In this study, the harvest of maize silage with the cross double row sowing method were tested with a single row disc silage machine in two different PTO applications (540 and 540E min-1) and at two different working speeds v1, v2 (1.8 and 2.5 km h-1). The possibilities of harvesting with a single row machine were revealed, and performance characteristics such as hourly fuel consumption, field-product fuel consumption and PTO power consumption were determined in the trials. The best results in terms of hourly fuel consumption and PTO power consumption were determined in the 540E PTO application and V1 working speed. When the fuel consumption of the field-product is evaluated, it is obtained with V2 working speed and 540E PTO application. As can be seen from the examination of all parameters, it has been concluded that the 540E PTO application for the forage harvester will provide advantages in terms of fuel consumption and area-product fuel consumption compared to the 540 application by taking action from the PTO. According to the results obtained from the study, it was suggested that the silage maize planted with the single-row machine and double-row sowing method can be harvested and the 540E PTO application was suggested as an important alternative to the 540 PTO application for silage machines with similar capacity and characteristics.
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreBotnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
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Abstract
Robotics manipulators with structural flexibility provide an attractive alternative to rigid robotics manipulators for many of the new and evolving applications in robotics. In certain applications their use is unavoidable. The increased complexity in modeling and control of such manipulators is offset by desirable performance enhancements in some respects. In this paperthe single- link flexible robotics manipulator was designed and implemented from Perspex and designed with 0.5 m length , 0.02 m width and with 0.004 m thickness with mass located at the tip. There are four subsystems; motion, control, accelerometer and gyro and a host computer subsystem. The work principle of single-link robotics manipul
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In this paper, a single-phase boost type ac-dc converter with power factor correction (PFC) technique is designed and implemented. A current mode control at a constant switching frequency is used as a control strategy for PFC converter. The PFC converter is a single-stage singleswitch boost converter that uses a current shaping technique to reshape the non-sinusoidal input current drawn by the bulky capacitor in the conventional rectifier. This technique should provide an input current with almost free-harmonics, comply with the IEC61000-3-2 limits, and a system operates with near unity power factor. The other function of the boost converter that should be
accomplished is to provide a regulated DC output voltage. The complete designed
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The influence of different thickness (500, 1000, 1500, and 2000) nm on the electrical conductivity and Hall effect measurements have been investigated on the films of copper indium gallium selenide CuIn1-xGaxSe2 (CIGS) for x= 0.6.The films were produced using thermal evaporation technique on glass substrates at R.T from (CIGS) alloy. The electrical conductivity (σ), the activation energies (Ea1, Ea2), Hall mobility and the carrier concentration are investigated and calculated as function of thickness. All films contain two types of transport mechanisms of free carriers, and increases films thickness was fond to increase the electrical cAnductivity whereas the activation energy (Ea) would vary with films thickness. Hall Effect analysis resu
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