Electrocoagulation (EC) is one of the efficient electrochemical approaches for industrial wastewater treatment. The present work aims to reach optimum conditions for achieving simultaneous removal of chromium and cadmium ions from synthetic wastewater by EC through assessment of different parameters like electrodes material, electrode configuration, initial pH, current density, initial temperature, and initial contaminate concentration. In addition, a comparison between chemical coagulation and EC efficiency for Chromium and cadmium removal was presented. Results showed that the (Fe-Al), an anode and cathode, achieved better removal efficiency than other electrodes configurations (Fe-Fe / Al-Fe / Al- Al). Also, the increase of initial temperature and current density enhanced the removal efficiency. In contrast, the increase in the initial concentration reduced the removal efficiency. The complete removal of Chromium achieved through the use of Fe-Al electrodes and current density was 12.50 mA/cm2 with solution pH of 5.8, temperature was 25oC and an initial concentration of 280 mg/L. On the other hand, Cadmium’s complete removal was achieved through the use of Fe-Allectrodes, at pH of 5.8, applied current 1.4 A and 60oC. Therefore, EC was proved to be better approach than conventional coagulation in case of treatment of wastewater containing different types of heavy metals ions with high initial concentrations.

Visual object tracking is a critical problem in the field of computer vision. The visual object tracker methods can be divided into Correlation Filters (CF) and non-correlation filters trackers. The main advantage of CF-based trackers is that they have an accepted real-time tracking response. In this article, we will focus on CF-based trackers, due to their key role in online applications such as an Unmanned Aerial Vehicle (UAV), through two contributions. In the first contribution, we proposed a set of new video sequences to address two uncovered issues of the existing standard datasets. The first issue is to create two video sequence that is difficult to be tracked by a human being for the movement of the Amoeba under the microscope; these two proposed video sequences include a new feature that combined background clutter and occlusion features in a unique way; we called it hard-to-follow-by-human. The second issue is to increase the difficulty of the existing sequences by increasing the displacement of the tracked object. Then, we proposed a thorough, practical evaluation of eight CF-base trackers, with the top performance, on the existing sequence features such as out-of-view, background clutters, and fast motion. The evaluation utilized the well-known OTB-2013 dataset as well as the proposed video sequences. The overall assessment of the eight trackers on the standard evaluation metrics, e.g., precision and success rates, revealed that the Large Displacement Estimation of Similarity transformation (LDES) tracker is the best CF-based tracker among the trackers of comparison. On the contrary, with a deeper analysis, the results of the proposed video sequences show an average performance of the LDES tracker among the other trackers. The eight trackers failed to capture the moving objects in every frame of the proposed Amoeba movement video sequences while the same trackers managed to capture the object in almost every frame of the sequences of the standard dataset. These results outline the need to improve the CF-based object trackers to be able to process sequences with the proposed feature (i.e., hard-to-follow-by-human).