abstract nowadays, due to the environmental uncertainty and rapid development of new technologies, economic variables are often predicted by using less data and short-term timeframes. therefore, prediction methods which require fewer amounts of data are needed. auto regressive integrated moving average (arima) model and artificial neural networks (anns) need large amounts of data to achieve acc...

A large number of recent observational data strongly suggest that we live in a flat, accelerating Universe composed of ∼ 1/3 of matter (baryonic + dark) and ∼ 2/3 of an exotic component with large negative pressure, usually named Dark Energy or Quintessence. The basic set of experiments includes: observations from SNe Ia, CMB anisotropies, large scale structure, X-ray data from galaxy clusters,...

Query performance prediction aims to determine in advance whether a user’s search request will return a useful answer set. The success of such prediction attempts are currently evaluated by calculating the correlation between the predicted performance and standard information retrieval metrics of system performance such as average precision. However, recent work suggests that there is little re...

AbstrAct The spatio-temporal prediction problem requires that one or more future values be predicted for time series input data obtained from sensors at multiple physical locations. Examples of this type of problem include weather prediction, flood prediction, network traffic flow, and so forth. In this chapter we provide an overview of this problem, highlighting the principles and issues that ...

Spectrum scarcity due to inefficient utilisation has ignited a plethora of dynamic spectrum access solutions to accommodate the expanding demand for future wireless networks. Dynamic spectrum access systems allow secondary users to utilise spectrum bands owned by primary users if the resulting interference is kept below a pre-designated threshold. Primary and secondary user spectrum occupancy p...

This paper presents the Modi ed Multiband Excitation Model used for speech coding. In many MBE model coders, speech quality is degraded when incorrect voicing decisions are made, particularly for high-pitched female speakers. The MMBE addresses this issue with a modi ed voiced/unvoiced decision algorithm and a more robust pitch estimate. The listening quality of speech produced using the MMBE m...

A comprehensive review of the propagation prediction models for terrestrial wireless communication systems is presented in this paper. The classic empirical models are briefly described and the focus is placed on the application of ray-tracing techniques to the development of deterministic propagation models. Schemes to increase the computational efficiency and accuracy are discussed. Tradition...

This paper reports a preliminary attempt on data-driven modeling of segmental (phoneme) duration for two Indian languages Hindi and Telugu. Classification and Regression Tree (CART) based data-driven duration modeling for segmental duration prediction is presented. A number of features are proposed and their usefulness and relative contribution in segmental duration prediction is assessed. Obje...

abstract background: gestational diabetes is the second common disorder in pregnancy period, which is detected in 24-28 weeks of gestational age through screening tests in low-risk women. the women with gestational diabetes are prone to prenatal mortality and development of future diabetes. therefore, detection of these individuals in the fi rst trimester and conducting preventive interventions...

objective: there are various attempts to confirm variables that could predict postpartum depression in advance. this study determined antenatal risk factors for postpartum depression in women at risk of developing this disorder. methods: a prospective cohort study was conducted with 2279 eligible women who attended at mazandaran province’ primary health centers from 32-42 weeks of pregnancy to ...