Transferability of Regional Permafrost Disturbance Susceptibility Modelling Using Generalized Linear and Generalized Additive Models

To effectively assess and mitigate risk of permafrost disturbance, disturbance-p rone areas can be predicted through the application of susceptibility models. In this study we developed regional susceptibility models for permafrost disturbances using a field disturbance inventory to test the transferability of the model to a broader region in the Canadian High Arctic. Resulting maps of susceptibility were then used to explore the effect of terrain variables on the occurrence of disturbances within this region. To account for a large range of landscape charac- teristics, the model was calibrated using two locations: Sabine Peninsula, Melville Island, NU, and Fosheim Pen- insula, Ellesmere Island, NU. Spatial patterns of disturbance were predicted with a generalized linear model (GLM) and generalized additive model (GAM), each calibrated using disturbed and randomized undisturbed lo- cations from both locations and GIS-derived terrain predictor variables including slope, potential incoming solar radiation, wetness index, topographic position index, elevation, and distance to water. Each model was validated for the Sabine and Fosheim Peninsulas using independent data sets while the transferability of the model to an independent site was assessed at Cape Bounty, Melville Island, NU. The regional GLM and GAM validated well for both calibration sites (Sabine and Fosheim) with the area under the receiver operating curves (AUROC) N 0.79. Both models were applied directly to Cape Bounty without calibration and validated equally with AUROC's of 0.76; however, each model predicted disturbed and undisturbed samples differently. Addition- ally, the sensitivity of the transferred model was assessed using data sets with different sample sizes. Results in- dicated that models based on larger sample sizes transferred more consistently and captured the variability within the terrain attributes in the respective study areas. Terrain attributes associated with the initiation of dis- turbances were similar regardless of the location. Disturbances commonly occurred on slopes between 4 and 15°, below Holocene marine limit, and in areas with low potential incoming solar radiation

San Diego region wind transport and wave overwash report : Coast of California Storm and Tidal Waves Study /

Mode of access: Internet.

A wind- and wave-driven nearshore current model : the one-dimentional model /

Cover title.

Preliminary evaluation of wind and wave effects at potential LNG terminal sites, State of California : appendix A : an evaluation of the relative wave climate at five onshore LNG sites considering island influences and topographic effects : final report /

"April 1978."

Correlating seabed drifter weights to sand threshold conditions in wave and wave/current environments /

"December 1994."

Hurricane hindcast methodology and wave statistics for Atlantic and Gulf hurricanes from 1956-1975 /

Mode of access: Internet.

Computer algorithm to calculate longshore energy flux and wave direction from a two pressure sensor array /

"August 1982."

The effect of wind and wave action on the mixing and dispersion of wastes /

Mode of access: Internet.

Waves and wave action; a bibliography of books, periodicals and society publications appearing from 1687 through March 1946.

Mode of access: Internet.

Rewinding and connecting alternating-current motors; fundamental principles involved in applying and checking lap and wave windings in alternating-current-motor stators and rotors together with practical winding procedure and extensive reference data in typical examples completely worked out, in winding diagrams and in 71 special tabulations, for everyday use by maintenance men in industrial plants, by winders in electrical service and repair shops and by students pursuing electrical courses,

Mode of access: Internet.

Wind and wave : selected tales /

Mode of access: Internet.

Ambulatory EEG monitoring in the diagnosis and treatment of epilepsy and related disorders

Ambulatory EEG recording enables patients with epilepsy and related disorders to be monitored in an unrestricted environment for prolonged periods. Attacks can therefore be recorded and EEG changes at the time can aid diagnosis. The relevant Iiterature is reviewed and a study made of' 250 clinical investigations. A study was also made of the artefacts,encountered during ambulatory recording. Three quarters of referrals were for distinguishing between epileptic and non-epileptic attacks. Over 60% of patients showed no abnormality during attacks. In comparison with the basic EEG the ambulatory EEG provided about ten times as much information. A preliminary follow-up study showed that results, of ambulatory monitoring agreed with the final diagnosis in 8 of 12 patients studied. Of 10 patients referred, for monitoring the occurrence of absence seizures, 8 showed abnormality during the baslcJ EEG .and 10 during the ambulatory EEG. Other patients. were referred: for sleep recording and to clarify the seizure type. An investigation into once daily (OD) versus twice daily administration of sodium valproate in patients with absence seizures showed that an OD regime was equally as effective as a BD regime. Circadian variations in spike and wave activity in patients on and off treatment were also examined. There was significant agreement between subjects on the time of occurrence of abnormality during sleep only, This pattern was not ,affected with treatment nor was there any difference in the daily pattern of occurrence of abnormality between the two regimes. Overall findings suggested that ambulatory monitoring was a valuable tool in the diagnosis and treatment of epilepsy which with careful planning and patient selection could be used in any EEG department and would benefit a:wide range of patients.

Generalized methods and solvers for noise removal from piecewise constant signals. I. Background theory

Removing noise from piecewise constant (PWC) signals is a challenging signal processing problem arising in many practical contexts. For example, in exploration geosciences, noisy drill hole records need to be separated into stratigraphic zones, and in biophysics, jumps between molecular dwell states have to be extracted from noisy fluorescence microscopy signals. Many PWC denoising methods exist, including total variation regularization, mean shift clustering, stepwise jump placement, running medians, convex clustering shrinkage and bilateral filtering; conventional linear signal processing methods are fundamentally unsuited. This paper (part I, the first of two) shows that most of these methods are associated with a special case of a generalized functional, minimized to achieve PWC denoising. The minimizer can be obtained by diverse solver algorithms, including stepwise jump placement, convex programming, finite differences, iterated running medians, least angle regression, regularization path following and coordinate descent. In the second paper, part II, we introduce novel PWC denoising methods, and comparisons between these methods performed on synthetic and real signals, showing that the new understanding of the problem gained in part I leads to new methods that have a useful role to play.

Generalized methods and solvers for noise removal from piecewise constant signals. II. New methods

Removing noise from signals which are piecewise constant (PWC) is a challenging signal processing problem that arises in many practical scientific and engineering contexts. In the first paper (part I) of this series of two, we presented background theory building on results from the image processing community to show that the majority of these algorithms, and more proposed in the wider literature, are each associated with a special case of a generalized functional, that, when minimized, solves the PWC denoising problem. It shows how the minimizer can be obtained by a range of computational solver algorithms. In this second paper (part II), using this understanding developed in part I, we introduce several novel PWC denoising methods, which, for example, combine the global behaviour of mean shift clustering with the local smoothing of total variation diffusion, and show example solver algorithms for these new methods. Comparisons between these methods are performed on synthetic and real signals, revealing that our new methods have a useful role to play. Finally, overlaps between the generalized methods of these two papers and others such as wavelet shrinkage, hidden Markov models, and piecewise smooth filtering are touched on.