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Mobile reading ranks No.4 on the permeate proportion of the mobile Internet applications and is increasing gradually. Understanding user behaviors of mobile reading is important for service provider. However, few work has been done on reading analysis. In this paper, we provide an approach to solve this problem based on cloud computing platform including HDFS and Apache Pig. Our study is carried out...
Brain computer interface (BCI) offers disabled people a nonmuscular communication pathway. Event-related potential (ERP) is an efficient way to achieve the BCI system. One of important issues for ERP classification is the under sample problem, that is the feature dimension is very high while the sample number is very strictly limited. In this paper, we introduce a P300 feature extraction and classification...
Link prediction is widely used in many applications in complex networks and it is also an alternative tool for community detection. Based on many kinds of hypotheses, lots of efforts have been made to solve the link prediction problem and research has shown that some link prediction heuristics are successful because they effectively estimate the similarity between nodes in some latent space. In this...
Motor imagery is usually hard to be classified with a high accuracy, since the task-related electroencephalogram (EEG) responses are likely to be contaminated by some ongoing noises. Design of an efficient classifier is considerably important for the realization of a brain-computer interface (BCI) system based on motor imagery. This study introduces a Bayesian extreme learning machine (BELM) based...
The magnitude of the decline in performance is very alarming when the features commonly used in normal speech recognition system are directly used as the input feature of whispered speech in the speech recognition system trained by normal speech. In this paper, in order to finding the characteristics of better matching degree between normal and whispered speech, we propose a spectrum sparse-based...
This paper uses digital speech as research object. A baseline system of Mandarin whispered digital speech recognition using Hidden Markov Model is built. In this paper, the performance of the baseline recognition system is analyzed in detail and we find there are three pairs of easily confused speech. Furthermore, the cause of confusion is analyzed in depth. Then a classifier for distinguishing between...
In order to address the matching problems of oblique remote sensing image with viewpoint change, geometric deformation and radiometric distortion, this paper presents a new point-based matching method which conducts feature extraction by building nonlinear space on simulation images derived from a full-range resample of the origin image. All distortions caused by the position change of camera are...
The paper is focused on the ambiguity problem in pose estimation of circle feature and a new method is proposed based on the concentric circle constraint. The pose of a single circle feature, in general, can be determined from its projection in the image plane with a pre-calibrated camera, but there are generally two possible sets of pose parameters. By introducing the concentric circle constraint,...
In order to strengthen the robustness of video object tracking and overcome the drastic appearance changes caused by diverse challenges, a generative algorithm based on sparse histogram was proposed. Firstly, the image was partitioned into patches by using overlapped sliding window. Secondly, the local features of the object were extracted, and the sparse representation was exploited to achieve the...
In this paper, we propose an efficient identity-based authentication and key agreement protocol for wireless roaming. In the protocol, a roaming user only needs one message transmission to achieve authentication and session key establishment with the roaming server. We then demonstrate that the protocol ensures the privacy of roaming users, by providing anonymity and untraceability.
This paper proposes a block-based least squares thresholding algorithm, according to the analysis and comparison of the shortcomings of Otsu and maximum entropy methods. The proposed algorithm deals with images by least squares processing methods, which stretch the gray level of images and make the gray values more uniform. In this way, the images can be more suitable for binarization.
The binocular visual collaborative video tracking method can simultaneously obtain Far-Range image in global field of view and Close-Range image in following field of view with which can track the target, but the error of PTZ(Pan Tilt and Zoom) motion parameters of the following camera is relatively large and the calibration algorithm is relatively complex. Thus, a new strategy for PTZ calibration...
A cyclic pursuit-based path following scheme is proposed to achieve the coordinated target enclosing using a group of underactuated marine surface vehicles (MSVs). Specifically, a line-of-sight based path following controller is firstly derived to force each vehicle to follow a parameterized path around the target. Then, a distributed path variable coordination control law is developed based on a...
In this paper, we estimate the total execution time of two applications under different input data size with linear regression model and error correction neural network model respectively. From the prediction results, we can conclude that error correction neural network model can predict the total execution time of these applications under different input data size accurately and the prediction accuracy...
Many digital map applications have the need to present large quantities of precise point data on the map. Such data can be PM2.5 value, weather information, population in towns, etc. With the development of Internet of Things, we expect such data will grow at a rapid pace. How to visualize such magnitude of data on mobile devices and web broswers becomes a problem. This paper describes a method for...
This paper analyzes the noise-free but highly overlapped and imbalanced data set involving six analytes. We explored the principal components in the feature space to observe which spectral bands contribute the most contrast or data spreading. We also compared the principal component analysis (PCA) results and the corresponding k-means clustering algorithm results generated using lower PCs, i.e. PC4...
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