65 resultados para LIVESTOCK PEST
Resumo:
In this work a mixed integer optimization linear programming (MILP) model was applied to mixed line rate (MLR) IP over WDM and IP over OTN over WDM (with and without OTN grooming) networks, with aim to reduce network energy consumption. Energy-aware and energy-aware & short-path routing techniques were used. Simulations were made based on a real network topology as well as on forecasts of traffic matrix based on statistical data from 2005 up to 2017. Energy aware routing optimization model on IPoWDM network, showed the lowest energy consumption along all years, and once compared with energy-aware & short-path routing, has led to an overall reduction in energy consumption up to 29%, expecting to save even more than shortest-path routing. © 2014 IEEE.
Resumo:
Discrete data representations are necessary, or at least convenient, in many machine learning problems. While feature selection (FS) techniques aim at finding relevant subsets of features, the goal of feature discretization (FD) is to find concise (quantized) data representations, adequate for the learning task at hand. In this paper, we propose two incremental methods for FD. The first method belongs to the filter family, in which the quality of the discretization is assessed by a (supervised or unsupervised) relevance criterion. The second method is a wrapper, where discretized features are assessed using a classifier. Both methods can be coupled with any static (unsupervised or supervised) discretization procedure and can be used to perform FS as pre-processing or post-processing stages. The proposed methods attain efficient representations suitable for binary and multi-class problems with different types of data, being competitive with existing methods. Moreover, using well-known FS methods with the features discretized by our techniques leads to better accuracy than with the features discretized by other methods or with the original features. (C) 2013 Elsevier B.V. All rights reserved.
Resumo:
With the increasing complexity of current networks, it became evident the need for Self-Organizing Networks (SON), which aims to automate most of the associated radio planning and optimization tasks. Within SON, this paper aims to optimize the Neighbour Cell List (NCL) for Long Term Evolution (LTE) evolved NodeBs (eNBs). An algorithm composed by three decisions were were developed: distance-based, Radio Frequency (RF) measurement-based and Handover (HO) stats-based. The distance-based decision, proposes a new NCL taking account the eNB location and interference tiers, based in the quadrants method. The last two algorithms consider signal strength measurements and HO statistics, respectively; they also define a ranking to each eNB and neighbour relation addition/removal based on user defined constraints. The algorithms were developed and implemented over an already existent radio network optimization professional tool. Several case studies were produced using real data from a Portuguese LTE mobile operator. © 2014 IEEE.
Resumo:
In video communication systems, the video signals are typically compressed and sent to the decoder through an error-prone transmission channel that may corrupt the compressed signal, causing the degradation of the final decoded video quality. In this context, it is possible to enhance the error resilience of typical predictive video coding schemes using as inspiration principles and tools from an alternative video coding approach, the so-called Distributed Video Coding (DVC), based on the Distributed Source Coding (DSC) theory. Further improvements in the decoded video quality after error-prone transmission may also be obtained by considering the perceptual relevance of the video content, as distortions occurring in different regions of a picture have a different impact on the user's final experience. In this context, this paper proposes a Perceptually Driven Error Protection (PDEP) video coding solution that enhances the error resilience of a state-of-the-art H.264/AVC predictive video codec using DSC principles and perceptual considerations. To increase the H.264/AVC error resilience performance, the main technical novelties brought by the proposed video coding solution are: (i) design of an improved compressed domain perceptual classification mechanism; (ii) design of an improved transcoding tool for the DSC-based protection mechanism; and (iii) integration of a perceptual classification mechanism in an H.264/AVC compliant codec with a DSC-based error protection mechanism. The performance results obtained show that the proposed PDEP video codec provides a better performing alternative to traditional error protection video coding schemes, notably Forward Error Correction (FEC)-based schemes. (C) 2013 Elsevier B.V. All rights reserved.
Resumo:
In this paper, a novel ROM-less RNS-to-binary converter is proposed, using a new balanced moduli set {22n-1, 22n + 1, 2n-3, 2n + 3} for n even. The proposed converter is implemented with a two stage ROM-less approach, which computes the value of X based only in arithmetic operations, without using lookup tables. Experimental results for 24 to 120 bits of Dynamic Range, show that the proposed converter structure allows a balanced system with 20% faster arithmetic channels regarding the related state of the art, while requiring similar area resources. This improvement in the channel's performance is enough to offset the higher conversion costs of the proposed converter. Furthermore, up to 20% better Power-Delay-Product efficiency metric can be achieved for the full RNS architecture using the proposed moduli set. © 2014 IEEE.
Resumo:
Floating-point computing with more than one TFLOP of peak performance is already a reality in recent Field-Programmable Gate Arrays (FPGA). General-Purpose Graphics Processing Units (GPGPU) and recent many-core CPUs have also taken advantage of the recent technological innovations in integrated circuit (IC) design and had also dramatically improved their peak performances. In this paper, we compare the trends of these computing architectures for high-performance computing and survey these platforms in the execution of algorithms belonging to different scientific application domains. Trends in peak performance, power consumption and sustained performances, for particular applications, show that FPGAs are increasing the gap to GPUs and many-core CPUs moving them away from high-performance computing with intensive floating-point calculations. FPGAs become competitive for custom floating-point or fixed-point representations, for smaller input sizes of certain algorithms, for combinational logic problems and parallel map-reduce problems. © 2014 Technical University of Munich (TUM).
Resumo:
A unified architecture for fast and efficient computation of the set of two-dimensional (2-D) transforms adopted by the most recent state-of-the-art digital video standards is presented in this paper. Contrasting to other designs with similar functionality, the presented architecture is supported on a scalable, modular and completely configurable processing structure. This flexible structure not only allows to easily reconfigure the architecture to support different transform kernels, but it also permits its resizing to efficiently support transforms of different orders (e. g. order-4, order-8, order-16 and order-32). Consequently, not only is it highly suitable to realize high-performance multi-standard transform cores, but it also offers highly efficient implementations of specialized processing structures addressing only a reduced subset of transforms that are used by a specific video standard. The experimental results that were obtained by prototyping several configurations of this processing structure in a Xilinx Virtex-7 FPGA show the superior performance and hardware efficiency levels provided by the proposed unified architecture for the implementation of transform cores for the Advanced Video Coding (AVC), Audio Video coding Standard (AVS), VC-1 and High Efficiency Video Coding (HEVC) standards. In addition, such results also demonstrate the ability of this processing structure to realize multi-standard transform cores supporting all the standards mentioned above and that are capable of processing the 8k Ultra High Definition Television (UHDTV) video format (7,680 x 4,320 at 30 fps) in real time.
Resumo:
In this paper a new PCA-based positioning sensor and localization system for mobile robots to operate in unstructured environments (e. g. industry, services, domestic ...) is proposed and experimentally validated. The inexpensive positioning system resorts to principal component analysis (PCA) of images acquired by a video camera installed onboard, looking upwards to the ceiling. This solution has the advantage of avoiding the need of selecting and extracting features. The principal components of the acquired images are compared with previously registered images, stored in a reduced onboard image database, and the position measured is fused with odometry data. The optimal estimates of position and slippage are provided by Kalman filters, with global stable error dynamics. The experimental validation reported in this work focuses on the results of a set of experiments carried out in a real environment, where the robot travels along a lawn-mower trajectory. A small position error estimate with bounded co-variance was always observed, for arbitrarily long experiments, and slippage was estimated accurately in real time.
Resumo:
Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.
Resumo:
Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.
Resumo:
Feature selection is a central problem in machine learning and pattern recognition. On large datasets (in terms of dimension and/or number of instances), using search-based or wrapper techniques can be cornputationally prohibitive. Moreover, many filter methods based on relevance/redundancy assessment also take a prohibitively long time on high-dimensional. datasets. In this paper, we propose efficient unsupervised and supervised feature selection/ranking filters for high-dimensional datasets. These methods use low-complexity relevance and redundancy criteria, applicable to supervised, semi-supervised, and unsupervised learning, being able to act as pre-processors for computationally intensive methods to focus their attention on smaller subsets of promising features. The experimental results, with up to 10(5) features, show the time efficiency of our methods, with lower generalization error than state-of-the-art techniques, while being dramatically simpler and faster.
Resumo:
Treatment of a dichloromethane solution of trans-[Mo(NCN){NCNC(O)R}(dppe)(2)]Cl [R = Me (1a), Et (1b)] (dppe = Ph2PCH2CH2PPh2) with HBF4, [Et3O][BF4] or EtC(O)Cl gives trans-[Mo(NCN)Cl-(dppe)(2)]X [X = BF4 (2a) or Cl (2b)] and the corresponding acylcyanamides NCN(R')C(O)Et (R' = H, Et or C(O)Et). X-ray diffraction analysis of 2a (X = BF4) reveals a multiple-bond coordination of the cyanoimide ligand. Compounds 1 convert to the bis(cyanoimide) trans-[Mo(NCN)(2)(dppe)(2)] complex upon reaction with an excess of NaOMe (with formation of the respective ester). In an aprotic medium and at a Pt electrode, compounds 1 (R = Me, Et or Ph) undergo a cathodically induced isomerization. Full quantitative kinetic analysis of the voltammetric behaviour is presented and allows the determination of the first-order rate constants and the equilibrium constant of the trans to cis isomerization reaction. The mechanisms of electrophilic addition (protonation) to complexes 1 and the precursor trans[Mo(NCN)(2)(dppe)(2)], as well as the electronic structures, nature of the coordination bonds and electrochemical behaviour of these species are investigated in detail by theoretical methods which indicate that the most probable sites of the proton attack are the oxygen atom of the acyl group and the terminal nitrogen atom, respectively.
Resumo:
Rhenium (I, III-V or VII) complexes bearing N-donor or oxo-ligands catalyse the Baeyer-Villiger oxidation of cyclic and linear ketones (e.g. 2-methylcyclohexanone, 2-methylcyclopentanone, cyclohexanone, cyclopentanone, cyclobutanone and 3,3-dimethyl-2-butanone) into the corresponding lactones or esters, in the presence of aqueous H2O2 (30%). The effects of various reaction parameters are studied allowing to achieve yields up to 54%.
Resumo:
New highly fluorescent calix[4]arene-containing phenylene-alt-ethynylene-3,6- and 2,7-carbazolylene polymers (CALIX-PPE-CBZs) have been synthesized for the first time and their photophysical properties evaluated. Both polymers were obtained in good isolated yields (70-84%), having M-w ranging from 7660-26,700 g mol(-1). It was found that the diethynyl substitution (3,6- or 2,7-) pattern on the carbazole monomers markedly influences the degree of polymerization. The amorphous yellow polymers are freely soluble in several nonprotic organic solvents and have excellent film forming abilities. TG/DSC analysis evidences similar thermal behaviors for both polymers despite their quite different molecular weight distributions and main-chain connectivities (T-g, in the range 83-95 degrees C and decomposition onsets around 270 degrees C). The different conjugation lengths attained by the two polymers dictates much of their photophysical properties. Thus, whereas the fully conjugated CALIX-PPE-2,7-CBZ has its emission maximum at 430 nm (E-g = 2.84 eV; Phi(F) = 0.62, CHCl3), the 3,6-linked counterpart (CALIX-PPE-3,6-CBZ) fluoresces at 403 nm with a significant lower quantum yield (E-g = 3.06 eV; Phi(F) = 0.31, CHCl3). The optical properties of both polymers are predominantly governed by the intrachain electronic properties of the conjugated backbones owing to the presence of calix[4]arenes along the polymer chain which disfavor significant interchain interactions, either in fluid- or solid-state.
Resumo:
A number of novel, water-stable redox-active cobalt complexes of the C-functionalized tripodal ligands tris(pyrazolyl)methane XC(pz)(3) (X = HOCH2, CH2OCH2Py or CH2OSO2Me) are reported along with their effects on DNA. The compounds were isolated as air-stable solids and fully characterized by IR and FIR spectroscopies, ESI-MS(+/-), cyclic voltammetry, controlled potential electrolysis, elemental analysis and, in a number of cases, also by single-crystal X-ray diffraction. They showed moderate cytotoxicity in vitro towards HCT116 colorectal carcinoma and HepG2 hepatocellular carcinoma human cancer cell lines. This viability loss is correlated with an increase of tumour cell lines apoptosis. Reactivity studies with biomolecules, such as reducing agents, H2O2, plasmid DNA and UV-visible titrations were also performed to provide tentative insights into the mode of action of the complexes. Incubation of Co(II) complexes with pDNA induced double strand breaks, without requiring the presence of any activator. This pDNA cleavage appears to be mediated by O-centred radical species.