In computer vision,convolutional neural networks have a wide range of uses.Images representmost of today’s data,so it’s important to know how to handle these large amounts of data efficiently.Convolutional neural ne...In computer vision,convolutional neural networks have a wide range of uses.Images representmost of today’s data,so it’s important to know how to handle these large amounts of data efficiently.Convolutional neural networks have been shown to solve image processing problems effectively.However,when designing the network structure for a particular problem,you need to adjust the hyperparameters for higher accuracy.This technique is time consuming and requires a lot of work and domain knowledge.Designing a convolutional neural network architecture is a classic NP-hard optimization challenge.On the other hand,different datasets require different combinations of models or hyperparameters,which can be time consuming and inconvenient.Various approaches have been proposed to overcome this problem,such as grid search limited to low-dimensional space and queuing by random selection.To address this issue,we propose an evolutionary algorithm-based approach that dynamically enhances the structure of Convolution Neural Networks(CNNs)using optimized hyperparameters.This study proposes a method using Non-dominated sorted genetic algorithms(NSGA)to improve the hyperparameters of the CNN model.In addition,different types and parameter ranges of existing genetic algorithms are used.Acomparative study was conducted with various state-of-the-art methodologies and algorithms.Experiments have shown that our proposed approach is superior to previous methods in terms of classification accuracy,and the results are published in modern computing literature.展开更多
How to quickly and accurately detect new topics from massive data online becomes a main problem of public opinion monitoring in cyberspace. This paperpresents a new event detection method for the current new event det...How to quickly and accurately detect new topics from massive data online becomes a main problem of public opinion monitoring in cyberspace. This paperpresents a new event detection method for the current new event detection system, based on sorted subtopic matching algorithm and constructs the entire design framework. In this p^per, the subtopics contained in old topics （or news stories） are sorted in descending order according to their importance to the topic（or news stories）, and form a sorted subtopic sequence. In the process of subtopic matching, subtopic scoring matrix is used to determine whether a new story is reporting a new event. Experimental results show that the sorted subtopic matching model improved the accuracy and effectiveness ofthenew event detection system in cyberspace.展开更多
A new file assignment strategy of parallel I/O, which is named heuristic file sorted assignment algorithm was proposed on cluster computing system. Based on the load balancing, it assigns the files to the same disk ac...A new file assignment strategy of parallel I/O, which is named heuristic file sorted assignment algorithm was proposed on cluster computing system. Based on the load balancing, it assigns the files to the same disk according to the similar service time. Firstly, the files were sorted and stored at the set I in descending order in terms of their service time, then one disk of cluster node was selected randomly when the files were to be assigned, and at last the continuous files were taken orderly from the set I to the disk until the disk reached its load maximum. The experimental results show that the new strategy improves the performance by 20.2% when the load of the system is light and by 31.6% when the load is heavy. And the higher the data access rate, the more evident the improvement of the performance obtained by the heuristic file sorted assignment algorithm.展开更多
The purpose of this study is to analyze the household waste reduction effect of sorted collection of recyclable waste in Japan using a panel data analysis, which considers time-series and cross-section data simultaneo...The purpose of this study is to analyze the household waste reduction effect of sorted collection of recyclable waste in Japan using a panel data analysis, which considers time-series and cross-section data simultaneously. Also, the study shows the effect of the type of sorted items on the quantity of household waste disposed. We used the data attained from 103 cities recorded over three years, and applied the quantity of total waste disposed, the quantity of combustible waste, the quantity of other waste （waste excluding combustible and recyclable waste）, and the quantity of combustible plus other waste as objective variables, respectively, in the models. The result suggests that when the number of sorted items is increased marginally, the quantity of household waste decreases by about 0.5%-3.3% or 1.28-4.17 grams per capita per day. In addition, it is shown that sorting out white trays is effective in reducing the quantity of combustible waste. Sorting out paper containers and packages is also effective in reducing the quantity of other waste and combustible plus other waste.展开更多
“See it, Say it, Sorted.”就是告诉乘客,你要是看到了什么可疑的行为,就找工作人员说出来,我们协助你解决。2005年,在伦敦经历了地铁恐怖袭击之后,英国国家铁路(NationalRail)和英国交通警察局(British Transport Police)与安全专家...“See it, Say it, Sorted.”就是告诉乘客,你要是看到了什么可疑的行为,就找工作人员说出来,我们协助你解决。2005年,在伦敦经历了地铁恐怖袭击之后,英国国家铁路(NationalRail)和英国交通警察局(British Transport Police)与安全专家、传播学者以及广告创意团队进行了多次讨论与头脑风暴。团队希望创造出一条易于理解、易于记忆,同时能促使行动的标语,“Seeit.Say it. Sorted.”由此诞生。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
The l1 norm is the tight convex relaxation for the l0 norm and has been successfully applied for recovering sparse signals.However,for problems with fewer samples than required for accurate l1 recovery,one needs to ap...The l1 norm is the tight convex relaxation for the l0 norm and has been successfully applied for recovering sparse signals.However,for problems with fewer samples than required for accurate l1 recovery,one needs to apply nonconvex penalties such as lp norm.As one method for solving lp minimization problems,iteratively reweighted l1 minimization updates the weight for each component based on the value of the same component at the previous iteration.It assigns large weights on small components in magnitude and small weights on large components in magnitude.The set of the weights is not fixed,and it makes the analysis of this method difficult.In this paper,we consider a weighted l1 penalty with the set of the weights fixed,and the weights are assigned based on the sort of all the components in magnitude.The smallest weight is assigned to the largest component in magnitude.This new penalty is called nonconvex sorted l1.Then we propose two methods for solving nonconvex sorted l1 minimization problems:iteratively reweighted l1 minimization and iterative sorted thresholding,and prove that both methods will converge to a local minimizer of the nonconvex sorted l1 minimization problems.We also show that both methods are generalizations of iterative support detection and iterative hard thresholding,respectively.The numerical experiments demonstrate the better performance of assigning weights by sort compared to assigning by value.展开更多
Acute ischemic stroke remains a significant health concern owing to the limited efficacy of current therapeutic options.In recent years,Neuregulin-1 has exhibited promising neuroprotective effects in cerebral ischemia...Acute ischemic stroke remains a significant health concern owing to the limited efficacy of current therapeutic options.In recent years,Neuregulin-1 has exhibited promising neuroprotective effects in cerebral ischemia.However,the sources and functions of Neuregulin-1 have not yet been fully understood,which hinders its translation and broad application.Here,we collected paired clot and peripheral blood samples from patients with acute ischemic stroke to determine the sources of Neuregulin-1.In addition,we established an in vivo transient middle cerebral artery occlusion mouse model to investigate the therapeutic effects of Neuregulin-1 and its underlying molecular biological mechanisms.We observed a significant elevation in serum Neuregulin-1 levels among patients with acute ischemic stroke that correlated with severity of neurological impairment and clinical outcome.Using single-cell sequencing,we identified Neuregulin-1-positive macrophages among peripheral blood mononuclear cells that produced Neuregulin-1 post-ischemia.In addition,Neuregulin-1 promoted repair of the infarcted area,alleviating neuronal and myelin damage and improving overall behavioral recovery in mice.We found that Neuregulin-1 may exert these neuroprotective effects by promoting angiogenesis in the infarct area,and that this effect is mediated by Akt/mTOR/VEGF-dependent signaling.Our findings suggest that peripheral macrophages are a source of Neuregulin-1 post-stroke.Neuregulin-1 exerts its neuroprotective effects by promoting angiogenesis via Akt/mTOR/VEGF-dependent signaling,showing promising clinical translation potential.展开更多
Gangue is inevitably mixed with coal during mining and transportation.Currently,the manual sorting and conventional mechanical separation technologies widely adopted in the coal mining industry are plagued by low effi...Gangue is inevitably mixed with coal during mining and transportation.Currently,the manual sorting and conventional mechanical separation technologies widely adopted in the coal mining industry are plagued by low efficiency,poor identification accuracy,severe environmental pollution,and other drawbacks.This paper proposes a machine vision-based intelligent coal gangue sorting robot system.Firstly,the OpenMV captures images of coal gangue and utilizes the MobileNetV20.35 lightweight convolutional neural network to train the FOMO(Faster Objects,More Objects)target detection model in the cloud.This enables prediction and recognition of gangue,along with the acquisition of its center point pixel coordinates.Secondly,the position information of the gangue is sent to the STM32 microcontroller using the serial communication protocol for coordinate system conversion,pose algorithm,and path planning.Finally,the STM32 microcontroller controls the start and stop of the conveyor belt through the working status of the relay.When the relay is absorbed,the conveyor belt stops,and at the same time,the robotic arm grasps the gangue for transfer action,thus realizing the sorting of coal and gangue.The experimental results demonstrate that the cloud-trained FOMO neural network model achieves an F1 score of 95.5%and a recall of 91.3%,with a test accuracy of 97.56%.The quantified model deployed on OpenMV can accurately identify multiple gangues and output their position information.The success rate of the robotic arm in tracking and sorting gangue reaches 90.13%,and the positioning error of the robotic arm is[9,12.5]mm.This system realizes high-precision identification,positioning,and intelligent sorting of coal and gangue,meeting the basic requirements for gangue sorting in coal mines.展开更多
Manned aerial vehicle-unmanned aerial vehicle(MAV-UAV)combat organization is a MAV-UAV combat collective formed from the perspective of organization design theory and methodology,and the generation of force formation ...Manned aerial vehicle-unmanned aerial vehicle(MAV-UAV)combat organization is a MAV-UAV combat collective formed from the perspective of organization design theory and methodology,and the generation of force formation plan is a key step in the organizational planning.Based on the description of the problem and the definition of organizational elements,the matching model of platform-target attack wave is constructed to minimize the redundancy of command and decision-making capability,resource capability and the number of platforms used.Based on the non-dominated sorting genetic algorithmⅢ(NSGA-Ⅲ)framework,which includes encoding/decoding method and constraint handling method,the generation model of organizational force formation plan is solved,and the effectiveness and superiority of the algorithm are verified by simulation experiments.展开更多
Background:Mastitis seriously affects the mammary health of humans and animals.Studies have found that inflammation and oxidative stress play key roles in the occur-rence and development of mastitis.Therefore,in-depth...Background:Mastitis seriously affects the mammary health of humans and animals.Studies have found that inflammation and oxidative stress play key roles in the occur-rence and development of mastitis.Therefore,in-depth research on related molecular mechanisms is of great significance.Methods:Postpartum mice were anesthetized with pentobarbital and administered lipopolysaccharide to develop the mouse mastitis model.Proteomic analysis was per-formed to compare protein expression in mitochondria-associated endoplasmic retic-ulum membranes(MAM)from two mouse mammary gland groups.Western blot was used to detect the expression of MAM-related proteins in mitochondria.AlphaFold3 was used to predict the molecular structures of phosphofurin acidic cluster sorting protein 2(PACS2)and mitofusin 2(MFN2)and their interaction levels.The MFN2-PACS2 interaction was investigated using co-immunoprecipitation and small interfer-ing RNA.Results:The results showed that the inflammation level in the mammary gland tissue of mice with mastitis significantly increased,the total antioxidant capacity decreased,and the expression of MAM-related proteins MFN2 and PACS2 was significantly downregulated.In cell experiments,overexpression of MFN2 can inhibit inflamma-tion and oxidative stress responses,and promote the interaction between MFN2 and PACS2 to affect the formation of MAMs.Conclusion:In summary,this study suggests that mastitis can alter the expression of MAM-related proteins in mouse breast tissue.The interaction between MFN2 and PACS2 regulates the formation of MAMs.Overexpression of MFN2 can promote the formation of MAMs and inhibit inflammation and oxidative stress response in mam-mary epithelial cells.Our results provided a new theoretical basis and potential thera-peutic targets for the prevention and treatment of mastitis.展开更多
Sorted constraint representation is a very useful representation in AI which combines class hierarchies and constraint networks. For such sorted constraint representation, a problem is how to generalize the idea of de...Sorted constraint representation is a very useful representation in AI which combines class hierarchies and constraint networks. For such sorted constraint representation, a problem is how to generalize the idea of default inheritance to constraint network, where the attributes in a class or between different classes interact with each other via the network. To give a formal account for the defeasible reasoning in such representation, a general sorted constraint logic is proposed, and a minimal-model semantics for the logic is presented.展开更多
煤矿井下安全生产是保障矿工生命安全和能源稳定供应的核心环节,但传统监控方法在检测实时性和准确性方面存在明显不足。针对复杂井下环境中人员入侵识别精度低的问题,研究提出一种基于改进You Only Look Once version 5(YOLOv5)和深度...煤矿井下安全生产是保障矿工生命安全和能源稳定供应的核心环节,但传统监控方法在检测实时性和准确性方面存在明显不足。针对复杂井下环境中人员入侵识别精度低的问题,研究提出一种基于改进You Only Look Once version 5(YOLOv5)和深度简单在线实时跟踪算法的电子围栏入侵检测技术。研究通过嵌入注意力机制增强模型对关键特征的感知能力,并利用扩展卡尔曼滤波与匈牙利算法提升跟踪稳定性。实验结果表明,改进后的模型的识别率最高,且随迭代次数的增加其识别率始终在90%以上。该技术在识别性能上,平均精度均值指标为92.5%,每秒帧数提升至116.7,训练时长缩短至8.5 h,漏检率显著降低。研究表明,该方法在光照不均、煤尘干扰等复杂场景下具备更高的检测精度与实时性。该技术的提出可为煤矿井下智能化安全管理提供有效技术支撑,从而提高煤矿安全生产水平,杜绝生产事故出现。展开更多
This paper introduces an intelligent garbage-handling trolley model based on an STM32 single chip microcomputer as the control core.The device is driven by four independent motors to achieve automatic tracking,automat...This paper introduces an intelligent garbage-handling trolley model based on an STM32 single chip microcomputer as the control core.The device is driven by four independent motors to achieve automatic tracking,automatic obstacle avoidance,and fixed-point docking.Using external execution structure to realize the car without the use of a mechanical arm,complete garbage collection,storage,and uninstall function.On this basis,the type of garbage is marked by color,and the color recognition sensor is applied to realize the type recognition after garbage collection and put into the corresponding unloading point,to realize its intelligent classification function.It can automatically complete the established task autonomously.展开更多
基金This research was supported by the Researchers Supporting Program(TUMAProject-2021-27)Almaarefa University,Riyadh,Saudi Arabia.
文摘In computer vision,convolutional neural networks have a wide range of uses.Images representmost of today’s data,so it’s important to know how to handle these large amounts of data efficiently.Convolutional neural networks have been shown to solve image processing problems effectively.However,when designing the network structure for a particular problem,you need to adjust the hyperparameters for higher accuracy.This technique is time consuming and requires a lot of work and domain knowledge.Designing a convolutional neural network architecture is a classic NP-hard optimization challenge.On the other hand,different datasets require different combinations of models or hyperparameters,which can be time consuming and inconvenient.Various approaches have been proposed to overcome this problem,such as grid search limited to low-dimensional space and queuing by random selection.To address this issue,we propose an evolutionary algorithm-based approach that dynamically enhances the structure of Convolution Neural Networks(CNNs)using optimized hyperparameters.This study proposes a method using Non-dominated sorted genetic algorithms(NSGA)to improve the hyperparameters of the CNN model.In addition,different types and parameter ranges of existing genetic algorithms are used.Acomparative study was conducted with various state-of-the-art methodologies and algorithms.Experiments have shown that our proposed approach is superior to previous methods in terms of classification accuracy,and the results are published in modern computing literature.
基金Funded by the Planning Project of National Language Committee in the "12th 5-year Plan"(No.YB125-49)the Foundation for Key Program of Ministry of Education,China(No.212167)the Fundamental Research Funds for the Central Universities(No.SWJTU12CX096)
文摘How to quickly and accurately detect new topics from massive data online becomes a main problem of public opinion monitoring in cyberspace. This paperpresents a new event detection method for the current new event detection system, based on sorted subtopic matching algorithm and constructs the entire design framework. In this p^per, the subtopics contained in old topics （or news stories） are sorted in descending order according to their importance to the topic（or news stories）, and form a sorted subtopic sequence. In the process of subtopic matching, subtopic scoring matrix is used to determine whether a new story is reporting a new event. Experimental results show that the sorted subtopic matching model improved the accuracy and effectiveness ofthenew event detection system in cyberspace.
文摘A new file assignment strategy of parallel I/O, which is named heuristic file sorted assignment algorithm was proposed on cluster computing system. Based on the load balancing, it assigns the files to the same disk according to the similar service time. Firstly, the files were sorted and stored at the set I in descending order in terms of their service time, then one disk of cluster node was selected randomly when the files were to be assigned, and at last the continuous files were taken orderly from the set I to the disk until the disk reached its load maximum. The experimental results show that the new strategy improves the performance by 20.2% when the load of the system is light and by 31.6% when the load is heavy. And the higher the data access rate, the more evident the improvement of the performance obtained by the heuristic file sorted assignment algorithm.
文摘The purpose of this study is to analyze the household waste reduction effect of sorted collection of recyclable waste in Japan using a panel data analysis, which considers time-series and cross-section data simultaneously. Also, the study shows the effect of the type of sorted items on the quantity of household waste disposed. We used the data attained from 103 cities recorded over three years, and applied the quantity of total waste disposed, the quantity of combustible waste, the quantity of other waste （waste excluding combustible and recyclable waste）, and the quantity of combustible plus other waste as objective variables, respectively, in the models. The result suggests that when the number of sorted items is increased marginally, the quantity of household waste decreases by about 0.5%-3.3% or 1.28-4.17 grams per capita per day. In addition, it is shown that sorting out white trays is effective in reducing the quantity of combustible waste. Sorting out paper containers and packages is also effective in reducing the quantity of other waste and combustible plus other waste.
文摘“See it, Say it, Sorted.”就是告诉乘客,你要是看到了什么可疑的行为,就找工作人员说出来,我们协助你解决。2005年,在伦敦经历了地铁恐怖袭击之后,英国国家铁路(NationalRail)和英国交通警察局(British Transport Police)与安全专家、传播学者以及广告创意团队进行了多次讨论与头脑风暴。团队希望创造出一条易于理解、易于记忆,同时能促使行动的标语,“Seeit.Say it. Sorted.”由此诞生。
文摘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。
基金partially supported by European Research Council,the National Natural Science Foundation of China(No.11201079)the Fundamental Research Funds for the Central Universities of China(Nos.20520133238 and 20520131169)the National Natural Science Foundation of United States(Nos.DMS-0748839 and DMS-1317602).
文摘The l1 norm is the tight convex relaxation for the l0 norm and has been successfully applied for recovering sparse signals.However,for problems with fewer samples than required for accurate l1 recovery,one needs to apply nonconvex penalties such as lp norm.As one method for solving lp minimization problems,iteratively reweighted l1 minimization updates the weight for each component based on the value of the same component at the previous iteration.It assigns large weights on small components in magnitude and small weights on large components in magnitude.The set of the weights is not fixed,and it makes the analysis of this method difficult.In this paper,we consider a weighted l1 penalty with the set of the weights fixed,and the weights are assigned based on the sort of all the components in magnitude.The smallest weight is assigned to the largest component in magnitude.This new penalty is called nonconvex sorted l1.Then we propose two methods for solving nonconvex sorted l1 minimization problems:iteratively reweighted l1 minimization and iterative sorted thresholding,and prove that both methods will converge to a local minimizer of the nonconvex sorted l1 minimization problems.We also show that both methods are generalizations of iterative support detection and iterative hard thresholding,respectively.The numerical experiments demonstrate the better performance of assigning weights by sort compared to assigning by value.
基金Chongqing Technology lnnovation and Application Development Program,No.CSTB2023TIAD-KPX0061(to ZZ)the National Natural Science Foundation of China,Nos.81971130(to ZZ),82201464(to XC).
文摘Acute ischemic stroke remains a significant health concern owing to the limited efficacy of current therapeutic options.In recent years,Neuregulin-1 has exhibited promising neuroprotective effects in cerebral ischemia.However,the sources and functions of Neuregulin-1 have not yet been fully understood,which hinders its translation and broad application.Here,we collected paired clot and peripheral blood samples from patients with acute ischemic stroke to determine the sources of Neuregulin-1.In addition,we established an in vivo transient middle cerebral artery occlusion mouse model to investigate the therapeutic effects of Neuregulin-1 and its underlying molecular biological mechanisms.We observed a significant elevation in serum Neuregulin-1 levels among patients with acute ischemic stroke that correlated with severity of neurological impairment and clinical outcome.Using single-cell sequencing,we identified Neuregulin-1-positive macrophages among peripheral blood mononuclear cells that produced Neuregulin-1 post-ischemia.In addition,Neuregulin-1 promoted repair of the infarcted area,alleviating neuronal and myelin damage and improving overall behavioral recovery in mice.We found that Neuregulin-1 may exert these neuroprotective effects by promoting angiogenesis in the infarct area,and that this effect is mediated by Akt/mTOR/VEGF-dependent signaling.Our findings suggest that peripheral macrophages are a source of Neuregulin-1 post-stroke.Neuregulin-1 exerts its neuroprotective effects by promoting angiogenesis via Akt/mTOR/VEGF-dependent signaling,showing promising clinical translation potential.
基金Supported by the National Natural Science Foundation of China(52074273)Natural Science Research Project of Universities in Anhui Province(2023AH050343)+4 种基金Anhui Innovative Team for Pollutant Sensitive Monitoring and Application(2023AH010043)Anhui Province Graduate Education Quality Project(2024jyjxggyjY204)Innovation and Entrepreneurship Training Programme for College Students in Anhui Province(S202410373037)Huaibei Normal University’s Postgraduate Education Quality Project(2024jgxm003)Open Project Funded by Anhui Province Key Laboratoryof Intelligent Computing and Applications(AFZNJS2025KF08)。
文摘Gangue is inevitably mixed with coal during mining and transportation.Currently,the manual sorting and conventional mechanical separation technologies widely adopted in the coal mining industry are plagued by low efficiency,poor identification accuracy,severe environmental pollution,and other drawbacks.This paper proposes a machine vision-based intelligent coal gangue sorting robot system.Firstly,the OpenMV captures images of coal gangue and utilizes the MobileNetV20.35 lightweight convolutional neural network to train the FOMO(Faster Objects,More Objects)target detection model in the cloud.This enables prediction and recognition of gangue,along with the acquisition of its center point pixel coordinates.Secondly,the position information of the gangue is sent to the STM32 microcontroller using the serial communication protocol for coordinate system conversion,pose algorithm,and path planning.Finally,the STM32 microcontroller controls the start and stop of the conveyor belt through the working status of the relay.When the relay is absorbed,the conveyor belt stops,and at the same time,the robotic arm grasps the gangue for transfer action,thus realizing the sorting of coal and gangue.The experimental results demonstrate that the cloud-trained FOMO neural network model achieves an F1 score of 95.5%and a recall of 91.3%,with a test accuracy of 97.56%.The quantified model deployed on OpenMV can accurately identify multiple gangues and output their position information.The success rate of the robotic arm in tracking and sorting gangue reaches 90.13%,and the positioning error of the robotic arm is[9,12.5]mm.This system realizes high-precision identification,positioning,and intelligent sorting of coal and gangue,meeting the basic requirements for gangue sorting in coal mines.
基金supported by the Natural Science Foundation of Shaanxi Province(2023-JC-QN-0728)the China Postdoctoral Science Foundation(2021M693942)。
文摘Manned aerial vehicle-unmanned aerial vehicle(MAV-UAV)combat organization is a MAV-UAV combat collective formed from the perspective of organization design theory and methodology,and the generation of force formation plan is a key step in the organizational planning.Based on the description of the problem and the definition of organizational elements,the matching model of platform-target attack wave is constructed to minimize the redundancy of command and decision-making capability,resource capability and the number of platforms used.Based on the non-dominated sorting genetic algorithmⅢ(NSGA-Ⅲ)framework,which includes encoding/decoding method and constraint handling method,the generation model of organizational force formation plan is solved,and the effectiveness and superiority of the algorithm are verified by simulation experiments.
基金National Natural Science Foundation of China,Grant/Award Number:32302826 and 32372961Jilin Provincial Special Project for Health Research Talents,Grant/Award Number:2020SCZ40China Postdoctoral Science Foundation,Grant/Award Number:2023M740623。
文摘Background:Mastitis seriously affects the mammary health of humans and animals.Studies have found that inflammation and oxidative stress play key roles in the occur-rence and development of mastitis.Therefore,in-depth research on related molecular mechanisms is of great significance.Methods:Postpartum mice were anesthetized with pentobarbital and administered lipopolysaccharide to develop the mouse mastitis model.Proteomic analysis was per-formed to compare protein expression in mitochondria-associated endoplasmic retic-ulum membranes(MAM)from two mouse mammary gland groups.Western blot was used to detect the expression of MAM-related proteins in mitochondria.AlphaFold3 was used to predict the molecular structures of phosphofurin acidic cluster sorting protein 2(PACS2)and mitofusin 2(MFN2)and their interaction levels.The MFN2-PACS2 interaction was investigated using co-immunoprecipitation and small interfer-ing RNA.Results:The results showed that the inflammation level in the mammary gland tissue of mice with mastitis significantly increased,the total antioxidant capacity decreased,and the expression of MAM-related proteins MFN2 and PACS2 was significantly downregulated.In cell experiments,overexpression of MFN2 can inhibit inflamma-tion and oxidative stress responses,and promote the interaction between MFN2 and PACS2 to affect the formation of MAMs.Conclusion:In summary,this study suggests that mastitis can alter the expression of MAM-related proteins in mouse breast tissue.The interaction between MFN2 and PACS2 regulates the formation of MAMs.Overexpression of MFN2 can promote the formation of MAMs and inhibit inflammation and oxidative stress response in mam-mary epithelial cells.Our results provided a new theoretical basis and potential thera-peutic targets for the prevention and treatment of mastitis.
文摘Sorted constraint representation is a very useful representation in AI which combines class hierarchies and constraint networks. For such sorted constraint representation, a problem is how to generalize the idea of default inheritance to constraint network, where the attributes in a class or between different classes interact with each other via the network. To give a formal account for the defeasible reasoning in such representation, a general sorted constraint logic is proposed, and a minimal-model semantics for the logic is presented.
文摘煤矿井下安全生产是保障矿工生命安全和能源稳定供应的核心环节,但传统监控方法在检测实时性和准确性方面存在明显不足。针对复杂井下环境中人员入侵识别精度低的问题,研究提出一种基于改进You Only Look Once version 5(YOLOv5)和深度简单在线实时跟踪算法的电子围栏入侵检测技术。研究通过嵌入注意力机制增强模型对关键特征的感知能力,并利用扩展卡尔曼滤波与匈牙利算法提升跟踪稳定性。实验结果表明,改进后的模型的识别率最高,且随迭代次数的增加其识别率始终在90%以上。该技术在识别性能上,平均精度均值指标为92.5%,每秒帧数提升至116.7,训练时长缩短至8.5 h,漏检率显著降低。研究表明,该方法在光照不均、煤尘干扰等复杂场景下具备更高的检测精度与实时性。该技术的提出可为煤矿井下智能化安全管理提供有效技术支撑,从而提高煤矿安全生产水平,杜绝生产事故出现。
文摘This paper introduces an intelligent garbage-handling trolley model based on an STM32 single chip microcomputer as the control core.The device is driven by four independent motors to achieve automatic tracking,automatic obstacle avoidance,and fixed-point docking.Using external execution structure to realize the car without the use of a mechanical arm,complete garbage collection,storage,and uninstall function.On this basis,the type of garbage is marked by color,and the color recognition sensor is applied to realize the type recognition after garbage collection and put into the corresponding unloading point,to realize its intelligent classification function.It can automatically complete the established task autonomously.
