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Predicting Bitter Orange (Citrus aurantium L.) Maturity by Machine Learning Based on Picking Force in Smart Picker
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Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that as fruits mature, their weight, CIE-L*a*b* values, and pH levels increase, while picking force and hardness decrease. Notably, picking force exhibited a strong correlation (93.5%) with maturity compared to other physical parameters. The Kruskal–Wallis test also showed that the relationship between picking force and bitter orange physical parameters, including weight, CIE-L*a*b*, pH, and hardness, was statistically significant. The extreme gradient boosting (XGBoost) model achieved the highest training accuracy (100%), outperforming stacking (99.91%), random forest (91.17%), and gradient boosting machine (89.08%) on all evaluation metrics. However, the stacking model is considered better, even though XGBoost achieved 100% training accuracy, as the former showed a better balance between training, testing, and validation. This study contributes to improving bitter orange quality by accurately predicting maturity through data collected from the smart picker.

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Publication Date
Sun Jul 01 2018
Journal Name
Journal Of Network And Computer Applications
L-CAQ: Joint link-oriented channel-availability and channel-quality based channel selection for mobile cognitive radio networks
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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Effect of Celery (Apium graveolens L.) Microgreens on Drosophila melanogaster
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Celery (Apium graveolens L. ; family : Apiaceae) was often used as a spice in daily food. However, this plant contains many antioxidant compounds useful for attenuating neurodegenerative disorders including Parkinson's disease. Planting celery in the form of microgreens harvested 15 days was expected to increase the content of bioactive compounds. In the current study, we intended to evaluate the neuromodulatory potential of methanol extract of celery microgreens on fruit flies (Drosophila melanogaster Meigen : family Drosophilidae ; ordo : Diptera) which were exposed to paraquat. Neuroprotective capacity was assessed by survival rate, locomotor performance, lipid peroxidation and dopamine content after being treated wi

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Publication Date
Tue Nov 01 2016
Journal Name
Research Journal Of Pharmaceutical, Biological And Chemical Sciences
Treating of oil-based drill cuttings by earthworms
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This study assessed the advantage of using earthworms in combination with punch waste and nutrients in remediating drill cuttings contaminated with hydrocarbons. Analyses were performed on day 0, 7, 14, 21, and 28 of the experiment. Two hydrocarbon concentrations were used (20000 mg/kg and 40000 mg/kg) for three groups of earthworms number which were five, ten and twenty earthworms. After 28 days, the total petroleum hydrocarbon (TPH) concentration (20000 mg/kg) was reduced to 13200 mg/kg, 9800 mg/kg, and 6300 mg/kg in treatments with five, ten and twenty earthworms respectively. Also, TPH concentration (40000 mg/kg) was reduced to 22000 mg/kg, 10100 mg/kg, and 4200 mg/kg in treatments with the above number of earthworms respectively. The p

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Content Based Image Retrieval (CBIR) by Statistical Methods
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            An image retrieval system is a computer system for browsing, looking and recovering pictures from a huge database of advanced pictures. The objective of Content-Based Image Retrieval (CBIR) methods is essentially to extract, from large (image) databases, a specified number of images similar in visual and semantic content to a so-called query image. The researchers were developing a new mechanism to retrieval systems which is mainly based on two procedures. The first procedure relies on extract the statistical feature of both original, traditional image by using the histogram and statistical characteristics (mean, standard deviation). The second procedure relies on the T-

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Crossref (8)
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Publication Date
Sat Oct 19 2024
Journal Name
Iraqi Statisticians Journal
Forecasting Gold prices by hybrid ANFIS-based algorithm
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In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

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Publication Date
Fri Dec 02 2022
Journal Name
Journal Of Physical Education
The Effect of Jigsaw Strategy on Learning Spiking in Volleyball for Sophomore Students
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The research aimed at designing teaching program using jigsaw in learning spiking in volleyball as well as identifying the effect of these exercises on learning spring in volleyball. The researchers used the experimental method on (25) students as experimental group and (27) students as controlling group and (15) students as pilot study group. The researchers conducted spiking tests then the data was collected and treated using proper statistical operations to conclude that the strategy have a positive effect in experimental group. Finally, the researchers recommended using the strategy in making similar studies on other subjects and skills.

Publication Date
Thu Jun 04 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Time-related salivary cathepsin B levels and periodontal status in different orthodontic force magnitudes
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Background: Biologically active substances, such as Cathepsin B (CAB) which is a lysosomalcystein protease may be involved in periodontal metabolism in the degradation of organic bone matrix containing collagen fibers in response to mechanical stress from orthodontic appliance. The aims of study were to determine and compare salivary levels of CAB, pH as well as clinical periodontal parameters (Plaque index PLI and gingival index GI) with different orthodontic force magnitudes at different time intervals. Materials and methods: A twenty-four patients (both gender) with age range (17-23) years had Angle's Class II division 1 malocclusion with GI >0.5 enrolled in this study. The level of salivary CAB and pH, in addition to the clinical period

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Publication Date
Mon Aug 30 2021
Journal Name
مجلة الجامعة العراقية
Contracts in light of the Corona pandemic between the emergency circumstance and force majeure
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The "Corona" pandemic that strikes the world has cast a shadow over contractual obligations, whether between individuals or companies, and emergency accidents and force majeure circumstances have a direct impact on them. Here, the legislation intervenes and sets the legal mechanisms to restore the obligations to their equal status and achieve the economic balance of the contract. Health crises are among the material facts whose effects are reflected and their features can be monitored on legal relations in general and contractual relations in particular, including the extent of the impact that this pandemic can have on the obligations that arise within the framework of a contractual relationship, which can be talked about in my theory Force

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Publication Date
Mon May 26 2025
Journal Name
Middle East Journal Of Digestive Diseases (mejdd)
Investigating the Role of sHLA-G in the Immunopathogenesis and predicting Gastroesophageal Reflux Disease
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Background : Gastroesophageal reflux disease (GERD) is one of chronic gastrointestinal diseases in which patient may be asymptomatic or was complained from heartburn and regurgitation or pulmonary symptoms. Aim of the study : Examine the serum level of sHLA-G in GERD patients and can be used as a biomarker for early detection of GERD disease. Materials and methods : The design of the study was a case- control prospective enrolled forty patients consulted Gastroenterology Unit- Al-Kindy Teaching Hospital, were diagnosed as GERD by their physician, and compared to second forty control healthy group form January-2023 to May-2024. Serum used for quantitative assessment of soluble HLA-G (sHLA-G) using a sandwich enzyme-linked immunosorbent a

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Information Engineering And Applications
Development of Prognosis Factors in a Scoring System for Predicting of Breast Cancer Mortality
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Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate

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