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

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

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

The regularity of points in multi-projective spaces

Let I = p_1^{m_1} \cap ... \cap p_s^{m_s} be the defining ideal of a scheme of fat points in P^{n_1} x ... x P^{n_k} with support in generic position. When all the m_i's are 1, we explicitly calculate the Castelnuovo-Mumford regularity of I. In general, if at least one m_i >= 2, we give an upper bound for the regularity of I, which extends the result of Catalisano, Trung and Valla to the multi-projective case.Comment: 12 pages with minor revisions. To appear in JPA