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.
The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmentation of nuclei from breast histopathology images are carried out by Localized Active Contour Model (LACM) utilizing bio-inspired optimization techniques...
For many decision making problems, all the possible alternatives are treated equally before one find the most desirable alternative. But, it is a little unreasonable if all alternatives are treated equally. So, in this paper by taking the aggregation operator into account, the weights of criteria can be determined successfully. There in to, the parameters for aggregation operator are the decision...
Hospitals can experience difficulty in detecting and responding to early signs of patient deterioration leading to late intensive care referrals, excess mortality and morbidity, and increased hospital costs. Our study aims to explore potential indicators of physiological deterioration by the analysis of vital-signs. The dataset used comprises heart rate (HR) measurements from MIMIC II waveform database,...
Specific Emitter Identification (SEI) is to identify the emitters with various RF fingerprints, originated from the nonlinearity of the emitter power amplifiers. This paper firstly develops an improved Approximate Entropy (imApEn) algorithm, by modifying the tolerance interval of Approximate Entropy (ApEn), to extract the nonlinear complexity of the signals as a new steady-state RF fingerprint. Then...
Heart rate variability (HRV) is a simple, non-invasive measure that can be used to quantify autonomic nervous system modulation. This method has been used to detect alterations of autonomic cardiovascular regulation in diabetes and metabolic syndrome (MetS). MetS is characterized by the clustering of glucose intolerance, central obesity, dyslipidemia, and hypertension. This study analyze the HRV using...
High-speed automaton is core component of small caliber artillery, because of its poor working condition, the crack and wear of each component and its working reliability have gradually become the focus of fault monitoring and diagnosis. This traditional test method (mainly used in the field of weapon) not only needs a lot of cost and time, but also is vulnerable to many uncertain factors. Therefore,...
Thyroiditis is a health disorder and it refers to “inflammation of the thyroid glands”. Once a thyroid nodule has been detected (or suspected), the first test that is routinely being performed is the fine needle aspiration (FNA) biopsy (invasive). This test result is helpful in the classification of the nodule being benign or malignant with the aid of bio-markers. Another common test is the Ultrasound...
Feature selection and reduction has assumed the position of a leading approach for many preprocessing step in machine learning. It is widely used as preprocessing in classification due to an exponential growth in data set as well as in feature set. The aim of this paper is to contribute in the domain of feature selection, which directly reduces the complexity and speed up the learning algorithm by...
A key assumption of distributed data fusion is that individual nodes have no knowledge of the global network topology and use only information which is available locally. This paper considers the weighted exponential product (WEP) rule as a methodology for conservatively fusing estimates with an unknown degree of correlation between them. We provide a preliminary investigation into how the methodology...
This paper proposes a novel evolutionary approach to the optimal selection of electrodes as well as relevant EEG features for effective classification of cognitive tasks. The problem has been formulated in the framework of a single objective optimization problem with an aim to simultaneously satisfy three criteria. The first criterion deals with maximization of the correlation between the features...
Technology innovation is an important driven force for the economic development, the risk of which deserves attentions, and to evaluate risk accurately and effectively can be helpful to improve the success rate of technology innovation. As the risk of technology innovation is of strong uncertainty and fuzziness, the existing risk evaluation methods have certain limitations, while matter-element model...
Personality prediction has broad prospects of application in real life. It can be accomplished by analyzing massive and variant data in social networks, which conveys one's personal traits through user generated contents, user's social relationships and behaviors. However, it is difficult to design an effective feature representation from such complex data to predict user's personality as well as...
Fingerprint detection is one of the primary methods for identifying individuals. Gray Level Co-occurrence Matrix (GLCM) is the oldest and prominent statistical textual feature extraction method applied in many fields for texture analysis. GLCM holds the distribution of co-occurring intensity patterns at a given offset over a given image. However, images occupy excessive space in storage by its original...
Depth maps are becoming increasingly important in the context of emerging video coding and processing applications. Depth images represent the scene surface and are characterized by areas of smoothly varying grey levels separated by sharp edges at the position of object boundaries. To enable high quality view rendering at the receiver side, preservation of these characteristics is important. Lossless...
In this paper, we present an analysis of recorded eye-fixation data from human subjects viewing video sequences. The purpose is to better understand visual attention for videos. Utilizing the eye-fixation data provided in the CRCNS (Collaborative Research in Computational Neuroscience) dataset, this paper focuses on the relation between the saliency of a pixel and that of its direct neighbors, without...
Image classification is a hot topic of pattern recognition in computer vision. In order to achieve high accuracy of classification, a certain amount of high quality pictures are needed. As a matter of fact, high quality pictures are scarce. Active learning can solve such a problem. Label dependences play an important role in multi-label active learning for image classification. The interdependences...
Content based image retrieval is a way of indexing or finding images in a database those are similar to a query image. This process uses visual contents of images and provides more effective management for automatic retrieval of images of interest than the traditional tagged based approach. In this paper, color and texture features are used as visual contents to retrieve similar images from the database...
To reduce the huge consumption of traditional sensing, a multi-centers estimation based sensing scheme is proposed in this paper. Firstly, all potential channels are clustered into highly related groups with some channels selected as detecting channels (DCs) using an unsupervised algorithm. In each group, the states of other channels (estimated channels, ECs) are estimated according to their correlations...
In a distributed video coding problem, use of a correct model for the correlation noise plays a significant role in improving the decoding performance and consequently in providing higher coding efficiency. In this work, we first study the predictive and additive correlation noise models at the DCT coefficient band level for transform-domain distributed video coding. Then, bounds on compression rates...
Traditional group evaluation methods for complex simulation system credibility are always ignore the correlations among the evaluation indices and those among evaluation experts which lead to the evaluation result inaccurate. To address this problem, a new group evaluation method for complex simulation system credibility with the correlated assumption for evaluation indices and evaluation experts...
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.