Improvement of a dynamic accumulator at ICICS 07 and its application in multi-user keyword-based retrieval on encrypted data

A dynamic accumulator is an algorithm, which merges a large set of elements into a constant-size value such that for an element accumulated, there is a witness confirming that the element was included into the value, with a property that accumulated elements can be dynamically added and deleted into/from the original set. Recently Wang et al. presented a dynamic accumulator for batch updates at ICICS 2007. However, their construction suffers from two serious problems. We analyze them and propose a way to repair their scheme. We use the accumulator to construct a new scheme for common secure indices with conjunctive keyword-based retrieval.

Kinetics of low-pressure, low-temperature graphene growth : toward single-layer, single-crystalline structure

Graphene grown on metal catalysts with low carbon solubility is a highly competitive alternative to exfoliated and other forms of graphene, yet a single-layer, single-crystal structure remains a challenge because of the large number of randomly oriented nuclei that form grain boundaries when stitched together. A kinetic model of graphene nucleation and growth is developed to elucidate the effective controls of the graphene island density and surface coverage from the onset of nucleation to the full monolayer formation in low-pressure, low-temperature CVD. The model unprecedentedly involves the complete cycle of the elementary gas-phase and surface processes and shows a precise quantitative agreement with the recent low-energy electron diffraction measurements and also explains numerous parameter trends from a host of experimental reports. These agreements are demonstrated for a broad pressure range as well as different combinations of precursor gases and supporting catalysts. The critical role of hydrogen in controlling the graphene nucleation and monolayer formation is revealed and quantified. The model is generic and can be extended to even broader ranges of catalysts and precursor gases/pressures to enable the as yet elusive effective control of the crystalline structure and number of layers of graphene using the minimum amounts of matter and energy.

How thick SiO2 cap layer is needed to achieve strong visible photoluminescence from SiO2-buffered SiNx films?

The effect of a SiO2 nanolayer and annealing temperature on the UV/visible room-temperature photoluminescence (PL) from SiNx films synthesized by rf magnetron sputtering is studied. The PL intensity can be maximized when the SiO2 layer is 510 nm thick at 800 °C annealing temperature and only 2 nm at 1000 °C. A compositionstructureproperty analysis reveals that the PL intensity is directly related to both the surface chemical states and the content of the SiO and SiN bonds in the SiNx films. These results are relevant for the development of advanced optoelectronic and photonic emitters and sensors. © 2010 Elsevier B.V. All rights reserved.

Development of thin layer mortared concrete masonry

This research was a step forward to developing data sets for thin layer mortared concrete masonry through systematic experimental and numerical studies. Since thin layer mortared concrete masonry is relatively new type of masonry construction, methodical research studies have been undertaken to properly address the gaps in understanding of this masonry system. As part of the ARC Linkage research project, this thesis has been developed to extend the knowledge on thin layer mortared concrete masonry.

Advanced mass spectrometry-based multi-omics technologies for exploring the pathogenesis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the primary hepatic malignancies and is the third most common cause of cancer related death worldwide. Although a wealth of knowledge has been gained concerning the initiation and progression of HCC over the last half century, efforts to improve our understanding of its pathogenesis at a molecular level are still greatly needed, to enable clinicians to enhance the standards of the current diagnosis and treatment of HCC. In the post-genome era, advanced mass spectrometry driven multi-omics technologies (e.g., profiling of DNA damage adducts, RNA modification profiling, proteomics, and metabolomics) stand at the interface between chemistry and biology, and have yielded valuable outcomes from the study of a diversity of complicated diseases. Particularly, these technologies are being broadly used to dissect various biological aspects of HCC with the purpose of biomarker discovery, interrogating pathogenesis as well as for therapeutic discovery. This proof of knowledge-based critical review aims at exploring the selected applications of those defined omics technologies in the HCC niche with an emphasis on translational applications driven by advanced mass spectrometry, toward the specific clinical use for HCC patients. This approach will enable the biomedical community, through both basic research and the clinical sciences, to enhance the applicability of mass spectrometry-based omics technologies in dissecting the pathogenesis of HCC and could lead to novel therapeutic discoveries for HCC.

Multi-scale hybrid numerical simulation of the growth of high-aspect-ratio nanostructures

Recently, a variety high-aspect-ratio nanostructures have been grown and profiled for various applications ranging from field emission transistors to gene/drug delivery devices. However, fabricating and processing arrays of these structures and determining how changing certain physical parameters affects the final outcome is quite challenging. We have developed several modules that can be used to simulate the processes of various physical vapour deposition systems from precursor interaction in the gas phase to gas-surface interactions and surface processes. In this paper, multi-scale hybrid numerical simulations are used to study how low-temperature non-equilibrium plasmas can be employed in the processing of high-aspect-ratio structures such that the resulting nanostructures have properties suitable for their eventual device application. We show that whilst using plasma techniques is beneficial in many nanofabrication processes, it is especially useful in making dense arrays of high-aspect-ratio nanostructures.

Dispersion properties of surface waves in a two-layer plasma structure bounded by a metal

The effect of the nonuniformity of the electron density on the dispersion properties of surface waves propagating in a direction transverse to an external magnetic field is studied for the model of a two-layer plasma structure bounded by a metal. It is shown that the spectra of the waves can be effectively controlled by varying the degree of nonuniformity of the density and the dimensions of the layers.

Effects of wall transition regions on surface-wave propagation in a plasma layer bounded by a metal

Effect of near-wall transition regions on the surface wave propagation in a magnetoactive plasma layer bounded by a metal. It is shown that the account for inhomogeneities of plasma density or magnetic field causes an appearance of coupling between surface waves, propagating across magnetic field and localized near difference boundaries of the structure. The resonance damping of surface waves is analyzed too.

Malleability attacks on multi-party key agreement protocols

Multi-party key agreement protocols indirectly assume that each principal equally contributes to the final form of the key. In this paper we consider three malleability attacks on multi-party key agreement protocols. The first attack, called strong key control allows a dishonest principal (or a group of principals) to fix the key to a pre-set value. The second attack is weak key control in which the key is still random, but the set from which the key is drawn is much smaller than expected. The third attack is named selective key control in which a dishonest principal (or a group of dishonest principals) is able to remove a contribution of honest principals to the group key. The paper discusses the above three attacks on several key agreement protocols, including DH (Diffie-Hellman), BD (Burmester-Desmedt) and JV (Just-Vaudenay). We show that dishonest principals in all three protocols can weakly control the key, and the only protocol which does not allow for strong key control is the DH protocol. The BD and JV protocols permit to modify the group key by any pair of neighboring principals. This modification remains undetected by honest principals.

Multi-stage collapse events in the South Soufrière Hills, Montserrat as recorded in marine sediment cores

We present new evidence for sector collapses of the South Soufrière Hills (SSH) edifice, Montserrat during the mid-Pleistocene. High-resolution geophysical data provide evidence for sector collapse, producing an approximately 1 km3 submarine collapse deposit to the south of SSH. Sedimentological and geochemical analyses of submarine deposits sampled by sediment cores suggest that they were formed by large multi-stage flank failures of the subaerial SSH edifice into the sea. This work identifies two distinct geochemical suites within the SSH succession on the basis of trace-element and Pb-isotope compositions. Volcaniclastic turbidites in the cores preserve these chemically heterogeneous rock suites. However, the subaerial chemostratigraphy is reversed within the submarine sediment cores. Sedimentological analysis suggests that the edifice failures produced high-concentration turbidites and that the collapses occurred in multiple stages, with an interval of at least 2 ka between the first and second failure. Detailed field and petrographical observations, coupled with SEM image analysis, shows that the SSH volcanic products preserve a complex record of magmatic activity. This activity consisted of episodic explosive eruptions of andesitic pumice, probably triggered by mafic magmatic pulses and followed by eruptions of poorly vesiculated basaltic scoria, and basaltic lava flows.

On secure multi-party computation in black-box groups

We study the natural problem of secure n-party computation (in the passive, computationally unbounded attack model) of the n-product function f G (x 1,...,x n ) = x 1 ·x 2 ⋯ x n in an arbitrary finite group (G,·), where the input of party P i is x i  ∈ G for i = 1,...,n. For flexibility, we are interested in protocols for f G which require only black-box access to the group G (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). Our results are as follows. First, on the negative side, we show that if (G,·) is non-abelian and n ≥ 4, then no ⌈n/2⌉-private protocol for computing f G exists. Second, on the positive side, we initiate an approach for construction of black-box protocols for f G based on k-of-k threshold secret sharing schemes, which are efficiently implementable over any black-box group G. We reduce the problem of constructing such protocols to a combinatorial colouring problem in planar graphs. We then give two constructions for such graph colourings. Our first colouring construction gives a protocol with optimal collusion resistance t < n/2, but has exponential communication complexity O(n*2t+1^2/t) group elements (this construction easily extends to general adversary structures). Our second probabilistic colouring construction gives a protocol with (close to optimal) collusion resistance t < n/μ for a graph-related constant μ ≤ 2.948, and has efficient communication complexity O(n*t^2) group elements. Furthermore, we believe that our results can be improved by further study of the associated combinatorial problems.

Theorizing in design science research : an abstraction layers framework

For Design Science Research (DSR) to gain wide credence as a research paradigm in Information Systems (IS), it must contribute to theory. “Theory cannot be improved until we improve the theorizing process, and we cannot improve the theorizing process until we describe it more explicitly, operate it more self-consciously, and decouple it from validation more deliberately” (Weick 1989, p. 516). With the aim of improved design science theorizing, we propose a DSR abstraction-layers framework that integrates, interlates, and harmonizes key methodological notions, primary of which are: 1) the Design Science (DS), Design Research (DR), and Routine Design (RD) distinction (Winter 2008); 2) Multi Grounding in IS Design Theory (ISDT) (Goldkuhl & Lind 2010); 3) the Idealized Model for Theory Development (IM4TD) (Fischer & Gregor 2011); and 4) the DSR Theorizing Framework (Lee et al. 2011). Though theorizing, or the abstraction process, has been the subject of healthy discussion in DSR, important questions remain. With most attention to date having focused on theorizing for Design Research (DR), a key stimulus of the layered view was the realization that Design Science (DS) produces abstract knowledge at a higher level of generality. The resultant framework includes four abstraction layers: (i) Design Research (DR) 1st Abstract Layer, (ii) Design Science (DS) 2nd Abstract Layer, (iii) DSR Incubation 3rd Layer, and (iv) Routine Design 4th Layer. Differentiating and inter-relating these layers will aid DSR researchers to discover, position, and amplify their DSR contributions. Additionally, consideration of the four layers can trigger creative perspectives that suggest unplanned outputs. The first abstraction layer, including its alternative patterns of activity, is well recognized in the literature. The other layers, however, are less well recognized; and the integrated representation of layers is novel.

Nonlinear Model Predictive Control for a multi-rotor with heavy slung load

In this paper a novel controller for stable and precise operation of multi-rotors with heavy slung loads is introduced. First, simplified equations of motions for the multi-rotor and slung load are derived. The model is then used to design a Nonlinear Model Predictive Controller (NMPC) that can manage the highly nonlinear dynamics whilst accounting for system constraints. The controller is shown to simultaneously track specified waypoints whilst actively damping large slung load oscillations. A Linear-quadratic regulator (LQR) controller is also derived, and control performance is compared in simulation. Results show the improved performance of the Nonlinear Model Predictive Control (NMPC) controller over a larger flight envelope, including aggressive maneuvers and large slung load displacements. Computational cost remains relatively small, amenable to practical implementation. Such systems for small Unmanned Aerial Vehicles (UAVs) may provide significant benefit to several applications in agriculture, law enforcement and construction.

Enhanced stochastic mobility prediction with multi-output Gaussian processes

Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain.

Global reconfiguration of a team of networked mobile robots among obstacles

This paper presents a full system demonstration of dynamic sensorbased reconfiguration of a networked robot team. Robots sense obstacles in their environment locally and dynamically adapt their global geometric configuration to conform to an abstract goal shape. We present a novel two-layer planning and control algorithm for team reconfiguration that is decentralised and assumes local (neighbour-to-neighbour) communication only. The approach is designed to be resource-efficient and we show experiments using a team of nine mobile robots with modest computation, communication, and sensing. The robots use acoustic beacons for localisation and can sense obstacles in their local neighbourhood using IR sensors. Our results demonstrate globally-specified reconfiguration from local information in a real robot network, and highlight limitations of standard mesh networks in implementing decentralised algorithms.