In order to detect web shells that hackers inject into web servers by exploiting system vulnerabilities or web page open sources, a novel web shell detection system based on the scoring scheme is proposed, named Evil-...In order to detect web shells that hackers inject into web servers by exploiting system vulnerabilities or web page open sources, a novel web shell detection system based on the scoring scheme is proposed, named Evil-hunter. First, a large set of malicious function samples normally used in web shells are collected from various sources on the Internet and security forums. Secondly, according to the danger level and the frequency of using these malicious functions in the web shells as well as in legal web applications, an assigning score strategy for each malicious sample is devised. Then, the appropriate score threshold value for each sample is obtained from the results of a statistical analysis. Finally, based on the threshold value, a simple algorithm is presented to identify files that contain web shells in web applications. The experimental results show that compared with other approaches, Evil-hunter can identify web shells more efficiently and accurately.展开更多
Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite （TAN...Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite （TANSAT）, a cloud-screening scheme was presented for the Cloud and Aerosol Polarization Imager （CAPI）, which only performs measurements in five channels located in the visible to near-infrared regions of the spectrum. The scheme for CAPI, based on previous cloud- screening algorithms, defines a method to regroup individual threshold tests for each pixel in a scene according to the derived clear confidence level. This scheme is proven to be more effective for sensors with few channels. The work relies upon the radiance data from the Visible and Infrared Radiometer （VIRR） onboard the Chinese FengYun-3A Polar-orbiting Meteoro- logical Satellite （FY-3A）, which uses four wavebands similar to that of CAPI and can serve as a proxy for its measurements. The scheme has been applied to a number of the VIRR scenes over four target areas （desert, snow, ocean, forest） for all seasons. To assess the screening results, comparisons against the cloud-screening product from MODIS are made. The evaluation suggests that the proposed scheme inherits the advantages of schemes described in previous publications and shows improved cloud-screening results. A seasonal analysis reveals that this scheme provides better performance during warmer seasons, except for observations over oceans, where results are much better in colder seasons.展开更多
The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detecti...The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detection scheme for the satellite-based AIS signal transmitted over the white Gaussian noise channel. Based on the maximum likelihood estimation and a Viterbi decoder, the proposed scheme is capable of tolerating a frequency offset up to 5% of the symbol rate. The complexity of the proposed scheme is reduced by the state-complexity reduction, which is based on per-survivor processing. Simulation results prove that the proposed non-coherent sequence detection scheme has high robustness to frequency offset compared to the relative scheme when messages collision exists.展开更多
Wavelet transform is an ideal way for edge detection because of its multi-scale property, localization both in time and frequency domain, sensitivity to the abrupt change of signals, and so on. An improved algorithm f...Wavelet transform is an ideal way for edge detection because of its multi-scale property, localization both in time and frequency domain, sensitivity to the abrupt change of signals, and so on. An improved algorithm for image edge detection based on Lifting Scheme is proposed in this paper. The simulation results show that our improved method can better reflect edge information of images.展开更多
An Adaptive Measurement Scheme (AMS) is investigated with Compressed Sensing (CS) theory in Cognitive Wireless Sensor Network (C-WSN). Local sensing information is collected via energy detection with Analog-to-Informa...An Adaptive Measurement Scheme (AMS) is investigated with Compressed Sensing (CS) theory in Cognitive Wireless Sensor Network (C-WSN). Local sensing information is collected via energy detection with Analog-to-Information Converter (AIC) at massive cognitive sensors, and sparse representation is considered with the exploration of spatial temporal correlation structure of detected signals. Adaptive measurement matrix is designed in AMS, which is based on maximum energy subset selection. Energy subset is calculated with sparse transformation of sensing information, and maximum energy subset is selected as the row vector of adaptive measurement matrix. In addition, the measurement matrix is constructed by orthogonalization of those selected row vectors, which also satisfies the Restricted Isometry Property (RIP) in CS theory. Orthogonal Matching Pursuit (OMP) reconstruction algorithm is implemented at sink node to recover original information. Simulation results are performed with the comparison of Random Measurement Scheme (RMS). It is revealed that, signal reconstruction effect based on AMS is superior to conventional RMS Gaussian measurement. Moreover, AMS has better detection performance than RMS at lower compression rate region, and it is suitable for large-scale C-WSN wideband spectrum sensing.展开更多
Structural damage detection is hard to conduct in large-scale civil structures due to enormous structural data and insufficient damage features.To improve this situation,a damage detection method based on model reduct...Structural damage detection is hard to conduct in large-scale civil structures due to enormous structural data and insufficient damage features.To improve this situation,a damage detection method based on model reduction and response reconstruction is presented.Based on the framework of two-step model updating including substructure-level localization and element-level detection,the response reconstruction strategy with an improved sensitivity algorithm is presented to conveniently complement modal information and promote the reliability of model updating.In the iteration process,the reconstructed response is involved in the sensitivity algorithm as a reconstruction-related item.Besides,model reduction is applied to reduce computational degrees of freedom(DOFs)in each detection step.A numerical truss bridge is modelled to vindicate the effectiveness and efficiency of the method.The results showed that the presented method reduces the requirement for installed sensors while improving efficiency and ensuring accuracy of damage detection compared to traditional methods.展开更多
With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, i...With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, its anonymity has provided new ways for Ponzi schemes to commit fraud, posing significant risks to investors. Current research still has some limitations, for example, Ponzi schemes are difficult to detect in the early stages of smart contract deployment, and data imbalance is not considered. In addition, there is room for improving the detection accuracy. To address the above issues, this paper proposes LT-SPSD (LSTM-Transformer smart Ponzi schemes detection), which is a Ponzi scheme detection method that combines Long Short-Term Memory (LSTM) and Transformer considering the time-series transaction information of smart contracts as well as the global information. Based on the verified smart contract addresses, account features, and code features are extracted to construct a feature dataset, and the SMOTE-Tomek algorithm is used to deal with the imbalanced data classification problem. By comparing our method with the other four typical detection methods in the experiment, the LT-SPSD method shows significant performance improvement in precision, recall, and F1-score. The results of the experiment confirm the efficacy of the model, which has some application value in Ethereum Ponzi scheme smart contract detection.展开更多
Lifting scheme is a useful and very general technique for constructing wavelet decomposition.The paper adapts the lifting into redundant lifting to obtain shift invariant wavelet transform.In prediction and update sta...Lifting scheme is a useful and very general technique for constructing wavelet decomposition.The paper adapts the lifting into redundant lifting to obtain shift invariant wavelet transform.In prediction and update stages of the lifting morphological operator is adopted for preserving local maxima of a signal over several scales,which is particularly useful in wavelet\|based signal detec tion.The new transform presented in the paper is applied in multiresoluti on edge detection of medical image and experim ent results are given to show better performance and applicable potentiali ty.展开更多
The accelerating factor （AF） method is a simple and appropriate way to investigate the atomic long-time deep diffusion at solid-solid interface. In the framework of AF hyperdynamics （HD） simulation, the relationsh...The accelerating factor （AF） method is a simple and appropriate way to investigate the atomic long-time deep diffusion at solid-solid interface. In the framework of AF hyperdynamics （HD） simulation, the relationship between the diffusion coefficient along the direction of z-axis which is normal to the Mg/Zn interface and temperature was investigated, and the AF＇s impact on the diffusion constant （D0） and activation energy （Q^＊） was studied. Then, two steps were taken to simulate the atomic diffusion process and the formation of new phases： one for acceleration and the other for equilibration. The results show that： the Arrhenius equation works well for the description of Dz with different accelerating factors; the AF has no effect on the diffusion constant Do in the case of no phase transition; and the relationship between Q＊ and Q conforms to Q^＊=Q/A. Then, the new Arrhenius equation for AFHD is successfully constructed as Dz=Doexp[-Q/（ART）]. Meanwhile, the authentic equilibrium conformations at any dynamic moment can only be reproduced by the equilibration simulation of the HD-simulated configurations. Key words： accelerating factor method; Arrhenius equation; two-steps scheme; Mg/Zn interface; hyperdynamic simulation展开更多
The emergence of smart contracts has increased the attention of industry and academia to blockchain technology,which is tamper-proofing,decentralized,autonomous,and enables decentralized applications to operate in unt...The emergence of smart contracts has increased the attention of industry and academia to blockchain technology,which is tamper-proofing,decentralized,autonomous,and enables decentralized applications to operate in untrustworthy environments.However,these features of this technology are also easily exploited by unscrupulous individuals,a typical example of which is the Ponzi scheme in Ethereum.The negative effect of unscrupulous individuals writing Ponzi scheme-type smart contracts in Ethereum and then using these contracts to scam large amounts of money has been significant.To solve this problem,we propose a detection model for detecting Ponzi schemes in smart contracts using bytecode.In this model,our innovation is shown in two aspects:We first propose to use two bytes as one characteristic,which can quickly transform the bytecode into a high-dimensional matrix,and this matrix contains all the implied characteristics in the bytecode.Then,We innovatively transformed the Ponzi schemes detection into an anomaly detection problem.Finally,an anomaly detection algorithm is used to identify Ponzi schemes in smart contracts.Experimental results show that the proposed detection model can greatly improve the accuracy of the detection of the Ponzi scheme contracts.Moreover,the F1-score of this model can reach 0.88,which is far better than those of other traditional detection models.展开更多
Many modeling approaches have been proposed to help forecast and detect incidents. Accident has received the most attention from researchers due to its impacts economically. The traffic congestion costs billions of do...Many modeling approaches have been proposed to help forecast and detect incidents. Accident has received the most attention from researchers due to its impacts economically. The traffic congestion costs billions of dollars to economy. The main reasons of major percentage of traffic congestion are the incidents. Road accidents continue to increase in digital age. There are many reasons for road accidents. This paper will discuss and introduce new algorithm for road accident detection. Various forecast schemes have been proposed to manage the traffic data. In this paper we will introduce road accident detection scheme based on improved exponential moving average. The proposed traffic incident detection algorithm is based on the automatic exponential moving average scheme. The detection algorithm is based on analyzing the collected traffic flow parameters. The detection algorithm is based on analyzing the collected traffic flow parameters. In addition a real-time accident forecast model was developed based on short-term variation of traffic flow characteristics.展开更多
Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the eff...Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems.We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this.This strategy is devised to streamline the data retrieval path,subsequently diminishing network strain.Crafting an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation tactics.This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge devices.The system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health anomalies.Given the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during crises.This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times.Furthermore,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize utility.Addressing the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a solution.Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark algorithms.The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution.To encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection system.Our methodology yields enhanced cache efficiency and data freshness.The corroborative numerical data accentuates the feasibility and relevance of our model,casting a beacon for the future trajectory of real-time health data monitoring systems.展开更多
Cognitive radio systems are helpful to access the unused spectrum using the popular technique, referred to as spectrum sensing. Spectrum sensing involves the detection of primary user (PU) signal using dynamic spectru...Cognitive radio systems are helpful to access the unused spectrum using the popular technique, referred to as spectrum sensing. Spectrum sensing involves the detection of primary user (PU) signal using dynamic spectrum access. Cooperative spectrum sensing takes advantage of the spatial diversity in multiple cognitive radio user networks to improve the sensing accuracy. Though the cooperative spectrum sensing schemes significantly improve the sensing accuracy, it requires the noise variance and channel state information which may lead to transmission overhead. To overcome the drawbacks in conventional cooperative spectrum sensing, this paper proposes a fuzzy system based cooperative spectrum sensing. Selection combining (SC) and maximum ratio combining (MRC) are used at fuzzy based fusion center to obtain the value of the sensing energy. These energy values are utilized in finding the presence of PU, results in improved sensing accuracy. In addition, an intelligent fuzzy fusion algorithm determines the PU presence without the channel state information based on multiple threshold values. Simulation results show that the proposed scheme outperforms the existing schemes in terms of sensing accuracy.展开更多
This paper aims to design a radar acoustic alarm including a circular antenna that emits microwave signals and sends a low frequency signal when receiving a reflected echo within a certain distance: radar detection mo...This paper aims to design a radar acoustic alarm including a circular antenna that emits microwave signals and sends a low frequency signal when receiving a reflected echo within a certain distance: radar detection module, triggered by the low frequency signal sent by the annular antenna and the signal output control signal: analog acoustic and relay execution module driven by the control signal of the radar detection module emit acoustic and optical alarm. Due to the use of the TWH9250 radar detection module, the distance of detection can be adjusted within 2-7m: the photocell can also control the alarm to only enter the monitoring state at night. The alarm circuit of the utility model is simple and easy to make with stable operation, high sensitivity and strong reliability andhas strong warning through sound and light alarm.展开更多
This paper deals with an efficient two-step time split explicit/implicit scheme applied to a two-dimensional nonlinear unsteady convection-diffusionreaction equation.The computational cost of the new algorithm at each...This paper deals with an efficient two-step time split explicit/implicit scheme applied to a two-dimensional nonlinear unsteady convection-diffusionreaction equation.The computational cost of the new algorithm at each time level is equivalent to solving a pentadiagonalmatrix equation with strictly dominant diagonal elements.Such a bandwidth matrix can be easily inverted using the Gaussian Decomposition and the corresponding linear system should be solved by the back substitutionmethod.The proposed approach is unconditionally stable,temporal second-order accuracy and fourth-order convergence in space.These results suggest that the developed technique is faster and more efficient than a large class of numerical methods studied in the literature for the considered initial-boundary value problem.Numerical experiments are carried out to confirm the theoretical analysis and to demonstrate the performance of the constructed numerical scheme.展开更多
Strong-field terahertz(THz) radiation holds significant potential in non-equilibrium state manipulation, electron acceleration, and biomedical effects. However, distortion-free detection of strong-field THz waveforms ...Strong-field terahertz(THz) radiation holds significant potential in non-equilibrium state manipulation, electron acceleration, and biomedical effects. However, distortion-free detection of strong-field THz waveforms remains an essential challenge in THz science and technology. To address this issue, we propose a ferromagnetic detection scheme based on Zeeman torque sampling, achieving distortion-free strong-field THz waveform detection in Py films. Thickness-dependent characterization(3–21 nm) identifies peak detection performance at 21 nm within the investigated range. Furthermore, by structurally engineering the Py ferromagnetic layer, we demonstrate strong-field THz detection in symmetric Ta(3 nm)/Py(9 nm)/Ta(3 nm) heterostructure while simultaneously resolving Zeeman torque responses and collective spin-wave dynamics in asymmetric W(4 nm)/Py(9 nm)/Pt(2 nm)heterostructure. We calculated spin wave excitations and spin orbit torque distributions in asymmetric heterostructures, along with spin wave excitations in symmetric modes. This approach overcomes the sensitivity limitations of conventional techniques in strong-field conditions.展开更多
TOD 项目盖上物业施工前,建设单位为了解既有车场或者车站的工程质量是否满足原设计要求,以及结构预留的柱头、钢筋等是否满足后续使用要求,委托检测单位对既有盖下项目进行工程质量检测。以重庆轨道交通四公里停车场为例,针对与检测相...TOD 项目盖上物业施工前,建设单位为了解既有车场或者车站的工程质量是否满足原设计要求,以及结构预留的柱头、钢筋等是否满足后续使用要求,委托检测单位对既有盖下项目进行工程质量检测。以重庆轨道交通四公里停车场为例,针对与检测相关的检测方案、现场检测内容以及结构工程质量分析等三大过程进行了探讨,为专业人员进行 TOD 项目的检测施工提供参考。展开更多
Sugarcane mechanized planting technology consists of seed preparation and field planting.This study aims at the issues of easy damage to the seeds during the operation of the automatic cutting machine for single-bud s...Sugarcane mechanized planting technology consists of seed preparation and field planting.This study aims at the issues of easy damage to the seeds during the operation of the automatic cutting machine for single-bud segment sugarcane,lack of intelligent seed selection and calibration technology,low recognition accuracy,and the need for manual feeding of the planting machine’s seed meter which leads to seed leakage.This study,based on machine vision and deep learning,optimizes the seed calibration method and proposes an improved YoloV5-STD target detection algorithm to improve the recognition accuracy of seed characteristics and optimize the overall engineering structure.For the planting machine,a new type of hopper for the seed meter is designed using natural rubber as the base material mixed with polystyrene,and the flexible automatic seed metering mechanism is analyzed to achieve automatic feeding and seed metering.Test assessment indicators were formulated based on the enterprise standards of the Institute of Agricultural Machinery Research,Chinese Academy of Tropical Agricultural Sciences.Experimental results show that the recognition accuracy of the 2DZ-2 type single-bud segment intelligent cutting machine is≥95%,the bud injury rate is<1.8%,the qualified rate of cutting is 95.8%,and the single-channel cutting efficiency is 64 buds/min.The 2CZD-2C type single-bud segment planter has a planting qualification rate of 96.6%,a planting efficiency of 208 buds/min,and a seed leakage rate of<2.1%.展开更多
基金The Science and Technology Support Program of Jiangsu Province(No.BE2011173)the Future Network Proactive Program of Jiangsu Province(No.BY2013095-5-03)the Program for Special Talent in Six Fields of Jiangsu Province(No.2011-DZ024)
文摘In order to detect web shells that hackers inject into web servers by exploiting system vulnerabilities or web page open sources, a novel web shell detection system based on the scoring scheme is proposed, named Evil-hunter. First, a large set of malicious function samples normally used in web shells are collected from various sources on the Internet and security forums. Secondly, according to the danger level and the frequency of using these malicious functions in the web shells as well as in legal web applications, an assigning score strategy for each malicious sample is devised. Then, the appropriate score threshold value for each sample is obtained from the results of a statistical analysis. Finally, based on the threshold value, a simple algorithm is presented to identify files that contain web shells in web applications. The experimental results show that compared with other approaches, Evil-hunter can identify web shells more efficiently and accurately.
基金sponsored by the National Basic Research(973)Program of China from the Ministry of Science and Technology of China(Grant No.2013CB430104)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA05040201)
文摘Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite （TANSAT）, a cloud-screening scheme was presented for the Cloud and Aerosol Polarization Imager （CAPI）, which only performs measurements in five channels located in the visible to near-infrared regions of the spectrum. The scheme for CAPI, based on previous cloud- screening algorithms, defines a method to regroup individual threshold tests for each pixel in a scene according to the derived clear confidence level. This scheme is proven to be more effective for sensors with few channels. The work relies upon the radiance data from the Visible and Infrared Radiometer （VIRR） onboard the Chinese FengYun-3A Polar-orbiting Meteoro- logical Satellite （FY-3A）, which uses four wavebands similar to that of CAPI and can serve as a proxy for its measurements. The scheme has been applied to a number of the VIRR scenes over four target areas （desert, snow, ocean, forest） for all seasons. To assess the screening results, comparisons against the cloud-screening product from MODIS are made. The evaluation suggests that the proposed scheme inherits the advantages of schemes described in previous publications and shows improved cloud-screening results. A seasonal analysis reveals that this scheme provides better performance during warmer seasons, except for observations over oceans, where results are much better in colder seasons.
文摘The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detection scheme for the satellite-based AIS signal transmitted over the white Gaussian noise channel. Based on the maximum likelihood estimation and a Viterbi decoder, the proposed scheme is capable of tolerating a frequency offset up to 5% of the symbol rate. The complexity of the proposed scheme is reduced by the state-complexity reduction, which is based on per-survivor processing. Simulation results prove that the proposed non-coherent sequence detection scheme has high robustness to frequency offset compared to the relative scheme when messages collision exists.
文摘Wavelet transform is an ideal way for edge detection because of its multi-scale property, localization both in time and frequency domain, sensitivity to the abrupt change of signals, and so on. An improved algorithm for image edge detection based on Lifting Scheme is proposed in this paper. The simulation results show that our improved method can better reflect edge information of images.
基金Supported by the National Natural Science Foundation of China (No. 61102066, 60972058)the China Postdoctoral Science Foundation (No. 2012M511365)the Scientific Research Project of Zhejiang Provincial Education Department (No. Y201119890)
文摘An Adaptive Measurement Scheme (AMS) is investigated with Compressed Sensing (CS) theory in Cognitive Wireless Sensor Network (C-WSN). Local sensing information is collected via energy detection with Analog-to-Information Converter (AIC) at massive cognitive sensors, and sparse representation is considered with the exploration of spatial temporal correlation structure of detected signals. Adaptive measurement matrix is designed in AMS, which is based on maximum energy subset selection. Energy subset is calculated with sparse transformation of sensing information, and maximum energy subset is selected as the row vector of adaptive measurement matrix. In addition, the measurement matrix is constructed by orthogonalization of those selected row vectors, which also satisfies the Restricted Isometry Property (RIP) in CS theory. Orthogonal Matching Pursuit (OMP) reconstruction algorithm is implemented at sink node to recover original information. Simulation results are performed with the comparison of Random Measurement Scheme (RMS). It is revealed that, signal reconstruction effect based on AMS is superior to conventional RMS Gaussian measurement. Moreover, AMS has better detection performance than RMS at lower compression rate region, and it is suitable for large-scale C-WSN wideband spectrum sensing.
基金Projects(51925808,52078504)supported by the National Natural Science Foundation of ChinaProject(2022JJ10082)supported by the Natural Science Fund for Distinguished Young Scholar of Hunan Province,ChinaProject(2021RC3016)supported by the Science and Technology Innovation Program of Hunan Province,China。
文摘Structural damage detection is hard to conduct in large-scale civil structures due to enormous structural data and insufficient damage features.To improve this situation,a damage detection method based on model reduction and response reconstruction is presented.Based on the framework of two-step model updating including substructure-level localization and element-level detection,the response reconstruction strategy with an improved sensitivity algorithm is presented to conveniently complement modal information and promote the reliability of model updating.In the iteration process,the reconstructed response is involved in the sensitivity algorithm as a reconstruction-related item.Besides,model reduction is applied to reduce computational degrees of freedom(DOFs)in each detection step.A numerical truss bridge is modelled to vindicate the effectiveness and efficiency of the method.The results showed that the presented method reduces the requirement for installed sensors while improving efficiency and ensuring accuracy of damage detection compared to traditional methods.
基金This work was granted by Qin Xin Talents Cultivation Program(No.QXTCP C202115)Beijing Information Science and Technology University+1 种基金the Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Fund(No.GJJ-23)National Social Science Foundation,China(No.21BTQ079).
文摘With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, its anonymity has provided new ways for Ponzi schemes to commit fraud, posing significant risks to investors. Current research still has some limitations, for example, Ponzi schemes are difficult to detect in the early stages of smart contract deployment, and data imbalance is not considered. In addition, there is room for improving the detection accuracy. To address the above issues, this paper proposes LT-SPSD (LSTM-Transformer smart Ponzi schemes detection), which is a Ponzi scheme detection method that combines Long Short-Term Memory (LSTM) and Transformer considering the time-series transaction information of smart contracts as well as the global information. Based on the verified smart contract addresses, account features, and code features are extracted to construct a feature dataset, and the SMOTE-Tomek algorithm is used to deal with the imbalanced data classification problem. By comparing our method with the other four typical detection methods in the experiment, the LT-SPSD method shows significant performance improvement in precision, recall, and F1-score. The results of the experiment confirm the efficacy of the model, which has some application value in Ethereum Ponzi scheme smart contract detection.
基金Supported by the National Natural Science Foundation dation of China(69983005)
文摘Lifting scheme is a useful and very general technique for constructing wavelet decomposition.The paper adapts the lifting into redundant lifting to obtain shift invariant wavelet transform.In prediction and update stages of the lifting morphological operator is adopted for preserving local maxima of a signal over several scales,which is particularly useful in wavelet\|based signal detec tion.The new transform presented in the paper is applied in multiresoluti on edge detection of medical image and experim ent results are given to show better performance and applicable potentiali ty.
基金Project (2012CB722805) supported by the National Basic Research Program of ChinaProjects (50974083, 51174131) supported by the National Natural Science Foundation of China+1 种基金Project (50774112) supported by the Joint Fund of NSFC and Baosteel, ChinaProject(07QA4021) supported by the Shanghai "Phosphor" Science Foundation, China
文摘The accelerating factor （AF） method is a simple and appropriate way to investigate the atomic long-time deep diffusion at solid-solid interface. In the framework of AF hyperdynamics （HD） simulation, the relationship between the diffusion coefficient along the direction of z-axis which is normal to the Mg/Zn interface and temperature was investigated, and the AF＇s impact on the diffusion constant （D0） and activation energy （Q^＊） was studied. Then, two steps were taken to simulate the atomic diffusion process and the formation of new phases： one for acceleration and the other for equilibration. The results show that： the Arrhenius equation works well for the description of Dz with different accelerating factors; the AF has no effect on the diffusion constant Do in the case of no phase transition; and the relationship between Q＊ and Q conforms to Q^＊=Q/A. Then, the new Arrhenius equation for AFHD is successfully constructed as Dz=Doexp[-Q/（ART）]. Meanwhile, the authentic equilibrium conformations at any dynamic moment can only be reproduced by the equilibration simulation of the HD-simulated configurations. Key words： accelerating factor method; Arrhenius equation; two-steps scheme; Mg/Zn interface; hyperdynamic simulation
基金This work was supported by the Scientific and Technological Project of Henan Province(Grant No.202102310340)Foundation of University Young Key Teacher of Henan Province(Grant Nos.2019GGJS040,2020GGJS027)+1 种基金Key Scientific Research Projects of Colleges and Universities in Henan Province(Grant No.21A110005)National Natual Science Foundation of China(61701170).
文摘The emergence of smart contracts has increased the attention of industry and academia to blockchain technology,which is tamper-proofing,decentralized,autonomous,and enables decentralized applications to operate in untrustworthy environments.However,these features of this technology are also easily exploited by unscrupulous individuals,a typical example of which is the Ponzi scheme in Ethereum.The negative effect of unscrupulous individuals writing Ponzi scheme-type smart contracts in Ethereum and then using these contracts to scam large amounts of money has been significant.To solve this problem,we propose a detection model for detecting Ponzi schemes in smart contracts using bytecode.In this model,our innovation is shown in two aspects:We first propose to use two bytes as one characteristic,which can quickly transform the bytecode into a high-dimensional matrix,and this matrix contains all the implied characteristics in the bytecode.Then,We innovatively transformed the Ponzi schemes detection into an anomaly detection problem.Finally,an anomaly detection algorithm is used to identify Ponzi schemes in smart contracts.Experimental results show that the proposed detection model can greatly improve the accuracy of the detection of the Ponzi scheme contracts.Moreover,the F1-score of this model can reach 0.88,which is far better than those of other traditional detection models.
文摘Many modeling approaches have been proposed to help forecast and detect incidents. Accident has received the most attention from researchers due to its impacts economically. The traffic congestion costs billions of dollars to economy. The main reasons of major percentage of traffic congestion are the incidents. Road accidents continue to increase in digital age. There are many reasons for road accidents. This paper will discuss and introduce new algorithm for road accident detection. Various forecast schemes have been proposed to manage the traffic data. In this paper we will introduce road accident detection scheme based on improved exponential moving average. The proposed traffic incident detection algorithm is based on the automatic exponential moving average scheme. The detection algorithm is based on analyzing the collected traffic flow parameters. The detection algorithm is based on analyzing the collected traffic flow parameters. In addition a real-time accident forecast model was developed based on short-term variation of traffic flow characteristics.
基金supported by National Natural Science Foundation of China(NSFC)under Grant Number T2350710232.
文摘Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems.We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this.This strategy is devised to streamline the data retrieval path,subsequently diminishing network strain.Crafting an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation tactics.This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge devices.The system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health anomalies.Given the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during crises.This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times.Furthermore,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize utility.Addressing the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a solution.Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark algorithms.The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution.To encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection system.Our methodology yields enhanced cache efficiency and data freshness.The corroborative numerical data accentuates the feasibility and relevance of our model,casting a beacon for the future trajectory of real-time health data monitoring systems.
文摘Cognitive radio systems are helpful to access the unused spectrum using the popular technique, referred to as spectrum sensing. Spectrum sensing involves the detection of primary user (PU) signal using dynamic spectrum access. Cooperative spectrum sensing takes advantage of the spatial diversity in multiple cognitive radio user networks to improve the sensing accuracy. Though the cooperative spectrum sensing schemes significantly improve the sensing accuracy, it requires the noise variance and channel state information which may lead to transmission overhead. To overcome the drawbacks in conventional cooperative spectrum sensing, this paper proposes a fuzzy system based cooperative spectrum sensing. Selection combining (SC) and maximum ratio combining (MRC) are used at fuzzy based fusion center to obtain the value of the sensing energy. These energy values are utilized in finding the presence of PU, results in improved sensing accuracy. In addition, an intelligent fuzzy fusion algorithm determines the PU presence without the channel state information based on multiple threshold values. Simulation results show that the proposed scheme outperforms the existing schemes in terms of sensing accuracy.
文摘This paper aims to design a radar acoustic alarm including a circular antenna that emits microwave signals and sends a low frequency signal when receiving a reflected echo within a certain distance: radar detection module, triggered by the low frequency signal sent by the annular antenna and the signal output control signal: analog acoustic and relay execution module driven by the control signal of the radar detection module emit acoustic and optical alarm. Due to the use of the TWH9250 radar detection module, the distance of detection can be adjusted within 2-7m: the photocell can also control the alarm to only enter the monitoring state at night. The alarm circuit of the utility model is simple and easy to make with stable operation, high sensitivity and strong reliability andhas strong warning through sound and light alarm.
文摘This paper deals with an efficient two-step time split explicit/implicit scheme applied to a two-dimensional nonlinear unsteady convection-diffusionreaction equation.The computational cost of the new algorithm at each time level is equivalent to solving a pentadiagonalmatrix equation with strictly dominant diagonal elements.Such a bandwidth matrix can be easily inverted using the Gaussian Decomposition and the corresponding linear system should be solved by the back substitutionmethod.The proposed approach is unconditionally stable,temporal second-order accuracy and fourth-order convergence in space.These results suggest that the developed technique is faster and more efficient than a large class of numerical methods studied in the literature for the considered initial-boundary value problem.Numerical experiments are carried out to confirm the theoretical analysis and to demonstrate the performance of the constructed numerical scheme.
基金supported by the Scientific Research Innovation Capability Support Project for Young Faculty (Grant No.ZYGXQNJSKYCXNLZCXMI3)the National Key Research and Development Program of China (Grant No.2022YFA1604402)+1 种基金the National Natural Science Foundation of China (Grant Nos.U23A6002,92250307,and 52225106)the Beijing Municipal Science and Technology Commission,Administrative Commission of Zhongguancun Science Park (Grant No.Z25110000692500)。
文摘Strong-field terahertz(THz) radiation holds significant potential in non-equilibrium state manipulation, electron acceleration, and biomedical effects. However, distortion-free detection of strong-field THz waveforms remains an essential challenge in THz science and technology. To address this issue, we propose a ferromagnetic detection scheme based on Zeeman torque sampling, achieving distortion-free strong-field THz waveform detection in Py films. Thickness-dependent characterization(3–21 nm) identifies peak detection performance at 21 nm within the investigated range. Furthermore, by structurally engineering the Py ferromagnetic layer, we demonstrate strong-field THz detection in symmetric Ta(3 nm)/Py(9 nm)/Ta(3 nm) heterostructure while simultaneously resolving Zeeman torque responses and collective spin-wave dynamics in asymmetric W(4 nm)/Py(9 nm)/Pt(2 nm)heterostructure. We calculated spin wave excitations and spin orbit torque distributions in asymmetric heterostructures, along with spin wave excitations in symmetric modes. This approach overcomes the sensitivity limitations of conventional techniques in strong-field conditions.
文摘TOD 项目盖上物业施工前,建设单位为了解既有车场或者车站的工程质量是否满足原设计要求,以及结构预留的柱头、钢筋等是否满足后续使用要求,委托检测单位对既有盖下项目进行工程质量检测。以重庆轨道交通四公里停车场为例,针对与检测相关的检测方案、现场检测内容以及结构工程质量分析等三大过程进行了探讨,为专业人员进行 TOD 项目的检测施工提供参考。
基金supported by the Project of Guangxi Zhuang Autonomous Region Key Technologies R&D Program(Grant No.GK AB23026069 and GN AB241484034)the Basic Scientific Research Expenses of Central Public Welfare Scientific Research Institutes(Grant No.1630132022001)+1 种基金the Basic Scientific Research Expenses of Chinese Academy of Tropical Agricultural Sciences(Grant No.1630132024004)the Zhanjiang Science and Technology Project(Grant No.2023A01009).
文摘Sugarcane mechanized planting technology consists of seed preparation and field planting.This study aims at the issues of easy damage to the seeds during the operation of the automatic cutting machine for single-bud segment sugarcane,lack of intelligent seed selection and calibration technology,low recognition accuracy,and the need for manual feeding of the planting machine’s seed meter which leads to seed leakage.This study,based on machine vision and deep learning,optimizes the seed calibration method and proposes an improved YoloV5-STD target detection algorithm to improve the recognition accuracy of seed characteristics and optimize the overall engineering structure.For the planting machine,a new type of hopper for the seed meter is designed using natural rubber as the base material mixed with polystyrene,and the flexible automatic seed metering mechanism is analyzed to achieve automatic feeding and seed metering.Test assessment indicators were formulated based on the enterprise standards of the Institute of Agricultural Machinery Research,Chinese Academy of Tropical Agricultural Sciences.Experimental results show that the recognition accuracy of the 2DZ-2 type single-bud segment intelligent cutting machine is≥95%,the bud injury rate is<1.8%,the qualified rate of cutting is 95.8%,and the single-channel cutting efficiency is 64 buds/min.The 2CZD-2C type single-bud segment planter has a planting qualification rate of 96.6%,a planting efficiency of 208 buds/min,and a seed leakage rate of<2.1%.
