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About the Journal
Governed by: Jiangsu Education Department
Sponsored by: National University
Published by: Editorial Office of Journal of Nantong University (Natural Science Edition)
Issues per year: 4
ISSN: 1673-2340
CN: 32-1755/N
A survey on radio frequency fingerprint signal analysis and intelligent identification
YAN Gaoli;FU Xue;WANG Yu;GUI GuanIn the context of next-generation wireless communications and multi-source heterogeneous network systems, traditional cryptographic mechanisms and security protocols pose significant risks in Internet of things(IoT) environments. There is an urgent demand for more efficient and reliable identity authentication technologies. Radio frequency fingerprinting identification(RFFI), which leverages the inherent signal characteristics of wireless devices, provides a novel approach to addressing device authentication and security challenges. Unlike existing reviews that focus on selected aspects of RFFI from a broad perspective, this paper proposes a systematic and comprehensive framework.It begins by explaining the fundamental principles and characteristics of radio frequency fingerprint(RFF). Then, from the perspectives of statistical features and deep learning(DL)-based features, the paper presents an in-depth review of RFFI classification and identification methods, along with a comparative analysis of the two approaches supported by experimental validation. Finally, several potential research directions in intelligent RFFI are discussed, and future trends of RFF technology are explored, aiming to offer both theoretical insights and practical guidance for ongoing research and real-world applications.
A Q-learning method for creating a Hex opening library
XU Zhifan;LI Yuan;WANG Jingwen;LI Zhuoxuan;CAO YidingHex is a perfect-information board game, and its opening library — an essential component of the game system — has traditionally been generated based on human expertise and Monte Carlo tree search(MCTS) algorithms.However, this approach is computationally expensive and may not consistently ensure accuracy. This study proposes a self-play method based on Q-learning for the efficient construction of Hex opening libraries. The proposed method employs multi-threaded simulations and an improved upper confidence bound applied to trees(UCT) algorithm to identify promising opening moves. An enhanced ε-greedy strategy is incorporated to improve the convergence rate of the Q-learning algorithm. To further improve performance, Q-values are integrated into the upper confidence bound(UCB) formula as prior knowledge, which is intended to enhance decision-making accuracy during gameplay. Experimental results indicate that after 3 000 training iterations, the Q-values across the board converge, suggesting the method′ s potential for stable policy learning. In comparative evaluations, the generated opening library achieved a62.9% average win rate against the improved UCT algorithm. When Q-values were used as prior input to the UCB formula, the average win rate increased to 75.9%. The method was also applied in the Chinese Computer Game Competition, where the implementation received a first-place award, supporting the practical applicability of the approach.
Core loss prediction method for magnetic components based on machine learning
YAO Qida;PING Peng;ZHU Xinyi;ZHU XinfanMagnetic components play a key role in energy transfer, storage, and filtering, directly affecting the size,weight, loss, and cost of power converters. Therefore, accurate prediction of core loss is essential. To address the significant influence of excitation waveforms on core loss, an ensemble learning-based waveform classification strategy is proposed. Support vector machine(SVM), random forest(RF), and gradient boosting decision tree(GBDT) are used as base classifiers. The classification outputs are combined with original features to construct a new feature set, which is then used to train a meta-classifier to enhance generalization. XGBoost is selected as the core model for core loss prediction. A genetic algorithm is applied for multi-objective optimization to identify the optimal operating condition with minimal core loss and maximal magnetic energy transfer. Experimental results show that the ensemble classification model can accurately classify excitation waveforms. Compared with traditional core loss prediction models and other machine learning methods, the XGBoost model demonstrates higher prediction accuracy and better regression performance. The optimized framework demonstrates the capability to meet both loss reduction and energy efficiency objectives.
A dynamic uplink random access method based on non-orthogonal multiple access technology
YANG Jing;LIU Yuxin;GAO Rui;ZHAO Jing;DONG Zhicheng;ZHANG ZhenghuaTo address access collisions caused by massive user access in networks, a dynamic uplink random access method based on non-orthogonal multiple access(NOMA) is proposed. The method incorporates an adaptive resource allocation mechanism that dynamically adjusts time slot configurations and updates the access class barring(ACB) factor according to network conditions. After each round of random access, the system records the number of idle, successful, and collided time slots. These statistics are then used to estimate the number of remaining users. The process is iteratively repeated until all users successfully access the network. To evaluate the proposed method, a complete theoretical analysis framework is established under the Nakagami-m fading channel environment, from which closed-form expressions for access success probability and system throughput are derived. Simulation results show that, compared with the traditional dynamic ACB-based NOMA random access algorithm(DNRA) and the fixed ACB-based orthogonal random-access algorithm(FORA), the proposed method improves system throughput by 30.41% and 48.22%, respectively. Furthermore, under varying user loads, the method consistently achieves higher access success probabilities and maintains high system throughput across different network conditions.
Blind estimation algorithm for frequency hopping parameters based on enhanced time-frequency ridge extraction
WAN Kai;CHANG Cheng;HOU Changbo;WU XiangyuIn existing blind estimation algorithms for frequency-hopping parameters based on time-frequency ridges,performance degrades significantly when the signal-to-noise ratio(SNR) falls below-5 dB. To address this issue, an improved blind estimation method based on time-frequency ridges is proposed. First, the time-frequency matrix of the received signal is obtained using the short-time Fourier transform(STFT). Then, Gaussian filtering is applied for signal smoothing and noise suppression. Since the energy distribution of fixed-frequency interference differs from that of frequency-hopping signals in the time-frequency matrix, an energy cancellation method is used to eliminate such interference. Next, OTSU thresholding is applied to the matrix after energy cancellation to further remove residual fixed-frequency interference and noise, yielding a clearer time-frequency representation. Time-frequency ridges are then extracted from this image, and the least-squares method is employed to fit the hopping instants along these ridges, enabling accurate estimation of frequency-hopping parameters. Simulation results show that the proposed method effectively produces clean time-frequency images even at SNR levels as low as-5 dB in the presence of fixed-frequency interference. The average relative estimation error of each parameter remains below 1%, and the method demonstrates strong robustness against varying intensity and quantity of interference.
Argument mining method in financial domain based on large language models
DING Fei;KANG Xin;In recent years, financial text analysis has been shifting from coarse-grained sentiment polarity classification to fine-grained inference tasks focusing on logical relations between sentence pairs. To address limitations in existing approaches—such as the inability to capture semantic relations like “Support,” “Attack,” and “Unrelated,” the lack of reasoning interpretability, and severe class imbalance—this study proposes a structure-enhanced Financial Prompt-based Argumentation Network(FinPromptNet). Built upon the LLaMA3-8B-Instruct large language model, FinPromptNet integrates structurally explicit prompt templates, chain-of-thought(CoT) reasoning guidance,partial parameter fine-tuning, and a joint strategy combining weighted sampling and cost-sensitive optimization. Experiments conducted on the NTCIR-17 FinArg-1 financial sentence-pair classification dataset demonstrate that FinPromptNet outperforms state-of-the-art baselines including FinBERT and T5 in terms of accuracy, micro-F1, and macro-F1. Specifically, it achieves a macro-F1 score of 67.1%, outperforming T5 by 7.3 percentage points, and yields over 10 percentage points of improvement in F1 for the underrepresented “Attack” class. These results highlight the effectiveness of structure-aware prompt design and imbalance-aware learning in improving both model performance and interpretability for financial logical reasoning tasks.
A Fuzzy Concept-Cognitive Learning Method Integrating Fuzzy Coverage
WU Yuqing;LIN Yidong;LIANG Taoju;Concept-cognitive learning is an emerging cross-cutting research hotspot area that aims to continuously learn new knowledge by imitating the human cognitive process. However, existing concept-cognitive learning models usually ignore the local variability of objects in concepts, the redundancy of concept space, and the interpretability of concepts, which leads to model cognitive bias and underutilization of valid information. Therefore, a fuzzy concept-cognitive learning model integrating membership degree and coverage is proposed in this paper. Firstly, to enhance the representation capability of the concept extent, a membership function with an offset threshold is introduced to explore the correlation between objects and the concept. A membership matrix is then constructed to further transform the concept space into a fuzzy coverage. Secondly, high-correlation objects are filtered through the fuzzyβcut set, and the status of different concepts is explored by the coverage rate. This enables the construction of a core concept space, which effectively reduces the redundancy of the concept space and enhances cognitive learning efficiency. Finally, the proposed model is compared with four machine learning algorithms and two concept-cognition algorithms using the ten-fold cross validation method. The experimental results demonstrate that the model achieves higher average accuracy than the other comparative algorithms across 14 datasets, with the smallest performance fluctuation range across different datasets. Moreover, it maintains a leading position in terms of precision, recall, and F_1score, fully validating the feasibility and effectiveness of the proposed model.
Research on the spatial pattern and influencing factors of public parking facilities in Suzhou based on POI
Leimin;Wangyin;Maoshaoqian;Suqihang;With the continuous surge in urban vehicle ownership in China, the supply-demand imbalance of public parking facilities has become a critical constraint on urban transportation development. This study takes Suzhou City—the first prefecture-level city in China to exceed 5 million registered vehicles—as a case study. Based on 2023Baidu Map POI data and employing spatial analysis methods such as standard deviation ellipse analysis and kernel density estimation, we systematically investigate the spatial patterns and driving mechanisms of public parking facilities. The findings reveal:(1) Suzhou's public parking facilities exhibit a “1 primary hub, 8 secondary nodes, 2 agglomeration corridors” polycentric structure. The primary hub is located in the core area of Gusu District, while secondary nodes are distributed across key towns within administrative units, forming two distinct agglomeration axes:Shishan–Jinji Lake and Yuanhe–Songling.(2) Significant spatial disparities exist in parking resource allocation. Urbanized areas and suburban regions show marked contrasts in parking availability, with coverage gaps notably observed in southern Wujiang District and other peripheral zones.Using a geographic detector model, we further analyze factors influencing spatial distribution. Factor detection identifies residential density(q=0.76), commercial density(q=0.71), and nighttime light intensity(q=0.45) as dominant drivers. Interaction detection highlights the synergistic effects of residential, commercial, and industrial density in shaping parking facility layouts. Based on these findings, targeted optimization strategies are proposed to enhance the spatial allocation of public parking facilities in Suzhou.
Carbon nanotube-based flexible solid-state infrared control device
CHEN Xiangjun;WANG Hongzhi;LI Kerui;Dynamic infrared control technology has great application value in the field of intelligent thermal management and adaptive camouflage, but its development faces the key bottleneck of traditional electrochromic devices.Mainstream electrochromic devices such as metal oxides and conductive polymers generally have problems such as strong dependence on the conductive layer and high interface impedance. The new infrared control devices based on carbon nanomaterials are limited by the complex preparation process and the risk of electrolyte leakage, which restricts their practical application. In order to solve these problems, this study innovatively proposed a synergistic construction strategy of single-walled carbon nanotube electrode prepared by spraying method and hot-pressed polyurethane solid electrolyte, and successfully developed a flexible solid-state infrared control device integrating functional layer and conductive layer. Experimental results demonstrate that the optimized device achieves a high emissivity modulation amplitude of 0.52 in the 8–14 μm wavelength range, along with a rapid switching speed on the order of seconds. After 400 cycles, the device maintains 86.3% of its initial modulation performance. Even after 200 mechanical bending cycles, it retains 94.6% of its original performance, highlighting excellent cycling stability and mechanical flexibility. This study provides a new idea for the development of flexible infrared control devices with high integration and bending resistance, and shows great application value in the fields of thermal management equipment and adaptive camouflage system.
Research progress on the preparation and applications of thermochromic materials in a ternary component system
MAO Lifen;XIAO Hong;DAI Guoliang;MA Wujun;LAN Chuntao;LI Min;Thermochromic materials, as a significant class of smart responsive materials, exhibit dynamic responses to external temperature variations through reversible molecular structural changes. Investigating their chromic mechanisms and performance optimization is of great importance for expanding their practical applications in fields such as smart displays, temperature sensors, and building energy efficiency. This review summarizes recent advances in three-component thermochromic materials. The working mechanism of the synergistic coloration system, composed of color formers, color developers, and solid solvents, is elucidated. Emphasis is placed on analyzing the regulatory effects of molecular structures of color formers, electron transfer characteristics of color developers, and phase transition behaviors of solid solvents on the materials' coloration temperature, response speed, and stability. To address the environmental stability limitations of existing materials, the advantages and disadvantages of microencapsulation techniques, such as interfacial polymerization and in-situ polymerization, are comprehensively compared. In terms of applications, innovative practices in smart buildings, dynamic anti-counterfeiting, and functional textiles are highlighted. Finally, current research shortcomings, including precise regulation within narrow temperature ranges and multi-responsive design, are identified. Future efforts should focus on developing molecular engineering optimization strategies, photo-thermal synergistic responsive systems, and environmentally friendly preparation processes to provide theoretical foundations and technical pathways for performance breakthroughs and application expansion of smart materials.
Application of Increasing PID Controlling Method in Temperature Controlling System
YAN Xiao-zhao,ZHANG Xing-guo(School of Mechanical Engineering,Nantong University,Nantong 226007,China)Temperature control is widely applied in scientific experiments and industrial processes.However,the temperature control system has characteristics of being nonlinear,time-varying and has hysteretic complicated large inertial system,and the effect of control is closely related to the algorithms adopted.In this paper,an experimental temperature control system is developed to meet the requirement of innovative ability training for mechatronic undergraduates.An increasing PID control algorithm is designed.The experimental results prove that the effect of the designed algorithm is better than the traditional PID algorithm.
Research and Development in Techniques of Dyeing Wastewater Treatment
JING Xiao-hui 1,YOUKe-fei 2,DING Xin-yu 2,CAI Zai-sheng 1(1.School of Chemistry and Chemical Engineering,Donghua University,Shanghai200051,China; 2.School of Chemistry and Chemical Engineering,Nantong University,Nantong226007,China)Reviewof the progress on treating methods of dyeing wastewater is presented,especially the advanced techniques are introduced,suchas membrane extraction,ultrasonic processes,high-energyphysical processes,advanced electrocatalytic oxidaˉtion processes and advanced photocatalytic oxidation processes.The treating trend for the dyeing wastewater is discussed.
The Application and the Development Foreground of Chitin and Chitosan
ZHANG Wei,LIN Hong,CHEN Yu-yue (School of Material Engineering,Soochow University,Suzhou 215021,China)The structure and the performance of chitin and chitosan are introduced and the application of chitin and chitosan in various fields is analyzed in this paper.The existing problems and the development foreground of chitin and chitosan are summarized in this paper.
Overview of SERS
LAN Yan-na,ZHOULing (Nantong Institute of Technology,Nantong226007,China)The principle of Raman spectrumis expounded first.Then the characteristics of SERS effect in experiment is summaˉrized and the mechanism of SERS is described.It's an accepted viewthat the mechanism of electromagnetic enhancement and the mechanismof chemical enhancement are both in existence.But which one is more important in different experiment depends on specific condition.
Application of ANSYS to Reinforced Concrete Beam
WANG Ya-ping 1,CHEN Jian-ping 2 ,CHEN Wu-zhou 3(1.Nantong Institute of Technology,Nantong226007,China;2.Nantong Architectural Design Institute of Industry,Nantong226001,China;3.Nantong Water Conservancy Construction Company,Nantong226005,China)In this article,taking features of reinforced concrete into account ,FEM software of ANSYS was used to calculate the beam' s deformation and the stress and strain of the normal section.At last,the answers to ANSYS(crack length,stress of reinforc-ing bar and concrete)and theoretical answers were compared in search of reasons and ways or measures that can amend it.
The Application and the Development Foreground of Chitin and Chitosan
ZHANG Wei,LIN Hong,CHEN Yu-yue (School of Material Engineering,Soochow University,Suzhou 215021,China)The structure and the performance of chitin and chitosan are introduced and the application of chitin and chitosan in various fields is analyzed in this paper.The existing problems and the development foreground of chitin and chitosan are summarized in this paper.
Application of Increasing PID Controlling Method in Temperature Controlling System
YAN Xiao-zhao,ZHANG Xing-guo(School of Mechanical Engineering,Nantong University,Nantong 226007,China)Temperature control is widely applied in scientific experiments and industrial processes.However,the temperature control system has characteristics of being nonlinear,time-varying and has hysteretic complicated large inertial system,and the effect of control is closely related to the algorithms adopted.In this paper,an experimental temperature control system is developed to meet the requirement of innovative ability training for mechatronic undergraduates.An increasing PID control algorithm is designed.The experimental results prove that the effect of the designed algorithm is better than the traditional PID algorithm.
Preparation of functionalized carbon nanomaterials and their energy storage applications
LI Qi;QIN Tian;GE Cunwang;Over the past decades, functional carbon nanomaterials(FCMs) have attracted much attention from the materials science community owning to their outstanding physical and chemical properties, such as high electronic conductivity/rapid mass transfer, plentiful active sites, good chemical stability, and robust mechanical stiffness. In view of the anisotropic and synergistic effects stemming from the functionalization as well as small size effect at the nanoscale,these multifunctional FCMs exhibit high potential especially in lithium-ion batteries, sodium-ion batteries, potassiumion batteries, lithium-sulfur batteries, organic solar cells, and supercapacitors. In this review, the functionalization strategies of carbon nanomaterials that have been developed over the last five years are comprehensively summarized and then application of FCMs in energy storage and conversion is introduced exhaustively. Finally, the pressing challenges and research directions are discussed according to the development trend.
Preparation of biochar and its application in environmental pollution management
WANG Jiayue;LING Qian;ZHANG Yunhao;WANG Xinyu;LIN Jiaqi;ZHANG Weitao;LIU Zhixin;WANG Xiangke;Biochar is a kind of environmentally friendly porous material which can be easily synthesized at low cost and in large scale. It has a wide range of applications in environmental pollution control and pollutants′ remediation and immobilization due to its large specific surface area and abundant surface functional groups. In this review, we mainly summarized the preparation of biochar, discussed the effect of preparation conditions on the properties of prepared biochar. The application of biochar in the removal of various pollutants from wastewater and soil improvement,the immobilization and elimination of different pollutants in soils, were reviewed in detail and the interaction mechanism was discussed. The removal of heavy metal ions was mainly attributed to the sorption of metal ions through the formation of surface complexes and part of metal ions could be reduced from high valence to low valence and then immobilized on biochar through adsorption-reduction-solidification strategy. The removal of organic pollutants from solution to biochar was mainly attributed to surface complexation, H bonding and π-π interaction on biochar surfaces.The organic pollutants could also be photocatalytic degraded by biochar or biochar-based materials under visible light irradiation. In conclusion, further research and discussion on the interaction mechanism of pollutant molecular with biochar at molecular level are helpful for the application of biochar in wastewater treatment and soil remediation. This review is of scientific significance for reducing the migration and transformation of pollutants in the environment and reducing the risk of environmental pollutants in the natural environment.
Modeling and simulation of proton exchange membrane electrolyzer system
WANG Huidong;YAO Haiyan;GUO Qiang;XIA Hongjun;Proton exchange membrane(PEM) electrolyzer converts electrical energy into chemical and heat energy,which is a green hydrogen production method, featuring fast response, high current density, compact structure, and other advantages. In the modeling of proton exchange membrane electrolysis water hydrogen production system,existing literature lacks a lumped parameter model that comprehensively describes the voltage and current changes of the electrolysis cell, as well as the temperature dynamics of each component of the system. This study establishes a steady-state voltage model of PEM electrolyzer and the thermal dynamic model of the system based on the basic principles of electrochemistry and the laws of thermodynamics. The simulation analysis was carried out based on MATLAB/Simulink software, and the simulation results were compared with the experimental data. The results showed that the voltage error is less than 0.02 V, and the temperature error is less than 1.6 K, which verifies the validity of the model. The established model can describe and predict the behavior of system parameters and provide support for system design and control. According to the efficiency model of PEM electrolyzer and the simulation results, the influence of different temperature and pressure on the performance of the electrolyzer was analyzed. It is concluded that increasing the temperature and decreasing the pressure can improve the efficiency of the electrolyzer, with temperature being the main factor. Using the simulation model, a feedforward PID controller was employed for temperature control, achieving an overshoot of less than 0.6 K and a settling time within 400 seconds. Comparison with a traditional PID controller demonstrates that the feedforward PID controller has advantages in terms of reduced overshoot and faster response.