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DEVELOPMENT AND EVALUATION OF A YOLO ALGORITHM-BASED ROBOTIC SPRAYER FOR REAL-TIME WEED DETECTION
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Abstract<p> Weed control with chemicals is a challenging process that should be performed in a rational way to reduce their negative impact on the surrounding environment. The growth of artificial intelligence algorithms encourages researchers to develop smart spraying robots that detect and spray weeds and distinguish them from the main crop which leads to sustainable use of these chemicals and achieves some of the sustainable development goals. However, few studies are available to comprehensively compare different versions of YOLO algorithm to detect weed. In this research, seven versions of YOLO algorithms were evaluated for their performance to detect and spray four types of weeds, namely, Cultivated licorice ( <italic>Glycyrrhiza glabra</italic> L.), Dyer’s Croton ( <italic>Chrozophora verbascifolia</italic> ), Lambsquarters ( <italic>Chenopodium album</italic> L.), and Puncturevine ( <italic>Tribulus terrestris</italic> L.) using a locally manufactured remotely controlled spraying robot. The results showed that YOLOv6n surpassed other algorithms which achieved the highest precision (0.89), recall (0.80), F1-score (0.84), mAp@0.50 (0.86), inference speed (18.83 fps), in addition to the field indicators including true positive rate (0.83), false negative rate (0.17), false positive rate (0.19), true negative rate (0.81). </p>
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Publication Date
Sat Oct 31 2020
Journal Name
Eastern-european Journal Of Enterprise Technologies
Design and development of high-accuracy machine for wire bending
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Publication Date
Wed May 01 2024
Journal Name
Scientific Visualization
Shadow Detection and Elimination for Robot and Machine Vision Applications
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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 intensit

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Experience of Kurdistan province of Iraq in light of the development of economic and social indicators for sustainable development
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Reflect the sustainable development of the interaction of three key elements are the economic component and the social component and the environmental component while focusing economic component to achieve economic growth and focuses social element to achieve social justice in the distribution of income and achieve prosperity, the environmental component related fields and including emphasizes the protection of the environment and to ensure the continuation and sustainability of resources physical, biological and form in which it believes the interaction required for development process real and effective and sustainable, and is considered the province of Kurdistan Iraq of important areas where the movement of developmental mount

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Applying some hybrid models for modeling bivariate time series assuming different distributions for random error with a practical application
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Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Efficient Task Scheduling Approach in Edge-Cloud Continuum based on Flower Pollination and Improved Shuffled Frog Leaping Algorithm
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The rise of edge-cloud continuum computing is a result of the growing significance of edge computing, which has become a complementary or substitute option for traditional cloud services. The convergence of networking and computers presents a notable challenge due to their distinct historical development. Task scheduling is a major challenge in the context of edge-cloud continuum computing. The selection of the execution location of tasks, is crucial in meeting the quality-of-service (QoS) requirements of applications. An efficient scheduling strategy for distributing workloads among virtual machines in the edge-cloud continuum data center is mandatory to ensure the fulfilment of QoS requirements for both customer and service provider. E

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Publication Date
Wed Mar 23 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Training Program for the Development of Moral Intelligence among Preparatory Students
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This current research aims to identify the effectiveness of a training program in developing moral intelligence and mutual social confidence among middle school students. The researcher made a number of hypotheses for this purpose to achieve the goal of the research.                             

The researcher relied on the (Al Zawaida 2011) scale prepared according to Coles (1997), including (60) items, and the mutual social trust scale for (Nazmi 2001) based on Roter's theory including (38) items.               &nbsp

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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effect of a Training Program to Develop the Skill of Organizing Time for the Kindergarten Department Students
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The current research aims to identify the time-management skills based on the post-test of the experimental group as well as to examine the effect of a training program on developing the skills of managing time among the study sample. To achieve the research objectives, the researcher designed a scale of time management skill included (30) paragraphs. The research reached that the training program is significantly effective in managing and organizing time. There are statistically significant differences in pre-posttest between the experimental and control groups.

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Experimental Analysis for the Influence of Ignition Time on Combustion Characteristics of a Free Piston Engine Linear Generator
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Abstract<p>Free Piston Engine Linear Generator (FPELG) is a modern engine and promising power generation engine. It has many advantages compared to conventional engines such as less friction, few numbers of parts, and high thermal efficiency. The cycle-to-cycle variation one of the big challenges of the FPELG because it is influence on the stability and output power of the engine. Therefore, in this study, the effect of ignition time on combustion characteristics is investigated. The single-cylinder FPELG with spark ignition (SI) combustion type by using compressed natural gas (CNG) fuel type was set to run. LabVIEW is used to run the engine and control of input parameters. All experimental data</p> ... Show More
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Publication Date
Mon Jan 13 2020
Journal Name
Day 3 Wed, January 15, 2020
Numerical Simulation of Gas Lift Optimization Using Genetic Algorithm for a Middle East Oil Field: Feasibility Study
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<p>Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t</p> ... Show More
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Publication Date
Tue Nov 19 2024
Journal Name
Aip Conference Proceedings
CT scan and deep learning for COVID-19 detection
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