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    Raw Wind Data Preprocessing: A Data-Mining Approach

    Le Zheng ; Wei Hu ; Yong Min
    Sustainable Energy, IEEE Transactions on

    Volume: 6 , Issue: 1
    DOI: 10.1109/TSTE.2014.2355837
    Publication Year: 2015 , Page(s): 11 - 19

    IEEE Journals & Magazines

    Wind energy integration research generally relies on complex sensors located at remote sites. The procedure for generating high-level synthetic information from databases containing large amounts of low-level data must therefore account for possible sensor failures and imperfect input data. The data input is highly sensitive to data quality. To address this problem, this paper presents an empirical methodology that can efficiently preprocess and filter the raw wind data using only aggregated active power output and the corresponding wind speed values at the wind farm. First, raw wind data properties are analyzed, and all the data are divided into six categories according to their attribute magnitudes from a statistical perspective. Next, the weighted distance, a novel concept of the degree of similarity between the individual objects in the wind database and the local outlier factor (LOF) algorithm, is incorporated to compute the outlier factor of every individual object, and this outlier factor is then used to assess which category an object belongs to. Finally, the methodology was tested successfully on the data collected from a large wind farm in northwest China. View full abstract»

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    Cooperative Control of Distributed Energy Storage Systems in a Microgrid

    Yinliang Xu ; Wei Zhang ; Hug, G. ; Kar, S. ; Zhicheng Li
    Smart Grid, IEEE Transactions on

    Volume: 6 , Issue: 1
    DOI: 10.1109/TSG.2014.2354033
    Publication Year: 2015 , Page(s): 238 - 248

    IEEE Journals & Magazines

    Energy storage systems (ESSs) are often proposed to support the frequency control in microgrid systems. Due to the intermittency of the renewable generation and constantly changing load demand, the charging/discharging of various ESSs in an autonomous microgrid needs to be properly coordinated to ensure the supply-demand balance. Recent research has discovered that the charging/discharging efficiency of ESSs has remarkable dependence on the charging/discharging rate and state-of-charge of the ESS. This paper proposes a distributed cooperative control strategy for coordinating the ESSs to maintain the supply-demand balance and minimize the total power loss associated with charging/discharging inefficiency. The effectiveness of the proposed approach is validated by simulation results. View full abstract»

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    The Cost of Speed: Work Policies for Crashing and Overlapping in Product Development Projects

    Meier, C. ; Browning, T.R. ; Yassine, A.A. ; Walter, U.
    Engineering Management, IEEE Transactions on

    Volume: 62 , Issue: 2
    DOI: 10.1109/TEM.2015.2411514
    Publication Year: 2015 , Page(s): 237 - 255

    IEEE Journals & Magazines

    Project management theory provides insufficient insight on the effects of crashing and overlapping in product development (PD) projects. The scholarly literature largely assumes that networks of project activities are acyclical. PD projects are iterative, however, and the time-cost implications of managerial actions, such as activity crashing and overlapping, differ in this context. We build a rich model that accounts for activity overlapping, crashing, and iteration in the project's activity network. Using a bank of thousands of artificial but realistic test problems, we test the performance of several alternative work policies—managerial rules about when to start work and rework, and when to allow crashing and overlapping—and compare their time-cost implications. We find that the time-cost benefits of crashing and overlapping increase with increasing iteration. However, whereas crashing works well in combination with an aggressive work policy that does not seek to minimize iteration and rework, overlapping ironically works better with a work policy that defers rework. No single work policy dominates in all situations, although an aggressive policy that precipitates rework may often be worth its added cost. We distill our findings into a set of propositions that pave the way for further theory development in this area. Our results also illuminate useful heuristics for managers of PD projects. View full abstract»

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    Combining Newton interpolation and deep learning for image classification

    Yongfeng Zhang ; Changjing Shang
    Electronics Letters

    Volume: 51 , Issue: 1
    DOI: 10.1049/el.2014.3223
    Publication Year: 2015 , Page(s): 40 - 42

    IET Journals & Magazines

    A novel approach for image classification, by integrating deep learning and feature interpolation, supported with advanced learning classification techniques, is presented. The recently introduced deep spatiotemporal inference network (DeSTIN) is employed to carry out limited original feature extraction. Newton interpolation is then used to artificially increase the dimensionality of the extracted feature sets for accurate classification, without incurring heavy computational cost. Support vector machines are utilised for image classification. The proposed approach is tested against the popular MNIST dataset of handwritten digits, demonstrating the potential of the approach. View full abstract»

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    Optimal Resource Allocation and Spectral-Energy Efficiency Trade-off in Hybrid Cognitive Relay Channels

    Hong, X. ; Zheng, C. ; Wang, J. ; Shi, J. ; Wang, Cheng-Xiang
    Wireless Communications, IEEE Transactions on

    Volume: PP , Issue: 99
    DOI: 10.1109/TWC.2015.2417550
    Publication Year: 2015 , Page(s): 1

    IEEE Early Access Articles

    Recent literature has suggested the benefits of integrating licensed radio and cognitive radio into a hybrid cooperative communication system. The fundamental properties of such hybrid systems, however, have not been thoroughly investigated. This paper studies the hybrid cognitive Gaussian relay channel (HCGRC), which uses licensed radio resource (RR) and cognitive/unlicensed RR for forward and relay transmissions, respectively. HCGRC fundamentally differs from conventional relay channels in that the licensed and cognitive RRs are not subject to a total resource constraint and that the cognitive RR is opportunistic in nature.With respect to both the upper and lower bounds, we derive the optimal power-bandwidth allocation strategies for the cognitive relay to maximize the capacity, spectrum efficiency (SE), and energy efficiency (EE). The Pareto-optimal EE-SE trade-off curve is also derived analytically. Our study leads to two key observations. First, the multi-objective powerbandwidth allocation problem is characterized by five regions, each representing a unique performance trade-off. Second, the reliability of cognitive RR has no impact on the EE-SE trade-off given unlimited bandwidth and power. View full abstract»

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    Commutation point estimation for sensorless brushless DC motor using back-electromagnetic force change rate by least-square method

    Jung-Hwan Kim ; Sun-Kyu Kim ; Joonhong Lim
    Electronics Letters

    Volume: 51 , Issue: 1
    DOI: 10.1049/el.2014.2588
    Publication Year: 2015 , Page(s): 31 - 33

    IET Journals & Magazines

    A new commutation point (CP) estimation method for a high-speed sensorless brushless motor using the back-electromagnetic force (EMF) change rate is proposed. Typical CP estimation methods may not work correctly either at high speed when the number of sampled data is not enough or at low speed when the back-EMF voltage is weak. In the proposed method, the back-EMF voltages are measured using an analogue-to-digital converter. The back-EMF voltage change rate is calculated from the measured values and utilised to estimate the CP by employing the least-square method. The experimental results show that the proposed estimation method works correctly over a wide speed-range operation. View full abstract»

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    Joint Access Control and Resource Allocation for Concurrent and Massive Access of M2M Devices

    Oh, C. ; Hwang, D. ; Lee, T.
    Wireless Communications, IEEE Transactions on

    Volume: PP , Issue: 99
    DOI: 10.1109/TWC.2015.2417873
    Publication Year: 2015 , Page(s): 1

    IEEE Early Access Articles

    Machine-to-machine (M2M) communications, also known as machine-type communications (MTC) in 3GPP LTE systems, provide autonomous connectivity between machines without human intervention to create new service, e.g., the Internet of Things and the smart grid. M2M communications normally involve a large number of MTC devices (MTCDs) to support a variety of sensor applications. Consequently, concurrent and massive access attempts of MTCDs to radio access networks (RANs) may cause intolerable delay, packet loss, and even service unavailability. In this paper, we propose a joint optimal physical random access channel (PRACH) resource allocation and access control mechanism to address the performance degradation caused by concurrent and massive access attempts of MTCDs in LTE systems. We define the notion of random access efficiency and formulate an optimization problem for maximization of the random access efficiency with random access delay constraint. We also propose a dynamic resource allocation and access control algorithm based on estimation of the number of MTCDs for a system with dynamically varying numbers of massive MTCDs. Then, an analytical model is provided using a discrete-time Markov chain for the proposed mechanism. The effectiveness of the proposed algorithm is demonstrated via analysis and simulations. The proposed algorithm was able to maintain the optimal random access efficiency while satisfying the average random access delay requirement of MTCDs in order to handle massive and dynamic MTCDs per cell. View full abstract»

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    Auto-adjusted shape prior-based interactive segmentation via point set registration

    Liman Liu ; Kunqian Li ; Wenbing Tao ; Haihua Liu
    Electronics Letters

    Volume: 51 , Issue: 1
    DOI: 10.1049/el.2014.3160
    Publication Year: 2015 , Page(s): 38 - 40

    IET Journals & Magazines

    A novel object specified segmentation approach based on the auto-adjusted shape prior by utilising the point set registration method is presented. Three steps are included in the proposed method: (i) initial segmentation, (ii) automatic shape prior adjustment by point set registration and (iii) object segmentation constrained by the adjusted shape prior. To repair the shape difference between the local targets and the given shape model, such as location, scale, rotation and local shape details, an excellent point set registration approach named coherent point drift (CPD) is adopted. The adjusted shape constraints under the coherent moving constraint implied in CPD give reliable boundary predictions. Experimental results on the ETHZ shape dataset have demonstrated the outstanding performance of the proposed method. View full abstract»

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    Scaling Multi-Core Network Processors Without the Reordering Bottleneck

    Shpiner, A. ; Keslassy, I. ; Cohen, R.
    Parallel and Distributed Systems, IEEE Transactions on

    Volume: PP , Issue: 99
    DOI: 10.1109/TPDS.2015.2421449
    Publication Year: 2015 , Page(s): 1

    IEEE Early Access Articles

    Today, designers of network processors strive to keep the packet reception and transmission orders identical, and therefore avoid any possible out-of-order transmission. However, the development of new features in advanced network processors has resulted in increasingly parallel architectures and increasingly heterogeneous packet processing times, leading to large reordering delays. In this paper, we introduce novel scalable scheduling algorithms for preserving flow order in parallel multi-core network processors. We show how these algorithms can reduce reordering delay while adapting to any load-balancing algorithm and keeping a low implementation complexity overhead. To do so, we use the observation that all packets in a given flow have similar processing requirements and can be described with a constant number of logical processing phases. We further define three possible knowledge frameworks of the time when a network processor learns about these logical phases, and deduce appropriate algorithms for each of these frameworks. Finally, we model our proposed algorithms and simulate them under both synthetic traffic and real-life traces, and show that they significantly outperform past approaches. View full abstract»

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    Perception-Based Personalization of Hearing Aids Using Gaussian Processes and Active Learning

    Nielsen, J.B.B. ; Nielsen, J. ; Larsen, J.
    Audio, Speech, and Language Processing, IEEE/ACM Transactions on

    Volume: 23 , Issue: 1
    DOI: 10.1109/TASLP.2014.2377581
    Publication Year: 2015 , Page(s): 162 - 173

    IEEE Journals & Magazines

    Personalization of multi-parameter hearing aids involves an initial fitting followed by a manual knowledge-based trial-and-error fine-tuning from ambiguous verbal user feedback. The result is an often suboptimal HA setting whereby the full potential of modern hearing aids is not utilized. This article proposes an interactive hearing-aid personalization system that obtains an optimal individual setting of the hearing aids from direct perceptual user feedback. Results obtained with ten hearing-impaired subjects show that ten to twenty pairwise user assessments between different settings-equivalent to 5-10 min-is sufficient for personalization of up to four hearing-aid parameters. A setting obtained by the system was significantly preferred by the subject over the initial fitting, and the obtained setting could be reproduced with reasonable precision. The system may have potential for clinical usage to assist both the hearing-care professional and the user. View full abstract»

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    Downlink Power Control in Self-Organizing Dense Small Cells Underlaying Macrocells: A Mean Field Game

    Semasinghe, P. ; Hossain, E.
    Mobile Computing, IEEE Transactions on

    Volume: PP , Issue: 99
    DOI: 10.1109/TMC.2015.2417880
    Publication Year: 2015 , Page(s): 1

    IEEE Early Access Articles

    A novel distributed power control paradigm is proposed for dense small cell networks co-existing with a traditional macrocellular network. The power control problem is first modeled as a stochastic game and the existence of the Nash Equilibrium is proven. Then we extend the formulated stochastic game to a mean field game (MFG) considering a highly dense network. An MFG is a special type of differential game which is ideal for modeling the interactions among a large number of entities. We analyze the performance of two different cost functions for the mean field game formulation. Both of these cost functions are designed using stochastic geometry analysis in such a way that the cost functions are valid for the MFG setting. A finite difference algorithm is then developed based on the Lax-Friedrichs scheme and Lagrange relaxation to solve the corresponding MFG. Each small cell base station can independently execute the proposed algorithm offline, i.e., prior to data transmission. The output of the algorithm shows how each small cell base station should adjust its transmit power in order to minimize the cost over a predefined period of time. Moreover, sufficient conditions for the uniqueness of the mean field equilibrium for a generic cost function are also given. The effectiveness of the proposed algorithm is demonstrated via numerical results. View full abstract»

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    Statistical analysis on the additional torque ripple caused by magnet tolerances in surface-mounted permanent magnet synchronous motors

    Hong Guo ; Zhiyong Wu ; Hao Qian ; Kaiping Yu ; Jinquan Xu
    Electric Power Applications, IET

    Volume: 9 , Issue: 3
    DOI: 10.1049/iet-epa.2014.0170
    Publication Year: 2015 , Page(s): 183 - 192

    IET Journals & Magazines

    In surface-mounted permanent magnet synchronous motors, two types of magnet tolerances: magnet misplacements and magnetisation errors, cause additional torque ripple harmonic components and lead to the dispersion of torque ripple in mass production of motors. This paper analyses the effects of the magnet tolerances on torque ripple and estimates the statistical values of the magnitudes in each harmonic of additional torque ripple resulting from Gaussian distributed magnet tolerances. By using synthesis method, the analytical expressions are derived which reveal the relationship between the magnet tolerances and the magnitudes of the additional torque ripple harmonics. Based on the analytical expressions, the statistical values of each harmonic's magnitude are predicted. The expected values and standard deviations of the harmonics' magnitudes are calculated and verified by both the simulations and experiments. View full abstract»

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    Mathematical modelling of forced circulation evaporator pilot plant

    Sukede, Abhijeet Kishorsingh
    Pervasive Computing (ICPC), 2015 International Conference on

    DOI: 10.1109/PERVASIVE.2015.7087006
    Publication Year: 2015 , Page(s): 1 - 4

    IEEE Conference Publications

    Process control, design and optimization are the key features of any industry and continue to improve because of highly increasing global competition. Pilot plant plays a vital role in analyzing the effect of variables at various process conditions and for optimal study of the process. This paper presents nonlinear mathematical model of a laboratory based forced circulation evaporator pilot plant. The modeling is done considering mass balance and energy balance equations. The open loop validation of entire model is done in MATLAB. Various key parameters like level, pressure and composition of material are considered and monitored while modeling. The obtained model was then used as basis for the implementing advanced control strategies, physical study of the pilot plant, controlling plant dynamics etc. View full abstract»

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    Hybrid Opportunistic Relaying and Jamming With Power Allocation for Secure Cooperative Networks

    Chao Wang ; Hui-Ming Wang ; Xiang-Gen Xia
    Wireless Communications, IEEE Transactions on

    Volume: 14 , Issue: 2
    DOI: 10.1109/TWC.2014.2354635
    Publication Year: 2015 , Page(s): 589 - 605
    Cited by:  Papers (1)

    IEEE Journals & Magazines

    This paper studies the cooperative transmission for securing a decode-and-forward (DF) two-hop network where multiple cooperative nodes coexist with a potential eavesdropper. Under the more practical assumption that only the channel distribution information (CDI) of the eavesdropper is known, we propose an opportunistic relaying with artificial jamming secrecy scheme, where a “best” cooperative node is chosen among a collection of N possible candidates to forward the confidential signal and the others send jamming signals to confuse the eavesdroppers. We first investigate the ergodic secrecy rate (ESR) maximization problem by optimizing the power allocation between the confidential signal and jamming signals. In particular, we exploit the limiting distribution technique of extreme order statistics to build an asymptotic closed-form expression of the achievable ESR and the power allocation is optimized to maximize the ESR lower bound. Although the optimization problems are non-convex, we propose a sequential parametric convex approximation (SPCA) algorithm to locate the Karush-Kuhn-Tucker (KKT) solutions. Furthermore, taking the time variance of the legitimate links' CSIs into consideration, we address the impacts of the outdated CSIs to the proposed secrecy scheme, and derive an asymptotic ESR. Finally, we generalize the analysis to the scenario with multiple eavesdroppers, and give the asymptotic analytical results of the achievable ESR. Simulation results confirm our analytical results. View full abstract»

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    Transforming Vertical Web Applications into Elastic Cloud Applications

    Tankovic, Nikola ; Grbac, Tihana Galinac ; Truong, Hong-Linh ; Dustdar, Schahram
    Cloud Engineering (IC2E), 2015 IEEE International Conference on

    DOI: 10.1109/IC2E.2015.15
    Publication Year: 2015 , Page(s): 135 - 144

    IEEE Conference Publications

    There exists a huge amount of vertical applications that are developed for isolated computing environments. Due to increasing demand for additional resources there is a clear need to adapt these applications to the distributed environments. However, this is not an easy task and numerous variants are possible. Moreover, in this transition a new quality requirements become important, such as application elasticity. Application elasticity has to be built into a software system to enable smooth cost optimization at the run-time. In this paper, we provide a framework for evaluating different transformation variants of vertical Java EE multi-tiered applications into elastic cloud applications. With support of this framework the software developer is guided how to transform its application achieving optimal elasticity strategy. The framework is evaluated on slicing and evaluating elasticity of existing SaaS multi-tiered Java application used in Croatian market. View full abstract»

  • Freely Available from IEEE

    IEEE Journal of Selected Topics in Signal Processing information for authors


    Selected Topics in Signal Processing, IEEE Journal of

    Volume: 9 , Issue: 2
    DOI: 10.1109/JSTSP.2015.2402371
    Publication Year: 2015 , Page(s): 374 - 375

    IEEE Journals & Magazines

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    Bit loading profiles for high-speed data in DOCSIS 3.1

    Mehmood, H. ; Rahman, S. ; Cioffi, J.
    Communications Magazine, IEEE

    Volume: 53 , Issue: 3
    DOI: 10.1109/MCOM.2015.7060491
    Publication Year: 2015 , Page(s): 114 - 120

    IEEE Journals & Magazines

    DOCSIS 3.1 aims to provide higher speeds over coaxial cable systems than existing cable standards. It uses multicarrier modulation and allows different bit loading per subcarrier. As the subcarrier SNRs for different cable modems are different, DOCSIS 3.1 allows adaptation of data transmission to cable modems by permitting multiple profiles. These provisions enable intelligent bit loading practices in DOCSIS 3.1. This article addresses the problem of assigning profiles to cable modems based on similarity in subcarrier SNRs. Simple algorithms are proposed to group together cable modems suitable for the same modulation profile. It is shown that as the number of allowed profiles increases, higher average data rate can be achieved. View full abstract»

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    Coordination of Marine Robots Under Tracking Errors and Communication Constraints

    Ferreira, B.M. ; Matos, A.C. ; Cruz, N.A. ; Moreira, A.P.
    Oceanic Engineering, IEEE Journal of

    Volume: PP , Issue: 99
    DOI: 10.1109/JOE.2015.2412992
    Publication Year: 2015 , Page(s): 1

    IEEE Early Access Articles

    This paper presents the development and the experimental validation of a centralized coordination control scheme that is robust to communication constraints and individual tracking errors for a team of possibly heterogeneous marine vehicles. By assuming the existence of a lower level target tracking control layer, a centralized potential-field-based coordination scheme is proposed to drive a team of robots along a path that does not necessarily need to be defined a priori. Furthermore, the formation is allowed to hold its position (the vehicles hold their positions with regard to a static virtual leader), which is particularly appreciated in several marine applications. As it is important to guarantee stability and mission completion in adverse environments with limited communications, the centralized control scheme for coordination is constructed in a way that makes it robust to tracking errors and intermittent communication links. The study and developments presented in this paper are complemented with field experiments in which vehicles have coordinated their operation to keep in formation over a dynamic path and static points. This work considers two types of communication technologies. Firstly, standard high rate radio communications are used to drive the formation and, secondly, acoustic communications are employed to assess the performance and the robustness of the proposed approach to degraded and highly variable conditions. View full abstract»

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    Predictive Coding of Bit Loading for Time-Correlated MIMO Channels with a Decision Feedback Receiver

    Li, Chien-Chang ; Lin, Yuan-Pei
    Signal Processing, IEEE Transactions on

    Volume: PP , Issue: 99
    DOI: 10.1109/TSP.2015.2421471
    Publication Year: 2015 , Page(s): 1

    IEEE Early Access Articles

    In this paper, we consider variable-rate transmission over a slowly varying multiple input multiple output (MIMO) channel with a decision feedback receiver. The transmission rate is adapted to the channel by dynamically assigning bits to the subchannels of the MIMO system. Predictive quantization is used for the feedback of bit loading to take advantage of the time correlation inherited from the temporally correlated channel. Due to the use of decision feedback at the receiver, the bit loading is related to the Cholesky decomposition of the channel Gram matrix. Assuming the channel is modeled by a slowly varying Gauss-Markov process, we show that the nested submatrices generated during the process of Cholesky decomposition can be updated as time evolves. Based on the update, we derive the optimal predictor of the next bit loading for predictive quantization. Furthermore, we derive the statistics of the prediction error, which are then exploited to design the quantizer to achieve a smaller quantization error. Simulations are given to demonstrate that the proposed predictive quantization gives a good approximation of the desired transmission rate with a low feedback rate. View full abstract»

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    Unsegmented Dialogue Act Annotation and Decoding With N-Gram Transducers

    Martinez-Hinarejos, C.-D. ; Benedi, J.-M. ; Tamarit, V.
    Audio, Speech, and Language Processing, IEEE/ACM Transactions on

    Volume: 23 , Issue: 1
    DOI: 10.1109/TASLP.2014.2377595
    Publication Year: 2015 , Page(s): 198 - 211

    IEEE Journals & Magazines

    Most studies on dialogue corpora, as well as most dialogue systems, employ dialogue acts as the basic units for interpreting discourse structure, user input and system actions. The definition of the discourse structure and the dialogue strategy consequently require the tagging of dialogue corpora in terms of dialogue acts. The tagging problem presents two basic variants: a batch variant (annotation of whole dialogues, in order to define dialogue strategy or study discourse structure) and an online variant (decoding of the dialogue act sequence of a given turn, in order to interpret user intentions). In the two variants is unusual having the segmentation of each turn into the dialogue meaningful units (segments) to which a dialogue act is assigned. In this paper we present the use of the N-Gram Transducer technique for tagging dialogues, without needing to provide a prior segmentation, in these two different variants (dialogue annotation and turn decoding). Experiments were performed in two corpora of different nature and results show that N-Gram Transducer models are suitable for these tasks and provide good performance. View full abstract»

  • Freely Available from IEEE

    [Front Cover]


    Software Analytics (SWAN), 2015 IEEE 1st International Workshop on

    DOI: 10.1109/SWAN.2015.7072655
    Publication Year: 2015 , Page(s): c1

    IEEE Conference Publications

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    REFLEX: An Adapted Production Simulation Methodology for Flexible Capacity Planning

    Hargreaves, J. ; Hart, E.K. ; Jones, R. ; Olson, A.
    Power Systems, IEEE Transactions on

    Volume: 30 , Issue: 3
    DOI: 10.1109/TPWRS.2014.2351235
    Publication Year: 2015 , Page(s): 1306 - 1315

    IEEE Journals & Magazines

    As intermittent energy resources become more significant in power production, traditional capacity planning may be insufficient to ensure reliable system operation. A system planner must ensure that flexibility solutions are available to respond to large and uncertain ramping events. These solutions may be operational, such as improved unit commitment and dispatch, curtailment of renewables, or demand response; procurement based, such as new fast ramping resources or batteries; or involve market reform. This paper outlines a new methodology for modeling the economic tradeoffs in implementing flexibility solutions for integrating renewables. The proposed model includes both a stochastic treatment of system states to account for a wide range of operating conditions and an adapted production simulation methodology that weighs the cost of reliability and subhourly flexibility violations against the cost of the operational flexibility solutions available to mitigate them. The model's functionality is demonstrated with a case study of California at a 50% RPS in 2030. The model tests the value of 1088 MW of generic flexible units, relative to the same capacity of must-run resources, finding an expected annual value of {$}347\pm 42 million/yr. Potential applications of the model for resource planning and procurement are also discussed. View full abstract»

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    Deep Representations for Iris, Face, and Fingerprint Spoofing Detection

    Menotti, D. ; Chiachia, G. ; Pinto, A. ; Robson Schwartz, W. ; Pedrini, H. ; Xavier Falcao, A. ; Rocha, A.
    Information Forensics and Security, IEEE Transactions on

    Volume: 10 , Issue: 4
    DOI: 10.1109/TIFS.2015.2398817
    Publication Year: 2015 , Page(s): 864 - 879

    IEEE Journals & Magazines

    Biometrics systems have significantly improved person identification and authentication, playing an important role in personal, national, and global security. However, these systems might be deceived (or spoofed) and, despite the recent advances in spoofing detection, current solutions often rely on domain knowledge, specific biometric reading systems, and attack types. We assume a very limited knowledge about biometric spoofing at the sensor to derive outstanding spoofing detection systems for iris, face, and fingerprint modalities based on two deep learning approaches. The first approach consists of learning suitable convolutional network architectures for each domain, whereas the second approach focuses on learning the weights of the network via back propagation. We consider nine biometric spoofing benchmarks - each one containing real and fake samples of a given biometric modality and attack type - and learn deep representations for each benchmark by combining and contrasting the two learning approaches. This strategy not only provides better comprehension of how these approaches interplay, but also creates systems that exceed the best known results in eight out of the nine benchmarks. The results strongly indicate that spoofing detection systems based on convolutional networks can be robust to attacks already known and possibly adapted, with little effort, to image-based attacks that are yet to come. View full abstract»

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    Assessing Performance Gains Through Global Resource Control of Heterogeneous Wireless Networks

    Amin, R. ; Martin, J.
    Mobile Computing, IEEE Transactions on

    Volume: PP , Issue: 99
    DOI: 10.1109/TMC.2015.2417871
    Publication Year: 2015 , Page(s): 1

    IEEE Early Access Articles

    We study the resource allocation and management issues related to heterogeneous wireless systems made up of several Radio Access Technologies (RATs) that collectively provide a unified wireless network to a diverse set of users through co-ordination managed by a centralized Global Resource Controller (GRC). We assume that the user devices are multimodal, which makes it possible for each device to use any available Access Point (AP)/Base Station (BS) of a RAT at any given time. Through detailed protocol level simulations performed in ns-2, we show an increase in spectral efficiency of up to 99% and an increase in short-term fairness of up to 28.5% for two greedy sort-based user device-to-AP/BS association algorithms implemented at the GRC compared to a distributed solution used in practice today where each user makes his/her own association decision. While the increase in overhead due to re-associations for a centralized solution grows only slightly (by up to 4.1%) compared to a distributed solution, we find the performance increase in spectral efficiency and short-term fairness attributes come at the cost of an order of magnitude increase (of up to 794%) in energy consumption. View full abstract»

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    Model of aeronautical ground lighting system transformers

    Lombarte, D.V. ; Monjo, L. ; Sainz, L. ; Pedra, J.
    Electric Power Applications, IET

    Volume: 9 , Issue: 3
    DOI: 10.1049/iet-epa.2014.0282
    Publication Year: 2015 , Page(s): 239 - 247

    IET Journals & Magazines

    Aeronautical ground lighting (AGL) systems provide visual reference to aircraft during airport operations. In AGL systems, constant current regulators feed a series circuit composed of luminaires supplied through transformers. Component modelling is necessary to simulate AGL systems, and thus characterise and predict their behaviour. This paper presents an AGL transformer model including transformer core saturation. Moreover, a procedure to estimate transformer model parameters is proposed. Both the model and the estimation method are validated with extensive measurements on more than 20 AGL transformers of different power ratings and trade names. View full abstract»

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