Traction force and power requirement when performing primary tillage occupy the minds of almost farmers, this field research had aim to determine and calculate the pulling force of the most commonly used moldboard and chisel plows, the research conducted in silt clay loam for chisel and moldboard plows as the main factor, two depths of tillage 18 and 25 cm as a second factor and three speeds of tractor 2.55, 4.30 and 6.15 km.h-1 as a third factor. Moldboard plow recorded least traction force 7.550 kN, drawbar power 11.583 hp, power losses due to slippage 1.088 hp, power on the rear axle of the tractor 15.770 hp and brake horse power 17.495 hp. Chisel plow recorded best traction efficiency 76.217 % and total traction efficiency 68.659 %. Dep

Abstract

Anaerobic digestion process of organic materials is biochemical decomposition process done by two types of digestion bacteria in the absence of oxygen resulting in the biogas production, which is produced as a waste product of digestion. The first type of bacteria is known as acidogenic which converts organic waste to fatty acids. The second type of bacteria is called methane creators or methanogenic which transforms the fatty acids to biogas (CH₄ and CO₂). The considerable amounts of biodegradable constitutes such as carbohydrates, lipids and proteins present in the microalgae biomass make it a suitable substrate for the anaerobic digestion or even c

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

The research aim at identifying the time of motor response to auditory and visual stimuli as well as identifying the accuracy of blocking and finding the relationship between motor repose time and blocking accuracy. The community was (7) primer soccer league of 2019 – 2020 and the subjects were (24) volleyball players from Al Jaish and Al Shorta clubs ten players from Al Shorta club performed the pilot study. The researchers used the descriptive method and the data was collected and treated using SPSS. The results showed a significant relationship between response time and blocking accuracy. The researchers recommended concentrating on applying scientific principles for developing time of motor response in a manner suitable for bl

The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

The aims of this study are to explore the commercial artifacts in the following three kinds of vegetables oils, Nigella Sativa, Trigonella foenum-graecum Linn,and Zingiber officinale. These oils have been very popular medicinal plants which are commonly used in traditional medicine .These commercial oils have been compared with the extracts of these plants.
The physical properties of extracts and commercial oils of these plants have been stuied. We observed that the refractive index of the plants matches and non-significant, while specific gravity of Nigella Sativa has similar specific gravity in both extracts and commercial oil in contrast with Trigonella foenum Linn,and Zingiber officinale and we found significant difference (P&lt

Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study