A5025337794- Adversarial Robustness in Machine Learning
- Advanced Wireless Communication Techniques
- Precipitation Measurement and Analysis
- Anomaly Detection Techniques and Applications
- Wireless Communication Security Techniques
- Radio Wave Propagation Studies
- Wireless Communication Networks Research
- Advanced Neural Network Applications
- Energy Harvesting in Wireless Networks
- Advanced MIMO Systems Optimization
- Cooperative Communication and Network Coding
- Distributed Sensor Networks and Detection Algorithms
- Phonetics and Phonology Research
- Wireless Body Area Networks
- Explainable Artificial Intelligence (XAI)
- Energy Efficient Wireless Sensor Networks
- Advanced Wireless Communication Technologies
- Smart Grid Energy Management
- COVID-19 diagnosis using AI
- Neuroscience and Music Perception
- Chaos-based Image/Signal Encryption
- Coding theory and cryptography
- Plant Reproductive Biology
- Hearing Loss and Rehabilitation
- Advanced Malware Detection Techniques
Henan University of Science and Technology
2016-2025
Nanjing Forestry University
2025
Gansu Agricultural University
2024
North China Electric Power University
2020-2024
Luoyang Institute of Science and Technology
2022-2024
Henan Academy of Sciences
2024
Institute of Physics
2024
IBM (United States)
2019-2023
China Agricultural University
2023
Institute of Atmospheric Physics
2019-2022
5G networks have been widely deployed all over the world, which involve massive multiple-in-put multiple-output (MIMO), millimeter-wave communication, and other technologies to improve performance of whole system. In contrast, emerging key including terahertz (THz) intelligent reflective surface (IRS), blockchain, so on proposed enhance signal quality for future 6G networks. IRS can program propagation by intelligently controlling a large number passive reflecting elements, blockchain system...
An electricity-promoted method for Friedel–Crafts acylation of biarylcarboxylic acids is described in this research. Various fluorenones can be accessed up to 99% yields. During the acylation, electricity plays an essential role, which might motivate chemical equilibrium by consuming generated TFA. This study predicted provide avenue realize a more environmentally friendly process.
It is widely known that convolutional neural networks (CNNs) are vulnerable to adversarial examples: images with imperceptible perturbations crafted fool classifiers. However, interpretability of these less explored in the literature. This work aims better understand roles and provide visual explanations from pixel, image network perspectives. We show adversaries have a promotion-suppression effect (PSE) on neurons' activations can be primarily categorized into three types: i)...
Membrane distillation technology, as a new membrane-based water treatment technology that combines the membrane and evaporation process, has advantages of using low-grade heat, working at atmospheric pressure with simple configuration, etc. In this study, heat mass transfer were coupled surfaces through user-defined function program. The effects feed temperature, velocity permeate on temperature polarization mainly investigated for high-concentration NaCl solution. was increased increase...
Contrastive learning (CL) can learn generalizable feature representations and achieve the state-of-the-art performance of downstream tasks by finetuning a linear classifier on top it. However, as adversarial robustness becomes vital in image classification, it remains unclear whether or not CL is able to preserve tasks. The main challenge that self-supervised pretraining + supervised paradigm, easily forgotten due task mismatch from finetuning. We call such 'cross-task transferability'. To...
Large Language Models (LLMs) trained on code are revolutionizing the software development process. Increasingly, LLMs being integrated into environments to improve productivity of human programmers, and LLM-based agents beginning show promise for handling complex tasks autonomously. Realizing full potential requires a wide range capabilities, including generation, fixing bugs, explaining documenting code, maintaining repositories, more. In this work, we introduce Granite series decoder-only...
In massive MIMO systems, the high complexity of signal detection comes mainly from computing a Gram matrix and its inversion. this correspondence, we propose low-complexity method based on Neumann series (NS), which does not require explicitly The proposed leverages statistical information to compute an initialization matrix, guarantees convergence NS expansion. is conducted implicitly by transforming inversion product operations into matrix-vector multiplication operations. By doing so, it...
This study investigated the physiological and biochemical responses of Styrax japonica Sieb. et Zucc. seedlings to normal water nutrient management (control group, CK), waterlogging (root submerged, T1), partial submergence (partial stem submergence, T2) over a period 25 days. Measurements root activity, malondialdehyde (MDA) content, hydrogen peroxide (H2O2) antioxidant enzyme (SOD, POD, CAT), anaerobic respiratory (LDH, ADH, PDC) activities were conducted every 5 The results showed...
This study investigates the framework of associating multiple‐input–multiple‐output (MIMO) beamforming with secure code to achieve unconditional communications in wireless passive eavesdropping environment. The schemes are based on a two‐step method under Wyner's wiretap channel model. First, MIMO transmit beamforming, one can utilise spatial degree freedom cripple eavesdroppers’ interceptions even when he does not know eavesdropper's state information. Consequently, by taking threshold...
Recent works have empirically shown that there exist adversarial examples can be hidden from neural network interpretability (namely, making interpretation maps visually similar), or is itself susceptible to attacks. In this paper, we theoretically show with a proper measurement of interpretation, it actually difficult prevent prediction-evasion attacks causing discrepancy, as confirmed by experiments on MNIST, CIFAR-10 and Restricted ImageNet. Spurred that, develop an interpretability-aware...
Zeroth-order (ZO) optimization is a subset of gradient-free that emerges in many signal processing and machine learning applications. It used for solving problems similarly to gradient-based methods. However, it does not require the gradient, using only function evaluations. Specifically, ZO iteratively performs three major steps: gradient estimation, descent direction computation, solution update. In this paper, we provide comprehensive review optimization, with an emphasis on showing...
Machine learning (ML) models that learn and predict properties of computer programs are increasingly being adopted deployed. These have demonstrated success in applications such as auto-completing code, summarizing large programs, detecting bugs malware programs. In this work, we investigate principled ways to adversarially perturb a program fool learned models, thus determine their adversarial robustness. We use obfuscations, which conventionally been used avoid attempts at reverse...
Abstract Mn‐based layered oxide cathodes for sodium‐ion batteries with anionic redox reactions hold great potential energy storage applications due to their ultra‐high capacity and cost effectiveness. However, achieving high requires overcoming challenges such as oxygen‐redox failure, sluggish kinetics, structural degradation. Herein, we employ an innovative crystal modulation strategy, using Na 0.72 Li 0.24 Mn 0.76 O 2 a representative cathode material, which shows that the highly exposed...