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A Survey of Motion and Task Planning Techniques for Unmanned Multicopter Systems

无人系统（英文） 2021年第2期9卷 165-198页

作者： Menglu Lan Shupeng Lai Tong H.Lee Ben M.Chen Graduate School for Integrative Science and Engineering National University of SingaporeSingapore Department of Electrical and Computer Engineering National University of SingaporeSingapore Department of Electrical and Computer Engineering National University of SingaporeSingapore Department of Mechanical and Automation E Chinese University of Hong Kong ShatinN.T.China

Unmanned aerial systems provide many applications with the ability to perform flying tasks autonomously,and hence have received significant research and commercial attention in the past *** of the most popular unmanned aerial platforms for such tasks is the small-scale rotorcraft with multiple rotors,commonly known as *** order for these platforms to perform fully autonomous missions and tasks,they require a sophisticated low-level flight control system that is integrated with advanced task and motion planning modules,which combine together to form the complete unmanned aerial system(UAS).In this paper,the planning module of unmanned multicopter systems is discussed in detail,and a comprehensive survey on techniques for both motion and task planning reported in literature and by the Unmanned Systems Research Group at the National University of Singapore is presented.

关键词： Task planning motion planning rotorcraft

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A Preliminary Study on the Collaborative Playing Piano Automatic with Deep Learning

A Preliminary Study on the Collaborative Playing Piano Autom...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Varinya Phanichraksaphong Karuna Yampray Department of Electronic Engineering International Graduate Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan College of Creative Design and Entertainment Technology Dhurakij Pundit University Bangkok Thailand

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

A great number of deep learning-based models have been recently proposed for automatic piano classification. In this paper, we describe our contribution to the challenge of automatic piano classification when the performer performs at the concert or stage. Among these models in deep learning, we use init-1D-WaveNet and init-2D-MLNet for comparison the accuracy in the piano beginning level of the Christmas song (Jingle bells). Our experimental results show that the assessment using the init-2D-MLNet still achieve high accuracy of 87.5%.

关键词： Deep learning Accuracy Instruments Collaboration Consumer electronics

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A novel random finite element model for holistically modeling of the frost effects on soils and cold region pavements

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Journal of Infrastructure Preservation and Resilience 2022年第1期3卷 1-14页

作者： Dong, Shaoyang Jiang, Yusheng Yu, Xiong Graduate Research Assistant Department of Civil and Environmental Engineering Case Western Reserve University ClevelandOH United States Opal J. and Richard A. Vanderhoof Professor and Chair Department of Civil and Environmental Engineering Professor of Electrical Engineering and Computer Science Case Western Reserve University ClevelandOH United States

This paper describes the development of a random finite element model (RFEM) that allows holistic simulation of frozen soil behaviors, including the effects of phase transition and the consequent internal stress and volume changes. The performance of the model is firstly validated with laboratory experiments. The model is implemented to simulate the effects of frost action on pavement. The coupled thermal-mechanical actions including the mechanical responses of subgrade soils subjected to freezing temperature and its effects on the pavement structure are analyzed. The results show that the frost action and expansion of ice lenses change the interaction modes between pavement layers. This leads to increase of stress and deformation in the pavement layer. Methods to mitigate the effects of frost heave are analyzed with this model. The simulation results indicate that the detrimental effects of frost heave on the pavement structure can be mitigated by increasing the thickness of base layer, use of thermal insulation layer or improve drainage in the subgrade layer. The RFEM combines the advantages of discrete element model (DEM) in holistically describing the microstructure effects and in the finite element model (FEM) in terms of computational efficiency. This allows to focus research on understanding the behaviors of individual soils phase and their interfacial interactions. © The Author(s) 2022.

关键词： Pavements

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Evaluating a frailty education program implemented through barbershops/salons in Japan: A preliminary study

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SN Social Sciences 2022年第5期2卷 1-13页

作者： Makabe, Sachiko Fujiwara, Katsuya Kume, Yu Kaga, Midori Munemura, Nobuko Kemuyama, Shoko Mitobe, Kazutaka Department of Nursing Akita University Graduate School of Health Sciences 1-1-1 Hondo Akita 010-8543 Japan Department of Mathematical Science and Electrical-Electronic-Computer Engineering Akita University Graduate School of Engineering Science Akita Japan Department of Occupational Therapy Akita University Graduate School of Health Sciences Akita Japan

Although frailty has detrimental physical and psychological effects on elderly people, it is potentially reversible. In this study, we aim to evaluate the effectiveness of a pilot frailty education program implemented through barbershops/salons in Japan. In January 2018, we selected five barbershops/salons in Japan where customers were educated on frailty, which was classified as “normal,” “prefrail,” and “frail.” We developed a web-based assessment tool to reduce the workload for barbers/stylists. Participants included 45 customers (82% women), with a median (interquartile range) age of 53.0 (47.5–57.5) years, and a mean ± SD BMI of 22.3 ± 2.7. Frailty scores indicated that 35% of participants were normal, 58% were prefrail, and 7% were frail. Frailty status scores reflected no significant differences after the intervention. Customers classified as frail were advised to visit the regional comprehensive support center for further professional frailty assessment. Participants, especially those aged over 65 years, found the web-based assessment difficult to use. In conclusion, a frailty education program implemented through barbershops/salons is possible because barbers/stylists can provide information on and assessment of frailty. Females and highly educated customers are more likely to be interested in participating. Nevertheless, a simple intervention is essential to expand the program nationwide. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.

关键词： Barbershop Frailty Health educator Salon Super-aging society

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Experimental Study of a MISO-VLC using two LED Luminaires

Experimental Study of a MISO-VLC using two LED Luminaires

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IEEE/LEOS International Conference on Optical MEMS

作者： David Esteban Farfán-Guillén Luis Carlos Vieira Alexandre De Almeida Prado Pohl Graduate Program in Electrical and Computer Engineering (CPGEI) Universidade TecnolÓgica Federal do Paraná (UTFPR) Curitiba Brazil

In this work, the multiple-input, single-output (MISO) technique is implemented with OFDM modulation and the variation of the cyclic prefix (CP) is used to optimize the performance of an indoor VLC link, while maintaining the lighting conditions within the recommended levels (300–500 lux). Results show that by increasing the number of luminaires and by selecting the appropriate value of the OFDM cyclic prefix, the system's bit error rate (BER ≤ 10– 3 ) is improved.

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Utilizing Battery Energy Storage Systems to Enhance the Integration of Photovoltaic Systems for Damping Oscillations

Utilizing Battery Energy Storage Systems to Enhance the Inte...

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IEEE Southeastcon

作者： Ilham Akbar Ariesa Budi Zakaria Mayur Basu Eduard Muliadi Suwarno Nanang Hariyanto Graduate Program PLN-ITB PLN Corporate University Auburn USA Electrical and Computer Engineering Auburn University Auburn USA School of Electrical Engineering and Informatics Institut Teknologi Bandung (ITB) Bandung Indonesia

As the integration of Variable Renewable Energy (VRE) generators into power systems increases, there is a potential decrease in overall system reliability, particularly in terms of stability. This research suggests the integration of a Battery Energy Storage System (BESS) into a power system with Variable Renewable Energy sources, such as a utility-scale Photovoltaic (PV) plant, to accelerate the damping of post-fault oscillations following a short-circuit disturbance. The objective is for a Power Oscillation Damping (POD) within the PV plant to address post-fault oscillations within a specific timeframe. The POD in the PV plant is designed to supply additional active and reactive power, responding to the system's demands after a disturbance. The addition of BESS to the system is anticipated to enhance the time required for the system to achieve a stable state, resulting in quicker system stabilization. Simulations conducted through PSCAD software can effectively depict the post-fault conditions of short-circuit disturbances, considering the impact of the integrated BESS.

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Strategies for Enhancing Static Object Detection Range in Autonomous Vehicles Using Monocular Camera Vision

Strategies for Enhancing Static Object Detection Range in Au...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Xingyou Li Hyoungrae Kim Hakil Kim Department of Electrical and Computer Engineering Inha University Incheon South Korea Department of Program in Future Vehicle Engineering Inha University Incheon South Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

The performance of object detection models for autonomous driving is increasingly advancing. However, to recognize static traffic targets such as traffic light recognition and traffic sign recognition, the detectable distance in images plays a crucial role in the planning strategies and performance of recognition algorithms for autonomous driving systems. This study analyzes the detection performance and detection range of traffic lights by a monocular camera on an autonomous driving vehicle. The detection model used is the YOLOv7-x model, with the original images segmented to 1x, 1/2x, and 1/3x of the model input size. The distances are obtained through high-precision maps and vehicle-mounted GPS/RTK. The results of this study indicate the scalability of the detection distance of a monocular camera’s object detection in an autonomous driving environment using a single model. It further demonstrates a proportional relationship between the detection distance and the model input size. It confirms the scalability of detection distances with cameras of different fields of view using a single model.

关键词： Image segmentation Image recognition Target recognition Scalability Object detection Cameras Market research Image restoration Planning Autonomous vehicles

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Convolutional Neural Network Using Res-Net For Organic and Anorganic Waste Classification 4

Convolutional Neural Network Using Res-Net For Organic and A...

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4th IEEE International Conference of computer Science and Information Technology, ICOSNIKOM 2022

作者： Girsang, Abba Suganda Yunanda, Rezky Syahputra, Muhammad Edo Peranginangin, Ezra Binus Graduate Program-Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350399073

Convolutional Neural network is state of the art of image recognition or image classification. However to build the robust model using CNN needs many parameters adjusted, and choosing the good combination hyperparameter which impacts taking much computation time. Genetic algorithm is one method metaheuristic which is robust for choosing the combinatorial possible hyperparameter. This model also uses ResNet-50 which is a pretrained model of convolutional neural network that consists 50 layers. By using a pretrained like ResNet-50, it will increase the performance model. CNN-ResNet with efficient genetic algorithm (EGA) to optimize the hyperparameter. The EGA algorithm utilizes transfer learning techniques in its algorithm so that the optimization process on CNN can achieve unified accuracy values quickly. The best performance model optimized using EGA outperformed the ResNet-50 model and the model optimized using GA and VLGA in classifying organic and inorganic materials. The accuracy value obtained from EGA is 97.53% with a loss of 0.08. © 2022 IEEE.

关键词： Convolutional neural networks

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Reducing Dependency on Imported Electricity: Utilizing Renewable Energy and Minimizing Fossil Fuel Power Plant Operations in West Kalimantan

Reducing Dependency on Imported Electricity: Utilizing Renew...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Ilham Akbar Ariesa Budi Zakaria Eduard Muljadi Suwarno Nanang Hariyanto Graduate Program PLN-ITB PLN Corporate University Auburn USA Electrical and Computer Engineering Auburn University Auburn USA School of Electrical Engineering and Informatics Institut Teknologi Bandung (ITB) Bandung Indonesia

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

This paper discusses West Kalimantan's dependency on imported electricity and fossil fuels and advocates for integrating renewable energy sources, especially solar power. With abundant solar resources and its equatorial location, West Kalimantan presents a significant solar PV generation opportunity. However, its dependence on imported electricity from the ASEAN Grid initiative poses risks to energy security. By promoting solar power as an alternative energy source and reducing reliance on fossil fuels, the paper aims to improve energy independence and sustainability. Integrating solar PV requires assessing frequency stability to ensure system resilience. Moreover, the interconnection between the two grids enhances system resilience and facilitates renewable energy integration. In summary, integrating solar PV power plants into the West Kalimantan system aims to decrease dependence on electricity imports from Sarawak while preserving the system's frequency stability.

关键词： Photovoltaic systems Renewable energy sources Fault tolerance Electricity Power system stability Fossil fuels Security Sustainable development Thermal stability Research and development

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Restoration of Time-Varying Graph Signals using Deep Algorithm Unrolling

Restoration of Time-Varying Graph Signals using Deep Algorit...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hayate Kojima Hikari Noguchi Koki Yamada Yuichi Tanaka Department of Electrical Engineering and Computer Science Tokyo University of Agriculture and Technology Department of Electrical Engineering Tokyo University of Science Graduate School of Engineering Osaka University

In this paper, we propose a restoration method of time-varying graph signals, i.e., signals on a graph whose signal values change over time, using deep algorithm unrolling. Deep algorithm unrolling is a method that learns parameters in an iterative optimization algorithm with deep learning techniques. It is expected to improve convergence speed and accuracy while the iterative steps are still interpretable. In the proposed method, the minimization problem is formulated so that the time-varying graph signal is smooth both in time and spatial domains. The internal parameters, i.e., time domain FIR filters and regularization parameters, are learned from training data. Experimental results using synthetic data and real sea surface temperature data show that the proposed method improves signal reconstruction accuracy compared to several existing time-varying graph signal re- construction methods.

关键词： Temperature distribution Sea surface Smoothing methods Finite impulse response filters Signal processing algorithms Training data Time-domain analysis

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