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Power requirements for corn silage harvesters and application of precision agricultural techniques: a review
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The energy requirements of corn silage harvesters and the application of precision agricultural techniques are essential for efficient and productive agricultural practices. The article aims to review previous studies on the energy requirements needed for different corn silage harvesting machines, and on the other hand, to present methods for measuring corn silage productivity directly in the field and monitoring it based on microcontrollers and artificial intelligence techniques. The process of making corn silage is done by cutting green fodder plants into small pieces, so special harvesters are used for this, called corn silage harvesters. The purpose of harvesting corn silage is to efficiently collect and store as many digestible nutrients as possible per unit of land area. The energy required to harvest corn silage is affected by many factors, including crop moisture, cutting lengths, particle size distribution, etc. This requires understanding the energy requirements of the harvesters used in the process. Using micro-sensors, the feed rate into corn silage harvesters is measured based on load cell data. This method helps in understanding the energy consumption and efficiency of the harvester during the feeding process, leading to more efficient and productive operations. On the other hand, artificial intelligence techniques are used to measure core size and cutting length to control machining parameters. We conclude from this review that precision agriculture techniques help farmers understand the efficiency of corn silage harvesters and know silage yield and quality, which helps them make informed decisions regarding energy use and thus obtain high productivity.

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
A Multi-variables Multi -sites Model for Forecasting Hydrological Data Series
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A multivariate multisite hydrological data forecasting model was derived and checked using a case study. The philosophy is to use simultaneously the cross-variable correlations, cross-site correlations and the time lag correlations. The case study is of two variables, three sites, the variables are the monthly rainfall and evaporation; the sites are Sulaimania, Dokan, and Darbandikhan.. The model form is similar to the first order auto regressive model, but in matrices form. A matrix for the different relative correlations mentioned above and another for their relative residuals were derived and used as the model parameters. A mathematical filter was used for both matrices to obtain the elements. The application of this model indicates i

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Publication Date
Sun Dec 31 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
A Ranked-Aware GA with HoG Features for Infant Cry Classification
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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science & Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
GIS as A Tool for Expansive Soil Detection at Sulaymaniyah City
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Geotechnical engineering like any other engineering field has to develop and cope with new technologies. This article intends to investigate the spatial relationships between soil’s liquid limit (LL), plasticity index (PI) and Liquidity index (LI) for particular zones of Sulaymaniyah City. The main objective is to study the ability to produce digital soil maps for the study area and determine regions of high expansive soil. Inverse Distance Weighting (IDW) interpolation tool within the GIS (Geographic Information System) program was used to produce the maps. Data from 592 boreholes for LL and PI and 245 boreholes for LI were used for this study. Layers were allocated into three depth ranges (1 to 2, 2 to 4 and 4 to 6)

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Publication Date
Sun Jan 01 2023
Journal Name
Materials Chemistry And Physics
BC2N nanotube as a promising anode for rechargeable calcium ion batteries
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Because of cost-effective production and abundant resources of calcium, Ca-ion batteries (CIBs) are an appropriate option to alternate Li-ion batteries (LIBs). A new category of anode materials for CIBs has emerged since the successful synthesis of carbon nanotubes, which are B and N doped derivatives of it. For high-performance CIBs, BC2N nanotube (BC2NNT) has been studied as promising anode materials. In order to comprehend electrochemical attributes, cycling stability, and adsorption behavior of BC2NNT, first-principles computations have been executed. Based on nuclear magnetic resonance computations, two types of hexagonal rings (B2C2N2 (I) and BC4N (II)) were specified that are non-aromatic. Ca has adsorption on B2C2N2 and BC4N with ad

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Publication Date
Sun Apr 11 2021
Journal Name
Environment, Development And Sustainability
Developing a system for assessing the sustainability in school building projects
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Publication Date
Tue Oct 16 2018
Journal Name
Springer Science And Business Media Llc
MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
360 degree reverse feedback / comparative analytical study for a sample of managers and heads of departments in the Central Electricity DepartmentAnd the General Directorate of Water and Sewage
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يسعى البحث إلى الاهتمام بإحدى الوظائف المهمة في إدارة الموارد البشرية وهي تقويم الأداء التي تواجه مجموعة من الانتقادات والآراء السلبية، اذ ظهر في الأّونة الأخيرة أنموذج جديد يمكن إن يتجاوز تلك السلبيات وهو أنموذج التغذية العكسية المتعدد المصادر درجة .وقد حاول الباحثان توظيف هذا المفهوم في اثنتين من المنظمات العامة العراقية هما (دائرة كهرباء الوسط) التابعة لوزارة الكهرباء
و (دائرة الماء والمجاري) ال

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Publication Date
Tue Jun 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Application of Neural Network in the Identification of the Cumulative Production from AB unit in Main pays Reservoir of South Rumaila Oil Field.
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A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited g

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