By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting ...By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting sort while maintaining the original stability. Compared with the original counting sort, it has a wider scope of application and better time and space efficiency. In addition, the accuracy of the above conclusions can be proved by a large amount of experimental data.展开更多
1 Introduction Estimating the number of triangles in a graph is a fundamental problem and has found applications in many fields.For example,in social network,it can help us understand how closely the local community s...1 Introduction Estimating the number of triangles in a graph is a fundamental problem and has found applications in many fields.For example,in social network,it can help us understand how closely the local community structure and nodes in the network are in close proximity.In this paper,we address this problem in the framework of graph streaming algorithms,which has received significant attention due to the increasing need to analyze large-scale graph data efficiently[1–3].However,most of these algorithms are not robust or are limited to unweighted graphs.展开更多
鱼群多目标准确计数是水生态智能监测和集约化养殖产业中的重要环节,对水域生态环境智能保护和水产养殖现代化具有重要作用。现有鱼群多目标准确追踪和计数方法主要适用于鱼群外观清晰、游速缓慢和方向稳定等较理想的情况,难以有效适用...鱼群多目标准确计数是水生态智能监测和集约化养殖产业中的重要环节,对水域生态环境智能保护和水产养殖现代化具有重要作用。现有鱼群多目标准确追踪和计数方法主要适用于鱼群外观清晰、游速缓慢和方向稳定等较理想的情况,难以有效适用于现实情况下存在的鱼群互相遮挡、游动迅速和方向多变等复杂情况。为此,结合轻量化目标检测模型YOLOv5n,提出基于水平相似度匹配机制的鱼群追踪与计数方法。将鱼群计数问题视为多目标检测与追踪问题,设计水平相似度匹配机制,并对SORT(Simple Online and Realtime Tracking)算法进行优化。通过高速水流中鱼群个体在帧与帧之间的位置关系对检测框中心点的水平距离进行限制,以有效解决SORT算法存在的目标匹配混乱问题,显著提高追踪效果。实验结果表明,所提方法在鱼群多目标追踪数据集上的性能显著优于现有追踪方法,对目标遮挡、方向变化等情况目标追踪性能提升显著,并且该方法结构简单,易于实际应用。展开更多
This study introduces a hybrid routing protocol,Low Energy Adaptive Clustering Hierarchy—Ant Colony Optimization—Genetic Algorithm(LEACH-ACO-GA),for wireless sensor networks.It combines regional ant colony optimizat...This study introduces a hybrid routing protocol,Low Energy Adaptive Clustering Hierarchy—Ant Colony Optimization—Genetic Algorithm(LEACH-ACO-GA),for wireless sensor networks.It combines regional ant colony optimization for cluster head selection with inter-cluster routing based on a genetic algorithm.The proposed method reduces energy consumption from 6.9 J(LEACH Classic)to 5.6 J(LEACH-ACO-GA)and decreases latency from 460 to 390 ms,while maintaining a packet delivery ratio of 0.97.These values are averaged over 70 rounds based on 30 independent simulation runs conducted on networks with 50 and 200 nodes.The hybrid method extends network lifetime by up to 50%compared to traditional LEACH and improves performance robustness in dense network environments.The results indicate that two-level metaheuristic optimization is effective for scalable and energy-efficient wireless sensor networks in Internet of Things scenarios.展开更多
A forecasting system of patent application counts is studied in this paper. The optimization model proposed in the research is based on support vector machines (SVM), in which cross-validation algorithm is used for ...A forecasting system of patent application counts is studied in this paper. The optimization model proposed in the research is based on support vector machines (SVM), in which cross-validation algorithm is used for preferences selection. Results of data simulation show that the proposed method has higher forecasting precision power and stronger generalization ability than BP neural network and RBF neural network. In addi- tion, it is feasible and effective in forecasting patent application counts.展开更多
针对单光子深度成像中探测器受散粒噪声和背景噪声的干扰,以及无人机在飞行过程中姿态变化带来的单轴图像偏差问题,在经典的SPIRAL-TAP重建框架基础上,提出了一种融合多尺度图像特征与自适应阈值筛选的新型深度图重建方法,旨在提升深度...针对单光子深度成像中探测器受散粒噪声和背景噪声的干扰,以及无人机在飞行过程中姿态变化带来的单轴图像偏差问题,在经典的SPIRAL-TAP重建框架基础上,提出了一种融合多尺度图像特征与自适应阈值筛选的新型深度图重建方法,旨在提升深度图像在低信号背景噪声比(SBR)或高信号背景噪声比下的重建质量。该方法首先通过多尺度梯度与局部方差计算生成图像加权矩阵,以刻画图像纹理复杂度;随后结合基于ROM(Rough Order Map)估计的尺度因子对阈值进行动态调整,以增强噪声鲁棒性;在阈值筛选阶段,提出自适应阈值策略,将尺度平滑与加权矩阵软调融合,限制阈值范围,使筛选更加稳定可靠。实验结果表明,在多种SBR和光子强度条件下,并考虑到无人机单轴姿态偏差影响下,本文方法均优于传统SPIRAL-TAP算法,具有更低的RMSE误差和更好的重建质量。在倾斜角为10°和15°时RMSE分别由0.32降至0.14和从0.43降至0.21。本文方法为无人机载单光子深度图像重建提供了有效的新思路,未来可用在机载高速单光子成像系统中。展开更多
This paper presents two one-pass algorithms for dynamically computing frequency counts in sliding window over a data stream-computing frequency counts exceeding user-specified threshold ε. The first algorithm constru...This paper presents two one-pass algorithms for dynamically computing frequency counts in sliding window over a data stream-computing frequency counts exceeding user-specified threshold ε. The first algorithm constructs subwindows and deletes expired sub-windows periodically in sliding window, and each sub-window maintains a summary data structure. The first algorithm outputs at most 1/ε + 1 elements for frequency queries over the most recent N elements. The second algorithm adapts multiple levels method to deal with data stream. Once the sketch of the most recent N elements has been constructed, the second algorithm can provides the answers to the frequency queries over the most recent n ( n≤N) elements. The second algorithm outputs at most 1/ε + 2 elements. The analytical and experimental results show that our algorithms are accurate and effective.展开更多
Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has b...Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.展开更多
在平抑光伏功率波动过程中,电池储能系统(battery energy storage system,BESS)因保持持续充、放电状态而导致寿命损耗较大。基于电池分组控制技术,提出考虑寿命延长的BESS平抑光伏分组功率分配办法。设计了食肉植物算法优化的改进雨流...在平抑光伏功率波动过程中,电池储能系统(battery energy storage system,BESS)因保持持续充、放电状态而导致寿命损耗较大。基于电池分组控制技术,提出考虑寿命延长的BESS平抑光伏分组功率分配办法。设计了食肉植物算法优化的改进雨流计数法,以获取光伏并网功率指令;利用小波包分解确定电池组数量及容量,同时根据设计的充、放电原则形成电池组的功率调节指令;进行电池组组别重置时,将BESS中诸多电池单元进行有序分配;提出二次功率分配策略,获取各电池单元的功率调节指令,二次分配时还应用了重复补发原则以最大限度跟踪功率调节指令,并保证组内电池单元荷电状态均衡。对所提功率分配方法进行了仿真验证,并与其他5种策略进行了对比,结果表明,所提功率分配方法实现了BESS对于功率调节指令的更好跟踪,降低了光伏并网功率波动率,延长了电池单元的使用寿命。展开更多
The deployment of intelligent surveillance systems to monitor tomato plant growth poses substantial challenges due to the dynamic nature of disease patterns and the complexity of environmental conditions such as backg...The deployment of intelligent surveillance systems to monitor tomato plant growth poses substantial challenges due to the dynamic nature of disease patterns and the complexity of environmental conditions such as background and lighting.In this study,an integrated cascade framework that synergizes detectors and trackers was introduced for the simultaneous identification of tomato leaf diseases and fruit counting.We applied an autonomous robot with smartphone camera to collect images for leaf disease and fruits in greenhouses.展开更多
Quantitative counting of fry is required for multiple reasons,including breeding,transportation,and sales and creating a fish-counting algorithm using image processing technology is proposed as a useful method.The ima...Quantitative counting of fry is required for multiple reasons,including breeding,transportation,and sales and creating a fish-counting algorithm using image processing technology is proposed as a useful method.The images for fish fry were preprocessed to extract the details of the target fish,using methods including binarization,dilation,and erosion.The thinning and the connected area algorithms were then independently adopted to count the fish fry within the image.The advantages and the disadvantages of the two algorithms under different densities were also compared,revealing that the fish fry pictures with a clear contrast between the foreground and background resulted in a higher accuracy.The main purpose of this research is to solve the problem of fry counting in the case of high density and high overlap.This research provides a reference point for this method based on image technology.展开更多
The decoding algorithms of two-dimensional Vernier anodes are deduced theoretically.The precision of decoding and uniqueness of encoding are proved.The influencing factors of detection sensitivity and spatial resoluti...The decoding algorithms of two-dimensional Vernier anodes are deduced theoretically.The precision of decoding and uniqueness of encoding are proved.The influencing factors of detection sensitivity and spatial resolution are discussed.The single photon imaging system is constructed,and the two-dimensional Vernier collector is fabricated.The image of the ultra-weak emission source is reconstructed.The spatial resolution of the system is about 100μm.展开更多
In this article, the error analysis in the quantum counting algorithm is investigated. It has been found that the random error plays as important a role as the systematic error does in the phase inversion operations. ...In this article, the error analysis in the quantum counting algorithm is investigated. It has been found that the random error plays as important a role as the systematic error does in the phase inversion operations. Both systematic and random errors are important in the Hadamard transformation. This is quite different from the Grover algorithm and the Shor algorithm.展开更多
摘要By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting sort while maintaining the original stability. Compared with the original counting sort, it has a wider scope of application and better time and space efficiency. In addition, the accuracy of the above conclusions can be proved by a large amount of experimental data.
基金supported in part by the Innovation Program for Quantum Science and Technology(No.2021ZD0302901)in part by the National Natural Science Foundation of China(Grant No.62272431).
摘要1 Introduction Estimating the number of triangles in a graph is a fundamental problem and has found applications in many fields.For example,in social network,it can help us understand how closely the local community structure and nodes in the network are in close proximity.In this paper,we address this problem in the framework of graph streaming algorithms,which has received significant attention due to the increasing need to analyze large-scale graph data efficiently[1–3].However,most of these algorithms are not robust or are limited to unweighted graphs.
摘要鱼群多目标准确计数是水生态智能监测和集约化养殖产业中的重要环节,对水域生态环境智能保护和水产养殖现代化具有重要作用。现有鱼群多目标准确追踪和计数方法主要适用于鱼群外观清晰、游速缓慢和方向稳定等较理想的情况,难以有效适用于现实情况下存在的鱼群互相遮挡、游动迅速和方向多变等复杂情况。为此,结合轻量化目标检测模型YOLOv5n,提出基于水平相似度匹配机制的鱼群追踪与计数方法。将鱼群计数问题视为多目标检测与追踪问题,设计水平相似度匹配机制,并对SORT(Simple Online and Realtime Tracking)算法进行优化。通过高速水流中鱼群个体在帧与帧之间的位置关系对检测框中心点的水平距离进行限制,以有效解决SORT算法存在的目标匹配混乱问题,显著提高追踪效果。实验结果表明,所提方法在鱼群多目标追踪数据集上的性能显著优于现有追踪方法,对目标遮挡、方向变化等情况目标追踪性能提升显著,并且该方法结构简单,易于实际应用。
摘要This study introduces a hybrid routing protocol,Low Energy Adaptive Clustering Hierarchy—Ant Colony Optimization—Genetic Algorithm(LEACH-ACO-GA),for wireless sensor networks.It combines regional ant colony optimization for cluster head selection with inter-cluster routing based on a genetic algorithm.The proposed method reduces energy consumption from 6.9 J(LEACH Classic)to 5.6 J(LEACH-ACO-GA)and decreases latency from 460 to 390 ms,while maintaining a packet delivery ratio of 0.97.These values are averaged over 70 rounds based on 30 independent simulation runs conducted on networks with 50 and 200 nodes.The hybrid method extends network lifetime by up to 50%compared to traditional LEACH and improves performance robustness in dense network environments.The results indicate that two-level metaheuristic optimization is effective for scalable and energy-efficient wireless sensor networks in Internet of Things scenarios.
基金Sponsored by "985" Philosophy and Social Science Innovation Base of the Ministry of Education of China (107008200400024)
摘要A forecasting system of patent application counts is studied in this paper. The optimization model proposed in the research is based on support vector machines (SVM), in which cross-validation algorithm is used for preferences selection. Results of data simulation show that the proposed method has higher forecasting precision power and stronger generalization ability than BP neural network and RBF neural network. In addi- tion, it is feasible and effective in forecasting patent application counts.
摘要针对单光子深度成像中探测器受散粒噪声和背景噪声的干扰,以及无人机在飞行过程中姿态变化带来的单轴图像偏差问题,在经典的SPIRAL-TAP重建框架基础上,提出了一种融合多尺度图像特征与自适应阈值筛选的新型深度图重建方法,旨在提升深度图像在低信号背景噪声比(SBR)或高信号背景噪声比下的重建质量。该方法首先通过多尺度梯度与局部方差计算生成图像加权矩阵,以刻画图像纹理复杂度;随后结合基于ROM(Rough Order Map)估计的尺度因子对阈值进行动态调整,以增强噪声鲁棒性;在阈值筛选阶段,提出自适应阈值策略,将尺度平滑与加权矩阵软调融合,限制阈值范围,使筛选更加稳定可靠。实验结果表明,在多种SBR和光子强度条件下,并考虑到无人机单轴姿态偏差影响下,本文方法均优于传统SPIRAL-TAP算法,具有更低的RMSE误差和更好的重建质量。在倾斜角为10°和15°时RMSE分别由0.32降至0.14和从0.43降至0.21。本文方法为无人机载单光子深度图像重建提供了有效的新思路,未来可用在机载高速单光子成像系统中。
基金Supported by the National Natural Science Foun-dation of China (60403027)
摘要This paper presents two one-pass algorithms for dynamically computing frequency counts in sliding window over a data stream-computing frequency counts exceeding user-specified threshold ε. The first algorithm constructs subwindows and deletes expired sub-windows periodically in sliding window, and each sub-window maintains a summary data structure. The first algorithm outputs at most 1/ε + 1 elements for frequency queries over the most recent N elements. The second algorithm adapts multiple levels method to deal with data stream. Once the sketch of the most recent N elements has been constructed, the second algorithm can provides the answers to the frequency queries over the most recent n ( n≤N) elements. The second algorithm outputs at most 1/ε + 2 elements. The analytical and experimental results show that our algorithms are accurate and effective.
基金support of the Natural Science Foundation of Jiangsu Province,China(BK20240977)the China Scholarship Council(201606850024)+1 种基金the National High Technology Research and Development Program of China(2016YFD0701003)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(SJCX23_1488)。
摘要Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.
摘要在平抑光伏功率波动过程中,电池储能系统(battery energy storage system,BESS)因保持持续充、放电状态而导致寿命损耗较大。基于电池分组控制技术,提出考虑寿命延长的BESS平抑光伏分组功率分配办法。设计了食肉植物算法优化的改进雨流计数法,以获取光伏并网功率指令;利用小波包分解确定电池组数量及容量,同时根据设计的充、放电原则形成电池组的功率调节指令;进行电池组组别重置时,将BESS中诸多电池单元进行有序分配;提出二次功率分配策略,获取各电池单元的功率调节指令,二次分配时还应用了重复补发原则以最大限度跟踪功率调节指令,并保证组内电池单元荷电状态均衡。对所提功率分配方法进行了仿真验证,并与其他5种策略进行了对比,结果表明,所提功率分配方法实现了BESS对于功率调节指令的更好跟踪,降低了光伏并网功率波动率,延长了电池单元的使用寿命。
基金partially supported by the Nation al Key Research and Development Program of China(2022YFD2100601)the Key Research and Development Program of Jiangsu Province(BE2021379)+4 种基金the Agricultural Independent Innovation of Jiangsu Province(CX225009)the National Natural Science Foundation of China(32102081)Fonds de Recherche du Québec Nature et technologies(FRQNT)Programme de recherche en partenariat—Agriculture durable(grant no.G259806 FRQ-NT 322853 X-Coded 259432)R.K.extends his appreciation for the scholarship provided by CSCthe fund from 333 High Levels Talents Cultivation of Jiangsu Province.
摘要The deployment of intelligent surveillance systems to monitor tomato plant growth poses substantial challenges due to the dynamic nature of disease patterns and the complexity of environmental conditions such as background and lighting.In this study,an integrated cascade framework that synergizes detectors and trackers was introduced for the simultaneous identification of tomato leaf diseases and fruit counting.We applied an autonomous robot with smartphone camera to collect images for leaf disease and fruits in greenhouses.
基金Research grants support from the Natural Science Foundation of China(No.31702393&No.32073028)Ningbo Public Welfare Key Project(No.2019C10098).
摘要Quantitative counting of fry is required for multiple reasons,including breeding,transportation,and sales and creating a fish-counting algorithm using image processing technology is proposed as a useful method.The images for fish fry were preprocessed to extract the details of the target fish,using methods including binarization,dilation,and erosion.The thinning and the connected area algorithms were then independently adopted to count the fish fry within the image.The advantages and the disadvantages of the two algorithms under different densities were also compared,revealing that the fish fry pictures with a clear contrast between the foreground and background resulted in a higher accuracy.The main purpose of this research is to solve the problem of fry counting in the case of high density and high overlap.This research provides a reference point for this method based on image technology.
基金supported by the National Natural Science Foundation of China (Grant No. 10878005/A03)
摘要The decoding algorithms of two-dimensional Vernier anodes are deduced theoretically.The precision of decoding and uniqueness of encoding are proved.The influencing factors of detection sensitivity and spatial resolution are discussed.The single photon imaging system is constructed,and the two-dimensional Vernier collector is fabricated.The image of the ultra-weak emission source is reconstructed.The spatial resolution of the system is about 100μm.
基金Supported by the National Natural Science Foundation of China under Grant Nos. 10325521, 60433050, and the National Basic 973 Research Program under Grant No. 001CB309308. Acknowledgement The authors would like to thank Mr. Nan Zhao for helpful discussions.
摘要In this article, the error analysis in the quantum counting algorithm is investigated. It has been found that the random error plays as important a role as the systematic error does in the phase inversion operations. Both systematic and random errors are important in the Hadamard transformation. This is quite different from the Grover algorithm and the Shor algorithm.