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Search Results: 1 - 10 of 58974 matches for " Fangwen Yang "
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Improvement and Innovation Analysis of China Special Express Mode—The Campus Express  [PDF]
Xiuli Tang, Fangwen Yang, Rui Wang
Modern Economy (ME) , 2016, DOI: 10.4236/me.2016.79102
Abstract: This paper analyzes the current situation of the Campus Express mode through the quantitative and qualitative methods to find the deficiencies in the existing model, and puts forward the improvement of the existing Campus Express mode. A new sorting method is adopted in the Campus unified distribution center for improving picking efficiency and solving the problem of “door-to-door” service. At the same time, the Platform of Campus Express—named “Crowdsourcing Express” mode is created, so that everyone can be involved in the activities of Campus Express. The plant can not only provide a better logistics service, but also combine commerce activities with Campus Express.
Efficiency Evaluation Study about the New and the Old Circulation Modes of Agricultural Products of Fruits and Vegetables in Beijing  [PDF]
Xiuli Tang, Rui Wang, Fangwen Yang, Lixiang Huang
Modern Economy (ME) , 2016, DOI: 10.4236/me.2016.710107
Abstract: Firstly, there is a brief introduction about the new and the old circulation modes of Agricultural Products of fruits and vegetables in Beijing. And there will be an empirical analysis about it by constructing DEA model. The conclusion is that efficiency of the new circulation mode is higher than the old one. And the new mode can compensate for the low efficiency of the old model circulation deficiencies and improve the efficiency of agricultural products circulation of fruits and vegetables in Beijing.
Adsorption and Desorption Mechanisms of Methylene Blue Removal with Iron-Oxide Coated Porous Ceramic Filter  [PDF]
Fangwen LI, Xiaoai WU, Songjiang MA, Zhongjian XU, Wenhua LIU, Fen LIU
Journal of Water Resource and Protection (JWARP) , 2009, DOI: 10.4236/jwarp.2009.11006
Abstract: Adsorption and desorption mechanisms of methylene blue (MB) removal with iron-oxide coated porous ce-ramics filter (IOCPCF) were investigated in batch and column mode. The results revealed that MB removal mechanisms included physical adsorption and chemical adsorption, of which chemical adsorption by surface ligand complex reaction played a dominant role after infrared spectrum analysis. Recycling agents were se-lected from dilute nitric acid (pH=3), sodium hydroxide solution (pH=12) and distilled water. Among three agents, dilute metric acid (pH=3) was the best recycling agent. Regeneration rate of IOCPCF arrived at 82.56% at batch adsorption and regeneration was finished in 75min at column adsorption. Adsorp-tion-desorption cycles of IOCPCF after batch and column adsorption were four and three times, respectively. Further, compared with fresh IOCPCF, MB removal rate with these desorbed IOCPCF adsorption only slightly decreased, which suggested that IOCPCF should be used repeatedly.
Resource Allocation in Communications and Computing
Yi Su,Fangwen Fu,Shuo Guo
Journal of Electrical and Computer Engineering , 2013, DOI: 10.1155/2013/328395
Abstract:
Resource Allocation in Communications and Computing
Yi Su,Fangwen Fu,Shuo Guo
Journal of Electrical and Computer Engineering , 2013, DOI: 10.1155/2013/328395
Abstract: Communication networks and computing systems have demonstrated their importance in the past few decades as a fundamental driver of economic growth. Over the years, they have not only expanded in their sizes, such as geographical area and number of terminals, but also in the variety of services, users, and deployment environments. The purpose of resource allocation in such environments is to intelligently assign the limited available resources among terminals/clients in an efficient way to satisfy end users’ service requirements. With the dramatic developments and fast evolution of communication networks and computing systems, resource allocation continues to be the fundamental challenge, because better quality of service is required with the increasing demand for bandwidth-hungry and/or computation-intensive services. In particular, it has to cope with various new emerging system architectures, such as cognitive networks, mesh networks, multihop networks, peer-to-peer networks, multistandard networks, cloud computing systems, and data centers, distributed intelligence in a multitude of devices operating autonomously enables shifting traditional centralized allocation mechanisms into fully distributed solutions. In recent years, many tools including optimization theory, control theory, game theory, and auction theory have been employed to model and solve a variety of practical resource allocation problems. Therefore, resource allocation in communication networks and computing systems is a pressing research topic that has huge applications. It is imperative to develop advanced resource allocation techniques for ensuring the optimal performance of these systems and networks. The goal of this special issue is to bring together the most updated research contributions in this area. Indeed, we see a wide range of new analytical techniques and novel application scenarios emerging as evidenced in the papers presented here. The nine accepted papers are relevant to resource allocations optimizations in orthogonal frequency division multiplexing (OFDM-) based communication systems, cognitive radio, satellite communications, grid computing, and network virtualization. J. Y. Baudais et al. in “Robustness maximization of parallel multichannel systems,” study bit-loading solutions of both robustness optimization problems over independent parallel channels. Their investigation is based on analytical approach, using generalized Lagrangian relaxation tool, and on greedy-type algorithm approach. The asymptotic convergence of both robustness optimizations is proved for both
Realizing quantum controlled phase-flip gate through quantum dot in silicon slow-light photonic crystal waveguide
Jie Gao,Fangwen Sun,Chee Wei Wong
Physics , 2008, DOI: 10.1063/1.2999588
Abstract: We propose a scheme to realize controlled phase gate between two single photons through a single quantum dot in slow-light silicon photonic crystal waveguide. Enhanced Purcell factor and beta factor lead to high gate fidelity over broadband frequencies compared to cavity-assisted system. The excellent physical integration of this silicon photonic crystal waveguide system provides tremendous potential for large-scale quantum information processing.
Structural Solutions for Cross-Layer Optimization of Wireless Multimedia Transmission
Fangwen Fu,Mihaela van der Schaar
Mathematics , 2009,
Abstract: In this paper, we propose a systematic solution to the problem of cross-layer optimization for delay-sensitive media transmission over time-varying wireless channels as well as investigate the structures and properties of this solution, such that it can be easily implemented in various multimedia systems and applications. Specifically, we formulate this problem as a finite-horizon Markov decision process (MDP) by explicitly considering the users' heterogeneous multimedia traffic characteristics (e.g. delay deadlines, distortion impacts and dependencies etc.), time-varying network conditions as well as, importantly, their ability to adapt their cross-layer transmission strategies in response to these dynamics. Based on the heterogeneous characteristics of the media packets, we are able to express the transmission priorities between packets as a new type of directed acyclic graph (DAG). This DAG provides the necessary structure for determining the optimal cross-layer actions in each time slot: the root packet in the DAG will always be selected for transmission since it has the highest positive marginal utility; and the complexity of the proposed cross-layer solution is demonstrated to linearly increase w.r.t. the number of disconnected packet pairs in the DAG and exponentially increase w.r.t. the number of packets on which the current packets depend on. The simulation results demonstrate that the proposed solution significantly outperforms existing state-of-the-art cross-layer solutions. Moreover, we show that our solution provides the upper bound performance for the cross-layer optimization solutions with delayed feedback such as the well-known RaDiO framework.
Structure-Aware Stochastic Control for Transmission Scheduling
Fangwen Fu,Mihaela van der Schaar
Mathematics , 2010,
Abstract: In this paper, we consider the problem of real-time transmission scheduling over time-varying channels. We first formulate the transmission scheduling problem as a Markov decision process (MDP) and systematically unravel the structural properties (e.g. concavity in the state-value function and monotonicity in the optimal scheduling policy) exhibited by the optimal solutions. We then propose an online learning algorithm which preserves these structural properties and achieves -optimal solutions for an arbitrarily small . The advantages of the proposed online method are that: (i) it does not require a priori knowledge of the traffic arrival and channel statistics and (ii) it adaptively approximates the state-value functions using piece-wise linear functions and has low storage and computation complexity. We also extend the proposed low-complexity online learning solution to the prioritized data transmission. The simulation results demonstrate that the proposed method achieves significantly better utility (or delay)-energy trade-offs when comparing to existing state-of-art online optimization methods.
Structural Solutions to Dynamic Scheduling for Multimedia Transmission in Unknown Wireless Environments
Fangwen Fu,Mihaela van der Schaar
Computer Science , 2010,
Abstract: In this paper, we propose a systematic solution to the problem of scheduling delay-sensitive media data for transmission over time-varying wireless channels. We first formulate the dynamic scheduling problem as a Markov decision process (MDP) that explicitly considers the users' heterogeneous multimedia data characteristics (e.g. delay deadlines, distortion impacts and dependencies etc.) and time-varying channel conditions, which are not simultaneously considered in state-of-the-art packet scheduling algorithms. This formulation allows us to perform foresighted decisions to schedule multiple data units for transmission at each time in order to optimize the long-term utilities of the multimedia applications. The heterogeneity of the media data enables us to express the transmission priorities between the different data units as a priority graph, which is a directed acyclic graph (DAG). This priority graph provides us with an elegant structure to decompose the multi-data unit foresighted decision at each time into multiple single-data unit foresighted decisions which can be performed sequentially, from the high priority data units to the low priority data units, thereby significantly reducing the computation complexity. When the statistical knowledge of the multimedia data characteristics and channel conditions is unknown a priori, we develop a low-complexity online learning algorithm to update the value functions which capture the impact of the current decision on the future utility. The simulation results show that the proposed solution significantly outperforms existing state-of-the-art scheduling solutions.
A Systematic Framework for Dynamically Optimizing Multi-User Wireless Video Transmission
Fangwen Fu,Mihaela van der Schaar
Computer Science , 2009,
Abstract: In this paper, we formulate the collaborative multi-user wireless video transmission problem as a multi-user Markov decision process (MUMDP) by explicitly considering the users' heterogeneous video traffic characteristics, time-varying network conditions and the resulting dynamic coupling between the wireless users. These environment dynamics are often ignored in existing multi-user video transmission solutions. To comply with the decentralized nature of wireless networks, we propose to decompose the MUMDP into local MDPs using Lagrangian relaxation. Unlike in conventional multi-user video transmission solutions stemming from the network utility maximization framework, the proposed decomposition enables each wireless user to individually solve its own dynamic cross-layer optimization (i.e. the local MDP) and the network coordinator to update the Lagrangian multipliers (i.e. resource prices) based on not only current, but also future resource needs of all users, such that the long-term video quality of all users is maximized. However, solving the MUMDP requires statistical knowledge of the experienced environment dynamics, which is often unavailable before transmission time. To overcome this obstacle, we then propose a novel online learning algorithm, which allows the wireless users to update their policies in multiple states during one time slot. This is different from conventional learning solutions, which often update one state per time slot. The proposed learning algorithm can significantly improve the learning performance, thereby dramatically improving the video quality experienced by the wireless users over time. Our simulation results demonstrate the efficiency of the proposed MUMDP framework as compared to conventional multi-user video transmission solutions.
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