A study of accent and identity in the music of Oasis by Maya Denton

“…In particular, the study considers the accent and singing styles present in the music of Manchester band Oasis. Previous studies have highlighted the prominence of American accent features used by artists like The Beatles, to emulate the success of popular American singers; whereas artists associated with the indie genre often purposely subvert these expectations by embracing their own ‘real’ accents in their singing. …”
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Monitoring Oasis Cotton Fields Expansion in Arid Zones Using the Google Earth Engine: A Case Study in the Ogan-Kucha River Oasis, Xinjiang, China by Lijing Han, Jianli Ding, Jinjie Wang, Junyong Zhang, Boqiang Xie, Jianping Hao

“…After the cotton fields were mulched, there was a significant increase in spectral reflectance in the visible, red-edge and near-infrared bands, and a decrease in the short-wave infrared band. …”
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Overview Kepuasan Pelanggan: Studi Kasus Pelayanan Rijstaffel di Restoran Oasis by Maria Pia Adiati, Agung Gita Subakti

“…The objective of this research is to analyze the level of consumer satisfaction and service quality in rijstaffel service at Oasis Restaurant. Research used qualitative method with library research by analyzing the questionnaire distributed by Oasis on Mei 2013 with 21 respondents. …”
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Soil Salinity Inversion Model of Oasis in Arid Area Based on UAV Multispectral Remote Sensing by Wenju Zhao, Chun Zhou, Changquan Zhou, Hong Ma, Zhijun Wang

“…In the arid area of Northwest China, oasis saline-alkali land threatens the development of agriculture and food security. …”
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Assessment of the Declining Degree of Farmland Shelterbelts in a Desert Oasis Based on LiDAR and Hyperspectral Imagery by Chengwei Luo, Yuli Yang, Zhiming Xin, Junran Li, Xiaoxiao Jia, Guangpeng Fan, Junying Zhu, Jindui Song, Zhou Wang, Huijie Xiao

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Mapping and Modelling Spatial Variation in Soil Salinity in the Al Hassa Oasis Based on Remote Sensing Indicators and Regression Techniques by Amal Allbed, Lalit Kumar, Priyakant Sinha

“…The aim of this study was to develop statistical regression models based on remotely sensed indicators to predict and map spatial variation in soil salinity in the Al Hassa oasis. Different spectral indices were calculated from original bands of IKONOS images. …”
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UAV hyperspectral analysis of secondary salinization in arid oasis cotton fields: effects of FOD feature selection and SOA-RF by Zeyuan Wang, Zeyuan Wang, Zeyuan Wang, Jianli Ding, Jianli Ding, Jianli Ding, Jiao Tan, Jiao Tan, Jiao Tan, Junhao Liu, Junhao Liu, Junhao Liu, Tingting Zhang, Weijian Cai, Weijian Cai, Weijian Cai, Shanshan Meng, Shanshan Meng, Shanshan Meng

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Investigation of the spatial and temporal variation of soil salinity using Google Earth Engine: a case study at Werigan–Kuqa Oasis, West China by Shilong Ma, Baozhong He, Boqiang Xie, Xiangyu Ge, Lijing Han

“…In this experiment, after Spearman correlation analysis of soil Electrical Conductivity (EC) with environmental variables, we found that the near-infrared band in the original band, the DEM in the topographic factor, the vegetation index based on remote sensing, and the salinity index soil EC had a strong correlation. …”
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Automatic Detection of Regional Snow Avalanches with Scattering and Interference of C-band SAR Data by Jinming Yang, Chengzhi Li, Lanhai Li, Jianli Ding, Run Zhang, Tao Han, Yang Liu

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Simulation of snowbands in the Baltic Sea area with the coupled atmosphere-ocean-ice model COSMO-CLM/NEMO by Trang Van Pham, Jennifer Brauch, Barbara Früh, Bodo Ahrens

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Estimation of the Multielement Content in Rocks Based on a Combination of Visible–Near-Infrared Reflectance Spectroscopy and Band Index Analysis by Guo Jiang, Xi Chen, Jinlin Wang, Shanshan Wang, Shuguang Zhou, Yong Bai, Tao Liao, He Yang, Kai Ma, Xianglian Fan

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Improving the Accuracy of Soil Organic Carbon Estimation: CWT-Random Frog-XGBoost as a Prerequisite Technique for In Situ Hyperspectral Analysis by Jixiang Yang, Xinguo Li, Xiaofei Ma

“…The CWT-XGBoost model based on random frog showed the best results, with R² = 0.86, RMSE = 2.44, and RPD = 2.78. The feature bands accounted for only 0.57% of the Vis-NIR bands, and the most important sensitive bands were distributed at 755–1195 nm, 1602 nm, 1673 nm, and 2213 nm. …”
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Possibility of Zhuhai-1 Hyperspectral Imagery for Monitoring Salinized Soil Moisture Content Using Fractional Order Differentially Optimized Spectral Indices by Yasenjiang Kahaer, Nigara Tashpolat, Qingdong Shi, Suhong Liu

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Early Monitoring of Cotton Verticillium Wilt by Leaf Multiple “Symptom” Characteristics by Mi Yang, Changping Huang, Xiaoyan Kang, Shizhe Qin, Lulu Ma, Jin Wang, Xiaoting Zhou, Xin Lv, Ze Zhang

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Establishment of a Monitoring Model for the Cotton Leaf Area Index Based on the Canopy Reflectance Spectrum by Xianglong Fan, Xin Lv, Pan Gao, Lifu Zhang, Ze Zhang, Qiang Zhang, Yiru Ma, Xiang Yi, Caixia Yin, Lulu Ma

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Spectrum Occupancy Model Based on Empirical Data for FM Radio Broadcasting in Suburban Environments by Ajalawit Chantaveerod, Kampol Woradit, Charernkiat Pochaiya

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Assessing Soil Organic Matter Content in a Coal Mining Area through Spectral Variables of Different Numbers of Dimensions by Chuanmei Zhu, Zipeng Zhang, Hongwei Wang, Jingzhe Wang, Shengtian Yang

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Desert Soil Salinity Inversion Models Based on Field In Situ Spectroscopy in Southern Xinjiang, China by Yu Wang, Modong Xie, Bifeng Hu, Qingsong Jiang, Zhou Shi, Yinfeng He, Jie Peng

“…To fill this knowledge gap, we collected Vis-NIR in situ spectral and lab-measured SS data from 135 surface soil samples in the Kongterik Pasture Nature Reserve (KPNR) in the desert oasis ecotone of southern Xinjiang, China. We used genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA) algorithms to select the feature bands of SS. …”
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A novel hybrid sand and dust storm detection method using MODIS data on GEE platform by Wei Wang, Alim Samat, Jilili Abuduwaili, Yongxiao Ge, Philippe De Maeyer, Tim Van de Voorde

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First study of Genetic diversity in watermelon (Citrullus lanatus) germplasm collected from Southern Tunisia using RAPD markers by Mokhtar Elbekkay, Hammadi Hamza, Tozer Bekri, Mansour Haddad, Ali Ferchichi

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