Chaos Identification Based on Component Reordering and Visibility Graph

The identification between chaotic systems and stochastic processes is not easy since they have numerous similarities. In this study, we propose a novel approach to distinguish between chaotic systems and stochastic processes based on the component reordering procedure and the visibility graph algorithm. It is found that time series and their reordered components will show diverse characteristics in the ＇visibility domain＇. For chaotic series, there are huge differences between the degree distribution obtained from the original series and that obtained from the corresponding reordered component. For correlated stochastic series, there are only small differences between the two degree distributions. For uncorrelated stochastic series, there are slight differences between them. Based on this discovery, the well-known Kullback Leible divergence is used to quantify the difference between the two degree distributions and to distinguish between chaotic systems, correlated and uncorrelated stochastic processes. Moreover, one chaotic map, three chaotic systems and three different stochastic processes are utilized to illustrate the feasibility and effectiveness of the proposed method. Numerical results show that the proposed method is not only effective to distinguish between chaotic systems, correlated and uncorrelated stochastic processes, but also easy to operate.

Graph-based Lexicalized Reordering Models for Statistical Machine Translation

Lexicalized reordering models are very important components of phrasebased translation systems.By examining the reordering relationships between adjacent phrases,conventional methods learn these models from the word aligned bilingual corpus,while ignoring the effect of the number of adjacent bilingual phrases.In this paper,we propose a method to take the number of adjacent phrases into account for better estimation of reordering models.Instead of just checking whether there is one phrase adjacent to a given phrase,our method firstly uses a compact structure named reordering graph to represent all phrase segmentations of a parallel sentence,then the effect of the adjacent phrase number can be quantified in a forward-backward fashion,and finally incorporated into the estimation of reordering models.Experimental results on the NIST Chinese-English and WMT French-Spanish data sets show that our approach significantly outperforms the baseline method.

BAR:a branch-alternation-resorting algorithm for locality exploration in graph processing

Unstructured and irregular graph data causes strong randomness and poor locality of data accesses in graph processing.This paper optimizes the depth-branch-resorting algorithm(DBR),and proposes a branch-alternation-resorting algorithm(BAR).In order to make the algorithm run in parallel and improve the efficiency of algorithm operation,the BAR algorithm is mapped onto the reconfigurable array processor(APR-16)to achieve vertex reordering,effectively improving the locality of graph data.This paper validates the BAR algorithm on the GraphBIG framework,by utilizing the reordered dataset with BAR on breadth-first search(BFS),single source shortest paht(SSSP)and betweenness centrality(BC)algorithms for traversal.The results show that compared with DBR and Corder algorithms,BAR can reduce execution time by up to 33.00%,and 51.00%seperatively.In terms of data movement,the BAR algorithm has a maximum reduction of 39.00%compared with the DBR algorithm and 29.66%compared with Corder algorithm.In terms of computational complexity,the BAR algorithm has a maximum reduction of 32.56%compared with DBR algorithm and53.05%compared with Corder algorithm.

Optimization of High-Concurrency Conflict Issues in Execute-Order-Validate Blockchain

With the maturation and advancement of blockchain technology,a novel execute-order-validate(EOV)architecture has been proposed,allowing transactions to be executed in parallel during the execution phase.However,parallel execution may lead to multi-version concurrency control(MVCC)conflicts during the validation phase,resulting in transaction invalidation.Based on different causes,we categorize conflicts in the EOV blockchain into two types:within-block conflicts and cross-block conflicts,and propose an optimization solution called FabricMan based on Fabric v2.4.For within-block conflicts,a reordering algorithm is designed to improve the transaction success rate and parallel validation is implemented based on the transaction conflict graph.We also merge transfer transactions to prevent triggering multiple version checks.For cross-block conflicts,a cache-based version validation mechanism is implemented to detect and terminate invalid transactions in advance.Experimental comparisons are conducted between FabricMan and two other systems,Fabric and Fabric++.The results show that FabricMan outperforms the other two systems in terms of throughput,transaction abort rate,algorithm execution time,and other experimental metrics.

Strategies Used by Chinese Students of English in Constructing Clause and Rhetorical Relations of Text: A Study Based on a Sentence Reordering Activity

This study investigated how advanced Chinese students of English construct clause relations when construing English texts. A deconstructed text was distributed in class to 42 graduate students of linguistics, who were required to organize the clauses into a conceivably good text. The result suggests that these students seemed to rely on explicit cohesive words （anaphoric references and repetitions） rather than meaning relations in text construction. They seemed to have difficulties in using cataphoric contextual information and the popular discourse pattern from general to specific. This study calls for an enhanced awareness of logico-semantic relations in teaching and learning text construction.

EXAFS study of cation reordering in NaYF_4:Yb^(3+),Tb^(3+) up-conversion luminescence materials

The NaYF4：yb3＋,Tb3＋ （Xyb： 0.20, XTb： 0.04） materials were prepared using the co-precipitation method, lne as-preparea material was washed either with or without water in addition to ethanol and thereafter annealed for 5 h at 500℃. This resulted in materials with moderate or very high up-conversion luminescence intensity, respectively. The structural study carried out with X-ray powder diffraction revealed microstrains in the rare earth （R） sublattice that were relaxed for the material with very high up-conversion intensity thus decreasing energy losses. The local structural details were investigated with R LⅢ and Y K edge ex- tended X-ray absorption fine structure （EXAFS） using synchrotron radiation. Around 10 tool.% of the Yb3＋ ions were found to occupy the Na site in the material with very high up-conversion intensity. These Yb species formed clusters with the Tb3＋ ions occupying the regular Na/R sites. Such clustering enhanced the energy transfer between Yb3＋ and Tb3＋ thus intensifying the up-conversion emission.

The Reordering of Relationship and the Shaping of a National Governance Structure in China

Various government documents tend to put the reordering of relationship together with institutional reform and functional transformation.If we fail to understand this important issue,we will be unable to understand China’s national governance system.The reordering of relationship has four dimensions:government and market;central and local government;the economy and society;and government and society.The routes to this reordering can be divided into separation,retention and postponement.On the one hand,the conflicts between these routes have affected China’s national governance structure,so that it seeks a balance between closure and opening up;on the other,the course taken by the reordering of relationship is rooted in the demands for generality and modernity that coexist within China’s national governance.One could say that the straightening out of relationship has reshaped the distinctive features of this governance.In the course of continuous reordering,some of its important elements have undergone a crucial change.From the perspective of the reordering of relationship,the openness with which these relations have been absorbed into a larger system is crucial to the future transformation of China’s national governance.

An Effective Discrete Artificial Bee Colony Based SPARQL Query Path Optimization by Reordering Triples

Semantic Web has emerged to make web content machine-readable,and with the rapid increase in the number of web pages,its importance has increased.Resource description framework(RDF)is a special data graph format where Semantic Web data are stored and it can be queried by SPARQL query language.The challenge is to find the optimal query order that results in the shortest period of time.In this paper,the discrete Artificial Bee Colony(dABCSPARQL)algorithm is proposed,based on a novel heuristic approach,namely reordering SPARQL queries.The processing time of queries with different shapes and sizes is minimized using the dABCSPARQL algorithm.The performance of the proposed method is evaluated on chain,star,cyclic,and chain-star queries of different sizes from the Lehigh University Benchmark(LUBM)dataset.The results obtained by the proposed method are compared with those of ARQ(a SPARQL processor for Jena)query engine,the Ant System,the Elitist Ant System,and MAX-MIN Ant System algorithms.The experiments demonstrate that the proposed method significantly reduces the processing time,and in most queries,the reduction rate is higher compared with other optimization methods.

Video coding using geometry based block partitioning and reordering discrete cosine transform

Geometry based block partitioning （GBP） has been shown to achieve better performance than the tree structure based block partitioning （TSBP） of H.264. However, the residual blocks of GBP mode after motion compensation still present some non-vertical/non-horizontal orientations, and the conventional discrete cosine transform （DCT） may generate many high-frequency coefficients. To solve this problem, in this paper we propose a video coding approach by using GBP and reordering DCT （RDCT） techniques. In the proposed approach, GBP is first applied to partition the macroblocks. Then, before performing DCT, a reordering operation is used to adjust the pixel positions of the residual macroblocks based on the partition information. In this way, the partition information of GBP can be used to represent the reordering information of RDCT, and the bitrate can be reduced. Experimental results show that, compared to H.264/AVC, the proposed method achieves on average 6.38% and 5.69% bitrate reductions at low and high bitrates, respectively.

Efficient semi-quantum secret sharing protocol using single particles

Semi-quantum secret sharing(SQSS)is a branch of quantum cryptography which only requires the dealer to have quantum capabilities,reducing the difficulty of protocol implementation.However,the efficiency of the SQSS protocol still needs to be further studied.In this paper,we propose a semi-quantum secret sharing protocol,whose efficiency can approach 100%as the length of message increases.The protocol is based on single particles to reduce the difficulty of resource preparation.Particle reordering,a simple but effective operation,is used in the protocol to improve efficiency and ensure security.Furthermore,our protocol can share specific secrets while most SQSS protocols could not.We also prove that the protocol is secure against common attacks.

Hierarchical Semantic-Category-Tree Model for Chinese-English Machine Translation

We introduce a novel Sermntic-Category- Tree （SCT） model to present the sen-antic structure of a sentence for Chinese-English Machine Translation （MT）. We use the SCT model to handle the reordering in a hierarchical structure in which one reordering is dependent on the others. Different from other reordering approaches, we handle the reordering at three levels： sentence level, chunk level, and word level. The chunk-level reordering is dependent on the sentence-level reordering, and the word-level reordering is dependent on the chunk-level reordering. In this paper, we formally describe the SCT model and discuss the translation strategy based on the SCT model. Further, we present an algorithm for analyzing the source language in SCT and transforming the source SCT into the target SCT. We apply the SCT model to a role-based patent text MT to evaluate the ability of the SCT model. The experimental results show that SCT is efficient in handling the hierarehical reordering operation in MT.

Robust scalable pre-compressed video coding based on MPEG4-FGS over the Internet

Streaming video is becoming increasingly popular among Internet multimedia applications. A robust coding scheme for DCT-based scalable video streaming over the Internet is proposed in this paper. Compared with conventional MPEG4-FGS (fine granular scalable) and progressive FGS(PFGS), the proposed method generates the base layer including some sub-base layers by DCT coefficient reordering and VLC reshuffling, which enables the video stream of to adapt itself to long-term bandwidth time-varying of channel. Furthermore, a novel end-to-end transmission architecture for scalable video streaming over the Internet is also presented, in which an adaptive unequal packet loss protection (AUPLP) strategy is proposed to determine the currently available network bandwidth and adjust the sending rates according to different situations, such as network congestion or unreliable transmission. Experimental results show that the proposed progressive scalable scheme can improve the average coding efficiency up to 1.2 dB compared with MPEG4-FGS and PFGS in lower bandwidth, and the AUPLP strategy can improve the transmitting performances not only of the proposed scheme, but also of MPEG4-FGS, PFGS system.

Dynamic graph exploration by interactively linked node-link diagrams and matrix visualizations

The visualization of dynamic graphs is a challenging task owing to the various properties of the underlying relational data and the additional time-varying property.For sparse and small graphs,the most efficient approach to such visualization is node-link diagrams,whereas for dense graphs with attached data,adjacency matrices might be the better choice.Because graphs can contain both properties,being globally sparse and locally dense,a combination of several visual metaphors as well as static and dynamic visualizations is beneficial.In this paper,a visually and algorithmically scalable approach that provides views and perspectives on graphs as interactively linked node-link and adjacency matrix visualizations is described.As the novelty of this technique,insights such as clusters or anomalies from one or several combined views can be used to influence the layout or reordering of the other views.Moreover,the importance of nodes and node groups can be detected,computed,and visualized by considering several layout and reordering properties in combination as well as different edge properties for the same set of nodes.As an additional feature set,an automatic identification of groups,clusters,and outliers is provided over time,and based on the visual outcome of the node-link and matrix visualizations,the repertoire of the supported layout and matrix reordering techniques is extended,and more interaction techniques are provided when considering the dynamics of the graph data.Finally,a small user experiment was conducted to investigate the usability of the proposed approach.The usefulness of the proposed tool is illustrated by applying it to a graph dataset,such as e co-authorships,co-citations,and a Comprehensible Perl Archive Network distribution.

OpenFIow Based Flow Slice Load Balancing

Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue with the fast growth of network applications.Although lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center networks.The main reason is the lack of efficient ways to obtain network traffic statistics from each network device.As a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized controller.However,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet reordering.To achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing algorithm.Through introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of flows.This scheme improves the performance of load balancing and also reduces the number of reordering packets.Using the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.

Single-period Two-product Inventory Model with Reorder and Substitution

In market, excess demands for many products can be met by reorder even during one period, and retailers usually adopt substitution strategy for more benefit. Under the retailer＇s substitution strategy and permission of reorder, we develop the profits maximization model for the two-substitutable-product inventory problem with stochastic demands and proportional costs and revenues. We show that the objective function is concave and submodular, and therefore the optimal policy exists. We present the optimal conditions for order quantity and provide some properties of the optimal order quantities. Comparing our model with Netessine and Rudi＇s, we prove that reorder and adoption of the substitution strategy can raise the general profits and adjust down the general stock level.

A reordered first fit algorithm based novel storage scheme for parallel turbo decoder

In this paper we discuss a novel storage scheme for simultaneous memory access in parallel turbo decoder. The new scheme employs vertex coloring in graph theory. Compared to a similar method that also uses unnatural order in storage, our scheme requires 25 more memory blocks but allows a simpler configuration for variable sizes of code lengths that can be implemented on-chip. Experiment shows that for a moderate to high decoding throughput （40-100 Mbps）, the hardware cost is still affordable for 3GPP＇s （3rd generation partnership project） interleaver.

TCP-R with EPDN: Handling out of Order Packets in Error Prone Satellite Networks

Studies have shown that packet reordering is common, especially in satellite networks where there are link level retransmissions and multipath routing. Moreover, traditional satellite networks exhibit high corruption rates causing packet losses. Reordering and corruption of packets decrease the TCP performance of a network, mainly because it leads to overestimation of the congestion in the network. We consider satellite networks and analyze the performance of such networks when reordering and corruption of packets occurs. We propose a solution that could significantly improve the performance of the network when reordering and corruption of packets occur in a satellite network. We report results of our simulation experiments, which support this claim.

Reordered Love, Reordered Lives： Rethinking Vice and Virtue

In this paper and presupposing a Christian Weltanschauung or biblical worldview, I will argue that vices are disordered loves and virtues are reordered loves. The Christian gospel makes the ~ansition from the former to the latter state possible. The seven deadly sins--pride, envy, anger, sloth, avarice, gluttony, and lust--are disordered loves; the seven cardinal virtues--faith, hope, love, courage, justice, temperance, and prudence--are reordered loves. Since love is central in human experience---rooted in the heart--it is also central in moral formation and deformation. Love （or the lack thereof） is the key to understanding the nature and action of both human vice and virtue.

Memory access optimization for particle operations in computational fluid dynamics-discrete element method simulations

Computational Fluid Dynamics-Discrete Element Method is used to model gas-solid systems in several applications in energy,pharmaceutical and petrochemical industries.Computational performance bot-tlenecks often limit the problem sizes that can be simulated at industrial scale.The data structures used to store several millions of particles in such large-scale simulations have a large memory footprint that does not fit into the processor cache hierarchies on current high-performance-computing platforms,leading to reduced computational performance.This paper specifically addresses this aspect of memory access bottlenecks in industrial scale simulations.The use of space-flling curves to improve memory access patterns is described and their impact on computational performance is quantified in both shared and distributed memory parallelization paradigms.The Morton space flling curve applied to uniform grids and k-dimensional tree partitions are used to reorder the particle data-structure thus improving spatial and temporal locality in memory.The performance impact of these techniques when applied to two benchmark problems,namely the homogeneous-cooling-system and a fluidized-bed,are presented.These optimization techniques lead to approximately two-fold performance improvement in particle focused operations such as neighbor-list creation and data-exchange,with~1.5 times overall improvement in a fluidization simulation with 1.27 million particles.

ROCO:Using a Solid State Drive Cache to Improve the Performance of a Host-Aware Shingled Magnetic Recording Drive

Shingled magnetic recording (SMR)can effectively increase the capacity of hard disk drives (HDDs).Hostaware SMR (HA-SMR)is expected to be more popular than other SMR models because of its backward compatibility and new SMR-specific APIs.However,an HA-SMR drive often suffers performance degradation under write-intensive workloads because of frequent non-sequential writes buffered in the disk cache.The non-sequential writes mainly come from update writes,small random writes and out-of-order writes.In this paper,we propose a hybrid storage system called ROCO which aims to use a solid state drive (SSD)cache to improve the performance of an HA-SMR drive.ROCO reorders out-of-order writes belonging to the same zone and uses the SSD cache to absorb update writes and small random writes.We also design a data replacement algorithm called CREA for the SSD cache.CREA first conducts zone-oriented hot/cold data identification to identify cold-cached zones and hot-cached zones,and then evicts data blocks belonging to colder zones with higher priorities that can be sequentially written or written through host-side read-modify-write operations.It gives the lowest priority to data blocks belonging to the hottest-cached zone that have to be non-sequentially written.Experimental results show that ROCO can effectively reduce non-sequential writes to the HA-SMR drive and improve the performance of the HA-SMR drive.