Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensities. In the third stage, the boundary of the target object is extracted, and in the fourth and fifth stages, respectively, the region of interest (ROI) is highlighted and reconstructed. Our model was tested and evaluated using realistic scenarios which include outdoor and indoor scenes. The results reflect the ability of our approach to detect and remove shadows and reconstruct a shadow free image with a small error of approximately 6%.
Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
... Show MoreWater hyacinth (Eichhornia crassipes) is a free-floating plant, growing plentifully in the tropical water bodies. It is being speculated that the large biomass can be used in wastewater treatment, heavy steel and dye remediation, as a substrate for bioethanol and biogas production, electrical energy generation, industrial uses, human food and antioxidants, medicines, feed, agriculture, and sustainable improvement. In this work, the adsorption of Congo Red (CR) from aqueous solution onto EC biomass was investigated through a series of batch experiments. The effects of operating parameters such as pH (3-9), dosage (0.1-0.9 g. /100 ml), agitated velocity (100-300), size particle (88-353μm), temperature (10-50˚C), initial dye
... Show MoreChurning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date. A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s
... Show MoreIn this paper a system is designed on an FPGA using a Nios II soft-core processor, to detect the colour of a specific surface and moving a robot arm accordingly. The surface being detected is bounded by a starting mark and an ending mark, to define the region of interest. The surface is also divided into sections as rows and columns and each section can have any colour. Such a system has so many uses like for example warehouses or even in stores where their storing areas can be divided to sections and each section is coloured and a robot arm collects objects from these sections according to the section’s colour also the robot arm can organize objects in sections according to the section’s colour.
In this paper a system is designed on an FPGA using a Nios II soft-core processor, to detect the colour of a specific surface and moving a robot arm accordingly. The surface being detected is bounded by a starting mark and an ending mark, to define the region of interest. The surface is also divided into sections as rows and columns and each section can have any colour. Such a system has so many uses like for example warehouses or even in stores where their storing areas can be divided to sections and each section is coloured and a robot arm collects objects from these sections according to the section’s colour also the robot arm can organize objects in sections according to the section’s colour.
This study investigates the feasibility of a mobile robot navigating and discovering its location in unknown environments, followed by the creation of maps of these navigated environments for future use. First, a real mobile robot named TurtleBot3 Burger was used to achieve the simultaneous localization and mapping (SLAM) technique for a complex environment with 12 obstacles of different sizes based on the Rviz library, which is built on the robot operating system (ROS) booted in Linux. It is possible to control the robot and perform this process remotely by using an Amazon Elastic Compute Cloud (Amazon EC2) instance service. Then, the map to the Amazon Simple Storage Service (Amazon S3) cloud was uploaded. This provides a database
... Show MoreThe current research seeks to identify mono-multi Vision and its relation to the psychological rebellion and personality traits of university students. To achieve this aim, the researcher has followed all the procedures of the descriptive correlational approach, as it is the closest approach to the objectives of the current research. The researcher has determined his research community for Baghdad University students for the academic year 2019-2020. As for the research sample, it was chosen by the random stratified method with a sample of (500) male and female students. In order to collect data from the research sample, the researcher adopted a mono-multi-dimensional scale
(Othman, 2007), the researcher designed a psychological r
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