With growing urban areas,the climate continues to change as a result of growing populations,and hence,the demand for better emergency response systems has become more important than ever.Human Behaviour Classi.cation(...With growing urban areas,the climate continues to change as a result of growing populations,and hence,the demand for better emergency response systems has become more important than ever.Human Behaviour Classi.cation(HBC)systems have started to play a vital role by analysing data from di.erent sources to detect signs of emergencies.These systems are being used inmany critical areas like healthcare,public safety,and disastermanagement to improve response time and to prepare ahead of time.But detecting human behaviour in such stressful conditions is not simple;it o.en comes with noisy data,missing information,and the need to react in real time.This review takes a deeper look at HBC research published between 2020 and 2025.and aims to answer.ve speci.c research questions.These questions cover the types of emergencies discussed in the literature,the datasets and sensors used,the e.ectiveness of machine learning(ML)and deep learning(DL)models,and the limitations that still exist in this.eld.We explored 120 papers that used di.erent types of datasets,some were based on sensor data,others on social media,and a few used hybrid approaches.Commonly used models included CNNs,LSTMs,and reinforcement learning methods to identify behaviours.Though a lot of progress has been made,the review found ongoing issues in combining sensors properly,reacting fast enough,and using more diverse datasets.Overall,from the.ndings we observed,the focus should be on building systems that use multiple sensors together,gather real-time data on a large scale,and produce results that are easier to interpret.Proper attention to privacy and ethical concerns needs to be addressed as well.展开更多
FB （floating-body） and BC （body-contact） partially depleted SOI nMOSFETs with HBC（half-back-channel） implantation are fabricated. Test results show that such devices have good performance in delaying the occurre...FB （floating-body） and BC （body-contact） partially depleted SOI nMOSFETs with HBC（half-back-channel） implantation are fabricated. Test results show that such devices have good performance in delaying the occurrence of the “kink” phenomenon and improving the breakdown voltage as compared to conventional PDSOI nMOS- FETs,while not decreasing the threshold voltage of the back gate obviously. Numerical simulation shows that a reduced electrical field in the drain contributes to the improvement of the breakdown voltage and a delay of the “kink” effect. A detailed analysis is given for the cause of such improvement of breakdown voltage and the delay of the “kink” effect.展开更多
文摘With growing urban areas,the climate continues to change as a result of growing populations,and hence,the demand for better emergency response systems has become more important than ever.Human Behaviour Classi.cation(HBC)systems have started to play a vital role by analysing data from di.erent sources to detect signs of emergencies.These systems are being used inmany critical areas like healthcare,public safety,and disastermanagement to improve response time and to prepare ahead of time.But detecting human behaviour in such stressful conditions is not simple;it o.en comes with noisy data,missing information,and the need to react in real time.This review takes a deeper look at HBC research published between 2020 and 2025.and aims to answer.ve speci.c research questions.These questions cover the types of emergencies discussed in the literature,the datasets and sensors used,the e.ectiveness of machine learning(ML)and deep learning(DL)models,and the limitations that still exist in this.eld.We explored 120 papers that used di.erent types of datasets,some were based on sensor data,others on social media,and a few used hybrid approaches.Commonly used models included CNNs,LSTMs,and reinforcement learning methods to identify behaviours.Though a lot of progress has been made,the review found ongoing issues in combining sensors properly,reacting fast enough,and using more diverse datasets.Overall,from the.ndings we observed,the focus should be on building systems that use multiple sensors together,gather real-time data on a large scale,and produce results that are easier to interpret.Proper attention to privacy and ethical concerns needs to be addressed as well.
文摘FB （floating-body） and BC （body-contact） partially depleted SOI nMOSFETs with HBC（half-back-channel） implantation are fabricated. Test results show that such devices have good performance in delaying the occurrence of the “kink” phenomenon and improving the breakdown voltage as compared to conventional PDSOI nMOS- FETs,while not decreasing the threshold voltage of the back gate obviously. Numerical simulation shows that a reduced electrical field in the drain contributes to the improvement of the breakdown voltage and a delay of the “kink” effect. A detailed analysis is given for the cause of such improvement of breakdown voltage and the delay of the “kink” effect.
