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检索条件"任意字段=7th International and Interdisciplinary Conference on Modeling and Using Context"

共 1249 条记录，以下是1-10 订阅

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modeling of a thick Cylindrical Pneumatic Leg for a Soft Parallel Robot 7

Modeling of a Thick Cylindrical Pneumatic Leg for a Soft Par...

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7th international conference on Soft Robotics (ROBOSOFT)

作者： Awada, Zeinab El Jjouaoui, Hamza Gouttefarde, Marc Haddab, Yassine Univ Montpellier CNRS LIRMM Montpellier France

ISBN: (纸本)9798350381818

Soft manipulators have experienced a significant development over the past few years thanks to their versatility, compliance, and safety. Soft manipulators made of hyperelastic materials present a modeling challenge due to their combined geometric and material nonlinearity, alongside their leveraged compliance. this paper considers a thick cylindrical pneumatic actuator in the context of a soft parallel robot. the input pressure and the external axial force to which it is subjected are modeled. the analytical solutions for these models are then derived using the Yeoh strain energy density function. the advantage of using the Yeoh material model is guaranteeing the existence of an analytical solution regardless of the material used for the fabrication of the cylindrical actuator. the accuracy of the models is evaluated using Finite Element Analysis, and a sensitivity analysis is also carried out to test their robustness. Finally, experimental results are provided and the importance of the material characterization is highlighted. the purpose of this work is to lay the foundation for future studies in modeling a soft parallel robot with three soft thick cylindrical "legs".

关键词： Pneumatic actuators

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Groundwater Level modeling Artificial Intelligence Approach of Features and Abilities 7

Groundwater Level Modeling Artificial Intelligence Approach ...

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7th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Kalele, Girish Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350341485

Creating precise soft computing techniques for estimating groundwater levels (GWL) to improve water resource scheduling and administration is crucial. Machine Learning (ML) algorithms have significantly improved GWL projection over the last twenty years. this research briefly summarizes the most widely used Artificial intelligence (AI) techniques and reviews the limited edition on AI approaches for groundwater level (GWL) modeling and estimation. Despite some flaws, the GWL temporal sequence in various groundwater can be effectively simulated and forecasted using AI methods if it is designed correctly. Examining these stages in the context of GWL modeling is advantageous due to the reliance of some phases of AI modeling on knowledge acquisition or iterative experimentation. the articles under review produced many limited and broad outcomes that can serve as valuable guidelines for scientists who wish to conduct comparative research in this area. this study also offers a few fresh concepts in the related field of inquiry for creating novel techniques and enhancing modeling quality. © 2023 IEEE.

关键词： Iterative methods

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Implementation of a Machine Learning Model using Neural Networks: a Case Study of Vehicle Motion modeling Task 7

Implementation of a Machine Learning Model Using Neural Netw...

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7th international conference on Information Technologies in Engineering Education, Inforino 2024

作者： Nosach, Dmitriy P. Fomina, Marina V. National Research University 'MPEI' Department of Computational Technologies Moscow Russia

ISBN: (纸本)9798350371369

the article explores reinforcement learning through the development of a model for automatic control of a vehicle on a track within the context of a computer game. It describes the Q-learning method and its application in the DQN algorithm for agent training. the challenge of selecting the right volume of training data is discussed. the gaming model created to assess the impact of the number of machine vision sensors and neural network structure on the success of learning is outlined. Such a project can be implemented by students for training purposes to enhance their engagement in the learning process. © 2024 IEEE.

关键词： Computer vision

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University Students interdisciplinary Training of Educational Resources Design for Computer modeling in School Engineering Learning 7

University Students Interdisciplinary Training of Educationa...

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7th international conference on Information Technologies in Engineering Education, Inforino 2024

作者： Dudysheva, Elena V. Shiling, Galina S. Zakharov, Pavel V. Altai State Pedagogical University Laboratory of Teacher Training in the Lifelong Pedagogical Education System Shukshin Altai State University for Humanities and Pedagogy Laboratory of Interdisciplinary Research in Education Biysk Russia Shukshin Altai State University for Humanities and Pedagogy Department of Mathematics Physics Informatics Biysk Russia Peter the Great St. Petersburg Polytechnic University Department of Physics St. Petersburg Russia

ISBN: (纸本)9798350371369

School graduates of technology profiles classes are often seen as the most prepared potential applicants for engineering universities. Future engineers will need to apply modeling to solve problems that emerge in professional activities building on the school primary engineering learning. the construction of physical processes 3D models in computer environments can aid in the development of engineering thinking and digital training. this requires the electronic educational resources design and the development of suitable methods. the collaboration between pedagogical and engineering universities can facilitate the accomplishment of these tasks provided with methodical basis and a consolidation of the universities scientific and practical developments in the network interaction. One of the popular areas for training future engineers is distance project design where tasks are distributed among several performers. the issue of interdisciplinary design of electronic educational resources to ensure the quality of engineering training in technological profiles in schools is significant for the theory and practice of innovation in engineering education, pedagogical methodology and technology, and digital didactics. the proposed methods include computer modeling of physical processes in engineering (using materials science example), pedagogical design, and educational outcomes analysis. the paper describes the results of experimental work on organizing interdisciplinary projects for the development of electronic educational resources for school engineering learning by student teams. these teams consist of pedagogical university students, future teachers, and polytechnic university students, future engineers. It concludes that interdisciplinary training of students from pedagogical and engineering universities in the electronic educational resources design on computer modeling for school primary engineering learning is effectively feasible using distributed educational techn

关键词： Engineers

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Agent-Based modeling and Simulation for Urban Air Quality Assessment 7th

Agent-Based Modeling and Simulation for Urban Air Quality As...

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7th international conference on Logistics Operations Management (GOL)

作者： Mashhadi, Neda Fonlupt, Cyril Puigt, Matthieu Roussel, Gilles Verel, Sebastien Univ Littoral Cote dOpale LISIC UR 4491 F-62228 Calais France

ISBN: (纸本)9783031686337;9783031686344

Urban pollution poses a pressing environmental challenge, with substantial impacts on public health, particularly in urban areas. this paper presents a original approach that integrates vehicle-specific emission factors, derived from real-time traffic data, into an agent-based transport modeling framework. We introduce an emission calculation tool, augmented by supplementary data from HBEFA, incorporated into the MATSim environment to simulate multi-agent transport dynamics. the comprehensive MATSim scenario, encompassing digital road networks and public transportation systems, is generated through the Eqasim pipeline. this pipeline ensures a dependable pathway from initial data inputs to the completion of transport simulations. We apply this methodology in the real-world context of Calais, France, modeling pollutants such as NO2, PM10, and PM2.5. this modeling effort generates emission maps that illustrate the results, offering valuable insights for emission analysis. Furthermore, our approach provides critical information for decision-makers involved in managing and assessing urban air quality, thus contributing to more informed environmental policies and interventions.

关键词： Multi-agent Transport Air quality Emission Urban Simulation

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Performance and Optimization of Coding Techniques for Deep Space Communication Channels 7

Performance and Optimization of Coding Techniques for Deep S...

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7th international conference on Automation Electronics and Electrical Engineering

作者： Guan, Wenqi Nanjing Univ Sch Elect Sci & Engn Nanjing Peoples R China

ISBN: (纸本)9798350377040;9798350377033

In today's world, space exploration and communication advancements are critical to ensuring effective connections for scientific missions, planetary exploration, and future interstellar travel. Deep space communication plays a pivotal role in supporting these endeavors, as it enables the transmission of vital data across vast distances and harsh environments. this paper presents a comprehensive study on the performance and optimization of coding techniques for deep-space communication channels. Based on the characteristics of the deep-space environment, the channels are modeled into three stages: near-Earth link, interstellar link, and near-planet link. the modeling for each channel type is summarized, and simulation results are provided. To evaluate coding techniques, M2M4, MMSE, and DNN are employed to approximate the signal-to-noise ratio (SNR), which serves as a critical parameter in assessing various encoding schemes. three coding techniques-Hamming, convolutional, and turbo codes-are tested in the context of these models, with a particular focus on the turbo coding method. Detailed exploration is carried out on the SOVA and Log-MAP algorithms, as well as the impact of transmission parameters such as code rate. Overall, the results aim to provide a foundation for reliable signal transmission and error correction in deep-space, addressing challenges inherent to the unique environment of deep-space communication.

关键词： deep-space communication channel modeling encoding methods SNR estimation hard and soft decisions

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modeling Continuous Emotions in Text Data using IEMOCAP Database 7

Modeling Continuous Emotions in Text Data using IEMOCAP Data...

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IEEE 7th international conference on Advanced Technologies, Signal and Image Processing (ATSIP)

作者： Messaoudi, Awatef Boughrara, Hayet Lachiri, Zied Univ Tunis El Manar Natl Engn Sch of Tunis Signal Image & Informat Technol Lab LR 11 ES17 Tunis Tunisia

ISBN: (纸本)9798350351491;9798350351484

Predicting emotional state and specifically valence (positivity or negativity), arousal (activation or intensity), and dominance (control or power) from text data remains a challenge due to the complexity and context dependency of human emotions. Recent advancements in deep learning, especially Transformer models like BERT, have significantly enhanced text analysis capabilities by capturing complex semantic relationships within text. this study explores the performance of various deep learning architectures in predicting emotional states using a speaker-dependent(SD) scenario for data splitting, where both training and testing sets contain samples from the same speakers. We compare a baseline Long Short Term Memory (LSTM) model, an LSTM model with GloVe word embeddings, and a pre-trained BERT model, all evaluated on the IEMOCAP dataset. Our Research shows that the BERT model achieves the highest Concordance Correlation Coefficient (CCC) scores 0.724 for valence, 0.423 for arousal, and 0.488 for dominance resulting in an average CCC score of 0.545, outperforming both the baseline LSTM and the LSTM+GloVe models. these results highlight Transformer's ability especially BERT to capture continuous emotions in textual data.

关键词： Emotion Recognition from Text VAD dimensional Deep Learning LSTM Glove BERT pretrained model

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Deriving Integrated Multi-Viewpoint modeling Languages from Heterogeneous modeling Languages: An Experience Report 16

Deriving Integrated Multi-Viewpoint Modeling Languages from ...

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16th ACM SIGPLAN international conference on Software Language Engineering (SLE) as part of SPLASH conference

作者： Heithoff, Malte Jansen, Nico Kirchhof, Jorg Christian Michael, Judith Rademacher, Florian Rumpe, Bernhard Rhein Westfal TH Aachen Software Engn Aachen Germany

ISBN: (纸本)9798400703966

In modern systems engineering, domain experts increasingly utilize models to define domain-specific viewpoints in a highly interdisciplinary context. Despite considerable advances in developing model composition techniques, their integration in a largely heterogeneous language landscape still poses a challenge. Until now, composition in practice mainly focuses on developing foundational language components or applying language composition in smaller scenarios, while the application to extensive, heterogeneous languages is still missing. In this paper, we report on our experiences of composing sophisticated modeling languages using different techniques simultaneously in the context of heterogeneous application areas such as assistive systems and cyber-physical systems in the Internet of things. We apply state-of-the-art practices, show their realization, and discuss which techniques are suitable for particular modeling scenarios. Pushing model composition to the next level by integrating complex, heterogeneous languages is essential for establishing modeling languages for highly interdisciplinary development teams.

关键词： Software Language Engineering Language Composition Domain-Specific Languages Language Families Reuse Internet of things Assistive Systems

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Lightweight Unsupervised Pre-trained Person Re-identification Implementation 7

Lightweight Unsupervised Pre-trained Person Re-identificatio...

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7th international conference on Automation Electronics and Electrical Engineering

作者： Huo, Qizhou Wang, Yiwei Zhu, Zhangziqing Du, Jie Qingdao Univ Sci & Technol Qingdao Peoples R China

ISBN: (纸本)9798350377040;9798350377033

Person Re-identification (Re-ID) is a critical task in computer vision with broad applications in surveillance and security systems. Achieving high accuracy while maintaining a lightweight and computationally efficient design remains a major challenge, particularly in resource-constrained environments. In this paper, we present a novel lightweight Re-ID model that integrates an additive attention mechanism with cross-layer adaptive weighting and multi-layer feature fusion. By adopting a hierarchical design, the model effectively balances local detail extraction in shallow layers with global semantic representation in deeper layers, ensuring both efficiency and performance. Extensive experiments conducted on the Market-1501 dataset demonstrate the effectiveness of our approach, achieving a mean Average Precision (mAP) of 75.6% and a Top-1 accuracy of 90.8%. the proposed model not only outperforms several existing methods but also undergoes diverse experimental validations to further confirm its practical applicability. this approach offers an innovative solution for lightweight Re-ID, delivering efficient and accurate performance in real-world scenarios.

关键词： person re-identification unsupervised learning lightweight model global context modeling computational efficiency

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7th EAI international conference on Innovations and interdisciplinary Solutions for Underserved Areas, InterSol 2024

7th EAI International Conference on Innovations and Interdis...

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7th EAI international conference on Innovations and interdisciplinary Solutions for Underserved Areas, InterSol 2024

ISBN: (纸本)9783031864926

the proceedings contain 28 papers. the special focus in this conference is on Innovations and interdisciplinary Solutions for Underserved Areas. the topics include: A Risk-Based Pedestrian Crossing Decision Model for Traffic Simulation in African Urban Traffic;modelling and Optimization of the Electrical Parameters of an InxGa1-xN Solar Cell Under Dynamic Frequency Illumination;assessment of Pavement Damage Caused by Speed Bumps Along Nyanya – Jikwoyi Road Abuja;analyzing Water’s Characteristics Health Impact with Classification Algorithms;optimizing Coverage in a Wireless Sensors Network by Selecting the Best Sensors;Towards a Single-Sign-On Authentication Architecture Based on OpenID Connect Protocol and Blockchain Technology;an Experimental 5G Standalone Testbed for Rural Connectivity;an Application of the Hough Transform and Convolutional Neural Networks to Detect Straight Lines;a Slotted Random Access Algorithm for Efficient Transmission in White Area: Case of Artisanal Fishing in West Africa;a New Delay History Predictor for Multi-skill Call Center;retrieving Data from Social Network Platforms: A State-of-Art Review;strabismus Diagnosis and Angular Deviation Calculation Based on Artificial Intelligence Approaches: A Review;Towards the Implementation of a Dynamic IDS for IoT: Anomaly Detection in MQTT Traffic;straight-Line Recognition in a Virtual Hexagonal Grid using Hough Transform;predicting the Rate of Aflatoxin Contamination in the White Corn Value Chain;the Impact of Agents Heterogeneous in Call Center Performance Measures;towards a Mobile, Intelligent, Personalized and Adaptive E-learning System Considering Learners’ context in Semi-nomadic and Conflict Zones;comparative Study of Machine Learning Models for the Detection of Abusive Messages: Case of Wolof-French Codes Mixing Data;towards an Ontology-Based Platform for Integrating Infectious Disease Simulation Models;AI-Based Control Approach of .SN Reserved Domain Names (***);efficient Combination of

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