The purpose of community detection in complex networks is to identify the structural location of nodes. Complex network methods are usually graphical, with graph nodes representing objects and edges representing conne...The purpose of community detection in complex networks is to identify the structural location of nodes. Complex network methods are usually graphical, with graph nodes representing objects and edges representing connections between things. Communities are node clusters with many internal links but minimal intergroup connections. Although community detection has attracted much attention in social media research, most face functional weaknesses because the structure of society is unclear or the characteristics of nodes in society are not the same. Also, many existing algorithms have complex and costly calculations. This paper proposes different Harris Hawk Optimization (HHO) algorithm methods (such as Improved HHO Opposition-Based Learning(OBL) (IHHOOBL), Improved HHO Lévy Flight (IHHOLF), and Improved HHO Chaotic Map (IHHOCM)) were designed to balance exploitation and exploration in this algorithm for community detection in the social network. The proposed methods are evaluated on 12 different datasets based on NMI and modularity criteria. The findings reveal that the IHHOOBL method has better detection accuracy than IHHOLF and IHHOCM. Also, to offer the efficiency of the , state-of-the-art algorithms have been used as comparisons. The improvement percentage of IHHOOBL compared to the state-of-the-art algorithm is about 7.18%.展开更多
Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).F...Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).Firstly,we used a Gaussian chaotic mapping strategy to initialize the positions of individuals in the population,which enriches the initial individual species characteristics.Secondly,by optimizing the energy parameter and introducing the cosine strategy,the algorithm's ability to jump out of the local optimum is enhanced,which improves the performance of the algorithm.Finally,comparison experiments with other intelligent algorithms were conducted on 13 classical test function sets.The results show that GHHO has better performance in all aspects compared to other optimization algorithms.The improved algorithm is more suitable for generalization to real optimization problems.展开更多
AIM:To develop a classifier for traditional Chinese medicine(TCM)syndrome differentiation of diabetic retinopathy(DR),using optimized machine learning algorithms,which can provide the basis for TCM objective and intel...AIM:To develop a classifier for traditional Chinese medicine(TCM)syndrome differentiation of diabetic retinopathy(DR),using optimized machine learning algorithms,which can provide the basis for TCM objective and intelligent syndrome differentiation.METHODS:Collated data on real-world DR cases were collected.A variety of machine learning methods were used to construct TCM syndrome classification model,and the best performance was selected as the basic model.Genetic Algorithm(GA)was used for feature selection to obtain the optimal feature combination.Harris Hawk Optimization(HHO)was used for parameter optimization,and a classification model based on feature selection and parameter optimization was constructed.The performance of the model was compared with other optimization algorithms.The models were evaluated with accuracy,precision,recall,and F1 score as indicators.RESULTS:Data on 970 cases that met screening requirements were collected.Support Vector Machine(SVM)was the best basic classification model.The accuracy rate of the model was 82.05%,the precision rate was 82.34%,the recall rate was 81.81%,and the F1 value was 81.76%.After GA screening,the optimal feature combination contained 37 feature values,which was consistent with TCM clinical practice.The model based on optimal combination and SVM(GA_SVM)had an accuracy improvement of 1.92%compared to the basic classifier.SVM model based on HHO and GA optimization(HHO_GA_SVM)had the best performance and convergence speed compared with other optimization algorithms.Compared with the basic classification model,the accuracy was improved by 3.51%.CONCLUSION:HHO and GA optimization can improve the model performance of SVM in TCM syndrome differentiation of DR.It provides a new method and research idea for TCM intelligent assisted syndrome differentiation.展开更多
Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been...Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.展开更多
The massive influx of traffic on the Internet has made the composition of web traffic increasingly complex.Traditional port-based or protocol-based network traffic identification methods are no longer suitable for to...The massive influx of traffic on the Internet has made the composition of web traffic increasingly complex.Traditional port-based or protocol-based network traffic identification methods are no longer suitable for today’s complex and changing networks.Recently,machine learning has beenwidely applied to network traffic recognition.Still,high-dimensional features and redundant data in network traffic can lead to slow convergence problems and low identification accuracy of network traffic recognition algorithms.Taking advantage of the faster optimizationseeking capability of the jumping spider optimization algorithm(JSOA),this paper proposes a jumping spider optimization algorithmthat incorporates the harris hawk optimization(HHO)and small hole imaging(HHJSOA).We use it in network traffic identification feature selection.First,the method incorporates the HHO escape energy factor and the hard siege strategy to forma newsearch strategy for HHJSOA.This location update strategy enhances the search range of the optimal solution of HHJSOA.We use small hole imaging to update the inferior individual.Next,the feature selection problem is coded to propose a jumping spiders individual coding scheme.Multiple iterations of the HHJSOA algorithmfind the optimal individual used as the selected feature for KNN classification.Finally,we validate the classification accuracy and performance of the HHJSOA algorithm using the UNSW-NB15 dataset and KDD99 dataset.Experimental results show that compared with other algorithms for the UNSW-NB15 dataset,the improvement is at least 0.0705,0.00147,and 1 on the accuracy,fitness value,and the number of features.In addition,compared with other feature selectionmethods for the same datasets,the proposed algorithmhas faster convergence,better merit-seeking,and robustness.Therefore,HHJSOAcan improve the classification accuracy and solve the problem that the network traffic recognition algorithm needs to be faster to converge and easily fall into local optimum due to high-dimensional features.展开更多
Since its publication in 2016,Paper Hawk has been studied by literary critics from different angles,such as its inheritance of the Chinese classical literature tradition,its conception of language and structure form,a...Since its publication in 2016,Paper Hawk has been studied by literary critics from different angles,such as its inheritance of the Chinese classical literature tradition,its conception of language and structure form,and even its usage of imagery.The historical imagination in the novel has also attracted great attention in academic circles.As one of the clues in the novel,Chinese cuisine enables the writer to outline the setting of the era and human nature,and reflect on traditional culture with a keen insight.Taking food as a starting point,I explores the path of historical evolution,its development as well as its ups and downs.A warm thanks also goes out to Dr.Xu Shiying for her interview on historical writing(Appendix follows),which represents the historical depth of Paper Hawk in a dialogue format.展开更多
Only one herbicide mode of action (ALS inhibitor) is currently available to Ontario dry bean producers for soil-applied broadleaf weed control. Four field studies were conducted over two years (2014, 2015) to examine ...Only one herbicide mode of action (ALS inhibitor) is currently available to Ontario dry bean producers for soil-applied broadleaf weed control. Four field studies were conducted over two years (2014, 2015) to examine the tolerance of four market classes of dry beans to sulfentrazone (210 and 420 g·ai·ha<sup>-1</sup>) and pyroxasulfone (100 and 200 g·ai·ha<sup>-1</sup>) applied alone and in combination. The registration of these two herbicides would provide Ontario dry bean producers with two additional modes of action for broadleaf weed control. Pyroxasulfone caused up to 23%, 6%, 7% and 10% injury in adzuki, kidney, small red Mexican and white bean, respectively;sulfentrazone caused up to 51%, 12%, 15% and 44% injury and the combination caused up to 90%, 23%, 29% and 62% injury, respectively. Kidney and small red Mexican bean density, height, seed moisture content and yield were not affected. Pyroxasulfone (200 g·ai·ha<sup>-1</sup>) + sulfentrazone (420 g·ai·ha<sup>-1</sup>) reduced adzuki and white bean density, shoot dry weight, height and yield. This study concludes that pyroxasulfone (100 g·ai·ha<sup>-1</sup>) + sulfentrazone (210 g·ai·ha<sup>-1</sup>) applied PRE can be safely used to control weeds in Ontario kidney and small red Mexican bean production.展开更多
Many species have been drastically affected by rapid urbanization.Harris' s hawks from their natural habitat of open spaces and a supply of rodents,lizards and other small prey have been forced to change their nat...Many species have been drastically affected by rapid urbanization.Harris' s hawks from their natural habitat of open spaces and a supply of rodents,lizards and other small prey have been forced to change their natural environment adapting to living in open spaces in sub-and periurban areas.Specific areas include playgrounds,parks and school courtyards.The migration of this predatory species into these areas poses a risk to individuals,and especially the children are often attacked by claws,talons and beaks intentionally or as collateral damage while attacking rodent prey.In addition,the diverse micro-organisms harbored in the beaks and talons can result in wound infections,presenting a challenge to clinical management.Here we would like to present a case of an 80-year-old man with cellulitis of bom hands after sustaining minor injuries from the talons of a Harris s hawk and review the management options.We would also like to draw attention to the matter that,even though previously a rarity,more cases of injuries caused by birds of prey may be seen in hospital settings.展开更多
Pedestrian signals, particularly at signalized, midblock crossings, delay drivers, which is termed ＂unnecessary delay＂ in this study. A pedestrian hybrid beacon was proven to be effective in decreasing this unnecess...Pedestrian signals, particularly at signalized, midblock crossings, delay drivers, which is termed ＂unnecessary delay＂ in this study. A pedestrian hybrid beacon was proven to be effective in decreasing this unnecessary delay to the drivers at midblock pedestrian crossings when compared to standard signalized midblock crossings. Two pedestrian hybrid beacons were installed at midblock pedestrian crossings in Lawrence, Kansas. A study was conducted at these two locations to determine the effectiveness of the pedestrian hybrid beacon in decreasing the unnecessary delay to drivers by comparing them with a signalized midblock on Massachusetts Street, Lawrence, Kansas. In addition to the delay measurements for drivers at pedestrian hybrid beacon and signalized treatment at midblock pedestrian crossings, other parameters such as driver compliance rate, pedestrian compliance rate, and other driver and pedestrian characteristics were also studied. Video cameras were used at these test locations and the effectiveness of the pedestrian hybrid beacon was analyzed from the video. A more than 90% reduction in delays was observed for the drivers at the pedestrian hybrid beacon at midblock crossings compared to the signalized crossing. Further, a better driver compliance rate was also recorded at the pedestrian hybrid beacon. Information about reductions in unnecessary delay to drivers and improvements to driver and pedestrian compliance rates from the use of pedestrian hybrid beacons would be useful to engineers, decision makers, and researchers to determine an optimum treatment at desired pedestrian crossings.展开更多
在正常井炮施工中,G3i仪器采用Shot ProⅡ作为编码器。由于其内部没有卫星信号接收芯片,因此无法引入外部GPS信号同步仪器时间,从而导致无法使用Hawk采集站采集到的原始地震数据进行有效分离。本文介绍了使用Pro Pak V3GPS接收机与G3i...在正常井炮施工中,G3i仪器采用Shot ProⅡ作为编码器。由于其内部没有卫星信号接收芯片,因此无法引入外部GPS信号同步仪器时间,从而导致无法使用Hawk采集站采集到的原始地震数据进行有效分离。本文介绍了使用Pro Pak V3GPS接收机与G3i仪器联机,实现了在井炮施工中引入UTC(Coordinated Universal Time,世界标准时间)时间的方法,从而利用该时间把有效地震数据从原始记录的数据中分离提取出来。展开更多
文摘The purpose of community detection in complex networks is to identify the structural location of nodes. Complex network methods are usually graphical, with graph nodes representing objects and edges representing connections between things. Communities are node clusters with many internal links but minimal intergroup connections. Although community detection has attracted much attention in social media research, most face functional weaknesses because the structure of society is unclear or the characteristics of nodes in society are not the same. Also, many existing algorithms have complex and costly calculations. This paper proposes different Harris Hawk Optimization (HHO) algorithm methods (such as Improved HHO Opposition-Based Learning(OBL) (IHHOOBL), Improved HHO Lévy Flight (IHHOLF), and Improved HHO Chaotic Map (IHHOCM)) were designed to balance exploitation and exploration in this algorithm for community detection in the social network. The proposed methods are evaluated on 12 different datasets based on NMI and modularity criteria. The findings reveal that the IHHOOBL method has better detection accuracy than IHHOLF and IHHOCM. Also, to offer the efficiency of the , state-of-the-art algorithms have been used as comparisons. The improvement percentage of IHHOOBL compared to the state-of-the-art algorithm is about 7.18%.
文摘Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).Firstly,we used a Gaussian chaotic mapping strategy to initialize the positions of individuals in the population,which enriches the initial individual species characteristics.Secondly,by optimizing the energy parameter and introducing the cosine strategy,the algorithm's ability to jump out of the local optimum is enhanced,which improves the performance of the algorithm.Finally,comparison experiments with other intelligent algorithms were conducted on 13 classical test function sets.The results show that GHHO has better performance in all aspects compared to other optimization algorithms.The improved algorithm is more suitable for generalization to real optimization problems.
基金Supported by Hunan Province Traditional Chinese Medicine Research Project(No.B2023043)Hunan Provincial Department of Education Scientific Research Project(No.22B0386)Hunan University of Traditional Chinese Medicine Campus level Research Fund Project(No.2022XJZKC004).
文摘AIM:To develop a classifier for traditional Chinese medicine(TCM)syndrome differentiation of diabetic retinopathy(DR),using optimized machine learning algorithms,which can provide the basis for TCM objective and intelligent syndrome differentiation.METHODS:Collated data on real-world DR cases were collected.A variety of machine learning methods were used to construct TCM syndrome classification model,and the best performance was selected as the basic model.Genetic Algorithm(GA)was used for feature selection to obtain the optimal feature combination.Harris Hawk Optimization(HHO)was used for parameter optimization,and a classification model based on feature selection and parameter optimization was constructed.The performance of the model was compared with other optimization algorithms.The models were evaluated with accuracy,precision,recall,and F1 score as indicators.RESULTS:Data on 970 cases that met screening requirements were collected.Support Vector Machine(SVM)was the best basic classification model.The accuracy rate of the model was 82.05%,the precision rate was 82.34%,the recall rate was 81.81%,and the F1 value was 81.76%.After GA screening,the optimal feature combination contained 37 feature values,which was consistent with TCM clinical practice.The model based on optimal combination and SVM(GA_SVM)had an accuracy improvement of 1.92%compared to the basic classifier.SVM model based on HHO and GA optimization(HHO_GA_SVM)had the best performance and convergence speed compared with other optimization algorithms.Compared with the basic classification model,the accuracy was improved by 3.51%.CONCLUSION:HHO and GA optimization can improve the model performance of SVM in TCM syndrome differentiation of DR.It provides a new method and research idea for TCM intelligent assisted syndrome differentiation.
文摘Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.
基金funded by the National Natural Science Foundation of China under Grant No.61602162.
文摘The massive influx of traffic on the Internet has made the composition of web traffic increasingly complex.Traditional port-based or protocol-based network traffic identification methods are no longer suitable for today’s complex and changing networks.Recently,machine learning has beenwidely applied to network traffic recognition.Still,high-dimensional features and redundant data in network traffic can lead to slow convergence problems and low identification accuracy of network traffic recognition algorithms.Taking advantage of the faster optimizationseeking capability of the jumping spider optimization algorithm(JSOA),this paper proposes a jumping spider optimization algorithmthat incorporates the harris hawk optimization(HHO)and small hole imaging(HHJSOA).We use it in network traffic identification feature selection.First,the method incorporates the HHO escape energy factor and the hard siege strategy to forma newsearch strategy for HHJSOA.This location update strategy enhances the search range of the optimal solution of HHJSOA.We use small hole imaging to update the inferior individual.Next,the feature selection problem is coded to propose a jumping spiders individual coding scheme.Multiple iterations of the HHJSOA algorithmfind the optimal individual used as the selected feature for KNN classification.Finally,we validate the classification accuracy and performance of the HHJSOA algorithm using the UNSW-NB15 dataset and KDD99 dataset.Experimental results show that compared with other algorithms for the UNSW-NB15 dataset,the improvement is at least 0.0705,0.00147,and 1 on the accuracy,fitness value,and the number of features.In addition,compared with other feature selectionmethods for the same datasets,the proposed algorithmhas faster convergence,better merit-seeking,and robustness.Therefore,HHJSOAcan improve the classification accuracy and solve the problem that the network traffic recognition algorithm needs to be faster to converge and easily fall into local optimum due to high-dimensional features.
基金FRG Research Project Fund of Hong Kong Baptist University:"A Study of the Relationship Between Chinese Urban Literature and Mass Culture"(FRG2/14-15/027,HKBU).
文摘Since its publication in 2016,Paper Hawk has been studied by literary critics from different angles,such as its inheritance of the Chinese classical literature tradition,its conception of language and structure form,and even its usage of imagery.The historical imagination in the novel has also attracted great attention in academic circles.As one of the clues in the novel,Chinese cuisine enables the writer to outline the setting of the era and human nature,and reflect on traditional culture with a keen insight.Taking food as a starting point,I explores the path of historical evolution,its development as well as its ups and downs.A warm thanks also goes out to Dr.Xu Shiying for her interview on historical writing(Appendix follows),which represents the historical depth of Paper Hawk in a dialogue format.
文摘Only one herbicide mode of action (ALS inhibitor) is currently available to Ontario dry bean producers for soil-applied broadleaf weed control. Four field studies were conducted over two years (2014, 2015) to examine the tolerance of four market classes of dry beans to sulfentrazone (210 and 420 g·ai·ha<sup>-1</sup>) and pyroxasulfone (100 and 200 g·ai·ha<sup>-1</sup>) applied alone and in combination. The registration of these two herbicides would provide Ontario dry bean producers with two additional modes of action for broadleaf weed control. Pyroxasulfone caused up to 23%, 6%, 7% and 10% injury in adzuki, kidney, small red Mexican and white bean, respectively;sulfentrazone caused up to 51%, 12%, 15% and 44% injury and the combination caused up to 90%, 23%, 29% and 62% injury, respectively. Kidney and small red Mexican bean density, height, seed moisture content and yield were not affected. Pyroxasulfone (200 g·ai·ha<sup>-1</sup>) + sulfentrazone (420 g·ai·ha<sup>-1</sup>) reduced adzuki and white bean density, shoot dry weight, height and yield. This study concludes that pyroxasulfone (100 g·ai·ha<sup>-1</sup>) + sulfentrazone (210 g·ai·ha<sup>-1</sup>) applied PRE can be safely used to control weeds in Ontario kidney and small red Mexican bean production.
文摘Many species have been drastically affected by rapid urbanization.Harris' s hawks from their natural habitat of open spaces and a supply of rodents,lizards and other small prey have been forced to change their natural environment adapting to living in open spaces in sub-and periurban areas.Specific areas include playgrounds,parks and school courtyards.The migration of this predatory species into these areas poses a risk to individuals,and especially the children are often attacked by claws,talons and beaks intentionally or as collateral damage while attacking rodent prey.In addition,the diverse micro-organisms harbored in the beaks and talons can result in wound infections,presenting a challenge to clinical management.Here we would like to present a case of an 80-year-old man with cellulitis of bom hands after sustaining minor injuries from the talons of a Harris s hawk and review the management options.We would also like to draw attention to the matter that,even though previously a rarity,more cases of injuries caused by birds of prey may be seen in hospital settings.
基金funded jointly by the Kansas State University Transportation Center with in-kind matching funds from city of Lawrence,Kansas
文摘Pedestrian signals, particularly at signalized, midblock crossings, delay drivers, which is termed ＂unnecessary delay＂ in this study. A pedestrian hybrid beacon was proven to be effective in decreasing this unnecessary delay to the drivers at midblock pedestrian crossings when compared to standard signalized midblock crossings. Two pedestrian hybrid beacons were installed at midblock pedestrian crossings in Lawrence, Kansas. A study was conducted at these two locations to determine the effectiveness of the pedestrian hybrid beacon in decreasing the unnecessary delay to drivers by comparing them with a signalized midblock on Massachusetts Street, Lawrence, Kansas. In addition to the delay measurements for drivers at pedestrian hybrid beacon and signalized treatment at midblock pedestrian crossings, other parameters such as driver compliance rate, pedestrian compliance rate, and other driver and pedestrian characteristics were also studied. Video cameras were used at these test locations and the effectiveness of the pedestrian hybrid beacon was analyzed from the video. A more than 90% reduction in delays was observed for the drivers at the pedestrian hybrid beacon at midblock crossings compared to the signalized crossing. Further, a better driver compliance rate was also recorded at the pedestrian hybrid beacon. Information about reductions in unnecessary delay to drivers and improvements to driver and pedestrian compliance rates from the use of pedestrian hybrid beacons would be useful to engineers, decision makers, and researchers to determine an optimum treatment at desired pedestrian crossings.
