An experiment was carried out evaluate the performance of RAU combined equipment under three levels of practical speed, (V1) 4.06 km. h-1, (V2) 4.43 km. hr-1 and (V3) 5.76 km. hr-1, and three levels of depth with 10,20and 30 cm. It is denoted by D1, D2, D3 respectively. A split plot design was used within the RCBD design with three replications. The experiment results showed that the first practical speed 4.06 km.hr-1 achieved the lowest slippage percentage from 9.61%, lowest traction power 14.65hp, lowest soil penetration resistance to1.34 kg.cm-2, and the highest total operating costs (40803.4 ID.ha-1, while the third speed achieved the opposite results. The first treatment depth achieved the lowest results for slippage percentage 8.52%, traction power 15.34hp, soil penetration resistance 1.17 kg. cm-2, and total operating costs 37215.0ID. ha-1, while the third depth achieved the opposite results. Interaction between treatment depth and practical speed showed that the first treatment depth with the first practical speed has the lowest average of slippage percentage 7.63%, the lowest value of the traction power 13.77 hp, and the lowest average of soil resistance to penetration 1.03 kg.cm-2, while the first treatment depth and third practical speed has lowest average of the operating costs 34533.4 ID.ha-1.
Collaborative learning is a way that prepares students practically for real-world applications. Working together as teamwork to execute various writing skills is essential in most professions since it increases the level of experience. Thus, the current study aims to identify the role collaborative writing in developing students' level of performance in writing. It is qualitative in nature since the researcher depended on the extant literature in achieving the objective of the study. The researcher touched upon related theories that addressed Collaborative learning, categories, and problems .It concluded that collaborative writing increases the students’ self-confidence, self-esteem, creativity, and motivation through the interact
... Show MoreTchebichef polynomials (TPs) play a crucial role in various fields of mathematics and applied sciences, including numerical analysis, image and signal processing, and computer vision. This is due to the unique properties of the TPs and their remarkable performance. Nowadays, the demand for high-quality images (2D signals) is increasing and is expected to continue growing. The processing of these signals requires the generation of accurate and fast polynomials. The existing algorithms generate the TPs sequentially, and this is considered as computationally costly for high-order and larger-sized polynomials. To this end, we present a new efficient solution to overcome the limitation of sequential algorithms. The presented algorithm us
... Show MoreIn modern hydraulic control systems, the trend in hydraulic power applications is to improve efficiency and performance. “Proportional valve” is generally applied to pressure, flow and directional-control valves which continuously convert a variable input signal into a smooth and proportional hydraulic output signal. It creates a variable resistance (orifice) upstream and downstream of a hydraulic actuator, and is meter in/meter out circuit and hence pressure drop, and power losses are inevitable. If velocity (position) feedback is used, flow pattern control is possible. Without aforementioned flow pattern, control is very “loose” and relies on “visual” feed back by the operator. At this point, we should examine how this valv
... Show MoreInstitutions and companies are looking to reduce spending on buildings and services according to scientific methods, provided they reach the same purpose but at a lower cost. On this basis, this paper proposes a model to measure and reduce maintenance costs in one of the public sector institutions in Iraq by using performance indicators that fit the nature of the work of this institution and the available data. The paper relied on studying the nature of the institution’s work in the maintenance field and looking at the type of data available to know the type and number of appropriate indicators to create the model. Maintenance data were collected for the previous six years by reviewing the maintenance and financial dep
... Show Moreتعتبر شبكية العين جزءًا مهمًا من العين لأن الأطباء يستخدمون صورها لتشخيص العديد من أمراض العيون مثل الجلوكوما واعتلال الشبكية السكري وإعتام عدسة العين. في الواقع، يعد تصوير الشبكية المجزأ أداة قوية للكشف عن النمو غير العادي في منطقة العين بالإضافة إلى تحديد حجم وبنية القرص البصري. يمكن أن يؤدي الجلوكوما إلى إتلاف القرص البصري، مما يغير مظهر القرص البصري للعين. تعمل تقنيتنا على الكشف عن الجلوكوما وتصنيفه
... Show MoreThe utilization of sugarcane molasses (SCM), a byproduct of sugar refining, offers a promising bio-based alternative to conventional chemical admixtures in cementitious systems. This study investigates the effects of SCM at five dosage levels, 0.25%, 0.50%, 0.75%, 1.00%, and 1.25% by weight of cement, on cement mortar performance across fresh, mechanical, thermal, durability, and density criteria. A comprehensive experimental methodology was employed, including flow table testing, compressive strength (7, 14, and 28 days) and flexural strength measurements, embedded thermal sensors for real-time hydration monitoring, water absorption and chloride ion penetration tests, as well as 28-day density determination. Results revealed clear
... Show MoreMO Khudhair, 2020
This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi
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