{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":25,"n_cols":5,"rows_kept":25,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[11,2,11,3],[12,2,12,3],[15,2,15,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNISA996508667303316"]
[null,null,"Titolo",null,"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"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-23092-2"]
[null,null,"Edizione",null,"[1st ed. 2022.]"]
[null,null,"Descrizione fisica",null,"1 online resource (482 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science, , 1865-0937 ; ; 1759"]
[null,null,"Disciplina",null,"943.005"]
[null,null,"Soggetti",null,"Electronic data processing"]
[{"$nulls":4},"Punched card systems"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"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-"]
[{"$nulls":4},"esteem and Recommending Methods to Reduce Addiction -- 1 Introduction -- 2 Related Work -- 3 Measures -- 3.1 Bergen Social Media Addiction Scale (BSMAS) [5] -- 3.2 Rosenberg Self-esteem Scale (RSES) [5] -- 3.3 Recommendation Methods [14, 15] -- 3.4 Dataset Collection 1 -- 3.5 Dataset Collection 2 -- 4 Proposed Methodology -- 4.1 Statistical Analysis -- 4.2 Recommendation System -- 5 Results and Discussion -- 5.1 Statistical Analysis."]
[{"$nulls":4},"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."]
[{"$nulls":4},"5 Comparison and Summary of Related Research Work -- 6 Future Work -- 7 Limitations and Challenges -- 8 Conclusion -- References -- Handwritten Signature Verification Using Convolution Neural Network (CNN) -- 1 Introduction -- 1.1 About the Domain -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Converting Image to Binary -- 3.2 Noise Removal -- 3.3 Image Enlargement -- 4 Feature Extraction -- 5 Feature Selection -- 6 Classification -- 7 Conclusion and Future Work -- References -- Comparative Analysis of Energy Consumption in Text Processing Models -- 1 Introduction -- 2 Existing Approaches -- 3 Exploration of the Data-Set -- 3.1 Average Word Length -- 3.2 Average Character Length -- 3.3 Number of Comments -- 4 Modelling -- 4.1 Simple Machine Learning Model -- 4.2 DistilBERT Model -- 4.3 Conv1D Model -- 4.4 Gated Recurrence Unit - GRU Model -- 5 Results -- 6 Conclusion -- References -- Evolution Towards 6G Wireless Networks: A Resource Allocation Perspective with Deep Learning Approach - A Review -- 1 Introduction -- 1.1 6G Vision -- 1.2 Technical Objectives of 6G -- 2 Resource Allocation for 6G Wireless Networks -- 3 Summary of Deep Learning Algorithms Used for 6G Wireless Networks Resource Allocation -- 4 Conclusion and Future Scope -- Appendix -- References -- Automation of Rice Leaf Diseases Prediction Using Deep Learning Hybrid Model VVIR -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 Results -- 5 Discussion -- References -- A Review "]
[{"$nulls":4},"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."]
[{"$nulls":4},"2 Literature Survey -- 3 Methodology -- 3.1 Umpire Gestures -- 3.2 Dataset -- 3.3 Feature Extraction -- 3.4 Classification of Umpire Gestures -- 3.5 Scorecard Updating Feature -- 4 Results and Discussion -- 5 Conclusion -- References -- Rating YouTube Videos: An Improvised and Effective Approach -- 1 Introduction -- 2 Previous Work -- 3 Implementation -- 3.1 Comment Collection and Preprocessing -- 3.2 Sentiment Measure -- 3.3 Word Cloud -- 3.4 Video Rating -- 4 Performance Review of Proposed Approach -- 4.1 Major Application: Detection of Clickbait Videos -- 5 Limitations and Loopholes -- 6 Result -- 7 Conclusion -- 8 Future Work -- References -- Classification of Tweet on Disaster Management Using Random Forest -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Preprocessing -- 3.2 Training, Validation and Testing -- 3.3 Feature Extraction -- 3.4 Random Forest Classification -- 3.5 Location Extraction -- 4 Results and Discussions -- 5 Datasets -- 6 Experiment -- 7 Validation -- 8 Conclusions -- References -- Numerical Investigation of Dynamic Stress Distribution in a Railway Embankment Reinforced by Geogrid Based Weak Soil Formation Using Hybrid RNN-EHO -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Model Clay Barrier's Compositional Characteristics -- 2.2 Geogrid -- 2.3 Measuring Subgrade Stiffness -- 2.4 Multi Objective Function -- 2.5 Improving Settlement-Based Geogrid using Hybrid RNN-EHO Technique -- 2.6 The Procedure of the EHO in Realizing the Learning of RNN -- 3 Results and Discussion -- 3.1 Uncertainty Analysis -- 4 Conclusion -- References -- Efficient Intrusion Detection and Classification Using Enhanced MLP Deep Learning Model -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 4 Results and Discussion -- 5 Conclusion -- References."]
[{"$nulls":4},"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, "]
[{"$nulls":4},"Grayscale and Color Spaced Images -- 1 Introduction -- 2 Overview of Image Matching Techniques -- 2.1 SIFT -- 2.2 SURF -- 2.3 ORB -- 3 Experimental Results -- 3.1 L*A*B* Color Space -- 4 Conclusion -- References -- Study of X Ray Detection Using CNN in Machine Learning -- 1 Introduction -- 2 Literature Review -- 2.1 Methods."]
[{"$nulls":4},"3 Algorithm CNN Model Algorithm Model = Sequential()."]
[null,null,null,"Sommario/riassunto","This two-volume constitutes the refereed proceedings of the First International Conference on Advancements in Smart Computing and Information Security, ASCIS 2022, held in Rajkot, India, in November 2022. The 37 full papers and 18 short papers presented were thoroughly reviewed and selected from the 206 submissions. The papers are organized in topical sections on artificial intelligence; smart computing; cyber security; industry."]