Geoproof : proofs of geographic location for cloud computing environment

Cloud computing has emerged as a major ICT trend and has been acknowledged as a key theme of industry by prominent ICT organisations. However, one of the major challenges that face the cloud computing concept and its global acceptance is how to secure and protect the data that is the property of the user. The geographic location of cloud data storage centres is an important issue for many organisations and individuals due to the regulations and laws that require data and operations to reside in specific geographic locations. Thus, data owners may need to ensure that their cloud providers do not compromise the SLA contract and move their data into another geographic location. This paper introduces an architecture for a new approach for geographic location assurance, which combines the proof of storage protocol (POS) and the distance-bounding protocol. This allows the client to check where their stored data is located, without relying on the word of the cloud provider. This architecture aims to achieve better security and more flexible geographic assurance within the environment of cloud computing.

Visual sea-floor mapping from low overlap imagery using bi-objective bundle adjustment and constrained motion

In most visual mapping applications suited to Autonomous Underwater Vehicles (AUVs), stereo visual odometry (VO) is rarely utilised as a pose estimator as imagery is typically of very low framerate due to energy conservation and data storage requirements. This adversely affects the robustness of a vision-based pose estimator and its ability to generate a smooth trajectory. This paper presents a novel VO pipeline for low-overlap imagery from an AUV that utilises constrained motion and integrates magnetometer data in a bi-objective bundle adjustment stage to achieve low-drift pose estimates over large trajectories. We analyse the performance of a standard stereo VO algorithm and compare the results to the modified vo algorithm. Results are demonstrated in a virtual environment in addition to low-overlap imagery gathered from an AUV. The modified VO algorithm shows significantly improved pose accuracy and performance over trajectories of more than 300m. In addition, dense 3D meshes generated from the visual odometry pipeline are presented as a qualitative output of the solution.

Diporphyrins linked by two-atom bridges synthestic, structural and theoretical studies

The syntheses, properties and electronic structures of a series of porphyrin dimers connected by two-atom bridges were compared. The study found that an azo linker results in the most efficient electronic communication between the two porphyrin rings, and is the superior connector for dimers, trimers and oligomers in the design of nonlinear optical materials. This has implications for the design of molecular probes and sensors, photodynamic therapy, microfabrication, and three-dimensional optical data storage. The research led to the synthesis of a number of new porphyrin monomers and dimers, which were characterised using structural, spectroscopic and spectrometric techniques.

Online estimation of Allan variance parameters

A new online method is presented for estimation of the angular randomwalk and rate randomwalk coefficients of inertial measurement unit gyros and accelerometers. In the online method, a state-space model is proposed, and recursive parameter estimators are proposed for quantities previously measured from offline data techniques such as the Allan variance method. The Allan variance method has large offline computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of approximately 100 calculations per data sample.

On-line estimation of Allan variance parameters

A new online method is presented for estimation of the angular random walk and rate random walk coefficients of IMU (inertial measurement unit) gyros and accelerometers. The online method proposes a state space model and proposes parameter estimators for quantities previously measured from off-line data techniques such as the Allan variance graph. Allan variance graphs have large off-line computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of O(100) calculations per data sample.

Viivesietoisten verkkojen nykytila ja tulevaisuuden haasteet

Delay and disruption tolerant networks (DTNs) are computer networks where round trip delays and error rates are high and disconnections frequent. Examples of these extreme networks are space communications, sensor networks, connecting rural villages to the Internet and even interconnecting commodity portable wireless devices and mobile phones. Basic elements of delay tolerant networks are a store-and-forward message transfer resembling traditional mail delivery, an opportunistic and intermittent routing, and an extensible cross-region resource naming service. Individual nodes of the network take an active part in routing the traffic and provide in-network data storage for application data that flows through the network. Application architecture for delay tolerant networks differs also from those used in traditional networks. It has become feasible to design applications that are network-aware and opportunistic, taking an advantage of different network connection speeds and capabilities. This might change some of the basic paradigms of network application design. DTN protocols will also support in designing applications which depend on processes to be persistent over reboots and power failures. DTN protocols could also be applicable to traditional networks in cases where high tolerance to delays or errors would be desired. It is apparent that challenged networks also challenge the traditional strictly layered model of network application design. This thesis provides an extensive introduction to delay tolerant networking concepts and applications. Most attention is given to challenging problems of routing and application architecture. Finally, future prospects of DTN applications and implementations are envisioned through recent research results and an interview with an active researcher of DTN networks.

A Method to Find Sequentially Separated Motifs in Biological Sequences (SSMBS)

Sequence motifs occurring in a particular order in proteins or DNA have been proved to be of biological interest. In this paper, a new method to locate the occurrences of up to five user-defined motifs in a specified order in large proteins and in nucleotide sequence databases is proposed. It has been designed using the concept of quantifiers in regular expressions and linked lists for data storage. The application of this method includes the extraction of relevant consensus regions from biological sequences. This might be useful in clustering of protein families as well as to study the correlation between positions of motifs and their functional sites in DNA sequences.

A hybrid computer for X-ray crystallography

A hybrid computer for structure factor calculations in X-ray crystallography is described. The computer can calculate three-dimensional structure factors of up to 24 atoms in a single run and can generate the scatter functions of well over 100 atoms using Vand et al., or Forsyth and Wells approximations. The computer is essentially a digital computer with analog function generators, thus combining to advantage the economic data storage of digital systems and simple computing circuitry of analog systems. The digital part serially selects the data, computes and feeds the arguments into specially developed high precision digital-analog function generators, the outputs of which being d.c. voltages, are further processed by analog circuits and finally the sequential adder, which employs a novel digital voltmeter circuit, converts them back into digital form and accumulates them in a dekatron counter which displays the final result. The computer is also capable of carrying out 1-, 2-, or 3-dimensional Fourier summation, although in this case, the lack of sufficient storage space for the large number of coefficients involved, is a serious limitation at present.

A modified sulphide capacity function

The sulphide capacity as originally defined by Fincham and Richardson is a strong function of composition in pseudobinary oxide melts of interest in extractive metallurgy. From an analysis of data available in the literature, it is shown that sulphide capacity is directly proportional to the activity of the basic oxide in the melt, within the uncertainty of experimental data. A single parameter is sufficient to describe the sulphide capacity of a binary slag system under isothermal and isobaric conditions. The correlation indicates that the activity coefficient of the sulphide ion or the neutral base metal sulphide dissolved in the melt is independent of composition in pseudobinary melts within experimental uncertainty. Structural variations in the melt with composition do not seem to affect the activity coefficient of the sulphide. A modified sulphide capacity function is defined which makes the treatment more elegant and greatly simplifies data storage and retrieval. The modified function is not based on any model for the melt.

Giant magnetoresistance in transition metal oxides

Some materials exhibit large changes in electrical resistance in the presence of a magnetic field, and this change can be used in applications from sensor technology to magnetic data storage. In their Perspective, Rao and Cheetham discuss magnetoresistance in perovskite manganates, where the effect is unusually strong. Much has been learned about these materials, and this understanding is driving the search for new materials with even more impressive properties.

Signal compression through spatial frequency-based motion estimation

The interest in low bit rate video coding has increased considerably. Despite rapid progress in storage density and digital communication system performance, demand for data-transmission bandwidth and storage capacity continue to exceed the capabilities of available technologies. The growth of data-intensive digital audio, video applications and the increased use of bandwidth-limited media such as video conferencing and full motion video have not only sustained the need for efficient ways to encode analog signals, but made signal compression central to digital communication and data-storage technology. In this paper we explore techniques for compression of image sequences in a manner that optimizes the results for the human receiver. We propose a new motion estimator using two novel block match algorithms which are based on human perception. Simulations with image sequences have shown an improved bit rate while maintaining ''image quality'' when compared to conventional motion estimation techniques using the MAD block match criteria.

Leakage current behavior in pulsed laser deposited Ba(Zr0.05Ti0.95)O3 thin films

Barium zirconium titanate [Ba(Zr0.05Ti0.95)O3, BZT] thin films were prepared by pulsed laser ablation technique and dc leakage current conduction behavior was extensively studied. The dc leakage behavior study is essential, as it leads to degradation of the data storage devices. The current-voltage (I-V) of the thin films showed an Ohmic behavior for the electric field strength lower than 7.5 MV/m. Nonlinearity in the current density-voltage (J-V) behavior has been observed at an electric field above 7.5 MV/m. Different conduction mechanisms have been thought to be responsible for the overall I-V characteristics of BZT thin films. The J-V behavior of BZT thin films was found to follow Lampert’s theory of space charge limited conduction similar to what is observed in an insulator with charge trapping moiety. The Ohmic and trap filled limited regions have been explicitly observed in the J-V curves, where the saturation prevailed after a voltage of 6.5 V referring the onset of a trap-free square region. Two different activation energy values of 1.155 and 0.325 eV corresponding to two different regions have been observed in the Arrhenius plot, which was attributed to two different types of trap levels present in the film, namely, deep and shallow traps.

Low temperature combustion synthesis and magnetostructural properties of Co-Mn nanoferrites

In the present work, Co1-xMnxFe2O4 nanoparticles were synthesized by the low-temperature auto-combustion method. The thermal decomposition process was investigated by means of differential and thermal gravimetric analysis (TG-DTA) that showed the precursor yield the final product above 450 degrees C. The phase purity and crystal lattice symmetry were estimated from X-ray diffraction (XRD). Microstructural features observed by scanning electron microscopy (SEM) demonstrates that the fine clustered particles were formed with an increase in average grain size with Mn2+ content. Fourier transform infrared spectroscopy (FTIR) study confirms the formation of spinel ferrite. Room temperature magnetization measurements showed that the magnetization M-s increases from 29 to 60 emu/g and H-c increases from 13 to 28 Oe with increase in Mn2+ content, which implies that these materials may be applicable for magnetic data storage and recording media. (C) 2013 Elsevier B.V. All rights reserved.