201 resultados para Standard IEEE 1149.1.


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Medical image segmentation finds application in computer-aided diagnosis, computer-guided surgery, measuring tissue volumes, locating tumors, and pathologies. One approach to segmentation is to use active contours or snakes. Active contours start from an initialization (often manually specified) and are guided by image-dependent forces to the object boundary. Snakes may also be guided by gradient vector fields associated with an image. The first main result in this direction is that of Xu and Prince, who proposed the notion of gradient vector flow (GVF), which is computed iteratively. We propose a new formalism to compute the vector flow based on the notion of bilateral filtering of the gradient field associated with the edge map - we refer to it as the bilateral vector flow (BVF). The range kernel definition that we employ is different from the one employed in the standard Gaussian bilateral filter. The advantage of the BVF formalism is that smooth gradient vector flow fields with enhanced edge information can be computed noniteratively. The quality of image segmentation turned out to be on par with that obtained using the GVF and in some cases better than the GVF.

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In this paper, we propose a new sub-band approach to estimate the glottal activity. The method is based on the spectral harmonicity and the sub-band temporal properties of voiced speech. We propose a method to represent glottal excitation signal using sub-band temporal envelope. Instants of maximum glottal excitation or Glottal Closure Instants (GCI) are extracted from the estimated glottal excitation pattern and the result is compared with a standard GCI computation method, DYPSA [1]. The performance of the algorithm is also compared for the noisy signal and it is shown that the proposed method is less variant to GCI estimation under noisy conditions compared to DYPSA. The algorithm is evaluated on the CMU-ARCTIC database.

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In this paper, we analyze the coexistence of a primary and a secondary (cognitive) network when both networks use the IEEE 802.11 based distributed coordination function for medium access control. Specifically, we consider the problem of channel capture by a secondary network that uses spectrum sensing to determine the availability of the channel, and its impact on the primary throughput. We integrate the notion of transmission slots in Bianchi's Markov model with the physical time slots, to derive the transmission probability of the secondary network as a function of its scan duration. This is used to obtain analytical expressions for the throughput achievable by the primary and secondary networks. Our analysis considers both saturated and unsaturated networks. By performing a numerical search, the secondary network parameters are selected to maximize its throughput for a given level of protection of the primary network throughput. The theoretical expressions are validated using extensive simulations carried out in the Network Simulator 2. Our results provide critical insights into the performance and robustness of different schemes for medium access by the secondary network. In particular, we find that the channel captures by the secondary network does not significantly impact the primary throughput, and that simply increasing the secondary contention window size is only marginally inferior to silent-period based methods in terms of its throughput performance.

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We address the problem of sampling and reconstruction of two-dimensional (2-D) finite-rate-of-innovation (FRI) signals. We propose a three-channel sampling method for efficiently solving the problem. We consider the sampling of a stream of 2-D Dirac impulses and a sum of 2-D unit-step functions. We propose a 2-D causal exponential function as the sampling kernel. By causality in 2-D, we mean that the function has its support restricted to the first quadrant. The advantage of using a multichannel sampling method with causal exponential sampling kernel is that standard annihilating filter or root-finding algorithms are not required. Further, the proposed method has inexpensive hardware implementation and is numerically stable as the number of Dirac impulses increases.

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The optimal tradeoff between average service cost rate and average delay, is addressed for a M/M/1 queueing model with queue-length dependent service rates, chosen from a finite set. We provide an asymptotic characterization of the minimum average delay, when the average service cost rate is a small positive quantity V more than the minimum average service cost rate required for stability. We show that depending on the value of the arrival rate, the assumed service cost rate function, and the possible values of the service rates, the minimum average delay either a) increases only to a finite value, b) increases without bound as log(1/V), or c) increases without bound as 1/V, when V down arrow 0. We apply the analysis to a flow-level resource allocation model for a wireless downlink. We also investigate the asymptotic tradeoff for a sequence of policies which are obtained from an approximate fluid model for the M/M/1 queue.

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The polyamidoamine (PAMAM) dendrimer prevents HIV-1 entry into target cells in vitro. Its mechanism of action, however, remains unclear and precludes the design of potent dendrimers targeting HIV-1 entry. We employed steered molecular dynamics simulations to examine whether the HIV-1 gp120-CD4 complex is a target of PAMAM. Our simulations mimicked single molecule force spectroscopy studies of the unbinding of the gp120-CD4 complex under the influence of a controlled external force. We found that the complex dissociates via complex pathways and defies the standard classification of adhesion molecules as catch and slip bonds. When the force loading rate was large, the complex behaved as a slip bond, weakening gradually. When the loading rate was small, the complex initially strengthened, akin to a catch bond, but eventually dissociated over shorter separations than with large loading rates. PAMAM docked to gp120 and destabilized the gp120-CD4 complex. The rupture force of the complex was lowered by PAMAM. PAMAM disrupted salt bridges and hydrogen bonds across the gp120-CD4 interface and altered the hydration pattern of the hydrophobic cavity in the interface. In addition, intriguingly, PAMAM suppressed the distinction in the dissociation pathways of the complex between the small and large loading rate regimes. Taken together, our simulations reveal that PAMAM targets the gp120-CD4 complex at two levels: it weakens the complex and also alters its dissociation pathway, potentially inhibiting HIV-1 entry.

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Low power consumption per channel and data rate minimization are two key challenges which need to be addressed in future generations of neural recording systems (NRS). Power consumption can be reduced by avoiding unnecessary processing whereas data rate is greatly decreased by sending spike time-stamps along with spike features as opposed to raw digitized data. Dynamic range in NRS can vary with time due to change in electrode-neuron distance or background noise, which demands adaptability. An analog-to-digital converter (ADC) is one of the most important blocks in a NRS. This paper presents an 8-bit SAR ADC in 0.13-mu m CMOS technology along with input and reference buffer. A novel energy efficient digital-to-analog converter switching scheme is proposed, which consumes 37% less energy than the present state-of-the-art. The use of a ping-pong input sampling scheme is emphasized for multichannel input to alleviate the bandwidth requirement of the input buffer. To reduce the data rate, the A/D process is only enabled through the in-built background noise rejection logic to ensure that the noise is not processed. The ADC resolution can be adjusted from 8 to 1 bit in 1-bit step based on the input dynamic range. The ADC consumes 8.8 mu W from 1 V supply at 1 MS/s speed. It achieves effective number of bits of 7.7 bits and FoM of 42.3 fJ/conversion-step.

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The problem addressed in this paper is concerned with an important issue faced by any green aware global company to keep its emissions within a prescribed cap. The specific problem is to allocate carbon reductions to its different divisions and supply chain partners in achieving a required target of reductions in its carbon reduction program. The problem becomes a challenging one since the divisions and supply chain partners, being autonomous, may exhibit strategic behavior. We use a standard mechanism design approach to solve this problem. While designing a mechanism for the emission reduction allocation problem, the key properties that need to be satisfied are dominant strategy incentive compatibility (DSIC) (also called strategy-proofness), strict budget balance (SBB), and allocative efficiency (AE). Mechanism design theory has shown that it is not possible to achieve the above three properties simultaneously. In the literature, a mechanism that satisfies DSIC and AE has recently been proposed in this context, keeping the budget imbalance minimal. Motivated by the observation that SBB is an important requirement, in this paper, we propose a mechanism that satisfies DSIC and SBB with slight compromise in allocative efficiency. Our experimentation with a stylized case study shows that the proposed mechanism performs satisfactorily and provides an attractive alternative mechanism for carbon footprint reduction by global companies.

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Auction based mechanisms have become popular in industrial procurement settings. These mechanisms minimize the cost of procurement and at the same time achieve desirable properties such as truthful bidding by the suppliers. In this paper, we investigate the design of truthful procurement auctions taking into account an additional important issue namely carbon emissions. In particular, we focus on the following procurement problem: A buyer wishes to source multiple units of a homogeneous item from several competing suppliers who offer volume discount bids and who also provide emission curves that specify the cost of emissions as a function of volume of supply. We assume that emission curves are reported truthfully since that information is easily verifiable through standard sources. First we formulate the volume discount procurement auction problem with emission constraints under the assumption that the suppliers are honest (that is they report production costs truthfully). Next we describe a mechanism design formulation for green procurement with strategic suppliers. Our numerical experimentation shows that emission constraints can significantly alter sourcing decisions and affect the procurement costs dramatically. To the best of our knowledge, this is the first effort in explicitly taking into account carbon emissions in planning procurement auctions.

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The amplitude-modulation (AM) and phase-modulation (PM) of an amplitude-modulated frequency-modulated (AM-FM) signal are defined as the modulus and phase angle, respectively, of the analytic signal (AS). The FM is defined as the derivative of the PM. However, this standard definition results in a PM with jump discontinuities in cases when the AM index exceeds unity, resulting in an FM that contains impulses. We propose a new approach to define smooth AM, PM, and FM for the AS, where the PM is computed as the solution to an optimization problem based on a vector interpretation of the AS. Our approach is directly linked to the fractional Hilbert transform (FrHT) and leads to an eigenvalue problem. The resulting PM and AM are shown to be smooth, and in particular, the AM turns out to be bipolar. We show an equivalence of the eigenvalue formulation to the square of the AS, and arrive at a simple method to compute the smooth PM. Some examples on synthesized and real signals are provided to validate the theoretical calculations.

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Waters, in 2009, introduced an important technique, called dual system encryption, to construct identity-based encryption (IBE) and related schemes. The resulting IBE scheme was described in the setting of symmetric pairing. A key feature of the construction is the presence of random tags in the ciphertext and decryption key. Later work by Lewko and Waters removed the tags and proceeding through composite-order pairings led to a more efficient dual system IBE scheme using asymmetric pairings whose security is based on non-standard but static assumptions. In this work, we have systematically simplified Waters 2009 IBE scheme in the setting of asymmetric pairing. The simplifications retain tags used in the original description. This leads to several variants, the first one of which is based on standard assumptions and in comparison to Waters’ original scheme reduces ciphertexts and keys by two elements each. Going through several stages of simplifications, we finally obtain a simple scheme whose security can be based on two standard assumptions and a natural and minimal extension of the decision Diffie-Hellman problem for asymmetric pairing groups. The scheme itself is also minimal in the sense that apart from the tags, both encryption and key generation use exactly one randomiser each. This final scheme is more efficient than both the previous dual system IBE scheme in the asymmetric setting due to Lewko and Waters and the more recent dual system IBE scheme due to Lewko. We extend the IBE scheme to hierarchical IBE (HIBE) and broadcast encryption (BE) schemes. Both primitives are secure in their respective full models and have better efficiencies compared to previously known schemes offering the same level and type of security.

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Development of simple functionalization methods to attach biomolecules such as proteins and DNA on inexpensive substrates is important for widespread use of low cost, disposable biosensors. Here, we describe a method based on polyelectrolyte multilayers to attach single stranded DNA molecules to conventional glass slides as well as a completely non-standard substrate, namely flexible plastic transparency sheets. We then use the functionalized transparency sheets to specifically detect single stranded Hepatitis B DNA sequences from samples. We also demonstrate a blocking method for reducing non-specific binding of target DNA sequences using negatively charged polyelectrolyte molecules. The polyelectrolyte based functionalization method, which relies on surface charge as opposed to covalent surface linkages, could be an attractive platform to develop assays on inexpensive substrates for low cost biosensing.

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For compressive sensing, we endeavor to improve the atom selection strategy of the existing orthogonal matching pursuit (OMP) algorithm. To achieve a better estimate of the underlying support set progressively through iterations, we use a least squares solution based atom selection method. From a set of promising atoms, the choice of an atom is performed through a new method that uses orthogonal projection along-with a standard matched filter. Through experimental evaluations, the effect of projection based atom selection strategy is shown to provide a significant improvement for the support set recovery performance, in turn, the compressive sensing recovery.

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Terminal impact angle control is crucial for enhancement of warhead effectiveness. In the literature, this problem has been addressed in the context of targets with lower speeds than the interceptor. However, in the current defence scenario, targets of much higher speed than the interceptor is a reality. This paper presents a generic proportional navigation (PN) based guidance law, that uses the standard PN and novel Retro-PN guidance laws based on the initial engagement geometry and terminal engagement requirements, for three dimensional engagement scenario against higher speed nonmaneuvering targets to control terminal impact angle. Results are obtained on the set of achievable impact angles and conditions on the navigation constant to achieve them. Simulation results are given to support the theoretical findings.

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Using the recently developed model predictive static programming (MPSP), a suboptimal guidance logic is presented in this paper for formation flying of small satellites. Due to the inherent nature of the problem formulation, MPSP does not require the system dynamics to be linearized. The proposed guidance scheme is valid both for high eccentricity chief satellite orbits as well as large separation distance between chief and deputy satellites. Moreover, since MPSP poses the desired conditions as a set of `hard constraints', the final accuracy level achieved is very high. The proposed guidance scheme has been tested successfully for a variety of initial conditions and for a variety of formation commands as well. Comparison with standard Linear Quadratic Regulator (LQR) solution (which serves as a guess solution for MPSP) and another nonlinear controller, State Dependent Riccati Equation (SDRE) reveals that MPSP guidance achieves the objective with higher accuracy and with lesser amount of control usage as well.