Synchronous measurements of prefrontal activity and pulse rate variability during online video game playing with functional near-infrared spectroscopy

Interactions between the central nervous system(CNS)and autonomic nervous system(ANS)play a crucial role in modulating perception,cognition,and emotion production.Previous studies on CNS–ANS interactions,or heart–brain coupling,have often used heart rate variability(HRV)metrics derived from electrocardiography(ECG)recordings as empirical measurements of sympathetic and parasympathetic activities.Functional near-infrared spectroscopy(fNIRS)is a functional brain imaging modality that is increasingly used in brain and cognition studies.The fNIRS signals contain frequency bands representing both neural activity oscillations and heartbeat rhythms.Therefore,fNIRS data acquired in neuroimaging studies can potentially provide a single-modality approach to measure task-induced responses in the brain and ANS synchronously,allowing analysis of CNS–ANS interactions.In this proof-of-concept study,fNIRS was used to record hemodynamic changes from the foreheads of 20 university students as they each played a round of multiplayer online battle arena(MOBA)game.From the fNIRS recordings,neural and heartbeat frequency bands were extracted to assess prefrontal activities and shortterm pulse rate variability(PRV),an approximation for short-term HRV,respectively.Under the experimental conditions used,fNIRS-derived PRV metrics showed good correlations with ECG-derived HRV golden standards,in terms of absolute measurements and video game playing(VGP)-related changes.It was also observed that,similar to previous studies on physical activity and exercise,the PRV metrics closely related to parasympathetic activities recovered slower than the PRV indicators of sympathetic activities after VGP.It is concluded that it is feasible to use fNIRS to monitor concurrent brain and ANS activations during online VGP,facilitating the understanding of VGP-related heart–brain coupling.

Game Theoretic Analysis of Joint Rate and Power Allocation in Cognitive Radio Networks

Spectrum sharing is an essential enabling functionality to allow the coexistence between primary user (PU) and cognitive users (CUs) in the same frequency band. In this paper, we consider joint rate and power allocation in cognitive radio networks by using game theory. The optimum rates and powers are obtained by iteratively maximizing each CU’s utility function, which is designed to guarantee the protection of primary user (PU) as well as the quality of service (QoS) of CUs. In addition, transmission rates of some CUs should be adjusted if corresponding actual signal-to-interference-plus-noise ratio (SINR) falls below the target SINR. Based on the modified transmission rate for each CU, distributed power allocation is introduced to further reduce the total power consumption. Simulation results are provided to demonstrate that the proposed algorithm achieves a significant gain in power saving.

A simplified differential game model for the optimal choice of tax rate

A classical problem on optimal choice of tax rate from the perspective of differential game approach is studied. Under some appropriate assumptions on the profit and utility functions, the open-loop Stackelberg equilibrium solution which is time- dependent is obtained. Result shows that 1) the optimal strategies derived from differential game and traditional unilateral optimal control approaches are different; 2) both marginal profit rate and the market rate of interest have great effect on the equilibrium solution; and 3) the government should think about the firm’s potential reaction when selecting tax rates and the timing of taxation.

Comparison Research on Anti-dumping Duty Rates between Administrative Review and Welfare Maximization under Dynamic Game of Perfect Information

Using economics and game theory, two kinds of models have been proposed in this paper under the assumption that foreign and domestic firms behave under the condition of dynamic game of perfect information. One model is for calculating Anti-dumping rate which is obtained according to current regulations of Anti-dumping, but it is not optimal. The other is an optimal model of Anti-dumping which is obtained according to the maximum principle of domestic social welfare. Then, through the comparison of this two models in detail, several shortages have been revealed about Anti-dumping rate model based on current regulations of Anti-dumping. Finally, a suggestion is indicated that WTO and China should use the optimal model to calculate Anti-dumping rate.

Impact of an active educational video game on children's motivation,science knowledge, and physical activity

Background： Active educational video games （AVGs） appear to have a positive effect on elementary school students＇ motivation leading to enhanced learning outcomes. The purpose of this study was to identify the effectiveness of an AVG on elementary school students＇ science knowledge learning, physical activity （PA） level, and interest-based motivation. Methods： In this randomized controlled study, 53 elementary school students were assigned to an experimental condition or a comparison condition. The experimental condition provided an AVG learning environment, whereas the comparison condition was based on sedentary educational video games. Results： The results of repeated measures analysis of variance （ANOVA） on the knowledge test showed that students in both groups performed better on the post-test than they did on the pre-test （p 〈 0.001, η2 = 0.486）, and their post-test scores did not differ significantly. The experimental condition provided a more active environment since the students＇ average heart rates （HRs） were in the Target-Heart-Rate-Zone （HR = 134 bpm）, which was significantly higher than the average HR （103 bpm） from the comparison condition （t = 7.212, p 〈 0.001）. Students in the experimental condition perceived a higher level of situational interest than their counterparts in the comparison group （p 〈 0.01, and η2 = 0.301）. Conclusion： These results suggest that AVGs benefit children more in terms of PA and motivation than traditional video games by providing an enjoyable learning experience and sufficient PA.

The evolution of cooperation in public good game with deposit

The emergence of cooperation still remains a fundamental conundrum in the social and behavior sciences.We introduce a new mechanism,deposit mechanism,into theoretical model to explore how this mechanism promotes cooperation in a well-mixed population.Firstly,we extend the common binary-strategy combination of cooperation and defection in public good game by adding a third strategy,namely,deposit cooperation.The players with deposit cooperation strategy pay a deposit in advance to obtain the benefits of public good at a lower contributions compared with the players with cooperation strategy,when the provision of public good is successful.Then,we explore the evolution of cooperation in the public good game with deposit by means of the replicator dynamics.Theoretical computations and stimulations show that the deposit mechanism can promote cooperation in a well-mixed population,and the numbers of equilibrium point are determined by variables of public good game.On the one hand,when the coexistence of cooperators and defectors is the stable equilibrium point in the evolutionary system,increasing the threshold of public good and adopting the weak altruism way for share benefits can enhance the level of cooperation in the population.On the other hand,if the coexistence of deposit cooperators and defectors is the stable equilibrium point,it is effective to promote the deposit cooperation by lowering the values of discount and deposit,and raising the threshold of public good.

Modelling the Iranian Petroleum Contract fiscal regime using bargaining game theory to guide contract negotiators

Based on Iran's sixth development plan,the country's oil and gas industry requires an investment of about$200 bn in the next five years to increase production.The Iranian government,to attract and motivate international oil company investment in their oil and gas fields,has presented a new type of risk service contract:the Iranian Petroleum Contract(IPC).This paper summarizes the features of the IPC and presents mathematical models of its fiscal regime for the benefit and guidance of both the National Iranian Oil Company(NIOC)and the contractors.Next,adopting bargaining game theory provides a mathematical model for reaching a win-win situation between the NIOC and the contractor.Finally,a numerical example is given and a sensitivity analysis performed to illustrate the implementation of the proposed models.The contractor and the NIOC may use these models when preparing their proposal and in the course of actual negotiations to calculate their internal rate of return,remuneration fee,and net present value for developing the fields at different conditions of their bargaining power,and derive a logical bargain to protect their best possible interests.

Coalition Game Based Full-Duplex Concurrent Scheduling in Millimeter Wave Wireless Backhaul Network

With the development of self-interference(SI) cancelation technology, full-duplex(FD) communication becomes possible. FD communication can theoretically double the spectral efficiency. When the time slot(TS) resources are limited and the number of flows is large, the scheduling mechanism of the flows becomes more important. Therefore, the effectiveness of FD scheduling mechanism for the flows is studied in millimeter wave wireless backhaul network with the limited TS resources. We proposed a full duplex concurrent scheduling algorithm based on coalition game(FDCG) to maximize the number of flows with their QoS requirements satisfied. We transformed the problem of maximizing the number of flows with their QoS requirements satisfied into the problem of maximizing sum rate of concurrently scheduled flows in each slot. We obtained the scheduled flows with maximum sum rate in first slot by using coalition game.And then with certain restrictions, the maximum sum rate of concurrently scheduled flows can also be achieved in subsequent time slots. The simulation results show that the proposed FDCG algorithm canachieve superior performance in terms of the number of flows that meet their QoS requirements and system throughput compared with other three algorithms.

Bit Rate Reduction in Cloud Gaming Using Object Detection Technique

The past two decades witnessed a broad-increase in web technology and on-line gaming.Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology.The immense utilization of web applications and games additionally prompted growth in the handled devices and moving the limited gaming experience from user devices to online cloud servers.As internet capabilities are enhanced new ways of gaming are being used to improve the gaming experience.In cloud-based video gaming,game engines are hosted in cloud gaming data centers,and compressed gaming scenes are rendered to the players over the internet with updated controls.In such systems,the task of transferring games and video compression imposes huge computational complexity is required on cloud servers.The basic problems in cloud gaming in particular are high encoding time,latency,and low frame rates which require a new methodology for a better solution.To improve the bandwidth issue in cloud games,the compression of video sequences requires an alternative mechanism to improve gaming adaption without input delay.In this paper,the proposed improved methodology is used for automatic unnecessary scene detection,scene removing and bit rate reduction using an adaptive algorithm for object detection in a game scene.As a result,simulations showed without much impact on the players’quality experience,the selective object encoding method and object adaption technique decrease the network latency issue,reduce the game streaming bitrate at a remarkable scale on different games.The proposed algorithm was evaluated for three video game scenes.In this paper,achieved 14.6%decrease in encoding and 45.6%decrease in bit rate for the first video game scene.

基于演化博弈的车联网分发消息激励机制

由于车联网中节点资源有限,车联网中存在不愿意传递消息的自私车辆节点,严重影响网络性能。为了改善网络性能,提出了一种基于演化博弈的车联网消息合作分发的激励机制,利用节点始终追求最大收益的有限理性的特点,根据节点传递消息的数量以及节点在固定时间内的空闲程度设计收益函数,引导自私节点努力参与到车联网中消息的传递过程,同时引入路边单元作为监管者加速车辆节点的策略更新过程。仿真结果表明自私节点比例越多,网络性能越差,而该激励机制可以有效地改善存在自私节点的车联网的网络性能。

计及设备变负载率特性的综合能源系统“源-荷-储”协同优化调度策略

针对传统综合能源系统忽略设备变负载率特性建模而导致调度方案经济性降低等问题,提出了一种计及设备变负载率特性的综合能源系统“源-荷-储”协同优化调度策略。文章基于对系统“源-储”两侧设备运行特性的研究,建立了设备的变负载率模型,以减少传统恒定效率模型带来的调度误差;引入主从博弈理论分析了综合能源系统供需两侧之间的交互过程,建立了计及设备变负载率特性的供需两侧主从博弈模型,进而证明了所提模型存在唯一博弈均衡,并提出相应求解流程;最后,对某园区综合能源系统进行仿真分析。结果表明:所提策略能够实现综合能源系统“源-荷-储”协同运行,提升供给侧与需求侧的经济效益。

新能源消纳与用户侧响应主从博弈的配电网智能软开关选址策略

分布式电源接入配电网后,配电网调控能力不足导致新能源消纳水平低、用户支出经济性指标差,提出一种新能源就地消纳和用户支出主从博弈的配电网智能软开关选址策略的嵌套模型和方法。外层建立以新能源渗透率最大、电能质量指标最佳且计及传统调控手段的模型结构;内层考虑新能源用户消纳的分时电价、储能装置充放电成本和日运行费用因素,构建能满足用户支出成本最低的需求响应模型。调用CPLEX求解器求解混合整数非线性规划模型,用户侧与配电网侧模型通过反复博弈优化决策变量,主从博弈内层优化采用改进粒子群优化算法加快收敛速度。以改进的IEEE 33节点系统为算例进行分析,验证了所提智能软开关选址策略的有效性。

奖励机制与用户意愿结合的高峰期负荷博弈调度策略

在高峰时段,居民冷/热设备占尖峰负荷的比重不断攀升,影响了低压配电网的安全稳定优化运行。为补充供给侧调节能力,提升调控灵活性,亟须引导用户侧可调资源参与电网供需互动。该文提出一种奖励机制与用户意愿相结合的高峰期负荷博弈调度策略。依据用户用能意愿对高峰时段用电负荷进行动态划分,制定基于负载率-奖励函数的差异化补贴机制。将高峰时段需要提升功率的负荷群视为领导者,将具有灵活削减能力的负荷群视为追随者,建立Stackelberg博弈模型,证明博弈均衡的唯一性。进而该文提出了Stackelberg博弈下的用电高峰期负荷日内优化调度方法,优化博弈双方在追求效益最大时的策略。该文构建多通路混合专家网络求解设备动作意愿,提出基于用户意愿的单功率-多功率级负荷联合控制策略,实现负荷的实时精细化调控。最后,算例表明所提策略能够在实现聚合商与用户侧双赢、遵从用户调控意愿的同时,有效地平抑用电高峰期的负荷波动,减小峰谷差。

基于双人零和博弈的孤岛微电网有界L2增益负荷频率控制

针对含不确定建模误差和新能源接入的孤岛微电网,提出了一种结合有界L2增益基线控制和扰动补偿的综合负荷频率控制(LFC)方法。首先,推导了微电网的全驱模型,将建模误差和新能源的影响总结成一个综合扰动。为提高系统的鲁棒性,该综合扰动被定义成控制信号的对手玩家。进一步,关于扰动抑制的有界L2增益问题被等价成求解综合扰动和控制信号的零和博弈Nash均衡,由此推导出有界L2增益基线控制器。为改善频率的二次控制,设计了基于五阶广义积分观测器的扰动补偿控制,并在此基础上引入了一种针对发电速率约束(GRC)的新型抗发电速率约束(anti-GRC)措施。最后,搭建了16 MW的新能源-柴油混合微电网仿真模型,并在多种工况下对所提出的综合LFC方法进行测试,验证了其有效性。

集装箱班轮公司与客户长期运输合同定价的博弈模型

运用鲁宾斯坦森轮流出价思想,建立了承运人和托运人关于集装箱班轮公司长期合同运价的博弈模型,模拟承托双方的谈判过程,研究了存在可信欺骗情况下的承托双方出价政策,讨论了在不同航运市场存在虚假报价情况下承托双方在博弈中的地位。分析结果表明:在航运市场运力过剩时,托运人在运价谈判中占主动地位,承运人第一阶段出价存在不确定性,若托运人理性协商,成交结果取决于运价的期望值及贴现率,若托运人非理性压价,而承运人未意识到时,报价走低,谈判结束,否则第一阶段博弈失效,进入第二阶段;当航运市场运力不足时,托运人在运价谈判中据被动地位,只要承运人的出价低于其承受底线值,便会接受报价。通过对模型求解,发现双方最终的博弈结构与航运市场环境、双方对未来市场的预期值、贴现因子以及出价政策有关。最后给出博弈双方在不同航运市场情景下的最优出价策略。

买方直接融资模式下的采购合约策略

在由单个制造商和供应商构成的二级供应链中,供应商的资金限制以及私有的生产努力成本信息显著影响制造商的采购策略。为深入探索这一动态,所构建的买方直接融资模式下的斯塔克伯格博弈模型结合了供应链金融和信息不对称的概念,与现有文献相比呈现出独特性。研究涉及信息对称和不对称两种场景,着重分析了制造商在信息不对称条件下如何制定最优采购合约,同时深入探讨了制造商获取信息的类型和精度如何影响供应链各方的决策与收益。研究发现,供应商的资产抵押物价值、获得的信息类型和信息的精确程度都在很大程度上影响制造商的采购价格和贷款利率决策。在信息不对称情况下,不同类型的信息对可交易范围产生差异效应。当制造商免费获得信息时,提高信息精度率有助于信息劣势下的制造商做出更合理的决策,从而实现更高的预期利润。然而,当制造商需要支付获取信息的成本时,实现利润最大化的最佳信息精度率并非总是越高越好,而是受到信息获取成本的制约。

Accelerated Value Iteration for Nonlinear Zero-Sum Games with Convergence Guarantee

In this paper,an accelerated value iteration(VI)algorithm is established to solve the zero-sum game problem with convergence guarantee.First,inspired by the successive over relaxation theory,the convergence rate of the iterative value function sequence is accelerated significantly with the relaxation factor.Second,the convergence and monotonicity of the value function sequence are analyzed under different ranges of the relaxation factor.Third,two practical approaches,namely the integrated scheme and the relaxation function,are introduced into the accelerated VI algorithm to guarantee the convergence of the iterative value function sequence for zero-sum games.The integrated scheme consists of the accelerated stage and the convergence stage,and the relaxation function can adjust the value of the relaxation factor.Finally,including the autopilot controller,the fantastic performance of the accelerated VI algorithm is verified through two examples with practical physical backgrounds.

年轻态势下的体感游戏运动效果及强度研究

目的:探究年轻化模式下的体感游戏对于青少年人群运动的心率影响和运动强度研究,探究体感游戏模式下的运动效果。方法:本研究共招募20名12~22周岁,BMI均处于正常范围内的受试者参与完成A组体感游戏《健身环大冒险》及B组体感游戏《Just Dance》,运用Mac1200心电监护仪检测各项心率数据,包括静息心率、最大心率、游戏平均心率,并参照运动强度划分区域来检测两项体感游戏的运动强度效果,以及对比强少年男女组别在参与体感游戏下的运动差异。结果:A组游戏中男女组别的精息心率、最大心率、游戏平均心率,游戏最大心率的p值分别为0.592、0.545、0.982、0.601,均无显著差异;B组实验中男女组别的精息心率、最大心率、游戏平均心率,游戏最大心率的p值分别为0.985、0.908、0.018、0.006,其中游戏平均心率和游戏最大心率具备显著差异。从运动强度来看A组B组男女运动强度均处在50%~69%的中等强度区域。结论:A、B组体感游戏可以提供中等强度的运动效果,从游戏平均心率和游戏最大心率来看,B组舞蹈类游戏强少年男女呈现显著差异,从游戏心率均值数据来看,体感游戏可以达到一定的运动效果。

基于三方博弈理论对装配式住宅持续发展影响

相较于现砌建筑,装配式施工方式被认为是提高建筑行业环境绩效和可持续发展的有效途径。但现今装配式住宅的发展依旧存在障碍,消费者和政府这两个主要因素直接影响装配式住宅企业的决策。对其发展起着主导作用。然而,现有的研究大多为实证研究或只关注政府的某些激励行为缺乏不同参与方视角的分析以及相互作用产生的影响。所以对政府、消费者、建筑企业三大利益相关者之间动态关系及其动态行为策略。建立三方博弈模型,对不同情景进行数据分析来说明三方的决策行为,为此提供理论和实践依据,从而为如今装配式住宅可持续发展提供见解。

考虑环保信用整体评级的环境污染第三方治理演化博弈分析

为提升环境污染第三方治理中多方环境行为,尤其针对第三方治理中环境污染责任难以界定导致监管难的问题,构建排污企业、治污企业、地方政府三方参与的演化博弈模型,重点研究实施环保信用评级对环境污染第三方治理带来的影响。研究表明,排污企业环保信用评级是实现排污企业、地方政府策略选择协同优化的有效措施;政府补助不能实现治污企业、地方政府策略选择的协同优化,而环保信用评级可以实现;相比排污企业,治污企业对环保信用评级更加敏感。然而对排污企业或治污企业实施环保信用评级均无法实现三者策略选择的协同优化,进而提出了环保信用整体评级机制,并验证了该机制的有效性;参数分析发现,实现三者策略选择协同优化的关键是提升治污企业环保信用评级收益;互赔系数的提高有助于排污企业、治污企业策略选择的优化,但取值过高会降低地方政府选择“积极监管”策略的概率。建议政府应积极实施排污企业与治污企业环保信用评级,并通过强化排污企业与治污企业相互监管的机制设计来优化监管方式。