European Broadband Tariffs Analysis: Broadband Tariff Analysis - EU 27, Q4 2010

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A unified framework for change point detection in high-dimensional linear models

In recent years, change point detection for high dimensional data has become increasingly important in many scientific fields. Most literature develop a variety of separate methods designed for specified models (e.g. mean shift model, vector auto-regressive model, graphical model). In this paper, we provide a unified framework for structural break detection which is suitable for a large class of models. Moreover, the proposed algorithm automatically achieves consistent parameter estimates during the change point detection process, without the need for refitting the model. Specifically, we introduce a three-step procedure. The first step utilizes the block segmentation strategy combined with a fused lasso based estimation criterion, leads to significant computational gains without compromising the statistical accuracy in identifying the number and location of the structural breaks. This procedure is further coupled with hard-thresholding and exhaustive search steps to consistently estimate the number and location of the break points. The strong guarantees are proved on both the number of estimated change points and the rates of convergence of their locations. The consistent estimates of model parameters are also provided. The numerical studies provide further support of the theory and validate its competitive performance for a wide range of models. The developed algorithm is implemented in the R package LinearDetect

Review of Hosein Aabad Sugar Factory (HASF) Wastewater and Assessment of its Pollution Load

Sugar industry is one of the largest industries in the world. Hosein Abad sugar factory (HASF) is located in Hamadan province of Iran. The aim of this research was to evaluate the quality and quantity of wastewater of the said factory and to estimate the pollution load and its emission factor as prerequisite of the management and environmental pollutions control in the region. Random grab sampling is used in twelve days between October 2010 and March 2011 during peak hours of activity. In this research, nine quality parameters as the key variables are measured to evaluate the quality of wastewater. The obtained results indicate that, the amount of wastewater produced by HASF is about 2740 m3/day. Based on the said results, the average amount of five days Biochemical Oxygen Demand (BOD5) and Chemical Oxygen Demand (COD) in the raw wastewater was 1296 and 2328 mg/l respectively. The results of this research showed that the effluent wastewater of HASF in the present conditions is highly polluted due to inappropriate treating and is not appropriate for artificial recharge use, discharge in rivers and lakes or utilization in agriculture, according to the DoE standards