Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE), Borderline-SMOTE + Imbalanced Ratio(IR), Adaptive Synthetic Sampling (ADASYN) +IR) Algorithm, where the work these techniques are generate the synthetic samples for the minority class to achieve balance between minority and majority classes and then calculate the IR between classes of minority and majority. Experimental results show ImprovedSMOTE algorithm outperform the Borderline-SMOTE + IR and ADASYN + IR algorithms because it achieves a high balance between minority and majority classes.
This research is studying technique sculptures super - realism, search through, how the method of work, and the search for the materials used in their manufacture, and this is the first study in the field of art and the field of academic study in the country.Research consists of an introduction, And four sections, The introduction containing information on: research problem, Importance of research, Goals of the research, Limits of research, research approach, and research tools.The first section contains a technical study sculptures super -realism in contemporary sculpture, while the second section includes a search for alternative materials available in the local markets, for making sculptures super - realism, the third section dedicate
... Show MoreThis study investigates the changes occurring in the province of Basra using geospatial methods and analyzes the variations in land surface temperature among the various types of land cover. For the months of July and December in the years 2013 and 2021, Landsat images were used in Landsat 8 OLI/TIRS, and satellite images were processed using ArcGIS 10.8 software. The study's categories for land use and land cover were generated through the application of supervised classification techniques, and the land surface temperature was calculated using data from a satellite sensor's brightness temperature. According to the study's findings, there has been an increase in urban areas (including barren land). From 2013 to 2021, a greater correlati
... Show MoreIn this study, a 3 mm thickness 7075-T6 aluminium alloy sheet was used in the friction stir welding process. Using the design of experiment to reduce the number of experiments and to obtain the optimum friction stir welding parameters by utilizing Taguchi technique based on the ultimate tensile test results. Orthogonal array of L9 (33) was used based on three numbers of the parameters and three levels for each parameter, where shoulder-workpiece interference depth (0.20, 0.25, and 0.3) mm, pin geometry (cylindrical thread flat end, cylindrical thread with 3 flat round end, cylindrical thread round end), and thread pitch (0.8, 1, and 1.2) mm) this technique executed by Minitab 17 software. The results showed th
... Show MoreBackground: despite the rise in the incidence of renal cell carcinoma attributed to availability of medical imaging, a considerable decline in mortality is an association. Morbidity-wise, the shift from radical nephrectomy to partial nephrectomy is the trend for now. Multiple scoring systems have been introduced over the past decades to help surgeons choose between radical and partial nephrectomy. One commonly used system is the RENAL nephrometry score that was first introduced by Kutikov and Uzzo in 2009.
Objective: to evaluate the role of RENAL nephrometry scoring system in predicting the surgical technique to use to resect renal masses and associated perioperative outcomes.
... Show MoreThin films ZrO2: MgO nanostructure have been synthesized by a radio frequency magnetron plasma sputtering technique at different ratios of MgO (0,6, 8 and 10)% percentage to be used as the gas sensor for nitrogen dioxide NO2. The samples were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) and sensing properties were also investigated. The average particle size of all prepared samples was found lower than 33.22nm and the structure was a monoclinic phase. The distribution of grain size was found lower than36.3 nm and uninformed particles on the surface. Finally, the data of sensing properties have been discussed, where the
... Show MoreThe purpose of this paper is to identifying the values of some physical and Bio- Kinematic variables during the performance of the jump spike serve skill, and identifying the effect of the proposed training program using intermittent training to develop some physical and Bio- Kinematic variables and accuracy of the jump spike serve skill among the research sample. The experimental method was used and the research was conducted on a deliberately chosen sample of the players of the Army Club, who were primarily advanced in volleyball, and the number of the sample was (10) players. The conclusions were reached that the proposed training program using intermittent training has a positive effect on some of the physical and Bio- Kinematic variabl
... Show MoreThe rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines
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