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MEMS Design Process Based Simulation and Analysis of a Hypothetical Sensor Design with Electromechanics Interface 2nd

MEMS Design Process Based Simulation and Analysis of a Hypot...

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2nd International Conference on Data Security and Privacy Protection, DSPP 2024

作者： Sathish, K. Ravikumar, C.V. Su, Chunhua Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Deemed University Chennai602105 India School of Electronics Engineering Vellore Institute of Technology Vellore632014 India Division of Computer Science University of Aizu Aizuwakamatsu City Fukushima965-8580 Japan

ISBN: (纸本)9789819785452

This study simulates and examinesthe MEMS design process for a hypothetical sensor with an electromechanical interface. Conceptualizing the sensor entails establishing its purpose, operational environment, and capacitive sensing mechanism for sensitivity and precision. Geometric and physical models are developed using advanced COMSOL Multiphysics software to create a moveable proof mass supported by micro-fabricated beams. Static and dynamic finite element analysis (FEA) simulations can be used to evaluate the sensor’s mechanical reaction to input signals and electrode electrostatic forces. This guarantees that mechanical signals are properly transformed into electrical signals. These data are evaluated to determine the best performance criteria such as sensitivity, linearity, and thermal stability, resulting in iterative design improvements. Robustness analysis, including tolerance and FMEA, ensures dependability. Additionally, typical MEMS manufacturing technologies are being examined for fabrication. This simulation-driven strategy prioritises electro-mechanical interface issues throughout the design process, resulting in high-performance, and dependable MEMS sensors for a wide range of applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Microchannels

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Mechanical Design of a Feline Robot for Dynamic Scaling Testing 13th

Mechanical Design of a Feline Robot for Dynamic Scaling Tes...

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13th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2024

作者： Budzichowski, Amy Riddle, Shane Batchu, Rucha Chen, Tina Jackson, Clayton B. Nourse, William R. P. Quinn, Roger D. Department of Mechanical and Aerospace Engineering Case Western Reserve University ClevelandOH44106-7222 United States Department of Electrical Computer and Systems Engineering Case Western Reserve University ClevelandOH44106-7222 United States

ISBN: (纸本)9783031725968

Animal size impacts locomotion, due to its effect on the influence of gravity, inertia, and an animal’s internal elasticity and damping. We are developing a cat robot to further explore the impact of these four characteristics on animal locomotion. This paper details the mechanical design of this cat robot’s rear limbs, as well as the simulated validation of this design. In future work, we plan to design forelimbs with a floating scapula and test the robot in split-belt treadmill experiments similar to those done in mammalian experiments as we develop its synthetic nervous system controller. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mammals

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The Hidden Influence of Latent Feature Magnitude When Learning with Imbalanced Data 4th

The Hidden Influence of Latent Feature Magnitude When Learn...

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4th International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2024

作者： Dablain, Damien A. Chawla, Nitesh V. Department Computer Science and Lucy Family Institute for Data and Society University of Notre Dame Notre DameIN46553 United States

ISBN: (纸本)9789819787012

Machine learning (ML) models have difficulty generalizing when the number of training class instances are numerically imbalanced. The problem of generalization in the face of data imbalance has largely been attributed to the lack of training data for under-represented classes and to feature overlap. The typical remedy is to implement data augmentation for classes with fewer instances or to assign a higher cost to minority class prediction errors or to undersample the prevalent class. However, we show that one of the central causes of impaired generalization when learning with imbalanced data is the inherent manner in which ML models perform inference. These models have difficulty generalizing due to their heavy reliance on the magnitude of encoded signals. During inference, the models predict classes based on a combination of encoded signal magnitudes that linearly sum to the largest scalar. We demonstrate that even with aggressive data augmentation, which generally improves minority class prediction accuracy, parametric ML models still associate a class label with a limited number of feature combinations that sum to a prediction, which can affect generalization. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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An Evolutionary Game Theoretic-Based Approach to Task Offloading in Hybrid Vehicular Cloud-Edge Environment 31st

An Evolutionary Game Theoretic-Based Approach to Task Offlo...

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31st International Conference on Web Services, ICWS 2024, Held as Part of the Services Conference Federation, SCF 2024

作者： Li, Jinpeng Xia, Yunni Liu, Hui Feng, Jiafeng Zhang, Ke Ding, Zhaoguang Dong, Yumin Yu, Yang Wang, Yu Peng, Qinglan Xu, Xifeng School of Computer Chongqing University Chongqing400030 China School of Computer Science and Technology Beijing Institute of Technology Beijing100083 China China Huadian Corporation Guangdong Branch Guangdong China Chongqing Normal University Chongqing China Nanjing Nanzi Huadun Digital Technology Co. Ltd. Nanjing China Henan University Henan China

ISBN: (纸本)9783031770715

Vehicle Edge Computing (VEC) is a novel computing paradigm that addresses the computational demands of intelligent vehicles by offloading tasks to edge servers. In a VEC environment, edge servers’ limited storage and processing capacity require a sensible task offloading strategy, where only a part of computing requirement can be offloaded directly to the VEC server and the remaining to the remote cloud. A primary challenge in this context is the creation of an effective and responsive task offloading algorithm that improves the utility. This study proposes an evolutionary game theoretic-based approach, utilizing a Dynamical-Resource Evolutionary Game (DREG) algorithm for decentralized task offloading. DREG leverages the Evolutionary Stable Strategy(ESS) and Adaptive Resource Allocation(ARA) method to optimize response delay and energy cost while increasing success rate. Experimental results indicate that DREG outperforms traditional methods across various performance metrics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Evolutionary game theoretic Fault tolerant Resource allocation Task offloading Vehicle edge computing

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Are Fact Checkers Effective in the Post Truth World? Assessing Impact of Fact Checkers Cross Medium and Platforms 25th

Are Fact Checkers Effective in the Post Truth World? Asses...

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25th International Conference on Web Information Systems Engineering, WISE 2024

作者： Masurkar, Hrishikesh Suleiman, Basem Yaqub, Waheeb Alibasa, Muhammad Johan School of Computer Science The University of Sydney Sydney Australia School of Computer Science and Engineering The University of New South Wales Sydney Australia Faculty of Engineering and Technology Sampoerna University Jakarta Indonesia

ISBN: (纸本)9789819605668

Social media platforms help users share opinions and find new information but also spread rumors, which misinforms the public. These rumour threads often prompt users (called guardians) to respond with fact-checking articles to debunk or verify the rumour. We examine how general users’ and rumour starter respond to these fact-checking (FC) comments. This study explores these aspects by analysing users’ textual and non-textual engagements. These engagements are examined across three main factors: platforms (Twitter and Reddit), rumour topics, and the primary medium (text, image, video, and GIF) in the rumour post. We observed minimal differences across primary mediums by analyzing 147K news posts and FC comments with 20.7 million replies. Furthermore, we found that Reddit users engage with FC comments more than Twitter users in terms of likes and the rumour starter’s reply-back rates. We found that no general users engaged with the rumour post before and after the guardian intervention. The most significant differences in the emotive characteristics of replies were across topics, with rumour starters expressing more anger, disgust, and offensive language when discussing rumours about terrorism and racism. These emotions indicate the backfire effect. Our findings raise concerns about the effectiveness of fact-checking interventions in updating misinformed users. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Tweets

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Efficient Low-Polygon Building Model Generation with Opening Detection 1

引用

41st computer Graphics International Conference, CGI 2024

作者： Wang, Yixian Lin, Boheng Chen, Weiya Wan, Lin School of Software and Engineering Huazhong University of Science and Technology Wuhan China School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783031820243

ISBN: (纸本)9783031820236

With the rapid increase of complexity and volume of 3D building models, industries such as digital games and computer-aided design face considerable challenges. One feasible solution is to generate low-polygon models for complex building meshes in a relatively short time to apply in a level of detail (LOD) algorithm. We propose an efficient building model simplification algorithm with opening detection, aiming to realize an extremely low polygon count while preserving their visual features. Our algorithm has three steps. We detect and construct the opening structures presented in the building model to incorporate in the subsequent carving process;improve the approach to generate a visual hull that represents the fundamental boundary of the building model and carve out details with high efficiency;and apply planarization and simplification algorithms to obtain the simplified model. Our algorithm can generate highly simplified building models while preserving important opening details to serve as the roughest level in the LOD hierarchy. Experimental results demonstrate that our algorithm efficiently handles building models with complex opening structures and outperforms other recent simplification algorithms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mesh generation

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Memory-Augmented Deep Deterministic Policy Gradient 16th

Memory-Augmented Deep Deterministic Policy Gradient

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16th International Conference on Social Robotics, ICSR + BioMed 2024

作者： Qiu, Qian Zeng, Fanyu Yang, Haigen Xing, Guanyu Ge, Shuzhi Sam School of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China College of Computer Science Sichuan University Chengdu China Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

ISBN: (纸本)9789819789627

With the advancement of intelligent technologies, particularly deep reinforcement learning, Unmanned Aerial Vehicles (UAVs) are being widely deployed across various scenarios. However, current remote-controlled UAV methods and existing intelligent decision-making algorithms struggle to effectively respond to dynamic and partially observable situations. To tackle this issue, we propose the Memory-augmented Deep Deterministic Policy Gradient (MemDDPG) algorithm. The MemDDPG algorithm leverages a Long Short-Term Memory (LSTM) network to use past state information for current decision-making, enabling UAVs to perform accurately in dynamic scenarios. By incorporating memory-based mechanisms, MemDDPG addresses the limitations of conventional methods, enhancing UAVs’ ability to manage complex environments. This algorithm improves decision-making and ensures UAVs operate more autonomously and efficiently in unpredictable situations. Experiments demonstrate the effectiveness and feasibility of the MemDDPG algorithm in enhancing the intelligent decision-making capabilities of UAVs, showing significant improvements in adaptability and decision-making accuracy in dynamic situations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep reinforcement learning

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CO-LEACH: Cooperative Data Collection Protocol for Data-Heterogeneous WSNs 18th

CO-LEACH: Cooperative Data Collection Protocol for Data-Het...

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18th International Conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2024

作者： Zhang, Xinyu Wu, Gaojie Fu, Luwei Mao, Wenliang Zhao, Zhiwei School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9783031714696

Wireless Sensor Networks (WSNs) are indispensable for providing crucial sensing and data collection services to IoT systems. The diversity of IoT applications leads to data heterogeneity, which has become a prevalent characteristic of WSNs. Most existing work can only cope with data-homogeneous WSNs, where the same policy for clustering and data processing is applied to all network nodes. However, in practical IoT systems, different policies are desired to support the diverse types of IoT data. The neglect of data heterogeneity may result in poor data collection performance or even non-functionality. In this paper, we propose a cooperative data collection protocol (CO-LEACH) for data-heterogeneous WSNs. Specifically, 1) To mitigate the impact of data heterogeneity, CO-LEACH introduces an efficient cooperative clustering algorithm, in which heterogeneous nodes jointly form clusters, nodes with a higher proportion of intra-cluster type are more likely to be elected as cluster heads, thereby improving data collection efficiency. 2) To cope with the heterogeneous data, CO-LEACH presents an adaptive reprogramming strategy, making cluster heads capable of processing heterogeneous data. Simulation experiments show that CO-LEACH makes a better energy balance of all devices than state-of-the-art protocols, and prolongs the network lifetime by 3–5 times in data-heterogeneous WSNs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Data collection

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Hardness and Approximation for the Star β -Hub Routing Cost Problem in Δβ -Metric Graphs 29th

Hardness and Approximation for the Star β -Hub Routing C...

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29th International Computing and Combinatorics Conference, COCOON 2023

作者： Tsai, Meng-Shiou Hsieh, Sun-Yuan Hung, Ling-Ju Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Department of Creative Technologies and Product Design National Taipei University of Business Taoyuan City Taiwan

ISBN: (纸本)9783031491894

Minimizing transportation costs through the design of a hub-and-spoke network is a crucial concern in hub location problems (HLP). Within the realm of HLP, the Δβ -Star p -Hub Routing Cost Problem (Δβ -SpHRP) represents an open problem stemming from the Star p -Hub Routing Cost Problem (SpHRP) discussed in a publication by [Yeh et al., Theoretical computer science, 2022]. The Δβ -SpHRP deals with a specific vertex c, a positive integer p, and a Δβ -metric graph denoted as G, which is an undirected, complete, and weighted graph adhering to the β -triangle inequality. The objective is to identify a spanning tree T that satisfies the following conditions: it is rooted at c, contains exactly p hubs adjacent to c, and assigns each remaining vertex to a hub while minimizing the routing cost of T. This paper expands the input instances from metric graphs to Δβ -metric graphs. Our research demonstrates that SpHRP is NP-hard for any β>12, indicating that SpHRP remains NP-hard for various subclasses of metric graphs. For approximation algorithms, we introduce two approaches that improve upon previous results, particularly when β is close to 12. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Stars

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KaiRacters: Character-Level-Based Writer Retrieval for Greek Papyri 27th

KaiRacters: Character-Level-Based Writer Retrieval for Gree...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Peer, Marco Sablatnig, Robert Serbaeva, Olga Marthot-Santaniello, Isabelle Computer Vision Lab TU Wien Austria Departement Altertumswissenschaften Universität Basel Basel Switzerland

ISBN: (纸本)9783031784941

This paper presents a character-based approach for enhancing writer retrieval performance in the context of Greek papyri. Our contribution lies in introducing character-level annotations for frequently used characters, in our case the trigram kai and four additional letters (Ε,κ,μ,ω), in Greek texts. We use a state-of-the-art writer retrieval approach based on NetVLAD and compare a character-level-based feature aggregation method against the current default baseline of using small patches located at SIFT keypoint locations for building the page descriptors. We demonstrate that by using only about 15 characters per page, we are able to boost the performance up to 4% mAP (a relative improvement of 11%) on the GRK-120 dataset. Additionally, our qualitative analysis offers insights into the similarity scores of SIFT patches and specific characters. We publish the dataset with character-level annotations, including a quality label and our binarized images for further research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Content based retrieval

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