Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Lightning characteristics observed by a VLF/LF lightning detection network (LINET) in Brazil, Australia, Africa and Germany

This paper describes lightning characteristics as obtained in four sets of lightning measurements during recent field campaigns in different parts of the world from mid-latitudes to the tropics by the novel VLF/LF (very low frequency/low frequency) lightning detection network (LINET). The paper gives a general overview on the approach, and a synopsis of the statistical results for the observation periods as a whole and for one special day in each region. The focus is on the characteristics of lightning which can specifically be observed by this system like intra-cloud and cloud-to-ground stroke statistics, vertical distributions of intra-cloud strokes or peak current distributions. Some conclusions regarding lightning produced NOx are also presented as this was one of the aims of the tropical field campaigns TROCCINOX (Tropical Convection, Cirrus and Nitrogen Oxides Experiment) and TroCCiBras (Tropical Convection and Cirrus Experiment Brazil) in Brazil during January/February 2005, SCOUT-O3 (Stratospheric-Climate Links with Emphasis on the Upper Troposphere and Lower Stratosphere) and TWP-ICE (Tropical Warm Pool-International Cloud Experiment) during November/December 2005 and January/February 2006, respectively, in the Darwin area in N-Australia, and of AMMA (African Monsoon Multidisciplinary Analyses) in W-Africa during June-November 2006.

NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations

Accurate long-term monitoring of total ozone is one of the most important requirements for identifying possible natural or anthropogenic changes in the composition of the stratosphere. For this purpose, the NDACC (Network for the Detection of Atmospheric Composition Change) UV-visible Working Group has made recommendations for improving and homogenizing the retrieval of total ozone columns from twilight zenith-sky visible spectrometers. These instruments, deployed all over the world in about 35 stations, allow measuring total ozone twice daily with limited sensitivity to stratospheric temperature and cloud cover. The NDACC recommendations address both the DOAS spectral parameters and the calculation of air mass factors (AMF) needed for the conversion of O-3 slant column densities into vertical column amounts. The most important improvement is the use of O-3 AMF look-up tables calculated using the TOMS V8 (TV8) O-3 profile climatology, that allows accounting for the dependence of the O-3 AMF on the seasonal and latitudinal variations of the O-3 vertical distribution. To investigate their impact on the retrieved ozone columns, the recommendations have been applied to measurements from the NDACC/SAOZ (Systeme d'Analyse par Observation Zenithale) network. The revised SAOZ ozone data from eight stations deployed at all latitudes have been compared to TOMS, GOMEGDP4, SCIAMACHY-TOSOMI, SCIAMACHY-OL3, OMI-TOMS, and OMI-DOAS satellite overpass observations, as well as to those of collocated Dobson and Brewer instruments at Observatoire de Haute Provence (44 degrees N, 5.5 degrees E) and Sodankyla (67 degrees N, 27 degrees E), respectively. A significantly better agreement is obtained between SAOZ and correlative reference ground-based measurements after applying the new O-3 AMFs. However, systematic seasonal differences between SAOZ and satellite instruments remain. These are shown to mainly originate from (i) a possible problem in the satellite retrieval algorithms in dealing with the temperature dependence of the ozone cross-sections in the UV and the solar zenith angle (SZA) dependence, (ii) zonal modulations and seasonal variations of tropospheric ozone columns not accounted for in the TV8 profile climatology, and (iii) uncertainty on the stratospheric ozone profiles at high latitude in the winter in the TV8 climatology. For those measurements mostly sensitive to stratospheric temperature like TOMS, OMI-TOMS, Dobson and Brewer, or to SZA like SCIAMACHY-TOSOMI, the application of temperature and SZA corrections results in the almost complete removal of the seasonal difference with SAOZ, improving significantly the consistency between all ground-based and satellite total ozone observations.

Automation in fault detection using neural network and model updating

In this article, an implementation of structural health monitoring process automation based on vibration measurements is proposed. The work presents an alternative approach which intent is to exploit the capability of model updating techniques associated to neural networks to be used in a process of automation of fault detection. The updating procedure supplies a reliable model which permits to simulate any damage condition in order to establish direct correlation between faults and deviation in the response of the model. The ability of the neural networks to recognize, at known signature, changes in the actual data of a model in real time are explored to investigate changes of the actual operation conditions of the system. The learning of the network is performed using a compressed spectrum signal created for each specific type of fault. Different fault conditions for a frame structure are evaluated using simulated data as well as measured experimental data.

Combined characterisation of GOME and TOMS total ozone measurements from space using ground-based observations from the NDSC

Several years of total ozone measured from space by the ERS-2 GOME, the Earth Probe TOMS, and the ADEOS TOMS, are compared with high-quality ground-based observations associated with the Network for the Detection of Stratospheric Change (NDSC), over an extended latitude range and a variety of geophysical conditions. The comparisons with each spaceborne sensor are combined altogether for investigating their respective solar zenith angle (SZA) dependence, dispersion, and difference of sensitivity. The space- and ground-based data are found to agree within a few percent on average. However, the analysis highlights for both GOME and TOMS several sources of discrepancies: (i) a SZA dependence with TOMS beyond 80° SZA; (ii) a seasonal SZA dependence with GOME beyond 70° SZA; (iii) a difference of sensitivity with GOME at high latitudes; (iv) a difference of sensitivity to low ozone values between satellite and SAOZ sensors around the southern tropics; (v) a north/south difference of TOMS with the ground-based observations; and (vi) internal inconsistencies in GOME total ozone. © 2001 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

Identification of steel bars immersed in reinforced concrete based on experimental results of eddy current testing and artificial neural network analysis

This paper presents an experimental research on the use of eddy current testing (ECT) and artificial neural networks (ANNs) in order to identify the gauge and position of steel bars immersed in concrete structures. The paper presents details of the ECT probe and concrete specimens constructed for the tests, and a study about the influence of the concrete on the values of measured voltages. After this, new measurements were done with a greater number of specimens, simulating a field condition and the results were used to generate training and validation vectors for multilayer perceptron ANNs. The results show a high percentage of correct identification with respect to both, the gauge of the bar and of the thickness of the concrete cover. © 2013 Copyright Taylor and Francis Group, LLC.

Monitoring in precision metal drilling process using multi-sensors and neural network

This paper presents a new method to estimate hole diameters and surface roughness in precision drilling processes, using coupons taken from a sandwich plate composed of a titanium alloy plate (Ti6Al4V) glued onto an aluminum alloy plate (AA 2024T3). The proposed method uses signals acquired during the cutting process by a multisensor system installed on the machine tool. These signals are mathematically treated and then used as input for an artificial neural network. After training, the neural network system is qualified to estimate the surface roughness and hole diameter based on the signals and cutting process parameters. To evaluate the system, the estimated data were compared with experimental measurements and the errors were calculated. The results proved the efficiency of the proposed method, which yielded very low or even negligible errors of the tolerances used in most industrial drilling processes. This pioneering method opens up a new field of research, showing a promising potential for development and application as an alternative monitoring method for drilling processes. © 2012 Springer-Verlag London Limited.

Complex network classification using partially self-avoiding deterministic walks

Complex networks have attracted increasing interest from various fields of science. It has been demonstrated that each complex network model presents specific topological structures which characterize its connectivity and dynamics. Complex network classification relies on the use of representative measurements that describe topological structures. Although there are a large number of measurements, most of them are correlated. To overcome this limitation, this paper presents a new measurement for complex network classification based on partially self-avoiding walks. We validate the measurement on a data set composed by 40000 complex networks of four well-known models. Our results indicate that the proposed measurement improves correct classification of networks compared to the traditional ones. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4737515]

Underlying Event measurements in pp collisions at root s=0.9 and 7 TeV with the ALICE experiment at the LHC

We present measurements of Underlying Event observables in pp collisions at root s = 0 : 9 and 7 TeV. The analysis is performed as a function of the highest charged-particle transverse momentum p(T),L-T in the event. Different regions are defined with respect to the azimuthal direction of the leading (highest transverse momentum) track: Toward, Transverse and Away. The Toward and Away regions collect the fragmentation products of the hardest partonic interaction. The Transverse region is expected to be most sensitive to the Underlying Event activity. The study is performed with charged particles above three different p(T) thresholds: 0.15, 0.5 and 1.0 GeV/c. In the Transverse region we observe an increase in the multiplicity of a factor 2-3 between the lower and higher collision energies, depending on the track p(T) threshold considered. Data are compared to PYTHIA 6.4, PYTHIA 8.1 and PHOJET. On average, all models considered underestimate the multiplicity and summed p(T) in the Transverse region by about 10-30%.

Arterial Spin Labeling Measurements of Cerebral Perfusion Territories in Experimental Ischemic Stroke

Collateral circulation, defined as the supplementary vascular network that maintains cerebral blood flow (CBF) when the main vessels fail, constitutes one important defense mechanism of the brain against ischemic stroke. In the present study, continuous arterial spin labeling (CASL) was used to quantify CBF and obtain perfusion territory maps of the major cerebral arteries in spontaneously hypertensive rats (SHRs) and their normotensive Wistar-Kyoto (WKY) controls. Results show that both WKY and SHR have complementary, yet significantly asymmetric perfusion territories. Right or left dominances were observed in territories of the anterior (ACA), middle and posterior cerebral arteries, and the thalamic artery. Magnetic resonance angiography showed that some of the asymmetries were correlated with variations of the ACA. The leptomeningeal circulation perfusing the outer layers of the cortex was observed as well. Significant and permanent changes in perfusion territories were obtained after temporary occlusion of the right middle cerebral artery in both SHR and WKY, regardless of their particular dominance. However, animals with right dominance presented a larger volume change of the left perfusion territory (23 +/- 9%) than animals with left dominance (7 +/- 5%, P<0.002). The data suggest that animals with contralesional dominance primarily safeguard local CBF values with small changes in contralesional perfusion territory, while animals with ipsilesional dominance show a reversal of dominance and a substantial increase in contralesional perfusion territory. These findings show the usefulness of CASL to probe the collateral circulation.

A scheme for synchronizing clocks connected by a packet communication network

Consider a communication system in which a transmitter equipment sends fixed-size packets of data at a uniform rate to a receiver equipment. Consider also that these equipments are connected by a packet-switched network, which introduces a random delay to each packet. Here we propose an adaptive clock recovery scheme able of synchronizing the frequencies and the phases of these devices, within specified limits of precision. This scheme for achieving frequency and phase synchronization is based on measurements of the packet arrival times at the receiver, which are used to control the dynamics of a digital phase-locked loop. The scheme performance is evaluated via numerical simulations performed by using realistic parameter values. (C) 2011 Elsevier By. All rights reserved.

Fog- and cloud-induced aerosol modification observed by the Aerosol Robotic Network (AERONET)

Large fine mode-dominated aerosols (submicron radius) in size distributions retrieved from the Aerosol Robotic Network (AERONET) have been observed after fog or low-altitude cloud dissipation events. These column-integrated size distributions have been obtained at several sites in many regions of the world, typically after evaporation of low-altitude cloud such as stratocumulus or fog. Retrievals with cloud-processed aerosol are sometimes bimodal in the accumulation mode with the larger-size mode often similar to 0.4-0.5 mu m radius (volume distribution); the smaller mode, typically similar to 0.12 to similar to 0.20 mu m, may be interstitial aerosol that were not modified by incorporation in droplets and/or aerosol that are less hygroscopic in nature. Bimodal accumulation mode size distributions have often been observed from in situ measurements of aerosols that have interacted with clouds, and AERONET size distribution retrievals made after dissipation of cloud or fog are in good agreement with particle sizes measured by in situ techniques for cloud-processed aerosols. Aerosols of this type and large size range (in lower concentrations) may also be formed by cloud processing in partly cloudy conditions and may contribute to the "shoulder" of larger-size particles in the accumulation mode retrievals, especially in regions where sulfate and other soluble aerosol are a significant component of the total aerosol composition. Observed trends of increasing aerosol optical depth (AOD) as fine mode radius increased suggests higher AOD in the near-cloud environment and higher overall AOD than typically obtained from remote sensing owing to bias toward sampling at low cloud fraction.

Estimating the monthly pCO2 distribution in the North Atlantic using a self-organizing neural network

[EN] Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a latitude by longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFSMODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437atm. The root mean square error (RMSE) of the neural network fit to the data is 11.6?atm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences.

Packet erasure correcting codes for wireless sensor networks: implementation and field trial measurements

This thesis regards the Wireless Sensor Network (WSN), as one of the most important technologies for the twenty-first century and the implementation of different packet correcting erasure codes to cope with the ”bursty” nature of the transmission channel and the possibility of packet losses during the transmission. The limited battery capacity of each sensor node makes the minimization of the power consumption one of the primary concerns in WSN. Considering also the fact that in each sensor node the communication is considerably more expensive than computation, this motivates the core idea to invest computation within the network whenever possible to safe on communication costs. The goal of the research was to evaluate a parameter, for example the Packet Erasure Ratio (PER), that permit to verify the functionality and the behavior of the created network, validate the theoretical expectations and evaluate the convenience of introducing the recovery packet techniques using different types of packet erasure codes in different types of networks. Thus, considering all the constrains of energy consumption in WSN, the topic of this thesis is to try to minimize it by introducing encoding/decoding algorithms in the transmission chain in order to prevent the retransmission of the erased packets through the Packet Erasure Channel and save the energy used for each retransmitted packet. In this way it is possible extend the lifetime of entire network.

Italian texts as networks: Topological measurements, Zipf and Heaps' laws

In questa tesi si è studiato un corpus di importanti testi della letteratura Italiana utilizzando la teoria dei network. Le misure topologiche tipiche dei network sono state calcolate sui testi letterari, poi sono state studiate le loro distribuzioni e i loro valori medi, per capire quali di esse possono distinguere un testo reale da sue modificazioni. Inoltre si è osservato come tutti i testi presentino due importanti leggi statistiche: la legge di Zipf e quella di Heaps.