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Weighted hypersoft configuration model

Physical Review Research 2020年第4期2卷 043157-043157页

作者： Ivan Voitalov Pim van der Hoorn Maksim Kitsak Fragkiskos Papadopoulos Dmitri Krioukov Department of Physics Northeastern University Boston Massachusetts 02115 USA Network Science Institute Northeastern University Boston Massachusetts 02115 USA Department of Mathematics and Computer Science Eindhoven University of Technology Postbus 513 5600 MB Eindhoven Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology 2628 CD Delft Netherlands Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology 33 Saripolou Street 3036 Limassol Cyprus Department of Mathematics Northeastern University Boston Massachusetts 02115 USA Department of Electrical and Computer Engineering Northeastern University Boston Massachusetts 02115 USA

Maximum entropy null models of networks come in different flavors that depend on the type of constraints under which entropy is maximized. If the constraints are on degree sequences or distributions, we are dealing with configuration models. If the degree sequence is constrained exactly, the corresponding microcanonical ensemble of random graphs with a given degree sequence is the configuration model per se. If the degree sequence is constrained only on average, the corresponding grand-canonical ensemble of random graphs with a given expected degree sequence is the soft configuration model. If the degree sequence is not fixed at all but randomly drawn from a fixed distribution, the corresponding hypercanonical ensemble of random graphs with a given degree distribution is the hypersoft configuration model, a more adequate description of dynamic real-world networks in which degree sequences are never fixed but degree distributions often stay stable. Here, we introduce the hypersoft configuration model of weighted networks. The main contribution is a particular version of the model with power-law degree and strength distributions, and superlinear scaling of strengths with degrees, mimicking the properties of some real-world networks. As a byproduct, we generalize the notions of sparse graphons and their entropy to weighted networks.

关键词： Complex systems Network structure Real world networks Scale free & inhomogeneous networks Weighted networks Statistical methods

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vieCap4H-VLSP 2021: Vietnamese Image Captioning for Healthcare Domain using Swin Transformer and Attention-based LSTM

arXiv

引用

arXiv 2022年

作者： Nguyen, Thanh Tin Nguyen, Long H. Pham, Nhat Truong Nguyen, Liu Tai Do, Van Huong Nguyen, Hai Nguyen, Ngoc Duy Human Computer Interaction Lab Sejong University Seoul Korea Republic of Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Division of Computational Mechatronics Institute for Computational Science Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam ASICLAND Suwon Korea Republic of Khoury College of Computer Sciences Northeastern University Boston United States Institute for Intelligent Systems Research and Innovation Deakin University Victoria Australia

This study presents our approach on the automatic Vietnamese image captioning for healthcare domain in text processing tasks of Vietnamese Language and Speech Processing (VLSP) Challenge 2021, as shown in Figure 1. In recent years, image captioning often employs a convolutional neural network-based architecture as an encoder and a long short-term memory (LSTM) as a decoder to generate sentences. These models perform remarkably well in different datasets. Our proposed model also has an encoder and a decoder, but we instead use a Swin Transformer in the encoder, and a LSTM combined with an attention module in the decoder. The study presents our training experiments and techniques used during the competition. Our model achieves a BLEU4 score of 0.293 on the vietCap4H dataset, and the score is ranked the 3rd place on the private leaderboard. Our code can be found at https://***/JDdJm. © 2022, CC BY.

关键词： Long short-term memory

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An Improved Wolf Pack Algorithm

An Improved Wolf Pack Algorithm

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Chinese Control and Decision Conference, CCDC

作者： Qiangyi Zhao Ran Tao Jiangning Li Yahui Mu College of Information Science and Engineering Northeastern University Shenyang China Faculty of Engineering and Information Technologies The University of Sydney Sydney NSW Australia Law School of Hainan University Haikou China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

This paper aims to overcome the shortcomings of original wolf pack algorithm (WPA). The shortcomings of original WPA include fixed scouting directions, scouting step length that cannot be adjusted dynamically, lack of information exchange between each other in artificial wolves and lead wolf does not participate in intelligent behavior. An improved wolf pack algorithm is proposed in this paper. The improved algorithm provides scout wolves variable scouting directions and scouting step length could adjust dynamically based on the Fibonacci Sequence by the improved algorithm. Furthermore, ferocious wolves could exchange information with scout wolves during raiding. Finally, the hunting principle of lead wolf is provided in the improved algorithm. Thus, WPA is improved from four aspects: global optimization, convergence speed, convergence accuracy and robustness. The simulation results show that compared with original WPA, the improved wolf pack algorithm not only increase the global search capability, but also avoids early-maturing of the algorithm. Furthermore, it has strong robustness and significant improvements in the search accuracy and rate of convergence.

关键词： Lead Heuristic algorithms Information exchange Convergence Electronic mail Optimization Robustness

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Servomotor Modelling and Control for Medical robots

Servomotor Modelling and Control for Medical Robots

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Leqiang Shi Jilai Song Chenglong Xu Gang Li Yanchao Zhang Chong Li Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China SIASUN Robot & Automation Co. Ltd Shenyang Liaoning China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

In the driving technology of brushless DC motor (BLDCM), there are two methods: vector control (sine wave control) and 120 degree square wave control (rectangular wave control). In the analysis of some applications of medical instruments by BLDCM, the vector control method makes the running noise of BLDCM small, and has good low-speed torque stability and stability, but the power loss of the vector control mode is large. In addition, the software structure is complex and the adaptability to the motor is relatively poor. In this paper, combined with the application of BLDCM in medical walking assisted robot, firstly, in Matlab/Simulink, the simulation model of the system is constructed. Then, PID parameters are obtained by modeling and analyzing the system. Through the simulation data comparison vector control and 120 degree square wave control, the speed following characteristics under two control modes prove that the superiority of using 120 degree square wave control under the premise of meeting the actual operation requirements. This paper has important guiding significance for the development of medical robot drive technology.

关键词： Mathematical model Brushless DC motors Control systems Torque Transfer functions

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A Robust Laser-Inertial Odometry and Mapping Method for Large-Scale Highway Environments

A Robust Laser-Inertial Odometry and Mapping Method for Larg...

引用

2019 IEEE/RSJ International Conference on Intelligent robots and Systems (IROS)

作者： Shibo Zhao Zheng Fang HaoLai Li Sebastian Scherer Faculty of Robot Science and Engineering Northeastern University Shenyang China Robotics Institute Carnegie Mellon University Pittsburgh Pennsylvania

In this paper, we propose a novel laser-inertial odometry and mapping method to achieve real-time, low-drift and robust pose estimation in large-scale highway environments. The proposed method is mainly composed of four sequential modules, namely scan pre-processing module, dynamic object detection module, laser-inertial odometry module and laser mapping module. Scan pre-processing module uses inertial measurements to compensate the motion distortion of each laser scan. Then, the dynamic object detection module is used to detect and remove dynamic objects from each laser scan by applying CNN segmentation network. After obtaining the undistorted point cloud without moving objects, the laser-inertial odometry module uses an Error State Kalman Filter to fuse the data of laser and IMU and output the coarse pose estimation at high frequency. Finally, the laser mapping module performs a fine processing step and the “Frame-to-Model'' scan matching strategy is used to create a static global map. We compare the performance of our method with two state-of-the-art methods, LOAM and SuMa, using KITTI dataset and real highway scene dataset. Experiment results show that our method performs better than the state-of-the-art methods in real highway environments and achieves competitive accuracy on the KITTI dataset.

关键词：

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Image-guided Breast Biopsy of MRI-visible Lesions with a Hand-mounted Motorised Needle Steering Tool

Image-guided Breast Biopsy of MRI-visible Lesions with a Han...

引用

International Symposium on Medical robotics (ISMR)

作者： Marta Lagomarsino Vincent Groenhuis Maura Casadio Marcel K. Welleweerd Françoise J. Siepel Stefano Stramigioli Robotics and Mechatronics (RAM) Laboratory Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede The Netherlands University of Genoa Genoa Italy Human-Robot Interfaces and Physical Interaction (HRII) Laboratory Istituto Italiano di Tecnologia Genoa Italy Politecnico di Milano Milan Italy

ISBN: (纸本)9781665406239

A biopsy is the only diagnostic procedure for accurate histological confirmation of breast cancer. When sonographic placement is not feasible, a Magnetic Resonance Imaging(MRI)-guided biopsy is often preferred. The lack of real-time imaging information and the deformations of the breast make it challenging to bring the needle precisely towards the tumour detected in pre-interventional Magnetic Resonance (MR) images. The current manual MRI-guided biopsy workflow is inaccurate and would benefit from a technique that allows real-time tracking and localisation of the tumour lesion during needle insertion. This paper proposes a robotic setup and software architecture to assist the radiologist in targeting MR-detected suspicious tumours. The approach benefits from image fusion of preoperative images with intraoperative optical tracking of markers attached to the patient’s skin. A hand-mounted biopsy device has been constructed with an actuated needle base to drive the tip toward the desired direction. The steering commands may be provided both by user input and by computer guidance. The workflow is validated through phantom experiments. On average, the suspicious breast lesion is targeted with a radius down to 2.3 mm. The results suggest that robotic systems taking into account breast deformations have the potentials to tackle this clinical challenge.

关键词： Target tracking Biopsy Phantoms Breast Needles Real-time systems Skin

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A New Approach for Training on EMG-based Prosthetic Hand Control

A New Approach for Training on EMG-based Prosthetic Hand Con...

引用

IEEE Global Conference on Life sciences and Technologies (LifeTech)

作者： Taro Shibanoki Go Nakamura Toshio Tsuji Kazuya Hashimoto Takaaki Chin The Graduate School of Science and Engineering Ibaraki University Ibaraki Japan Robot Rehabilitation Center The Hyogo Institute of Assistive Technology Kobe Japan Faculty of Engineering Hiroshima University Hiroshima Japan

ISBN: (数字)9781728170633

ISBN: (纸本)9781728170640

This paper proposes a training system for myoelectric prosthetic hand control in dual-arm operation. The system can train muscular cooperation timing of both arms. Training experiments under two conditions were conducted with an experienced participant and the results showed that the user could generate accurate EMG patterns at the specified timing.

关键词： electromyogram (EMG) training system virtual reality (VR) prosthetic hand dual-arm operation Prosthetic hand Training Functional training

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An Acceleration Method Using CUDA based on ORB-SLAM2

An Acceleration Method Using CUDA based on ORB-SLAM2

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Zhenzhen Li Lei Zhang Chenglong Xu Fengshan Zou Jilai Song Daji Tian Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China SIASUN Robot & Automation Co. Ltd Shenyang Liaoning China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

In order to solve the problem of poor real-time performance and low position accuracy when mobile robots apply the technology of simultaneous localization and mapping, this paper proposed an improved algorithm using CUDA parallel computing to do the ORB feature extraction and matching portion to reduce the running time of the algorithm based on open source ORB - SLAM2 visual SLAM algorithm. After that.,testing the algorithm with public stereo datasets by doing some comparative experiments using the laptop and camera. the experiment result shows that the proposed method by this paper can greatly reduce the time of extracting feature points, calculating feature descriptors and image matching, and also improve the accuracy of localization. Therefore, the improved algorithm can improve the operation efficiency of the algorithm and the robustness of mobile robot SLAM.

关键词： Feature extraction Graphics processing units Cameras Simultaneous localization and mapping robot vision systems Optimization

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Research on ORB-SLAM Autonomous Navigation Algorithm

Research on ORB-SLAM Autonomous Navigation Algorithm

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： C.L. Xu D.K. Qu C.D. Wu Z. Z. Li P. Di J. L. Song D. J. Tian Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China SIASUN Robot & Automation Co. Ltd Shenyang Liaoning China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

The autonomous navigation algorithm of ORB-SLAM and its problems were studied and improved in this paper. ORB-SLAM is a fast and accurate navigation algorithm using visual image feature to calculate the position and attitude. But when there are few characteristic points in the unknown environment, ORB-SLAM algorithm falls into the situation of infinite solution, local localization error occurs, and global mapping is interrupted. Researchers have proposed an IMU/Vision fusion algorithm that neatly solves this problem. In this process, the calibration between inertial components and camera is very important, the desirable outcome of which will slow down the divergence speed of autonomous navigation system and further improve the system accuracy. In this paper, the algorithm of calibration between IMU/OE and Stereo vision exploiting the improved recursive least squares with forgetting factor (RFF) method is proposed, and then the algorithm is verified by experimental datas. The results show that the accuracy and the stability of the DR navigation system are improved, which can be applied to IMU/Vision integrated navigation system and enhance robustness of navigation system.

关键词： Simultaneous localization and mapping Dead reckoning Acceleration Autonomous robots Visualization

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A Cascade Dual-Decoder Model for Joint Entity and Relation Extraction

arXiv

引用

arXiv 2021年

作者： Cheng, Jian Zhang, Tian Zhang, Shuang Ren, Huimin Yu, Guo Zhang, Xiliang Gao, Shangce Ma, Lianbo The Research Institute of Mine Artificial Intelligence in Chinese Institute of Coal Science State Key Laboratory of Intelligent Coal Mining and Strata Control Tiandi Science and Technology Co. Ltd. Beijing100013 China The College of Software Northeastern University Shenyang China The Institute of Intelligent Manufacturing Nanjing Tech University Nanjing211816 China The School of Intelligent Manufacturing and Control Engineering Shanghai Polytechnic University Shanghai China The Faculty of Engineering University of Toyama Toyama-shi930-8555 Japan Foshan Graduate School of Innovation Northeastern University Foshan China

In knowledge graph construction, a challenging issue is how to extract complex (e.g., overlapping) entities and relationships from a small amount of unstructured historical data. The traditional pipeline methods are to divide the extraction into two separate subtasks, which misses the potential interaction between the two subtasks and may lead to error propagation. In this work, we propose an effective cascade dual-decoder method to extract overlapping relational triples, which includes a text-specific relation decoder and a relation-corresponded entity decoder. Our approach is straightforward and it includes a text-specific relation decoder and a relation-corresponded entity decoder. The text-specific relation decoder detects relations from a sentence at the text level. That is, it does this according to the semantic information of the whole sentence. For each extracted relation, which is with trainable embedding, the relation-corresponded entity decoder detects the corresponding head and tail entities using a span-based tagging scheme. In this way, the overlapping triple problem can be tackled naturally. We conducted experiments on a real-world open-pit mine dataset and two public datasets to verify the method's generalizability. The experimental results demonstrate the effectiveness and competitiveness of our proposed method and achieve better F1 scores under strict evaluation metrics. Our implementation is available at https://***/prastunlp/DualDec. Copyright © 2021, The Authors. All rights reserved.

关键词： Decoding

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