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"The classic survey design reference, updated for the digital ageFor over two decades, Dillman's classic text on survey design has aided both students and professionals in effectively planning and conducting mail, telephone, and, more recently, Internet surveys. The new edition is thoroughly updated and revised, and covers all aspects of survey research. It features expanded coverage of mobile phones, tablets, and the use of do-it-yourself surveys, and Dillman's unique Tailored Design Method is also thoroughly explained. This invaluable resource is crucial for any researcher seeking to increase response rates and obtain high-quality feedback from survey questions. Consistent with current emphasis on the visual and aural, the new edition is complemented by copious examples within the text and accompanying website.This heavily revised Fourth Edition includes: Strategies and tactics for determining the needs of a given survey, how to design it, and how to effectively administer it How and when to use mail, telephone, and Internet surveys to maximum advantage Proven techniques to increase response rates Guidance on how to obtain high-quality feedback from mail, electronic, and other self-administered surveys Direction on how to construct effective questionnaires, including considerations of layout The effects of sponsorship on the response rates of surveys Use of capabilities provided by newly mass-used media: interactivity, presentation of aural and visual stimuli. The Fourth Edition reintroduces the telephone--including coordinating land and mobile. Grounded in the best research, the book offers practical how-to guidelines and detailed examples for practitioners and students alike"--

Qualitative methods in social research --- Market research --- Enquêtes --- Sociaalwetenschappelijk onderzoek --- Social surveys. --- Questionnaires. --- Data Collection. --- Surveys and Questionnaires. --- Baseline Survey --- Community Surveys --- Methodology, Survey --- Nonrespondents --- Questionnaire Design --- Randomized Response Technique --- Repeated Rounds of Survey --- Respondents --- Survey Methodology --- Questionnaires --- Survey Methods --- Surveys --- Baseline Surveys --- Community Survey --- Design, Questionnaire --- Designs, Questionnaire --- Methods, Survey --- Nonrespondent --- Questionnaire --- Questionnaire Designs --- Questionnaires and Surveys --- Randomized Response Techniques --- Respondent --- Response Technique, Randomized --- Response Techniques, Randomized --- Survey --- Survey Method --- Survey, Baseline --- Survey, Community --- Surveys, Baseline --- Surveys, Community --- Techniques, Randomized Response --- Data Aggregation --- Data Collection Methods --- Dual Data Collection --- Aggregation, Data --- Collection Method, Data --- Collection Methods, Data --- Collection, Data --- Collection, Dual Data --- Data Collection Method --- Method, Data Collection --- Methods, Data Collection --- Medical History Taking --- Empirical Research --- Community surveys --- Surveys, Social --- Social sciences --- Research --- sociaal onderzoek --- 301.08 --- #SBIB:303H4 --- #SBIB:303H32 --- Informatica in de sociale wetenschappen --- Waarneming en participerende waarneming, gecontroleerde observatie, groepsdiscussie (vragenlijsten, interviews, experimenten) --- Social surveys --- Data Collection --- Surveys and Questionnaires --- Enquêtes

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From an award-winning project comes an inspiring, collaborative book that makes data artistic, personal, and open to all. Each week for a year, Giorgia and Stefanie sent each other a postcard describing what had happened to them during that week around a particular theme. But they didn't write it, they drew it: a week of smiling, a week of apologies, a week of desires. Presenting their fifty-two cards, along with thoughts and ideas about the data-drawing process, Dear Data hopes to inspire you to draw, slow down and make connections with other people, to see the world through a new lens, where everything and anything can be a creative starting point for play and expression.

Information visualization. --- Data Collection. --- 741.07 --- 741.039 --- Tekenkunst ; getekende dagboeken ; 2014-2016 ; G. Lupi & St. Posavec --- Visuele communicatie ; tekeningen van concrete en abstracte thema's --- Postkaarten ; gemaakt door kunstenaars ; 20ste en 21ste eeuw --- Ansichtkaarten ; prentbriefkaarten ; van kunstenaars --- Lupi, Giorgia °? (°Mirandola, Italië) --- Posavec, Stephanie °? (°Denver, Colorado, Verenigde Staten) --- Data Aggregation --- Data Collection Methods --- Dual Data Collection --- Aggregation, Data --- Collection Method, Data --- Collection Methods, Data --- Collection, Data --- Collection, Dual Data --- Data Collection Method --- Method, Data Collection --- Methods, Data Collection --- Medical History Taking --- Empirical Research --- Data visualization --- Visualization of information --- Information science --- Visual analytics --- Tekenkunst ; tekenkunstenaars A - Z --- Tekenkunst ; 2000 - 2050 --- Information visualization --- Data Collection --- 766.022 --- 741.071 POSAVEC --- 741.071 LUPI --- prentkaarten --- postkaarten --- eenentwintigste eeuw --- information design --- informatiedesign --- grafisch ontwerp --- grafisch design --- grafische vormgeving --- tekenkunst --- Lupi Giorgia --- Posavec Stephanie --- Curiosities and wonders. --- 766.32.044 --- Mail art --- Grafische industrie en ontwerp ; beeld ; illustratie ; thema's ; infographics --- Lupi, Giorgia --- Posavec, Stefanie

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Rats as laboratory animals --- Toxicology, Experimental --- Data Collection. --- Rats, Inbred Strains. --- Toxicology --- Evidence Based Toxicology --- Evidence-Based Toxicology --- Toxinology --- Based Toxicologies, Evidence --- Based Toxicology, Evidence --- Evidence Based Toxicologies --- Evidence-Based Toxicologies --- Toxicologies, Evidence Based --- Toxicologies, Evidence-Based --- Toxicology, Evidence Based --- Toxicology, Evidence-Based --- Pharmacogenetics --- Experimental toxicology --- Laboratory animals --- Inbred Rat Strains --- Inbred Strain of Rat --- Inbred Strain of Rats --- Inbred Strains of Rats --- Rat, Inbred Strain --- August Rats --- August Rat --- Inbred Rat Strain --- Inbred Strain Rat --- Inbred Strain Rats --- Inbred Strains Rat --- Inbred Strains Rats --- Rat Inbred Strain --- Rat Inbred Strains --- Rat Strain, Inbred --- Rat Strains, Inbred --- Rat, August --- Rat, Inbred Strains --- Rats Inbred Strain --- Rats Inbred Strains --- Rats, August --- Rats, Inbred Strain --- Strain Rat, Inbred --- Strain Rats, Inbred --- Strain, Inbred Rat --- Strains, Inbred Rat --- Data Aggregation --- Data Collection Methods --- Dual Data Collection --- Aggregation, Data --- Collection Method, Data --- Collection Methods, Data --- Collection, Data --- Collection, Dual Data --- Data Collection Method --- Method, Data Collection --- Methods, Data Collection --- Medical History Taking --- Empirical Research --- Tables --- Data collection. --- Rats --- Toxicology, experimental --- Toxicology. --- Inbred strains. --- Tables. --- Data Collection --- Rats, Inbred Strains

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This book compiles a set of original and innovative papers included in the Special Issue on UAVs for vegetation monitoring, which proves the wide scope of UAVs in very diverse vegetation applications, both in agricultural and forestry scenarios, ranging from the characterization of relevant vegetation features to the detection of plant or crop stressors. New methods and techniques are developed and applied to diverse vegetation scenarios to meet the main challenge of sustainability.

Research & information: general --- UAS --- UAV --- vegetation cover --- multispectral --- land cover --- forest --- Acacia --- Indonesia --- tropics --- vegetation ground cover --- vegetation indices --- agro-environmental measures --- olive groves --- southern Spain --- sUAS --- water stress --- ornamental --- container-grown --- artificial intelligence --- machine learning --- deep learning --- neural network --- visual recognition --- precision agriculture --- canopy cover --- image analysis --- crop mapping --- evapotranspiration (ET) --- GRAPEX --- remote sensing --- Two Source Energy Balance model (TSEB) --- contextual spatial domain/resolution --- data aggregation --- eddy covariance (EC) --- Fusarium wilt --- crop disease --- banana --- multispectral remote sensing --- purple rapeseed leaves --- unmanned aerial vehicle --- U-Net --- plant segmentation --- nitrogen stress --- Glycine max --- RGB --- canopy height --- close remote sensing --- growth model --- curve fitting --- NDVI --- solar zenith angle --- flight altitude --- time of day --- operating parameters --- CNN --- Faster RCNN --- SSD --- Inception v2 --- patch-based CNN --- MobileNet v2 --- detection performance --- inference time --- disease detection --- cotton root rot --- plant-level --- single-plant --- plant-by-plant --- classification --- UAV remote sensing --- crop monitoring --- RGB imagery --- multispectral imagery --- century-old biochar --- semantic segmentation --- random forest --- crop canopy --- multispectral image --- chlorophyll content --- remote sensing technique --- individual plant segmentation --- plant detection --- transfer learning --- maize tassel --- tassel branch number --- convolution neural network --- VGG16 --- plant nitrogen estimation --- vegetation index --- image segmentation --- transpiration --- method comparison --- oil palm --- multiple linear regression --- support vector machine --- artificial neural network --- UAV hyperspectral --- wheat yellow rust --- disease monitoring --- texture --- spatial resolution --- RGB camera --- thermal camera --- drought tolerance --- forage grass --- HSV --- CIELab --- broad-sense heritability --- phenotyping gap --- high throughput field phenotyping --- UAV digital images --- winter wheat biomass --- multiscale textures --- red-edge spectra --- least squares support vector machine --- variable importance --- drone --- hyperspectral --- thermal --- nutrient deficiency --- weed detection --- disease diagnosis --- plant trails

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This book compiles a set of original and innovative papers included in the Special Issue on UAVs for vegetation monitoring, which proves the wide scope of UAVs in very diverse vegetation applications, both in agricultural and forestry scenarios, ranging from the characterization of relevant vegetation features to the detection of plant or crop stressors. New methods and techniques are developed and applied to diverse vegetation scenarios to meet the main challenge of sustainability.

UAS --- UAV --- vegetation cover --- multispectral --- land cover --- forest --- Acacia --- Indonesia --- tropics --- vegetation ground cover --- vegetation indices --- agro-environmental measures --- olive groves --- southern Spain --- sUAS --- water stress --- ornamental --- container-grown --- artificial intelligence --- machine learning --- deep learning --- neural network --- visual recognition --- precision agriculture --- canopy cover --- image analysis --- crop mapping --- evapotranspiration (ET) --- GRAPEX --- remote sensing --- Two Source Energy Balance model (TSEB) --- contextual spatial domain/resolution --- data aggregation --- eddy covariance (EC) --- Fusarium wilt --- crop disease --- banana --- multispectral remote sensing --- purple rapeseed leaves --- unmanned aerial vehicle --- U-Net --- plant segmentation --- nitrogen stress --- Glycine max --- RGB --- canopy height --- close remote sensing --- growth model --- curve fitting --- NDVI --- solar zenith angle --- flight altitude --- time of day --- operating parameters --- CNN --- Faster RCNN --- SSD --- Inception v2 --- patch-based CNN --- MobileNet v2 --- detection performance --- inference time --- disease detection --- cotton root rot --- plant-level --- single-plant --- plant-by-plant --- classification --- UAV remote sensing --- crop monitoring --- RGB imagery --- multispectral imagery --- century-old biochar --- semantic segmentation --- random forest --- crop canopy --- multispectral image --- chlorophyll content --- remote sensing technique --- individual plant segmentation --- plant detection --- transfer learning --- maize tassel --- tassel branch number --- convolution neural network --- VGG16 --- plant nitrogen estimation --- vegetation index --- image segmentation --- transpiration --- method comparison --- oil palm --- multiple linear regression --- support vector machine --- artificial neural network --- UAV hyperspectral --- wheat yellow rust --- disease monitoring --- texture --- spatial resolution --- RGB camera --- thermal camera --- drought tolerance --- forage grass --- HSV --- CIELab --- broad-sense heritability --- phenotyping gap --- high throughput field phenotyping --- UAV digital images --- winter wheat biomass --- multiscale textures --- red-edge spectra --- least squares support vector machine --- variable importance --- drone --- hyperspectral --- thermal --- nutrient deficiency --- weed detection --- disease diagnosis --- plant trails