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[null,"1.","Record Nr.",null,"UNINA990001688710403321"]
[null,null,"Autore",null,"Gymer, Roger G."]
[null,null,"Titolo",null,"La chimica e la natura / Roger G. Gymer ; traduzione a cura del prof. Antonino Fava"]
[null,null,"Pubbl/distr/stampa",null,"Milano : Piccin Ed., 1983"]
[null,null,"ISBN",null,"88-212-1069-3"]
[null,null,"Descrizione fisica",null,"XV, 572 p. : ill. ; 24 cm"]
[null,null,"Disciplina",null,"540"]
[{"$nulls":4},"577.14"]
[null,null,"Locazione",null,"FAGBC"]
[null,null,"Collocazione",null,"60 577.14 GYMR 1983"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910736019003321"]
[null,null,"Autore",null,"Nguyen Ngoc Thanh"]
[null,null,"Titolo",null,"The 12th Conference on Information Technology and Its Applications : Proceedings of the International Conference CITA 2023 / / edited by Ngoc Thanh Nguyen, Hoa Le-Minh, Cong-Phap Huynh, Quang-Vu Nguyen"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"9783031368868"]
[{"$nulls":4},"303136886X"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (414 pages)"]
[null,null,"Collana",null,"Lecture Notes in Networks and Systems, , 2367-3389 ; ; 734"]
[null,null,"Disciplina",null,"004"]
[null,null,"Soggetti",null,"Engineering - Data processing"]
[{"$nulls":4},"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Data Engineering"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Conference Organization -- Contents -- Data Science and Artificial Intelligence -- A New ConvMixer-Based Approach for Diagnosis of Fault Bearing Using Signal Spectrum -- 1 Introduction -- 2 Related Work -- 2.1 Conv-Mixer Neural Networks -- 2.2 Siamese Neural Networks -- 3 Methodology -- 3.1 General Architecture for Failure Diagnosis -- 3.2 The Proposed Siamese-Based Conv-Mixer Model -- 3.3 Diagnosis Network -- 4 Experiment -- 4.1 Datasets -- 4.2 Training -- 4.3 Results -- 4.4 Comparison -- 5 Conclusion -- References -- Differentially-Private Distributed Machine Learning with Partial Worker Attendance: A Flexible and Efficient Approach -- 1 Introduction -- 1.1 Background -- 1.2 Our Contributions -- 1.3 Paper Organization -- 2 Preliminaries -- 3 Our Proposed Algorithm -- 4 Experiments -- 5 Conclusion -- References -- Building Legal Knowledge Map Repository with NLP Toolkits -- 1 Introduction -- 2 Legal Knowledge Maps -- 2.1 Modeling -- 2.2 Hierarchy of Legislation -- 2.3 Legal Ontology Design -- 2.4 Legal Knowledge Map Construction -- 3 Implementation -- 3.1 Materials -- 3.2 Vietnamese NLP Toolkits -- 3.3 Building VLegalKMaps as Linked Data -- 4 "]
[{"$nulls":4},"Validations -- 4.1 Experiment Setup -- 4.2 Case Study -- 4.3 Statistics and Discussions -- 5 Conclusions and Future Works -- References -- Classification of Ransomware Families Based on Hashing Techniques -- 1 Introduction -- 2 Overview of Hashing Techniques in Malware Analysis -- 3 The Proposed Method -- 3.1 The Combined Analysis Method of Imphash, File Level Ssdeep Hashing, and Section Level Ssdeep Hashing -- 3.2 Preparing the Database -- 3.3 Predictive Model -- 3.4 Evaluation Criteria -- 4 Evaluations and Results -- 4.1 Experiment with Test Set Containing only Ransomware -- 4.2 Experiment with Test Set Containing both Malicious and Benign Samples."]
[{"$nulls":4},"4.3 Advantages and Limitations of the Proposed Method -- 5 Conclusions -- References -- Towards a New Multi-tasking Learning Approach for Human Fall Detection -- 1 Introduction -- 2 Related Work -- 2.1 Simulated Falls -- 2.2 Real Falls -- 2.3 Multi-task Learning -- 2.4 Summary -- 3 Multi-task Deep Neural Network for Fall Detection -- 3.1 Multiple Classifiers -- 3.2 Temporal Convolutional Network as a Feature Extractor -- 3.3 Re-sampling for Class and Task Balance -- 3.4 Data Augmentation -- 4 Experiments -- 4.1 Datasets -- 4.2 Experiment Settings -- 4.3 Evaluation and Discussion -- 5 Conclusion and Future Work -- References -- A Comparative Study of Wrapper Feature Selection Techniques in Software Fault Prediction -- 1 Introduction -- 2 Related Work -- 3 Feature Selection -- 3.1 Software Metrics -- 3.2 Genetic Algorithm -- 3.3 Particle Swarm Optimization -- 3.4 Whale Optimization Algorithm -- 3.5 Cuckoo Search -- 3.6 Mayfly Algorithm -- 3.7 Binary Bat Algorithm -- 3.8 Feature Selection Details -- 4 Methodology -- 4.1 Proposed Approach -- 4.2 VanillaGAN for Handling Imbalanced Data -- 4.3 Dataset -- 4.4 Evaluation Measurement -- 5 Experimental Result -- 6 Conclusion -- References -- Incorporating Natural Language-Based and Sequence-Based Features to Predict Protein Sumoylation Sites -- 1 Introduction -- 2 Methodology -- 2.1 Data Preparation and Pre-processing -- 2.2 Feature Extraction and Encoding -- 2.3 Model Construction, Learning and Evaluation -- 3 Results and Discussion -- 3.1 Impact of Amino Acid Composition and Single Features -- 3.2 Impact of Hybrid Features -- 3.3 RSXSUMO Model Construction -- 3.4 Comparison with Other Predictors -- 4 Conclusion -- References -- A Model for Alliance Partner Selection Based on GM (1, 1) and DEA Frameworks - Case of Vietnamese Coffee Industry -- 1 Introduction -- 2 Related Works -- 2.1 Strategic Alliance."]
[{"$nulls":4},"2.2 Grey Forecasting Model -- 2.3 Data Envelopment Analysis -- 3 Proposal Research -- 4 Case Study -- 4.1 DMU Collection -- 4.2 Inputs and Outputs Selection -- 4.3 Forecast the Performance of All DMU by GM (1, 1) Model. -- 4.4 Analysis Performance Before Alliance -- 4.5 Analysis the Performance After Alliance -- 5 Conclusions -- References -- Car Detector Based on YOLOv5 for Parking Management -- 1 Introduction -- 2 Related Works -- 2.1 Traditional Machine Learning-Based Methods -- 2.2 CNN-Based Methods -- 3 Methodology -- 3.1 Proposed Network Architecture -- 3.2 Loss Function -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Setup -- 4.3 Experimental Results -- 4.4 Ablation Study -- 5 Conclusion -- References -- Deep Learning-Based Approach for Automatic Detection of Malaria in Peripheral Blood Smear Images -- 1 Introduction -- 2 Related Works -- 3 Experiments -- 3.1 Data Collection -- 3.2 Exploratory Data Analysis -- 3.3 Two-Stage Approach -- 4 Results and Discussions -- 4.1 Evaluation Metrics -- 4.2 Results -- 5 Conclusion -- References -- An Improved Transfer Learning-Based Approach for Detecting Abnormal Cervical Cells from Pap Smear Microscopic Images -- 1 "]
[{"$nulls":4},"Introduction -- 2 Abnormal Cervical Cells and Preprocessing Data -- 2.1 Abnormal Cervical Cells -- 2.2 Exploratory Data Analysis and Preprocessing -- 3 Transfer Learning and Proposed Approach -- 3.1 ResNet50v2 -- 3.2 EfficientNetv2L -- 3.3 Proposed Approach Based on Transfer Learning -- 4 Experimental Results -- 5 Conclusion -- References -- Digital Economy -- Emotional Intelligence and Social Media Site Experiences' Effects on College Choice Behavior: The Mediating Role of Brand Attitude -- 1 Introduction -- 2 Theoretical Background and Hypotheses -- 2.1 Website Experiences and Emotional intelligence -- 2.2 The Attitude Toward Website Model - AWS Model."]
[{"$nulls":4},"2.3 The Research Model and Hypotheses -- 3 Research Method -- 4 Research Result -- 4.1 Descriptive Data Statistics -- 4.2 Reliability Test Results -- 4.3 Exploratory Factor Analysis (EFA) Results -- 4.4 Research Model Testing -- 5 Discussion -- 6 Conclusion -- References -- Image and Natural Language Processing -- A Multi Context Decoder-based Network with Applications for Polyp Segmentation in Colonoscopy Images -- 1 Introduction -- 2 Related Work -- 2.1 Vision Transformer -- 2.2 Fusion On Multi Resolution Feature Map -- 3 Methodology -- 3.1 Overview -- 3.2 Generate Context Feature Map (GCF) -- 3.3 Decoder Block -- 4 Experiments -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Implementation Details -- 4.4 Representative Results -- 4.5 Comparative Results -- 5 Conclusion -- References -- AMG-Mixer: A Multi-Axis Attention MLP-Mixer Architecture for Biomedical Image Segmentation -- 1 Introduction -- 2 Related Work -- 3 Proposed Network Architecture -- 3.1 AxialMBConv Token Mix and Mixer Building Block -- 3.2 Multi-scale Multi-axis MLP Gated (MS-MAMG) -- 3.3 Decoder Unit -- 4 Experiments -- 4.1 Datasets -- 4.2 Training Strategy -- 4.3 Evaluation Metrics -- 4.4 Representative Results -- 4.5 Comparative Results -- 5 Conclusion -- References -- Investigating YOLO Models for Rice Seed Classification -- 1 Introduction -- 2 Methodology -- 2.1 YOLOv5 -- 2.2 YOLOv6 -- 2.3 YOLOv7 -- 3 Experiments and Results -- 3.1 Data Description -- 3.2 Performance Indicator -- 3.3 Result and Discussion -- 4 Conclusion -- References -- Extending OCR Model for Font and Style Classification -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 Problem Formulation -- 3.2 Overview -- 3.3 Encoder -- 3.4 Decoder -- 3.5 Image-wise Font Clsasification -- 3.6 Style Classification -- 3.7 Loss Function -- 4 Experiments -- 4.1 Experiment Setting -- 4.2 Benchmarks."]
[{"$nulls":4},"4.3 Experiment Result and Discussion -- 5 Conclusion -- References -- STG-SimVP: Spatiotemporal GAN-Based SimVP for Video Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Video Frame Synthesis -- 2.2 Generative Adversarial Networks - GAN -- 2.3 SimVP -- 3 Proposed Methods -- 3.1 STG-SimVP -- 3.2 Dual Discriminators -- 3.3 Objective Function -- 4 Experiments -- 4.1 Datasets -- 4.2 Training Details -- 4.3 Comparisons With State-of-the-Art Methods -- 5 Ablation Study -- 6 Limitations -- 7 Conclusion -- References -- Tritention U-Net: A Modified U-Net Architecture for Lung Tumor Segmentation -- 1 Introduction -- 2 Tritention U-Net Architechture (TU-Net) -- 2.1 Architechture Overview -- 2.2 Backbone U-Net Architecture -- 2.3 Tritention Gate -- 3 Experimental and Results -- 3.1 Dataset -- 3.2 Experimental Setup -- 3.3 Results -- 4 Conclusion -- References -- Multi-modal with Multiple Image Filters for Facial Emotion Recognition -- 1 Introduction -- 2 Multiple Filter Levels for FER -- 2.1 Multiple Model -- 2.2 Dropping Pixels - Processor -- 2.3 Blurring Image - Processor -- 3 Experimental and Results -- 3.1 Dataset -- 3.2 Experimental Setup -- 3.3 Results -- 4 Conclusion -- References -- Few-Shots Novel Space-Time View Synthesis from Consecutive Photos "]
[{"$nulls":4},"-- 1 Introduction -- 2 Related Work -- 3 Proposed Methods -- 3.1 Background: Neural Scene Flow Fields (NSFF) -- 3.2 NSFF with Encoder -- 4 Experiments -- 4.1 Implement Details -- 4.2 Evaluations -- 5 Limitations -- 6 Conclusion -- References -- Information Technology Skills Extractor for Job Descriptions in vku-ITSkills Dataset Using Natural Language Processing -- 1 Introduction -- 2 Preliminary -- 3 Construct IT Skills Dictionary and vku-ITSkills Dataset -- 4 The Proposed NLP Pipeline for IT Skills Extractor -- 4.1 Tokenizer -- 4.2 Transformers Based Token Embedding."]
[{"$nulls":4},"4.3 Part of Speech (POS) Tagging, Noun Phrases and Combination Rules."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed proceedings of the 12th Conference on Information Technology and its Applications, CITA 2023, taking place on July 28-29, 2023 in Da Nang City, the most beautiful and livable city in Vietnam. CITA is an annual scientific conference on information technology and its applications in all fields. The main objective of the conference is to create a forum to gather and connect Vietnamese and international researchers, scientists in the fields of information technology and its applications. The book includes 33 papers, selected from 144 papers submitted to CITA 2023 whose authors come from over 20 countries around the world, which were carefully reviewed by at least two members of the Program Committee, with professional advice from reputable scientists in the field of information technology and technology, digital economy such as Prof. Dr.Sc. Ngoc-Thanh Nguyen (Poland), Prof. Dr. Dosam Hwang (Korea), Assoc. Prof. Dr. Le Minh Hoa (UK), and Prof.Dr. Nguyen Thanh Thuy (Vietnam). The acceptance rate of CITA 2023 is about 24%. The papers in the book are organized in the following topical sections: Data Science and Artificial Intelligence; Image and Natural Language Processing; Software Engineering and Information Systems; Network and Communications; and Digital Economy. The accepted and presented papers focus on new trends and challenges facing the information and communication technology as well as digital economy community. If you are scientists, lecturers, doctoral students, we hope that you will find many useful and good quality results from the book for your future research."]