Bayesian and Non-Bayesian Analysis for the Sine Generalized Linear Exponential Model under Progressively Censored Data

This article introduces a novel variant of the generalized linear exponential(GLE)distribution,known as the sine generalized linear exponential(SGLE)distribution.The SGLE distribution utilizes the sine transformation to enhance its capabilities.The updated distribution is very adaptable and may be efficiently used in the modeling of survival data and dependability issues.The suggested model incorporates a hazard rate function(HRF)that may display a rising,J-shaped,or bathtub form,depending on its unique characteristics.This model includes many well-known lifespan distributions as separate sub-models.The suggested model is accompanied with a range of statistical features.The model parameters are examined using the techniques of maximum likelihood and Bayesian estimation using progressively censored data.In order to evaluate the effectiveness of these techniques,we provide a set of simulated data for testing purposes.The relevance of the newly presented model is shown via two real-world dataset applications,highlighting its superiority over other respected similar models.

Design, Construction and Ocean Testing of Wave Energy Conversion System with Permanent Magnet Tubular Linear Generator

In this paper, the design, construction and ocean testing of a wave energy conversion system are studied. Based on the motion characteristics of double buoys in ocean waves, a wave energy conversion system with permanent magnet tubular linear generator （PMTLG） is proposed to convert ocean wave energy into electricity. The wave energy conversion system was installed in the Yellow Sea near Lianyungang, China. The ocean test re- suits indicate that it had dynamic and static performance, and obtained an expected amount of electricity. The calcu- lation result indicates the average output power was about 1 000 W, and the conversion efficiency from wave en- ergy into electricity was 1.4%. In addition, the wireless data communication, mechanics and oceanography were also discussed.

Research on Coupling Transfer Characteristics of Vibration Energy of Free Piston Linear Generator

In order to clarify the mechanism and main influencing factors of the vibration energy coupling transmission with a dual-piston structure,a thermodynamic and dynamic coupling model of the free piston linear generator(FPLG)was established.The system energy conversion,vibration energy coupling transmission,and influencing factors were studied in detail.The coupling transmission paths and the secondary influence mechanism from in-cylinder combustion on vibration energy transmission were obtained.In addition,the influence of the movement characteristics of the dual-piston on the vibration energy transmission was studied,and the typical parameter variation law was obtained,which provides theoretical guidance for the subsequent vibration reduction design of the FPLG.

Generating Electricity from Mechanical Vibrations:Optimization of Linear a Generator

Energy preservation is one of the key components in developing eco-friendly machines.In industry,the majority of machines lose a considerable amount of energy through mechanical vibrations.However,the wasted energy through vibration can be utilized as a renewable energy source to compensate for the overall energy loss.The research work presented in this paper discusses the ability to design a linear power generator utilizing Nd Fe-B magnets,which can generate energy through mechanical vibrations.A pilot model was developed and simulated to understand the efficiency and limitation.The results showed that the model could reduce 14% rotor bulk with a marginal impact on the current generation.

Starting Control of Free Piston Stirling Linear Generator System Based on FOC

Aiming at the problem of poor system dynamic performance caused by low parameter matching in the coordinated control of Stirling engine and linear generator in the starting stage control of free piston Stirling linear generator system,a joint control method of free piston Stirling permanent magnet synchronous linear generator system based on field orientation control is proposed,based on the theoretical derivation of the mathematical model of the system and the principle of controller parameters setting,the simulation experiments of the system starting stage under several Stirling engine working conditions are carried out under simulation.The experimental results show that the stability and rapidity of the system are improved,and the dynamic response speed of generator parameters under different working conditions is accelerated,what fully verifies the correctness and effectiveness of the method.It provides an effective way to improve the control performance of the system and stabilize the power generation operation.

Linear Generator Used in Hybrid System Solar Biomass

The aim of this paper is to present the linear generator （Stirling solar dish） in the context of a HSSB （hybrid system solar biomass）, project P ＆ D （research and development P ＆ D 0041, in cooperation and partnership with CPFL--LIght and Force Paulista Company-Campinas, Piratininga, S.P. Brazil）. The other components of the system will be the solar ORC （organic Rankine cycle）, the rotary Stifling and the biomass gasifier. The integration of the complete system will be described in the paper, and is projected to be hydraulic one.

Time Series-, Time-Frequency- and Spectral Analyses of Sensor Measurements in an Offshore Wave Energy Converter Based on Linear Generator Technology

Inside the second experimental wave energy converter (WEC) launched at the Lysekil research site on the Swedish west coast in March 2009 a number of sensor systems were installed for measuring the mechanical performance of the WEC and its mechanical subsystems. One of the measurement systems was a set-up of 7 laser triangulation sensors for measuring relative displacement of the piston rod mechanical lead-through transmission in the direct drive. Two measurement periods, separated by 2.5 month, are presented in this paper. One measurement is made two weeks after launch and another 3 months after launch. Comparisons and correlations are made between different sensors measuring simultaneously. Noise levels are investigated. Filtering is discussed for further refinement of the laser triangulation sensor signals in order to separate noise from actual physical displacement and vibration. Measurements are presented from the relative displacement of the piston rod mechanical lead-through, from magnetic flux in the air gap, mechanical strain in the WEC structure, translator position and piston rod axial displacement and active AC power. Investigation into the measurements in the time domain with close-ups, in the frequency domain with Fast Fourier transform (FFT) and with time-frequency analysis with short time Fourier transform (STFT) is carried out to map the spectral content in the measurements. End stop impact is clearly visible in the time-frequency analysis. The FFT magnitude spectra are investigated for identifying the cogging bandwidth among other vibrations. Generator cogging, fluctuations in the damping force and in the Lorenz forces in the stator are distinguished and varies depending on translator speed. Vibrations from cogging seem to be present in the early measurement period while not so prominent in the late measurement period. Vibration frequencies due to wear are recognized by comparing with the noise at generator standstill and the vibration sources in the generator. It is concluded that a moving average is a sufficient filter in the time domain for further analysis of the relative displacement of the piston rod mechanical lead-through transmission.

Prediction of the Inductance in a Synchronous Linear Permanent Magnet Generator

This paper presents calculations of the varying inductances profile for a synchronous linear surface mounted permanent magnet generator in an ABC reference system. Calculations are performed by utilizing the reluctance term, known from analytic calculations and finite element method simulations. With the inductance term identified, the voltage difference between the generator’s no load and load voltage can be calculated and an external circuit can be designed for optimal use of the generator. Two different operation intervals of the linear generator are considered and the results are discussed. The result indicates that time costly finite element simulations can be replaced with simple analytical calculations for a surface mounted permanent magnet linear generator.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Generalized linear joint PP-PS inversion based on two constraints

Conventional joint PP-PS inversion is based on approximations of the Zoeppritz equations and assumes constant VP/VS;therefore,the inversion precision and stability cannot satisfy current exploration requirements.We propose a joint PP-PS inversion method based on the exact Zoeppritz equations that combines Bayesian statistics and generalized linear inversion.A forward model based on the exact Zoeppritz equations is built to minimize the error of the approximations in the large-angle data,the prior distribution of the model parameters is added as a regularization item to decrease the ill-posed nature of the inversion,low-frequency constraints are introduced to stabilize the low-frequency data and improve robustness,and a fast algorithm is used to solve the objective function while minimizing the computational load.The proposed method has superior antinoising properties and well reproduces real data.

Yttrium cuprates modification in linear generator application for power generation

Yttrium barium copper oxide(YBCO)is used for special applications in linear generators because of its excitation loss,lower weight,and higher efficiency.These qualities enable the compound to operate better than the conventional copper wire coil in the stator unit of the linear generator.However,the continuous use of YBCO in linear generators has a fundamental challenge that affects industrial production and material stability after prolonged use.This paper seeks to sustain the adoption of YBCO by improving its quality for linear generator applications.The yttrium cuprates modification(YBYbCO)was synthesized using the solid-state reaction technique by doping YBCO with ytterbium.The crystalline structure,microstructural pattern,and stability of the new sample were adequately measured and found to be structurally stable to ensure durability.It was reported that applyingYBYbCO in the linear generator would lead to a 200%increase in energy generation.The higher number of particles and lower individual particulate resistance enable it to withstand chemical pressure,thereby prolonging the lifespan of the linear generator.

Prediction and driving factors of forest fire occurrence in Jilin Province,China

Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.

Numerical Simulation of a Spark Ignited Two-Stroke Free-Piston Engine Generator

A numerical program is built to simulate the performance of a spark ignited two-stroke free-piston engine coupled with a linear generator. The computational model combines a series of dynamic and thermodynamic equations that are solved simultaneously to predict the performances of the engines. The dynamic analysis performed consists of an evaluation of the frictional force and load force introduced by the generator. The thermodynamic analysis used a single zone model to describe the engine＇ s working cycle which includes intake, scavenging, compression, combustion and expansion, and to evaluate the effect of heat transfer based on the first law of thermodynamics and the ideal gas state equation. Because there is no crankshaft, a time based Wiebe equation was used to express the fraction of fuel burned in the combustion. The calculated results were validated by using the experimental data from another research group. The results indicate that the free-piston generator has some advantages over conventional engines.

A New Type of Solution Method for the Generalized Linear Complementarity Problem over a Polyhedral Cone

This paper addresses the generalized linear complementarity problem （GLCP） over a polyhedral cone. To solve the problem, we first equivalently convert the problem into an affine variational inequalities problem over a closed polyhedral cone, and then propose a new type of method to solve the GLCP based on the error bound estimation. The global and R-linear convergence rate is established. The numerical experiments show the efficiency of the method.

Some inequalities for the generalized linear distortion function

In this paper, we establish several inequalities for the the generalized linear distortion function λ（a, K） by using the monotonicity and convexity of certain combinations λ（a, K）.

A New Conjugate Gradient Projection Method for Solving Stochastic Generalized Linear Complementarity Problems

In this paper, a class of the stochastic generalized linear complementarity problems with finitely many elements is proposed for the first time. Based on the Fischer-Burmeister function, a new conjugate gradient projection method is given for solving the stochastic generalized linear complementarity problems. The global convergence of the conjugate gradient projection method is proved and the related numerical results are also reported.

Preconditioned iterative methods for solving weighted linear least squares problems

A class of preconditioned iterative methods, i.e., preconditioned generalized accelerated overrelaxation （GAOR） methods, is proposed to solve linear systems based on a class of weighted linear least squares problems. The convergence and comparison results are obtained. The comparison results show that the convergence rate of the preconditioned iterative methods is better than that of the original methods. Furthermore, the effectiveness of the proposed methods is shown in the numerical experiment.

Noether's theory of generalized linear nonholonomic mechanical systems

By introducing the quasi-symmetry of the infinitesimal transformation of the transformation group Gr, the Noether＇s theorem and the Noether＇s inverse theorem for generalized linear nonholonomic mechanical systems are obtained in a generalized compound derivative space. An example is given to illustrate the application of the result.

Temporal Statistical Downscaling of Precipitation and Temperature Forecasts Using a Stochastic Weather Generator

Statistical downscaling is based on the fact that the large-scale climatic state and regional/local physiographic features control the regional climate. In the present paper, a stochastic weather generator is applied to seasonal precipitation and temperature forecasts produced by the International Research Institute for Climate and Society （IRI）. In conjunction with the GLM （generalized linear modeling） weather generator, a resampling scheme is used to translate the uncertainty in the seasonal forecasts （the IRI format only specifies probabilities for three categories： below normal, near normal, and above normal） into the corresponding uncertainty for the daily weather statistics. The method is able to generate potentially useful shifts in the probability distributions of seasonally aggregated precipitation and minimum and maximum temperature, as well as more meaningful daily weather statistics for crop yields, such as the number of dry days and the amount of precipitation on wet days. The approach is extended to the case of climate change scenarios, treating a hypothetical return to a previously observed drier regime in the Pampas.

Asymptotic Normality of Multi-Dimension Quasi Maximum Likelihood Estimate in Generalized Linear Models withAdaptive Design

We study the quasi likelihood equation in Generalized Linear Models（GLM） with adaptive design ∑（i=1）^n xi（yi-h（x＇iβ））=0, where yi is a q=vector, and xi is a p×q random matrix. Under some assumptions, it is shown that the Quasi- Likelihood equation for the GLM has a solution which is asymptotic normal.