Cyberbullying,a critical concern for digital safety,necessitates effective linguistic analysis tools that can navigate the complexities of language use in online spaces.To tackle this challenge,our study introduces a ...Cyberbullying,a critical concern for digital safety,necessitates effective linguistic analysis tools that can navigate the complexities of language use in online spaces.To tackle this challenge,our study introduces a new approach employing Bidirectional Encoder Representations from the Transformers(BERT)base model(cased),originally pretrained in English.This model is uniquely adapted to recognize the intricate nuances of Arabic online communication,a key aspect often overlooked in conventional cyberbullying detection methods.Our model is an end-to-end solution that has been fine-tuned on a diverse dataset of Arabic social media(SM)tweets showing a notable increase in detection accuracy and sensitivity compared to existing methods.Experimental results on a diverse Arabic dataset collected from the‘X platform’demonstrate a notable increase in detection accuracy and sensitivity compared to existing methods.E-BERT shows a substantial improvement in performance,evidenced by an accuracy of 98.45%,precision of 99.17%,recall of 99.10%,and an F1 score of 99.14%.The proposed E-BERT not only addresses a critical gap in cyberbullying detection in Arabic online forums but also sets a precedent for applying cross-lingual pretrained models in regional language applications,offering a scalable and effective framework for enhancing online safety across Arabic-speaking communities.展开更多
Modern medicine is increasingly interested in advanced sensors to detect and analyze biochemical indicators.Ion sensors based on potentiometric methods are a promising platform for monitoring physiological ions in bio...Modern medicine is increasingly interested in advanced sensors to detect and analyze biochemical indicators.Ion sensors based on potentiometric methods are a promising platform for monitoring physiological ions in biological subjects.Current semi-implantable devices are mainly based on single-parameter detection.Miniaturized semi-implantable electrodes for multiparameter sensing have more restrictions on the electrode size due to biocompatibility considerations,but reducing the electrode surface area could potentially limit electrode sensitivity.This study developed a semi-implantable device system comprising a multiplexed microfilament electrode cluster(MMEC)and a printed circuit board for real-time monitoring of intra-tissue K^(+),Ca^(2+),and Na^(+)concentrations.The electrode surface area was less important for the potentiometric sensing mechanism,suggesting the feasibility of using a tiny fiber-like electrode for potentiometric sensing.The MMEC device exhibited a broad linear response(K^(+):2–32 mmol/L;Ca^(2+):0.5–4 mmol/L;Na^(+):10–160 mmol/L),high sensitivity(about 20–45 mV/decade),temporal stability(>2weeks),and good selectivity(>80%)for the above ions.In vitro detection and in vivo subcutaneous and brain experiment results showed that the MMEC system exhibits good multi-ion monitoring performance in several complex environments.This work provides a platform for the continuous real-time monitoring of ion fluctuations in different situations and has implications for developing smart sensors to monitor human health.展开更多
In this paper, a model-free approach is presented to design an observer-based fault detection system of linear continuoustime systems based on input and output data in the time domain. The core of the approach is to d...In this paper, a model-free approach is presented to design an observer-based fault detection system of linear continuoustime systems based on input and output data in the time domain. The core of the approach is to directly identify parameters of the observer-based residual generator based on a numerically reliable data equation obtained by filtering and sampling the input and output signals.展开更多
When a cold rolled strip is being treated in a continuous annealing furnace which is full of protective gas, the gas tightness of the furnace body, the connected facilities and the gas channels become an important ind...When a cold rolled strip is being treated in a continuous annealing furnace which is full of protective gas, the gas tightness of the furnace body, the connected facilities and the gas channels become an important indicator that directly affects the product＇s surface quality and shows the technical level of the design, the manufacture and the installation. By considering the problems of the gas tightness of a vertical annealing furnace in the installation and maintenance, this thesis evaluates the gas tightness indicator and gas tightness related level of the furnace body and the circulation duct, while studying and analyzing the technologies of negative-pressure leak detection and sealing.展开更多
Differential detection of continuous phase modulation suffers from significant intersymbol interference. To reduce bit error rate, multi-branch fractional multi-bit differential detection (MFMDD) with decision feed-ba...Differential detection of continuous phase modulation suffers from significant intersymbol interference. To reduce bit error rate, multi-branch fractional multi-bit differential detection (MFMDD) with decision feed-back is proposed. By introducing decision feedback in multi-bit differential detected signals, severe inter-symbol interference can be removed. Simulation results show that the proposed structure can greatly im-proves the performance compared with MFMDD without decision feedback, and the performance of 9 FMDD is very near to the performance of the coherent detection.展开更多
In this paper,the spectral estimation algorithm is extended to the detection of human vi-tal signs by mm-wave frequency modulated continuous wave(FMCW)radar,and a comprehensive algorithm based on spectrum refinement a...In this paper,the spectral estimation algorithm is extended to the detection of human vi-tal signs by mm-wave frequency modulated continuous wave(FMCW)radar,and a comprehensive algorithm based on spectrum refinement and the extended differentiate and cross multiply al-gorithm(DCMA)has been proposed.Firstly,the improved DFT algorithm is used to accurately obtain the distance window of human body.Secondly,phase ambiguity in phase extraction is avoided based on extended DCMA algorithm.Then,the spectrum range of refinement is determ-ined according to the peak position of the spectrum,and the respiratory and heartbeat frequency information is obtained by using chirp z-transform(CZT)algorithm to perform local spectrum re-finement.For verification,this paper has simulated the radar echo signal modulated by the simu-lated cardiopulmonary signal according to the proposed algorithm.By recovering the simulated car-diopulmonary signal,the high-precision respiratory and heartbeat frequency have been obtained.The results show that the proposed algorithm can effectively restore human breathing and heart-beat signals,and the relative error of frequency estimation is basically kept below 1.5%.展开更多
针对无线体域网(wireless body area network,WBAN)异常数据检测方法忽视人体异常数据的连续性,缺乏异常数据集检测等问题,提出一种基于Hampel滤波器和DBSCAN分层的WBAN异常数据检测方法。根据时间相关性利用Hampel滤波器检测异常数据点...针对无线体域网(wireless body area network,WBAN)异常数据检测方法忽视人体异常数据的连续性,缺乏异常数据集检测等问题,提出一种基于Hampel滤波器和DBSCAN分层的WBAN异常数据检测方法。根据时间相关性利用Hampel滤波器检测异常数据点,保证数据的连续性,使用改进的基于滑动时间窗的DBSCAN算法,检测异常数据集。实验结果表明,所提方法和其它方法相比,实现了分层的异常数据检测,在保证检测精度的同时准确标注出了异常数据集,具有空间复杂度小的优势。展开更多
基金funded by Scientific Research Deanship at University of Ha’il-Saudi Arabia through Project Number RG-23092。
文摘Cyberbullying,a critical concern for digital safety,necessitates effective linguistic analysis tools that can navigate the complexities of language use in online spaces.To tackle this challenge,our study introduces a new approach employing Bidirectional Encoder Representations from the Transformers(BERT)base model(cased),originally pretrained in English.This model is uniquely adapted to recognize the intricate nuances of Arabic online communication,a key aspect often overlooked in conventional cyberbullying detection methods.Our model is an end-to-end solution that has been fine-tuned on a diverse dataset of Arabic social media(SM)tweets showing a notable increase in detection accuracy and sensitivity compared to existing methods.Experimental results on a diverse Arabic dataset collected from the‘X platform’demonstrate a notable increase in detection accuracy and sensitivity compared to existing methods.E-BERT shows a substantial improvement in performance,evidenced by an accuracy of 98.45%,precision of 99.17%,recall of 99.10%,and an F1 score of 99.14%.The proposed E-BERT not only addresses a critical gap in cyberbullying detection in Arabic online forums but also sets a precedent for applying cross-lingual pretrained models in regional language applications,offering a scalable and effective framework for enhancing online safety across Arabic-speaking communities.
基金The authors would like to acknowledge financial support from the National Key R&D Program of China(Nos.2021YFF1200700 and 2021YFA0911100)the National Natural Science Foundation of China(Nos.T2225010,32171399,and 32171456)+4 种基金the Fundamental Research Funds for the Central Universities,Sun Yat-Sen University(No.22dfx02)Pazhou Lab,Guangzhou(No.PZL2021KF0003)The authors also would like to thank the funding support from the Opening Project of Key Laboratory of Microelectronic Devices&Integrated Technology,Institute of Microelectronics,Chinese Academy of Sciences,and State Key Laboratory of Precision Measuring Technology and Instruments(No.pilab2211)QQOY would like to thank the China Postdoctoral Science Foundation(No.2022M713645)JL would like to thank the National Natural Science Foundation of China(No.62105380)and the China Postdoctoral Science Foundation(No.2021M693686).
文摘Modern medicine is increasingly interested in advanced sensors to detect and analyze biochemical indicators.Ion sensors based on potentiometric methods are a promising platform for monitoring physiological ions in biological subjects.Current semi-implantable devices are mainly based on single-parameter detection.Miniaturized semi-implantable electrodes for multiparameter sensing have more restrictions on the electrode size due to biocompatibility considerations,but reducing the electrode surface area could potentially limit electrode sensitivity.This study developed a semi-implantable device system comprising a multiplexed microfilament electrode cluster(MMEC)and a printed circuit board for real-time monitoring of intra-tissue K^(+),Ca^(2+),and Na^(+)concentrations.The electrode surface area was less important for the potentiometric sensing mechanism,suggesting the feasibility of using a tiny fiber-like electrode for potentiometric sensing.The MMEC device exhibited a broad linear response(K^(+):2–32 mmol/L;Ca^(2+):0.5–4 mmol/L;Na^(+):10–160 mmol/L),high sensitivity(about 20–45 mV/decade),temporal stability(>2weeks),and good selectivity(>80%)for the above ions.In vitro detection and in vivo subcutaneous and brain experiment results showed that the MMEC system exhibits good multi-ion monitoring performance in several complex environments.This work provides a platform for the continuous real-time monitoring of ion fluctuations in different situations and has implications for developing smart sensors to monitor human health.
基金This work was supported was supported in part by the European Union under grant NeCST.
文摘In this paper, a model-free approach is presented to design an observer-based fault detection system of linear continuoustime systems based on input and output data in the time domain. The core of the approach is to directly identify parameters of the observer-based residual generator based on a numerically reliable data equation obtained by filtering and sampling the input and output signals.
文摘When a cold rolled strip is being treated in a continuous annealing furnace which is full of protective gas, the gas tightness of the furnace body, the connected facilities and the gas channels become an important indicator that directly affects the product＇s surface quality and shows the technical level of the design, the manufacture and the installation. By considering the problems of the gas tightness of a vertical annealing furnace in the installation and maintenance, this thesis evaluates the gas tightness indicator and gas tightness related level of the furnace body and the circulation duct, while studying and analyzing the technologies of negative-pressure leak detection and sealing.
文摘Differential detection of continuous phase modulation suffers from significant intersymbol interference. To reduce bit error rate, multi-branch fractional multi-bit differential detection (MFMDD) with decision feed-back is proposed. By introducing decision feedback in multi-bit differential detected signals, severe inter-symbol interference can be removed. Simulation results show that the proposed structure can greatly im-proves the performance compared with MFMDD without decision feedback, and the performance of 9 FMDD is very near to the performance of the coherent detection.
文摘In this paper,the spectral estimation algorithm is extended to the detection of human vi-tal signs by mm-wave frequency modulated continuous wave(FMCW)radar,and a comprehensive algorithm based on spectrum refinement and the extended differentiate and cross multiply al-gorithm(DCMA)has been proposed.Firstly,the improved DFT algorithm is used to accurately obtain the distance window of human body.Secondly,phase ambiguity in phase extraction is avoided based on extended DCMA algorithm.Then,the spectrum range of refinement is determ-ined according to the peak position of the spectrum,and the respiratory and heartbeat frequency information is obtained by using chirp z-transform(CZT)algorithm to perform local spectrum re-finement.For verification,this paper has simulated the radar echo signal modulated by the simu-lated cardiopulmonary signal according to the proposed algorithm.By recovering the simulated car-diopulmonary signal,the high-precision respiratory and heartbeat frequency have been obtained.The results show that the proposed algorithm can effectively restore human breathing and heart-beat signals,and the relative error of frequency estimation is basically kept below 1.5%.
文摘针对无线体域网(wireless body area network,WBAN)异常数据检测方法忽视人体异常数据的连续性,缺乏异常数据集检测等问题,提出一种基于Hampel滤波器和DBSCAN分层的WBAN异常数据检测方法。根据时间相关性利用Hampel滤波器检测异常数据点,保证数据的连续性,使用改进的基于滑动时间窗的DBSCAN算法,检测异常数据集。实验结果表明,所提方法和其它方法相比,实现了分层的异常数据检测,在保证检测精度的同时准确标注出了异常数据集,具有空间复杂度小的优势。
