Intelligent Human Computer Interaction : 15th International Conference, IHCI 2023, Daegu, South Korea, November 8-10, 2023, Revised Selected Papers, Part II

• Record Nr.: UNISA996587859903316
• Autore: Choi Bong Jun
• Pubbl/distr/stampa: Cham : , : Springer, , 2024; ©2024
• ISBN: 3-031-53830-7
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (355 pages)
• Collana: Lecture Notes in Computer Science Series ; ; v.14532
• Altri autori (Persone): SinghDhananjay; TiwaryUma Shanker; ChungWan-Young
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- AI and Big Data -- Automated Fashion Clothing Image Labeling System -- 1 Introduction -- 2 Related Research -- 3 Fashion Clothing Image Labeling System -- 3.1 Dataset Collection -- 3.2 Image Preprocessing -- 3.3 Yolo Training and Labeling Results -- 4 Conclusion -- References -- AI-Based Estimation from Images of Food Portion Size and Calories for Healthcare Systems -- 1 Introduction -- 2 Dataset of Uzbek Foods -- 3 Proposed Method -- 4 Experimental Results and Analysis -- 5 Limitation and Future Work -- 6 Conclusions -- References -- Blockchain Technology as a Defense Mechanism Against Data Tampering in Smart Vehicle Systems -- 1 Introduction -- 2 Background and Literature Review -- 3 Data Tampering in Smart Vehicle Systems -- 4 Blockchain Technology as a Solution in Smart Vehicle Systems -- 4.1 Technical Foundations of Blockchain in Smart Vehicle Systems -- 4.2 Practical Implementations and Prototypes -- 5 Conclusion -- References -- Classification of Weeds Using Neural Network Algorithms and Image Classifiers -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Pre-processing -- 3.3 Classification Models Architectures and Algorithms -- 4 Results -- 5 Future Scope and Conclusion -- ; References -- Weed and Crop Detection in Rice Field Using R-CNN and Its Hybrid Models -- 1 Introduction -- 2 Related Work -- 3 Methods and Materials -- 3.1 Experimental Site and Image Acquisition -- 3.2 Data Pre-processing -- 4 Weed Detection Method -- 4.1 Regions with RCNN -- 4.2 Regions with RCNN-LSTM -- 4.3 Regions with RCNN-GRU -- 5 Results and Discussions -- 6 Conclusion -- References -- Deep Learning -- Spatial Attention Transformer Based Framework for Anomaly Classification in Image Sequences -- 1 Introduction -- 2 Related Study.; 3 Proposed Framework -- 3.1 Spatial Attention Module (SAM) -- 3.2 Shifted Window Transformer (SWIN) -- 3.3 SST for Anomaly Detection -- 4 Experimental Results and Discussions -- 4.1 Datasets -- 4.2 Results and Discussions -- 5 Conclusions -- References -- Development of LSTM-Based Sentence Generation Model to Improve Recognition Performance of OCR System -- 1 Introduction -- 2 Related Works -- 3 LSTM-Based Sentence Generation Model -- 3.1 Training Dataset -- 3.2 Implemented LSTM Model -- 4 Experiments and Results -- 5 Conclusion -- References -- Satellite Imagery Super Resolution Using Classical and Deep Learning Algorithms -- 1 Introduction -- 2 Background -- 2.1 Image Resolution -- 2.2 Interpolation for Image Enhancement -- 2.3 DWT and Noise Removal Techniques -- 3 Deep Learning Based Architectures for Image Super Resolution -- 3.1 High Level Architecture -- 3.2 Enhanced Deep Residual Networks for Single Image Super-Resolution(EDSR) -- 3.3 Wide Activation for Efficient and Accurate Image Super-Resolution(WDSR) -- 3.4 Deep Alternating Network(DAN) -- 4 Evaluation Metrics -- 5 Comparisons and Challenges -- 6 Comparisons and Challenges -- References -- Traffic Sign Recognition by Image Preprocessing and Deep Learning -- 1 Introduction -- 2 Related Works -- 2.1 Traditional Approach -- 2.2 Deep Learning Based Methods -- 3 Our Methodology -- 3.1 Dark Channel Prior Based Image Dehazing -- 3.2 Improved Detection Model -- 3.3 Data Augmentation -- 4 Experiments and Analysis -- 4.1 Results -- 4.2 Experimental Analysis and Discussion -- 5 Conclusion -- References -- Convolutional Autoencoder for Vision-Based Human Activity Recognition -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Convolutional Autoencoder (Conv-AE) -- 3.2 Convolutional Neural Network (CNN) -- 3.3 Pre-processing -- 3.4 Feature Representation -- 3.5 Classification.; 4 Experimental Results -- 4.1 Datasets -- 4.2 Results and Discussions -- 5 Conclusions and Future Scope -- References -- Deep Learning Approach for Enhanced Object Recognition and Assembly Guidance with Augmented Reality -- 1 Introduction -- 2 Methodology -- 2.1 Dataset Collection and Image Pre-processing -- 2.2 Step Detection -- 3 Results and Discussion -- 3.1 Prototype -- 3.2 SSD Performance -- 3.3 YOLOv7 Performance -- 3.4 User Testing -- 4 Conclusion -- References -- 3D Facial Reconstruction from a Single Image Using a Hybrid Model Based on 3DMM and Deep Learning -- 1 Introduction -- 2 Related Work -- 2.1 3DMM-Based Methods -- 2.2 Image-Based Methods -- 3 Methodology -- 3.1 3D Morphable Model -- 3.2 Camera Model -- 3.3 Illumination Model -- 3.4 Model Fitting -- 4 Results Analysis -- 5 Conclusion -- References -- Human Activity Recognition with a Time Distributed Deep Neural Network -- 1 Introduction -- 2 Related Works -- 3 The Proposed Method -- 3.1 Input Dataset -- 3.2 Data Pre-processing -- 3.3 Time Distributed Frame Conversion -- 3.4 Time Distributed CNN Layers -- 3.5 LSTM Layers -- 3.6 Training and Testing -- 3.7 Evaluation -- 4 Experimental Results and Discussion -- 4.1 UCI Sensor Dataset [2] Results -- 4.2 OPPORTUNITY Sensor Dataset Results -- 5 Conclusions -- References -- Intelligent Systems ; -- Artificial Neural Network to Estimate Deterministic Indices in Control Loop Performance Monitoring -- 1 Introduction -- 2 Background -- 2.1 Control Performance Monitoring -- 2.2 CPM Performance Indices -- 2.3 Machine Learning -- 2.4 Control-Loop Performance Assessment Whit Machine Learning -- 3 Methodology -- 4 Results -- 4.1 The Model with Machine Learning -- 5 Conclusions -- References -- Interference Mitigation in Multi-radar Environment Using LSTM-Based Recurrent Neural Network -- 1 Introduction.; 2 Signal Model and Interference Effect Analysis -- 3 LSTM-RNN Architecture -- 4 Methodology, Results and Discussions -- 5 Conclusions -- References -- Centrifugal Pump Health Condition Identification Based on Novel Multi-filter Processed Scalograms and CNN -- 1 Introduction -- 2 Experimental Setup -- 3 Proposed Framework -- 4 Results and Performance Evaluation -- 5 Conclusion -- References -- A Closer Look at Attacks on Lightweight Cryptosystems: Threats and Countermeasures -- 1 Introduction -- 1.1 Lightweight Cryptography -- 2 Related Work -- 2.1 Side-Channel Analysis and Countermeasures: -- 2.2 Light Lightweight Cryptographic Algorithm Design: -- 3 Types of Attacks on Cryptosystems -- 3.1 Passive Attacks -- 3.2 Active Attacks -- 4 Cryptographic Attacks -- 4.1 Ciphertext Only Attacks (COA) -- 4.2 Known Plaintext Attack (KPA) -- 4.3 Dictionary Attack -- 4.4 Brute Force Attack (BFA) -- 4.5 Man in Middle Attack (MIM) -- 5 Countermeasures for Lightweight Encryption -- 5.1 Fault Injection Attacks and Protections: -- 5.2 Post-quantum Lightweight Cryptography: -- 5.3 Energy-Efficient Cryptography: -- 5.4 Machine Learning and Lightweight Cryptography: -- 6 Conclusion -- References -- A Prototype of IoT Medication Management System for Improved Adherence -- 1 Introduction -- 2 The Design Methodology of an Innovative Pharmaceutical IoT Medication Product -- 2.1 External Technology of the Product -- 2.2 Internal Technology of the Product -- 2.3 Mobile Application to Control the Product -- 3 Prototype Development of an Innovative Pharmaceutical -- 4 Final Discussion -- References -- Mobile Computing and Ubiquitous Interactions -- Navigating the Complexities of 60 GHz 5G Wireless Communication Systems: Challenges and Strategies -- 1 Introduction -- 2 Weaknesses of the 60 GHz Massive MIMO System -- 3 Proposed Algorithm -- 3.1 Channel Model of Sparse Multipath.; 3.2 SAMP Algorithm -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- A Survey on Channel Estimation Technique Classifications and Various Algorithms -- 1 Introduction -- 2 Channel Estimation -- 2.1 Channel Estimation Classification -- 2.2 Channel Estimation Algorithms -- 3 Discussions and Future Research -- References -- Wearable-Based SLAM with Sensor Fusion in Firefighting Operations -- 1 Introduction -- 2 Method -- 2.1 System Overview -- 2.2 Map Points Calculation (MPC) -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Conclusion -- References -- The Novel Electrocardiograph Sensor and Algorithm for Arrhythmia Computer Aided Detection -- 1 Introduction -- 2 Material and Methods -- 2.1 Proposed ECG Sensor -- 2.2 Pan-Tomkins Algorithm -- 2.3 P-QRS-T Detection -- 3 Experimental Results -- 4 Conclusion -- References -- Optimizing Sensor Subset Selection with Quantum Annealing: A Large-Scale Indoor Temperature Regulation Application -- 1 Introduction -- 2 SSSO Problem in Relation to Temperature Regulation -- 3 Quantum Motivation -- 4 Materials and Methods -- 4.1 Large-Scale Indoor Temperature Sensor Dataset -- 4.2 Our Implementation of the SSSO Problem -- 4.3 Experimental Setup -- 4.4 Hybrid Quantum Implementation Using D-Wave Quantum Annealer -- 5 Experimental ; Results -- 6 Conclusion -- References -- Smart IoT-Based Wearable Lower-Limb Rehabilitation Assistance System -- 1 Introduction -- 2 System Design -- 2.1 Hardware Design -- 2.2 Data Flow and Application Design -- 2.3 Lower-Limb Rehabilitation Activity State Classification Algorithm -- 3 Conclusion -- References -- Using Machine Learning of Sensor Data to Estimate the Production of Cutter Suction Dredgers -- 1 Introduction -- 2 Literature Review -- 2.1 Dredger Productivity Estimation -- 2.2 Dredging Productivity Estimation in Similar Areas -- 2.3 Soil Classification.; 3 Research Setting and Methodology.

Comorbid Conditions Among Children with Autism Spectrum Disorders / / edited by Johnny L. Matson

• Record Nr.: UNINA9910254683903321
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
• ISBN: 3-319-19183-7
• Edizione: [1st ed. 2016.]
• Descrizione fisica: 1 online resource (327 p.)
• Collana: Autism and Child Psychopathology Series, , 2192-922X
• Disciplina: 616.8588200835
• Soggetti: Child psychology; School psychology; Psychiatry; Social work; Child and School Psychology; Social Work
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
• Nota di contenuto: Part 1. Overview.- Chapter 1. The History of Comorbidity in Autism Spectrum Disorders (ASD).- Chapter 2. Scope and Prevalence of the Problem.- Part 2. Assessment.- Chapter 3. Methods and Procedures for Measuring Comorbid Disorders: Psychological.- Chapter 4. Methods and Procedures for Measuring Comorbid Disorders: Medical.- Chapter 5. Methods and Procedures for Measuring Comorbid Disorders: Motor ; Movement and Activity.- Part 3. Psychological Disorders.- Chapter 6. Challenging Behaviors -- Chapter 7. Psychopathology.- Chapter 8. Feeding Disorders -- Chapter 9. Sleep Disorders.- Chapter 10. Epilepsy.- Chapter 11. Gastrointestinal.- Chapter 12. Intellectual Disability (ID).- Part 4. Motor Movement and Activity.- Chapter 13. Developmental Coordination Disorder (DCD).
• Sommario/riassunto: This book presents the similarities and intersections between Autism Spectrum Disorders and comorbid conditions in children. It describes the prevalence and magnitude of comorbid conditions occurring in conjunction with ASD that complicate diagnosis and can potentially lead to inappropriate treatment and negative outcomes. It addresses the strengths and limitations of age-appropriate assessment measures as well as activity and motor skill measurement methods. Specific comorbid disorders are examined through the review of core symptoms, prognostic and diagnostic issues, and treatment options for children on the ASD spectrum. Featured topics include: Challenging behaviors in children with ASD. Conditions ranging from feeding and gastrointestinal disorders to epilepsy. Developmental coordination disorder (DCD). Intellectual disability (ID). Methods and procedures for measuring comorbid psychological, medical, and motor disorders. < Comorbid Conditions Among Children with Autism Spectrum Disorders is a must-have resource for researchers, clinicians and professionals, and graduate students across such fields as clinical child, school, and developmental psychology, child and adolescent psychiatry, and social work as well as rehabilitation medicine/therapy, behavioral therapy, pediatrics, and educational psychology.