Structure of adjectives in Japanese

Call number: LD2668 .T4 1964 I26Master of Scienc

Name Her Reiko! : The Ikemiya Diaspora

This creative-nonfiction project encapsulates a Japanese family diaspora to America beginning in the late 1880s. Through short stories, poems, and monologues, the author expresses familial struggles such as living in a foreign land and being Japanese in White America. The author reflects on her grandparents\u27 time in the Japanese internment camps where they faced hardship and hegemonic oppression as well as her father\u27s experience of growing up Japanese-American in Los Angeles. The stories weave together history, hardship, and race to create a unique diaspora story

Automatic Piano Transcription with Hierarchical Frequency-Time Transformer

Taking long-term spectral and temporal dependencies into account is essential for automatic piano transcription. This is especially helpful when determining the precise onset and offset for each note in the polyphonic piano content. In this case, we may rely on the capability of self-attention mechanism in Transformers to capture these long-term dependencies in the frequency and time axes. In this work, we propose hFT-Transformer, which is an automatic music transcription method that uses a two-level hierarchical frequency-time Transformer architecture. The first hierarchy includes a convolutional block in the time axis, a Transformer encoder in the frequency axis, and a Transformer decoder that converts the dimension in the frequency axis. The output is then fed into the second hierarchy which consists of another Transformer encoder in the time axis. We evaluated our method with the widely used MAPS and MAESTRO v3.0.0 datasets, and it demonstrated state-of-the-art performance on all the F1-scores of the metrics among Frame, Note, Note with Offset, and Note with Offset and Velocity estimations.Comment: 8 pages, 6 figures, to be published in ISMIR202

Monte Carlo simulation of metal deposition on foreign substrates

The deposition of a metal on a foreign substrate is studied by means of grand canonical Monte Carlo simulations and a lattice-gas model with pair potential interactions between nearest neighbors. The influence of temperature and surface defects on adsorption isotherms and differential heat of adsorption is considered. The general trends can be explained in terms of the relative interactions between adsorbate atoms and substrate atoms. The systems Ag/Au(100), Ag/Pt(100), Au/Ag(100) and Pt/Ag(100) are analyzed as examples.Comment: 26 pages, 9 figure

The structural analysis of Cu(111)-Te (√3 × √3) R30° and (2√3 × 2√3)R30° surface phases by quantitative LEED and DFT,

The chemisorption of tellurium on atomically clean Cu(111) surface has been studied under ultra-high vacuum conditions. At room temperature, the initial stage of growth was an ordered 23×23R30° phase (0.08 ML). An ordered 3×3R30° phase is formed at 0.33 ML coverage of Te. The adsorption sites of the Te atoms on the Cu(111) surface at 0.08 ML and 0.33 ML coverages are explored by quantitative low energy electron diffraction (LEED) and density functional theory (DFT). Our results indicate that substitutional surface alloy formation starts at very low coverages

Controlling Activity and Selectivity Using Water in the Au-Catalysed Preferential Oxidation of CO in H\u3csub\u3e2\u3c/sub\u3e

Industrial hydrogen production through methane steam reforming exceeds 50 million tons annually and accounts for 2–5% of global energy consumption. The hydrogen product, even after processing by the water–gas shift, still typically contains ∼1% CO, which must be removed for many applications. Methanation (CO + 3H2 → CH4 + H2O) is an effective solution to this problem, but consumes 5–15% of the generated hydrogen. The preferential oxidation (PROX) of CO with O2 in hydrogen represents a more-efficient solution. Supported gold nanoparticles, with their high CO-oxidation activity and notoriously low hydrogenation activity, have long been examined as PROX catalysts, but have shown disappointingly low activity and selectivity. Here we show that, under the proper conditions, a commercial Au/Al2O3 catalyst can remove CO to below 10 ppm and still maintain an O2-to-CO2 selectivity of 80–90%. The key to maximizing the catalyst activity and selectivity is to carefully control the feed-flow rate and maintain one to two monolayers of water (a key CO-oxidation co-catalyst) on the catalyst surface