Soil tillage is a critical agricultural practice that creates favorable conditions for seedbed preparation and plant growth. This study presents an innovative application of artificial intelligence (AI) in agriculture by employing the YOLOv7 algorithm to classify and assess post-tillage soil surface conditions, a domain underexplored in current research. The integration of mechanical operation parameters with AI-based image classification enables optimization of tillage quality and mitigation of soil compaction, highlighting the novelty of this approach. The study aims to improve the efficiency of moldboard plow operations by examining the effects of tillage speed and depth on soil clod distribution, fuel consumption, and power requirements. The YOLOv7 model was used to analyze soil surface imagery and identify optimal tillage outcomes characterized by minimal soil clod presence. Results indicate that increasing tillage speed and depth led to higher fuel and power consumption. Conversely, smaller soil clod sizes, indicative of better surface quality, were achieved at higher speeds and shallower depths. Model performance demonstrated strong accuracy: recall of 78.5%, precision of 82.0%, and F1-score of 80.2%. The mean Average Precision at 0.5 IoU ([email protected]) reached 77.4%, with validation and test set values of 78% and 75%, respectively. These results confirm the effectiveness of YOLOv7 in detecting and localizing soil clods, enabling real-time assessment of tillage quality. The proposed framework supports data-driven decision-making in precision agriculture, enhances operational efficiency, and promotes improved seedbed conditions for optimal crop establishment.
It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in
... Show MoreRA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2
One of the most recent research areas in subsurface applications, including well drilling, is the use of eco-friendly and sustainably synthesized nanoparticles to improve drilling fluid efficiency. Typically, Shale formations present significant challenges to traditional drilling fluids, including fluid infiltration and shale swelling, which jeopardize wellbore stability. Although water-based drilling fluids (WBM) are environmentally preferred, their performance often requires enhancement through advanced additives. This study thus examines the synthesis of silica (SiO₂) and alumina (Al₂O₃) nanoparticles (NPs) using sustainable methods, employing Iraqi bentonite for silica and recycled aluminum scrap for alumina, to improve WBM effici
... Show MoreThis paper proposes a new encryption method. It combines two cipher algorithms, i.e., DES and AES, to generate hybrid keys. This combination strengthens the proposed W-method by generating high randomized keys. Two points can represent the reliability of any encryption technique. Firstly, is the key generation; therefore, our approach merges 64 bits of DES with 64 bits of AES to produce 128 bits as a root key for all remaining keys that are 15. This complexity increases the level of the ciphering process. Moreover, it shifts the operation one bit only to the right. Secondly is the nature of the encryption process. It includes two keys and mixes one round of DES with one round of AES to reduce the performance time. The W-method deals with
... Show MoreAccording to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through
... Show MoreThe research aims to derive the efficient industrial plans for Al – shaheed public company under risk by using Target MOTAD as a linear alternative model for the quadratic programming models.
The results showed that there had been a sort of (trade- off) between risk and the expected gross margins. And if the studied company strives to get high gross margin, it should tolerate risk and vice versa. So the management of Al- Shaheed Company to be invited to apply the suitable procedures in the production process, in order to get efficient plans that improves it's performance .
NAA Mustafa, University of Sulaimani, Ms. c Thesis, 2010 - Cited by 4
Phase-change materials (PCMs) have a remarkable potential for use as efficient energy storage means. However, their poor response rates during energy storage and retrieval modes require the use of heat transfer enhancers to combat these limitations. This research marks the first attempt to explore the potential of dimple-shaped fins for the enhancement of PCM thermal response in a shell-and-tube casing. Fin arrays with different dimensions and diverse distribution patterns were designed and studied to assess the effect of modifying the fin geometric parameters and distribution patterns in various spatial zones of the physical domain. The results indicate that increasing the number of
Background: Tap waters play an important role in fulfilling the people needs for drinking and domestic purposes. Contaminate the tap water with different pollutants has become an issue of great concern for 90% of people who are depended on the tap water as the main source of drinking. Pollutants can make their way easily into the delivering pipes which suffer from the leaking resulting in decreasing the quality of water. Objective: Therefore, assess the water quality for drinking purpose by calculating the water quality index is an important tool to ascertain whether the water is suitable for human consumption or not. Methods: In the present work, the water quality of the Al-Salam, western region of Baghdad city, Iraq was investigated for 7
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