LEADER 04158nam 22007215 450 001 9910851982603321 005 20240424130420.0 010 $a9789819703272 010 $a9819703271 024 7 $a10.1007/978-981-97-0327-2 035 $a(CKB)31636418200041 035 $a(MiAaPQ)EBC31304027 035 $a(Au-PeEL)EBL31304027 035 $a(DE-He213)978-981-97-0327-2 035 $a(Exl-AI)31304027 035 $a(EXLCZ)9931636418200041 100 $a20240424d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence and Sustainable Computing $eProceedings of ICSISCET 2023 /$fedited by Manjaree Pandit, M. K. Gaur, Sandeep Kumar 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (714 pages) 225 1 $aAlgorithms for Intelligent Systems,$x2524-7573 311 08$a9789819703265 311 08$a9819703263 327 $aPreface -- Contents -- About the Editors -- 1 A Novel Intelligence System for Hybrid Crop Suitable Landform Prediction Using Machine Learning Techniques and IoT -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Dataset Description -- 5 Feature Engineering -- 6 Experiments -- 6.1 Logistic Regression -- 6.2 K-Nearest Neighbours (KNN) -- 6.3 Extreme Gradient Boosting (XGBoost) -- 6.4 Implementation in Cloud -- 7 Results and Discussion -- 8 Conclusion -- 9 Future Work -- References -- 2 Indian Annual Report Assessment Using Large Language Models -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Objective -- 1.3 Contribution -- 2 Related Work -- 3 Methodology -- 3.1 Dataset Preparation -- 3.2 Class Labels -- 4 Results -- 4.1 Fine-Tuning Language Model -- 4.2 Sentence Transformers$7Generated by AI. 330 $aThis book presents high-quality research papers presented at the 5th International Conference on Sustainable and Innovative Solutions for Current Challenges in Engineering and Technology (ICSISCET 2023) held at Madhav Institute of Technology & Science (MITS), Gwalior, India, during October 21?22, 2023. The book extensively covers recent research in artificial intelligence (AI) that knit together nature-inspired algorithms, evolutionary computing, fuzzy systems, computational intelligence, machine learning, deep learning, etc., which is very useful while dealing with real problems due to their model-free structure, learning ability, and flexible approach. These techniques mimic human thinking and decision-making abilities to produce systems that are intelligent, efficient, cost-effective, and fast. The book provides a friendly and informative treatment of the topics which makes this book an ideal reference for both beginners and experienced researchers. 410 0$aAlgorithms for Intelligent Systems,$x2524-7573 606 $aComputational intelligence 606 $aElectronic circuits 606 $aCooperating objects (Computer systems) 606 $aInternet of things 606 $aMachine learning 606 $aComputational Intelligence 606 $aElectronic Circuits and Systems 606 $aCyber-Physical Systems 606 $aInternet of Things 606 $aMachine Learning 615 0$aComputational intelligence. 615 0$aElectronic circuits. 615 0$aCooperating objects (Computer systems) 615 0$aInternet of things. 615 0$aMachine learning. 615 14$aComputational Intelligence. 615 24$aElectronic Circuits and Systems. 615 24$aCyber-Physical Systems. 615 24$aInternet of Things. 615 24$aMachine Learning. 676 $a006.3 700 $aPandit$b Manjaree$01430267 701 $aGaur$b M. K$01430268 701 $aKumar$b Sandeep$0860947 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910851982603321 996 $aArtificial Intelligence and Sustainable Computing$93569977 997 $aUNINA LEADER 06407oam 22006495 450 001 9910954026503321 005 20240501070555.0 010 $a9781464809057 010 $a1464809054 024 7 $a10.1596/978-1-4648-0904-0 035 $a(CKB)3710000000769501 035 $a(EBL)4605625 035 $a(OCoLC)953999699 035 $a(MiAaPQ)EBC4605625 035 $a(The World Bank)210904 035 $a(US-djbf)210904 035 $a(Perlego)1483940 035 $a(EXLCZ)993710000000769501 100 $a20020129d2016 uf 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMobile Phone Panel Surveys in Developing Countries : $eA Practical Guide for Microdata Collection /$fAndrew Dabalen 205 $a1st ed. 210 1$aWashington, D.C. :$cThe World Bank,$d2016. 215 $a1 online resource (128 pages) 225 1 $aDirections in Development;Directions in Development - Poverty 300 $aDescription based upon print version of record. 311 08$a9781464809040 311 08$a1464809046 320 $aIncludes bibliographical references at the end of each chapters. 327 $aFront Cover; Contents; Foreword; Acknowledgments; About the Authors and Contributors; Abbreviations; Introduction; Chapter 1 The Rationale for Mobile Phone Panel Surveys; Why Mobile Phone Panel Surveys?; The MPPS Approach; Advantages of MPPSs; Inquiry on Mobile Data Collection: Voice and the Alternatives; Steps in Conducting Representative MPPSs; Notes; References; Chapter 2 Designing a Mobile Phone Panel Survey; Introduction; Cross-Section or Panel Design?; The Implications of Frequency and Duration for Data Quality and Bias; Respondent Selection; Sampling Frames; MPPS-Specific Challenges 327 $aSample Size CalculationStratification and Clustering; Sample Weights and Reweighting; Notes; References; Chapter 3 The Baseline Survey; Introduction; Groundwork: The Distribution of Mobile Phones and Solar Chargers; Considerations in Purchasing Mobile Phones and Solar Chargers; Handling the Registration of SIM Cards; Choosing the Mode of Data Collection during the Baseline Survey; Obtaining Official Licensing for the Survey; MPPS Instruments: The Baseline Survey; Piloting an MPPS; Building Team Spirit and Community Engagement; Challenges Associated with the MPPS Baseline Survey; Notes 327 $aReferencesChapter 4 Setting Up a Call Center; Introduction; Building an In-House Call Center vs. Outsourcing; Technology Considerations; The Recruitment and Training of Call Center Staff; Incentives and Other Considerations; Quality Control Measures; Notes; References; Chapter 5 Conducting Mobile Phone Panel Interviews; Introduction; Nonresponse, Attrition, and the Survey Participation Decision; Respondent Decisions to Participate; The Mobile Phone Survey Questionnaire; Duration and Frequency of Mobile Phone Surveys; Review, Translation, Pretest, Scripting, Training, and Piloting 327 $aData CollectionResponse Correlates and the Effect of Incentives; Attrition Management: A Review; Notes; References; Chapter 6 Data Analysis and Management; Introduction; Data Analysis; Report Writing; Data Dissemination; The Open Data Principle; Chapter 7 How Much Does It Cost?; Appendix A Head of Household Consent Form; Appendix B Respondent Agreement Form; Appendix C Baseline Survey Checklist; Appendix D Sample Mobile Phone Questionnaire; Appendix E Sample Phone Survey Round Calendar; Appendix F Sauti za Wananchi Report 9 (March 2014); Appendix G Checklist of Budget Items for MPPSs; Boxes 330 3 $aHousehold survey data are very useful for monitoring living conditions of citizens of any country. In developing countries, a lot of this data are collected through "traditional" face-to-face household surveys. Due to the remote and dispersed nature of many populations in developing countries, but also because of the complex nature of many survey questionnaires, collection of timely welfare data has often proved expensive and logistically challenging. Yet, there is a need for faster, cheaper to collect, lighter, more nimble data collection methods to address data gaps between big household surveys. The recent proliferation of mobile phone networks has opened new possibilities. By combining baseline data from a traditional household survey with subsequent interviews of selected respondents using mobile phones, this facilitates welfare monitoring and opinion polling almost real time. The purpose of this handbook is to contribute to the development of the new field of mobile phone data collection in developing countries. The handbook documents how this innovative approach to data collection works, its advantages and challenges. The handbook draws primarily from the authors' first-hand experiences with mobile phone surveys in Africa and also benefits from experiences elsewhere. It is intended to serve a diverse audience including those involved in collecting (representative) data using mobile phones, and those using data collected through this approach. For those who will be implementing a mobile phone panel survey, the different chapters guide them through every stage of the implementation process. For potential users of the data collected via mobile phone technology, the handbook presents a new approach to data collection which they can use for monitoring programs and facilitate almost real time decision-making. A further purpose of this book is to contribute to the debate regarding the advantages of the method as well as the challenges associated with it. 410 0$aDirections in Development - Poverty 410 0$aWorld Bank e-Library. 606 $aTelephone surveys$zDeveloping countries$xMethodology 607 $aDeveloping countries$2fast 615 0$aTelephone surveys$xMethodology. 676 $a001.433 700 $aDabalen$b Andrew$01804167 701 $aDabalen$b Andrew$01804167 701 $aEtang$b Alvin$01813985 701 $aHoogeveen$b Johannes$01793954 701 $aMushi$b Elvis$01813986 701 $aSchipper$b Youdi$0614063 701 $avon Engelhardt$b Johannes$01813987 801 0$bDJBF 801 1$bDJBF 906 $aBOOK 912 $a9910954026503321 996 $aMobile Phone Panel Surveys in Developing Countries$94367539 997 $aUNINA