Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in comparison with existing SVM algorithms.
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreTrajectory tracking and vibration suppression are essential objectives in a flexible joint manipulator control. The flexible joint manipulator is an under-actuated system, in which the number of control actions is less than the degree of freedom to be controlled. It is very challenging to control the underactuated nonlinear system with two degree of freedom. This paper presents a hierarchical sliding mode control (HSMC) for a rotary flexible joint manipulator (RFJM). Firstly, the rotary flexible joint manipulator is modeled by two subsystems. Secondly, the sliding surfaces for both subsystems are constructed. Finally, the control action is designed based on the Lyapunov function. Computer simulation results demonstrate the effectiveness of
... Show MoreThe educational sector is one of the important sectors in the world, and it is considered one of the means of community development. In addition, it is one of the means of making the country’s renaissance and devel-opment because it represents the factory of thinking minds that make change. There is no doubt that this sector is the same as any other sector. The deficit in the studied scientific planning has been prolonged, which led to its deterioration, and the problems of education remain diverse and inherited from previous time periods, where the hierarchical cluster analysis was used on postgraduate students in universities in Iraq, except for Kurdistan region, and the number of universities that were included in the study was
... Show MoreA common approach to the color image compression was started by transform
the red, green, and blue or (RGB) color model to a desire color model, then applying
compression techniques, and finally retransform the results into RGB model In this
paper, a new color image compression method based on multilevel block truncation
coding (MBTC) and vector quantization is presented. By exploiting human visual
system response for color, bit allocation process is implemented to distribute the bits
for encoding in more effective away.
To improve the performance efficiency of vector quantization (VQ),
modifications have been implemented. To combines the simple computational and
edge preservation properties of MBTC with high c
The current world seeks to supply the most of the fruits of human knowledge and tries hard to search for the most important scientific facts, programs, means and advanced devices in various fields, including the sports field, and among these means is the use of various and advanced training devices and programs for the purpose of achieving the desired goal, which is to reach the desired level, the basketball game is one of the sports that need high technology in training according to scientifically studied principles because it is one of the games that relate to the abundance of its variables, composition and speed of change, all of which require a technical and high training depth and the players ’possession of different physical charact
... Show MoreBackground: Although there is evidence of peer support in high-income countries, the use of peer support as an intervention for cardiometabolic disease management, including type 2 diabetes (T2DM), in low- and middle-income countries (LMICs), is unclear. Methods: A scoping review methodology was used to search the databases MEDLINE, Embase, Emcare, PsycINFO, LILACS, CDSR, and CENTRAL. Results: Twenty-eight studies were included in this scoping review. Of these, 67% were developed in Asia, 22% in Africa, and 11% in the Americas. The definition of peer support varied; however, peer support offered a social and emotional dimension to help individuals cope with negative emotions and barriers while promoting disease management. Conclusio
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