Dear Editor,This letter deals with the tracking problem for non-cooperative maneuvering targets based on the underwater sensor networks. Considering the acoustic intensity feature of underwater targets, a feature-aide...Dear Editor,This letter deals with the tracking problem for non-cooperative maneuvering targets based on the underwater sensor networks. Considering the acoustic intensity feature of underwater targets, a feature-aided multi-model tracking method for maneuvering targets is proposed.展开更多
Dear Editor,This letter is concerned with the energy-aware multiple sensor coscheduling for bearing-only target tracking in the underwater wireless sensor networks(UWSNs).Considering the traditional methods facing wit...Dear Editor,This letter is concerned with the energy-aware multiple sensor coscheduling for bearing-only target tracking in the underwater wireless sensor networks(UWSNs).Considering the traditional methods facing with the problems of strong environment dependence and lack flexibility,a novel sensor scheduling algorithm based on the deep reinforcement learning is proposed.Firstly,the sensors’co-scheduling strategy in UWSNs is formulated as Markov decision process(MDP).展开更多
Defect inspection,also known as defect detection,is significant in mobile screen quality control.There are some challenging issues brought by the characteristics of screen defects,including the following:(1)the proble...Defect inspection,also known as defect detection,is significant in mobile screen quality control.There are some challenging issues brought by the characteristics of screen defects,including the following:(1)the problem of interclass similarity and intraclass variation,(2)the difficulty in distinguishing low contrast,tiny-sized,or incomplete defects,and(3)the modeling of category dependencies for multi-label images.To solve these problems,a graph reasoning module,stacked on a classification module,is proposed to expand the feature dimension and improve low-quality image features by exploiting category-wise dependency,image-wise relations,and interactions between them.To further improve the classification performance,the classifier of the classification module is redesigned as a cosine similarity function.With the help of contrastive learning,the classification module can better initialize the category-wise graph of the reasoning module.Experiments on the mobile screen defect dataset show that our two-stage network achieves the following best performances:97.7%accuracy and 97.3%F-measure.This proves that the proposed approach is effective in industrial applications.展开更多
Very recently,a novel coronavirus,2019-nCoV,emerged in Wuhan,China and then quickly spread worldwide,resulting in>17,388 confirmed cases and 361 deaths as of 3 February 2020,thus calling for the development of safe...Very recently,a novel coronavirus,2019-nCoV,emerged in Wuhan,China and then quickly spread worldwide,resulting in>17,388 confirmed cases and 361 deaths as of 3 February 2020,thus calling for the development of safe and effective therapeutics and prophylatics.1,2 Similar to severe acute respiratory syndrome(SARS)-CoV,2019-nCoV belongs to lineage B betacoronavirus,and it has the ability to utilize human angiotensin-converting enzyme 2(ACE2)as a receptor to infect human cells.展开更多
Coronavirus disease 2019(COVID-19),caused by the novel human coronavirus SARS-CoV-2,is currently a major threat to public health worldwide.The viral spike protein binds the host receptor angiotensin-converting enzyme ...Coronavirus disease 2019(COVID-19),caused by the novel human coronavirus SARS-CoV-2,is currently a major threat to public health worldwide.The viral spike protein binds the host receptor angiotensin-converting enzyme 2(ACE2)via the receptor-binding domain(RBD),and thus is believed to be a major target to block viral entry.Both SARS-CoV-2 and SARS-CoV share this mechanism.Here we functionally analyzed the key amino acid residues located within receptor binding motif of RBD that may interact with human ACE2 and available neutralizing antibodies.The in vivo experiments showed that immunization with either the SARS-CoV RBD or SARS-CoV-2 RBD was able to induce strong clade-specific neutralizing antibodies in mice;however,the cross-neutralizing activity was much weaker,indicating that there are distinct antigenic features in the RBDs of the two viruses.This finding was confirmed with the available neutralizing monoclonal antibodies against SARS-CoV or SARS-CoV-2.It is worth noting that a newly developed SARS-CoV-2 human antibody,HA001,was able to neutralize SARS-CoV-2,but failed to recognize SARS-CoV.Moreover,the potential epitope residues of HA001 were identified as A475 and F486 in the SARS-CoV-2 RBD,representing new binding sites for neutralizing antibodies.Overall,our study has revealed the presence of different key epitopes between SARS-CoV and SARSCoV-2,which indicates the necessity to develop new prophylactic vaccine and antibody drugs for specific control of the COVID-19 pandemic although the available agents obtained from the SARS-CoV study are unneglectable.展开更多
This paper describes a route planner that enables an autonomous underwater vehicle to selectively complete part of the predetermined tasks in the operating ocean area when the local path cost is stochastic.The problem...This paper describes a route planner that enables an autonomous underwater vehicle to selectively complete part of the predetermined tasks in the operating ocean area when the local path cost is stochastic.The problem is formulated as a variant of the orienteering problem.Based on the genetic algorithm(GA),we propose the greedy strategy based GA(GGA)which includes a novel rebirth operator that maps infeasible individuals into the feasible solution space during evolution to improve the efficiency of the optimization,and use a differential evolution planner for providing the deterministic local path cost.The uncertainty of the local path cost comes from unpredictable obstacles,measurement error,and trajectory tracking error.To improve the robustness of the planner in an uncertain environment,a sampling strategy for path evaluation is designed,and the cost of a certain route is obtained by multiple sampling from the probability density functions of local paths.Monte Carlo simulations are used to verify the superiority and effectiveness of the planner.The promising simulation results show that the proposed GGA outperforms its counterparts by 4.7%–24.6%in terms of total profit,and the sampling-based GGA route planner(S-GGARP)improves the average profit by 5.5%compared to the GGA route planner(GGARP).展开更多
Robots need more intelligence to complete cognitive tasks in home environments.In this paper,we present a new cloud-assisted cognition adaptation mechanism for home service robots,which learns new knowledge from other...Robots need more intelligence to complete cognitive tasks in home environments.In this paper,we present a new cloud-assisted cognition adaptation mechanism for home service robots,which learns new knowledge from other robots.In this mechanism,a change detection approach is implemented in the robot to detect changes in the user’s home environment and trigger the adaptation procedure that adapts the robot’s local customized model to the environmental changes,while the adaptation is achieved by transferring knowledge from the global cloud model to the local model through model fusion.First,three different model fusion methods are proposed to carry out the adaptation procedure,and two key factors of the fusion methods are emphasized.Second,the most suitable model fusion method and its settings for the cloud–robot knowledge transfer are determined.Third,we carry out a case study of learning in a changing home environment,and the experimental results verify the efficiency and effectiveness of our solutions.The experimental results lead us to propose an empirical guideline of model fusion for the cloud–robot knowledge transfer.展开更多
基金supported by the National Natural Science Foundation of China (62173299, U1909206)the Zhejiang Provincial Natural Science Foundation of China (LZ23F030006)+1 种基金the Joint Fund of Ministry of Education for Pre-research of Equipment (8091B022147)the Fundamental Research Funds for the Central Universities (xtr072022001)。
文摘Dear Editor,This letter deals with the tracking problem for non-cooperative maneuvering targets based on the underwater sensor networks. Considering the acoustic intensity feature of underwater targets, a feature-aided multi-model tracking method for maneuvering targets is proposed.
基金This work was supported by the National Natural Science Foundation of China(62173299,U1809202)the Joint Fund of Ministry of Education for Pre-Research of Equipment(8091B022147)the Fundamental Research Funds for the Central Universities(072022001).
文摘Dear Editor,This letter is concerned with the energy-aware multiple sensor coscheduling for bearing-only target tracking in the underwater wireless sensor networks(UWSNs).Considering the traditional methods facing with the problems of strong environment dependence and lack flexibility,a novel sensor scheduling algorithm based on the deep reinforcement learning is proposed.Firstly,the sensors’co-scheduling strategy in UWSNs is formulated as Markov decision process(MDP).
基金Project supported by the National Key Research and Development Program of China(No.2020AAA0108302)the Fundamental Research Funds for the Central Universities,China(No.xtr072022001)。
文摘Defect inspection,also known as defect detection,is significant in mobile screen quality control.There are some challenging issues brought by the characteristics of screen defects,including the following:(1)the problem of interclass similarity and intraclass variation,(2)the difficulty in distinguishing low contrast,tiny-sized,or incomplete defects,and(3)the modeling of category dependencies for multi-label images.To solve these problems,a graph reasoning module,stacked on a classification module,is proposed to expand the feature dimension and improve low-quality image features by exploiting category-wise dependency,image-wise relations,and interactions between them.To further improve the classification performance,the classifier of the classification module is redesigned as a cosine similarity function.With the help of contrastive learning,the classification module can better initialize the category-wise graph of the reasoning module.Experiments on the mobile screen defect dataset show that our two-stage network achieves the following best performances:97.7%accuracy and 97.3%F-measure.This proves that the proposed approach is effective in industrial applications.
基金This work was supported by the National Megaprojects of China for Major Infectious Diseases(2018ZX10301403).
文摘Very recently,a novel coronavirus,2019-nCoV,emerged in Wuhan,China and then quickly spread worldwide,resulting in>17,388 confirmed cases and 361 deaths as of 3 February 2020,thus calling for the development of safe and effective therapeutics and prophylatics.1,2 Similar to severe acute respiratory syndrome(SARS)-CoV,2019-nCoV belongs to lineage B betacoronavirus,and it has the ability to utilize human angiotensin-converting enzyme 2(ACE2)as a receptor to infect human cells.
基金supported by the National Natural Science Foundation of China(82041015)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB19000000)+1 种基金the Key International Partnership Program of the Chinese Academy of Sciences(153D31KYSB20180055)the National Major Science and Technology Projects of China(2018ZX10301403).
文摘Coronavirus disease 2019(COVID-19),caused by the novel human coronavirus SARS-CoV-2,is currently a major threat to public health worldwide.The viral spike protein binds the host receptor angiotensin-converting enzyme 2(ACE2)via the receptor-binding domain(RBD),and thus is believed to be a major target to block viral entry.Both SARS-CoV-2 and SARS-CoV share this mechanism.Here we functionally analyzed the key amino acid residues located within receptor binding motif of RBD that may interact with human ACE2 and available neutralizing antibodies.The in vivo experiments showed that immunization with either the SARS-CoV RBD or SARS-CoV-2 RBD was able to induce strong clade-specific neutralizing antibodies in mice;however,the cross-neutralizing activity was much weaker,indicating that there are distinct antigenic features in the RBDs of the two viruses.This finding was confirmed with the available neutralizing monoclonal antibodies against SARS-CoV or SARS-CoV-2.It is worth noting that a newly developed SARS-CoV-2 human antibody,HA001,was able to neutralize SARS-CoV-2,but failed to recognize SARS-CoV.Moreover,the potential epitope residues of HA001 were identified as A475 and F486 in the SARS-CoV-2 RBD,representing new binding sites for neutralizing antibodies.Overall,our study has revealed the presence of different key epitopes between SARS-CoV and SARSCoV-2,which indicates the necessity to develop new prophylactic vaccine and antibody drugs for specific control of the COVID-19 pandemic although the available agents obtained from the SARS-CoV study are unneglectable.
基金supported by the National Natural Science Foundation of China and Zhejiang Joint Fund for the Integration of Industrialization and Informatization(Nos.U1809212 and U1909206)the Fundamental Research Funds for the Zhejiang Provincial Universities(No.2021XZZX014)the National Natural Science Foundation of China(No.62088102)。
文摘This paper describes a route planner that enables an autonomous underwater vehicle to selectively complete part of the predetermined tasks in the operating ocean area when the local path cost is stochastic.The problem is formulated as a variant of the orienteering problem.Based on the genetic algorithm(GA),we propose the greedy strategy based GA(GGA)which includes a novel rebirth operator that maps infeasible individuals into the feasible solution space during evolution to improve the efficiency of the optimization,and use a differential evolution planner for providing the deterministic local path cost.The uncertainty of the local path cost comes from unpredictable obstacles,measurement error,and trajectory tracking error.To improve the robustness of the planner in an uncertain environment,a sampling strategy for path evaluation is designed,and the cost of a certain route is obtained by multiple sampling from the probability density functions of local paths.Monte Carlo simulations are used to verify the superiority and effectiveness of the planner.The promising simulation results show that the proposed GGA outperforms its counterparts by 4.7%–24.6%in terms of total profit,and the sampling-based GGA route planner(S-GGARP)improves the average profit by 5.5%compared to the GGA route planner(GGARP).
基金Project supported by the National Natural Science Foundation of China(Nos.U21A20485 and 62088102)the Natural Science Foundation of China-Shenzhen Basic Research Center Project(No.U1713216)the Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT20026)。
文摘Robots need more intelligence to complete cognitive tasks in home environments.In this paper,we present a new cloud-assisted cognition adaptation mechanism for home service robots,which learns new knowledge from other robots.In this mechanism,a change detection approach is implemented in the robot to detect changes in the user’s home environment and trigger the adaptation procedure that adapts the robot’s local customized model to the environmental changes,while the adaptation is achieved by transferring knowledge from the global cloud model to the local model through model fusion.First,three different model fusion methods are proposed to carry out the adaptation procedure,and two key factors of the fusion methods are emphasized.Second,the most suitable model fusion method and its settings for the cloud–robot knowledge transfer are determined.Third,we carry out a case study of learning in a changing home environment,and the experimental results verify the efficiency and effectiveness of our solutions.The experimental results lead us to propose an empirical guideline of model fusion for the cloud–robot knowledge transfer.
