摘要：Bionic devices are an integral part of human life,and continuous innovations in their design and functions with the help of nanotechnology has revolutionized the area of neuroscience and ***-interfaces play a key role in bionic devices such as neural implants for efficient transfer of the signal to smart *** report here on the design of a new microelectrode,comprising Carbon Nanofiber (CNF) and a biopolymer,namely carboxymethyl xyloglucan (CMX) hydrogel inside the CNF,which enhances the current density across the interface,Microelectrode was prepared by in-situ cross-linking of CMX inside CNF,with optimized CMX:CNF ratio,resulting in continuous ionic channels confined within the hollow core of *** microscopy images of microelectrodes illustrate the formation ofCMX hydrogel network inside the CNF hollow core without wrapping its *** presence of hydrogel in the CNF was confirmed by Scanning Electron Microscope (SEM) and Transmission Electron Microscopy (TEM).The electrochemical studies indicate the enhancement in charge density as well as the active surface area of the microelectrodes due to the presence ofCMX hydrogel *** microelectrodes have great potential as neural interfaces for designing smart prosthetics with voluntary control.

摘要：Convolutional neural networks(CNNs)have shown tremendous progress and performance in recent *** emergence,CNNs have exhibited excellent performance in most of classification and segmentation ***,the CNN family includes various architectures that dominate major vision-based recognition ***,building a neural network(NN)by simply stacking convolution blocks inevitably limits its optimization ability and introduces overfitting and vanishing gradient *** of the key reasons for the aforementioned issues is network singularities,which have lately caused degenerating manifolds in the loss *** situation leads to a slow learning process and lower *** this scenario,the skip connections turned out to be an essential unit of the CNN design to mitigate network *** proposed idea of this research is to introduce skip connections in NN architecture to augment the information flow,mitigate singularities and improve *** research experimented with different levels of skip connections and proposed the placement strategy of these links for any *** prove the proposed hypothesis,we designed an experimental CNN architecture,named as Shallow Wide ResNet or SRNet,as it uses wide residual network as a base network *** have performed numerous experiments to assess the validity of the proposed ***-10 and CIFAR-100,two well-known datasets are used for training and testing *** final empirical results have shown a great many of promising outcomes in terms of performance,efficiency and reduction in network singularities issues.

摘要：A multilayer perceptron(MLP) artificial neural network(ANN) model has been optimized by the multi-objective ant colony optimization(MOACO) algorithm, which uses three objective functions. A sensitivity analysis to choose MOACO parameter values is carried out by calculating hypervolume metric, and the proposed approach adopts the Vlsekriterijumska Optimizacija I Kompromisno Resenje(VIKOR) decision method to choose final compromised solution on the Pareto front obtained from MOACO. As a result, we used the MLP-MOACO developed model to estimate the value of engine emissions of NOxin a four stroke, spark ignition(SI) gasoline engine and observed acceptable correlation coefficient(R^2) of 0.99978.

摘要：Studying the piled raft behavior has been the subject of many types of research in the field of geotechnical *** studies have been conducted to understand the behavior of these types of foundations,which are often used for uniform loading on the raft and piles with the same length,while generally the transition load from the upper structure to the foundation is non-uniform and the choice of uniform length for piles in the above model will not be optimally economic and *** most common method in identifying the behavior of piled rafts is the use of theoretical relationships and software *** precise identification of this type of foundation behavior can be very difficult due to several influential parameters and interaction of set behavior,and it will be done by doing time-consuming computer analyses or costly full-scale physical *** the meantime,the technique of artificial neural networks can be used to achieve this goal with minimum time consumption,in which data from physical and numerical modeling can be used for network *** of the advantages of this method is the speed and simplicity of using *** this paper,a model is presented based on multi-layer perceptron artificial neural *** this model pile diameter,pile length,and pile spacing is considered as an input parameter that can be used to estimate maximum settlement,maximum differential settlement,and maximum raft *** this model,we can create an extensive domain of results for optimum system selection in the desired piled raft *** of neural network indicate its proper ability in identifying the piled raft *** presented procedure provides an interesting solution and economically enhancing the design of the piled raft foundation *** innovative design method reduces the time spent on software analyses.

摘要：Corrosion in complex coupling environments is an important issue in corrosion field, because it is difficult to take into account a large number of environment factors and their interactions. Design of Experiment(DOE) can present a methodology to deal with this difficulty, although DOE is not commonly spread in corrosion field. Thus, modeling corrosion of Ni-Cr-Mo-V steel in deep sea environment was performed in order to provide example demonstrating the advantage of DOE. In addition, an artificial neural network mapping using back-propagation method was developed for Ni-Cr-Mo-V steel such that the ANN model can be used to predict polarization curves under different complex sea environments without experimentation. Furthermore, roles of environment factors on corrosion of Ni-Cr-Mo-V steel in deep sea environment were discussed.

摘要：Monitoring the electrophysiology activity of neurons and blood calcium signals can enable a better understanding of disease-related neural system ***,currently,in situ calcium ion monitoring tools are scarce and exhibit low integration and limited *** this letter,we propose an implantable probe with an integrated in situ Ag/AgCl reference electrode(ISA/ARE)that can monitor action potential(AP)and Ca^(2+) concentrations.

摘要：Based on the model of a formal neuron proposed by McCulloch and Pitts,a kind ofneural circuit,which is a CMOS Variable Threshold Logic(VTL)circuit,is given in this paperconsidering the features of the binary image processing *** theoretical analysis,andthe simulations for the building block circuits such as D/A converters,comparator and so on *** layout design of the whole circuit are also *** binary image processing can berealized by using the VTL circuit combined with its external auxiliary circuits.

摘要：This paper motivated and inspired by an interdisciplinary critical educational issue adopted for a research work approach. It concerned with application of realistic Artificial neural Networks (ANNs) models integrating reading brain function with multi-sensory cognitive learning theory. Specifically, these models adopted to improve tutoring quality (academic achievement) while teaching children “how to read?” considering the analysis and evaluation of phonics methodology. Herein, quantitative analysis and evaluation of this issue performed by considering two computer aided learning (CAL) packages concerned with a specific selected mathematical topic namely: long division process. Via realistic modeling of packages using (ANNs) based upon associative memory learning paradigm. In more details, at educational field practice; both CAL packages have been applied for teaching children algorithmic steps performing long division processes. Moreover, learning performance evaluation of presented packages considers children outcomes’ achievement after tutoring for suggested Mathematical Topic either with or without associated tutor’s voice. Interestingly, statistical analysis of obtained educational case study results at children classrooms (for both applied packages) versus classical tutoring proved to be in well agreement with obtained after ANNs computer simulation results.

摘要：In this paper, a hybrid Fuzzy neural Network (FNN) system for function approximation is presented. The proposed FNN can handle numeric and fuzzy inputs simultaneously. The numeric inputs are fuzzified by input nodes upon presentation to the network while the Fuzzy rule based knowledge is translated directly into network architecture. The connections between input to hidden nodes represent rule antecedents and hidden to output nodes represent rule consequents. All the connections are represented by Gaussian fuzzy sets. The method of activation spread in the network is based on a fuzzy mutual subsethood measure. Rule (hidden) node activations are computed as a fuzzy inner product. For a given numeric o fuzzy input, numeric outputs are computed using volume based defuzzification. A supervised learning procedure based on gradient descent is employed to train the network. The model has been tested on two different approximation problems: sine-cosine function approximation and Narazaki-Ralescu function and shows its natural capability of inference, function approximation, and classification.

摘要：This paper presents the effect of the high voltage direct current (HVDC) transmission system based on voltage source converter (VSC) on the sub synchronous resonance (SSR) and low frequency oscillations (LFO) in power system. Also, a novel adaptive neural controller based on neural identifier is proposed for the HVDC which is capable of damping out LFO and sub synchronous oscillations (SSO). For comparison purposes, results of system based damping neural controller are compared with a lead-lag controller based on quantum particle swarm optimization (QPSO). It is shown that implementing adaptive damping controller not only improves the stability of power system but also can overcome drawbacks of conventional compensators with fixed parameters. In order to determine the most effective input of HVDC system to apply supplementary controller signal, analysis based on singular value decomposition is performed. To evaluate the performance of the proposed controller, transient simulations of detailed nonlinear system are considered.