Study on the treatment of Limestone cave and soil cave in the construction of power transformation project

2019 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
Liu Rong ◽  
Song Ke
Keyword(s):  
Power Transformation ◽  
Limestone Cave ◽  
Soil Cave

Novel Development of Power Transformation Technology Supporting Electric Power and Energy

2012 ◽  
Vol 132 (5) ◽  
pp. 388-391
Author(s):  
Kenji Okubo ◽  
Shoji Nishimura ◽  
Yutaka Goda ◽  
Yoshihiro Baba
Keyword(s):  
Electric Power ◽  
Power Transformation ◽  
Power And Energy

scholarly journals Radiographic analysis and virtual cleaning of a bioarchaeological remain enclosed in mineral deposits from a limestone cave

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Patrick E. Eppenberger ◽  
Mislav Čavka ◽  
Siniša Radović ◽  
Dalibor Paar ◽  
Nenad Buzjak ◽  
...  
Keyword(s):  
Mineral Deposits ◽  
Radiographic Analysis ◽  
Limestone Cave

scholarly journals The effects of climate change on the Pleistocene rock art of Sulawesi

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
J. Huntley ◽  
M. Aubert ◽  
A. A. Oktaviana ◽  
R. Lebe ◽  
B. Hakim ◽  
...  
Keyword(s):  
Climate Change ◽  
Rock Art ◽  
Rice Fields ◽  
Present Evidence ◽  
Ambient Temperatures ◽  
Limestone Cave ◽  
Salt Crystallisation ◽  
Standing Water ◽  
Aquaculture Ponds ◽  
Consecutive Dry Days

AbstractThe equatorial tropics house some of the earliest rock art yet known, and it is weathering at an alarming rate. Here we present evidence for haloclasty (salt crystallisation) from Pleistocene-aged rock art panels at 11 sites in the Maros-Pangkep limestone karsts of southern Sulawesi. We show how quickly rock art panels have degraded in recent decades, contending that climate-catalysed salt efflorescence is responsible for increasing exfoliation of the limestone cave surfaces that house the ~ 45 to 20-thousand-year-old paintings. These artworks are located in the world’s most atmospherically dynamic region, the Australasian monsoon domain. The rising frequency and severity of El Niño-induced droughts from anthropogenic climate change (that is, higher ambient temperatures and more consecutive dry days), combined with seasonal moisture injected via monsoonal rains retained as standing water in the rice fields and aquaculture ponds of the region, increasingly provide ideal conditions for evaporation and haloclasty, accelerating rock art deterioration.

A note on seasonal Markov chains with gamma or gamma-like distributions

1979 ◽  
Vol 16 (1) ◽  
pp. 117-128 ◽  
Author(s):  
E. H. Lloyd ◽  
S. D. Saleem
Keyword(s):  
Markov Chain ◽  
Laplace Transform ◽  
Weighted Sums ◽  
Power Transformation ◽  
Exponential Form ◽  
Continuous State ◽  
Bessel Distribution ◽  
Storage Theory ◽  
Special Case ◽  
Type Of Transition

Weighted sums defined on a Markov chain (MC) are important in applications (e.g. to reservoir storage theory). The rather intractable theory of such sums simplifies to some extent when the transition p.d.f. of the chain {Xt} has a Laplace transform (LT) L(Xt+1; θ |Χ t=x) of the ‘exponential' form H(θ) exp{ – G(θ)x}. An algorithm is derived for the computation of the LT of Σat,Χ t for this class, and for a seasonal generalization of it.A special case of this desirable exponential type of transition LT for a continuous-state discrete-time MC is identified by comparison with the LT of the Bessel distribution. This is made the basis for a new derivation of a gamma-distributed MC proposed by Lampard (1968).A seasonal version of this process is developed, valid for any number of seasons.Reference is made to related chains with three-parameter gamma-like distributions (of the Kritskii–Menkel family) that may be generated from the above by a simple power transformation.

Forecasting Performance Comparison by Using Power Transformation between VAR and Bayesian VAR Models

2014 ◽  
Vol 529 ◽  
pp. 621-624
Author(s):  
Syang Ke Kung ◽  
Chi Hsiu Wang
Keyword(s):  
Time Series ◽  
Industrial Production ◽  
Multivariate Time Series ◽  
Performance Comparison ◽  
Power Transformation ◽  
Var Models ◽  
Bayesian Var ◽  
Forecasting Performance ◽  
The U.S ◽  
Forecasting Practice

This article is devoted to examine the performance of power transformation in VAR and Bayesian VAR (BVAR) forecasts, in comparison with log-transformation. The effect of power transformation in multivariate time series model forecasts is still untouched in the literature. We examined the U.S. macroeconomic data from 1960 to 1987 and the Taiwan’s technology industrial production from 1990 to 2000. Our results showed that the power transformation provides outperforming forecasts in both VAR and BVAR models. Moreover, the non-informative prior BAVR with power transformation is the best predictive model and is recommendable to forecasting practice.

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