基于生成矩阵的LDPC/Turbo码的构造及内外迭代译码新技术

美国相关公司在美国对中国维生素C生产企业提起“价格串通”的美国反托拉斯(反垄断)诉讼。这是中国企业第一次面临美国的反托拉斯诉讼的域外管辖。本文分析的案例报告主要涉及中国企业试图从程序方面即根据“国家强迫行为”理论来申请中止证据调查程序。本文在对该案归纳的基础上,还就本案可能涉及的其他问题,如对美国反托拉斯法的域外适用的抗辩理由;美国反托拉斯法上价格串通构成的要素进行了评析。此外,本案还提醒我国行业协会和企业在应对美国反倾销指控的同时,需防止被指控价格串通而触犯后果更为严厉的美国反托拉斯法。     

电子商务技能型人才需求与高职教育培养匹配研究

产业转型升级发展对专业技能型人才的需求发生变化,作为技能型人才重要培养主体的高职院校,面临着如何培养新时代高素质技能人才的挑战。通过招聘大数据挖掘电子商务技能型人才的需求特征,同时调研相关高职院校电子商务专业人才培养现状,分析供需匹配度。结果表明:电商企业需要德技并修的高素质技能型人才,而高职院校的课程体系以专业技能、商务技能等硬技能教学为主,忽视综合素养软技能教育,同时,高职院校电子商务专业课程开设未能根据行业技术更新和产业转型发展及时调整。基于研究结果,从课程体系建设、校企合作深化、工匠精神培育等方面提出相关建议。     

下一代互联网:OpenFlow-Kmeans流表聚类算法

互联网的发展,对传输质量要求越来愈高,本文针对OpenFlow流表转发,提出并实现OpenFlow-Kmeans流表聚类转发算法,该算法提升准确率27.64%,实验表明,该算法能够满足复杂环境下,对流表的分类转发需求。     

财权和事权相匹配关系研究

在政府间财政关系中,财权和事权的匹配是主要的财政关系之一,明确财权和事权的划分,保证财权和事权相匹配是我国财税改革的关键。然而,当前政府间财权和事权划分不明确,导致了财权上移、事权下放等问题,没有达到真正意义上的匹配。文中在此回顾各方意见,总结政府间财权与事权的理论依据和存在的问题,并对现阶段的改革对政府间财权事权关系的影响做了简要评述。     

基于供应链的物流企业战略匹配能力研究

文中通过回顾之前对物流能力所作的研究及相关理论背景的基础上，认为物流企业战略匹配能力是企业物流能力的一个重要方面，并做了简单的探讨分析，丰富了对物流企业能力的研究。     

基于人工免疫的乳品供应链质量安全风险预警研究

针对日益凸显的乳品质量安全问题,建立及时有效的乳品预警机制已经变得至关重要。文中从供应链的角度构建乳品质量安全风险指标体系。结合人工免疫及负选择算法并加以改进,建立基于人工免疫的乳品质量安全风险模型,并对某乳品企业的乳品质量安全风险进行了预警分析。研究结果表明文中建立的乳品质量安全风险预警模型能够定量分析乳品质量安全状态并有效预警,为实施乳品安全供应链监管提供了新思路和方法。     

GIS在矿产资源经济价值评估中的应用

随着地理信息科学的发展,GIS(地理信息系统)已经运用于许多行业。在地质矿产领域,以往GIS以基本的叠加、缓冲、插值等应用,主要研究地学数据库如何建立。在矿产资源基础空间据库建立的基础上,去发掘数据库具有价值的隐藏信息,丰富数据库深层次的数据处理功能,并建立矿产资源基础空间数据库,多对象影响下的矿产资源经济价值模型的建立与算法分析,为矿产资源经济价值的评估提供更丰富的科学依据。     

Optimal capacity and operation design of a robot logistics system for the hotel industry

This study introduces an optimal capacity and operation design of a robot logistics system that can reduce human workload in the hotel industry. In hotels, there are several duties that can be replaced by robots such as accompanying guests to the certain areas, delivering specific items to the guest rooms, and transporting some items that guests want to be removed from the guest rooms. To apply the robot logistics system in the hotel industry, the capacity and operation design should be prepared adequately. For that, a mathematical model-based optimization technique is used to decide the number of robots with the concept of minimizing total investment cost and to derive the optimal job assigning with the purpose of maximizing total covered jobs. In addition, a numerical example is performed to validate the proposed mathematical model and the sensitivity tests are examined to reflect the random features.     

基于改进粒子群算法的无人机航迹规划

针对当前基本粒子群算法无人机航迹规划在后期收敛速度比较慢、效率不高、易陷入局部最优等问题,提出一种改进粒子群算法。首先,在迭代前期和后期分段设置惯性权值的调整,实现粒子惯性和寻优行为的平衡;其次,设置一个定值与相邻2次适应度函数最优值比较策略,防止陷入局部最优;最后,引入遗传算法的交叉、变异机制,得出更优的结果。并通过仿真验证了改进粒子群算法在三维空间航迹规划的有效性和可行性。结果表明,与其他航迹规划算法相比,新算法具有路径长度更短、耗时更少、路径更平滑等优点,加快了收敛速度,提高了航迹规划效率和稳定性。因此,改进算法的航迹规划可得到满足约束关系的最优航迹,对实现自主飞行有重要的参考价值。     

An extended likelihood framework for modelling discretely observed credit rating transitions

The estimation of the parameters of a continuous-time Markov chain from discrete-time observations, also known as the embedding problem for Markov chains, plays in particular an important role for the modeling of credit rating transitions. This missing data problem boils down to a latent variable setting and thus, maximum likelihood estimation is usually conducted using the expectation-maximization (EM) algorithm. We illustrate that the EM algorithm is likely to get stuck in local maxima of the likelihood function in this specific problem setting and adapt a stochastic approximation simulated annealing scheme (SASEM) as well as a genetic algorithm (GA) to combat this issue. Above that, our main contribution is to extend our method GA by a rejection sampling scheme, which allows one to derive stochastic monotone maximum likelihood estimates in order to obtain proper (non-crossing) multi-year probabilities of default. We advocate the use of this procedure as direct constrained optimization (of the likelihood function) will not be numerically stable due to the large number of side conditions. Furthermore, the monotonicity constraint enables one to combine structural knowledge of the ordinality of credit ratings with real-life data into a statistical estimator, which has a stabilizing effect on far off-diagonal generator matrix elements. We illustrate our methods by Standard and Poor’s credit rating data as well as a simulation study and benchmark our novel procedure against an already existing smoothing algorithm.