11057nam 22005053 450 991085539560332120240506084508.03-031-58604-2(MiAaPQ)EBC31316740(Au-PeEL)EBL31316740(CKB)31892975300041(MiAaPQ)EBC31319725(Au-PeEL)EBL31319725(EXLCZ)993189297530004120240506d2024 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAdvancements in Smart Computing and Information Security Second International Conference, ASCIS 2023, Rajkot, India, December 7-9, 2023, Revised Selected Papers, Part I1st ed.Cham :Springer International Publishing AG,2024.©2024.1 online resource (509 pages)Communications in Computer and Information Science Series ;v.20373-031-58603-4 Intro -- Preface -- Organization -- Abstract of Keynotes -- Generative AI vs Chat GPT vs Cognitive AI Impact on Cyber Security Real World Applications -- Empowering Smart Computing Through the Power of Light -- Optimal Transport Algorithms with Machine Learning Applications -- Some Research Issues on Cyber Security -- Smart Infrastructure and Smart Agriculture- Japan Use Cases -- Unveiling the Dynamics of Spontaneous Micro and Macro Facial Expressions -- AI Advancements in Biomedical Image Processing: Challenges, Innovations, and Insights -- Emerging Technologies and Models for Data Protection and Resource Management in Cloud Environments -- Artificial Intelligence and Jobs of the Future 2030 -- New Age Cyber Risks Due to AI Intervention -- Challenges of 5G in Combat Networks -- Dark Side of Artificial Intelligence -- Blockchain Integrated Security Solution for Internet of Drones (IoD) -- Generative Intelligence: A Catalyst for Safeguarding Society in the Age of GenAI -- Contents - Part I -- Artificial Intelligence and Machine Learning -- Calorie Measurement and Food Recognition Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Algorithm Employed in the Project: The Below Algorithm 1 Serves as a Representation of the Suggested Approach -- 4 Experimental Results and Discussion -- 5 Conclusion -- References -- Mean Harris Hawks Optimization (MHHO) Based Feature Selection and FFNN-LBAAA for Semen Quality Predictive Model -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Data Source and Pre-processing -- 3.2 Instance Balancing Using SMOTE -- 3.3 Feature Selection Using Mean Harris Hawks Optimization (HHO) -- 3.4 Feed Forwarded Neural Network (FFNN) Classification -- 3.5 LBAAA for Optimization -- 4 Results and Discussion -- 4.1 Dataset Balancing for Training Classifiers.4.2 Evaluation Metrics -- 4.3 Results Comparison -- 5 Conclusion and Future Work -- References -- An Extensive Examination of Utilizing Big Data Analytics in Cancer Detection Techniques -- 1 Introduction -- 2 Related Work -- 3 Literature Review -- 4 Conclusion and Future Work -- References -- Price Forecasting of Potato Using ARIMA Model on Cloud Platform -- 1 Introduction -- 2 Monitoring of Price -- 3 Reviews of Literature -- 4 Methodology -- 4.1 Material and Methods Used -- 4.2 Method for Data Analysis -- 5 Discussion of Result -- 6 Conclusion and Future Work -- References -- Analysis of Exoplanet Habitability Using RNN and Causal Learning -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 Results -- 5 Conclusion -- 6 Future Scope -- References -- Evident Based Perspective Assessment and Evaluation of the Current Educational System for Hard of Hearing and Mutant Students -- 1 Introduction -- 1.1 Auditory System -- 1.2 Causes of Disabling Hearing Loss -- 1.3 Types of Disabling Hearing Loss -- 1.4 Impact of Disabling Hearing Loss in Education -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Data Collection -- 3.2 Data Analysis -- 4 Results and Discussion -- 5 Future Study -- 6 Conclusion -- References -- Exploring and Improving Deep Learning-Based Image Filtering and Segmentation Techniques for Enhancing Leukemia Images -- 1 Introduction -- 2 Literature Review -- 3 Dataset -- 4 Methodology -- 4.1 Image Filtering Techniques -- 5 Performance Analysis of Image Filtering Methods -- 5.1 Mean Squared Error (MSE) -- 5.2 Peak Signal-to-Noise Ratio -- 5.3 Structural Similarity Index -- 5.4 Normalized Root Mean Squared Error -- 6 Image Segmentation Algorithms -- 6.1 Otsu Method -- 6.2 GrabCut and Global Thresholding -- 7 Performance Analysis of Image Segmentation Methods -- 8 Result and Discussion -- 9 Conclusion -- References.Ocular Disease Prediction Using Feature Maps with Convolutional Neural Network (CNN) Method -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 3.1 Data Collection -- 4 Results and Discussion -- 5 Conclusion -- References -- Modified Extreme Gradient Boosting Algorithm for Prediction of Air Pollutants in Various Peak Hours -- 1 Introduction -- 2 Literature Review -- 3 Research and Data -- 4 Methodology -- 4.1 Extreme Gradient Boost (XG Boost) Algorithm -- 4.2 Modified Extreme Gradient Boost Algorithm (MXGBA) -- 5 Results and Discussion -- 6 Future Study -- 7 Conclusion -- References -- Deep Learning RBFNN MPPT Developmemt for Hybrid Energy Microgrid -- 1 Introduction -- 2 Proposed System Description -- 3 Modeling of the Proposed System -- 4 Results and Discussions -- 5 Conclusion -- References -- AI-Powered Automated Methods for Predicting Liver Disease: A Recent Review -- 1 Introduction -- 2 AI Powered Diagnosis of Liver Diseases -- 2.1 Clinical Information Based Diagnosis Methods -- 2.2 Image Based Diagnosis Methods -- 3 Conclusion -- References -- Development of Processing Algorithms for the Retrieval of Snow/Ice Parameters from SAR Data -- 1 Introduction -- 1.1 Background -- 1.2 Problem Statement -- 2 Literature Review -- 2.1 Work Associated with -- 3 Research Methodology -- 3.1 Theoretical Framework -- 3.2 Dilemma and Solution Conceptual Examination -- 3.3 Proposed Approach -- 4 Experimental Result -- 4.1 General -- 4.2 Analysis of Results -- 5 Conclusion and Next Steps -- 5.1 Results -- 5.2 Future Work -- References -- Image Quality Enhancement of Digital Mammograms Through Hybrid Filter and Contrast Enhancement -- 1 Introduction -- 1.1 Research Contribution -- 2 Related Work -- 3 Image Dataset -- 4 Proposed Method -- 4.1 Noise and Artifacts Removal and Image Resize -- 4.2 Contrast Enhancement -- 5 Performance Metrics.6 Results and Discussion -- 6.1 Comparative Analysis -- 7 Conclusion and Future Recommendations -- References -- Math Word Problem Solving with Guided-Context Tree-Structured Model -- 1 Introduction -- 2 Literature Survey -- 2.1 Seq2seq Models -- 2.2 Tree-Structured Neural Model -- 2.3 Sub-tree Embedding via Recursive Neural Network -- 2.4 Complex Relation Extraction via Deductive Reasoner -- 2.5 Enhancing Data Interpretability Using Content Planner -- 3 Methodology -- 3.1 Content Planner -- 3.2 RoBERTa Deduct Reasoner (RDR) -- 3.3 Combined Model -- 4 Implementation -- 4.1 Content Planner Implementation -- 4.2 RDR Implementation -- 4.3 Final Combined Implementation -- 5 Results and Conclusion -- 5.1 Answer Accuracy -- 5.2 Expression Accuracy -- 5.3 Performance Based on Expression Length -- 6 Conclusion and Future Scope -- References -- Multi-model Chatbot and Image Classifier for Plant Disease Detection -- 1 Introduction -- 2 Research Gaps -- 3 Related Works and Literature Survey -- 4 Proposed Methodology -- 4.1 Pre-processing Techniques -- 4.2 Model for Image Classification -- 4.3 Model for Integrated Chat-Bot -- 4.4 Data-Set Description -- 5 Results and Conclusion -- References -- Generating Bug Reports Using Topic-Modelling and Sentimental Analysis -- 1 Introduction -- 2 Topic Modelling -- 2.1 Types of Topic Modelling Techniques: -- 3 Sentimental Analysis -- 4 Methodology -- 4.1 Data Collection and Preprocessing -- 4.2 Topic Modelling and Sentimental Analysis -- 5 Results and Discussions -- 5.1 Overview of Results -- 5.2 Topic Modelling Results -- 5.3 Sentimental Analysis Results -- 6 Related Work -- 7 Conclusion -- References -- Smart Dam Control: Embedded Systems and LSTM-Based Water Level Prediction -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 4 Results -- 5 Conclusion -- References.The Datafication of Everything: Challenges and Opportunities in a Hyperconnected World -- 1 Introduction -- 1.1 Research Questions or Objectives -- 1.2 Outline the Structure of the Paper -- 2 Literature Review -- 3 Datafication in a Hyperconnected World -- 4 Challenges of Datafication -- 5 Opportunities of Datafication -- 6 Findings and Discussions -- 7 Future Trends -- 8 Conclusion -- References -- Deep Learning Approaches for Liver Tumor Segmentation -- 1 Introduction -- 1.1 Objective of the Work -- 1.2 Scope of the Work -- 1.3 Deep Learning -- 1.4 Convolutional Neural Network (CNN) -- 1.5 LeNet -- 1.6 Python -- 2 Previous Works -- 3 Dataset Used -- 4 Methodology Used -- 5 Design and Development of System -- 5.1 Pre-processing of Data -- 5.2 Training and Testing -- 5.3 Dice Coefficient Technique -- 5.4 Data Augmentation -- 5.5 Classification Using CNN -- 5.6 Segmentation Using Lenet -- 6 Results and Discussion -- 6.1 Data Visualization -- 7 Conclusion -- References -- Anemia Prediction Using Machine Learning Algorithms -- 1 Introduction -- 2 Concepts of Machine Learning -- 3 Literature Review -- 4 Proposed Methodology -- 4.1 Data Collection -- 4.2 Data Preprocessing -- 4.3 Investigating MCH -- 4.4 Investigating MCV -- 4.5 Investigating MCHC -- 5 Ml Classifiers -- 5.1 Decision Tree -- 5.2 Random Forest Classifier -- 5.3 Naive Bayes Algorithm -- 6 Results -- 6.1 Precision -- 6.2 Recall -- 7 Conclusion -- References -- A Sentiment Analysis on Opinions of COVID-19 Vaccination in Social Networking Site -- 1 Introduction -- 2 Methods -- 3 Word Cloud -- 4 Sentiment Analysis -- 5 Outcome and Review -- 6 Conclusion -- References -- Freezing of Gait Prognostication in Parkinson's Disease -- 1 Introduction -- 2 Aim and Objective -- 2.1 Aim -- 2.2 Objective -- 3 Problem Specification -- 3.1 Data Description -- 3.2 Literature Review -- 4 Methodology.4.1 Data Collection.Communications in Computer and Information Science SeriesRajagopal Sridaran1737751Popat Kalpesh1737752Meva Divyakant1737753Bajeja Sunil1737754MiAaPQMiAaPQMiAaPQBOOK9910855395603321Advancements in Smart Computing and Information Security4159684UNINA