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Breakthroughs in digital biometrics and forensics / / Kevin Daimi, Guillermo Francia III, and Luis Hernández Encinas
| Breakthroughs in digital biometrics and forensics / / Kevin Daimi, Guillermo Francia III, and Luis Hernández Encinas |
| Autore | Daimi Kevin |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2022] |
| Descrizione fisica | 1 online resource (419 pages) |
| Disciplina | 006.4 |
| Soggetto topico |
Biometric identification - Technological innovations
Digital forensic science |
| ISBN | 3-031-10706-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910617306703321 |
Daimi Kevin
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| Cham, Switzerland : , : Springer International Publishing, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Breakthroughs in digital biometrics and forensics / / Kevin Daimi, Guillermo Francia III, and Luis Hernández Encinas
| Breakthroughs in digital biometrics and forensics / / Kevin Daimi, Guillermo Francia III, and Luis Hernández Encinas |
| Autore | Daimi Kevin |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2022] |
| Descrizione fisica | 1 online resource (419 pages) |
| Disciplina | 006.4 |
| Soggetto topico |
Biometric identification - Technological innovations
Digital forensic science |
| ISBN | 3-031-10706-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996495562703316 |
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Daimi Kevin
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| Cham, Switzerland : , : Springer International Publishing, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Cutting Edge Applications of Computational Intelligence Tools and Techniques
| Cutting Edge Applications of Computational Intelligence Tools and Techniques |
| Autore | Daimi Kevin |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (355 pages) |
| Altri autori (Persone) |
AlsadoonAbeer
CoelhoLuis |
| Collana | Studies in Computational Intelligence Series |
| ISBN | 3-031-44127-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- CI in Human-Machine Interaction -- Brain-Computer Interfaces: High-Tech Race to Merge Minds and Machines -- 1 Introduction -- 1.1 History of BCIs -- 2 Science of BCIs -- 3 Technology of BCIs -- 4 Ethics of BCIs -- 5 Application of BCIs -- 6 Discussion -- 7 Conclusion -- References -- Using Artificial Neural Networks to Predict Critical Displacement and Stress Values in the Proximal Femur for Distinct Geometries and Load Cases -- 1 Introduction -- 2 Materials and Methods -- 2.1 Neural Networks -- 2.2 Problem Summary -- 2.3 Data Gathering -- 2.4 Neural Network Architecture -- 3 Results and Discussion -- 4 Conclusion -- References -- An Integrated Model for Automated Identification and Learning of Conversational Gestures in Human-Robot Interaction -- 1 Introduction -- 2 Background and Fundamentals -- 2.1 Gesture -- 2.2 Petri Net -- 2.3 Synchronization in Gesture Motions and Speech -- 2.4 Models for Deep Learning -- 2.5 Conceptual Dependency Analysis -- 3 Conversational Gestures Classifications -- 3.1 Discourse Based Gesture Classification by Cognitive Psychologists -- 3.2 Extending Deictic Gestures Subclassification -- 3.3 Extending Iconic Gestures Subclassification -- 3.4 Extending Conversational Classification for Integrated Computational Analysis -- 4 Gesture Recognition Approaches -- 4.1 Data Collection and Analysis -- 4.2 Machine and Deep Learning Based Gesture Classification -- 4.3 Automated Learning by Mimicking -- 5 Synchronous Colored Petri Net (SCPN) Model -- 5.1 Modeling Composite Synchronized Motions -- 5.2 Signature of a Gesture -- 6 Conversational Gesture Recognition Using SCPN -- 6.1 Recognizing Conversational Head-Gestures -- 6.2 Recognizing Deictic Gestures -- 6.3 Recognizing Iconic Gestures-Contour Segment Pattern (CSP) Analysis.
6.4 Ambiguity Resolution Using Decision Trees -- 7 Limitations and Future Work -- 8 Conclusion -- References -- Computational Intelligence Methods for User Matching -- 1 Introduction -- 2 Efficiency and Effectiveness of User Matching -- 2.1 Efficiency -- 2.2 Effectiveness -- 3 The Process of User Matching -- 3.1 Pre-filtering -- 3.2 User's Similarity with Spatiotemporal Awareness -- 3.3 User Matching -- 4 Other Models for User Matching -- 4.1 Based on Username and Display Name -- 4.2 Based on User Friendship -- 4.3 Based on User Generated Content -- 5 Challenges and Future of User Matching -- 6 Conclusion -- References -- CI in Robotics and Automation -- ATIAS: A Model for Understanding Intentions to Use AI Technology -- 1 Introduction -- 2 Background and Theoretical Foundation -- 2.1 Trust and Its Components -- 2.2 Trust in Human-Machine Interaction (HMI) -- 2.3 Technology Acceptance Model -- 2.4 ATIAS Components -- 3 Research Method -- 3.1 Research Design -- 3.2 Research Questions and Hypotheses -- 3.3 Measurement Development -- 4 Findings -- 5 Discussion -- 5.1 Interpretation of the Findings and Research Question -- 5.2 Limitations and Next Steps -- Appendix -- Definition of Key Terms -- References -- Electronics Engineering Perspectives on Computer Vision Applications: An Overview of Techniques, Sub-areas, Advancements and Future Challenges -- 1 Introduction -- 1.1 History (Key Events) -- 1.2 Computer Vision Main Tasks -- 2 Key Techniques and Algorithms in Computer Vision -- 2.1 Key Techniques -- 2.2 Key Algorithms -- 3 Main Sub-areas of Computer Vision -- 3.1 Image Classification -- 3.2 Object Detection -- 3.3 Image Semantic Segmentation -- 4 Application Scenarios -- 4.1 Autonomous Driving -- 4.2 Medical Diagnosis -- 4.3 UAV Monitoring -- 4.4 Face Recognition -- 5 Future Trends and Challenges -- 6 Conclusions -- References. CI in Manufacturing, Engineering, and Industry -- Feature Importance Study for Biogas Production from POME Treatment Plants Using Out-of-Bag Permutation -- 1 Introduction -- 2 Materials and Methods -- 3 Results and Discussion -- 4 Conclusions -- References -- Convolutional Neural Networks for Part Orientation in Additive Manufacturing -- 1 Introduction -- 2 State of the Art of Related Works -- 2.1 Part Orientation -- 2.2 Convolutional Neural Network -- 3 The Method -- 3.1 Regression Task -- 4 The Datasets -- 5 Results -- 5.1 Regression Task -- 5.2 Classification Task -- 5.3 Analysis of the Results -- 6 Conclusions -- References -- CI in Recognition and Processing -- SINATRA: A Music Genre Classifier Based on Clustering and Graph Analysis -- 1 Introduction -- 2 Related Work -- 2.1 Genre Classification Based on Song's Audio Signals -- 2.2 Genre Classification Based on Song's Metadata -- 3 Description of the SINATRA Framework -- 3.1 Training of the Classifier -- 3.2 Production Stage -- 4 Evaluation of SINATRA -- 4.1 Dataset Description -- 4.2 Exploratory Analysis -- 4.3 Generation of the Core Genres -- 4.4 Generation of the CG-KNN Instance -- 4.5 Evaluation Metric -- 4.6 Evaluation Parameters -- 4.7 Result Discussion -- 4.8 Classification Examples -- 5 Conclusion and Future Work -- References -- Towards an Enhanced and Lightweight Face Authentication System -- 1 Introduction -- 2 Method 1: A Dual-Task Relation Regulated Unified System -- 2.1 Background -- 2.2 Formulation of the Relationship Between Two-Tasks -- 2.3 Design of Loss and Training Strategy -- 2.4 Experiments and Discussion -- 3 Method 2: A Multi-teacher Assisted Multi-task Learning Framework -- 3.1 Experiments and Discussion -- 4 Conclusion -- References -- CI in Finance, Business, Economics and Education. Conceptual Intelligence, Digital Transformation, and Leadership Skills: Key Concepts for Modern Business Success -- 1 Introduction -- 1.1 Digital Transformation -- 1.2 Conceptual Intelligence -- 1.3 Leadership Skills for Digital Transformation -- 2 Digital Transformation -- 2.1 Improved Operational Efficiency -- 2.2 Enhanced Customer Experience -- 2.3 Increased Revenue -- 2.4 New Growth Opportunities -- 3 Leadership Skills -- 3.1 Visionary Leadership -- 3.2 Change Management -- 3.3 Digital Literacy -- 3.4 Data-Driven Decision-Making -- 3.5 Collaborative Leadership -- 3.6 Agility and Innovation -- 4 Advantages and Possibilities for Leaders with Excellent Digital Literacy -- 5 Leaders -- Then Versus Now -- 6 Digital Leaders with Academic Excellence Versus, Digital Leaders with Digital Hands-on Experience -- 6.1 Digital Leaders with Academic Excellence -- 6.2 Digital Leaders with Hands-on Digital Skills -- 6.3 Comparing Digital Leaders with Academic Excellence and Hands-on Digital Skills -- 7 Conclusion -- References -- GEMM-SaFIN(FRIE)++: Explainable Artificial Intelligence Visualisation System with Episodic Memory -- 1 Introduction -- 2 Architecture of GEMM-SaFIN(FRIE)++ -- 2.1 Overall Architecture -- 2.2 Self-Learning Rule Generation -- 2.3 Computation of Rule Activation -- 2.4 Rules Obsoletion -- 2.5 GEMM Mechanism -- 3 Explainable AI Visualization System for GEMM-SaFIN(FRIE)++ -- 3.1 Development Process -- 3.2 GUI of Explainable AI Visualization System -- 3.3 Features of Interpolation/Extrapolation -- 3.4 Merging of Membership Functions -- 3.5 Deletion of Rules -- 3.6 Neuro-fuzzy Network in Explainable AI Visualization System -- 3.7 Animating Activation of Rules in Explainable AI Visualization System -- 4 Experimental Analysis and Benchmarking -- 4.1 Experiments by Nakanishi Dataset -- 4.2 Event Detection of Stock Market Crisis. 5 Conclusions and Future Work -- References -- CI in Vehicles, Smart Cities/Energy, and Networking -- Traffic Sign Recognition Robustness in Autonomous Vehicles Under Physical Adversarial Attacks -- 1 Introduction -- 2 Traffic Signs Recognition in Autonomous Vehicles -- 3 Adversarial Attacks in Computer Vision -- 4 Towards Attacking Traffic Signs Recognition Systems -- 5 Experimental Study -- 6 Discussion -- 7 Conclusion -- References -- Computational Intelligence in Smart Cities and Smart Energy Systems -- 1 Introduction -- 2 Margin Setting Algorithm -- 3 Smart Cities Application: Human Activity Recognition -- 4 Smart Energy Systems Application: False Data Injection Detection -- 5 Conclusion -- References -- Ontology-Based Similarity Estimates for Fuzzy Data: Semantic Wiki Approach -- 1 Introduction -- 2 Classification of Non-classical Data Types -- 3 Problem Definition -- 4 Taxonomy of NCD -- 5 Methods of NCD Processing -- 6 Semantic Similarity Estimations of Data -- 7 Dirty Data and Semantic Wikis -- 8 Conclusion -- References. |
| Record Nr. | UNINA-9910768174503321 |
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Daimi Kevin
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| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23) / / edited by Kevin Daimi, Abeer Al Sadoon
| Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23) / / edited by Kevin Daimi, Abeer Al Sadoon |
| Autore | Daimi Kevin |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (670 pages) |
| Disciplina | 004 |
| Altri autori (Persone) | Al SadoonAbeer |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Cooperating objects (Computer systems) Engineering—Data processing Medical informatics Computational Intelligence Cyber-Physical Systems Data Engineering Health Informatics |
| Soggetto non controllato | Mathematics |
| ISBN | 3-031-33743-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Community Opinion Network Maximization for Mining Top K Seed Social Network Users -- Taxonomy for an Automated Sleep Stage Scoring -- Convolutional Neural Networks Based Classification of Mammograms -- Finding Insights in Florida Voter Participation -- HealthCare Text Analytics using Recent ML Techniques -- Emotion Recognition Techniques with IoT and Deep Learning Technologies -- Augmented Reality for Cognitive Impairment and Dementia -- Analysis on Malicious Intruder Threats to Data Integrity -- Smart Product Recommendation System -- Detection and Prediction of Epileptic Seizures Using Machine Learning Model. . |
| Record Nr. | UNINA-9910728395603321 |
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Daimi Kevin
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the Second International Conference on Advances in Computing Research (ACR'24)
| Proceedings of the Second International Conference on Advances in Computing Research (ACR'24) |
| Autore | Daimi Kevin |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2024 |
| Descrizione fisica | 1 online resource (570 pages) |
| Altri autori (Persone) | Al SadoonAbeer |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 3-031-56950-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910847085903321 |
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Daimi Kevin
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| Cham : , : Springer International Publishing AG, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the Second International Conference on Innovations in Computing Research (ICR’23) / / edited by Kevin Daimi, Abeer Al Sadoon
| Proceedings of the Second International Conference on Innovations in Computing Research (ICR’23) / / edited by Kevin Daimi, Abeer Al Sadoon |
| Autore | Daimi Kevin |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (460 pages) |
| Disciplina | 004.072 |
| Altri autori (Persone) | Al SadoonAbeer |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Cooperating objects (Computer systems) Engineering - Data processing Medical informatics Computational Intelligence Cyber-Physical Systems Data Engineering Health Informatics |
| ISBN | 3-031-35308-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910731479303321 |
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Daimi Kevin
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the Third International Conference on Innovations in Computing Research (ICR'24)
| Proceedings of the Third International Conference on Innovations in Computing Research (ICR'24) |
| Autore | Daimi Kevin |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2024 |
| Descrizione fisica | 1 online resource (794 pages) |
| Altri autori (Persone) | Al SadoonAbeer |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 3-031-65522-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Data Science -- Extracting Official Agencies' Communication Patterns During the COVID-19 Pandemic: A Text Mining Approach -- 1 Introduction -- 2 Related Work -- 3 Text Mining Methodology -- 3.1 Data Collection and Pre-processing -- 3.2 Text Mining Approaches -- 4 Results and Discussion -- 4.1 Word Analysis -- 4.2 Collocation Analysis -- 4.3 Topic Modeling -- 4.4 Sentiment and Correlation Analysis -- 5 Conclusion and Future Work -- References -- Towards Automated Policy Predictions via Structured Attribute-Based Access Control -- 1 Introduction -- 2 Algorithm Overview -- 3 Application -- 3.1 Data Set -- 3.2 Policy Prediction with Time Series -- 4 Related Work -- 5 Conclusions and Future Work -- References -- Exploratory Analysis of Gamblers' Financial Transactions to Mine Behavioral Pattern Data -- 1 Introduction -- 2 Previous Works -- 3 Data -- 4 Exploring Data Slices -- 5 80th and 99th Percentiles -- 6 99th Percentiles -- 7 Dynamic Time Frames -- 8 Quantitative Comparisons of Session Series -- 9 Limitations -- 10 Discussion -- References -- The Detection of Misstated Financial Reports Using XBRL Mining and Intelligible MLP -- 1 Introduction -- 2 The Conceptual Framework -- 2.1 AI-Based Financial Analysis -- 2.2 Cross-Section Characterisation of Reported Numbers -- 3 Methodology -- 3.1 Web-Mining of XBRL Financial Reports -- 3.2 Input Pre-selection, MLP Topology and Learning -- 4 Results -- 5 Conclusion -- References -- University Student Enrollment Prediction: A Machine Learning Framework -- 1 Introduction -- 2 Literature Review -- 3 Methodology and Framework -- 4 Results and Discussion -- 5 Conclusion -- References -- Early Prediction of Sepsis Utilizing Multi-branches Multi-tasks Hybrid Deep Learning Model -- 1 Introduction -- 2 Review of Previous Studies.
3 Multi-branches Multi-tasks Hybrid Deep Learning Model for Sepsis Predicting -- 3.1 Global Feature Extraction Module (Branch 1) -- 3.2 Local Feature Extraction Module (Branch 2) -- 3.3 Multi-tasks Learning -- 4 Experiments -- 5 Conclusion -- References -- Comprehensive Analysis of Iris Dataset Using K-Mean and Fuzzy K-Mean Clustering Algorithm -- 1 Introduction -- 2 Background -- 2.1 Clustering -- 2.2 Big Data -- 2.3 Data Stream -- 3 Material and Methods -- 3.1 Dataset Description -- 3.2 Preprocessing -- 3.3 K-Nearest Neighbor -- 3.4 Parameter Evaluation -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- An Efficient and Reliable scRNA-seq Data Imputation Method Using Variational Autoencoders -- 1 Introduction -- 2 Related Work -- 2.1 Classic Methods -- 2.2 Deep Learning Methods -- 3 Methods -- 3.1 A Brief on VAE -- 3.2 Our Data Imputation Approach Based VAE -- 4 Experiments -- 4.1 Datasets -- 4.2 Data Preprocessing -- 5 Results -- 5.1 Mean Square Error (MSE) -- 5.2 Clustering Results -- 5.3 Running Time -- 6 Conclusion -- References -- Prediction of Automotive Vehicles Engine Health Using MLP and LR -- 1 Introduction -- 2 Related Work -- 3 Data Preprocessing -- 4 Multi-Layer Perceptron -- 4.1 Working Flow -- 5 Logistic Regression -- 5.1 Model Implementation and Training -- 5.2 Model Evaluation -- 5.3 Hyperparameter Tuning with BayesSearch CV -- 6 Results -- 6.1 MLP Before Data Preprocessing -- 6.2 MLP After Data Preprocessing and Optimization -- 6.3 Comparing MLP Results -- 6.4 Logistic Regression -- 6.5 Comparing MLP with LR -- 7 Conclusion -- 8 Future Work -- References -- Medical Image Character Recognition Using Attention-Based Siamese Networks for Visually Similar Characters with Low Resolution -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Model Architecture -- 3.2 Model + Attention Mechanism. 4 Experiment, Result and Analysis -- 4.1 Dataset Description -- 4.2 Training Strategy -- 4.3 Result -- 4.4 Performance Analysis on AUC-ROC Curve -- 4.5 Performance Analysis Using Feature Map Visualisation -- 4.6 Quantitative Analysis with Related Works with Background Interference -- 5 Conclusion -- References -- Toward Smart Bicycle Safety: Leveraging Machine Learning Models and Optimal Lighting Solutions -- 1 Introduction -- 2 Using AI in Bikes Lights -- 3 Methodology -- 3.1 Data Collection -- 3.2 Pre-processing -- 3.3 Term Frequency-Inverse Document Frequency Features (TF-IDF) -- 3.4 Model Development -- 3.5 Model Evaluation -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- vThrot: Fine-Grained, Virtual I/O Resource Redistribution Scheme -- 1 Introduction -- 2 vThrot -- 2.1 System Architecture -- 2.2 The Reclamation Process of vThrot -- 2.3 The Redistribution Process of vThrot -- 2.4 vThrot Priority-Based I/O Processing -- 3 Performance Evaluation -- 4 Conclusion -- References -- Bayesian Optimization-Based CNN Model for Blood Glucose Estimation Using Photoplethysmography Signals -- 1 Introduction -- 2 Literature Review -- 3 Methodology Overview -- 3.1 Dataset and Pre-processing -- 3.2 Basic Architecture of the CNN Model -- 3.3 Bayesian Optimization -- 4 Results and Discussion -- 5 Conclusion -- References -- Comparing Convolutional Neural Networks and Transformers in a Points-of-Interest Experiment -- 1 Introduction -- 2 Overview of Deep Learning Architectures -- 2.1 Convolutional Neural Network (CNN) -- 2.2 Transformers -- 3 Construction of Mini-Places Dataset -- 3.1 Dataset Selection -- 3.2 Dataset Optimization -- 4 Training of Deep Learning Models -- 4.1 Image Classification Models -- 4.2 Comparison of the Models -- 5 Assessment of Experimental Findings -- 6 Conclusion -- References. Gender and Age Extraction from Audio Signal Using Convolutional Neural Network, MFCC and Spectrogram -- 1 Introduction -- 1.1 Speaker Gender Recognition -- 2 CORPUS -- 3 Methodology -- 3.1 Proposed Model Architecture -- 4 Results -- 4.1 Gender Recognition -- 4.2 Age Extraction -- 5 Conclusion -- References -- The Hybrid Model Combination of Deep Learning Techniques, CNN-LSTM, BERT, Feature Selection, and Stop Words to Prevent Fake News -- 1 Introduction -- 2 Literature Review -- 2.1 Materials and Methods -- 2.2 Counterfeit News Prevention Challenges -- 2.3 Previous Fake News Prevention Attempts -- 2.4 Accuracy Results and Discussion -- 3 Methodology for Hybrid Model of CNN-LSTM + BERT + Feature Selection + Stop Words -- 3.1 LSTM + CNN -- 3.2 Stop Words -- 3.3 BERT -- 3.4 TFIDF and Feature Selection -- 4 Critical Analysis -- 5 Conclusion -- References -- Comparative Analysis of Decision Tree Algorithms Using Gini and Entropy Criteria on the Forest Covertypes Dataset -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Decision Tree Classifier -- 3.3 Evaluation Metrics -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- A Comparative Analysis of Random Forest and Support Vector Machine Techniques on the UNSW-NB15 Dataset -- 1 Introduction -- 2 Related Works -- 3 Proposed Intrusion Detection Systems -- 3.1 Data Extraction -- 3.2 Data Balancing -- 3.3 Data Transformation -- 3.4 Model Parameter Selection -- 3.5 Model Fitting -- 4 Evaluation of the Models -- 4.1 Confirmation of the Candidate Model Using SMOTE -- 5 Conclusion and Future Directions -- References -- A Comparative Study of Speed Measurement Using Radar Guns and Pneumatic Counter -- 1 Introduction -- 2 Materials and Methods -- 2.1 Study Area -- 2.2 Equipment and Tools -- 2.3 Methodology -- 3 Results and Discussion -- 3.1 Cosine Effect Correction. 3.2 Statistical Description of Data Obtained -- 3.3 Dispersion and Regression Statistical Analysis -- 3.4 Suggested Fitting Equation -- 3.5 Discussions -- 4 Conclusions -- References -- Comparative Analysis of Preprocessing Techniques for KNN Classification on the Diabetes Dataset -- 1 Introduction -- 2 Related Work -- 3 Material and Methods -- 3.1 Dataset Description -- 3.2 Preprocessing -- 3.3 K-Nearest Neighbor -- 3.4 Parameter Evaluation -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Computer Science and Computer Engineering Education -- Code Smells for Assessing and Improving Students' Coding Skills and Practices -- 1 Introduction -- 2 Background -- 2.1 Code Smells -- 2.2 Teaching Object-Oriented Programming -- 3 Motivation -- 4 Our Approach -- 4.1 Implementation and Experiment -- 5 Results -- 5.1 Size Complexities -- 5.2 Distribution of Code Smells -- 5.3 Code Smells Density -- 5.4 Code Smells and Earned Grades -- 5.5 Code Smells Trends -- 5.6 Summary -- 6 Conclusion -- References -- An Investigation on Assessment Strategies, Student Engagement, and Retention for Large Cohorts Affected by COVID Learning Disruptions -- 1 Introduction -- 2 Background and Pedagogy -- 2.1 Assessment Strategies -- 2.2 Study Design and Procedure -- 3 Results and Discussions -- 3.1 Results -- 3.2 Student Engagement -- 3.3 Student Retention -- 4 Conclusion -- References -- Self-organization as a Key Principle of Adaptive Intelligence -- 1 Introduction -- 2 From Single Synapse to Neural Network -- 2.1 Neural Timing -- 2.2 Basic Adaptive Response -- 3 Self-organized Network Learning -- 3.1 Winner-Take-All -- 3.2 Reinforcement -- 4 Modular Functional Connectivity -- 4.1 Functional Specificity -- 4.2 Functional Plasticity -- 5 The Receptive Field Concept -- 5.1 Sensitivity and Selectivity to Input Dimensions. 5.2 From-Simple-to-Complex Functional Organization. |
| Record Nr. | UNINA-9910878985003321 |
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Daimi Kevin
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| Cham : , : Springer International Publishing AG, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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