A scalable and robust framework for agent-based heterogeneous database operation

How to operate database efficiently and unfailingly in agent-based heterogeneous data source environment is becoming a big problem. In this paper, we contribute a framework and develop a couple of agent-oriented matchmakers with logical ring organization structure to match task agents' requests with middleware agents of databases. The middleware agent is a wrapper of a specific database and is run on the same server with the database management system. The matchmaker is of the features of proliferation and self-cancellation according to the sensory input from its environment. The ring-based coordination mechanism of matchmakers is designed. Two kinds of matchmakers, namely, host and duplicate, are designed for improving the scalability and robustness of agent-based system. The middleware agents are improved for satisfying the framework. We demonstrate the potentials of the framework by case study and present theoretical and empirical evidence that our approach is scalable and robust.

A scalable and extensible segment-event-object-based sports video retrieval system

Sport video data is growing rapidly as a result of the maturing digital technologies that support digital video capture, faster data processing, and large storage. However, (1) semi-automatic content extraction and annotation, (2) scalable indexing model, and (3) effective retrieval and browsing, still pose the most challenging problems for maximizing the usage of large video databases. This article will present the findings from a comprehensive work that proposes a scalable and extensible sports video retrieval system with two major contributions in the area of sports video indexing and retrieval. The first contribution is a new sports video indexing model that utilizes semi-schema-based indexing scheme on top of an Object-Relationship approach. This indexing model is scalable and extensible as it enables gradual index construction which is supported by ongoing development of future content extraction algorithms. The second contribution is a set of novel queries which are based on XQuery to generate dynamic and user-oriented summaries and event structures. The proposed sports video retrieval system has been fully implemented and populated with soccer, tennis, swimming, and diving video. The system has been evaluated against 20 users to demonstrate and confirm its feasibility and benefits. The experimental sports genres were specifically selected to represent the four main categories of sports domain: period-, set-point-, time (race)-, and performance-based sports. Thus, the proposed system should be generic and robust for all types of sports.

Scalable One-Step Wet-Spinning of Graphene Fibers and Yarns from Liquid Crystalline Dispersions of Graphene Oxide: Towards Multifunctional Textiles

Key points in the formation of liquid crystalline (LC) dispersions of graphene oxide (GO) and their processability via wet-spinning to produce long lengths of micrometer-dimensional fibers and yarns are addressed. Based on rheological and polarized optical microscopy investigations, a rational relation between GO sheet size and polydispersity, concentration, liquid crystallinity, and spinnability is proposed, leading to an understanding of lyotropic LC behavior and fiber spinnability. The knowledge gained from the straightforward formulation of LC GO “inks” in a range of processable concentrations enables the spinning of continuous conducting, strong, and robust fibers at concentrations as low as 0.075 wt%, eliminating the need for relatively concentrated spinning dope dispersions. The dilute LC GO dispersion is proven to be suitable for fiber spinning using a number of coagulation strategies, including non-solvent precipitation, dispersion destabilization, ionic cross-linking, and polyelectrolyte complexation. One-step continuous spinning of graphene fibers and yarns is introduced for the first time by in situ spinning of LC GO in basic coagulation baths (i.e., NaOH or KOH), eliminating the need for post-treatment processes. The thermal conductivity of these graphene fibers is found to be much higher than polycrystalline graphite and other types of 3D carbon based materials.

Scalable Solid-Template Reduction for Designed Reduced Graphene Oxide Architectures

Herein, we report a solid-state reduction process (in contrast to solution-based approach) by using an environmentally friendly reductant, such as vitamin C (denoted VC), to be directly employed to solid-state graphene oxide (GO) templates to give the highly active rGO architecture with a sheet resistance of as low as 10 Ω sq–1. In addition, predesigned rGO patterns/tracks with tunable resistivity can be directly “written” on a preprepared solid GO film via the inkjet-printing technique using VC/H2O as the printing-ink. This advanced reduction process allows foreign active materials to be preincorporated into the GO matrix to form quality active composite architectures.

Scalable RFID security framework and protocol supporting Internet of Things

Radio-frequency identification (RFID) is seen as one of the requirements for the implementation of the Internet-of-Things (IoT). However, an RFID system has to be equipped with a holistic security framework for a secure and scalable operation. Although much work has been done to provide privacy and anonymity, little focus has been given to performance, scalability and customizability issues to support robust implementation of IoT. Also, existing protocols suffer from a number of deficiencies such as insecure or inefficient identification techniques, throughput delay and inadaptability. In this paper, we propose a novel identification technique based on a hybrid approach (group-based approach and collaborative approach) and security check handoff (SCH) for RFID systems with mobility. The proposed protocol provides customizability and adaptability as well as ensuring the secure and scalable deployment of an RFID system to support a robust distributed structure such as the IoT. The protocol has an extra fold of protection against malware using an incorporated malware detection technique. We evaluated the protocol using a randomness battery test and the results show that the protocol offers better security, scalability and customizability than the existing protocols. © 2014 Elsevier B.V. All rights reserved.

High N-content holey few-layered graphene electrocatalysts: Scalable solvent-less production

Few layered nitrogen doped graphene (NG) attracts great interest in energy storage and conversion applications due to its electronic and catalytic properties. However, its bulk production cannot be envisioned by the current synthetic methods. Here we report a facile, solvent-less, low cost and high yield process for the synthesis of NG. Mechanochemical solid-state exfoliation allows scalable synthesis of holey and crumple nitrogen-doped few-layered graphene from graphite with controlled high concentration N doping and a high surface area through ball-milling. By adjusting the ratio of starting materials, the nitrogen content can be modulated from 4.87 to 17.83 at.%. Furthermore, the types of nitrogen-containing species in few-layered graphene can also be controlled. The resultant NG exhibits superior oxygen reduction reaction performance and more reliable stability than commercial Pt/C catalysts. This journal is

Scalable production of wrinkled and few-layered graphene sheets and their use for oil and organic solvent absorption

High-quality wrinkled and few-layered graphene sheets have been produced via a mechano-thermal exfoliation process for a simple, effective and low-cost mass production. Graphene sheets were produced by first ball milling of graphite with ammonium chloride followed by thermal annealing at 800 °C in nitrogen gas. The few layered graphene sheets show highly efficient selectivity and capacity for the absorption of petroleum products as well as organic solvents such as ethanol, cyclohexane and chloroform (up to 82, 42 and 98 times of their own weight, respectively). The saturated few-layered graphene sheets can be cleaned for reuse by simply burning in air. The low-cost strategy for mass production and easy recycling routes demonstrate the great potential of few-layered graphene sheets for oil removal.

Scalable approximating SVD algorithm for recommender systems

With the rapid development of Internet, the amount of information on the Web grows explosively, people often feel puzzled and helpless in finding and getting the information they really need. For overcoming this problem, recommender systems such as singular value decomposition (SVD) method help users finding relevant information, products or services by providing personalized recommendations based on their profiles. SVD is a powerful technique for dimensionality reduction. However, due to its expensive computational requirements and weak performance for large sparse matrices, it has been considered inappropriate for practical applications involving massive data. Thus, to extract information in which the user is interested from a massive amount of data, we propose a personalized recommendation algorithm which is called ApproSVD algorithm based on approximating SVD in this paper. The trick behind our algorithm is to sample some rows of a user-item matrix, rescale each row by an appropriate factor to form a relatively smaller matrix, and then reduce the dimensionality of the smaller matrix. Finally, we present an empirical study to compare the prediction accuracy of our proposed algorithm with that of Drineas's LINEARTIMESVD algorithm and the standard SVD algorithm on MovieLens dataset and Flixster dataset, and show that our method has the best prediction quality. Furthermore, in order to show the superiority of the ApproSVD algorithm, we also conduct an empirical study to compare the prediction accuracy and running time between ApproSVD algorithm and incremental SVD algorithm on MovieLens dataset and Flixster dataset, and demonstrate that our proposed method has better performance overall.

A scalable and automatic mechanism for resource allocation in self-organizing cloud

Taking advantage of the huge potential of consumers’ untapped computing power, self-organizing cloud is a novel computing paradigm where the consumers are able to contribute/sell their computing resources. Meanwhile, host machines held by the consumers are connected by a peer-to-peer (P2P) overlay network on the Internet. In this new architecture, due to large and varying multitudes of resources and prices, it is inefficient and tedious for consumers to select the proper resource manually. Thus, there is a high demand for a scalable and automatic mechanism to accomplish resource allocation. In view of this challenge, this paper proposes two novel economic strategies based on mechanism design. Concretely, we apply the Modified Vickrey Auction (MVA) mechanism to the case where the resource is sufficient; and the Continuous Double Auction (CDA) mechanism is employed when the resource is insufficient. We also prove that aforementioned mechanisms have dominant strategy incentive compatibility. Finally, extensive experiment results are conducted to verify the performance of the proposed strategies in terms of procurement cost and execution efficiency.

Highly crumpled boron nitride nanosheets as adsorbents: scalable solvent-less production

Boron nitride nanosheets (BNNSs), so-called “white graphene”, have recently received increasing attention, both theoretically and experimentally. Although many synthetic procedures have been proposed for the synthesis of BNNSs, finding a simple, solvent-less, catalyst-free, and large-scale production route is still a challenge. Here, a facile, solvent-less, low cost, and high yield process is developed, in which mechanical solid-state exfoliation allows scalable production of crumple BNNSs from commercial BN powders with a high surface area. Importantly, these BNNSs show unprecedentedly high adsorption of proteins described by various adsorption isotherms and kinetics models. In addition, the saturated BNNSs exhibit excellent recyclability, and maintain a high sorption capacity even after five cycles through simply regeneration process of heating in air. This easy recyclability route further demonstrates the great potential of BNNSs for water cleaning application.

Scalable hierarchical rings based routing to a mobile robot in wireless sensor networks

Location service provides location information of robots to sensors, to enable event reporting. Existing protocols apply partial flooding to trace robots, leading to poor scalability. We propose a novel scalable location service, which applies hierarchical rings to update robot location and guide routing toward it. Each mobile robot creates a set of hierarchical update rings of doubling radii. Whenever the robot leaves its k-th ring, it updates its new location to sensors along its newly defined k-th ring, and re-defines all smaller rings for future decisions. When a sensor needs to route to the mobile robot, it starts searching from its smallest ring and sends location query to the sensors along the ring. If the query fails, the search then extends to the next larger ring, until it intersects an existing update ring, from which the search can be directed towards reported center. The location of destination is updated whenever another more recent ring is intersected. Our scheme guarantees message delivery if robot remains connected to sensors during its move. The theoretical analysis and simulation results demonstrate better scalability than previous protocols for the similar goal. © 2014 IEEE.