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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...
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...
Financial variables are of primary importance in financial modeling, fraud detection, financial distress management, price modeling, credit and risk evaluations and in evaluating the return on assets and portfolios. There usually exist a large number of financial variables, where their exhaustive integration in a model increases its dimensionality and the associated computational time. We extensively...
Aiming at the problem of fault detection for satellite communication system, a prediction method based on Gaussian mixture model is proposed. Firstly, the observation sequence is collected by modem as well as frequency conversion equipment. Then feature parameters are extracted after pre-processing. The expectation maximum algorithm is applied to train the Gaussian mixture model. The posterior probabilities...
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,...
Via online social interactions, users in social networks can form their personal attitudes toward other users. Some of the personal social attitudes will be expressed explicitly, which are represented as the signed social links from the initiators to the recipients. In this paper, we will study the "social Attitude exPression prEdiction" (APE) problem, which aims at inferring both the expression...
Post silicon trimming is extensively used to counter the effects of manufacturing process variation on certain critical electrical parameters of an integrated circuit (IC). Usually, trimming is performed iteratively by adjusting the resistance value of a trim circuit to specific discrete values. Test programs represent those values by codes and apply common search algorithms in order to find a code...
In recent years remaining useful life prediction of metro bearing is paid much more attention. Different faults have different prediction models for bearings. In this paper, the remaining useful life prediction based on fault diagnosis is proposed. With the aid of the cyclic stability characteristic of the bearing signal, a spectral correlation density combination method is proposed and used to fault...
Text categorization, or text classification, is one of key tasks for representing the semantic information of documents. Multi-label text categorization is finer-grained approach to text categorization which consists of assigning multiple target labels to documents. It is more challenging compared to the task of multi-class text categorization due to the exponential growth of label combinations. Existing...
Friend recommendation has been one of the most challenging problems as the social networks grow rapidly, due to the needs of seeking people who are acquaintances in real life or share the common interests. In this paper, we tackle the problem by treating it as a link prediction task and propose a hybrid algorithm that exploits the existing friendship links, users' history ratings and the tags annotated...
The predictive maintenance of industrial machines is one of the challenging applications in the new era of Industry 4.0. Thanks to the predictive capabilities offered by the emerging smart data analytics, data-driven approaches for condition monitoring are becoming widely used for early detection of anomalies on production machines. The aim of this paper is to provide insights on the predictive maintenance...
The goal of this paper is to study how friendship clusters evolve in online social networks. Results obtained from our work on Facebook data indicate that the set of friends who actively interact during a particular time interval is only a fraction of the total number of listed friends and this set of active friends tends to evolve with time. Interaction footprints on the timeline are used to cluster...
Automatic image annotation has been an important research topic in facilitating large scale image management and retrieval. Existing methods focus on learning image-tag correlation or correlation between tags to improve annotation accuracy. However, most of these methods evaluate their performance using top-k retrieval performance, where k is fixed. Although such setting gives convenience for comparing...
Imaging-genetic data mapping is important for clinical outcome prediction like survival analysis. In this paper, we propose a supervised conditional Gaussian graphical model (SuperCGGM) to uncover survival associated mapping between pathological images and genetic data. The proposed method integrates heterogeneous modal data into the survival model by weighted projection within the data. To obtain...
human splicing branchpoints are functional elements of the alternative splicing, and the study on branchpoints can help to understand the mechanism of human pre-mRNA transcript. There are a large number of human splicing branchpoints, but the wet methods that identify branchpoints are labor-intensive and time-consuming. In this paper, we utilize machine learning techniques to build models for the...
While both spectral and prosody transformation are important for voice conversion (VC), traditional methods have focused on the conversion of spectral features with less emphasis on prosody transformation. This paper presents a novel pitch transformation method for VC. As the correlation of spectral features and fundamental frequency in pitch perceptions has been proved, well-converted spectrum should...
Early detection of depression is important to improve human well-being. This paper proposes a new method to detect depression through time-frequency analysis of Internet behaviors. We recruited 728 postgraduate students and obtained their scores on a depression questionnaire (Zung Self-rating Depression Scale, SDS) and digital records of Internet behaviors. By time-frequency analysis, we built classification...
This paper puts forward a testability modeling method for analog circuit fault prediction. It firstly gets the grey correlation entropy of each test point in the analog circuit. Then it treats each grey correlation entropy as a correlation coefficient to form the dependency matrix of testability. After that, according to the dependency matrix we get, the paper uses the method of PSO (Particle Swarm...
Social network is a hot topic of interest for the researchers in the field of computer science in recent years. The vast amount of data generated by these social networks play a very important role in information diffusion. Social network data are generated by its users. So, user's behavior and activities are being investigated by the researchers to get a logical view of social network platform. This...
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