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This study investigates the effects of transmission losses, constraints and increased renewable energy penetration on planning energy storage allocation and investment. By modifying a DC optimal power flow model using a linearised approximation for ohmic losses, the authors were able to understand which network characteristic or inhibitor drives the most change in expanding utility-scale storage. Four different storage technologies were explored: compressed air energy storage, pumped hydro storage, lithium-ion battery and fly wheel. Each had different charging, capacity and cost characteristics. The results of the storage allocation trials revealed that network congestion was a more influential network inhibitor than were line losses. Losses only had substantial effects on a free-flowing network but produced marginal changes in allocation in congested ones. The conclusion of the investment trials revealed two things: (i) storage investment is not significantly affected by transmission constraints so long as renewable generation stays constant and relatively low,(ii) more flexible technologies like flywheels are favoured at lower volumes of renewable penetration for their load balancing capabilities while cheaper technologies are best as the volume of renewable power generated increases. [ABSTRACT FROM AUTHOR]

Abstract This paper considers the linear output regulation problem for uncertain over-actuated plants. The general form of input redundancy considered in this work implies the existence of multiple control inputs and state trajectories compatible with a prescribed reference for the output. On-line selection, according to certain performance criteria, of the most suitable of these inputs-state trajectories leads to a linear output regulation problem with dynamic redundancy allocation. We present a solution that augments the well known internal model control scheme with two additional dynamical systems. The first one, named annihilator , parametrizes the inputs and the corresponding state trajectories that are invisible from the output. The second one, named redundancy allocator , dynamically selects the best solution according to a predefined performance criterion. We derive explicit solutions for the performance criterion equal to relaxed 1, 2, and ∞ - norms of the plant input. This set-up is a particular case of the dynamic redundancy allocation problem named dynamic input allocation. The proposed solutions can be implemented in an error feedback form and are especially suitable for optimizing sparsity, power and amplitude of the control input. Finally, structural stability, robustness and existence of a unique steady-state are proven. [ABSTRACT FROM AUTHOR]

The growing demands of large-capacity flash-based storages have facilitated the downscaling process of NAND flash memory. However, the downscaling of traditional planar floating-gate flash memory faces several challenges. Therefore, new NAND flash technologies have been explored to provide larger capacity with low cost. Among these new technologies, the 3-D charge-trap flash is regarded as one of the most promising candidates. The 3-D charge-trap flash is composed of several gate-stack layers and vertical cylindrical channels to provide high-density and low cell-to-cell interference. Owing to the cylindrical geometry of vertical channels, the access performance of each page in one block is distinctive, and this situation is exacerbated in the 3-D charge-trap flash with the fast-growing number of gate-stack layers. In this paper, a progressive performance boosting strategy is proposed to boost the performance of 3-D charge-trap flash by utilizing its asymmetric page access speed feature. A series of experiments was conducted to demonstrate the capability of the proposed strategy on improving the access performance of 3-D charge-trap flash. [ABSTRACT FROM AUTHOR]

Recall decreases across a series of subspan immediate-recall trials but rebounds if the semantic category of the words is changed, an example of release from proactive interference (RPI). The size of the rebound depends on the semantic categories used and ranges from 0% to 95%. We used a corpus of novels to create vectors representing the meaning of about 40,000 words using the BEAGLE algorithm. The distance between categories and spread within categories jointly predicted the size of the RPI. We used a holographic model for recall equipped with a lexicon of BEAGLE vectors representing the meaning of words. The model captured RPI using a hologram as an interface to bridge information from episodic and semantic memory; it is the first account of RPI to capture release at the level of individual words in categorized lists. [ABSTRACT FROM AUTHOR]

Purpose The contemporary e-tailing marketplace insists that distribution centers are playing the roles of both wholesalers and retailers which require different storage-handling load sizes due to different product variants. To fulfill piecewise retail orders, a separate small size-fast pick area is design called “forward buffer” wherein pallets are allocated from reserve area. Due to non-uniform pallets, the static allocation policy diminishes forward space utilization and also, more than practically required buffer size has been identified as wastage. Thus, dynamic storage allocation policy is required to design for reducing storage wastage and improving throughput considering non-uniform unit load sizes. The purpose of this paper is to model such policy and develop an e-decision support system assisting enterprise practitioners with real-time decision making.Design/methodology/approach The research method is developed as a dynamic storage allocation policy and mathematical modeled as knapsack-based heuristics. The execution procedure of policy is explained as an example and tested with case-specific data. The developed model is implemented as a web-based support system and tested with rational data instances, as well as overcoming prejudices against single case findings.Findings The provided model considers variable size storage-handling unit loads and recommends number of pallets allocations in forward area reducing storage wastes. The algorithm searches and suggests the “just-right” amount of allocations for each product balancing existing forward capacity. It also helps to determine “lean buffer” size for forward area ensuring desired throughput. Sensitivity and buffer performance analysis is carried out for Poisson distributed data sets followed by research synthesis.Practical implications Warehouse practitioners can use this model ensuring a desired throughput level with least forward storage wastages. The model driven e-decision support system (DSS) helps for effective real-time decision making under complicated business scenarios wherein products are having different physical dimensions. It assists the researchers who would like to explore the emerging field of “lean” adoption in enterprise information and retail-distribution management.Originality/value The paper provides an inventive approach endorsing lean thinking in storage allocation policy design for a forward-reserve model. Also, the developed methodology incorporating features of e-DSS along with quantitative modeling is an inimitable research contribution justifying rational data support. [ABSTRACT FROM AUTHOR]

Cloud computing delivers resources and services through virtual machines on a pay-as-you-go basis. The allocation of storage space to users is usually determined by means of open allocation mechanisms that cannot guarantee an efficient allocation. Current allocation mechanisms do not consider user requests when making provisioning decisions. In other words, they assume that the storage spaces are fixed. In this study, we propose an algorithm for allocating storage spaces based on the requests of users. We present a unified storage allocation scheme (USAS) for cloud computing. USAS is a dynamic storage allocation framework for unlimited, limited, and free users. Our proposed approach is based on a storage partitioning policy, and we have compared our proposed scheme with open storage scheme and fixed storage scheme with common partition. We show through simulation study that USAS dynamically allocates space for different user requirements for all traffic loads. [ABSTRACT FROM AUTHOR]

As the era of big data is coming, more and more users choose to store data in the cloud. Cloud storage provides users with flexible, dynamic and cost effective data storage service. However, the new paradigm of service introduces new security challenges such as users loss control of the remote data and they cannot ensure data integrity in the cloud. Moreover, supporting dynamic data updates is also a practical requirement of cloud storage. It is imperative to provide an efficient and secure dynamic auditing protocol to check the data integrity in the cloud. In this paper, we first analyze the dynamic performance of some prior works. In order to solve the inefficiency problem caused by the Merkle Hash Tree (MHT) in dynamic update, the Large Branching Tree (LBT) data structure was introduced in our Dynamic Provable Data Possession (DPDP) scheme. LBT structure simplifies the process of updates and supports updating several blocks synchronously, and reduces the auxiliary information during the challenge-respond process as well. Our scheme is able to efficiently support fully dynamic data updates and batch updates. Based on the LBT structure, we use bilinear algebraic maps to optimize the authenticate process. A signature scheme is used to authenticate both the value and the position of data blocks, which reduces computation overhead during the dynamic update phase. The security and performance analysis show that our DPDP scheme is provably secure and efficient. [ABSTRACT FROM AUTHOR]

Purpose The retail revolution swing from traditional distribution to e-tailing services and unprecedented increase in internet adoption insist practitioners to diversely plan warehousing strategies. More than practically required storage space has been identified as wastes, and also it does not improve performance. An organized framework integrating storage design policies, operational performance and customer value improvement for retail-distribution management is lacking. Therefore, the purpose of this paper is to develop broad guidelines to design the “just-right” amount of forward area, i.e., “lean buffer” answering the following questions: “What should be lean buffer size? How effective the forward area is? As per demand variations, which storage waste (SKU) should be allocated with how much storage space? What is the amount of storage waste (SW)? How smooth the material flow is in between reserve-forward area?” for storage allocation in cosmetics distribution centers.Design/methodology/approach After forecasting static storage allocation between two planning horizons, if a particular SKU is less or non-moving, then it will cause SW, as the occupied location can be utilized by other competing SKUs, and also it impedes material flow for an instance. A dynamically efficient and self-adaptive, knapsack instance based heuristics is developed in order to make effective storage utilization.Findings The existing state-of-the-art under study is supported with a distribution center case, and the study investigates the need of a model adopting lean management approach in storage allocation policies along with test results in LINGO. The sensitivity analysis describes the impact of varying demand and buffer size on performance. The results are compared with uniform and exponential distributed demands, and findings reveal that the proposed heuristics improves efficiency and reduce SWs in forward-reserve area.Originality/value The presented model demonstrates a novel thinking of lean adoption in designing storage allocation strategy and its performance measures while reducing wastes and improving customer value. Future research issues are highlighted, which may be of great help to the researchers who would like to explore the emerging field of lean adoption for sustainable retail and distribution operations. [ABSTRACT FROM AUTHOR]

The potential for dynamic storage to serve as a metric of basin behaviour was assessed using data from five drainage basins with headwaters on the thick sand and gravel deposits of the Oak Ridges Moraine in southern Ontario, Canada. Dynamic storage was directly correlated with the ratio of variability of δ2H in streamflow relative to that in precipitation. This ratio has previously been shown to be inversely related to basin mean transit time ( MTT), suggesting an inverse relationship between dynamic storage and MTT for the study basins. Dynamic storage was also directly correlated with interannual variability in stream runoff, baseflow and baseflow:runoff ratio, implying that basins with smaller dynamic storage have less interannual variability in their streamflow regimes. These preliminary results suggest that dynamic storage may serve as a readily derived and useful metric of basin behaviour for inter-basin comparisons. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We consider a map of the unit square which is not 1-1, such as the memory map studied in Góra (Statistical and deterministic dynamics of maps with memory, ). Memory maps are defined as follows: $$x_{n+1}=M_{\alpha }(x_{n-1},x_{n})=\tau (\alpha \cdot x_{n}+(1-\alpha )\cdot x_{n-1}),$$ where $$\tau $$ is a one-dimensional map on $$I=[0,1]$$ and $$0<\alpha <1$$ determines how much memory is being used. In this paper we let $$\tau $$ to be the symmetric tent map. To study the dynamics of $$M_\alpha $$ , we consider the two-dimensional map The map $$G_\alpha $$ for $$\alpha \in (0,3/4]$$ was studied in Góra (Statistical and deterministic dynamics of maps with memory, ). In this paper we prove that for $$\alpha \in (3/4,1)$$ the map $$G_\alpha $$ admits a singular Sinai-Ruelle-Bowen measure. We do this by applying Rychlik's results for the Lozi map. However, unlike the Lozi map, the maps $$G_\alpha $$ are not invertible which creates complications that we are able to overcome. [ABSTRACT FROM AUTHOR]

This article defines a new dynamic storage assignment problem (DSAP) and develops an integrated mechanism for optimization purpose, based on the ABC classification and mutual affinity of products. A product affinity-based heuristic (PABH)-a technique based on data mining-is developed for calculation of pairwise relationships between products. It is shown that the analytical and multi-parametric DSAP is a quadratic assignment problem (QAP) and thus non-deterministic polynomial-time (NP)-hard. A greedy genetic algorithm (GA) is therefore developed for handling the computational complexity of the DSAP. Performance comparisons between the new approach and the traditional ABC classification method are conducted. The experimental results show that a preferred storage assignment approach is to simultaneously maximize the sum of affinity values and the product of zone indicators and order frequencies based on traditional ABC classification. The experiments on a distribution center of a family care product manufacturer indicate 7.14 to 104.48 % improvement in the average order picking time. [ABSTRACT FROM AUTHOR]

In this paper we focus on two scheduling problems in container terminal: (i) the Yard Truck Scheduling Problem (YTSP) which assigns a fleet of trucks to transport containers between the QCs and the storage yard to minimize the makespan, (ii) the integrated Yard Truck Scheduling Problem and Storage Allocation Problem (YTS–SAP) which extends the first problem to consider storage allocation strategy for discharging containers. Its object is to minimize the total delay for all jobs. The second model is improved to consider the truck ready time. Due to the computational intractability, two recently developed solution methods, based on swarm intelligence technique, are developed for problem solution, namely, particle swarm optimization (PSO) and bacterial colony optimization (BCO). As these two algorithms are originally designed for continuous optimization problems, we proposed a particular mapping method to implement them for YTSP and YTS–SAP, both of which are discrete optimization problems. Through comparing the PSO algorithms and BCO algorithm with GA by an experiment conducted on different scale instances, we can draw a conclusion that LPSO perform best in YTSP while BCO perform best in YTS–SAP. [ABSTRACT FROM AUTHOR]

This work presents a study of the effects of the leakage currents in the control transistors of a dynamic storage cell intended to be used with Bulk-BICS circuits. A means to introduce a controlled discharge current to the storage element is presented, making the dynamic storage cell stable in the reset-state at rest. This self-reset feature allows eliminating the recurrent reset pulse necessary in the previous version for stabilization of the memory cell. A reduction in the current consumption when the circuit is idle is also achieved with this technique. [ABSTRACT FROM AUTHOR]

Storage allocation of outbound containers is a key factor of the performance of container handling system in automated container terminals. Improper storage plans of outbound containers make QC waiting inevitable; hence, the vessel handling time will be lengthened. A simulation-based optimization method is proposed in this paper for the storage allocation problem of outbound containers in automated container terminals (SAPOBA). A simulation model is built up by Timed-Colored-Petri-Net (TCPN), used to evaluate the QC waiting time of storage plans. Two optimization approaches, based on Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), are proposed to form the complete simulation-based optimization method. Effectiveness of this method is verified by experiment, as the comparison of the two optimization approaches. [ABSTRACT FROM AUTHOR]

A method is suggested that allows thermodynamic data to be dynamically stored and retrieved. The purpose of the method is to reduce computer simulation time when Calphad type databases are being used. Some test simulations are presented and these indicate that simulations can be made to run 5–40 times faster without any significant loss of accuracy. [ABSTRACT FROM AUTHOR]

A Supply Hub in Industrial Park (SHIP) is a third-party business entity that leases storage space and logistics services among manufacturers located in the same industrial park. Manufacturers may hire warehouses outside the park if SHIP's storage price is exorbitant. This paper discusses how SHIP and manufacturers interact to optimize their decisions on storage pricing, replenishment, and delivery. A dynamic storage pricing strategy depending on storage length is adopted. This problem is modeled as a bilevel program where the SHIP is the leader and manufacturers are followers. Based on further assumptions, the proposed bilevel model is solved in closed-form. A series of sensitivity analyses are conducted to examine the influences of major cost parameters. The results show that SHIP's delivery charge has little impact on the total cost of large manufacturers, and its increase will not always bring profit improvement to SHIP. Contrary to intuition, the SHIP could attract more space demands from large manufacturers when charging higher in delivery or when the public warehouse's delivery charge is lower, and more space demands from small manufacturers when the market storage price is lower. [ABSTRACT FROM AUTHOR]

Yard truck scheduling and storage allocation problems (YTS-SAP) are two important issues that influence the efficiency of a container terminal. These two problems aim to determine the routing of trucks and proper storage locations for discharging containers from incoming vessels. This paper integrates YTS and SAP as a whole and tries to minimize the weighted summation of total delay and total yard trucks travel time. A genetic algorithm (GA) is proposed to deal with the problem. In the proposed GA, guidance mutation approach and exhaustive heuristic for local searching are used in order to force the GA to converge faster and be steadier. To test the performance of the proposed GA, both small scale and large scale cases are studied. The results of these cases are compared with CPLEX for the small scale cases. Since this problem is an NP-hard problem, which CPLEX cannot solve, a simple GA is studied for comparison in large scale cases. The comparison demonstrates that the proposed GA can obtain near optimal solutions in much shorter computational time for small scale cases. In addition, the proposed GA can obtain better results than other methods in reasonable time for large scale cases. [ABSTRACT FROM AUTHOR]

To guarantee the design quality and improve the design efficiency of mechanical products, taking arc water chamber of steam turbine condenser as example, the paper researches the key technologies in the development process of parametric design system, which can generate both 3D models and associated 2D drawings automatically. Adopting database as the interface of UG and AutoCAD, 2D/3D bidirectional associated relationship is established across platforms. A nonpermanent record is set within the database to save parameters temporarily. Dynamic storage and invocation of parts information is realized by introducing linked- list data structure. Automatic assembly method based on named datum is proposed. Development process and insertion algorithm of modularized geometric figure are also presented. The experimental result shows that this parameter-driven software is a successful application of computer-aided design. [ABSTRACT FROM AUTHOR]

The goal of optimal allocation is to increase stored data availability subject to minimizing the storage budget. Symmetric allocation based on the network coding has been proved to be optimal for distributed storage systems if node availability is not considered. However, because of network conditions and the inherent properties of nodes, each node will have a different availability. This paper focuses on the problem of optimizing distributed data storage when considering node availability. Using a probability model for storage systems, we redefine symmetric allocation in terms of probability-symmetric allocation and propose a probability-symmetric allocation model and strategy based on network coding. These are shown to be optimal in general. Compared with the symmetric allocation scheme proposed by Leong et al., the proposed probability-symmetric allocation scheme not only improves data availability in distributed storage systems but also is more practical. [ABSTRACT FROM AUTHOR]

The viscoelastic behavior of ethylene-propylene-diene (EPDM) reinforced with zinc dimethacrylate (ZDMA) was studied with the use of a rubber process analyzer. ZDMA was in situ prepared in the EPDM matrix through the neutralization reaction of zinc oxide (ZnO) and methacrylic acid (MAA). Strain sweep and frequency sweep tests of uncured and cured samples were performed at different temperatures. The variations of storage modulus (G′) and loss modulus (G′′) against strain or frequency were recorded. Results obtained revealed that the viscoelastic behavior of the composites was influenced remarkably by the loadings of ZDMA. As ZDMA was increased, the initial storage modules (G0′) of the vulcanizates increased, and an apparent Payne effect was observed. However, the Payne effect observed in the uncured compounds was weaker than that in the cured composites. The dynamic storage shear modulus of the filled EPDM had a stronger dependence on strain than that of the unfilled EPDM. There was a synergistic effect between vulcanization and reinforcement of ZDMA on the storage modulus due to the formation of ionic cross-link bonds and homo-PZDMA (poly-ZDMA). In addition, all the samples with various loadings of ZDMA revealed an increase in elasticity with increasing frequency, and those with high ZDMA loadings gave a more time-dependent elastic response. [ABSTRACT FROM AUTHOR]

Dynamic Spectrum Access systems offer temporarily available spectrum to opportunistic users capable of spreading transmissions over a number of non-contiguous subchannels. Such methods can be highly beneficial in terms of spectrum utilization, but excessive fragmentation degrades performance and hence off-sets the benefits. To get some insight into acceptable levels of fragmentation, we present experimental and analytical results derived from a mathematical model. According to the model, a system operates at capacity serving requests for bandwidth by assigning a collection of one or more gaps of unused bandwidth to each request as bandwidth becomes available. Our main result is a proof that, even if fragments can be arbitrarily small, the system remains stable in the sense that the average total number of fragments remains bounded. Within the class of dynamic fragmentation models, including models of dynamic storage allocation that have been around for many decades, this result appears to be the first of its kind. In addition, we provide extensive experimental results that describe behavior, at times unexpected, of fragmentation as parameter values are varied. Different scanning rules for searching gaps of available spectrum, all covered by the above stability result, are also studied. Our model applies to dynamic linked-list storage allocation, and provides a novel analysis in that domain. We prove that, interestingly, a version of the 50 % rule of the classical, non-fragmented allocation model holds for the new model as well. Overall, the paper provides insights into the behavior of practical fragmentation algorithms. [ABSTRACT FROM AUTHOR]

We consider models of queue storage, where items arrive accordingly to a Poisson process of rate λ and each item takes up one cell in a linear array of cells, which are numbered {1, 2, 3,…}. The arriving item is placed in the lowest numbered available cell. The total service rate provided to the items is the constant μ (with ρ = λ/μ), but service may be provided simultaneously to more than one item. If there are 𝒩 items stored and each is serviced at the rate μ/𝒩, this corresponds to processor-sharing (PS). We analyze several models of this type, which have been shown to provide bounds on the PS model. We shall assume that (1) the server works only on the leftmost item, (2) on the two rightmost items, or (3) on all items by the PS discipline, but with a departure of the rightmost item causing a rearrangement of the items within the cells, so that the wasted space remains unchanged. The set of occupied cells at any time is {i 1, i 2,…, i 𝒩} where i 1 < i 2 < …