Pre-Breakdown Processes in the Hollow Cathode Region of a Transient Hollow Cathode Discharge

Discharge formation in the A–K space of transient hollow cathode discharge (THCD) is causally linked with the emission of high energy electron beams originating in the hollow cathode region (HCR). Ionization in the A–K gap proceeds through the formation of a moving virtual anode, whose time evolution is strongly correlated with different periods in the electron beam activity. Here, we report on time and space resolved observations of different ionization events inside the HCR, which are time correlated with ionization processes inside the A–K gap. The experiments have been performed in Hydrogen, at pressures between 50 and 400 mTorr. A statistical study of the characteristic times associated with the different ionization events, based on von Laue plots, shows that the time distribution of events is well described by a single Gaussian distribution.     

Constraints of Housing Age and Migration on Residential Mobility

This paper investigates the role of housing age in constraining residential mobility, measured as the percent of households that have moved into their homes in the past 15 months. The leading explanation for why mobility rates differ so much among regions of the United States has been the overall level of growth. The present analysis shows that the growth effect operates through both the newness of population (migration) and the newness of housing available for occupancy by all local residents. The posited explanation for this housing age effect is that progressively older units contain increasingly settled occupants, yielding fewer opportunities for in-movers in areas with older housing. It is empirically demonstrated that households in older housing have lower likelihood of recent mobility even after controlling for age, tenure, migration status, and state location of residence. The analysis reveals the temporal interdependency of mobility, migration, person age, and housing age.     

Acoustic bubble counting technique using sound speed extracted fromsound attenuation

Sound attenuation has been solely used to estimate bubble size distributions of bubbly water in the conventional acoustic bubble sizing methods. These conventional methods are useful for the void fraction around 10^-6 or lower. However, the change of compressibility in the bubbly water also should be considered in bubble sizing for the void fraction around 10^-5 or higher. Recently the sound speed as well as sound attenuation was considered for acoustic bubble size estimation in bubbly water. In this paper, the sound speed estimated from sound attenuation in bubbly water by an iterative method is used for a bubble counting. This new iterative inverse bubble sizing technique is numerically tested for bubble distributions of single-size Gaussian, and power-law functions. The numerical simulation results are in agreement with the given bubble distributions even for the high void fractions of 10^-4-10^-3. It suggests that the iterative inverse technique can be a very powerful tool for practical use in acoustic bubble counting in the ocean     

Some experiments and considerations for development of Doppler-based riverine sonars

Sonar counting devices have been utilized by fisheries biologists to estimate annual spawning migrations of anadromous salmon. Recent developments in signal detection based on the Doppler principle, and new information on fish sound scattering characteristics at the high frequencies used in riverine sonar, should result in much improved detection and classification capability. These are discussed along with some practical considerations for the deployment of sonar devices for counting fish in rivers.     

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

Constructing rainfall depth-frequency curves considering a linear trend in rainfall observations

Comprehensive flood prevention plans are established in large basins to cope with recent abnormal floods in South Korea. In order to make economically effective plans, appropriate design rainfalls are critically determined from the rainfall depth-frequency curves which take the occurrence of abnormal floods into consideration. Conventional approaches to construct the rainfall depth-frequency curves are based on the stationarity assumption. However, this assumption has a critical weak aspect in that it cannot reflect non-stationarities in rainfall observations. As an alternative, this study suggests the non-stationary Gumbel model (NSGM) which incorporates a linear trend of rainfall observations into rainfall frequency analysis to construct the rainfall depth-frequency curves. A comparison of various schemes employed in the model found that the proposed NSGM permits the estimation of the distribution parameters even when shifted in the future by using linear relationships between rainfall statistics and distribution parameters, and produces more acceptable estimates of design rainfalls in the future than the conventional model. The NSGM was applied at several stations in South Korea and then expected the design rainfalls to increase by up to 15–30% in 2050.     

Analysis of recent climate change over the Arctic using ERA-Interim reanalysis data

This study investigates recent climate change over the Arctic and its link to the mid-latitudes using the ERA-Interim global atmospheric reanalysis data from the European Center for Medium-Range Weather Forecast （ECMWF）. Since 1979, sub- stantial surface warming, associated with the increase in anthropogenic greenhouse gases, has occurred over the Arctic. The great- est warming in winter has taken place offshore in the Kara-Barents Sea, and is associated with the increase in turbulent heat fluxes from the marginal ice zone. In contrast to the marked warming over the Arctic Ocean in winter, substantial cooling appears over Siberia and eastern Asia, linked to the reduction of Arctic sea ice during the freezing season （September-March）. However, in summer, very little change is observed in surface air temperature over the Arctic because increased radiative heat melts the sea ice and the amount of turbulent heat gain from the ocean is relatively small. The heat stored in the upper ocean mixed layer in summer with the opening of the Arctic Ocean is released back to the atmosphere as turbulent heat fluxes during the autumn and through to the following spring. This warming of the Arctic and the reduced sea ice amplifies surface cooling over Siberia and eastern Asia in winter.     

Conservation of Korean Rural Heritage through the Use of Ecomuseums

Rural heritage that involves agricultural heritage could be critical to enhancing community identity through a conservational approach. The purpose of this research is to develop conservational methods for rural heritage that include agricultural heritage areas through the use of ecomuseums. To conduct the research, we first reviewed the concepts of ecomuseum and rural heritage. Secondly, we defined the concept of the Korean rural ecomuseum by taking into consideration the concept defined by Riviere, Globally Important Agricultural Heritage Systems (GIAHS), the rural heritage policy of Europe, and the agricultural heritage systems of Korea. Thirdly, we also describe methods that are applicable to Korean rural ecomuseums, which include type classification and components. Finally, we applied the ecomuseum concept to two pilot models in the Cheongsando and Gurae areas, both Korea Important Agricultural Heritage System (KIAHS) sites. We conclude that it is desirable to expand the range of targets for conservation from agricultural heritage to rural heritage areas. From this point of view, the rural ecomuseum can be a highly valuable tool that can help preserve agricultural heritage sites and neighboring areas. Furthermore, the ecomuseum can enhance community identities, and strengthen local economies.     

Comparison of radiocarbon and OSL dating methods for a Late Quaternary sediment core from Lake Ulaan,Mongolia

Both radiocarbon and optically stimulated luminescence (OSL) dating methods were applied to test their suitability for establishing a chronology of arid-zone lacustrine sediments using a 5.88-m-long core drilled from Lake Ulaan, southern Mongolia. Although the radiocarbon and OSL ages agree in some samples, the radiocarbon ages are older than the corresponding OSL ages at the 550-cm depth horizon (late Pleistocene) and in the 100–300-cm interval (early to late Holocene). In the early to late Holocene, radiocarbon ages are consistently older than OSL ages by 4,100–5,800 years, and in the late Pleistocene by 2,700–3,000 years. Grain-size analysis of early to late Holocene sediments and one late Pleistocene sediment sample (550-cm depth) indicates that eolian processes were the dominant sediment-transport mechanism. Also, two late Pleistocene sediments samples (from 400- to 500-cm depths) are interpreted to have been deposited by both eolian and glaciofluvial processes. Accordingly, the radiocarbon ages that were older than the corresponding OSL ages during the Holocene seem to have been a consequence of the influx of ¹⁴C-deficient carbon delivered from adjacent soils and Paleozoic carbonate rocks by the westerly winds, a process that is also active today. In addition to the input of old reworked carbon by eolian processes, the late Pleistocene sediments were also influenced by old carbon delivered by deglacial meltwater. The results of this study suggest that when eolian sediment transport is suspected, especially in lakes of arid environments, the OSL dating method is superior to the radiocarbon dating method, as it eliminates a common ‘old-carbon’ error problem.