Novel E2E-QoE Metric for PHY Optimization:A Cross-Layered Framework

Existing systems use key performance indicators(KPIs)as metrics for physical layer(PHY)optimization,which suffers from the problem of overoptimization,because some unnecessary PHY enhancements are imperceptible to terminal users and thus induce additional cost and energy waste.Therefore,it is necessary to utilize directly the quality of experience(QoE)of user as a metric of optimization,which can achieve the global optimum of QoE under cost and energy constraints.However,QoE is still a metric of application layer that cannot be easily used to design and optimize the PHY.To address this problem,we in this paper propose a novel end-to-end QoE(E2E-QoE)based optimization architecture at the user-side for the first time.Specifically,a cross-layer parameterized model is proposed to establish the relationship between PHY and E2E-QoE.Based on this,an E2E-QoE oriented PHY anomaly diagnosis method is further designed to locate the time and root cause of anomalies.Finally,we investigate to optimize the PHY algorithm directly based on the E2E-QoE.The proposed frameworks and algorithms are all validated using the data from real fifth-generation(5G)mobile system,which show that using E2E-QoE as the metric of PHY optimization is feasible and can outperform existing schemes.

Multi-objective Optimization of Co-cured Composite Laminates with Embedded Viscoelastic Damping Layer

Presented herein is a methodology for the multi-objective optimization of damping and bending stiffness of cocoured composite laminates with embedded viscoelastic damping layer. The embedded viscoelastic damping layer is perforated with a series of small holes, and the ratio of the perforation area to the total damping area is the design variable of the methodology. The multi-objective optimization is converted into a single-objective problem by an evaluation function which is a liner weigh sum of the two sub-objective functions. The proposed methodology was carried out to determine the optimal perforation area ratios of two viscoelstic layers with different perforation distance embedded in two composite plates. Both the optimal perforation area ratios are approximate to 2.2%. However, the objective value of the plate with greater perforation distance in embedded viscoelatic layer is much greater.

Optimization for sound insulation of a sandwich plate with a corrugation and auxetic honeycomb hybrid core

A sandwich plate with a corrugation and auxetic honeycomb hybrid core is constructed,and its sound insulation and optimization are investigated.First,the motion governing equation of the sandwich plate is established by the third-order shear deformation theory(TSDT),and then combined with the fluid-structure coupling conditions,and the sound insulation is solved.The theoretical results are validated by COMSOL simulation results,and the effects of the structural parameter on the sound insulation are analyzed.Finally,the standard genetic algorithm is adopted to optimize the sound insulation of the sandwich plate.

Interface optimization and defects suppression via Na F introduction enable efficient flexible Sb_(2)Se_(3) thin-film solar cells

Sb_(2)Se_(3) with unique one-dimensional(1D) crystal structure exhibits exceptional deformation tolerance,demonstrating great application potential in flexible devices.However,the power conversion efficiency(PCE) of flexible Sb_(2)Se_(3) photovoltaic devices is temporarily limited by the complicated intrinsic defects and the undesirable contact interfaces.Herein,a high-quality Sb_(2)Se_(3) absorber layer with large crystal grains and benign [hkl] growth orientation can be first prepared on a Mo foil substrate.Then NaF intermediate layer is introduced between Mo and Sb_(2)Se_(3),which can further optimize the growth of Sb_(2)Se_(3)thin film.Moreover,positive Na ion diffusion enables it to dramatically lower barrier height at the back contact interface and passivate harmful defects at both bulk and heterojunction.As a result,the champion substrate structured Mo-foil/Mo/NaF/Sb_(2)Se_(3)/CdS/ITO/Ag flexible thin-film solar cell delivers an obviously higher efficiency of 8.03% and a record open-circuit voltage(V_(OC)) of 0.492 V.This flexible Sb_(2)Se_(3) device also exhibits excellent stability and flexibility to stand large bending radius and multiple bending times,as well as superior weak light photo-response with derived efficiency of 12.60%.This work presents an effective strategy to enhance the flexible Sb_(2)Se_(3) device performance and expand its potential photovoltaic applications.

Security-Reliability Analysis and Optimization for Cognitive Two-Way Relay Network with Energy Harvesting

This paper investigates the security and reliability of information transmission within an underlay wiretap energy harvesting cognitive two-way relay network.In the network,energy-constrained secondary network(SN)nodes harvest energy from radio frequency signals of a multi-antenna power beacon.Two SN sources exchange their messages via a SN decode-and-forward relay in the presence of a multiantenna eavesdropper by using a four-phase time division broadcast protocol,and the hardware impairments of SN nodes and eavesdropper are modeled.To alleviate eavesdropping attacks,the artificial noise is applied by SN nodes.The physical layer security performance of SN is analyzed and evaluated by the exact closed-form expressions of outage probability(OP),intercept probability(IP),and OP+IP over quasistatic Rayleigh fading channel.Additionally,due to the complexity of OP+IP expression,a self-adaptive chaotic quantum particle swarm optimization-based resource allocation algorithm is proposed to jointly optimize energy harvesting ratio and power allocation factor,which can achieve security-reliability tradeoff for SN.Extensive simulations demonstrate the correctness of theoretical analysis and the effectiveness of the proposed optimization algorithm.

Optimization methods of production layer combination for coalbed methane development in multi-coal seams

Based on the productivity equation of coalbed methane(CBM) wells, three indexes, main production layer optimization index, main production layer expansion index and capacity contribution index are proposed, with which the three-step optimization method of production-layer combination is established. In selecting main production layer, the coal seam thickness, CBM content, coal seam permeability, coal seam reservoir pressure and coal structure are considered comprehensively to evaluate the potential of the production layer. In selecting expansion of the main production layer combination, on the premise of ensuring full and slow desorption of the main production layer and non-exposure of the main production layer out of liquid surface, the degree of mutual interference between the main and non-main production layers is comprehensively evaluated by coupling the critical desorption pressure, layer spacing and reservoir pressure gradient difference. In optimizing production layer combination, the main concern is the economic efficiency of the combined layers. Only when the contribution coefficient of the main production layer is greater than 30% and the contribution index of the other production layers is more than 10%, the economic benefit of a CBM well after being put into production can be ensured. Based on the comparative analysis of the development effect of the development test wells in Songhe of Guizhou province, it is proved that the "three-step method" for the optimization of production-layer combination is scientific and practical, and can be used to design the multi-layer commingling scheme of coalbed methane.

System optimization-oriented spare parts dynamic configuration model for multi-echelon multi-indenture system

In order to optimize the spares configuration project at different stages during the life cycle, the factor of time is considered to relax the assumption of the spares steady demand in multi-echelon technique for recoverable item control (METRIC) theory. According to the method of systems analysis, the dynamic palm theorem is introduced to establish the prediction model of the spares demand rate, and its main influence factors are analyzed, based on which, the spares support effectiveness evaluation index system is studied, and the system optimization-oriented spares dynamic configuration method for multi-echelon multi-indenture system is proposed. Through the analysis of the optimization algorithm, the layered marginal algorithm is designed to improve the model calculation efficiency. In a given example, the multi-stage spares configuration project during its life cycle is gotten, the research result conforms to the actual status, and it can provide a new way for the spares dynamic optimization.

A Uniaxial Optimal Perfectly Matched Layer Method for Time-harmonic Scattering Problems

We develop a uniaxial optimal perfectly matched layer （opt PML） method for solving the time-harmonic scattering problems by choosing a particular absorbing function with unbounded integral in a rectangular domain. With this choice, the solution of the optimal PML problem not only converges exponentially to the solution of the original scatting problem, but also is insensitive to the thickness of the PML layer for sufficiently small parameter ε0. Numerical experiments are included to illustrate the competitive behavior of the proposed optimal method.

Optimization of Composite Wind Turbine Blade Based on Modal Sensitivity

This study develops a method for the full-size structural design of blade,involving the optimal layer thickness configuration of the blade to maximize its bending stiffness using a genetic algorithm.Numerical differentiation is employed to solve the sensitivity of blade modal frequency to the layer thickness of each part of blade.The natural frequencies of first-order flapwise and edgewise modes are selected as the optimal objectives.Based on the modal sensitivity analysis of all design variables,the effect of discretized layer thickness on bending stiffness of the blade is explored,and 14 significant design variables are filtered to drive the structural optimization.The best solution predicts an increase in natural frequencies of first-order flapwise and edgewise blade modes by up to 12%and 10.4%,respectively.The results show that the structural optimization method based on modal sensitivity is more effective to improve the structural performance.

MAC-PHY Cross-Layer for High Channel Capacity of Multiple-Hop MIMO Relay System

For the high end-to-end channel capacity, the amplify-and-forward scheme multiple-hop MIMO relays system is considered. The distance between each transceiver is optimized to prevent some relays from being the bottleneck and guarantee the high end-to-end channel capacity. However, in some cases, the location of relays can’t be set at the desired location, the transmit power of each relay should be optimized. Additionally, in order to achieve the higher end-to-end channel capacity, the distance and the transmit power are optimized simultaneously. We propose the Markov Chain Monte Carlo method to optimize both the distance and the transmit power in complex propagation environments. Moreover, when the system has no control over transmission of each relay, the interference signal is presented and the performance of system is deteriorated. The general protocol of control transmission for each relay on the MAC layer is analyzed and compared to the Carrier Sense Multiple Access-Collision Avoidance protocol. According to the number of relays, the Mac layer protocol for the highest end-to-end channel capacity is changed. We also analyze the end-to-end channel capacity when the number of antennas and relays tends to infinity.

Optimal Homotopy Analysis of MHD Natural Convection Flow of Thixotropic Fluid under Subjection of Thermal Stratification: Boundary Layer Analysis

In this article, the model of a non-Newtonian fluid (Thixotropic) flow past a vertical surface in the presence of exponential space and temperature dependent heat source in a thermally stratified medium is studied. It is assumed that free convection is induced by buoyancy and exponentially decaying internal heat source across the space. The dynamic viscosity is taken to be constant and thermal conductivity of this particular fluid model is assumed to vary linearly with temperature. Thermal stratification has been properly incorporated into the governing equation so that its effect can be revealed and properly reported. The governing partial differential equations describing the model are transformed and parameterized to a system of non-linear ordinary differential equation using similarity transformations. Approximate analytic solutions were obtained by adopting Optimal Homotopy Analysis Method (OHAM). The results show that for both cases of non-Newtonian parameters (Thixotropic) (K1=K2=0?& K1=K2=1.0), increasing stratification parameters, relate to decreasing in the heat energy entering into the fluid region and thus reducing the temperature of the Thixotropic fluid as it flows.

Study of Temperature Field and Structure Optimization for Runways in Permafrost Regions

Pavement construction in permafrost regions is complicated by the fact that the permafrost properties are influenced by the temperature and are extremely unstable.The numerical model for runway structures in permafrost regions is applied to analyze the time–space characteristics of the temperature field and the depth of the frozen layer.The influence of the installation layer is studied to enable structural optimization of the runway.Numerical results show that the temperature stabilization depth,low-and high-temperature interlayer response ranges,and maximum depth of the frozen layer are greater in runway engineering than in highway and railway engineering.The time history curves for the pavement and natural surface are similar,and the development of freezing and thawing is approximately linear.The pavement and natural surface have similar thawing rates,but the freezing rate of the natural surface is faster than that of the pavement.The depth of the frozen layer and the time of the frozen are greater for the natural surface than for the pavement.The installation layer helps to stabilize the temperature of the subgrade and reduces the freezing and thawing rates.This study provides technical support for the design and maintenance of runways in permafrost regions.

Extreme learning with chemical reaction optimization for stock volatility prediction

Extreme learning machine(ELM)allows for fast learning and better generalization performance than conventional gradient-based learning.However,the possible inclusion of non-optimal weight and bias due to random selection and the need for more hidden neurons adversely influence network usability.Further,choosing the optimal number of hidden nodes for a network usually requires intensive human intervention,which may lead to an ill-conditioned situation.In this context,chemical reaction optimization(CRO)is a meta-heuristic paradigm with increased success in a large number of application areas.It is characterized by faster convergence capability and requires fewer tunable parameters.This study develops a learning framework combining the advantages of ELM and CRO,called extreme learning with chemical reaction optimization(ELCRO).ELCRO simultaneously optimizes the weight and bias vector and number of hidden neurons of a single layer feed-forward neural network without compromising prediction accuracy.We evaluate its performance by predicting the daily volatility and closing prices of BSE indices.Additionally,its performance is compared with three other similarly developed models—ELM based on particle swarm optimization,genetic algorithm,and gradient descent—and find the performance of the proposed algorithm superior.Wilcoxon signed-rank and Diebold–Mariano tests are then conducted to verify the statistical significance of the proposed model.Hence,this model can be used as a promising tool for financial forecasting.

Finding optimal Bayesian networks by a layered learning method

It is unpractical to learn the optimal structure of a big Bayesian network(BN)by exhausting the feasible structures,since the number of feasible structures is super exponential on the number of nodes.This paper proposes an approach to layer nodes of a BN by using the conditional independence testing.The parents of a node layer only belong to the layer,or layers who have priority over the layer.When a set of nodes has been layered,the number of feasible structures over the nodes can be remarkably reduced,which makes it possible to learn optimal BN structures for bigger sizes of nodes by accurate algorithms.Integrating the dynamic programming(DP)algorithm with the layering approach,we propose a hybrid algorithm—layered optimal learning(LOL)to learn BN structures.Benefitted by the layering approach,the complexity of the DP algorithm reduces to O(ρ2^n?1)from O(n2^n?1),whereρ<n.Meanwhile,the memory requirements for storing intermediate results are limited to O(C k#/k#^2 )from O(Cn/n^2 ),where k#<n.A case study on learning a standard BN with 50 nodes is conducted.The results demonstrate the superiority of the LOL algorithm,with respect to the Bayesian information criterion(BIC)score criterion,over the hill-climbing,max-min hill-climbing,PC,and three-phrase dependency analysis algorithms.

Design of multi-layered porous fibrous metals for optimal sound absorption in the low frequency range

We present a design method for calculating and optimizing sound absorption coefficient of multi-layered porous fibrous metals （PFM） in the low frequency range. PFM is simplified as an equivalent idealized sheet with all metallic fibers aligned in one direction and distributed in periodic hexagonal patterns. We use a phenomenological model in the literature to investigate the effects of pore geometrical parameters （fiber diameter and gap） on sound absorption performance. The sound absorption coefficient of multi- layered PFMs is calculated using impedance translation theorem, To demonstrate the validity of the present model, we compare the predicted results with the experimental data. With the average sound absorption （low frequency range） as the objective function and the fiber gaps as the design variables, an optimization method for multi-layered fibrous metals is proposed. A new fibrous layout with given porosity of multi-layered fibrous metals is suggested to achieve optimal low frequency sound absorption. The sound absorption coefficient of the optimal multi-layered fibrous metal is higher than the single- layered fibrous metal, and a significant effect of the fibrous material on sound absorption is found due to the surface Dorosity of the multi-layered fibrous.

Influence of layer thickness on formation quality,microstructure,mechanical properties,and corrosion resistance of WE43 magnesium alloy fabricated by laser powder bed fusion

Laser powder bed fusion(L-PBF)of Mg alloys has provided tremendous opportunities for customized production of aeronautical and medical parts.Layer thickness(LT)is of great significance to the L-PBF process but has not been studied for Mg alloys.In this study,WE43 Mg alloy bulk cubes,porous scaffolds,and thin walls with layer thicknesses of 10,20,30,and 40μm were fabricated.The required laser energy input increased with increasing layer thickness and was different for the bulk cubes and porous scaffolds.Porosity tended to occur at the connection joints in porous scaffolds for LT40 and could be eliminated by reducing the laser energy input.For thin wall parts,a large overhang angle or a small wall thickness resulted in porosity when a large layer thicknesses was used,and the porosity disappeared by reducing the layer thickness or laser energy input.A deeper keyhole penetration was found in all occasions with porosity,explaining the influence of layer thickness,geometrical structure,and laser energy input on the porosity.All the samples achieved a high fusion quality with a relative density of over 99.5%using the optimized laser energy input.The increased layer thickness resulted to more precipitation phases,finer grain sizes and decreased grain texture.With the similar high fusion quality,the tensile strength and elongation of bulk samples were significantly improved from 257 MPa and 1.41%with the 10μm layer to 287 MPa and 15.12%with the 40μm layer,in accordance with the microstructural change.The effect of layer thickness on the compressive properties of porous scaffolds was limited.However,the corrosion rate of bulk samples accelerated with increasing the layer thickness,mainly attributed to the increased number of precipitation phases.

Coordinating optimization-based sliding mode variable structure control for electro-hydraulic servo system

A sliding mode variable structure control （SMVSC） based on a coordinating optimization algorithm has been developed. Steady state error and control switching frequency are used to constitute the system performance indexes in the coordinating optimization, while the tuning rate of boundary layer width （BLW） is employed as the optimization parameter. Based on the mathematical relationship between the BLW and steady-state error, an optimized BLW tuning rate is added to the nonlinear control term of SMVSC. Simulation experiment results applied to the positioning control of an electro-hydraulic servo system show the comprehensive superiority in dynamical and static state performance by using the proposed controller is better than that by using SMVSC without optimized BLW tuning rate. This succeeds in coordinately considering both chattering reduction and high-precision control realization in SMVSC.

Joint Optimization Scheme for the Reconfigurable Intelligent Surface-Assisted Untrusted Relay Networks

To further improve the secrecy rate,a joint optimization scheme for the reconfigurable intelligent surface(RIS)phase shift and the power allocation is proposed in the untrusted relay(UR)networks assisted by the RIS.The eavesdropping on the UR is interfered by a source-based jamming strategy.Under the constraints of unit modulus and total power,the RIS phase shift,the power allocation between the confidential signal and the jamming signal,and the power allocation between the source node and the UR are jointly optimized to maximize the secrecy rate.The complex multivariable coupling problem is decomposed into three sub-problems,and the non-convexity of the objective function and the constraints is solved with semi-definite relaxation.Simulation results indicate that the secrecy rate is remarkably enhanced with the proposed scheme compared with the equal power allocation scheme,the random phase shift scheme,and the no-RIS scheme.

Joint optimization for secure ambient backscatter communication in NOMA-enabled IoT networks

Non-Orthogonal Multiple Access(NOMA)has emerged as a novel air interface technology for massive connectivity in Sixth-Generation(6G)era.The recent integration of NOMA in Backscatter Communication(BC)has triggered significant research interest due to its applications in low-powered Internet of Things(IoT)networks.However,the link security aspect of these networks has not been well investigated.This article provides a new optimization framework for improving the physical layer security of the NOMA ambient BC system.Our system model takes into account the simultaneous operation of NOMA IoT users and the Backscatter Node(BN)in the presence of multiple EavesDroppers(EDs).The EDs in the surrounding area can overhear the communication of Base Station(BS)and BN due to the wireless broadcast transmission.Thus,the chief aim is to enhance link security by optimizing the BN reflection coefficient and BS transmit power.To gauge the performance of the proposed scheme,we also present the suboptimal NOMA and conventional orthogonal multiple access as benchmark schemes.Monte Carlo simulation results demonstrate the superiority of the NOMA BC scheme over the pure NOMA scheme without the BC and conventional orthogonal multiple access schemes in terms of system secrecy rate.

Optimization of DC Resistance Divider Up to 1200 kV Using Thermal and Electric Field Analysis

Self-heating and electric field distribution are the primary factors affecting the accuracy of the Ultra High Voltage Direct Current(UHVDC)resistive divider.Reducing the internal temperature rise of the voltage divider caused by self-heating,reducing the maximum electric field strength of the voltage divider,and uniform electric field distribution can effectively improve the UHVDC resistive divider’s accuracy.In this paper,thermal analysis and electric field distribution optimization design of 1200 kV UHVDC resistive divider are carried out:(1)Using the proposed iterative algorithm,the heat dissipation and temperature distribution of the high voltage DC resistive divider are studied,and the influence of the ambient temperature and the power of the divider on the temperature of the insulating medium of the divider is analyzed;(2)Established the finite element models of 1200 kV and 2×600 kV DC resistive dividers,analyzed the influence of the size of the grading ring and the installation position on the maximum electric field strength of the voltage divider,and calculated the impact of the shielding resistor layer on the vicinity of the measuring resistor layer.The research indicates that:(1)The temperature of the insulating medium is linearly related to the horsepower of the voltage divider and the ambient temperature;(2)After the optimized design of the electric field,the maximum electric field strength of the 1200 kV DC resistive divider is reduced to 1471 V/mm,which is about 24% lower than that of the unoptimized design;(3)Installing the shielding resistor layer can significantly improve the electric field near the measuring resistor layer.This paper has an important reference function for improving the accuracy of the UHVDC resistive divider.