A Universal Activation Function for Deep Learning

Recently,deep learning has achieved remarkable results in fields that require human cognitive ability,learning ability,and reasoning ability.Activation functions are very important because they provide the ability of artificial neural networks to learn complex patterns through nonlinearity.Various activation functions are being studied to solve problems such as vanishing gradients and dying nodes that may occur in the deep learning process.However,it takes a lot of time and effort for researchers to use the existing activation function in their research.Therefore,in this paper,we propose a universal activation function(UA)so that researchers can easily create and apply various activation functions and improve the performance of neural networks.UA can generate new types of activation functions as well as functions like traditional activation functions by properly adjusting three hyperparameters.The famous Convolutional Neural Network(CNN)and benchmark datasetwere used to evaluate the experimental performance of the UA proposed in this study.We compared the performance of the artificial neural network to which the traditional activation function is applied and the artificial neural network to which theUA is applied.In addition,we evaluated the performance of the new activation function generated by adjusting the hyperparameters of theUA.The experimental performance evaluation results showed that the classification performance of CNNs improved by up to 5%through the UA,although most of them showed similar performance to the traditional activation function.

THE COMBINATORY METHOD FOR DETERMINATION OF THE TURBULENT FLUXES AND UNIVERSAL FUNCTIONS IN THE SURFACE LAYER

A combinatory method of determining the turbulent fluxes in the surface layer has been developed and their general representations have been thus obtained.The universal functions of the (M-O) similarity in the surface layer can be de- termined by the method.The results calculated by using the ITCE's data indicate that the method is feasible.

Universal function of the diffractive process in color dipole picture

In this study,we obtain the universal function corresponding to the diffractive process and show that the cross section exhibits geometrical scaling.It is observed that diffractive theory according to the color dipole approach at small-x is a convenient framework that reveals the color transparency and saturation phenomena.We also calculate the contribution of heavy quark production in the diffractive cross section at high energy that is determined by the small size dipole configuration.The ratio of the diffractive cross section to the total cross section in electron-proton collision is the other important quantity that is computed in this work.

A UNIVERSAL ANALYTIC POTENTIAL-ENERGY FUNCTION BASED ON A PHASE FACTOR

Using a field equation with a phase factor, a universal analytic potential-energy function applied to the interactions between diatoms or molecules is derived, and five kinds of potential curves of common shapes are obtained adjusting the phase factors. The linear thermal expansion coefficients and Young's moduli of eleven kinds of face-centered cubic (fcc) metals - Al, Cu, Ag, etc. are calculated using the potential-energy function; the computational results are quite consistent with experimental values. Moreover, an analytic relation between the linear thermal expansion coefficients and Young's moduli of fcc metals is given using the potential-energy function. Finally, the force constants of fifty-five kinds of diatomic moleculars with low excitation state are computed using this theory, and they are quite consistent with RKR (Rydberg-Klein-Rees) experimental values.

A universal potential energy function and precise calculations on the molecular spectra

By using a function with a phase factor,a universal analytic potential energy function applied to the interactions between diatoms or molecules is derived and six kinds of potential curves of common shapes are obtained by adjusting the phase factor.The spectroscopic parameters of ten diatomic molecules are calculated by using the potential energy function;as a consequence,all calculation results are in good agreement with experimental data.

Improved Discrete Interval-Valued Stress-Strength Interference Model Based on Extended Universal Generating Function

In practical engineering,sometimes the probability density functions( PDFs) of stress and strength can not be exactly determined,or only limited experiment data are available. In these cases,the traditional stress-strength interference( SSI) model based on classical probabilistic approach can not be used to evaluate reliabilities of components. To solve this issue, the traditional universal generating function( UGF) is introduced and then it is extended to represent the discrete interval-valued random variable.Based on the extended UGF,an improved discrete interval-valued SSI model is proposed, which has higher calculation precision compared with the existing methods. Finally,an illustrative case is given to demonstrate the validity of the proposed model.

Reliability Bounds based on Universal Generating Function and Discrete Stress-strength Interference Model

A method for estimating the component reliability is proposed when the probability density functions of stress and strength can not be exactly determined. For two groups of finite experimental data about the stress and strength, an interval statistics method is introduced. The processed results are formulated as two interval-valued random variables and are graphically represented component reliability are proposed based on the by using two histograms. The lower and upper bounds of universal generating function method and are calculated by solving two discrete stress-strength interference models. The graphical calculations of the proposed reliability bounds are presented through a numerical example and the confidence of the proposed reliability bounds is discussed to demonstrate the validity of the proposed method. It is showed that the proposed reliability bounds can undoubtedly bracket the real reliability value. The proposed method extends the exciting universal generating function method and can give an interval estimation of component reliability in the case of lake of sufficient experimental data. An application example is given to illustrate the proposed method

Why the Incoherent Paradigm Is for the Future Wireless Networks?

This material is aimed to attract attention to the “incoherent approach for power NOMA-RIS-MIMO transmission in wireless channels”. Such kind of approach might be successfully applied in future dense networks formed by High-Speed Vehicles (HSV networks, etc.). Those scenarios take place in doubly selective communication channels typical for such kind of radio networks. The proposal for the presented hereafter incoherent view (“paradigm”) is based on several basic principles: 1) Shift from the “coherent “ideology”, i.e. rejection of the application of any type of Channel State Information (CSI, CSIT);2) Application of the so-called “invariant” to the communication channel’s features (distortions) modulation technique together with its incoherent demodulation;3) Orthogonal channel decomposition by means of “universal” eigen basis (in the form of Prolate Spheroidal Wave Functions, PSWF) as “artificial trajectories” of wave propagation;4) Chaotic filtering (chaos parameter settings as UE signatures) together with sequential multiuser parallel detection algorithms for users’ identification (classification). It is shown that the proposed approach might provide an effective use of the radio resource and it is relatively simple for implementation.

Discrete Stress-strength Interference Model of Reliability Analysis under Multi-operating Conditions

The conventional stress-strength interference（SSI） model is a basic model for reliability analysis of mechanical components. In this model, the component reliability is defined as the probability of the strength being larger than the stress, where the component stress is generally represented by a single random variable（RV）. But for a component under multi-operating conditions, its reliability can not be calculated directly by using the SSI model. The problem arises from that the stress on a component under multi-operating conditions can not be described by a single RV properly. Current research concerning the SSI model mainly focuses on the calculation of the static or dynamic reliability of the component under single operation condition. To evaluate the component reliability under multi-operating conditions, this paper uses multiple discrete RVs based on the actual stress range of the component firstly. These discrete RVs have identical possible values and different corresponding probability value, which are used to represent the multi-operating conditions of the component. Then the component reliability under each operating condition is calculated, respectively, by employing the discrete SSI model and the universal generating function technique, and from this the discrete SSI model under multi-operating conditions is proposed. Finally the proposed model is applied to evaluate the reliability of a transmission component of the decelerator installed in an aeroengine. The reliability of this component during taking-off, cruising and landing phases of an aircraft are calculated, respectively. With this model, a basic method for reliability analysis of the component under complex load condition is provided, and the application range of the conventional SSI model is extended.

Reliability Analysis of Electromechanical Systems with Degraded Components Containing Multiple Performance Parameters

Components of electromechanical systems usually contain multiple performance parameters and degrade over time. In previous studies, the reliability of these electromechanical systems was analyzed by the traditional method, and the system reliability was estimated based on the reliability of components and the structures of the systems. The system reliability estimated by the traditional method could not reflect the performance of the systems. A new method is proposed in this paper to analyze the system reliability according to the data of multiple performance degraded processes of components. The performance distribution of a degraded component is obtained by the performance degradation analysis, and then states of the component are defined and corresponding state probabilities are estimated. The universal generating function method is proposed and extended to compute the performance distribution and reliability of the system based on the performances of components. A numerical example illustrates the proposed method. The results of the example show that the proposed method can relate the performance of the system to the performances of components and absolutely reflect the relationship between reliability and performance. Compared with the exact values of the system reliability, the results obtained by the proposed method is almost the same with the exact values, and the results obtained by the traditional method are conservative. The proposed method overcomes the shortcomings of the traditional method and provides a new approach to analyze the reliability of electromechanical systems with degraded components containing multiple performance parameters.

Universal generating function based probabilistic production simulation for wind power integrated power systems

According to the demand of sustainable development and low-carbon electricity, it is important to develop clean resources and optimize scheduling generation mix. Firstly, a novel method for probabilistic production simulation for wind power integrated power systems is proposed based on universal generating function(UGF), which completes the production simulation with the chronological wind power and load demand. Secondly,multiple-period multiple-state wind power model and multiple-state thermal unit power model are adopted, and both thermal power and wind power are coordinately scheduled by the comprehensive cost including economic cost and environmental cost. Furthermore, the accommodation and curtailment of wind power is synergistically considered according to the available regulation capability of conventional generators in operation. Finally, the proposed method is verified and compared with conventional convolution method in the improved IEEE-RTS 79 system.

Reliability Analysis of Excavator Rectifier Feedback System with Multi-State Components Based on Belief Universal Generating Function Method

In view of the complexity and uncertainty of system, both the state performances and state probabilities of multi-state components can be expressed by interval numbers. The belief function theory is used to characterize the uncertainty caused by various factors. A modified Markov model is proposed to obtain the state probabilities of components at any given moment and subsequently the mass function is used to represent the precise belief degree of state probabilities. Based on the primary studies of universal generating function(UGF)method, a belief UGF(BUGF) method is utilized to analyze the reliability and the uncertainty of excavator rectifier feedback system. This paper provides an available method to evaluate the reliability of multi-state systems(MSSs) with interval state performances and state probabilities, and also avoid the interval expansion problem.

Reliability Evaluation of Compressor Systems Based on Universal Generating Function Method

At present, universal generating function(UGF) is a reliability evaluation technique which holds the bare-looking and easily program-realized merits in multi-state system. Thus, it is meaningful to apply this method to an actual industry system. Compressor systems in natural gas pipelines are series-parallel multi-state systems,where the compressor units in each compressor station work in a parallel way and these pressure-boosting stations in the pipeline are series connected. Considering the characteristic of gas pipelines, this paper develops two different UGFs to evaluate the system reliability. One(Model 1) establishes a system model from every compressor unit while the other(Model 2) considers the whole system as a combination of multi-state components. Besides, all the parameters of "weight" in UGFs are obtained from thermal-hydraulic models based on the actual engineering and"probability" from Monte Carlo simulation. The results show that the system reliabilities calculated by different UGFs are approximately equal. In addition, the demand of gas and the gas pipeline transportation system show a reverse trend. Because the number of parameters needed in Model 2 is far less than that needed in Model 1,Model 2 is simpler programming and faster solved.

Short-term reliability evaluation for power stations by using Lz-transform

A short-term reliability evaluation is used for power stations,where each power generating unit is presented by a multi-state Markov model.The main obstacle for reliability evaluation in such a case is a“curse of dimensionality”—a great(huge)number of states of entire power station that should be analyzed.A modern approach is proposed based on using Lz-transform that drastically simplifies computation.The proposed approach is useful for power system security analysis and short-term operating decisions.In order to illustrate the proposed approach,the short-term reliability evaluation for a power station with different coal fired generating units is presented.

Science and technology innovation promotes realization of university education concept

In modem society, universities take on three main functions. Through science and technology innovation, it makes effort to create research achievements needed by society, promotes different modes of technology transfer to real productivity, and realize the mission of university for talent education and social service.

Probabilistic production simulation of a power system with wind power penetration based on improved UGF techniques

Universal Generating Function(UGF)techniques have been applied to Multi-State System(MSS)reliability analysis,such as long term reserve expansion of power systems with high wind power penetration.However,using simple steady-state distribution models for wind power and large generating units in reliability assessment can yield pessimistic appraisals.To more accurately assess the power system reliability,UGF techniques are extended to dynamic probabilistic simulation analysis on two aspects of modelling improvement.Firstly,a principal component analysis(PCA)combined with a hierarchal clustering algorithm is used to achieve the salient and time-varying patterns of wind power,then a sequential UGF equivalent model of wind power output is established by an apportioning method.Secondly,other than the traditional two-state models,the conventional generator UGF equivalent model is established as a four discrete-state continuous-time Markov model by Lztransform.In the construction process of such a UGF model,the state values are transformed into the integral multiples of one common factor by choosing proper common factors,thus effectively restraining the exponential growth of its state number and alleviating the explosion thereof.The method is suitable for reliability assessment with dynamic probabilistic distributed random variables.In addition,by acquiring the clustering information of wind power,the system reliability indices,such as fuel cost and CO_(2) emissions through different seasons and on different workdays,are calculated.Finally,the effectiveness of the method is verified by a modified IEEE-RTS 79 system integrated with several wind farms of historical hourly wind power data of Zhangbei wind farm in North China.

Construction of a key-dependent message secure symmetric encryption scheme in the ideal cipher model

Key-dependent message （KDM） security is an important security issue that has attracted much research in recent years. In this paper, we present a new construction of the symmetric encryption scheme in the the ideal cipher model （ICM）; we prove that our scheme is KDM secure against active attacks with respect to arbitrary polynomialtime challenge functions. Our main idea is to introduce a universal hash function （UHF） h as a random value for each encrypfion, and then use s = h（sk） as the key of the ideal cipher F, where sk is the private key of our symmetric encryption scheme. Although many other schemes that are secure against KDM attacks have already been proposed, in both the ideal standard models, the much more significance of our paper is the simplicity in which we implement KDM security against active attacks.