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| 1 | Minimum Structural Similarity Distortion for Reversible Data Hiding显示文摘Until now, most Reversible data hiding(RDH) techniques have been evaluated by Peak signal-tonoise ratio(PSNR), which based on Mean squared error(MSE). Unfortunately, MSE turns out to be an extremely poor measure when the purpose is to predict perceived signal fidelity or quality. The Structural similarity(SSIM)index has gained widespread popularity as an alternative motivating principle for the design of image quality measures. How to utilize the characterize of SSIM to design RDH algorithm is very critical. We propose an optimal RDH algorithm under structural similarity constraint. We deduce the metric of the structural similarity constraint,and further we prove it does not hold Non-crossing-edges(NCE) property. We construct the rate-distortion function of optimal structural similarity constraint, which is equivalent to minimize the average distortion for a given embedding rate, and then we can obtain the optimal transition probability matrix under the structural similarity constraint. Experiments show that our proposed method can be used to improve the performance of previous RDH schemes evaluated by SSIM. | XU Jiajia ZHANG Weiming JIANG Ruiqi YU Nenghai HU Xiaocheng | 2018 | Chinese Journal of Electronics2018，27，3： | 2 |
| 2 | A RESEARCH OF UWB RAKE RECEIVER BASED ON NOVEL RLS ADAPTIVE ALGORITHM显示文摘A modified RAKE receiver based on novel Recursive Least Squares (RLS) adaptive algorithm is proposed. The receiver uses L-fingered correlators, which are composed of RLS adaptive filters, to enhance the performance of multipath receiving. It can also track the amplitude of the received signal to form a real-time amplitude estimation which is correlated with the power of excess delay bin. The simulation results based on the IEEE UltraWide Band (UWB) channel models (CMl to CM4) show that the novel RLS algorithm can alter the attenuation estimation with the finger's power delay profile, and RAKE receiver with few fingers can be employed to get high performance. | Yin Yong Yu Nenghai Dong Weijie | 2006 | Journal of Electronics(China)2006，23，3： | 2 |
| 3 | Asynchronous Parallel Finite Automaton: a new mechanism for deep packet in- spection in cloud computing 显示文摘 | ZHENG LI NENGHAI YU YANG LI | 2010 | Journal of Internet Technology2010，11，2： | 1 |
| 4 | Semantics preserving bag-of-words models and applications显示文摘 | WU LEI HOI S C H YU Nenghai | 2010 | IEEE Transactions on Image Proces sing2010，19，7： | 1 |
| 5 | Asynchronous parallel finite automaton: a new mechanism for deep packet in- spection in cloud computing显示文摘 | Li Zheng Yu Nenghai Li Yang | 2010 | Journal of Internet Technology2010，11，2： | 1 |
| 6 | Passive detection of doctored JPEG image via block artifact grid extraction 显示文摘 | LI WEIHAI YUAN YUAN YU NENGHAI | 2009 | Signal Processing2009，89，9： | 1 |
| 7 | Adaptive Packet Classification Algorithm Based on IXP2800 Network Processor显示文摘 | CHEN Zheng ZHANG Zhenhua YU Nenghai TANG Xinan | 2008 | Chinese Journal of Electronics2008，17，3： | 1 |
| 8 | Fast Salient Object Detection Based on Segments显示文摘 | Liansheng ZHUANG Ketan TANG Nenghai YU | 2009 | In-ternational Conference on Measuring Technology and Mechatronics Automation of IEEE2009，，： | 1 |
| 9 | A privacy-preserving remote data integrity checking protocol with data dynamics and public verifiability 显示文摘 | Hao Zhuo Zhong Sheng Yu Nenghai | 2011 | IEEE Transaction on Knowledge and Data Engineering2011，23，9： | 1 |
| 10 | Performance Analysis of Multi-path Routing in Wireless Ad Hoc Networks显示文摘 | Wang Hui Ma Ke Yu Nenghai | 2005 | Wireless Communications Networking and Mobile Computing2005，，2： | 1 |
| 11 | People Summarization by Combining Named Entity Recognition and Relation Extraction显示文摘 | Xiaojiang Liu Nenghai Yu | 2010 | Journal of Convergence Information Technology2010，5，10： | 1 |
| 12 | A New Nonlinear Fea- ture Extraction Method for Face Recognition显示文摘 | Pang Yanwei Liu Zhengkai Yu Nenghai | 2006 | Neurocomputing2006，69，： | 1 |
| 13 | Future Event Prediction Based on Temporal Knowledge Graph Embedding显示文摘Accurate prediction of future events brings great benefits and reduces losses for society in many domains,such as civil unrest,pandemics,and crimes.Knowledge graph is a general language for describing and modeling complex systems.Different types of events continually occur,which are often related to historical and concurrent events.In this paper,we formalize the future event prediction as a temporal knowledge graph reasoning problem.Most existing studies either conduct reasoning on static knowledge graphs or assume knowledges graphs of all timestamps are available during the training process.As a result,they cannot effectively reason over temporal knowledge graphs and predict events happening in the future.To address this problem,some recent works learn to infer future events based on historical eventbased temporal knowledge graphs.However,these methods do not comprehensively consider the latent patterns and influences behind historical events and concurrent events simultaneously.This paper proposes a new graph representation learning model,namely Recurrent Event Graph ATtention Network(RE-GAT),based on a novel historical and concurrent events attention-aware mechanism by modeling the event knowledge graph sequence recurrently.More specifically,our RE-GAT uses an attention-based historical events embedding module to encode past events,and employs an attention-based concurrent events embedding module to model the associations of events at the same timestamp.A translation-based decoder module and a learning objective are developed to optimize the embeddings of entities and relations.We evaluate our proposed method on four benchmark datasets.Extensive experimental results demonstrate the superiority of our RE-GAT model comparing to various base-lines,which proves that our method can more accurately predict what events are going to happen. | Zhipeng Li Shanshan Feng Jun Shi Yang Zhou Yong Liao Yangzhao Yang Yangyang Li Nenghai Yu Xun Shao | 2023 | Computer Systems Science & Engineering2023，44，3： | 1 |
| 14 | A privacypreserving remote data integrity checking protocol with data dynamics and public verifiability显示文摘 | Hao Zhuo Zhong Sheng Yu Nenghai | | 0，，09： | 1 |
| 15 | Reversibility ImprovedData Hiding in Encrypted Images 显示文摘 | ZHANG Weiming MA Kede YU Nenghai | 2014 | Signal Processing2014，94，1： | 1 |
| 16 | A new nonlinear feature extraction method for face recognition 显示文摘 | PANG YANWEI LIU ZHENGKAI YU NENGHAI | 2006 | Nerocomputing2006，69，79： | 1 |
| 17 | A design method of sat- uration test image based on CIEDE2000显示文摘 | Yang Yang Ming Jun Yu Nenghai | 2012 | Advances in Multimedia2012，2012，： | 1 |
| 18 | Pefformance analysis of multi-path routing in wireless ad hoc networks显示文摘 | WANG HUI MA KE YU NENGHAI | 2005 | Wireless Communications Networking and Mobile Computing2005，2，： | 1 |
| 19 | Passive detection of doctored JPEG image via block artifact grid extraction显示文摘 | Li Weihai Yuan Yuan Yu Nenghai | 2009 | Signal Processing2009，，： | 1 |
| 20 | Improving various reversible data biding schemes via optimal codes for binary covers 显示文摘 | Zhang Weiming Chen Biao Yu Nenghai | 2012 | IEEE Transaction on Image Proce-ssing2012，21，6： | 1 |
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