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$\rho$ -Dominant Skyline Computation on data Stream

IEEE Access 2018年 6卷 53201-53213页

作者： Zhiqiong Wang Junchang Xin Linlin Ding Jianmin Ba Xiaosong Gao Neusoft Institute of Intelligent Healthcare Technology Co. Ltd. Key Laboratory of Big Data Management and Analytics Shenyang China School of Information Liaoning University Shenyang China School of Computer Science and Engineering Northeastern University Shenyang China Sino-Dutch Biomedical and Information Engineering School Northeastern University Shenyang China

Skyline query is widely used in multi-standard decision making process. As the extension to skyline query, p-dominant skyline query controls the base of the result set by adjusting data proportion, which is suitable for the application on fast deciding data stream. However, skyline query on data stream cannot satisfy the need for skyline query of corresponding value ratio, and the traditional p-dominant skyline query cannot provide skyline query with frequent data update. As a result, a data stream-based algorithm that can achieve the goal of p-dominant skyline query is proposed. First, the definitions of full-dominant relationship and p-dominance are given, after which the definitions of p-dominant skyline and p-dominant skyline based on data stream are proposed. Second, by analyzing the characters of data stream-based p-dominant skyline, a new data filtering method is established. Based on the method, p-Dominant Skyline Query on data stream over Sliding Window (DSSW) is proposed in order to improve the efficiency of p-dominant skyline query. After that, we expend the p-dominant skyline query of data stream into n-of-N p-dominant skyline query and the (n1, n 2 )-of-Np-dominant skyline query in data stream. Finally, we prove that DSSW has obvious advantages in responding time and storage skyline space by comparing with the traditional p-dominant skyline query algorithms through abundant experiments.

关键词： IEEE merchandise Microsoft Windows Indexes Decision making Heuristic algorithms Computer science

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Cascade control for supply air temperature in a variable air volume system

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IOP Conference Series. Earth and Environmental Science 2019年第1期238卷 012021-012021页

作者： Zhuang, Junhua Chen, Yimin Wu, Jie School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing China School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing China Department of Civil Architectural and Environmental Engineering Drexel University Philadelphia PA 19104 USA Beijing ZXT M&E Engineering Consultant Co. Ltd

Most supply air temperature in variable air volume systems is typically set at 55F(13 °C) that is design value in these systems. However, sometimes the load of cooling varies greatly in different zones, and it means the indoor temperature of low-load zones is lower than comfortable value, even if the supply air damper is at the minimum value that is not closed for minimum outside air requirement. Meanwhile, in transition season, the indoor temperature is also lower due to low outdoor temperature. These factors provided an opportunity to apply higher supply air temperature to reduce air handling unit (AHU) cooling load and box reheating. In this paper, a cascade control method is used to raise the supply air temperature. The external control loop controls the setting value of supply air temperature with the minimum supply air volume as the control target. And the internal control loop controls the supply air temperature by regulating valve. The cascade structure can solve the problem that the time constant of the system is too large. The simulation results show that the quality of control is good and the reheating can be cancelled.

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Improving Breast Cancer Diagnosis in Ultrasound Images Using Deep Learning with Feature Fusion and Attention Mechanism

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Academic radiology 2025年

作者： Sohaib Asif Yuqi Yan Bojian Feng Meiling Wang Yuxin Zheng Tian Jiang Ruyi Fu Jincao Yao Lujiao Lv Mei Song Lin Sui Zheng Yin Vicky Yang Wang Dong Xu Taizhou Key Laboratory of Minimally Invasive Interventional Therapy & Artificial Intelligence Taizhou Campus of Zhejiang Cancer Hospital (Taizhou Cancer Hospital) Taizhou Zhejiang 317502 China (S.A. Y.Y. B.F. L.S. D.X.) Center of Intelligent Diagnosis and Therapy (Taizhou) Hangzhou Institute of Medicine (HIM) Chinese Academy of Sciences Taizhou Zhejiang 317502 China (S.A. Y.Y. B.F. L.S. V.Y.W. D.X.) Wenling Institute of Big Data and Artificial Intelligence in Medicine Taizhou Zhejiang 317502 China (S.A. Y.Y. B.F. L.S. V.Y.W. D.X.) Department of Diagnostic Ultrasound Imaging & Interventional Therapy Zhejiang Cancer Hospital Hangzhou Institute of Medicine (HIM) Chinese Academy of Sciences Hangzhou Zhejiang 310022 China (S.A. Y.Y. B.F. T.J. J.Y. L.L. M.S. M.S. L.S. V.Y.W. D.X.). Department of Diagnostic Ultrasound Imaging & Interventional Therapy Zhejiang Cancer Hospital Hangzhou Institute of Medicine (HIM) Chinese Academy of Sciences Hangzhou Zhejiang 310022 China (S.A. Y.Y. B.F. T.J. J.Y. L.L. M.S. M.S. L.S. V.Y.W. D.X.) Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology Hangzhou 310022 China (Y.Y. T.J. J.Y. L.S. D.X.). Second Clinical College Zhejiang University of Traditional Chinese Medicine Hangzhou China (M.W. Y.Z. Z.Y.). Hangzhou Fuyang Hospital of Orthopedics of Traditional Chinese Medicine Special Inspection Department Zhejiang China (R.F.). Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology Hangzhou 310022 China (Y.Y. T.J. J.Y. L.S. D.X.) Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province Hangzhou 310022 China (J.Y.). Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology Hangzhou 310022 China (Y.Y. T.J. J.Y. L.S. D.X.). Electronic address: xudong@***.

RATIONALE AND OBJECTIVES:Early detection of malignant lesions in ultrasound images is crucial for effective cancer diagnosis and treatment. While traditional methods rely on radiologists, deep learning models can improve accuracy, reduce errors, and enhance efficiency. This study explores the application of a deep learning model for classifying benign and malignant lesions, focusing on its performance and interpretability. MATERIALS AND METHODS:In this study, we proposed a feature fusion-based deep learning model for classifying benign and malignant lesions in ultrasound images. The model leverages advanced architectures such as MobileNetV2 and DenseNet121, enhanced with feature fusion and attention mechanisms to boost classification accuracy. The clinical dataset comprises 2171 images collected from 1758 patients between December 2020 and May 2024. Additionally, we utilized the publicly available BUSI dataset, consisting of 780 images from female patients aged 25 to 75, collected in 2018. To enhance interpretability, we applied Grad-CAM, Saliency Maps, and shapley additive explanations (SHAP) techniques to explain the model's decision-making. A comparative analysis with radiologists of varying expertise levels is also conducted. RESULTS:The proposed model exhibited the highest performance, achieving an AUC of 0.9320 on our private dataset and an area under the curve (AUC) of 0.9834 on the public dataset, significantly outperforming traditional deep convolutional neural network models. It also exceeded the diagnostic performance of radiologists, showcasing its potential as a reliable tool for medical image classification. The model's success can be attributed to its incorporation of advanced architectures, feature fusion, and attention mechanisms. The model's decision-making process was further clarified using interpretability techniques like Grad-CAM, Saliency Maps, and SHAP, offering insights into its ability to focus on relevant image features for accurate classi

关键词： Attention mechanisms Deep learning Feature fusion Medical diagnostics Ultrasound imaging

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A Lexical Updating Algorithm for Sentiment Analysis on Chinese Movie Reviews 5

A Lexical Updating Algorithm for Sentiment Analysis on Chine...

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5th International Conference on Advanced Cloud and big data, CBD 2017

作者： Song, Yiwei Gu, Kaiwen Li, Huakang Sun, Guozi Bell Honor School Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing China

ISBN: (纸本)9781538610725

With the prevalence of Internet, sentiment analysis gets popularity among the world. Researchers have made use of kinds of online documents like commodities reivews and movie reviews as training samples to train their models and classfiers, by which they could speculate the underlying emotion in new ones. Douban is a Chinese online community where users share their personal reviews to express their feelings about movies. Those Chinese movie reviews were utilized by us to train our lexicon-based model. Yet multiple words in a ready-made lexicon do not agree with the movie reviews in a specific domain, which means the original lexicon acquires being updated to gain higher accuracy. In this paper we introduce a lexical updating algorithm based on a widely used lexicon. After turns of training of updating, this lexicon is capable of classifying sentiment among movie reviews. The experimental result shows our model using the updated lexicon could get a better performance than the primitive lexicon-based model. © 2017 IEEE.

关键词： Sentiment analysis

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Multi-temporal MOD09A1-based detecting of major growth stages of paddy rice on a provincial scale 37

Multi-temporal MOD09A1-based detecting of major growth stage...

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37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017

作者： Huang, Linsheng Zhang, Shasha Zhao, Jinling Huang, Wenjiang Huang, Jinyang Qi, Xiaobo Anhui Engineering Laboratory Agro-Ecological Big Data Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing100094 China

ISBN: (纸本)9781509049516

Growth stage information is a very primary parameter for managing the grain crop. In this study, time series Enhanced Vegetation Index (EVI) data in 2015 were obtained in Anhui Province, China based on 8-day composite MOD09A1 data products, and the extraction method of rice phenology was specifically analyzed at a provincial scale. HANTS (Harmonic Analysis of Time Series) filtering algorithm was firstly used to smooth the time series EVI curves and identify every growth and development period of paddy rice. The results indicate that HANTS has a better performance in removing noise, restoring original information and retain the change information of multi-temporal EVI curves. The primary planting regions were located in the southern Huai-River areas, from early June to late June in 2015. It turned into the transplanting stage in succession from south to north and followed by the heading stage in succession in early August. From early September to late October, it turned into mature stage from south to north in succession. © 2017 IEEE.

关键词： Indexes

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Analysis on Attention Mechanism Application Schemes for Automatic Question Answering Systems

Analysis on Attention Mechanism Application Schemes for Auto...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Xinyuan Lu Xiaolong Xu Yanfei Sun Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing Jiangsu China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing Jiangsu China Office of Scientific R&D Nanjing University of Posts and Telecommunications Nanjing Jiangsu China

ISBN: (纸本)9781538676738;9781538676721

An automatic question answering system is generally composed of the question analysis module, the information retrieval module, the answer selection module, etc. The core component of automatic question answering system is the answer selection module, which focuses on extracting adequate information from the questions and answers and representing them effectively. The performance of answer selection directly determines the quality of the answers submitted to users. In this paper, we studied the answer selection schemes, especially the Attentive LSTM scheme, focusing on the application of the attention mechanism commonly utilized in deep learning models. Meanwhile, a self-attentive LSTM is proposed by combining the Attentive LSTM with self-attention which is capable of extracting the local features and the global features of texts at the same time. In addition, a multi-attentive LSTM is proposed so that multiple parts of information in the question are available for the answer. We performed a series of experiments based on the datasets InsuranceQA and TrecQA, compared and analyzed on the performances of the above schemes.

关键词： Feature extraction Task analysis Neural networks Logic gates data mining Knowledge discovery Deep learning

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A parallel k-means clustering algorithm based on redundance elimination and extreme points optimization employing MapReduce

A parallel k-means clustering algorithm based on redundance ...

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作者： Tang, Zhuo Liu, Kunkun Xiao, Jinbo Yang, Li Xiao, Zheng College of Information Science and Engineering Hunan University Hunan410082 China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410004 China

When facing massive statistical data, the k-means algorithm is very difficult to satisfy the need of data processing as it lacks an effective parallel mechanism. This paper proposes an improved k-means algorithm (IMR-KCA) to conduct clustering analysis based on medical data employing MapReduce computing framework. Through analyzing the defects of vast redundancy in the traditional k-means algorithms, a selection model is firstly proposed to simplify the computations with multiple clustering centers. Based on several proposed theorems, we prove the correctness of this selection model. Second, this paper provides a method to calculate the distances from extreme points to central points, and the original Euclidean distance is replaced with Manhattan distance. For this simplification, a group of theorems are proposed to prove the correctness. Next, we provide a group of implementation algorithms to complete the parallelism of the clustering computation employing the MapReduce framework. Finally, the experimental results illustrate that IMR-KCA is more reliable and efficient than the direct parallelization of the traditional clustering algorithms based on MapReduce. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

关键词： MapReduce

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Stability Analysis and Hopf Bifurcation Research for DNA Strand Displacement with Time Delay

Stability Analysis and Hopf Bifurcation Research for DNA Str...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Yanhong Liu Hui Lv Changjun Zhou Zhixiang Yin Xianwen Fang Zhonglong Zheng Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China School of Mathematics and Big Data Anhui University of Science and Technology Huaian China College of Mathematics Zhejiang Normal University Jinhua China Department of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (纸本)9781538693810;9781538693803

In this paper, a nonlinear system with time delay mode for DNA strand displacement based on toehold exchange firstly is proposed. The boundedness of all the state variables of the DNA strand displacement system is proved. After that, local stability analysis is performed around the positive equilibrium point to obtain a necessary and sufficient condition for local stability, which depend on the coefficients of the characteristic equation corresponding to linearization of the system. In addition, the existence of the Hopf bifurcation is analyzed, which shows that the time delay parameter will guarantee that the system is stable within a certain range. However, Hopf bifurcation and chaos occur when the time delay parameter increases continuously and even exceeds the critical value. At last, numerical simulations have verified the correctness and validity of the DNA strand displacement studies.

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Comments on cut-set bounds on network function computation

Comments on cut-set bounds on network function computation

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作者： Huang, Cupjin Tan, Zihan Yang, Shenghao Guang, Xuan Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Department of Computer Science University of Chicago ChicagoIL60637 United States School of Science and Engineering Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen518172 China School of Mathematical Sciences and LPMC Nankai University Tianjin China Institute of Network Coding Chinese University of Hong Kong Hong Kong Hong Kong

A function computation problem over a directed acyclic network has been considered in the literature, where a sink node is required to compute a target function correctly with the inputs arbitrarily generated at multiple source nodes. The network links are error free but capacity limited, and the intermediate nodes perform network coding. The computing rate of a network code is the average number of times that the target function is computed for one use of the network, i.e., each link in the network is used at most once. In the existing papers, two cut-set bounds were proposed on the computing rate. However, we in this paper show that these bounds are not valid for general network function computation problems. We analyze the reason of the invalidity and propose a general cut-set bound by using a new equivalence relation associated with the inputs of the target function. Moreover, some results in the existing papers were proved by applying the invalid upper bound. We also justify the validity of these results. © 1963-2012 IEEE.

关键词： Network coding

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A relation prediction method based on PU learning

A relation prediction method based on PU learning

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International Conference on intelligent System and Knowledge Engineering, ISKE

作者： Gao-Jing Peng Ke-Jia Chen Shijun Xue Bin Liu Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing Jiangsu China

This paper studies relation prediction in heterogeneous information networks under PU learning context. One of the challenges of this problem is the imbalance of data number between the positive set P (the set of node pairs with the target relation) and the unlabeled set U (the set of node pairs without the target relation). We propose a K-means and voting mechanism based technique SemiPUclus to extract the reliable negative set RN from U under a new relation prediction framework PURP. The experimental results show that PURP achieves better performance than comparative methods in DBLP co-authorship network data.

关键词： Reliability Artificial neural networks Clustering algorithms Algorithm design and analysis Prediction methods Sun

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