75kW中频感应加热电源的研制

针对中频感应加热电源对油田油井加热问题,本文采用PWM控制技术实现了功率可调。为使系统的功率因数较高,采用串联谐振和频率跟踪技术。中频感应加热电源采用IGBT作为开关器件,可工作在10 Hz-10 kHz频段。它充分利用中频趋肤效应、邻近效应和圆环效应原理,通过感应加热器和油管柱,使电能有效的转化为热能,从而达到原油降粘降稠、稳产高产的目的。     

基于MATLAB提高Pt100测温系统响应速度的研究

通过对外加保护铜套的Pt100测温系统的实验研究,利用MATLAB建立了该系统对温度输入响应的数学模型,并通过合理增设串联相位超前校正网络提高了Pt100测温系统的响应速度。对于不同组成的Pt100测温系统,可选择不同的串联相位超前校正装置参数实现响应速度的提高。     

Personality and older consumers’ green behaviour in the UK

The UK government has set an ambitious target of reducing greenhouse gas emissions by 80% before 2050. An interesting segment that could help to achieve this is older consumers, due to their growing numbers. There seems to be a lack of attention, in the research looking specifically at different age categories of older consumers’ green behaviour, and whether their level of greenness can be explained by their personality. Using Socioemotional Selectivity Theory and Time Perspective, the research presented here was designed to provide an exploratory analysis of how the green behaviour of older consumers is explained by their personality types. Based on the responses of 204 older consumers in the UK, our results find the openness personality trait to be positively linked to green behaviour, whilst the extraversion personality trait is negatively related to green behaviour. Although the level of green behaviour increased with older consumers’ age, this did not reach significance.     

Forecasting accuracy evaluation of tourist arrivals

This paper evaluates the use of several parametric and nonparametric forecasting techniques for predicting tourism demand in selected European countries. We find that no single model can provide the best forecasts for any of the countries in the short-, medium- and long-run. The results, which are tested for statistical significance, enable forecasters to choose the most suitable model (from those evaluated here) based on the country and horizon for forecasting tourism demand. Should a single model be of interest, then, across all selected countries and horizons the Recurrent Singular Spectrum Analysis model is found to be the most efficient based on lowest overall forecasting error. Neural Networks and ARFIMA are found to be the worst performing models.     

Assessing efficiency and investment opportunities in commodities: A time series and portfolio simulations approach

This paper investigates the informational efficiency hypothesis in the short and long term for four major commodity markets (oil, gas, electricity, and coal) from January 1997 to January 2016. Unlike previous studies, we provide a more concise comparative analysis by focusing on different classes of commodities for a large sample, including 5 developed and 3 emerging regions and covering 46 countries. We apply different parametric and non-parametric econometric tests. Our study provides two interesting findings. First, we show that commodity markets are informationally inefficient in the short term. Our portfolio simulations highlight that commodities might provide “good” investment opportunities, but those opportunities vary according to commodity class and regions. Second, we show that most commodity markets become informationally efficient in the long term, thereby reducing investors' interest for the duration. Thus, commodity markets might be used to hedge investor’s portfolios, particularly for speculators and chartists in the short term, while these investments might not be appealing in these markets in the long term.     

Solving the income fluctuation problem with unbounded rewards

This paper studies the income fluctuation problem without imposing bounds on utility, assets, income or consumption. We prove that the Coleman operator is a contraction mapping over the natural class of candidate consumption policies when endowed with a metric that evaluates consumption differences in terms of marginal utility. We show that this metric is complete, and that the fixed point of the operator coincides with the unique optimal policy. As a consequence, even in this unbounded setting, policy function iteration always converges to the optimal policy at a geometric rate.     

A critical overview of privacy-preserving approaches for collaborative forecasting

Cooperation between different data owners may lead to an improvement in forecast quality—for instance, by benefiting from spatiotemporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection concerns, however, said data owners might be unwilling to share their data. Interest in collaborative privacy-preserving forecasting is thus increasing. This paper analyzes the state-of-the-art and unveils several shortcomings of existing methods in guaranteeing data privacy when employing vector autoregressive models. The methods are divided into three groups: data transformation, secure multi-party computations, and decomposition methods. The analysis shows that state-of-the-art techniques have limitations in preserving data privacy, such as (i) the necessary trade-off between privacy and forecasting accuracy, empirically evaluated through simulations and real-world experiments based on solar data; and (ii) iterative model fitting processes, which reveal data after a number of iterations.     

基于泰勒公式的交错级数审敛准则的改进

本文利用泰勒公式,对文献[2]中交错级数的一种收敛准则给出了新的证明,并将此准则进行了改进,使其可以应用于由复合函数构成的更复杂的级数形式。     

Time,space and accounting at Nonantola Abbey (1350–1449)

Accounting historians have provided several accounts of monastic life and accounting's role in it, considering important settings such as Montecassino and San Pietro abbeys in Italy and Durham Cathedral Priory in England. Research has shown how their governance arrangements and common values enabled the Benedictines to manage their monasteries in an efficient manner which was essential in tackling the misappropriation of resources by organisational actors, including abbots. Other studies have shed light on the use of practical and effective accounting practices by the Benedictines to manage their considerable wealth and pursue their spiritual and temporal goals. Nevertheless, this body of literature is yet to explicitly consider the dimensions of time and space and their relationship with accounting practices. This study begins to address this oversight by analysing the surviving accounting records of the Benedictine abbey of Nonantola in northern Italy from 1350 to 1449. In the accounting books of Nonantola Abbey linear and cyclical conceptions of time coexisted and had an impact on the way in which transactions were reflected in the accounts. At the same time, the abbey was at the centre of a complex network of accountabilities which included lay accountants, farmers and the lessees of the abbey's properties. The main characteristic of this system was not the accuracy of the records in detailing the assets, liabilities, expenses and revenue of the abbey but the maintenance of a control system to administer an extensive agricultural network and the identification of the relationships between the abbey and the stakeholders inhabiting its space.