Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effecti...Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effective solution, GPU-acceleration achieves the state-of-the-art result of 3.3×109 traversed edges per second on a NVIDIA Tesla C2050 GPU. A novel vertex frontier based GPU BFS algorithm is proposed, and its main features are three-fold. Firstly, to obtain a better workload balance for irregular graphs, a virtual-queue task decomposition and mapping strategy is introduced for vertex frontier expanding. Secondly, a global deduplicate detection scheme is proposed to remove reduplicative vertices from vertex frontier effectively. Finally, a GPU-based bottom-up BFS approach is employed to process large frontier. The experimental results demonstrate that the algorithm can achieve 10% improvement over the state-of-the-art method on diverse graphs. Especially, it exhibits 2-3 times speedup on low-diameter and scale-free graphs over the state-of-the-art on a NVIDIA Tesla K20 c GPU, reaching a peak traversal rate of 11.2×109 edges/s.展开更多
Many cognitive studies have indicated that the path simplicity may be as important as its distance travelled.However,the optimality of paths for current navigation system is often judged purely on the distance travell...Many cognitive studies have indicated that the path simplicity may be as important as its distance travelled.However,the optimality of paths for current navigation system is often judged purely on the distance travelled or time cost,and not the path simplicity.To balance these factors,this paper presented an algorithm to compute a path that not only possesses fewest turns but also is as short as possible by utilizing the breadth-first-search strategy.The proposed algorithm started searching from a starting point,and expanded layer by layer through searching zero-level reachable points until the endpoint is found,and then deleted unnecessary points in the reverse direction.The forward searching and backward cleaning strategies were presented to build a hierarchical graph of zero-level reachable points,and form a fewestturn-path graph(G^(*)).After that,a classic Dijkstra shortest path algorithm was executed on the G^(*) to obtain a fewestturn-and-shortest path.Comparing with the shortest path in Baidu map,the algorithm in this work has less than half of the turns but the nearly same length.The proposed fewest-turn-and-shortest path algorithm is proved to be more suitable for human beings according to human cognition research.展开更多
Ensuring the correctness of answers to substring queries has not been a concern for consumers working within the traditional confines of their own organisational infrastructure. This is due to the fact that organisati...Ensuring the correctness of answers to substring queries has not been a concern for consumers working within the traditional confines of their own organisational infrastructure. This is due to the fact that organisations generally trust their handling of their own data hosted on their own servers and networks. With cloud computing however, where both data and processing are delegated to unknown servers, guarantees of the correctness of queries need to be available. The verification of the results of substring searches has not been given much focus to date within the wider scope of data and query, verification. We present a verification scheme for existential substring searc, hes on text files, which is the first of its kind to satisfy the desired properties of authenticity, completeness, and freshness. The scheme is based on suffix arrays, Merkle hash trees and cryptographic hashes to provide strong guarantees of correctness for the consumer, even in fully untrusted environments. We provide a description of our scheme, along with the results of experiments conducted on a fully-working prototype.展开更多
Geologists explore the ground to locate mineral resources,investigate and characterise the properties and behaviour the soils and rocks as part of a geotechnical ground investigation and for geohazard assessments.Simi...Geologists explore the ground to locate mineral resources,investigate and characterise the properties and behaviour the soils and rocks as part of a geotechnical ground investigation and for geohazard assessments.Similarly,the police may search the ground to locate homicide graves,weapons,firearms,drugs or items of value that have been buried beneath the ground surface as part of a criminal or terrorist act.Historically,the methods and techniques used by geologists and law enforcement evolved separately.Conventionally,geologists and law enforcement officers worked in isolation to explore and investigate or search the ground.Over the past decade the authors,with different and complimentary capabilities,began working in collaboration during the search for a grave.This provided the opportunity and incentive for geological and law enforcement investigative strategies to be brought together.This has enabled the development of a high assurance ground search strategy.This paper provides an overview of ground searches how these have advanced and developed.展开更多
Many difficult engineering problems cannot be solved by the conventional optimization techniques in practice. Direct searches that need no recourse to explicit derivatives are revived and become popular since the new ...Many difficult engineering problems cannot be solved by the conventional optimization techniques in practice. Direct searches that need no recourse to explicit derivatives are revived and become popular since the new century. In order to get a deep insight into this field, some notes on the direct searches for non-smooth optimization problems are made. The global convergence vs. local convergence and their influences on expected solutions for simulation-based stochastic optimization are pointed out. The sufficient and simple decrease criteria for step acceptance are analyzed, and why simple decrease is enough for globalization in direct searches is identified. The reason to introduce the positive spanning set and its usage in direct searches is explained. Other topics such as the generalization of direct searches to bound, linear and non-linear constraints are also briefly discussed.展开更多
In this paper, we compute the non-detection probability of a randomly moving target by a stationary or moving searcher in a square search region. We find that when the searcher is stationary, the decay rate of the non...In this paper, we compute the non-detection probability of a randomly moving target by a stationary or moving searcher in a square search region. We find that when the searcher is stationary, the decay rate of the non-detection probability achieves the maximum value when the searcher is fixed at the center of the square search region;when both the searcher and the target diffuse with significant diffusion coefficients, the decay rate of the non-detection probability only depends on the sum of the diffusion coefficients of the target and searcher. When the searcher moves along prescribed deterministic tracks, our study shows that the fastest decay of the non-detection probability is achieved when the searcher scans horizontally and vertically.展开更多
In this paper,two methods are proposed to embed visual watermark into direct binary search(DBS)halftone images,which are called Adjusted Direct Binary Search(ADBS)and Dual Adjusted Direct Binary Search(DADBS).DADBS is...In this paper,two methods are proposed to embed visual watermark into direct binary search(DBS)halftone images,which are called Adjusted Direct Binary Search(ADBS)and Dual Adjusted Direct Binary Search(DADBS).DADBS is an improved version of ADBS.By using the proposed methods,the visual watermark will be embedded into two halftone images separately,thus,the watermark can be revealed when these two halftone images are overlaid.Experimental results show that both methods can achieve excellent image visual quality and decoded visual patterns.展开更多
For more than two decades rudimentary versions of the fixed sample and sequential search strategies have provided the primary theoretical foundation for the study of mate choice decisions by searchers. The theory that...For more than two decades rudimentary versions of the fixed sample and sequential search strategies have provided the primary theoretical foundation for the study of mate choice decisions by searchers. The theory that surrounds these models has expanded markedly over this time period. In this paper, we review and extend results derived from these models, with a focus on the empirical analysis of searcher behavior. The basic models are impractical for empirical purposes because they rely on the as- sumption that searchers--and, for applied purposes, researchers--assess prospective mates based on their quality, the fitness consequences of mate choice decisions. Here we expound versions of the models that are more empirically useful, reformulated to reflect decisions based on male phenotypic characters. For some organisms, it may be possible to use preference functions to de- rive predictions from the reformulated models and thereby avoid difficulties associated with the measurement of male quality per se. But predictions derived from the two models are difficult to differentiate empirically, regardless of how the models are formu- lated. Here we develop ideas that illustrate how this goal might be accomplished. In addition, we clarify how the variability of male quality should be evaluated and we extend what is known about how this variability influences searcher behavior under each model. More general difficulties associated with the empirical study of mate choice decisions by searchers are also discussed [Current Zoology 59 （2）： 184-199, 2013].展开更多
Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,curr...Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.展开更多
We studied the information search behaviors of Chinese consumers of miniature automobiles. First, we identified the main sources where consumers acquire or seek information about miniature automobiles and discussed th...We studied the information search behaviors of Chinese consumers of miniature automobiles. First, we identified the main sources where consumers acquire or seek information about miniature automobiles and discussed their extent of information search. Then, based on logistic regression and optimal scaling regression of statistics, we studied the influences of characteristics of consumers of miniature automobiles on the extent of information search and on Internet usage. The results indicate that consumers often utilize four sources to obtain information about miniature automobiles. The dominant information source for consumers is their friends/family, followed by dealers, newspapers, and TV. Age, occupation, education and income significantly affect the extent of information search, but gender and city of residence do not have significant impacts. Age, city of residence, occupation, education and income produce significant influences on Internet usage. Gender has an insignificant influence on whether a consumer uses the Internet to search for information.展开更多
THE ceremonious premiere was recently held of a Chinese film whose theme is the grim search by a policeman in a small town for his missing gun. The film is the maiden work of a young director. It starred Jiang Wen, cur-
In this paper,we give a review of direct detection searches reported by the DAMA(China as a Co-Ⅰ),and indirect detection searches reported by the ATIC(China as a Co-Ⅰ).We also outline the future plans of dark matter...In this paper,we give a review of direct detection searches reported by the DAMA(China as a Co-Ⅰ),and indirect detection searches reported by the ATIC(China as a Co-Ⅰ).We also outline the future plans of dark matter search in China.展开更多
Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement structures.The study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Ext...Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement structures.The study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input parameters.Also,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the models.The models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat rate.Model validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the SBS.Results show that these models accurately predict SBS,with LGBM providing outstanding performance.SHAP(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on SBS.Consequently,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.展开更多
The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making co...The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making collision avoidance significantly more challenging than that for space debris.Much existing research focuses on the continuous thrust model,whereas the impulsive maneuver model is more appropriate for long-duration and long-distance avoidance missions.Additionally,it is important to minimize the impact on the original mission while avoiding noncooperative targets.On the other hand,the existing avoidance algorithms are computationally complex and time-consuming especially with the limited computing capability of the on-board computer,posing challenges for practical engineering applications.To conquer these difficulties,this paper makes the following key contributions:(A)a turn-based(sequential decision-making)limited-area impulsive collision avoidance model considering the time delay of precision orbit determination is established for the first time;(B)a novel Selection Probability Learning Adaptive Search-depth Search Tree(SPL-ASST)algorithm is proposed for non-cooperative target avoidance,which improves the decision-making efficiency by introducing an adaptive-search-depth mechanism and a neural network into the traditional Monte Carlo Tree Search(MCTS).Numerical simulations confirm the effectiveness and efficiency of the proposed method.展开更多
In order to meet the urgent need of infrared search and track applications for accurate identification and positioning of infrared guidance aircraft,an active-detection mid-wave infrared search and track system(ADMWIR...In order to meet the urgent need of infrared search and track applications for accurate identification and positioning of infrared guidance aircraft,an active-detection mid-wave infrared search and track system(ADMWIRSTS)based on"cat-eye effect"was developed.The ADMWIRSTS mainly consists of both a light beam control subsystem and an infrared search and track subsystem.The light beam control subsystem uses an integrated opto-mechanical two-dimensional pointing mirror to realize the control function of the azimuth and pitch directions of the system,which can cover the whole airspace range of 360°×90°.The infrared search and track subsystem uses two mid-wave infrared cooled 640×512 focal plane detectors for co-aperture beam expanding,infrared and illumination laser beam combining,infrared search,and two-stage track opto-mechanical design.In this work,the system integration design and structural finite-element analysis were conducted,the search imaging and two-stage track imaging for external scenes were performed,and the active-detection technologies were experimentally verified in the laboratory.The experimental investigation results show that the system can realize the infrared search and track imaging,and the accurate identification and positioning of the mid-wave infrared guidance,or infrared detection system through the echo of the illumination laser.The aforementioned work has important technical significance and practical application value for the development of compactly-integrated high-precision infrared search and track,and laser suppression system,and has broad application prospects in the protection of equipment,assets and infrastructures.展开更多
An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-ste...An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-step converter consisting of a 6-bit coarse quantization and a 6-bit fine quantization,which supports a time resolution of 120 ps and multiphoton counting up to 2 GHz without a GHz reference frequency.The proposed hTDC is designed in 0.11μm CMOS process with an area consumption of 6900μm^(2).The data from a behavioral-level model is imported into the designed hTDC circuit for simulation verification.The post-simulation results show that the proposed hTDC achieves 0.8%depth precision in 9 m range for short-range system design specifications and 0.2%depth precision in 48 m range for long-range system design specifications.Under 30×10^(3) lux background light conditions,the proposed hTDC can be used for SPAD-based flash LiDAR sensor to achieve a frame rate to 40 fps with 200 ps resolution in 9 m range.展开更多
The Runge-Kutta optimiser(RUN)algorithm,renowned for its powerful optimisation capabilities,faces challenges in dealing with increasing complexity in real-world problems.Specifically,it shows deficiencies in terms of ...The Runge-Kutta optimiser(RUN)algorithm,renowned for its powerful optimisation capabilities,faces challenges in dealing with increasing complexity in real-world problems.Specifically,it shows deficiencies in terms of limited local exploration capabilities and less precise solutions.Therefore,this research aims to integrate the topological search(TS)mechanism with the gradient search rule(GSR)into the framework of RUN,introducing an enhanced algorithm called TGRUN to improve the performance of the original algorithm.The TS mechanism employs a circular topological scheme to conduct a thorough exploration of solution regions surrounding each solution,enabling a careful examination of valuable solution areas and enhancing the algorithm’s effectiveness in local exploration.To prevent the algorithm from becoming trapped in local optima,the GSR also integrates gradient descent principles to direct the algorithm in a wider investigation of the global solution space.This study conducted a serious of experiments on the IEEE CEC2017 comprehensive benchmark function to assess the enhanced effectiveness of TGRUN.Additionally,the evaluation includes real-world engineering design and feature selection problems serving as an additional test for assessing the optimisation capabilities of the algorithm.The validation outcomes indicate a significant improvement in the optimisation capabilities and solution accuracy of TGRUN.展开更多
基金Projects(61272142,61103082,61003075,61170261,61103193)supported by the National Natural Science Foundation of ChinaProject supported by the Program for New Century Excellent Talents in University of ChinaProjects(2012AA01A301,2012AA010901)supported by the National High Technology Research and Development Program of China
文摘Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effective solution, GPU-acceleration achieves the state-of-the-art result of 3.3×109 traversed edges per second on a NVIDIA Tesla C2050 GPU. A novel vertex frontier based GPU BFS algorithm is proposed, and its main features are three-fold. Firstly, to obtain a better workload balance for irregular graphs, a virtual-queue task decomposition and mapping strategy is introduced for vertex frontier expanding. Secondly, a global deduplicate detection scheme is proposed to remove reduplicative vertices from vertex frontier effectively. Finally, a GPU-based bottom-up BFS approach is employed to process large frontier. The experimental results demonstrate that the algorithm can achieve 10% improvement over the state-of-the-art method on diverse graphs. Especially, it exhibits 2-3 times speedup on low-diameter and scale-free graphs over the state-of-the-art on a NVIDIA Tesla K20 c GPU, reaching a peak traversal rate of 11.2×109 edges/s.
基金This research was supported by the National Natural Science Foundation of China(Nos.41471332 and 41101354)the National High Technology Research and Development Program of China(863 Program)(No.2013AA12A302)+1 种基金the Fundamental Research Funds for the Central Universities(No.ZYGX2011J077)the Fund of China Scholarship Council.
文摘Many cognitive studies have indicated that the path simplicity may be as important as its distance travelled.However,the optimality of paths for current navigation system is often judged purely on the distance travelled or time cost,and not the path simplicity.To balance these factors,this paper presented an algorithm to compute a path that not only possesses fewest turns but also is as short as possible by utilizing the breadth-first-search strategy.The proposed algorithm started searching from a starting point,and expanded layer by layer through searching zero-level reachable points until the endpoint is found,and then deleted unnecessary points in the reverse direction.The forward searching and backward cleaning strategies were presented to build a hierarchical graph of zero-level reachable points,and form a fewestturn-path graph(G^(*)).After that,a classic Dijkstra shortest path algorithm was executed on the G^(*) to obtain a fewestturn-and-shortest path.Comparing with the shortest path in Baidu map,the algorithm in this work has less than half of the turns but the nearly same length.The proposed fewest-turn-and-shortest path algorithm is proved to be more suitable for human beings according to human cognition research.
文摘Ensuring the correctness of answers to substring queries has not been a concern for consumers working within the traditional confines of their own organisational infrastructure. This is due to the fact that organisations generally trust their handling of their own data hosted on their own servers and networks. With cloud computing however, where both data and processing are delegated to unknown servers, guarantees of the correctness of queries need to be available. The verification of the results of substring searches has not been given much focus to date within the wider scope of data and query, verification. We present a verification scheme for existential substring searc, hes on text files, which is the first of its kind to satisfy the desired properties of authenticity, completeness, and freshness. The scheme is based on suffix arrays, Merkle hash trees and cryptographic hashes to provide strong guarantees of correctness for the consumer, even in fully untrusted environments. We provide a description of our scheme, along with the results of experiments conducted on a fully-working prototype.
文摘Geologists explore the ground to locate mineral resources,investigate and characterise the properties and behaviour the soils and rocks as part of a geotechnical ground investigation and for geohazard assessments.Similarly,the police may search the ground to locate homicide graves,weapons,firearms,drugs or items of value that have been buried beneath the ground surface as part of a criminal or terrorist act.Historically,the methods and techniques used by geologists and law enforcement evolved separately.Conventionally,geologists and law enforcement officers worked in isolation to explore and investigate or search the ground.Over the past decade the authors,with different and complimentary capabilities,began working in collaboration during the search for a grave.This provided the opportunity and incentive for geological and law enforcement investigative strategies to be brought together.This has enabled the development of a high assurance ground search strategy.This paper provides an overview of ground searches how these have advanced and developed.
基金supported by the Key Foundation of Southwest University for Nationalities(09NZD001).
文摘Many difficult engineering problems cannot be solved by the conventional optimization techniques in practice. Direct searches that need no recourse to explicit derivatives are revived and become popular since the new century. In order to get a deep insight into this field, some notes on the direct searches for non-smooth optimization problems are made. The global convergence vs. local convergence and their influences on expected solutions for simulation-based stochastic optimization are pointed out. The sufficient and simple decrease criteria for step acceptance are analyzed, and why simple decrease is enough for globalization in direct searches is identified. The reason to introduce the positive spanning set and its usage in direct searches is explained. Other topics such as the generalization of direct searches to bound, linear and non-linear constraints are also briefly discussed.
文摘In this paper, we compute the non-detection probability of a randomly moving target by a stationary or moving searcher in a square search region. We find that when the searcher is stationary, the decay rate of the non-detection probability achieves the maximum value when the searcher is fixed at the center of the square search region;when both the searcher and the target diffuse with significant diffusion coefficients, the decay rate of the non-detection probability only depends on the sum of the diffusion coefficients of the target and searcher. When the searcher moves along prescribed deterministic tracks, our study shows that the fastest decay of the non-detection probability is achieved when the searcher scans horizontally and vertically.
文摘In this paper,two methods are proposed to embed visual watermark into direct binary search(DBS)halftone images,which are called Adjusted Direct Binary Search(ADBS)and Dual Adjusted Direct Binary Search(DADBS).DADBS is an improved version of ADBS.By using the proposed methods,the visual watermark will be embedded into two halftone images separately,thus,the watermark can be revealed when these two halftone images are overlaid.Experimental results show that both methods can achieve excellent image visual quality and decoded visual patterns.
文摘For more than two decades rudimentary versions of the fixed sample and sequential search strategies have provided the primary theoretical foundation for the study of mate choice decisions by searchers. The theory that surrounds these models has expanded markedly over this time period. In this paper, we review and extend results derived from these models, with a focus on the empirical analysis of searcher behavior. The basic models are impractical for empirical purposes because they rely on the as- sumption that searchers--and, for applied purposes, researchers--assess prospective mates based on their quality, the fitness consequences of mate choice decisions. Here we expound versions of the models that are more empirically useful, reformulated to reflect decisions based on male phenotypic characters. For some organisms, it may be possible to use preference functions to de- rive predictions from the reformulated models and thereby avoid difficulties associated with the measurement of male quality per se. But predictions derived from the two models are difficult to differentiate empirically, regardless of how the models are formu- lated. Here we develop ideas that illustrate how this goal might be accomplished. In addition, we clarify how the variability of male quality should be evaluated and we extend what is known about how this variability influences searcher behavior under each model. More general difficulties associated with the empirical study of mate choice decisions by searchers are also discussed [Current Zoology 59 （2）： 184-199, 2013].
基金supported by the National Natural Science Foundation of China(NSFC)under Grant(No.51677058).
文摘Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.
基金the Natural Science Foundation of China ( No. 70472016).
文摘We studied the information search behaviors of Chinese consumers of miniature automobiles. First, we identified the main sources where consumers acquire or seek information about miniature automobiles and discussed their extent of information search. Then, based on logistic regression and optimal scaling regression of statistics, we studied the influences of characteristics of consumers of miniature automobiles on the extent of information search and on Internet usage. The results indicate that consumers often utilize four sources to obtain information about miniature automobiles. The dominant information source for consumers is their friends/family, followed by dealers, newspapers, and TV. Age, occupation, education and income significantly affect the extent of information search, but gender and city of residence do not have significant impacts. Age, city of residence, occupation, education and income produce significant influences on Internet usage. Gender has an insignificant influence on whether a consumer uses the Internet to search for information.
文摘THE ceremonious premiere was recently held of a Chinese film whose theme is the grim search by a policeman in a small town for his missing gun. The film is the maiden work of a young director. It starred Jiang Wen, cur-
文摘In this paper,we give a review of direct detection searches reported by the DAMA(China as a Co-Ⅰ),and indirect detection searches reported by the ATIC(China as a Co-Ⅰ).We also outline the future plans of dark matter search in China.
基金the University of Transport Technology under grant number DTTD2022-12.
文摘Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement structures.The study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input parameters.Also,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the models.The models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat rate.Model validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the SBS.Results show that these models accurately predict SBS,with LGBM providing outstanding performance.SHAP(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on SBS.Consequently,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.
基金co-supported by the Foundation of Shanghai Astronautics Science and Technology Innovation,China(No.SAST2022-114)the National Natural Science Foundation of China(No.62303378),the National Natural Science Foundation of China(Nos.124B2031,12202281)the Foundation of China National Key Laboratory of Science and Technology on Test Physics&Numerical Mathematics,China(No.08-YY-2023-R11)。
文摘The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making collision avoidance significantly more challenging than that for space debris.Much existing research focuses on the continuous thrust model,whereas the impulsive maneuver model is more appropriate for long-duration and long-distance avoidance missions.Additionally,it is important to minimize the impact on the original mission while avoiding noncooperative targets.On the other hand,the existing avoidance algorithms are computationally complex and time-consuming especially with the limited computing capability of the on-board computer,posing challenges for practical engineering applications.To conquer these difficulties,this paper makes the following key contributions:(A)a turn-based(sequential decision-making)limited-area impulsive collision avoidance model considering the time delay of precision orbit determination is established for the first time;(B)a novel Selection Probability Learning Adaptive Search-depth Search Tree(SPL-ASST)algorithm is proposed for non-cooperative target avoidance,which improves the decision-making efficiency by introducing an adaptive-search-depth mechanism and a neural network into the traditional Monte Carlo Tree Search(MCTS).Numerical simulations confirm the effectiveness and efficiency of the proposed method.
基金Supported by the Fundamental Scientific Research Plan of China(JCKY2021130B033)。
文摘In order to meet the urgent need of infrared search and track applications for accurate identification and positioning of infrared guidance aircraft,an active-detection mid-wave infrared search and track system(ADMWIRSTS)based on"cat-eye effect"was developed.The ADMWIRSTS mainly consists of both a light beam control subsystem and an infrared search and track subsystem.The light beam control subsystem uses an integrated opto-mechanical two-dimensional pointing mirror to realize the control function of the azimuth and pitch directions of the system,which can cover the whole airspace range of 360°×90°.The infrared search and track subsystem uses two mid-wave infrared cooled 640×512 focal plane detectors for co-aperture beam expanding,infrared and illumination laser beam combining,infrared search,and two-stage track opto-mechanical design.In this work,the system integration design and structural finite-element analysis were conducted,the search imaging and two-stage track imaging for external scenes were performed,and the active-detection technologies were experimentally verified in the laboratory.The experimental investigation results show that the system can realize the infrared search and track imaging,and the accurate identification and positioning of the mid-wave infrared guidance,or infrared detection system through the echo of the illumination laser.The aforementioned work has important technical significance and practical application value for the development of compactly-integrated high-precision infrared search and track,and laser suppression system,and has broad application prospects in the protection of equipment,assets and infrastructures.
基金National Key Research and Development Program of China(2022YFB2804401)。
文摘An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-step converter consisting of a 6-bit coarse quantization and a 6-bit fine quantization,which supports a time resolution of 120 ps and multiphoton counting up to 2 GHz without a GHz reference frequency.The proposed hTDC is designed in 0.11μm CMOS process with an area consumption of 6900μm^(2).The data from a behavioral-level model is imported into the designed hTDC circuit for simulation verification.The post-simulation results show that the proposed hTDC achieves 0.8%depth precision in 9 m range for short-range system design specifications and 0.2%depth precision in 48 m range for long-range system design specifications.Under 30×10^(3) lux background light conditions,the proposed hTDC can be used for SPAD-based flash LiDAR sensor to achieve a frame rate to 40 fps with 200 ps resolution in 9 m range.
基金Natural Science Foundation of Zhejiang Province,Grant/Award Numbers:LTGS23E070001,LZ22F020005,LTGY24C060004National Natural Science Foundation of China,Grant/Award Numbers:62076185,62301367,62273263。
文摘The Runge-Kutta optimiser(RUN)algorithm,renowned for its powerful optimisation capabilities,faces challenges in dealing with increasing complexity in real-world problems.Specifically,it shows deficiencies in terms of limited local exploration capabilities and less precise solutions.Therefore,this research aims to integrate the topological search(TS)mechanism with the gradient search rule(GSR)into the framework of RUN,introducing an enhanced algorithm called TGRUN to improve the performance of the original algorithm.The TS mechanism employs a circular topological scheme to conduct a thorough exploration of solution regions surrounding each solution,enabling a careful examination of valuable solution areas and enhancing the algorithm’s effectiveness in local exploration.To prevent the algorithm from becoming trapped in local optima,the GSR also integrates gradient descent principles to direct the algorithm in a wider investigation of the global solution space.This study conducted a serious of experiments on the IEEE CEC2017 comprehensive benchmark function to assess the enhanced effectiveness of TGRUN.Additionally,the evaluation includes real-world engineering design and feature selection problems serving as an additional test for assessing the optimisation capabilities of the algorithm.The validation outcomes indicate a significant improvement in the optimisation capabilities and solution accuracy of TGRUN.
