Southern California's megaflood event of ca. 1605 AD linked to large-scale atmospheric forcing

A distinct, 1- to 2-cm-thick flood deposit found in Santa Barbara Basin with a varve-date of 1605 AD ± 5 years testifies to an intensity of precipitation that remains unmatched for later periods when historical or instrumental records can be compared against the varve record. The 1605 AD ± 5 event correlates well with Enzel's (1992) finding of a Silver Lake playa perennial lake at the terminus of the Mojave River (carbon-14-dated 1560 AD ± 90 years), in relative proximity to the rainfall catchment area draining into Santa Barbara Basin. According to Enzel, such a persistent flooding of the Silver Lake playa occurred only once during the last 3,500 years and required a sequence of floods, each comparable in magnitude to the largest floods in the modern record. To gain confidence in dating of the 1605 AD ± 5 event, we compare Southern California's sedimentary evidence against historical reports and multi-proxy time-series that indicate unusual climatic events or are sensitive to changes in large-scale atmospheric circulation patterns. The emerging pattern supports previous suggestions that the first decade of the 17th century was marked by a rapid cooling of the Northern Hemisphere, with some indications for global coverage. A burst of volcanism and the occurrence of El Nino seem to have contributed to the severity of the events. The synopsis of the 1605 AD ± 5 years flood deposit in Santa Barbara Basin, the substantial freshwater body at Silver Lake playa, and much additional paleoclimatic, global evidence testifies for an equatorward shift of global wind patterns as the world experienced an interval of rapid, intense, and widespread cooling.

The near-AD 1600 multi-proxy puzzle

EXTRACT (SEE PDF FOR FULL ABSTRACT): A varve chronology with annual resolution (AD 1117-1992) has been developed recently for Santa Barbara Basin. Varve thickness and water content show an exponential trend consistent with expected patterns in the presence of sediment compaction over time. Annual varve thickness was decomposed into orthogonal components using singular spectrum analysis (SSA) to identify and retrieve inter-decadal oscillations. ... This suggests a connection with global-scale decadal cycles identified in the subtropical Pacific gyre circulation and, possibly, with solar-driven phenomena. The near-1600 AD event coincides with (a) a similarly sudden change of state in nearby Santa Monica Basin that triggered the onset of anoxic conditions and the preservation of laminated sediments, (b) an extreme drought over the American Southwest, (c) a transformation of the age structure in a number of forest populations throughout Arizona and New Mexico. Total organic carbon burial flux in Santa Barbara Basin varves also shows a marked change after AD 1600. A possible climatic link is proposed that involves pathways for moisture transport in the Southwest at decadal and longer time scales.

Modified Kanerva model. Results for real time word recognition

This paper describes results obtained using the modified Kanerva model to perform word recognition in continuous speech after being trained on the multi-speaker Alvey 'Hotel' speech corpus. Theoretical discoveries have recently enabled us to increase the speed of execution of part of the model by two orders of magnitude over that previously reported by Prager & Fallside. The memory required for the operation of the model has been similarly reduced. The recognition accuracy reaches 95% without syntactic constraints when tested on different data from seven trained speakers. Real time simulation of a model with 9,734 active units is now possible in both training and recognition modes using the Alvey PARSIFAL transputer array. The modified Kanerva model is a static network consisting of a fixed nonlinear mapping (location matching) followed by a single layer of conventional adaptive links. A section of preprocessed speech is transformed by the non-linear mapping to a high dimensional representation. From this intermediate representation a simple linear mapping is able to perform complex pattern discrimination to form the output, indicating the nature of the speech features present in the input window.

Voluntary guidelines for securing sustainable small-scale fisheries in the context of food security and poverty eradication: summary

The Voluntary Guidelines for Securing Sustainable Small-scale Fisheries in the Context of Food Security and Poverty Eradication (SSF Guidelines) were adopted by member countries of the Food and Agriculture Organization of the United Nations (FAO) and were officially approved as an international instrument in June 2014. What is very special about the SSF Guidelines is that it was created as a result of a very long history of the struggles of small-scale fishworkers around the world appealing for greater recognition of their status and their role in the fisheries sector of their countries. These Guidelines have 100 paragraphs which are distributed across 13 sections. This document is only a summation of the contents of the Guidelines. It was produced for ICSF by John Kurien, founder Member of ICSF, who has worked for the last four decades with small-scale fishing communities in many areas around the world, particularly in Kerala, India.

Generation of conjugate meshes for complex geometries for coupled multi-physics simulations

Over recent years we have developed and published research aimed at producing a meshing, geometry editing and simulation system capable of handling large scale, real world applications and implemented in an end-to-end parallel, scalable manner. The particular focus of this paper is the extension of this meshing system to include conjugate meshes for multi-physics simulations. Two contrasting applications are presented: export of a body-conformal mesh to drive a commercial, third-party simulation system; and direct use of the cut-Cartesian octree mesh with a single, integrated, close-coupled multi-physics simulation system. Copyright © 2010 by W.N.Dawes.

Semi-supervised video segmentation using tree structured graphical models

We present a novel, implementation friendly and occlusion aware semi-supervised video segmentation algorithm using tree structured graphical models, which delivers pixel labels alongwith their uncertainty estimates. Our motivation to employ supervision is to tackle a task-specific segmentation problem where the semantic objects are pre-defined by the user. The video model we propose for this problem is based on a tree structured approximation of a patch based undirected mixture model, which includes a novel time-series and a soft label Random Forest classifier participating in a feedback mechanism. We demonstrate the efficacy of our model in cutting out foreground objects and multi-class segmentation problems in lengthy and complex road scene sequences. Our results have wide applicability, including harvesting labelled video data for training discriminative models, shape/pose/articulation learning and large scale statistical analysis to develop priors for video segmentation. © 2011 IEEE.

Coarse-level object recognition using interlevel products of complex wavelets

This paper introduces the Interlevel Product (ILP) which is a transform based upon the Dual-Tree Complex Wavelet. Coefficients of the ILP have complex values whose magnitudes indicate the amplitude of multilevel features, and whose phases indicate the nature of these features (e.g. ridges vs. edges). In particular, the phases of ILP coefficients are approximately invariant to small shifts in the original images. We accordingly introduce this transform as a solution to coarse scale template matching, where alignment concerns between decimation of a target and decimation of a larger search image can be mitigated, and computational efficiency can be maintained. Furthermore, template matching with ILP coefficients can provide several intuitive "near-matches" that may be of interest in image retrieval applications. © 2005 IEEE.

Biologically-inspired object recognition system with features from complex wavelets

In this paper, a novel cortex-inspired feed-forward hierarchical object recognition system based on complex wavelets is proposed and tested. Complex wavelets contain three key properties for object representation: shift invariance, which enables the extraction of stable local features; good directional selectivity, which simplifies the determination of image orientations; and limited redundancy, which allows for efficient signal analysis using the multi-resolution decomposition offered by complex wavelets. In this paper, we propose a complete cortex-inspired object recognition system based on complex wavelets. We find that the implementation of the HMAX model for object recognition in [1, 2] is rather over-complete and includes too much redundant information and processing. We have optimized the structure of the model to make it more efficient. Specifically, we have used the Caltech 5 standard dataset to compare with Serre's model in [2] (which employs Gabor filter bands). Results demonstrate that the complex wavelet model achieves a speed improvement of about 4 times over the Serre model and gives comparable recognition performance. © 2011 IEEE.

Syllable language models for Mandarin speech recognition: exploiting character language models.

Mandarin Chinese is based on characters which are syllabic in nature and morphological in meaning. All spoken languages have syllabiotactic rules which govern the construction of syllables and their allowed sequences. These constraints are not as restrictive as those learned from word sequences, but they can provide additional useful linguistic information. Hence, it is possible to improve speech recognition performance by appropriately combining these two types of constraints. For the Chinese language considered in this paper, character level language models (LMs) can be used as a first level approximation to allowed syllable sequences. To test this idea, word and character level n-gram LMs were trained on 2.8 billion words (equivalent to 4.3 billion characters) of texts from a wide collection of text sources. Both hypothesis and model based combination techniques were investigated to combine word and character level LMs. Significant character error rate reductions up to 7.3% relative were obtained on a state-of-the-art Mandarin Chinese broadcast audio recognition task using an adapted history dependent multi-level LM that performs a log-linearly combination of character and word level LMs. This supports the hypothesis that character or syllable sequence models are useful for improving Mandarin speech recognition performance.

Multi-Modal Image Retrieval from Construction Databases and Model-Based Systems

In the modern and dynamic construction environment it is important to access information in a fast and efficient manner in order to improve the decision making processes for construction managers. This capability is, in most cases, straightforward with today’s technologies for data types with an inherent structure that resides primarily on established database structures like estimating and scheduling software. However, previous research has demonstrated that a significant percentage of construction data is stored in semi-structured or unstructured data formats (text, images, etc.) and that manually locating and identifying such data is a very hard and time-consuming task. This paper focuses on construction site image data and presents a novel image retrieval model that interfaces with established construction data management structures. This model is designed to retrieve images from related objects in project models or construction databases using location, date, and material information (extracted from the image content with pattern recognition techniques).

Statistical inference for single- and multi-band probabilistic amplitude demodulation.

Amplitude demodulation is an ill-posed problem and so it is natural to treat it from a Bayesian viewpoint, inferring the most likely carrier and envelope under probabilistic constraints. One such treatment is Probabilistic Amplitude Demodulation (PAD), which, whilst computationally more intensive than traditional approaches, offers several advantages. Here we provide methods for estimating the uncertainty in the PAD-derived envelopes and carriers, and for learning free-parameters like the time-scale of the envelope. We show how the probabilistic approach can naturally handle noisy and missing data. Finally, we indicate how to extend the model to signals which contain multiple modulators and carriers.

Transcription of multi-genre media archives using out-of-domain data

We describe our work on developing a speech recognition system for multi-genre media archives. The high diversity of the data makes this a challenging recognition task, which may benefit from systems trained on a combination of in-domain and out-of-domain data. Working with tandem HMMs, we present Multi-level Adaptive Networks (MLAN), a novel technique for incorporating information from out-of-domain posterior features using deep neural networks. We show that it provides a substantial reduction in WER over other systems, with relative WER reductions of 15% over a PLP baseline, 9% over in-domain tandem features and 8% over the best out-of-domain tandem features. © 2012 IEEE.

Preliminary laboratory-scale model auger installation and testing of carbonated soil-MgO columns

This paper presents details of the installation and performance of carbonated soil-MgO columns using a laboratory-scale model auger setup. MgO grout was mixed with the soil using the auger and the columns were then carbonated with gaseous CO2 introduced in two different ways: one using auger mixing and the other through a perforated plastic tube system inserted into the treated column. The performance of the columns in terms of unconfined compressive strength (UCS), stiffness, strain at failure and microstructure (using X-ray diffraction and scanning electron microscopy) showed that the soil-MgO columns were carbonated very quickly (in under 1 h) and yielded relatively high strength values, of 2.4-9.4 MPa, which on average were five times that of corresponding 28-day ambient cured uncarbonated columns. This confirmed, together with observations of dense microstructure and hydrated magnesium carbonates, that a good degree of carbonation had taken place. The results also showed that the carbonation method and period have a significant effect on the resulting performance, with the carbonation through the perforated pipe producing the best results. Copyright © 2013 by ASTM International.

Computational engineering design for micro-scale combustors

At present, optimisation is an enabling technology in innovation. Multi-objective and multi-disciplinary design tools are essential in the engineering design process, and have been applied successfully in aerospace and turbomachinery applications extensively. These approaches give insight into the design space and identify the trade-offs between the competing performance measures satisfying a number of constraints at the same time. It is anticipated here that the same benefits can be obtained for the design of micro-scale combustors. In this paper, a multi-disciplinary automated design optimisation system was developed for this purpose, which comprises a commercial computational fluid dynamics package and a multi-objective variant of the Tabu Search optimisation algorithm. The main objectives that are considered in this study are to optimise the main micro-scale combustor design characteristics and to satisfy manufacturability considerations from the very beginning of the whole design operation. Hydrogen-air combustion as well as 14 geometrical and 2 operational parameters are used to describe and model the design problem. Two illustrative test cases will be presented, in which the most important device operational requirements are optimised, and the efficiency of the developed optimisation system is demonstrated. The identification, assessment and suitability of the optimum design configurations are discussed in detail. Copyright © 2012 by ASME.

Computational engineering design for micro-scale combustion devices: A thermally improved configuration

A multi-objective design optimisation study has been carried out with the objectives to improve the overall efficiency of the device and to reduce the fuel consumption for the proposed micro-scale combustor design configuration. In a previous study we identified the topology of the combustion chamber that produced improved behaviour of the device in terms of the above design criteria. We now extend our design approach, and we propose a new configuration by the addition of a micro-cooling channel that will improve the thermal behaviour of the design as previously suggested in literature. Our initial numerical results revealed an improvement of 2.6% in the combustion efficiency when we applied the micro-cooling channel to an optimum design configuration we identified from our earlier multi-objective optimisation study, and under the same operating conditions. The computational modelling of the combustion process is implemented in the commercial computational fluid dynamics package ANSYS-CFX using Finite Rate Chemistry and a single step hydrogen-air reaction. With this model we try to balance good accuracy of the combustion solution and at the same time practicality within the context of an optimisation process. The whole design system comprises also the ANSYS-ICEM CFD package for the automatic geometry and mesh generation and the Multi-Objective Tabu Search algorithm for the design space exploration. We model the design problem with 5 geometrical parameters and 3 operational parameters subject to 5 design constraints that secure practicality and feasibility of the new optimum design configurations. The final results demonstrate the reliability and efficiency of the developed computational design system and most importantly we assess the practicality and manufacturability of the revealed optimum design configurations of micro-combustor devices. Copyright © 2013 by ASME.