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Multiple Photon Sampling Technique Based on Stochastic Progressive Photon Mapping

Journal of Physics: Conference Series 2020年第1期1518卷

作者： Liyan Yang Chunmeng Kang School of Information Science and Engineering Shandong Normal University Jinan 250014 China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan 250014 China

This paper introduces a multiple photon sampling technique based on stochastic progressive photon mapping. We use the image space concept to divide the scene into continuous sub-blocks and then we calculate our proposed distance function and photon number function in each of the sub-blocks. The distance function is used to calculate the distance error of the hit point and to determine whether each sub-block is located at a boundary between different objects. The photon number function is used to calculate the photon number error and to determine whether the photon distribution in each sub-block is uniform. Based on the values of the distance error and the photon number error, the multiple photon sampling technique is used to acquire multiple samples of the hit point in each sub-block. Instead of using a single radius for the radiance estimate, we use three different radii and compute the final radiance estimate as a weighted average of the three values. When compared with the existing stochastic progressive photon mapping method, our method provides a better solution to the photon distribution problem and can also reduce bias and noise, especially in the scene with drastic changes in light and dark.

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A embedding model for text classification

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Expert Systems 2019年第6期36卷 e12460-e12460页

作者： Liu, Wenfeng Liu, Peiyu Yang, Yuzhen Yi, Jing Zhu, Zhenfang School of Information Science and Engineering Shandong Normal University Jinan China School of Computer Heze University Heze China Shandong Normal University Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China School of Computer Science and Technology Shandong Jianzhu University Jinan China School of Information Science and Electrical Engineering Shandong Jiaotong University Jinan China

Existing word embeddings learning algorithms only employ the contexts of words, but different text documents use words and their relevant parts of speech very differently. Based on the preceding assumption, in order to obtain appropriate word embeddings and further improve the effect of text classification, this paper studies in depth a representation of words combined with their parts of speech. First, using the parts of speech and context of words, a more expressive word embeddings can be obtained. Further, to improve the efficiency of look-up tables, we construct a two-dimensional table that is in the format to represent words in text documents. Finally, the two-dimensional table and a Bayesian theorem are used for text classification. Experimental results show that our model has achieved more desirable results on standard data sets. And it has more preferable versatility and portability than alternative models. © 2019 John Wiley & Sons, Ltd

关键词： Embeddings

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A Transmission Power Control Algorithm for Wireless Body Area Networks

A Transmission Power Control Algorithm for Wireless Body Are...

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International Conference on computer Supported Cooperative Work in Design

作者： Zhuoran Zhengl Xiangwei Zheng Jie Tian Minglei Shu Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Ji'nan China Qilu University of Technology Shandong Provincial Key Laboratory of Computer Networks

Energy efficiency is a key issue for wireless sensor nodes, especially for wireless body area networks (WBANs) that operate near the human body or in the human body. Aiming at the problem that WBAN system still has too fast energy consumption, we propose a ZigBee star network model with multiple sensing nodes as end nodes, and design an adaptive transmission power correction control algorithm with adjustment factors to select the appropriate transmit power to reduce the energy consumption. Experiments show that the proposed power control algorithm reduces the overall energy consumption by reasonably controlling the transmission power in the ZigBee star network model.

关键词： Power control Wireless communication Body area networks Prediction algorithms ZigBee Energy consumption Wireless sensor networks

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25th International Conference on Neural Information Processing, ICONIP 2018

作者： Liu, Wenfeng Liu, Peiyu Yi, Jing Yang, Yuzhen Liu, Weitong Li, Nana School of Information Science and Engineering Shandong Normal University Jinan250014 China School of Computer Heze University Heze274015 China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250014 China School of Computer Science and Technology Shandong Jianzhu University Jinan250101 China

ISBN: (纸本)9783030041816

How to effectively measure the similarity between two sentences is a challenging task in natural language processing. In this paper, we propose a sentence similarity comparison method that combines word embeddings and syntactic structure. First of all, by generating the corresponding syntactic tree, we synthetically analyze the two sentences and block them according to the syntactic components. Secondly, we prune the syntactic tree, remove the stop words and perform morphological restoration. Then, some important operations will be performed, such as passive flipping, negative flipping, and so on. Finally, the similarity of two sentence pairs is calculated by weighting the block embeddings of the syntactic tree. Experiments show the effectiveness of this method. © Springer Nature Switzerland AG 2018.

关键词： Embeddings

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Fake comment detection based on time series and density peaks clustering 18th

Fake comment detection based on time series and density peak...

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18th International Conference on Algorithms and Architectures for Parallel Processing - ICA3PP 2018 Collocated Workshops: ICA3PP 2018 Workshop on Intelligent Algorithms for Large-scale Complex Optimization Problems, IALCOP 2018, ICA3PP 2018 Workshop on Security and Privacy in Data Processing, SPDP 2018

作者： Di, Ruitong Wang, Hong Fang, Youli Zhou, Ying School of Information Science and Engineering Shandong Normal University Jinan250014 China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250014 China Institute of Biomedical Sciences Shandong Normal University Jinan250014 China

ISBN: (纸本)9783030052331

This paper proposes a fake comment recognition method based on time series and density peaks clustering. Firstly, an anomaly recognition model based on multi-dimensional time series is constructed. Secondly, according to the idea of multi-scale features, seven benchmark-scale and corresponding subdivision-scale features are extracted hierarchically, and further, 49 features are finally obtained. At last, an optimized detection model based on density peaks clustering is proposed for identifying the fake comments, so as to improve the anti-noise ability of our method. The effectiveness of our proposed method is verified by several experiments, with the AUC value reaching 92%. © Springer Nature Switzerland AG 2018.

关键词： Time series

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Fire Video Image Detection Based on a Convolutional Neural Network

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Journal of Physics: Conference Series 2020年第1期1453卷

作者： Wen Wang Tianping Li Shandong Key Laboratory for Normal Distributed Computer Software Technology School of Physics and Electronic Science Shandong Normal University Jinan Shandong 250358 China School of Physics and Electronic Science Shandong Normal University Jinan Shandong 250358 China

computer vision-based and real-time flame detection is very important to inmodern surveillance system. At present, convolutional neural network (CNN) has become a topic discussed by more and more researchers because of its high recognition accuracy and wide application. The preprocessind process of the traditional image processing method is complicated and the false positive rate is high. So, in this paper we proposed an algorithm for detecting flame in real time using CNN technology. Firstly, to improve the accuracy of detection, we proposed a suspicious target regions segmentation for disposing the suspected flame regions. This algorithm could locate the target area and segment the target area to improve the flame detection and recognition accuracy. Then, we designed a model based on CNN to classify the extracted feature maps of candidate areas. Finally, we could get the detection of flame according to the the classification results. The experimental results show that the approach has high recognition accuracy.

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Personalized gesture interactions for cyber-physical smart-home environments

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Science China(Information Sciences) 2017年第7期60卷 144-158页

作者： Yihua LOU Wenjun WU Radu-Daniel VATAVU Wei-Tek TSAI State Key Laboratory of Software Development Environment Beihang University Mint Viz Research Lab Integrated Center for Research Developmentand Innovation in Advanced MaterialsNanotechnologies and Distributed Systems for Fabrication and Control (MANSiD) & Department of Computer Science University Stefan cel Mare of Suceava

A gesture-based interaction system for smart homes is a part of a complex cyber-physical environment, for which researchers and developers need to address major challenges in providing personalized gesture interactions. However, current research efforts have not tackled the problem of personalized gesture recognition that often involves user identification. To address this problem, we propose in this work a new event-driven service-oriented framework called gesture services for cyber-physical environments(GS-CPE) that extends the architecture of our previous work gesture profile for web services(GPWS). To provide user identification functionality, GS-CPE introduces a two-phase cascading gesture password recognition algorithm for gesture-based user identification using a two-phase cascading classifier with the hidden Markov model and the Golden Section Search, which achieves an accuracy rate of 96.2% with a small training dataset. To support personalized gesture interaction, an enhanced version of the Dynamic Time Warping algorithm with multiple gestural input sources and dynamic template adaptation support is implemented. Our experimental results demonstrate the performance of the algorithm can achieve an average accuracy rate of 98.5% in practical scenarios. Comparison results reveal that GS-CPE has faster response time and higher accuracy rate than other gesture interaction systems designed for smart-home environments.

关键词： gesture interaction personalization gesture recognition user identification event-driven architec ture

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Crowd intelligence in AI 2.0 era

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Frontiers of Information Technology & Electronic Engineering 2017年第1期18卷 15-43页

作者： Wei LI Wen-jun WU Huai-min WANG Xue-qi CHENG Hua-jun CHEN Zhi-hua ZHOU Rong DING State Key Laboratory of Software Development Beihang University National Laboratory for Parallel and Distributed Processing College of ComputerNational University of Defense Technology Institute of Computing Technology Chinese Academy of Sciences College of Computer Science and Technology Zhejiang University National Key Laboratory for Novel Software Technology Nanjing University

The Internet based cyber-physical world has profoundly changed the information environment for the development of artificial intelligence(AI), bringing a new wave of AI research and promoting it into the new era of AI 2.0. As one of the most prominent characteristics of research in AI 2.0 era, crowd intelligence has attracted much attention from both industry and research communities. Specifically, crowd intelligence provides a novel problem-solving paradigm through gathering the intelligence of crowds to address challenges. In particular, due to the rapid development of the sharing economy, crowd intelligence not only becomes a new approach to solving scientific challenges, but has also been integrated into all kinds of application scenarios in daily life, e.g., online-tooffline(O2O) application, real-time traffic monitoring, and logistics management. In this paper, we survey existing studies of crowd intelligence. First, we describe the concept of crowd intelligence, and explain its relationship to the existing related concepts, e.g., crowdsourcing and human computation. Then, we introduce four categories of representative crowd intelligence platforms. We summarize three core research problems and the state-of-the-art techniques of crowd intelligence. Finally, we discuss promising future research directions of crowd intelligence.

关键词： Crowd intelligence Artificial intelligence 2.0 Crowdsourcing Human computation

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Cooperative Co-evolutionary Artificial Bee Colony Algorithm Based on Hierarchical Communication Model

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Chinese Journal of Electronics 2016年第3期25卷 570-576页

作者： HU Chunyu LIU Hong ZHANG Peng School of Information Science and Engineering Shandong Normal University Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology

Canonical Artificial bee colony(ABC) algorithm with a single species is insufficient to extend the diversity of solutions and may be trapped into the local optimal solution. This paper proposes a new co-evolutionary ABC algorithm(HABC) based on Hierarchical communication model(HCM). HCM combines advantages of global and local communication pattern. With adjustment strategies on species and groups, HCM can reduce the computational complexity dynamically. Performance tests show that the HABC algorithm exhibit good performance on accuracy, robustness and convergence speed. Compared with ABC and Integrated co-evolution algorithm(IABC),HABC performs better in solving complex multimodal functions.

关键词： Artificial bee colony(ABC) algorithm Multi-species co-evolution Hierarchical communication model(HCM) Dynamical adjustment

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Bayesian multi-hypothesis Wyner-Ziv video coding

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Journal of Information Hiding and Multimedia Signal Processing 2017年第2期8卷 478-485页

作者： Meng, Li Li Zong, Jing Xiu Sun, Gui Na Cheng, Jie Zhang, Jia Zhao, Meng Chen Department of Information Science and Engineering Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Shandong Normal University No.88 Wenhua East Road Jinan250014 China

The performance of distributed video coding (DVC) relies heavily on the quality of the side information (SI), and better performance can be expected if multiple SIs are employed. In this paper, we consider the scenario with two SIs, which are obtained by forward and backward predictions respectively. In this case, a couple of ad hoc approaches have been proposed to approximate the conditional probability density function (pdf) of a Wyner-Ziv-coded frame given the two SIs. However, the optimal conditional pdf and the relative performances of these ad hoc approaches with respect to the optimal solution have not been studied. In this paper, using Bayes’ formula, we derive the closed-form expression of the conditional pdf. Experimental results show that the Bayesian solution has similar performance to previous methods. Moreover, simulation results reveal that when better SIs are available, the Bayesian solution could outperform other methods. This analysis sheds some lights on developing future DVC schemes. © 2017 ISSN.

关键词： Probability density function

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