Person to Person in Japan

While still in the midst of their study abroad experiences, students at Linfield College write reflective essays. Their essays address issues of cultural similarity and difference, compare lifestyles, mores, norms, and habits between their host countries and home, and examine changes in perceptions about their host countries and the United States. In this essay, Van Ha describes his observations during his study abroad program at Rikkyo University in Tokyo, Japan

A comparison of classification techniques for monitoring and mapping land cover and land use changes in the subtropical region of Thai Nguyen, Vietnam : a thesis presented in partial fulfilment of the requirements for the degree of Master of Environmental Management at Massey University, Palmerston North, New Zealand

Deriving land cover/land-use information from earth observation satellite data is one of the most common applications for environmental monitoring, evaluation and management. Many parametric and non-parametric classification algorithms have been developed and applied to such applications. This study looks at the classification accuracies of three algorithms for different spatial and spectral resolution data. The performance of Random Forest (RF) was compared to Maximum Likelihood (MLC) and Artificial Neural Network (ANN) algorithms for the separation of subtropical land cover/land-use categories using Sentinel-2 and Landsat 8 data. The overall, producers’ and users’ accuracies were derived from the confusion matrix, while local land use statistics were also collected to evaluate the accuracy of classified images. The accuracy assessment showed the RF algorithm regularly outperformed the MLC and ANN in both types of imagery data (>90%). This approach also exhibited potential in dealing with the challenge of separating similar man-made features such as urban/built-up and mining extraction classes. The ANN algorithm had the lowest accuracy among the three classification algorithms, while Landsat 8 imagery was most suitable for the classification of subtropical mixed and complex landscapes. As the RF algorithm demonstrated a robustness and potential for mapping subtropical land cover/land-use, this study chose it to monitor and map temporal land cover/land-use changes in Thai Nguyen, Vietnam between 2000 and 2016. The results of this temporal monitoring revealed that there were substantial changes in land cover/land use over the course of 16 years. Agricultural and forest land decreased, while urban and mining extraction land expanded significantly, and water increased slightly. Changes in land cover/land-use are strongly associated with geographic locations. The conversion of agriculture and forest into urban/builtup and mining extraction land was detected largely in the Thai Nguyen central city and southern regions. In addition, further GIS analysis revealed that approximately 69.6% (100.2km2) of new built-up areas had occurred within 2km of primary roads, and nearly 96% (137.6km2) of new built-up expansion was detected within a 5-km buffer of the main roads. This study also demonstrates the potential of multi-temporal Landsat data and the combination of remote sensing, GIS and R programming to provide a timely, accurate and economical means to map and analyse temporal changes for long-term local land use development planning. Keywords: Random forest; Land cover mapping; Remote Sensing; Vietna

Estimating the Division Kernel of a Size-Structured Population

We consider a size-structured population describing the cell divisions. The cell population is described by an empirical measure and we observe the divisions in the continuous time interval [0, T ]. We address here the problem of estimating the division kernel h (or fragmentation kernel) in case of complete data. An adaptive estimator of h is constructed based on a kernel function K with a fully data-driven bandwidth selection method. We obtain an oracle inequality and an exponential convergence rate, for which optimality is considered

Effects of grain size distribution on the initial strain shear modulus of calcareous sand

The soil’s small strain shear modulus, Gmax or G0, is applied in dynamic behavior analyses and is correlated to other soil properties (density and void ratio) for predicting soil dynamic behavior under seismic loadings such as earthquakes, machinery or traffic vibrations. However, for calcareous sands, selecting representative samples for the field conditions is difficult; therefore, almost all measured soil parameters (post-seismic properties) do not reflect exactly the soil state before seismic loading. In some cases of dynamic loading, a change in grain size distribution (GSD) of soils, especially for calcareous sands might occur. Moreover, many of these sand types behave differently from silica sands owing to their mineralogy, particle characterization, soil skeleton, and the continuous changing of particle size. For this reason, a series of isotropic consolidation tests in ranges of confining pressure from 25 to 300 kPa as well as bender element measurements on a calcareous sand and on a reference silica sand were performed in this study. The effects of differences in gradation and in the type of material on the soil’s small strain shear modulus, Gmax, are discussed

Association between estrus and onset of seizures in dogs with idiopathic epilepsy

Background: Catamenial epilepsy in humans is defined as changes in seizure frequency over the course of the menstrual cycle. Three hormonally based patterns of seizure exacerbation have been determined. Objectives: The aim of this study was to evaluate whether there is an association between onset of seizures and the estrous cycle in intact bitches with presumptive idiopathic epilepsy and whether a pattern to the onset of seizures could be recognized. Animals: Forty- five intact female dogs from a hospital population with a presumptive diagnosis of idiopathic epilepsy. Methods: In a retrospective study, the database of a small animal hospital in Sweden was searched for medical records of intact female dogs diagnosed with epilepsy or seizures. The stage of the estrous cycle as reported either by the owner or the veterinarian at the time of the first seizure was noted. Results: Of the 45 dogs with idiopathic epilepsy, 17 ( 38%) had their first seizure when in heat and six dogs ( 13%) had their first seizure 1- 3 months after heat. Nine dogs ( 20%) had seizures reoccurring in relation to their estrous cycle. Conclusions and Clinical Importance: These findings suggest an association between estrus and onset of seizures in intact bitches with presumptive idiopathic epilepsy. Two hormonally based patterns could be recognized: one during heat and one during a specific time point at the end of diestrus. This could be explained by the proconvulsive effects of estrogen or loss of protective effect against seizures of progesterone, respectively