检索结果-内蒙古大学图书馆

Training Multi-Layer Perceptron with Enhanced Brain Storm Optimization Metaheuristics

Computers, Materials & Continua 2022年第2期70卷 4199-4215页

作者： Nebojsa Bacanin Khaled Alhazmi Miodrag Zivkovic K.Venkatachalam Timea Bezdan Jamel Nebhen Singidunum University Danijelova11000BelgradeSerbia National Center for Robotics and IoT Communication and Information Technology Research InstituteKing Abdulaziz City for Science and Technology(KACST)Riyadh12371Saudi Arabia Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Prince Sattam Bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia

In the domain of artificial neural networks,the learning process represents one of the most challenging *** the classification accuracy highly depends on theweights and biases,it is crucial to find its optimal or suboptimal values for the problem at ***,to a very large search space,it is very difficult to find the proper values of connection weights and *** traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local *** commonly,back-propagation is used formulti-layer-perceptron training and it can lead to vanishing gradient *** an alternative approach,stochastic optimization algorithms,such as nature-inspired metaheuristics are more reliable for complex optimization tax,such as finding the proper values of weights and biases for neural network *** thiswork,we propose an enhanced brain storm optimization-based algorithm for training neural *** the simulations,ten binary classification benchmark datasets with different difficulty levels are used to evaluate the efficiency of the proposed enhanced brain storm optimization *** results show that the proposed approach is very promising in this domain and it achieved better results than other state-of-theart approaches on the majority of datasets in terms of classification accuracy and convergence speed,due to the capability of balancing the intensification and diversification and avoiding the local *** proposed approach obtained the best accuracy on eight out of ten observed dataset,outperforming all other algorithms by 1-2%on *** mean accuracy is observed,the proposed algorithm dominated on nine out of ten datasets.

关键词： Artificial neural network optimization metaheuristics algorithm hybridization brain storm optimization

来源：评论

学校读者我要写书评

暂无评论

Examination of an independently actuated multi-air pad mattress for preventing pressure ulcers

引用

Journal of institute of Control, robotics and Systems 2021年第10期27卷 695-702页

作者： Yang, Kyon-Mo Park, Min-Ro Koo, Jaewan Lee, Jong-Il Gwak, Donggi Lee, Seokjae Sohn, Dong-Seop Kim, Min-Gyu Seo, Kap-Ho Korea Institute of Robotics & Technology Convergence Korea Republic of Dept. of Robot and Smart System Engineering Kyungpook National University Korea Republic of Korea Republic of

This study examined the structure of an independently actuated multi-air pad mattress for preventing pressure ulcers, owing to lower body pressure, in specific locations of the body where pressure sores can occur. The contributions of this study are as follows: 1) The parameters were derived and simulations were performed to design air pad units of different sizes with similar heights. 2) The mattress was manufactured by examining the bending of the folding bed, with 36 air pads and three different sizes. 3) Each air pad was independently controlled to inflate, contract, and retain to reduce the pressure on specific body positions. 4) Finally, using the fabricated prototype, the proposed designs were experimentally verified. © ICROS 2021.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Global Stabilization of Antipodal Points on n-Sphere with Application to Attitude Tracking

arXiv

引用

arXiv 2023年

作者： Tong, Xin Cheng, Shing Shin Department of Mechanical and Automation Engineering CUHK T Stone Robotics Institute The Chinese University of Hong Kong Hong Kong Department of Mechanical and Automation Engineering CUHK T Stone Robotics Institute Shun Hing Institute of Advanced Engineering Multi-Scale Medical Robotics Center The Chinese University of Hong Kong Hong Kong

Existing approaches to robust global asymptotic stabilization of a pair of antipodal points on unit n-sphere Sn typically involve the non-centrally synergistic hybrid controllers for attitude tracking on unit quaternion space. However, when switching faults occur due to parameter errors, the non-centrally synergistic property can lead to the unwinding problem or in some cases, destabilize the desired set. In this work, a hybrid controller is first proposed based on a novel centrally synergistic family of potential functions on Sn, which is generated from a basic potential function through angular warping. The synergistic parameter can be explicitly expressed if the warping angle has a positive lower bound at the undesired critical points of the family. Next, the proposed approach induces a new quaternion-based controller for global attitude tracking. It has three advantageous features over existing synergistic designs: 1) it is consistent, i.e., free from the ambiguity of unit quaternion representation;2) it is switching-fault-tolerant, i.e., the desired closed-loop equilibria remain asymptotically stable even when the switching mechanism does not work;3) it relaxes the assumption on the parameter of the basic potential function in literature. Comprehensive simulation confirms the high robustness of the proposed centrally synergistic approach compared with existing non-centrally synergistic approaches. © 2023, CC BY-NC-ND.

关键词： Hybrid systems

来源：评论

学校读者我要写书评

暂无评论

An improved CNN-LSTM deep model for Classification of guideRNA in CRISPR-Casl2 System 2

An improved CNN-LSTM deep model for Classification of guideR...

引用

2nd IEEE International Conference on Artificial Intelligence in Everything, AIE 2022

作者： Ameen, Zubaida Said Ibrahim, Abdullahi Umar Mubarak, Auwalu Saleh Al-Turjman, Fadi Near East University Research Genter for Ai and IoT Ai and Robotics Institute Artificial Intelligence Dept. Turkey Near East University Biomedical Engineering Nicosia Turkey Ai and Robotics Institute NearEast University Artificial Intelligence Engineering Dept. Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Cyprus

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

Gene editing with CRISPR-Cas12 method has immense applications in diverse organisms from bacteria, and plants to humans especially in treating genetic diseases. GuideRNA and Cas enzyme are the two components required by the Cas12 gene editing method. However, the CRISPR-Cas12 system varies depending on the guideRNA sequence used. Therefore, it is important to develop improved methods for designing guideRNA sequences needed for gene editing. Here, we utilized a combination of convolutional neural networks and long short-term memory a type of recurrent neural network (bi-LSTM) model to classify guideRNA as either active or inactive, and the addition of an embedding layer for encoding guideRNA sequence improved model performance. Accuracy, AUC and F1-score were used to evaluate CNN-LSTM and achieved outstanding performance. CNN-LSTM will help in the design of guideRNA for genes with CRISPR-Cas12 system. © 2022 IEEE.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Design and path planning for a Worm-Snake-Inspired Metameric(WSIM) Robot

Design and path planning for a Worm-Snake-Inspired Metameric...

引用

IEEE International Conference on robotics and Biomimetics

作者： Zhihai Bi Jian Xu Hongbin Fang Institute of AI and Robotics Fudan University Shanghai China MOE Engineering Research Center of AI & Robotics and Shanghai Engineering Research Center of AI & Robotics Fudan University Shanghai China

ISBN: (纸本)9781665481106

Compared with the traditional wheeled and legged robots, limbless metameric robots such as snake-like and worm-like robots are more efficient in moving in an unstructured environment, which can better satisfy the requirements of special tasks such as earthquake rescue and pipeline inspection. To this end, this paper presents a renewed sense of design and the path-planning algorithm for the WSIM robot. Then, a robot prototype is established and analyzed. Experiments reveal that the robot has the ability of multi-modal locomotion, which is suitable for both open and narrow terrains. In addition, a collision-free path planning method considering kinematic constraints is proposed based on the trajectory library, bounding box, and discrete A* algorithm. The simulation results show that the algorithm is robust and well fits the WSIM robot with multi-modal locomotion capability.

关键词： Legged locomotion Simulation Pipelines Prototypes Kinematics Inspection Robot sensing systems

来源：评论

学校读者我要写书评

暂无评论

A Novel Dense Object Detector with Scale Balanced Sample Assignment and Refinement

引用

IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Dong, Jinpeng Yao, Dingyi Hu, Yufeng Zhou, Sanping Zheng, Nanning Xi’an Jiaotong University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi’an710049 China Xi’an Jiaotong University Shaanxi Xi’an710049 China

Scale variation of objects remains one of the crucial challenges in object detection. Currently, conventional dense detectors with fixed receptive fields and label weights are not conducive to the detection of multi-scale objects. However, the design limitations of unbalanced label weights and fixed refinement for multi-scale objects and multi-tasks in these studies make it difficult to achieve better detection performance. In this paper, we propose a novel dense detector named Balanced FCOS which consists of two components: Balanced Label Assignment (BLA) and Flexible Shape-based Refinement (FSR). The BLA implements scale-balanced sample assignment by introducing reweighting factors consisting of localization and classification scores into the label assignment. Low-quality but high-weight samples can be weakened by the BLA. Furthermore, we design a cross-reweighting mechanism in the BLA to ensure score consistency between classification and localization. The FSR implements scale-balanced sample refinement by learning flexible sample points’ offsets for multi-scale objects and multi-tasks based on objects’ coarse features to get more discriminative features with appropriate receptive field. In addition, better features obtained by FSR are beneficial to get better classification and localization scores, which can be used by BLA to produce accurate label weights. Only equipped with the BLA, we can achieve 41.7/46.6 AP under R50/R101-FCOS without any additional parameters. When combining the BLA with the FSR, our Balanced FCOS achieves SOTA results among dense detectors on the COCO test-dev set. Experiments conducted on other heads (T-Head, DyHead), detectors (DINO), and datasets (AI-TOD) further demonstrate the effectiveness of our method. (Figure presented) © 1991-2012 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Bioinspired Soft Robotic Fish for Wireless Underwater Control of Gliding Locomotion

ADVANCED INTELLIGENT SYSTEMS

引用

ADVANCED INTELLIGENT SYSTEMS 2022年第7期4卷

作者： Lee, Jinwoo Yoon, Yeosang Park, Huijae Choi, Joonhwa Jung, Yeongju Ko, Seung Hwan Yeo, Woon-Hong George W. Woodruff School of Mechanical Engineering College of Engineering Georgia Institute of Technology Atlanta GA USA IEN Center for Human-Centric Interfaces and Engineering Institute for Electronics and Nanotechnology Georgia Institute of Technology Atlanta GA USA Applied Nano and Thermal Science Lab Department of Mechanical Engineering Seoul National University Seoul Korea Applied Nano and Thermal Science Lab Department of Mechanical Engineering Seoul National University Seoul Korea Institute of Advanced Machinery and Design (SNU-IAMD) Seoul National University Seoul Korea Institute of Engineering Research Seoul National University Seoul Republic of Korea George W. Woodruff School of Mechanical Engineering College of Engineering Georgia Institute of Technology Atlanta GA USA IEN Center for Human-Centric Interfaces and Engineering Institute for Electronics and Nanotechnology Georgia Institute of Technology Atlanta GA USA Wallace H. Coulter Department of Biomedical Engineering Parker H. Petit Institute for Bioengineering and Biosciences Institute for Materials Neural Engineering Center Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta GA USA

Animal locomotion offers valuable references as it is a critical component of survival as animals adapting to a specific environment. Especially, underwater locomotion poses a challenge because water exerts a high antagonistic drag force against the direction of progress. However, marine vertebrates usually use much lower aerobic energy for locomotion than aerial or terrestrial vertebrates due to their unique intermittent gliding locomotion. None of the prior works demonstrate the locomotive strategies of marine vertebrates. Herein, an untethered soft robotic fish capable of reconstructing the marine vertebrates' effective locomotion and traveling underwater by controlling localized buoyancy with thermoelectric pneumatic actuators is introduced. The actuators enable both heating and cooling to control a localized buoyancy while providing a substantial driving force to the system. Besides mimicking the locomotion, the bidirectional communication system enables the untethered delivery of commands to the underwater subject and real-time acquisition of the robotic fish's physical information. Underwater imaging validates the fish's practical use as a drone, allowing for inspecting the aquatic environment that is not easily accessible to humans. Future work studies the operation of the robotic fish as a collective swarm to examine a broader range of the underwater area and conduct various strategic missions.

关键词： biomimetics locomotion pneumatic actuators soft robots thermoelectric devices untethered electronics

来源：评论

学校读者我要写书评

暂无评论

A Review on On Device Privacy and Machine Learning Training 2

A Review on On Device Privacy and Machine Learning Training

引用

2nd IEEE International Conference on Artificial Intelligence in Everything, AIE 2022

作者： Tonga, Paul Audu Ameen, Zubaida Said Mubarak, Auwalu Saleh Al-Turjman, Fadi Ai and Robotics Institute Near East University Research Center for Ai and IoT Artificial Intelligence Dept Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Cyprus

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

On device machine learning has in recent times attracted growing attention and applications, ranging from advanced OCR and handwriting recognition, smart sleep tracking in Apple iOS, mobile virtual assistants and Image recognition, text translation in android;and more. As a result, there is increasing demand for user privacy and security in machine learning applications. Federated Learning (FL), a new method, allows users to cooperatively train a global model while keeping the data local, thereby resolving the issue of data privacy protection through the encryption mechanism. The server aggregates models until convergence while the clients train their local models. In this procedure, the server employs a reward system to persuade users to provide huge amounts of high-quality data in order to enhance the overall model. This paper explores a few FL techniques that can be applied alongside on-device learning, in order to achieve better privacy and security. © 2022 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Design and Development of the Dual-Arm Robot DARO

Design and Development of the Dual-Arm Robot DARO

引用

WRC Symposium on Advanced robotics and Automation (WRC SARA)

作者： Yun Liu Qiulang Huang Pu Zhang Mindong Yan Dingkun Liang Lingyu Kong Xin Wang Anhuan Xie Jason Gu Shiqiang Zhu Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Electrical and Computer Engineering Dalhousie University Halifax NS Canada

This paper presents the design and development of a humanoid dual-arm robot called DARO, along with its improved version, DARO-N. DARO and DARO-N consist of two arms and humanoid hands, each with 6/7 degrees of freedom for the arms and 7 active degrees of freedom for the hands. Modular commercial actuators are employed as the driving joints of the arms, allowing for reduced development time and cost. The design principles of modularity, simplicity, lightweight construction, human likeness, information perception capability, and scalability are incorporated into the design. Furthermore, this work establishes a control framework for the humanoid dual-arm robot and conducts simulations and multiple physical experiments to validate the performance of the robots.

关键词：

来源：评论

学校读者我要写书评

暂无评论

HawkDrive: A Transformer-driven Visual Perception System for Autonomous Driving in Night Scene

HawkDrive: A Transformer-driven Visual Perception System for...

引用

IEEE Symposium on Intelligent Vehicle

作者： Ziang Guo Stepan Perminov Mikhail Konenkov Dzmitry Tsetserukou Intelligent Space Robotics Laboratory Center for Digital Engineering Skolkovo Institute of Science and Technology Moscow Russia LLC IntegraNT Moscow Russia

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

Many established vision perception systems for autonomous driving scenarios ignore the influence of light conditions, one of the key elements for driving safety. To address this problem, we present HawkDrive, a novel perception system with hardware and software solutions. Hardware that utilizes stereo vision perception, which has been demonstrated to be a more reliable way of estimating depth information than monocular vision, is partnered with the edge computing device Nvidia Jetson Xavier AGX. Our software for low light enhancement, depth estimation, and semantic segmentation tasks, is a transformer-based neural network. Our software stack, which enables fast inference and noise reduction, is packaged into system modules in Robot Operating System 2 (ROS2). Our experimental results have shown that the proposed end-to-end system is effective in improving the depth estimation and semantic segmentation performance. Our dataset and codes will be released at https://***/ZionGo6/HawkDrive.

关键词： Semantic segmentation Estimation Cameras Transformers Hardware Software Stereo vision

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：