Reconstruction of Missing Hourly Precipitation Data to Increase Training Data Set for ANN

This paper investigates the hourly precipitation estimation capacities of ANN using raw data and reconstructed data using proposed Precipitation Sliding Window Period (PSWP) method. The precipitation data from 11 Automatic Weather Station (AWS) of Delhi has been obtained from Jan 2015 to Feb 2016. The proposed PSWP method uses both time and space dimension to fill the missing precipitation values. Hourly precipitation follows patterns in particular period along with its neighbor stations. Based on these patterns of precipitation, Local Cluster Sliding Window Period (LCSWP) and Global Cluster Sliding Window Period (GCSWP) are defined for single AWS and all AWSs respectively. Further, GCSWP period is classified into four different categories to fill the missing precipitation data based on patterns followed in it. The experimental results indicate that ANN trained with reconstructed data has better estimation results than the ANN trained with raw data. The average RMSE for ANN trained with raw data is 0.44 and while that for neural network trained with reconstructed data is 0.34.

A NEW GLOBAL REVOLUTION IN SCIENCE AND EDUCATION

The article notes that the formation of the global world is taking place and this world is reflected in science and education, and these spheres vice versa the world formation. It is shown that a global research direction has already been formed, including globalistics, global scientific disciplines, globalization studies, global evolutionism and a number of other scientific research areas. Although this global cluster of scientific knowledge is most intensively developed only since the second half of the last century, its origins are found in the works of Vladimir I. Vernadsky at the beginning of the same century. The global cluster of scientific knowledge is associated with the globalization of education and the formation of global education. The main integrative characteristics and features in the forms and content of these global evolutionary processes in education are identified. The authors use global and systemic approaches, integrative-interdisciplinary research methods, historical and evolutionary approaches, methods of forecasting, as well as a number of general scientific methods. It is shown that integrative tendencies related to the global-evolutionary changes of civilization and its interaction with nature are unfolding in education. The article notes that the globalization of education is mainly focused on formal and organizational ways of integrating various systems and forms of education; the most significant directions of this process are highlighted. Global education is characterized by qualitative and meaningful transformations of the educational process, the subject field of which is “filled” with universal and integrative knowledge obtained in the course of global research. It is assumed that the globalization of science and education begins a new global revolution in the scientific and educational space, and the phenomenon of “globality” appears as global processe and system.

Collective dynamics of repeated inference in variational autoencoder rapidly find cluster structure

Deep neural networks are good at extracting low-dimensional subspaces (latent spaces) that represent the essential features inside a high-dimensional dataset. Deep generative models represented by variational autoencoders (VAEs) can generate and infer high-quality datasets, such as images. In particular, VAEs can eliminate the noise contained in an image by repeating the mapping between latent and data space. To clarify the mechanism of such denoising, we numerically analyzed how the activity pattern of trained networks changes in the latent space during inference. We considered the time development of the activity pattern for specific data as one trajectory in the latent space and investigated the collective behavior of these inference trajectories for many data. Our study revealed that when a cluster structure exists in the dataset, the trajectory rapidly approaches the center of the cluster. This behavior was qualitatively consistent with the concept retrieval reported in associative memory models. Additionally, the larger the noise contained in the data, the closer the trajectory was to a more global cluster. It was demonstrated that by increasing the number of the latent variables, the trend of the approach a cluster center can be enhanced, and the generalization ability of the VAE can be improved.

ON THE THEORY OF THE ORIGIN OF GLOBAL CLUSTER SYSTEMS AROUND THE GALAXIES

The origin of poor and moderate globular cluster systems around galaxies against the background of a nonlinear non-stationary model of collapsing galaxies is studied. The stability of the model with respect to four perturbation modes is studied, and the degree of the mode determines on average the number of clusters in the system. A critical dependence of the initial virial relation on the degree of rotation is constructed for each mode. The dependences of the instability increments on the physical parameters of the model are found.

FORMATION OF AN INNOVATIVE MEDICAL CLUSTER IN THE STRUCTURE OF THE REGION

The article is devoted to the consideration of the formation of an innovative medical cluster in the structure of the region. The importance of cluster policy as a tool for increasing regional competitiveness is emphasized. A classification of the concept of cluster policy is given from the position of the state’s role in stimulating innovation, as well as the formation by cluster participants of an interaction mechanism based on a breakthrough idea. Tendencies in the development of global cluster initiatives in medicine are systematized. The main types of medical clusters existing in the world practice are highlighted and their key characteristics are given. A comparison of the level of development of European and Russian clusters in the biopharmaceutical and medical industries is given. The main features of the innovative medical cluster in the Sverdlovsk region are formulated, its model is presented. The vision of the medical cluster management system is shown.

Science And Education In The Conditions Of Formation Of The Global World

One of the main social transformations is that the formation of the global world is taking place and this world is reflected in science and education, and these last begin to form it. It is shown that to a large extent a global direction of research has already been formed, which includes globalistics, global scientific disciplines, globalization research, global evolutionism and a number of other areas of scientific research. Although this global cluster of scientific knowledge is most intensively developed only in the second half of the last century, its origins are found in the works of V. I. Vernadsky at the beginning of the same century. The global cluster of scientific knowledge is associated with the globalization of education and the formation of global education. The main integrative characteristics and features in the forms and content of these global evolutionary processes in education are revealed. It is shown that integrative tendencies connected with global-evolutionary changes of civilization and its interaction with nature are developed in education. It is noted that the globalization of education is focused mainly on the formal and organizational methods of integration of different systems and forms of education; the most important directions of this process are highlighted. And global education is characterized by qualitative and meaningful transformations of the educational process, the subject field of which is "filled" with universal-integrative knowledge obtained in the course of global studies. It is assumed that with the globalization of science and education begins a new global revolution in the scientific and educational space.