Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

National Institute of Standards and Technology における超伝導研究及び生活

http://ieeexplore.ieee.org/iel5/5610941/5624686/05624745.pdf

Power electronics

Usually, a proof of a theorem contains more knowledge than the mere fact that the theorem is true. For instance, to prove that a graph is Hamiltonian it suffices to exhibit a Hamiltonian tour in it; however, this seems to contain more knowledge than the single bit Hamiltonian/non-Hamiltonian.In this paper a computational complexity theory of the “knowledge” contained in a proof is developed. Zero-knowledge proofs are defined as those proofs that convey no additional knowledge other than the correctness of the proposition in question. Examples of zero-knowledge proof systems are given for the languages of quadratic residuosity and 'quadratic nonresiduosity. These are the first examples of zero-knowledge proofs for languages not known to be efficiently recognizable.

/pdf/the-knowledge-complexity-of-interactive-proof-systems-31apre0ecf.pdf

The knowledge complexity of interactive proof-systems

Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables systematic development of optimal vision algorithms when used with optimization principles. This detailed and thoroughly enhanced third edition presents a comprehensive study / reference to theories, methodologies and recent developments in solving computer vision problems based on MRFs, statistics and optimisation. It treats various problems in low- and high-level computational vision in a systematic and unified way within the MAP-MRF framework. Among the main issues covered are: how to use MRFs to encode contextual constraints that are indispensable to image understanding; how to derive the objective function for the optimal solution to a problem; and how to design computational algorithms for finding an optimal solution. Easy-to-follow and coherent, the revised edition is accessible, includes the most recent advances, and has new and expanded sections on such topics as: Discriminative Random Fields (DRF) Strong Random Fields (SRF) Spatial-Temporal Models Total Variation Models Learning MRF for Classification (motivation + DRF) Relation to Graphic Models Graph Cuts Belief Propagation Features: Focuses on the application of Markov random fields to computer vision problems, such as image restoration and edge detection in the low-level domain, and object matching and recognition in the high-level domain Presents various vision models in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation Uses a variety of examples to illustrate how to convert a specific vision problem involving uncertainties and constraints into essentially an optimization problem under the MRF setting Introduces readers to the basic concepts, important models and various special classes of MRFs on the regular image lattice and MRFs on relational graphs derived from images Examines the problems of parameter estimation and function optimization Includes an extensive list of references This broad-ranging and comprehensive volume is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It has been class-tested and is suitable as a textbook for advanced courses relating to these areas.

Markov Random Field Modeling in Image Analysis

Analysis of information flow security in cyber–physical systems

DAWGS—a distributed compute server utilizing idle workstations

-The FREEDM microgrid is a test bed for a smart grid integrated with Distributed Grid Intelligence (DGI) to efficiently manage the distribution and storage of renewable energy. Within the FREEDM system, DGI applies distributed algorithms in a unique way to achieve economically feasible utilization and storage of alternative energy sources in a distributed fashion. The FREEDM microgrid consists of residential or industrial nodes with each node running a portion of the DGI process called Intelligent Energy Management (IEM). Such IEM nodes within FREEDM coordinate among themselves to efficiently and economically manage their power generation, utility and storage. Among a variety of services offered by the DGI, the Power Balancing scheme optimizes the distribution of power generation and storage among the IEMs. This paper presents the key aspects in implementing such a scheme and outlines the preliminary results obtained by integrating the proposed methodology with a functional SST model of FREEDM. The results demonstrate the potential benefits of adopting advanced 'smart' technology on a local grid.

/pdf/distributed-power-balancing-for-the-freedm-system-4lspdet6wz.pdf

Distributed Power Balancing for the FREEDM System

This paper presents a general theory of event compensation as an information flow security enforcement mechanism for Cyber-Physical Systems (CPSs). The fundamental research problem being investigated is that externally observable events in modern CPSs have the propensity to divulge sensitive settings to adversaries, resulting in a confidentiality violation. This is a less studied yet emerging concern in modern system security. A viable method to mitigate such violations is to use information flow security based enforcement mechanisms since access control based security models cannot impose restrictions on information propagation. Further, the disjoint nature of security analysis is not appropriate for systems with highly integrated physical and cyber infrastructures. The proposed compensation based security framework is foundational work that unifies cyber and physical aspects of security through the shared semantics of information flow. A DC circuit example is presented to demonstrate this concept.

/pdf/enforcing-information-flow-security-properties-in-cyber-1nl3q6xwk6.pdf

Enforcing Information Flow Security Properties in Cyber-Physical Systems: A Generalized Framework Based on Compensation

Existing maximum flow algorithms use one processor for all calculations or one processor per vertex in a graph to calculate the maximum possible flow through a graph's vertices. This is not suitable for practical implementation. We extend the max-flow work of Goldberg and Tarjan to a distributed algorithm to calculate maximum flow where the number of processors is less than the number of vertices in a graph. Our algorithm is applied to maximizing electrical flow within a power network where the power grid is modeled as a graph. Error detection measures are included to detect problems in a simulated power network. We show that our algorithm is successful in executing quickly enough to prevent catastrophic power outages.

/pdf/power-transmission-control-using-distributed-max-flow-2gxhmf479w.pdf

Bruce M. McMillin

Papers

Analysis of information flow security in cyber–physical systems

DAWGS—a distributed compute server utilizing idle workstations

Distributed Power Balancing for the FREEDM System

Enforcing Information Flow Security Properties in Cyber-Physical Systems: A Generalized Framework Based on Compensation

Power transmission control using distributed max-flow