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Mid-Infrared (MIR) spectroscopy has emerged as the most economically viable technology to determine milk values as well as to identify a set of animal phenotypes related to health, feeding, well-being and environment. However, Fourier transform-MIR spectra incurs a significant amount of redundant data. This creates critical issues such as increased learning complexity while performing Fog and Cloud...
In recent years, the importance of feature engineering has been confirmed by the exceptional performance of deep learning techniques, that automate this task for some applications. For others, feature engineering requires substantial manual effort in designing and selecting features and is often tedious and non-scalable. We present AutoLearn, a regression-based feature learning algorithm. Being data-driven,...
It is found that the GARCH (1,1) model has a good fitting effect on the time series by the statistical analysis of the logarithmic yield of the closing price of the Shanghai Composite Index. Therefore, this paper first uses the model GARCH (1,1) predicts the daily closing price of the Shanghai Composite Index, and then uses the Fourier series to correct the predicted residuals to obtain the final...
Networks are models representing relationships between entities. Often these relationships are explicitly given, or we must learn a representation which generalizes and predicts observed behavior in underlying individual data (e.g. attributes or labels). Whether given or inferred, choosing the best representation affects subsequent tasks and questions on the network. This work focuses on model selection...
Precipitation prediction, such as short-term rainfall prediction, is a very important problem in the field of meteorological service. In practice, most of recent studies focus on leveraging radar data or satellite images to make predictions. However, there is another scenario where a set of weather features are collected by various sensors at multiple observation sites. The observations of a site...
Aerosol optical depth (AOD), one of the key factors affecting the atmosphere visibility, has great influence on the prediction of radiation intensity and photovoltaic power generation. Considering the problem that AOD is difficult to obtain real-timely and conveniently with high accuracy, in this paper, PM2.5 concentration, PM10 concentration and temperature, wind speed grade and relative humidity...
Parkinson's disease is a debilitating and chronic disease of the nervous system. Traditional Chinese Medicine (TCM) is a new way for diagnosing Parkinson, and the data of Chinese Medicine for diagnosing Parkinson is a multi-label data set. Considering that the symptoms as the labels in Parkinson data set always have correlations with each other, we can facilitate the multi-label learning process by...
As average life expectancy continuously rises, assisting the elderly population with living independently is of great importance. Detecting abnormal behaviour of the elderly living at home is one way to assist the eldercare systems with the increase of the elderly population. In this study, we perform an initial investigation to identify abnormal behaviour of household residents using energy consumption...
Load forecasting is the basis of the design and implementation of the control strategy of the combined cooling heating and power (CCHP) system, and the precision affects the comprehensive energy efficiency of the system directly. In this paper, the gray relational analysis method is used to indicate the strong coupling relationship among the loads of heating, cooling and electricity in the system...
Free-head 3D gaze tracking outputs both the eye location and the gaze vector in 3D space, and it has wide applications in scenarios such as driver monitoring, advertisement analysis and surveillance. A reliable and low-cost monocular solution is critical for pervasive usage in these areas. Noticing that a gaze vector is a composition of head pose and eyeball movement in a geometrically deterministic...
As a state-of-the-art ensemble method, random forest which exhibits a good ability to predict and generalize on various dataset is often composed of a large number of trees. Redundancy of ensemble and connotative decision rules result in expensive operational costs as well as difficulties in comprehension. In this paper, novel leaf node-level pruning methods for random forest are proposed. Each leaf...
A protein is a long one-dimensional amino acid sequence. Some subsequences of this sequence are given names and β-strand in one such subsequence. β-strands are very common and two or more such strands within one protein can form a β-sheet in the secondary structure of proteins. In its natural form, a protein is a three-dimensional entity composed of β-sheets, α-helices, and other types of substructures...
Every year, a number of the students who obtain their bachelor's degree attend a university in order to continue their graduate studies. Most universities attempt to encourage their top students to continue education in the same university. On the other hand, they receive applicants from other universities, and selecting the top students among these candidates without a thorough examination may not...
In this paper, we study the influence from the sentiment of regular tweets on retweeting. We propose a method to calculate the sentiment score for each tweet and each Twitter user. This method enables us to place the tweets and retweets into the same time period to explore the sentiment factor. We adopt the correlation coefficient between the sentiment scores of regular tweets and those of retweets...
Accurately predicting driving service orders in different regions is an essential task for service companies, in order to improve the service quality. In this paper, a specific ensemble multi-view prediction framework is proposed to address this task. It ensembles several different multi-view-based models with a weighted linear combination. Specifically, we have designed three specific multi-view-based...
Bike sharing systems (BSSs) have become common in many cities worldwide, providing a new transportation mode for residents' commutes. However, the management of these systems gives rise to many problems. As the bike pick-up demands at different places are unbalanced at times, the systems have to be rebalanced frequently. Rebalancing the bike availability effectively, however, is very challenging as...
A heterogeneous memory system (HMS) consists of multiple memory components with different properties. GPU is a representative architecture with HMS. It is challenging to decide optimal placement of data objects on HMS because of the large exploration space and complicated memory hierarchy on HMS. In this paper, we introduce performance modeling techniques to predict performance of various data placements...
Heterogeneous defect prediction (HDP) aims to predict defect-prone software modules in one project using heterogeneous data collected from other projects. Recently, several HDP methods have been proposed. However, these methods do not sufficiently incorporate the two characteristics of the defect prediction data: (1) data could be linearly inseparable, and (2) data could be highly imbalanced. These...
Prediction of fouling in power plant heat exchanger is greatly influenced by the periodic fouling process and change in dynamics of the operational parameters. In order to address this, a prediction model using Nonlinear Auto Regressive with eXogenous inputs (NARX) neural network is proposed to monitor cleanliness factor. The experimental results demonstrate that the proposed model can predict the...
Advanced spatio-temporal electric load modeling and accurate spatio-temporal load forecast are essential to both short-term operation and long-term planning of power systems. This paper explores the spatio-temporal dependencies of electric load time series. The Southern California feeder load data show that feeders which are spatially close to each other share a more similar load pattern than those...
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