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12th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2016

作者： Liu, Zijuan Wang, Lin Liu, Wenyuan Li, Binbin School of Information Science and Engineering Yanshan University China Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province China School of Economics and Management Yanshan University Qinhuangdao HeBei China

ISBN: (纸本)9781509056965

Under the influence of multipath effects and small scale fading, the robustness and reliability of the existing human detection methods based on radio frequency signals are easy to be impaired. In this paper, we propose a novel design that using the multi-layer filtering of channel state information (CSI) to identify moving targets in dynamic environments and analyze the gait periodicity of human. We employ an efficient CSI subcarrier feature difference to the multi-layer filtering method leveraging principal component analysis (PCA) and discrete wavelet transform (DWT) to eliminate the noises. Furthermore, we propose a profile matching mechanism for human detection and a periodicity analysis mechanism for human gait taking advantage of the above design. We evaluated it with the commodity Wi-Fi infrastructures in different environments. Experimental results indicate that our approach performs identification of human with an average accuracy of 94%. © 2016 IEEE.

关键词： Principal component analysis

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Research on Recommendation Strategies Integrating Emotional Tendency and User Influences 20

Research on Recommendation Strategies Integrating Emotional ...

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2020 International Conference on Internet Computing for Science and Engineering, ICICSE 2020 and the 13th International Conference on Advanced computer Theory and Engineering, ICACTE 2020

作者： Jing, Chen Liuqian, Duan Hong, Zhang College of Information Science and Engineering Yanshan University Qinhuangdao China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China Software Engineering Laboratory in Hebei Province Qinhuangdao China

ISBN: (纸本)9781450377348

At present, the topic model based on LDA as an information recommendation method has the defect of neglecting the emotional information in social platform. Therefore, a microblog user recommendation strategy I-TES (influence topic emotionality similarity model) is proposed which combines emotional orientation with user influence model in this paper. Firstly, the user's theme distribution and emotional tendency is obtained based on JST model, the JS distance is used to calculate the similarity of user's theme probability distribution, and the two is combined to get the user's interest similarity score. Secondly, the user's influence measurement indicators are summarized into microblog influence, user's activity and fan's influence, and the weights of the three indicators are calculated according to AHP(analytic hierarchy process). Finally, the combination of the two is used to obtain the final score as the recommendation result. The strategy is tested on Sina Weibo user data set, and the experiment shows that this strategy has higher recommendation accuracy than the traditional recommendation method. © 2020 ACM.

关键词： Probability distributions

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Multi-resolution terrain rendering seamlessly by function curve fitting

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Journal of Computational Information systems 2012年第24期8卷 10399-10409页

作者： Nie, Junlan Guo, Dongliang Kong, Lingfu Wang, Yanfen The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao 066004 China

During the process of real-time multi-resolution terrain rendering, avoiding cracks between LOD (Level of Detail) has always been a tedious task that requires extra complicated handling. In this paper, we propose a novel algorithm called Function Curve Fitting (FCF) to repair T-junction cracks of regular data-based LODs. FCF, as a time-efficient algorithm, uses regular grid as rendering element, could be conveniently integrated with existing algorithms and achieve seamless meshes with excellent image quality and frame rates. Compared with other existing LOD crack-repairing algorithms based on terrain rendering, the experiments on surface quality and rendering performance demonstrate the effectiveness of our FCF approach. © 2011 by Binary Information Press.

关键词： Curve fitting

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Rapid modeling for large scale anhui-styled architectures

Rapid modeling for large scale anhui-styled architectures

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2012 International Conference on systems and Informatics, ICSAI 2012

作者： Xue, Feng Wang, Xiaotao School of Computer Science and Information Hefei University of Technology Hefei 230009 China State Key Lab of Virtual Reality Technology and System Beihang University Beijing 100191 China

ISBN: (纸本)9781467301992

To construct Anhui-Styled Architecture (ASA) models rapidly and automatically, we proposed an automatic modeling method by analyzing the basic structure of ASA in-depth. Firstly, we built modules' database, composition rule database and repository database of ASA. Then, we translated each module of architecture into a node of graph and traverse these nodes using Breadth-First Traversal(BFS) algorithm of Graph to get descript document of single building. Finally, large scale scene of ASA were constructed automatically by combine the descript document and large scale ground scenes. Experimental results show that our method is rapid and effective for constructing ASA models. © 2012 IEEE.

关键词： Database systems

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Capacity planning of the registration server in cloud storage

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International Journal of High Performance systems Architecture 2017年第2期7卷 105-112页

作者： Gu, Rui Jin, Shunfu Wu, Haixing School of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Avenue Qinhuangdao066004 China Science and Technology on Communication Networks Laboratory No. 589 West Zhongshan Road Shijiazhuang050081 China

Cloud storage is one of the key services in cloud computing. In order to appeal more users to the cloud storage, free cloud experience is provided to potential users. A registration server is set specially for intentional users who are satisfied with the free experience and want to register as very important persons (VIPs). In order to mathematically evaluate the system performance and optimally plan the registration server, we establish a queueing network-based system model. We analyse the steady-state distribution of the system model and derive the performance measures of the system in terms of the average response time of potential users and the utilisation of registration server. For balancing different performance measures, we establish a cost function and develop an optimisation algorithm to plan the capacity of the registration server with a reasonable service rate. © Copyright 2017 Inderscience Enterprises Ltd.

关键词： Queueing networks

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BAT: Mining Binary-API Topic for Multi-service Application Development 26

BAT: Mining Binary-API Topic for Multi-service Application D...

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： He, Pengfei Liu, Linlin You, Dianlong Shen, Limin Chen, Zhen Yanshan University School of Information Science and Engineering Qinhuangdao China Chinese Academy of Sciences National Science Libraries Beijing China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

ISBN: (纸本)9798350331684

With the growing popularity of API-driven multiservice application (mashup) development, the burgeoning web APIs have left developers drowning in the sea of web API selections. Matching developers with the most appropriate APIs is the key to improving user satisfaction and promoting more popular web applications. As a result, more and more researchers pay attention to web API recommender systems based on collaborative filtering. However, employing collaborative filtering to recommend APIs is challenging due to the severe sparsity of mashup and API interactions. To address this problem, we propose a probabilistic generative model, called the Binary-API Topic model (BAT), to parameterize mashups and APIs. Technically, BAT is equipped with a mechanism to extract binary-APIs and predict unknown pairwise interactions. To improve generality and capture more relevance from a limited number of interactions, we learn binary-API topics by directly modeling the generation of API co-occurrence patterns across the repository (all mashup collections from ***). The main advantage of BAT is that it preserves API co-occurrence patterns in model learning and exploits the rich global relevance. Finally, through extensive experiments, we demonstrate that BAT can achieve the highest performance on the sparse real-world data set. © 2023 IEEE.

关键词： Collaborative filtering

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Detecting shilling profiles in collaborative recommender systems via multidimensional profile temporal features

Detecting shilling profiles in collaborative recommender sys...

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作者： Hao, Yaojun Zhang, Fuzhi School of Information Science and Engineering Yanshan University Qinhuangdao Hebei Province China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao Hebei Province China Department of Computer Science and Technology Xinzhou Teachers University Xinzhou Shanxi Province China

To defend recommender systems, various methods have been proposed to detect shilling profiles, which can be categorised as user- and item-based detection methods. Most of the user-based methods identify shilling profiles via statistical signatures of rating values and suffer from low precision when detecting different types of attacks. Most of the item-based methods use temporal information to detect the anomaly items, but they assume that the fake ratings were injected in short periods. So they are invalid for the long duration and decentralised injection attacks. To address these limitations, the authors extract the multidimensional profile temporal features and present a shilling detection method. First, from the user profile view, user rating behaviours are characterised by corrected conditional entropy and the dissimilarity with the rest-rating model. Second, from the item profile view, the user features are extracted according to item temporal popularity. Third, the features based on weighted deviation from dynamic mean are extracted according to the fact that the items mean changes with time. Finally, support vector machine is exploited to detect shilling profiles based on the proposed features. Experimental results on the Netflix dataset indicate that the performance of the proposed method is better than that of the benchmark methods. © The Institution of Engineering and technology 2018.

关键词： User profile

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Effects of nicotine stimulation on spikes, theta frequency oscillations, and spike-theta oscillation relationship in rat medial septum diagonal band Broca slices

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中国药理学报（英文版） 2013年第4期34卷 464-472页

作者： Dong WEN Ce PENG Gao-xiang OU-YANG Zainab HENDERSON Xiao-li LI Cheng-biao LU The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao 066004 China School of Electrical Engineering Yanshan University Qinhuangdao 066004 China Institute of Membrane Biology Leeds University of Leeds United Kingdom The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao 066004 China School of Electrical Engineering Yanshan University Qinhuangdao 066004 China

Aim: Spiking activities and neuronal network oscillations in the theta frequency range have been found in many cortical areas during information processing. The aim of this study is to determine whether nicotinic acetylcholine receptors (nAChRs) mediate neuronal network activity in rat medial septum diagonal band Broca (MSDB) slices. Methods: Extracellular field potentials were recorded in the slices using an Axoprobe 1A amplifier. Data analysis was performed off- line. Spike sorting and local field potential (LFP) analyses were performed using Spike2 software. The role of spiking activity in the generation of LFP oscillations in the slices was determined by analyzing the phase-time relationship between the spikes and LFP oscil- lations. Circular statistic analysis based on the Rayleigh test was used to determine the significance of phase relationships between the spikes and LFP oscillations. The timing relationship was examined by quantifying the spike-field coherence (SFC), Results: Application of nicotine (250 nmol/L) induced prominent LFP oscillations in the theta frequency band and both small- and large-amplitude population spiking activity in the slices. These spikes were phase-locked to theta oscillations at specific phases. The Rayleigh test showed a statistically significant relationship in phase-locking between the spikes and theta oscillations. Larger changes in the SFC were observed for large-amplitude spikes, indicating an accurate timing relationship between this type of spike and LFP oscillations, The nicotine-induced spiking activity (large-amplitude population spikes) was suppressed by the nAChR antagonist dihydro-~-erythroidine (0.3 pmol/L). Conclusion: The results demonstrate that large-amplitude spikes are phase-locked to theta oscillations and have a high spike-timing accuracy, which are likely a main contributor to the theta oscillations generated in MSDB during nicotine receptor activation.

关键词： medial septum diagonal band of Broca theta oscillations spike LFP nicotinic acetylcholine receptor nicotine dihydro-β-erythroidine brain slice electrophysiology

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Dynamic community mining based on behavior prediction

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International Journal of Performability Engineering 2018年第7期14卷 1590-1599页

作者： Chen, Xiao Hu, Xinzhuan Pan, Xiao Guo, Jingfeng Network Technology Center Hebei Normal University of Science and Technology Qinhuangdao066004 China College of Economics and Management YanShan University Qinhuangdao066004 China College of Economic and Management Shijiazhuang Tiedao University Shijiazhuang050043 China College of Information Science and Engineering YanShan University Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao066004 China

Dynamic network research has been a new trend in recent years. Based on the influence of vertex behavior on community structure, this paper studies signed network dynamic community mining. Firstly, the set pair connection degree is introduced to describe the relation between vertices, and the edge prediction model of signed network is proposed by taking into account the variability of the relation between vertices. Secondly, based on the prediction model, a set pair signed networks dynamic model is proposed by adding time axis T to the signed network. Then, based on the dynamic model, the evolution of signed networks and community discovering are studied. Finally, network evolution law and community stability are analyzed by using the connection trend and connection entropy in set pair theory, and the accuracy and validity of the dynamic community mining algorithm are verified by experiments. © 2018 Totem Publishers Ltd. All rights reserved.

关键词： Dynamic models

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Association Rule Guided Web API Complementary Function Recommendation for Mashup Creation: An Explainable Perspective 17th

Association Rule Guided Web API Complementary Function Recom...

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17th CCF Conference on computer Supported Cooperative Work and Social Computing, ChineseCSCW 2022

作者： He, Pengfei Qi, Wenchao Liu, Xiaowei Liu, Linlin You, Dianlong Shen, Limin Chen, Zhen School of Information Science and Engineering Yanshan University Qinhuangdao China National Science Libraries Chinese Academy of Sciences Beijing China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao China

ISBN: (纸本)9789819923557

As more and more service providers encapsulate and publish their data and services on the internet in the form of Web APIs, the number of Web APIs is ever-increasing. For this reason, Web API recommendation is gaining momentum and has achieved high performance in accuracy. However, few studies paid attention to function recommendation. As an indispensable entity in the mashup-API ecosystem, function is not only the in-facto basis of API taxonomy, but also determines the compatibility and the internal construction pattern of mashup composition. Considering that users adopt multiple function invocations during a development cycle and the number of functions is also increasing, we propose the complementary function recommendation(CFR), a function-to-function problem. To solve the CFR, we regard each mashup as a transaction set for frequent pattern mining and propose an association rule-based complementary function recommendation(ARCFR) system, which provides function recommendation and corresponding probability explanation. Our experiments show that ARCFR can recommend complementary function effectively, and we give two applicable scenarios to demonstrate the practical value of our method in more aspects. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Association rules

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