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Energy efficient user association and resource allocation in active array aided HetNets

IET COMMUNICATIONS 2018年第6期12卷 672-679页

作者： Li, Qing Yang, Qinghai Qin, Meng Kwak, Kyung-Sup Xidian Univ Sch Telecommun Engn Collaborat Innovat Ctr Informat Sensing & Underst State Key Lab ISN 2 Taibainan Lu Xian Shaanxi Peoples R China Inha Univ Grad Sch Informat Technol & Telecommun 253 Yonghyun Dong Incheon South Korea

To enable sustainable wireless networks, though new technologies have been proposed to improve the system spectrum efficiency, the energy efficiency (EE) is also of vital importance due to the increasing users and devices. Active array system (AAS) and heterogeneous networks (HetNets) have been reckoned as an enormous enhancement in spectrum efficiency and EE. In this study, the energy efficient user association and resource allocation problem for preference-aware multicast service in AAS aided HetNets is investigated, formulated as a mixed-integer non-linear fractional programming. By generalised fractional programming theory and Lagrangian dual decomposition, an iterative algorithm is devised to determine user association and resource allocation. Further, an efficient solution is proposed to perform quality of service-guaranteed user association and resource allocation to maximise the EE. Simulation results demonstrate the convergence performance and potential gain of the proposed algorithms in terms of EE.

关键词： energy conservation resource allocation multicast communication nonlinear programming integer programming quality of service cellular radio iterative methods energy efficient user association active array-aided HetNet sustainable wireless networks system spectrum efficiency active array system heterogeneous networks resource allocation problem preference-aware multicast service AAS-aided HetNet spectrum efficiency mixed-integer nonlinear fractional programming generalised fractional programming theory Lagrangian dual decomposition iterative algorithm quality of service-guaranteed user association

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'Buy n times, get one free' loyalty cards: Are they profitable for competing firms? A game theoretic analysis

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2018年第2期265卷 621-630页

作者： Bazargan, Amirhossein Karray, Salma Zolfaghari, Saeed Ryerson Univ 350 Victoria St Toronto ON M5B 2K3 Canada Univ Ontario Inst Technol 2000 Simcoe St North Oshawa ON L1H 7K4 Canada

This paper evaluates whether firms offering loyalty programs (LPs) should choose a restricted redemption policy by imposing a specific number of purchases before customers can redeem their points. Such restriction is commonly offered in form of 'buy n times, get one free' loyalty cards. We develop a multinomial logit model where consumer's utility depends on the value of the product and of the rewards. Using an iterative algorithm, we numerically solve a Nash game for two firms offering loyalty programs. Optimal strategies and profits are obtained for three different scenarios (games): (1) both firms do not restrict redemption;(2) both firms restrict redemption;and (3) only one firm restricts redemption while the other firm does not. Our main findings indicate that each firm's optimal strategies are significantly affected by whether the competitor decides to restrict or not to restrict redemption. "In particular, a firm that restricts reward redemption should offer a higher price if its competitor also restricts redemption. Further, the dominant strategy of the game depends on customers' valuations of time and rewards. For example, when customers highly value time but do not highly value rewards, the dominant strategy for both firms is not to restrict redemption. Alternatively, firms can face a Prisoner dilemma situation leading to unrestricted redemption policy for intermediate levels of customer valuation of both time and rewards. (C) 2017 Elsevier B.V. All rights reserved.

关键词： OR in marketing iterative algorithm Multinomial logit models Loyalty programs Game theory

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Primal dual based ontology sparse vector learning for similarity measuring and ontology mapping

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2018年第4期35卷 4525-4531页

作者： Gong, Shu Tian, Liwei Imran, Muhammad Gao, Wei Guangdong Univ Sci & Technol Dept Comp Sci Dongguan 523083 Peoples R China United Arab Emirates Univ Dept Math Sci Al Ain U Arab Emirates Yunnan Normal Univ Sch Informat Sci & Technol Kunming Yunnan Peoples R China

From the mathematical point of view, the goal of ontology learning is to obtain the dimensionality function f : R-p -> R, and the p-dimensional vector corresponding to the ontology vertex is mapped into one-dimensional real number. In the background of big data applications, the ontology concept corresponds to the high complexity of information, and thus sparse tricks are used in ontology learning algorithm. Through the ontology sparse vector learning, the ontology function f is obtained via ontology sparse vector beta, and then applied to ontology similarity computation and ontology mapping. In this paper, the ontology optimization strategy is obtained by coordinate descent and dual optimization, and the optimal solution is obtained by iterative procedure. Furthermore, the greedy method and active sets are applied in the iterative process. Two experiments are presented where we will apply our algorithm to plant science for ontology similarity measuring and to mathematics ontologies for ontology mapping, respectively. The experimental data show that our primal dual based ontology sparse vector learning algorithm has high efficiency.

关键词： Ontology similarity measure ontology mapping machine learning iterative algorithm

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Multienergy element-resolved cone beam CT (MEER-CBCT) realized on a conventional CBCT platform

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MEDICAL PHYSICS 2018年第10期45卷 4461-4470页

作者： Shen, Chenyang Li, Bin Lou, Yifei Yang, Ming Zhou, Linghong Jia, Xun Univ Texas Southwestern Med Ctr Dallas Dept Radiat Oncol Dallas TX 75390 USA Sun Yat Sen Univ State Key Lab Oncol South China Ctr Canc Collaborat Innovat Ctr Canc Med Guangzhou 510060 Guangdong Peoples R China Univ Texas Dallas Dept Math Sci Dallas TX 75080 USA Southern Med Univ Dept Biomed Engn Guangzhou 510515 Guangdong Peoples R China

PurposeCone beam CT (CBCT) has been widely used in radiation therapy. However, its main application is still to acquire anatomical information for patient positioning. This study proposes a multienergy element-resolved (MEER) CBCT framework that employs energy-resolved data acquisition on a conventional CBCT platform and then simultaneously reconstructs images of x-ray attenuation coefficients, electron density relative to water (rED), and elemental composition (EC) to support advanced applications. MethodsThe MEER-CBCT framework is realized on a Varian TrueBeam CBCT platform using a kVp-switching scanning scheme. A simultaneous image reconstruction and elemental decomposition model is formulated as an optimization problem. The objective function uses a least square term to enforce fidelity between x-ray attenuation coefficients and projection measurements. Spatial regularization is introduced via sparsity under a tight wavelet-frame transform. Consistency is imposed among rED, EC, and attenuation coefficients and inherently serves as a regularization term along the energy direction. The EC is further constrained by a sparse combination of ECs in a dictionary containing tissues commonly existing in humans. The optimization problem is solved by a novel alternating-direction minimization scheme. The MEER-CBCT framework was tested in a simulation study using an NCAT phantom and an experimental study using a Gammex phantom. ResultsMEER-CBCT framework was successfully realized on a clinical Varian TrueBeam onboard CBCT platform with three energy channels of 80, 100, and 120kVp. In the simulation study, the attenuation coefficient image achieved a structural similarity index of 0.98, compared to 0.61 for the image reconstructed by the conventional conjugate gradient least square (CGLS) algorithm, primarily because of reduction in artifacts. In the experimental study, the attenuation image obtained a contrast-to-noise ratio 60, much higher than that of CGLS results (simila

关键词： cone beam CT dictionary elemental-resolved reconstruction iterative algorithm kVp-switching multi-energy

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Transmission of an X-ray beam through a two-dimensional photonic crystal and the Talbot effect

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JOURNAL OF SYNCHROTRON RADIATION 2018年第2期25卷 425-431页

作者： Kohn, V. G. Natl Res Ctr Kurchatov Inst Kurchatov Sq 1 Moscow 123182 Russia

Results of computer simulations of the transmission of an X-ray beam through a two-dimensional photonic crystal as well as the propagation of an X-ray beam in free space behind the photonic crystal are reported. The photonic crystal consists of a square lattice of silicon cylinders of diameter 0.5 mm. The amount of matter in the path of the X-ray beam rapidly decreases at the sides of the cylinder projections. Therefore the transmission is localized near the boundaries, and appears like a channeling effect. The iterative method of computer simulations is applied. This method is similar to the multi-slice method that is widely used in electron microscopy. It allows a solution to be obtained with acceptable accuracy. A peculiarity in the intensity distribution inside the Talbot period z(T) in free space was found when the intensity is approximately equal to the initial value at a distance 0.46z(T), and it is shifted by half a period at distance 0.5z(T). The reason for this effect is the existence of a periodic phase of the wavefunction of radiation inside the intensity peaks. Simulations with zero phase do not show this effect. Symmetry rules for the Talbot effect are discussed.

关键词： X-ray transmission two-dimensional photonic crystal Talbot effect computer simulations iterative algorithm

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LAIM: A Linear Time iterative Approach for Efficient Influence Maximization in Large-Scale Networks

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IEEE ACCESS 2018年 6卷 44221-44234页

作者： Wu, Hongchun Shang, Jiaxing Zhou, Shangbo Feng, Yong Qiang, Baohua Xie, Wu Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China Chongqing Univ Minist Educ Key Lab Dependable Serv Comp Cyber Phys Soc Chongqing 400044 Peoples R China Guilin Univ Elect Technol Guangxi Cooperat Innovat Ctr Cloud Comp & Big Dat Guilin 541004 Peoples R China Guilin Univ Elect Technol Guangxi Coll & Univ Key Lab Cloud Comp & Complex Guilin 541004 Peoples R China Guilin Univ Elect Technol Guangxi Key Lab Trusted Software Guilin 541004 Peoples R China

The problem of influence maximization (IM) has been extensively studied in recent years and has many practical applications such as social advertising and viral marketing. Given the network and diffusion model, IM aims to find an influential set of seed nodes so that targeting them as diffusion sources will trigger the maximum cascade of influenced individuals. The largest challenge of the IM problem is its NP-hardness, and most of the existing approaches are with polynomial time complexity, making themselves unscalable to very large networks. To address this issue, in this paper, we propose LAIM: a linear time iterative approach for efficient IM on large-scale networks. Our framework has two steps: 1) influence approximation and 2) seed set selection. In the first step, we propose an iterative algorithm to compute the local influence of a node based on a recursive formula and use the local influence to approximate its global influence. In the second step, the k influential seed nodes are mined based on the approximated influence in the first step. Based on our model, we theoretically prove that the proposed approach has linear time and space complexity. We further accelerate our algorithm with simple modifications and propose its fast version. Experimental results on eight real-world large-scale networks exhibit the superiority of our approach over the state-of-the-art methods in terms of both effectiveness and efficiency.

关键词： Influence maximization iterative algorithm social networks analysis information diffusion computational complexity

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Stabilization for Singular Fractional-Order Systems via Static Output Feedback

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IEEE ACCESS 2018年 6卷 71678-71684页

作者： Guo, Ying Lin, Chong Chen, Bing Wang, Qing-Guo Qingdao Univ Inst Complex Sci Qingdao 266071 Peoples R China Zaozhuang Univ Sch Math & Stat Zaozhuang 277160 Peoples R China Univ Johannesburg Fac Engn & Built Environm Inst Intelligent Syst Johannesburg South Africa

The stabilization problem of singular fractional-order systems with fractional commensurate order 0 < alpha < 2 via static output feedback is studied in this paper. For the 0 < alpha < 1 case, two methods for the static output feedback control design are provided. In the first method, the controller is designed without decomposing the system matrix, and less variables are within the second method. Furthermore, a method that is similar to the second method of the 0 < alpha < 1 case is provided for the 1 <= alpha < 2 case. The controller 6 parameters are computed by solving matrix inequalities, and efficient iterative algorithms are built to solve the resultant matrix inequalities. Numerical examples are provided to show the effectiveness of the proposed results.

关键词： Singular fractional-order systems linear matrix inequality (LMI) static output feedback iterative algorithm

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A Provenance-Aware Multi-dimensional Reputation System for Online Rating Systems

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ACM TRANSACTIONS ON INTERNET TECHNOLOGY 2018年第4期18卷 1–20页

作者： Rezvani, Mohsen Ignjatovic, Aleksandar Bertion, Elisa Shahrood Univ Technol Fac Comp Engn Shahrood *** Iran Univ New South Wales Sydney NSW Australia Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA UNSW Sydney Sch Comp Sci & Engn Sydney NSW 2052 Australia

Online rating systems are widely accepted as means for quality assessment on the web and users increasingly rely on these systems when deciding to purchase an item online. This makes such rating systems frequent targets of attempted manipulation by posting unfair rating scores. Therefore, providing useful, realistic rating scores as well as detecting unfair behavior are both of very high importance. Existing solutions are mostly majority based, also employing temporal analysis and clustering techniques. However, they are still vulnerable to unfair ratings. They also ignore distances between options, the provenance of information, and different dimensions of cast rating scores while computing aggregate rating scores and trustworthiness of users. In this article, we propose a robust iterative algorithm which leverages information in the profile of users and provenance of information, and which takes into account the distance between options to provide both more robust and informative rating scores for items and trustworthiness of users. We also prove convergence of iterative ranking algorithms under very general assumptions, which are satisfied by the algorithm proposed in this article. We have implemented and tested our rating method using both simulated data as well as four real-world datasets from various applications of reputation systems. The experimental results demonstrate that our model provides realistic rating scores even in the presence of a massive amount of unfair ratings and outperforms the well-known ranking algorithms.

关键词： Reputation system rating provenance iterative algorithm online rating

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Mim: A Merge Iteration and Its Applications for Big Data

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IEEE ACCESS 2018年 6卷 66984-66997页

作者： Song, Jie Wang, Han Zhang, Yichuan Bao, Yubing Yu, Ge Northeastern Univ Software Coll Shenyang 110819 Liaoning Peoples R China Northeastern Univ Sch Comp Sci & Engn Shenyang 110819 Liaoning Peoples R China

With the rapid development of technologies like the Internet, sensors and bioinformatics, and data has grown explosively. In the big data era, more and more iterative algorithms have been applied in the fields of data mining and machine learning. In most situation, the iterative algorithms compute in the entire dataset which are merged from the partial ones. Given the iterative results on partial datasets, it is efficient if the results on the entire dataset can be merged from them, otherwise the re-computing on entire one is time consuming. Unfortunately, current iteration model do not support the results merging. We propose merge iteration computing model (Mim) in this paper. Mim is a solution but not a platform. It states how to execute iterative algorithm effectively through reusing the exiting results without sacrificing the accuracy, and such mechanism is suitable for the most iterative algorithms. We explain the in-partition iteration step, error evaluation step, compensation step (optional), and merge iteration step of Mim, in addition, the in-partition iteration step is preliminary of merging iteration and should be done before the partial datasets are merged. We also analyze the accuracy and performance advantages of Mim theoretically. In the application scenarios, we implement Mim over Spark framework, and applied the Mim to the financial data analysis in a city. Finally, through a series of experiments, we prove the efficiency and accuracy of the proposed Mim on the PageRank and K-means algorithms. Under the various test cases, the maximum optimization ratio of Mim is 25% and 56% comparing with regular iteration on PageRank and K-means, respectively. And the errors are negligible.

关键词： Big data iterative computing model merge iteration iterative algorithm

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H_∞ consensus for linear heterogeneous multi-agent systems with state and output feedback control

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NEUROCOMPUTING 2018年 275卷 2635-2644页

作者： Han, Ji Zhang, Huaguang Jiang, He Sun, Xun Northeastern Univ Coll Informat Sci & Engn Box 134 Shenyang 110819 Liaoning Peoples R China

In this paper, the problem of H-infinity consensus for linear heterogeneous multi-agent systems (HMASs) with state and output feedback control is investigated. By using the linear matrix inequality (LMI) theory, some basic properties of symmetric positive definite matrix and a series of analysis, the novel consensus conditions of using state and output feedback control and the corresponding algorithm are provided. The key idea of this paper is to convert one kind of nonlinear matrix inequality condition into a series of novel conditions that can be solved by using LMI toolbox and the most important characteristic of this paper is that the necessary and sufficient conditions of H-infinity consensus are provided while only sufficient conditions were given in some existing results. First, an equivalent condition for a special kind of nonlinear matrix inequality is given. Second, by using this equivalent condition, the necessary and sufficient conditions of H-infinity consensus for linear HMASs under state and output feedback control approaches are provided, respectively. Third, according to iterative algorithm and the property of trace of matrix, a feasible algorithm for calculating the controllers is proposed. Fourth, the obtained results are extended to solve the H-infinity control problem for general linear system with some additional conditions. At last, two numerical examples are given to support our results. (C) 2017 Elsevier B. V. All rights reserved.

关键词： H-infinity consensus Linear heterogeneous multi-agent system LMI theory State and output feedback iterative algorithm

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