There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Data Mining Practical Machine Learning Tools and Techniques

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

The author systematically examines one of the important issues of information — establishing the market price. He introduces the concept of «search» — where a buyer wanting to get a better price, is forced to question sellers. The article deals with various aspects of finding the necessary information.

Economics of Information

Maximum Principle for the Time-Space Fractional Diffusion Equations

Traffic station classification based on deep spatio-temporal network

This is the preprint version of our paper on EUROGRAPHICS 2015 A big city visual analysis platform based on Web Virtual Reality Geographical Information System (WEBVRGIS) is presented Extensive model editing functions and spatial analysis functions are available, including terrain analysis, spatial analysis, sunlight analysis, traffic analysis, population analysis and community analysis

Preprint Big City 3D Visual Analysis

Whole constraint and partial triplet-center loss for infrared-visible re-identification

There exists growing evidence that circRNAs are concerned with many complex diseases physiological processes and pathogenesis and may serve as critical therapeutic targets. Identifying disease-associated circRNAs through biological experiments is time-consuming, and designing an intelligent, precise calculation model is essential. Recently, many models based on graph technology have been proposed to predict circRNA-disease association. However, most existing methods only capture the neighborhood topology of the association network and ignore the complex semantic information. Therefore, we propose a Dual-view Edge and Topology Hybrid Attention model for predicting CircRNA-Disease Associations (DETHACDA), effectively capturing the neighborhood topology and various semantics of circRNA and disease nodes in a heterogeneous network. The 5-fold cross-validation experiments on circRNADisease indicate that the proposed DETHACDA achieves the area under receiver operating characteristic curve of 0.9882, better than four state-of-the-art calculation methods.

Zhihan Lv

Papers

Maximum Principle for the Time-Space Fractional Diffusion Equations

Traffic station classification based on deep spatio-temporal network

Preprint Big City 3D Visual Analysis

Whole constraint and partial triplet-center loss for infrared-visible re-identification

DETHACDA: A Dual-view Edge and Topology Hybrid Attention Model for CircRNA-Disease Associations Prediction.