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.

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.

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.

Modelling of Energy Storage Photonic Medium by Wavelength-Based Multivariable Second-Order Differential Equation

Wavelength-dependent mathematical modelling of the differential energy change of a photon has been performed inside a proposed hypothetical optical medium.The existence of this medium demands certain mathematical constraints,which have been derived in detail.Using reverse modelling,a medium satisfying the derived conditions is proven to store energy as the photon propagates from the entry to exit point.A single photon with a given intensity is considered in the analysis and hypothesized to possess a definite non-zero probability of maintaining its energy and velocity functions analytic inside the proposed optical medium,despite scattering,absorption,fluorescence,heat generation,and other nonlinear mechanisms.The energy and velocity functions are thus singly and doubly differentiable with respect to wavelength.The solution of the resulting second-order differential equation in two variables proves that energy storage or energy flotation occurs inside a medium with a refractive index satisfying the described mathematical constraints.The minimum-value-normalized refractive index profiles of the modelled optical medium for transformed wavelengths both inside the medium and for vacuum have been derived.Mathematical proofs,design equations,and detailed numerical analyses are presented in the paper.

Harmonic Retrieval Embedded in Hybrid Colored Noise: a Novel Pisarenko Method Based on Cross high order Cumulant

Spectral estimation method is an effective method in the case of parameter estimation of sinusoid signal in noises.It always applies cross spectral estimation theory and high order self spectral estimation methods up to now.Yule Walker equation based on cross fourth order cumulant is developed and Pisarenko method is provided in this paper.Simulation results show that the method is effective to retrieve sinusoid signal frequencies from hybrid colored noises and has good performance.

Organic fast ion-conductor with ordered Li-ion conductive nano-pathways and high ionic conductivity for electrochemical energy storage

Solid electrolyte(SE)is the most crucial factor to fabricate safe and high-performance all-solid-state lithium-ion batteries.However,the most commonly reported SE,including solid polymer electrolyte(SPE)and inorganic oxides and sulfides,suffer problems of low ionic conductivity at room temperature for SPE and large interfacial impedance with electrodes for inorganic electrolytes.Here we for the first time demonstrate a novel ionic plastic crystal lithium salt solid electrolyte(OLiSSE)fast ion-conductor dilithium(1,3-diethyl-4,5-dicarboxylate)imidazole bromide with ordered Li-ion conductive nanopathways and an exceptional ionic conductivity of 4.4×10^(−3)Scm^(−1)at 30℃.The prepared OLiSSE exhibits apparent characters of typical ionic plastic crystals in the temperature range of−20 to 70℃,and shows remarkable thermal stability and electrochemical stability below 150℃ and 4.7 V,respectively.No lithium dendrite or short circuit behavior is detected for the Li|OLiSSE|Li cell after the galvanostatic charge-discharge test for 500 h.The fabricated Li|OLiSSE|LiFePO_(4) all-solid-state cell without using any separator and liquid plasticizer directly delivers an initial discharge capacity of 151.4 mAh g^(−1) at the discharge rate of 0.1 C,and shows excellent charge-discharge cycle stability,implying large potential application in the next generation of safe and flexible all-solid-state lithium batteries.

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.

Retrieval of high-order susceptibilities of nonlinear metamaterials

Active metamaterials embedded with nonlinear elements are able to exhibit strong nonlinearity in microwave regime.However, existing S-parameter based parameter retrieval approaches developed for linear metamaterials do not apply in nonlinear cases. In this paper, a retrieval algorithm of high-order susceptibilities for nonlinear metamaterials is derived.Experimental demonstration shows that, by measuring the power level of each harmonic while sweeping the incident power,high-order susceptibilities of a thin-layer nonlinear metamaterial can be effectively retrieved. The proposed approach can be widely used in the research of active metamaterials.

OPTICAL STORAGE MECHANISM AND HIGH-ORDER DIFFRACTION PROPERTIES OF NITROAZOBENZENE-CONTAINING POLYESTER FILMS

Using Nd:YAG second harmonic pulse (100 ps), the optical storage properties of two novel polyesters, poly [4'-bis (N, N-oxyethylene) imino-4-nitroazobenzene succinyl] and poly [2'-chloro-4'-bis (N, N-oxyethylene) imino-4-nitroazobenzene succinyl] have been studied by multiwave mixing. The high-order diffractions of the orientation gratings induced by anisotropy via the reorientation of nitroazobenzene groups and optical information storage with long-term stability have been realized by multiwave mixing in their films. Up to 3rd order forward diffraction was detected in two wave mixing, while up to 4th order backward diffraction was observed in degenerated four wave mixing. The recording mechanism was explained by the trans-cis-trans isomerization cycles of azobenzene groups. The isomerization of these azobenzene groups probably undergoes with inversion mechanism under the experimental conditions. The information recorded in these films has been kept for more than 6 months.

Financial Derivatives Market and Storage Management

It’s known to all that under ideal condition the s to rage cost is kept in lower level when storage management be arranged by Economic Order Quantity(EOQ).Does this mean that any companies should set up their own storing system in proportion to the scale of the commodities’ producing or sell ing Furthermore, even if they manage storage in EOQ, because of different oper ation scale, geographical condition or ability borrowing money from financial ma rket, different companies pay unequal cost in storing the same commodity.In thi s paper, except for supplying commodities from our own storage system, the autho rs have analyzed other two supplying ways without whole storage system, they are forward contracts and futures contracts.The authors have discussed variable su pply cost for above different supply measures.According to the cost of each sup ply way, the managers can choose the most economical way in supplying the commod ity and predict the price of futures from storage management arranged by EOQ.Th e summary content is as follow: 1. The comparing of supply cost between forward contracts and storing system a rranged by EOQ. (1) The supply cost from forward contracts (2) The supply cost from storage system arranged by Economic Order Quantity (3) The application example for comparing cost in different supply way 2.The comparing of supply cost between futures going physical and storing syst em arranged by Economic Order Quantity. (1) The supply cost from futures going physical (2) The correlation between futures contracts and storage management arranged b y EOQ (3) The application example for comparing cost in different supply way 3.How does storing system of scale economic affect the price of forward and fu tures contracts (1) How does the price of forward and futures contracts fluctuate (2) How do we calculate the price of a commodity at future point from the cost of scale economic storing (3) How do we operate efficiently in derivatives market by using the cost of sc ale economic storing (4) The application example for analyzing the price of futures 4.The correlation among storage managementforward contracts and futures mark et.

Gulong shale oil enrichment mechanism and orderly distribution of conventional–unconventional oils in the Cretaceous Qingshankou Formation,Songliao Basin,NE China

Through the study of organic matter enrichment,hydrocarbon generation and accumulation process of black shale of the Cretaceous Qingshankou Formation in the Songliao Basin,the enrichment mechanism of Gulong shale oil and the distribution of conventional–unconventional oil are revealed.The Songliao Basin is a huge interior lake basin formed in the Early Cretaceous under the control of the subduction and retreat of the western Pacific plate and the massive horizontal displacement of the Tanlu Fault Zone in Northeast China.During the deposition of the Qingshankou Formation,strong terrestrial hydrological cycle led to the lake level rise of the ancient Songliao Basin and the input of a large amount of nutrients,resulting in planktonic bacteria and algae flourish.Intermittent seawater intrusion events promoted the formation of salinization stratification and anoxic environment in the lake,which were beneficial to the enrichment of organic matters.Biomarkers analysis confirms that the biogenic organic matter of planktonic bacteria and algae modified by microorganisms plays an important role in the formation of high-quality source rocks with high oil generation capability.There are four favorable conditions for the enrichment of light shale oil in the Qingshankou Formation of the Gulong Sag,Songliao Basin:the moderate organic matter abundance and high oil potential provide sufficient material basis for oil enrichment;high degree of thermal evolution makes shale oil have high GOR and good mobility;low hydrocarbon expulsion efficiency leads to a high content of retained hydrocarbons in the source rock;and the confinement effect of intra-layer cement in the high maturity stage induces the efficient accumulation of light shale oil.The restoration of hydrocarbon accumulation process suggests that liquid hydrocarbons generated in the early(low–medium maturity)stage of the Qingshankou Formation source rocks accumulated in placanticline and slope after long-distance secondary migration,forming high-quality conventional and tight oil reservoirs.Light oil generated in the late(medium–high maturity)stage accumulated in situ,forming about 15 billion tons of Gulong shale oil resources,which finally enabled the orderly distribution of conventional–unconventional oils that are contiguous horizontally and superposed vertically within the basin,showing a complete pattern of“whole petroleum system”with conventional oil,tight oil and shale oil in sequence.

有序介孔炭负载Pt-MoO_(x)催化剂的制备及其催化甲基环己烷脱氢性能

以有序介孔炭(CMK-3)作为载体,采用原子层沉积技术制备出催化剂y Pt CMK-3及MoO_(x)助剂调控催化剂y Pt-z MoO_(x)CMK-3(y、z分别为Pt和MoO_(x)的沉积循环次数),研究了沉积循环次数对Pt金属分散度和催化剂甲基环己烷脱氢性能的影响。结果表明,适中的Pt分散度和适量原子级分散的MoO_(x)助剂能显著提升Pt基催化剂的性能。与10Pt CMK-3相比,10Pt-1MoO_(x)CMK-3催化剂上的脱氢速率(单位时间内单位质量Pt产生H_(2)的物质的量)从79.02 mol(g·h)提高至97.88 mol(g·h),甲基环己烷转化率由71%提高到91%。MoO_(x)助剂加入对Pt颗粒分散度影响较小,主要提高了Pt表面电子密度,降低了催化剂的起活温度。此外,MoO_(x)助剂还通过氢溢流促进H_(2)在催化剂表面的脱附,从而提高H_(2)产率。

支持策略检索的属性基可搜索加密方案

为解决现有属性基可搜索加密方案仅支持单关键词检索或联合多关键词检索的问题,提升用户检索的灵活性,提出一种支持策略检索的属性基可搜索加密方案。使用LSSS(linear secret sharing schemes)技术构造用户检索陷门,支持任意单调布尔公式表示的搜索策略。结合属性加密实现对密文细粒度的访问控制。通过与现有方案进行计算和存储效率的对比分析,并进行实验仿真,结果表明,提出的方案在效率和安全性方面均有显著提升。

考虑订单拆分策略的AGV拣选效率优化方法

为提高智能仓库系统中AGV的拣选效率,针对AGV订单拣选优化问题分为AGV-货架任务分配、多AGV无冲突路径规划两个子问题进行研究,根据订单特点引入订单拆分策略,并以最小化AGV完成所有订单的总时间为目标构建数学模型。首先,设计了确定货架优先级的AGV-货架任务分配算法(AGV-shelf task allocation algorithm, ASTA)求解匹配问题。然后,提出一种带有贪婪参数并嵌入冲突消解策略的改进Q-Learning算法,得到拆分策略下最优无冲突拣选路径方案。最后,通过在40 m×40 m仓库布局中的订单集数值实验对比分析,所提算法与现有的两种算法对比结果显示,AGV完成所有订单的总时间分别平均减少11.63%和26.74%,验证了拆分策略的有效性,并且通过AGV使用数量、完成订单时间和路径冲突等待时间占比三个指标的对比验证了拆分策略和所提算法能有效缓解拥堵情况,减少行驶路径长度,提高拣选效率。此外,针对AGV数量灵敏度分析,在不同数量的AGV对行驶时间和路径冲突等待时间的影响方面,发现19台AGV数量是最佳配置,验证了模型的可行性和算法的有效性。

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。