The proceedings contain 19 papers. The topics discussed include: artificial intelligence application in renewable energy sources;intelligent system for visual testing of software products;verifying the economic potent...
The proceedings contain 19 papers. The topics discussed include: artificial intelligence application in renewable energy sources;intelligent system for visual testing of software products;verifying the economic potential of low-carbon energy using artificial intelligence in transport;enhancing the efficiency of decision support systems in the warehousing sector;data transformation review in deep learning;comparative analysis of CNN architecture for emotion classification on human faces;content analysis of court decisions: a GPT-4 based sentence-by-sentence data generation and association rules mining;exploring the future of UAE judiciary: ai integration, bias mitigation, and systemic enhancements;comparative analysis of stress factors of humanities and technical specialities students;integrated approach to the international aspects of online dispute resolution formation;fuzzy audit system of enterprise activity;and does expectations affect inflation forecasting abilities of machinelearning techniques: case of Ukraine.
The proceedings contain 7 papers. The topics discussed include: interactive trace clustering to enhance incident completion time prediction in process mining;pattern-based reconstruction of anomalous traces in busines...
The proceedings contain 7 papers. The topics discussed include: interactive trace clustering to enhance incident completion time prediction in process mining;pattern-based reconstruction of anomalous traces in business process event logs;impact of non-fitting cases for remaining time prediction in a multi-attribute process-aware method;continual-learning-as-a-service (CLaaS): on-demand efficient adaptation of predictive models;efficient anomaly detection on temporal data via echo state networks and dynamic thresholding;making FreeRTOS pervasive systems learn to select energy saving technique for mixed taskset;and a cloud-based continual learning system for road sign classification in autonomous driving.
The acceleration of smart grid construction imposes higher demands on the intelligent planning of power transmission and transformation projects. To address the inefficiencies and high costs in existing planning metho...
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ISBN:
(纸本)9798400707032
The acceleration of smart grid construction imposes higher demands on the intelligent planning of power transmission and transformation projects. To address the inefficiencies and high costs in existing planning methods, this paper proposes an intelligent planning approach based on multi-source heterogeneous data integration and artificial intelligence. By integrating multi-source heterogeneous data to analyze on-site information, and utilizing Bayesian networks and Convolutional Neural Networks with Attention Mechanisms (CNNAM), the planning and construction processes of power transmission and transformation projects are optimized. This approach significantly improves the accuracy and reliability of cost estimation, providing strong data support and technical assurance for the intelligent planning of power transmission and transformation projects, thereby making the planning process more effective and practical.
In this paper, we delve into the intricate relationship between technology, music, and success. Our research focuses on leveraging the capabilities of machinelearning algorithms to forecast the success and popularity...
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The proceedings contain 12 papers. The special focus in this conference is on Explainable Artificial Intelligence in Healthcare. The topics include: Interpreting machinelearning Models for Survival Analysis: A S...
ISBN:
(纸本)9783031543029
The proceedings contain 12 papers. The special focus in this conference is on Explainable Artificial Intelligence in Healthcare. The topics include: Interpreting machinelearning Models for Survival Analysis: A study of Cutaneous Melanoma Using the SEER database;probExplainer: A Library for Unified Explainability of Probabilistic Models and an Application in Interneuron Classification;An Explainable AI Framework for Treatment Failure Model for Oncology Patients;explanations of Symbolic Reasoning to Effect Patient Persuasion and Education;explainable Artificial Intelligence in Response to the Failures of Musculoskeletal Disorder Rehabilitation;phenotypes vs Processes: Understanding the Progression of Complications in Type 2 Diabetes. A Case study;A data-Driven Framework for Improving Clinical Managements of Severe Paralytic Ileus in ICU: From Path Discovery, Model Generation to Validation;preface;understanding Prostate Cancer Care Process Using Process mining: A Case study;From Script to Application. A bupaR Integration into PMApp for Interactive Process mining Research.
The proceedings contain 16 papers. The topics discussed include: artificial intelligence for the future of construction;cobots and industrial robots;predictive maintenance for wind turbine bearings: an MLOps approach ...
The proceedings contain 16 papers. The topics discussed include: artificial intelligence for the future of construction;cobots and industrial robots;predictive maintenance for wind turbine bearings: an MLOps approach with the DIAFS machinelearning model;development of an artificial intelligence tool and sensing in informatization systems of mobile robots;PCA-NuSVR framework for predicting local and global indicators of tunneling-induced building damage;design and deployment of data development toolkit in cloud manufacturing environments;research and development of image processing algorithms for effective recognition of various gestures in real time;machinelearning models for the recognition of commands in smart home technologies;responsive dehydration: sensor-driven optimisation of production cycles in a solar dehydrator;and formation of the method of description and control of the relative position of the links of the upper limbs of the grip of an anthropomorphic robot.
In response to the challenge of surface waste detection, an advanced surface waste recognition algorithm based on YOLOV8 has been carefully developed. The RepVGG module is used to replace the traditional Conv module, ...
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ISBN:
(纸本)9798400707032
In response to the challenge of surface waste detection, an advanced surface waste recognition algorithm based on YOLOV8 has been carefully developed. The RepVGG module is used to replace the traditional Conv module, so the detection speed and accuracy of the model are significantly improved in the inference stage. At the same time, in order to further enhance the training effect of the model, Wasserstein Distance Loss was introduced as a loss function to optimize the training process of the model and further enhance its training accuracy. After rigorous experimental verification, the experimental data have excellent performance, and the improved network model has an average precision mean (mAP) of 82.6%, which proves its high-precision performance in target detection, effectively reduces the case of missing detection, and meets the strict requirements for surface garbage detection.
In the current transition of warehousing and logistics companies from traditional databases to knowledge bases, numerous challenges arise, including low efficiency due to massive data volumes and extended investment r...
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ISBN:
(纸本)9798400707032
In the current transition of warehousing and logistics companies from traditional databases to knowledge bases, numerous challenges arise, including low efficiency due to massive data volumes and extended investment recovery periods due to high implicit costs. To address these issues and enable the rapid construction of a Knowledge Graph (KG) utilizing existing semi-structured data, this paper introduces an automated method for reading Excel content, identifying KG ontologies and entities, and importing data into Neo4j software. Firstly, the method is designed to automatically extract internal data from Excel, achieving the automatic recognition of KG ontologies and entity information. Secondly, this method is tailored to the KG triplet structure, enabling the automated transcription of these triplets into Neo4j software. Thirdly, to enhance the universal adaptability of the method, the functionality has been extended to enable arbitrary additions, reductions, and modifications to the content and data length of Excel spreadsheets. Finally, experiments have validated the method's effectiveness, universal applicability, and convenience. Moreover, this method is broadly applicable across various industries, offering an efficient approach for the automatic construction of KGs by business personnel.
The proceedings contain 36 papers. The special focus in this conference is on Web Information Systems Engineering. The topics include: Effective Transparent Monitoring of Personal data;iCNN-LstM: An Incremental C...
ISBN:
(纸本)9789819614820
The proceedings contain 36 papers. The special focus in this conference is on Web Information Systems Engineering. The topics include: Effective Transparent Monitoring of Personal data;iCNN-LstM: An Incremental CNN-LstM Based Ransomware Detection System;a Mini Review on Purchaser Security in the Metaverse: Challenges and Solutions;low-Resource dataset Synthetic Generation for Hate Speech Detection;Web Open data to SDG Indicators: Towards an LLM-Augmented Knowledge Graph Solution;leveraging Sentence-Transformers to Overcome Query-Document Vocabulary Mismatch in Information Retrieval;time Distance Aware for Multi-component Graph Collaborative Filtering;scientific Documents Recommendation Based on Graph Convolutional Network;semantic Communication of Images Using Image Generation and Image Captioning Models;leveraging Optimization Techniques for Effective Arabic Query Expansion;DURLLCON: Deep Reinforcement learning for URLLC Optimization in Multi-edge Networks;FMM-RNS: A Fast HMM Map Matching Method Based on Road Network Simplification;Context-Aware Selection of machinelearning as a Service (MLaaS) in IoT Environments;GraphTFD: A Fraud Detection System Based on Graph Transformer;MLGE-AC-UFD: Multi-level Graph Embedding and Approximate Computation for Unsupervised Fraud Detection;SeCORE: Quantitative Security Assurance and Evaluation Platform;developing Geospatial Web Applications Using Question Answering Engines, Knowledge Graphs and Linked data Tools;A Visual Query Builder for DBpedia;FL-PPELA: Partial Parameter Enhancement and Local Adaptive Aggregation for Personalized Federated learning;ORCPM: An Online Regional Core patternmining System;MTRM: A Web-Miner Multi-Threshold mining Co-location patterns to Mitigate Redundancy;constrained Path Optimization on Time-Dependent Road Networks;prompt strategies for Sarcastic Meme Detection: A Comparative Analysis;Deepfake Detection in Cancer Medical Imaging Using CNN Architectures;strengthening Cybersecurity: The Influence o
Sign Language Processing (SLP) provides a foundation for a more inclusive future in language technology;however, the field faces several significant challenges that must be addressed to achieve practical, real-world a...
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Sign Language Processing (SLP) provides a foundation for a more inclusive future in language technology;however, the field faces several significant challenges that must be addressed to achieve practical, real-world applications. This work addresses multi-view isolated sign recognition (MV-ISR), and highlights the essential role of 3D awareness and geometry in SLP systems. We introduce the NGT200 dataset, a novel spatio-temporal multi-view benchmark, establishing MV-ISR as distinct from single-view ISR (SV-ISR). We demonstrate the benefits of synthetic data and propose conditioning sign representations on spatial symmetries inherent in sign language. Leveraging an SE(2) equivariant model improves MV-ISR performance by 8%-22% over the baseline. Copyright 2024 by the author(s).
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