40 Result(s)
within
English
Computer Science
Computation by Abstract Devices
Pattern Recognition
Dong-**ng Wang
Conference Paper
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Chapter and Conference Paper
Classifying DNA Microarray for Cancer Diagnosis via Method Based on Complex Networks
Performing microarray expression data classification can improve the accuracy of a cancer diagnosis. The varying technique including Support Vector Machines (SVMs), Neuro-Fuzzy models (NF), K-Nearest Neighbor ...
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Chapter and Conference Paper
Prediction of Subcellular Localization of Multi-site Virus Proteins Based on Convolutional Neural Networks
Prediction of subcellular localization is critical for the analysis of mechanism and functions of proteins and biological research. A series of efficient methods have been proposed to identify subcellular loca...
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Chapter and Conference Paper
The Study on Grade Categorization Model of Question Based on on-Line Test Data
To tackle with the blindness of random questions choosing for exercise and test of the on-line learning system, this paper clusters questions exploiting various feature subsets and parameters via K-means. For...
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Chapter and Conference Paper
Identity Authentication Technology of Mobile Terminal Based on Cloud Face Recognition
The face recognition of mobile terminal plays an important role in the identity authentication technology. But there are some problems such as long detection time and low recognition rate due to the performanc...
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Chapter and Conference Paper
Improved Convolutional Neural Networks for Identifying Subcellular Localization of Gram-Negative Bacterial Proteins
Prediction of subcellular localization of Gram-negative bacterial proteins plays a vital role in the development of antibacterial drugs. Computational approaches have made remarkable progress in bacterial prot...
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Chapter and Conference Paper
Distributed Processing of Continuous Range Queries Over Moving Objects
With the widespread usage of wireless network and mobile devices, the scale of spatial-temporal data is dramatically increasing and a good deal of real world applications can be formulated as processing conti...
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Chapter and Conference Paper
Learning Bayesian Networks Structure Based Part Mutual Information for Reconstructing Gene Regulatory Networks
As a kind of high-precision correlation measurement method, Part Mutual Information (PMI) was firstly introduced into Bayesian Networks (BNs) structure learning algorithm in the paper. Compared to the general ...
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Chapter and Conference Paper
The Feature Extraction Method of EEG Signals Based on the Loop Coefficient of Transition Network
High accuracy of epilepsy EEG automatic detection has important clinical research significance. The combination of nonlinear time series analysis and complex network theory made it possible to analyze time ser...
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Chapter and Conference Paper
Global Adaptive and Local Scheduling Control for Smart Isolated Intersection Based on Real-Time Phase Saturability
Linking real-time phase saturability directly to the traffic signal control, the global adaptive control scheme for traffic light loop and the local scheduling control strategy for phase green time are propose...
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Chapter and Conference Paper
Predicting Multisite Protein Sub-cellular Locations Based on Correlation Coefficient
With the development of proteomics and cell biology, protein sub-cellular location has become a hot topic in bioinformatics. As the time goes on, more and more researchers make great efforts on studying protei...
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Chapter and Conference Paper
Safety Inter-vehicle Policy Based on the Longitudinal Dynamics Behaviors
The analysis of the safety inter-vehicle distance plays important roles for driving assistant system, which can give the warning signal to drivers timely. In order to provide the drivers a warning signal about...
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Chapter and Conference Paper
Using a Hierarchical Classification Model to Predict Protein Tertiary Structure
To predict protein tertiary structure accurately is helpful for understanding the functions of proteins. In this study, a hierarchical classification method based on flexible neural tree was proposed to predic...
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Chapter and Conference Paper
Prediction and Analysis of Mature microRNA with Flexible Neural Tree Model
miRNA is a class of small non-coding RNA molecules, length of about 20–24 nucleotides. It combines with mRNA by the principle of complementary base pairing to achieve the objective of cracking or suppressing m...
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Chapter and Conference Paper
Credit Risk Assessment Based on Long Short-Term Memory Model
At present, with continuously expanding of Chinese credit market, thus large amounts of P2P (person-to-person borrow or lend money in Internet Finance) platform were born and have been in development. Most of ...
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Chapter and Conference Paper
Deep and Sparse Learning in Speech and Language Processing: An Overview
Large-scale deep neural models, e.g., deep neural networks (DNN) and recurrent neural networks (RNN), have demonstrated significant success in solving various challenging tasks of speech and language processin...
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Chapter and Conference Paper
A Simple Review of Sparse Principal Components Analysis
Principal Component Analysis (PCA) is a common tool for dimensionality reduction and feature extraction, which has been applied in many fields, such as biology, medicine, machine learning and bioinformatics. B...
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Chapter and Conference Paper
Can Machine Generate Traditional Chinese Poetry? A Feigenbaum Test
Recent progress in neural learning demonstrated that machines can do well in regularized tasks, e.g., the game of Go. However, artistic activities such as poem generation are still widely regarded as human’s s...
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Chapter and Conference Paper
A Novel Feature Extraction Method for Epileptic Seizure Detection Based on the Degree Centrality of Complex Network and SVM
Epilepsy is a kind of ancient disease, which is affecting the life of patients. With the increasing of incidence of epilepsy, automatic epileptic seizure detection with high performance is of great clinical si...
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Chapter and Conference Paper
Application of Graph Regularized Non-negative Matrix Factorization in Characteristic Gene Selection
Nonnegative matrix factorization (NMF) has become a popular method and widely used in many fields, for the reason that NMF algorithm can deal with many high dimension, non-negative problems. However, in real g...
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Chapter and Conference Paper
Automatic Seizure Detection in EEG Based on Sparse Representation and Wavelet Transform
Sparse representation has been widely applied to pattern classification in recent years. In the framework of sparse representation based classification (SRC), the test sample is represented as a sparse linear ...
