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AI Driven IoT Web-based Application for Automatic Segmentation and Reconstruction of Abdominal Organs from Medical images 18

AI Driven IoT Web-Based Application for Automatic Segmentati...

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18th Annual international conference on Distributed Computing in Sensor systems (DCOSS)

作者： Villarini, Barbara Asaturyan, Hykoush A. Univ Westminster Sch Comp Sci & Engn London England

ISBN: (纸本)9781665495127

Medical imaging technology has rapidly advanced in the last few decades, providing detailed images of the human body. The accurate analysis of these images and the segmentation of anatomical structures can produce significant morphological information, provide additional guidance toward subject stratification after diagnosis or before a clinical trial, and help predict a medical condition. Usually, medical scans are manually segmented by expert operators, such as radiologists and radiographers, which is complex, time-consuming and prone to inter-observer variability. A system that generates automatic, accurate quantitative organ segmentation on a large scale could deliver a clinical impact, supporting current investigations in subjects with medical conditions and aiding early diagnosis and treatment planning. This paper proposes a web-based application that automatically segments multiple abdominal organs and muscle, produces respective 3D reconstructions and extracts valuable biomarkers using a deep learning backend engine. Furthermore, it is possible to upload image data and access the medical image segmentation tool without installation using any device connected to the internet. The final aim is to deliver a webbased image-processing service that clinical experts, researchers and users can seamlessly access through IoT devices without requiring knowledge of the underpinning technology.

关键词： IoT Web Application Deep Learning 3D Reconstruction Web technology Medical image Computing Organ Segmentation

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15th EAI international conference on Bio-inspired Information and Communications Technologies, BICT 2024

15th EAI International Conference on Bio-inspired Informatio...

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15th EAI international conference on Bio-inspired Information and Communications Technologies, BICT 2024

ISBN: (纸本)9783031815980

The proceedings contain 16 papers. The special focus in this conference is on Bio-inspired Information and Communication Technologies. The topics include: Optimizing Drug Delivery Strategies by Pathway Analysis for Waveform Modulation-based Molecular Communication;Enhancing DNA-based IoBNT Throughput and Reducing Congestion with Yin-Yang Coding;a Molecular Communication Model Driven by Magnetic Field Force;CDM based on Izhikevich Neuron Model;multi-user Diffusive Molecular Communication systems with A Passive Relay Node: Receiver Design and Performance Analysis;machine Learning-based Detection Time Estimation for Molecular Communication;taming signal-Dependent Counting Noise with Machine Learning for Molecular Communication;energy-Efficient Transmitter Creation in Molecular Communication;a Method for Determining Relay Node Location in Molecular Communication;glycemic Oscillation Decomposition-based Personalized Blood Glucose Prediction with Continuous Glucose Monitoring;A Compact Bio-inspired Microstrip Antenna (Bi-MPA) for Medical Microwave Imaging Applications;image Encryption and Decryption Algorithm based on DNA Sequence: Performance Analysis of Channel Fusion Processing;Optimizing the Classification of SSVEP signals in Brain-Computer Interfaces: A Novel Sliding Window Data Segmentation Method based on Weighted Voting Mechanism;spontaneous Motion of Nanorobots Inspired Computational technology for Tumor Boundary Exploration.

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Research on adolescents with CHD-PAH based on the Choi-Williams analysis of the Second Heart Sound 3

Research on adolescents with CHD-PAH based on the Choi-Willi...

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3rd international conference on Biomedical and Intelligent systems, IC-BIS 2024

作者： Fan, Qingling Pan, Jiahua Yang, Hongbo Wang, Weilian School of Electrical Engineering and Intelligent Manufacturing Chongqing Metropolitan College of Science and Technology Chongqing China Yunnan Fuwai Cardiovascular Disease Hospital Kunming China School of Information Science and Technology Yunnan University Kunming China

ISBN: (纸本)9781510681279

Congenital Heart Disease (CHD) complicated with Pulmonary Artery Hypertension (CHD-PAH) is one of the more harmful CHD-related complications. The objective of this paper was to develop a algorithm to study CHD-PAH from the perspective of heart sounds. This could enable adolescents to be detected and treated early without the need for expensive equipment or specialist skills. For this purpose an algorithm was designed. According to the pathological signs of CHDPAH in terms of heart sounds, i.e., it is mainly reflected in the hyperactive P2 of pulmonary valve component and the presence of A2 and P2 splitting. An image generator was used to feed the Choi-Williams distribution features of the Second Heart Sound (S2) into a convolutional neural network for training. A accuracy of 94.1% and a sensitivity of 94.9% were achieved using novel signal processing techniques and an ensemble of neural networks as classifier. © 2024 SPIE.

关键词： Heart

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Research on Acquisition Method of DSSS System based on PMF-FFT 8

Research on Acquisition Method of DSSS System Based on PMF-F...

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8th international conference on Communication, image and signal Processing, CCISP 2023

作者： Wang, Xinyu Jiang, Kun Chu, Ran Zhang, Haozhe Wang, Changheng School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China Shanghai Aerospace Electronic Technology Institute Shanghai Academy of Spaceflight Technology Shanghai China Jiangsu YEE-Space Aerospace Technology Co. LTD Starboard Electronics Department Nanjing China

ISBN: (纸本)9798350305838

Spread spectrum communication, as an essential communication technique, has a wide range of applications in the real world. This article focuses on the acquisition methods in DSSS (direct sequence spread spectrum) systems. The PMF-FFT (Partial Match Filtering Fast Fourier Transform) algorithm, recognized as an excellent acquisition algorithm, combines timedomain and frequency-domain acquisition algorithms, exhibiting characteristics such as high dynamic range and fast acquisition speed. Firstly, the basic principles of the PMF - FFT algorithm are introduced, and a corresponding mathematical model is established to analyze the characteristics of this algorithm. Secondly, improvements are made in response to the practical design requirements and issues in multi-rate, multi-user communication systems. These improvements mainly include the selection of spread spectrum sequences, frame composition, and acquisition architecture. Through these improvements, the algorithm's performance is enhanced. Finally, through simulation verification at rates of 16Kbps and 128Kbps, the improved algorithm successfully achieved acquisition of eight different time slots under a significant Doppler frequency. © 2023 IEEE.

关键词： Fast Fourier transforms

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Knowledge graph construction for power grid systems based on fuzzy matching algorithm 3

Knowledge graph construction for power grid systems based on...

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3rd international conference on Advanced Algorithms and signal image Processing, AASIP 2023

作者： Haitao, Gui Junyang, Tian Heming, Hou Renming, Li Guilin Power Supply Bureau Guangxi Power Grid Co Ltd Guilin Guangxi541002 China Guangxi Power Grid Power Dispatching and Control Center Nanning Guangxi530023 China

ISBN: (纸本)9781510668522

To facilitate the processing of data pertaining to defects and faults in the power grid regulation system, as well as knowledge graph-based support to help regulators in their decision-making, a knowledge graph construction method employing a fuzzy matching algorithm has been devised, the outcomes are presented in the form of a visual knowledge graph. Initially, a fuzzy matching algorithm is devised to to match the defect with the defect-fault database. Subsequently, the Neo4j database is utilized to construct a knowledge graph that provides guidance on fault locations. Lastly, by conducting a case analysis of the data extracted from a specific region's distribution network, experimental results demonstrate the method's capability to accurately match target data. Moreover, the visual knowledge graph constructed has proven effective in enhancing regulators' decision-making efficiency. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Defects

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Revolutionizing Travel Planning: An image based Destination Recognition and Recommendation System 1

Revolutionizing Travel Planning: An Image Based Destination ...

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1st international conference on Advanced Computing and Emerging Technologies, ACET 2024

作者： Gupta, Megha Goyal, Vanshika Rathi, Vanshika Jss Academy of Technical Education Computer Science and Engineering Uttar Pradesh Noida India

ISBN: (纸本)9798350367720

Due to the abundance of information available online and the wide range of possibilities available, our preparation has become more difficult and time-consuming. This is especially true given that every visitor has different interests and preferred destinations in addition to tour-specific limitations like vaccination records and travel restrictions due to pandemics. A number of travel agencies and organizations have sprung up with more advanced internet services in an attempt to take advantage of the growing global travel market by employing technology to provide travelers with relevant recommendations. However, these systems often use a destination-based recommendation strategy and are sold in packages with little room for modification to account for the tastes of individual travelers. In order to overcome these restrictions. With the use of artificial intelligence-powered picture recognition, our TravelGaze system can now identify destinations from user-uploadedimages, marking a significant advancement in travel technology. In addition to recognition, the system offers customized trip suggestions that include neighboring lodging options, eateries, art galleries, and current weather information. The solution improves destination recognition accuracy and revolutionizes travel planning by utilizing cutting-edge AI algorithms. This paper offers insights for developers and stakeholders looking to reinvent how consumers explore and plan their travels, adding to the ongoing conversation on intelligent travel solutions. © 2024 IEEE.

关键词： Tourism

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A multi-level and multi-agent collaborative control platform for city-scale virtual power plants based on a cloud-pipe-edge-end fusion architecture 4

A multi-level and multi-agent collaborative control platform...

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4th international signal Processing, Communications and Engineering Management conference, ISPCEM 2024

作者： Baorong, Zhou Jiangnan, Li Wenmeng, Zhao Tao, Wang Biao, Zhao Wenyuan, Zheng Guanglei, Huang Mingyu, Ou Electric Power Research Institute China Southern Grid Guangzhou510530 China Shenzhen Power Supply Bureau Co. Ltd. Shenzhen518000 China Tsinghua University Shenzhen International Graduate School Shenzhen518000 China

ISBN: (纸本)9798331528676

With the continuous expansion and complexity of urban power grids, traditional power control methods are difficult to meet the needs of multi-agent, multi-energy and multi-level in modern power grids. To address this problem, this paper proposes a multi-level and multi-agent collaborative control platform for urban-scale virtual power plants based on a cloud-pipe-edge-end fusion architecture. By introducing technologies such as cloud computing, edge computing and the internet of Things, the platform designs a multi-level control architecture that includes functional modules such as physical information modeling, resource aggregation optimization, automatic power control and instruction decomposition. The innovation of the platform lies in its ability to enable the full process of adjustable resources on the load side of the virtual power plant to participate in the automatic generation control (AGC) and automatic voltage control (AVC) of the power grid, and integrates intelligent monitoring and traceability technology of electric carbon, providing real-time and efficient power control and carbon emission management. Through actual case analysis and verification, the platform is significantly superior to traditional systems in terms of supply and demand balance, response speed, energy efficiency optimization and carbon emission management, which improves the overall operation efficiency and stability of the power grid and provides strong technical support for the intelligent management of urban power grids. ©2024 IEEE.

关键词： Cloud platforms

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Joint Beam-Time Allocation of Phased Array Radar based on Variable False Alarm Rate Detection 8

Joint Beam-Time Allocation of Phased Array Radar Based on Va...

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8th international conference on signal and image Processing, ICSIP 2023

作者： Liao, Maosen Tan, Rui Xiong, Kui Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China

ISBN: (纸本)9798350397932

Conventional searching methods with only one constant false alarm rate can no longer provide effective detection performance for different remote targets associated with distinct signal-to-noise ratios in radar systems. To overcome this problem, this paper presents a dynamic joint beam and time resource allocation strategy based on variable false alarm rate detection framework for phased array radar for remote target searching. Specifically, a multi-stage searching framework of the phased array radar is first developed, where the false alarm probability for detection increases adaptively with the stage evolving. Then, a constrained allocation model of the beam and time is formulated. Simulation results demonstrate the effectiveness and superiority of the proposed algorithm against some counterparts in terms of detection performance and efficiency of resource utilization. © 2023 IEEE.

关键词： Errors

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Intelligent Edge-based System for Driver Drowsiness Monitoring in Mobile Crowd-sourcing Environments 2

Intelligent Edge-Based System for Driver Drowsiness Monitori...

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2nd international conference on Recent Trends in Microelectronics, Automation, Computing, and Communications systems, ICMACC 2024

作者： Neels Ponkumar, D. David Ramesh, S. Ahamed, A. Niyas Baskar, S. Ashok, Chitrada Charan, M. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India School of Computing College of Engineering and Technology SRMIST Department of Computing Technologies Kattankulathur Campus Tamil Nadu Chengalpattu India Thamirabharani Engineering College Department of Electronics and Communication Engineering Tamil Nadu Tirunelveli India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Civil Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350366570

Using CNN and GAN improves road safety, says study. Modern machine learning techniques for mobile crowdsourcing may identify driver fatigue early. Our convolutional neural network (CNN) model detects drivers' fatigue using facial expressions, head movements, and other visual clues. Mobile devices and high-resolution cameras make the system straightforward to install in automobiles. GAN (Generative Advisal Network) handles unequal and limited training data. Creating realistic, synthetic weary driver photos improves the dataset and helps CNN learn from different driving scenarios and face features. Our edge-based computing distinguishes it. In mobile crowdsourcing with unpredictable internet connections, processing data locally on users' smartphones minimizes latency and bandwidth. The edge-based solution processes sensitive data locally on the device rather than sending it to servers, increasing user privacy. Extensive testing showed our system diagnosed driver weariness better than others. GAN-generated data increased model performance in under-represented training datasets. The study shows how to merge CNN and GAN in edge computing with 98.4% accuracy and driver fatigue monitoring. We found important implications for mobile crowdsourcing and intelligent transportation system development. © 2024 IEEE.

关键词： Convolutional neural networks

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18th international KES conference on Agents and Multi-Agent systems: Technologies and Applications, KES-AMSTA 2024

18th International KES Conference on Agents and Multi-Agent ...

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18th international KES conference on Agents and Multi-Agent systems: Technologies and Applications, KES-AMSTA 2024

ISBN: (纸本)9789819764686

The proceedings contain 34 papers. The special focus in this conference is on Agents and Multi-Agent systems: Technologies and Applications. The topics include: Fair Path Generation for Formation Control Combining Ant Colony and Particle Swarm Optimizations;preference Definition in a Multi-agent System Approach for User-Centric internet of Things Smart Environments;AI-Driven Nitrogen Stress Management in Cereal Crops via Drone technology;agent-based Simulation for Withdrawal of Energy-Inefficient Housing;resource Limitations of Business Process Simulations: Literature Study;data Augmentation for Business Process Alignment: Proof of Concept and Experimental Design;smart Scheduling in Urban Traffic: A Multi-Agent System for Dynamic Vanpooling;analysis of the Impact on Area Prices Using Propensity Score Matching, Considering the Proportions of Photovoltaic and Thermal Power Generation Simultaneously;consideration of Building a Simulator to Evaluate Methods to Maximize the Effectiveness of Advertising to Households;Human-AI-Collaboration SECI Model: The Knowledge Management Model of the Experts’ Tacit Knowledges with Augmented LLM-based AI;modeling Agent Awareness After Hierarchical Managerial Training;development of An Application for Extracting Needs Related to Actual Gas Use Using Text Mining;Impact of Intelligent systems in the Home Office on Employee Satisfaction—Lessons Learned from the COVID-19 Pandemic;agile Methodologies in Software Development: A Study of Effective Management Strategies for Companies in the Digital Era;predictive Analysis of Cyclical Sales Data;EMG signal Classification Using Machine Learning for Augmentative Assistance in Cerebral Palsy;wellnessWave—Platform for the Digitization of the Romanian Public Medical System;TRIAGE Predictive Model based on Artificial Neural Networks and Deep Learning;platform for Automated Assessment of Obstetric Ultrasounds, Using Machine Learning;identification of Fonts in Unstructured Environments Through Deep Lea

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