Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Metric Multidimensional Scaling-Based Nonlinear Manifold Learning Approach for Unsupervised Data Reduction
Biomedical research has entered a new era of characterizing a disease or a protein on a global scale. In the post-genomic era, Proteomics now plays an increasingly important role in dissecting molecular functions of proteins and discovering biomarkers in human diseases. Mass spectrometry, two-dimensional gel electrophoresis, and high-density antibody and protein arrays are some of the most commonly used methods in the Proteomics field.
The topic ‘elite’ may be dealt with either in a few lines, or in many pages.
There is no half way. In fact, it encompasses issues which are crucial to
the social sciences, such as the relation between the distribution of wealth,
prestige and power; the exercise of power and the composition of the group
that holds it. The list is extensive.
This project measures and classifies language variation. In contrast to earlier dialectology, we seek a comprehensive characterization of (potentially gradual) differences between dialects, rather than a geographic delineation of (discrete) features of individual words or pronunciations. More general characterizations of dialect differences then become available. We measure phonetic (un)relatedness between dialects using Levenshtein distance, and classify by clustering distances but also by analysis through multidimensional scaling.
In order to realize their full potential, multimodal systems need to support not just input from multiple modes, but also synchronized integration of modes. Johnston et al (1997) model this integration using a unification operation over typed feature structures. This is an effective solution for a broad class of systems, but limits multimodal utterances to combinations of a single spoken phrase with a single gesture. We show how the unification-based approach can be scaled up to provide a full multimodal grammar formalism.
Navigation in large, complex and multidimensional information spaces is still a challenging task. The search is even more difﬁcult in small devices such as MP3 players, which only have a reduced screen and lack of a proper keyboard. In the MIAMM project 1 we have developed a multimodal dialogue system that uses speech, haptic interaction and advanced techniques for information visualization to allow a natural and fast access to music databases on small scale devices.