Fast and Accurate Detection of Masked Faces Using CNNs and LBPs

Face mask detection has several applications,including real-time surveillance,biometrics,etc.Identifying face masks is also helpful for crowd control and ensuring people wear them publicly.With monitoring personnel,it is impossible to ensure that people wear face masks;automated systems are a much superior option for face mask detection and monitoring.This paper introduces a simple and efficient approach for masked face detection.The architecture of the proposed approach is very straightforward;it combines deep learning and local binary patterns to extract features and classify themasmasked or unmasked.The proposed systemrequires hardware withminimal power consumption compared to state-of-the-art deep learning algorithms.Our proposed system maintains two steps.At first,this work extracted the local features of an image by using a local binary pattern descriptor,and then we used deep learning to extract global features.The proposed approach has achieved excellent accuracy and high performance.The performance of the proposed method was tested on three benchmark datasets:the realworld masked faces dataset(RMFD),the simulated masked faces dataset(SMFD),and labeled faces in the wild(LFW).Performancemetrics for the proposed technique weremeasured in terms of accuracy,precision,recall,and F1-score.Results indicated the efficiency of the proposed technique,providing accuracies of 99.86%,99.98%,and 100%for RMFD,SMFD,and LFW,respectively.Moreover,the proposed method outperformed state-of-the-art deep learning methods in the recent bibliography for the same problem under study and on the same evaluation datasets.

Digital Cross-Correlation Detection of Multi-Laser Beams Measuring System for Wind Field Detection

A cross-correlation detection method to process backscatter signals of multi-laser beams measuring （MLBM） is presented, which can be firstly filtered by the digital filter composed of average median filter and finite impulse response （FIR） digital filter. The processing of backscatter signals using single-pulse and three-pulse cross-correlation detection methods is depicted in detail. From calculation results, the multi-pulse cross-correlation detection could effectively improve signal-to-noise ratio （SNR）. Finally, both wind velocity and direction are determined by the peak-delay method based on the correlation function which shows high measuring precision and high SNR of the MLBM system with the assistance of the digital cross- correlation detection.

Blackout Prevention by Power Swing Detection and Out-of-Step Protection

Power swing evoked by sudden changes like faults or switching operations will become more and more important for protective relaying, due to the growing load flow in electrical power networks. Unwanted trips of the distance protection function must be avoided to prevent cascading effects and blackouts in the network. Selective out-of-step-tripping is required to stop unstable power swing and to prevent damage to affected generators. Therefore a reliable method for detection of power swing is presented, which requires no settings for operation. Power swing can be detected from 0.1 Hz up to 10 Hz swing frequency, also during open pole condition and during asymmetrical operation. A blocking logic prevents unselective trips by the distance protection. However, faults that occur during a power swing must be detected and cleared with a high degree of selectivity and dependability. For unstable power swing a flexible out of step tripping function will be proposed. The coordination of power swing detection, distance protection and out of step protection provides a reliable system protection.

Development of data acquisition and over-current protection systems for a suppressor-grid current with a neutral-beam ion source

Neutral beam injection is one of the effective auxiliary heating methods in magnetic-confinementfusion experiments. In order to acquire the suppressor-grid current signal and avoid the grid being damaged by overheating, a data acquisition and over-current protection system based on the PXI（PCI e Xtensions for Instrumentation） platform has been developed. The system consists of a current sensor, data acquisition module and over-current protection module. In the data acquisition module,the acquired data of one shot will be transferred in isolation and saved in a data-storage server in a txt file. It can also be recalled using NBWave for future analysis. The over-current protection module contains two modes： remote and local. This gives it the function of setting a threshold voltage remotely and locally, and the forbidden time of over-current protection also can be set by a host PC in remote mode. Experimental results demonstrate that the data acquisition and overcurrent protection system has the advantages of setting forbidden time and isolation transmission.

Fault Detection and Protection System of Electric Railway Substation

The industrial power systems are moving to digital networks,and unmanned systems are increasing recently with the technological development of information and communication technology.In particular,reliability of system operation is very important for stable power supply.Most industrial power distribution facilities use a 154 kV or 22.9 kV extra HV(high voltage)power system,and a special monitoring system is required because a large loss occurs when an error occurs in the power facility in the field.Although digital protection relay(IED;intelligent electronic device)and FR(fault recorder)are applied to the field to protect the power system,various improvement activities are still ongoing.In this paper,a 22.9 kV high-voltage panel and its test bed,which are widely used in railway stations,tunnels,substations and large plants,were tested as test subjects.The developed fault detection system automatically starts the AL(auto-lock)circuit or outputs an alarm signal to user by monitoring in real time problems such as CT(current transformer)-open and poor-contact that the existing digital protection relay cannot cover.In addition,it is intended to increase the safety and reliability of the power system by blocking various accidents in the system in advance and accurately analyzing the causes of faults with the developed fault detection system.

Design and implementation of self-protection agent for network-based intrusion detection system

Static secure techniques, such as firewall, hierarchy filtering, distributed disposing,layer management, autonomy agent, secure communication, were introduced in distributed intrusion detection. The self-protection agents were designed, which have the distributed architecture,cooperate with the agents in intrusion detection in a loose-coupled manner, protect the security of intrusion detection system, and respond to the intrusion actively. A prototype self-protection agent was implemented by using the packet filter in operation system kernel. The results show that all the hosts with the part of network-based intrusion detection system and the whole intrusion detection system are invisible from the outside and network scanning, and cannot apperceive the existence of network-based intrusion detection system. The communication between every part is secure. In the low layer, the packet streams are controlled to avoid the buffer leaks exist ing in some system service process and back-door programs, so as to prevent users from misusing and vicious attack like Trojan Horse effectively.

Electron Beam Desulfurization Project of Chengdu Cogeneration Power Plant Started Construction - A new cooperation in environment protection between China and Japan

On March 25 1996, the electron beam flue gas desulfurization demonstration project of Chengdu Cogeneration Power Plant started formal construction This is at present the largest electron beam desulfurization project in power plants in the world, and is jointly constructed by Sichuan Electric Power Bureau and the EBARA Works of Japan, This is an important cooperation project in environment protection between

Research on degradation of 2, 4 dichlorophenol and pentachlorophenol in water by electron beam irradiation

Electron beam was successfully used for the degradation of 2,4-dichlorophenol (2,4-DCP) and pentachlorophenol (PCP) in water. The effects of radiation doses on substrate degradation and dechlorination of solutions with concentrations of 50 mg/L for both chlorophenols were investigated. The effects of initial concentration, pH and absence of oxygen on the degradation were also investigated. The concentrations of 2,4-DCP and PCP remaining in solution after irradiation were measured by high-performance liquid chromatograph (HPLC). The results showed that an increased radiation dose led to increased degradation of the chlorophenols and increased Cl- yields. In all cases, the rate of degradation was found to be higher than the corresponding inorganic chloride yield from the parent compound. Deoxygenation was also found to increase the rate of degradation of the chlorophenols in water while degradation under alkaline condition was lower than at low to neutral pH.

Protective Effects of Shikonin on Brain Injury Induced by Carbon Ion Beam Irradiation in Mice

Radiation encephalopathy is the main complication of cranial radiotherapy. It can cause necrosis of brain tissue and cognitive dysfunction. Our previous work had proved that a natural antioxidant shikonin possessed protective effect on cerebral ischemic injury. Here we investigated the effects of shikonin on carbon ion beam induced radiation brain injury in mice. Pretreatment with shikonin significantly increased the SOD and CAT activities and the ratio of GSH/GSSG in mouse brain tissues compared with irradiated group （P〈0.01）, while obviously reduced the MDA and PCO contents and the RO$ levels derived from of the brain mitochondria.

Fault Detection Based on Hierarchical Cluster Analysis in Wide Area Backup Protection System

In wide area backup protection of electric power systems, the prerequisite of protection device's accurate, fast and reliable performance is its corresponding fault type and fault location can be discriminated quickly and defined exactly. In our study, global information will be introduced into the backup protection system. By analyzing and computing real-time PMU measurements, basing on cluster analysis theory, we are using mainly hierarchical cluster analysis to search after the statistical laws of electrical quantities' marked changes. Then we carry out fast and exact detection of fault components and fault sections, and finally accomplish fault isolation. The facts show that the fault detection of fault component (fault section) can be performed successfully by hierarchical cluster analysis and calculation. The results of hierarchical cluster analysis are accurate and reliable, and the dendrograms of hierarchical cluster analysis are in intuition.

Effects of laser beam divergence angle on airborne LIDAR positioning errors

The influence of laser beam divergence angle on the positioning accuracy of scanning airborne light detection and ranging （LIDAR） is analyzed and simulated. Based on the data process and positioning principle of airborne LIDAR, the errors from pulse broadening induced by laser beam di vergence angle are modeled and qualitatively analyzed for different terrain surfaces. Simulated results of positioning errors and suggestions to reduce them are given for the flat surface, the downhill of slope surface, and the uphill surface.

A New Method of Early Short Circuit Detection

To reduce the pressure on contacts and circuit breaker and realize the zone selective interlocking (ZSI) function above the instantaneous protection threshold (e.g., >10In), the short circuit current needs to be early detected. The state-of–art of early short circuit detection (ESCD) method is reviewed. Based on the equivalent model of the short circuit, a new method based on the current and its integration is proposed. The prospective current value can be detected in the early stage of the short circuit. According to the evaluation result, the short circuit current can be early forecasted with the proposed method.

Islanding Protection and Islanding Detection in Low Voltage CIGRE Distribution Network with Distributed Generations

The Power Quality (PQ), security, reliability etc., are the prime objectives of the power system. The protection is developed in such a way that it should be selective, fast, reliable and the cost effective. The study about the islanding protection in Low Voltage (LV) CIGRE distribution and networks like this has been proposed in this paper. This is achieved by developing the protection against the short circuit faults which might appear at the Medium Voltage (MV) bus. The protection of the network with significant penetration of the Distributed Generations (DGs) is a complicated process. The DG units which are directly connected to the grid such as synchronous or induction generators contribute large short power, whereas the DG units which are connected to the grid via inverters carry small amount of the short circuit power. This creates the problems in the protection of the network. If the proper protection coordination measures have not been taken, it might cause the mal-function of the protection devices which put the portion of the power network into the security threats. The selection of the islanding protection devices in this paper is made to protect the network against bi-directional currents at the time of short circuit fault. The LV CIGRE distribution network will enter into islanding if a fault is cleared at the MV bus by the proposed islanding protection devices. It is therefore, essential to detect the islanding in the CIGRE power network. The detection of the island in this network is another major objective of this paper. The detection of the island is proposed by using the technique which is based on the voltage phase angle difference. The simulations are carried out by using DIgSILENT power factory software version 15.0.

Real-Time Safety Helmet Detection Using Yolov5 at Construction Sites

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.

AN IMPEDANCE ANALYSIS FOR CRACK DETECTION IN THE TIMOSHENKO BEAM BASED ON THE ANTI-RESONANCE TECHNIQUE

An alternative technique for crack detection in a Timoshenko beam based on the first anti-resonant frequency is presented in this paper. Unlike the natural frequency, the anti-resonant frequency is a local parameter rather than a global parameter of structures, thus the proposed technique can be used to locate the structural defects. An impedance analysis of a cracked beam stimulated by a harmonic force based on the Timoshenko beam formulation is investigated. In order to characterize the local discontinuity due to cracks, a rotational spring model based on fracture mechanics is proposed to model the crack. Subsequently, the proposed method is verified by a numerical example of a simply-supported beam with a crack. The effect of the crack size on the anti-resonant frequency is investigated. The position of the crack of the simply-supported beam is also determined by the anti-resonance technique. The proposed technique is further applied to the ＂contaminated＂ anti-resonant frequency to detect crack damage, which is obtained by adding 1-3% noise to the calculated data. It is found that the proposed technique is effective and free from the environment noise. Finally, an experimental study is performed, which further verifies the validity of the proposed crack identification technique.

Development and Application of Lightning Protection Technologies in Power Grids of China

In recent years,along with the rapid expansion of power grids,the increasing complication of grid structures,and the development of smart grids and energy technologies,the lightning protection of power grids becomes increasingly prominent.Power grids of China have acquired significant achievements on lightning protection technologies,which are reviewed in this paper.A technical route of lightning protection is introduced in detail; it allows us to find problems through detection and measurement of lightning,to analyze problems through evaluation and simulation of lightning,to solve problems through lightning protection measures,and to prevent problems through hazard risk warning of lightning.Following the route,the technical breakthroughs of these four aspects in China are presented,including the chinese lightning detection network(CLDN),natural lightning observations,lightning faults detection at transmission lines,lightning current measurements,progresses in lightning distribution maps,lightning fault replays,lightning hazard risk evaluations,and lightning simulated experiments,as well as novel lightning protection measures.The practical devices and systems corresponding to the technologies mentioned above are also introduced and discussed.Due to the progress of lightning protection technologies in recent years,despite the rapidly growing length of transmission lines in China,the lightning accident rate is controlled at a certain level.

Robust Broadband Beam-Forming Based on the Feature of Underwater Target Radiated Noise

To the problem of the unknown underwater target detection, according to the feature that the underwater target radiated noise contains the stable line spectrum, a weighted method based on the main-to-side lobe ratio （MSLR） is proposed for broadband beam-forming. This weighted method can be implemented by using the following steps. Firstly, optimize the spatial spectrum of each frequency unit by the second-order cone programming （SOCP）, and obtain the optimized spatial spectrum with lower side lobe. Secondly, construct weighting factors based on the MSLR of the optimized spatial spectrums to from weight factors. Lastly, cumulate the spatial spectrum of each frequency unit via the weight statistical method of this paper. This method can restrain the disturbance of background noise, enhance the output signal-to-noise ratio （SNR）, and overcome the difficulty of traditional four-dimensional display. The theoretical analysis and simulation results both verify that this method can well enhance the spatial spectrum of line spectrum units, restrain the spatial spectrum of background noise units, and improve the performance of the broadband beam-forming.

Damage assessment of a continuous beam bridge based on the strain mode

Based on the method of strain mode, damage identification of continuous beam bridges by comparing the variance of several curves of strain modes difference is studied. Three cases of numerical simulation demonstrate that the proposed method is applicable to detecting many a damage in a continuous beam bridge, which accurately identifies the damaged positions of the bridge, and detects the damage severity of an element by its according peak value of the curve of strain modes difference that is found to increase with the increasing damage severity.

An Automated Detection Approach of Protective Equipment Donning for Medical Staff under COVID-19 Using Deep Learning

Personal protective equipment(PPE)donning detection for medical staff is a key link of medical operation safety guarantee and is of great significance to combat COVID-19.However,the lack of dedicated datasets makes the scarce research on intelligence monitoring of workers’PPE use in the field of healthcare.In this paper,we construct a dress codes dataset for medical staff under the epidemic.And based on this,we propose a PPE donning automatic detection approach using deep learning.With the participation of health care personnel,we organize 6 volunteers dressed in different combinations of PPE to simulate more dress situations in the preset structured environment,and an effective and robust dataset is constructed with a total of 5233 preprocessed images.Starting from the task’s dual requirements for speed and accuracy,we use the YOLOv4 convolutional neural network as our learning model to judge whether the donning of different PPE classes corresponds to the body parts of the medical staff meets the dress codes to ensure their self-protection safety.Experimental results show that compared with three typical deeplearning-based detection models,our method achieves a relatively optimal balance while ensuring high detection accuracy(84.14%),with faster processing time(42.02 ms)after the average analysis of 17 classes of PPE donning situation.Overall,this research focuses on the automatic detection of worker safety protection for the first time in healthcare,which will help to improve its technical level of risk management and the ability to respond to potentially hazardous events.

The Coupled Effect of Temperature Changes and Damage Depth on Natural Frequencies in Beam-Like Structures

A significant amount of research is concerned with dynamic modal parameters for damage detection of structural conditions due to their simplicity in use and feasibility.However,their use for damage detection should be performed with special attention,particularly in operational and environmental conditions subjected to temperature changes.Beams in construction industries experience different loading types,such as temperature changes leading to crack initiation and propagation.Changed physical and dynamic properties such as natural frequencies and mode shapes indicate that damage has occurred within the structures.In this study,vibration analysis of cantilever and cantilever simply supported beams has been carried out on intact and damaged beams to investigate the coupled effect of temperature changes and damage depth on natural frequencies.A numerical analysis of beams is completed using ANSYS software.The results of numerical simulation are validated using two other studies from literature.Numerical results revealed that in order to perform a successful damage assessment using the frequency shift,the vibration modes should be selected properly.In addition,an increase in temperature results in a decrease in structural frequencies.The assessment of the effect of damage depth on natural frequencies also confirms that when damage depth is increased,there is a significant decrease in natural frequency responses.