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Versatile Tasks on Integrated Aerial Platforms Using Only Onboard Sensors: Control, Estimation, and Validation

IEEE Transactions on Robotics 2025年 41卷 3518-3538页

作者： Wang, Kaidi Lai, Ganghua Yu, Yushu Du, Jianrui Sun, Jiali Xu, Bin Franchi, Antonio Sun, Fuchun Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Beijing Institute of Technology School of Mechanical Engineering Beijing100081 China University of Twente Robotics and Mechatronics Lab Faculty of Electrical Engineering Mathematics and Computer Science Enschede7500 AE Netherlands Tsinghua University Department of Computer Science and Technology China

Connecting multiple aerial vehicles to a rigid central platform through passive spherical joints holds the potential to construct a fully-actuated aerial platform. The integration of multiple vehicles enhances efficiency in tasks like mapping and object reconnaissance. This paper proposes a control and state estimation framework for the Integrated Aerial Platform (IAP), enabling it to perform versatile tasks like object reconnaissance and physical interactive tasks with only onboard sensors. In the framework, the 6D motion control serves as the low-level controller, while the high-level controller comprises a 6D admittance filter and a perception-aware attitude correction module. The 6D admittance filter, serving as the interaction controller, is adaptable for aerial interaction tasks. The perception-aware attitude correction algorithm is carefully designed by adopting a geometric Model Predictive Controller (MPC). This algorithm, incorporating both offline and online calculations, proves to be well-suited for the intricate dynamics of an IAP. A 6D direct wrench controller is also developed for the IAP. Notably, both the interaction controller and the direct wrench controller operate without reliance on force/torque sensors. Instead, a wrench observer algorithm is devised, considering external disturbances. Additionally, based on the kinematics constraints of the multiple aerials in the platform, a fusion algorithm for multiple Visual-Inertial Odometry (VIO) and kinematics constraints is developed, providing more accurate localization. A prototype of the IAP is constructed, and its capabilities are demonstrated through experiments including perception-aware object reconnaissance, aerial mapping, aerial peg-in-hole task, and 6D contact wrench generation. All experiments are conducted exclusively with onboard sensors. These tasks exemplify the merits of the proposed IAP and validate the effectiveness of the proposed control framework and fusion algorithm. © 2004-2012

关键词： State estimation

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Defer No Time, Delays have Dangerous Ends: Slow HTTP/2 DoS Attacks into the Wild 14

Defer No Time, Delays have Dangerous Ends: Slow HTTP/2 DoS A...

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14th International Conference on COMmunication Systems and NETworkS, COMSNETS 2022

作者： Tripathi, Nikhil Shaji, Abhijith Kalayil Indian Institute of Information Technology Computer Science and Engineering Group Chittoor India Otto von Guericke University Faculty of Computer Science Magdeburg Germany

ISBN: (纸本)9781665421041

Slow Rate DoS attacks intend to prevent the legitimate clients from accessing the target application (web, mail, etc.) running over the victim server. These attacks target application layer protocols, and HTTP/1.1 is one of the most studied protocols against Slow Rate DoS attacks. HTTP/2, the successor of HTTP/1.1, is also found to be vulnerable to these attacks. However, the impact of these attacks on real HTTP/2 servers on the Internet has not been studied yet. In this preliminary work, we test the behaviour of Alexa top 500K websites on the Internet against Slow Rate DoS attacks. We first conduct experiments to find the websites that serve web content over HTTP/2. Subsequently, we test their web servers against the Slow Rate DoS attacks and furnish the results. We observe that several HTTP/2 servers on the Internet are vulnerable to these attacks, thereby, advocate developing a robust real-time detection strategy. Towards the end of the paper, we also discuss some possible defense mechanisms to counter the attacks. © 2022 IEEE.

关键词： HTTP

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Traffic Priority-Aware medical Data Dissemination Scheme for IoT Based WBASN Healthcare Applications

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computers, Materials & Continua 2022年第6期71卷 4443-4456页

作者： Muhammad Anwar Farhan Masud Rizwan Aslam Butt Sevia Mahdaliza Idrus Mohammad Nazir Ahmad Mohd Yazid Bajuri Department of Computer Science NFC Institute of Engineering and Fertilizer ResearchFaisalabadPakistan Department of Statistics and Computer Science Faculty of Life Sciences Business ManagementUniversity of Veterinary and Animal SciencesLahorePakistan Department of Electronics Engineering NED University of Engineering and TechnologyKarachiPakistan School of Electrical Engineering Universiti Teknologi MalaysiaJohor BahruMalaysia Institute of IR4.0 Universiti Kebangsaan MalaysiaBangiSelangorMalaysia Department of Orthopedics and Traumatology Faculty of MedicineUniversiti Kebangsaan MalaysiaKuala LumpurMalaysia

Wireless Body Area Sensor Network(WBASN)is an automated system for remote health monitoring of *** under umbrella of Internet of Things(IoT)is comprised of small Biomedical Sensor Nodes(BSNs)that can communicate with each other without human *** BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital *** BSNs generate critical data as it is related to patient’s *** data traffic can be classified as Sensitive Data(SD)and Non-sensitive Data(ND)packets based on the value of vital *** data packets have different priority to *** ND packets may tolerate some delay or packet loss whereas,the SD packets required to be delivered on time with minimized packet loss otherwise it can be life threating to the *** this research,we propose a Traffic Priority-aware medical Data Dissemination(TPMD2)scheme forWBASN to deliver the data packets according to their priority based on the sensitivity of the *** assessment of the proposed scheme is carried out in various *** simulation results of the TPMD2 scheme indicate a significant improvement in packets delivery,transmission delay and energy efficiency in comparison with the existing schemes.

关键词： WBANS wearable technology priority routing eHealth applications remote health monitoring

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Recognition of Urdu Handwritten Alphabet Using Convolutional Neural Network (CNN)

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computers, Materials & Continua 2022年第11期73卷 2967-2984页

作者： Gulzar Ahmed Tahir Alyas Muhammad Waseem Iqbal Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi Department of Computer Science University of South AsiaLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Handwritten character recognition systems are used in every field of life nowadays,including shopping malls,banks,educational institutes,*** is the national language of Pakistan,and it is the fourth spoken language in the ***,it is still challenging to recognize Urdu handwritten characters owing to their cursive *** paper presents a Convolutional Neural Networks(CNN)model to recognize Urdu handwritten alphabet recognition(UHAR)offline and online *** research contributes an Urdu handwritten dataset(aka UHDS)to empower future works in this *** offline systems,optical readers are used for extracting the alphabets,while diagonal-based extraction methods are implemented in online ***,our research tackled the issue concerning the lack of comprehensive and standard Urdu alphabet datasets to empower research activities in the area of Urdu text *** this end,we collected 1000 handwritten samples for each alphabet and a total of 38000 samples from 12 to 25 age groups to train our CNN model using online and offline ***,we carried out detailed experiments for character recognition,as detailed in the *** proposed CNN model outperformed as compared to previously published approaches.

关键词： Urdu handwritten text recognition handwritten dataset convolutional neural network artificial intelligence machine learning deep learning

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CoarseUCB: A Context-Aware Bitrate Adaptation Algorithm for VBR-encoded Video Streaming

CoarseUCB: A Context-Aware Bitrate Adaptation Algorithm for ...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Chengrun Yang Gangqiang Zhou Miao Hu Qinglin Zhao Di Wu School of Computer Science and Engineering Sun Yat-sen University Guangzhou Guangdong China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology Macau China

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Variable bitrate (VBR) encoding has gained considerable interest due to its capacity to enhance video quality and mitigate transmission congestion in contrast to constant bitrate (CBR) encoding. However, adaptive bitrate (ABR) streaming faces challenges when dealing with VBR-encoded videos, primarily stemming from the significant variability in chunk size and the consequent bitrate fluctuations. This paper proposes CoarseUCB, a context-aware online learning algorithm for bitrate adaptation in VBR-encoded videos. CoarseUCB considers important aspects of VBR-encoded video streaming and uses the upper confidence bound (UCB) method for bitrate selection. The UCB method does not require precise bandwidth estimation and balances the exploration and exploitation of each action effectively. Additionally, CoarseUCB accounts for the impact of multiple future video chunks when making the bitrate decision for the current chunk. To evaluate the effectiveness of CoarseUCB, we conduct experiments to assess its efficiency. The results show that CoarseUCB delivers a higher average user quality of experience (QoE) compared to state-of-the-art ABR algorithms, resulting in an improvement of up to 9.81%.

关键词： Wireless communication Fluctuations Bit rate Streaming media Throughput Encoding Quality assessment

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Cloud-Native Mobile Application Applied for Law and Regulations Harmonization 3

Cloud-Native Mobile Application Applied for Law and Regulati...

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3rd International Conference on Intelligent Cybernetics technology and Applications, ICICyTA 2023

作者： Al Qausar, Muhammad Juan Heryadi, Yaya Lukas, Lukas Suparta, Wayan Sonata, Ilvico Doctor of Computer Science Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta Indonesia Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350394559

Navigating the complex legal and regulatory landscape requires a sophisticated platform that is not only comprehensive but also user-friendly and enables seamless analysis and document comparison in the legal realm. To address this challenging requirement, this research is dedicated to the user experience (UX) design of state-of the-art cloud-native mobile applications specifically designed for legal and regulatory harmonization. The methodology used is based on design thinking principles and takes advantage of the benefits of cloud computing. These include, but are not limited to, scalability, reliability, and security. The result is a solution that is not only powerful but also cost-effective. The core of this application follows a user-centered design philosophy and involves potential users closely in the design process. A comprehensive evaluation is performed using the System Usability Scale (SUS) methodology to measure the effectiveness and usability of the application. The results of this comprehensive approach are convincing. The application has an impressive 95.5% usage rate, indicating strong user engagement. Furthermore, user satisfaction ratings are particularly high and transformative impact of this application in a complex environment of legal harmonization. Through its innovative design, seamless functionality, and user-centric approach, this application has proven to be not only a technical solution, but also a catalyst for positive change in the legal and regulatory harmonization process. © 2023 IEEE.

关键词： Cost effectiveness

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Exams Item Analysis, Online Examination, and Education Evaluation System Via Internet 20

Exams Item Analysis, Online Examination, and Education Evalu...

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20th International Conference on Electrical engineering/Electronics, computer, Telecommunications and Information technology, ECTI-CON 2023

作者： Chaidee, Kamonlak Boontasri, Kanchana Chaidee, Ekkachai Punthura, Kittichai Kumtip, Narong Pankham, Yotsanan Rajamangala University of Technology Lanna Chiangrai Faculty of Business Administration and Liberal Arts Department of Computer Information System Chiang Rai Thailand Rajamangala University of Technology Lanna Chiangrai Faculty of Science and Agricultural Technology Department of Information Technology Chiang Rai Thailand Rajamangala University of Technology Lanna Chiangrai Faculty of Electrical Engineering Department of Electrical Engineering Chiang Rai Thailand

ISBN: (纸本)9798350310467

The objective of this study is to develop an exams item bank management system on the internet. The exam item analysis system is used to determine the reliability of the exams using K-R 20 and K-R 21 formulas. The difficulty and power of discrimination values are determined using a choice analysis and percentages of high and lower groups technique. The create exams set system can be performed randomly or identified through the difficulty level. The examination can be performed online and the exam results can be immediately announced. The grading system is used to support the decision-making to evaluate learning achievement. The system's accuracy was tested and found to be accurate compared with the hand calculation results. The system was tested with a sample group and satisfaction was assessed through questionnaires. The satisfaction of teachers and students was highest, while that of administrators was high. The developed exams item bank management system operates as a web application with a security system for supporting in learning activity. © 2023 IEEE.

关键词： Decision making

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DFD-Net:lung cancer detection from denoised CT scan image using deep learning

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Frontiers of computer science 2021年第2期15卷 119-131页

作者： Worku J.SORI Jiang FENG Arero W.GODANA Shaohui LIU Demissie J.GELMECHA School of Electrical Engineering and Computing Department of Computer Science and EngineeringAdama Science and Technology UniversityAdama1888Ethiopia Faculty of Natural Computational Science Department of Mathematics Bule Hora UniversityBule HoraHagere Maryam144Ethiopia School of Computer Science and Technology Harbin Institute of TechnologyHarbin150001China Peng Cheng Laboratory Shenzhen518052China School of Electrical Engineering and Computing Department of Electronics and Communications EngineeringAdama Science and Technology UniversityAdama1888Ethiopia

The availability of pulmonary nodules in CT scan image of lung does not completely specify *** noise in an image and morphology of nodules,like shape and size has an implicit and complex association with cancer,and thus,a careful analysis should be mandatory on every suspected nodules and the combination of information of every *** this paper,we introduce a“denoising first”two-path convolutional neural network(DFD-Net)to address this *** introduced model is composed of denoising and detection part in an end to end ***,a residual learning denoising model(DR-Net)is employed to remove noise during the preprocessing ***,a two-path convolutional neural network which takes the denoised image by DR-Net as an input to detect lung cancer is *** two paths focus on the joint integration of local and global *** this end,each path employs different receptive field size which aids to model local and global *** further polish our model performance,in different way from the conventional feature concatenation approaches which directly concatenate two sets of features from different CNN layers,we introduce discriminant correlation analysis to concatenate more representative ***,we also propose a retraining technique that allows us to overcome difficulties associated to the image labels *** found that this type of model easily first reduce noise in an image,balances the receptive field size effect,affords more representative features,and easily adaptable to the inconsistency among nodule shape and *** intensive experimental results achieved competitive results.

关键词： medical image discriminant correlation analysis features fusion image detection denoising

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User Mobility Prediction in 5G Networks Using Recurrent Neural Networks

User Mobility Prediction in 5G Networks Using Recurrent Neur...

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2024 IEEE International Conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Shrestha, Anubhav Sharma, Vikalp Hussein, Layth Aishwarya, M. Satyanarayana, A.N. Saimanohar, T. Chandigarh Group of Colleges Chandigarh Engineering College Department of Computer Application Punjab Jhanjeri Mohali140307 India Ies College of Technology Department of Computer Science & Engineering M.P. Bhopal India The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq The Islamic University Of Al Diwaniyah College Of Technical Engineering Department Of Computers Techniques Engineering Al Diwaniyah Iraq Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Sreenidhi Institute of Science and Technology Ece Department Hyderabad India Saveetha Institute of Medical and Technical Sciences Department CSE-AI Tamilnadu Chennai India

ISBN: (纸本)9798350390759

The use of new possibilities introduced by 5G networks also creates new problems and concerns, specifically in the field of user mobility in wireless communication systems. In this paper, the Authors investigate the effectiveness of Recurrent Neural Networks (RNNs) in the mobility prediction context in order to exploit the temporal component in the users movement data for improved prediction performance. To drive this process, the input datasets are obtained from the GeoLife GPS Trajectories dataset, then follow the data pre-processing steps, constructing an LSTM-based RNN model, and using Python with TensorFlow and Keras. From the analyses, we detected that the accomplishment of using LSTM and hybrid RNN-CNN is significant and higher than the traditional approaches of EN, RFM, and CL. The test results demonstrate that the LSTM model can reduce the MAE and RMSE values by 19. 49% and 14. 82%, respectively. However, the execution of these models has some issues that include compute time, instantaneous prediction that is needed in many real-world applications, and case. Such problems can be solved with the help of such approaches as edge computing and distributed processing. Besides, it is pivotal to put measures in place to maintain the confidentiality and security of user information. This paper highlights the applicative potential of RNNs in redesigning user mobility prediction in 5G networks, and thus helping toward a better ownership of the network players and assets. © 2024 IEEE.

关键词： 5G mobile communication systems

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First principle calculation of electronic structures and hole concentration of YBCO family compounds 4

First principle calculation of electronic structures and hol...

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4th International Conference on Separation technology, ICoST 2023

作者： Min Cheong, Choon Kien Chen, Soo School of Engineering INTI International Collge Penang Pulau Pinang11900 Malaysia Faculty of Computer Science & Information Technology Universiti Malaya Kuala Lumpur57100 Malaysia Department of Physics Faculty of Science Universiti Putra Malaysia Selangor Darul Ehsan Serdang43300 Malaysia

Yttrium barium copper oxide (YBCO) family compounds are similar in structure but have different superconducting temperatures. It is well known that superconducting properties arise from the crystal lattice and electronic structure of compounds. This work reveals and discusses the electronic structures of YBCO family compounds (YBa2Cu3O6, YBa2Cu3O6.5, YBa2Cu3O7, and YBa2Cu4O8) based on density functional theory (DFT). The electronic structure results show that Cu-O chains are the trigger components for conduction, and only Cu-O chains and Cu-O2planes play important roles in electronic and superconducting properties. The results also reveal that additional hole doped will be non-trivially distributed between the Cu-O chains and the Cu-O2planes, and hence a more comprehensive method is required to calculate the hole concentration in the Cu-O2plane. This work also demonstrates the calculation of hole concentrations using DFT. By DFT calculation, the Y1236 has hole concentration of 0.5 and the hole doped of Y12365, Y1237 and Y124 are 0.09, 0.16 and 0.10, respectively. The results are consistent with the cuprate-superconductor phase diagram and the bond-valence sum (BVS) calculations. © 2024 Elsevier Ltd. All rights reserved.

关键词： Electronic structure

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