A vehicle conflict detection and resolution method is proposed based on the concept of vehicle infrastructure integration ( Ⅶ) system to prevent vehicle accident beforehand at blind crossing. After analyzing traffic ...A vehicle conflict detection and resolution method is proposed based on the concept of vehicle infrastructure integration ( Ⅶ) system to prevent vehicle accident beforehand at blind crossing. After analyzing traffic conflict characteristics and vehicle collision scenarios at intersection,a vehicle dynamics model and an intervehicle communication method are discussed. In the inter-vehicle communication environment,the relative relationship between two encountered vehicles are designed. Then vehicle conflict detection and resolution algorithms under two conflict scenarios are put forward to represent the conflict-free movements of vehicles with adjusting vehicle velocity at crossing. Finally,simulation studies are carried out and the results prove that the proposed algorithms are effective for vehicle conflict resolution at blind crossing.展开更多
Knowledge graph(KG)conflict resolution is to solve knowledge conflicts problem in the construction of KG.Aiming at the problem of KG conflict resolution,a KG conflict resolution algorithm NGDcrm is proposed,which is a...Knowledge graph(KG)conflict resolution is to solve knowledge conflicts problem in the construction of KG.Aiming at the problem of KG conflict resolution,a KG conflict resolution algorithm NGDcrm is proposed,which is a numeric graph dependency-based conflict resolution method.NGDcrm utilizes the dependency graph to perform arithmetic calculation and predicate comparison of numerical entity knowledge in the KG.NGDcrm first uses a parallel segmentation method to segment the KG;then,it extracts the features of the KG according to KG embedding;finally,it uses numerical graph dependencies to detect and correct the wrong facts in the KG based on the extracted features.The experimental results on real data show that NGDcrm is better than the state-of-the-art knowledge conflict resolution method.Among them,the AUC value of NGDcrm on the DBpedia dataset is 15.4%higher than the state-of-the-art method.展开更多
Collaborative design is a new style for modern mechanical design to meet the requirement of increasing competition. Designers of different places complete the same work, but the conflict appears in the process of desi...Collaborative design is a new style for modern mechanical design to meet the requirement of increasing competition. Designers of different places complete the same work, but the conflict appears in the process of design which may interface the design. Case-based reasoning (CBR) method is applied to the problem of conflict resolution, which is in the artificial intelligence field. However, due to the uncertainties in knowledge representation, attribute description, and similarity measures of CBR, it is very difficult to find the similar cases from case database. A fuzzy CBR method was proposed to solve the problem of conflict resolution in collaborative design. The process of fuzzy CBR was introduced. Based on the feature attributes and their relative weights determined by a fuzzy technique, a fuzzy CBR retrieving mechanism was developed to retrieve conflict resolution cases that tend to enhance the functions of the database. By indexing, calculating the weight and defuzzicating of the cases, the case similarity can be obtained. Then the case consistency was measured to keep the right result. Finally, the fuzzy CBR method for conflict resolution was demonstrated by means of a case study. The prototype system based on web is developed to illustrate the methodology.展开更多
A conflict is an event in which two or more aircraft experience a loss of minimum separation. In this paper, we formulate the problem of solving conflicts arising among several aircraft moving in a shared airspace as ...A conflict is an event in which two or more aircraft experience a loss of minimum separation. In this paper, we formulate the problem of solving conflicts arising among several aircraft moving in a shared airspace as a Constraint Satisfaction Problem (CSP). The constraint satisfaction problem being NP-complete, the algorithms developed to solve it have been of two types: non-systematic and systematic search methods. In this paper, we have considered a breakout algorithm as an example of non-systematic search methods and a backtracking procedure that maintains Arc Consistency (MAC) as an example of systematic search methods. The performance of these algorithms was compared experimentally and the Breakout algorithm is shown to be clearly superior.展开更多
To the issues of low efficiency of conflict resolution method in collaborative design, we proposed a method, which is conflict resolution about collaborative design based on grid ser-vices. It uses the grid services f...To the issues of low efficiency of conflict resolution method in collaborative design, we proposed a method, which is conflict resolution about collaborative design based on grid ser-vices. It uses the grid services from the current design points, uses the method of retrospective thinking to find the conflict point by detecting, and then uses the corresponding method to resolve the conflict point according to the conflict characteristic, after that carried on the conflict detection again. If there is still the conflict, resolve the conflict point again, until the conflict no longer exists. This method combines various traditional resolution methods, makes full use of the grid idle high-performance large-scale shar-ing resources. With this method the collaborative design conflict resolution cost reduced and the conflict resolution efficiency was raised. And then the problem which is not handled completely was then solved, so that the conflict resolution quality was guaranteed.展开更多
Conflicts among different fisher groups are a global concern, and the Okavango Delta fishery is no exception, which is composed of commercial, subsistence and recreational fishers. Possibly due to conflicting value/us...Conflicts among different fisher groups are a global concern, and the Okavango Delta fishery is no exception, which is composed of commercial, subsistence and recreational fishers. Possibly due to conflicting value/use systems, and ill-defined user rights, there have been documented cases of conflict between commercial and recreational fishers, which may affect livelihoods for local fishers. Therefore, this study’s aim was to identify causes of conflict between these groups and to propose management inventions. Primary data collected in three fishing villages showed that lack of access, misconceptions about each other, and overlapping use were identified as some of the major causes of conflict. Subsequently, this paper proposes a spatial and temporal zoning of fishing grounds as a management tool towards conflict resolution. One proposal is that recreational fishers can utilize the main channel, commercial fishers the floodplains and lagoons, while basket fishers can utilize the fringes of floodplains, lagoons and river channel. Moreover, a co-management regime has also been developed in the fishery, upon which a code of conduct was developed to also reduce conflict in the fishery. It is envisaged that this approach will reduce conflict and create an enabling environment for efficient and sustainable fish utilization in the Delta.展开更多
The multi-UAV adversary swarm defense(MUASD)problem is to defend a static base against an adversary UAV swarm by a defensive UAV swarm.Decomposing the problem into task assignment and low-level interception strategies...The multi-UAV adversary swarm defense(MUASD)problem is to defend a static base against an adversary UAV swarm by a defensive UAV swarm.Decomposing the problem into task assignment and low-level interception strategies is a widely used approach.Learning-based approaches for task assignment are a promising direction.Existing studies on learning-based methods generally assume decentralized decision-making architecture,which is not beneficial for conflict resolution.In contrast,centralized decision-making architecture is beneficial for conflict resolution while it is often detrimental to scalability.To achieve scalability and conflict resolution simultaneously,inspired by a self-attention-based task assignment method for sensor target coverage problem,a scalable centralized assignment method based on self-attention mechanism together with a defender-attacker pairwise observation preprocessing(DAP-SelfAtt)is proposed.Then,an imperative-priori conflict resolution(IPCR)mechanism is proposed to achieve conflict-free assignment.Further,the IPCR mechanism is parallelized to enable efficient training.To validate the algorithm,a variant of proximal policy optimization algorithm(PPO)is employed for training in scenarios of various scales.The experimental results show that the proposed algorithm not only achieves conflict-free task assignment but also maintains scalability,and significantly improve the success rate of defense.展开更多
The research examined the role of media in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo.The security situation in the Democratic Republic of the Congo(DRC),particularly in the eas...The research examined the role of media in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo.The security situation in the Democratic Republic of the Congo(DRC),particularly in the eastern region of North Kivu,has been deteriorating.The study was anchored in social identity theory.The research methodology employed for this study was qualitative,focusing on the analysis of Mr.Edgar Mateso’s contributions to Radio Okapi’s“Dialogue entre Congolais”program during the period from 2019 to 2023.The research was conducted within the broader context of the persistent war and conflict in the Democratic Republic of Congo,providing valuable insights into the dynamics and challenges of addressing the ongoing insecurity and violence in the region.The study found that media,exemplified by Radio Okapi,plays a multifaceted and significant role in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo(DRC).It serves as a critical source of accurate information,enabling informed decision-making regarding ceasefire agreements,peace talks,and humanitarian aid.Media fosters dialogue and understanding among different stakeholders,contributing to reconciliation efforts.Additionally,it raises awareness about the human cost of the conflict,challenges misinformation,monitors peace agreements,amplifies the concerns of the affected population,and promotes human rights and justice.Media also engages youth,serves as an early warning system,and attracts global attention to the conflict.It is recommended that media organizations in North Kivu continue their efforts to facilitate dialogue and understanding among different stakeholder groups.Additionally,media should maintain its focus on raising awareness about the human cost of the conflict,ensuring that the suffering of civilians remains in the spotlight and generates international empathy and support.Media outlets should also continue their role as watchdogs by closely monitoring the implementation of ceasefire agreements and reporting any violations transparently.To strengthen media’s role in promoting peace,there should be continued advocacy for peace through dedicated radio programs,news reports,and editorial content.Internationally,media should continue to provide comprehensive coverage of the conflict in North Kivu,attracting global attention and shaping the perception of the conflict on the global stage.Lastly,media organizations should preserve a lasting legacy of peace by archiving peace-related content,documentaries,and narratives of reconciliation.展开更多
DCR-OL is a Distributed Collaborative Reasoning multi-agent model with an Online Learning thataims to identify human activities in smart homes from distributed, heterogeneous and dynamicsensor data. In this model, dis...DCR-OL is a Distributed Collaborative Reasoning multi-agent model with an Online Learning thataims to identify human activities in smart homes from distributed, heterogeneous and dynamicsensor data. In this model, distributed learning agents with diverse classifiers, detect sensorstream data, make local predictions, communicate and collaborate to identify current activities.Then, they learn from their collaborations to improve their own performance in activity recognition.Conflict resolution strategies are applied to generate one final predicted activity when thelocal predicted activity of an agent is different from received predicted activities of other agents.In this paper, two conflict resolution strategies using online learning, w-max-trust and w-maxfreq,are proposed. We experimentally test these strategies by performing an evaluation studyon the Aruba dataset. The obtained results indicate an enhancement in terms of accuracy and Fmeasuremetrics compared to the offline strategies max-trust and max-freq and also to the onlineexisting one max-wPerf .展开更多
Unmanned aerial vehicles(UAVs)have gained much attention from academic and industrial areas due to the significant number of potential applications in urban airspace.A traffic management system for these UAVs is neede...Unmanned aerial vehicles(UAVs)have gained much attention from academic and industrial areas due to the significant number of potential applications in urban airspace.A traffic management system for these UAVs is needed to manage this future traffic.Tactical conflict resolution for unmanned aerial systems(UASs)is an essential piece of the puzzle for the future UAS Traffic Management(UTM),especially in very low-level(VLL)urban airspace.Unlike conflict resolution in higher altitude airspace,the dense high-rise buildings are an essential source of potential conflict to be considered in VLL urban airspace.In this paper,we propose an attention-based deep reinforcement learning approach to solve the tactical conflict resolution problem.Specifically,we formulate this task as a sequential decision-making problem using Markov Decision Process(MDP).The double deep Q network(DDQN)framework is used as a learning framework for the host drone to learn to output conflict-free maneuvers at each time step.We use the attention mechanism to model the individual neighbor's effect on the host drone,endowing the learned conflict resolution policy to be adapted to an arbitrary number of neighboring drones.Lastly,we build a simulation environment with various scenarios covering different types of encounters to evaluate the proposed approach.The simulation results demonstrate that our proposed algorithm provides a reliable solution to minimize secondary conflict counts compared to learning and non-learning-based approaches under different traffic density scenarios.展开更多
Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values...Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.展开更多
We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement ti...We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution measurement.Mimicking the characteristics of the human retina system,the resolution distribution follows the principle of gradually decreasing.The system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a user.The system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements.展开更多
Human pose estimation aims to localize the body joints from image or video data.With the development of deeplearning,pose estimation has become a hot research topic in the field of computer vision.In recent years,huma...Human pose estimation aims to localize the body joints from image or video data.With the development of deeplearning,pose estimation has become a hot research topic in the field of computer vision.In recent years,humanpose estimation has achieved great success in multiple fields such as animation and sports.However,to obtainaccurate positioning results,existing methods may suffer from large model sizes,a high number of parameters,and increased complexity,leading to high computing costs.In this paper,we propose a new lightweight featureencoder to construct a high-resolution network that reduces the number of parameters and lowers the computingcost.We also introduced a semantic enhancement module that improves global feature extraction and networkperformance by combining channel and spatial dimensions.Furthermore,we propose a dense connected spatialpyramid pooling module to compensate for the decrease in image resolution and information loss in the network.Finally,ourmethod effectively reduces the number of parameters and complexitywhile ensuring high performance.Extensive experiments show that our method achieves a competitive performance while dramatically reducing thenumber of parameters,and operational complexity.Specifically,our method can obtain 89.9%AP score on MPIIVAL,while the number of parameters and the complexity of operations were reduced by 41%and 36%,respectively.展开更多
The history of mankind contains so many illustrations of well-classified and violent struggles against various animals over crop production in agricultural fields, attacks on human life or competition in order to have...The history of mankind contains so many illustrations of well-classified and violent struggles against various animals over crop production in agricultural fields, attacks on human life or competition in order to have access to certain natural resources. The aim of this study is to characterise the human-wildlife conflicts that occur around the KBNP, especially with regard to primates. Surveys were carried out in 260 households selected using the snowball method. The results showed that human-wildlife conflicts around the KBNP are characterised by the destruction of crops in riparian fields by monkeys, chimpanzees and gorillas, the destruction of houses, physical attacks and zoonoses. Despite the conservation and protection measures for wildlife and local populations put in place by the Park’s managers, conflicts between local populations and the Park’s wild animals are still visible. These conflicts lead to the detention of wild animals by local people roaming in the villages and to poaching on the Park’s boundaries. The weakness of the community management policy on the part of the park managers and the resentment of the indigenous peoples towards the restriction of their access to natural resources are the major constraints on the sustainable management of conflicts between the local populations and the wild animals in the KBNP. The strategies for the sustainable resolution of human-wildlife conflicts around the KBNP must be geared towards and integrated into a community conservation approach.展开更多
As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path pla...As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.展开更多
“Human-elephant conflict(HEC)”,the alarming issue,in present day context has attracted the attention of environmentalists and policy makers.The rising conflict between human beings and wild elephants is common in Bu...“Human-elephant conflict(HEC)”,the alarming issue,in present day context has attracted the attention of environmentalists and policy makers.The rising conflict between human beings and wild elephants is common in Buxa Tiger Reserve(BTR)and its adjoining area in West Bengal State,India,making the area volatile.People’s attitudes towards elephant conservation activity are very crucial to get rid of HEC,because people’s proximity with wild elephants’habitat can trigger the occurrence of HEC.The aim of this study is to conduct an in-depth investigation about the association of people’s attitudes towards HEC with their locational,demographic,and socio-economic characteristics in BTR and its adjoining area by using Pearson’s bivariate chi-square test and binary logistic regression analysis.BTR is one of the constituent parts of Eastern Doors Elephant Reserve(EDER).We interviewed 500 respondents to understand their perceptions to HEC and investigated their locational,demographic,and socio-economic characteristics including location of village,gender,age,ethnicity,religion,caste,poverty level,education level,primary occupation,secondary occupation,household type,and source of firewood.The results indicate that respondents who are living in enclave forest villages(EFVs),peripheral forest villages(PFVs),corridor village(CVs),or forest and corridor villages(FCVs),mainly males,at the age of 18–48 years old,engaged with agriculture occupation,and living in kancha and mixed houses,have more likelihood to witness HEC.Besides,respondents who are illiterate or at primary education level are more likely to regard elephant as a main problematic animal around their villages and refuse to participate in elephant conservation activity.For the sake of a sustainable environment for both human beings and wildlife,people’s attitudes towards elephants must be friendly in a more prudent way,so that the two communities can live in harmony.展开更多
Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrat...Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrates high spatial resolution remote sensing imagery with deep learning techniques,proposing a novel method for identifying rooftops of traditional Chinese village buildings using high-definition remote sensing images.Using 0.54 m spatial resolution imagery of traditional village areas as the data source,this method analyzes the geometric and spectral image characteristics of village building rooftops.It constructs a deep learning feature sample library tailored to the target types.Employing a semantically enhanced version of the improved Mask R-CNN(Mask Region-based Convolutional Neural Network)for building recognition,the study conducts experiments on localized imagery from different regions.The results demonstrated that the modified Mask R-CNN effectively identifies traditional village building rooftops,achieving an of 0.7520 and an of 0.7400.It improves the current problem of misidentification and missed detection caused by feature heterogeneity.This method offers a viable and effective approach for industrialized data monitoring of traditional villages,contributing to their sustainable development.展开更多
基金Supported by the National High Technology Research and Development Program of China("863"Program) (2011AA1104032011AA110402)
文摘A vehicle conflict detection and resolution method is proposed based on the concept of vehicle infrastructure integration ( Ⅶ) system to prevent vehicle accident beforehand at blind crossing. After analyzing traffic conflict characteristics and vehicle collision scenarios at intersection,a vehicle dynamics model and an intervehicle communication method are discussed. In the inter-vehicle communication environment,the relative relationship between two encountered vehicles are designed. Then vehicle conflict detection and resolution algorithms under two conflict scenarios are put forward to represent the conflict-free movements of vehicles with adjusting vehicle velocity at crossing. Finally,simulation studies are carried out and the results prove that the proposed algorithms are effective for vehicle conflict resolution at blind crossing.
基金Supported by the Henan Province Science and Technology Department Foundation(No.202102310237,192102210133,202102310295)the Doctoral Research Fund of Zhengzhou University of Light Industry(No.2018BSJJ039)the Internet Medical and Health Service Henan Collaborative Innovation Center Open Project Fund(No.IH2019006).
文摘Knowledge graph(KG)conflict resolution is to solve knowledge conflicts problem in the construction of KG.Aiming at the problem of KG conflict resolution,a KG conflict resolution algorithm NGDcrm is proposed,which is a numeric graph dependency-based conflict resolution method.NGDcrm utilizes the dependency graph to perform arithmetic calculation and predicate comparison of numerical entity knowledge in the KG.NGDcrm first uses a parallel segmentation method to segment the KG;then,it extracts the features of the KG according to KG embedding;finally,it uses numerical graph dependencies to detect and correct the wrong facts in the KG based on the extracted features.The experimental results on real data show that NGDcrm is better than the state-of-the-art knowledge conflict resolution method.Among them,the AUC value of NGDcrm on the DBpedia dataset is 15.4%higher than the state-of-the-art method.
基金supported by research fund for the Doctoral program of higher education of China (No.200601013)
文摘Collaborative design is a new style for modern mechanical design to meet the requirement of increasing competition. Designers of different places complete the same work, but the conflict appears in the process of design which may interface the design. Case-based reasoning (CBR) method is applied to the problem of conflict resolution, which is in the artificial intelligence field. However, due to the uncertainties in knowledge representation, attribute description, and similarity measures of CBR, it is very difficult to find the similar cases from case database. A fuzzy CBR method was proposed to solve the problem of conflict resolution in collaborative design. The process of fuzzy CBR was introduced. Based on the feature attributes and their relative weights determined by a fuzzy technique, a fuzzy CBR retrieving mechanism was developed to retrieve conflict resolution cases that tend to enhance the functions of the database. By indexing, calculating the weight and defuzzicating of the cases, the case similarity can be obtained. Then the case consistency was measured to keep the right result. Finally, the fuzzy CBR method for conflict resolution was demonstrated by means of a case study. The prototype system based on web is developed to illustrate the methodology.
文摘A conflict is an event in which two or more aircraft experience a loss of minimum separation. In this paper, we formulate the problem of solving conflicts arising among several aircraft moving in a shared airspace as a Constraint Satisfaction Problem (CSP). The constraint satisfaction problem being NP-complete, the algorithms developed to solve it have been of two types: non-systematic and systematic search methods. In this paper, we have considered a breakout algorithm as an example of non-systematic search methods and a backtracking procedure that maintains Arc Consistency (MAC) as an example of systematic search methods. The performance of these algorithms was compared experimentally and the Breakout algorithm is shown to be clearly superior.
基金the National High Technology Research and Development Program of China (863 Program) (2002AA414060, 2001AA411310)the Key Science and Technology Program of Shaanxi Province (2006K05- G10)
文摘To the issues of low efficiency of conflict resolution method in collaborative design, we proposed a method, which is conflict resolution about collaborative design based on grid ser-vices. It uses the grid services from the current design points, uses the method of retrospective thinking to find the conflict point by detecting, and then uses the corresponding method to resolve the conflict point according to the conflict characteristic, after that carried on the conflict detection again. If there is still the conflict, resolve the conflict point again, until the conflict no longer exists. This method combines various traditional resolution methods, makes full use of the grid idle high-performance large-scale shar-ing resources. With this method the collaborative design conflict resolution cost reduced and the conflict resolution efficiency was raised. And then the problem which is not handled completely was then solved, so that the conflict resolution quality was guaranteed.
文摘Conflicts among different fisher groups are a global concern, and the Okavango Delta fishery is no exception, which is composed of commercial, subsistence and recreational fishers. Possibly due to conflicting value/use systems, and ill-defined user rights, there have been documented cases of conflict between commercial and recreational fishers, which may affect livelihoods for local fishers. Therefore, this study’s aim was to identify causes of conflict between these groups and to propose management inventions. Primary data collected in three fishing villages showed that lack of access, misconceptions about each other, and overlapping use were identified as some of the major causes of conflict. Subsequently, this paper proposes a spatial and temporal zoning of fishing grounds as a management tool towards conflict resolution. One proposal is that recreational fishers can utilize the main channel, commercial fishers the floodplains and lagoons, while basket fishers can utilize the fringes of floodplains, lagoons and river channel. Moreover, a co-management regime has also been developed in the fishery, upon which a code of conduct was developed to also reduce conflict in the fishery. It is envisaged that this approach will reduce conflict and create an enabling environment for efficient and sustainable fish utilization in the Delta.
基金supported in part by the National Natural Science Foundation of China Basic Science Research Center Program under Grant No.62088101the National Natural Science Foundation of China under Grant Nos.7217117 and 92367101+2 种基金the Aeronautical Science Foundation of China under Grant No.2023Z066038001Shanghai Municipal Science and Technology Major Project under Grant No.2021SHZDZX0100Chinese Academy of Engineering,Strategic Research and Consulting Program under Grant No.2023-XZ-65.
文摘The multi-UAV adversary swarm defense(MUASD)problem is to defend a static base against an adversary UAV swarm by a defensive UAV swarm.Decomposing the problem into task assignment and low-level interception strategies is a widely used approach.Learning-based approaches for task assignment are a promising direction.Existing studies on learning-based methods generally assume decentralized decision-making architecture,which is not beneficial for conflict resolution.In contrast,centralized decision-making architecture is beneficial for conflict resolution while it is often detrimental to scalability.To achieve scalability and conflict resolution simultaneously,inspired by a self-attention-based task assignment method for sensor target coverage problem,a scalable centralized assignment method based on self-attention mechanism together with a defender-attacker pairwise observation preprocessing(DAP-SelfAtt)is proposed.Then,an imperative-priori conflict resolution(IPCR)mechanism is proposed to achieve conflict-free assignment.Further,the IPCR mechanism is parallelized to enable efficient training.To validate the algorithm,a variant of proximal policy optimization algorithm(PPO)is employed for training in scenarios of various scales.The experimental results show that the proposed algorithm not only achieves conflict-free task assignment but also maintains scalability,and significantly improve the success rate of defense.
文摘The research examined the role of media in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo.The security situation in the Democratic Republic of the Congo(DRC),particularly in the eastern region of North Kivu,has been deteriorating.The study was anchored in social identity theory.The research methodology employed for this study was qualitative,focusing on the analysis of Mr.Edgar Mateso’s contributions to Radio Okapi’s“Dialogue entre Congolais”program during the period from 2019 to 2023.The research was conducted within the broader context of the persistent war and conflict in the Democratic Republic of Congo,providing valuable insights into the dynamics and challenges of addressing the ongoing insecurity and violence in the region.The study found that media,exemplified by Radio Okapi,plays a multifaceted and significant role in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo(DRC).It serves as a critical source of accurate information,enabling informed decision-making regarding ceasefire agreements,peace talks,and humanitarian aid.Media fosters dialogue and understanding among different stakeholders,contributing to reconciliation efforts.Additionally,it raises awareness about the human cost of the conflict,challenges misinformation,monitors peace agreements,amplifies the concerns of the affected population,and promotes human rights and justice.Media also engages youth,serves as an early warning system,and attracts global attention to the conflict.It is recommended that media organizations in North Kivu continue their efforts to facilitate dialogue and understanding among different stakeholder groups.Additionally,media should maintain its focus on raising awareness about the human cost of the conflict,ensuring that the suffering of civilians remains in the spotlight and generates international empathy and support.Media outlets should also continue their role as watchdogs by closely monitoring the implementation of ceasefire agreements and reporting any violations transparently.To strengthen media’s role in promoting peace,there should be continued advocacy for peace through dedicated radio programs,news reports,and editorial content.Internationally,media should continue to provide comprehensive coverage of the conflict in North Kivu,attracting global attention and shaping the perception of the conflict on the global stage.Lastly,media organizations should preserve a lasting legacy of peace by archiving peace-related content,documentaries,and narratives of reconciliation.
文摘DCR-OL is a Distributed Collaborative Reasoning multi-agent model with an Online Learning thataims to identify human activities in smart homes from distributed, heterogeneous and dynamicsensor data. In this model, distributed learning agents with diverse classifiers, detect sensorstream data, make local predictions, communicate and collaborate to identify current activities.Then, they learn from their collaborations to improve their own performance in activity recognition.Conflict resolution strategies are applied to generate one final predicted activity when thelocal predicted activity of an agent is different from received predicted activities of other agents.In this paper, two conflict resolution strategies using online learning, w-max-trust and w-maxfreq,are proposed. We experimentally test these strategies by performing an evaluation studyon the Aruba dataset. The obtained results indicate an enhancement in terms of accuracy and Fmeasuremetrics compared to the offline strategies max-trust and max-freq and also to the onlineexisting one max-wPerf .
基金supported by the National Research Foundation(NRF),Singapore,and the Civil Aviation Authority of Singapore(CAAS),under the Aviation Transformation Programme(ATP).
文摘Unmanned aerial vehicles(UAVs)have gained much attention from academic and industrial areas due to the significant number of potential applications in urban airspace.A traffic management system for these UAVs is needed to manage this future traffic.Tactical conflict resolution for unmanned aerial systems(UASs)is an essential piece of the puzzle for the future UAS Traffic Management(UTM),especially in very low-level(VLL)urban airspace.Unlike conflict resolution in higher altitude airspace,the dense high-rise buildings are an essential source of potential conflict to be considered in VLL urban airspace.In this paper,we propose an attention-based deep reinforcement learning approach to solve the tactical conflict resolution problem.Specifically,we formulate this task as a sequential decision-making problem using Markov Decision Process(MDP).The double deep Q network(DDQN)framework is used as a learning framework for the host drone to learn to output conflict-free maneuvers at each time step.We use the attention mechanism to model the individual neighbor's effect on the host drone,endowing the learned conflict resolution policy to be adapted to an arbitrary number of neighboring drones.Lastly,we build a simulation environment with various scenarios covering different types of encounters to evaluate the proposed approach.The simulation results demonstrate that our proposed algorithm provides a reliable solution to minimize secondary conflict counts compared to learning and non-learning-based approaches under different traffic density scenarios.
基金This work was funded by the National Natural Science Foundation of China Nos.U22A2099,61966009,62006057the Graduate Innovation Program No.YCSW2022286.
文摘Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.
基金Project supported by the Natural Science Foundation of Shandong Province,China(Grant Nos.ZR2020MF119 and ZR2020MA082)the National Natural Science Foundation of China(Grant No.62002208)the National Key Research and Development Program of China(Grant No.2018YFB0504302).
文摘We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution measurement.Mimicking the characteristics of the human retina system,the resolution distribution follows the principle of gradually decreasing.The system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a user.The system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements.
基金the National Natural Science Foundation of China(Grant Number 62076246).
文摘Human pose estimation aims to localize the body joints from image or video data.With the development of deeplearning,pose estimation has become a hot research topic in the field of computer vision.In recent years,humanpose estimation has achieved great success in multiple fields such as animation and sports.However,to obtainaccurate positioning results,existing methods may suffer from large model sizes,a high number of parameters,and increased complexity,leading to high computing costs.In this paper,we propose a new lightweight featureencoder to construct a high-resolution network that reduces the number of parameters and lowers the computingcost.We also introduced a semantic enhancement module that improves global feature extraction and networkperformance by combining channel and spatial dimensions.Furthermore,we propose a dense connected spatialpyramid pooling module to compensate for the decrease in image resolution and information loss in the network.Finally,ourmethod effectively reduces the number of parameters and complexitywhile ensuring high performance.Extensive experiments show that our method achieves a competitive performance while dramatically reducing thenumber of parameters,and operational complexity.Specifically,our method can obtain 89.9%AP score on MPIIVAL,while the number of parameters and the complexity of operations were reduced by 41%and 36%,respectively.
文摘The history of mankind contains so many illustrations of well-classified and violent struggles against various animals over crop production in agricultural fields, attacks on human life or competition in order to have access to certain natural resources. The aim of this study is to characterise the human-wildlife conflicts that occur around the KBNP, especially with regard to primates. Surveys were carried out in 260 households selected using the snowball method. The results showed that human-wildlife conflicts around the KBNP are characterised by the destruction of crops in riparian fields by monkeys, chimpanzees and gorillas, the destruction of houses, physical attacks and zoonoses. Despite the conservation and protection measures for wildlife and local populations put in place by the Park’s managers, conflicts between local populations and the Park’s wild animals are still visible. These conflicts lead to the detention of wild animals by local people roaming in the villages and to poaching on the Park’s boundaries. The weakness of the community management policy on the part of the park managers and the resentment of the indigenous peoples towards the restriction of their access to natural resources are the major constraints on the sustainable management of conflicts between the local populations and the wild animals in the KBNP. The strategies for the sustainable resolution of human-wildlife conflicts around the KBNP must be geared towards and integrated into a community conservation approach.
基金supported by National Natural Science Foundation of China(No.62073212)Shanghai Science and Technology Commission(No.23ZR1426600).
文摘As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.
文摘“Human-elephant conflict(HEC)”,the alarming issue,in present day context has attracted the attention of environmentalists and policy makers.The rising conflict between human beings and wild elephants is common in Buxa Tiger Reserve(BTR)and its adjoining area in West Bengal State,India,making the area volatile.People’s attitudes towards elephant conservation activity are very crucial to get rid of HEC,because people’s proximity with wild elephants’habitat can trigger the occurrence of HEC.The aim of this study is to conduct an in-depth investigation about the association of people’s attitudes towards HEC with their locational,demographic,and socio-economic characteristics in BTR and its adjoining area by using Pearson’s bivariate chi-square test and binary logistic regression analysis.BTR is one of the constituent parts of Eastern Doors Elephant Reserve(EDER).We interviewed 500 respondents to understand their perceptions to HEC and investigated their locational,demographic,and socio-economic characteristics including location of village,gender,age,ethnicity,religion,caste,poverty level,education level,primary occupation,secondary occupation,household type,and source of firewood.The results indicate that respondents who are living in enclave forest villages(EFVs),peripheral forest villages(PFVs),corridor village(CVs),or forest and corridor villages(FCVs),mainly males,at the age of 18–48 years old,engaged with agriculture occupation,and living in kancha and mixed houses,have more likelihood to witness HEC.Besides,respondents who are illiterate or at primary education level are more likely to regard elephant as a main problematic animal around their villages and refuse to participate in elephant conservation activity.For the sake of a sustainable environment for both human beings and wildlife,people’s attitudes towards elephants must be friendly in a more prudent way,so that the two communities can live in harmony.
文摘Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrates high spatial resolution remote sensing imagery with deep learning techniques,proposing a novel method for identifying rooftops of traditional Chinese village buildings using high-definition remote sensing images.Using 0.54 m spatial resolution imagery of traditional village areas as the data source,this method analyzes the geometric and spectral image characteristics of village building rooftops.It constructs a deep learning feature sample library tailored to the target types.Employing a semantically enhanced version of the improved Mask R-CNN(Mask Region-based Convolutional Neural Network)for building recognition,the study conducts experiments on localized imagery from different regions.The results demonstrated that the modified Mask R-CNN effectively identifies traditional village building rooftops,achieving an of 0.7520 and an of 0.7400.It improves the current problem of misidentification and missed detection caused by feature heterogeneity.This method offers a viable and effective approach for industrialized data monitoring of traditional villages,contributing to their sustainable development.
