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Minimizing power consumption in bandwidth limited optical traffic grooming networks is presented as a two-objective optimization problem. Since the main objective is to route a connection, the network throughput is maximized first, and then the minimum power consumption solution is found for this maximized throughput. Both transparent IP over WDM (Tp-IPoWDM) and translucent IP over WDM (Tl-IPoWDM) network may be applied to examine such bi-objective algorithms. Simulations show that the bi-objective algorithms are more energy-efficient than the single objective algorithms where only the throughput is optimized. For a Tp-IPoWDM network, both link based ILP (LB-ILP) and path based ILP (PB-ILP) methods are formulated and solved. Simulation results show that PB-ILP can save more power than LB-ILP because PB-ILP has more path selections when lightpath lengths are limited. For a Tl-IPoWDM network, only PB-ILP is formulated and we show that the Tl-IPoWDM network consumes less energy than the Tp-IPoWDM network, especially under a sparse network topology. For both kinds of networks, it is shown that network energy efficiency can be improved by over-provisioning wavelengths, which gives the network more path choices. [ABSTRACT FROM AUTHOR]

In this study, a portable electronic nose (E-nose) was self-developed to identify rice wines with different marked ages-all the operations of the E-nose were controlled by a special Smartphone Application. The sensor array of the E-nose was comprised of 12 MOS sensors and the obtained response values were transmitted to the Smartphone thorough a wireless communication module. Then, Aliyun worked as a cloud storage platform for the storage of responses and identification models. The measurement of the E-nose was composed of the taste information obtained phase (TIOP) and the aftertaste information obtained phase (AIOP). The area feature data obtained from the TIOP and the feature data obtained from the TIOP-AIOP were applied to identify rice wines by using pattern recognition methods. Principal component analysis (PCA), locally linear embedding (LLE) and linear discriminant analysis (LDA) were applied for the classification of those wine samples. LDA based on the area feature data obtained from the TIOP-AIOP proved a powerful tool and showed the best classification results. Partial least-squares regression (PLSR) and support vector machine (SVM) were applied for the predictions of marked ages and SVM (R2 = 0.9942) worked much better than PLSR. [ABSTRACT FROM AUTHOR]

Dense Heterogeneous Cellular Networks(HCNs) offer a promising approach to meet the target of 1000x increase in aggregate data rates in 5G wireless communication systems. However how to best utilize the available radio resources at densely deployed small cells remains an open problem as those small cells are typically unplanned. In this paper we focus on balancing loads across macro cells and small cells by offloading users to small cells, as well as dynamically switching off underutilized small cells. We propose a joint user association and base station(BS) sleep management(UA-BSM) scheme that proactively offloads users to a fraction of the densely deployed small cells. We propose a heuristic algorithm that iteratively solves the user association problem and puts BSs with low loads into sleep. An interference relation matrix(IRM) is constructed to help us identify the candidate BSs that can be put into sleep. User associations are then aggregated to selected small cells that remain active. Simulation results show that our proposed approach achieves load balancing across macro and small cells and reduces the number of active BSs. Numerical results show user signal to interference ratio(SINR) can be improved by small cell sleep control. [ABSTRACT FROM AUTHOR]

Zoomable video streaming refers to a new class of interactive video applications, where users can zoom into a video stream to view a selected region of interest in higher resolutions and pan around to move the region of interest. The zoom and pan effects are typically achieved by breaking the source video into a grid of independently decodable tiles. Streaming the tiles to a set of heterogeneous users using broadcast is challenging, as users have different link rates and different regions of interest at different resolution levels. In this article, we consider the following problem: Given the subset of tiles that each user requested, the link rate of each user, and the available time slots, at which resolution should each tile be sent, to maximize the overall video quality received by all users. We design an efficient algorithm to solve this problem and evaluate the solution on a testbed using 10 mobile devices. Our method is able to achieve up to 12dB improvements over other heuristic methods. [ABSTRACT FROM AUTHOR]

Composed of a single proton exchange membrane fuel cell (PEMFC), a sensor module, and a ZigBee wireless communication module, a fault diagnostic system is proposed in this work to monitor the operation of a fuel cell system. Accordingly, such quantities as cells output voltage, current, operating temperature, and pressures of gases supplied are monitored. Subsequently, an extension matter-element model is built according to malfunctions of the fuel cell system, which are further categorized into 7 types, each with 12 sorts of characteristics. An extension evaluation method is then directly applied to diagnose such fuel cell system. A human machine interface built under Lab VIEW 2009 is incorporated in such a way that a fault(s) can be detected and fixed in a timely manner such that the life cycle of such fuel cell system can be extended. [ABSTRACT FROM AUTHOR]

A multistage adaptive beamformer for wireless communications is proposed. The beamformer adopts a novel nested system architecture to reduce the system complexity and to achieve the system optimization which is carried out independently at each stage. It is shown that this method attains an improved performance in comparison to another competitive method. [ABSTRACT FROM AUTHOR]

Energy saving is a critical issue for typical wireless sensor networks (WSNs) and the energy consumption is a big challenge to the design of WSNs. In this paper, we investigate this problem by a cross-layer design approach to minimize energy consumption and maximize network lifetime (NL) for a multiple-source and single-sink (MSSS) WSN with energy constraints. The optimization problem for the MSSS WSNs can be formulated as a mixed integer convex optimization problem with adoption of time division multiple access (TDMA) at medium access control (MAC) layer and it becomes a convex problem by relaxing an integer constraint on time slots. First of all, we have employed the Karush-Kuhn-Tucker(KKT) optimality conditions to derive analytical expressions of the globally optimal NL for a linear SSSS topology. Then a decomposition and combination (D&C) approach has been proposed to obtain suboptimal solutions. As a result, an analytical expression of the suboptimal NL has been derived for WSNs with a linear MSSS topology. To validate the analysis, numerical results show that the upper-bounds of the NL obtained by our proposed optimization models are tight. Important insights into the NL and benefits of cross-layer design for WSN NLM are also summarized. [ABSTRACT FROM AUTHOR]