Structure analysis of single- and multi-frequency subspace migrations in inverse scattering problems

In this literature, we carefully investigate the structure of single- and multi-frequency imaging functions, that are usually employed in inverse scattering problems. Based on patterns of the singular vectors of the Multi-Static Response (MSR) matrix, we establish a relationship between imaging functions and the Bessel function. This relationship indicates certain properties of imaging functions and the reason behind enhancement in the imaging performance by multiple frequencies. Several numerical simulations with a large amount of noisy data are performed in order to support our investigation.Comment: 11 pages, 10 figure

アカマツとクロマツの種子の生産量に関する研究 (2)

この研究はアカマツの種子生産量に関する一連の研究として, アカマツの種子の生産量を京都市岩倉のアカマツ林で調査した結果をとりまとめたものである。1973年10月に20×20mの方形区を設け毎木調査した後, 6本の試料木を伐採し各部分の量や球果の数を測定した。そしてSeed Trapによる調査を1973年10月から1974年6月まで行なった。 その結果は次のようであった。アカマツの球果の数と技乾重との間にはもっとも高い相関関係が認められた。一方球果の数と葉乾重との間には一定の関係が認められたが, その相関係数は低い値を示した。球果の全数は樹令が高くなるに従いおおむね増加する傾向が認められた。球果の生産量は年によって大きく変化するようであった。またその年の球果を多くつけている個体は翌年度の球果生産量も多くなる傾向が認められるようであった。Seed Trapを用いた場合アカマツ種子の生産量は710, 000粒/haと推定された。一方種子数 - D_2H関係から推定された種子生産数は1, 300, 000粒/haとなりSeed Trapの場合より著しく過大な値を示した。枝葉単位 (kg) あたりの球果数は個体の上部ほど増加する傾向が見受けられた。アカマツの種子は12月以前に68％以上が落下するようであった。This study was carried out to estimate seed production in the Japanese red pine stand, a private forest located at Iwakura, northeastern part of Kyoto, during the period from October 1973 to June 1974. Analysis was made for 6 trees, sampled from the above mentioned forest, and seed trap method was applied as a supplementary experiment. The results are as follows; 1) Among several factors, the correlation between cone number and branch weight was high. 2) Total cones, disseminating cones, and conelets increase with age, but the points along the regression line were scattered widely. 3) The relation between total cone number and leaf weight seemed to be comparativley low. 4) A large annual variation was observed in cone crop at the Iwakura pine forest. 5) A significant correlation between cone and conelet was observed (r=0. 93 at Iwakura, r=0. 82 at Kamigamo). 6) Trapping seed number was 710, 000/ha, while estimation by D_2・H factor was 1, 300, 000/ha. The estimation by D_2•H factor seems to be overestimated compared with the seed trap method. 7) Viewing the vertical distribution of cones the higher part of the tree crown, the larger cone numbers when cone number is counted in terms of cone number per unit weight ofleaf and branch. 8) More than 68 per cent of seeds fell before December at the experiment stan

Analysis of Weighted Multifrequency MUSIC-Type Algorithm for Imaging of Arc-Like, Perfectly Conducting Cracks

The main purpose of this paper is to investigate the structure of the weighted multifrequency multiple signal classification (MUSIC) type imaging function in order to improve the traditional MUSIC-type imaging. For this purpose, we devise a weighted multifrequency MUSIC-type imaging function and examine a relationship between weighted multifrequency MUSIC-type function and Bessel functions of integer order of the first kind. Some numerical results are demonstrated to support the survey

Understanding Dynamic Spatio-Temporal Contexts in Long Short-Term Memory for Road Traffic Speed Prediction

Reliable traffic flow prediction is crucial to creating intelligent transportation systems. Many big-data-based prediction approaches have been developed but they do not reflect complicated dynamic interactions between roads considering time and location. In this study, we propose a dynamically localised long short-term memory (LSTM) model that involves both spatial and temporal dependence between roads. To do so, we use a localised dynamic spatial weight matrix along with its dynamic variation. Moreover, the LSTM model can deal with sequential data with long dependency as well as complex non-linear features. Empirical results indicated superior prediction performances of the proposed model compared to two different baseline methods.Comment: 10pages, 2 tables, 4 figures, 2017 KDD Cu