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Psoriasis is one of the most stressful skin diseases. The accurate assessment and effective management of the disease is one of the contributing factors in reducing the time required for relieving the disease symptoms. As the treatment is unusually subjective, an automatic and efficient computer aided assessment technique is an active area of research. In this study, we developed an automatic psoriasis...
Biomarkers have tremendous potential in different phases of treatment such as risk assessment, screening/detection, diagnosis and patient's response prediction. In this paper, we present an approach for development of a generic tool for an end to end analysis of expression data to identify the probable biomarkers. We follow machine learning as well as network analysis approaches in parallel. We use...
The paper considers the problem of feature selection in learning using privileged information (LUPI), where some of the features (referred to as privileged ones) are only available for training, while being absent for test data. In the latest implementation of LUPI, these privileged features are approximated using regressions constructed on standard data features, but this approach could lead to polluting...
A novel fault detection method based on margin statistics of generalized non-negative matrix factorization (GNMF) is proposed. The construction of traditional process monitoring method based on multivariate statistical that neglects the correlation relation and feature distribution of latent variables at different sampling times, and the method also need to assume that latent variables satisfy a particular...
In this paper, we aimed to investigate the difference between the surface electromyogram (sEMG) signals recorded from the right hand and left hand by means of the statistical analysis of the root mean square (RMS). Twenty-five healthy subjects participated in this experiment. For the entail 19 s recorded data of every repetition, we selected a window length of 250 ms data start from the beginning...
In many biological studies, statistical and data mining methods are extensively used to analyze the data and discover actionable knowledge. But, bad data quality causing incorrect analysis results and wrong interpretations may induce misleading conclusions and inadequate decisions. To ensure the validity of the results, avoid bias and data misuse, it is necessary to control not only the whole analytical...
The new social media have become popular for information spreading, allowing online users to publish latest events and personal opinions. However, massive spam comments seriously decrease users' reading experience. To detect spam comments in Chinese social media, we employ semantic analysis to build the self-extensible dictionary which updates and extends itself with new cyber words automatically...
This paper is mainly through the following research process to show: first of all, making a pretreatment to news text corpus in football field, including word segmentation, de-stop words and POS tagging, and then extract the candidate concept set in the processed corpus, And then use the Word2Vec tool to train the corpus to get the multidimensional vector model file for all the words in the corpus,...
Opinion mining based on Chinese online comments has been widely concerned, and its goal is to analyze user's attitude towards commodities' features from massive online comments. Commodity feature extraction is the basis of opinion mining. Most existing commodity feature extraction methods cannot achieve cooperating analysis of semantic rules and commodity feature extraction, or applying statistical...
The maintenance of static standing balance is not only essential for performing everyday activities but is also an important risk factor for prediction of falls in the elderly adults. Human balance / posture control is controlled by complex integration of different senses. The changes in steadiness of balance can be characterized by center-of-pressure (COP) signals measured from a 3-D force plate...
The diagnosis of disease with the aid of computer programs has been developing more and more in recent years. This paper presents an approach which is based on frequency technique for the objective quantitative analysis of facial paralysis. In this method, limited-orientation modified circular Gabor filters (LO-MCGFs) are used to enhance the desirable frequencies in images. Then, features are extracted...
Gas recognition, smell identification and source localization are among complex problems in today's industry. In this study, we employed an electronic nose (Enose) and applied the Locally Linear Embedding (LLE) algorithm to detect and classify four kinds of industrial gas including C02, NH3, CH4, Volatile Organic Compounds (VOCs). The AIRSENSE PEN3 Enose was used for gas detection and odor data acquisition...
Defects in apples cause food safety concerns touching the general public and strongly affect the commodity market. Due to the increasing incidence, the detection of bruises is a challenge now a day's especially when the bruises are not visible externally. Infrared imaging provides an important window for detection of bruises that are not visible externally. The study has been investigated on the infrared...
In this paper, the statistical properties of pixel displacements in turbulence degraded images are analyzed. Two main problems are addressed before that. One is the computation of pixel displacements. Dense optical flow is used since blur makes features like points and edges hard to track. The other one is selection of statistical samples. We use 2D-Hilbert transform to extract feature points, and...
Generally different websites have different web page structures, which would heavily affect the extraction quality when the web content is automatically collected. On the basis of a statistical analysis on content features and structure characteristics of News domain web pages, this paper proposes a maximum continuous sum of text density (MCSTD) method to efficiently and effectively extract web content...
Medical research is experiencing a paradigm shift from “one-size-fits-all” strategy to a precision medicine approach where the right therapy, for the right patient, and at the right time, will be prescribed. We propose a statistical method to estimate the optimal individualized treatment rules (ITRs) that are tailored according to subject-specific features using electronic health records (EHR) data...
The Paper propose a processing method for LiDAR data in power line inspection tour. The classification of the point cloud with the data feature in the patrol is the first step. On this basis, using the geometric information of different types of point cloud in feature extraction and statistical analysis to obtain the cross-cutting and security risks information which is required by the power line...
In this paper, in order to explore underlying the interaction mechanisms between brain regions, the cross entropy measures: cross sample entropy (C-SampEn) and cross fuzzy entropy (C-FuzzyEn) were used to measure the brain synchrony through analyzing the background electroencephalograph (EEG) signals in Alzheimer's disease (AD) patients. It was demonstrated that the values of both the two features...
This paper presents a novel humming feature extraction algorithm based on locality statistical analysis to tackle the problem of the instability of humming features in the query by humming (QBH) system. By carrying out statistics to humming notes sequences in both longitudinal vocal range distribution and horizontal temporal variation distribution, we can obtain the locality statistical humming features...
This study presents a machine learning approach applied to ElectroEnchephaloGraphic (EEG) response in a group of subjects when exposed to a controlled olfactory stimulation experiment. In the literature, in fact, there are controversial results on EEG response to odorants. This study proposes a robust leave-one-subject-out classification method to recognize features extracted from EEG signals belonging...
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