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Automatic search for photoacoustic marker using automated transrectal ultrasound

Biomedical Optics Express 2023年第11期14卷 6016-6030页

作者： Wu, Zijian Moradi, Hamid Yang, Shuojue Song, Hyunwoo Boctor, Emad M. Salcudean, Septimiu E. Johns Hopkins University Laboratory for Computational Sensing and Robotics BaltimoreMD United States University of British Columbia Dept. of Electrical and Computer Engineering VancouverBC Canada University of Texas at Austin Walker Department of Mechanical Engineering AustinTX United States Johns Hopkins University Dept. of Computer Science BaltimoreMD United States

Real-time transrectal ultrasound (TRUS) image guidance during robot-assisted laparoscopic radical prostatectomy has the potential to enhance surgery outcomes. Whether conventional or photoacoustic TRUS is used, the robotic system and the TRUS must be registered to each other. Accurate registration can be performed using photoacoustic (PA markers). However, this requires a manual search by an assistant [IEEE Robot. Autom. Lett 8, 1287 (2023).]. This paper introduces the first automatic search for PA markers using a transrectal ultrasound robot. This effectively reduces the challenges associated with the da Vinci-TRUS registration. This paper investigated the performance of three search algorithms in simulation and experiment: Weighted Average (WA), Golden Section Search (GSS), and Ternary Search (TS). For validation, a surgical prostate scenario was mimicked and various ex vivo tissues were tested. As a result, the WA algorithm can achieve 0.53°±0.30° average error after 9 data acquisitions, while the TS and GSS algorithm can achieve 0.29◦±0.31◦ and 0.48°±0.32° average errors after 28 data acquisitions. © 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Urology

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Preference detection of the humanoid robot face based on EEG and eye movement

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Neural Computing and Applications 2024年第19期36卷 11603-11621页

作者： Wang, Pengchao Mu, Wei Zhan, Gege Wang, Aiping Song, Zuoting Fang, Tao Zhang, Xueze Wang, Junkongshuai Niu, Lan Bin, Jianxiong Zhang, Lihua Jia, Jie Kang, Xiaoyang Laboratory for Neural Interface and Brain Computer Interface Engineering Research Center of AI and Robotics Ministry of Education Shanghai Engineering Research Center of AI and Robotics MOE Frontiers Center for Brain Science State Key Laboratory of Medical Neurobiology Institute of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai200433 China Ji Hua Laboratory Guangdong Province Foshan528200 China Department of Rehabilitation Medicine Huashan Hospital Fudan University Shanghai200040 China Yiwu Research Institute of Fudan University Zhejiang Yiwu322000 China Research Center for Intelligent Sensing Zhejiang Lab Hangzhou311121 China

The face of a humanoid robot can affect the user experience, and the detection of face preference is particularly important. Preference detection belongs to a branch of emotion recognition that has received much attention from researchers. Most of the previous preference detection studies have been conducted based on a single modality. In this paper, we detect face preferences of humanoid robots based on electroencephalogram (EEG) signals and eye movement signals for single modality, canonical correlation analysis fusion modality, and bimodal deep autoencoder (BDAE) fusion modality, respectively. We validated the theory of frontal asymmetry by analyzing the preference patterns of EEG and found that participants had higher alpha wave energy for preference faces. In addition, hidden preferences extracted by EEG signals were better classified than preferences from participants' subjective feedback, and also, the classification performance of eye movement data was improved. Finally, experimental results showed that BDAE multimodal fusion using frontal alpha and beta power spectral densities and eye movement information as features performed best, with the highest average accuracy of 83.13% for the SVM and 71.09% for the KNN. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Electroencephalography

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Maize EfficientNet Fusion: Advancing Maize Disease Detection with MF-NET 25

Maize EfficientNet Fusion: Advancing Maize Disease Detection...

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25th International Conference on Digital Image Computing: Techniques and Applications, DICTA 2024

作者： Khalid, Fatima Hanif, Muhammad Ul Ain, Qurat Ghulam Ishaq Khan Institute of Engineering Sciences and Engineering Faculty of Computer Science and Engineering KPK Topi Pakistan Ghulam Ishaq Khan Institute of Engineering Sciences and Engineering Aerial Robotics and Vision Lab KPK Topi Pakistan Shifa Tameer-E-Millat University Department of Computing Islamabad Pakistan

ISBN: (纸本)9798350379037

Maize is a vital global crop, essential for food security but highly susceptible to diseases that threaten yield and quality. Traditional methods for detecting these diseases are computationally intensive and rely on high-quality images, limiting their practical use in diverse field conditions. This research addresses these challenges by proposing MF-Net, a novel model that leverages two EfficientNet-b0 architectures with ReLU and Swish activation functions. Our approach involves partially training Model R with frozen early layers using ReLU, and fully training Model S with Swish activation for enhanced optimization and robustness. We employ model concatenation and feature fusion techniques to create a lightweight yet powerful model, complemented by additional layers for improved feature extraction and regularization. Experimental results on the Corn Disease and Severity (CD&S) dataset are compelling: MF-Net achieves a remarkable 95.7% accuracy and 96% precision in disease classification, and 88.3% accuracy and 88.46% precision in severity level detection. These results highlight the model's effectiveness under challenging conditions such as cluttered backgrounds and variable lighting, significantly reducing computation time without compromising accuracy. Hence, MF-Net presents an innovative and efficient solution for maize disease detection and severity assessment, offering significant advancements for agricultural practices and crop management. © 2024 IEEE.

关键词： CD&S Dataset EffiecientNet-b0 Fused Truncated EfficientNet Maize Disease Maize Severity Level

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Global Solar Radiation Prediction using Empirical based Models 1

Global Solar Radiation Prediction using Empirical based Mode...

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1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022

作者： Sivakumar, Mahima Priya, S. Jeba Subathra, M.S.P Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India Karunya Institute of Technology and Sciences Department of Robotics Engineering Coimbatore India

ISBN: (纸本)9781665497107

Solar Radiation (SR) is crucial for the energy balance at the Earth's surface, evaporation, snow melting, plant water needs, and catchment hydrological regulation. In this regard, the major goal of this research is constructing a mathematical model or in other words empirical model to estimate the amount of SR upon a horizontal region in terms of latitude for four Indian cities. The cities considered for this work are NewDelhi, Chennai, Hyderabad and Coimbatore. Based on the input parameters, two categories of empirical models are developed namely, category 1 is sunshine duration (SD) based models and category 2 is air temperature (AT) based models. For performance evaluation, the metrics mean percentage error (MPE), mean bias error (MBE), mean absolute bias error (MABE), root mean square error (RMSE), mean absolute percentage error (MAPE) and coefficient of determination (R2). The results signify that both the category of empirical models have a promising capability in this field of research and can hence be an efficient option for solar forecasting. © 2022 IEEE.

关键词： Solar energy

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Benefits of Internet of Things (IoT) Applications in Health care - An Overview 1

Benefits of Internet of Things (IoT) Applications in Health ...

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Chaudhary, Preeti Yadav, Satya Prakash Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Nicosia Artificial Intelligence Engineering Dept. Mersin10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty OfEngineering Kyrenia Mersin10 Turkey Graphic Era Hill University Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

In a nutshell, the IoT refers to the idea of integrating high-tech technology in the form of "smart"gadgets and sensors into a single setting to gather data. There are still numerous areas in which machines cannot compete favorably with people, but data collection and analysis are undeniably two of their strongest points. The Internet of Things makes it possible to fully or partially automation data, it involves related activities, which is obviously very important for the healthcare industry. What exactly is the Internet connected medical things, and how exactly might it make a significant impact on the sector? By having to apply the concept of the internet of things (IoT) to the field of medicine, several significant advancements have become possible, including the ability to automatically control the thermostat of containers while transmitting inoculations and antibiotics, the accurate tracking of the ailments of a lot of illnesses without a need for additional meetings with a general practitioner, the correct and most useful use of meds, and a great deal more. All of this is realizable because of the capability of MedTech gadgets to carry out continuous monitoring system. The potential applications of internet of things technology in healthcare are very interesting. Let's review the ways in which this technology. © 2023 IEEE.

关键词： Medical applications

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Vision-Based Object Sorting in Dynamic Environments using YOLO for RoboCup ARM Challenge 2023 7

Vision-Based Object Sorting in Dynamic Environments using YO...

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7th IEEE Conference on Information and Communication Technology, CICT 2023

作者： Sahu, Yash Kumar Mittal, Radhika Patel, Deep Maiti, Chayan Sreekumar, M. Indian Institute of Information Technology Design and Manufacturing Centre for AI IoT and Robotics Department of Mechanical Engineering Kancheepuram Chennai India Indian Institute of Information Technology Design and Manufacturing Centre for AI IoT and Robotics Department of Computer Science Kancheepuram Chennai India

ISBN: (纸本)9798350305173

In the intersection of Artificial Intelligence (AI) and robotics, autonomous object manipulation has emerged as a pivotal research domain, finding applications in sectors as diverse as manufacturing and healthcare. While significant strides have been made in object identification, trajectory planning, and manipulation tasks, these advancements often fall short in real-world, dynamic settings, revealing a critical research gap in algorithmic adaptability and computational efficiency. This paper addresses the gap by applying YOLOv4, a state-of-the-art object detection AI algorithm, within the context of the RoboCup Autonomous Robot Manipulation (ARM) Challenge - a competitive platform designed to simulate real-world complexities in autonomous systems. The research objectives are twofold: firstly, the performance of YOLOv4 in object detection and classification under dynamically changing conditions is rigorously evaluated, employing varied training strategies in both simulated and real-world scenarios. Secondly, the robustness and adaptability of the algorithm in object manipulation tasks are scrutinized and facilitated by the real-world dynamics inherent to the competition. Empirical results demonstrate the algorithm's high accuracy, efficiency, and robustness in dynamic environments, substantiating its broader applicability in the development of autonomous systems. © 2023 IEEE.

关键词： Object detection

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Ball sition ature bedded Group Activity Recognition del for Team Sport Games 4

Ball sition ature bedded Group Activity Recognition del for ...

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4th International Conference on Machine Learning and Intelligent Systems, MLIS 2022

作者： Jamsrandorj, Ankhzaya Chao, Vanyi Oo, Yin May Mun, Kyung-Ryoul Kim, Jinwook Department of Human Computer Interface & Robotics Engineering University of Science & Technology Korea Republic of Department of Ai Robotics University of Science & Technology Korea Republic of Center for Artificial Intelligence Korea Institute of Science and Technology Korea Republic of

ISBN: (纸本)9781643683560

Most group activity recognition models focus mainly on spatio-temporal features from the players in sports games. Often they do not pay enough attention to the game object, which heavily affects not only individual action but also a group activity. We propose a new group activity recognition model for sports games that incorporates players' motion information and game object positional information. The proposed method uses a transformer encoder for temporal feature extraction and a 'simple' conventional convolutional neural network for extracting spatial features and fusing them with the relative ball position-embedded features. The experimental results show that our model achieved comparable results to state-of-the-art methods on the Volleyball dataset by using only one transformer encoder block and the ball position. © 2022 The authors and IOS Press.

关键词： Sports

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Nonlinear Model Predictive Control for Optimal Dose Administration in Radiotherapy 15th

Nonlinear Model Predictive Control for Optimal Dose Administ...

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15th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2024

作者： Araújo, João C. G. Guerreiro, Bruno J. Oliveira, Luis B. da Silva, Filipe Ferreira CTS-UNINOVA and LASI Department of Electrical and Computer Engineering NOVA School of Science and Technology Caparica2829-516 Portugal Institute for Systems and Robotics LARSyS Lisbon1049-001 Portugal CEFITEC Department of Physics NOVA School of Science and Technology Caparica2829-516 Portugal

ISBN: (纸本)9783031638503

This work discusses the nonlinear modeling of healthy and cancer cell population growth under the influence of radiotherapy, and proposes predictive control techniques to determine the optimal dose for tumor control, while sparing surrounding healthy tissue. Radiation effects are modelled by a linear-quadratic formalism, coupled with a novel population-specific delayed dose response. Numerical simulations of the open- and closed-loop system are conducted, and robustness against model uncertainty is studied. Results illustrate the controller’s performance when dealing with imperfect information and unexpected system behavior, and how it can be tuned to produce the desired treatment outcome. However, optimal operation is conditioned by a limited prediction horizon, as well as strict adherence to treatment schedules and dose restrictions. © IFIP International Federation for Information Processing 2024.

关键词： Nonlinear systems

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Design and Development of Semi-Steering and IoT Systems for Electric Mobility Systems 6

Design and Development of Semi-Steering and IoT Systems for ...

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6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Abdelmalek, Shady R. Retig, Ma Althea F. B. Ansari, Fakeha S. Gomaa, Mennatallah A. Alaaeldin, Amr Kaddah, Sahar S. Badr, Basem M. University of Genoa Faculty of Engineering Robotics Department Italy The British University in Dubai Faculty of Engineering and It Computer Science Department United Arab Emirates Mansoura University Renewable and Sustainable Energy Department Mansoura Egypt Mansoura University Faculty of Engineering Electrical Power Department Mansoura Egypt Mansoura University Faculty of Engineering Electrical Engineering Department Mansoura Egypt Lotus Power VancouverBC Canada

ISBN: (纸本)9798350378511

Connecting electric mobility (E-Mobility) systems with Internet of Things (IoT) technology is a crucial strategy for modern transportation and driving assistance systems. IoT and Advanced Driver Assistance Systems (ADAS) applications in the field are examined in this research. Different techniques are designed and developed for ADAS functionality, such as lane and object detection via image and video segmentations. Multiple lane detection models are developed and tested, each of which is then deployed on AWS (Amazon Web Services) cloud and optimized using OpenVINO to speed up inference. Furthermore, telemetry data from various embedded devices are transmitted to AWS IoT core and presented on an easy-to-use web application. This paper shows how deploying systems on cloud platforms like AWS improves scalability and operational efficiency. It also highlights how IoT and cloud technologies may improve the performance of E-Mobility systems and offers a strong foundation for further advancements in the ADAS area. © 2024 IEEE.

关键词： Web services

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Customized Touch UI Development for E-Cockpit in Automobile 3

Customized Touch UI Development for E-Cockpit in Automobile

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3rd International Conference on Smart Technologies, Communication and robotics, STCR 2023

作者： Sivaraj, D. Rathika, P.D. Jayasree, D. Dwarkesh Psg College of Technology Department of Electronics and Communication Engineering Coimbatore India Psg College of Technology Department of Robotics and Automation Engineering Coimbatore India Psg Polytechnic College Department of Electronics and Communication Engineering Coimbatore India Psg College of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350370867

In recent times, the automotive industry has made significant steps towards digitization by focusing on electronic cockpits (E-Cockpits) to enhance the driving experience, comfort and safety. The incorporation of Touch-Based User Interface (UI) technologies has played a crucial role in revolutionizing Driver-Vehicle interaction [10]. The project of E-Cockpit represents a concept that consolidates various internal car systems onto one unified digital platform, enabling seamless control and access to essential infotainment, safety features, and connectivity services [14]. For the realization of the complete potential of an E-Cockpit, it is important to develop an innovative and User-Friendly touch UI as this directly influences both user experience and safety concerns. © 2023 IEEE.

关键词： User interfaces

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