Further, multiple UAVs can be detected accurately using the proposed method.
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Ma, Qinghua, Lin Chen, Manyi Du, Yongan Zhang, and Yaoxiang Zhang. "Localized and Moderate Phosphorus Application Improves Plant Growth and Phosphorus Accumulation in Rosa multiflora Thunb. ex Murr. via Efficient Root System Development." Forests 11, no. 5 (2020): 570. http://dx.doi.org/10.3390/f11050570.
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Roots have high plasticity with the ability to adapt to heterogeneous nutrient distribution, but little is known about the effects of phosphorus (P) supply methods and levels on Rosa multiflora Thunb. ex Murr. root growth and nutrient accumulation. A pot study was conducted with two P supply methods (mixed and localized application) and three levels (P-deficient, P-moderate and P-adequate). The results showed that with localized application, P-deficient and P-moderate treatments significantly improved total root length, total surface area, total length of fine roots, shoot DW and total P accumulation in Rosa multiflora compared with their respective mixed application at 45 days after being transplanted (DAT) and 92 DAT; for P-adequate supply, the same trends were observed at 45 DAT, but not at 92 DAT. At 92 DAT, with localized application, when P levels increased from P-deficient to P-moderate, total P accumulation increased by 43.3%; but when P levels increased from P-moderate to P-adequate, no effect was observed. Furthermore, higher P accumulation in leaves was observed in localized P-moderate condition; decreased P uptake per root dry weight and greater root/shoot ratio were observed in localized P-adequate at 92 DAT. Total P accumulation was positively correlated with total root length and root surface area (R2: 0.68~0.94). There was a significant interaction effect among treatment days, P supply methods and levels (p ≤ 0.05) on shoot DW, root DW, root/shoot ratio and total P accumulation. These findings indicated that localized and moderate P supply appear efficient for improving R. multiflora growth and P accumulation via efficient root system development.
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Chatterjee, Kaushik, C. S. Singh, A. K. Singh, Ashok Kr Singh, and S. K. Singh. "Performance of wheat cultivars at varying fertility levels under system of wheat intensification and conventional method of wheat production system." Journal of Applied and Natural Science 8, no. 3 (2016): 1427–33. http://dx.doi.org/10.31018/jans.v8i3.977.
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A field experiment was conducted during rabi season of 2009-10 at Ranchi, Jharkhand to evaluate the performance of wheat cultivars at varying fertility levels under system of wheat intensification and conventional method of cultivation. The morpho-physiological analysis of growth and yield in wheat revealed that system of wheatintensification manifested higher total tillers m-2, leaf area index, dry matter accumulation, crop growth rate, number of spikes m-2, grains per spike and 1000-grain weight resulting in higher grain and straw yield over conventional method of cultivation. The net return and benefit: cost ratio as well as the nutrient uptake of nitrogen, phosphorus and potash was also recorded significantly higher under system of wheat intensification. Higher fertility level of 120 kg N ha-1, 60 kg P2O5 ha-1 and 40 kg K2O ha-1 also significantly improved the plant height, total tillers m-2, leaf area index, dry matter accumulation, crop growth rate, number of spikes m-2, grains per spike, 1000-grain weight, grain yield, straw yield, net return, benefit: cost ratio and nutrient uptake of nitrogen, phosphorus and potash. Among the wheat cultivars, K 9107 manifested significant improvement in growth attributes at all the growth stages resulting in significantly higher yield attributes, grain yield, straw yield, net return, benefit: cost ratio and nutrient uptake of nitrogen, phosphorus and potash than Birsa Gehu 3, HUW 468 and K 0307. Thus it can be concluded that the wheat variety K 9107 fertilized with 120 kg N ha-1, 60 kg P2O5 ha-1 and 40 kg K2O ha-1 under System of Wheat Intensification may able to boost up the wheat productivity under irrigated ecosystem of Chhotanagpur plateau region, India.
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He, Z. H., J. Parajka, F. Q. Tian, and G. Blöschl. "Estimating degree day factors from MODIS for snowmelt runoff modeling." Hydrology and Earth System Sciences Discussions 11, no. 7 (2014): 8697–735. http://dx.doi.org/10.5194/hessd-11-8697-2014.
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Abstract. Degree-day factors are widely used to estimate snowmelt runoff in operational hydrological models. Usually, they are calibrated on observed runoff, and sometimes on satellite snow cover data. In this paper, we propose a new method for estimating the snowmelt degree-day factor (DDFS) directly from MODIS snow covered area (SCA) and ground based snow depth data without calibration. Subcatchment snow volume is estimated by combining SCA and snow depths. Snow density is estimated as the ratio of observed precipitation and changes in the snow volume for days with snow accumulation. Finally, DDFS values are estimated as the ratio of changes in the snow water equivalent and degree-day temperatures for days with snow melt. We compare simulations of basin runoff and snow cover patterns using spatially variable DDFS estimated from snow data with those using spatially uniform DDFS calibrated on runoff. The runoff performances using estimated DDFS are slightly improved, and the simulated snow cover patterns are significantly more plausible. The new method may help reduce some of the runoff model parameter uncertainty by reducing the total number of calibration parameters.
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He, Z. H., J. Parajka, F. Q. Tian, and G. Blöschl. "Estimating degree-day factors from MODIS for snowmelt runoff modeling." Hydrology and Earth System Sciences 18, no. 12 (2014): 4773–89. http://dx.doi.org/10.5194/hess-18-4773-2014.
Full textAbstract:
Abstract. Degree-day factors are widely used to estimate snowmelt runoff in operational hydrological models. Usually, they are calibrated on observed runoff, and sometimes on satellite snow cover data. In this paper, we propose a new method for estimating the snowmelt degree-day factor (DDFS) directly from MODIS snow covered area (SCA) and ground-based snow depth data without calibration. Subcatchment snow volume is estimated by combining SCA and snow depths. Snow density is estimated to be the ratio between observed precipitation and changes in the snow volume for days with snow accumulation. Finally, DDFS values are estimated to be the ratio between changes in the snow water equivalent and difference between the daily temperature and the melt threshold value for days with snow melt. We compare simulations of basin runoff and snow cover patterns using spatially variable DDFS estimated from snow data with those using spatially uniform DDFS calibrated on runoff. The runoff performances using estimated DDFS are slightly improved, and the simulated snow cover patterns are significantly more plausible. The new method may help reduce some of the runoff model parameter uncertainty by reducing the total number of calibration parameters. This method is applied to the Lienz catchment in East Tyrol, Austria, which covers an area of 1198 km2. Approximately 70% of the basin is covered by snow in the early spring season.
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Zhu, Zijuan, Zengxiang Zhang, Lijun Zuo, et al. "Study on the Classification and Change Detection Methods of Drylands in Arid and Semi-Arid Regions." Remote Sensing 14, no. 5 (2022): 1256. http://dx.doi.org/10.3390/rs14051256.
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The aim of this study was to clarify the distribution of irrigated drylands in arid and semi-arid areas, where complex terrain, diverse crops and staggered cultivated lands exist. This paper studied the classification methods of irrigated drylands based on temperature, precipitation, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) from Landsat data in the one-harvest area of the northern Loess Plateau of China by using the Google Earth Engine (GEE) platform. An extraction method was proposed for irrigated drylands in arid and semi-arid regions of northwest China. In addition, the change types of irrigated and rainfed drylands in the two periods were classified, and a method was also put forward to directly classify the change types by using the image differences between the two periods combined with the classification results of each period. It was found that combining the ratio of NDVI and NDWI with the accumulated values of temperature and precipitation of the 30 days before imaging could effectively improve the classification accuracy. Moreover, directly classifying the gaps of remote sensing factors in the time dimension before combining spatial clustering information could yield a more accurate type of change, because the accumulation of errors in the change maps obtained from the overlay analysis of distribution maps of the two periods could be avoided. The accuracy of classification could be improved by introducing the dynamic information of time dimension into the classification of historical periods. This study complements the extraction method for this type of irrigated dryland, and the classification results can improve the accuracy of existing products in terms of spatial resolution, which can fill the shortage of detailed distribution data for irrigated and rainfed drylands in this region.
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Wang, Zhi, Jiajia Zhou, Linjian Song, and Long Li. "Experimental Study of Low Cycle Fatigue Properties for Epoxy Resins with Dibutyl Phthalate (Dbp)." Archives of Civil Engineering 64, no. 2 (2018): 147–59. http://dx.doi.org/10.2478/ace-2018-0021.
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AbstractIn order to improve the toughness of traditional epoxy resin, dibutyl phthalate (DBP) was introduced into the epoxy resin. The static mechanical performance of plasticized and unplasticized epoxy resin was evaluated. The test results showed that the DBP modified epoxy resin can obtain a higher toughness than conventional epoxy resin, but the elastic modulus and the tensile strength were slightly reduced. The low cycle fatigue test results indicated that the stress ratio and the stress level were two critical factors of fatigue life, which was increased with the growth of stress ratio. It was also found that the fatigue life of plasticized specimen was much less than that of the unplasticized specimen because of the plastic deformation. A logarithmic linear relationship was then established to predict the fatigue life for plasticized epoxy resin. The strain energy density was also applied to demonstrate the accumulation of energy loss. In addition, the fatigue toughness can be obtained by the hysteresis loop area method.
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Tawde, Sayli Atul, Anil V. Kulkarni, and Govindasamy Bala. "An estimate of glacier mass balance for the Chandra basin, western Himalaya, for the period 1984–2012." Annals of Glaciology 58, no. 75pt2 (2017): 99–109. http://dx.doi.org/10.1017/aog.2017.18.
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ABSTRACTAn improved understanding of fresh water stored in the Himalaya is crucial for water resource management in South Asia and can be inferred from glacier mass-balance estimates. However, field investigations in the rugged Himalaya are limited to a few individual glaciers and short duration. Therefore, we have recently developed an approach that combines satellite-derived snowlines, a temperature-index melt model and the accumulation-area ratio method to estimate annual mass balance of glaciers at basin scale and for a long period. In this investigation, the mass balance of 146 glaciers in the Chandra basin, western Himalaya, is estimated from 1984 to 2012. We estimate the trend in equilibrium line altitude of the basin as +113 m decade−1and the mean mass balance as −0.61 ± 0.46 m w.e. a−1. Our basin-wide mass-balance estimates are in agreement with the geodetic method during 1999–2012. Sensitivity analysis suggests that a 20% increase in precipitation can offset changes in mass balance for a 1 °C temperature rise. A water loss of 18% of the total basin volume is estimated, and 67% for small and low-altitude glaciers during 1984–2012, indicating a looming water scarcity crisis for villages in this valley.
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Sun, Yongshuai, Xinyan Zhong, Jianguo Lv, and Guihe Wang. "Experimental Study on Silt Soil Improved by Microbial Solidification with the Use of Lignin." Microorganisms 11, no. 2 (2023): 281. http://dx.doi.org/10.3390/microorganisms11020281.
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At present, in the field of geotechnical engineering and agricultural production, with increasingly serious pollution an environmentally friendly and efficient means is urgently needed to improve the soil mass. This paper mainly studied the microbial induced calcium carbonate precipitation (MICP) technology and the combined effect of MICP technology and lignin on the improvement of silt in the Beijing area. Through unconfined compressive strength and dynamic triaxial test methods, samples improved by microorganisms were studied to obtain the optimal values of cement concentration and lignin under these two test schemes. The results show that after the incubation time of Sporosarcina pasteurii reached 24 h, the OD600 value was 1.7–2.0 and the activity value (U) was 930–1000 mM ms/min. In the unconfined static pressure strength test, after MICP treatment the optimal concentration of cementitious solution for constant temperature and humidity samples and constant-temperature immersion samples was 1.25 mol/L. The compressive strength of the constant temperature and humidity sample was 1.73 MPa, and the compressive strength of the constant-temperature immersion sample was 3.62 Mpa. At the concentration of 1.25 mol/L of cement solution, MICP technology combined with lignin could improve the constant temperature and humidity silt sample. The optimal addition ratio of lignin was 4%, and its compressive strength was 1.9 MPa. The optimal lignin addition ratio of the sample soaked at a constant temperature was 3%, and the compressive strength was 4.84 MPa. In the dynamic triaxial multi-stage cyclic load test, the optimal concentration of cementation solution for the constant temperature and humidity sample after MICP treatment was 1.0 mol/L, and the failure was mainly inclined cracks. However, in the condition of joint improvement of MICP and lignin, the sample mainly had a drum-shaped deformation, the optimal lignin addition ratio was 4%, and the maximum axial load that the sample could bear was 306.08 N. When the axial dynamic load reached 300 N, the strain accumulation of the 4% group was only 2.3 mm. In this paper, lignin, an ecofriendly material, was introduced on the basis of MICP technology. According to the failure shape and relevant results of the sample, the addition of lignin was beneficial for the improvement of the compressive strength of the sample.
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Yao, Lili, Qing Wang, Jinbo Yang, et al. "UAV-Borne Dual-Band Sensor Method for Monitoring Physiological Crop Status." Sensors 19, no. 4 (2019): 816. http://dx.doi.org/10.3390/s19040816.
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Unmanned aerial vehicles (UAVs) equipped with dual-band crop-growth sensors can achieve high-throughput acquisition of crop-growth information. However, the downwash airflow field of the UAV disturbs the crop canopy during sensor measurements. To resolve this issue, we used computational fluid dynamics (CFD), numerical simulation, and three-dimensional airflow field testers to study the UAV-borne multispectral-sensor method for monitoring crop growth. The results show that when the flying height of the UAV is 1 m from the crop canopy, the generated airflow field on the surface of the crop canopy is elliptical, with a long semiaxis length of about 0.45 m and a short semiaxis of about 0.4 m. The flow-field distribution results, combined with the sensor’s field of view, indicated that the support length of the UAV-borne multispectral sensor should be 0.6 m. Wheat test results showed that the ratio vegetation index (RVI) output of the UAV-borne spectral sensor had a linear fit coefficient of determination (R2) of 0.81, and a root mean square error (RMSE) of 0.38 compared with the ASD Fieldspec2 spectrometer. Our method improves the accuracy and stability of measurement results of the UAV-borne dual-band crop-growth sensor. Rice test results showed that the RVI value measured by the UAV-borne multispectral sensor had good linearity with leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW); R2 was 0.62, 0.76, and 0.60, and RMSE was 2.28, 1.03, and 10.73, respectively. Our monitoring method could be well-applied to UAV-borne dual-band crop growth sensors.