A recurrent neural network using historical data to predict time series indoor PM2.5 concentrations for residential buildings

Due to the severe outdoor PM2.5 pollution in China, many people have installed air-cleaning systems in homes. To make the systems run automatically and intelligently, we developed a recurrent neural network (RNN) that uses historical data to predict the future indoor PM2.5 concentration. The RNN architecture includes an autoencoder and a recurrent part. We used data measured in an apartment over the course of an entire year to train and test the RNN. The data include indoor/outdoor PM2.5 concentration, environmental parameters and time of day. By comparing three different input strategies, we found that a strategy employing historical PM2.5 and time of day as inputs performed best. With this strategy, the model can be applied to predict the relatively stable trend of indoor PM2.5 concentration in advance. When the input length is 2 h and the prediction horizon is 30 min, the median prediction error is 8.3 µg/m³ for the whole test set. For times with indoor PM2.5 concentrations between (20,50] µg/m³ and (50,100] µg/m³, the median prediction error is 8.3 and 9.2 µg/m³, respectively. The low prediction error between the ground-truth and predicted values shows that the RNN can predict indoor PM2.5 concentrations with satisfactory performance.     

Policy reforms and productivity change in the judiciary system: a cost function approach applied to time series of the Dutch judiciary system between 1980 and 2016

The judiciary is constantly undergoing change in order to respond to a wide range of social developments that have brought the sector under increasing pressure. In order to deal with the constant call for enhancing budgets, different policy measures have been taken to downsize the appeal to the judiciary and to improve productivity. One of the central questions hereby is whether these measures have actually contributed to a more productive sector. This paper focuses on the development of productivity in the judiciary and how policy measures have affected productivity. In this empirical analysis, we apply a cost function model to time series data of the Dutch judiciary between 1980 and 2016. The results show a dramatic decline of productivity over the entire period (?50%), in spite of various policy measures. The year 2001 can be regarded as a turning point, as since then productivity has remained more or less stable. It seems that this is largely due to the establishment of the Council for the Judiciary and the associated increase in (financial and operational) autonomy for the judiciary. Another striking result is that technical change is biased toward using more personnel through time.     

Fourier Analysis of Serial Dependence Measures

Classical spectral analysis is based on the discrete Fourier transform of the autocovariances. In this article we investigate the asymptotic properties of new frequency‐domain methods where the autocovariances in the spectral density are replaced by alternative dependence measures that can be estimated by U‐statistics. An interesting example is given by Kendall's τ, for which the limiting variance exhibits a surprising behavior.     

飞行时间二次离子质谱对矿物表面性质的研究

随着易选矿石的逐步枯竭,低品位、嵌布粒度细等难选矿石的开发利用已成必然趋势。目前,矿物加工已经从实践生产阶段发展到了理论研究指导实践生产的阶段,因此具有分辨率高、信息量大、灵敏快速以及样品用量少等特点的矿物表层研究方法来支撑理论研究是必不可少的。飞行时间二次离子质谱法(TOF-SIMS)是近年来在矿物加工中使用较多的一种矿物表面化学分析方法,具有表面质谱、化学成像、深度剖析、快速灵敏及数据精准的优点,因此总结归纳了近年来TOF-SIMS在矿物加工中应用取得的成果,以期为学者提供可靠的理论依据及技术支持。     

都市生长——基于“时间”的城市设计初探

文章通过对2014年马群地铁站城市设计课题的记录,试图探讨在城市设计学习中引入"时间"概念的意义和反思     

Designed damping controller for SSSC to improve stability of a hybrid offshore wind farms considering time delay

This paper presents the stability improvement results of hybrid doubly fed induction generator (DFIG)-based and permanent magnet generator (PMG)-based offshore wind farms (OWFs) using a static synchronous series compensator (SSSC). An adaptive-network-based fuzzy inference system (ANFIS) controller of the proposed SSSC is designed to render adequate damping characteristics to the studied system. A frequency-domain approach based on a linearized system model using eigenvalue technique analysis is performed. A time-domain scheme based on a nonlinear system model subject to a three-phase short circuit fault at infinite bus with variations in the signal transmission delays has also been investigated to compare the damping of the studied system in cases of with and without controller. The simulation results with MATLAB/SIMULINK toolbox have been presented. It can be concluded from the simulation results that the proposed SSSC joined with the designed ANFIS damping controller can offer adequate damping performance to the studied hybrid DFIG-based and PMG-based OWFs under severe disturbance.     

Fraud detection in registered electricity time series

This paper analyses time series without the seasonal component of consumers’ power consumption at low voltage in order to detect fraud and illogical consumption by customers. Statistical process control is used, where the process represents the process of using electricity. XMR charts are used to indicate major changes (decrease) in registered customers’ consumption. Verification of this method was tested on time series of a set of customers who were caught stealing during a time series. It shows that symptoms of non-random factors in time series of customers are revealed in a high percentage, which indirectly confirms the method’s ability to successfully detect electricity fraud.     

Reaction Kinetics of Ozone Gas in Green Gram (Vigna radiate)

This study was carried out to evaluate the reaction kinetics of ozone gas in different height (5 and 10 cm), moisture content (10.6 and 13.4% (d.b.)) and gas flow rate (2 and 4 L/min). The decomposition kinetics obtained was first-order model. As far as the half-life of ozone is considered, the highest value obtained was equivalent to 8.72 min for grains ozonated at 5 cm height, 10.6% (d.b.) moisture content and 2 L/min gas flow rate. In the process of ozone reaction rate in green gram grains, height (p < 0.01) and moisture content (p < 0.01) were found to be the key factor for the effectiveness of ozone fumigation.     

Testing local search move operators on the vehicle routing problem with split deliveries and time windows

The vehicle routing problem (VRP) is an important transportation problem. The literature addresses several extensions of this problem, including variants having delivery time windows associated with customers and variants allowing split deliveries to customers. The problem extension including both of these variations has received less attention in the literature. This research effort sheds further light on this problem. Specifically, this paper analyzes the effects of combinations of local search (LS) move operators commonly used on the VRP and its variants. We find when paired with a MAX-MIN Ant System constructive heuristic, Or-opt or 2-opt⁎ appear to be the ideal LS operators to employ on the VRP with split deliveries and time windows with Or-opt finding higher quality solutions and 2-opt⁎ requiring less run time.