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Advancements in Smart Computing and Information Security : Second International Conference, ASCIS 2023, Rajkot, India, December 7-9, 2023, Revised Selected Papers, Part I
Advancements in Smart Computing and Information Security : Second International Conference, ASCIS 2023, Rajkot, India, December 7-9, 2023, Revised Selected Papers, Part I
Autore Rajagopal Sridaran
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer International Publishing AG, , 2024
Descrizione fisica 1 online resource (509 pages)
Altri autori (Persone) PopatKalpesh
MevaDivyakant
BajejaSunil
Collana Communications in Computer and Information Science Series
ISBN 3-031-58604-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNINA-9910855395603321
Rajagopal Sridaran  
Cham : , : Springer International Publishing AG, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advancements in Smart Computing and Information Security : Second International Conference, ASCIS 2023, Rajkot, India, December 7-9, 2023, Revised Selected Papers, Part II
Advancements in Smart Computing and Information Security : Second International Conference, ASCIS 2023, Rajkot, India, December 7-9, 2023, Revised Selected Papers, Part II
Autore Rajagopal Sridaran
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer International Publishing AG, , 2024
Descrizione fisica 1 online resource (515 pages)
Altri autori (Persone) PopatKalpesh
MevaDivyakant
BajejaSunil
Collana Communications in Computer and Information Science Series
ISBN 3-031-59097-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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 II -- Artificial Intelligence and Machine Learning -- Classification of Rule Mining for Biomedical and Healthcare Data -- 1 Introduction -- 1.1 Specification of Software -- 1.2 Data Pre-processing -- 2 The Process of Classification Rule Mining -- 2.1 Random Forest Classifier Algorithm -- 2.2 Logistic Regression -- 2.3 Naive Bayes Algorithm -- 2.4 K-Nearest Neighbor Algorithm -- 3 Conclusion -- References -- Multimodal Sentiment Analysis Using Deep Learning: A Review -- 1 Introduction -- 2 Literature Review -- 3 Result and Discussion -- 4 Conclusion -- References -- Machine Learning Technique for Deteching Leaf Disease -- 1 Introduction -- 1.1 Rice Leaf Blast Diseases -- 1.2 Bacterial Blight Disease -- 1.3 Sheath Blight Disease -- 1.4 Brown Spot Disease -- 2 Related Works -- 3 Pre-trained CNN -- 3.1 Transfer Learning -- 3.2 Inception-v3 Model.
3.3 Factorization into Smaller Convolutions -- 3.4 Auxiliary Classifiers -- 4 Modeling the Features -- 4.1 Random Forest -- 5 Experimental Results -- 5.1 Datasets -- 5.2 Pre-trained Inception-v3 Used as a Feature Extractor -- 5.3 Classification Using Random Forest with Inception v3 -- 6 Conclusion -- References -- Cardio Vascular Disease Prediction Based on PCA-ReliefF Hybrid Feature Selection Method with SVM -- 1 Introduction -- 2 Types of CVDs -- 3 Significance of Computing Techniques in CVD Prediction -- 4 Related Works -- 5 Proposed Methodology -- 5.1 Dataset Collection and Preprocessing -- 5.2 Feature Extraction Techniques -- 5.3 Data Splitting -- 5.4 Classification -- 6 Results and Discussion -- 6.1 Dataset Description -- 6.2 Evaluation Metrics Analysis -- 7 Conclusion -- References -- DRL-CNN Technique for Diabetes Prediction -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Feature Selection -- 3.2 Decision Tree (DT) -- 3.3 Random Forest (RF) -- 3.4 Delta Rule Learning Based Optimized CNN(DRL-OCNN) -- 4 Result and Discussion -- 4.1 Dataset Description -- 4.2 PID (Pima Indians Diabetes) Dataset Analysis -- 5 Conclusion -- References -- A Novel Method for Predicting Kidney Disease using Optimized Multi-Layer Perceptron (PKD-OMLP) Classifier -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Z-score for Preprocessing -- 3.2 Feature Selection -- 3.3 Linear Regression (LR) -- 3.4 Support Vector Machine (SVM) -- 3.5 Multi-Layer Perceptron (MLP) -- 3.6 PKD-OMLP Classifier -- 4 Result and Discussions -- 4.1 Dataset Description -- 4.2 Chronic Kidney Disease (CKD) Analysis -- 5 Conclusion and Future Work -- References -- Classification of Heart Diseases Using Logistic Regression with Various Preprocessing Techniques -- 1 Introduction -- 2 Types of Heart Diseases.
3 Significance of Predicting Heart Diseases Using ML Models -- 4 Related Studies -- 5 Proposed Model -- 5.1 Data Collection -- 5.2 Preprocessing -- 5.3 Model Training -- 6 Results and Discussion -- 6.1 Heart Failure Clinical Records -- 6.2 Evaluation Metrics -- 7 Conclusion -- References -- Plant Disease Detection Automation Using Deep Neural Networks -- 1 Introduction -- 2 Literature Review -- 3 Base Architecture: ConvNet -- 3.1 Input Layer -- 3.2 Convolution and Pooling Layer -- 3.3 Fully Connected Layer -- 4 Approaches and Results -- 4.1 Dataset -- 4.2 Data Augmentation -- 4.3 Alexnet -- 4.4 Resnet-50 -- 4.5 Proposed Model: ProliferateNet -- 5 Prevention and Recommendation -- 6 Conclusion -- References -- CT and MRI Image Based Lung Cancer Feature Selection and Extraction Using Deep Learning Techniques -- 1 Introduction -- 2 Related Works -- 3 Proposed Model -- 4 Performance Analysis -- 5 Conclusion -- References -- Text Classification with Automatic Detection of COVID-19 Symptoms from Twitter Posts Using Natural Language Programming (NLP) -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 3.1 Dataset -- 3.2 Working of GRU and LSTM for Data Modeling -- 4 Experimental Results -- 5 Conclusion -- References -- A Novel Image Filtering and Enhancement Techniques for Detection of Cancer Blood Disorder -- 1 Introduction -- 2 Literature Survey -- 3 Materials and Methods -- 3.1 Image Preprocessing -- 4 Results and Discussion -- 4.1 Simulation Results -- 4.2 Evaluation of Filtering Algorithms -- 4.3 Peak Signal to Noise Ratio (PSNR) -- 5 Conclusion -- References -- Enhanced Oxygen Demand Prediction in Effluent Re-actors with ANN Modeling -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Architecture and Methodology -- 3.1 Data Pre-processing -- 3.2 Construction of the Model -- 3.3 Model Deployment in Cloud -- 4 Results and Conclusion.
References -- Comparative and Comprehensive Analysis of Cotton Crop Taxonomy Classification -- 1 Introduction -- 1.1 Overview of Indian Economy and Agriculture -- 1.2 Overview of Cotton Disease Detection -- 1.3 Role of Machine Learning Algorithm in Cotton Disease Detection -- 2 Recent Literature Findings -- 2.1 Literature Review -- 3 Comparative and Comprehensive Analysis -- 4 Discussion and Future Scope -- 5 Conclusion -- References -- Efficient College Students Higher Education Prediction Using Machine Learning Approaches -- 1 Introduction -- 2 Importance of ML in Student Performance Prediction -- 3 Problems in the Prediction Model -- 4 Literature Review -- 5 Proposed Methodology -- 5.1 Support Vector Machine (SVM) -- 5.2 Random Forest (RF) -- 5.3 Convolution Neural Network (CNN) -- 6 Result and Discussion -- 6.1 Accuracy Analysis -- 6.2 Precision -- 6.3 Recall -- 6.4 Precision and Recall Analysis -- 7 Outcome of the Prediction System -- 8 Conclusion and Future Work -- References -- Efficient Lung Cancer Segmentation Using Deep Learning-Based Models -- 1 Introduction -- 2 Traditional Lung Cancer Diagnostic Tests -- 3 Importance of Deep Learning in Lung Cancer Segmentation -- 4 Problem Definition -- 5 Literature Review -- 6 Proposed Methodology -- 6.1 U-Net -- 6.2 Mask R-CNN -- 6.3 V-Net -- 7 Results and Discussion -- 7.1 Dataset Description -- 7.2 Evaluation Metrics -- 8 Conclusion -- 9 Future Scope -- References -- CSDM-DEEP-CNN Based Skin Multi-function Disease Detection with Minimum Execution Time -- 1 Introduction -- 2 Related Works -- 3 CSDM Design and Implementation -- 3.1 Pre-processed Image -- 3.2 Input Image Size Process -- 3.3 Convolutional Neural Network Prediction Process -- 3.4 Optimization Process -- 4 Results and Discussion -- 5 Conclusion -- References.
Improving Skin Lesion Diagnosis: Hybrid Blur Detection for Accurate Dermatological Image Analysis -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Hybrid Blur Detection Method: Elliptical Fourier Analysis and Convolutional Neural Networks -- 3.2 Performance Evaluation of the Hybrid Method for Blur Region Identification and Localization -- 3.3 Clinical Impact and Utility Assessment of the Hybrid Method in Skin Lesion Diagnosis and Treatment Decision-Making -- 4 Experimental Results -- 5 Conclusion -- References -- Swarm Based Enhancement Optimization Method for Image Enhancement for Diabetic Retinopathy Detection -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Dataset -- 3.2 Geometrical Correction -- 3.3 RGB Color Space -- 3.4 Noise Elimination -- 3.5 Image Enhancement -- 4 Results and Discussion -- 4.1 Mean Square Error (MSE) Analysis -- 4.2 Peak Signal-to-Noise-Ratio (PSNR) -- 4.3 Structure Similarity Index Measure (SSIM) -- 5 Conclusion and Future Work -- References -- Classification of Intrusion Using CNN with IQR (Inter Quartile Range) Approach -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 3.1 SMOTE -- 3.2 Z-SCORE -- 3.3 Inter Quartile Range (IQR) -- 3.4 CNN -- 4 Results and Discussion -- 4.1 UCI Cyber Hacking Dataset -- 4.2 Accuracy Analysis -- 4.3 Precision Analysis -- 4.4 Recall Analysis -- 4.5 F-Measure Analysis -- 5 Conclusion -- 6 Future Enhancement -- References -- Enhancing Heart Disease Prediction Using Artificial Neural Network with Preprocessing Techniques -- 1 Introduction -- 2 Related Works -- 3 Objectives -- 4 Proposed Methodology -- 4.1 Input Dataset -- 4.2 Preprocessing -- 4.3 Z-Score Normalization (ZS) -- 4.4 Interquartile Range (IQR) -- 4.5 Synthetic Minority Over-Sampling Technique (SMOTE) -- 4.6 Artificial Neural Network (ANN) -- 5 Results and Discussion.
5.1 Evaluation Metrics.
Record Nr. UNINA-9910855366703321
Rajagopal Sridaran  
Cham : , : Springer International Publishing AG, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advancements in smart computing and information security : first international conference, ASCIS 2022, Rajkot, India, November 24-26, 2022, revised selected papers, part I / / edited by Sridaran Rajagopal, Parvez Faruki, Kalpesh Popat
Advancements in smart computing and information security : first international conference, ASCIS 2022, Rajkot, India, November 24-26, 2022, revised selected papers, part I / / edited by Sridaran Rajagopal, Parvez Faruki, Kalpesh Popat
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (482 pages)
Disciplina 943.005
Collana Communications in Computer and Information Science
Soggetto topico Electronic data processing
Punched card systems
ISBN 3-031-23092-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynotes -- Post-pandemic Applications of AI and Machine Learning -- Smart and Soft Computing Methods for Prioritizing Software Requirements in Large-Scale Software Projects -- Your Readiness for Industry 4.0 -- Securing NexGen Automotives - Threats and Trends -- Cyber Attacks Classification and Attack Handling Methods Using Machine Learning Methods -- The Internet of Things (IoT) Ecosystem Revolution in the World of Global Sports -- Orchestration of Containers: Role of Artificial Intelligence -- Enterprise Cybersecurity Strategies in the Cloud -- Contents - Part I -- Contents - Part II -- Artificial Intelligence -- Galaxy Classification Using Deep Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset Collection -- 3.2 Proposed Deep Galaxies CNN Model -- 3.3 Overview of Algorithms -- 4 Comparative Results -- 4.1 Model Accuracy -- 5 Conclusion and Future Scope -- References -- Word Sense Disambiguation for Hindi Language Using Neural Network -- 1 Introduction -- 2 Related Work -- 2.1 Background -- 2.2 Variants of Word Sense Disambiguation Work -- 2.3 Existing Approaches for Disambiguation -- 3 Proposed Approach for WSD -- 3.1 Architecture of the Proposed WSD Model -- 3.2 Implementation Details -- 4 Result Discussion -- 5 Conclusion and Future Directions -- References -- Social Media Addiction: Analysis on Impact of Self-esteem and Recommending Methods to Reduce Addiction -- 1 Introduction -- 2 Related Work -- 3 Measures -- 3.1 Bergen Social Media Addiction Scale (BSMAS) [5] -- 3.2 Rosenberg Self-esteem Scale (RSES) [5] -- 3.3 Recommendation Methods [14, 15] -- 3.4 Dataset Collection 1 -- 3.5 Dataset Collection 2 -- 4 Proposed Methodology -- 4.1 Statistical Analysis -- 4.2 Recommendation System -- 5 Results and Discussion -- 5.1 Statistical Analysis.
5.2 Recommendation System -- 6 Conclusion -- References -- A Combined Method for Document Image Enhancement Using Image Smoothing, Gray-Level Reduction and Thresholding -- 1 Introduction -- 2 Types of Noises -- 2.1 Speckle Noise -- 2.2 Gaussian Noise -- 2.3 Salt and Pepper Noise -- 3 Proposed Work for Document Image Enhancement -- 3.1 Edge Preserving Image Smoothing -- 3.2 Gray Level Reduction -- 3.3 Image Thresholding Using Otsu's Method -- 4 Experimentation and Results -- 5 Conclusions and Future Work -- References -- A Comparative Assessment of Deep Learning Approaches for Opinion Mining -- 1 Introduction -- 2 Literature Review -- 3 Tools for Opinion Mining -- 4 Deep Learning Techniques -- 4.1 Convolutional Neural Network (CNN) -- 4.2 Recurrent Neural Network (RNN) -- 4.3 Long Short Term Memory (LSTM) -- 4.4 Deep Neural Networks (DNN) -- 4.5 Deep Belief Networks (DBN) -- 4.6 Recursive Neural Network (RECNN) -- 4.7 Hybrid Neural Network -- 5 System Architecture -- 6 Advantages of Deep Learning -- 7 When to Use Deep Learning -- 8 Disadvantages of Deep Learning -- 9 Conclusion -- References -- Performance Enhancement in WSN Through Fuzzy C-Means Based Hybrid Clustering (FCMHC) -- 1 Introduction -- 2 Related Work -- 3 Network Model -- 3.1 Radio Model -- 3.2 Assumptions -- 4 Proposed Algorithm -- 4.1 Cluster Formation Phase -- 4.2 Cluster Head Selection Phase -- 4.3 Communication Phase -- 5 Analytical Evaluation of Performance -- 5.1 Performance Metrics -- 5.2 Simulation Parameters -- 5.3 Results and Discussion -- 6 Conclusion -- References -- A Review of Gait Analysis Based on Age and Gender Prediction -- 1 Introduction -- 2 Gait Analysis and Feature Extraction -- 2.1 Gait and Gait Cycle -- 2.2 Gait and Gait Cycle -- 2.3 Gait and Gait Cycle -- 2.4 Motivation and Application of GEI Motivation -- 3 Evolution Metric -- 4 Related Work.
5 Comparison and Summary of Related Research Work -- 6 Future Work -- 7 Limitations and Challenges -- 8 Conclusion -- References -- Handwritten Signature Verification Using Convolution Neural Network (CNN) -- 1 Introduction -- 1.1 About the Domain -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Converting Image to Binary -- 3.2 Noise Removal -- 3.3 Image Enlargement -- 4 Feature Extraction -- 5 Feature Selection -- 6 Classification -- 7 Conclusion and Future Work -- References -- Comparative Analysis of Energy Consumption in Text Processing Models -- 1 Introduction -- 2 Existing Approaches -- 3 Exploration of the Data-Set -- 3.1 Average Word Length -- 3.2 Average Character Length -- 3.3 Number of Comments -- 4 Modelling -- 4.1 Simple Machine Learning Model -- 4.2 DistilBERT Model -- 4.3 Conv1D Model -- 4.4 Gated Recurrence Unit - GRU Model -- 5 Results -- 6 Conclusion -- References -- Evolution Towards 6G Wireless Networks: A Resource Allocation Perspective with Deep Learning Approach - A Review -- 1 Introduction -- 1.1 6G Vision -- 1.2 Technical Objectives of 6G -- 2 Resource Allocation for 6G Wireless Networks -- 3 Summary of Deep Learning Algorithms Used for 6G Wireless Networks Resource Allocation -- 4 Conclusion and Future Scope -- Appendix -- References -- Automation of Rice Leaf Diseases Prediction Using Deep Learning Hybrid Model VVIR -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 Results -- 5 Discussion -- References -- A Review Based on Machine Learning for Feature Selection and Feature Extraction -- 1 Introduction -- 2 Preliminaries -- 2.1 Feature Selection -- 2.2 Reducing the Dimensionality -- 3 Related Works -- 3.1 Feature Selection Approaches -- 3.2 Feature Extraction Approaches -- 4 Discussion -- 5 Conclusion -- References -- Automating Scorecard and Commentary Based on Umpire Gesture Recognition -- 1 Introduction.
2 Literature Survey -- 3 Methodology -- 3.1 Umpire Gestures -- 3.2 Dataset -- 3.3 Feature Extraction -- 3.4 Classification of Umpire Gestures -- 3.5 Scorecard Updating Feature -- 4 Results and Discussion -- 5 Conclusion -- References -- Rating YouTube Videos: An Improvised and Effective Approach -- 1 Introduction -- 2 Previous Work -- 3 Implementation -- 3.1 Comment Collection and Preprocessing -- 3.2 Sentiment Measure -- 3.3 Word Cloud -- 3.4 Video Rating -- 4 Performance Review of Proposed Approach -- 4.1 Major Application: Detection of Clickbait Videos -- 5 Limitations and Loopholes -- 6 Result -- 7 Conclusion -- 8 Future Work -- References -- Classification of Tweet on Disaster Management Using Random Forest -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Preprocessing -- 3.2 Training, Validation and Testing -- 3.3 Feature Extraction -- 3.4 Random Forest Classification -- 3.5 Location Extraction -- 4 Results and Discussions -- 5 Datasets -- 6 Experiment -- 7 Validation -- 8 Conclusions -- References -- Numerical Investigation of Dynamic Stress Distribution in a Railway Embankment Reinforced by Geogrid Based Weak Soil Formation Using Hybrid RNN-EHO -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Model Clay Barrier's Compositional Characteristics -- 2.2 Geogrid -- 2.3 Measuring Subgrade Stiffness -- 2.4 Multi Objective Function -- 2.5 Improving Settlement-Based Geogrid using Hybrid RNN-EHO Technique -- 2.6 The Procedure of the EHO in Realizing the Learning of RNN -- 3 Results and Discussion -- 3.1 Uncertainty Analysis -- 4 Conclusion -- References -- Efficient Intrusion Detection and Classification Using Enhanced MLP Deep Learning Model -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 4 Results and Discussion -- 5 Conclusion -- References.
Classification of Medical Datasets Using Optimal Feature Selection Method with Multi-support Vector Machine -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Results and Discussions -- 5 Conclusions -- References -- Predicting Students' Outcomes with Respect to Trust, Perception, and Usefulness of Their Instructors in Academic Help Seeking Using Fuzzy Logic Approach -- 1 Introduction -- 2 Literature Review -- 3 Proposed Work -- 4 Results and Discussions -- 5 Conclusion -- References -- Smart Computing -- Automatic Cotton Leaf Disease Classification and Detection by Convolutional Neural Network -- 1 Introduction -- 2 Literature Review -- 3 List of Cotton Diseases -- 4 Materials and Methods -- 4.1 Dataset and Data Augmentation -- 4.2 CNN Pre-trained Architectures -- 4.3 Classification by Proposed CNN -- 5 Results and Discussions of Research -- 5.1 Pre-trained Model -- 6 Conclusion -- References -- Analytical Review and Study on Emotion Recognition Strategies Using Multimodal Signals -- 1 Introduction -- 2 Literature Survey -- 2.1 Classification of Emotion Recognition Strategies -- 3 Research Gaps and Issues -- 4 Analysis and Discussion -- 4.1 Analysis with Respect to Publication years -- 4.2 Analysis on the Basis of Strategies -- 4.3 Analysis on the Basis of Implementation Tool -- 4.4 Analysis in Terms of Employed Datasets -- 4.5 Analysis on the Basis of Evaluation Measures -- 4.6 Analysis Using Evaluation Measures Values -- 5 Conclusion -- References -- An Image Performance Against Normal, Grayscale and Color Spaced Images -- 1 Introduction -- 2 Overview of Image Matching Techniques -- 2.1 SIFT -- 2.2 SURF -- 2.3 ORB -- 3 Experimental Results -- 3.1 L*A*B* Color Space -- 4 Conclusion -- References -- Study of X Ray Detection Using CNN in Machine Learning -- 1 Introduction -- 2 Literature Review -- 2.1 Methods.
3 Algorithm CNN Model Algorithm Model = Sequential().
Record Nr. UNINA-9910644261503321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advancements in smart computing and information security : first international conference, ASCIS 2022, Rajkot, India, November 24-26, 2022, revised selected papers, part II / / edited by Sridaran Rajagopal, Parvez Faruki, Kalpesh Popat
Advancements in smart computing and information security : first international conference, ASCIS 2022, Rajkot, India, November 24-26, 2022, revised selected papers, part II / / edited by Sridaran Rajagopal, Parvez Faruki, Kalpesh Popat
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (315 pages)
Disciplina 330
Collana Communications in Computer and Information Science
Soggetto topico Hardware
ISBN 3-031-23095-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynotes -- Post-pandemic Applications of AI and Machine Learning -- Smart and Soft Computing Methods for Prioritizing Software Requirements in Large-Scale Software Projects -- Your Readiness for Industry 4.0 -- Securing NexGen Automotives - Threats and Trends -- Cyber Attacks Classification and Attack Handling Methods Using Machine Learning Methods -- The Internet of Things (IoT) Ecosystem Revolution in the World of Global Sports -- Orchestration of Containers: Role of Artificial Intelligence -- Enterprise Cybersecurity Strategies in the Cloud -- Contents - Part II -- Contents - Part I -- Cyber Security -- A Comprehensive Study on Cyber Legislation in G20 Countries -- 1 Introduction -- 2 Literature Review -- 2.1 Argentina -- 2.2 Australia -- 2.3 Brazil -- 2.4 Canada -- 2.5 China -- 2.6 France -- 2.7 Germany -- 2.8 India -- 2.9 Indonesia -- 2.10 Italy -- 2.11 Japan -- 2.12 South Korea -- 2.13 Mexico -- 2.14 Russia -- 2.15 Saudi Arabia -- 2.16 South Africa -- 2.17 Turkey -- 2.18 United Kingdom -- 2.19 United State of America -- 2.20 European Union -- 3 Conclusions -- References -- Image Encryption Algorithm Based on Timeout, Pixel Transposition and Modified Fisher-Yates Shuffling -- 1 Introduction -- 2 Proposed Work -- 2.1 Key Generation -- 2.2 Encryption Process -- 2.3 Decryption Process -- 3 Library and Packages -- 4 Performance Analysis and Results -- 4.1 NPCR & -- UACI Test -- 4.2 Mean Square Error (MSE) -- 4.3 Root Mean Square Error (RMSE) -- 4.4 Peak Signal to Noise Ratio (PSNR) -- 4.5 Key Space Analysis -- 4.6 Key Sensitivity Test -- 4.7 Encryption Time -- 4.8 Correlation Analysis -- 4.9 Mono-bit Test -- 4.10 Entropy Analysis -- 4.11 Average Difference (AD) and Maximum Difference (MD) -- 4.12 Structural Content (SC) -- 5 Conclusion -- References.
EXAM: Explainable Models for Analyzing Malicious Android Applications -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Data Set Preparation -- 3.2 Feature Extraction -- 3.3 Pre-processing the Feature Set and FVT Creation -- 3.4 Model Preparation and Classification -- 3.5 Obfuscation of Samples -- 3.6 Interpretation of Results Using SHAP -- 4 Experiments and Results -- 4.1 Evaluation Measures -- 4.2 Research Questions -- 4.3 Comparison with State-of-the-Art Approaches -- 5 Conclusion -- References -- Data Encryption Approach Using Hybrid Cryptography and Steganography with Combination of Block Ciphers -- 1 Introduction -- 1.1 Research Contribution -- 1.2 Paper Organisation -- 2 Related Work in the Domain -- 3 Proposed Methodology -- 4 Results and Discussions -- 5 Conclusion -- References -- Mitigation and Prevention Methods for Distributed Denial-of-Service Attacks on Network Servers -- 1 Introduction -- 2 Proposed Survey -- 2.1 Motivation for DDoS Attacks -- 2.2 Attack Strategies and Phases -- 2.3 Attack Methods -- 3 Prevention Methods -- 3.1 Prevention Using Filters -- 3.2 Secure Overlay -- 3.3 Honeypots -- 3.4 Load Balancing -- 3.5 Additional Security Patches -- 4 DDoS Mitigation Methods -- 4.1 Detection of DDoS Attacks -- 5 Conclusion -- References -- A Machine Learning Framework for Automatic Detection of Malware -- 1 Introduction -- 2 Literature Review -- 3 Proposed Framework -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- DNNdroid: Android Malware Detection Framework Based on Federated Learning and Edge Computing -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 4 Machine Learning Technique -- 5 Proposed Framework Architecture -- 6 Evaluation of Proposed Framework -- 7 Comparison of Proposed Framework -- 7.1 Comparison on the Basis of Framework Available in the Literature.
7.2 Comparison of the Proposed Framework with Different Anti-virus Scanners -- 8 Experimental Findings -- 9 Conclusion -- References -- An Improved Symmetric Key Encryption Method Using Randomized Matrix Generation -- 1 Introduction -- 2 Types of Encryption Technique -- 2.1 AES -- 2.2 DES -- 2.3 Blowfish -- 3 Proposed Technique -- 3.1 Random Key Generation Algorithm -- 3.2 Text Message Encryption Algorithm -- 3.3 Text Message Decryption Algorithm -- 4 Matrix Operations -- 4.1 Matrix Determinant -- 4.2 Matrix Multiplication -- 4.3 Matrix Transpose Operation -- 5 Performance Analysis -- 5.1 Implementation of System -- 5.2 Text Encryption Algorithms Performance Analysis -- 5.3 Analysis of Complexity for Random Key Generation -- 5.4 Analysis of Execution Time -- 5.5 Analysis of Throughput -- 6 Conclusion -- References -- Performance Analyses of Black Hole Attack in AODV Routing Protocol in Vanet Using NS3 -- 1 Introduction -- 1.1 AODV Routing Protocol -- 1.2 Black Hole Attack -- 1.3 Literature Survey -- 1.4 Simulation Set-Up -- 1.5 Result Analyses -- 1.6 Conclusion -- References -- Comparative Analysis of Several Approaches of Encoding Audio Files -- 1 Introduction -- 2 Overview of Cryptography -- 3 Aims of Cryptography -- 3.1 The Many Forms that Cryptography Can Take -- 4 Cryptographic Algorithms at a Glance -- 4.1 DES -- 4.2 3DES -- 4.3 AES -- 4.4 Blowfish -- 4.5 RC4 -- 4.6 Twofish -- 4.7 ThreeFish -- 5 Background and Related Works -- 5.1 Related Research and Development on Audio Encryption -- 6 Recent Works on Audio Encryption -- 7 Limitations -- 8 Conclusion -- References -- A Secure Mechanism for Safeguarding Cloud Infrastructure -- 1 Introduction -- 2 Literature Review -- 3 Types of Security in Cloud Computing -- 3.1 Information Security -- 3.2 Identity Security -- 3.3 Network Security -- 3.4 Software Security -- 3.5 Infrastructure Security.
4 Security Concerns in Cloud -- 4.1 Virtualization -- 4.2 Public-Cloud Storage -- 4.3 Multitenancy -- 4.4 Identity and Access Management (IAM) -- 5 Security of Data in Cloud-Computing -- 6 Major Security Challenges -- 6.1 Internal Attacks -- 6.2 Partial/Incomplete Data Deletion -- 6.3 Interception of Data -- 6.4 Failure of Isolation -- 7 Using Encryption for Data Protection -- 7.1 Block-Cipher -- 7.2 Stream Ciphers -- 7.3 Hash Functions -- 8 Case Study on Cloud Based Cyber Security Model for Identification of Safe and Malicious Request -- 9 Conclusion -- References -- Phishing URLs Detection Using Machine Learning -- 1 Introduction -- 2 Related Work -- 2.1 Literature Review -- 2.2 URLs Descriptions -- 3 Research Methodology -- 4 Result and Analysis -- 4.1 Result -- 4.2 Analysis -- 5 Conclusion -- References -- Android Malware Detection with Classification Based on Hybrid Analysis and N-gram Feature Extraction -- 1 Introduction -- 1.1 Average Cost of a Data Breach -- 1.2 Growth Rate of Malware Infections -- 1.3 India and Asia Statistics on Malware Attacks -- 1.4 Trends in the Number of Attacks -- 1.5 Users Attacked by Malware -- 2 Research Objective/Problem Statement -- 3 Challenges in Malware Detection -- 4 Theoretical Framework -- 5 Hypothesis Declaration -- 6 Methodology -- 7 Approach -- 8 Outline of the Work Proposed -- 8.1 Process for the Proposed Scheme of Work -- 9 Conclusion -- 10 Further Research -- References -- Industry -- Image Processing and Deep Neural Networks for Face Mask Detection -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 3.1 Machine Learning Approach -- 3.2 Supervised Learning -- 3.3 Unsupervised Learning -- 3.4 Viola Jones algorithm -- 4 Mathematical Formulation -- 5 Results and Discussion -- 6 Conclusion -- References -- An Analysis of Lightweight Cryptographic Algorithms for IoT-Applications.
1 Introduction -- 2 Introduction of IoT -- 3 Software and Hardware Performance Metrics -- 4 Research Directions and Open Research Challenges -- 5 Conclusion -- Appendix 1 -- Hardware and Software Performances of LWC Algorithm -- References -- Permissioned Blockchain-Based Solution to Document Processing in the Real Estate Industry -- 1 Introduction -- 1.1 Blockchain Technology -- 1.2 Indian Real Estate Sector -- 1.3 Impact of Blockchain Technology on the Indian Real Estate Sector -- 2 Related Research Work and Limitations -- 2.1 Summarization of Recent Research Work -- 2.2 Research Gap -- 3 Proposed Research Work -- 3.1 Designed Framework and Components -- 3.2 Core Transaction Process Flow -- 3.3 Proposed Algorithms -- 3.4 Deployment -- 4 Conclusion and Future Scope -- References -- Automatic Evaluation of Free Text Answers: A Review -- 1 Introduction -- 2 Related Work -- 3 A Systematic Review -- 4 Discussion -- 5 Conclusions and Future Work -- References -- Blockchain Federated Learning Framework for Privacy-Preservation -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 4 Performance Evaluation -- 4.1 Datasets -- 4.2 Simulation Setup -- 4.3 Evaluation Metrics -- 4.4 Results and Discussion -- 5 Conclusion -- References -- Path Planning and Static Obstacle Avoidance for Unmanned Aerial Systems -- 1 Introduction -- 2 Methodology -- 2.1 A* Search -- 2.2 Rapidly-Exploring Random Tree -- 2.3 Ant Colony Optimization -- 2.4 Imitation Learning -- 3 Results and Discussion -- 4 Conclusion and Future Work -- References -- Comparative Study of Various Algorithms for Vehicle Detection and Counting in Traffic -- 1 Introduction -- 2 Literature Review -- 2.1 YOLO Real-Time Object Tracking -- 3 Methodology -- 3.1 YOLOv3 Architecture -- 3.2 YOLOv4 Architecture -- 3.3 YOLOv5 Architecture -- 3.4 YOLOv6 Architecture -- 3.5 YOLOv7 Architecture.
4 Results and Discussion.
Record Nr. UNISA-996508667503316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advancements in smart computing and information security : first international conference, ASCIS 2022, Rajkot, India, November 24-26, 2022, revised selected papers, part I / / edited by Sridaran Rajagopal, Parvez Faruki, Kalpesh Popat
Advancements in smart computing and information security : first international conference, ASCIS 2022, Rajkot, India, November 24-26, 2022, revised selected papers, part I / / edited by Sridaran Rajagopal, Parvez Faruki, Kalpesh Popat
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (482 pages)
Disciplina 943.005
Collana Communications in Computer and Information Science
Soggetto topico Electronic data processing
Punched card systems
ISBN 3-031-23092-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynotes -- Post-pandemic Applications of AI and Machine Learning -- Smart and Soft Computing Methods for Prioritizing Software Requirements in Large-Scale Software Projects -- Your Readiness for Industry 4.0 -- Securing NexGen Automotives - Threats and Trends -- Cyber Attacks Classification and Attack Handling Methods Using Machine Learning Methods -- The Internet of Things (IoT) Ecosystem Revolution in the World of Global Sports -- Orchestration of Containers: Role of Artificial Intelligence -- Enterprise Cybersecurity Strategies in the Cloud -- Contents - Part I -- Contents - Part II -- Artificial Intelligence -- Galaxy Classification Using Deep Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset Collection -- 3.2 Proposed Deep Galaxies CNN Model -- 3.3 Overview of Algorithms -- 4 Comparative Results -- 4.1 Model Accuracy -- 5 Conclusion and Future Scope -- References -- Word Sense Disambiguation for Hindi Language Using Neural Network -- 1 Introduction -- 2 Related Work -- 2.1 Background -- 2.2 Variants of Word Sense Disambiguation Work -- 2.3 Existing Approaches for Disambiguation -- 3 Proposed Approach for WSD -- 3.1 Architecture of the Proposed WSD Model -- 3.2 Implementation Details -- 4 Result Discussion -- 5 Conclusion and Future Directions -- References -- Social Media Addiction: Analysis on Impact of Self-esteem and Recommending Methods to Reduce Addiction -- 1 Introduction -- 2 Related Work -- 3 Measures -- 3.1 Bergen Social Media Addiction Scale (BSMAS) [5] -- 3.2 Rosenberg Self-esteem Scale (RSES) [5] -- 3.3 Recommendation Methods [14, 15] -- 3.4 Dataset Collection 1 -- 3.5 Dataset Collection 2 -- 4 Proposed Methodology -- 4.1 Statistical Analysis -- 4.2 Recommendation System -- 5 Results and Discussion -- 5.1 Statistical Analysis.
5.2 Recommendation System -- 6 Conclusion -- References -- A Combined Method for Document Image Enhancement Using Image Smoothing, Gray-Level Reduction and Thresholding -- 1 Introduction -- 2 Types of Noises -- 2.1 Speckle Noise -- 2.2 Gaussian Noise -- 2.3 Salt and Pepper Noise -- 3 Proposed Work for Document Image Enhancement -- 3.1 Edge Preserving Image Smoothing -- 3.2 Gray Level Reduction -- 3.3 Image Thresholding Using Otsu's Method -- 4 Experimentation and Results -- 5 Conclusions and Future Work -- References -- A Comparative Assessment of Deep Learning Approaches for Opinion Mining -- 1 Introduction -- 2 Literature Review -- 3 Tools for Opinion Mining -- 4 Deep Learning Techniques -- 4.1 Convolutional Neural Network (CNN) -- 4.2 Recurrent Neural Network (RNN) -- 4.3 Long Short Term Memory (LSTM) -- 4.4 Deep Neural Networks (DNN) -- 4.5 Deep Belief Networks (DBN) -- 4.6 Recursive Neural Network (RECNN) -- 4.7 Hybrid Neural Network -- 5 System Architecture -- 6 Advantages of Deep Learning -- 7 When to Use Deep Learning -- 8 Disadvantages of Deep Learning -- 9 Conclusion -- References -- Performance Enhancement in WSN Through Fuzzy C-Means Based Hybrid Clustering (FCMHC) -- 1 Introduction -- 2 Related Work -- 3 Network Model -- 3.1 Radio Model -- 3.2 Assumptions -- 4 Proposed Algorithm -- 4.1 Cluster Formation Phase -- 4.2 Cluster Head Selection Phase -- 4.3 Communication Phase -- 5 Analytical Evaluation of Performance -- 5.1 Performance Metrics -- 5.2 Simulation Parameters -- 5.3 Results and Discussion -- 6 Conclusion -- References -- A Review of Gait Analysis Based on Age and Gender Prediction -- 1 Introduction -- 2 Gait Analysis and Feature Extraction -- 2.1 Gait and Gait Cycle -- 2.2 Gait and Gait Cycle -- 2.3 Gait and Gait Cycle -- 2.4 Motivation and Application of GEI Motivation -- 3 Evolution Metric -- 4 Related Work.
5 Comparison and Summary of Related Research Work -- 6 Future Work -- 7 Limitations and Challenges -- 8 Conclusion -- References -- Handwritten Signature Verification Using Convolution Neural Network (CNN) -- 1 Introduction -- 1.1 About the Domain -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Converting Image to Binary -- 3.2 Noise Removal -- 3.3 Image Enlargement -- 4 Feature Extraction -- 5 Feature Selection -- 6 Classification -- 7 Conclusion and Future Work -- References -- Comparative Analysis of Energy Consumption in Text Processing Models -- 1 Introduction -- 2 Existing Approaches -- 3 Exploration of the Data-Set -- 3.1 Average Word Length -- 3.2 Average Character Length -- 3.3 Number of Comments -- 4 Modelling -- 4.1 Simple Machine Learning Model -- 4.2 DistilBERT Model -- 4.3 Conv1D Model -- 4.4 Gated Recurrence Unit - GRU Model -- 5 Results -- 6 Conclusion -- References -- Evolution Towards 6G Wireless Networks: A Resource Allocation Perspective with Deep Learning Approach - A Review -- 1 Introduction -- 1.1 6G Vision -- 1.2 Technical Objectives of 6G -- 2 Resource Allocation for 6G Wireless Networks -- 3 Summary of Deep Learning Algorithms Used for 6G Wireless Networks Resource Allocation -- 4 Conclusion and Future Scope -- Appendix -- References -- Automation of Rice Leaf Diseases Prediction Using Deep Learning Hybrid Model VVIR -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 Results -- 5 Discussion -- References -- A Review Based on Machine Learning for Feature Selection and Feature Extraction -- 1 Introduction -- 2 Preliminaries -- 2.1 Feature Selection -- 2.2 Reducing the Dimensionality -- 3 Related Works -- 3.1 Feature Selection Approaches -- 3.2 Feature Extraction Approaches -- 4 Discussion -- 5 Conclusion -- References -- Automating Scorecard and Commentary Based on Umpire Gesture Recognition -- 1 Introduction.
2 Literature Survey -- 3 Methodology -- 3.1 Umpire Gestures -- 3.2 Dataset -- 3.3 Feature Extraction -- 3.4 Classification of Umpire Gestures -- 3.5 Scorecard Updating Feature -- 4 Results and Discussion -- 5 Conclusion -- References -- Rating YouTube Videos: An Improvised and Effective Approach -- 1 Introduction -- 2 Previous Work -- 3 Implementation -- 3.1 Comment Collection and Preprocessing -- 3.2 Sentiment Measure -- 3.3 Word Cloud -- 3.4 Video Rating -- 4 Performance Review of Proposed Approach -- 4.1 Major Application: Detection of Clickbait Videos -- 5 Limitations and Loopholes -- 6 Result -- 7 Conclusion -- 8 Future Work -- References -- Classification of Tweet on Disaster Management Using Random Forest -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Preprocessing -- 3.2 Training, Validation and Testing -- 3.3 Feature Extraction -- 3.4 Random Forest Classification -- 3.5 Location Extraction -- 4 Results and Discussions -- 5 Datasets -- 6 Experiment -- 7 Validation -- 8 Conclusions -- References -- Numerical Investigation of Dynamic Stress Distribution in a Railway Embankment Reinforced by Geogrid Based Weak Soil Formation Using Hybrid RNN-EHO -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Model Clay Barrier's Compositional Characteristics -- 2.2 Geogrid -- 2.3 Measuring Subgrade Stiffness -- 2.4 Multi Objective Function -- 2.5 Improving Settlement-Based Geogrid using Hybrid RNN-EHO Technique -- 2.6 The Procedure of the EHO in Realizing the Learning of RNN -- 3 Results and Discussion -- 3.1 Uncertainty Analysis -- 4 Conclusion -- References -- Efficient Intrusion Detection and Classification Using Enhanced MLP Deep Learning Model -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 4 Results and Discussion -- 5 Conclusion -- References.
Classification of Medical Datasets Using Optimal Feature Selection Method with Multi-support Vector Machine -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Results and Discussions -- 5 Conclusions -- References -- Predicting Students' Outcomes with Respect to Trust, Perception, and Usefulness of Their Instructors in Academic Help Seeking Using Fuzzy Logic Approach -- 1 Introduction -- 2 Literature Review -- 3 Proposed Work -- 4 Results and Discussions -- 5 Conclusion -- References -- Smart Computing -- Automatic Cotton Leaf Disease Classification and Detection by Convolutional Neural Network -- 1 Introduction -- 2 Literature Review -- 3 List of Cotton Diseases -- 4 Materials and Methods -- 4.1 Dataset and Data Augmentation -- 4.2 CNN Pre-trained Architectures -- 4.3 Classification by Proposed CNN -- 5 Results and Discussions of Research -- 5.1 Pre-trained Model -- 6 Conclusion -- References -- Analytical Review and Study on Emotion Recognition Strategies Using Multimodal Signals -- 1 Introduction -- 2 Literature Survey -- 2.1 Classification of Emotion Recognition Strategies -- 3 Research Gaps and Issues -- 4 Analysis and Discussion -- 4.1 Analysis with Respect to Publication years -- 4.2 Analysis on the Basis of Strategies -- 4.3 Analysis on the Basis of Implementation Tool -- 4.4 Analysis in Terms of Employed Datasets -- 4.5 Analysis on the Basis of Evaluation Measures -- 4.6 Analysis Using Evaluation Measures Values -- 5 Conclusion -- References -- An Image Performance Against Normal, Grayscale and Color Spaced Images -- 1 Introduction -- 2 Overview of Image Matching Techniques -- 2.1 SIFT -- 2.2 SURF -- 2.3 ORB -- 3 Experimental Results -- 3.1 L*A*B* Color Space -- 4 Conclusion -- References -- Study of X Ray Detection Using CNN in Machine Learning -- 1 Introduction -- 2 Literature Review -- 2.1 Methods.
3 Algorithm CNN Model Algorithm Model = Sequential().
Record Nr. UNISA-996508667303316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advancements in Smart Computing and Information Security : First International Conference, ASCIS 2022, Rajkot, India, November 24–26, 2022, Revised Selected Papers, Part II / / edited by Sridaran Rajagopal, Parvez Faruki, Kalpesh Popat
Advancements in Smart Computing and Information Security : First International Conference, ASCIS 2022, Rajkot, India, November 24–26, 2022, Revised Selected Papers, Part II / / edited by Sridaran Rajagopal, Parvez Faruki, Kalpesh Popat
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022
Descrizione fisica 1 online resource (315 pages)
Disciplina 330
006.3
Collana Communications in Computer and Information Science
Soggetto topico Artificial intelligence
Computer networks
Computer systems
Coding theory
Information theory
Application software
Data protection
Artificial Intelligence
Computer Communication Networks
Computer System Implementation
Coding and Information Theory
Computer and Information Systems Applications
Data and Information Security
ISBN 3-031-23095-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynotes -- Post-pandemic Applications of AI and Machine Learning -- Smart and Soft Computing Methods for Prioritizing Software Requirements in Large-Scale Software Projects -- Your Readiness for Industry 4.0 -- Securing NexGen Automotives - Threats and Trends -- Cyber Attacks Classification and Attack Handling Methods Using Machine Learning Methods -- The Internet of Things (IoT) Ecosystem Revolution in the World of Global Sports -- Orchestration of Containers: Role of Artificial Intelligence -- Enterprise Cybersecurity Strategies in the Cloud -- Contents - Part II -- Contents - Part I -- Cyber Security -- A Comprehensive Study on Cyber Legislation in G20 Countries -- 1 Introduction -- 2 Literature Review -- 2.1 Argentina -- 2.2 Australia -- 2.3 Brazil -- 2.4 Canada -- 2.5 China -- 2.6 France -- 2.7 Germany -- 2.8 India -- 2.9 Indonesia -- 2.10 Italy -- 2.11 Japan -- 2.12 South Korea -- 2.13 Mexico -- 2.14 Russia -- 2.15 Saudi Arabia -- 2.16 South Africa -- 2.17 Turkey -- 2.18 United Kingdom -- 2.19 United State of America -- 2.20 European Union -- 3 Conclusions -- References -- Image Encryption Algorithm Based on Timeout, Pixel Transposition and Modified Fisher-Yates Shuffling -- 1 Introduction -- 2 Proposed Work -- 2.1 Key Generation -- 2.2 Encryption Process -- 2.3 Decryption Process -- 3 Library and Packages -- 4 Performance Analysis and Results -- 4.1 NPCR & -- UACI Test -- 4.2 Mean Square Error (MSE) -- 4.3 Root Mean Square Error (RMSE) -- 4.4 Peak Signal to Noise Ratio (PSNR) -- 4.5 Key Space Analysis -- 4.6 Key Sensitivity Test -- 4.7 Encryption Time -- 4.8 Correlation Analysis -- 4.9 Mono-bit Test -- 4.10 Entropy Analysis -- 4.11 Average Difference (AD) and Maximum Difference (MD) -- 4.12 Structural Content (SC) -- 5 Conclusion -- References.
EXAM: Explainable Models for Analyzing Malicious Android Applications -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Data Set Preparation -- 3.2 Feature Extraction -- 3.3 Pre-processing the Feature Set and FVT Creation -- 3.4 Model Preparation and Classification -- 3.5 Obfuscation of Samples -- 3.6 Interpretation of Results Using SHAP -- 4 Experiments and Results -- 4.1 Evaluation Measures -- 4.2 Research Questions -- 4.3 Comparison with State-of-the-Art Approaches -- 5 Conclusion -- References -- Data Encryption Approach Using Hybrid Cryptography and Steganography with Combination of Block Ciphers -- 1 Introduction -- 1.1 Research Contribution -- 1.2 Paper Organisation -- 2 Related Work in the Domain -- 3 Proposed Methodology -- 4 Results and Discussions -- 5 Conclusion -- References -- Mitigation and Prevention Methods for Distributed Denial-of-Service Attacks on Network Servers -- 1 Introduction -- 2 Proposed Survey -- 2.1 Motivation for DDoS Attacks -- 2.2 Attack Strategies and Phases -- 2.3 Attack Methods -- 3 Prevention Methods -- 3.1 Prevention Using Filters -- 3.2 Secure Overlay -- 3.3 Honeypots -- 3.4 Load Balancing -- 3.5 Additional Security Patches -- 4 DDoS Mitigation Methods -- 4.1 Detection of DDoS Attacks -- 5 Conclusion -- References -- A Machine Learning Framework for Automatic Detection of Malware -- 1 Introduction -- 2 Literature Review -- 3 Proposed Framework -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- DNNdroid: Android Malware Detection Framework Based on Federated Learning and Edge Computing -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 4 Machine Learning Technique -- 5 Proposed Framework Architecture -- 6 Evaluation of Proposed Framework -- 7 Comparison of Proposed Framework -- 7.1 Comparison on the Basis of Framework Available in the Literature.
7.2 Comparison of the Proposed Framework with Different Anti-virus Scanners -- 8 Experimental Findings -- 9 Conclusion -- References -- An Improved Symmetric Key Encryption Method Using Randomized Matrix Generation -- 1 Introduction -- 2 Types of Encryption Technique -- 2.1 AES -- 2.2 DES -- 2.3 Blowfish -- 3 Proposed Technique -- 3.1 Random Key Generation Algorithm -- 3.2 Text Message Encryption Algorithm -- 3.3 Text Message Decryption Algorithm -- 4 Matrix Operations -- 4.1 Matrix Determinant -- 4.2 Matrix Multiplication -- 4.3 Matrix Transpose Operation -- 5 Performance Analysis -- 5.1 Implementation of System -- 5.2 Text Encryption Algorithms Performance Analysis -- 5.3 Analysis of Complexity for Random Key Generation -- 5.4 Analysis of Execution Time -- 5.5 Analysis of Throughput -- 6 Conclusion -- References -- Performance Analyses of Black Hole Attack in AODV Routing Protocol in Vanet Using NS3 -- 1 Introduction -- 1.1 AODV Routing Protocol -- 1.2 Black Hole Attack -- 1.3 Literature Survey -- 1.4 Simulation Set-Up -- 1.5 Result Analyses -- 1.6 Conclusion -- References -- Comparative Analysis of Several Approaches of Encoding Audio Files -- 1 Introduction -- 2 Overview of Cryptography -- 3 Aims of Cryptography -- 3.1 The Many Forms that Cryptography Can Take -- 4 Cryptographic Algorithms at a Glance -- 4.1 DES -- 4.2 3DES -- 4.3 AES -- 4.4 Blowfish -- 4.5 RC4 -- 4.6 Twofish -- 4.7 ThreeFish -- 5 Background and Related Works -- 5.1 Related Research and Development on Audio Encryption -- 6 Recent Works on Audio Encryption -- 7 Limitations -- 8 Conclusion -- References -- A Secure Mechanism for Safeguarding Cloud Infrastructure -- 1 Introduction -- 2 Literature Review -- 3 Types of Security in Cloud Computing -- 3.1 Information Security -- 3.2 Identity Security -- 3.3 Network Security -- 3.4 Software Security -- 3.5 Infrastructure Security.
4 Security Concerns in Cloud -- 4.1 Virtualization -- 4.2 Public-Cloud Storage -- 4.3 Multitenancy -- 4.4 Identity and Access Management (IAM) -- 5 Security of Data in Cloud-Computing -- 6 Major Security Challenges -- 6.1 Internal Attacks -- 6.2 Partial/Incomplete Data Deletion -- 6.3 Interception of Data -- 6.4 Failure of Isolation -- 7 Using Encryption for Data Protection -- 7.1 Block-Cipher -- 7.2 Stream Ciphers -- 7.3 Hash Functions -- 8 Case Study on Cloud Based Cyber Security Model for Identification of Safe and Malicious Request -- 9 Conclusion -- References -- Phishing URLs Detection Using Machine Learning -- 1 Introduction -- 2 Related Work -- 2.1 Literature Review -- 2.2 URLs Descriptions -- 3 Research Methodology -- 4 Result and Analysis -- 4.1 Result -- 4.2 Analysis -- 5 Conclusion -- References -- Android Malware Detection with Classification Based on Hybrid Analysis and N-gram Feature Extraction -- 1 Introduction -- 1.1 Average Cost of a Data Breach -- 1.2 Growth Rate of Malware Infections -- 1.3 India and Asia Statistics on Malware Attacks -- 1.4 Trends in the Number of Attacks -- 1.5 Users Attacked by Malware -- 2 Research Objective/Problem Statement -- 3 Challenges in Malware Detection -- 4 Theoretical Framework -- 5 Hypothesis Declaration -- 6 Methodology -- 7 Approach -- 8 Outline of the Work Proposed -- 8.1 Process for the Proposed Scheme of Work -- 9 Conclusion -- 10 Further Research -- References -- Industry -- Image Processing and Deep Neural Networks for Face Mask Detection -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 3.1 Machine Learning Approach -- 3.2 Supervised Learning -- 3.3 Unsupervised Learning -- 3.4 Viola Jones algorithm -- 4 Mathematical Formulation -- 5 Results and Discussion -- 6 Conclusion -- References -- An Analysis of Lightweight Cryptographic Algorithms for IoT-Applications.
1 Introduction -- 2 Introduction of IoT -- 3 Software and Hardware Performance Metrics -- 4 Research Directions and Open Research Challenges -- 5 Conclusion -- Appendix 1 -- Hardware and Software Performances of LWC Algorithm -- References -- Permissioned Blockchain-Based Solution to Document Processing in the Real Estate Industry -- 1 Introduction -- 1.1 Blockchain Technology -- 1.2 Indian Real Estate Sector -- 1.3 Impact of Blockchain Technology on the Indian Real Estate Sector -- 2 Related Research Work and Limitations -- 2.1 Summarization of Recent Research Work -- 2.2 Research Gap -- 3 Proposed Research Work -- 3.1 Designed Framework and Components -- 3.2 Core Transaction Process Flow -- 3.3 Proposed Algorithms -- 3.4 Deployment -- 4 Conclusion and Future Scope -- References -- Automatic Evaluation of Free Text Answers: A Review -- 1 Introduction -- 2 Related Work -- 3 A Systematic Review -- 4 Discussion -- 5 Conclusions and Future Work -- References -- Blockchain Federated Learning Framework for Privacy-Preservation -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 4 Performance Evaluation -- 4.1 Datasets -- 4.2 Simulation Setup -- 4.3 Evaluation Metrics -- 4.4 Results and Discussion -- 5 Conclusion -- References -- Path Planning and Static Obstacle Avoidance for Unmanned Aerial Systems -- 1 Introduction -- 2 Methodology -- 2.1 A* Search -- 2.2 Rapidly-Exploring Random Tree -- 2.3 Ant Colony Optimization -- 2.4 Imitation Learning -- 3 Results and Discussion -- 4 Conclusion and Future Work -- References -- Comparative Study of Various Algorithms for Vehicle Detection and Counting in Traffic -- 1 Introduction -- 2 Literature Review -- 2.1 YOLO Real-Time Object Tracking -- 3 Methodology -- 3.1 YOLOv3 Architecture -- 3.2 YOLOv4 Architecture -- 3.3 YOLOv5 Architecture -- 3.4 YOLOv6 Architecture -- 3.5 YOLOv7 Architecture.
4 Results and Discussion.
Record Nr. UNINA-9910644266803321
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022
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