Effects of Emotion on Decision-Making ofMethamphetamine Users: Based on theEmotional Iowa Gambling Task

The relapse of methamphetamine (meth) is associated with decision-making dysfunction. The present study aims to investigate theimpact of different emotions on the decision-making behavior of meth users. We used 2 (gender: male, female) × 3 (emotion:positive, negative, neutral) × 5 (block: 1, 2, 3, 4, 5) mixed experiment design. The study involved 168 meth users who weredivided into three groups: positive emotion, negative emotion and neutral emotion group, and tested by the emotional IowaGambling Task (IGT). The IGT performance of male users exhibited a decreasing trend from Block 1 to Block 3. Female methusers in positive emotion had the best performance in IGT than females in the other two groups. In positive emotion, the IGTperformance of female meth users was significantly better than that of men. Female meth users in positive emotion had betterdecision-making than those in negative or neutral emotion. Female meth users in positive emotion had better decision-makingperformance than males in positive emotion. In negative and neutral emotions, there was no significant gender difference indecision-making.

The Main Task of Water Transportation in 2004

The coastal port deep-water berths from existing 135 berths increase to 164 berths, and the throughput capacity will rising from current 231 million tons to 340 million tons which include build container berths from current 54 berths increase to 69 berths, the throughput capacity will from current 12 million TEUs increase to 19.4 million TEUs. In the final stage of Tenth Five-year plan, the quantity of national coastal port deep-water berths will from current 800 berths increase to

Traumatic Brain Injury in Prisoners: Relation to Risky Decision-Making, Aggression and Criminal Behavior

The objective of this cross-sectional study was to investigate if Traumatic Brain Injury (TBI) is related to decision-making deficits as well as to heightened levels of (reactive) aggression and criminal behavior in a group of Dutch male prisoners. Characteristics of aggression were assessed using three self-report questionnaires as well as systematic staff observations, complemented with data from criminal records. A semi-structured interview was conducted to rate lifetime prevalence of TBI and the Iowa Gambling Task (IGT) was completed to assess risky decision-making. Out of the total of 133 participants, 74 (55.6%) reported having sustained one or more incidents with potential TBI. Statistical comparisons between offenders with and without TBI indicated that the offenders with TBI reported significantly higher levels of (reactive) aggression on two out of three questionnaires than offenders without TBI (p-values ranging from 0.003 to 0.008), but no significant differences were found on staff observations of aggression and on the IGT. The higher conviction rates in offenders with TBI compared to the non-TBI group showed a trend. The confirmed relationship between TBI and higher aggressive tendencies is especially relevant for forensic populations due to the high prevalence rates of TBI in offenders. How this relates to specific cognitive processes remains unclear. The lack of a statistical difference between offenders with and without TBI on the IGT is in contrast with literature in non-offender samples, but seems to be in line with other studies in forensic populations.

Characteristics of Decision-Making by Family Members When Older Adults Are Hospitalized in Emergency Cases with Life-Threatening Conditions

Aim: This study aims to elucidate decision-making characteristics based on interviews with family members with experience in having to select treatments for older adult patients who have been hospitalized following emergency transport to the hospital. Design: Semi-structured interviews were conducted with 10 individuals with experience in surrogate decision-making for an older adult family member. Methods: The recorded interview data were transcribed verbatim, divided into minimum semantic units, and coded. Next, categories and subcategories were abstracted. A comparison was made with the conceptual constructs of a previous study that examined decision-making by families in a life-threatening crisis. Results: Four categories were extracted from 489 antecedents, 370 attributes, and 388 consequences. One new category was abstracted for each of: 1) antecedents: observing abnormalities and responding, while being worried about death;2) attributes: deliberating on the patient prognosis, the relationship with the patient, and what they believe the patient would want;and 3) consequences: continuing support during convalescence. It is desirable to provide support based on the characteristics of families of older adults, including considering the psychological burden on the families who make surrogate decisions, and also the burden of subsequent caregiving because it is not and in the present environment has not been common for patients to express their wishes beforehand.

MADDPG-D2: An Intelligent Dynamic Task Allocation Algorithm Based on Multi-Agent Architecture Driven by Prior Knowledge

Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinforce-ment learning(DRL)theory and an improved Multi-Agent Deep Deterministic Policy Gradient(MADDPG-D2)algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA.The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm,and considers the introduction of a double noise mechanism to increase the action exploration space in the early stage of the algorithm,and the introduction of a double experience pool to improve the data utilization rate;at the same time,in order to accelerate the training speed and efficiency of the agents,and to solve the cold-start problem of the training,the a priori knowledge technology is applied to the training of the algorithm.Finally,the MADDPG-D2 algorithm is compared and analyzed based on the digital battlefield of ground and air confrontation.The experimental results show that the agents trained by the MADDPG-D2 algorithm have higher win rates and average rewards,can utilize the resources more reasonably,and better solve the problem of the traditional single agent algorithms facing the difficulty of solving the problem in the high-dimensional decision space.The MADDPG-D2 algorithm based on multi-agent architecture proposed in this paper has certain superiority and rationality in DTA.

Performance of Children and Adolescents from a School of the City of Sogamoso on a Decision-Making Test

The aim of this study was to describe the performance on a decision-making task of children and adolescents (aged 7 - 17 years) from a school in the city of Sogamoso. This non-experimental descriptive, cross-sectional study was conducted by means of a non probability sampling of type cases. The sample consisted of 325 subjects, to whom the Hungry Donkey Task in its version adapted for Colombia was applied. Through descriptive statistics, the test performance trend was established, finding that participants aged 7 to 11 years had better performance than adolescents 12 to 14 years old, which partially supports the hypothesis of decision-making development in J shape. Subjects aged 15 to 17 years had the most disadvantageous performance, which may indicate immaturity and slow development of prefrontal areas and the influence of the trend towards risk-taking, characteristic of this age range.

融合NSGA-II和CSA的多目标车间调度

针对在灵活车间系统中调度作业和自动引导车(automated guide vehicle,AGV)的同时调度问题,考虑在有限多个AGV和加工机台的情况下,以最小化最大完工时间、单个AGV搬运消耗时间及所有AGV搬运总消耗时间为目标函数,设计融合NSGA-II(non-dominated sorting genetic algorithms)和克隆选择(clonal selection algorithm,CSA)的改进算法INGCSA来解决此类问题。采用工件、加工机台和AGV三部分编码;引入非支配排序和目标函数值大小排序后总得分进行种群分层,从而有效地保留优秀个体;针对克隆后的种群,对不同等级的种群采取不同的变异概率,并对染色体进行内部交换与均匀交叉混合交换的基因重组,有效地提高了种群的多样性与防止陷入局部最优。通过三组对比实验,验证了该算法在探索最优解时,具有运行时间短、稳定性高和收敛性好等优点。

新时期我国交通运输业碳减排的任务与对策——“交通7+1论坛”第六十次会议

交通运输业碳排放量占全国碳排放总量的10%,在支撑国民经济发展的同时自身也肩负着碳减排的重任,是落实双碳战略的重要战场之一。本次论坛以“新时期我国交通运输业碳减排的任务与对策”为主题,以双碳战略目标为引领,以各种运输方式比较优势的充分利用为切入点,明确交通运输各方式的减排任务和重点减排领域,同时综合考虑新时期经济社会发展情况、新能源产品替代程度以及未来新技术的经济可行性,探讨重点领域的减排对策和可行路径。

基于强化学习的自动化物料运输系统调度策略

为提高自动化物料运输系统生产运输效率,根据晶圆厂的混合式布局建立轨道的图网络模型,提出一种基于强化学习的动态调度策略。将调度过程划分为运输任务指派与运输路径规划两个阶段。任务指派使用基于实时交通信息的匈牙利算法求解。将运输路径规划问题表述为路径决策问题,使用基于离线策略的Q-Learning算法与玻尔兹曼探索策略构建的强化模型来求解路径决策问题。实验结果表明,所提方法可以有效提高自动化物料运输系统运输效率。

智能网联汽车边缘计算任务卸载研究综述

移动边缘计算作为一种新兴计算模式,已在车联网场景中展现出巨大的潜力。任务卸载是移动边缘计算中的关键问题,对于提高系统性能和用户体验至关重要,对此,针对移动边缘计算下车辆任务卸载研究展开综述。首先介绍移动边缘计算的基本概念,然后总结了评价指标与任务卸载问题公式和卸载决策等方面的研究,并对任务卸载方法和一些算法进行归纳,最后探讨了移动边缘计算任务卸载在未来的研究方向与挑战。通过对的研究现状概述和未来挑战的讨论,可更好地了解移动边缘计算任务卸载的前沿动态,为相关研究和应用提供指导和启示。

基于最优传输理论的无人艇编队任务分配方法

无人艇编队的任务分配问题是无人艇编队协同控制领域的一个重要研究问题。合理的任务分配方案将有助于无人艇编队快速决断和高效执行。现有方法在对无人艇编队的任务分配问题进行建模时,鲜有将无人艇的姿态和动力学模型纳入考虑。首先,建立带姿态的无人艇编队的任务分配问题模型;接着,通过将该模型与流形上的最优传输问题联系起来,得到离散求解形式;最后,仿真实验表明对于无人艇编队的任务分配中考虑无人艇姿态的必要性,以及提出的计算方法的有效性。

考虑能耗的海铁联运集装箱码头多设备协同调度

随着多式联运和绿色港口的发展,提高海铁联运效率和降低能源消耗成为码头亟需解决的问题。针对集装箱码头铁路作业区与码头作业区共堆场布局下设备利用率低与作业能耗高的问题,构建混合装卸作业下轨道吊、自动导向车(AGV)及场桥的协同调度优化模型,旨在实现作业完工时间最短、轨道吊和AGV的作业能耗最优,以及提高轨道吊协同作业的利用率。该模型综合考虑轨道吊间相互干涉、AGV伴侣容量限制以及AGV和轨道吊装卸过程中的重载、空载与等待状态下的不同能耗等约束,并针对轨道吊的干涉约束引入轨道吊任务分配策略。同时,采用改进的混合灰狼遗传算法对模型进行求解,具体改进策略包括引入灰狼算法位置更新策略优化遗传算法的交叉方式以提高最优解搜索效率,以及在遗传算法的选择步骤前引入基于奖励机制的评估器增强算法的局部搜索能力。实验结果表明,与轨道吊作业范围已知相比,考虑轨道吊任务分配使轨道吊的平均利用率提升了3%~8%。与自适应混沌遗传算法、遗传算法相比,改进混合灰狼遗传算法能在较短的作业完工时间内节约更多的能耗。

复杂真实环境下的调度电话转录算法研究

调度电话的应答是调度员日常工作的重要部分,也是事故回放审查的重要依据。为了提高事故分析及回放审查的效率,为调度指挥智能化打下基础,提出一种基于注意力机制及连接时序分类联合训练的调度电话转录算法,旨在提高复杂现实环境中调度电话的转录精确率及稳定性。通过在公开数据上添加调度大厅噪音来模拟现场环境,从而测试不同信噪比条件下算法的转录性能。在0 dB、1 dB、5 dB、10 dB的信噪比条件下测试转录错字率,结果分别是17.37%,16.48%,12.46%和9.69%,证明算法在强噪声环境下依旧能够保持稳定。算法包含半监督训练,实验表明,在小规模数据上,半监督训练相较于有监督训练可保证1%~2%的错字率降低。最后,算法在调度电话数据集上进行测试,并取得87.39%的关键字转录正确率。

基于资源约束的地铁运营施工任务调度研究

针对地铁运营施工资源有限、时间严格、任务繁重等特点,本文以地铁运营施工任务调度为研究对象,建立运营施工调度优化模型与算法。模型以任务优先级、施工人员和施工工区限制等为约束条件,以完工时间最小化、施工人员工作负荷均衡化为目标;设计一种联合线性规划与资源交叉(CPLEX-ROC)的混合求解算法;通过对某实际地铁运营线路展开案例研究,验证模型和算法的可行性与先进性。案例研究结果表明:相较于人工调度、遗传算法(GA)、教学优化算法(TLBO)方法,最大完工时间分别降低32.90%、15.11%和10.75%;施工人员工作负荷均衡指标相较GA、TLBO分别优化了15.44%和10.62%。计算结果验证了本模型能够提升地铁运营施工任务整体作业效率,同时实现施工人员工作负荷均衡。

Hierarchical Decision-Making Framework for Multi-UAV Task Assignment via Enhanced Pigeon-Inspired Optimization

Effective task assignment decisions are paramount for ensuring reliable task execution in multi-UAV systems.However,in the development of feasible plans,challenges stemming from extensive and prolonged task requirements are encountered.This paper establishes a decision-making framework for multiple unmanned aerial vehicles(multi-UAV)based on the well-known pigeon-inspired optimization(PIO)algorithm.By addressing the problem from a hierarchical structural perspective,the initial stage involves minimizing the global objective of the flight distance cost after obtaining the entire task distribution and task requirements,utilizing the global optimization capability of the classical PIO algorithm to allocate feasible task spaces for each UAV.In the second stage,building upon the decisions made in the preceding stage,each UAV is abstracted as an agent maximizing its own task execution benefits.An improved version of the PIO algorithm modified with a sine-cosine search mechanism is proposed,enabling the acquisition of the optimal task execution sequence.Simulation experiments involving two different scales of UAVs validate the effectiveness of the proposed methodology.Moreover,dynamic events such as UAV damage and task changes are considered in the simulation to validate the efficacy of the two-stage framework.

基于车辆任务可靠性的协同车辆路径问题

研究一类属于不同公司的配送中心共享车队、仓储等资源为客户协同配送货物的协同车辆路径问题,将之视为"部分客户被一车辆访问"的集合划分问题。考虑车辆容量、车辆行驶最大里程、车辆配送任务的可靠性概率、时间窗等约束条件,建立以车辆配送总费用最小为目标的混合整数规划模型,并设计了求解该问题的遗传算法求解该问题。最后,通过一个算例验证了模型的正确性和合理性。

基于“卓越计划”的运输管理学教学改革研究

运输管理学是物流工程专业核心课程之一。今依据对物流企业的调研结果,从课程定位、教材选择、课堂内容及课堂教学方法等方面进行课程教学改革研究,提出教学内容的模块化、工作项目化及驱动任务设计等环节,构建多种手段并用的课程教学体系。结果表明,教学改革充分发挥了学生的积极性和创造力,为培养出高质量的物流工程技术人才打下了基础。

驾驶任务缓急与汽车驾驶倾向性的相关性

以驾驶任务缓急程度为研究对象,对50名被测试者分别进行3次不同缓急程度运输任务的实验研究,获取在不同任务缓急程度下驾驶员的各项生理和心理特征数据,计算相应的汽车驾驶倾向性预判值.运用单因素方差分析方法,分析任务缓急程度与驾驶倾向性的相关性.研究结果显示,在较缓、一般缓急和较急3种任务缓急程度的情况下,驾驶倾向性影响因子(驾驶员的速度估计偏差、操作反应时间、注意力和情绪等)的值显著不同,表明任务的缓急对驾驶倾向性影响显著.

闭环供应链的激励机制研究

运用信息经济学的委托代理理论研究了闭环供应链的激励机制问题,在单一制造商和单一零售商构成的闭环供应链中,按照任务是否易于观测,将零售商参与闭环供应链的活动定义为易于观测的正向物流活动和不易观测的逆向物流活动。通过建立闭环供应链的多任务委托-代理模型,经定性描述、定量推导与求解,确定了激励合同中最优激励强度系数的数量关系,并得到了一系列有意义的结论。最后通过算例进行了分析和说明,为设计和管理闭环供应链的激励机制提供理论依据。

带多处理器任务的动态混合流水车间调度问题

研究了具有多处理器任务的混合流水车间调度问题,且考虑相邻两阶段之间的运输时间、机器故障和工件动态到达的实际生产特征。由于该问题不但求解非常复杂,对它的不同部分的简化还会使其变成其他不同的典型调度问题,探讨该类问题的近似解法具有挑战性和广义性。据此分别采用结合次梯度算法的拉格朗日松弛算法、结合次梯度和bundle算法的交替算法(交替S&B算法)的拉格朗日松驰算法进行求解。对多达100个工件的问题进行测试,结果表明,所设计的算法能够在合理的CPU时间内产生较好的时间表。