Advances and Applications of Artificial Intelligence and Machine Learning : Proceedings of ICAAAIML 2022 |
Autore | Unhelkar Bhuvan |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Singapore : , : Springer, , 2023 |
Descrizione fisica | 1 online resource (782 pages) |
Altri autori (Persone) |
PandeyHari Mohan
AgrawalArun Prakash ChoudharyAnkur |
Collana | Lecture Notes in Electrical Engineering Series |
ISBN | 981-9959-74-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Contents -- About the Editors -- Development of Big Data Dimensionality Reduction Methods for Effective Data Transmission and Feature Enhancement Algorithms -- 1 Introduction -- 2 Works -- 3 Objectives -- 4 Proposed Dimensionality Reduction Method -- 5 Analysis of the Obtained Results -- 6 Conclusion -- References -- IndianFood-7: Detecting Indian Food Items Using Deep Learning-Based Computer Vision -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Our Experimentation on Object Detection Models -- 4 Results -- 5 Conclusion -- References -- Prediction of Protein-Protein Interaction Using Support Vector Machine Based on Spatial Distribution of Amino Acids -- 1 Introduction -- 2 Experimental Setup -- 3 Methodology -- 3.1 Data Set -- 3.2 Feature Representation -- 3.3 Support Vector Machines (SVM) -- 4 Results and Discussion -- 4.1 Evaluation Metrics -- 4.2 Performance of Proposed Model -- 4.3 Proposed Model Comparison Against Various Predictors -- 5 Conclusion -- References -- A Computational Comparison of VGG16 and XceptionNet for Mango Plant Disease Recognition -- 1 Introduction -- 2 Methodology and Dataset -- 2.1 Architecture of the Proposed System -- 2.2 Dataset Description -- 2.3 Data Pre-processing -- 2.4 Models Used -- 2.5 Training and Compiling the Model -- 3 Result and Analysis -- 4 Conclusion -- References -- Generate Artificial Human Faces with Deep Convolutional Generative Adversarial Network (DCGAN) Machine Learning Model -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Experimental Setup -- 3.2 Dataset Description -- 3.3 Model Description -- 4 Results -- 5 Future Scope and Conclusion -- References -- Robust Approach for Person Identification Using Three-Triangle Concept -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Block Diagram of Recommended System.
3.2 Algorithm Used -- 4 Circuit Layout -- 5 Interfacing of Components -- 6 Experimental Results -- 7 Conclusions -- 8 Future Scope -- References -- COVID-19 Disease Detection Using Explainable AI -- 1 Introduction -- 2 Explainable Artificial Intelligence -- 3 Dataset Description -- 4 Approach to the Proposed System -- 4.1 Support Vector Machine -- 4.2 Convolutional Neural Networks -- 4.3 ResNet50 -- 4.4 Implementation of Explainable AI -- 5 Proposed Methodology -- 6 Results -- 7 Conclusion and Future Scope -- References -- Towards Helping Visually Impaired People to Navigate Outdoor -- 1 Introduction -- 1.1 Convolutional Neural Network -- 1.2 Visual Geometry Group -- 2 Literature -- 3 Methodology -- 3.1 Create the Dataset -- 3.2 Applying Existing Approach -- 3.3 Analyzing the Existing Approach -- 3.4 Detect Objects in Image -- 3.5 Train and Test the Model -- 3.6 Analyzing the Results -- 4 Experimentation -- 5 Conclusion and Future Work -- References -- An Analysis of Deployment Challenges for Kubernetes: A NextGen Virtualization -- 1 Introduction -- 2 Origin, History of Kubernetes, and the Community Behind -- 3 Related Works -- 3.1 Literature Review -- 3.2 Objective -- 4 Deployment of Application in Kubernetes Cluster in Public Cloud -- 4.1 Survey to Examine Kubernetes Impact -- 5 Analysis of Deployment Failure Strategies and Measures -- 6 Result Analysis -- 7 Result Analysis -- 8 Conclusion -- References -- A New Task Offloading Scheme for Geospatial Fog Computing Environment Using M/M/C Queueing Approach -- 1 Introduction -- 2 Related Work -- 3 Establishing the Model -- 4 Numerical and Simulation Examples -- 5 Conclusions and Future Work -- References -- Face Recognition Using Deep Neural Network with MobileNetV3-Large -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Pre-processing -- 3.3 MobileNetV3Large Model. 3.4 Hyperparameter Tuning -- 4 Result -- 5 Conclusion -- References -- Detection of BotNet Using Extreme Learning Machine Tuned by Enhanced Sine Cosine Algorithm -- 1 Introduction -- 2 Background and Related Work -- 2.1 BotNet and DDOS -- 2.2 Extreme Learning Machine -- 2.3 Population-Based Metaheuristics -- 3 Proposed Method -- 3.1 Suggested Improved SCA -- 4 Experiments and Discussion -- 4.1 Dataset Description, Pre-processing and Evaluation Metrics -- 4.2 Research Findings and Comparative Analysis -- 5 Conclusion -- References -- Cloud Services Management Using LSTM-RNN -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Forecast Utilizing LSTM-RNN -- 3.2 Workload Prediction Using LSTM Pseudocode -- 4 Result -- 5 Conclusion and Future Scope -- References -- Detection of Various Types of Thyroid-Related Disease Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed System -- 3.1 Dataset -- 3.2 Exploratory Data Analysis -- 3.3 Data Preprocessing -- 3.4 Training Phase -- 3.5 Testing the Model -- 4 Results and Discussion -- 5 Conclusion -- References -- Implementation of WSN in the Smart Hanger to Facilitate MRO Operations on Aircraft Fuselage Using Machine Learning -- 1 Introduction -- 2 Acquisition and Dataset -- 2.1 Complexity of Model and Training Dataset -- 2.2 Learning from Imbalanced Data -- 3 Existing Machine Learning Approaches -- 3.1 DNN (Deep Neural Networks) -- 3.2 Support Vector Machine (SVM) -- 3.3 Algorithmic Approach Using Minimal Data: Few-Shot Learning -- 4 State of the Art Method Evaluation -- 4.1 Experiment -- 4.2 Result -- 5 Proposed Approach -- 6 Conclusion and Prospects -- References -- Wi-Fi Controlled Smart Robot for Objects Tracking and Counting -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Wi-Fi Controlled Smart Robot Through Web Server. 3.2 Proposed Methodology for Color Detection -- 3.3 Object Tracking for Counting Objects -- 4 Results and Discussion -- 5 Conclusion -- References -- Speech Recognition for Kannada Using LSTM -- 1 Introduction -- 2 Literature Review -- 3 Overview of LSTM and Kaldi -- 3.1 Markov Models -- 3.2 RNN -- 3.3 LSTM -- 3.4 Kaldi -- 4 Methodology -- 4.1 Audio Data Collection -- 4.2 Text Data Pre-processing -- 4.3 Feature Extraction and Preparing Language Models -- 4.4 Experiments with Monophone, Triphone Models -- 4.5 Experiments with DNN and LSTM -- 5 Results -- 6 Conclusion -- References -- Computer Vision-Based Smart Helmet with Voice Assistant for Increasing Driver Safety -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Deep Learning Model Development -- 3.2 Rear-End Collision Warning System -- 3.3 Deployment of Deep Learning Model via Server -- 3.4 Architecture of Helmet Software -- 3.5 Building Helmet (Hardware) Prototype -- 3.6 Comparison and Analysis of Models -- 4 Result -- 5 Conclusion and Future Scope -- References -- Predicting Aging Related Bugs with Automated Feature Selection Techniques in Cloud Oriented Softwares -- 1 Research Motivation and Aim -- 1.1 Imbalanced Data -- 1.2 High Dimensional Data -- 2 Related Work -- 3 Research Contributions -- 4 Research Framework -- 4.1 Automated Bug Report Extraction -- 4.2 Feature Selection Techniques -- 4.3 Datasets -- 4.4 Software Metrics -- 4.5 Imbalance Mitigation Procedure-SMOTE -- 4.6 Machine Learning Classifiers -- 4.7 Performance Measures -- 5 Experimental Setup -- 6 Results and Discussions -- 6.1 Detailed Analysis of Feature Ranking -- 6.2 Relative Comparison of Techniques -- 7 Conclusion -- 8 Threats to Validity and Future Work -- References -- Time Series Analysis of Crypto Currency Using ARIMAX -- 1 Introduction -- 2 Literature Review -- 3 Methodology. 4 Components Taken into Consideration -- 4.1 Factors that Affect Crypto Currency -- 4.2 Dataset Used -- 4.3 ARIMAX Algorithm -- 5 Experimental Setup -- 5.1 Cointegrated Pair -- 5.2 Selection of Features -- 5.3 Building the Model -- 6 Result Analysis -- 7 Conclusion -- References -- A Machine Learning Approach Towards Prediction of User's Responsiveness to Notifications with Best Device Identification for Notification Delivery -- 1 Introduction -- 2 Related Work -- 3 Proposed System Architecture -- 3.1 Notification Module -- 3.2 User Identification Module -- 3.3 Active Device and Proximity Detection Module -- 3.4 Privacy and Access Control Module -- 3.5 Intelligent Delivery System Module -- 3.6 Notification Storage Bucket -- 4 Predicting User's Responsiveness to Notifications -- 4.1 Dataset -- 4.2 Predicting User's Responsiveness Using Machine Learning -- 5 Results and Discussions -- 6 Conclusion and Future Work -- References -- Real-Time Full Body Tracking for Life-Size Telepresence -- 1 Introduction -- 2 Related Work -- 3 Material and Method -- 3.1 Full-Body Tracking -- 3.2 Background Removal -- 3.3 Remote User Setting -- 4 Results and Discussion -- 5 Conclusion -- References -- Solar Power Generation Forecasting Using Deep Learning -- 1 Introduction -- 2 Use of Artificial Intelligence in Predicting Data -- 3 Methodology -- 3.1 Data Collection -- 3.2 Pre-processing -- 3.3 Split Data into Train and Testing Sets -- 3.4 Data Standardization -- 3.5 Building Model -- 3.6 Training Model -- 4 Model Building and Implementation -- 5 Model Evaluation -- 6 Results -- 7 Conclusion -- References -- Applications of Big Five Personality Test in Job Performance -- 1 Introduction -- 1.1 Dimensions of Job Performance -- 1.2 Personality Model with Five Traits -- 2 Literature Review -- 3 Objectives of the Study -- 4 Research Design -- 4.1 Measuring Instruments. 5 Data Analysis Technique Employed. |
Record Nr. | UNINA-9910763599703321 |
Unhelkar Bhuvan
![]() |
||
Singapore : , : Springer, , 2023 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Applications of artificial intelligence and machine learning : select proceedings of ICAAAIML 2020 / / edited by Ankur Choudhary [and three others] |
Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (725 pages) |
Disciplina | 016.403 |
Collana | Lecture Notes in Electrical Engineering |
Soggetto topico | Artificial intelligence |
ISBN | 981-16-3067-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- ICAAAIML-2020 -- Preface -- Contents -- About the Editors -- Artificial Intelligence and Its Applications in Smart Education -- Building a Language Data Set in Telugu Using Machine Learning Techniques to Address Suicidal Ideation and Behaviors in Adolescents -- 1 Introduction -- 2 Suicidal Data Set Creation in Telugu -- 3 Technique Used for Data Gathering to Create Required Data Set -- 4 Data Collection -- 4.1 Scrapping -- 4.2 Cleaning -- 4.3 Annotation -- 4.4 Data Set Statistics -- 5 Methodology -- 6 Experiments and Results -- 6.1 Accuracy by ML Classifiers -- 6.2 Binary Classification Measures -- 7 Conclusion -- 8 Future Work -- References -- Feature Selection and Performance Comparison of Various Machine Learning Classifiers for Analyzing Students' Performance Using Rapid Miner -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 4 Experiment and Results -- 5 Conclusion -- References -- Internet of Things (IoT) Based Automated Light Intensity Model Using NodeMcu ESP 8266 Microcontroller -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Objectives -- 2 Research Methodology -- 3 Literature Survey -- 4 Performance Analysis -- 4.1 Analysis Outcomes -- 5 Conclusion and Future Scope -- References -- Handwritten Mathematical Symbols Classification Using WEKA -- 1 Introduction -- 2 Literature Review and Related Work -- 3 Proposed Work -- 4 Implementation -- 5 Conclusion and Future Scope -- References -- Enhancing Sociocultural Learning Using Hyperlocal Experience -- 1 Introduction -- 2 Literature Survey -- 3 Working of the System -- 3.1 Overview -- 3.2 Hyperlocal Forecasting -- 3.3 Architecture -- 3.4 Methodology -- 3.5 Proposed Solution -- 3.6 Algorithm -- 4 Conclusion -- 5 Future Enhancements -- References -- Subsequent Technologies Behind IoT and Its Development Roadmap Toward Integrated Healthcare Prototype Models.
1 Introduction -- 2 Technologies Behind IoT -- 2.1 IoT Development Boards and IoT Hardware -- 2.2 IDE (Integrated Development Environment) -- 2.3 Protocols -- 2.4 Network Spine -- 2.5 Internetwork Cloud Stages/server -- 2.6 Software -- 3 IoT Gateway Device -- 4 IoT Development Roadmap and Healthcare Prototype -- 5 Conclusion -- References -- Big Data and Data Mining -- Bug Assignment-Utilization of Metadata Features Along with Feature Selection and Classifiers -- 1 Introduction -- 2 Literature Survey -- 3 Proposed En-TRAM Triager -- 4 Experimental Setup and Results -- 4.1 Experiment Setup -- 4.2 Results -- 5 Conclusion -- References -- Role of Artificial Intelligence in Detection of Hateful Speech for Hinglish Data on Social Media -- 1 Introduction -- 1.1 Previous Work -- 2 Corpus Creation and Annotation -- 2.1 Annotations -- 3 Methodology -- 3.1 Bidirectional Encoder Representations from Transformers (BERT) -- 3.2 Embeddings from Language Models (ELMo) -- 3.3 Flair -- 4 System Design -- 4.1 Data Pre-Processing -- 4.2 Fine-Tuning Approaches -- 5 Results and Discussion -- 6 Conclusion -- 6.1 Future Scope -- References -- From Web Scraping to Web Crawling -- 1 Introduction -- 2 Methodologies Involved in Web Scraping -- 2.1 DOM Tree Parsing -- 2.2 String Matching -- 2.3 Semantic Framework -- 2.4 Machine Learning-Based Web Scraping -- 3 Web Crawling -- 3.1 Scrapy and Spider -- 4 Scraping Conference Data -- 4.1 Settings.py -- 4.2 Spider -- 4.3 Items.py -- 4.4 Pipelines.py -- 4.5 Middlewares.py -- 5 Restrictions Imposed on Web Scraping -- 5.1 Bypass Restrictions Using User-Agents -- 5.2 Bypass Restrictions Using Proxies -- 5.3 Bypass Restrictions by Logging in the Web site -- 6 Conclusion -- References -- Selection of Candidate Views for Big Data View Materialization -- 1 Introduction -- 2 Big Data View Materialization -- 3 Big Data View Structure Graph. 4 Algorithm BDCV& -- QP -- 5 An Example -- 6 Conclusion -- References -- A Machine Learning Approach to Sentiment Analysis on Web Based Feedback -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Data Collection -- 3.2 Pre-Processing Data -- 3.3 Feature Extraction -- 3.4 Training and Classification -- 4 Implementation -- 5 Result and Discussion -- 6 Conclusions and Future Scope -- References -- Forecasting of Stock Price Using LSTM and Prophet Algorithm -- 1 Introduction -- 2 Related Work -- 3 Stock Market Prediction -- 4 Methodology -- 4.1 Artificial Neural Network (ANN) -- 4.2 Recurrent Neural Network -- 4.3 LSTM (Long Short Term Memory) -- 4.4 Prophet Algorithm -- 5 Results -- 5.1 Implementation of LSTM -- 5.2 Implementation of Prophet Algorithm -- 6 Discussion and Conclusion -- References -- Towards a Federated Learning Approach for NLP Applications -- 1 Introduction -- 2 Related Works -- 3 Federated Learning Infrastructure -- 3.1 Design and Implementation -- 3.2 Dataset and Model -- 4 Results -- 5 Conclusion and Future Work -- References -- Challenges of Smart Cities Future Research Directions -- Analysis of Groundwater Quality Using GIS-Based Water Quality Index in Noida, Gautam Buddh Nagar, Uttar Pradesh (UP), India -- 1 Introduction -- 2 Study Area -- 3 Materials and Methods -- 3.1 Methodology -- 3.2 Physico-Chemical Parameters -- 3.3 Spatial Analysis -- 3.4 Machine Learning Techniques -- 4 GIS Statistical Model -- 5 Results and Discussions -- 6 Spatial Distribution of GIS-Based WQI -- 7 Conclusions -- References -- An Artificial Neural Network Based Approach of Solar Radiation Estimation Using Location and Meteorological Details -- 1 Introduction -- 2 Artificial Neural Network Based Solar Radiation Estimation -- 3 Solar Radiation Estimation Modeling -- 4 Results -- 5 Results -- References. Applications of Machine Learning and Artificial Intelligence in Intelligent Transportation System: A Review -- 1 Introduction -- 2 Applications of ML in ITS -- 2.1 Road Anomaly Detection -- 2.2 Traffic Flow Detection and Travel Time Prediction -- 2.3 Accident Detection and Prevention -- 2.4 Smart City Lights -- 2.5 City Infrastructure -- 3 Applications of AI in Smart Transportation -- 3.1 Safety and Emergency Management System -- 3.2 Autonomous Vehicles -- 3.3 Smart Parking Management -- 3.4 Incident Detection -- 3.5 Predictive Models -- 4 Challenges of AI and ML in ITS -- 5 Future Trends in Intelligent Transportation System -- 6 Conclusion -- References -- Analyzing App-Based Methods for Internet De-Addiction in Young Population -- 1 Introduction -- 2 Prior Work -- 3 Methodology -- 3.1 Mobile Applications -- 3.2 The Basic Methodology -- 4 Results and Analysis -- 4.1 Step 1: Polynomial Regression -- 4.2 Step 2: ANOVA -- 4.3 Step 3: Multivariate Analysis of Variance (MANOVA) -- 5 Conclusion -- References -- Revolution of AI-Enabled Health Care Chat-Bot System for Patient Assistance -- 1 Introduction -- 1.1 History of Chat-Bots -- 1.2 Ease of Use -- 2 Literature Review -- 3 Proposed System -- 3.1 Processing of Chat-Bot -- 3.2 Some Common Mistakes -- 3.3 Building Bot Using Dialog Flow API -- 3.4 Tabular Design of Disease Record -- 3.5 Decision Tree of Chat-Bot -- 3.6 Developing Chat-Bot -- 3.7 Normalizing the Tech Inside Present Digital Channels -- 3.8 Ensuring the Chat-Bot Suits in with Emblem Identity -- 3.9 Handling Chat-Bot -- 3.10 Coping When Matters Go Wrong -- 3.11 Knowing When a Human Need to Take Over -- 4 Results -- 5 Future Work -- 6 Conclusion -- References -- Air Quality Prediction Using Regression Models -- 1 Introduction -- 2 Related Work -- 3 Overview of the Proposed Work -- 3.1 Multiple Linear Regression -- 3.2 Support Vector Regression. 3.3 Decision Tree Regression -- 4 Experimental Setup and Result -- 4.1 Dataset -- 4.2 Preprocessing of Data -- 4.3 Results -- 5 Conclusion -- References -- Anomaly Detection in Videos Using Deep Learning Techniques -- 1 Introduction -- 2 Anomaly Detection Recent Surveys -- 3 Proposed Work -- 3.1 CNN Model -- 3.2 VGG 16 Model -- 4 Implementation -- 4.1 UCF-Crime Dataset -- 4.2 VGG16 & -- CNN Model Implementation -- 5 Results and Analysis -- 6 Conclusion and Future Scope -- References -- Unsupervised Activity Modelling in a Video -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Pre-processing -- 3.2 Feature Extraction -- 3.3 Recognition -- 4 Experimental Results -- 4.1 Dataset -- 4.2 Result Analysis -- 5 Conclusion and Future Work -- References -- Performance Comparison of Various Feature Extraction Methods for Object Recognition on Caltech-101 Image Dataset -- 1 Introduction -- 2 Related Work -- 3 Feature Extraction Methods -- 3.1 Local Features -- 3.2 Deep Features -- 4 Classification Methods -- 4.1 Gaussian Naïve Bayes -- 4.2 K-Nearest Neighbor (k-NN) -- 4.3 Decision Tree -- 4.4 Random Forest -- 4.5 XGBoosting Classifier -- 5 Experimental Results and Discussion -- 5.1 Dataset and Data-Partitioning Methodologies -- 5.2 Performance Evaluation -- 6 Conclusion -- References -- Leukemia Prediction Using SVNN with a Nature-Inspired Optimization Technique -- 1 Introduction -- 1.1 The Novelty of This Paper -- 2 Motivation -- 2.1 Literature Survey -- 3 Proposed Method of Leukemia Detection -- 3.1 Preprocessing of the Input Image -- 3.2 Blast Cell Segmentation -- 3.3 Identification of WBCs -- 3.4 Detection of Leukemia -- 4 Results and Discussion -- 4.1 Performance Analysis -- 4.2 Comparative Analysis -- 5 Conclusion -- References -- Selection of Mobile Node Using Game and Graph Theory for Video Streaming Application -- 1 Introduction. 2 Literature Survey. |
Record Nr. | UNISA-996464494003316 |
Singapore : , : Springer, , [2021] | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|
Applications of artificial intelligence and machine learning : select proceedings of ICAAAIML 2020 / / edited by Ankur Choudhary [and three others] |
Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (725 pages) |
Disciplina | 016.403 |
Collana | Lecture Notes in Electrical Engineering |
Soggetto topico | Artificial intelligence |
ISBN | 981-16-3067-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- ICAAAIML-2020 -- Preface -- Contents -- About the Editors -- Artificial Intelligence and Its Applications in Smart Education -- Building a Language Data Set in Telugu Using Machine Learning Techniques to Address Suicidal Ideation and Behaviors in Adolescents -- 1 Introduction -- 2 Suicidal Data Set Creation in Telugu -- 3 Technique Used for Data Gathering to Create Required Data Set -- 4 Data Collection -- 4.1 Scrapping -- 4.2 Cleaning -- 4.3 Annotation -- 4.4 Data Set Statistics -- 5 Methodology -- 6 Experiments and Results -- 6.1 Accuracy by ML Classifiers -- 6.2 Binary Classification Measures -- 7 Conclusion -- 8 Future Work -- References -- Feature Selection and Performance Comparison of Various Machine Learning Classifiers for Analyzing Students' Performance Using Rapid Miner -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 4 Experiment and Results -- 5 Conclusion -- References -- Internet of Things (IoT) Based Automated Light Intensity Model Using NodeMcu ESP 8266 Microcontroller -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Objectives -- 2 Research Methodology -- 3 Literature Survey -- 4 Performance Analysis -- 4.1 Analysis Outcomes -- 5 Conclusion and Future Scope -- References -- Handwritten Mathematical Symbols Classification Using WEKA -- 1 Introduction -- 2 Literature Review and Related Work -- 3 Proposed Work -- 4 Implementation -- 5 Conclusion and Future Scope -- References -- Enhancing Sociocultural Learning Using Hyperlocal Experience -- 1 Introduction -- 2 Literature Survey -- 3 Working of the System -- 3.1 Overview -- 3.2 Hyperlocal Forecasting -- 3.3 Architecture -- 3.4 Methodology -- 3.5 Proposed Solution -- 3.6 Algorithm -- 4 Conclusion -- 5 Future Enhancements -- References -- Subsequent Technologies Behind IoT and Its Development Roadmap Toward Integrated Healthcare Prototype Models.
1 Introduction -- 2 Technologies Behind IoT -- 2.1 IoT Development Boards and IoT Hardware -- 2.2 IDE (Integrated Development Environment) -- 2.3 Protocols -- 2.4 Network Spine -- 2.5 Internetwork Cloud Stages/server -- 2.6 Software -- 3 IoT Gateway Device -- 4 IoT Development Roadmap and Healthcare Prototype -- 5 Conclusion -- References -- Big Data and Data Mining -- Bug Assignment-Utilization of Metadata Features Along with Feature Selection and Classifiers -- 1 Introduction -- 2 Literature Survey -- 3 Proposed En-TRAM Triager -- 4 Experimental Setup and Results -- 4.1 Experiment Setup -- 4.2 Results -- 5 Conclusion -- References -- Role of Artificial Intelligence in Detection of Hateful Speech for Hinglish Data on Social Media -- 1 Introduction -- 1.1 Previous Work -- 2 Corpus Creation and Annotation -- 2.1 Annotations -- 3 Methodology -- 3.1 Bidirectional Encoder Representations from Transformers (BERT) -- 3.2 Embeddings from Language Models (ELMo) -- 3.3 Flair -- 4 System Design -- 4.1 Data Pre-Processing -- 4.2 Fine-Tuning Approaches -- 5 Results and Discussion -- 6 Conclusion -- 6.1 Future Scope -- References -- From Web Scraping to Web Crawling -- 1 Introduction -- 2 Methodologies Involved in Web Scraping -- 2.1 DOM Tree Parsing -- 2.2 String Matching -- 2.3 Semantic Framework -- 2.4 Machine Learning-Based Web Scraping -- 3 Web Crawling -- 3.1 Scrapy and Spider -- 4 Scraping Conference Data -- 4.1 Settings.py -- 4.2 Spider -- 4.3 Items.py -- 4.4 Pipelines.py -- 4.5 Middlewares.py -- 5 Restrictions Imposed on Web Scraping -- 5.1 Bypass Restrictions Using User-Agents -- 5.2 Bypass Restrictions Using Proxies -- 5.3 Bypass Restrictions by Logging in the Web site -- 6 Conclusion -- References -- Selection of Candidate Views for Big Data View Materialization -- 1 Introduction -- 2 Big Data View Materialization -- 3 Big Data View Structure Graph. 4 Algorithm BDCV& -- QP -- 5 An Example -- 6 Conclusion -- References -- A Machine Learning Approach to Sentiment Analysis on Web Based Feedback -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Data Collection -- 3.2 Pre-Processing Data -- 3.3 Feature Extraction -- 3.4 Training and Classification -- 4 Implementation -- 5 Result and Discussion -- 6 Conclusions and Future Scope -- References -- Forecasting of Stock Price Using LSTM and Prophet Algorithm -- 1 Introduction -- 2 Related Work -- 3 Stock Market Prediction -- 4 Methodology -- 4.1 Artificial Neural Network (ANN) -- 4.2 Recurrent Neural Network -- 4.3 LSTM (Long Short Term Memory) -- 4.4 Prophet Algorithm -- 5 Results -- 5.1 Implementation of LSTM -- 5.2 Implementation of Prophet Algorithm -- 6 Discussion and Conclusion -- References -- Towards a Federated Learning Approach for NLP Applications -- 1 Introduction -- 2 Related Works -- 3 Federated Learning Infrastructure -- 3.1 Design and Implementation -- 3.2 Dataset and Model -- 4 Results -- 5 Conclusion and Future Work -- References -- Challenges of Smart Cities Future Research Directions -- Analysis of Groundwater Quality Using GIS-Based Water Quality Index in Noida, Gautam Buddh Nagar, Uttar Pradesh (UP), India -- 1 Introduction -- 2 Study Area -- 3 Materials and Methods -- 3.1 Methodology -- 3.2 Physico-Chemical Parameters -- 3.3 Spatial Analysis -- 3.4 Machine Learning Techniques -- 4 GIS Statistical Model -- 5 Results and Discussions -- 6 Spatial Distribution of GIS-Based WQI -- 7 Conclusions -- References -- An Artificial Neural Network Based Approach of Solar Radiation Estimation Using Location and Meteorological Details -- 1 Introduction -- 2 Artificial Neural Network Based Solar Radiation Estimation -- 3 Solar Radiation Estimation Modeling -- 4 Results -- 5 Results -- References. Applications of Machine Learning and Artificial Intelligence in Intelligent Transportation System: A Review -- 1 Introduction -- 2 Applications of ML in ITS -- 2.1 Road Anomaly Detection -- 2.2 Traffic Flow Detection and Travel Time Prediction -- 2.3 Accident Detection and Prevention -- 2.4 Smart City Lights -- 2.5 City Infrastructure -- 3 Applications of AI in Smart Transportation -- 3.1 Safety and Emergency Management System -- 3.2 Autonomous Vehicles -- 3.3 Smart Parking Management -- 3.4 Incident Detection -- 3.5 Predictive Models -- 4 Challenges of AI and ML in ITS -- 5 Future Trends in Intelligent Transportation System -- 6 Conclusion -- References -- Analyzing App-Based Methods for Internet De-Addiction in Young Population -- 1 Introduction -- 2 Prior Work -- 3 Methodology -- 3.1 Mobile Applications -- 3.2 The Basic Methodology -- 4 Results and Analysis -- 4.1 Step 1: Polynomial Regression -- 4.2 Step 2: ANOVA -- 4.3 Step 3: Multivariate Analysis of Variance (MANOVA) -- 5 Conclusion -- References -- Revolution of AI-Enabled Health Care Chat-Bot System for Patient Assistance -- 1 Introduction -- 1.1 History of Chat-Bots -- 1.2 Ease of Use -- 2 Literature Review -- 3 Proposed System -- 3.1 Processing of Chat-Bot -- 3.2 Some Common Mistakes -- 3.3 Building Bot Using Dialog Flow API -- 3.4 Tabular Design of Disease Record -- 3.5 Decision Tree of Chat-Bot -- 3.6 Developing Chat-Bot -- 3.7 Normalizing the Tech Inside Present Digital Channels -- 3.8 Ensuring the Chat-Bot Suits in with Emblem Identity -- 3.9 Handling Chat-Bot -- 3.10 Coping When Matters Go Wrong -- 3.11 Knowing When a Human Need to Take Over -- 4 Results -- 5 Future Work -- 6 Conclusion -- References -- Air Quality Prediction Using Regression Models -- 1 Introduction -- 2 Related Work -- 3 Overview of the Proposed Work -- 3.1 Multiple Linear Regression -- 3.2 Support Vector Regression. 3.3 Decision Tree Regression -- 4 Experimental Setup and Result -- 4.1 Dataset -- 4.2 Preprocessing of Data -- 4.3 Results -- 5 Conclusion -- References -- Anomaly Detection in Videos Using Deep Learning Techniques -- 1 Introduction -- 2 Anomaly Detection Recent Surveys -- 3 Proposed Work -- 3.1 CNN Model -- 3.2 VGG 16 Model -- 4 Implementation -- 4.1 UCF-Crime Dataset -- 4.2 VGG16 & -- CNN Model Implementation -- 5 Results and Analysis -- 6 Conclusion and Future Scope -- References -- Unsupervised Activity Modelling in a Video -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Pre-processing -- 3.2 Feature Extraction -- 3.3 Recognition -- 4 Experimental Results -- 4.1 Dataset -- 4.2 Result Analysis -- 5 Conclusion and Future Work -- References -- Performance Comparison of Various Feature Extraction Methods for Object Recognition on Caltech-101 Image Dataset -- 1 Introduction -- 2 Related Work -- 3 Feature Extraction Methods -- 3.1 Local Features -- 3.2 Deep Features -- 4 Classification Methods -- 4.1 Gaussian Naïve Bayes -- 4.2 K-Nearest Neighbor (k-NN) -- 4.3 Decision Tree -- 4.4 Random Forest -- 4.5 XGBoosting Classifier -- 5 Experimental Results and Discussion -- 5.1 Dataset and Data-Partitioning Methodologies -- 5.2 Performance Evaluation -- 6 Conclusion -- References -- Leukemia Prediction Using SVNN with a Nature-Inspired Optimization Technique -- 1 Introduction -- 1.1 The Novelty of This Paper -- 2 Motivation -- 2.1 Literature Survey -- 3 Proposed Method of Leukemia Detection -- 3.1 Preprocessing of the Input Image -- 3.2 Blast Cell Segmentation -- 3.3 Identification of WBCs -- 3.4 Detection of Leukemia -- 4 Results and Discussion -- 4.1 Performance Analysis -- 4.2 Comparative Analysis -- 5 Conclusion -- References -- Selection of Mobile Node Using Game and Graph Theory for Video Streaming Application -- 1 Introduction. 2 Literature Survey. |
Record Nr. | UNINA-9910495217103321 |
Singapore : , : Springer, , [2021] | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|