Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)最新文献_第7页

Regulating Airflow Using Hybrid LCN for Soft Pneumatic Circuits 用混合LCN调节软气动回路的气流

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-10 DOI: 10.1002/aisy.202401069

Elif Kurt, Youssef M. Golestani, Efstathios Barmpoutsis, Sergio Picella, Robin L. B. Selinger, Johannes T. B. Overvelde, Danqing Liu

{"title":"Regulating Airflow Using Hybrid LCN for Soft Pneumatic Circuits","authors":"Elif Kurt, Youssef M. Golestani, Efstathios Barmpoutsis, Sergio Picella, Robin L. B. Selinger, Johannes T. B. Overvelde, Danqing Liu","doi":"10.1002/aisy.202401069","DOIUrl":"10.1002/aisy.202401069","url":null,"abstract":"Being flexible and adaptive to various environments, soft robotics shows promise as a more robust alternative in many applications compared to traditional, rigid robotics. Of many employable different actuation strategies, pneumatically driven soft robotics have gained attraction owing to their relative straightforward manufacturing and capability to produce significant force to their environment upon interaction. To enable more autonomous pneumatic systems, however, there is an emerging need for developing smarter fluidic elements responding to environmental cues, to provide embodied control and regulation. Herein, a liquid crystal network (LCN)-based fluid regulator is designed to impart stimuli responsiveness and regulation into fluidic circuits by combining radially aligned nematic and nonaligned isotropic LCNs. Assisted by a finite element method, the thermoresponsiveness of the LCN is discussed. Finally, the regulating behavior of the responsive pneumatic regulator is demonstrated, which alters its fluidic resistance with changing temperature. This work emphasizes the potential of advancing responsive soft robotics that can interact with their environment through multiphysical stimuli.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"7 6","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202401069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

D-HAT: A Diatom-Inspired Structure for a Helmet Concept Against Trauma D-HAT：一种硅藻启发结构的头盔概念抗创伤

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-10 DOI: 10.1002/aisy.202570022

Ludovico Musenich, Lorenzo Strozzi, Massimiliano Avalle, Flavia Libonati

引用次数: 0

Targeted Chemical Looping Materials Discovery by an Inverse Design 基于逆设计的靶向化学环材料发现

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-10 DOI: 10.1002/aisy.202570021

Brett A. Duell, Ali Ramazani, Sittichai Natesakhawat, Eric J. Popczun, Jonathan W. Lekse, Yuhua Duan

引用次数: 0

A Soft Robotic Textile-Actuated Anthropomorphic Artificial Shoulder Mechanism 柔性机器人织物驱动的拟人人工肩部机构

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-10 DOI: 10.1002/aisy.202570020

Bibhu Sharma, James Davies, Emanuele Nicotra, Adrienne Ji, Kefan Zhu, Phuoc Thien Phan, Chi Cong Nguyen, Trung Thien Hoang, Jingjing Wan, Patrick Pruscino, Hoang-Phuong Phan, Nigel H. Lovell, Thanh Nho Do

引用次数: 0

Text-to-Haptics: Enhancing Multisensory Storytelling through Emotionally Congruent Midair Haptics 文本到触觉：通过情感一致的空中触觉增强多感官讲故事

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-10 DOI: 10.1002/aisy.202570017

Maciej Stroinski, Kamil Kwarciak, Mateusz Kowalewski, Daria Hemmerling, William Frier, Orestis Georgiou

引用次数: 0

Cooperative Merging in Mixed Traffic Based on Strategic Influence of Connected Automated Vehicles on Human-Driven Vehicle Behavior 基于车联网对人驾驶车辆行为战略影响的混合交通协同归并

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-10 DOI: 10.1002/aisy.202400797

Kyunghwan Choi, Seongjae Shin, Minseok Seo

{"title":"Cooperative Merging in Mixed Traffic Based on Strategic Influence of Connected Automated Vehicles on Human-Driven Vehicle Behavior","authors":"Kyunghwan Choi, Seongjae Shin, Minseok Seo","doi":"10.1002/aisy.202400797","DOIUrl":"10.1002/aisy.202400797","url":null,"abstract":"Cooperative on-ramp merging control for connected and automated vehicles (CAVs) can significantly enhance traffic flow and fuel efficiency at highway merging points. However, in mixed traffic scenarios where CAVs coexist with human-driven vehicles (HDVs), the unpredictable behavior of HDVs poses challenges to safety and coordination. While many cooperative merging strategies focus on individual CAV control, fewer have addressed the coordination of multiple CAVs in such settings. This study introduces an optimization-based cooperative merging strategy for all CAVs within a control zone, considering interactions with HDVs of uncertain intentions. A key innovation is the strategic influence of CAVs on HDV behavior by slowing down the CAV preceding HDVs, thereby allowing other CAVs on the adjacent road to merge in front of the HDVs with reduced uncertainty. The optimal slowdown pattern is identified by evaluating CAV throughput across various candidate patterns, with dynamic optimization applied at each time a new vehicle enters the control zone to effectively manage HDV uncertainties. Experimental results from various mixed-traffic scenarios show that the proposed strategy reduces the average travel time delay by up to 31% compared to an existing optimization-based approach.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"7 7","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202400797","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144681403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Anomaly Forecasting in Time-Series Data: Feedback Connection between Forecasting and Detecting Algorithms with Applications to Power Systems 一种新的时间序列数据异常预测：预测与检测算法之间的反馈联系及其在电力系统中的应用

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-06 DOI: 10.1002/aisy.202401141

Hyung Tae Choi, Hae Yeon Park, Taewan Kim, Jung Hoon Kim

{"title":"A Novel Anomaly Forecasting in Time-Series Data: Feedback Connection between Forecasting and Detecting Algorithms with Applications to Power Systems","authors":"Hyung Tae Choi, Hae Yeon Park, Taewan Kim, Jung Hoon Kim","doi":"10.1002/aisy.202401141","DOIUrl":"10.1002/aisy.202401141","url":null,"abstract":"This article is concerned with developing a novel structure of machine learning-based anomaly forecasting, by which both forecasting the future states and detecting the anomalies in these states can be achieved at the same time. The main idea of this article is to introduce a feedback connection to combine several algorithms with respect to the forecasting and the detecting in a single algorithm. More precisely, Xgboost and long short-term memory are used for forecastor and one-class support vector machine and robust random cut forest are used for detector. Combining those 2 × 2 schemes leads to the overall four algorithms, and future anomalies can be detected before they occur. The effectiveness of the proposed algorithms is verified through some comparative simulations of an IEEE 3-bus system with various faults. More interestingly, the detecting accuracies obtained through the two schemes of taking robust random cut forest are shown to be improved by 10% than those of employing the one-class support vector machine. For the forecasting part, Xgboost is regarded as involving the fastest prediction speed for online implementations, and thus the combination of Xgboost and robust random cut forest can be the most suitable choice for anomaly forecasting for power system fault events.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"7 5","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202401141","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fairness in Federated Learning: Trends, Challenges, and Opportunities 联邦学习中的公平性：趋势、挑战和机遇

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-06 DOI: 10.1002/aisy.202400836

Noorain Mukhtiar, Adnan Mahmood, Quan Z. Sheng

{"title":"Fairness in Federated Learning: Trends, Challenges, and Opportunities","authors":"Noorain Mukhtiar, Adnan Mahmood, Quan Z. Sheng","doi":"10.1002/aisy.202400836","DOIUrl":"10.1002/aisy.202400836","url":null,"abstract":"At the intersection of the cutting-edge technologies and privacy concerns, federated learning (FL) with its distributed architecture, stands at the forefront in a bid to facilitate collaborative model training across multiple clients while preserving data privacy. However, the applicability of FL systems is hindered by fairness concerns arising from numerous sources of heterogeneity that can result in biases and undermine a system's effectiveness, with skewed predictions, reduced accuracy, and inefficient model convergence. This survey thus explores the diverse sources of bias, including but not limited to, data, client, and model biases, and thoroughly discusses the strengths and limitations inherited within the array of the state-of-the-art techniques utilized in the literature to mitigate such disparities in the FL training process. A comprehensive overview of the several notions, theoretical underpinnings, and technical aspects associated with fairness and their adoption in FL-based multidisciplinary environments are delineated. Furthermore, the salient evaluation metrics leveraged to measure fairness quantitatively are examined. Finally, exciting open research directions that have the potential to drive future advancements in achieving fairer FL frameworks, in turn, offering a strong foundation for future research in this pivotal area are envisaged.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"7 6","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202400836","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Module Micro/Nanorobots for Biomedical and Environmental Remediation Applications 用于生物医学和环境修复的多模块微/纳米机器人

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-06 DOI: 10.1002/aisy.202400779

Bairong Zhu, Amar Salehi, Lei Xu, Wei Yuan, Tingting Yu

{"title":"Multi-Module Micro/Nanorobots for Biomedical and Environmental Remediation Applications","authors":"Bairong Zhu, Amar Salehi, Lei Xu, Wei Yuan, Tingting Yu","doi":"10.1002/aisy.202400779","DOIUrl":"10.1002/aisy.202400779","url":null,"abstract":"Micro/nanorobots (MNRs) are untethered, small-scale devices designed to perform complex tasks in challenging and inaccessible environments, with promising biomedicine and environmental remediation applications. Recent advancements in multi-module MNRs, which incorporate functional components such as actuators, propellers, imaging modalities, and manipulators, have significantly expanded their capabilities while addressing the limitations of single-module designs. This article reviews recent progress in these core modules, emphasizing their application in biomedicine, including targeted drug delivery, tissue repair, and diagnosis, as well as in environmental remediation, such as pollutant removal and microorganism treatment. It highlights practical strategies to address real-world challenges in these domains, with a focus on the multi-module design in enhancing functionality. Despite substantial advancements, key challenges persist, including scalability, real-time imaging, and intelligent control. Future research directions include the development of intelligent modules equipped with memory, data processing, and communication functions, enabling autonomous decision-making and closed-loop control. These developments hold the potential to foster innovation in medicine, environmental sustainability, and other critical fields.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"7 7","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202400779","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144681141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing Large Multimodal Models for One-Shot Learning and Interpretability in Biomedical Image Classification. 评估生物医学图像分类中一次学习和可解释性的大型多模态模型。

IF 6.1

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2025-04-06 DOI: 10.1002/aisy.202400947

Wenpin Hou, Qi Liu, Huifang Ma, Yilong Qu, Zhicheng Ji

引用次数: 0