The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integratin...
The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.
Analog layout design heavily involves interactive processes between humans and design tools. Electronic Design automation (EDA) tools for this task are usually designed to use scripting commands or visualized buttons ...
详细信息
This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teach...
详细信息
ISBN:
(数字)9798331521950
ISBN:
(纸本)9798331521967
This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints.
Swarm robotics has garnered significant attention due to its ability to accomplish elaborate and synchronized tasks. Existing methodologies for motion planning of swarm robotic systems mainly encounter difficulties in...
详细信息
Using the wireless waveform superposition property, over-the-air computation (OAC) enables federated learning (FL) to achieve fast model aggregation. However, this computing paradigm is vulnerable to poisoning attacks...
Using the wireless waveform superposition property, over-the-air computation (OAC) enables federated learning (FL) to achieve fast model aggregation. However, this computing paradigm is vulnerable to poisoning attacks due to the openness of a wireless channel over time, where malicious mobile devices can introduce cumulative errors for the global FL model in a time-varying wireless environment for each communication round. This article presents a trust online OAC (TO-OAC) scheme to minimize impacts on the global model introduced by malicious devices adjusting to dynamic attack and wireless channel fluctuations over time. TO-OAC achieves this by utilizing trustworthy security quantification of OAC for each FL training round. To optimize the cumulative training loss at the aggregation node with the long-term power and trust constraints of mobile devices, we propose a joint trust, power, and channel-aware algorithm to flexibly update local and global models in response to the dynamic changes in the wireless and secure environment. We analyze the performance limits for the aggregation of trust models, considering metrics for computation and communication through time. We then propose another trust online regularization over-the-air computation (TOR-OAC) as an improved version of the TO-OAC scheme to decrease convergence time while ensuring long-term trust and power limitation. Experimental results performed on real-life datasets show that the two proposed schemes (TO-OAC and TOR-OAC) outperform prior works, especially in noisy, time-varying wireless channels and malicious attacks. 2002-2012 IEEE.
The utilization of visual sensors for three-dimensional (3D) reconstruction of continuum manipulators is a well-established technique, offering essential support for precise control and accurate state estimation. This...
详细信息
ISBN:
(数字)9798350389807
ISBN:
(纸本)9798350389814
The utilization of visual sensors for three-dimensional (3D) reconstruction of continuum manipulators is a well-established technique, offering essential support for precise control and accurate state estimation. This approach has been widely adopted across various fields, including surgical robotics, bionic systems, and industrial automation. However, the effectiveness of visual sensors is substantially constrained in environments characterized by occlusions or spatial limitations, where accurate reconstruction becomes challenging. To overcome these limitations, we propose an advanced 3D reconstruction method leveraging X-ray imaging, enabling robust shape reconstruction and automated tracking of continuum manipulators, even under occluded conditions. In the X-ray-based 3D shape reconstruction method, the intrinsic and extrinsic parameters of the computed tomography (CT) device are calibrated. Besides, the X-ray images are processed with identification and segmentation, centerline detection and Bézier curve fitting. Finally, the 3D shapes of a continuum manipulator are accomplished by matching the two images acquired from two distinct CT device rotation angles and reconstruction. The measurement experiment has demonstrated the accuracy of 3D shape reconstruction achieved 0.5383 mm. The shape reconstruction experimental results also showed the effectiveness of the X-ray-based 3D shape reconstruction method.
Brain-computer interfaces(BCIs),invasive or non-invasive,have projected unparalleled vision and promise for assisting patients in need to better their interaction with the *** by the BCI-based rehabilitation technolog...
详细信息
Brain-computer interfaces(BCIs),invasive or non-invasive,have projected unparalleled vision and promise for assisting patients in need to better their interaction with the *** by the BCI-based rehabilitation technologies for nerve-system impairments and amputation,we propose an electromagnetic brain-computer-metasurface(EBCM)paradigm,regulated by human’s cognition by brain signals directly and *** experimentally show that our EBCM platform can translate human’s mind from evoked potentials of P300-based electroencephalography to digital coding information in the electromagnetic domain non-invasively,which can be further processed and transported by an information metasurface in automated and wireless *** wireless communications of the human minds are performed between two EBCM operators with accurate text ***,several other proof-of-concept mind-control schemes are presented using the same EBCM platform,exhibiting flexibly-customized capabilities of information processing and synthesis like visual-beam scanning,wave modulations,and pattern encoding.
This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teach...
详细信息
Complex structural variants(CSVs) are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural ***,detecting the compounded mutational signals of C...
详细信息
Complex structural variants(CSVs) are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural ***,detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match *** a result,there has been limited progress for CSV discovery compared with simple structural ***,we systematically analyzed the multi-breakpoint connection feature of CSVs,and proposed Mako,utilizing a bottom-up guided model-free strategy,to detect CSVs from paired-end short-read ***,we implemented a graph-based pattern growth approach,where the graph depicts potential breakpoint connections,and pattern growth enables CSV detection without pre-defined *** evaluations on both simulated and real datasets revealed that Mako outperformed other ***,validation rates of CSVs on real data based on experimental and computational validations as well as manual inspections are around 70%,where the medians of experimental and computational breakpoint shift are 13 bp and 26 bp,***,the Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types,including two novel types of adjacent segment swap and tandem dispersed *** analysis of these CSVs also revealed the impact of sequence homology on the formation of *** is publicly available at https://***/xjtu-omics/Mako.
The paper introduces a novel framework for safe and autonomous aerial physical interaction in industrial settings. It comprises two main components: a neural network-based target detection system enhanced with edge co...
详细信息
ISBN:
(数字)9798350357882
ISBN:
(纸本)9798350357899
The paper introduces a novel framework for safe and autonomous aerial physical interaction in industrial settings. It comprises two main components: a neural network-based target detection system enhanced with edge computing for reduced onboard computational load, and a control barrier function (CBF)-based controller for safe and precise maneuvering. The target detection system is trained on a dataset under challenging visual conditions and evaluated for accuracy across various unseen data with changing lighting conditions. Depth features are utilized for target pose estimation, with the entire detection framework offloaded into low-latency edge computing. The CBF-based controller enables the UAV to converge safely to the target for precise contact. Simulated evaluations of both the controller and target detection are presented, alongside an analysis of real-world detection performance.
暂无评论