A5100768452- Parallel Computing and Optimization Techniques
- Embedded Systems Design Techniques
- Real-Time Systems Scheduling
- Robotics and Sensor-Based Localization
- Interconnection Networks and Systems
- Advanced Vision and Imaging
- Advanced Neural Network Applications
- Soft Robotics and Applications
- Robotic Path Planning Algorithms
- Retinal and Macular Surgery
- Advanced Memory and Neural Computing
- Distributed and Parallel Computing Systems
- Distributed systems and fault tolerance
- Reinforcement Learning in Robotics
- Intraocular Surgery and Lenses
- Autonomous Vehicle Technology and Safety
- Robotic Locomotion and Control
- Robot Manipulation and Learning
- Neuroscience and Neural Engineering
- User Authentication and Security Systems
- Remote Sensing and LiDAR Applications
- Neural dynamics and brain function
- Image Processing Techniques and Applications
- Spam and Phishing Detection
- Advanced Image and Video Retrieval Techniques
Sun Yat-sen University
2016-2025
Beijing University of Posts and Telecommunications
2021-2024
Harbin Institute of Technology
2024
Zhengzhou University
2024
Second Affiliated Hospital of Shantou University Medical College
2024
Shantou University
2023-2024
Zhejiang Province Institute of Architectural Design and Research
2013-2024
Zhejiang University
2014-2024
Central Hospital of Wuhan
2024
Aerospace Information Research Institute
2022-2024
We previously discovered that Xiaozhang Tie (XZT) was helpful for cirrhotic ascites, with obvious abdominal distention relief, suggesting it may improve gastrointestinal (GI) motility. However, the underlying mechanisms of GI motility in ascites are unclear. Here, we aimed to discover explored effect XZT on animal and probed action mechanism affecting by regulating SCF/c-kit pathway ICCs hormones. First, rat models were developed then divided randomly into following three subgroups: model...
Abstract Highly sensitive and humidity‐resistive detection of the most common physical stimuli is primary importance for practical application in real‐time monitoring. Here, a simple yet effective strategy reported to achieve highly humidity‐stable hybrid composite that enables simultaneous accurate pressure temperature sensing single sensor. The improved electronic performance due enhanced planarity poly (3,‐4ethylenedioxythiophene) (PEDOT) charge transfer between PEDOT:polystyrene...
Modern multiprocessor embedded systems execute a large number of tasks on shared processors and handle their complex communications communication networks. Traditional methods from the HW /SW codesign or general purpose computing domain cannot be applied any more to cope with this new class systems. To overcome problem, framework called Distributed Operation Layer (DOL) is proposed that enables efficient execution parallel applications platforms. Two main services are offered by DOL:...
Energy optimization is a critical design concern for embedded systems. Combining D VFS +D PM considered as one preferable technique to reduce energy consumption. There have been optimal algorithms periodic independent tasks running on uniprocessor in the literature. Optimal combination of and dependent multicore systems however not yet reported. The challenge this problem that idle intervals cores are easy model. In article, novel proposed directly model individual such both can be optimized...
Subretinal injection is a delicate and complex microsurgery. The main surgical difficulties come from the surgeon's hand tremor, dexterous motion, insufficient visual feedback. In order to begin addressing these challenges, this article presents robot system for subretinal insertion integrated with intraoperative optical coherence tomography (OCT). workflow using consists of two parts. first part manual control, which aims target before approaching retinal surface, while considering remote...
In recent years, the subject of deep reinforcement learning (DRL) has developed very rapidly, and is now applied in various fields, such as decision making control tasks. However, artificial agents trained with RL algorithms require great amounts training data, unlike humans that are able to learn new skills from few examples. The concept meta-reinforcement (meta-RL) been recently proposed enable similar but a small amount experience by leveraging set tasks shared structure. Due task...
Tactile perception systems as the medium between ambient environment and robotics lie in heart of modern artificial intelligence. By providing different electronic readouts under various circumstances, they can give easily captured information for post-processing. However, applications most reported tactile systems, external location assistances are still needed. Here, inspired by platypus' sixth sense, we developed a new kind system based on triboelectric sensors with additional function...
Learning-based methods have demonstrated clear advantages in controlling robot tasks, such as the information fusion abilities, strong robustness, and high accuracy. Meanwhile, on-board systems of robots limited computation energy resources, which are contradictory with state-of-the-art learning approaches. They either too lightweight to solve complex problems or heavyweight be used for mobile applications. On other hand, training spiking neural networks (SNNs) biological plausibility has...
Visual object tracking plays an essential role in various maritime applications. However, most of the existing methods belong to generative models, which only focus on features and require target has significant visual saliency for accurate tracking. While is available common conditions, these may fail when facing challenging situations. In this paper, a deep learning based method proposed track ships, namely, SiamFPN. SiamFPN, modified Siamese Network combined with multi-RPNs build...
Pedestrian detection has attracted enormous research attention in the field of Intelligent Transportation System (ITS) due to that pedestrians are most vulnerable traffic participants. So far, almost all pedestrian solutions based on conventional frame-based camera. However, they cannot perform very well scenarios with bad light condition and high-speed motion. In this work, a Dynamic Active Pixel Sensor (DAVIS), whose two channels concurrently output gray-scale frames asynchronous...
A key challenge for autonomous driving is to process a massive amount of sensor data and make safe reliable decisions in real time. However, vehicles often have insufficient onboard resources provide the required computation capacity. To address this problem, article advocates novel approach offload computation-intensive services roadside units cloud swift executions. Our combines an integer linear programming (ILP) formulation offline optimization scheduling strategy fast heuristics...
In this research, oat resistant starch (ORS) was prepared by autoclaving-retrogradation cycle (ORS-A), enzymatic hydrolysis (ORS-B), and ultrasound combined (ORS-C). Differences in their structural features, physicochemical properties digestive were studied. Results of particle size distribution, XRD, DSC, FTIR, SEM vitro digestion showed that ORS-C a B + C-crystal, had larger size, the smallest span value, highest relative crystallinity, most ordered stable double helix structure, roughest...
A flexible spine is critical to the motion capability of most animals and plays a pivotal role in their agility. Although state-of-the-art legged robots have already achieved very dynamic agile movement solely relying on legs, they still exhibit type stiff that compromises efficiency. The integration thus appears be promising approach improve agility, especially for small underactuated quadruped are underpowered because size limitations. Here, we show lateral flexion compliant can promote...
Detecting moving objects is of great importance for autonomous unmanned vehicle systems, and a challenging task especially in complex dynamic environments. This paper proposes novel approach the detection estimation their motion states using consecutive stereo image pairs on mobile platforms. First, we use variant semi-global matching algorithm to compute initial disparity maps. Second, assisted by disparities, boundaries segmentation produced simple linear iterative clustering are...
Snake-like robots with 3D locomotion ability have significant advantages of adaptive travelling in diverse complex terrain over traditional legged or wheeled mobile robots. Despite numerous developed gaits, these snake-like suffer from unsmooth gait transitions by changing the speed, direction, and body shape, which would potentially cause undesired movement abnormal torque. Hence, there exists a knowledge gap for to achieve autonomous locomotion. To address this problem, paper presents...
Visual SLAM in low illumination scenes remains a considerably challenging task since the available amount of appearance information frequently stays insufficient. To tackle with this problem, we propose novel framework by using both and thermal information, which possesses illumination-free recognizable contents, flexible manner. The key idea is to continuously update RGB-T map, contains RGB map points implement location mapping. More specifically, our system, detect features images combine...
With rapid development in UAV technologies, it is now possible to reconstruct large-scale outdoor scenes using only images captured by low-cost drones. The problem, however, becomes how plan the aerial path for a drone capture so that two conflicting goals are optimized: maximizing reconstruction quality and minimizing mid-air image acquisition effort. Existing approaches either resort pre-defined dense thus inefficient view sampling strategy, or adaptively but require onsite flight passes...
In recent decades, unmanned aerial vehicles (UAVs) have developed rapidly and been widely applied in many domains, including photography, reconstruction, monitoring, search rescue. such applications, one key issue is path view planning, which tells UAVs exactly where to fly how search. With specific consideration for three popular UAV applications (scene environment exploration, cinematography), we present a survey that should assist researchers positioning evaluating their works the context...
A challenge of chronic diseases that remains to be solved is how liberate patients and medical resources from the burdens long-term monitoring periodic visits. Precise management based on artificial intelligence (AI) holds great promise; however, a clinical application fully integrates prediction telehealth computing has not been achieved, further efforts are required validate its real-world benefits. Taking congenital cataract as representative, we used Bayesian deep-learning algorithms...