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Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols i...
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Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; 2) longitudinal studies, where temporal structural or anatomical changes are investigated; and 3) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner.
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Although the North American power grid has been recognized as the most important engineering achievement of the 20th century, the modern power grid faces major challenges [87]. Increasingly complex interconnections even at the con...
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Although the North American power grid has been recognized as the most important engineering achievement of the 20th century, the modern power grid faces major challenges [87]. Increasingly complex interconnections even at the continent size render prevention of the rare yet catastrophic cascade failures a strenuous concern. Environmental incentives require carefully revisiting how electrical power is generated, transmitted, and consumed, with particular emphasis on the integration of renewable energy resources. Pervasive use of digital technology in grid operation demands resiliency against physical and cyberattacks on the power infrastructure. Enhancing grid efficiency without compromising stability and quality in the face of deregulation is imperative. Soliciting consumer participation and exploring new business opportunities facilitated by the intelligent grid infrastructure hold a great economic potential.
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Lattice codes are known to achieve capacity in the Gaussian point-to-point channel, achieving the same rates as i.i.d. random Gaussian codebooks. Lattice codes are also known to outperform random codes for certain channel models t...
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Lattice codes are known to achieve capacity in the Gaussian point-to-point channel, achieving the same rates as i.i.d. random Gaussian codebooks. Lattice codes are also known to outperform random codes for certain channel models that are able to exploit their linearity. In this paper, we show that lattice codes may be used to achieve the same performance as known i.i.d. Gaussian random coding techniques for the Gaussian relay channel, and show several examples of how this may be combined with the linearity of lattices codes in multisource relay networks. In particular, we present a nested lattice list decoding technique in which lattice codes are shown to achieve the decode-and-forward (DF) rate of single source, single destination Gaussian relay channels with one or more relays. We next present two examples of how this DF scheme may be combined with the linearity of lattice codes to achieve new rate regions which for some channel conditions outperform analogous known Gaussian random coding techniques in multisource relay channels. That is, we derive a new achievable rate region for the two-way relay channel with direct links and compare it to existing schemes, and derive a new achievable rate region for the multiple access relay channel. We furthermore present a lattice compress-and-forward (CF) scheme for the Gaussian relay channel which exploits a lattice Wyner–Ziv binning scheme and achieves the same rate as the Cover–El Gamal CF rate evaluated for Gaussian random codes. These results suggest that structured/lattice codes may be used to mimic, and sometimes outperform, random Gaussian codes in general Gaussian networks.
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We extend quantum rate-distortion theory by considering auxiliary resources that might be available to a sender and receiver performing lossy quantum data compression. The first setting we consider is that of quantum rate-distorti...
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We extend quantum rate-distortion theory by considering auxiliary resources that might be available to a sender and receiver performing lossy quantum data compression. The first setting we consider is that of quantum rate-distortion coding with the help of a classical side channel. Our result here is that the regularized entanglement of formation characterizes the quantum rate-distortion function, extending earlier work of Devetak and Berger. We also combine this bound with the entanglement-assisted bound from our prior work to obtain the best known bounds on the quantum rate-distortion function for an isotropic qubit source. The second setting we consider is that of quantum rate-distortion coding with quantum side information (QSI) available to the receiver. In order to prove results in this setting, we first state and prove a quantum reverse Shannon theorem with QSI (for tensor-power states), which extends the known tensor-power quantum reverse Shannon theorem. The achievability part of this theorem relies on the quantum state redistribution protocol, while the converse relies on the fact that the protocol can cause only a negligible disturbance to the joint state of the reference and the receiver's QSI. This quantum reverse Shannon theorem with QSI naturally leads to quantum rate-distortion theorems with QSI, with or without entanglement assistance.
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This paper discusses a novel method for the analysis of MOSFET commutations and the investigation of related losses and spike current issues in the switching power converter (SPC) design. The synchronous rectification switching ce...
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This paper discusses a novel method for the analysis of MOSFET commutations and the investigation of related losses and spike current issues in the switching power converter (SPC) design. The synchronous rectification switching cell (SRSC) configuration is considered for the investigation, which is used in the high-frequency high-efficiency (H$^{2}$EF) SPC design. The proposed method is aimed at providing an effective tool for quick feasibility investigations and comparative evaluations among design solutions using different MOSFET combinations for the design of H$^{2}$EF SPCs. The method allows us to use nonlinear models of interelectrode MOSFET capacitances and adopts a novel numerical technique specifically developed to solve the SRSC model ensuring robust and fast simulations. Capacitive pulsating currents circulating through the MOSFETs and the SPC during commutations can be analyzed in detail by using the proposed method. Different examples are discussed to show how MOSFETs characteristics and operating conditions may affect switching losses, because of the pulsing currents circulation through the SPC.
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Explicit nonasymptotic upper bounds on the sizes of multiple-deletion correcting codes are presented. In particular, the largest single-deletion correcting code for $q$-ary alphabet and string length $n$ is shown to be of size at...
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Explicit nonasymptotic upper bounds on the sizes of multiple-deletion correcting codes are presented. In particular, the largest single-deletion correcting code for $q$-ary alphabet and string length $n$ is shown to be of size at most $ {{ q^{n}-q}over { (q-1)(n-1)}}$. An improved bound on the asymptotic rate function is obtained as a corollary. Upper bounds are also derived on sizes of codes for a constrained source that does not necessarily comprise of all strings of a particular length, and this idea is demonstrated by application to sets of run-length limited strings. The problem of finding the largest deletion correcting code is modeled as a matching problem on a hypergraph. This problem is formulated as an integer linear program. The upper bound is obtained by the construction of a feasible point for the dual of the linear programming relaxation of this integer linear program. The nonasymptotic bounds derived imply the known asymptotic bounds of Levenshtein and Tenengolts and improve on known nonasymptotic bounds. Numerical results support the conjecture that in the binary case, the Varshamov–Tenengolts codes are the largest single-deletion correcting codes.
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What are the aesthetics of platform games and what makes a platform level engaging, challenging, and/or frustrating? We attempt to answer such questions through mining a large set of crowdsourced gameplay data of a clone of the cl...
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What are the aesthetics of platform games and what makes a platform level engaging, challenging, and/or frustrating? We attempt to answer such questions through mining a large set of crowdsourced gameplay data of a clone of the classic platform game Super Mario Bros (SMB). The data consist of 40 short game levels that differ along six key level design parameters. Collectively, these levels are played 1560 times over the Internet, and the perceived experience is annotated by experiment participants via self-reported ranking (pairwise preferences). Given the wealth of this crowdsourced data, as all details about players' in-game behavior are logged, the problem becomes one of extracting meaningful numerical features at the appropriate level of abstraction for the construction of generic computational models of player experience and, thereby, game aesthetics. We explore dissimilar types of features, including direct measurements of event and item frequencies, and features constructed through frequent sequence mining, and go through an in-depth analysis of the interrelationship between level content, players' behavioral patterns, and reported experience. Furthermore, the fusion of the extracted features allows us to predict reported player experience with a high accuracy, even from short game segments. In addition to advancing our insight on the factors that contribute to platform game aesthetics, the results are useful for the personalization of game experience via automatic game adaptation.
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The use of incoherent multilevel modulation formats with high spectral efficiency (more than two bits per symbol) has been proposed in order to enable the next generation of very high-speed Time-Division Multiplexing Passive Optic...
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The use of incoherent multilevel modulation formats with high spectral efficiency (more than two bits per symbol) has been proposed in order to enable the next generation of very high-speed Time-Division Multiplexing Passive Optical Networks (TDM-PONs). Incoherent multilevel modulation is attractive for access applications since multilevel formats allow the scaling of the bit rate with electronic and photonic components operating at a fraction of the bit rate. On the other hand, incoherent detection reduces the requirement for complicated Digital Signal Processing (DSP) and crucially an additional local oscillator, compared to coherent receivers. The modulation formats examined are Differential 8 Phase-Shift Keying (D8PSK) and three versions of incoherent 16 Quadrature Amplitude Modulation (QAM), specifically Star 16QAM, coded square 16QAM and 16QAM with pre-integration. Generation and detection of these formats is discussed, as well as the implementation challenges associated with such advanced modulation formats. The performance of these modulation formats was evaluated through extensive simulation and experimental work. Results indicate that incoherent modulation can fulfill important requirements of networks operators, namely increased bit rate and increased splitting ratio, and provide a cost-effective solution for Next-Generation Optical Access Networks.
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This paper analyzes the dynamics of an offshore boom crane and proposes a high-performance nonlinear controller to drive the system states to track some constructed trajectories. Specifically, by employing Lagrange's method in an ...
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This paper analyzes the dynamics of an offshore boom crane and proposes a high-performance nonlinear controller to drive the system states to track some constructed trajectories. Specifically, by employing Lagrange's method in an attached frame, a dynamic model is obtained for the offshore crane system consisting of the boom and a payload, with specific emphasis on the effect of the vessel's motion on the payload swing. Based on the model, a novel nonlinear control law is designed for the underactuated boom crane, which makes the system states track some planned trajectories successfully, even in the presence of persistent disturbance in harsh sea conditions. The stability of the designed closed-loop system is proven by Lyapunov techniques. Simulation and experimental results are included to demonstrate that the proposed control method significantly reduces the impact of the disturbance in harsh sea conditions.
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Cooperative spectrum sensing (CSS) is a promising technique in cognitive radio networks (CRNs) that utilises multiuser diversity to mitigate channel instability and noise uncertainty. In this study, the relationship between 'coope...
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Cooperative spectrum sensing (CSS) is a promising technique in cognitive radio networks (CRNs) that utilises multiuser diversity to mitigate channel instability and noise uncertainty. In this study, the relationship between 'cooperation mechanisms' and 'spatial-spectral diversity' over multiple channels jointly sensing is investigated in the presence of an imperfect reporting channel. The multiple channels are sensed at the receiver built on the filter bank-based multi-carrier system. The multi-channel CSS strategies are modelled by the introduced 'cooperative ratio' to balance the requirements on 'sensing accuracy', 'efficiency' and 'overhead', which is quantitatively characterised by the energy consumption. The target of CSS is to maximise the aggregate opportunistic throughput of secondary users (SUs) by jointly considering constraints on sensing overhead and the aggregate interference to primary users (PUs). The optimisation is divided into two sequential suboptimisation processes, 'multi-user diversity optimisation' and 'multi-channel diversity optimisation'. An approach is developed from generic algorithms to solve the two sub-problems. Numerical results show that the optimal CSS scheme is effective in improving channel utilisation for SUs with low interference to PUs. This study establishes a valuable cooperative model for the design of multi-channel spectrum sensing algorithms in CRNs.
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