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Detection of Various Dental Conditions on Dental Panoramic Radiography Using Faster R-CNN

IEEE Access 2023年 11卷 127388-127401页

作者： Chen, Shih-Lun Chen, Tsung-Yi Mao, Yi-Cheng Lin, Szu-Yin Huang, Ya-Yun Chen, Chiung-An Lin, Yuan-Jin Chuang, Mian-Heng Abu, Patricia Angela R. Chung Yuan Christian University Department of Electronic Engineering Taoyuan320314 Taiwan Feng Chia University Department of Electronic Engineering Taichung407102 Taiwan Chang Gung Memorial Hospital Department of General Dentistry Taoyuan61363 Taiwan National Ilan University Department of Computer Science and Information Engineering Yilan26047 Taiwan Academy of Innovative Semiconductor and Sustainable Manufacturing Department of Program on Semiconductor Manufacturing Technology National Cheng Kung University Tainan717005 Taiwan Ming Chi University of Technology Department of Electrical Engineering New Taipei243303 Taiwan Ateneo de Manila University Department of Information Systems and Computer Science Quezon1108 Philippines

The dental panoramic radiograph (DPR) is a pivotal diagnostic tool in dentistry. However, despite the growing prevalence of artificial intelligence (AI) across various medical domains, manual methods remain the prevailing means of interpreting DPR images. This study aims to introduce an advanced identification system for detecting seven dental conditions in DPR images by utilizing Faster R-CNN. The primary objectives are to enhance dentists' efficiency and evaluate the performance of various CNN models as foundational training networks. This study contributes significantly to the field in several notable ways. Firstly, including a Butterworth filter in the training process yielded an approximately 7% enhancement in judgment accuracy. Secondly, the proposed enhancement technology tailored to different dental symptoms effectively bolstered the training model's accuracy. Consequently, all dental conditions attained an accuracy rate exceeding 95% in CNN analysis. These accuracy enhancements ranged from 1.34% to 13.24% compared to existing recognition technologies. Thirdly, this study pioneers the application of Faster R-CNN for identifying dental conditions, achieving an impressive accuracy rate of 94.18%. The outcomes of this study mark a substantial advancement compared to prior research and offer dentists a more efficient and convenient means of pre-diagnosing dental conditions. © 2013 IEEE.

关键词： Image segmentation

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Experimental Evaluation of the Impact of Using Oriented Steel in Proportion to Segmentation on Core Loss of AC Electric Machine Stator

Experimental Evaluation of the Impact of Using Oriented Stee...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Bhuvan Khoshoo Anmol Aggarwal John Agapiou Shanelle N. Foster Department of Electrical & Computer Engineering Michigan State University East Lansing MI USA General Motors Pontiac MI USA Manufacturing Systems Research Laboratory General Motors Warren MI USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

The strategic incorporation of oriented steel in a segmented stator AC electric machine has the potential to enhance machine performance by reducing core losses compared to a machine designed with non-oriented steel. However, the introduction of cut-edges and the stress on individual segments resulting from segmented stator construction may have unintended consequences. Despite several attempts to assess the impact of cut-edges or oriented steel on core losses in segmented stators, the literature lacks an analysis of the loss separation between tooth and back-iron components using manufactured stators. This gap in understanding prevents a comprehensive assessment of the true impact of using oriented steel in segmented stator construction for core loss improvement. In this work, the loss of each tooth and back-iron segment is calculated by conducting experiments with three different electromagnetic devices, specifically H-shaped steel laminations. By comparing the results from three manufactured stators, we elucidate the influence of oriented steel in proportion to the segmented stator construction.

关键词： Electromagnetic devices Stator cores Lamination Core loss Energy conversion Loss measurement Iron Sensors Steel Stress

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Extended gate organic field effect transistor for calcium ion sensing towards biomedical applications

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Sensors and Actuators Reports 2025年 9卷

作者： Viola, F․ A. Hatami, D. Mariani, F. Gualandi, I. Terranova, F. Scavetta, E. Bonfiglio, A. Spanu, A. Department of Electrical and Electronic Engineering University of Cagliari via Marengo Cagliari09123 Italy Piazza della Vittoria 15 Pavia27100 Italy Department of Industrial Chemistry "Toso Montanari" University of Bologna Via Piero Gobetti 85 Bologna Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Genova Italy

The measurement of calcium ions (Ca2+) concentration is crucial for several biomedical applications because it plays a key role in various physiological processes, including cellular signalling, muscle contraction, bone metabolism, and the release of neurotransmitters. In this paper, we propose an innovative flexible sensor based on an Extended Gate Organic Field Effect Transistor (ExG-OFET) coupled with a liquid-processable ion-selective membrane. This novel approach enables highly sensitive (exceeding 60 mV dec‑1) and selective ion detection, with a limit of detection in the low μM range, outperforming conventional ion-sensitive electrodes (ISEs) due to the intrinsic electronic amplification of the transistor architecture. Moreover, the simple fabrication process and the use of flexible, cost-effective materials, make this device a versatile, low-cost solution for a wide range of biomedical applications, from in vitro electrophysiology to epidermal electronics. This study highlights the potential of the ExG-OFET platform as a promising alternative to traditional ion detection systems. © 2025 The Author(s)

关键词： Bone

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Enhancing Robustness in Manipulability Assessment: The Pseudo-Ellipsoid Approach

Enhancing Robustness in Manipulability Assessment: The Pseud...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Erfan Shahriari Kim Kristin Peper Matej Hoffmann Sami Haddadin Chair of Robotics and Systems Intelligence Munich Institute of Robotics and Machine Intelligence Technical University of Munich (TUM) Germany Department of Mechanical Engineering Newman Laboratory for Biomechanics and Human Rehabilitation Massachusetts Institute of Technology (MIT) USA Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague (CTU) Czech Republic

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Manipulability analysis is a methodology employed to assess the capacity of an articulated system, at a specific configuration, to produce motion or exert force in diverse directions. The conventional method entails generating a virtual ellipsoid using the system’s configuration and model. Yet, this approach poses challenges when applied to systems such as the human body, where direct access to such information is limited, necessitating reliance on estimations. Any inaccuracies in these estimations can distort the ellipsoid’s configuration, potentially compromising the accuracy of the manipulability assessment. To address this issue, this article extends the standard approach by introducing the concept of the manipulability pseudo-ellipsoid. Through a series of theoretical analyses, simulations, and experiments, the article demonstrates that the proposed method exhibits reduced sensitivity to noise in sensory information, consequently enhancing the robustness of the approach.

关键词： Analytical models Visualization Accuracy Sensitivity analysis Noise Force Estimation Robustness Ellipsoids Standards

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The Impact of SBOM Generators on Vulnerability Assessment in Python: A Comparison and a Novel Approach

arXiv

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arXiv 2024年

作者： Benedetti, Giacomo Cofano, Serena Brighente, Alessandro Conti, Mauro Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Italy IMT School for Advanced Studies Lucca Italy Department of Mathematics University of Padua Italy Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Netherlands

The Software Supply Chain (SSC) security is a critical concern for both users and developers. Recent incidents, like the SolarWinds Orion compromise, proved the widespread impact resulting from the distribution of compromised software. The reliance on open-source components, which constitute a significant portion of modern software, further exacerbates this risk. To enhance SSC security, the Software Bill of Materials (SBOM) has been promoted as a tool to increase transparency and verifiability in software composition. However, despite its promise, SBOMs are not without limitations. Current SBOM generation tools often suffer from inaccuracies in identifying components and dependencies, leading to the creation of erroneous or incomplete representations of the SSC. Despite existing studies exposing these limitations, their impact on the vulnerability detection capabilities of security tools is still unknown. In this paper, we perform the first security analysis on the vulnerability detection capabilities of tools receiving SBOMs as input. We comprehensively evaluate SBOM generation tools by providing their outputs to vulnerability identification software. Based on our results, we identify the root causes of these tools' ineffectiveness and propose PIP-sbom, a novel pip-inspired solution that addresses their shortcomings. PIP-sbom provides improved accuracy in component identification and dependency resolution. Compared to best-performing state-of-the-art tools, PIP-sbom increases the average precision and recall by 60%, and reduces by ten times the number of false positives. © 2024, CC BY-SA.

关键词： Input output programs

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Model-Based Design of a Collaborative Human-Robot Workspace

Model-Based Design of a Collaborative Human-Robot Workspace

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Rifa Rahmayanti Juan C. Alvarez Diego Alvarez Antonio M. López Department of Electrical Electronic Computer and Systems Engineering Multisensor Systems and Robotics Group (SiMuR) University of Oviedo Gijón Spain

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

This paper presents a complete design and validation of a specific case of a Human-Robot collaborative workspace consisting of a robot arm and a human operator working in a pick & place task in close proximity. The human motion monitoring is made with IMU-based wearables and optical markers, and the robot motion planning method considers safety distance criteria as prescribed in ISO/TS 15066. This case study is meant to illustrate the design of collaborative environments by using the Model-based Design approach. The goal is to systematically address the problems of safety assurance and performance optimization, allowing the use of optimization and machine learning approaches.

关键词： Wearable computers Collaboration Machine learning Manipulators Safety Planning Task analysis

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A Scalable Real-time Semantic Segmentation Network for Autonomous Driving 1

A Scalable Real-time Semantic Segmentation Network for Auton...

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1st Workshop on Advanced Multimedia Computing for Smart Manufacturing and engineering, AMC-SME 2023

作者： Liu, Jun Wu, Chao Yuan, Geng Niu, Wei Zhang, Wenbin Song, Houbing Herbert Robotics Institute of School of Computer Science Carnegie Mellon University Pittsburgh United States Department of Electrical & Computer Engineering Northeastern University Boston United States School of Computing University of Georgia Athens United States Department of Computer Science Michigan Technological University Houghton United States Department of Information Systems University of Maryland Baltimore County Baltimore United States

ISBN: (纸本)9798400702730

Computational resources are limited on real-time embedded devices, so the available computing cost of deployment on the target platform must be considered. We develop a feature extraction module based on the MobileNet backbone that can be adjusted in terms of computational complexity and capacity using the depth multiplier parameter, classifier depth, and kernel depth. These three parameters allow us to control the count of channels within the network, effectively managing the model's capacity and computational requirements. To achieve semantic segmentation, we incorporate additional components, such as an extension module. This extension module typically includes 1x1 pointwise convolutional layers for pixel-level classification and a transposed convolutional layer for upsampling the output to the original input image size. By combining the feature extraction module with this extension module, we can create a complete architecture capable of performing semantic segmentation tasks. The feature extraction module provides the initial feature extraction and the extension module adds the necessary components for accurate pixel-wise classification and upsampling. Compared to Hardware-aware Neural Architecture Search (NAS), pruning, runtime pruning, and knowledge distillation methods, our model has several advantages in terms of modular design, structural controllability, ease of implementation, and cost-effectiveness. Our computational efficiency, as measured by FLOPS, is highly competitive. Our method is distinguished by solving the problem of MobileNet's inability to adjust the size and number of convolution kernels. It achieves this through adaptable parameter tuning, including MobileNet's depth multiplier, the kernel size in the FCN head's Separable Convolution layer, and the depth of the first Point-wise Convolution layer. These adjustments are customized to match hardware's max multiply-accumulates (MACs), optimizing network capacity and maximizing resource utilizat

关键词： Feature extraction

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Rapid Maintenance based improved design for omnidirectional controlled wheels for VirtuSphere system

Rapid Maintenance based improved design for omnidirectional ...

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International Symposium for Design and Technology of Electronics Packages (SIITME)

作者： Lidia Cristina Bazavan Horatiu Roibu Daniela Coman Stefan Irinel Cismaru Anca Petrisor Nicu George Bizdoaca Mechatronics and Robotics Department Faculty of Automation Computers and Electronics University of Craiova Craiova Romania Engineering and Management of the Technological Systems Department Faculty of Mechanics University of Craiova Craiova Romania Electrical Energy and Aerospace Engineering Department Faculty of Electrical Engineering University of Craiova Craiova Romania

Designing for rapid maintenance requires an approach whereby the replacement of rapidly wearing sub-assemblies can be easily replaced while ensuring that the degree of wear can be tracked in real-time if possible. The redesign of the movement system of the Virtusfera platform by the authors previously led to an omnidirectional platform with increased integration facilities in virtual environments. The article presents two solutions for redesigning some subsystems that make up the new experimentally validated solution, presenting at the same time the study based on which the subsystems with the lowest reliability were identified and a proposal for a real-time tracking solution for those subsystems. Numerical simulations of the two solutions are presented, and conclusions and directions are formulated regarding the practical implementation of these subsystems based on the concept of design based on rapid maintenance.

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Compensation Control of PMSMs Based on a High-order Sliding Mode Observer with Inertia Identification

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Li, Ke Ding, Jie Sun, Xiaodong Lei, Gang Dianov, Anton Demidova, Galina Prakht, Vladimir Jiangsu University School of Electrical and Information Engineering Zhenjiang212013 China Jiangsu University Automotive Engineering Research Institute Zhenjiang212013 China University of Technology Sydney School of Electrical and Data Engineering NSW2007 Australia Wenzhou University Pingyang Institute of Intelligent Manufacturing Wenzhou325035 China ITMO University Faculty of Control Systems and Robotics Petersburg197101 Russia Ural Federal University Department of Electrical Engineering Ekaterinburg620062 Russia

This article proposes a new sliding mode control (NSMC) reaching law to improve the speed tracking and anti-interference performance of permanent magnet synchronous motors (PMSMs). The NSMC improves the sliding mode control (SMC) in approaching speed and reducing chattering. Firstly, considering that the external load interference will adversely affect the control system, a high-order sliding mode observer (HOSMO) is designed to observe the load torque, and the observed value is compensated to the output of the speed controller. Then, combined with the Landau algorithm, a variable adaptive gain algorithm is introduced to decrease the impact of inertia mismatch on the system control performance. The algorithm identifies the rotational inertia online, reduces the effect of load disturbance on the identification performance, and updates the identification results to the observation in processors and controllers. Experimental results show that the proposed control method reduces the speed and current fluctuations of the system when load torque and inertia vary and improves the system's robustness. © 2013 IEEE.

关键词： Permanent magnets

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A Carryover Storage Valuation Framework for Medium-Term Cascaded Hydropower Planning: A Portland general Electric System Study

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IEEE Transactions on Sustainable Energy 2025年

作者： Chen, Xianbang Liu, Yikui Zhong, Zhiming Fan, Neng Zhao, Zhechong Wu, Lei Stevens Institute of Technology ECE Department HobokenNJ07030 United States Sichuan University Electrical Engineering Department Chengdu610017 China University of Arizona Department of Systems and Industrial Engineering TucsonAZ85721 United States Portland General Electric PortlandOR97204 United States

Medium-term planning of cascaded hydropower (CHP) determines appropriate carryover storage levels in reservoirs to optimize the usage of available water resources. This optimization seeks to maximize the hydropower generated in the current period (i.e., immediate benefit) plus the potential hydropower generation in the future period (i.e., future value). Thus, in the medium-term planning, properly quantifying the future value deposited in carryover storage is essential to achieve a balanced trade-off between immediate benefit and future value. To this end, this paper presents a framework to quantify the future value of carryover storage, which consists of three major steps: i) constructing a deterministic model to calculate the maximum possible hydropower generation that a given level of carryover storage can deliver in the future period;ii) extracting the implicit locational marginal water value (LMWV) of carryover storage for each reservoir by applying a partition-then-extract algorithm to the constructed model;and iii) developing a set of analytical rules based on the extracted LMWV to effectively calculate the future value. These rules can be seamlessly integrated into medium-term CHP planning models as tractable mixed-integer linear constraints to quantify the future value properly, and can be easily visualized to offer valuable insights for CHP operators. Finally, numerical results on Portland general Electric's CHP demonstrate the effectiveness of the presented framework in aiding medium-term CHP planning to identify suitable carryover storage strategies. © 2010-2012 IEEE.

关键词： Reservoirs (water)

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