Data-based detection and quantification of causation in complex,nonlinear dynamical systems is of paramount importance to science,engineering,and *** by the widely used methodology in recent years,the cross-map-based ...
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Data-based detection and quantification of causation in complex,nonlinear dynamical systems is of paramount importance to science,engineering,and *** by the widely used methodology in recent years,the cross-map-based techniques,we develop a general framework to advance towards a comprehensive understanding of dynamical causal mechanisms,which is consistent with the natural interpretation of *** particular,instead of measuring the smoothness of the cross-map as conventionally implemented,we define causation through measuring the scaling law for the continuity of the investigated dynamical system *** uncovered scaling law enables accurate,reliable,and eficient detection of causation and assessment of its strength in general complex dynamical systems,outperforming those existing representative *** continuity scaling-based framework is rigorously established and demonstrated using datasets from model complex systems and the real world.
With the explosive 3D data growth, the urgency of utilizing zero-shot learning to facilitate data labeling becomes evident. Recently, methods transferring language or language-image pre-training models like Contrastiv...
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Handheld ultrasound devices face usage limitations due to user inexperience and cannot benefit from supervised deep learning without extensive expert annotations. Moreover, the models trained on standard ultrasound de...
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Text mining was used to examine the academic publications on blockchain technology and cybersecurity that were published in huge digital libraries. Automated text mining methods like topic modeling and key word extrac...
Text mining was used to examine the academic publications on blockchain technology and cybersecurity that were published in huge digital libraries. Automated text mining methods like topic modeling and key word extraction are utilized in this literature study to extract topics from a vast corpus of literature. This article emphasizes the cross-disciplinary character of blockchain technology in the context of cybersecurity. The outcomes also show the risks and security holes that emerge as blockchain technology matures. Nevertheless, the investigation this article also outlines research gaps in the area of computer security and recommends research directions for future work that will be necessary to create safe blockchain platforms.
Terahertz (THz) (0.1-10 THz) wireless communication is one of the cornerstones of the next 6G wireless networks. THz frequencies have the ability to dramatically increase wireless capacity performance and enable high-...
Terahertz (THz) (0.1-10 THz) wireless communication is one of the cornerstones of the next 6G wireless networks. THz frequencies have the ability to dramatically increase wireless capacity performance and enable high-resolution environment sensing if applied properly due to the enormous quantity of accessible bandwidth. However, the usage of wireless devices in high-frequency bands like THz is constrained by a very unpredictable and dynamic channel. The ultimate result is essentially unreliable intermittent connections since these channel constraints have a naturally restricted communication range and a high susceptibility to blocking and chemical absorption. Because of this, the THz band's potential for high-rate communications and high-resolution sensing may be hindered. This study thoroughly examines the steps necessary to build up and operate next-generation THz wireless networks that will work together to deliver a variety of communication and sensing services in this environment. We first lay the groundwork for this by defining the THz frequency range's fundamentals. Using these fundamentals as a foundation, we outline and carefully investigate seven specific qualities that characterize THz wireless systems: Some of the subjects discussed include the quasi-opticality of the band, wireless architectures suited for THz, synergy with lower frequency bands, cooperative sensing and communication systems, PHY-layer protocols, spectrum access techniques, and real-time network optimization. These seven distinctive features enable our understanding of how to re-engineer wireless systems as we know them today to fit THz bands and their specific settings. On the one hand, THz systems make use of its quasi-optimality and may turn any sensing opportunity into a communication problem, aiding in the development of a new breed of flexible wireless systems that can do many jobs beyond straightforward communications. THz systems can alternatively use intelligent surfaces, lower
Mobile Edge Computing (MEC) provides users with low-latency, highly responsive services by deploying Edge Servers (ESs) near applications. MEC allows any edge-hosted application or service to be migrated between diffe...
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Transformer architectures have become the model of choice in natural language processing and are now being introduced into computervision tasks such as image classification, object detection, and semantic segmentatio...
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This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either complete scene specifications or extrins...
This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either complete scene specifications or extrinsic sensor measurements, e.g., cameras, that occasionally suffer from occlusions. We propose a novel approach for stable object placing that combines tactile feedback and proprioceptive sensing. We devise a neural architecture called PlaceNet that estimates a rotation matrix, resulting in a corrective gripper movement that aligns the object with the placing surface for the subsequent object manipulation. We compare models with different sensing modalities, such as force-torque, an external motion capture system, and two classical baseline models in real-world object placing tasks with different objects. The experimental evaluation of our placing policies with a set of unseen everyday objects reveals significant generalization of our proposed pipeline, suggesting that tactile sensing plays a vital role in the intrinsic understanding of robotic dexterous object manipulation. Code, models, and supplementary videos are available on https://***/view/placing-by-touching.
Culverts, essential components of drainage systems, require regular inspection to ensure optimal functionality. However, culvert inspections pose numerous challenges, including accessibility, manpower, defect localiza...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
Culverts, essential components of drainage systems, require regular inspection to ensure optimal functionality. However, culvert inspections pose numerous challenges, including accessibility, manpower, defect localization, and reliance on superficial assessments. To address these challenges, we propose a novel Culvert Autonomous Inspection Robotic System (CAIS) equipped with advanced sensing and evaluation capabilities. Our solution integrates an RGBD camera, deep learning, lighting systems, and non-destructive evaluation (NDE) techniques to enable accurate and comprehensive condition assessments. We present a pioneering Partially Observable Markov Decision Process (POMDP) framework to resolve uncertainty in autonomous inspections, especially in confined and unstructured environments like culverts or tunnels. The framework outputs detailed 3D maps highlighting visual defects and NDE condition assessments, demonstrating consistent and reliable performance in both indoor and outdoor scenarios. Additionally, we provide an open-source implementation of our framework on GitHub, contributing to the advancement of autonomous inspection technology and fostering collaboration within the research community. Source codes are available
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Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potent...
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