I will report on a study of the usefulness of ARMA time scale algorithms to synchronize clocks on a digital network. The algorithm acquires periodic time differences between a local system clock and a remote time server by means of any of the standard message formats such as the format used by the Network Time Protocol. It models the current time difference as a linear combination of previous t...

Diarrhoea is still a considerable public-health problem in developing countries, especially among children aged less than five years. The well-known relationship between seasonal variation and aetiological agents of diarrhoeal diseases helps inform the decisions about the prevention and control measures. The aim of this study was to identify the temporal patterns of deaths due to diarrhoea in c...

It is an important issue to study the prediction precision of Particulate Matter 2.5, PM2.5 (28 μg/m3), concentration change. The concentration of PM2.5 is influenced by many factors, and its change is characterized by non-linearity and randomness. This paper establishes a prediction model of PM2.5 concentration change to fit the nonlinear and random trend by combining Auto-Regressive Integrate...

This paper presents a new method of self-sensing both of the displacement and the external applied force at the tip of piezoelectric cantilevers. Integrated electric current across piezoelectric actuators is compensated against material nonlinearities (creep, hysteresis) to provide reliable information. We propose to compensate the hysteresis by using the Prandtl-Ishlinskii static approach whil...

One of the most natural and primary ways of data collection in wireless sensor networks is to periodically report sensed data values from sensor node to aggregator. However, this kind of data collection mechanism comes at the cost of power consumption and packet collision. In this paper, we developed an automatic ARIMA (Auto Regressive Integrated Moving Average) modeling based data aggregation ...

A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on ...

OBJECTIVE To evaluate the effectiveness of an adherence promotion intervention provided to patients and families referred to a clinical service. METHODS 6 patients and their caregivers representing 5 different chronic conditions were seen for comprehensive psychological intervention that was evaluated based on electronic monitoring of adherence to prescribed oral medication. RESULTS Time se...

Received Jul 22, 2012 Revised Oct 23, 2012 Accepted Nov 14, 2012 Time series forecasting is an active research area that has drawn considerable attention for applications in a variety of areas. Auto-Regressive Integrated Moving Average (ARIMA) models are one of the most important time series models used in financial market forecasting over the past three decades but not very often used to forec...

To begin a zero accident campaign for industry, the first thing is to estimate the industrial accident rate and the zero accident time systematically. This paper considers the social and technical change of the business environment after beginning the zero accident campaign through quantitative time series analysis methods. These methods include sum of squared errors (SSE), regression analysis ...

The application of multivariate time series is so large,it can be used in many systems, like ecnomic systems,biological systems, and so on.This paper introduced the method’s building and the structure of ARIMAX model (auto-regressive integrated moving average model with explanatory variables) and its SAS realizing. The paper analysed the tertiaryindustry in China with the realty business to be ...