In recent years, particle swarm optimization (PSO) has been extensively applied in various optimization problems because of its structural and implementation simplicity. However, the PSO can sometimes find local optima or exhibit slow convergence speed when solving complex multimodal problems. To address these issues, an improved PSO scheme called fusion global-local-topology particle swarm optimization (FGLT-PSO) is proposed in this study. The algorithm employs both global and local topologies in PSO to jump out of the local optima. FGLT-PSO is evaluated using twenty (20) unimodal and multimodal nonlinear benchmark functions and its performance is compared with several well-known PSO algorithms. The experimental results showed that the proposed method improves the performance of PSO algorithm in terms of solution accuracy and convergence speed.

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Previously, there were many extraction methods that had been done on extracting the oil such as centrifugation, chilling and thawing, hot and cold extraction, on seeds, waste products and plants. Based on those oil extraction methods (OEM), further study is needed to develop more effective processes as most of the methods were having many disadvantages in term of time, cost, quality and safety. Ultrasonic-assisted extraction (UAE) is used in this project as it is a rapid and effective extraction technique that uses ultrasound to generate rapid movement of solvents, resulting in a higher mass transfer speed as well as acceleration of extraction. Compared to other advanced extraction techniques, UAE is more economic, eco-friendly, and convenient by the reduction of time consumption, higher oil quality and cost reduction. The principle of acoustic cavitation ultrasound which is explained by a series of compression and rarefaction waves induced in the molecules of the medium and the collapse of the bubble during the process of UAE may be discussed. Parameters involved also play the important role in the extraction such as extraction time (ET), extraction temperature (ETem), solvent to material ratio (S/M Ratio) and type of solvent selected. Thus, the paper discusses the application of UAE on oil extraction.

The stipulation of internet content rises dramatically in recent years. Servers have become extremely powerful and the bandwidth of end user connections and backbones grew constantly during the previous decade. Nonetheless, users frequently experience poor performance to access web sites or download files primarily if mobile devices have been used due to their limited storage, processing, display, power and communication resources. The causes are often performance which access directly on the servers (e.g. pitiable performance of server-side applications or during burst crowds) and network infrastructure (e.g. long geographical distances, network overloads, etc.). Hence, the goal of this study is to propose Rough Set (RS) as a knowledge representation for uncertainty in data of client behavior and mobile event specification with resource dependencies to reduce latency by prefetching selected resources to resolve the problems in handling dynamic web pages. We conducted the trace-based experiments on the RS approach for better classification outcomes.