In this study, the dynamic modeling and step input tracking control of single flexible link is studied. The Lagrange-assumed modes approach is applied to get the dynamic model of a planner single link manipulator. A Step input tracking controller is suggested by utilizing the hybrid controller approach to overcome the problem of vibration of tip position through motion which is a characteristic of the flexible link system. The first controller is a modified version of the proportional-derivative (PD) rigid controller to track the hub position while sliding mode (SM) control is used for vibration damping. Also, a second controller (a fuzzy logic based proportional-integral plus derivative (PI+D) control scheme) is developed for both vibra

Peer-Reviewed Journal

This study focuses on producing wood-plastic composites using unsaturated polyester resin reinforced with Pistacia vera shell particles and wood industry waste powder. Composites with reinforcement ratios of 0%, 20%, 30%, and 40% were prepared and tested for thermal conductivity, impact strength, hardness, and compressive strength. The results revealed that thermal conductivity increases with reinforcement, while maintaining good thermal insulation, reaching a peak value of 0.633453 W/m·K. Hardness decreased with increased reinforcement, reaching a minimum nominal hardness value of 0.9479. Meanwhile, impact strength and compressive strength improved, with peak values of 14.103 k/m² and 57.3864568 MPa, respectively. The main aim is to manu

The current research deals with short term forecasting of demand on Blood material, and its' problem represented by increasing of forecast' errors in The National Center for Blood Transfusion because using inappropriate method of forecasting by Centers' management, represented with Naive Model. The importance of research represented by the great affect for forecasts accuracy on operational performance for health care organizations, and necessity of providing blood material with desired quantity and in suitable time. The literatures deal with subject of short term forecasting of demand with using the time series models in order to getting of accuracy results, because depending these models on data of last demand, that is being sta

Insurance is one of effective high-impact activities in the economic and social aspects of development and that the insurance companies after the creation of stability, balance and support other sectors. The insurance of financial institutions with economic and social importance has an impact on the development and help shoulder the burden of risk and distribution. And measuring Indicators of service and cost her help in evaluating the performance and activity of insurance, and the study of sectors needed by society, institutions and individuals and development of the company. Covering all aspects of life and activity. In this study will focus on the insurance sector in the field of car accidents and so plentiful and their problems and d

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o