The dual transmitter implements the equivalent anti-magnetic flux transient electromagnetic method, which can effectively reduce the scope of the transient electromagnetic detection blind area. However, this method is...The dual transmitter implements the equivalent anti-magnetic flux transient electromagnetic method, which can effectively reduce the scope of the transient electromagnetic detection blind area. However, this method is rarely reported in the detection of pipelines in urban geophysical exploration and the application of coal mines. Based on this, this paper realizes the equivalent anti-magnetic flux transient electromagnetic method based on the dual launcher. The suppression effect of this method on the blind area is analyzed by physical simulation. And the detection experiment of underground pipelines is carried out outdoors. The results show that the dual launcher can significantly reduce the turn-off time, thereby effectively reducing the impact of the blind area on the detection results, and the pipeline detection results verify the device’s effectiveness. Finally, based on the ground experimental results, the application prospect of mine advanced detection is discussed. Compared with other detection fields, the formation of blind areas is mainly caused by the equipment. If the dual launcher can be used to reduce the blind area, the accuracy of advanced detection can be improved more effectively. The above research results are of great significance for improving the detection accuracy of the underground transient electromagnetic method.展开更多
In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared ban...In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared band. A cloud detection method over ice-snow covered areas in Antarctica is presented. On account of different texture features of cloud and ice-snow areas, five texture features are extracted based on GLCM. Nonlinear SVM is then used to obtain the optimal classification hyperplane from training data. The experiment results indicate that this algorithm performs well in cloud detection in Antarctica, especially for thin cirrus detection. Furthermore, when images are resampled to a quarter or 1/16 of the full size, cloud percentages are still at the same level, while the processing time decreases exponentially.展开更多
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 qui...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.展开更多
Modern vehicles are equipped with multiple Electronic Control Units(ECUs)that support various convenient driving functions,such as the Advanced Driver Assistance System(ADAS).To enable communication between these ECUs...Modern vehicles are equipped with multiple Electronic Control Units(ECUs)that support various convenient driving functions,such as the Advanced Driver Assistance System(ADAS).To enable communication between these ECUs,the Controller Area Network(CAN)protocol is widely used.However,since CAN lacks any security technologies,it is vulnerable to cyber attacks.To address this,researchers have conducted studies on machine learning-based intrusion detection systems(IDSs)for CAN.However,most existing IDSs still have non-negligible detection errors.In this paper,we pro-pose a new filtering-based intrusion detection system(FIDS)to minimize the detection errors of machine learning-based IDSs.FIDS uses a whitelist and a blacklist created from CAN datasets.The whitelist stores the cryptographic hash value of normal packet sequences to correct false positives(FP),while the blacklist corrects false negatives(FN)based on transmission intervals and identifiers of CAN packets.We evaluated the performance of the proposed FIDS by implementing a machine learning-based IDS and applying FIDS to it.We conducted the evaluation using two CAN attack datasets provided by the Hacking and Countermeasure Research Lab(HCRL),which confirmed that FIDS can effectively reduce the FP and FN of the existing IDS.展开更多
Recently,automotive intrusion detection systems(IDSs)have emerged as promising defense approaches to counter attacks on in-vehicle networks(IVNs).However,the effectiveness of IDSs relies heavily on the quality of the ...Recently,automotive intrusion detection systems(IDSs)have emerged as promising defense approaches to counter attacks on in-vehicle networks(IVNs).However,the effectiveness of IDSs relies heavily on the quality of the datasets used for training and evaluation.Despite the availability of several datasets for automotive IDSs,there has been a lack of comprehensive analysis focusing on assessing these datasets.This paper aims to address the need for dataset assessment in the context of automotive IDSs.It proposes qualitative and quantitative metrics that are independent of specific automotive IDSs,to evaluate the quality of datasets.These metrics take into consideration various aspects such as dataset description,collection environment,and attack complexity.This paper evaluates eight commonly used datasets for automotive IDSs using the proposed metrics.The evaluation reveals biases in the datasets,particularly in terms of limited contexts and lack of diversity.Additionally,it highlights that the attacks in the datasets were mostly injected without considering normal behaviors,which poses challenges for training and evaluating machine learning-based IDSs.This paper emphasizes the importance of addressing the identified limitations in existing datasets to improve the performance and adaptability of automotive IDSs.The proposed metrics can serve as valuable guidelines for researchers and practitioners in selecting and constructing high-quality datasets for automotive security applications.Finally,this paper presents the requirements for high-quality datasets,including the need for representativeness,diversity,and balance.展开更多
In Wireless Body Area Networks(WBANs)with respect to health care,sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically.The great challenges posed to healthca...In Wireless Body Area Networks(WBANs)with respect to health care,sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically.The great challenges posed to healthcare WBANs are the black hole and sink hole attacks.Data from deployed sensor nodes are attracted by sink hole or black hole nodes while grabbing the shortest path.Identifying this issue is quite a challenging task as a small variation in medicine intake may result in a severe illness.This work proposes a hybrid detection framework for attacks by applying a Proportional Coinciding Score(PCS)and an MK-Means algorithm,which is a well-known machine learning technique used to raise attack detection accuracy and decrease computational difficulties while giving treatments for heartache and respiratory issues.First,the gathered training data feature count is reduced through data pre-processing in the PCS.Second,the pre-processed features are sent to the MK-Means algorithm for training the data and promoting classification.Third,certain attack detection measures given by the intrusion detection system,such as the number of data packages trans-received,are identified by the MK-Means algorithm.This study demonstrates that the MK-Means framework yields a high detection accuracy with a low packet loss rate,low communication overhead,and reduced end-to-end delay in the network and improves the accuracy of biomedical data.展开更多
Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas.This study took Gansu Province,China,a typical area with comp...Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas.This study took Gansu Province,China,a typical area with complex terrain and variable climate,as the research subject.Based on Google Earth Engine,we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022,and quantitatively analyzed the main causes of regional differences in surface water area.The findings revealed that surface water area in Gansu Province expanded by 406.88 km2 from 1985 to 2022.Seasonal surface water area exhibited significant fluctuations,while permanent surface water area showed a steady increase.Notably,terrestrial water storage exhibited a trend of first decreasing and then increasing,correlated with the dynamics of surface water area.Climate change and human activities jointly affected surface hydrological processes,with the impact of climate change being slightly higher than that of human activities.Spatially,climate change affected the'source'of surface water to a greater extent,while human activities tended to affect the'destination'of surface water.Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted.Therefore,we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water'supply-demand'balance strategies.The study not only sheds light on the dynamics of surface water area in Gansu Province,but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.展开更多
Active worms can cause widespread damages at so high a speed that effectively precludes human-directed reaction, and patches for the worms are always available after the damages have been caused, which has elevated th...Active worms can cause widespread damages at so high a speed that effectively precludes human-directed reaction, and patches for the worms are always available after the damages have been caused, which has elevated them self to a first-class security threat to Metropolitan Area Networks (MAN). Multi-agent system for Worm Detection and Containment in MAN (MWDCM) is presented to provide a first-class automatic reaction mechanism that automatically applies containment strategies to block the propagation of the worms and to protect MAN against worm scan that wastes a lot of network bandwidth and crashes the routers. Its user agent is used to detect the known worms. Worm detection agent and worm detection correlation agent use two-stage based decision method to detect unknown worms. They adaptively study the accessing in the whole network and dynamically change the working parameters to detect the unknown worms. MWDCM confines worm infection within a macro-cell or a micro-cell of the metropolitan area networks, the rest of the accesses and hosts continue functioning without disruption. MWDCM integrates Worm Detection System (WDS) and network management system. Reaction measures can be taken by using Simple Network Management Protocol (SNMP) interface to control broadband access server as soon as the WDS detect the active worm. MWDCM is very effective in blocking random scanning worms. Simulation results indicate that high worm infection rate of epidemics can be avoided to a degree by MWDCM blocking the propagation of the worms.展开更多
There were differences between real boundary and blast hole controlling boundary of irregular mined-out area in underground metal mines. There were errors in numerical analysis of stability for goaf, if it was analyze...There were differences between real boundary and blast hole controlling boundary of irregular mined-out area in underground metal mines. There were errors in numerical analysis of stability for goaf, if it was analyzed as regular 3D mined-out area and the influence of coupling stress-seepage-disturbance was not considered adequately. Taking a lead zinc mine as the background, the model was built by the coupling of Surpac and Midas-Gts based on the goaf model precisely measured by CMS.According to seepage stress fundamental equations based on the equivalent continuum mechanical and the theory about equivalent load of dynamic disturbance in deep-hole blasting, the stability of mined-out area under multi-field coupling of stress-seepage-dynamic disturbance was numerically analyzed. The results show that it is more consistent between the numerical analysis model based on the real model of irregular 3D shape goaf and the real situation, which could faithfully reappear the change rule of stress–strain about the surrounding rock under synthetic action of blasting dynamic loading and the seepage pressure. The mined-out area multi-field coupling formed by blasting excavation is stable. Based on combination of the advantages of the CMS,Surpac and Midas-Gts, and fully consideration of the effects of multi-field coupling, the accurate and effective way could be provided for numerical analysis of stability for mined-out area.展开更多
Dynamic analysis steps and general flow of fast lagrangian analysis of continua in 3 dimensions(FLAC3D) were discussed. Numerical simulation for influence of excavation and blasting vibration on stability of mined-out...Dynamic analysis steps and general flow of fast lagrangian analysis of continua in 3 dimensions(FLAC3D) were discussed. Numerical simulation for influence of excavation and blasting vibration on stability of mined-out area was carried out with FLAC3D. The whole analytical process was divided into two steps, including the static analysis and the dynamic analysis which were used to simulate the influence of excavation process and blasting vibration respectively. The results show that the shape of right upper boundary is extremely irregular after excavation, and stress concentration occurs at many places and higher tensile stress appears. The maximum tensile stress is higher than the tensile strength of rock mass, and surrounding rock of right roof will be damaged with tension fracture. The maximum displacement of surrounding rock is 4.75 mm after excavation. However, the maximum displacement increases to 5.47 mm after the blasting dynamic load is applied. And the covering area of plastic zones expands obviously, especially at the foot of right upper slope. The analytical results are in basic accordance with the observed results on the whole. Damage and disturbance on surrounding rock to some degree are caused by excavation, while blasting dynamic load increases the possibility of occurrence of dynamic instability and destruction further. So the effective supporting and vibration reducing measures should be taken during mining.展开更多
To identify the instability on large scale underground mined-out area in the metal mine effectively,the parameters of radial basis function were determined through clustering method and the improved fuzzy radial basis...To identify the instability on large scale underground mined-out area in the metal mine effectively,the parameters of radial basis function were determined through clustering method and the improved fuzzy radial basis function neural network(FRBFNN)model of instability identification model about large scale underground mined-out area in the metal mine was built.The improved FRBFNN model was trained and tested.The results show that the improved FRBFNN model has high training accuracy and generalization ability.Parameters such as pillar area ratio,filling level and the value of rock quality designation have strong influence on instability of large scale underground mined-out area.Correctness of analysis about the improved FRBFNN model was proved by the practical application results about instability discrimination of surrounding rock in large-scale underground mined-out area of a metal mine in south China.展开更多
Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in develope...Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multisensor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 multispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into built-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.展开更多
To relieve the increasing traffic load, many early built highways need to be widened or reconstructed. The rapid performance detection to existing subgrades is important to their reasonable evaluation and maximized ut...To relieve the increasing traffic load, many early built highways need to be widened or reconstructed. The rapid performance detection to existing subgrades is important to their reasonable evaluation and maximized utilization. Based on five kinds of soils taken from an existing highway in southern China, three commonly detecting methods were used to determine their moisture contents, compaction degrees and resilient moduli. The results showed that the measured moisture contents were greater than the design value, and the compaction degrees decreased sharply compared to the original ones. The moisture and heat exchange produced a decrease in the resilient modulus of plate loading test(PLT) from the standard 60 MPa down to 40 MPa. Afterwards, the portable falling weight deflectometer(PFWD) and dynamic cone penetrometer(DCP) were used to evaluate the subgrade performances. The measured PFWD moduli and the DCP penetration rates were correlated with the resilient moduli of PLT, deflections of the Beckman beam test, compaction degrees and moisture contents. The correlation analysis indicates that both of two methods are suitable in rapid detecting subgrade performances, but PFWD method is more recommended for it has higher accuracy and efficiency.展开更多
The engineering and geological characteristics of a steep slope consisting of coal gangue, rock and soil medium in Huating coal mine have been comprehensively investigated. Owing to humid weather, heavy rainfall, vege...The engineering and geological characteristics of a steep slope consisting of coal gangue, rock and soil medium in Huating coal mine have been comprehensively investigated. Owing to humid weather, heavy rainfall, vegetation and porous characteristics of the soil and rock mass, the steep slope will be destabilized and induce mud-rock flow or derive hazard easily. Firstly, based on the classical slope reinforcement theory, some regularity between the shear and displacement in the destabilized zone of the slope with or without root strength contribution is presented. Then, based on the experimental and statistical analysis of root strength, hydrological characteristics and stability status, etc., some possible biotechnical techniques for reinforcement of the steep slope have been suggested. These methods are important for quantitative analysis of destabilization of the slope and design of the biotechnical reinforcement.展开更多
The surface subsidence is a common environmental hazard in mined-out area. Based on careful analysis of the regularity of surface subsidence in mined-out area, we proposed a new time function based on Harris curve mod...The surface subsidence is a common environmental hazard in mined-out area. Based on careful analysis of the regularity of surface subsidence in mined-out area, we proposed a new time function based on Harris curve model in consideration of the shortage of current surface subsidence time functions. By analyzing the characteristics of the new time function, we found that it could meet the dynamic process, the velocity change process and the acceleration change process during surface subsidence. Then its rationality had been verified through project cases. The results show that the proposed time function model can give a good reflection of the regularity of surface subsidence in mined-out area and can accurately predict surface subsidence. And the prediction data of the model are a little greater than measured data on condition of proper measured data quantity, which is safety in the engineering. This model provides a new method for the analysis of surface subsidence in mined-out area and reference for future prediction, and it is valuable to engineering application.展开更多
A method to detect airports in large space-borne synthetic aperture radar（SAR） imagery is studied.First,the large SAR imagery is segmented according to amplitude characteristics using maximum a posteriori（MAP） est...A method to detect airports in large space-borne synthetic aperture radar（SAR） imagery is studied.First,the large SAR imagery is segmented according to amplitude characteristics using maximum a posteriori（MAP） estimator based on the heavytailed Rayleigh model.The attention is then paid on the object of interest（OOI） extracted from the large images.The minimumarea enclosing rectangle（MER） of OOI is created via a rotating calipers algorithm.The projection histogram（PH） of MER for OOI is then computed and the scale and rotation invariant feature for OOI are extracted from the statistical characteristics of PH.A support vector machine（SVM） classifier is trained using those feature parameters and the airport is detected by the SVM classifier and Hough transform.The application in space-borne SAR images demonstrates the effectiveness of the proposed method.展开更多
We propose a ground moving target detection method for dual-channel Wide Area Surveillance(WAS) radar based on Compressed Sensing(CS).Firstly,the method of moving target detection of the WAS radar is studied.In order ...We propose a ground moving target detection method for dual-channel Wide Area Surveillance(WAS) radar based on Compressed Sensing(CS).Firstly,the method of moving target detection of the WAS radar is studied.In order to reduce the sample data quantity of the radar,the echo data is randomly sampled in the azimuth direction,then,the matched filter is used to perform the range direction focus.We can use the compressive sensing theory to recover the signal in the Doppler domain.At last,the phase difference between the two channels is compensated to suppress the clutter.The result of the simulated data verifies the effectiveness of the proposed method.展开更多
Focusing on controlling the press-assembly quality of high-precision servo mechanism,an intelligent early warning method based on outlier data detection and linear regression is proposed.Linear regression is used to d...Focusing on controlling the press-assembly quality of high-precision servo mechanism,an intelligent early warning method based on outlier data detection and linear regression is proposed.Linear regression is used to deal with the relationship between assembly quality and press-assembly process,then the mathematical model of displacement-force in press-assembly process is established and a qualified press-assembly force range is defined for assembly quality control.To preprocess the raw dataset of displacement-force in the press-assembly process,an improved local outlier factor based on area density and P weight(LAOPW)is designed to eliminate the outliers which will result in inaccuracy of the mathematical model.A weighted distance based on information entropy is used to measure distance,and the reachable distance is replaced with P weight.Experiments show that the detection efficiency of the algorithm is improved by 5.6 ms compared with the traditional local outlier factor(LOF)algorithm,and the detection accuracy is improved by about 2%compared with the local outlier factor based on area density(LAOF)algorithm.The application of LAOPW algorithm and the linear regression model shows that it can effectively carry out intelligent early warning of press-assembly quality of high precision servo mechanism.展开更多
Drought events across the world are increasingly becoming a critical problem owing to its negative effects on water resources. There is need to understand on-site drought characteristics for the purpose of planning mi...Drought events across the world are increasingly becoming a critical problem owing to its negative effects on water resources. There is need to understand on-site drought characteristics for the purpose of planning mitigation measures. In this paper, meteorological drought episodes on spatial, temporal and trend domains were detected using Standardized Precipitation Index (SPI) and Effective Drought Index (EDI) in the upper Tana River basin. 41 years (1980-2016) monthly precipitation data from eight meteorological stations were used in the study. The SPI and EDI were used for reconstruction of the drought events and used to characterize the spatial, temporal and trend distribution of drought occurrence. Drought frequency was estimated as the ratio of a defined severity to its total number of events. The change in drought events was detected using a non-parametric man-Kendall trend test. The main drought conditions detected by SPI and EDI are severe drought, moderate drought, near normal, moderate wet, very wet and extremely wet conditions. From the results the average drought frequency between 1970 and 2010 for the south-eastern and north-western areas ranged from 12.16 to 14.93 and 3.82 to 6.63 percent respectively. The Mann-Kendall trend test show that drought trend increased in the south-eastern parts of the basin at 90% and 95% significant levels. However, there was no significant trend that was detected in the North-western areas. This is an indication that the south-eastern parts are more drought-prone areas compared to the North-western areas of the upper Tana River basin. Both the SPI and the EDI were effective in detecting the on-set of drought, description of the temporal variability, severity and spatial extent across the basin. It is recommended that the findings be adopted for decision making for drought-early warning systems in the river basin.展开更多
文摘The dual transmitter implements the equivalent anti-magnetic flux transient electromagnetic method, which can effectively reduce the scope of the transient electromagnetic detection blind area. However, this method is rarely reported in the detection of pipelines in urban geophysical exploration and the application of coal mines. Based on this, this paper realizes the equivalent anti-magnetic flux transient electromagnetic method based on the dual launcher. The suppression effect of this method on the blind area is analyzed by physical simulation. And the detection experiment of underground pipelines is carried out outdoors. The results show that the dual launcher can significantly reduce the turn-off time, thereby effectively reducing the impact of the blind area on the detection results, and the pipeline detection results verify the device’s effectiveness. Finally, based on the ground experimental results, the application prospect of mine advanced detection is discussed. Compared with other detection fields, the formation of blind areas is mainly caused by the equipment. If the dual launcher can be used to reduce the blind area, the accuracy of advanced detection can be improved more effectively. The above research results are of great significance for improving the detection accuracy of the underground transient electromagnetic method.
基金Supported by the Antarctic Geography Information Acquisition and Environmental Change Research of China (No.14601402024-04-06).
文摘In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared band. A cloud detection method over ice-snow covered areas in Antarctica is presented. On account of different texture features of cloud and ice-snow areas, five texture features are extracted based on GLCM. Nonlinear SVM is then used to obtain the optimal classification hyperplane from training data. The experiment results indicate that this algorithm performs well in cloud detection in Antarctica, especially for thin cirrus detection. Furthermore, when images are resampled to a quarter or 1/16 of the full size, cloud percentages are still at the same level, while the processing time decreases exponentially.
文摘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.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.NRF-2021R1A4A1029650).
文摘Modern vehicles are equipped with multiple Electronic Control Units(ECUs)that support various convenient driving functions,such as the Advanced Driver Assistance System(ADAS).To enable communication between these ECUs,the Controller Area Network(CAN)protocol is widely used.However,since CAN lacks any security technologies,it is vulnerable to cyber attacks.To address this,researchers have conducted studies on machine learning-based intrusion detection systems(IDSs)for CAN.However,most existing IDSs still have non-negligible detection errors.In this paper,we pro-pose a new filtering-based intrusion detection system(FIDS)to minimize the detection errors of machine learning-based IDSs.FIDS uses a whitelist and a blacklist created from CAN datasets.The whitelist stores the cryptographic hash value of normal packet sequences to correct false positives(FP),while the blacklist corrects false negatives(FN)based on transmission intervals and identifiers of CAN packets.We evaluated the performance of the proposed FIDS by implementing a machine learning-based IDS and applying FIDS to it.We conducted the evaluation using two CAN attack datasets provided by the Hacking and Countermeasure Research Lab(HCRL),which confirmed that FIDS can effectively reduce the FP and FN of the existing IDS.
基金supported in part by the 2021 Autonomous Driving Development Innovation Project of the Ministry of Science and ICT,‘Development of Technology for Security and Ultra-High-Speed Integrity of the Next-Generation Internal Net-Work of Autonomous Vehicles’(No.2021-0-01348)and in part by the National Research Foundation of Korea(NRF)grant funded by the Korean Government Ministry of Science and ICT(MSIT)under Grant NRF-2021R1A2C2014428.
文摘Recently,automotive intrusion detection systems(IDSs)have emerged as promising defense approaches to counter attacks on in-vehicle networks(IVNs).However,the effectiveness of IDSs relies heavily on the quality of the datasets used for training and evaluation.Despite the availability of several datasets for automotive IDSs,there has been a lack of comprehensive analysis focusing on assessing these datasets.This paper aims to address the need for dataset assessment in the context of automotive IDSs.It proposes qualitative and quantitative metrics that are independent of specific automotive IDSs,to evaluate the quality of datasets.These metrics take into consideration various aspects such as dataset description,collection environment,and attack complexity.This paper evaluates eight commonly used datasets for automotive IDSs using the proposed metrics.The evaluation reveals biases in the datasets,particularly in terms of limited contexts and lack of diversity.Additionally,it highlights that the attacks in the datasets were mostly injected without considering normal behaviors,which poses challenges for training and evaluating machine learning-based IDSs.This paper emphasizes the importance of addressing the identified limitations in existing datasets to improve the performance and adaptability of automotive IDSs.The proposed metrics can serve as valuable guidelines for researchers and practitioners in selecting and constructing high-quality datasets for automotive security applications.Finally,this paper presents the requirements for high-quality datasets,including the need for representativeness,diversity,and balance.
基金funded by Stefan cel Mare University of Suceava,Romania.
文摘In Wireless Body Area Networks(WBANs)with respect to health care,sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically.The great challenges posed to healthcare WBANs are the black hole and sink hole attacks.Data from deployed sensor nodes are attracted by sink hole or black hole nodes while grabbing the shortest path.Identifying this issue is quite a challenging task as a small variation in medicine intake may result in a severe illness.This work proposes a hybrid detection framework for attacks by applying a Proportional Coinciding Score(PCS)and an MK-Means algorithm,which is a well-known machine learning technique used to raise attack detection accuracy and decrease computational difficulties while giving treatments for heartache and respiratory issues.First,the gathered training data feature count is reduced through data pre-processing in the PCS.Second,the pre-processed features are sent to the MK-Means algorithm for training the data and promoting classification.Third,certain attack detection measures given by the intrusion detection system,such as the number of data packages trans-received,are identified by the MK-Means algorithm.This study demonstrates that the MK-Means framework yields a high detection accuracy with a low packet loss rate,low communication overhead,and reduced end-to-end delay in the network and improves the accuracy of biomedical data.
基金This research was supported by the Third Xinjiang Scientific Expedition Program(2021xjkk010102)the National Natural Science Foundation of China(41261047,41761043)+1 种基金the Science and Technology Plan of Gansu Province,China(20YF3FA042)the Youth Teacher Scientific Capability Promoting Project of Northwest Normal University,Gansu Province,China(NWNU-LKQN-17-7).
文摘Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas.This study took Gansu Province,China,a typical area with complex terrain and variable climate,as the research subject.Based on Google Earth Engine,we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022,and quantitatively analyzed the main causes of regional differences in surface water area.The findings revealed that surface water area in Gansu Province expanded by 406.88 km2 from 1985 to 2022.Seasonal surface water area exhibited significant fluctuations,while permanent surface water area showed a steady increase.Notably,terrestrial water storage exhibited a trend of first decreasing and then increasing,correlated with the dynamics of surface water area.Climate change and human activities jointly affected surface hydrological processes,with the impact of climate change being slightly higher than that of human activities.Spatially,climate change affected the'source'of surface water to a greater extent,while human activities tended to affect the'destination'of surface water.Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted.Therefore,we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water'supply-demand'balance strategies.The study not only sheds light on the dynamics of surface water area in Gansu Province,but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.
基金Partially supported by the Teaching and Research Award for Outstanding Young Teachers in High Education Institutions of MOE, China (No.200065).
文摘Active worms can cause widespread damages at so high a speed that effectively precludes human-directed reaction, and patches for the worms are always available after the damages have been caused, which has elevated them self to a first-class security threat to Metropolitan Area Networks (MAN). Multi-agent system for Worm Detection and Containment in MAN (MWDCM) is presented to provide a first-class automatic reaction mechanism that automatically applies containment strategies to block the propagation of the worms and to protect MAN against worm scan that wastes a lot of network bandwidth and crashes the routers. Its user agent is used to detect the known worms. Worm detection agent and worm detection correlation agent use two-stage based decision method to detect unknown worms. They adaptively study the accessing in the whole network and dynamically change the working parameters to detect the unknown worms. MWDCM confines worm infection within a macro-cell or a micro-cell of the metropolitan area networks, the rest of the accesses and hosts continue functioning without disruption. MWDCM integrates Worm Detection System (WDS) and network management system. Reaction measures can be taken by using Simple Network Management Protocol (SNMP) interface to control broadband access server as soon as the WDS detect the active worm. MWDCM is very effective in blocking random scanning worms. Simulation results indicate that high worm infection rate of epidemics can be avoided to a degree by MWDCM blocking the propagation of the worms.
基金Project(2012BAK09B02-05)supported by the National"Twelfth Five"Science and Technology Support Program,ChinaProject(51274250)supported by the National Natural Science Foundation of China+2 种基金Project(2013zzts057)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(11KF02)supported by the Research Fund of the State Key Laboratory of Coal Resources and Mine safety,CUMT,ChinaProject(2012M511417)supported by China Postdoctoral Science Foundation
文摘There were differences between real boundary and blast hole controlling boundary of irregular mined-out area in underground metal mines. There were errors in numerical analysis of stability for goaf, if it was analyzed as regular 3D mined-out area and the influence of coupling stress-seepage-disturbance was not considered adequately. Taking a lead zinc mine as the background, the model was built by the coupling of Surpac and Midas-Gts based on the goaf model precisely measured by CMS.According to seepage stress fundamental equations based on the equivalent continuum mechanical and the theory about equivalent load of dynamic disturbance in deep-hole blasting, the stability of mined-out area under multi-field coupling of stress-seepage-dynamic disturbance was numerically analyzed. The results show that it is more consistent between the numerical analysis model based on the real model of irregular 3D shape goaf and the real situation, which could faithfully reappear the change rule of stress–strain about the surrounding rock under synthetic action of blasting dynamic loading and the seepage pressure. The mined-out area multi-field coupling formed by blasting excavation is stable. Based on combination of the advantages of the CMS,Surpac and Midas-Gts, and fully consideration of the effects of multi-field coupling, the accurate and effective way could be provided for numerical analysis of stability for mined-out area.
基金Project (50490272) supported by the National Natural Science Foundation of China project(NCET-05-0687) supportedby Programfor New Century Excellent Talents project (040109) supported bythe Doctor Degree Paper Innovation Engineering of CentralSouth University
文摘Dynamic analysis steps and general flow of fast lagrangian analysis of continua in 3 dimensions(FLAC3D) were discussed. Numerical simulation for influence of excavation and blasting vibration on stability of mined-out area was carried out with FLAC3D. The whole analytical process was divided into two steps, including the static analysis and the dynamic analysis which were used to simulate the influence of excavation process and blasting vibration respectively. The results show that the shape of right upper boundary is extremely irregular after excavation, and stress concentration occurs at many places and higher tensile stress appears. The maximum tensile stress is higher than the tensile strength of rock mass, and surrounding rock of right roof will be damaged with tension fracture. The maximum displacement of surrounding rock is 4.75 mm after excavation. However, the maximum displacement increases to 5.47 mm after the blasting dynamic load is applied. And the covering area of plastic zones expands obviously, especially at the foot of right upper slope. The analytical results are in basic accordance with the observed results on the whole. Damage and disturbance on surrounding rock to some degree are caused by excavation, while blasting dynamic load increases the possibility of occurrence of dynamic instability and destruction further. So the effective supporting and vibration reducing measures should be taken during mining.
基金financially supported by the National"Twelfth-Five-Year"Science&Technology Support Plan(No.2012BAK09B02-05)the National Natural Science Foundation of China(No.51274250)
文摘To identify the instability on large scale underground mined-out area in the metal mine effectively,the parameters of radial basis function were determined through clustering method and the improved fuzzy radial basis function neural network(FRBFNN)model of instability identification model about large scale underground mined-out area in the metal mine was built.The improved FRBFNN model was trained and tested.The results show that the improved FRBFNN model has high training accuracy and generalization ability.Parameters such as pillar area ratio,filling level and the value of rock quality designation have strong influence on instability of large scale underground mined-out area.Correctness of analysis about the improved FRBFNN model was proved by the practical application results about instability discrimination of surrounding rock in large-scale underground mined-out area of a metal mine in south China.
基金supported by the National Natural Science Foundation of China (NSFC) (No.30571112).
文摘Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multisensor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 multispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into built-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.
基金Project(2017YFC0805307) supported by the National Key Research and Development Program of ChinaProjects(51878078, 51927814, 51911530215) supported by the National Natural Science Foundation of China+4 种基金Project(2018-025) supported by the Training Program for High-level Technical Personnel in Transportation Industry, ChinaProject (2018JJ1026) supported by the Excellent Youth Foundation of Natural Science Foundation of Hunan Province, ChinaProject(17A008) supported by the Key Project of Education Department of Hunan Province, ChinaProjects(kfj150103, kfj170104) supported by the Open Research Fund of State Engineering Laboratory of Highway Maintenance Technology, Changsha University of Science & Technology, ChinaProject(CX20190644) supported by the Postgraduate Scientific Research Innovation Project of Hunan Province, China。
文摘To relieve the increasing traffic load, many early built highways need to be widened or reconstructed. The rapid performance detection to existing subgrades is important to their reasonable evaluation and maximized utilization. Based on five kinds of soils taken from an existing highway in southern China, three commonly detecting methods were used to determine their moisture contents, compaction degrees and resilient moduli. The results showed that the measured moisture contents were greater than the design value, and the compaction degrees decreased sharply compared to the original ones. The moisture and heat exchange produced a decrease in the resilient modulus of plate loading test(PLT) from the standard 60 MPa down to 40 MPa. Afterwards, the portable falling weight deflectometer(PFWD) and dynamic cone penetrometer(DCP) were used to evaluate the subgrade performances. The measured PFWD moduli and the DCP penetration rates were correlated with the resilient moduli of PLT, deflections of the Beckman beam test, compaction degrees and moisture contents. The correlation analysis indicates that both of two methods are suitable in rapid detecting subgrade performances, but PFWD method is more recommended for it has higher accuracy and efficiency.
基金This work was financially supported by the National Natural Science Foundation of China (No. 10402033) and the Key Lab. Foun-dation of the Ministry of Education of China (No.04JS19).
文摘The engineering and geological characteristics of a steep slope consisting of coal gangue, rock and soil medium in Huating coal mine have been comprehensively investigated. Owing to humid weather, heavy rainfall, vegetation and porous characteristics of the soil and rock mass, the steep slope will be destabilized and induce mud-rock flow or derive hazard easily. Firstly, based on the classical slope reinforcement theory, some regularity between the shear and displacement in the destabilized zone of the slope with or without root strength contribution is presented. Then, based on the experimental and statistical analysis of root strength, hydrological characteristics and stability status, etc., some possible biotechnical techniques for reinforcement of the steep slope have been suggested. These methods are important for quantitative analysis of destabilization of the slope and design of the biotechnical reinforcement.
基金supported by the Key Program of the National Natural Science Foundation of China (No. 50334060)
文摘The surface subsidence is a common environmental hazard in mined-out area. Based on careful analysis of the regularity of surface subsidence in mined-out area, we proposed a new time function based on Harris curve model in consideration of the shortage of current surface subsidence time functions. By analyzing the characteristics of the new time function, we found that it could meet the dynamic process, the velocity change process and the acceleration change process during surface subsidence. Then its rationality had been verified through project cases. The results show that the proposed time function model can give a good reflection of the regularity of surface subsidence in mined-out area and can accurately predict surface subsidence. And the prediction data of the model are a little greater than measured data on condition of proper measured data quantity, which is safety in the engineering. This model provides a new method for the analysis of surface subsidence in mined-out area and reference for future prediction, and it is valuable to engineering application.
文摘A method to detect airports in large space-borne synthetic aperture radar（SAR） imagery is studied.First,the large SAR imagery is segmented according to amplitude characteristics using maximum a posteriori（MAP） estimator based on the heavytailed Rayleigh model.The attention is then paid on the object of interest（OOI） extracted from the large images.The minimumarea enclosing rectangle（MER） of OOI is created via a rotating calipers algorithm.The projection histogram（PH） of MER for OOI is then computed and the scale and rotation invariant feature for OOI are extracted from the statistical characteristics of PH.A support vector machine（SVM） classifier is trained using those feature parameters and the airport is detected by the SVM classifier and Hough transform.The application in space-borne SAR images demonstrates the effectiveness of the proposed method.
文摘We propose a ground moving target detection method for dual-channel Wide Area Surveillance(WAS) radar based on Compressed Sensing(CS).Firstly,the method of moving target detection of the WAS radar is studied.In order to reduce the sample data quantity of the radar,the echo data is randomly sampled in the azimuth direction,then,the matched filter is used to perform the range direction focus.We can use the compressive sensing theory to recover the signal in the Doppler domain.At last,the phase difference between the two channels is compensated to suppress the clutter.The result of the simulated data verifies the effectiveness of the proposed method.
文摘Focusing on controlling the press-assembly quality of high-precision servo mechanism,an intelligent early warning method based on outlier data detection and linear regression is proposed.Linear regression is used to deal with the relationship between assembly quality and press-assembly process,then the mathematical model of displacement-force in press-assembly process is established and a qualified press-assembly force range is defined for assembly quality control.To preprocess the raw dataset of displacement-force in the press-assembly process,an improved local outlier factor based on area density and P weight(LAOPW)is designed to eliminate the outliers which will result in inaccuracy of the mathematical model.A weighted distance based on information entropy is used to measure distance,and the reachable distance is replaced with P weight.Experiments show that the detection efficiency of the algorithm is improved by 5.6 ms compared with the traditional local outlier factor(LOF)algorithm,and the detection accuracy is improved by about 2%compared with the local outlier factor based on area density(LAOF)algorithm.The application of LAOPW algorithm and the linear regression model shows that it can effectively carry out intelligent early warning of press-assembly quality of high precision servo mechanism.
文摘Drought events across the world are increasingly becoming a critical problem owing to its negative effects on water resources. There is need to understand on-site drought characteristics for the purpose of planning mitigation measures. In this paper, meteorological drought episodes on spatial, temporal and trend domains were detected using Standardized Precipitation Index (SPI) and Effective Drought Index (EDI) in the upper Tana River basin. 41 years (1980-2016) monthly precipitation data from eight meteorological stations were used in the study. The SPI and EDI were used for reconstruction of the drought events and used to characterize the spatial, temporal and trend distribution of drought occurrence. Drought frequency was estimated as the ratio of a defined severity to its total number of events. The change in drought events was detected using a non-parametric man-Kendall trend test. The main drought conditions detected by SPI and EDI are severe drought, moderate drought, near normal, moderate wet, very wet and extremely wet conditions. From the results the average drought frequency between 1970 and 2010 for the south-eastern and north-western areas ranged from 12.16 to 14.93 and 3.82 to 6.63 percent respectively. The Mann-Kendall trend test show that drought trend increased in the south-eastern parts of the basin at 90% and 95% significant levels. However, there was no significant trend that was detected in the North-western areas. This is an indication that the south-eastern parts are more drought-prone areas compared to the North-western areas of the upper Tana River basin. Both the SPI and the EDI were effective in detecting the on-set of drought, description of the temporal variability, severity and spatial extent across the basin. It is recommended that the findings be adopted for decision making for drought-early warning systems in the river basin.
