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Optical Elastography and Tissue Biomechanics VIII 2021

作者： Liu, Hsiao-Chuan Kijanka, Piotr Urban, Matthew W. Dept. of Radiology Mayo Clinic RochesterMN55905 United States Dept. of Robotics and Mechatronics AGH University of Science and Technology Krakow30059 Poland Dept. of Physiology and Biomedical Engineering Mayo Clinic RochesterMN55905 United States

ISBN: (数字)9781510641266

ISBN: (纸本)9781510641259

Tissue mechanics have been widely studied for the past two decades because they are significantly associated with disease states. The variations of mechanical properties in soft tissues are considerable indicators used for clinical diagnosis and disease monitoring. Optical coherence elastography (OCE) has been extensively developed to characterize the mechanical properties of various tissues. However, these methods are generally based on time-domain data and measure the time-of-flight of the localized shear wave propagations. Here, we propose a method to evaluate phase velocity in four-dimensional (4D) space (x, y, z, f), called 4D-OCE phase velocity, and applied it to a heterogeneous phantom with a 4 mm diameter inclusion. A 7.5 MHz highly focused transducer transmitting a toneburst of 500 µs was used to provide an acoustic radiation force (ARF) for transient elastography. A customized 4D acquisition pattern was developed under Microsoft Visual C++ 2019 development environment. The 3D-OCE group velocity was reconstructed to compare with 4D-OCE phase velocity as cross-verification. The experimental result from the heterogeneous phantom showed that 4D-OCE phase velocity is capable of accurately reconstructing a 4D-OCE phase velocity map and provides good contrast between two gelatin materials with different concentrations, 7% versus 14%. The proposed 4D-OCE phase velocity can provide further information to better understand the delicate change of mechanical properties of various biological tissues in each voxel over a range of temporal frequencies. © 2021 SPIE

关键词： Tissue

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Methodology of Low Orbit Satellites Signal Processing in the Electromagnetically Noisy Environment

Methodology of Low Orbit Satellites Signal Processing in the...

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Electrical, Electronic and Information Sciences (eStream), Open Conference of

作者： Viktor Masalskyi Vytautas Bučinskas Andrius Dzedzickis Aramais Tyshchenko Oleksandr Masalskyi Dept. of Mechatronics Robotics and Digital Manufacturing Vilnius Gediminas Technical University Vilnius Lithuania Department of Engineering University of Warwick Coventry UK Department of Physics Vilnius Gediminas Technical University Vilnius Lithuania

This paper dedicated to the problematics of low orbit satellite data acquisition and processing. Efforts to improve the quality and reliability of receiving these signals in a noisy electromagnetic environment presented here as theoretical and practical solution. Paper defines the requirements for equipment, provides definition of required parameters and delivers experimental tests methodology and obtained results. The experimental results deliver a hope for reliable reception; there are necessary to use a receiver with a dynamic range of at least 70 dB. Test environment was performed on the campus of the university, where located near antennas of high power FM transmitters, digital television and other communication services. Solutions for signal acquisition in the mentioned environment described as means to improve the quality and reliability of reception. Here provided number of technological improvements performed in configuration of the receiving station: implemented high precision angle sensors, a low-noise amplifier, a high-gain antenna and RF filters. Proposed to use a complex filtering stage consisting of three filters: band pass, notch and high-pass filter. To compensate for receiver noise and losses in the antenna-feeder path, a low-noise amplifier installed nearby the antenna. The obtained test results confirmed efficiency of the receiving station upgrade. Finally, paper delivers some conclusions.

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A Tool to Evaluate Industrial Cobot Safety Readiness from a System-Wide Perspective: an Empirical Validation

SSRN

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SSRN 2023年

作者： Berx, Nicole Decré, Wilm Pintelon, Liliane Dept. Mechanical Engineering Centre for Industrial Management/Traffic and Infrastructure KU Leuven Leuven3001 Belgium Dept. Mechanical Engineering Division Robotics Automation and Mechatronics KU Leuven Leuven3001 Belgium Core Lab M&A Flanders Make@KU Leuven Heverlee3001 Belgium

The emergence of collaborative robots (cobots) has transformed the interaction between humans and robots in industrial workspaces. While cobots offer significant advantages in productivity and flexibility, their unique interaction model with humans introduces additional safety considerations. Moreover, the adoption of cobots remains limited, partly due to a lack of awareness and knowledge about their safety. To address these challenges, the Cobot Safety Readiness Assessment Tool (CSRAT) evaluates cobot safety readiness, the combination of awareness and knowledge, from a system-wide perspective. The CSRAT is grounded in maturity grid models evaluating the readiness of technological and other safety risk factors such as operator trust, privacy, and training. It allows practitioners to self-assess their cobot safety readiness and perceived importance of risk factors. Additionally, the tool aims to facilitate alignment among internal stakeholders on cobot safety. The CSRAT prototype underwent iterative development and validation by experts from academia and industry. Empirical validation results highlight the tool's usefulness, effectiveness, and usability. It successfully enhances users' awareness and knowledge of safety risk factors and serves as a conversation starter among internal *** industry practitioners, the CSRAT offers practical relevance in enhancing safety readiness, guiding decision-making, and addressing overlooked risk factors. Academically, this research contributes to the fields of human-robot interaction, safety evaluation, usability research, and cobot adoption. In conclusion, this research provides a comprehensive approach to evaluating cobot safety readiness and promoting informed decision-making for safer human-robot collaborations. While acknowledging CSRAT's value and limitations, the paper also points towards potential future research directions. © 2023, The Authors. All rights reserved.

关键词： Industry 4.0

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Sensor based target tracking with application to autonomous docking and self-reconfigurability

Sensor based target tracking with application to autonomous ...

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ASME 2020 International Design engineering Technical Conferences and Computers and Information in engineering Conference, IDETC-CIE 2020

作者： Sohal, Shubhdildeep S. Ben-Tzvi, Pinhas Robotics and Mechatronics Lab Mechanical Engineering Dept. Virginia Tech BlacksburgVA United States

ISBN: (纸本)9780791883990

This paper presents a target detection technique, which combines a supervised learning model with sensor data to eliminate false positives for a given input image frame. Such a technique aids with selective docking procedures where multiple robots are present in the environment. Hence the sensor data provides additional information for this decision making process. Senor accuracy plays a crucial role when the motion of the robot is defined by the use of data recorded by its sensors. The uncertainties in the sensory data can cause misalignments due to poor calibration of the sensor, which can result in poor positioning of the robot relative to its target. Such misalignments can play a significant role where certain accuracy is desired. Therefore, it is necessary to minimize such misalignments to achieve certainty for the robot interaction with its target. The work proposed in this paper allows achieving such accuracy using a vision-based approach by eliminating all false occurrences leading to selective interactions with the target. The proposed methodology is validated using a self-reconfigurable mobile robot capable of hybrid Wheeled-Tracked mobility, as an application towards autonomous docking of mobile robotic modules. Copyright © 2020 ASME

关键词： Target tracking

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Simulation and Control of Inverted Pendulum System Dynamics over Control Area Network using TrueTime 8

Simulation and Control of Inverted Pendulum System Dynamics ...

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8th IEEE R10 Humanitarian Technology Conference, R10-HTC 2020

作者： Abdulrab, Hakim Qaid Abdullah Hussin, Fawnizu Azmadi Motea, Zakarya Zaidi, Rose Neezar Rose Universiti Teknologi Petronas Dept. of Electrical and Electronic Engineering Perak Malaysia Universiti Teknologi Malaysia Dept. of Control and Mechatronics Engineering Johor Malaysia Dept. of Mechatronics and Robotics Engineering Faculty of Engineering and IT Taiz University Taiz Yemen

ISBN: (纸本)9781728111100

Inverted pendulum is one the most popular systems that has been used and studied in the field of control engineering. Even its simplest form is an under-actuated system and highly unstable with high non-linear dynamics. Therefore, it is a challenging control task and have been referred to as benchmark for testing control algorithms. This paper discusses modelling and control of inverted pendulum using Linear Quadratic Regulator (LQR) controller. Then, the same model and controller are inserted to a real time Simulink model for the purpose of analysing the scheduling of tasks and testing control area network (CAN) performance. This is done by utilizing True Time toolbox. In this paper both nonlinear and linearized models were analysed. Four sensors, an actuator and a controller are used in analysing the response of the inverted pendulum. Different scheduling techniques and the response of the system after changing the period of one of the sensors in the system were also investigated. By changing the period of one sensor and maintaining the other 3 sensors, the system became unstable as discussed throughout the paper. © 2020 IEEE.

关键词： Inverted pendulum

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Towards human-like kinematics in industrial robotic arms: a case study on a UR3 robot

arXiv

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arXiv 2024年

作者： Wolniakowski, Adam Miatliuk, Kanstantsin Quintana, Jose J. Ferrer, Miguel A. Diaz, Moises Faculty of Electrical Engineering Bialystok University of Technology Bialystok Poland IDeTIC Institute University of Las Palmas de G.C. Las Palmas Spain Dept. of Robotics and Mechatronics Bialystok University of Technology Bialystok Poland Dept. of Automatic and Electronic University of Las Palmas de G.C. Las Palmas Spain

Safety in industrial robotic environments is a hot research topic in the area of human-robot interaction (HRI). Up to now, a robotic arm on an assembly line interacts with other machines away from human workers. Nowadays, robotic arm manufactures are aimed to their robots could increasingly perform tasks collaborating with humans. One of the ways to improve this collaboration is by making the movement of robots more humanlike. This way, it would be easier for a human to foresee the movement of the robot and approach it without fear of contact. The main difference between the movement of a human and of a robotic arm is that the former has a bell-shaped speed profile while the latter has a uniform speed one. To generate this speed profile, the kinematic theory of rapid human movements and its Sigma-Lognormal model has been used. This model is widely used to explain most of the basic phenomena related to the control of human movements. Both human-like and robotic-like movements are transferred to the UR3 robot. In this paper we detail the how the UR3 robot was programmed to produce both kinds of movement. The dissimilarities result between the input motion and output motion to the robot confirm the possibility to develop human-like velocities in the UR3 robot. © 2024, CC BY-NC-ND.

关键词： Robotic arms

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New High Boost DC-DC Converter for Renewable Energy Conversion

New High Boost DC-DC Converter for Renewable Energy Conversi...

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International Conference on Communications and Electronics, ICCE

作者： Dinh-Tuyen Nguyen Truong-Khang Duong Truong-Duy Duong Trong-Nha Quang Ton Duc Do Faculty of Electrical and Electronics Engineering Ho Chi Minh City University of TechnologyVNU-HCM Ho Chi Minh City Vietnam Dept. Electrical and Computer Engineering Wayne State University Detroit MI USA High Volume Power Design Advanced Energy Industries Inc Eden Prairie MN USA Dept. Robotics and Mechatronics School of Science and Technology Nazarbayev University Kazakhstan

ISBN: (数字)9798350379792

ISBN: (纸本)9798350379808

This paper proposes a high-boost power converter for renewable energy systems. The suggested converter exhibits a simplified structure by replacing a diode in the switched-inductor cell with an active power switch to reduce the total voltage stress on the semiconductor device, get cost reduction, and improve efficiency. Additionally, the common ground feature inherent in the introduced topology expands its potential for renewable energy applications. Finally, the simulation verifications are performed using PSIM software to confirm the effectiveness of the suggested approach, and a detailed comparison study between the basic switched-inductor converter and the suggested converter is also presented.

关键词： Renewable energy sources Costs Simulation Prototypes Voltage Switches Software

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Development of a Sign Language for Total Paralysis and Interpretation using Deep Learning 1

Development of a Sign Language for Total Paralysis and Inter...

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1st International Conference on Image Processing and robotics, ICIPRoB 2020

作者： Sarowar Dhrubo, Zahan Zib Islam Hridoy, Md. Ashiful Jamal, Lafifa Sarker, Sujan Shidujaman, Mohammad University of Dhaka Department of Robotics and Mechatronics Engineering Dhaka Bangladesh Tsinghua University Academy of Arts and Design X-Studio Dept. of Information Art and Design Beijing China

ISBN: (纸本)9781728165417

People with total paralysis suffer not just from physical disability but also from the agony of the inability to communicate and express their feelings. Researches have long tried to solve this problem with various techniques such as collecting the patient's message directly from the brain using Brain-Computer interface and determining the gaze of the patient on a screen that contains letters and symbols. The first approach proved to be expensive and less accurate. The second one needs very fine calculation of the pupil center and even if done correctly the drifting of the human eye makes it hard to get a better accuracy. Again, all of these methods are dependent on electronic devices. In this paper, we proposed a solution that does not require the help of any electronic devices by developing a sign language for eye movements. We also proposed an approach to automatically interpret the patient's sign using Convolutional Neural Network and achieved great accuracy on the training data. This suggests that our network can be used to provide a better communication method for paralyzed patients. © 2020 IEEE.

关键词： Convolutional neural networks

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A Study on the Perception of Digitalization and Use of Digital Technologies in Higher-Education Institutions

A Study on the Perception of Digitalization and Use of Digit...

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International Conference on System Theory, Control, and Computing (ICSTCC)

作者： Marius Marian Ilie Borcoși Eugen Ganea Corina-Ana Borcoși Dorin Popescu Adelin Cusman Dept. of Computers and IT University of Craiova Craiova Romania Fac. of Engineering “Constantin Brâncuși” University Tg. Jiu Romania Institute of Rsch. Dev. and Innovation “Constantin Brâncuși” University Tg. Jiu Romania Dept. of Mechatronics and Robotics University of Craiova Craiova Romania CERT DIGITAL Centrul de Calcul S.A. Tg. Jiu Romania

Correlating the education and training system with the evolution of today’s technologies is a complex but necessary process for training, improvement, and lifelong learning. Digital technologies are present today in all fields, and have become increasingly necessary in higher education institutions, not only to attract students, to bring them into a familiar environment, but also to initiate and improve their skills in what is an evolution in science. The digitalization of education services is necessary to have a more accessible, interactive, and personalized educational process and this also involves the use of digital technologies, elements that contribute to people’s self-education, and education outside of schools’ walls. In this paper we present aspects related to the digitalization of education, both from the perspective of educators and learners. It is a study carried out in two Romanian universities, the University of Craiova and the “Constantin Brâncuși” University of Târgu Jiu. The purpose of this work is to emphasize the necessity of digitalization, its importance, but also to emphasize the stage in which the two universities are now, in relation to what is meant by digitalization, who should be involved in the digitalization of the institution, what activities should be digitalized, knowledge of the digital signature concept or whether respondents use machine learning tools such as ChatGPT, or others. The results of this study reflect the opinion of the teachers and students of the two universities.

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COVIDXception-Net: A Bayesian Optimization Based Deep Learning Approach to Diagnose COVID-19 from X-Ray Images

Research Square

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Research Square 2020年

作者： Arman, Shifat E. Rahman, Sejuti Deowan, Shamim Ahmed Dept. of Robotics and Mechatronics Engineering University of Dhaka Dhaka Bangladesh

Background: The Coronavirus Disease 2019 (COVID-19) is highly contagious and spreading around the world like wildfire. For this reason, fast and accurate diagnosis of COVID-19 is of tremendous importance. Chest X-rays can be used to diagnose COVID-19 but there is a global shortage of radiologists who can interpret X-rays. This study aims to develop an artificial intelligence system that can diagnose COVID-19 from chest X-rays with no human intervention. Methods: In this study, we used four pre-trained architectures - VGG16, MobileNetV2, InceptionV3 and Xception to detect COVID-19 from chest x-ray images. The architectures are optimized using Bayesian optimization and we used a weighted loss function to get better generalization capability in our models. Results: Of the four architectures we optimized, our proposed model called COVIDXception-Net performed best on the test set with an accuracy 0.94, precision 0.95, recall 0.94, and F1-score 0.94. It outperforms previous state-of-the-art methods in terms of these evaluation metrics on similar datasets. In the ablation studies, we found that the accuracy of our model dropped from 0.994 to 0.950 when we used random search instead of Bayesian optimization and 0.994 to 0.983 when we used regular loss function instead of a weighted loss function. Conclusions: In this study, we developed a model called COVIDXception-Net to diagnose COVID-19 from X-ray images. We hope that our research will assist all those involved in handling this pandemic. © 2020, CC BY.

关键词： Coronavirus

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