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2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Gökhan Ince Kazuhiro Nakadai Tobias Rodemann Yuji Hasegawa Hiroshi Tsujino Jun-ichi Imura Department of Mechanical and Environmental Informatics Graduate School of Information Science and Engineering Tokyo Institute of Technology Meguro Tokyo Japan Honda Research Institute Japan Company Limited Wako Saitama Japan Honda Research Institute Europe GmbH Offenbach Germany

While a robot is moving, the joints inevitably generate noise due to its motors, i.e. ego-motion noise. This problem is very crucial, especially in humanoid robots, because it tends to have a lot of joints and the motors are located closer to the microphones than the sound sources. In this work, we investigate methods for the prediction and suppression of the ego-motion noise. In the first part, we analyze the performance of different noise subtraction strategies, assuming that the noise prediction problem has been solved. In the second part, we present some results for a noise prediction scheme based on the current robot joint status. Performance is evaluated for a number of criteria, including Automatic Speech Recognition (ASR). We demonstrate that our method improves recognition performance during ego-motion considerably.

关键词： Acoustic noise Noise cancellation Noise generators Automatic speech recognition Microphone arrays Intelligent robots Micromotors Databases Neural networks Robotics and automation

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SAR analysis of resonant cavity applicator using dielectric bolus with anatomical human model by finite element method

SAR analysis of resonant cavity applicator using dielectric ...

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International Symposium on Medical Information & Communication technology (ISMICT)

作者： Yuya Iseki Jiro Arakawa Kazuki Watanabe Kazuo Kato Yasuhiro Shindo Mitsunori Kubo Hideaki Takahashl Takeo Uzukas Graduate School of Science and Technology Meiji University Kanagawa Japan Department of Mechanical Engineering Informatics Meiji University Kanagawa Japan Future Creation Laboratory Olympus Company Limited Tokyo Japan The Niigata Cancer Center Section of Neurosurgery Niigata Japan

In this study, we propose a new heating method using a resonant cavity applicator to control the heated area using a dielectric bolus. The dielectric bolus is filled with a dielectric material such as water and is attached to a human head inside the cavity. In this paper, first, the proposed heating method using the dielectric bolus was described. Second, a 3-D anatomical human head model, which was constructed from 2-D MRI and X-ray CT images, was presented. Finally, from the results of specific absorption rate (SAR) distributions using 3-D FEM, it was shown that the heated area inside a human brain could be controlled by changing the electromagnetic field distribution. From these results, it was found that the proposed method for controlling the heated area was useful for effective hyperthermia treatments.

关键词： Dielectrics Heating Cavity resonators Hyperthermia Tumors Applicators Brain modeling

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Pothole Detection Based on Disparity Transformation and Road Surface Modeling

arXiv

引用

arXiv 2019年

作者： Fan, Rui Ozgunalp, Umar Hosking, Brett Liu, Ming Pitas, Ioannis The Robotics Institute Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Hong Kong The Electrical and Electronic Engineering Near East University Nicosia Cyprus The National Oceanography Centre Southampton United Kingdom The School of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

Pothole detection is one of the most important tasks for road maintenance. Computer vision approaches are generally based on either 2D road image analysis or 3D road surface modeling. However, these two categories are always used independently. Furthermore, the pothole detection accuracy is still far from satisfactory. Therefore, in this paper, we present a robust pothole detection algorithm that is both accurate and computationally efficient. A dense disparity map is first transformed to better distinguish between damaged and undamaged road areas. To achieve greater disparity transformation efficiency, golden section search and dynamic programming are utilized to estimate the transformation parameters. Otsu’s thresholding method is then used to extract potential undamaged road areas from the transformed disparity map. The disparities in the extracted areas are modeled by a quadratic surface using least squares fitting. To improve disparity map modeling robustness, the surface normal is also integrated into the surface modeling process. Furthermore, random sample consensus is utilized to reduce the effects caused by outliers. By comparing the difference between the actual and modeled disparity maps, the potholes can be detected accurately. Finally, the point clouds of the detected potholes are extracted from the reconstructed 3D road surface. The experimental results show that the successful detection accuracy of the proposed system is around 98.7% and the overall pixel-level accuracy is approximately 99.6%. Copyright © 2019, The Authors. All rights reserved.

关键词： Dynamic programming

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On multichromatic numbers of widely colorable graphs

arXiv

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arXiv 2021年

作者： Gujgiczer, Anna Simonyi, Gábor Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Hungary Alfréd Rényi Institute of Mathematics Budapest Hungary MTA-BME Lendület Arithmetic Combinatorics Research Group Hungary

A coloring is called s-wide if no walk of length 2s − 1 connects vertices of the same color. A graph is s-widely colorable with t colors if and only if it admits a homomorphism into a universal graph W (s, t). Tardif observed that the value of the rth multichromatic number χr(W (s, t)) of these graphs is at least t + 2(r − 1) and equality holds for r = s = 2. He asked whether there is equality also for r = s = 3. We show that χs(W (s, t)) = t+2(s−1) for all s thereby answering Tardif's question. We observe that for large r (with respect to s and t fixed) we cannot have equality and that for s fixed and t going to infinity the fractional chromatic number of W (s, t) also tends to infinity. The latter is a simple consequence of another result of Tardif on the fractional chromatic number of generalized Mycielski *** Codes 05C15 (Primary) 05C60, 05C72 (Secondary) Copyright © 2021, The Authors. All rights reserved.

关键词： Graphic methods

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Smart Healthcare System for Severity Prediction and Critical Tasks Management of COVID-19 Patients in IoT-Fog Computing Environments

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Computational Intelligence and Neuroscience 2022年第0期2022卷 5012962页

作者： Hameed Abdulkareem, Karrar Awad Mutlag, Ammar Musa Dinar, Ahmed Frnda, Jaroslav Abed Mohammed, Mazin Hasan Zayr, Fawzi Lakhan, Abdullah Kadry, Seifedine Ali Khattak, Hasan Nedoma, Jan College of Agriculture Al-Muthanna University Samawah66001 Iraq College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Ministry of Education General Directorate of Curricula Pure Science Department Baghdad Iraq Engineering Department University of Technology- Iraq Baghdad Iraq Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and Communication University of Žilina Žilina Slovakia Department of Telecommunications Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Poruba Ostrava Czech Republic College of Computer Science and Information Technology University of Anbar 11 Ramadi Anbar Iraq Department of Biochemistry College of Medicine University of Wasit Wasit Iraq Department of Computer Science and Artificial Intelligence Wenzhou University Wenzhou325035 China Noroff University College Kristiansand Norway Islamabad44500 Pakistan

COVID-19 has depleted healthcare systems around the world. Extreme conditions must be defined as soon as possible so that services and treatment can be deployed and intensified. Many biomarkers are being investigated in order to track the patient's condition. Unfortunately, this may interfere with the symptoms of other diseases, making it more difficult for a specialist to diagnose or predict the severity level of the case. This research develops a Smart Healthcare System for Severity Prediction and Critical Tasks Management (SHSSP-CTM) for COVID-19 patients. On the one hand, a machine learning (ML) model is projected to predict the severity of COVID-19 disease. On the other hand, a multi-agent system is proposed to prioritize patients according to the seriousness of the COVID-19 condition and then provide complete network management from the edge to the cloud. Clinical data, including Internet of Medical Things (IoMT) sensors and Electronic Health Record (EHR) data of 78 patients from one hospital in the Wasit Governorate, Iraq, were used in this study. Different data sources are fused to generate new feature pattern. Also, data mining techniques such as normalization and feature selection are applied. Two models, specifically logistic regression (LR) and random forest (RF), are used as baseline severity predictive models. A multi-agent algorithm (MAA), consisting of a personal agent (PA) and fog node agent (FNA), is used to control the prioritization process of COVID-19 patients. The highest prediction result is achieved based on data fusion and selected features, where all examined classifiers observe a significant increase in accuracy. Furthermore, compared with state-of-the-art methods, the RF model showed a high and balanced prediction performance with 86% accuracy, 85.7% F-score, 87.2% precision, and 86% recall. In addition, as compared to the cloud, the MAA showed very significant performance where the resource usage was 66% in the proposed model and 34% in

关键词： COVID-19

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Heating analysis of resonant cavity applicator with blood perfusion

Heating analysis of resonant cavity applicator with blood pe...

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International Symposium on Medical Information & Communication technology (ISMICT)

作者： Liro Arakawa Junichi Nagasawa Yasuhiro Shindo Kazuo Kato Mitsunori Kubo Takeo Uzuka Hideaki Takahashi Graduate school of Science and Technology Meiji University Kanagawa Japan Department of Mechanical Engineering Informatics Meiji University Kanagawa Japan The Future Creation Laboratory Olympus Company Limited Tokyo Japan Section of Neurosurgery Niigata Cancer Center Niigata Japan

This paper describes the heating properties of a resonant cavity applicator for heating brain tumors, calculated by a finite element method (FEM) with blood perfusion. We have already proposed the resonant cavity applicator for treating brain tumors and checked the effectiveness of the applicator experimentally, using a prototype heating system with an agar phantom. In this paper, first, we constructed a simple model with blood vessels for calculating temperature distributions using the FEM. In the simple model, a single thick blood vessel branches into two narrow blood vessels. Second, calculated temperature distributions were presented by solving the heat-flow equation, respectively. Also, a comparison of the temperature distributions when the flow conditions were changed were discussed. From these results, it was found that the cooling effects of blood perfusion appear at the heated area approximately 2 cm away from the blood vessels.

关键词： Blood flow Mathematical model Temperature distribution Equations Heating Blood

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DataLoc+: A data augmentation technique for machine learning in room-level indoor localization

arXiv

引用

arXiv 2021年

作者： Hilal, Amr Arai, Ismail El-Tawab, Samy Informatics Lab Virginia Tech BlacksburgVA United States Information Initiative Center Nara Institute of Science and Technology Ikoma Nara Japan College of Integrated Science and Engineering James Madison University HarrisonburgVA United States The Department of Computer and Systems Engineering Alexandria University Egypt James Madison University VA United States

Indoor localization has been a hot area of research over the past two decades. Since its advent, it has been steadily utilizing the emerging technologies to improve accuracy, and machine learning has been at the heart of that. Machine learning has been increasingly used in fingerprint-based indoor localization to replace or emulate the radio map that is used to predict locations given a location signature. The prediction quality of a machine learning model primarily depends on how well the model was trained, which relies on the amount and quality of data used to train it. Data augmentation has been used to improve quality of the trained models by synthetically producing more training data, and several approaches were used in the literature that tackles the problem of lack of training data from different angles. In this paper, we propose DataLoc+, a data augmentation technique for room-level indoor localization that combines different approaches in a simple algorithm. We evaluate the technique by comparing it to the typical direct snapshot approach using data collected from a field experiment conducted in a hospital. Our evaluation shows that the model trained using the proposed technique achieves higher accuracy. We also show that the technique adapts to larger problems using a limited dataset while maintaining high accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Indoor positioning systems

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A hybrid framework for ego noise cancellation of a robot

A hybrid framework for ego noise cancellation of a robot

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IEEE International Conference on Robotics and Automation (ICRA)

Noise generated due to the motion of a robot is not desired, because it deteriorates the quality and intelligibility of the sounds recorded by robot-embedded microphones. It must be reduced or cancelled to achieve automatic speech recognition with a high performance. In this work, we divide ego-motion noise problem into three subdomains of arm, leg and head motion noise, depending on their complexity and intensity levels. We investigate methods that make use of single-channel and multi-channel processing in order to suppress ego noise separately. For this purpose, a framework consisting of a microphone-array-based geometric source separation, a consequent post filtering process and a parallel module for template subtraction is used. Furthermore, a control mechanism is proposed, which is based on signal-to-noise ratio and instantaneously detected motions, to switch to the most suitable method to deal with the current type of noise. We evaluate the proposed techniques on a humanoid robot using automatic speech recognition (ASR). The preliminary results of isolated word recognition show the effectiveness of our methods by increasing the word correct rates up to 50% compared to the single channel recognition in arm and leg motion noises and up to 25% in very strong head motion noises.

关键词： Noise cancellation Robots Acoustic noise Robotics and automation Automatic speech recognition Noise level Leg Signal to noise ratio Switches Noise generators

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A Bibliometric Analysis and Research Landscape of Artificial Intelligence in Education

A Bibliometric Analysis and Research Landscape of Artificial...

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IEEE International Conference on Control System, Computing and engineering (ICCSCE)

作者： Samuel-Soma M. Ajibade Bayan Issa Muhammed Basheer Jasser Farrukh Hassan Ghassan Saleh ALDharhani Ismail Ahmed Al-Qasem Al-Hadi Kayode Akinlekan Akintoye Almighty Cortezo Tabuena Department of Computing and Information Systems School of Engineering and Technology Sunway University No. 5 Jalan Universiti Bandar Sunway Selangor Darul Ehsan Malaysia Department of Computer Engineering Istanbul Ticaret University Istanbul Turkiye Faculty of Informatics Engineering University of Aleppo Syria Institute of Computer Science and Digital Innovation UCSI University Kuala Lumpur Malaysia Faculty of Information Science and Technology UKM University Bangi Selangor Malaysia Department of Computer Science The Federal Polytechnic Ado Ekiti Ekiti State Nigeria College of Arts and Sciences University of the City of Valenzuela Philippines

ISBN: (数字)9798350364507

ISBN: (纸本)9798350364514

This study examines the academic field of Artificial Intelligence in Education (AI-ED) by examining the publications and indexed documents in Scopus from 2010 to 2023. Consequently, we examined the publishing trends, exemplary articles, and the most engaged participants and funding institutions in the domain of AI-ED research. A bibliometric analysis was performed to examine the network of co-authorships, keywords, and citations in the domain of AIED research. The Scopus search resulted in the discovery of 10,474 published documents on AI-ED. Additionally, trends analysis indicated a significant increase of over 3,000% in publications between 2010 and 2023. Conference papers are the most often utilized document type, including 6757 publications or $64.5 \%$ of the overall amount. The ACM International Conference Proceeding Series is the primary source for published materials, accounting for 675 publications or $6.44 \%$ of the total publications on the topic. The most prolific researchers in the field of AI-ED are Breazeal, C and Chai C.S, each having published 18 documents. Additionally, the two institutions that have produced the highest number of published documents are Carnegie Mellon University (CMU) and the University of NC State University (NCSU). The output of the affiliations active in the topic is primarily attributed to the funders, specifically the National science Foundation, which is the leading funding institution based in the United States and has contributed to 354 publications. An analysis of keyword co-occurrence revealed 6 main study areas that cover the essential tools, theories, methodologies, and socioeconomic and financial aspects of artificial intelligence in education (AIED). Future research in the field of artificial intelligence in education will focus on employing sophisticated deep learning, machine learning, and neural network algorithms to precisely predict students’ learning patterns.

关键词： Deep learning Education Bibliometrics Neural networks Market research Prediction algorithms Stakeholders Artificial intelligence Socioeconomics Meteorology

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The Implementation of Innovation in Educational technology to Improve the Quality of Website Learning in Industrial Revolution Era 4.0 Using Waterfall Method 1

The Implementation of Innovation in Educational Technology t...

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2018 1st Workshop on engineering, Education, Applied sciences, and technology, WEAST 2018

作者： Sudrajat, Dadang Achdisty, Mega Kurniasih, Nuning Roslina Parwito Mulyati, Sri Purnomo, Agung Sallu, Sulfikar Informatics Engineering STMIK IKMI Cirebon Jawa Barat Indonesia Education Technology Institut Pendidikan Indonesia Garut Jawa Barat Indonesia Faculty of Communication Science Library and Information Science Program Universitas Padjajaran Jarinangor Bandung Jawa Barat Indonesia English Language Education Universitas Sembilanbelas November Kolaka Sulawesi Tenggara Indonesia Department Agrotechnlogy Universitas Ratu Samban Bengkulu Indonesia Indonesian Language Education FKIP Universitas Panca Sakti Tegal Indonesia Enterpreneurship Program Bina Nusantara Institute of Creative Technoogy Malang Jawa Timur Indonesia Faculty of Information Technology Universitas Sembilanbelas November Kolaka Sulawesi Tenggara Indonesia

Implementation of learning technology is one of the necessary ways to demonstrate the competence of qualified graduates. This research aim to make model of website Implementation to improve student quality. The Current Study Provided only provides the existing General Implementation. The Participants of this study were lecturers, undergraduate and postgraduate students and education practitioners throughout Indonesia using online form. Data collection Methods used were direct interview, online survey and needs analysis using waterfall method. The results show that the implementation of existing learning does not lead to the needs in the industry era 4.0 almost no change. This research produces a complete learning implementation innovation as required by the Policy Makers. © Published under licence by IOP Publishing Ltd.

关键词： Websites

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