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Comparison of the Effect Using Color Sensor and Pixy2 Camer on the Classification of Pepper Crop
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Image processing applications are currently spreading rapidly in industrial agriculture. The process of sorting agricultural fruits according to their color comes first among many studies conducted in industrial agriculture. Therefore, it is necessary to conduct a study by developing an agricultural crop separator with a low economic cost, however automatically works to increase the effectiveness and efficiency in sorting agricultural crops. In this study, colored pepper fruits were sorted using a Pixy2 camera on the basis of algorithm image analysis, and by using a TCS3200 color sensor on the basis of analyzing the outer surface of the pepper fruits, thus This separation process is done by specifying the pepper according to the color of its outer surface, afterward selecting the fruit is achieved, then the crop is sorted by color. An electromechanical system was developed for this process with three different belt conveyor speeds (0.8, 2 and 3 m /s). The image processing algorithms and external surface color analysis that were developed within the scope of the study were tested on this system in real practical time. Moreover, choosing the appropriate speed for the conveyor belt, depending on the time sufficient to process the images or analyze the colors of the outer surface of the pepper fruits. The highest successav erage of 93.33% was recorded along with the lowest error average of 6.66%, at the first speed using the Pixy2 camera, whereas the sorting process using the TCS3200 color sensor recorded the highest success average of 83.33% along with the lowest error average of 16.66%, at the first speed. It is evident from the above-mentioned values, that the method of sorting the pepper with the Pixy2 camera is more successful than the second method of using the TCS3200 color sensor, nevertheless, the second method can also be used in the process of sorting the pepper fruits.

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between the Methods of Ridge Regression and Liu Type to Estimate the Parameters of the Negative Binomial Regression Model Under Multicollinearity Problem by Using Simulation
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The problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline

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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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Publication Date
Mon Jan 01 2024
Journal Name
Recent Research On Geotechnical Engineering, Remote Sensing, Geophysics And Earthquake Seismology
Evaluating the Accuracy of iPhone Lidar Sensor for Building Façades Conservation
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Publication Date
Sat Jun 15 2019
Journal Name
Agriculture
Cover Crop Influence on Soil Enzymes and Selected Chemical Parameters for a Claypan Corn–Soybean Rotation
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Cover crops (CC) improve soil quality, including soil microbial enzymatic activities and soil chemical parameters. Scientific studies conducted in research centers have shown positive effects of CC on soil enzymatic activities; however, studies conducted in farmer fields are lacking in the literature. The objective of this study was to quantify CC effects on soil microbial enzymatic activities (β-glucosidase, β-glucosaminidase, fluorescein diacetate hydrolase, and dehydrogenase) under a corn (Zea mays L.)–soybean (Glycine max (L.) Merr.) rotation. The study was conducted in 2016 and 2018 in Chariton County, Missouri, where CC were first established in 2012. All tested soil enzyme levels were significantly different between 2016 and 2018

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Publication Date
Fri Jan 31 2025
Journal Name
Aip Conference Proceedings
Classification of oral cavity cancer using linear discriminant analysis (LDA) and principal component analysis (PCA)
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Publication Date
Tue Feb 10 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Antibacterial effect of cardamom and black tea aqueous extract on mutans streptococci in comparison to chlorhexidine (in vitro study)
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Background: Antimicrobial agents have been considered as having potential for the prevention of dental caries. This study aimed to test the effect of different concentrations of cardamom and black tea extracts on the sensitivity and growth of salivary mutans streptococci in comparison to chlorhexidine gluconate (0.2%) in vitro. Materials and methods: In this study. Mutans streptococci were isolated from saliva of 34 healthy people (aged between 22-40yrs). The bacteria was isolated, purifiedand diagnosed according to morphologicalcharacteristic and biochemical tests. Aqueous extracts of cardamom and black tea were prepared. Different concentrations of extracts were prepared and estimated in gm/ 100ml deionized water. The agar diffusion techn

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agriculture And Statistical Science
COMPARISON OF FORECASTING OF THE RISK OF CORONAVIRUS (COVID-19) IN HIGH-QUALITY AND LOW-QUALITY HEALTHCARE SYSTEMS, USING ANN MODELS
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COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Zankoy Sulaimani - Part A
A Comparison Study on the Formation of Administrative and Leadership Policies for the Team and Individual Olympic Games in the Iraqi National Olympic Committee
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The planning for the formation of administrative policies and guidance through leadership are important things for managing administrative processes and sporting activities. As both contribute in the stability of the administrative conditions, and their development in the sport federations, whether they both were attentive about team and individual Olympic Games. The two researchers observe that, there is a variation in the correct way of application. Particularly in the formulation of administrative policies and leadership describing it as, modern management standards for both team and individual Olympic Games in the Iraqi National Olympic Committee. That led to cause a misconception and lack of clarity for some administrators of those uni

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Publication Date
Tue Dec 31 2024
Journal Name
Journal Of Soft Computing And Computer Applications
Enhancing Image Classification Using a Convolutional Neural Network Model
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In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

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Publication Date
Wed Nov 25 2015
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Subject Independent Facial Emotion Classification Using Geometric Based Features
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Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

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