检索结果-内蒙古大学图书馆

1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Chaudhary, Preeti Yadav, Satya Prakash Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Nicosia Artificial Intelligence Engineering Dept. Mersin10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty OfEngineering Kyrenia Mersin10 Turkey Graphic Era Hill University Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

In a nutshell, the IoT refers to the idea of integrating high-tech technology in the form of "smart"gadgets and sensors into a single setting to gather data. There are still numerous areas in which machines cannot compete favorably with people, but data collection and analysis are undeniably two of their strongest points. The Internet of Things makes it possible to fully or partially automation data, it involves related activities, which is obviously very important for the healthcare industry. What exactly is the Internet connected medical things, and how exactly might it make a significant impact on the sector? By having to apply the concept of the internet of things (IoT) to the field of medicine, several significant advancements have become possible, including the ability to automatically control the thermostat of containers while transmitting inoculations and antibiotics, the accurate tracking of the ailments of a lot of illnesses without a need for additional meetings with a general practitioner, the correct and most useful use of meds, and a great deal more. All of this is realizable because of the capability of MedTech gadgets to carry out continuous monitoring system. The potential applications of internet of things technology in healthcare are very interesting. Let's review the ways in which this technology. © 2023 IEEE.

关键词： Medical applications

来源：评论

学校读者我要写书评

暂无评论

Wireless Sensor Networks and Green Networking for 6G communication- An Overview 1

Wireless Sensor Networks and Green Networking for 6G communi...

引用

1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Bordoloi, Dibyahash Yadav, Satya Prakash Near East University Ai and Robotics Institute Research Center for Ai and IoT Department of Computer Engineering Nicosia Turkey Near East University Ai and Robotics Institute Artificial Intelligence Engineering Dept. Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Turkey Graphic Era Hill University Dehradun Rs Cse Graphic Era University Dept. of Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

Wireless sensor networks and green networking have been major research areas in the field of communication technology for the past few decades. In particular, the development of 6G communication systems has brought renewed focus on these areas, as the demands for higher data rates, more diverse applications, and lower energy consumption continue to increase. The use of wireless sensor networks in 6G communication systems has been widely explored in the literature, and has shown great potential for a wide range of applications, including environmental monitoring, industrial process control, and healthcare. However, a key challenge in the deployment of these networks is ensuring their energy efficiency, as the demands on the network will be much higher than in previous generations. To address this challenge, researchers have proposed various green networking techniques, such as energy harvesting and low-power communication protocols, which have been shown to significantly reduce the energy consumption of the sensors. In addition to improving the energy efficiency of wireless sensor networks, researchers have also studied their reliability, scalability, and adaptability. These properties are important in 6G communication systems, as the demands on the network are expected to be much higher than in previous generations. Researchers have proposed various methods to improve the reliability, scalability, and adaptability of wireless sensor networks, including the use of error-correction codes, redundant communication channels, and machine learning algorithms. © 2023 IEEE.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

InteLiPlan: An Interactive Lightweight LLM-Based Planner for Domestic Robot Autonomy

arXiv

引用

arXiv 2024年

作者： Ly, Kim Tien Lu, Kai Havoutis, Ioannis Oxford Robotics Institute University of Oxford United Kingdom Department of Computer Science University of Oxford United Kingdom

We introduce an interactive LLM-based framework designed to enhance the autonomy and robustness of domestic robots, targeting embodied intelligence. Our approach reduces reliance on large-scale data and incorporates a robot-agnostic pipeline that embodies an LLM. Our framework, InteLiPlan, ensures that the LLM’s decision-making capabilities are effectively aligned with robotic functions, enhancing operational robustness and adaptability, while our human-in-the-loop mechanism allows for real-time human intervention when user instruction is required. We evaluate our method in both simulation and on the real Toyota Human Support Robot (HSR). Our method achieves a 93% success rate in the ‘fetch me’ task completion with failure recovery, highlighting its capability in both failure reasoning and task planning. InteLiPlan achieves comparable performance to state-of-the-art large-scale LLM-based robotics planners, while using only real-time onboard computing. More information about InteLiPlan can be found at the project website: https://***/InteLiPlan. Copyright © 2024, The Authors. All rights reserved.

关键词： Human robot interaction

来源：评论

学校读者我要写书评

暂无评论

Internet of Intelligent Things (IoT) - An Overview 1

Internet of Intelligent Things (IoT) - An Overview

引用

1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Aeri, Manisha Yadav, Satya Prakash Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin Nicosia10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Mersin10 Turkey Graphic Era Hill University Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

The basic goal of the IoT is to permit the online connection and communication of everyday physical objects like appliances, vehicles, and other gadgets. This paves the way for effortless and automated data collection and exchange, as well as interaction between the objects themselves and with humans. The Internet of Everything (IoE) is an expansion of the Internet of Things (IoT) that aims to maximize and improve human life by connecting and making the most of all available resources (humans, information, and technology). The transportation, healthcare, agricultural, energy, and manufacturing sectors are all examples. The IoIT aims to incorporate AI and ML within the IoT's interconnected network of physical items. These objects can then independently behave in response to the information they have gathered and the instructions they have been given. This has the potential to lead to smarter, more efficient systems that can react to new information and human input in real time. The Internet of Things, the Internet of Everything, and the Industrial Internet of Things all have the same overarching goal: to pave the way for the development of more efficient and intelligent systems and processes that can enhance a wide range of human endeavors. However, in order to make sure that these technologies are used in a responsible and ethical way, it will be necessary to carefully analyze their consequences and the issues they provide. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Multiview Compounding for Linear Array-Based 3D Photoacoustic Imaging

Multiview Compounding for Linear Array-Based 3D Photoacousti...

引用

Photons Plus Ultrasound: Imaging and Sensing 2023

作者： Garje, Yash Tang, Yichuan Jaupi, Enxhi Zhang, Haichong K. Robotics Engineering Department Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States Biomedical Engineering Department Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States Computer Science Department Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States

ISBN: (纸本)9781510658639

Two-dimensional and three-dimensional photoacoustic (PA) visualization is an emerging diagnostic procedure for investigation and research in vascular studies. Current manual/mechanized target scanning techniques involve sweeping the target along the elevation to generate 3D visuals. However, since the linear array probes exhibit poor resolution along the direction orthogonal to its focal plane, these techniques are prone to miss out on the organic structures parallel to the lateral direction. This could result in a misrepresentation of the target and is a critical shortfall of the method. We propose a multiview scanning and compounding technique to overcome the directionality bias and obtain more accurate and isotropic imaging performance. Using electromechanical translatory and rotary stages for multiview data acquisition, we generate a unified 3D visualization. A data processing pipeline illustrates an axial implementation of the Hilbert transform followed by spatial integration of the volumetric data to obtain the output. A 6-directional scanning approach improves the completeness of the structural details. We validated the technique using sub-millimeter-sized balls and wire phantoms. We first observed an enhanced resemblance of the outcome with the actual target in the ball phantom. Secondly, we observed imaging quality improvement with isotropic intensity distribution prominently in the wire phantom. A comparative analysis showed around a 50% reduction in the standard deviation of intensity distribution as compared to conventional unidirectional 3D PA imaging. © 2023 SPIE.

关键词： Phantoms

来源：评论

学校读者我要写书评

暂无评论

Information Elicitation from Decentralized Crowd Without Verification 21

Information Elicitation from Decentralized Crowd Without Ver...

引用

21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023

作者： Chen, Kexin Huang, Chao Huang, Jianwei The School of Science and Engineering The Chinese University of HongKong Shenzhen518172 China The Department of Computer Science The University of California Davis United States School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of HongKong Shenzhen518172 China

ISBN: (纸本)9783903176553

Information Elicitation Without Verification (IEWV) refers to the problem of eliciting high-accuracy solutions from crowd members when the ground truth is unverifiable. A high-accuracy team solution (aggregated from members’ solutions) requires members’ effort exertion, which should be incentivized properly. Previous research on IEWV mainly focused on scenarios where a central entity (e.g., the crowdsourcing platform) provides incentives to motivate crowd members. Still, the proposed designs do not apply to practical situations where no central entity exists. This paper studies the overlooked decentralized IEWV scenario, where crowd members act as both incentive contributors and task solvers. We model the interactions among members with heterogeneous team solution accuracy valuations as a two-stage game, where each member decides her incentive contribution strategy in Stage 1 and her effort exertion strategy in Stage 2. We analyze members’ equilibrium behaviors under three incentive allocation mechanisms: Equal Allocation (EA), Output Agreement (OA), and Shapley Value (SV). We show that at an equilibrium under any allocation mechanism, a low-valuation member exerts no more effort than a high-valuation member. Counter-intuitively, a low-valuation member provides incentives to the collaboration while a high-valuation member does not at an equilibrium under SV. This is because a high-valuation member who values the aggregated team solution more needs fewer incentives to exert effort. In addition, when members’ valuations are sufficiently heterogeneous, SV leads to team solution accuracy and social welfare no smaller than EA and OA. © 2023 IFIP.

关键词： Information dissemination

来源：评论

学校读者我要写书评

暂无评论

One-Shot Gesture Recognition for Underwater Diver-To-Robot Communication

arXiv

引用

arXiv 2025年

作者： Joshi, Rishikesh Sattar, Junaed Department of Computer Science and Engineering Minnesota Robotics Institute University of Minnesota – Twin Cities MinneapolisMN United States

Reliable human-robot communication is essential for effective underwater human-robot interaction (U-HRI), yet traditional methods such as acoustic signaling and predefined gesture-based models suffer from limitations in adaptability and robustness. In this work, we propose One-Shot Gesture Recognition (OSG), a novel method that enables real-time, pose-based, temporal gesture recognition underwater from a single demonstration, eliminating the need for extensive dataset collection or model retraining. OSG leverages shape-based classification techniques, including Hu moments, Zernike moments, and Fourier descriptors, to robustly recognize gestures in visually-challenging underwater environments. Our system achieves high accuracy on real-world underwater video data and operates efficiently on embedded hardware commonly found on autonomous underwater robots (AUVs), demonstrating its feasibility for deployment on-board robots. Compared to deep learning approaches, OSG is lightweight, computationally efficient, and highly adaptable, making it ideal for diver-to-robot communication. We evaluate OSG’s performance on an augmented gesture dataset and real-world underwater video data, comparing its accuracy against deep learning methods. Our results show OSG’s potential to enhance U-HRI by enabling the immediate deployment of user-defined gestures without the constraints of predefined gesture languages. Copyright © 2025, The Authors. All rights reserved.

关键词： Human robot interaction

来源：评论

学校读者我要写书评

暂无评论

Extremely Weak Feedback Method for Controlling Chaotic Resonance

Extremely Weak Feedback Method for Controlling Chaotic Reson...

引用

2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Iinuma, Takahiro Ebato, Yudai Nobukawa, Sou Tran, Anh Tu Wagatsuma, Nobuhiko Inagaki, Keiichiro Doho, Hirotaka Yamanishi, Teruya Nishimura, Haruhiko Graduate School of Information and Computer Science Chiba Institute of Technology Chiba Japan Chiba Institute of Technology Department of Computer Science Japan Toho University Faculty of Science Department of Information Science Chiba Japan Chubu University Department of Artificial Intelligence and Robotics Aichi Japan Kouchi University Faculty of Education Teacher Training Division Kochi Japan Osaka Seikei University Faculty of Data Science Osaka Japan Yamato University Faculty of Informatics Osaka Japan

ISBN: (纸本)9798350337020

Chaotic resonance, resembling stochastic resonance, is induced by internal fluctuations (i.e., chaos). This phenomenon has been observed in numerous systems. The most representative form of chaotic resonance is the synchronization with respect to weak applied signals under chaos-chaos intermittency, where a chaotic orbit moves among multiple attractors. Chaotic resonance exhibits higher sensitivity than stochastic resonance, but its engineering applications are limited by concerns such as the requirement to adjust the state of chaos by internal system parameters to induce chaotic resonance rather than the external noise strength. However, achieving this adjustment is challenging, especially in biological systems. Therefore, to handle this limitation, we proposed a novel double-Gaussian-filtered reduced region of orbit (RRO) method (called the DG-RRO method) for obtaining perturbed feedback signals lower than the conventional RRO method. This DG-RRO feedback signal is determined by the inverse sign of the map function and double-Gaussian filters around the local maximum/minimum values of the map. Because of its fine local specification, the DG-RRO feedback signal induces a chaotic resonance by one-third the feedback strength of the conventional signal. This method may pave the way for using chaotic resonance in engineering applications. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Autonomous robotic re-alignment for face-to-face underwater human-robot interaction*

Autonomous robotic re-alignment for face-to-face underwater ...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Demetrious T. Kutzke Ashwin Wariar Junaed Sattar Department of Computer Science & Engineering Minnesota Robotics Institute University of Minnesota–Twin Cities Minneapolis MN USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The use of autonomous underwater vehicles (AUVs) to accomplish traditionally challenging and dangerous tasks has proliferated thanks to advances in sensing, navigation, manipulation, and on-board computing technologies. Utilizing AUVs in underwater human-robot interaction (UHRI) has witnessed comparatively smaller levels of growth due to limitations in bi-directional communication and significant technical hurdles to bridge the gap between analogies with terrestrial interaction strategies and those that are possible in the underwater domain. A necessary component to support UHRI is establishing a system for safe robotic-diver approach to establish face-to-face communication that considers nonstandard human body pose. In this work, we introduce a stereo vision system for enhancing UHRI that utilizes threedimensional reconstruction from stereo image pairs and machine learning for localizing human joint estimates. We then establish a convention for a coordinate system that encodes the direction the human is facing with respect to the camera coordinate frame. This allows automatic setpoint computation that preserves human body scale and can be used as input to an image-based visual servo control scheme. We show that our setpoint computations tend to agree both quantitatively and qualitatively with experimental setpoint baselines. The methodology introduced shows promise for enhancing UHRI by improving robotic perception of human orientation underwater.

关键词： Visualization Navigation Robot kinematics Human-robot interaction Machine learning Robot sensing systems Stereo vision

来源：评论

学校读者我要写书评

暂无评论

A Scalable Real-time Semantic Segmentation Network for Autonomous Driving 1

A Scalable Real-time Semantic Segmentation Network for Auton...

引用

1st Workshop on Advanced Multimedia Computing for Smart Manufacturing and Engineering, AMC-SME 2023

作者： Liu, Jun Wu, Chao Yuan, Geng Niu, Wei Zhang, Wenbin Song, Houbing Herbert Robotics Institute of School of Computer Science Carnegie Mellon University Pittsburgh United States Department of Electrical & Computer Engineering Northeastern University Boston United States School of Computing University of Georgia Athens United States Department of Computer Science Michigan Technological University Houghton United States Department of Information Systems University of Maryland Baltimore County Baltimore United States

ISBN: (纸本)9798400702730

Computational resources are limited on real-time embedded devices, so the available computing cost of deployment on the target platform must be considered. We develop a feature extraction module based on the MobileNet backbone that can be adjusted in terms of computational complexity and capacity using the depth multiplier parameter, classifier depth, and kernel depth. These three parameters allow us to control the count of channels within the network, effectively managing the model's capacity and computational requirements. To achieve semantic segmentation, we incorporate additional components, such as an extension module. This extension module typically includes 1x1 pointwise convolutional layers for pixel-level classification and a transposed convolutional layer for upsampling the output to the original input image size. By combining the feature extraction module with this extension module, we can create a complete architecture capable of performing semantic segmentation tasks. The feature extraction module provides the initial feature extraction and the extension module adds the necessary components for accurate pixel-wise classification and upsampling. Compared to Hardware-aware Neural Architecture Search (NAS), pruning, runtime pruning, and knowledge distillation methods, our model has several advantages in terms of modular design, structural controllability, ease of implementation, and cost-effectiveness. Our computational efficiency, as measured by FLOPS, is highly competitive. Our method is distinguished by solving the problem of MobileNet's inability to adjust the size and number of convolution kernels. It achieves this through adaptable parameter tuning, including MobileNet's depth multiplier, the kernel size in the FCN head's Separable Convolution layer, and the depth of the first Point-wise Convolution layer. These adjustments are customized to match hardware's max multiply-accumulates (MACs), optimizing network capacity and maximizing resource utilizat

关键词： Feature extraction

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：