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Contact Force-Velocity Control for a Planar Aerial Manipulator

IFAC-PapersOnLine 2022年第1期55卷 1-7页

作者： Prakashkumar D. Suthar Vivek Sangwan PhD Student Department of Mechanical Engineering Indian Institute of Technology Bombay Mumbai India Assistant Professor (Corresponding Author) Department of Mechanical Engineering Indian Institute of Technology Bombay Mumbai India

This paper addresses the challenge of controlling contact force and velocity between the end-point of a manipulator mounted on an aerial robot and an external surface. This has numerous applications involving tactile interactions such as painting of walls, cleaning window panes on skyscrapers, maintenance of bridges, solar farms etc. First, this paper presents a static analysis of a planar UAV with a two-link manipulator to determine conditions that the configuration variables (degrees-of-freedom) need to satisfy to generate a desired normal contact force. Following this, a hybrid force/velocity control strategy is presented to track (i) a desired normal contact force with a vertical wall and (ii) a desired velocity of the point of contact along the wall. Finally, to demonstrate the effectiveness of this controller, numerical simulation results of this controller with a dynamic model of a planar two link aerial manipulator are presented.

关键词： Unmanned Aerial Vehicle Aerial Manipulator Velocity/Force Control

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How chief risk officers (CROs) can have meaningful and productive dealings with insurance agencies: a leading example

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SN Business and Economics 2021年第5期1卷 1-25页

作者： Bettanti, Alberto Lanati, Antonella PhD RIMS-CRMP Department of Mechanical Energy Logistics Engineering and Engineering Management (DIME) University of Genoa Genoa Italy Engineering MSc Consultant Valore Qualità Pavia Italy

In broad terms, risk management (RM) covers four conventional actions in addressing operational risks (OpRisks), i.e., actions to mitigate, eliminate, accept, and transfer operational risks. In relation to transferring OpRisks to external third parties, this study aids chief risk officers (CROs) in addressing issues related to the reduction of economic exposure to OpRisk. In this respect, the economic handling of OpRisks and their coverage through specific insurance programs are among the major challenges that CROs face within their roles. The aim of this paper is to provide CROs with an analytical pathway to addressing these challenges by applying the total cost of risk (TCoR) method tailored to their purposes. Through a leading example, this paper demonstrates that the TCoR approach meaningfully and productively supports CROs’ decisions when striving to deal with OpRisk. In fact, the TCoR approach implementation, together with the application of Monte Carlo simulation as a computational tool, drives TCoR value optimization when OpRisk is transferred to insurance agencies. In addition, by applying a TCoR framework, CROs can find the correct and cost-effective balance between the company’s retention level—consistent with the company’s risk appetite—and the premiums paid to insurance agencies. In conclusion, this paper provides CROs with a methodological approach for efficiently building relationships with insurance agencies by consistently addressing TCoR-based dealings. © The Author(s) 2021.

关键词： Chief risk officer (CRO) Insurable risk Operational risk (OpRisk) Total cost of risk (TCoR)

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Utilizing Hybrid Deep Reinforcement Learning and Transformer Networks for Predictive Maintenance in Product Safety engineering

Utilizing Hybrid Deep Reinforcement Learning and Transformer...

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Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA), International Conference on

作者： Divya Nimma Mathi Kannaiyan Deepak Gupta Manidipa Roy Mohammed Saleh Al Ansari A. Balakumar PhD in Computational Science University of Southern Mississippi Data Analyst in UMMC USA Department of Mechanical Engineering University College of Kancheepuram Anna University Kancheepuram Campus Kanchipuram Tamil Nadu India Department of Mechanical Engineering Graphic Era Hill University Dehradun Uttarakhand India Department of Mechanical Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of ECE ABES Engineering College Ghaziabad Uttar Pradesh India Department of Chemical Engineering College of Engineering University of Bahrain Bahrain Department of ECE K.Ramakrishnan College of Engineering Trichy India

ISBN: (数字)9798331517953

ISBN: (纸本)9798331517960

Predictive maintenance (PdM) is essential to make sure the protection and reliability of the technology. This paper affords a remarkable technique that mixes hybrid deep reinforcement getting to know (DRL) with transformer networks to enhance predictive protection strategies for protection in material safety engineering. In most cases, inefficient and costly implementation strategies are based on predefined guidelines or ad hoc practices in traditional management. A system that integrates DRL and Transformer Networks to quickly identify and predict operational needs and respond effectively to various conditions. Hybrid DRL approach has the capability of non-modeling and reinforcing model-based learning for maintenance a it is best through communication with the system. enabling the study of systems Environmental and historical data. The recognized efficiency of transformer networks in sequential data processing will enhances the ability of the model to process and interpret the time series sensor data, helps to improves the prediction performanceThis method uses dual stage architecture which extract the time based features from sensor data. This approach agrees real-time optimization of emerging patterns and anomalies, This will improves prediction capabilities and reduces false positives. This model was tested on various industrial datasets, indicating significant developments in prediction accuracy and maintenance scheduling efficiency compared to traditional methods. By integrating these advanced techniques, The approach provides a more vigorous and adaptive solution for ensuring product safety and reliability in complex industrial environments. Proposed model achieved a notable reduction in Mean Absolute Error (MAE) 0.15 compared to traditional predictive maintenance methods.

关键词： Adaptation models Time series analysis Predictive models Transformers Feature extraction Data models Real-time systems Maintenance Protection Predictive maintenance

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Comparative Analysis of AD8232 and BioAmp EXG Pill Analog Front-End Devices in ECG Signal Processing

Comparative Analysis of AD8232 and BioAmp EXG Pill Analog Fr...

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IEEE Conference on Systems, Process & Control (ICSPC)

作者： Tanakrit Mamee Panason Manorost Chakkapong Chamroon Kittiya Thunsiri Department of Mechanical Engineering PhD Program in Mechanical Engineering Under the CMU Presidential Scholarship Chiang Mai University Chiang Mai Thailand Faculty of bioscience engineering KU Leuven University Leuven Belgium Biomedical Engineering Institute Chiang Mai University Chiang Mai Thailand Department of Mechanical Engineering Chiang Mai University Chiang Mai Thailand Faculty of Engineering Chiang Mai University Chiang Mai Thailand

The development of compact portable ECG monitoring devices often entails the pursuit of downsizing measurement systems. This objective frequently involves additional efforts, such as custom PCB fabrication for analog front-end systems and exploration of alternative electrode types and configurations. In this study, we investigate the feasibility of using the BioAmp EXG Pill, a miniature commercial analog front-end board, in comparison to the well-established AD8232. Our analysis focuses on comparing ECG signals from five adult subjects, examining both frequency components using the welch estimation method and ECG parameters extracted from time-domain signals. The results reveal that both devices provided similar outcomes in time-domain measurements, with a slightly lower standard deviation observed in the AD8232. In terms of spectral density, both devices proficiently captured low-frequency components within the 0–3 Hz range. However, in higher-frequency domains, the AD8232 demonstrated superior capability in capturing finer frequency details.

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Enhanced light-driven photoelectrochemical catalysis of water splitting by TiO2 nanotubes grown on acid-etched titanium foils

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International Journal of Hydrogen Energy 2024年第PartA期51卷 1483-1493页

作者： Hsiao, Yu-Cheng Lai, Jhih-Hong Fan, Yu-Min Chen, Hung-Ming Yougbaré, Sibidou Saukani, Muhammad Chen, Chih-Yu Wu, Yung-Fu Lin, Lu-Yin International PhD Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Stanford Byers Center for Biodesign Stanford University CA94305-5428 United States Graduate Institute of Biomedical Optomechatronics College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan Department of Chemical Engineering Ming Chi University of Technology New Taipei City24301 Taiwan Gingen Technology Co. LTD. Rm. 7 10F. No.189 Sec. 2 Keelung Rd. Xinyi Dist. Taipei11054 Taiwan /Nanoro 03 B.P 7192 Ouagadougou03 Burkina Faso Department of Mechanical Engineering Faculty of Engineering Universitas Islam Kalimantan MAB Jl. Adhyaksa No. 2 Banjarmasin70124 Indonesia Department of Orthopedics Shuang Ho Hospital Taipei Medical University New Taipei City23561 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Cell Physiology and Molecular Image Research Center Wan Fang Hospital Taipei Medical University Taipei11696 Taiwan

Titanium dioxide with suitable band edges is one of promising photocatalysts for water splitting. Nanotubes with one-dimensional structure can induce efficient charge transfers and hollow centers can provide large surface area for surface reactions. Modifying Ti foils for anodization can enhance light utilization of TiO2 nanotube photoelectrodes. In this work, it is firstly to fabricate TiO2 nanotube photoelectrodes on acid-etched Ti foils by anodization (MNT) for photoelectrochemical catalyzing water splitting. Different acid-etching durations are applied on Ti foils to induce various rugged surfaces. The resulting photoelectrodes present largely enhanced light utilization than that fabricated by the pristine Ti foil. The anodization duration is also optimized to find suitable lengths of MNT. The smallest overpotential of 524.7 mV at 10 mA/cm2 and Tafel slope of 167 mV/dec are obtained for the optimal MNT photoelectrode. The TiO2 nanotubes grown on the pristine Ti foil shows the overpotential of 679.3 mV at 10 mA/cm2 and Tafel slope of 285 mV/dec. This result opens a blueprint for raising the photocatalytic ability by simply modifying the surface property of the conductive substrate. Other modifications may be applicable to enhance the roughness of Ti foils for growing more efficient MNT array as photocatalysis of water splitting. © 2023 Hydrogen Energy Publications LLC

关键词： Titanium dioxide

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Rapid Escherichia coli Cloned DNA Detection in Serum Using an Electrical Double Layer-Gated Field-Effect Transistor-Based DNA Sensor

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Analytical Chemistry 2023年第17期95卷 6871-6878页

作者： Paulose, Akhil K. Hou, Yueh-Ju Huang, Yu-Shan Chakkalaparambil Dileep, Navyamol Chiu, Chia-Lin Pal, Arnab Kalaimani, Vishal Mani Lin, Zong-Hong Chang, Chuang-Rung Chen, Cheng-Pin Lin, Yi-Chun Cheng, Chien-Yu Cheng, Shu-Hsing Cheng, Chao-Min Wang, Yu-Lin Institute of Nanoengineering and Microsystems National Tsing Hua University Hsinchu30013 Taiwan Department of Power Mechanical Engineering National Tsing Hua University Hsinchu30013 Taiwan College of Semiconductor Research National Tsing Hua University Hsinchu30013 Taiwan Department of Life Sciences National University of Kaohsiung Kaohsiung811726 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Institute of Biotechnology National Tsing Hua University Hsinchu30013 Taiwan Department of Infectious Diseases Taoyuan General Hospital Ministry of Health and Welfare Taoyuan32748 Taiwan Institute of Biomedical Engineering National Tsing Hua University Hsinchu30013 Taiwan International Intercollegiate PhD Program National Tsing Hua University Hsinchu30013 Taiwan

In this study, a rapid diagnosis platform was developed for the detection of Escherichia coli O157:H7. An electrical double layer (EDL)-gated field-effect transistor-based biosensor (BioFET) as a point-of-care testing device is demonstrated with its high sensitivity, portability, high selectivity, quick response, and ease of use. The specially designed ssDNA probe was immobilized on the extended gate electrode to bind the target complementary DNA segment of E. coli, resulting in a sharp drain current change within minutes. The limit of detection for target DNA is validated to a concentration of 1 fM in buffer solution and serum. Meanwhile, the results of a Kelvin probe force microscope were shown to have reduced surface potential of the DNA immobilized sensors before and after the cDNA detection, which is consistent with the decreased drain current of the BioFET. A 1.2 kb E. coli duplex DNA synthesized in plasmid was sonicated and detected in serum samples with the sensor array. Gel electrophoresis was used to confirm the efficiency of sonication by elucidating the length of DNA. Those results show that the EDL-gated BioFET system is a promising platform for rapid identification of pathogens for future clinical needs. © 2023 American Chemical Society

关键词： DNA

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Magnetic Field Aided Vehicle Localization with Acceleration Correction

Magnetic Field Aided Vehicle Localization with Acceleration ...

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

作者： Mrunmayee Deshpande Manoranjan Majji J. Humberto Ramos PhD Student at the Aerospace Engineering Department Texas A&M University College Station TX USA Associate Professor at the Aerospace Engineering Department Texas A&M University College Station TX USA Research Assistant Scientist at the Department of Mechanical and Aerospace Engineering University of Florida Fl USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper presents a novel approach for vehicle localization by leveraging the ambient magnetic field within a given environment. Our approach involves introducing a global mathematical function for magnetic field mapping, combined with Euclidean distance-based matching technique for accurately estimating vehicle position in suburban settings. The mathematical function based map structure ensures efficiency and scalability of the magnetic field map, while the batch processing based localization provides continuity in pose estimation. Additionally, we establish a bias estimation pipeline for an onboard accelerometer by utilizing the updated poses obtained through magnetic field matching. Our work aims to showcase the potential utility of magnetic fields as supplementary aids to existing localization methods, particularly beneficial in scenarios where Global Positioning System (GPS) signal is restricted or where cost-effective navigation systems are required.

关键词： Location awareness Accelerometers Three-dimensional displays Scalability Pose estimation Vehicle driving Pipelines Trajectory Magnetic fields Global Positioning System

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A review on role of artificial intelligence in food processing and manufacturing industry

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Materials Today: Proceedings 2022年 51卷 2462-2465页

作者： Ramirez-Asis, Edwin Vilchez-Carcamo, Juan Thakar, Chetan M. Phasinam, Khongdet Kassanuk, Thanwamas Naved, Mohd Research professor Department of Business and tourism faculty Universidad Nacional Santiago Antúnez de Mayolo Huaraz Peru Phd in management Department of Business and tourism faculty Universidad Nacional Santiago Antúnez de Mayolo Huaraz Peru Assistant Professor Department of Mechanical Engineering Government College of Engineering Maharashtra Karad India School of Agricultural and Food Engineering Faculty of Food and Agricultural Technology Pibulsongkram Rajabhat University Phitsanulok Thailand Assistant Professor Department of Business Analytics Jagannath University Delhi-NCR India

Food is essential for humans. It is critical to decrease food waste, optimize the supply chain, and enhance food logistics, food delivery, and food safety. To a large extent, artificial intelligence and machine learning aid in accomplishing these goals. The increasingly widespread and sophisticated computing networks enable modern industrial and logistical systems. Data are continually created by sensors, machines, systems, intelligent devices and people inside these networks. This Big Data is analyzed quicker, more extensively and deeper than ever with increasing computer powers. These breakthroughs have redeveloped and created a new age known as Industry 4.0 or the Smart Factory, the value of artificial information technology (AI). This article discusses machine learning and artificial intelligence applications in the food industry and manufacturing. Major applications include supply chain optimization, crop selection, logistics, food delivery, and forecasting maintenance in food processing machines. © 2022

关键词： Supply chains

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CAD-CAM complete digital dentures: An improved clinical and laboratory workflow

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Journal of Prosthetic Dentistry 2025年第6期133卷 1430-1435页

作者： Grande, Francesco Pavone, Lorenzo Molinelli, Fabrizio Mussano, Federico Srinivasan, Murali Catapano, Santo PhD student Department of Mechanical and Aerospace Engineering Polytechnic University of Turin Turin Italy and Research Assistant Department of Prosthodontics University of Ferrara Ferrara Italy Research Assistant Department of Surgical Sciences CIR Dental School University of Turin Turin Italy Dental Technician Private practice Ispra Italy Department of Surgical Sciences CIR Dental School University of Turin Turin Italy Clinic of General- Special Care and Geriatric Dentistry Center of Dental Medicine University of Zurich Zurich Switzerland and Department Head Department of Prosthodontics University of Ferrara Ferrara Italy

The purpose of this article was to present a novel clinical workflow for the fabrication of complete dentures using computer-aided design and computer-aided manufacturing (CAD-CAM) technology. The dental technique consists of 3 clinical steps and 2 laboratory phases that result in the production of 2 CAD-CAM milled complete denture bases with prefabricated teeth. The integration of analog and digital procedures and materials maximizes their benefits in the planning and fabrication of complete dentures, with the goal of improving clinical outcomes. © 2024

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Comparative analysis of various oxygen production techniques using multi-criteria decision-making methods

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International Journal of Thermofluids 2023年 17卷

作者： Aljaghoub, Haya Alasad, Shamma Alashkar, Adnan AlMallahi, Maryam Hasan, Ranem Obaideen, Khaled Alami, Abdul Hai Department of Industrial Engineering and Engineering Management University of Sharjah Sharjah United Arab Emirates Mechanical Engineering Department American University of Sharjah Sharjah United Arab Emirates Materials Science and Engineering PhD Program American University of Sharjah Sharjah United Arab Emirates Department of Mechanical and Aerospace Engineering United Arab Emirates University Al Ain City United Arab Emirates Department of Sustainable and Renewable Energy Engineering University of Sharjah Sharjah United Arab Emirates Sustainable Energy and Power Systems Research Center RISE University of Sharjah Sharjah United Arab Emirates Center for Advanced Materials Research University of Sharjah Sharjah United Arab Emirates

The current pandemic has adversely affected oxygen production and supply chain, where oxygen treatment is essential for the emergency treatment protocol of patients infected by the virus. This work reports on various techniques of oxygen generation methods, as well as the challenges facing its production, storage, and transportation. Moreover, this study offers a comparative analysis of various oxygen production techniques using Multi-Criteria Decision-Making Methods (MCDM). Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), in addition to the weighting methodologies, Multiplicative Exponential Weighting (MEW) and Simple Additive Weighting (SAW) are chosen as tools to carry out the statistical analysis and rank the oxygen production methods. The ranking criteria includes cost, performance, environmental impact and safety. Moreover, this paper utilizes the Entropy Weight Method (EWM), Criteria Importance Through Inter-criteria Correlation (CRITIC) method, and the Stochastic Dominance (SD) method to distribute the criteria weights. The results show thar oxygen production using membrane technologies is the optimal technique based on all the provided tools and criteria. as it attained the maximum Entropy and Sd values of 0.548 through the TOPSIS method, and the highest CRITIC value through SAW and MEW methods which were 0.260 and 0.236, respectively. © 2022 The Author(s)

关键词： Stochastic systems

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