星载大容量固态存储控制器的级联编码设计

航天器大容量数据存储设备主要采用基于NAND Flash的固态存储器,但由于空间环境中单粒子翻转效应的影响,以及存储器芯片在操作过程中因为阈值电压偏移导致的位比特错误等原因,存储设备的可靠性降低。为提高数据存储设备的数据容错性,依据NAND Flash芯片物理结构和数据存储结构,具有针对性地提出RS(256,252)码+LDPC(8192,7154)码级联的纠检错并行编码设计,并优化编码算法的电路实现方法。建模仿真和地面测试系统测试结果表明:该设计具有低硬件开销、低功耗和高可靠性的优点。存储系统的数据总容量达512 Gb,有效数据吞吐率为700 Mb/s,能够满足航天器固态存储控制器对大容量数据控制和高数据吞吐量的设计需求。     

维度汇总性问题及其对策

在联机分析处理中,为了提高查询的响应速度,预聚合是一种常用的方法,但在已有的研究中,关于维度汇总性的研究还相当少。从维度汇总性的基本概念及其分类出发,对维度汇总性的判断方法进行了研究,最后还给出了处理维度汇总性问题时的一些对策。     

基于镜像的高可用数据对象布局算法

镜像是提高数据可用性的流行方法。借鉴RAID的方法,在算法一级实现数据的冗余分布,提出基于镜像的高可用数据对象布局算法。在数据对象和存储节点失效时,利用冗余数据重构数据对象和存储节点,有效保证存储系统的高可用性。采用马尔可夫激励模型对存储系统进行定量的可用性分析,计算结果表明该方法是有效的。     

基于卷积神经网络的卫星网络协调态势评估方法

为充分发掘利用海量卫星网络数据,提高决策效率,加强空间频轨资源获取与储备的分析手段,尤其是对地球静止轨道资源的协调获取问题,提出基于机器学习算法的卫星网络态势评估策略。通过对卫星网络协调因素进行特征分析,选择卷积神经网络(Convolution Neural Network, CNN)为目标算法模型,并建立算法模型的训练数据集及Label规则,采用分裂信息增益度量方法对数据进行降维处理,建立CNN评估模型,并进行了验证分析。结果表明,CNN模型对卫星网络协调态势评估问题测试的正确率高达80%以上,具有较高的评估效能。随着数据量的增多,CNN评估效果逐步提升,是一种在卫星网络协调态势分析、资源储备的有效评估方法。     

Transactional and in-store display data of a large supermarket for data-driven decision-making

This article describes daily and monthly transactional and in-store display data of a large supermarket from January to October in 2019 associated with 28 757 stock-keeping units (SKUs) in 5 categories and 41 subcategories. The database contains five parts, including information about each SKU, in-store display, daily sales, inventory, and replenishment. We also propose some research questions related to assortment planning, pricing, inventory management, and customer behavior. Researchers are welcome to develop data-driven models or other innovative methods to address these questions or other practical problems using this database.     

基于双星编队SAR的差分干涉研究

结合系统特点,分析了利用双星编队SAP,进行差分干涉测量的特殊性和优越性,对双星编队SAR的立体基线进行分解,得到了差分干涉的有效基线分量,建立了双星编队SAR的差分干涉模型,并利用冗余图像采用数据融合的方法提高了测量精度,用地形形变量检测的仿真实验验证了模型和方法的正确性和有效性.     

Capacitated warehouse location model with risk pooling

In this article, we introduce the capacitated warehouse location model with risk pooling (CLMRP), which captures the interdependence between capacity issues and the inventory management at the warehouses. The CLMRP models a logistics system in which a single plant ships one type of product to a set of retailers, each with an uncertain demand. Warehouses serve as the direct intermediary between the plant and the retailers for the shipment of the product and also retain safety stock to provide appropriate service levels to the retailers. The CLMRP minimizes the sum of the fixed facility location, transportation, and inventory carrying costs. The model simultaneously determines warehouse locations, shipment sizes from the plant to the warehouses, the working inventory, and safety stock levels at the warehouses and the assignment of retailers to the warehouses. The costs at each warehouse exhibit initially economies of scale and then an exponential increase due to the capacity limitations. We show that this problem can be formulated as a nonlinear integer program in which the objective function is neither concave nor convex. A Lagrangian relaxation solution algorithm is proposed. The Lagrangian subproblem is also a nonlinear integer program. An efficient algorithm is developed for the linear relaxation of this subproblem. The Lagrangian relaxation algorithm provides near‐optimal solutions with reasonable computational requirements for large problem instances. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

What you should know about location modeling

Facility location models have been applied to problems in the public and private sectors for years. In this article, the author first presents a taxonomy of location problems based on the underlying space in which the problem is embedded. The article illustrates problems from each part of the taxonomy with an emphasis on discrete location problems. Selected recent research in the area is also discussed. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Analysis and optimal design of discrete order picking technologies along a line

Order picking accounts for most of the operating expense of a typical distribution center, and thus is often considered the most critical function of a supply chain. In discrete order picking a single worker walks to pick all the items necessary to fulfill a single customer order. Discrete order picking is common not only because of its simplicity and reliability, but also because of its ability to pick orders quickly upon receipt, and thus is commonly used by e‐commerce operations. There are two primary ways to reduce the cost (walking distance required) of the order picking system. First is through the use of technology—conveyor systems and/or the ability to transmit order information to pickers via mobile units. Second is through the design—where best to locate depots (where workers receive pick lists and deposit completed orders) and how best to lay out the product. We build a stochastic model to compare three configurations of different technology requirements: single‐depot, dual‐depot, and no‐depot. For each configuration we explore the optimal design. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

The logistic–exponential survival distribution

For various parameter combinations, the logistic–exponential survival distribution belongs to four common classes of survival distributions: increasing failure rate, decreasing failure rate, bathtub‐shaped failure rate, and upside‐down bathtub‐shaped failure rate. Graphical comparison of this new distribution with other common survival distributions is seen in a plot of the skewness versus the coefficient of variation. The distribution can be used as a survival model or as a device to determine the distribution class from which a particular data set is drawn. As the three‐parameter version is less mathematically tractable, our major results concern the two‐parameter version. Boundaries for the maximum likelihood estimators of the parameters are derived in this article. Also, a fixed‐point method to find the maximum likelihood estimators for complete and censored data sets has been developed. The two‐parameter and the three‐parameter versions of the logistic–exponential distribution are applied to two real‐life data sets. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008