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IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Carter Green Martin Bouchard Rafik Goubran Rebecca Robillard Caitlin Higginson Elliott Lee Frank Knoefel School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada School of Electrical Engineering and Computer Science Bruyere Research Institute University of Ottawa Ottawa ON Canada Systems and Computer Engineering Carleton University Bruyere Research Institute Ottawa ON Canada School of Psychology University of Ottawa Sleep Research Unit U. of Ottawa Institute for Mental Health Research at the Royal Ottawa ON Canada Sleep Research Unit University of Ottawa Institute for Mental Health Research at the Royal Ottawa ON Canada Sleep Disorders Clinic Royal Ottawa Mental Health Center Sleep Research Unit U. of Ottawa Institute for Mental Health Research at the Royal Ottawa ON Canada Systems and Computer Engineering Carleton University Bruyere Research Institute Faculty of Medicine University of Ottawa Ottawa Canada

Polysomnography, the gold standard of sleep measurement, is a time-intensive, costly, and rather invasive procedure. Using under-bed pressure sensor arrays data simultaneously recorded with standard polysomnography, this study demonstrates that deep learning can be used to classify body position and differentiate sleep from wake. All measurements were performed in people with suspected sleep disorders referred for clinical assessments at a sleep laboratory. To perform the classification tasks, we used supervised learning and temporal convolution networks. Performance was assessed with leave-one-out cross validation on 84 participants for body position classification and 70 participants for sleep-wake classification. Results demonstrate that a pressure sensor array placed under the mattress with less than 100 sensors can outperform previous sleep-wake detection methods and is competitive with previous methods for body position classification. Our pressure sensor arrays differ from the mats used in previous work as they use significantly less sensors and are located under the mattress, making them less obtrusive. This tool has great potential as a cost-efficient mean of assessing sleep while reducing patient burden and the workload of specialized staff.

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Communication-based and Communication-less approaches for Robust Cooperative Planning in Construction with a Team of UAVs

Communication-based and Communication-less approaches for Ro...

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International Conference on Unmanned Aircraft systems (ICUAS)

作者： Elena Umili Marco Tognon Dario Sanalitro Giuseppe Oriolo Antonio Franchi Sapienza University of Rome Rome Italy Autonomous Systems Lab ETH Zurich Zürich Switzerland LAAS-CNRS Université de Toulouse CNRS Toulouse France Robotics and Mechatronics lab Faculty of Electrical Engineering Mathematics & Computer Science University of Twente Enschede The Netherlands

ISBN: (数字)9781728142784

ISBN: (纸本)9781728142791

In this paper, we analyze the coordination problem of groups of aerial robots for assembly applications. With the enhancement of aerial physical interaction, construction applications are becoming more and more popular. In this domain, the multi-robot solution is very interesting to reduce the execution time. However, new methods to coordinate teams of aerial robots for the construction of complex structures are required. In this work, we propose an assembly planner that considers both assembly and geometric constraints imposed by the particular desired structure and employed robots, respectively. An efficient graph representation of the task dependencies is employed. Based on this framework, we design two assembly planning algorithms that are robust to robot failures. The first is centralized and communication-based. The second is distributed and communication-less. The latter is a solution for scenarios in which the communication network is not reliable. Both methods are validated by numerical simulations based on the assembly scenario of Challenge 2 of the robotic competition MBZIRC2020.

关键词： Task analysis Robot kinematics Robotic assembly Planning Resource management Robustness

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CSI-EPT: A novel contrast source approach to MRI based electric properties tomography and patient-specific SAR

CSI-EPT: A novel contrast source approach to MRI based elect...

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International Conference on Electromagnetics in Advanced Applications (ICEAA)

作者： E. Balidemaj J. Trinks C. A. T. van den Berg A. J. Nederveen A. L. van Lier L. J. A. Stalpers J. Crezee R. F. Remis Radiotherapy and Radiology Departments University of Amsterdam Amsterdam Netherlands Radiotherapy Department Utrecht University Utrecht Netherlands Universiteit van Amsterdam Amsterdam Noord-Holland NL Circuits and Systems Group Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands

In this paper, we present a novel method (Contrast Source Inversion - Electric Properties Tomography or CSI-EPT) to dielectric imaging of biological tissue using so-called B 1 + data measurable by Magnetic Resonance Imaging (MRI) systems. Integral representations for the electromagnetic field quantities are taken as a starting point and we follow an iterative contrast source inversion approach to retrieve the dielectric tissue parameters from measured field data. Numerical results illustrate the performance of the method and show that reliable results are produced near tissue boundaries as opposed to the currently used methods. Fine structures can be resolved as well and since CSI-EPT reconstructs the electric field strength inside a scanning region of interest, it is also a promising candidate to determine the patient-specific SAR deposition during an MRI scan.

关键词： Magnetic resonance imaging Equations Conductivity Permittivity Mathematical model Biomedical imaging Electromagnetics

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Determining liquid properties by extraordinary acoustic transmission through phononic crystals

Determining liquid properties by extraordinary acoustic tran...

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IEEE SENSORS

作者： R. Lucklum M. Zubtsov M. Ke A. Oseev U. Hempel B. Henning Institute of Micro and Sensor Systems (IMOS) Tto-von-Guericke-University Magdeburg Germany Department of Physics Wuhan University of China Wuhan China Institute of Automation and Communication (ifak) Magdeburg Germany Faculty of Electrical Engineering Computer Science and Mathematics University of Paderborn Paderborn Germany

ISBN: (纸本)9781424492909

This contribution shows how a resonance-induced extraordinary acoustic transmission through a phononic crystal structure can be used as sensor for liquid properties. The phononic crystal consists of a metal plate with a periodic array of holes. Ultrasound propagates in a way that the incidence direction of sound is perpendicular to the plate. A characteristic transmission peak has been found to strongly depend on liquid sound velocity. The respective peak maximum frequency serves as measure for liquid composition. Numerical calculations based on FDTD and FEA reveal more insides to the propagation characteristics, in particular the presence of specific plate modes. Experimental investigations using a laser vibrometer and the Schlieren method support the theoretical findings.

关键词： Acoustics Photonic crystals Frequency measurement Laser beams Crystals Time domain analysis Lattices

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A New THL model for high accuracy of predicted journal surface temperature

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Toraibarojisuto/Journal of Japanese Society of Tribologists 2018年第5期63卷 360-367页

作者： Hatakenaka, Kiyoshi Baba, Yoshitaka Kämeyama, Yuki Department of Mechanical Information Science and Technology Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka-shi Fukuoka820-8502 Japan Technical Development Department Development Center Machinery Business KOBE STEEL Ltd. 3-1 Shinhama 2-chome Arai-cho Takasago-shi Hyogo676-8670 Japan

A thermo-hydrodynamic lubrication (THL) theory is applied to journal bearings that support large-sized high-speed rotary machineries and it is confirmed that the maximum pad surface temperature under operation is below an allowable limit value. The temperature predicted by the traditional THL model is in good agreement with the measurement. However, the predicted journal surface temperature is not comparable with the measurement. In the present paper, it is firstly shown that the amount of heat, which is generated by the shear flow in the oil film and is discharged out of the film, is evaluated appropriately in the film near the pad surface while it is evaluated excessively in the film near the journal surface. Secondly, a new THL model is proposed that the oil film temperature near the pad surface and the temperature near the journal surface are obtained independently, that is, the conventional energy equation for the oil film is solved for the former temperature while the equation described in the relative coordinate system with the journal surface as the reference one is used for the latter temperature. Lastly, it is shown that the THL model can predict the journal surface temperature comparable with the measurement without deteriorating the accuracy of the predicted maximum pad surface temperature. © 2018 Japanese Society of Tribologists. All rights reserved.

关键词： Surface temperature

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A Sliding Mode Control for Slip Ratio of Electric Vehicle

A Sliding Mode Control for Slip Ratio of Electric Vehicle

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Society of Instrument and Control Engineers Annual Conference

作者： Shaobo Li Ko Nakamura Tohru Kawabe Koichi Morikawa Department of Computer Science University of Tsukuba Division of Information Engineering Faculty of Engineering Information and Systems University of Tsukuba Division of Chassis System Bosch Corporation

ISBN: (纸本)9781467322591

This paper presents a slip ratio controller using sliding mode control for electric vehicle with parameter variations, which is important in obtaining desired vehicle motion in acceleration. A robust sliding mode controller is designed to obtain the maximum driving force by maintaining the value of slip ratio at a reference value. The simulations for one wheel model of vehicle under variations in mass of vehicle and road conditions are performed and analyzed to show the effectiveness of the proposed controller.

关键词： Sliding Mode Control Slip Ratio Electric Vehicle Robustness Energy Saving

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Development of a Real-Space Sharing Edutainment System based on Communication Support with Make-Believe Play

Development of a Real-Space Sharing Edutainment System based...

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SICE Annual Conference

作者： Masaru Yamane Michiya Yamamoto Tomio Watanabe Graduate School of Science and Technology Kwansei Gakuin University School of Science and Technology Kwansei Gakuin University Faculty of Computer Science and Systems Engineering Okayama Prefectural University

ISBN: (纸本)9784907764388

Various e-learning systems that support remote education have been developed utilizing information technology. However, it is still not easy to communicate smoothly and to evaluate how well users of such systems have understood. We focus on communication support with make-believe play and propose a real-space sharing edutainment system that allows its users to enjoy make-believe play. We develop a prototype of the system in which we introduce distinctive CG characters and communication support functions to enhance user communication through a virtual environment. Finally, we confirm the effectiveness of the system through an evaluation experiment.

关键词： Embodied communication Embodied interaction Edutainment

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An Enhanced Aquila-Based Resource Allocation for Efficient Indoor IoT Visible Light Communication

An Enhanced Aquila-Based Resource Allocation for Efficient I...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Selma Yahia Yassine Meraihi Sylia Mekhmoukh Taleb Seyedali Mirjalili Amar Ramdane-Cherif Tu Dac Ho Hossien B. Eldeeb Sami Muhaidat LIST Laboratory University of M’Hamed Bougara Boumerdes Boumerdes Algeria Centre for Artificial Intelligence Research and Optimisation Torrens University Australia Brisbane Australia LISV Laboratory University of Versailles St-Quentin-en-Yvelines Velizy France Department of Electrical Engineering Faculty of Engineering Science and Technology UiT Arctic University of Norway Electrical Engineering Computer Science Center of Cyber-Physical Systems Khalifa University UAE

Visible light communication (VLC) is a rapidly growing wireless communication technology for the Internet of Things (IoT) that offers high data rates and low latency, making it ideal for massive connectivity. Efficient resource allocation is essential in VLC networks to minimize inter-symbol and cochannel interferences, which can greatly improve network performance and user satisfaction. This paper focuses on an indoor IoT-based VLC system that utilizes photodetectors (PDs) on users’ cell phones as receivers, with the goal of maximizing system performances and reducing power consumption by selectively activating some PDs while deactivating others. However, this objective presents a challenge due to the inherent non-convex nature of the multi-objective optimization problem, which cannot be solved by analytical means. To address this, we propose an enhanced Aquila optimization (EAO) scheme that improves upon the Aquila Optimizer (AO) by incorporating a fitness distance balance (FDB) function. We evaluate our proposed EAO in various scenarios under different settings, considering both capacity and fairness metrics. Through simulations, we demonstrate the effectiveness of our approach and its superiority over classical algorithms such as Aquila Optimizer (AO), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) in finding the optimal solution. Our results confirm that the proposed EAO algorithm can efficiently optimize the system capacity and ensure fairness among all users, providing a promising solution for indoor VLC systems.

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Attribute Selection Using Information Gain and Naïve Bayes for Traffic Classification

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Journal of Physics: Conference Series 2019年第1期1196卷

作者： Ahmad Fali Oklilas Tasmi Sri Desy Siswanti Mira Afrina Herri Setiawan Department of Computer Engineering Faculty of Computer Science Universitas Sriwijaya Indonesia Computer Engineering Computer Science Department Indo Global Mandiri University Department of Information Systems Faculty of Computer Science Universitas Sriwijaya Indonesia Engineering Informatics Computer Science Department Indo Global Mandiri University

This paper presents the value of good attributes in carrying out the package classification process Furthermore, attribute selection results can be of value in determining one type of data packet traffic. In obtaining the results (data) this study uses several stages of Data Capture, Feature Extraction and Feature Selection, but in this study only focuses on the process of feature selection using the gain and Entropy Information and Naïve Bayes algorithm. The testing process by dividing raw data into parts is 70 per cent for Training data and 30 per cent for testing data. The total data used is 6632, so for the training data obtained is 4642, while the data for testing is 1990. The results obtained are for the https data package type is 9 attributes, while for the HTTP data is 10 attributes. For further research can be added using another classification method as a comparison of data.

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Comparative Analysis of Machine Learning Models in Online Payment Fraud Prediction

Comparative Analysis of Machine Learning Models in Online Pa...

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Intelligent Methods, systems, and Applications (IMSA)

作者： Ahmed Younes Shdefat Mennatallah Mohamed Shahd Khaled Farrah Hany Hanaa Fathi Diaa Salama AbdElminaam College of Engineering and Technology American University of the Middle East Egaila Kuwait Faculty of Computer Science Misr International University Cairo Egypt Applied Science Research Center Applied Science Private University Amman Jordan Jadara Research Center Jadara University Irbid Jordan Information Systems department Faculty of Computers and Artificial Intelligence Benha University Benha Egypt MEU Research Unit Middle East University Amman Jordan

ISBN: (数字)9798350362633

ISBN: (纸本)9798350362640

With the substantial increase in Cybercrime, the pressing need for effective solutions in the light of the rising amount of corporate financial losses, is a concern f or many researchers. The widespread adoption of ecommerce and diverse online payment methods has contributed to the surge in a major form of cybercrime—online payment fraud. This further highlights the critical need to control and reduce the widespread danger of fraudulent behaviour on the internet. However, predicting online payment fraud is difficult as fraudsters are constantly changing their tactics, transactions happen quickly and in large volumes, transactions involve different regions and countries, stolen data is often used and other factors. Our goal is to improve the accuracy and usability of online payment fraud prediction through the use of machine learning. A well-established and widely recognized dataset specifically designed for studying online payment fraud was used. The six proposed algorithms trained and tested were (SVM), Decision Tree, Naïve Bayes, Random Forest, (KNN) and Logistic Regression. After rigorous testing, Decision Tree presented the highest accuracy in performance of 98.58%. However, as ten-fold cross validation was implemented on the dataset, Decision Tree suffered a loss while Random Forest had an increase in accuracy making it the best model with accuracy of 98.47%. As shown in this paper, machine learning has proven to be a reliable and ever-evolving approach for the prediction of Online Payment Fraud and results can be further improved in collaboration with financial and cybercrime specialists.

关键词： Support vector machines Accuracy Machine learning algorithms Predictive models Prediction algorithms Fraud Bayes methods

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