With the rapid development of artificial intelligence technology,AIGC(Artificial Intelligence-Generated Content)has triggered profound changes in the field of high-level language programming courses.This paper deeply ...With the rapid development of artificial intelligence technology,AIGC(Artificial Intelligence-Generated Content)has triggered profound changes in the field of high-level language programming courses.This paper deeply explored the application principles,advantages,and limitations of AIGC in intelligent code generation,analyzed the new mode of human-computer collaboration in high-level language programming courses driven by AIGC,discussed the impact of human-computer collaboration on programming efficiency and code quality through practical case studies,and looks forward to future development trends.This research aims to provide theoretical and practical guidance for high-level language programming courses and promote innovative development of high-level language programming courses under the human-computer collaboration paradigm.展开更多
In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operati...In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.展开更多
Voice, motion, and mimicry are naturalistic control modalities that have replaced text or display-driven control in human-computer communication (HCC). Specifically, the vocals contain a lot of knowledge, revealing de...Voice, motion, and mimicry are naturalistic control modalities that have replaced text or display-driven control in human-computer communication (HCC). Specifically, the vocals contain a lot of knowledge, revealing details about the speaker’s goals and desires, as well as their internal condition. Certain vocal characteristics reveal the speaker’s mood, intention, and motivation, while word study assists the speaker’s demand to be understood. Voice emotion recognition has become an essential component of modern HCC networks. Integrating findings from the various disciplines involved in identifying vocal emotions is also challenging. Many sound analysis techniques were developed in the past. Learning about the development of artificial intelligence (AI), and especially Deep Learning (DL) technology, research incorporating real data is becoming increasingly common these days. Thus, this research presents a novel selfish herd optimization-tuned long/short-term memory (SHO-LSTM) strategy to identify vocal emotions in human communication. The RAVDESS public dataset is used to train the suggested SHO-LSTM technique. Mel-frequency cepstral coefficient (MFCC) and wiener filter (WF) techniques are used, respectively, to remove noise and extract features from the data. LSTM and SHO are applied to the extracted data to optimize the LSTM network’s parameters for effective emotion recognition. Python Software was used to execute our proposed framework. In the finding assessment phase, Numerous metrics are used to evaluate the proposed model’s detection capability, Such as F1-score (95%), precision (95%), recall (96%), and accuracy (97%). The suggested approach is tested on a Python platform, and the SHO-LSTM’s outcomes are contrasted with those of other previously conducted research. Based on comparative assessments, our suggested approach outperforms the current approaches in vocal emotion recognition.展开更多
With the breakthrough of AlphaGo,human-computer gaming AI has ushered in a big explosion,attracting more and more researchers all over the world.As a recognized standard for testing artificial intelligence,various hum...With the breakthrough of AlphaGo,human-computer gaming AI has ushered in a big explosion,attracting more and more researchers all over the world.As a recognized standard for testing artificial intelligence,various human-computer gaming AI systems(AIs)have been developed,such as Libratus,OpenAI Five,and AlphaStar,which beat professional human players.The rapid development of human-computer gaming AIs indicates a big step for decision-making intelligence,and it seems that current techniques can handle very complex human-computer games.So,one natural question arises:What are the possible challenges of current techniques in human-computer gaming and what are the future trends?To answer the above question,in this paper,we survey recent successful game AIs,covering board game AIs,card game AIs,first-person shooting game AIs,and real-time strategy game AIs.Through this survey,we 1)compare the main difficulties among different kinds of games and the corresponding techniques utilized for achieving professional human-level AIs;2)summarize the mainstream frameworks and techniques that can be properly relied on for developing AIs for complex human-computer games;3)raise the challenges or drawbacks of current techniques in the successful AIs;and 4)try to point out future trends in human-computer gaming AIs.Finally,we hope that this brief review can provide an introduction for beginners and inspire insight for researchers in the field of AI in human-computer gaming.展开更多
To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA...To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.展开更多
The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remai...The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Xizang Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.展开更多
When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game ...When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.展开更多
Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate...Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate this impulse game problem with the modified objective function including interaction costs among the players in a discontinuous fashion,and subsequently,to derive a verification theorem for identifying the feedback Nash equilibrium strategy.展开更多
The article studies the evolutionary dynamics of two-population two-strategy game models with and without impulses. First, the payment matrix is given and two evolutionary dynamics models are established by adding sto...The article studies the evolutionary dynamics of two-population two-strategy game models with and without impulses. First, the payment matrix is given and two evolutionary dynamics models are established by adding stochastic and impulse. For the stochastic model without impulses, the existence and uniqueness of solution, and the existence of positive periodic solutions are proved, and a sufficient condition for strategy extinction is given. For the stochastic model with impulses, the existence of positive periodic solutions is proved. Numerical results show that noise and impulses directly affect the model, but the periodicity of the model does not change.展开更多
The Stackelberg prediction game(SPG)is a bilevel optimization frame-work for modeling strategic interactions between a learner and a follower.Existing meth-ods for solving this problem with general loss functions are ...The Stackelberg prediction game(SPG)is a bilevel optimization frame-work for modeling strategic interactions between a learner and a follower.Existing meth-ods for solving this problem with general loss functions are computationally expensive and scarce.We propose a novel hyper-gradient type method with a warm-start strategy to address this challenge.Particularly,we first use a Taylor expansion-based approach to obtain a good initial point.Then we apply a hyper-gradient descent method with an ex-plicit approximate hyper-gradient.We establish the convergence results of our algorithm theoretically.Furthermore,when the follower employs the least squares loss function,our method is shown to reach an e-stationary point by solving quadratic subproblems.Numerical experiments show our algorithms are empirically orders of magnitude faster than the state-of-the-art.展开更多
Background Autism spectrum disorder(ASD)is a pervasive developmental disorder characterized by difficulties in social communication and restricted,repetitive behaviors.Early intervention is essential to improve develo...Background Autism spectrum disorder(ASD)is a pervasive developmental disorder characterized by difficulties in social communication and restricted,repetitive behaviors.Early intervention is essential to improve developmental outcomes in children with ASD.Serious games,which combine educational objectives with game based interactions,have shown potential as tools for early intervention in patients with ASD.However,in China,the development of serious games specifically designed for children with ASD remains in its infancy,with significant gaps in technical frameworks and effective data management methods.Method This paper proposes a framework aimed at facilitating the development of multimodal serious games designed for ASD interventions.We demonstrated the feasibility of the framework by developing and integrating several components,such as web applications,mobile games,and augmented reality games.These tools are interconnected to achieve data connectivity and management.Additionally,adaptive mechanics were employed within the framework to analyze real-time player data,which allowed the game difficulty to be dynamically adjusted and provide a personalized experience for each child.Results The framework successfully integrated various multimodal games,ensuring that real-time data management supported personalized game experiences.This approach ensured that the interventions remained appropriately challenging while still achievable.Conclusion The results indicate that the proposed framework enhances collaboration among therapists,parents,and developers while also improving the effectiveness of ASD interventions.By delivering personalized gameplay experiences that are both challenging and achievable,the framework offers a scalable platform for the future development of serious games.展开更多
In this paper,we investigate analytical numerical iterative strategies for the pursuit-evasion game involving spacecraft with leader–follower information.In the proposed problem,the interplay between two spacecraft g...In this paper,we investigate analytical numerical iterative strategies for the pursuit-evasion game involving spacecraft with leader–follower information.In the proposed problem,the interplay between two spacecraft gives rise to a dynamic and real-time game,complicated further by the presence of perturbation.The primary challenge lies in crafting control strategies that are both efficient and applicable to real-time game problems within a nonlinear system.To overcome this challenge,we introduce the model prediction and iterative correction technique proposed in model predictive static programming,enabling the generation of strategies in analytical iterative form for nonlinear systems.Subsequently,we proceed by integrating this model predictive framework into a simplified Stackelberg equilibrium formulation,tailored to address the practical complexities of leader–follower pursuit-evasion scenarios.Simulation results validate the effectiveness and exceptional efficiency of the proposed solution within a receding horizon framework.展开更多
This paper presents a mode-switching collaborative defense strategy for spacecraft pursuit-evasiondefense scenarios.In these scenarios,the pursuer tries to avoid the defender while capturing the evader,while the evade...This paper presents a mode-switching collaborative defense strategy for spacecraft pursuit-evasiondefense scenarios.In these scenarios,the pursuer tries to avoid the defender while capturing the evader,while the evader and defender form an alliance to prevent the pursuer from achieving its goal.First,the behavioral modes of the pursuer,including attack and avoidance modes,were established using differential game theory.These modes are then recognized by an interactive multiple model-matching algorithm(IMM),that uses several smooth variable structure filters to match the modes of the pursuer and update their probabilities in real time.Based on the linear-quadratic optimization theory,combined with the results of strategy identification,a two-way cooperative optimal strategy for the defender and evader is proposed,where the evader aids the defender to intercept the pursuer by performing luring maneuvers.Simulation results show that the interactive multi-model algorithm based on several smooth variable structure filters perform well in the strategy identification of the pursuer,and the cooperative defense strategy based on strategy identification has good interception performance when facing pursuers,who are able to flexibly adjust their game objectives.展开更多
This paper proposes a novel impulsive thrust strategy guided by optimal continuous thrust strategy to address two-player orbital pursuit-evasion game under impulsive thrust control.The strategy seeks to enhance the in...This paper proposes a novel impulsive thrust strategy guided by optimal continuous thrust strategy to address two-player orbital pursuit-evasion game under impulsive thrust control.The strategy seeks to enhance the interpretability of impulsive thrust strategy by integrating it within the framework of differential game in traditional continuous systems.First,this paper introduces an impulse-like constraint,with periodical changes in thrust amplitude,to characterize the impulsive thrust control.Then,the game with the impulse-like constraint is converted into the two-point boundary value problem,which is solved by the combined shooting and deep learning method proposed in this paper.Deep learning and numerical optimization are employed to obtain the guesses for unknown terminal adjoint variables and the game terminal time.Subsequently,the accurate values are solved by the shooting method to yield the optimal continuous thrust strategy with the impulse-like constraint.Finally,the shooting method is iteratively employed at each impulse decision moment to derive the impulsive thrust strategy guided by the optimal continuous thrust strategy.Numerical examples demonstrate the convergence of the combined shooting and deep learning method,even if the strongly nonlinear impulse-like constraint is introduced.The effect of the impulsive thrust strategy guided by the optimal continuous thrust strategy is also discussed.展开更多
In recent years,the availability of space orbital resources has been declining,and the increasing frequency of spacecraft close approach events has heightened the urgency for enhanced space security measures.This pape...In recent years,the availability of space orbital resources has been declining,and the increasing frequency of spacecraft close approach events has heightened the urgency for enhanced space security measures.This paper establishes a comprehensive framework for intelligent orbital game technology in space,encompassing four core technologies:threat perception of noncooperative targets,intent recognition,situation assessment,and intelligent orbital game countermeasures.The concepts of multi-turn,multi-round and multi-match in space orbital games are defined,clarifying the core technological requirements for intelligent space orbital games and establishing a cohesive technological framework.Subsequently,the current status of research on these four core technologies is investigated.The challenges faced in the existing research are analyzed,and potential solutions for future studies are proposed.This paper aims to provide readers with a thorough understanding of the latest advancements in space intelligent orbital game technology.along with insights into the future directions and challenges in this field.展开更多
Most developing countries continue to face challenges in accessing sustainable energy.This study investigates a solar panel and battery-powered system for an urban off-grid microgrid in Nigeria,where demand-sideflexib...Most developing countries continue to face challenges in accessing sustainable energy.This study investigates a solar panel and battery-powered system for an urban off-grid microgrid in Nigeria,where demand-sideflexibility and strategic interactions between households and utilities can optimize system sizing.A nonlinear programming model is built using bilevel problem formulation that incorporates both the households’willingness to reduce their energy consumption and the utility’s agreement to provide price rebates.The results show that,for an energy community of 10 households with annual energy demand of 7.8 MWh,an oversized solar-storage system is required(12 kWp of photovoltaic solar panels and 26 kWh of battery storage).The calculated average cost of 0.31€/kWh is three times higher than the current tariff,making it unaffordable for most Nigerian households.To address this,the utility company could implement Demand Response programs with direct load control that delay the use of certain appliances,such as fans,irons and air conditioners.If these measures reduce total demand by 5%,both the required system size and overall costs could decrease significantly,by approximately one-third.This adjustment leads to a reduced tariffof 0.20€/kWh.When Demand Response is imple-mented through negotiation between the utility and households,the amount of load-shaving achieved is lower.This is because house-holds experience discomfort from curtailment and are generally less willing to provideflexibility.However,negotiation allows for greaterflexibility than direct control,due to dynamic interactions and more active consumer participation in the energy transition.Nonetheless,tariffs remain higher than current market prices.Off-grid contracts could become competitive iffinancial support is pro-vided,such as low-interest loans and capital grants covering up to 75%of the upfront cost.展开更多
Online gaming has become a daily norm,leading to unique forms of game-bullying distinct from traditional cyberbullying due to its immersive nature and ranking systems.This study examined how game-bullying victimizatio...Online gaming has become a daily norm,leading to unique forms of game-bullying distinct from traditional cyberbullying due to its immersive nature and ranking systems.This study examined how game-bullying victimization(GBV)affects depression via self-esteem,moderated by resilience and the state offlow,among 359 Chinese MOBA(Multiplayer-online-battle-arena)gamers(30.7%female,mean age=23.8 years,SD=4.57 years).The analysis revealed a direct link between GBV and depression.Self-esteem mediates this relationship,with higher GBV associated with lower self-esteem and subsequently greater depression.Resilience moderates both direct and indirect effects,mitigating GBV’s impact on self-esteem and depression in those with higher resilience.However,the state offlow did not moderate the mediation process.These results underscore that game-bullying affects more than just gaming addicts,highlighting the crucial roles of self-esteem and resilience.Thefindings suggest expanding the SOR model to account for personality traits susceptible to GBV,an emerging psychological harm.展开更多
I was so excited to be a volunteer for the 2025 Asian Winter Games.It was a wonderful chance to meet people from all over Asia.During the Games,I helped players find their way around the stadium.I also answered questi...I was so excited to be a volunteer for the 2025 Asian Winter Games.It was a wonderful chance to meet people from all over Asia.During the Games,I helped players find their way around the stadium.I also answered questions from visitors.Everyone was friendly,and I felt happy to help them.展开更多
Soccer is a very popular sport.Kids and adults play it all over the world.Kids play it in school yards and on the street.Others play it in parks and on soccer fields.Professional soccer players play it in stadiums.The...Soccer is a very popular sport.Kids and adults play it all over the world.Kids play it in school yards and on the street.Others play it in parks and on soccer fields.Professional soccer players play it in stadiums.The idea of the game is simple.Two teams play.Each team has 11 players.Players run up and down the field.They have to kick the ball into the other team's goal.Then they score a goal.The team with the most goals wins.展开更多
A park hydrogen-doped integrated energy system(PHIES)can maximize energy utilization as a system with multiple supplies.To realize win-win cooperation between the PHIES and active distribution network(ADN),the coopera...A park hydrogen-doped integrated energy system(PHIES)can maximize energy utilization as a system with multiple supplies.To realize win-win cooperation between the PHIES and active distribution network(ADN),the cooperative operation problem of multi-PHIES connected to the same ADN is studied.A low-carbon hybrid game coordination strategy for multi-PHIES accessing ADN based on dynamic carbon base price is proposed in the paper.Firstly,multi-PHIES are constructed to form a PHIES alliance,including a hydrogen-doped gas turbine(HGT),hydrogen-doped gas boiler(HGB),power to gas and carbon capture system(P2G-CCS),and other equipment.Secondly,a hybrid game system model of the ADN and PHIES alliance is constructed,in which the ADN and PHIES alliance constitute a master-slave game,and the members of the PHIES alliance constitute a cooperative game.An improved Shapley value is proposed to deal with the problem of cost share among members in the alliance.Thirdly,an improved stepped carbon trading based on dynamic carbon baseline price is proposed.Thecarbon emissions at each moment and the total carbon emissions in a cycle are set as the dynamic adjustment factors of the carbon baseline price.The pricing mechanism of carbon baseline price increases with carbon emissions is constructed so that carbon emissions decrease.Finally,the quadratic interpolation optimization(QIO)algorithm is combined with Gurobi to solve the model.The results of the example analysis show that the cost of ADN is reduced by 4.47%,the cost of PHIES 1 is reduced by 3.67%,the cost of PHIES 2 is reduced by 0.97%,and the cost of PHIES 3 is reduced by 4.91%respectively.The total carbon emissions of the PHIES alliance are reduced by 7.08%.The low-carbon and economical operation of the multi-PHIES accessing ADN is achieved.展开更多
基金Education and Teaching Research Project of Beijing University of Technology(ER2024KCB08)。
文摘With the rapid development of artificial intelligence technology,AIGC(Artificial Intelligence-Generated Content)has triggered profound changes in the field of high-level language programming courses.This paper deeply explored the application principles,advantages,and limitations of AIGC in intelligent code generation,analyzed the new mode of human-computer collaboration in high-level language programming courses driven by AIGC,discussed the impact of human-computer collaboration on programming efficiency and code quality through practical case studies,and looks forward to future development trends.This research aims to provide theoretical and practical guidance for high-level language programming courses and promote innovative development of high-level language programming courses under the human-computer collaboration paradigm.
基金the Talent Fund of Beijing Jiaotong University(Grant No.2024XKRC055).
文摘In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.
基金The author Dr.Arshiya S.Ansari extends the appreciation to the Deanship of Postgraduate Studies and Scientific Research at Majmaah University for funding this research work through the project number(R-2025-1538).
文摘Voice, motion, and mimicry are naturalistic control modalities that have replaced text or display-driven control in human-computer communication (HCC). Specifically, the vocals contain a lot of knowledge, revealing details about the speaker’s goals and desires, as well as their internal condition. Certain vocal characteristics reveal the speaker’s mood, intention, and motivation, while word study assists the speaker’s demand to be understood. Voice emotion recognition has become an essential component of modern HCC networks. Integrating findings from the various disciplines involved in identifying vocal emotions is also challenging. Many sound analysis techniques were developed in the past. Learning about the development of artificial intelligence (AI), and especially Deep Learning (DL) technology, research incorporating real data is becoming increasingly common these days. Thus, this research presents a novel selfish herd optimization-tuned long/short-term memory (SHO-LSTM) strategy to identify vocal emotions in human communication. The RAVDESS public dataset is used to train the suggested SHO-LSTM technique. Mel-frequency cepstral coefficient (MFCC) and wiener filter (WF) techniques are used, respectively, to remove noise and extract features from the data. LSTM and SHO are applied to the extracted data to optimize the LSTM network’s parameters for effective emotion recognition. Python Software was used to execute our proposed framework. In the finding assessment phase, Numerous metrics are used to evaluate the proposed model’s detection capability, Such as F1-score (95%), precision (95%), recall (96%), and accuracy (97%). The suggested approach is tested on a Python platform, and the SHO-LSTM’s outcomes are contrasted with those of other previously conducted research. Based on comparative assessments, our suggested approach outperforms the current approaches in vocal emotion recognition.
基金National Natural Science Foundation of China(No.61906197).
文摘With the breakthrough of AlphaGo,human-computer gaming AI has ushered in a big explosion,attracting more and more researchers all over the world.As a recognized standard for testing artificial intelligence,various human-computer gaming AI systems(AIs)have been developed,such as Libratus,OpenAI Five,and AlphaStar,which beat professional human players.The rapid development of human-computer gaming AIs indicates a big step for decision-making intelligence,and it seems that current techniques can handle very complex human-computer games.So,one natural question arises:What are the possible challenges of current techniques in human-computer gaming and what are the future trends?To answer the above question,in this paper,we survey recent successful game AIs,covering board game AIs,card game AIs,first-person shooting game AIs,and real-time strategy game AIs.Through this survey,we 1)compare the main difficulties among different kinds of games and the corresponding techniques utilized for achieving professional human-level AIs;2)summarize the mainstream frameworks and techniques that can be properly relied on for developing AIs for complex human-computer games;3)raise the challenges or drawbacks of current techniques in the successful AIs;and 4)try to point out future trends in human-computer gaming AIs.Finally,we hope that this brief review can provide an introduction for beginners and inspire insight for researchers in the field of AI in human-computer gaming.
基金supported by the National Key Research and Development Program of China(2021YFB1600601)the Joint Funds of the National Natural Science Foundation of China and the Civil Aviation Administration of China(U1933106)+2 种基金the Scientific Research Project of Tianjin Educational Committee(2019KJ134)the Natural Science Foundation of TianjinIntelligent Civil Aviation Program(21JCQNJ C00900)。
文摘To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.
基金supported by the National Key Research and Development Program of China(2021YFB3901205)National Institute of Natural Hazards,Ministry of Emergency Management of China(2023-JBKY-57)。
文摘The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Xizang Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.
基金National Natural Science Foundation of China(NSFC61773142,NSFC62303136)。
文摘When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.
基金supported in part by the National Natural Science Foundation of China(62173051)the Fundamental Research Funds for the Central Universities(2024CDJCGJ012,2023CDJXY-010)+1 种基金the Chongqing Technology Innovation and Application Development Special Key Project(CSTB2022TIADCUX0015,CSTB2022TIAD-KPX0162)the China Postdoctoral Science Foundation(2024M763865)
文摘Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate this impulse game problem with the modified objective function including interaction costs among the players in a discontinuous fashion,and subsequently,to derive a verification theorem for identifying the feedback Nash equilibrium strategy.
基金Supported by the National Natural Science Foundation of China(10671182)。
文摘The article studies the evolutionary dynamics of two-population two-strategy game models with and without impulses. First, the payment matrix is given and two evolutionary dynamics models are established by adding stochastic and impulse. For the stochastic model without impulses, the existence and uniqueness of solution, and the existence of positive periodic solutions are proved, and a sufficient condition for strategy extinction is given. For the stochastic model with impulses, the existence of positive periodic solutions is proved. Numerical results show that noise and impulses directly affect the model, but the periodicity of the model does not change.
文摘The Stackelberg prediction game(SPG)is a bilevel optimization frame-work for modeling strategic interactions between a learner and a follower.Existing meth-ods for solving this problem with general loss functions are computationally expensive and scarce.We propose a novel hyper-gradient type method with a warm-start strategy to address this challenge.Particularly,we first use a Taylor expansion-based approach to obtain a good initial point.Then we apply a hyper-gradient descent method with an ex-plicit approximate hyper-gradient.We establish the convergence results of our algorithm theoretically.Furthermore,when the follower employs the least squares loss function,our method is shown to reach an e-stationary point by solving quadratic subproblems.Numerical experiments show our algorithms are empirically orders of magnitude faster than the state-of-the-art.
基金Supported by the Public Welfare Technology Application Research Project of Zhejiang Province(No.LTGY23F020001)the Provincial Construction Programme for First-Class Online and Offline Blended Courses(No.Z202Y22513)the Higher Education Teaching Reform Research Programme of Communication University of Zhejiang“Research on Contextualized Teaching Mode for the New Generation of Engineering Students Based on Convergence Media”。
文摘Background Autism spectrum disorder(ASD)is a pervasive developmental disorder characterized by difficulties in social communication and restricted,repetitive behaviors.Early intervention is essential to improve developmental outcomes in children with ASD.Serious games,which combine educational objectives with game based interactions,have shown potential as tools for early intervention in patients with ASD.However,in China,the development of serious games specifically designed for children with ASD remains in its infancy,with significant gaps in technical frameworks and effective data management methods.Method This paper proposes a framework aimed at facilitating the development of multimodal serious games designed for ASD interventions.We demonstrated the feasibility of the framework by developing and integrating several components,such as web applications,mobile games,and augmented reality games.These tools are interconnected to achieve data connectivity and management.Additionally,adaptive mechanics were employed within the framework to analyze real-time player data,which allowed the game difficulty to be dynamically adjusted and provide a personalized experience for each child.Results The framework successfully integrated various multimodal games,ensuring that real-time data management supported personalized game experiences.This approach ensured that the interventions remained appropriately challenging while still achievable.Conclusion The results indicate that the proposed framework enhances collaboration among therapists,parents,and developers while also improving the effectiveness of ASD interventions.By delivering personalized gameplay experiences that are both challenging and achievable,the framework offers a scalable platform for the future development of serious games.
基金supported,in part,by the National Natural Science Foundation of China(Nos.12372050 and 62088101)the Zhejiang Provincial Natural Science Foundation of China(No.LR20F030003).
文摘In this paper,we investigate analytical numerical iterative strategies for the pursuit-evasion game involving spacecraft with leader–follower information.In the proposed problem,the interplay between two spacecraft gives rise to a dynamic and real-time game,complicated further by the presence of perturbation.The primary challenge lies in crafting control strategies that are both efficient and applicable to real-time game problems within a nonlinear system.To overcome this challenge,we introduce the model prediction and iterative correction technique proposed in model predictive static programming,enabling the generation of strategies in analytical iterative form for nonlinear systems.Subsequently,we proceed by integrating this model predictive framework into a simplified Stackelberg equilibrium formulation,tailored to address the practical complexities of leader–follower pursuit-evasion scenarios.Simulation results validate the effectiveness and exceptional efficiency of the proposed solution within a receding horizon framework.
基金the Science and Technology Department,Heilongjiang Province under Grant Agreement No JJ2022LH0315。
文摘This paper presents a mode-switching collaborative defense strategy for spacecraft pursuit-evasiondefense scenarios.In these scenarios,the pursuer tries to avoid the defender while capturing the evader,while the evader and defender form an alliance to prevent the pursuer from achieving its goal.First,the behavioral modes of the pursuer,including attack and avoidance modes,were established using differential game theory.These modes are then recognized by an interactive multiple model-matching algorithm(IMM),that uses several smooth variable structure filters to match the modes of the pursuer and update their probabilities in real time.Based on the linear-quadratic optimization theory,combined with the results of strategy identification,a two-way cooperative optimal strategy for the defender and evader is proposed,where the evader aids the defender to intercept the pursuer by performing luring maneuvers.Simulation results show that the interactive multi-model algorithm based on several smooth variable structure filters perform well in the strategy identification of the pursuer,and the cooperative defense strategy based on strategy identification has good interception performance when facing pursuers,who are able to flexibly adjust their game objectives.
基金funded by the National Natural Science Foundation of China(No.U21B6001)。
文摘This paper proposes a novel impulsive thrust strategy guided by optimal continuous thrust strategy to address two-player orbital pursuit-evasion game under impulsive thrust control.The strategy seeks to enhance the interpretability of impulsive thrust strategy by integrating it within the framework of differential game in traditional continuous systems.First,this paper introduces an impulse-like constraint,with periodical changes in thrust amplitude,to characterize the impulsive thrust control.Then,the game with the impulse-like constraint is converted into the two-point boundary value problem,which is solved by the combined shooting and deep learning method proposed in this paper.Deep learning and numerical optimization are employed to obtain the guesses for unknown terminal adjoint variables and the game terminal time.Subsequently,the accurate values are solved by the shooting method to yield the optimal continuous thrust strategy with the impulse-like constraint.Finally,the shooting method is iteratively employed at each impulse decision moment to derive the impulsive thrust strategy guided by the optimal continuous thrust strategy.Numerical examples demonstrate the convergence of the combined shooting and deep learning method,even if the strongly nonlinear impulse-like constraint is introduced.The effect of the impulsive thrust strategy guided by the optimal continuous thrust strategy is also discussed.
基金co-supported by the National Natural Science Foundation of China(Nos.124B2031,12202281)the Shanghai Natural Science Foundation,China(No.23ZR1461800)the Northwestern Polytechnical University Scientific Research Initiation Foundation,China(No.G2024KY05103).
文摘In recent years,the availability of space orbital resources has been declining,and the increasing frequency of spacecraft close approach events has heightened the urgency for enhanced space security measures.This paper establishes a comprehensive framework for intelligent orbital game technology in space,encompassing four core technologies:threat perception of noncooperative targets,intent recognition,situation assessment,and intelligent orbital game countermeasures.The concepts of multi-turn,multi-round and multi-match in space orbital games are defined,clarifying the core technological requirements for intelligent space orbital games and establishing a cohesive technological framework.Subsequently,the current status of research on these four core technologies is investigated.The challenges faced in the existing research are analyzed,and potential solutions for future studies are proposed.This paper aims to provide readers with a thorough understanding of the latest advancements in space intelligent orbital game technology.along with insights into the future directions and challenges in this field.
基金support from Nantes Universite through the project AAP II GENOME(Ges-tion des Energies Nouvelles et Optimisation Electrique)and LEAP-RE MiDiNa project,grant N°NR-23-LERE-0002-01.
文摘Most developing countries continue to face challenges in accessing sustainable energy.This study investigates a solar panel and battery-powered system for an urban off-grid microgrid in Nigeria,where demand-sideflexibility and strategic interactions between households and utilities can optimize system sizing.A nonlinear programming model is built using bilevel problem formulation that incorporates both the households’willingness to reduce their energy consumption and the utility’s agreement to provide price rebates.The results show that,for an energy community of 10 households with annual energy demand of 7.8 MWh,an oversized solar-storage system is required(12 kWp of photovoltaic solar panels and 26 kWh of battery storage).The calculated average cost of 0.31€/kWh is three times higher than the current tariff,making it unaffordable for most Nigerian households.To address this,the utility company could implement Demand Response programs with direct load control that delay the use of certain appliances,such as fans,irons and air conditioners.If these measures reduce total demand by 5%,both the required system size and overall costs could decrease significantly,by approximately one-third.This adjustment leads to a reduced tariffof 0.20€/kWh.When Demand Response is imple-mented through negotiation between the utility and households,the amount of load-shaving achieved is lower.This is because house-holds experience discomfort from curtailment and are generally less willing to provideflexibility.However,negotiation allows for greaterflexibility than direct control,due to dynamic interactions and more active consumer participation in the energy transition.Nonetheless,tariffs remain higher than current market prices.Off-grid contracts could become competitive iffinancial support is pro-vided,such as low-interest loans and capital grants covering up to 75%of the upfront cost.
文摘Online gaming has become a daily norm,leading to unique forms of game-bullying distinct from traditional cyberbullying due to its immersive nature and ranking systems.This study examined how game-bullying victimization(GBV)affects depression via self-esteem,moderated by resilience and the state offlow,among 359 Chinese MOBA(Multiplayer-online-battle-arena)gamers(30.7%female,mean age=23.8 years,SD=4.57 years).The analysis revealed a direct link between GBV and depression.Self-esteem mediates this relationship,with higher GBV associated with lower self-esteem and subsequently greater depression.Resilience moderates both direct and indirect effects,mitigating GBV’s impact on self-esteem and depression in those with higher resilience.However,the state offlow did not moderate the mediation process.These results underscore that game-bullying affects more than just gaming addicts,highlighting the crucial roles of self-esteem and resilience.Thefindings suggest expanding the SOR model to account for personality traits susceptible to GBV,an emerging psychological harm.
文摘I was so excited to be a volunteer for the 2025 Asian Winter Games.It was a wonderful chance to meet people from all over Asia.During the Games,I helped players find their way around the stadium.I also answered questions from visitors.Everyone was friendly,and I felt happy to help them.
文摘Soccer is a very popular sport.Kids and adults play it all over the world.Kids play it in school yards and on the street.Others play it in parks and on soccer fields.Professional soccer players play it in stadiums.The idea of the game is simple.Two teams play.Each team has 11 players.Players run up and down the field.They have to kick the ball into the other team's goal.Then they score a goal.The team with the most goals wins.
基金supported by the Central Government Guides the Local Science and Technology Development Fund Project(2023ZY0020)Key R&D and Achievement Transformation Project in Inner Mongolia Autonomous Region(2022YFHH0019)+4 种基金the Fundamental Research Funds for Inner Mongolia University of Science and Technology(2022053)Natural Science Foundation of Inner Mongolia Autonomous Region(2022LHQN05002)NationalNatural Science Foundation of China(52067018)Natural Science Foundation of InnerMongoliaAutonomous Region of China(2025MS05052)Control Science and Engineering Quality Improvement and Cultivation Discipline Project in Inner Mongolia University of Science and Technology.
文摘A park hydrogen-doped integrated energy system(PHIES)can maximize energy utilization as a system with multiple supplies.To realize win-win cooperation between the PHIES and active distribution network(ADN),the cooperative operation problem of multi-PHIES connected to the same ADN is studied.A low-carbon hybrid game coordination strategy for multi-PHIES accessing ADN based on dynamic carbon base price is proposed in the paper.Firstly,multi-PHIES are constructed to form a PHIES alliance,including a hydrogen-doped gas turbine(HGT),hydrogen-doped gas boiler(HGB),power to gas and carbon capture system(P2G-CCS),and other equipment.Secondly,a hybrid game system model of the ADN and PHIES alliance is constructed,in which the ADN and PHIES alliance constitute a master-slave game,and the members of the PHIES alliance constitute a cooperative game.An improved Shapley value is proposed to deal with the problem of cost share among members in the alliance.Thirdly,an improved stepped carbon trading based on dynamic carbon baseline price is proposed.Thecarbon emissions at each moment and the total carbon emissions in a cycle are set as the dynamic adjustment factors of the carbon baseline price.The pricing mechanism of carbon baseline price increases with carbon emissions is constructed so that carbon emissions decrease.Finally,the quadratic interpolation optimization(QIO)algorithm is combined with Gurobi to solve the model.The results of the example analysis show that the cost of ADN is reduced by 4.47%,the cost of PHIES 1 is reduced by 3.67%,the cost of PHIES 2 is reduced by 0.97%,and the cost of PHIES 3 is reduced by 4.91%respectively.The total carbon emissions of the PHIES alliance are reduced by 7.08%.The low-carbon and economical operation of the multi-PHIES accessing ADN is achieved.
