Neural mechanism of proposer's decision-making in the ultimatum and dictator games

Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer＇s decision-making in the ultimatum game compared with the dictator game. The present functional magnetic resonance imaging study revealed that proposing fair offers in the dictator game elicited greater activation in the right supramarginal gyrus, right medial frontal gyrus and left anterior cingulate cortex compared with proposing fair offers in the ultimatum game in 23 Chinese undergraduate and graduate students from Beijing Normal University in China. However, greater activation was found in the right superior temporal gyrus and left cingulate gyrus for the reverse contrast. ＂The results indicate that proposing fair offers in the dictator game is more strongly associated with cognitive control and conflicting information processing compared with proposing fair offers in the ultimatum game.

The modulation recognition based on decision-making mechanism and neural network integrated classifier

A neural network integrated classifier(NNIC) designed with a new modulation recognition algorithm based on the decision-making tree is proposed in this paper.Firstly,instantaneous parameters are extracted in the time domain by the coordinated rotation digital computer(CORDIC) algorithm based on the extended convergence domain and feature parameters of frequency spectrum and power spectrum are extracted by the time-frequency analysis method.All pattern identification parameters are calculated under the I/Q orthogonal two-channel structure,and constructed into the feature vector set.Next,the classifier is designed according to the modulation pattern and recognition performance of the feature parameter set,the optimum threshold is selected for each feature parameter based on the decision-making mechanism in a single classifier,multi-source information fusion and modulation recognition are realized based on feature parameter judge process in the NNIC.Simulation results show NNIC is competent for all modulation recognitions,8 kinds of digital modulated signals are effectively identified,which shows the recognition rate and anti-interference capability at low SNR are improved greatly,the overall recognition rate can reach 100%when SNR is12dB.

The Effect of Queuing Mechanisms First in First out (FIFO), Priority Queuing (PQ) and Weighted Fair Queuing (WFQ) on Network’s Routers and Applications

The paper presents the simulation results of the comparison of three Queuing Mechanisms, First in First out (FIFO), Priority Queuing (PQ), and Weighted Fair Queuing (WFQ). Depending on their effects on the network’s Routers, the load of any algorithm of them over Router’s CPUs and memory usage, the delay occurred between routers when any algorithm has been used and the network application throughput. This comparison explains that, PQ doesn’t need high specification hardware (memory and CPU) but when used it is not fair, because it serves one application and ignore the other application and FIFO mechanism has smaller queuing delay, otherwise PQ has bigger delay.

APPROACH FOR FUZZY MULTI-ATTRIBUTE DECISION-MAKING WITH FUZZY COMPLEMENTARY PREFERENCE RELATION ON ALTERNATIVES

In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternatives. Firstly, the decision-making information based on the subjective preference information in the form of the fuzzy complementary judgment matrix is uniform by using a translation function. Then an objective programming model is established. Attribute weights are obtained by solving the model, thus the fuzzy overall values of alternatives are derived by using the additive weighting method. Secondly, the ranking approach of alternatives is proposed based on the degree of similarity between the fuzzy positive ideal solution of alternatives （FPISA） and the fuzzy overall values. The method can sufficiently utilize the objective information of alternatives and meet the subjective requirements of the DM as much as possible. It is easy to be operated and implemented on a computer. Finally, the proposed method is applied to the project evaluation in the venture investment.

Fuzzy synthetic evaluation on layoff mechanism for human resource

According to the modern theory of human resource management, the condition of buyout mainly depends on two variables of an employee: his interior value of product and exterior work reward. There exist shortages in evaluating the value of the employees in an enterprise. Consequently, a lot of employees might be laid off. Hence, this paper puts forward a two-stage method for decision-making to carry out a selective plan of buyout, based on the fuzzy synthetic evaluation involing many factors impacting on human resource. Moreover, a positive analysis is also given.

Use of Research Evidence in Policy and Decision-Making: Views, Attitudes and Practices of Health Policy Makers in Lusaka Province of Zambia

Background: The integration of relevant high-quality research evidence into the health decision and policy formulation process is a key strategy for improving health systems especially in developing countries such as Zambia. However, the lack of capacity to understand and value research evidence by policy and decision makers makes it difficult for them to find and use research evidence in a timely manner even when motivated to do so. This study aimed to establish the views, attitudes and practices of policy makers on the use of research evidence in policy and decision-making process in Zambia. Methodology: This descriptive cross-sectional study was conducted in Lusaka, Zambia among selected public health decision and policy making institutions. A purposive sample of 21 consenting policy makers who were working in different positions in the Ministry of Health Headquarters, Provincial and District Health Offices, Health Professions Regulatory Bodies, United Nations Agencies, International Non-Governmental Organizations and University Deans from the University of Zambia participated in the study. A self-administered questionnaire was used to collect data. The IBM? SPSS? Statistics for Windows Version 20.0 was used for data analysis. Results: The concept of Evidence Informed Health Policy was not well understood such that only less than half (47.5%) of the participants reported having heard specifically about Evidence Informed Health Policy meanwhile almost two thirds (61.9%) reported that they used research evidence in decision making and policy formulation. Similar discrepancy was expressed in the understanding of and use of rapid response mechanisms such that although (47.6%) of the participants reported having heard about it, (57%) had never used rapid response mechanisms for deci-sion-making. With regard to the sources of information, about half (52.3) of the participants reported scholarly articles as their main source of evidence. Con-clusion and Recommendations: There is need for more sensitization and ca-pacity building among the decision and policy makers on the importance of using research evidence in decision and policy making process as incorporation of relevant high-quality research evidence into the health policy making pro-cess is a key strategy for improving health systems.

Prioritizing the efforts:lived experiences of family when taking care of people with cancer

Objective:Cancer has one of the highest disease mortality rates.Families are very important in the treatment of people with cancer.By using a phenomenological design,this study aimed to explore the experience of families in caring for a person with cancer and to identify the needs of these families.Methods:First,eight interviews were under taken with family members selected through a purposive sampling method.Then,another three interviews were conducted for data validation.The collected data were analyzed using the framework method of analysis.Results:The core theme,“Prioritizing the efforts:Being aware of the best we could do for our family,”reflected family’s experiences of caring for a person with cancer and was underpinned by five themes:“Decisions to make,”“Keeping up the good support,”“Acknowledging the others’contributions,”“Assisting my family to alleviate the disease,”and“Adapting to the current situation.”Conclusions:The results suggest that building mutual trust and communication between family and healthcare professionals is vital in decision-making for people with cancer.Family may also work with the person in fulfilling their needs,without disregarding the needs of the family.When suppor ting the needs of people with diabetes,the family requires appropriate information,and thus,healthcare professionals wisely select which information can help the family make a decision regarding the treatment.After administering the treatment and providing information for people with cancer and their family,asking for feedback is required for evaluation.

混合异构无线传感器网络覆盖漏洞修补算法

在无线传感器网络(WSN)中,增强传感器覆盖范围是核心问题。文章提出一种基于优先级机制的、适用于混合异构WSN的覆盖漏洞修补算法。该算法通过评估漏洞大小和设定补丁节点优先级,提升覆盖率,减少冗余,平衡资源。结果显示,改进后的算法在覆盖率和节点冗余上均优于传统算法,为WSN覆盖优化提供新思路。

面向充电桩时间分配的在线双边拍卖机制设计

随着新能源汽车的快速发展,充电时间分配问题成为关注的焦点。现有研究主要集中在根据预先规划的驾驶路线选择充电桩,但对于车主的动态需求却没有提供即时解决方案。为解决该问题,文章首先根据车主的需求量、地理位置以及充电完成度等因素设计了一种需求者优先级函数,然后将充电桩的时间分配问题建模为密封竞价在线双边拍卖,在此基础上,提出了一种真实的交易机制。理论分析证明了该机制不仅满足个体理性、预算平衡,还能够引导供需双方报告真实的到达离开时间以及物品估值。最后通过具体的实验证明了该拍卖机制的实用性和有效性。所提出拍卖机制满足双边市场中交易个体的属性偏好和在线环境的交易特征,为当前的在线充电平台提供了有益的参考。

基于多维度优先级经验回放机制的深度确定性策略梯度算法

为进一步提高深度确定性策略梯度算法在处理强化学习连续动作任务中的收敛速度,提出了一种基于多维度优先级经验回放机制的深度确定性策略梯度算法。首先,针对经验回放机制中样本数据利用率低的问题,利用时间差分误差指标对样本进行分类;其次,利用稀缺性和新奇性两个指标对样本进行评分,并将稀缺性和新奇性的评分进行加权组合,得到最终的优先级评分;最后,将设计的多维度优先级经验回放机制方法应用在深度确定性策略梯度算法中,在强化学习连续控制任务中对改进算法进行测试,实验结果表明,改进算法的收敛速度有所提升。

基于因果机理和邻近影响的拱坝温度场监测数据缺值插补

利用实测温度场是提高拱坝变形监控模型性能的重要途径之一,但由于监测系统异常等原因,部分温度测点的监测数据存在缺值。为此,根据缺值段在温度时间序列中所处位置及其相对变化幅值制定判断准则,优选单测点缺值插补方法,基于动态时间规整法量化时间序列之间的相似性,构建拱坝温度场缺值插补的多测点分层标准和同层优先级准则,建立兼顾因果机理和邻近影响的插补预测模型。通过对某高拱坝的实施结果表明,所提出的方法和准则可有效实现拱坝温度场全部测点温度时间序列的系统性插补,将因果机理和邻近影响相结合的插补预测模型对84.0%以上的测点具有提升作用。

我国建设工程承包人及相关方权益保护问题研究

根据我国法律规定及司法实践,虽然权利人可以按照合同约定直接行使权利或依靠法定的特殊保护机制进行权利救济,但很多权利救济难以充分保护相关方的权益。针对这些问题,我国亟需建立一种“技工留置权”制度来完善建设工程承包人及相关方权益保护,这一制度允许为建设工程提供劳务、材料或服务的参与方在未获得报酬时,对相关不动产主张类似于留置权的权利,以保障其获得应得的报酬。司法实践中,可适当扩大权利主体范围、确立权利法律性质及优先效力、建立初步通知和权利登记程序、引入权利完善和动态维护机制、建立标准化操作和电子化管理系统等,逐步完善全面、有效的权益保护体系。

Impact of Artificial Intelligence on Corporate Leadership

Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.

无轨胶轮车转向机构优化与验证

为解决无轨胶轮车转向机构在转向过程中压力振动严重,导致管路爆裂以及液压元器件损坏的问题,在对无轨胶轮车转向机构分析的基础上,分别对其关键部件(优先阀和转向器)的特性进行仿真分析;建立无轨胶轮车转向机构机液联合仿真模型,查找导致振摆问题的主要原因,并通过对左右转向油缸铰接参数进行优化,解决振摆问题,最后对优化效果进行了验证。

基于电液比例和负载敏感技术的非公路矿用自卸车线控液压转向系统

提出了一种基于电液比例技术和负载敏感技术的兼容有人驾驶和无人驾驶转向功能的大流量和中小流量液压转向系统,分别阐述了两种系统的组成、液压原理和控制方法,为各流量需求的兼容有人驾驶和无人驾驶转向功能的非公路矿用自卸车液压转向系统的设计提供了一种原理方案。

一种主从式卫星集群的星间组网系统设计

为解决主从式卫星集群在离散稀疏拓扑下的组网通信问题,保障其星间实时交互遥控遥测及任务信息的需求,根据主从式卫星集群的分层、分簇的空间拓扑特点,本文提出了一套通信系统架构和星间组网协议栈的设计方案。首先,在网络层的设计上,给出了网络层的数据结构、基于多权重优先级代价函数的子网簇首选择备份机制以及子星建网入网的流程;其次,在数据链路层,根据分包遥控和分包遥测体制按照层次化对数据进行处理;然后,在物理层的设计中采用扩跳频作为星间链路的通信体制,采用时分多址方式实现卫星集群的多用户通信,并给出了星间链路的具体通信指标;最后,对星间通信进行了链路计算,计算结果表明物理层设计满足各星通信需求。

THE ANALYSIS OF CELL LOSS RATES IN AN ATM MUX WITH LOSS PRIORITIES

The analysis of cell loss rates in an ATM Mux with loss priorities is an important problem in the-study of traffic control in ATM networks. In this paper, the loss rates of the cells with different priorities in an ATM Mux are analyzed by approximating the actual input process with two-state MMDP and fluid flow technique, and the analytical expressions of the relation between the loss rates and the buffer size are obtained. Simulation shows that the approach is sulliciently accurate for applications.

Fuzzy Approach to Determining Priority Preorders of Water Resources Projects

In this paper,the criteria set related to the priority preorders of water resources projects is introduced.A fuzzy multiple criteria group decision-making model is established,which incorporates quantitative analysis,judgments,experience and preferences of decision-makers.The model is used in practice to determine the priority preorders of five water resources projects,and the results show that the best choice can supply more new employment,domestic water and irrigation water,and has better quality.

Research on self-adaptive decision-making mechanism for competition strategies in robot soccer

In the robot soccer competition platform, the cur- rent confrontation decision-making system suffers from dif- ficulties in optimization and adaptability. Therefore, we pro- pose a new self-adaptive decision-making （SADM） strategy. SADM compensates for the restrictions of robot physical movement control by updating the task assignment and role assignment module using situation assessment techniques. It designs a self-adaptive role assignment model that assists the soccer robot in adapting to competition situations similar to how humans adapt in real time. Moreover, it also builds an accurate motion model for the robot in order to improve the competition ability of individual robot soccer. Experimental results show that SADM can adapt quickly and positively to new competition situations and has excellent performance in actual competition.

Path analysis on educational fiscal decision-making mechanism in China

In China’s current educational fiscal decision making,problems are as follows:no law to trust or not abiding by available laws,absence of equity and efficiency,as well as the standardization of decision-making procedures.It is necessary to set up effective fiscal decision-making mechanism in education and rationally devise reliable paths.