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26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Mohan, Michael D. Latifi, Neda Simmons, Craig A. Young, Edmond W.K. Department of Mechanical & Industrial Engineering University of Toronto TorontoON Canada Institute of Biomedical Engineering University of Toronto TorontoON Canada

ISBN: (纸本)9781733419048

Pancreatic ductal adenocarcinoma comprises over 90% of all pancreatic cancers, with a dense fibrotic region or stroma being a significant contributor to aggressive tumor biology and therapeutic resistance. To this point, traditional microfluidic architectures have been lacking in ability to model and provide on-chip access for downstream analysis of stroma-mediated therapeutic resistance. We present here a reversibly bonded multilayer microfluidic platform with direct access to a centrally positioned hydrogel, enabling optical and direct physical access for on-chip stiffness analysis. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Multilayers

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A Physical-Based Artificial Neural Networks Compact Modeling Framework for Emerging FETs

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IEEE Transactions on Electron Devices 2024年第1期71卷 223-230页

作者： Yang, Ya-Shu Li, Yiming Kola, Sekhar Reddy Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory The Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan

We report a compact modeling framework based on the Grove-Frohman (GF) model and artificial neural networks (ANNs) for emerging gate-all-around (GAA) MOSFETs. The framework consists of two ANNs;the first ANN constructed with the drain current model not only can capture the main trend of device I - V characteristics but also can predict its variation even when the amount of training data for the ANN is insufficient or outside the range of applied biases. The second one is then designed to improve the model accuracy by further minimizing the errors between the target and the model outputs. We implement the proposed framework to accurately model emerging GAA nanosheet (NS) MOSFETs and complementary FETs (CFETs) without suffering from divergent issues in circuit simulation. In addition, nonphysical behaviors, such as nonzero current at zero bias, do not occur in the modeling framework. Compared to recently reported machine-learning (ML) models, our approach can achieve a similar level of model accuracy with merely 20% amount of the training data. © 1963-2012 IEEE.

关键词： Neural networks

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Synergy-based Knee Angle Estimation on Stairs and Slopes for A Powered Transfemoral Prosthesis 46

Synergy-based Knee Angle Estimation on Stairs and Slopes for...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Mo, Lifen Gao, Fei Sun, Yiou Tang, Zhipeng Jie, Jing Song, Zhenhua Liao, Wei-Hsin Liang, Fengyan Yin, Ming Chinese Academy of Sciences Shenzhen Institute of Advanced Technology Shenzhen China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Shatin Hong Kong Hainan University Key Laboratory of Biomedical Engineering of Hainan Province School of Biomedical Engineering Sanya China Central South University Affiliated Haikou Hospital of Xiangya Medical College Department of Rehabilitation Medicine Haikou China

ISBN: (纸本)9798350371499

Above-knee amputees have difficulties in locomotion on stairs and slopes. One of the most challenging issues in controlling powered transfemoral prostheses is the design of adaptive knee trajectories for different users and terrains. The synergy-based trajectory generation approach is becoming a promising approach to solving this issue. It estimates a user-adaptive knee trajectory from the motion of the residual limb in amputees for the prosthesis, based on the synergy. In a previous study, we have validated the feasibility of this approach in level-ground walking. Herein, we aim to evaluate the performance of this approach in scenarios of slope descent/ascent and stair descent/ascent. Results indicate that the sequence-to-sequence (Seq2Seq) model achieved RMSE values of 2.71°, 2.38°, 2.29°, and 2.15° for predicting knee angles during ascent and descent on slopes and stairs, respectively. It surpasses other state-of-the-art methods in overall performance. Our study shows the promise of the synergy-based approach for above-knee prostheses on slopes and stairs by generating adaptive trajectories, eliminating the need for manual adjustments of prosthetic parameters based on terrains or users. © 2024 IEEE.

关键词： Knee prostheses

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Heading Angle Estimation Using Intelligent Fusion for Autonomous Vehicles

Heading Angle Estimation Using Intelligent Fusion for Autono...

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2023 Advances in Science and engineering Technology International Conferences, ASET 2023

作者： Barakat, Ali A. Jardat, Mohammad A. Elsergany, Ahmed M. Sherif, Nidal A. American University of Sharjah Mechanical Engineering Department Sharjah United Arab Emirates American University of Sharjah Mechatronics Engineering Graduate Program Sharjah United Arab Emirates

ISBN: (纸本)9781665454742

Low-cost navigation systems for ground vehicles often rely on the fusion with Global Positioning System (GPS) for improved state estimation. In this study a low-cost gyroscope is fused with a GPS for improved vehicle heading angle estimation using several Artificial Intelligence (AI) based architectures that include Shallow Neural Networks (SNN), Multi-Layer Neural Networks (MLNN), and Adaptive Neuro- Fuzzy Inference Systems (ANFIS). The primary goal behind using AI based sensor fusion is to obtain a highly accurate vehicle heading estimation suitable for autonomous navigation applications. When available, the GPS signal is used to correct the vehicle's heading angle. The neural networks and ANFIS methods both use the difference between the GPS signal and the heading angle from the integrated gyroscope as inputs. The performance achieved is shown and analyzed. According to the results obtained, the MLNN provides the most accurate heading estimates. © 2023 IEEE.

关键词： Global positioning system

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Space-Based Solar Power for Operational Robustness in Lunar EVAs and Exploration Architectures

Space-Based Solar Power for Operational Robustness in Lunar ...

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2024 IAF Space Power Symposium at the 75th International Astronautical Congress, IAC 2024

作者： Hoying, Madelyn Tretiakova, Anna Chen, Vanessa Ma, Clara Patel, Palak Mckinney, Lanie MIT Department of Aeronautics and Astronautics MIT-Harvard Medical School Health Sciences and Technology Massachusetts General Hospital Wellnum Center for Photomedicine United States Boston University Mechanical Engineering United States University of Waterloo Biomedical Engineering Canada MIT Department of Aeronautics and Astronautics Technology and Policy Planning United States MIT Department of Mechanical Engineering United States MIT Department of Aeronautics and Astronautics United States

ISBN: (纸本)9798331312213

Human exploration of the lunar surface has large power requirements for both the lunar base and for rover exploration. NASA's recent contract awards indicate a reliance on fission surface power. While nuclear options provide reliable power to lunar base locations, they have a limited reach that restricts exploration capacity. The Space Explo¬ration Vehicle's 125-mile range only allows coverage of 0.34% of the lunar surface. A constellation of space-based solar power (SBSP) satellites paired with pressurized rovers allows 24-hour, full-surface coverage on excursions from the lunar base. Instead of narrowing exploration and science capabilities to the area around the base, preliminary anal¬ysis indicates the ability to extend a surface campaign's capabilities to full-surface coverage with 30 satellites in a 3 plane Walker-Delta Constellation with 54.7° inclination. This also provides dissimilar redundancy in the lunar surface power supply to add robustness to the overall mission architecture by providing an alternative method of powering the life support and critical power needs of the habitat in an emergency. A case study of constellation design, cost, lifetime, and power provided is conducted. In this study, we evaluate the impact of the additional exploration capacity on the MARTEMIS mission concept, which was named Best in Theme in the 2024 NASA RASC-AL design competition. MARTEMIS includes a campaign of 13 manned surface missions intended to evaluate architectural decisions and crit¬ical technologies for future Mars missions. Throughout the campaign, 148 astronauts will visit the lunar surface and conduct 332 EVAs. This campaign has the potential to significantly advance NASA's lunar science objectives while demonstrating Moon to Mars operations and technologies. A 125-mile EVA radius from a South Pole base reaches up to 8 of the 48 lunar geologic units;lunar science objectives target widespread sampling across all geologic units. The proposed SBSP constellation

关键词： NASA

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Current research status of tumor cell biomarker detection

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Microsystems & Nanoengineering 2023年第5期9卷 17-34页

作者： Liying Jiang Xinyi Lin Fenghua Chen Xiaoyun Qin Yanxia Yan Linjiao Ren Hongyu Yu Lingqian Chang ang Wang School of Electrical and Information Engineering Zhengzhou University of Light IndustryZhengzhou 450002China Academy for Quantum Science and Technology Zhengzhou University of Light IndustryZhengzhou 450002China Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong Kong SARChina key Laboratory of Biomechanics and Mechanobiology(Beihang University) Ministry of EducationBeijing Advanced Innovation Center for Biomedical EngineeringSchool of Biological Science and Medical EngineeringBeihang UniversityBeijing 100083China School of Engineering Medicine Beihang UniversityBeijing 100083China

With the annual increases in the morbidity and mortality rates of tumors,the use of biomarkers for early diagnosis and real-time monitoring of tumor cells is of great *** used for tumor cell detection in body fluids include circulating tumor cells,nucleic acids,protein markers,and extracellular *** them,circulating tumor cells,circulating tumor DNA,and exosomes have high potential for the prediction,diagnosis,and prognosis of tumor diseases due to the large amount of valuable information on tumor characteristics and evolution;in addition,in situ monitoring of telomerase and miRNA in living cells has been the topic of extensive research to understand tumor development in real *** techniques,such as enzyme-linked immunosorbent assays,immunoblotting,and mass spectrometry,have been widely used for the detection of these *** them,the detection of tumor cell markers in body fluids based on electrochemical biosensors and fluorescence signal analysis is highly preferred because of its high sensitivity,rapid detection and portable ***,we summarize recent research progress in the detection of tumor cell biomarkers in body fluids using electrochemical and fluorescence biosensors,outline the current research status of in situ fluorescence monitoring and the analysis of tumor markers in living cells,and discuss the technical challenges for their practical clinical application to provide a reference for the development of new tumor marker detection methods.

关键词： diagnosis mortality diseases

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Modeling the mechanical Properties of Primary Recycled Type II Dental Plaster Blend Using Desirability Optimization Methodology 2

Modeling the Mechanical Properties of Primary Recycled Type ...

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2nd International Conference on Multidisciplinary engineering and Applied Science, ICMEAS 2023

作者： Barnabas, Ugwuanyi Uchenna Remigius, Diovu Chidiebere John, Emaimo Chinonso, Okpe Promise Olufemi, Ojo Akintayo Emeka, Ukwueze Bonaventure Federal College of Dental Technology and Therapy Department of Biomedical Engineering Enugu Nigeria Federal College of Dental Technology and Therapy Department of Dental Technology Enugu Nigeria Universti Kebangsaan Department of Mechanical and Material Engineering Malaysia

ISBN: (纸本)9798350358834

Dentistry promotes the use of different materials for various dental treatments. This leads to the generation of wastes that result in environmental pollution which are inimical to human health. Incineration and landfill techniques have proven to be ineffective in dealing with this problem. This paper proposes a pragmatic approach where wastes can be recycled and reused. The methodology involved modeling the mechanical properties of primary recycled Type II dental plaster blend, as a basis for recyclability programme using desirability optimization methodology. Three test standards (ASTM D695, ASTM D6272 and ASTM E384) were utilized in determining compressive, flexural strength and vicker hardness properties respectively of recycled dental plaster and the results compared favourably with that of virgin dental plaster. The implication is that dental practitioners can leverage this technology to reduce the harmful effects of wastes on the environment thereby sustaining dental practice and controlling pollution. © 2023 IEEE.

关键词： Bending strength

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Experimental investigation of the effect of the offset ratio on the flow characteristics and heat transfer behaviour of a wall-bounded dual jet flow

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International Journal of Thermofluids 2025年 26卷

作者： Murphy, P.J. Alimohammadi, S. O'Shaughnessy, S.M. Department of Mechanical Manufacturing and Biomedical Engineering University of Dublin Trinity College Dublin 02 Ireland School of Mechanical Engineering Technological University Dublin Dublin Ireland

A wall-bounded dual jet is formed through combining a wall jet, flowing directly adjacent to a solid wall, with a parallel, co-flowing offset jet. The combination of a wall and offset jet in this manner is commonly encountered across many industrial applications, such as electronics cooling, wastewater evacuation, and noise suppression technologies, despite remaining relatively misunderstood across the published literature. This study aims to contribute to the available dual jet experimental data and further fundamental knowledge of dual jet flows and their accompanying heat transfer characteristics. The primary objective of this experimental investigation is to analyse the effect of varying the separation distance between the wall and offset jets, i.e., the offset ratio (OR), on the dual jet flow and heat transfer behaviour, therefore providing the very first experimental dataset relating to a dual jet for varying OR. For this investigation, a uniform heat flux of 1670 W/m2 is applied to the bounding wall for 5500 ≤ Re ≤ 12,000 and 1 ≤ OR ≤ 7, while the velocity ratio is maintained at a constant value of 1. This is achieved through a two-part experimental investigation, which separately adopts infrared thermography and particle image velocimetry techniques to respectively capture the heat transfer and flow characteristics. The results reveal a strong dependence on OR near the jet exit, while the flow characteristics remain generally unaffected further downstream. Increasing OR leads to a growth in the recirculation region, therefore increasing the streamwise position of the merge point. This consequentially moves the respective locations of the local minimum and maximum values in the characteristic local Nusselt number (Nux) profiles further downstream, while also inducing a general decline in the surface-averaged Nusselt number. Distinct differences in the observed flow and heat transfer behaviour are noted for OR ≤ 2 and OR ≥ 3, where lower OR values produce a un

关键词： Nusselt number

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Agriculture Yield Estimation Using Machine Learning Algorithms

Agriculture Yield Estimation Using Machine Learning Algorith...

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2024 IEEE International Conference on Automation and Computation, AUTOCOM 2024

作者： Raman, Ramakrishnan Kantari, Hanumaji Gokhale, Atul A Elangovan, K. Meenakshi, B. Srinivasan, S. Symbiosis Institute of Business Management Pune Maharashtra Pune India Malla Reddy Institute of Engineering and Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India Symbiosis School of Culinary Arts Maharashtra Pune India Dhanalakshmi Srinivasan Engineering College Department of Mechanical Engineering Tamil Nadu Chennai India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350382723

Storage, distribution, pricing, marketing, import/export, and other policy considerations all depend on accurate and timely crop output estimates. The directorates of economics and statistics issues official predictions advance estimates in the form of estimates and projections for key grains and commercial crops. However, these guesses in advance are not the actual projections. Using the K-Nearest Neighbors (KNN) method to estimate agricultural yields is a good choice since it is easy to understand, can handle non-linearity, and works well with small to medium datasets. Given these features, KNN is a good choice for agricultural stakeholders, including academics, decision-makers, and farmers who may not have a lot of experience with machine learning. With the use of the KNN method, agricultural yield estimate models may be trained to provide precise crop production predictions given pertinent input data. There is a lot of subjective judgment based on a variety of qualitative criteria involved in arriving at these estimations. As a result, it's important to provide objective, statistically reliable projections of future crop areas and yields. Technological developments in computers and data storage have made an enormous amount of Information available. The difficulty has been in gleaning insight from this mountain of data, but recent advances in areas like data mining have opened a door from this data to more precise estimates of agricultural yield. Results show that the accuracy is 90%, and the error value is 10% using the KNN algorithm for the given agriculture datasets. © 2024 IEEE.

关键词： Crops

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Optimizing Routing Paths in Mobile Wireless Sensor Networks: A Sub-Flow Adaptive Multipath Approach for Energy Efficiency and Delay Sensitivity 8

Optimizing Routing Paths in Mobile Wireless Sensor Networks:...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Raja, R. Vinston Siddiqui, Shavej Ali Avilasha, B.G. Kannan, L. Mohana Srm Institute of Science and Technology Faculty of Engineering and Technology School of Computing Department of Computational Intelligence Chennai Tamil Nadu Kattankulathur India Khwaja Moinuddin Chishti Language University Faculty of Engineering and Technology Deparment of Applied Science and Humanities Lucknow India Dayanandasagar College of Engineering Deparment of Mechanical Engineering Bangalore India Erode Sengunthar Engineering College Department of Biomedical Engineering Tamil Nadu Perundurai India

ISBN: (纸本)9798350376425

Wireless Sensor Networks (WSNs) have become crucial in various domains such as social applications, healthcare, and the military. However, their diversity makes them susceptible to a wide range of attacks, leading to challenges like poor throughput, high network latency, and excessive energy consumption. This study proposes a novel approach that combines residual Riemannian neural networks with the Sub-Flow Adaptive Multipath Routing algorithm for enhanced routing and attack detection in WSNs. By leveraging node position data, the Sub-Flow Adaptive Multipath Routing algorithm optimizes energy consumption and extends network lifespan. Simultaneously, residual Riemannian neural networks analyze residual patterns in network traffic data to accurately detect rogue nodes, thereby enhancing security. Blockchain technology is then employed to securely store classified data, ensuring data integrity and security. This integrated approach significantly improves network performance, maintains robust security against potential threats, and enhances the reliability of WSNs in demanding environments. © 2024 IEEE.

关键词： Energy utilization

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