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Disconnection from mechanical ventilation, called the weaning process, is an additional difficulty in the management of patients in intensive care units (ICU). Unnecessary delays in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we propose an extubation index based on the power of the respiratory flow signal (Pi). A total of 132 patients...
Biopsy remains the gold standard for the diagnosis of chronic liver diseases. However, the concordance between readers is subject to variability causing an increasing need of objective tissue description methods. A complete framework has been implemented to analyze histological images from any kind of tissue. Based on the feature selection approach, it computes the most relevant subset of descriptors...
This paper presents a comparison between two different technologies of acquisition systems (BrainNet36 and Emotiv Epoc) for an Independent-BCI based on Steady-State Visual Evoked Potential (SSVEP). Two stimuli separated by a viewing angle < 1° were used. Multivariate Synchronization Index (MSI) technique was used as feature extractor and five subjects participated in the experiments. The class...
Water army means a special group of online users who get paid for posting comments and new threads or articles on different online communities and websites for some hidden purposes. Due to the fact that the nature of the posting behavior of water army is not fully and understood, the driving force detection of the bursty topic for web forum is still a difficult problem to solve. According to the analysis...
Over the past decade Online Social Networks (OSNs) have been helping hundreds of millions of people develop reliable computer-mediated relations. However, many user profiles in OSNs contain misleading, inconsistent or false information. Existing studies have shown that lying in OSNs is quite widespread, often for protecting a user's privacy. In order for OSNs to continue expanding their role as a...
The bump hunting, proposed by Friedman and Fisher, has become important in many fields such as marketing and medical fields, and etc. Among them, to answer the unresolved question of molecular heterogeneity and of tumoral phenotype in cancer, the local sparse bump hunting algorithm, such as CART (Classification and Regression Trees) and PRIM (Patient Rule Induction Method), is useful. In the bump...
Leaf chlorophyll content (LCC) is an important indicator for wheat growth monitor. In this paper, the integrated inversion approach was developed to estimate the wheat LCC. Based on the PROSAIL simulation data set, three hyperspectral vegetation indices (VIs), PRI, TCARI and TCARI/OSVAI, were comparative analyzed to screen out optimal VI for wheat LCC estimation. The integrated inversion models to...
Diverse flight situations will have different influences on the function of a pilot's brain. To study these influences and confirm the sensitivity of related measurements, flight simulation tasks are carried out on an aircraft cockpit ergonomics evaluation experimental base. Subjects are required to monitor the changes of flight information and make corresponding flight operations simultaneously....
This paper proposes a method for estimating the green space ratio in urban areas by using airborne LiDAR and aerial photographs. The index is defined as the ratio of an area occluded by vegetation to the whole of an area in an azimuth-elevation angle space. Vegetation is detected by a combination of segmented LiDAR data point clouds and image brightness data. The occlusion by vegetation is calculated...
Real-time non-destructive diagnosis of crop nitrogen (N) status is crucially important for the success of in-season site-specific N management. Chlorophyll meter (CM) has been commonly used to non-destructively estimate crop leaf chlorophyll concentration, and indirectly estimate crop N status. Dualex 4 is a newly developed leaf fluorescence sensor that can estimate both leaf chlorophyll concentration...
The research on community structure is a key to analyze the network functionality and topology, and thus it is significant to detect and analysis the community structure. During the abstract process from an actual system to a network, especially for a large-scale network, it is inevitable to have mistaken connections between nodes or have connection missing. In addition, in real applications, from...
Emerging Patterns (EPs) can discover biologic gene rules from microarray. It can classify test samples, and help people developing drugs to adjust the gene expression to normal value. However, current EP can discover only one cut point to classify the two types for each gene expression array. But in fact, microarray datasets always have more than two types to predict, namely, multi-classification...
Link prediction is a fundamental problem in social network analysis. The key technique in link prediction is to find an appropriate similarity measure between nodes of a network. Generally, external information besides the network topology is considered in many similarity measures. However, these external information is generally not available or not true. Usage of these external information may result...
In this paper, we present a novel self-maintaining, domain-independent, and context-sensitive Sentiment Lexicon (SL) which finds and maps opinion words and phrases to a fuzzy sentiment score ranging from strong negative to strong positive. We show that our automatically built SL has advantage over other already existing lexicons in various aspects, namely, reducing the number of word false-matches...
A high frequency voltage standard of NIM from 30 kHz to 30 MHz is designed based on thermal voltage converters. In this standard, seven TVCs of different sizes are used to cover the voltage range from 0.1 V to a maximum of 100 V with UHF vacuum thermocouples and non-inductive resistors. The new high-frequency standard has been shown to have an accuracy of 0.01% at 1 MHz and 1 V by comparing it with...
Stability of feature selection from high-dimensional data is an important and active research area. Ensemble feature selection has emerged as an effective method to improve the stability of feature selection. However, it results in a significant increase of computational cost in many real world applications. In this paper, we propose an improved ensemble feature selection framework using random sampling...
Comparing with the traditional method of credit evaluation, this paper presents a classification evaluation method based on the projection pursuit and the fuzzy rules. Firstly, we use projection pursuit technology to reducing the dimensionality of the training sample, and use genetic algorithm to optimize the projection direction to find the best projection value, classification in accordance with...
For some classification tasks the data can be partitioned into disjoint subsets based on some attribute, for example a disease subtype. It then seems logical to train a classifier with the same classes as the original classification problem for each subtype separately, such that the performance per subtype is optimized. Unfortunately, the influence of the subtype performances on the aggregated overall...
A novel concept, uniqueness logic represented via decimal numbers (UL-D), is proposed and defined in this paper. Aiming at achieving the UL-D, we construct a neural network (i.e., NN) based on weights-and-structure-determination algorithm (i.e., the resultant WASD-NN). Differing from the back-propagation neural network (BP-NN) adjusting weights by lengthy iterative process and being unable to acquire...
In this paper, we address the problem of defect detection in textile images, and present a novel hybrid method where independent vector analysis, a statistical method, is combined with wavelet transformation, a spectral method. Independent vector analysis, a generalization of independent component analysis, uses vectorized signals, thus, enables exploiting multiple datasets and offers a fully multivariate...
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