Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain

Practical and financial constraints associated with traditional field-based lithological mapping are often responsible for the generation of maps with insufficient detail and inaccurately located contacts. In arid areas with well exposed rocks and soils, high-resolution multi- and hyperspectral imagery is a valuable mapping aid as lithological units can be readily discriminated and mapped by automatically matching image pixel spectra to a set of reference spectra. However, the use of spectral imagery in all but the most barren terrain is problematic because just small amounts of vegetation cover can obscure or mask the spectra of underlying geological substrates. The use of ancillary information may help to improve lithological discrimination, especially where geobotanical relationships are absent or where distinct lithologies exhibit inherent spectral similarity. This study assesses the efficacy of airborne multispectral imagery for detailed lithological mapping in a vegetated section of the Troodos ophiolite (Cyprus), and investigates whether the mapping performance can be enhanced through the integration of LiDAR-derived topographic data. In each case, a number of algorithms involving different combinations of input variables and classification routine were employed to maximise the mapping performance. Despite the potential problems posed by vegetation cover, geobotanical associations aided the generation of a lithological map - with a satisfactory overall accuracy of 65.5% and Kappa of 0.54 - using only spectral information. Moreover, owing to the correlation between topography and lithology in the study area, the integration of LiDAR-derived topographic variables led to significant improvements of up to 22.5% in the overall mapping accuracy compared to spectral-only approaches. The improvements were found to be considerably greater for algorithms involving classification with an artificial neural network (the Kohonen Self-Organizing Map) than the parametric Maximum Likelihood Classifier. The results of this study demonstrate the enhanced capability of data integration for detailed lithological mapping in areas where spectral discrimination is complicated by the presence of vegetation or inherent spectral similarities.     

Satellite observations of circulation features associated with a bowhead whale feeding ‘hotspot’ near Barrow, Alaska

Satellite images, along with oceanographic, meteorological, and whale aerial survey data, are used to illustrate aspects of ocean circulation associated with a bowhead whale feeding ‘hotspot’ near Barrow, Alaska. In response to weak winds, a strong front forms near the shelf-break along the southern edge of Barrow Canyon when the Alaska Coastal Current flows adjacent to the southern flank of Barrow Canyon or intrudes onto the western Beaufort shelf. This front is of particular local interest because it is indicative of aggregation and retention of zooplankton on the western Beaufort shelf and, as a result, is a locus for bowhead whales pausing to feed during their westward fall migration. Groups (4 or more individuals) of bowhead whales are primarily seen on the western Beaufort shelf following wind conditions that promote the formation of this front.     

An evolutionary real options framework for the design and management of projects and systems with complex real options and exercising conditions

To address the issue of decision support for designing and managing flexible projects and systems in the face of uncertainties, this paper integrates real options valuation, decision analysis techniques, Monte Carlo simulations and evolutionary algorithms in an evolutionary real options framework. The proposed evolutionary real options framework searches for an optimized portfolio of real options and makes adaptive plans to cope with uncertainties as the future unfolds. Exemplified through a test case, the evolutionary framework not only compares favorably with traditional fixed design approaches but also delivers considerable improvements over prevailing real options practices.     

ADL: An Activity Description Language for Real-Time Networks

This paper introduces and motivates ADL, a new formal notation for the specification of the temporal and functional behaviour of concurrent processes. ADL is tailored to be directly compatible with the DORIS design method. It combines a graphical Activity State-Machine (ASM) notation and a model-based Activity Functional Behaviour (AFB) notation. The abstract syntax, and static and dynamic semantics for the ASM notation are given, the dynamic semantics being given proof-theoretically in many-sorted logic extended with the RTL ‘occurrence’ relation, Θ, and the ERTL ‘holding’ relation, Φ. ADL is used to specify a small network, and proofs are given of its timeliness and safety properties. Received November 1998 / Accepted in revised form May 2000     

Probability-Based Chinese Text Processing and Retrieval

We discuss the use of probability-based natural language processing for Chinese text retrieval. We focus on comparing different text extraction methods and probabilistic weighting methods. Several document processing methods and probabilistic weighting functions are presented. A number of experiments have been conducted on large standard text collections. We present the experimental results that compare a word-based text processing method with a character-based method. The experimental results also compare a number of term-weighting functions including both single-unit weighting and compound-unit weighting functions.     

Proactive Use of Shared L3 Caches to Enhance Cache Communications in Multi-Core Processors

The software and hardware techniques to exploit the potential of multi-core processors are falling behind, even though the number of cores and cache levels per chip is increasing rapidly. There is no explicit communications support available, and hence inter-core communications depend on cache coherence protocols, resulting in demand-based cache line transfers with their inherent latency and overhead. In this paper, we present Software Controlled Eviction (SCE) to improve the performance of multithreaded applications running on multi-core processors by moving shared data to shared cache levels before it is demanded from remote private caches. Simulation results show that SCE offers significant performance improvement (8-28%) and reduces L3 cache misses by 88-98%.     

Neuroproteomics and systems biology-based discovery of protein biomarkers for traumatic brain injury and clinical validation

The rapidly growing field of neuroproteomics has expanded to track global proteomic changes underlying various neurological conditions such as traumatic brain injury (TBI), stroke, and Alzheimer's disease. TBI remains a major health problem with approximately 2?million incidents occurring annually in the United States, yet no affective treatment is available despite several clinical trials. The absence of brain injury diagnostic biomarkers was identified as a significant road-block to therapeutic development for brain injury. Recently, the field of neuroproteomics has undertaken major advances in the area of neurotrauma research, where several candidate markers have been identified and are being evaluated for their efficacy as biological biomarkers in the field of TBI. One scope of this review is to evaluate the current status of TBI biomarker discovery using neuroproteomics techniques, and at what stage we are at in their clinical validation. In addition, we will discuss the need for strengthening the role of systems biology and its application to the field of neuroproteomics due to its integral role in establishing a comprehensive understanding of specific brain disorder and brain function in general. Finally, to achieve true clinical input of these neuroproteomic findings, these putative biomarkers should be validated using preclinical and clinical samples and linked to clinical diagnostic assays including ELISA or other high-throughput assays.     

A well-based reverse-phase protein array applicable to extracts from formalin-fixed paraffin-embedded tissue

Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue offers significant diagnostic utility but is complicated due to the high level of covalently crosslinked proteins arising from formalin fixation. To address these challenges, we developed a reliable protein extraction method for FFPE tissue, based on heat-induced antigen retrieval within a pressure cooker. The protein extraction yield from archival FFPE tissue section is approximately 90% of that recovered from frozen tissue. This method demonstrates preservation of immunoreactivity and recovery of full-length proteins by Western blotting. Additionally, we developed a well-based RP protein array platform utilizing an electrochemiluminescence detection system. Protein samples derived from FFPE tissue by means of laser capture dissection, with as few as 500 shots demonstrate measurable signal differences for different proteins. The lysates coated to the array plate, remain stable over 1?month at room temperature. Theses data suggest that this new protein-profiling platform coupled with the protein extraction method can be used for molecular profiling analysis in FFPE tissue, and contribute to the validation and development of biomarkers in clinical studies.     

Adventure tourism and adventure sports injury: the New Zealand experience

The primary aims of this study were to establish a client injury baseline for the New Zealand adventure tourism and adventure sport sector, and to examine patterns and trends in claims for injury during participation in adventure activities. Content analysis of narrative text data for compensated injuries occurring in a place for recreation and sport over a 12-month period produced over 15,000 cases involving adventure tourism and adventure sport. As found in previous studies in New Zealand, highest claim counts were observed for activities that are often undertaken independently, rather than commercially. Horse riding, tramping, surfing and mountain biking were found to have highest claim counts, while hang gliding/paragliding/parasailing and jet boating injuries had highest claim costs, suggesting greatest injury severity. Highest claim incidence was observed for horse riding, with female claimants over-represented for this activity. Younger male claimants comprised the largest proportion of adventure injuries, and falls were the most common injury mechanism.     

Feature subset selection and ranking for data dimensionality reduction

A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one at a time, by estimating the capability of each specified candidate feature subset to represent the overall features in the measurement space. A squared correlation function is employed as the criterion to measure the dependency between features and this makes the new algorithm easy to implement. The forward orthogonalization strategy, which combines good effectiveness with high efficiency, enables the new algorithm to produce efficient feature subsets with a clear physical interpretation