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In the last few years, with the emergence of ambient assisted living, the study of human behavioral pattern took a wide interest from research communities around the world. In many literatures, pattern recognition was widely adopted approach to implements in human behavior study from computing perspective. Pattern recognition brings a promising results in terms of accuracy for modeling human behavior...
Aiming at the problem that the semantic explanation of the existing topic model is poor and the accuracy is not high, a semi-supervised topic learning and representation method based on association rules and metadata is proposed. First, we used the metadata as a priori knowledge to guide the topic learning, and got the probability distribution of the term in the document. Then, we got the frequent...
It is more and more common to use function words as an important text feature of Chinese, such as the research on “A Dream of Red Mansions” of Li Xianping. But the effect of using all function words as a feature in distinguishing writers' writing style is not prominent. Our study finds that using the classical Chinese function words and sentence tail function words as a feature is better than differentiated...
A general methodology of device array mismatch characterization is introduced, analyzed and verified. Instead of measuring each device's parameter individually, the device array is configured as a data converter and the mismatch information is extracted from the differential linearity (DNL) of the converter. Systematic and random mismatch are characterized separately using the proposed decomposition...
Light emitting diode (LED) lighting is the most promising energy saving solution for future lighting application. For some LED applications, such as the building or bridge lighting application, the corresponding LED lighting system will be expected to be functional as long as the objects stand. Therefore it is necessary to obtain the degradation regularity of LED lighting systems and predict when...
As part of a longer-term project to compare different methods of extracting emission-area data from ideal Fowler-Nordheim plots, this Poster investigates refinements to the extraction-parameter approach. It is shown that varying the choice of the scaled fitting parameter ft, depending on the range of values used for the independent variable, does make a noticeable difference. However, the (usually...
This tutorial lecture provides an introduction (suitable for those relatively new to the subject) to methods available for the extraction of emitter characterization data from field electron emission (FE) current-voltage data, to the problems of doing this reliably, and to some recent progress in developing better understanding of the issues involved.
A curve fitting method based on automatically extracting subsection points is proposed to fit the wheel tread profile accurately. Firstly, the subsection points are determined by segmenting discrete points of wheel tread profile based on given errors and threshold. Secondly, the segmentation interval is determined with the respective segment point as the center, and the least squares curve fitting...
In the background of large data, information security faces more opportunities and challenges. Image steganography as an important means of information hiding, is widely used in military, medical, commercial and other important occasions. Two-dimensional code image as a convenient means of information exchange everywhere. In this paper, an improved LSB information hiding algorithm is designed based...
Tapioca starch is the important for Thai agricultural industry economy. According to the 4th industrial revolution, cyber-physical system becomes the key technology to enable vertical and horizontal automation system integration. This study aims to develop cyber-physical system based production monitoring for tapioca starch production. To achieve the service oriented architecture (SOA) based solution...
The blast furnace gas is an important secondary energy for the iron and steel production. Establishing an effective model to describe the state of BFG system is of great significant to maintain the system balance and stability. Considering the strong coupling characteristics of the blast furnace gas system and the high level noises in the industrial data, a simplex unscented Kalman filter-based Wang-Mendel...
For nonlinear estimation, the Gaussian sum filter (GSF) provides a flexible and effective framework. It approximates the posterior probability density function (pdf) by a Gaussian mixture in which each Gaussian component is obtained using a linear minimum mean squared error (LMMSE) estimator. However, for a highly nonlinear problem with large measurement noise, the estimation performance of the LMMSE...
Given a collection of event-related documents, event ranking generates a list of ranked events based on the input query. Ranking news events, which takes event related news documents for the generation of ranked events, is both an essential research issue and important component for many security oriented applications, such as public event monitoring, retrieval, detection and mining. Previous related...
A rapid development of E-Commerce platforms has allowed retailers to introduce online product recommendations to persuade consumers purchase decisions. Recommendations system in E-Commerce can be implemented through development of opinion review or feedback system. The visibility of opinion review as a persuasive communication tool in recommendation context has been proven as an important role in...
We present a new algorithm for discovering clusters in noisy data streams using dynamic and cluster-specific temporal decay factors. Our improvement helps identify and adapt to evolving trends by adapting the weighting of stream data based on both content attributes and temporal arrival patterns. Our experimental results show that the proposed algorithm can discover better quality clusters in noisy...
Information sharing among e-marketplace consumers can reflect trust and distrust in products and sellers. Trustworthiness of products and sellers helps consumers to make a good purchase decision. E-marketplace websites, who encourage consumers to rate their products using only a single dimension such as five-star rating system, is unable to reveal the consumer satisfaction in details. In this paper,...
Credit scoring is an important process in every financial institution and bank. Its high accuracy in classifying customers helps decrease the credit risk and increase reliability and profit. In this paper, we propose a binary classification approach that can classify customers who apply for loans. A statistical technique called Stepwise Regression (SR) is used as a pre-process to select important...
Physical modeling studies at the laboratory scale close the gap between computer simulations and field experiments. In ground-penetrating radar (GPR), such physical models are, for example, useful to study wave propagation phenomena, to evaluate mathematical models, and to develop tools for data analysis, processing, and interpretation. Here, we present an experiment, which has been designed to study...
Main purpose of this paper is to outline options of atmospheric pressure determination with help of TDOA method location. The TDOA system uses the ASTERIX data format. There is the exploration of profitable data extraction from ASTERIX data format. Also the principle of atmospheric pressure determination is explained. As a results there are shown derived atmospheric pressure data and its accuracies.
In this study, the estimation performances of Multiple Linear Regression, Random Forest, and Artificial Neural Network are examined comparatively. For comparison of these data mining techniques, the power production data from a Photovoltaic Module was used in the research. In this study, the model was constituted from seven variables. One of the variables is dependent (power) and the others are independent...
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