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Data science and algorithms in systems . Volume 2 : proceedings of 6th Computational Methods in Systems and Software 2022 / / edited by Radek Silhavy, Petr Silhavy, and Zdenka Prokopova



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Titolo: Data science and algorithms in systems . Volume 2 : proceedings of 6th Computational Methods in Systems and Software 2022 / / edited by Radek Silhavy, Petr Silhavy, and Zdenka Prokopova Visualizza cluster
Pubblicazione: Cham, Switzerland : , : Springer, , [2023]
©2023
Edizione: 1st ed. 2023.
Descrizione fisica: 1 online resource (1038 pages)
Disciplina: 005.1
Soggetto topico: Software engineering
Persona (resp. second.): SilhavyRadek
SilhavyPetr
ProkopovaZdenka
Note generali: Includes index.
Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Understanding the General Framework for Teaching Semantics and Syntaxes of Visual Languages to Computer Education Students Based on Notion of Abstract Visual Syntax Graphs -- 1 Introduction -- 2 Related Work -- 2.1 Syntax of Visual Languages -- 2.2 Semantics of Visual Languages -- 2.3 Graph Representation -- 2.4 Abstract Visual Syntax Graph and Graph Grammar -- 2.5 Logical Semantics -- 3 The three Notable Visual Languages -- 3.1 Euler Diagrams (Circle) -- 3.2 VEX -- 3.3 Show and Tell -- 4 Conclusions and Future Work -- References -- A Prediction System Using AI Techniques to Predict Students' Learning Difficulties Using LMS for Sustainable Development at KFU -- 1 Introduction -- 1.1 Practitioner Notes -- 2 Related Work -- 3 Machine Learning -- 3.1 Logistics Regression (LR) -- 3.2 K-Nearest Neighbor (KNN) -- 3.3 Decision Tree (DT) -- 3.4 Naive Bayes Algorithm (NB) -- 3.5 Random Forest (RF) -- 3.6 Stochastic Gradient Descent (SGD) -- 3.7 Ridge Classifier -- 3.8 Nearest Centroid -- 4 Dataset Description -- 5 Methodology -- 6 Data Transformation -- 7 Data Partitioning -- 8 Performance Evaluation -- 9 Results -- 10 Conclusion -- 11 Discussion -- References -- COVID-19 Detection from Chest X-Ray Images Using Detectron2 and Faster R-CNN -- 1 Introduction -- 2 Deep Learning Based Object Detection -- 2.1 R-CNN -- 2.2 Fast R-CNN -- 2.3 Faster R-CNN -- 2.4 YOLO -- 3 Methodology -- 3.1 Dataset -- 3.2 Baseline Models -- 3.3 Evaluating Object Detection Models -- 3.4 Training Process for Different Models -- 4 Results and Discussion -- 5 Conclusion -- References -- Effective SNOMED-CT Concept Classification from Natural Language using Knowledge Distillation -- 1 Introduction -- 2 Related work -- 2.1 SNOMED-CT (Systemized Nomenclature of Medicine Clinical Term) -- 2.2 Medical Natural Language Document.
2.3 Methods for Inferring Terms for Binding SNOMED-CT -- 2.4 Knowledge Distillation -- 2.5 BioBert ch4ref11 -- 3 Methodology -- 3.1 Problem statement -- 3.2 Proposed Model -- 3.3 Data Preprocessing -- 3.4 Learning Method and Architecture -- 4 Results and Discussions -- 5 Conclusion -- References -- Analyze Mental Health Disorders from Social Media: A Review -- 1 Introduction -- 2 Methodology -- 3 Result -- 3.1 RQ1: What Technique Is Most Commonly Used in the Mental Health Analysis in the Last Five Years? -- 3.2 RQ2: What Data Sources or Applications Are Widely Used to Retrieve Test Data? -- 3.3 Synthetic Result -- 4 Conclusion -- References -- Methods of Solution to the Task on Early Detection of Fire Outbreaks Based on Images and Video Streams from Controlled Territories -- 1 Introduction -- 2 Review of Existing Methods -- 3 Set up of the Task -- 4 Realization of Experiments -- 4.1 Task of Binary Classification -- 4.2 Extraction of Places with Fire Based on YOLO -- 5 Conclusion -- References -- 3D Building Internal Structural Component Segmentation from Point Cloud Data Using DBSCAN and Modified RANSAC with Normal Deviation Conditions -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Preprocessing -- 3.2 Segmentation -- 4 Experimental Results -- 5 Conclusion -- References -- Contrast Enhancement of UAV-Based Maize Plant Images for Automatic Detection of Fall Armyworm -- 1 Introduction -- 2 Proposed Solution -- 2.1 Evaluation Parameter -- 2.2 Proposed Algorithm -- 3 Experimental Results and Discussion -- 4 Conclusion -- References -- Smart Services in Education: Facilitating Teachers to Deliver Personalized Learning Experiences -- 1 Introduction -- 2 Theoretical Background -- 2.1 Smart Services and Smart Service Systems -- 2.2 The Teacher Impact on the Student Satisfaction -- 2.3 The New Learning Paradigm.
2.4 Strategies for Learning Personalization -- 3 Smart Services Implementation in the Learning Process -- 4 A Model of Smart Service Platform -- 5 Conclusion and Future Work -- References -- Optimized 8-Parameter Relay-Based Delayed Thermal Process Model Identification via Saturated Relay and Artificial Delay -- 1 Introduction -- 2 Mathematical Models -- 2.1 Model 1 -- 2.2 Model 2 -- 3 Improved and Extended Relay-Feedback Test -- 3.1 Saturated Relay -- 3.2 Artificial Delay -- 4 Optimization Problems and the Solution Technique -- 4.1 Optimization Problems Definition -- 4.2 Nelder-Mead Algorithm -- 5 Algorithm Summary and Numerical Example -- 5.1 Identification Algorithm Summary -- 5.2 Simulation Example -- 6 Conclusions -- References -- Augmenting Historical Alphabet Datasets Using Generative Adversarial Networks -- 1 Introduction -- 1.1 Letter Classification -- 1.2 Getting Data for Letter Classification from Historical Documents -- 1.3 Current State of Art of Palmyrene Alphabet Classification -- 2 Methods of Image Augmentation -- 2.1 Keras Generator -- 2.2 Roboflow -- 3 Generative Adversarial Networks -- 4 Using GAN for Palmyrene Alphabet Augmentation -- 4.1 Network Architecture -- 4.2 Training Parameters -- 5 Results -- 5.1 GAN Success Rate -- 5.2 Classifier Improvement -- 6 Discussion -- 7 Conclusion -- References -- Ensemble Machine Learning Models for Simulating the Missile Defense System -- 1 Introduction -- 1.1 Background and Motivation of Research -- 1.2 Research Content -- 2 Related Work -- 3 System Model -- 3.1 Simulator Description -- 3.2 Ensemble Machine Learning Models -- 4 Performance Evaluation -- 4.1 The Main Flow Chart of the Proposed System -- 4.2 Application Development Environment -- 4.3 Simulator -- 4.4 Prediction Factor Data Information -- 4.5 Confusion Matrix -- 4.6 Performance Measurement Results -- 5 Conclusion -- References.
Validating Radar and Satellite Precipitation Estimates Against Rain Gauge Records in Slovakia -- 1 Introduction -- 2 Related Works -- 3 Data -- 4 Methodology -- 5 Results and Discussion -- 6 Conclusions -- References -- Improvement on Management of Tags Using an Event Queue -- 1 Backgrounds and Needs -- 2 Design of the Asynchronous Tag Loading Scheme -- 2.1 Event Queue -- 2.2 Proposed Tag Management System Architecture -- 3 Performance Evaluation -- 3.1 Preparation of Samples Under the Test -- 3.2 Improvement on Network Performance -- 3.3 Improvement in Tag Omission -- 4 Conclusions -- References -- Memetic Algorithm with GPU Optimization -- 1 Introduction -- 2 Related Work -- 2.1 GP and Evolutionary Programming -- 2.2 Parallel GP on GPU -- 2.3 Metaheuristic Algorithm -- 2.4 Parallel Metaheuristics -- 2.5 Memetic Algorithms -- 2.6 Memetic Algorithm on GPU -- 3 Implemented Program -- 3.1 Development Settings and Tools -- 3.2 Description of Implementation -- 4 Result and Discussion -- 5 Conclusion -- References -- Application of Machine Learning Techniques to Enterprise Model Classification: An Approach and First Experimental Results -- 1 Introduction -- 2 Related Work -- 2.1 Enterprise Model Representation -- 2.2 Graph Neural Networks for Graph Classification -- 2.3 Sentence Embedding -- 3 Research Approach -- 3.1 Dataset -- 3.2 Methodology -- 4 Experimentation Results -- 4.1 Enterprise Models Classification Based on the Graph Topological Features -- 4.2 Enterprise Models Classification Based on Topological and Semantic Features -- 5 Conclusion -- References -- Conceptual Linked Data Model for South African Municipalities Public Services Domain -- 1 Introduction -- 2 Methodology -- 3 Literature Review -- 4 Data Sources Selection and Ontology Mapping to Municipality Public Domain -- 4.1 Requirement -- 4.2 Formalization -- 4.3 Ontology Classes Modeling.
5 Linking Ontologies Represented in OWL -- 6 Conclusion -- References -- On the CPU Usage of Deep Learning Models on an Edge Device -- 1 Introduction -- 2 YOLO Models for Object Detection -- 3 Deep Learning Use-Cases at the Edge -- 4 Related Work -- 5 Experimentation and Results -- 5.1 Application Scenario -- 5.2 Results -- 6 Conclusion -- References -- Stratification Languages of Socio-economic Systems -- 1 Introduction -- 2 Phenomenon of Language -- 3 Probabilistic Concept of Language -- 4 Classification of Languages -- 5 Formal Scheme Language -- 6 Formal Description of the SES -- 7 Conclusion -- References -- Analysis and Prediction of the Complementary Dynamics of Computer Viruses -- 1 Introduction -- 2 Methods and Results -- 3 Conclusion -- References -- Distance Learning in the Post-pandemic Period: Trends, Limitations and Symmetry of Knowledge -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 3.1 Distance Learning -- 3.2 Massive Open Online Courses -- 4 Discussion -- 5 Conclusions -- References -- Model of Contact Interaction of Rough Surfaces in Statics -- 1 Introduction -- 2 Problem Statement -- 3 Single Contact -- 4 Contact Interaction of Rough Surfaces in Statics -- 5 Conclusion -- References -- Churn Prediction in Telecoms Using a Random Forest Algorithm -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Removal of Zero Value Variables -- 3.2 Outlier Analysis -- 3.3 Label Encoding -- 3.4 Normalization -- 3.5 Feature Importance -- 3.6 Data Sampling -- 3.7 Model Execution -- 4 Implementation -- 5 Results Discussion -- 6 Conclusion and Future Work -- References -- Problems of Non-linear Symmetry -- 1 Introduction -- 2 Statement of the Problem -- 2.1 Complementarity Principle -- 3 Research Method -- 4 Conclusion -- References -- CVR: An Automated CV Recommender System Using Machine Learning Techniques -- 1 Introduction.
2 Related Work.
Sommario/riassunto: This book offers real-world data science and algorithm design topics linked to systems and software engineering. Furthermore, articles describing unique techniques in data science, algorithm design, and systems and software engineering are featured. This book is the second part of the refereed proceedings of the 6th Computational Methods in Systems and Software 2022 (CoMeSySo 2022). The CoMeSySo 2022 conference, which is being hosted online, is breaking down barriers. CoMeSySo 2022 aims to provide a worldwide venue for debate of the most recent high-quality research findings.
Titolo autorizzato: Data Science and Algorithms in Systems  Visualizza cluster
ISBN: 3-031-21438-2
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910640388103321
Lo trovi qui: Univ. Federico II
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Serie: Lecture Notes in Networks and Systems, . 2367-3389 ; ; 597