On the task assignment with group fairness for spatial crowdsourcing

Task assignment, the core problem of Spatial Crowdsourcing (SC), is often modeled as an optimization problem with multiple constraints, and the quality and efficiency of its solution determines how well the SC system works. Fairness is a critical aspect of task assignment that affects worker participation and satisfaction. Although the existing studies on SC have noticed the fairness problem, they mainly focus on fairness at the individual level rather than at the group level. However, differences among groups in certain attributes (e.g. race, gender, age) can easily lead to discrimination in task assignment, which triggers ethical issues and even deteriorates the quality of the SC system. Therefore, we study the problem of task assignment with group fairness for SC. According to the principle of fair budget allocation, we define a well-designed constraint that can be considered in the task assignment problem of SC systems, resulting in assignment with group fairness. We mainly consider the task assignment problem in a common One-to-One SC system (O2-SC), and our goal is to maximize the quality of the task assignment while satisfying group fairness and other constraints such as budget and spatial constraints. Specifically, we first give the formal definition of task assignment with group fairness constraint for O2-SC. Then, we prove that it is essentially an NP-hard combinatorial optimization problem. Next, we provide a novel fast algorithm with theoretical guarantees to solve it. Finally, we conduct extensive experiments using both synthetic and real datasets. The experimental results show that the proposed constraint can significantly improve the group fairness level of algorithms, even for a completely random algorithm. The results also show that our algorithm can efficiently and effectively complete the task assignment of SC systems while ensuring group fairness.     

Reviewer assignment algorithms for peer review automation: A survey

Assigning paper to suitable reviewers is of great significance to ensure the accuracy and fairness of peer review results. In the past three decades, many researchers have made a wealth of achievements on the reviewer assignment problem (RAP). In this survey, we provide a comprehensive review of the primary research achievements on reviewer assignment algorithm from 1992 to 2022. Specially, this survey first discusses the background and necessity of automatic reviewer assignment, and then systematically summarize the existing research work from three aspects, i.e., construction of candidate reviewer database, computation of matching degree between reviewers and papers, and reviewer assignment optimization algorithm, with objective comments on the advantages and disadvantages of the current algorithms. Afterwards, the evaluation metrics and datasets of reviewer assignment algorithm are summarized. To conclude, we prospect the potential research directions of RAP. Since there are few comprehensive survey papers on reviewer assignment algorithm in the past ten years, this survey can serve as a valuable reference for the related researchers and peer review organizers.     

MINRES法和有限元法解奇摄动反应扩散方程

讨论奇摄动反应扩散方程 的数值逼近求解问题, 及 均为正实数. 利用有限元方法并结合最小残量法, 给出求解该问题的一个新方 法, 该方法修正了单纯采用有限元方法求解时在边界附近呈现出的非正常扰动的 现象, 避免了因为 过小所引起的解的变异, 从而得到更加精确的数值结果.     

基于遗传算法的高校排课系统设计与实现

随着高等教育的发展,学生人数不断增加,而教室资源和教师资源有可能相对有限,排课就成为教学管理中十分重要且又相当繁重的工作之一。文章根据高校排课特点,在对排课系统及遗传算法基本理论分析的基础上,使用基本遗传算法SGA,设计并开发出了一个基于B/S模式的排课系统CAS,以满足高校教学管理工作不断发展的需要。     

非结构化数据分类整合在贵州项目网中的设计与实现

针对贵州项目网中非结构数据量大的特点和不易管理的问题,文章采用了基于遗传算法分类的方法和数据库管理的方法对贵州项目网进行了数据管理的重构设计并在贵州项目网建设中得以实践。结果表明基于遗传算法分类与数据库管理适用于整合管理大量的非结构数据。     

八数码问题的搜索算法比较

搜索策略是人工智能研究的主攻方向之一,采用不同的搜索策略在求解问题的过程中也会存在差异.通过对于八数码的搜索求解分析,采用盲目搜索中的广度优先搜索算法和启发式搜索中的A*算法进行实现,将广度优先搜索算法与A*算法进行比较,从而评价这两种搜索算法的优劣性.     

G代码行PIDP编译算法

G代码的解释或编译是数控系统软件中的一个不可缺少的环节。对此,提出了一个新的算法,阐述了该算法的原理和实现方法。该算法将G代码编译成协议整型数据包PIDP,利用PIDP,使控制软件的实现更加方便。其算法软件是一种用于上下位机结构开放式数控系统的新型G代码编译器中的关键模块,它编译出的目标码为上下位机奠定了一个软件接口基础。     

Refreshing File Aggregate of Distributed Data Warehouse in Sets of Electric Apparatus

Integrating heterogeneous data sources is a precondition to share data for enterprises. Highly-efficient data updating can both save system expenses, and offer real-time data. It is one of the hot issues to modify data rapidly in the pre-processing area of the data warehouse. An extract transform loading design is proposed based on a new data algorithm called Diff-Match, which is developed by utilizing mode matching and data-filtering technology. It can accelerate data renewal, filter the heterogeneous data, and seek out different sets of data. Its efficiency has been proved by its successful application in an enterprise of electric apparatus groups.     

不同图像之间拼接篡改的数字图像检测研究

对基于CFA（颜色滤波阵列）模型的篡改检测算法进行了改进。其检测过程为：首先,利用插值算法得到像素位置的预测误差,根据预测误差计算出CFA单元特征;然后,利用EM（期望最大化）算法估计特征模型的参数,算法对篡改位置的均值不做事先确定（从实验来看这种改进具有较好的效果）;最后,利用贝叶斯理论计算出每个像素点的似然率,根据似然率的不同来定位篡改区域。在进行单CFA阵列模式检测的情况下,对多种CFA阵列模式的图像也进行了检测分析,实验结果显示,该算法能够对多种CFA阵列模式的图像准确定位篡改区域。     

决策树挖掘技术在手术诊断上的实现

在ID3算法基础上提出了基于卡方测试的前剪枝算法,并在Jbuilder2006系统下构建了一个基于决策树挖掘技术的可视化决策系统。该研究基于B/S架构的系统,通过浏览器自动将服务器上的Applet下载到客户端来访问系统,实现了医疗系统的手术诊断数据表的数据挖掘,所得到的实验结果与专家诊断结果基本吻合,取得了较好的实际应用效果。