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Sentence Alignment Method Based on Maximum Entropy Model Using Anchor Sentences

Sentence Alignment Method Based on Maximum Entropy Model Usi...

第十五届全国计算语言学学术会议(CCL2016)暨第四届基于自然标注大数据的自然语言处理国际学术研讨会(NLP-NABD-2016)

作者： Chao Che Wenwen Guo Jianxin Zhang Key Laboratory of Advanced Design and Intelligent Computing(Dalian University) Ministry of EducationDalian

The paper proposes a sentence alignment method based on maximum entropy model using anchor sentences to align ancient and modern Chinese sentences in historical *** method selects the sentence pairs with the same phrases at the beginning or the end of the sentence or with the same time phrases as anchor sentence pairs,which are employed to divide the paragraph into several ***,the sentences in each section are aligned using dynamic programming algorithm according to the entropy calculated by maximum entropy *** maximum entropy model employs improved Chinese co-occurrence character feature,length feature and sentence alignment mode *** Chinese co-occurrence characters feature is improved by giving different weights to characters in different position based on the contribution to align *** the experiment performed on ShiJi,the precision and recall of the proposed method reaches 95.9%and 95.6%respectively,which outperforms other sentence alignment methods significantly.

关键词： anchor sentences maximum entropy model Chinese co-occurrence character sentence alignment

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Study and application of DNA cellular automata self-assembly

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 472卷 654-658页

作者： Zhou, Shihua Wang, Bin Zheng, Xuedong Zhou, Changjun Key Laboratory of Advanced Design and Intelligent Computing of Ministry of Education Dalian University DalianLiaoning116622 China

ISBN: (纸本)9783662450482

Because DNA self-assembly technique has its unique molecular function and control of nanomaterials synthesis, DNA computing model based on the self-assembly owns great prospects for development. At present, humans have been widely used image to record and express the objective world, and image also becomes a kind of extremely important multimedia information storage and transmission format. In order to enhance the security of image, people have started to use DNA self-assembly to study DNA cryptography-based image encryption. In this paper, design of image encryption-oriented DNA self-assembly is introduced. The paper gives the self-assembly definition of elementary XOR-DNA cellular automata and elementary T-shaped XOR-DNA cellular automata. Combined with the characteristics of image encryption, the design of image encryption self-assembly is given by the definition of elementary T-shaped DNA cellular automata. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Cellular automata

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Palmprint recognition based on CNN and local coding features 6

Palmprint recognition based on CNN and local coding features

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6th International Conference on Computer Science and Network Technology, ICCSNT 2017

作者： Yang, Aoqi Zhang, Jianxin Sun, Qiule Zhang, Qiang Key Lab of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China Faculty of Electronic Information and Electric Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9781538604922

The convolutional neural network(CNN) has received an excellent performance in the recent tasks of image retrieval and image classification. Besides, some local coding methods have been focused on because of their outstanding local description. In this paper, we present a novel method for palmprint recognition, which combines CNN and local coding techniques. We conduct feature extraction on palmprint images using the pre-trained networks and obtain the local convolutional features. Then three different local coding methods are adopted to code the features from CNN, including Bag of Visual Word(BoVW), Locality-constrained Linear Coding(LLC) and Vector of Locally Aggregated Descriptors (VLAD). The features extracted from CNN have better representation. Meanwhile, the local coding makes local features more important. Hence the combination of them can get the anticipated better results. The proposed method is extensively evaluated on the PolyU palmprint database and PolyU multispectral palmprint database, illuminating the remarkable performance on palmprint recognition. © 2017 IEEE.

关键词： Palmprint recognition

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Blockchain-Based Privacy-Preserving and Accountable Mobile Edge Outsourcing computing Framework for the Metaverse

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年第2期9卷 711-724页

作者： Li, Chunpei Liu, Chen Liu, Peng Li, Xianxian Qiu, Wangjie Lei, Lei Jin, Yanli Guangxi Normal University Key Laboratory of Educational Blockchain and Intelligent Technology Ministry of Education Guangxi Key Lab of Multi-Source Information Mining and Security Guilin541004 China Zhongguancun Laboratory China Beihang University Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beijing China

Mobile Edge computing (MEC) enables Metaverse Terminal Devices (MTD) to perform complex tasks, including graphic rendering and physical simulation, by leveraging low-latency outsourced computing. However, existing research has not fully addressed the challenge of establishing an efficient outsourced computing service within an open and dynamic MEC environment that simultaneously ensures privacy and accountability. To address this, we proposes a blockchain-based privacy-preserving and accountable mobile edge outsourcing computing framework for the Metaverse, termed Meta-BMEOC. Specifically, we have designed an outsourcing computing protocol based on smart contracts and threshold secret sharing, enabling MTD to outsource tasks to multiple edge servers while preserving privacy. Furthermore, we have developed an off-chain smart contract protocol based on a Trusted Execution Environment. This protocol is designed to reduce the risk of malicious edge servers colluding to reconstruct the computational tasks of MTD, and it enables accountability for servers that return erroneous results. Additionally, we designed an incentive mechanism to resist malicious attacks and ensure system security and stability. Security analysis and experimental evaluation show that Meta-BMEOC not only ensures the privacy and accountability of outsourced computing but also provides outsourced computing services with lower computational latency. © 2017 IEEE.

关键词： Differential privacy

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DNA computing-based cryptography

DNA computing-based cryptography

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Xing Wang Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

DNA computing theories can be applied in cryptography and it is a very hopeful direction. Though still in primitive level, it applies in many fields and solved some hard problems successfully. The art of cryptography security is to make anybody can not read it by encoding message. This paper use a new way to show how cryptography works with DNA computing, it can transmit message securely and effectively. The RSA algorithm belongs to asymmetric key cryptography, it is used in this paper connecting with DNA computing technique to encrypt message.

关键词： DNA computing Cryptography Encoding Arithmetic Turing machines Chemicals Art Security Computational modeling Qualifications

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A stratified image-hiding method based on chaos

A stratified image-hiding method based on chaos

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Ying Li Qiang Zhang Na Ma Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

This paper presents a stratified image hiding scheme based on chaotic algorithm. In the pretreatment process chaotic sequences are used to encrypt the secret image. The histogram of the processed image is similar to that of white noise. A stratified secret data embedding thought is adopted in the embedding process. As the experimental results show, this algorithm has relatively large embedding capacity, good invisibility and robustness.

关键词： Cryptography Algorithm design and analysis Discrete wavelet transforms PSNR Pixel

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A multilevel image encryption algorithm based on chaos and DNA coding

A multilevel image encryption algorithm based on chaos and D...

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Qian Wang Qiang Zhang Changjun Zhou Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

Chaos has been attracted much attention in current research of image encryption. In this paper, we change the location of pixels and pixel values through the combination of chaos with DNA coding. First of all, we transform the digital image into DNA coding matrix based on DNA code rules. Secondly, we divided this matrix into four sub matrixes, and disorder these sub matrixes through logistic chaotic sequence. Then, we scramble the sub matrixes by adding new logistic chaotic sequences and get the new sub matrixes. Finally, we join all scrambled DNA sub-matrixes in a DNA sequence and decode the scramble DNA matrix to image matrix. The experiment results demonstrate that the proposed scheme is effective, and it has wide secret key space, strong sensibility, high security and good ability of resisting statistic attack.

关键词： Cryptography Chaos DNA Image coding Sequences Logistics Digital images Decoding Security Statistics

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Cross-Stage Mutual Distillation for Replay Attack Detection

Cross-Stage Mutual Distillation for Replay Attack Detection

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6th International Conference on intelligent computing and Signal Processing (ICSP)

作者： Yinqing Cheng Lasheng Zhao Ling Wang Han Wang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Automated speaker verification systems face a higher risk of replay attacks in practice. However, the existing studies face the problem of limited detection capabilities and insufficient use of shallow fine-grained information. To address these issues, we propose the cross-stage mutual distillation(CS-MD) framework, which involves two models learning from a deep network output of each other in different stages of training. This mutual learning approach enhances the ability of shallow networks to capture fine-grained speech information. Additionally, we use an attentional feature fusion module to integrate shallow information more effectively. The multi-scale attention mechanisms in this module can combine local and global speech features while preserving detailed information. Experimental results on the ASVspoof 2019 physical access dataset demonstrate that our proposed method outperforms state-of-the-art methods in terms of EER and min t-DCF metrics, validating the effectiveness of our CS-MD framework.

关键词： Training Voice activity detection Measurement Knowledge engineering Attention mechanisms Speech enhancement Signal processing Feature extraction Faces

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Semi-Supervised Semantic Segmentation Based on Class Balanced Framework

Semi-Supervised Semantic Segmentation Based on Class Balance...

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IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Jiacheng Yang Jing Dong Pengfei Yi Rui Liu Ling Wang The Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

ISBN: (数字)9798350350920

ISBN: (纸本)9798350350937

Semi-supervised semantic segmentation is a task that utilizes a small amount of labeled data and a large amount of unlabeled data to achieve pixel-level annotation. Due to the common long tail distribution phenomenon in semi-supervised semantic segmentation datasets and the fixed threshold strategy commonly used in filtering pseudo labels, the model tends to favor the head classes when generating pseudo labels, resulting in poor segmentation performance on tail data. This article proposes a semi-supervised semantic segmentation method based on a class- balanced framework, which improves the model's recognition ability for minority classes and the quality of pseudo labels through tail classes oversampling and dynamic threshold adjustment. This method first constructs a Class Prediction Sampling-based Self-balancing Module (CPS 2 M). It identifies tail classes through Intersection-over-Union (IoU) analysis and constrains the random oversampling process based on the tail classes data distribution degree. Subsequently, the sampled labeled data is mixed with unlabeled samples to transfer prior knowledge, increase training frequency for tail classes, and solve the experience mismatch problem. Finally, we design a Dynamic Threshold Updating module (DTU) based on a non-linear function. The confidence threshold can dynamically change according to the model's learning ability to avoid discarding correct tail classes with low confidence, which alleviates the class imbalance problem of generating pseudo-labels. Based on the DeepLabV3+ network framework and ResNet-101 pre-training model, this method achieves 82.1 mIoU under 1464 labeled partition protocols on the Classic Pascal VOC 2012 dataset, demonstrating the most advanced performance compared to existing methods.

关键词： Training Protocols Filtering Annotations Semantic segmentation Semantics Tail

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Image encryption algorithm based on DNA biological properties and chaotic systems

Image encryption algorithm based on DNA biological propertie...

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Qian Wang Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian university Dalian China

With the rapid development of DNA computing, people began to use DNA technology to encrypt information. In this paper, we combine the biological characteristics of DNA and the improved sequence of Logistic mapping method, encrypt the image. The biological characteristics of DNA can better scramble image pixel, and the improved sequence can better change the pixel values. The encryption effect of this paper is better than traditional encryption, and the correlation of adjacent pixels is very low.

关键词： Biomedical imaging Cryptography Clocks Biology

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