X-RESTORE: Middleware for XML's Relational Storage and Retrieve

We propose a new approach to store and query XML data in an RDBMS basing on the idea of the numbering scheme and inverted list. O ur approach allows us to quickly determine the precedence, sibling and ancestor/ descendant relationships between any pair of nodes in the hierarchy of XML, and utilize path index to speed up calculating of path expressions. Examples have de monstrated that our approach can effectively and efficiently support both XQuery queries and keyword searches. Our approach is also flexible enough to support X ML documents both with Schema and without Schema, and applications both retrieva l and update. We also present the architecture of middleware for application acc essing XML documents stored in relations, and an algorithm translating a given X ML document into relations effectively.

Water storage changes in North America retrieved from GRACE gravity and GPS data

As global warming continues,the monitoring of changes in terrestrial water storage becomes increasingly important since it plays a critical role in understanding global change and water resource management.In North America as elsewhere in the world,changes in water resources strongly impact agriculture and animal husbandry.From a combination of Gravity Recovery and Climate Experiment（GRACE） gravity and Global Positioning System（GPS） data,it is recently found that water storage from August,2002 to March,2011 recovered after the extreme Canadian Prairies drought between 1999 and 2005.In this paper,we use GRACE monthly gravity data of Release 5 to track the water storage change from August,2002 to June,2014.In Canadian Prairies and the Great Lakes areas,the total water storage is found to have increased during the last decade by a rate of 73.8 ± 14.5 Gt/a,which is larger than that found in the previous study due to the longer time span of GRACE observations used and the reduction of the leakage error.We also find a long term decrease of water storage at a rate of-12.0 ± 4.2 Gt/a in Ungava Peninsula,possibly due to permafrost degradation and less snow accumulation during the winter in the region.In addition,the effect of total mass gain in the surveyed area,on present-day sea level,amounts to-0.18 mm/a,and thus should be taken into account in studies of global sea level change.

Travel time and alternative configurations analysis for automated storage/retrieval systems based on geometrical method

In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-based analytical model is presented.The model can be used to compute the expected single-command and dual-command travel time for a storage/retrieval(S/R)machine which can travel simultaneously horizontally and vertically as it moves along a storage aisle.The rack may be either square in time or non square in time.Additionally,the alternative layouts of the AS/RS and travel-time models are examined.Comparing with setting the I/O point at the left-lower corner of the rack,setting the I/O point at any point at the vertical edge can help enhance the efficiency of the AS/RS.

The Cloud Storage Ciphertext Retrieval Scheme Based on ORAM

Due to its characteristics distribution and virtualization, cloud storage also brings new security problems. User＇s data is stored in the cloud, which separated the ownership from management. How to ensure the security of cloud data, how to increase data availability and how to improve user privacy perception are the key issues of cloud storage research, especially when the cloud service provider is not completely trusted. In this paper, a cloud storage ciphertext retrieval scheme based on AES and homomorphic encryption is presented. This ciphertext retrieval scheme will not only conceal the user retrieval information, but also prevent the cloud from obtaining user access pattern such as read-write mode, and access frequency, thereby ensuring the safety of the ciphertext retrieval and user privacy. The results of simulation analysis show that the performance of this ciphertext retrieval scheme requires less overhead than other schemes on the same security level.

A Multi-stage Heuristic Algorithm for Matching Problem in the Modified Miniload Automated Storage and Retrieval System of E-commerce

E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.

IOTA-Based Data Encryption Storage and Retrieval Method

At present,the traditional blockchain for data storage and retrieval reflects the characteristics of slow data uploading speed,high cost,and transparency,and there are a lot of corresponding problems,such as not supporting private data storage,large data operation costs,and not supporting Data field query.This paper proposes a method of data encryption storage and retrieval based on the IOTA distributed ledger,combined with the fast transaction processing speed and zero-value transactions of the IOTA blockchain,through the Masked Authenticated Messaging technology,so that the data is encrypted in the data stream.The form is stored in the distributed ledger,quickly retrieved through the field index mechanism established by the data form,and the data operation is carried out on the chain.Experimental results show that this system has high storage,encryption and retrieval performance,and good practicability.

On-Demand Photon Storage and Retrieval with a Solid-State Photon Molecule at Room Temperature

Deterministically achieving on-chip photon storage and retrieval is a fundamental challenge for integrated photonics.Moreover,this requirement is increasingly urgent as photon storage and retrieval is crucial to realize truly scalable room-temperature quantum computing.However,most of existing quantum memories integrated on chips must either work at cryogenic temperature or else are strongly coupled with the environment,which hugely reduces the efficiency.Here,we propose an on-chip room-temperature quantum memory comprising three coupled microcavities,which presents an ideal dark state decoupled by a waveguide,thereby allowing on-demand photon storage and retrieval with high efficiency and high fidelity simultaneously.Furthermore,we demonstrate that the single-photon temporal duration can be increased or decreased by a factor of 10^(3),thereby enabling many crucial quantum applications.Our error-robust approach highlights the potential for a solid-state photonic molecule for use as on-chip quantum memory and for optical quantum computing.

NEW APPROACH TO HARMONIC RETRIEVAL IN NOISE

This paper addresses the harmonic retrieval problem in non-Gaussian ARMA noise. A hybrid ESPRIT approach using second-and third-order statistics is proposed. First, third-order statistics are used to identify the AR part of the non-Gaussian noise process, then the noisy measurements are filtered by AR polynomial, finally, the harmonic signal parameters are estimated. Simulation examples show the effectiveness and high resolution of the new approach.

Loss of Certified Maize (<i>Zea mays</i>L.) and Cowpea (<i>Vigna unguiculata</i>(L.) Walp.) Seed Viability during Storage in a Sub-Saharan Region: Analysis of Environmental Factors

The objective of this study was to characterize environment factors involved in loss of seed viability during storage in open granaries. The temperature and relative humidity of the granary as well as the equilibrium moisture content of seeds were determined monthly. Their effects on the loss of viability of maize (Zea mays L.) and cowpea (Vigna unguiculata (L.) Walp.) seeds were examined. The results showed that relative humidity levels > 65% associated with temperatures > 25°C (conditions in the open granary) do not guarantee safe storage of maize lots for a period of 9 to 12 months. Based on these data and the results of seed viability analysis, local environmental conditions in Gandajika (DR-Congo) and seed genetic background are the main factors for the rapid deterioration of seeds during storage. The germination rate correlated negatively with storage duration (-0.94) and temperature (-0.57) while it correlates positively with the relative humidity (0.58) for both lots of maize analyzed. The same trend was observed with the two-cowpea varieties studied (IT82D-889 and Diamant). Similar work using more varieties in other granaries is required to validate key factors involved in seed viability during storage in targeted regions.

Organic cathode materials for rechargeable magnesium-ion batteries:Fundamentals, recent advances, and approaches to optimization

Rechargeable magnesium-ion batteries(MIBs) are favorable substitutes for conventional lithium-ion batteries(LIBs) because of abundant magnesium reserves, a high theoretical energy density, and great inherent safety. Organic electrode materials with excellent structural tunability,unique coordination reaction mechanisms, and environmental friendliness offer great potential to promote the electrochemical performance of MIBs. However, research on organic magnesium battery cathode materials is still preliminary with many significant challenges to be resolved including low electrical conductivity and unwanted but severe dissolution in useful electrolytes. Herein, we provide a detailed overview of reported organic cathode materials for MIBs. We begin with basic properties such as charge storage mechanisms(e.g., n-, p-, and bipolartype), moving to recent advances in various types of organic cathodes including carbonyl-, nitrogen-, and sulfur-based materials. To shed light on the diverse strategies targeting high-performance Mg-organic batteries, elaborate summaries of various approaches are presented.Generally, these strategies include molecular design, polymerization, mixing with carbon, nanosizing and electrolyte/separator optimization.This review provides insights on exploring high-performance organic cathodes in rechargeable MIBs.

DCRL-KG: Distributed Multi-Modal Knowledge Graph Retrieval Platform Based on Collaborative Representation Learning

The knowledge graph with relational abundant information has been widely used as the basic data support for the retrieval platforms.Image and text descriptions added to the knowledge graph enrich the node information,which accounts for the advantage of the multi-modal knowledge graph.In the field of cross-modal retrieval platforms,multi-modal knowledge graphs can help to improve retrieval accuracy and efficiency because of the abundant relational infor-mation provided by knowledge graphs.The representation learning method is sig-nificant to the application of multi-modal knowledge graphs.This paper proposes a distributed collaborative vector retrieval platform(DCRL-KG)using the multi-modal knowledge graph VisualSem as the foundation to achieve efficient and high-precision multimodal data retrieval.Firstly,use distributed technology to classify and store the data in the knowledge graph to improve retrieval efficiency.Secondly,this paper uses BabelNet to expand the knowledge graph through multi-ple filtering processes and increase the diversification of information.Finally,this paper builds a variety of retrieval models to achieve the fusion of retrieval results through linear combination methods to achieve high-precision language retrieval and image retrieval.The paper uses sentence retrieval and image retrieval experi-ments to prove that the platform can optimize the storage structure of the multi-modal knowledge graph and have good performance in multi-modal space.

基于改进启发式算法的四向穿梭车系统双端预编组研究

四向穿梭车存储系统是一种新型密集存储系统,可以满足电商环境下仓储快速响应的需求。四向库具有双端检索货物的功能,以释放库存潜力并提升出入库的效率。由于系统的多深位特性,出库过程中会涉及额外的检索操作,因此提前对货物进行预编组排序至关重要。针对四向库预编组问题,设计了一种改进的启发式算法,在非高峰出库时段通过双端检索排序使货物达到有序状态,减少出库移动步数和检索时间,从而提高仓储作业的效率。结果表明:相较于L公司现有算法,该算法平均减少了12.82%的移动步数;采用矩形布局和双端出库布局可以进一步减少移动步数,分别平均减少了35.44%和12.82%的移动次数。

混合蛙跳算法在旋转货架货位优化中的应用

以集群旋转式货架存储货物的自动化立体仓库为研究对象,以提高货架整体和运动状态的单层稳定性、货物相关性和出入库效率等基本货位优化原则为目标,提出一种通用性较强的多参数混合蛙跳算法,对多目标优化问题进行建模,使用MATLAB工具进行仿真。通过实验结果的对比可知,多参数混合蛙跳算法比混合蛙跳算法具有一定的优越性,并且对于分析其他问题的适应性较强,对于多目标优化问题具有一定的理论意义。

具有多层级货架的自动小车存取系统排队网建模与分析

为了满足多楼层生产车间之间的物料运输需求,同时减少企业成本,自动存取系统的设计问题变得愈发重要。带有多层级货架的自动小车存取系统因其优秀的吞吐能力和柔性,具有很好的应用前景。为了分析多层车间中带有多层级货架自动小车存取系统并行作业的性能,在分析自动导引小车(AGV)和电梯、伸缩臂作业方式的基础上,构建了半开排队网络模型,并设计了基于近似均值分析法的近似求解算法。该方法首先将半开排队网内部网络分为不同的单独网络模型,并分别重构为等效的闭排队网络模型。这些网络模型最终被聚合成一个节点,与外部的同步节点联合构建闭排队网络模型求解吞吐率。最后,针对内部网络的单独节点进行分析计算,得到其他系统性能指标。通过设计仿真实验,验证了所提方法的有效性和准确性。

自动化立体仓库退库货位优化问题及其求解算法

针对自动化立体仓库出库作业过程中剩余货物退库问题,以堆垛机作业总能耗最小化为目标,以退库货位分配为决策变量,建立了自动化立体仓库退库货位优化模型,提出了基于深度强化学习的自动化立体仓库退库货位优化框架。在该框架内,以立体仓库实时存储信息和出库作业信息构建多维状态,以退库货位选择构建动作,建立自动化立体仓库退库货位优化的马尔科夫决策过程模型;将立体仓库多维状态特征输入双层决斗网络,采用决斗双重深度Q网络(dueling double deep Q-network,D3QN)算法训练网络模型并预测退库动作目标价值,以确定智能体的最优行为策略。实验结果表明D3QN算法在求解大规模退库货位优化问题上具有较好的稳定性。

基于情境法的高校宿舍柜类家具收纳空间优化设计——以桂林理工大学为例

运用情境法对中国高校宿舍柜类家具收纳空间进行优化设计,为大学生解决常见宿舍收纳空间问题。采用实地调研法、无结构式访谈法,建立典型人物角色模型,以此模拟大学生在日常宿舍生活中遇到的收纳问题,借助情境分析解决大学生对宿舍柜类家具收纳空间的需求,并根据获得的需求进行设计实践。设计出满足当代大学生需求的宿舍柜类家具,在具备满足收纳空间大、功能分区明确等需求的同时兼备舒适性。运用情境法发现当代高校宿舍柜类家具使用痛点,进行系统性优化设计。在设计实践中将家具的使用空间进行最大化利用,深化功能分区,并结合人机工程学知识,设计出具备舒适性、功能性且有强大收纳空间的学生宿舍柜类家具。

纳米光纤-半导体量子点分子耦合系统中光孤子的存储与读取

本文解析研究了基于纳米光纤-半导体量子点分子耦合系统中时间光孤子存储和读取.结果表明,由于半导体量子点分子中点间隧穿诱导透明效应,系统中的光吸收被大大抑制.同时,纳米光纤的横向约束能增强光与系统的相互作用,增强的系统非线性响应能平衡色散效应得到稳定的时间光孤子.进一步研究表明,通过关闭和打开点间隧穿耦合,系统中可实现光孤子的高效率和高保真度的存储与读取.上述结果对于固体量子材料中全光信息处理的实际应用具有一定的指导意义和潜在的应用价值.

基于改进人工蜂群算法的四向穿梭车仓储系统货位优化研究

目的针对四向穿梭车仓储系统中多设备并行作业的特点和高效作业的需求,对其货位优化进行研究。方法建立了考虑入库效率、货架稳定性、作业均衡度和货物关联性4个因素的货位分配组合优化模型,设计了改进人工蜂群算法求解该模型。利用多目标Pareto支配解概念生成初始解,融合遗传算法和变邻域搜索算法思想进行解的优化搜索,以提高算法的性能。为更好地确定算法参数,进行了算法参数敏感性试验。针对3种(大、中、小)入库规模和9种不同仓位下的入库,进行了改进人工蜂群算法、遗传算法和蚁群算法3种算法的求解。结果入库规模越大,改进人工蜂群算法优势越明显,大规模下相比遗传算法和蚁群算法,其性能分别提升了13.14%和19.32%;不同仓位下相比另2种算法,其性能提升了6.38%~26.76%。结论文中所建立的货位分配优化模型更接近仓储系统的实际工作状态,所提出的算法能够有效进行入库货位分配,提高了仓库运作效率。

考虑充电的多层级货架自动小车存取系统的资源配置优化

自动小车存取系统是近年来新兴的自动化物流技术,依托自动导引小车(AGV)和升降机的灵活配置,该系统具备较高的吞吐能力与柔性。随着物流需求的不断增长,如何在保持高效运作的同时,最小化系统的投资和能耗成本,成为亟待解决的问题。因此,提出最小化投资成本和平均任务能耗成本的优化目标,构建了以平均任务周期时间和平均空闲AGV数量为双重约束的随机非线性整数规划模型。模型考虑了AGV运行过程中能耗与充电情况的相互影响,并通过排队网模型来近似求解分析系统性能指标。同时为了进一步优化系统配置,将排队网模型的近似求解算法嵌入到启发式算法中进行求解,提升求解效率和解的质量。算例结果验证了所提方法的有效性和准确性,此外,敏感性分析结果为AGV和升降机的参数优化提供了有价值的参考,进一步验证了所提方法的适用性。

浙江省抽水蓄能产业发展的思路与建议

浙江省抽水蓄能站址资源丰富,开发条件优良。该省正全力打造华东抽水蓄能基地,培育发展抽水蓄能产业是浙江省充分发挥抽水蓄能电站综合效益,助力建设新型能源体系的重要抓手。本文全面系统分析了浙江省发展抽水蓄能产业的SWOT分析(优势、劣势、机遇和挑战),提出发展思路和培育方向,最后从建链、强链、补链和延链方面,提出加快建设抽水蓄能基地、培育发展抽水蓄能装备产业、做强抽水蓄能勘测设计与施工建造、推动生态文旅一体化开发运营,打造电站科普与教培中心五方面的发展路径。