Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Chloride migration in concrete with superabsorbent polymers

Superabsorbent polymers (SAP) can be used as a means for internal curing of concrete. In the present study, the development of transport properties of concrete with SAP is investigated. The chloride migration coefficient according to NT BUILD 492 is used as a measure of this. Twenty concrete mixtures are tested 7, 14, and 28 days after casting. The development of degree of hydration is followed for 20 corresponding paste mixtures.Both when SAP is added with extra water to compensate the SAP water absorption in fresh concrete and without extra water, the internal curing water held by SAP may contribute to increase the degree of hydration. No matter if SAP is added with or without extra water, it appears that the so-called gel space ratio can be used as a key parameter to link age and mixture proportions (water-to-cement ratio and SAP dosage) to the resulting chloride migration coefficient; the higher the volume of gel solid relative to the space available for it, the lower the chloride migration coefficient, because the pore system becomes more tortuous and the porosity becomes less.     

Multiplex PCR system to track authorized and unauthorized genetically modified soybean events in food and feed

A diverse range of genetic elements has been used to develop genetically modified organisms (GMOs) over the last 18 years. Screening methods that target few elements, such as the Cauliflower Mosaic Virus 35S promoter (P-35S) and Agrobacterium tumefaciens nopaline terminator (T-nos), are not sufficient to screen GMOs. In the present study, a multiplex PCR system for all globally commercialized GM soybean events was developed to easily trace the events. For this purpose, screening elements of 24 GM soybean events were investigated and 9 screening targets were selected and divided into three individual triplex PCR systems: P-35S, ribulose-1,5-bisphosphate carboxylase small subunit promoter of Arabidopsis thaliana, T-nos, T-35S, pea E9 terminator, open reading frame 23 terminator of A. tumefaciens, proteinase inhibitor II terminator of potato, acetohydroxy acid synthase large subunit terminator of A. thaliana, and the revealed 3′ flanking sequences of DP-305423-1. The specificity of the assays was confirmed using thirteen GM soybean events as the respective positive/negative controls. The limit of detection of each multiplex set, as determined using certified reference materials of specific GM events, ranged from 0.03 to 0.5%, depending upon target. Furthermore, 26 food samples that contained soybean ingredients, which were purchased from the USA, China, Japan, and Korea, were analyzed, 17 of which contained one or more GM soybean events. These results suggest that the developed screening method can be used to efficiently track and identify 24 GM soybean events in food and feed.     

Prediction of rock mass P wave velocity using blasthole drilling information

In this paper, the development of the models for the prediction of rock mass P wave velocity is presented. For model development, the database of 53 cases including widely used and recorded drilling parameters and P wave velocity was constructed from the field studies conducted in 13 open pit lignite mines. Both conventional linear, non-linear multiple regression and Adaptive Neuro Fuzzy Inference System (ANFIS) were used for model development. Prediction performance indicators showed that ANFIS model presented the best performance and it can successfully be used for the preliminary prediction of P wave velocities of rock masses.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

Simultaneous determination of mycotoxin in commercial coffee

Mycotoxins are secondary metabolites produced by filamentous fungi that usually contaminate food products. Coffee is a natural product susceptible to mycotoxin contamination. The present study evaluates the presence of nivalenol, deoxynivalenol, T-2 and HT-2 Toxin, diacetoxyscirpenol, aflatoxin B₁, aflatoxin B₂, aflatoxin G₁, aflatoxin G₂, fumonisin B₁, fumonisin B₂, ochratoxin A, zearalenone, enniatin A, enniatin A₁, enniatin B, enniatin B₁, and beauvericin in coffee samples, using liquid chromatography tandem mass spectrometry (LC-MS/MS). The results show that zearalenone was not present in any sample. In the positive samples the contents of fumonisins ranged from 58.62 to 537.45 μg/kg, emerging mycotoxins ranged from 0.10 to 3569.92 μg/kg, aflatoxins ranged from 0.25 to 13.12 μg/kg, and trichothecenes, excepting nivalenol, ranged from 5.70 to 325.68 μg/kg. Nivalenol presented the highest concentrations, from 0.40 to 25.86 mg/kg. Ochratoxin A ranged from 1.56 to 32.40 μg/kg, and five samples exceeded the maximum limit established by the European Commission.     

无源光网络标准发展及关键技术研究

无源光网络(Passive Optical Network,PON)作为当今接入网的主要技术解决方案,具有带宽使用效率高、传输距离远、抗干扰能力强等特点.通过研究PON技术的发展动态,本文首先归纳了各种PON技术的产生背景和应用特点,整理出各技术间的连接关系及主要标准;其次介绍了PON技术的帧结构,并对带宽、波长、传输模式等PON技术的主要参数进行了汇总;然后将国内外研究热点进行划分,围绕媒体访问控制协议、帧结构、动态带宽分配算法、节能机制等关键技术,阐述了其研究现状及在PON中的重要作用;最后对PON技术的发展趋势进行了展望.     

Pull out of FRP reinforcement from masonry pillars: Experimental and numerical results

In this paper, debonding phenomena between carbon fiber reinforced polymer (CFRP) strips and masonry support were investigated on the basis of single-lap shear tests, considering different dimensions of the bond length. To capture the post-peak response of the CFRP–masonry joint, the slip between the support and the reinforcement strip was controlled using a clip gauge positioned at the end of the reinforcement. The tests were simulated by means of a finite element model able to capture the post-peak snap-back behavior due to the failure process. The numerical model is based on zero-thickness interface elements and on a proper non-linear cohesive law. The comparison between experimental and numerical results was performed in terms of overall response, measured by both the machine stroke and the clip gauge positioned at the free end of the reinforcement. The cases of effective bond length greater and lesser than the minimum anchorage length, suggested by the CNR Italian recommendation, were considered.     

Annealing and doping-dependent magnetoresistance in single layer poly(3-hexyl-thiophene) organic semiconductor device

We compare the current density–voltage (J–V) and magnetoconductance (MC) response of a poly(3-hexyl-thiophene) (P3HT) device (Au/P3HT(350 nm)/Al) before and after annealing above the glass transition temperature of 150 °C under vacuum. There is a decrease of more than 3 orders of magnitude in current density due to an increase of the charge injection barriers after de-doping through annealing. An increase, approaching 1 order of magnitude, in the negative MC response after annealing can be explained by a shift in the Fermi level due to de-doping, according to the bipolaron mechanism. We successfully tune the charge injection barrier through re-doping by photo-oxidation. This leads to the charge injection and transport transitioning from unipolar to ambipolar, as the bias increases, and we model the MC response using a combination of bipolaron and triplet-polaron interaction mechanisms.     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.