19,992 research outputs found

    Three new species of Helicopsyche (Trichoptera, Helicopsychidae) from northern Vietnam, with a key to Helicopsyche species of Vietnam

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    Three new species of Helicopsyche Siebold, 1856 are described from Vietnam: Helicopsyche melina sp. nov., Helicopsyche meander sp. nov., and Helicopsyche lamnata sp. nov. All species were described from Melinh Station for Biodiversity in the Me Linh District of Vinh Phuc Province. The species were collected mainly in Malaise traps situated across a small stream surrounded by lowland forest. Some individuals were also collected on light in traps situated at the stream bank

    Blooming in a non-local, coupled phytoplankton-nutrient model

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    Recently, it has been discovered that the dynamics of phytoplankton concentrations in an ocean exhibit a rich variety of patterns, ranging from trivial states to oscillating and even chaotic behavior [J. Huisman, N. N. Pham Thi, D. M. Karl, and B. P. Sommeijer, Nature, 439 (2006), pp. 322–325]. This paper is a first step towards understanding the bifurcational structure associated with nonlocal coupled phytoplankton-nutrient models as studied in that paper. Its main subject is the linear stability analysis that governs the occurrence of the first nontrivial stationary patterns, the deep chlorophyll maxima (DCMs) and the benthic layers (BLs). Since the model can be scaled into a system with a natural singularly perturbed nature, and since the associated eigenvalue problem decouples into a problem of Sturm–Liouville type, it is possible to obtain explicit (and rigorous) bounds on, and accurate approximations of, the eigenvalues. The analysis yields bifurcation-manifolds in parameter space, of which the existence, position, and nature are confirmed by numerical simulations. Moreover, it follows from the simulations and the results on the eigenvalue problem that the asymptotic linear analysis may also serve as a foundation for the secondary bifurcations, such as the oscillating DCMs, exhibited by the model

    An Efficient Data-aided Synchronization in L-DACS1 for Aeronautical Communications

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    L-band Digital Aeronautical Communication System type-1 (L-DACS1) is an emerging standard that aims at enhancing air traffic management (ATM) by transitioning the traditional analog aeronautical communication systems to the superior and highly efficient digital domain. L-DACS1 employs modern and efficient orthogonal frequency division multiplexing (OFDM) modulation technique to achieve more efficient and higher data rate in comparison to the existing aeronautical communication systems. However, the performance of OFDM systems is very sensitive to synchronization errors. L-DACS1 transmission is in the L-band aeronautical channels that suffer from large interference and large Doppler shifts, which makes the synchronization for L-DACS more challenging. This paper proposes a novel computationally efficient synchronization method for L-DACS1 systems that offers robust performance. Through simulation, the proposed method is shown to provide accurate symbol timing offset (STO) estimation as well as fractional carrier frequency offset (CFO) estimation in a range of aeronautical channels. In particular, it can yield excellent synchronization performance in the face of a large carrier frequency offset.Comment: In the proceeding of International Conference on Data Mining, Communications and Information Technology (DMCIT

    Faster K-Means Cluster Estimation

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    There has been considerable work on improving popular clustering algorithm `K-means' in terms of mean squared error (MSE) and speed, both. However, most of the k-means variants tend to compute distance of each data point to each cluster centroid for every iteration. We propose a fast heuristic to overcome this bottleneck with only marginal increase in MSE. We observe that across all iterations of K-means, a data point changes its membership only among a small subset of clusters. Our heuristic predicts such clusters for each data point by looking at nearby clusters after the first iteration of k-means. We augment well known variants of k-means with our heuristic to demonstrate effectiveness of our heuristic. For various synthetic and real-world datasets, our heuristic achieves speed-up of up-to 3 times when compared to efficient variants of k-means.Comment: 6 pages, Accepted at ECIR 201

    CP asymmetry and branching ratio of B -> pi pi

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    We investigate the branching ratios and CP asymmetries of the B -> pi pi processes measured in B factory experiments. Fits to the experimental data of this process indicate a large ratio of color-suppressed (C) to color-allowed (T) tree contributions. We investigate whether the large C/T can be explained within the QCD based model computation with i) a large effect from the end-point singularity or with ii) large final-state-interaction phase between two different isospin amplitudes. We show that the current experimental data do not exclude either possibility but we may be able to distinguish these two effects in future measurements of direct CP asymmetry of B -> pi^0 pi^0.Comment: 8 pages, 10 figure

    Relationship Between Obesity and Periodontal Status in Vietnamese Patients

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    This study aims to investigate periodontal status, and the relationship between obesity and periodontal status in patients who first visited the Institute of Traditional Medicine, Ho Chi Minh City, Vietnam. 118 patients aged 18 or older, including 56 obese subjects (BMI≥27.5, mean age: 33.8, males: 11, females: 45) and 62 non-obese subjects (BMI<27.5, mean age: 34.3, males: 4, females: 58) were enrolled for a period of 5 months from February 2014 to June 2014. The information on socio-demographic characteristics and dental habits were collected by questionnaire. Periodontal status (PLI, GI, BOP, PD, CAL) was examined and the anthropometric index was measured. There was significantly higher prevalence of periodontitis (39.3%) in the obese group than the non-obese group (16.4%). Means of GI, BOP, PD, and CAL in obese subjects were significantly higher than those in non-obese subjects. Significantly higher percentages of subjects who had lower education, visited dental offices, scaled and polished their teeth regularly were in the non-obese group than in the obese group. Multiple logistic regression analysis revealed that age (OR=3.10), routine of dental visit (OR=3.34) and obesity (OR=2.79) were risk factors significantly related to periodontitis. Periodontal status in obese subjects was poorer than non-obese subjects. Obesity might be the risk factor for periodontitis in Vietnamese patients

    Efficient multi-standard cognitive radios on FPGAs

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    Cognitive radios that support multiple standards and modify operation depending on environmental conditions are becoming more important as the demand for higher bandwidth and efficient spectrum use increases. Traditional implementations in custom ASICs cannot support such flexibility, with standards changing at a faster pace, while software baseband implementations fail to achieve the performance required. Hence, FPGAs offer an ideal platform bringing together flexibility, performance, and efficiency. This work explores the possible techniques for designing multi-standard radios on FPGAs, and explores how partial reconfiguration can be leveraged in a way that is amenable for domain experts with minimal FPGA knowledge

    The Self-Organization of Interaction Networks for Nature-Inspired Optimization

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    Over the last decade, significant progress has been made in understanding complex biological systems, however there have been few attempts at incorporating this knowledge into nature inspired optimization algorithms. In this paper, we present a first attempt at incorporating some of the basic structural properties of complex biological systems which are believed to be necessary preconditions for system qualities such as robustness. In particular, we focus on two important conditions missing in Evolutionary Algorithm populations; a self-organized definition of locality and interaction epistasis. We demonstrate that these two features, when combined, provide algorithm behaviors not observed in the canonical Evolutionary Algorithm or in Evolutionary Algorithms with structured populations such as the Cellular Genetic Algorithm. The most noticeable change in algorithm behavior is an unprecedented capacity for sustainable coexistence of genetically distinct individuals within a single population. This capacity for sustained genetic diversity is not imposed on the population but instead emerges as a natural consequence of the dynamics of the system

    Shaping spectral leakage for IEEE 802.11 p vehicular communications

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    IEEE 802.11p is a recently defined standard for the physical (PHY) and medium access control (MAC) layers for Dedicated Short-Range Communications. Four Spectrum Emission Masks (SEMs) are specified in 802.11p that are much more stringent than those for current 802.11 systems. In addition, the guard interval in 802.11p has been lengthened by reducing the bandwidth to support vehicular communication (VC) channels, and this results in a narrowing of the frequency guard. This raises a significant challenge for filtering the spectrum of 802.11p signals to meet the specifications of the SEMs. We investigate state of the art pulse shaping and filtering techniques for 802.11p, before proposing a new method of shaping the 802.11p spectral leakage to meet the most stringent, class D, SEM specification. The proposed method, performed at baseband to relax the strict constraints of the radio frequency (RF) front-end, allows 802.11p systems to be implemented using commercial off-the- shelf (COTS) 802.11a RF hardware, resulting in reduced total system cost

    Use of statistical outlier detection method in adaptive evolutionary algorithms

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    In this paper, the issue of adapting probabilities for Evolutionary Algorithm (EA) search operators is revisited. A framework is devised for distinguishing between measurements of performance and the interpretation of those measurements for purposes of adaptation. Several examples of measurements and statistical interpretations are provided. Probability value adaptation is tested using an EA with 10 search operators against 10 test problems with results indicating that both the type of measurement and its statistical interpretation play significant roles in EA performance. We also find that selecting operators based on the prevalence of outliers rather than on average performance is able to provide considerable improvements to adaptive methods and soundly outperforms the non-adaptive case
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