The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety(OHS)is of prime importance.Like in other developing countries,this indust...The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety(OHS)is of prime importance.Like in other developing countries,this industry pays very little,rather negligible attention to OHS practices in Pakistan,resulting in the occurrence of a wide variety of accidents,mishaps,and near-misses every year.One of the major causes of such mishaps is the non-wearing of safety helmets(hard hats)at construction sites where falling objects from a height are unavoid-able.In most cases,this leads to serious brain injuries in people present at the site in general and the workers in particular.It is one of the leading causes of human fatalities at construction sites.In the United States,the Occupational Safety and Health Administration(OSHA)requires construction companies through safety laws to ensure the use of well-defined personal protective equipment(PPE).It has long been a problem to ensure the use of PPE because round-the-clock human monitoring is not possible.However,such monitoring through technological aids or automated tools is very much possible.The present study describes a systema-tic strategy based on deep learning(DL)models built on the You-Only-Look-Once(YOLOV5)architecture that could be used for monitoring workers’hard hats in real-time.It can indicate whether a worker is wearing a hat or not.The proposed system usesfive different models of the YOLOV5,namely YOLOV5n,YOLOv5s,YOLOv5 m,YOLOv5l,and YOLOv5x for object detection with the support of PyTorch,involving 7063 images.The results of the study show that among the DL models,the YOLOV5x has a high performance of 95.8%in terms of the mAP,while the YOLOV5n has the fastest detection speed of 70.4 frames per second(FPS).The proposed model can be successfully used in practice to recognize the hard hat worn by a worker.展开更多
ICSED (Improved Cluster Shade Edge Detection) algorithm and other various methods to accurately and efficiently detect edges on satellite data are presented. Error rate criterion is used to statistically evaluate the ...ICSED (Improved Cluster Shade Edge Detection) algorithm and other various methods to accurately and efficiently detect edges on satellite data are presented. Error rate criterion is used to statistically evaluate the performances of these methods in detecting oceanic features for both noise free and noise contaminated AVHRR (Advanced Very High Resolution Radiometer) IR image with Kuroshio. Also, practical experiments in detecting the eddy of Kuroshio with these methods are carried out for comparison. Results show that the ICSED algorithm has more advantages than other methods in detecting mesoscale features of ocean. Finally, the effectiveness of window size of ICSED method to oceanic features detection is quantitatively discussed.展开更多
In the infrared spectrum absorbed type gas concentration sensor,voltage signal obtained from the two-channel thermopile infrared detector TPS2534 is very weak.In order to solve this problem,the authors have establishe...In the infrared spectrum absorbed type gas concentration sensor,voltage signal obtained from the two-channel thermopile infrared detector TPS2534 is very weak.In order to solve this problem,the authors have established the structure of the sensor and designed weak signal detecting circuit of the sensor based on infrared spectrum absorption principle,differential de-noising principle and weak signal detecting principle.The authors have made experiments using CH4 gas.The results show that the circuit can remove noise effectively and detect weak electrical signal obtained from the detector.展开更多
The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing...The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing with moving dim point targets. In this paper we propose a new approach in processing of the Infrared image sequence for moving dim point targets detection built on the transformation of the IR-image sequence into 4-vectors for each frame in the sequence. The results of testing the proposed approach on a set of frames having a simple single pixel target performing a different motion patterns show the validity of the approach for detecting the motion, with simplicity in calculation and low time consumption.展开更多
The extremely high sampling rate is a challenge for ultra-wideband (UWB) communication. In this paper, we study the compressed sensing (CS) based impulse radio UWB (IR-UWB) signal detection and propose an IR-UWB signa...The extremely high sampling rate is a challenge for ultra-wideband (UWB) communication. In this paper, we study the compressed sensing (CS) based impulse radio UWB (IR-UWB) signal detection and propose an IR-UWB signal detection algorithm based on compressive sampling matching pursuit (CoSaMP). The proposed algorithm relies on the fact that UWB received signal is sparse in the time domain. The new algorithm can significantly reduce the sampling rate required by the detection and provides a better performance in case of the low signal-to-noise ratio when comparing with the existing matching pursuit (MP) based detection algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm.展开更多
Metal nano layer coating for increasing the sensitivity of spectroscopic measurements is proposed and experimentally demonstrated in this paper. The metal nano layer will attract the micro-poisons from any measured aq...Metal nano layer coating for increasing the sensitivity of spectroscopic measurements is proposed and experimentally demonstrated in this paper. The metal nano layer will attract the micro-poisons from any measured aqueous sample increasing the concentration of the micro-poison in the vicinity of the surface and significantly improves the sensitivity of the spectroscopic measurement. The demonstration was carried out using Fourier Transform Infra-Red (FTIR) operating in the MIR 400 cm-1 - 4000 cm-1 and 5 nm Gold layer which was grown on silicon oxide substrate. In the experimental demonstration Malathion organophosphate pesticide was used as micro-poison. The spectroscopic measurement proves that Malathion was attracted to the metal nano layer. Furthermore, the absorption lines of Malathion were detected and recognized. This proof of principle can be applied to any Internal Reflection Elements (IRE) and it can be used to purify any aqueous solutions and atmosphere from micro-poisons which will be attracted to the metal Nano layer.展开更多
针对无线传感器网络节点低成本、低运算能力的特点,基于脉冲超宽带技术的无线传感器网络提出了一种基于能量检测的两步测距法。这种方法针对DP(direct path)分量进行TOA(time of arrival)估计,具体包含对DP所在能量块的广义似然比检验...针对无线传感器网络节点低成本、低运算能力的特点,基于脉冲超宽带技术的无线传感器网络提出了一种基于能量检测的两步测距法。这种方法针对DP(direct path)分量进行TOA(time of arrival)估计,具体包含对DP所在能量块的广义似然比检验和能量块内对DP精确位置的极大似然估计两部分。给出了DP能量块检测概率和估计结果的闭合表达式,通过理论和数值分析了积分长度等系统参数对于TOA估计性能的影响,并建立了估计误差的数学模型。最后通过仿真结果进行了性能比较,并验证了分析结论。与传统方法比较的结果表明,该算法可以在复杂度较低的条件下取得一定的性能提升。展开更多
文摘The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety(OHS)is of prime importance.Like in other developing countries,this industry pays very little,rather negligible attention to OHS practices in Pakistan,resulting in the occurrence of a wide variety of accidents,mishaps,and near-misses every year.One of the major causes of such mishaps is the non-wearing of safety helmets(hard hats)at construction sites where falling objects from a height are unavoid-able.In most cases,this leads to serious brain injuries in people present at the site in general and the workers in particular.It is one of the leading causes of human fatalities at construction sites.In the United States,the Occupational Safety and Health Administration(OSHA)requires construction companies through safety laws to ensure the use of well-defined personal protective equipment(PPE).It has long been a problem to ensure the use of PPE because round-the-clock human monitoring is not possible.However,such monitoring through technological aids or automated tools is very much possible.The present study describes a systema-tic strategy based on deep learning(DL)models built on the You-Only-Look-Once(YOLOV5)architecture that could be used for monitoring workers’hard hats in real-time.It can indicate whether a worker is wearing a hat or not.The proposed system usesfive different models of the YOLOV5,namely YOLOV5n,YOLOv5s,YOLOv5 m,YOLOv5l,and YOLOv5x for object detection with the support of PyTorch,involving 7063 images.The results of the study show that among the DL models,the YOLOV5x has a high performance of 95.8%in terms of the mAP,while the YOLOV5n has the fastest detection speed of 70.4 frames per second(FPS).The proposed model can be successfully used in practice to recognize the hard hat worn by a worker.
文摘ICSED (Improved Cluster Shade Edge Detection) algorithm and other various methods to accurately and efficiently detect edges on satellite data are presented. Error rate criterion is used to statistically evaluate the performances of these methods in detecting oceanic features for both noise free and noise contaminated AVHRR (Advanced Very High Resolution Radiometer) IR image with Kuroshio. Also, practical experiments in detecting the eddy of Kuroshio with these methods are carried out for comparison. Results show that the ICSED algorithm has more advantages than other methods in detecting mesoscale features of ocean. Finally, the effectiveness of window size of ICSED method to oceanic features detection is quantitatively discussed.
文摘In the infrared spectrum absorbed type gas concentration sensor,voltage signal obtained from the two-channel thermopile infrared detector TPS2534 is very weak.In order to solve this problem,the authors have established the structure of the sensor and designed weak signal detecting circuit of the sensor based on infrared spectrum absorption principle,differential de-noising principle and weak signal detecting principle.The authors have made experiments using CH4 gas.The results show that the circuit can remove noise effectively and detect weak electrical signal obtained from the detector.
文摘The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing with moving dim point targets. In this paper we propose a new approach in processing of the Infrared image sequence for moving dim point targets detection built on the transformation of the IR-image sequence into 4-vectors for each frame in the sequence. The results of testing the proposed approach on a set of frames having a simple single pixel target performing a different motion patterns show the validity of the approach for detecting the motion, with simplicity in calculation and low time consumption.
文摘The extremely high sampling rate is a challenge for ultra-wideband (UWB) communication. In this paper, we study the compressed sensing (CS) based impulse radio UWB (IR-UWB) signal detection and propose an IR-UWB signal detection algorithm based on compressive sampling matching pursuit (CoSaMP). The proposed algorithm relies on the fact that UWB received signal is sparse in the time domain. The new algorithm can significantly reduce the sampling rate required by the detection and provides a better performance in case of the low signal-to-noise ratio when comparing with the existing matching pursuit (MP) based detection algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm.
文摘Metal nano layer coating for increasing the sensitivity of spectroscopic measurements is proposed and experimentally demonstrated in this paper. The metal nano layer will attract the micro-poisons from any measured aqueous sample increasing the concentration of the micro-poison in the vicinity of the surface and significantly improves the sensitivity of the spectroscopic measurement. The demonstration was carried out using Fourier Transform Infra-Red (FTIR) operating in the MIR 400 cm-1 - 4000 cm-1 and 5 nm Gold layer which was grown on silicon oxide substrate. In the experimental demonstration Malathion organophosphate pesticide was used as micro-poison. The spectroscopic measurement proves that Malathion was attracted to the metal nano layer. Furthermore, the absorption lines of Malathion were detected and recognized. This proof of principle can be applied to any Internal Reflection Elements (IRE) and it can be used to purify any aqueous solutions and atmosphere from micro-poisons which will be attracted to the metal Nano layer.
文摘针对无线传感器网络节点低成本、低运算能力的特点,基于脉冲超宽带技术的无线传感器网络提出了一种基于能量检测的两步测距法。这种方法针对DP(direct path)分量进行TOA(time of arrival)估计,具体包含对DP所在能量块的广义似然比检验和能量块内对DP精确位置的极大似然估计两部分。给出了DP能量块检测概率和估计结果的闭合表达式,通过理论和数值分析了积分长度等系统参数对于TOA估计性能的影响,并建立了估计误差的数学模型。最后通过仿真结果进行了性能比较,并验证了分析结论。与传统方法比较的结果表明,该算法可以在复杂度较低的条件下取得一定的性能提升。
