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作者： Chen, Jingqiang Zhuge, Hai Nanjing University of Posts and Telecommunications No.9 Wenyuan RoadYadong New District Nanjing210023 China Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

People often read with aims and reading process significantly influences understanding. This paper defines a new measure of information in text named Aimed Information Quantity in Text by simulating human reading process with reading aims. Aimed Information Quantity in Text reflects not only human memory of words but also relevancy between words emerging in aimed reading process. We demonstrate its application in recommendation. © 2015 John Wiley & Sons, Ltd.

关键词： Behavioral research

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A new method for image fusion based on fuzzy neural network

A new method for image fusion based on fuzzy neural network

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International Conference on Modelling, Identification and Control (ICMIC)

作者： De-gan Zhang Yuan-yuan Wang Wei-wei Liu Xiao-li Zhang Tianjin Key Lab of Intelligent Computing & Novel software Technology Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology China

In pervasive computing paradigm, the image data obtained by a variety of multimedia, information equipment. In order to make use of these information reasonably and efficiently, a new method for image fusion based on fuzzy neural network has presented in this paper. It can fuse massive data from the multi-sensor image. Here, fuzzy neural network is a parallel information processing model, there are more adaptive and self-organization, and can accomplish the complexity of real-time computing and mass data retrieval, it demonstrate its unique superiority of image understanding, pattern recognition and the handling of incomplete information. The fuzzy neural network system developed by us can be used in multi-sensor image fusion. Based on our experiments, it has been proved that the fusion is fast, effective, and can meet the real-time requirements of pervasive computing.

关键词： Image resolution Annealing Weight measurement Adaptation model Gain measurement

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Accurate Recommendation Approach of Psychological Consultation Information Based on User Portrait and TAG_SVD_CF

Research Square

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Research Square 2021年

作者： Zhang, De-Gan Liu, Zi-Xian Fu, Tian-Zheng Zhang, Xin Wen, Kai-Yan Liu, Bing Ministry of Education 300384 China Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology 300384 China

A hybrid recommendation algorithm of psychological counseling information based on user profile and item tag attribute with singular value decomposition （SVD） technology is developed. To solve the problem of data sparsity of the recommendation algorithm, the SVD technology is applied to collaborative filtering algorithm for optimizing the user item rating matrix. The recommendation algorithm includes two parts: generating medical user profile in accurate recommendation of medical information, and realizing the storage, query and update of user profile, where the index system of medical portrait was established from demographic attribute, interest label dimension and business social dimension. The performances of the developed algorithm are investigated by compared with the traditional cosine similarity and Pearson similarity. The results show that the proposed similarity has a lower mean absolute error and significantly improves the accuracy of the system. © 2021, CC BY.

关键词： User profile

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A novel method for segmentation of the cardiac MR images using generalized DDGVF snake models with shape priors

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Information technology Journal 2009年第4期8卷 486-494页

作者： Liu, Lixiong Wu, Yuwei Wang, Yuanquan Beijing Laboratory of Intelligent Information Technology School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China

In this study, a novel method is presented for segmentation of the endocardium and epicardium of the left ventricle in cardiac magnetic resonance images using snake models. We first generalize the DDGVF snake model by introducing two spatially varying weighting functions which characterize the boundary information: this generalized DDGVF snake can conquer the spurious edges raised by artifacts while maintaining the desirable properties of DDGVF of distinguishing the positive and negative boundaries. This is especially helpful for the tasks on hand because the endocardium and epicardium of the LV in MR images can be characterized as positive and negative boundaries. Observed that the left ventricle is roughly a circle, a shape constraint based on circle is introduced into the snake model. This new constraint can prevent the snake contour from being trapped and leaking out so as to maintain the global shape of the snake contour during evolution. In addition, fourth-order PDEs are employed for noise removal. We demonstrate the proposed approach on an in vivo datasct and compare the segmented contours with manual collections;the results show its effectiveness. © 2009 Asian Network for Scientific Information.

关键词： Magnetic resonance imaging

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MFPR: A Personalized Ranking Recommendation with Multiple Feedback

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ACM Transactions on Social computing 2018年第2期1卷 1–22页

作者： Shi, Chuan Liu, Jian Zhang, Yiding Hu, Binbin Liu, Shenghua Yu, Philip S. Beijing Key Lab of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and Telecommunications No. 10 Xi Tu Cheng Road Beijing China Cas Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences No.6 Kexueyuan South Road Zhongguancun Beijing China Department of Computer Science University of Illinois at Chicago 851 South Morgan Street Chicago United States

Recently, recommender systems have played an important role in improving web user experiences and increasing profits. Recommender systems exploit users' behavioral history (i.e., feedback on items) to build models. The feedback usually includes explicit feedback (e.g., ratings) and implicit feedback (e.g., browsing history, click logs), which are both useful for improving recommendations. However, as far as we are concerned, no existing works have integrated both explicit and multiple implicit feedback simultaneously. Therefore, we propose a unified and flexible model, named Multiple Feedback-based Personalized Ranking (MFPR), to make full use of multiple feedback, which uses a personalized ranking framework. To train model MFPR, we design an algorithm to generate ordered item pairs as labeled data, with consideration of both rating scores and multiple implicit feedback. Extensive experiments on two real-world datasets validate the effectiveness of the MFPR model. With the integration of multiple feedback, MFPR significantly improves recommendation performance. © 2018 ACM.

关键词： Recommender systems

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A new Service Mining Method Based on Semantic Process

A New Service Mining Method Based on Semantic Process

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Advances in Information technology and Education

作者： Xin-wei Zhai De-gan Zhang Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education

Service mining is the important research field in universal environment. Locating a network service or a device on demand is a challenging task for pervasive computing. We introduce a new approach that explores the use of Semantic Web language in building architecture for service mining in mobile environment in this paper. We propose a Web Ontology Language based ontology for service description, and for supporting logic-based service matchmaking. We introduced a semantic process algorithm according to the ontology. The algorithm takes the semantic meaning of service into account, enable interact between between device and device. It improves the veracity of service process, and paves the way for fuzzy process and service composition.

关键词： Service mining semantic Ontology Web Ontology Language

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Epilepsy Classification for Mining Deeper Relationships between EEG Channels based on GCN

Epilepsy Classification for Mining Deeper Relationships betw...

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2020 International Conference on Computer Vision, Image and Deep Learning, CVIDL 2020

作者： Chen, Xin Zheng, Yuanjie Niu, Yi Li, Chengiiang Shandong Normal University School of Information Science and Engineering Jinan250358 China Key Lab of Intelligent Computing and Information Security Universities of Shandong Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Institute of Biomedical Sciences Jinan250358 China Department of Electrical Engineering Information Technology Shandong University of Science and Technology Jinan250031 China

ISBN: (纸本)9781728194813

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. © 2020 IEEE.

关键词： Electroencephalography

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A Detection Method for Overlapped Spikes

A Detection Method for Overlapped Spikes

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The 2011 International Conference on Materials Engineering for Advanced Technologies(ICMEAT 2011)

作者： Jia Qi Min Dai Gang Zheng Tong-Tong Liu Tianjin Key Lab of Intelligent Computing & Novel Software Technology Tianjin University of Technology Key Laboratory of Computer Vision and System Ministry of EducationTianjin University of Technology

A new spike detection method is proposed in order to detect the overlapped spikesIn order to avoid missing overlapped spikes, the method adds threshold detection based on window detection methodMoreover, nonlinear energy operator is introduced to make the method strong even under low signal-to-noise ratio situationIn addition, the method solves the repeated detection problem by estimating slopesExperiments show that the method is good for any occasion whatever the low signal-to-noise ratio or baseline wanderEspecially for the overlapped spikes detection, it has much lower false-negative-rate than other traditional detection methods.

关键词： spike sorting overlapped spikes window detection method nonlinear energy operator

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A comprehensive QoS determination model for Infrastructure-as-a-Service clouds

A comprehensive QoS determination model for Infrastructure-a...

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2013 IEEE International Conference on Automation Science and Engineering, CASE 2013

作者： Xia, Yunni Zhou, Mengchu Luo, Xin Zhu, Qingsheng Software Theory and Technology Chongqing Key Lab Chongqing University Chongqing 400030 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

ISBN: (纸本)9781479915156

Cloud computing is a recently developed new technology for complex systems with massive service sharing, which is different from the resource sharing of the grid computing systems. In a cloud environment, service requests from users go through numerous provider specific steps from the instant it is submitted to when the service is fully delivered. Quality modeling and analysis of clouds are not easy tasks because of the complexity of the provisioning mechanism and the dynamic cloud environment. This study proposes an analytical modelbased approach for quality evaluation of Infrastructure-as-a-Service cloud and consider expected request completion time, rejection probability, and system overhead rate as key QoS metrics. It also features with the modeling of different warming and cooling strategies of machines and the ability to identify the optimal balance between system overhead and performance. © 2013 IEEE.

关键词： Quality control

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new service discovery algorithm based on DHT for mobile application

New service discovery algorithm based on DHT for mobile appl...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： De-gan Zhang Wen-bin Li Zhen Ma Key Laboratory of Computer Vision and System Ministry of Education China Tianiin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology China

In order to solve how to enhance the discovery efficiency and coverage, based on DHT (Distributed Hash Table), we put forward a new algorithm of service discovery for mobile application. In traditional DHT discovery algorithm, each node maintains the finger-table that store node information of adjacent node. By using Small-World Theory, we put forward adding a remote node into the finger-table and adding the corresponding remote index. It is different from selecting the remote connection node randomly. We select the remote connection node by calculating local node and it can assure not only the cove range of service discovery but also not increase the length of finger-table, which simplifies the calculation of the finger-table and maintenance work. The simulation proved that the algorithm can reduce the path length of service discovery effectively, improve success rate of service discovery.

关键词： Fingers Peer-to-peer computing Algorithm design and analysis Redundancy Servers Mobile applications Conferences

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