This paper extends the covariant derivative un der curved coordinate systems in 3D Euclid space. Based on the axiom of the covariant form invariability, the classical covariant derivative that can only act on componen...This paper extends the covariant derivative un der curved coordinate systems in 3D Euclid space. Based on the axiom of the covariant form invariability, the classical covariant derivative that can only act on components is ex tended to the generalized covariant derivative that can act on any geometric quantity including base vectors, vectors and tensors. Under the axiom, the algebra structure of the gen eralized covariant derivative is proved to be covariant dif ferential ring. Based on the powerful operation capabilities and simple analytical properties of the generalized covariant derivative, the tensor analysis in curved coordinate systems is simplified to a large extent.展开更多
Ants rank among the most ecologically dominant and evolutionarily remarkable insects on the planet,capturing the imagination of both curious children and thoughtful scholars alike.Aristotle,impressed by their division...Ants rank among the most ecologically dominant and evolutionarily remarkable insects on the planet,capturing the imagination of both curious children and thoughtful scholars alike.Aristotle,impressed by their division of labor and cooperative behavior,described them as“political animals”.In Aesop’s Fables,they are celebrated for their foresight and diligence in preparing for hardship.Traditional Chinese narratives similarly portray ants as modest creatures that,through collective effort,achieve extraordinary power and influence.展开更多
The ability of queens and males of most ant species to disperse by flight has fundamentally contributed to the group’s evolutionary and ecological success and is a determining factor to take into account for biogeogr...The ability of queens and males of most ant species to disperse by flight has fundamentally contributed to the group’s evolutionary and ecological success and is a determining factor to take into account for biogeographic studies(Wagner and Liebherr 1992;Peeters and Ito 2001;Helms 2018).展开更多
Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN ...Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN planning remains a challenge,especially in scenarios where traditional search algorithms struggle to navigate the vast solution space efficiently.This research proposes a novel technique to enhance HTN planning by integrating the Ant Colony Optimization(ACO)algorithm into the refinement process.The Ant System algorithm,inspired by the foraging behavior of ants,is well-suited for addressing optimization problems by efficiently exploring solution spaces.By incorporating ACO into the refinement phase of HTN planning,the authors aim to leverage its adaptive nature and decentralized decision-making to improve plan generation.This paper involves the development of a hybrid strategy called ACO-HTN,which combines HTN planning with ACO-based plan selection.This technique enables the system to adaptively refine plans by guiding the search towards optimal solutions.To evaluate the effectiveness of the proposed technique,this paper conducts empirical experiments on various domains and benchmark datasets.Our results demonstrate that the ACO-HTN strategy enhances the efficiency and effectiveness of HTN planning,outperforming traditional methods in terms of solution quality and computational performance.展开更多
Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of t...Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.展开更多
Broadband and omnidirectional antireflection coating is generally an effective way to improve solar cell efficiency, because the destructive interference between the reflected and incident light can maximize the light...Broadband and omnidirectional antireflection coating is generally an effective way to improve solar cell efficiency, because the destructive interference between the reflected and incident light can maximize the light transmission into the absorption layer. In this paper, we report the incident quantum efficiency ηin, not incident energy or power, as the evaluation function by the ant colony algorithm optimization method, which is a swarm-based optimization method. Also, SPCTRL2 is proposed to be incorporated for accurate optimization because the solar irradiance on a receiver plane is dependent on position, season, and time. Cities of Quito, Beijing and Moscow are selected for two-and three-layer antireflective coating optimization over λ = [300,1100] nm and θ = [0°, 90°]. The ηin increases by 0.26%, 1.37% and 4.24% for the above 3 cities, respectively, compared with that calculated by other rigorous optimization algorithms methods, which is further verified by the effect of position and time dependent solar spectrum on the antireflective coating design.展开更多
Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a ...Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.展开更多
In order to effectively conduct emotion recognition from spontaneous, non-prototypical and unsegmented speech so as to create a more natural human-machine interaction; a novel speech emotion recognition algorithm base...In order to effectively conduct emotion recognition from spontaneous, non-prototypical and unsegmented speech so as to create a more natural human-machine interaction; a novel speech emotion recognition algorithm based on the combination of the emotional data field （EDF） and the ant colony search （ACS） strategy, called the EDF-ACS algorithm, is proposed. More specifically, the inter- relationship among the turn-based acoustic feature vectors of different labels are established by using the potential function in the EDF. To perform the spontaneous speech emotion recognition, the artificial colony is used to mimic the turn- based acoustic feature vectors. Then, the canonical ACS strategy is used to investigate the movement direction of each artificial ant in the EDF, which is regarded as the emotional label of the corresponding turn-based acoustic feature vector. The proposed EDF-ACS algorithm is evaluated on the continueous audio）＇visual emotion challenge （AVEC） 2012 dataset, which contains the spontaneous, non-prototypical and unsegmented speech emotion data. The experimental results show that the proposed EDF-ACS algorithm outperforms the existing state-of-the-art algorithm in turn-based speech emotion recognition.展开更多
The antibacterial effects of waste liquor of essence oil extraction from Sabina vulgaris Ant on Escherichia coil, Staphylococcus aureus, Salmonella, Bacillus subtilis, Bacillus magaterium and Bacillus cereus in foods ...The antibacterial effects of waste liquor of essence oil extraction from Sabina vulgaris Ant on Escherichia coil, Staphylococcus aureus, Salmonella, Bacillus subtilis, Bacillus magaterium and Bacillus cereus in foods were evaluated by paper disk method. The results showed that the waste liquor of essence oil extraction from S. vulgaris had inhibitory effects on E. coil, S. aureus and Salmonella with bet- ter inhibitory effects on E. coil and Salmonella; the bacteriostatic effect of water steam distillation waste liquor was better than that of water extraction waste liquor. The more times the waste liquor was distilled, the higher the active ingredients content was, and the better the bacteriostatic effect was.展开更多
Path planning is an important issue for autonomous underwater vehicles （AUVs） traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning usi...Path planning is an important issue for autonomous underwater vehicles （AUVs） traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization （ACO） were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.展开更多
基金supported by the NSFC(11072125 and 11272175)the NSF of Jiangsu Province(SBK201140044)the Specialized Research Fund for Doctoral Program of Higher Education(20130002110044)
文摘This paper extends the covariant derivative un der curved coordinate systems in 3D Euclid space. Based on the axiom of the covariant form invariability, the classical covariant derivative that can only act on components is ex tended to the generalized covariant derivative that can act on any geometric quantity including base vectors, vectors and tensors. Under the axiom, the algebra structure of the gen eralized covariant derivative is proved to be covariant dif ferential ring. Based on the powerful operation capabilities and simple analytical properties of the generalized covariant derivative, the tensor analysis in curved coordinate systems is simplified to a large extent.
基金supported by the National Natural Science Foundation of China(32388102 to G.Z.,32370668 to W.L.)Yunnan Provincial Science and Technology Department,Yunnan Fundamental Research Projects(202201AT070129 and 202401BC070017 to W.L.)。
文摘Ants rank among the most ecologically dominant and evolutionarily remarkable insects on the planet,capturing the imagination of both curious children and thoughtful scholars alike.Aristotle,impressed by their division of labor and cooperative behavior,described them as“political animals”.In Aesop’s Fables,they are celebrated for their foresight and diligence in preparing for hardship.Traditional Chinese narratives similarly portray ants as modest creatures that,through collective effort,achieve extraordinary power and influence.
基金funded by the“Departments of Excellence”program of the Italian Ministry for University and Research(MIUR,2018-2022 and MUR,2023-2027).
文摘The ability of queens and males of most ant species to disperse by flight has fundamentally contributed to the group’s evolutionary and ecological success and is a determining factor to take into account for biogeographic studies(Wagner and Liebherr 1992;Peeters and Ito 2001;Helms 2018).
基金supported by the Ministry of Science and High Education of the Russian Federation by the grant 075-15-2022-1137supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R323),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN planning remains a challenge,especially in scenarios where traditional search algorithms struggle to navigate the vast solution space efficiently.This research proposes a novel technique to enhance HTN planning by integrating the Ant Colony Optimization(ACO)algorithm into the refinement process.The Ant System algorithm,inspired by the foraging behavior of ants,is well-suited for addressing optimization problems by efficiently exploring solution spaces.By incorporating ACO into the refinement phase of HTN planning,the authors aim to leverage its adaptive nature and decentralized decision-making to improve plan generation.This paper involves the development of a hybrid strategy called ACO-HTN,which combines HTN planning with ACO-based plan selection.This technique enables the system to adaptively refine plans by guiding the search towards optimal solutions.To evaluate the effectiveness of the proposed technique,this paper conducts empirical experiments on various domains and benchmark datasets.Our results demonstrate that the ACO-HTN strategy enhances the efficiency and effectiveness of HTN planning,outperforming traditional methods in terms of solution quality and computational performance.
基金supported by the National Natural Science Foundation of China(62276055).
文摘Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.
基金supported by the National Key Research and Development of China (No. 2017YFF0104801)the National Natural Science Foundation of China (Nos. 61675046, 61804012)the Open Fund of IPOC (No. IPOC2017B011)
文摘Broadband and omnidirectional antireflection coating is generally an effective way to improve solar cell efficiency, because the destructive interference between the reflected and incident light can maximize the light transmission into the absorption layer. In this paper, we report the incident quantum efficiency ηin, not incident energy or power, as the evaluation function by the ant colony algorithm optimization method, which is a swarm-based optimization method. Also, SPCTRL2 is proposed to be incorporated for accurate optimization because the solar irradiance on a receiver plane is dependent on position, season, and time. Cities of Quito, Beijing and Moscow are selected for two-and three-layer antireflective coating optimization over λ = [300,1100] nm and θ = [0°, 90°]. The ηin increases by 0.26%, 1.37% and 4.24% for the above 3 cities, respectively, compared with that calculated by other rigorous optimization algorithms methods, which is further verified by the effect of position and time dependent solar spectrum on the antireflective coating design.
基金The National Natural Science Foundation of China(No.61074147)the Natural Science Foundation of Guangdong Province(No.S2011010005059)+2 种基金the Foundation of Enterprise-University-Research Institute Cooperation from Guangdong Province and Ministry of Education of China(No.2012B091000171,2011B090400460)the Science and Technology Program of Guangdong Province(No.2012B050600028)the Science and Technology Program of Huadu District,Guangzhou(No.HD14ZD001)
文摘Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.
基金The National Natural Science Foundation of China(No.61231002,61273266,61571106)the Foundation of the Department of Science and Technology of Guizhou Province(No.[2015]7637)
文摘In order to effectively conduct emotion recognition from spontaneous, non-prototypical and unsegmented speech so as to create a more natural human-machine interaction; a novel speech emotion recognition algorithm based on the combination of the emotional data field （EDF） and the ant colony search （ACS） strategy, called the EDF-ACS algorithm, is proposed. More specifically, the inter- relationship among the turn-based acoustic feature vectors of different labels are established by using the potential function in the EDF. To perform the spontaneous speech emotion recognition, the artificial colony is used to mimic the turn- based acoustic feature vectors. Then, the canonical ACS strategy is used to investigate the movement direction of each artificial ant in the EDF, which is regarded as the emotional label of the corresponding turn-based acoustic feature vector. The proposed EDF-ACS algorithm is evaluated on the continueous audio）＇visual emotion challenge （AVEC） 2012 dataset, which contains the spontaneous, non-prototypical and unsegmented speech emotion data. The experimental results show that the proposed EDF-ACS algorithm outperforms the existing state-of-the-art algorithm in turn-based speech emotion recognition.
基金Supported by Special Fund for Forest-scientific Research in the Public Interest of China(201104061)~~
文摘The antibacterial effects of waste liquor of essence oil extraction from Sabina vulgaris Ant on Escherichia coil, Staphylococcus aureus, Salmonella, Bacillus subtilis, Bacillus magaterium and Bacillus cereus in foods were evaluated by paper disk method. The results showed that the waste liquor of essence oil extraction from S. vulgaris had inhibitory effects on E. coil, S. aureus and Salmonella with bet- ter inhibitory effects on E. coil and Salmonella; the bacteriostatic effect of water steam distillation waste liquor was better than that of water extraction waste liquor. The more times the waste liquor was distilled, the higher the active ingredients content was, and the better the bacteriostatic effect was.
基金Supported by State Key Laboratory of Robotics and System (HIT) under Grant No.SKLRS200706the Heilongjiang Scientific Research Foundation for Postdoctoral Financial Assistance under Grant No.323630221the Project of Harbin Technological Talent Research Foundation under Grant No.RC2006QN009015
文摘Path planning is an important issue for autonomous underwater vehicles （AUVs） traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization （ACO） were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.
