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Assessing underlying pulsatile structures with laparoscopic tools using proximal vibroacoustic sensing

Current Directions in Biomedical engineering 2024年第1期10卷 37-40页

作者： Kaabachi, Syrine Illanes, Alfredo Esmaeili, Nazila Sühn, Thomas Spiller, Moritz Friebe, Michael Hansen, Christian Boese, Axel INKA-Innovation Laboratory for Image Guided Therapy Otto-von-Guericke University Magdeburg Germany SURAG Medical GmbH Leipzig Germany Computer Aided Medical Procedures and Augmented Reality Technical University of Munich Munich Germany AGH University of Science and Technology Department of Biocybernetics and Biomedical Engineering Krakow Poland CIBE - Center of Innovation Business Development & Entrepreneurship FOM University of Applied Sciences Essen Germany Research Campus STIMULATE Otto von Guericke University Magdeburg Germany

This work presents a novel approach for detecting underlying pulsatile structures with laparoscopic tools by using proximal vibroacoustic sensing. This new method could detect pulsations at a depth of up to 1.5 cm. The outcome of this work indicates the potential of identifying deep-seated pulsatile structures during robot-assisted laparoscopy, where haptic feedback is highly limited, to help surgeons prevent vascular damage that may lead to injuries. © 2024 by Walter de Gruyter Berlin/Boston.

关键词： Laparoscopy

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FEASIBILITY INVESTIGATION ON CLASSIFICATION OF TWO-PHASE FLOW REGIMES IN A 3×3 ROD BUNDLE CHANNEL USING ARTIFICIAL NEURAL NETWORK 30

FEASIBILITY INVESTIGATION ON CLASSIFICATION OF TWO-PHASE FLO...

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30th International Conference on Nuclear engineering, ICONE 2023

作者： Chen, Shao-Wen Ruan, Pei-Syuan Chen, Han-Yao Huang, Lung-Hung Lin, Min-Song Lee, Jin-Der Wang, Jong-Rong Institute of Nuclear Engineering and Science National Tsing Hua University Hsinchu Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu Taiwan Nuclear Science and Technology Development Center National Tsing Hua University Hsinchu Taiwan Nuclear and New Energy Education and Research Foundation Hsinchu Taiwan

ISBN: (纸本)9784888982566

In this study, two-phase flow tests have been carried out in a 3×3 rod bundle channel to investigate the feasibility on flow regime classification using artificial neural network (ANN). The rod bundle channel was constructed with nine 11.5 mm-diameter rods in a rectangular array with a pitch of 15.4 mm and enclosed by a 52×52 mm rectangular channel, and the overall height was about 5 m. The test flow conditions covered the superficial gas and liquid velocities of = 0.02-10 m/s and = 0.02-2 m/s. The transient void fraction of each test was measured and converted into probability density function (PDF) and cumulative probability distribution function (CPDF) and rearranged as the input matrices for Kohonen neural network for training and classification with the training epoch of 1500 times. While assigning 3 groups, the bubbly and cap-bubbly flows can be clearly distinguished;whereas when assigning 5 groups, the bubbly and cap-bubbly flow can be further subdivided with an additional transition region, and the cap-turbulent and churn flows can be roughly separated. This study has preliminarily demonstrated the feasibility on classification of two-phase flow regimes in the 3×3 rod bundle channel using artificial neural network technique. © 2023 by JSME.

关键词： Two phase flow

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CPU Execution Time Analysis based on RISC-V ISA Simulators: A Survey 16

CPU Execution Time Analysis based on RISC-V ISA Simulators: ...

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16th International Conference on development and Application Systems, DAS 2022

作者： Iuga, Nicolai Zagan, Ionel Gaitan, Vasile Gheorghita Stefan cel Mare University Faculty of Electrical Engineering and Computer Science Suceava Romania Integrated Center for Research Development and Innovation in Advanced Materials Suceava Romania

ISBN: (纸本)9781665481625

Multiple components affect the behavior of CPU execution tasks, mainly mutual exclusion during access to the shared resources and synchronous transmissions between tasks that require specific priorities. Referring to real-time task scheduling, the most important issues addressed are monitoring the deadline of the tasks, the probability of non-compliance with the deadline and ensuring that they are completed within the deadline imposed by the controlled system. This leads to the fact that a tasks set is feasible if the system has adequate resources to execute the tasks without losing any deadlines. To approach this challenge, this article addresses the feasibility analysis of runtime for real-time tasks to be performed in a virtual space before applying to a real embedded device. These processes take place offline, even before a system executes a set of tasks. In order to perform the feasibility analysis of the system, efforts are being made to provide virtual environments and simulators, such as the RISC-V ISA simulator and the WCET (Worst Case Execution Time) measurement, subsequently. These simulators have application-specific requirements, with their own advantages. © 2022 IEEE.

关键词： Simulators

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Hydrodynamic Performance of a New Box-type Floating Breakwater with a Protruding Bottom Plate

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Journal of Marine Environmental engineering 2025年第1期12卷 49-67页

作者： Lv, Jiao Fan, Ning Niu, Guoxu Pan, Wei Ma, Tianchi Song, Laifu Zhao, Xizeng College of Civil Engineering and Architecture Wenzhou University Wenzhou325035 China Wenzhou Academy of Agricultural Sciences Wenzhou325006 China Southern Zhejiang Key Laboratory of Crop Breeding Wenzhou325006 China Key Laboratory of Engineering and Technology for Soft Soil Foundation and Tideland Reclamation of Zhejiang Province Wenzhou325035 China Zhejiang International Science and Technology Cooperation Base of Ultra-soft Soil Engineering and Smart Monitoring Wenzhou325035 China Beijing Langrun Innovation Technology Company Limited Beijing100080 China Zhejiang Engineering Research Center of Disaster Prevention and Mitigation for Coastal Soft Soil Foundation Wenzhou325035 China Ocean College Zhejiang University Zhoushan316021 China

Floating breakwaters can effectively resist wave impacts and maintain a relatively calm water environment. To solve the problem of insufficient wave attenuation performance of traditional box-type floating breakwaters with increasing wave periods, a new box-type floating breakwater (NFB) with a protruding bottom plate was proposed in this study. Based on the computational fluid dynamics (CFD) approach, a series of numerical simulations of the interaction between regular waves and floating breakwaters were carried out. The evolution of the vortices and the wave dissipation mechanism of the NFB were investigated. The effect of the change in the dimension of the protruding bottom plate of the NFB on the hydrodynamic performance was analysed, and a reasonable length of the protruding bottom plate was recommended. Finally, the hydrodynamic performance of the proposed approach was compared with that of the traditional box-type floating breakwaters under identical breakwater draft and width conditions. The results showed that the transmission coefficient of the NFB is improved by approximately 20% on average, and the reflection coefficient, maximum horizontal wave forces and negative maximum vertical wave forces are significantly reduced, indicating that the NFB has good application prospects. © 2025 Old City Publishing, Inc.

关键词： Floating breakwaters

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A Convolutional Neural Network-Weighted Cellular Automaton Model for the Fast Prediction of Urban Pluvial Flooding Processes

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International Journal of Disaster Risk science 2024年第5期15卷 754-768页

作者： Jiarui Yang Kai Liu Ming Wang Gang Zhao Wei Wu Qingrui Yue School of National Safety and Emergency Management Beijing Normal UniversityBeijing 100875China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC‑FEMD) Nanjing University of Information Science and TechnologyNanjing 210044China Department of Transdisciplinary Science and Engineering Tokyo Institute of TechnologyTokyo 226‑8501Japan National Disaster Reduction Center of China Ministry of Emergency ManagementBeijing 100124China Research Institute of Urbanization and Urban Safety University of Science and Technology BeijingBeijing 100083China National Science and Technology Institute of Urban Safety Development Shenzhen 518046China

Deep learning models demonstrate impressive performance in rapidly predicting urban floods,but there are still limitations in enhancing physical connectivity and *** study proposed an innovative modeling approach that integrates convolutional neural networks with weighted cellular automaton(CNN-WCA)to achieve the precise and rapid prediction of urban pluvial flooding processes and enhance the physical connectivity and reliability of modeling *** study began by generating a rainfall-inundation dataset using WCA and LISFLOOD-FP,and the CNN-WCA model was trained using outputs from LISFLOOD-FP and ***,the pre-trained model was applied to simulate the flood caused by the 20 July 2021 rainstorm in Zhengzhou *** predicted inundation spatial distribution and depth by CNN-WCA closely aligned with those of LISFLOOD-FP,with the mean absolute error concentrated within 5 mm,and the prediction time of CNN-WCA was only 0.8%that of *** CNN-WCA model displays a strong capacity for accurately predicting changes in inundation depths within the study area and at susceptible points for urban flooding,with the Nash-Sutcliffe e fficiency values of most flood-prone points exceeding ***,the physical connectivity of the inundation distribution predicted by CNN-WCA is better than that of the distribution obtained with a *** CNN-WCA model with additional physical constraints exhibits a reduction of around 34%in instances of physical discontinuity compared to *** results prove that the CNN model with multiple physical constraints has signifi cant potential to rapidly and accurately simulate urban flooding processes and improve the reliability of prediction.

关键词： Convolutional neural networks Physical continuity Rapid prediction Urban pluvial flooding processes Weighted cellular automata

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Enhancing Sovereign Allocation of Resources in Cloud Milieus Using a Causal Dilated Geometric Algebra Approach for Dynamic Scalability 2

Enhancing Sovereign Allocation of Resources in Cloud Milieus...

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Katru, Chandrasekhar Rao Srinivasan, Sathish Kumar, Mohan Yadwad, Sunita Satish, G. Maranan, Ramya Lead Software Engineer Indian LandSC29707 United States Machine Learning & AI Development Oracle Cloud Infrastructure Division San FranciscoCA United States Nitte Meenakshi Institute of Technology Department of Information Science and Engineering Karnataka Bengaluru India Parul institute of Engineering and Technology Parul University Computer science and Engineering Faculty of Engineering and Technology Gujarat India Sree Dattha Institute of Engineering and Science Department of Electrical and Electronics Engineering Telangana Sheriguda India Saveetha School of Engineering SIMATS Department of Research and Innovation Tamil Nadu Chennai India

ISBN: (纸本)9798331505745

Cloud environments utilize availability and usage of resources as crucial components in order to produce scalability, reliability and low cost. Such resource capabilities require autonomous systems that can handle these resources dynamically in spite of fluctuating workloads and service delivery requirements. Static models of resource management suffer from scalability and inability to react on the fly and accurately predict the demand thus causing Service Level Agreement (SLA) breaches and affecting the Quality of Service (QoS) as well as energy consumption profile. Advanced and elaborative cloud workloads require an intelligent system that can analyse the temporal and spatial patterns without impacting the overall system's performance significantly. Inspired by these challenges, this research proposes a Causal Dilated Geometric Algebra Convolutional Transformer Network (CATNet) along with the Prairie-Dog Optimizer (P-DogO), referred to as CAT-DogNet to learn and predict the dynamic scalability. CATNet integrates Causal Dilated Convolutional Networks in time domain for temporal structure capturing and Geometric Algebra Transformer for spatial resource coding. P-DogO adjusts weight parameters and losses for resource allocation, enhancing them depending on a work environment. A set of comprehensive assessments demonstrate a 0.85% SLA violation rate, average response time of less than 10ms, and overall 12.3% less energy consumption than baseline methods. The system had favourable predictability rates over 99.4% for the resource demand estimate. CAT-DogN et presents a sound and agnostic architecture for autonomous resource allocation in cloud environment, which indeed extend the state of art by considering flexibility, power consumption and QoS compliance. © 2025 IEEE.

关键词： Infrastructure as a service (IaaS)

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Integrating Longitudinal Electronic Health Records with Machine Learning for Personalized Cancer Management 2

Integrating Longitudinal Electronic Health Records with Mach...

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Kaliappan, S. Maranan, Ramya Ali, H.Mohammed Kumar, Bura Vijay Lovely Professional University Division of Research and Development Jalandhar - Delhi G.T.Road Punjab Phagwara144411 India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai602105 India Srm Institute of Science and Technology Department Mechanical Engineering Ramapuram Campus Chennai89 India School of Computer Science and Artificial Intelligence Sr University Telangana Warangal506371 India

ISBN: (纸本)9798350370188

This study proposes an innovative approach to personalized cancer management by integrating Longitudinal Electronic Health Records (LEHR) with ensemble machine learning algorithms. The method encompasses data preprocessing, feature engineering, and model development. Data preprocessing involves the critical task of cleaning and transforming raw LEHR data to ensure suitability for further analysis. Feature engineering aims to extract meaningful attributes from the preprocessed data. The heart of the approach lies in model development using ensemble learning, combining diverse base models to form a robust predictive model. The ensemble model enhances prediction accuracy, adapts to varying data types, and exhibits computational efficiency. © 2024 IEEE.

关键词： Computational efficiency

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Trial Study on Energy Loss and Vibration Intensity of Centrifugal Pump 12

Trial Study on Energy Loss and Vibration Intensity of Centri...

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12th Academic Conference of Geology Resource Management and Sustainable development, GRMSD 2024

作者： Zhang, Zhongtao Jia, Chenchuan Zhou, Guangjie Shi, Yongjiang HeBei University of Architecture Hebei Zhangjiakou075000 China Hebei Provincial Engineering Research Center for Renewable Energy Heating Hebei Zhangjiakou075000 China Hebei Energy Heating Technology Innovation Center Hebei Zhangjiakou075000 China Hebei Provincial Green Building Collaborative Innovation Center Hebei 075000 China Hebei Science and Technology Department of Science and Technology Research and Development Platform Construction Special Hebei Energy Storage Heating Technology Innovation Center Performance Subsidies China Scientific and Technological Innovation Exemption is to Enjoy the Preferential Enterprise Policy Municipal Subsidy Funds Project

ISBN: (纸本)9798331314545

Based on the law of conservation of energy, this paper analyzes the vibration intensity of centrifugal pump from the energy perspective, classifying energy losses under two regulation methods: throttling and variable frequency, to obtain the vibration energy loss of centrifugal pumps. The derived vibration energy is compared with the trial vibration intensity for error analysis, and the results show that the vibration energy loss of centrifugal pumps is closely related to the vibration intensity, while confirming that the derived vibration energy is not significantly different from the actual trial conditions. © 2024 Proceedings of the 12th Academic Conference of Geology Resource Management and Sustainable development, GRMSD 2024. All rights reserved.

关键词： Centrifugal pumps

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Urban flood risk analysis using presence-only machine learning approach: an integrated MaxEnt-cloud model framework in Harbin, China

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Natural Hazards 2025年 1-30页

作者： Hu, Jinhui Pang, Aoxuan Deng, Changtao School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan China Pearl River Water Resources Research Institute Guangzhou China Qingdao Harbin Engineering University Innovation and Development Center Yantai China

Urban flooding is a devastating global natural disaster requiring robust risk assessment. Traditional methods often struggle with presence-only data (locations where floods occurred, without data on non-flood locations) and clear risk level classification. This study introduces an innovative integrated framework for urban flood risk analysis in Harbin, China, combining Maximum Entropy (MaxEnt) modeling, which excels with presence-only data, with Cloud Model theory for improved risk classification. Methodologically, our framework incorporates: (1) MaxEnt modeling using various environmental and socioeconomic factors; (2) spatial autocorrelation analysis to understand flood distribution; (3) Cloud Model theory implementation, which transforms probability values into linguistic risk levels while representing the uncertainty and fuzziness in these transitions; and (4) a comparative evaluation against other machine learning models. Key findings reveal that the MaxEnt model demonstrated strong predictive performance (AUC = 0.871), comparable to other approaches, despite only needing flood presence data. Human-related factors contributed over half of the total influence on flood risk. Clay loam soil showed the highest flood probability. Spatial analysis identified significant clustering of flood events in low-lying urban areas with inadequate drainage. The Cloud Model classification effectively translated flood probabilities into five risk levels, highlighting that low-risk areas predominate in peripheral high-elevation districts, while high-risk areas are concentrated in Harbin's urban core. This pioneering integration of MaxEnt with Cloud Model theory offers a robust methodology for urban flood risk assessment. The implications include providing a more nuanced, data-driven yet expert-knowledge-informed basis for urban planning, infrastructure development, and emergency management in flood-prone regions.

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Driving toward hydrogen mobility: A life cycle cost analysis of conventional, electric, and hydrogen fuel cell vehicles in Qatar

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Energy 2025年 330卷

作者： Méndez, Carlos Contestabile, Marcello Bicer, Yusuf Division of Sustainable Development College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar Qatar Environment and Energy Research Institute Doha Qatar

Qatar's transport sector is dominated by the use of personal vehicles, increasing the nation's environmental footprint. To mitigate this, the nation has introduced electrified means of transport such as metro, tram, and buses. Nonetheless, the dependency on hydrocarbon-based power plants diminishes the positive impact of said approach. For this reason, the present article analyses the potential of deploying hydrogen fuel cell vehicles to reduce the environmental footprint of Qatar's transport sector. To carry out the study environmental and economic aspects are considered in a life cycle cost (LCC) analysis to compare conventional, electric, and hydrogen fuel cell buses and cars. Results indicate that initially, conventional vehicles exhibit the best LCC, followed by electric and hydrogen fuel cell vehicles;however, nonetheless, the latter gains parity with the former technologies in due time. This outcome is further analyzed while introducing policy instruments to incentivize hydrogen fuel cel vehicle adoption. As a result, while implementing a 20 % purchase subsidy, HFCV's LCC will become more competitive than EVs by 2030, yielding 0.19 and 0.20 US$/km, respectively. Moreover, a 40 % purchase tax on conventional vehicles will transform them into the least attractive option by 2030, with an LCC of 0.237 US$/km. © 2025

关键词： Cost benefit analysis

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