The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper develops a general framework for learning interpretable data representation via Long Short-Term Memory (LSTM) recurrent neural networks over hierarchal graph structures. Instead of learning LSTM models over the pre-fixed structures, we propose to further learn the intermediate interpretable multi-level graph structures in a progressive and stochastic way from data during the LSTM network...
In recent years, Deep Learning has been successfully applied to multimodal learning problems, with the aim of learning useful joint representations in data fusion applications. When the available modalities consist of time series data such as video, audio and sensor signals, it becomes imperative to consider their temporal structure during the fusion process. In this paper, we propose the Correlational...
Subspace learning has been widely used in signal processing, machine learning, computer vision and so on. Matrix rank minimizing is a fundamental model. Nuclear norm is a convex relaxation for rank minimizing. In this paper, we propose a polynomial function to smoothen the nuclear norm. Lagrange multipliers method is employed to solve the problem. The optimal solution is obtained by iterative procedure...
There has been incredible growth of events over the internet in recent years. Google has become the giant source of knowledge for any event which has happened or happening over the internet. Some networking sites such as face book, micro blogging sites such as twitter are evolved with time and became the highly used sites over the internet. Various E-commerce websites such as Amazon, Ebay, Flipkart...
In recent years, CubeSats have emerged as a platform of intense interest for a wide range of applications, including remote sensing. Of specific interest in this paper are data processing challenges associated with the MIT's Microwave Atmospheric Satellite (MicroMAS). Due to the motion of MicroMAS and the geometry of the data acquisition process, measurements are not collected on a regular grid of...
This paper discusses a methodology to construct a synthetic dataset using realistic geophysical data and the L-MEB model to compute synthetic brightness temperatures (Tb's) and to train a Neural Network (NN) for global retrievals of soil moisture (SM). The trained NNs are applied to real Tb's measured by the Soil Moisture and Ocean Salinity (SMOS) satellite (L-MEB NN). The objective is twofold. First,...
With the requirements of antenna pointing accuracy increasing, the high frequency flexible characteristics have become the important factor of limiting the control performance for antenna servo systems. In this paper, an identification method is given to identify the mobile satcom antenna (MSCA) servo system with flexible structure. Using PRBS as the input signal, the impulse response is acquired...
Because of the characteristics of the availability and practicability, mobile media technology had got a rapid development in the whole world. So, people now often use mobile devices through a mobile application (APP). Based on this, this study established a mobile application customer engagement model to carry on the investigation and research about mobile application of customers' recommendation...
With the demand of power information construction and the application of D5000 platform, the standardization and management of all kinds of data becomes a necessary condition for data sharing and application integration between systems. In order to realize the safe, convenient and efficient information resource sharing of power enterprises and improve the information management level, the fusion method...
Multi-view correlation learning has attracted great attention with the proliferation of heterogeneous data. Typical methods, such as Canonical Correlation Analysis (CCA) and its variants, usually maximize one-to-one corresponding correlation of inter-view data, while most of them neglect discriminative multi-label information and local structure of each view data. In this paper, we propose multi-label...
Nowadays, in order to observe and control data centers in an optimized way, people collect a variety of monitoring data continuously. Along with the rapid growth of data centers, the increasing size of monitoring data will become an inevitable problem in the future. This paper proposes a correlation-based reduction method for streaming data that derives quantitative formulas between correlated indicators,...
Explaining observations in terms of cause-and-effect (causal) relations is central to empirical science. However, in his seminal 1964 work [1], John Bell showed that the correlations between entangled quantum systems cannot be explained in terms of, possibly hidden, cause and effect relations. After four decades of experimental effort, Bell's prediction has recently been confirmed in an unambiguous...
This work explores the true user QoE according to the users' preferences and behaviors when the users know that they are being observed and concern about their privacy. We propose a systematic privacy-aware QoE evaluation scheme based on the observable user data. Firstly, we translate the subjective privacy- aware QoE evaluation problem into the objective rational user analysis procedure. Then, a...
The service technology and crowdsourcing movement have spawned a host of successful efforts that promote the rapid development of the human service ecosystem. In this ecosystem, a large number of globally-distributed freelancers are organized to tackle a range of tasks over the web. These crowdsourcing services provide convenience for civilians with lower price and shorter response time. However,...
Search results in technical forums are typically keyword based. The relevance of a link is usually gauged by closest content match. However, it has been shown in literature that users' click behavior is an integral part of deciding the relevance of a search result. Moreover, it is not just the number of clicks that matter, but time spent on a clicked link, order in which the links were clicked etc...
Prediction of the behavior of the grouped users in the future is a meaningful research question. In this paper, we take the transit users as an example to introduce the phase space reconstruction method and use the massive sequence data to model the large-scale system with a dynamic evolution model. At the same time, considering the shortcomings of the general prediction method in large data set,...
The present paper addresses the problem of the estimation of the day-ahead generated power (GP) of a photovoltaic plant using predicted regional solar radiation (SR). The contribution is twofold. First, it investigates the problems related to the design of day-ahead SR predictors and then studies their combination with the prediction data obtained from a meteorological service. Different setups of...
Variations in sensor data collected from equipment have been widely analyzed by using anomaly detection methods for predictive maintenance. Our experience shows that correlations between sensors effectively predict failures because the correlations usually reflect the status of equipment with higher sensitivity. In this paper, we present a method that exploits correlations between sensors for pre-processing...
ICT in education is a significant strategic to promote the development and innovation of education. Most research studies focus on the establishment of the evaluation indicator system, but performance evaluation is important to the development of ICT in education. Based on the gray theory and fuzzy algorithm, this study analyzed the evaluation model of ICT in education, designed an evaluation system...
Categorical data exist in many domains, such as text data, gene sequences, or data from Census Bureau. While such data are easy for human interpretation, they cannot be directly used by many classification methods, such as support vector machines and others, which require underlying data to be represented in a numerical format. To date, most existing learning methods convert categorical data into...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.