A5102792802- Transition Metal Oxide Nanomaterials
- Solar-Powered Water Purification Methods
- Supercapacitor Materials and Fabrication
- Adversarial Robustness in Machine Learning
- Millimeter-Wave Propagation and Modeling
- Ferroelectric and Negative Capacitance Devices
- Thermal Radiation and Cooling Technologies
- Advanced Memory and Neural Computing
- Advanced MIMO Systems Optimization
- Anomaly Detection Techniques and Applications
- Explainable Artificial Intelligence (XAI)
- Traffic Prediction and Management Techniques
- Advanced battery technologies research
- Advancements in Battery Materials
- Reinforcement Learning in Robotics
- Microwave Engineering and Waveguides
- Advanced Sensor and Energy Harvesting Materials
- Radiative Heat Transfer Studies
- Nanoparticle-Based Drug Delivery
- Urban Heat Island Mitigation
- Membrane Separation Technologies
- Machine Learning and ELM
- Luminescence and Fluorescent Materials
- Forensic Fingerprint Detection Methods
- Data Management and Algorithms
Shandong Jianzhu University
2025
Nanjing University
2025
Wayne State University
2022-2024
Hainan University
2024
South China University of Technology
2023
Huazhong University of Science and Technology
2022-2023
Wuhan Textile University
2023
Hunan University of Science and Technology
2023
Monash University
2017-2023
Nanjing Tech University
2023
Photochromic materials have been extensively studied because they are quite attractive and promising for many applications.
Manufacturing abrasion-resistant superhydrophobic matters is challenging due to the fragile feature of introduced micro-/nanoscale surface roughness. Besides long-term durability, large scale at meter level, and 3D complex structures are great importance for objects used across diverse industries. Here it shown that abrasion-resistant, half-a-meter scaled can be one-step realized by selective laser sintering (SLS) printing technology using hydrophobic-fumed-silica (HFS)/polymer composite...
There is great attention to develop hardware accelerator with better energy efficiency, as well throughput, than GPUs for convolutional neural network (CNN). The existing solutions have relatively limited parallelism large power consumption (including leakage power). In this paper, we present a resistive random access memory (ReRAM)-accelerated CNN that can achieve significantly higher throughput and efficiency when the trained binary constraints on both weights activations, further mapped...
Albumin-based hydrogels have emerged as promising nanoparticle systems for the effective delivery of hydrophobic anticancer drugs. Anti-cancer drugs often cause some adverse effects, such toxicity and rapid clearance by mononuclear phagocytic systems. Herein, a new strategy synthesizing N-hydroxysuccinimide (NHS)-activated linker to form crosslinkable albumin-based (CABH) is reported. The CABH favored physiochemical characteristics improvement doxorubicin (Dox) drug release. was constructed...
The recently emerging resistive random-access memory (RRAM) can provide nonvolatile storage but also intrinsic computing for matrix-vector multiplication, which is ideal the low-power and high-throughput data analytics accelerator performed in memory. However, existing RRAM crossbar--based mainly assumed as a multilevel analog computing, whose result sensitive to process nonuniformity well additional overhead from AD-conversion I/O. In this article, we explore multiplication on binary...
In an intelligent transportation system, the key problem of traffic forecasting is how to extract periodic temporal dependencies and complex spatial correlations. Current state-of-the-art methods for predicting flow are based on graph architectures sequence learning models, but they do not fully exploit dynamic spatial-temporal information in system. Specifically, short-range diluted by recurrent neural networks. Moreover, local also ignored existing because their convolution operation uses...
Cross-sea cable-stayed bridges encounter challenges associated with cable corrosion and cable-force relaxation during their service life, which significantly affects structural performance seismic response. This study focuses on a cross-sea bridge located in Hainan Province. Utilizing an LSTM deep learning model, this aims to fill the gaps short-term cable-monitoring data from past year using available cable-force-monitoring same period. The authors of interpolated absence sensors employed...
While achieving tremendous success in various fields, existing multi-agent reinforcement learning (MARL) with a black-box neural network makes decisions an opaque manner that hinders humans from understanding the learned knowledge and how input observations influence decisions. In contrast, interpretable approaches usually suffer weak expressivity low performance. To bridge this gap, we propose MIXing Recurrent soft decision Trees (MIXRTs), novel architecture can represent explicit processes...
As one of the most important urban public spaces, design and management streets have shifted from “two-dimensional plan” to “three-dimensional space”, higher requirements been put forward for scale precision design. The core research question this is how refine street spatial quality measurement evaluation based on multitemporal view images, while providing basic data corresponding decision support updates renovations. “One Garden Twelve Fangs” in Jinan old city area Commercial Port...
Abstract Outdoor heat stress can cause health hazards for workers and reduce labor productivity, thus leading to an annual burden of US $6.2 billion the Australian workforce. Because outdoor temperature fluctuates within a day, self‐regulating textiles are urgently needed keep human body stable. Smart able sense their surrounding environment respond by adapting behaviors accordingly. However, there number challenges in utilizing functional materials achieve smart thermal radiation management...
Convolutional neural network (CNN) based machine learning requires a highly parallel as well low power consumption (including leakage power) hardware accelerator. In this paper, we will present digital ReRAM crossbar CNN accelerator that can achieve significantly higher throughput and lower than state-of-arts. The is trained with binary constraints on both weights activations such all operations become bitwise. With further use of 1-bit comparator, the bitwise model be naturally realized...
Four types of flowerlike manganese dioxide in nano scale was synthesized via a liquid phase method KMnO 4 -H 2 SO solution and Cu particles, wherein the effect particles investigated detail. The obtained powder characterized by XRD, SEM TEM, supercapacity properties MnO electrode materials were measured. results showed that doping carbon black can benefit to better dispersion copper resulting generated smaller size morphology nanoparticles dominated particles. study synthesis different...
Abstract Electrochemical degradation is a commonly used strategy to remove organic contaminations in water. However, some remote areas where electricity insufficient, electrochemical may become ineffective due the absence of power supply. Here, unique self‐powered system (SPES) proposed accomplish power‐free tetracyclines (TCs) and dyes water with assistance flexible magnetoelectric flag generators (MFGs). These MFGs convert wind energy into electricity. Under speed 6.3 m s −1 , 22 × 30 cm 2...
A major challenge to implement the compressed sensing method for channel state information (CSI) acquisition lies in design of a well-performed measurement matrix reduce dimension sparse vectors. The widely adopted randomized matrices drawn from Gaussian or Bernoulli distribution are not optimal. To tackle this problem, we propose fully data-driven approach optimize beamspace compression, and trains mathematically interpretable autoencoder constructed according iterative solution recovery....
Future data-oriented computing requires intensive memory access with burden of I/O interconnection. Traditional wired interconnect has limited bandwidth and energy-efficiency no feature configurability. This paper introduces an adaptive sub-THz wireless between cores main (DRAMs) using MIMO beamforming. To satisfy the requirement energy efficiency latency, a configuration problem for channel management at controller is formulated to find optimal value beamforming matrix. A low latency...
Abstract Manganese dioxide (MnO 2 ) has been extensively investigated as an electrode material for supercapacitors because of its high theoretical capacitance, great abundance, and low toxicity. To obtain satisfactory capacitance performance, in recent years, many efforts have dedicated to the fabrication MnO nanoparticles that offer a larger specific surface area escalated chemical activity. Beyond them, ideal dispersibility liquid medium is also vital importance when processing those...
Indoor positioning technology is vital for various location-aware applications while visible light (VLP) especially promising due to its ubiquitous and energy-efficient features. VLP has been widely investigated under the assumption of line sight (LoS), yet, signal blockage can happen frequently in a practical indoor environment brings about outage problems localization/tracking services. However, this problem usually overlooked or sidestepped existing works. Our work, first time,...
Taxi arrival time prediction is essential for building intelligent transportation systems. Traditional methods mainly rely on extracting features from traffic maps, which cannot model complex situations and nonlinear spatial temporal relationships. Therefore, we propose Multi-View Spatial-Temporal Model (MVSTM) to capture the mutual dependence of spatial-temporal relations trajectory features. Specifically, use graph2vec view, dual-channel module structural embedding semantics. Experiments...
The future robots are expected to work in a shared physical space with humans [1]; however, the presence of leads dynamic environment that is challenging for mobile navigate. Due lack simulation frameworks, path planning algorithms designed navigate collision-free complex human environments often tested real environments. This paper identifies critical requirements an ideal simulator this task, evaluates existing and, most importantly, challenges and limitations techniques. First foremost,...
While achieving tremendous success in various fields, existing multi-agent reinforcement learning (MARL) with a black-box neural network architecture makes decisions an opaque manner that hinders humans from understanding the learned knowledge and how input observations influence decisions. Instead, interpretable approaches, such as traditional linear models decision trees, usually suffer weak expressivity low accuracy. To address this apparent dichotomy between performance interpretability,...
Recent advancements in solving large-scale traveling salesman problems (TSP) utilize the heatmap-guided Monte Carlo tree search (MCTS) paradigm, where machine learning (ML) models generate heatmaps, indicating probability distribution of each edge being part optimal solution, to guide MCTS solution finding. However, our theoretical and experimental analysis raises doubts about effectiveness ML-based heatmap generation. In support this, we demonstrate that a simple baseline method can...