The current research presents a numerical investigation of the mixed convection inside a horizontal rectangular duct combined with an open trapezoidal cavity. The region in the bottom wall of the cavity is heated by using two discrete heat sources. The cold airflow enters the duct horizontally at a fixed velocity and a constant temperature. All the other walls of the duct and the cavity are adiabatic. Throughout this study, four various cases were investigated depending on the driven walls. The effects of the Richardson number and Reynolds number ratio are studied under various cases related to the lid-driven sidewalls. The results are presented in terms of the flow and thermal fields and the average Nusselt number. The yielded data show that the average Nusselt number rises as the Richardson number and Reynolds number ratio increases. Furthermore, the Reynolds number ratio and the movement of the cavity sidewall(s) have a significant effect on the velocity and temperature contours. By the end of the study, it is shown that the maximum rates of heat transfer are related to Case 1 where the left sidewall moves downward and heater 2, which is placed near the left sidewall.

Recently, video surveillance systems have gained significant interest in several application areas. The examination of video sequences for the detection and tracking of objects remains a major issue in the field of image processing and computer vision. The object detection and tracking process includes the extraction of moving objects from the frames and continual tracking over time. The latest advances in computation intelligence (CI) techniques have become popular in the field of image processing and computer vision. In this aspect, this study introduces a novel computational intelligence-based harmony search algorithm for real-time object detection and tracking (CIHSA-RTODT) technique on video surveillance systems. The CIHSA-RTODT technique mainly focuses on detecting and tracking the objects that exist in the video frame. The CIHSA-RTODT technique incorporates an improved RefineDet-based object detection module, which can effectually recognize multiple objects in the video frame. In addition, the hyperparameter values of the improved RefineDet model are adjusted by the use of the Adagrad optimizer. Moreover, a harmony search algorithm (HSA) with a twin support vector machine (TWSVM) model is employed for object classification. The design of optimal RefineDet feature extraction with the application of HSA to appropriately adjust the parameters involved in the TWSVM model for object detection and tracking shows the novelty of the work. A wide range of experimental analyses are carried out on an open access dataset, and the results are inspected in several ways. The simulation outcome reported the superiority of the CIHSA-RTODT technique over the other existing techniques.

The thermal performance enhancement of a vertical helical coil heat exchanger using distilled water-based copper oxide-graphene hybrid nanofluid has been analyzed experimentally. Accordingly, the focus of this study is the preparation of CuO-Gp (80-20%) hybrid nanoparticles-based suspensions with various mass fractions (0% ≤ wt ≤ 1%). The volume flow rate is ranged from 0.5 L·min⁻¹ to 1.5 L·min⁻¹ to keep the laminar flow regime (768 ≤ Re ≤ 1843) and the supplied hot fluid’s temperature was chosen to equal 50 °C. To ensure the dispersion and avoid agglomeration an ultrasound sonicator is used and the thermal conductivity is evaluated via KD2 Pro Thermal Properties Analyzer. It has been found that the increment in nanoparticles mass fraction enhances considerably the thermal conductivity and the thermal energy exchange rate. In fact, an enhancement of 23.65% in the heat transfer coefficient is obtained with wt = 0.2%, while it is as high as 79.68% for wt = 1%. Moreover, increasing Reynolds number results in a considerable augmentation of the heat transfer coefficient.