Sentence alignment, as one of the most active and fundamental tasks in the field of natural language processing (NLP), is usually realized in two categories of methods. One is traditional methods which are firstly pro...
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ISBN:
(纸本)9781450377607
Sentence alignment, as one of the most active and fundamental tasks in the field of natural language processing (NLP), is usually realized in two categories of methods. One is traditional methods which are firstly proposed, the other, which are adopted later, is based on the Neural Network method. Presently, under the limitation that the existing mainstream data corpora are mostly in the form of 1-to-1, the alignment models with relatively good performance mainly apply to the cases of 1-to-1 sentence alignment. However, under the circumstance that a sentence contains too much information, 1-to-N sentence alignment can actually have a better effect on sentence translation tasks, compared with the 1-to-1 form, since it is more flexible and can reduce the complexity of the original sentence. As a result, we attempt to exploit neural networks with relatively good performance in the cases of 1-to-1 to fit in the cases of 1-to-N. In this paper, a novel 1-N Bilingual word Embedding with Sentence Combination CNN Improved Framework (1-NBESCC) is proposed in order to align 1-to-N sentences more precisely. Experiments show that our proposed model performs as good as the traditional methods such as BLEUALIGN in 1-to-1 situation, but much better in 1-to-N situation.
Epilepsy is a brain disorder caused by abnormal discharges of neurons in brain. It is one of the most commonly studied disorders in neurology. The research of epilepsy electroencephalogram (EEG) has become a hot resea...
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ISBN:
(数字)9781728194813
ISBN:
(纸本)9781728194820
Epilepsy is a brain disorder caused by abnormal discharges of neurons in brain. It is one of the most commonly studied disorders in neurology. The research of epilepsy electroencephalogram (EEG) has become a hot research topic. We find that in epilepsy EEG detection task, many previous methods focused on directly collecting the data of each channel, but these methods seldom analyse relationships between signals. Therefore, we propose the Epilepsy EEG Graph Convolutional Network EGCN, which makes full use of correlations between channels to deeply mine data information. We specifically design 5-layer graph convolutional network structure for classification of healthy and epileptic patients. The method is applied to public data set (Boon and CHB-MIT) to establish a reasonable classification model. And we compare it with some advanced algorithms. The experimental results show that the E-GCN method is superior to many existing methods in classification accuracy. In brief, the E-GCN method can be effectively used in classification and detection for epilepsy. This provides new ideas for colleagues, who study epilepsy EEG. In addition, this also provides richer experience for diagnosis of epilepsy.
With the high frequent use of social applications on Android platform, the cache file privacy disclosure issues have become increasingly serious. To our best knowledge, there is no effective privacy protection solutio...
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ISBN:
(纸本)9781509035403
With the high frequent use of social applications on Android platform, the cache file privacy disclosure issues have become increasingly serious. To our best knowledge, there is no effective privacy protection solution for social applications cache files. In this paper, we analyze the present situation of social applications cache file leaks on Android platform, and provide a privacy disclosure assessment criterion based on file storage directories and security state machines. And a cache file privacy protection framework, X-Prcaf (Xposed-based-Protecting-Cache-File), is proposed, which can make social applications avoid privacy data leaks in running process. This framework mainly uses taint tracking technology, operating system hook technology, and cryptographic technology. It aims to protect the entire life cycle of the social applications cache files, by strategy pre-generation, real-time monitoring and security reinforcement. Experiments demonstrate that X-Prcaf has a good effect on the cache file leaks of social software.
The traffic flow is critical for the traffic control and traffic guidance. As the short-term traffic flow has the characteristics of highly nonlinear, complexity and chaos, the traditional neural networks can not tota...
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The traffic flow is critical for the traffic control and traffic guidance. As the short-term traffic flow has the characteristics of highly nonlinear, complexity and chaos, the traditional neural networks can not totally satisfy the performance in the aspects of prediction accuracy, training speed and stability. In order to solve those problems, a novel traffic flow prediction model based on echo state networks (ESN) is proposed. The model is established based on the chaotic property of traffic flow. Firstly, through phase space reconstruction of chaotic traffic flow data, the suitable input and output of ESN can be obtained. Then, by optimizing its key parameters of ESN, the ESN can make full use of the chaotic property of the input and output data to get more accurate prediction results. The propose model is applied to a real-world traffic flow prediction problem in the area of Xizhimen bridge of Beijing city, and compare with back-propagation neural networks (BPNN), Elman neural networks (Elman) and wavelet neural networks (WNN). The prediction results show that the model outperforms comparative other models in accuracy, training speed and stability.
The task of Chinese word segmentation is to split sequence of Chinese characters into tokens so that the Chinese information can be more easily retrieved by web search engine. Due to the dramatic increase in the amoun...
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This paper proposes a novel robust image copy detection scheme using multi-resolution histogram. In this method, the multi-resolution histogram, a global feature descriptor, is exploited to characterize an image. It s...
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ISBN:
(纸本)9781605588155
This paper proposes a novel robust image copy detection scheme using multi-resolution histogram. In this method, the multi-resolution histogram, a global feature descriptor, is exploited to characterize an image. It shares many desirable properties with the plain color histogram including that they are both fast to compute, efficient for storage, invariant to rigid motions, and robust to noise. In addition, it encodes spatial information directly, which is essential to the discrimination of image signature for an image copy detection scheme. In order to verify the robustness of the proposed method, an intensive simulation has been performed. The experimental results demonstrate that our method is robust against both geometric distortions and signal-processing like attacks. P-R curves obtained under various attacks show that the performance of our method is better than such a few classical methods selected for comparison. Copyright 2010 ACM.
In order to access sensitive documents shared over government, army and enterprise intranets, users rely on an indexing facility where they can quickly locate relevant documents they are allowed to access, (1) without...
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This paper proposes an edge-adaptive interpolation algorithm for Super-resolution reconstruction. The objective is to recover high-resolution image from low-resolution image. At first, from a low-resolution image, a h...
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In order to access sensitive documents shared over government, army and enterprise intranets, users rely on an indexing facility where they can quickly locate relevant documents they are allowed to access, (1) without...
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In order to access sensitive documents shared over government, army and enterprise intranets, users rely on an indexing facility where they can quickly locate relevant documents they are allowed to access, (1) without leaking information about the remaining documents, (2) without imposing large load on the receptionist, and (3) with a balanced load on the index servers. To address this problem, we propose Mimir, a distributed cipher retrieval system for sensitive documents. Mimir constructs the distributed indexes based on load balanced term distribution for better search efficiency and load balanced query. Mimir utilizes encryption with random key, partial key update, and access control based on role and user to protect sensitive data and improve query efficiency. Mimir uses dynamic pipelined search strategy to balance the load of the management server and reduce the search delay. Our experiments show that Mimir can effectively protect secret data and answer queries nearly as fast as an ordinary inverted index.
In this paper, a fast and robust video copy detection scheme is proposed, which is suitable for the DCT-coded video sequences. To address the efficiency and effectiveness issue, we extract the video signature directly...
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