Cyber Defense is becoming a major issue for every organization to keep business continuity intact.The presented paper explores the effectiveness of a meta-heuristic optimization algorithm-Artificial Bees Colony Algori...Cyber Defense is becoming a major issue for every organization to keep business continuity intact.The presented paper explores the effectiveness of a meta-heuristic optimization algorithm-Artificial Bees Colony Algorithm(ABC)as an Nature Inspired Cyber Security mechanism to achieve adaptive defense.It experiments on the Denial-Of-Service attack scenarios which involves limiting the traffic flow for each node.Businesses today have adapted their service distribution models to include the use of the Internet,allowing them to effectively manage and interact with their customer data.This shift has created an increased reliance on online services to store vast amounts of confidential customer data,meaning any disruption or outage of these services could be disastrous for the business,leaving them without the knowledge to serve their customers.Adversaries can exploit such an event to gain unauthorized access to the confidential data of the customers.The proposed algorithm utilizes an Adaptive Defense approach to continuously select nodes that could present characteristics of a probable malicious entity.For any changes in network parameters,the cluster of nodes is selected in the prepared solution set as a probable malicious node and the traffic rate with the ratio of packet delivery is managed with respect to the properties of normal nodes to deliver a disaster recovery plan for potential businesses.展开更多
A new bionic approach is presented to find the optimal topologies of a structure with tension-only or compression-onlymaterial based on bone remodelling theory.By traditional methods,the computational cost of topology...A new bionic approach is presented to find the optimal topologies of a structure with tension-only or compression-onlymaterial based on bone remodelling theory.By traditional methods,the computational cost of topology optimization of thestructure is high due to material nonlinearity.To improve the efficiency of optimization,the reference-interval with material-replacement method is presented.In the method,firstly,the optimization process of a structure is considered as bone remodellingprocess under the same loading conditions.A reference interval of Strain Energy Density (SED),corresponding to thedead zone or lazy zone in bone mechanics,is adopted to control the update of the design variables.Secondly,a material-replacement scheme is used to simplify the Finite Element Analysis (FEA) of structure in optimization.In the operation ofmaterial-replacement,the original tension-only or compression-only material in design domain is replaced with a new isotropicmaterial and the Effective Strain Energy Density (ESED) of each element can be obtained.Finally,the update of design variablesis determined by comparing the local ESED and the current reference interval of SED,e.g.,the increment of a relativedensity is nonzero if the local ESED is out of the current reference interval.Numerical results validate the method.展开更多
With the emergence of pre-trained models,current neural networks are able to give task performance that is comparable to humans.However,we know little about the fundamental working mechanism of pre-trained models in w...With the emergence of pre-trained models,current neural networks are able to give task performance that is comparable to humans.However,we know little about the fundamental working mechanism of pre-trained models in which we do not know how they approach such performance and how the task is solved by the model.For example,given a task,human learns from easy to hard,whereas the model learns randomly.Undeniably,difficulty-insensitive learning leads to great success in natural language processing(NLP),but little attention has been paid to the effect of text difficulty in NLP.We propose a human learning matching index(HLM Index)to investigate the effect of text difficulty.Experiment results show:1)LSTM gives more human-like learning behavior than BERT.Additionally,UID-SuperLinear gives the best evaluation of text difficulty among four text difficulty criteria.Among nine tasks,some tasks’performance is related to text difficulty,whereas others are not.2)Model trained on easy data performs best in both easy and medium test data,whereas trained on hard data only performs well on hard test data.3)Train the model from easy to hard,leading to quicker convergence.展开更多
Nature has provided us the assurance and inspiration for thousands of years in synthesizing value-added chemicals,with the assistance of reactive hydrogen species,and water as the ultimate hydrogen source.However,the ...Nature has provided us the assurance and inspiration for thousands of years in synthesizing value-added chemicals,with the assistance of reactive hydrogen species,and water as the ultimate hydrogen source.However,the natural photosynthesis is inefficient due to some intrinsic properties,urging people not only to learn from but also surpass during nature imitation.In this review,we summarized recent progresses on reactive hydrogen species-assisted nanocatalytic reduction of organic molecules towards value-added fine chemicals and pharmaceuticals,with water as the hydrogen source,and especially highlighted how photocatalytically or electrocatalytically evolved reactive hydrogen species synergize with biocatalytic centers and nanocatalytic sites for reduction of organic molecules.The design principles of collaborative semi-artificial systems and nanocatalytic artificial systems,the structure tuning of catalysts for the evolution and utilization of hydrogen species,and the determination of reactive hydrogen species for mechanistic insights were discussed in detail.Finally,perspectives were provided for further advancing this emerging area of nanocatalytic reduction of organic molecules from water(or proton)and organics.展开更多
Learning from nature has traditionally and continuously provided important insights to drive a paradigm shift in technology.In particular,recent studies show that many biological organisms exhibit spectacular surface ...Learning from nature has traditionally and continuously provided important insights to drive a paradigm shift in technology.In particular,recent studies show that many biological organisms exhibit spectacular surface topography such as shape,size,spatial organization,periodicity,interconnectivity,and hierarchy to endow them with the capability to adapt dynamically and responsively to a wide range of environments.More excitingly,in a broader perspective,these normally neglected topological features have the potential to fundamentally change the way of how engineering surface works,such as how fluid flows,how heat is transported,and how energy is generated,saved,and converted,to name a few.Thus,the design of nature-inspired surface topography for unique functions will spur new thinking and provide paradigm shift in the development of the new engineering surfaces.In this review,we first present a brief introduction to some insights extracted from nature.Then,we highlight recent progress in designing new surface topographies and demonstrate their applications in emerging areas including thermal-fluid transport,anti-icing,water harvesting,power generation,adhesive control,and soft robotics.Finally,we offer our perspectives on this emerging field,with the aim to stimulate new thinking on the development of next-generation of new materials and devices,and dramatically extend the boundaries of traditional engineering.展开更多
文摘Cyber Defense is becoming a major issue for every organization to keep business continuity intact.The presented paper explores the effectiveness of a meta-heuristic optimization algorithm-Artificial Bees Colony Algorithm(ABC)as an Nature Inspired Cyber Security mechanism to achieve adaptive defense.It experiments on the Denial-Of-Service attack scenarios which involves limiting the traffic flow for each node.Businesses today have adapted their service distribution models to include the use of the Internet,allowing them to effectively manage and interact with their customer data.This shift has created an increased reliance on online services to store vast amounts of confidential customer data,meaning any disruption or outage of these services could be disastrous for the business,leaving them without the knowledge to serve their customers.Adversaries can exploit such an event to gain unauthorized access to the confidential data of the customers.The proposed algorithm utilizes an Adaptive Defense approach to continuously select nodes that could present characteristics of a probable malicious entity.For any changes in network parameters,the cluster of nodes is selected in the prepared solution set as a probable malicious node and the traffic rate with the ratio of packet delivery is managed with respect to the properties of normal nodes to deliver a disaster recovery plan for potential businesses.
基金the National Natural Science Foundation of China(Grant No.50908190)the Human Resources Foundation of Northwest A&F University(Grant No.Z111020903)
文摘A new bionic approach is presented to find the optimal topologies of a structure with tension-only or compression-onlymaterial based on bone remodelling theory.By traditional methods,the computational cost of topology optimization of thestructure is high due to material nonlinearity.To improve the efficiency of optimization,the reference-interval with material-replacement method is presented.In the method,firstly,the optimization process of a structure is considered as bone remodellingprocess under the same loading conditions.A reference interval of Strain Energy Density (SED),corresponding to thedead zone or lazy zone in bone mechanics,is adopted to control the update of the design variables.Secondly,a material-replacement scheme is used to simplify the Finite Element Analysis (FEA) of structure in optimization.In the operation ofmaterial-replacement,the original tension-only or compression-only material in design domain is replaced with a new isotropicmaterial and the Effective Strain Energy Density (ESED) of each element can be obtained.Finally,the update of design variablesis determined by comparing the local ESED and the current reference interval of SED,e.g.,the increment of a relativedensity is nonzero if the local ESED is out of the current reference interval.Numerical results validate the method.
基金the support of the National Natural Science Foundation of China(Nos.U22B2059,62176079)National Natural Science Foundation of Heilongjiang Province,China(No.YQ 2022F005)the Industry-University-Research Innovation Foundation of China University(No.2021ITA05009).
文摘With the emergence of pre-trained models,current neural networks are able to give task performance that is comparable to humans.However,we know little about the fundamental working mechanism of pre-trained models in which we do not know how they approach such performance and how the task is solved by the model.For example,given a task,human learns from easy to hard,whereas the model learns randomly.Undeniably,difficulty-insensitive learning leads to great success in natural language processing(NLP),but little attention has been paid to the effect of text difficulty in NLP.We propose a human learning matching index(HLM Index)to investigate the effect of text difficulty.Experiment results show:1)LSTM gives more human-like learning behavior than BERT.Additionally,UID-SuperLinear gives the best evaluation of text difficulty among four text difficulty criteria.Among nine tasks,some tasks’performance is related to text difficulty,whereas others are not.2)Model trained on easy data performs best in both easy and medium test data,whereas trained on hard data only performs well on hard test data.3)Train the model from easy to hard,leading to quicker convergence.
基金the financial support of the National Natural Science Foundation of China(Nos.22102102,21805191 and 21972094)China Postdoctoral Science Foundation(No.2021T140472)+4 种基金Guangdong Basic and Applied Basic Research Foundation(No.2020A1515010982)Educational Commission of Guangdong Province(No.839-0000013131)Shenzhen Stable Support Project(Nos.20200812160737002 and 20200812122947002)Shenzhen Peacock Plan(Nos.KQTD2016053112042971,20210308299C,20180921273B,20210802524B,and 827-000421)Shenzhen Science and Technology Program(Nos.JCYJ20190808142001745 and RCJC20200714114434086)。
文摘Nature has provided us the assurance and inspiration for thousands of years in synthesizing value-added chemicals,with the assistance of reactive hydrogen species,and water as the ultimate hydrogen source.However,the natural photosynthesis is inefficient due to some intrinsic properties,urging people not only to learn from but also surpass during nature imitation.In this review,we summarized recent progresses on reactive hydrogen species-assisted nanocatalytic reduction of organic molecules towards value-added fine chemicals and pharmaceuticals,with water as the hydrogen source,and especially highlighted how photocatalytically or electrocatalytically evolved reactive hydrogen species synergize with biocatalytic centers and nanocatalytic sites for reduction of organic molecules.The design principles of collaborative semi-artificial systems and nanocatalytic artificial systems,the structure tuning of catalysts for the evolution and utilization of hydrogen species,and the determination of reactive hydrogen species for mechanistic insights were discussed in detail.Finally,perspectives were provided for further advancing this emerging area of nanocatalytic reduction of organic molecules from water(or proton)and organics.
基金supported by the National Key Research and Development Program of China(Grant No.2018YFA0209500)the Research Council of Hong Kong(Grant Nos.C1018-17G,and 11275216)+3 种基金the Shenzhen Science and Technology Innovation Council(Grant No.JCYJ20170413141208098)the National Natural Science Foundation of China(Grant No.51706100)the Natural Science Foundation of Jiangsu Province(Grant No.BK20180477)the City University of Hong Kong(Grant No.9360140)
文摘Learning from nature has traditionally and continuously provided important insights to drive a paradigm shift in technology.In particular,recent studies show that many biological organisms exhibit spectacular surface topography such as shape,size,spatial organization,periodicity,interconnectivity,and hierarchy to endow them with the capability to adapt dynamically and responsively to a wide range of environments.More excitingly,in a broader perspective,these normally neglected topological features have the potential to fundamentally change the way of how engineering surface works,such as how fluid flows,how heat is transported,and how energy is generated,saved,and converted,to name a few.Thus,the design of nature-inspired surface topography for unique functions will spur new thinking and provide paradigm shift in the development of the new engineering surfaces.In this review,we first present a brief introduction to some insights extracted from nature.Then,we highlight recent progress in designing new surface topographies and demonstrate their applications in emerging areas including thermal-fluid transport,anti-icing,water harvesting,power generation,adhesive control,and soft robotics.Finally,we offer our perspectives on this emerging field,with the aim to stimulate new thinking on the development of next-generation of new materials and devices,and dramatically extend the boundaries of traditional engineering.
