Evaluation of ICA and CEM algorithms with Landsat-8/ASTER data for geological mapping in inaccessible regions

Many regions remain poorly studied in terms of geological mapping and mineral exploration in inaccessible regions especially in the Arctic and Antarctica due to harsh conditions and logistic difficulties. Application of specialized image processing techniques is capable of revealing the hidden linear mixing spectra in multispectral and hyperspectral satellite images. In this study, the applications of Independent component analysis (ICA) and Constrained Energy Minimization (CEM) algorithms were evaluated for Landsat-8 and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data for geological mapping in Morozumi Range and Helliwell Hills areas, Northern Victoria Land (NVL), Antarctica. The results of this investigation demonstrate the capability of the two algorithms in distinguishing pixel and subpixel targets in the multispectral satellite data. The application of the methods for identifying poorly exposed geologic materials and subpixel exposures of alteration minerals has invaluable implications for geological mapping and mineral exploration in inaccessible regions.     

Characterizing the effect of heavy metal contamination on marine mussels using metabolomics

Marine mussels (Mytilus) are widely used as bioindicators to measure pollution in marine environments. In this study, (1)H NMR spectroscopy and multivariate statistical analyses were used to differentiate mussel groups from a heavy metal-polluted area (Onsan Bay) and a clean area (Dokdo area). Principal component analysis and orthogonal projection to latent structure-discriminant analysis revealed significant separation between extracts of mussels from Onsan Bay and from the Dokdo area. Organic osmolytes (betaine and taurine) and free amino acids (alanine, arginine, glutamine, phenylalanine, and threonine) were more highly accumulated in Onsan Bay mussels compared with Dokdo mussels. These results demonstrate that NMR-based metabolomics can be used as an efficient method for characterizing heavy metal contamination derived from polluted area compared to clean area and to identify metabolites related to environments that are contaminated with heavy metals.     

Segmentation of the Housing Market and its Determinants: Seoul and its neighbouring new towns in Korea

This study identifies the spatial pattern of housing price changes and their determinants in Seoul and its neighbouring new towns. The results of a cluster analysis show that the spatial pattern of housing price change rates is nor correlated with housing prices. It is found that housing price change rates vary with the Chonse price index and money supply, building permit area, stock price index, and yield on 3 year corporate bonds. It is also shown that the more apartment units that are built in a region, the lower the housing price change rate.     

EK-Fenton process for removal of phenanthrene in a two-dimensional soil system

Feasibility of electrokinetic (EK) process combined with Fenton-like reaction was investigated for the removal of phenanthrene in a two-dimensional cell. Sandy soil and bentonite were selected as a model soil and a filling material to inhibit the leak of electrolyte solution within the electrode reservoirs into the soil by hydraulic pressure difference, respectively. The effects of parameters including current, electroosmotic flow (EOF), electrolyte pH, and moisture content on the removal efficiency were examined under constant voltage.

At the end of operation for 21 days, the concentration of phenanthrene near the anode was lower than the other positions of soil specimen and increased gradually towards the cathode because hydrogen peroxide solution was supplied from anode to cathode region following the direction of EOF. The concentration of phenanthrene at the bottom soil was lower than that at the top soil. Because capillary attraction in the sandy soil with high porosity was too low to maintain appropriate moisture at the top of the cell, EOF moved through the bottom soil with higher moisture content. Overall removal efficiency at 140 V was 81.6%, which was higher than 68.9% at 100 V because total EOF increased by a factor of 1.5 upon increase of the voltage from 100 to 140 V. In addition, power consumptions at 100 and 140 V were 7.2 and 19.4 kWh, respectively.     

Remote sensing of ocean sound speed profiles by a perceptron neuralnetwork

A method is developed to estimate ocean sound speed profiles through synthesis of remotely measured environmental data and historical statistics of sound speed obtained at a remotely sensed location. Sound speed profiles are represented by an expansion of empirical orthogonal functions (EOF) of the historical sound speed variation, while the remotely sensed environmental data provide real-time information to determine the expansion coefficients. Environmental inputs are limited to sea surface temperature available from satellite infrared sensors, acoustic time-of-flight and ocean bottom temperature measurable from bottom mounted acoustic and thermal transducers. A multilayer perceptron neural network is implemented to learn the functional transformation from the measured environmental input to the desired EOF coefficient output on a set of representative sound speed profiles. Sea surface temperature, time-of-year, and time-of-flight from the acoustic multipath that maximally samples the vertical sound speed are found to be the dominant inputs. The trained network is computationally efficient and produces estimates for untrained environmental inputs with a mean error of 1.1-4.4 m/s     

The influence of context on lifeline behavior: Local policies under wind storm and earthquake scenarios

Local policies can play an important role in establishing a context that shapes vulnerability and influences subsequent recovery of lifelines under the natural hazards of extreme wind and seismic events. External factors, such as access availability, have long been known to influence the rate of restoration of utility systems following blackouts. Thus, since system performance takes place within a socio-technical-political context, it can be anticipated that selected local policies may also influence either the geographic extent of damage or the rate of restoration or both. This project empirically validates the assumption that selected local non-design policies establish a context that significantly (measurably) influences system functionality in terms of spatial extent and duration of outage.