Recently, research studies were directed to the construction of a universal defect prediction model. Such models are trained using different projects to have enough training data and be generic. One of the main challenges in the construction of a universal model is the different distributions of metrics in various projects. In this study, we aim to build a universal defect prediction model to

As a powerful optimization algorithm for solving nonlinear, complex and tough global optimization problems, differential evolution (DE) has been widely applied in various science and engineering fields. In this article, considering that the evolution direction of each individual is not fully exploited to guide the search process in most DE algorithms, a new DE variant ( named ADEwSE), which

Left ventricle (LV) segmentation is crucial to assess left ventricle global function. U-Net; a Convolutional Neural Network (CNN); boosted the performance of many biomedical image segmentation tasks. In LV segmentation, U-Net suffered from accurately extracting small objects such as the apical short-axis slices. In this paper, we propose a fully automated left ventricle segmentation method for

This paper develops a lane-change geometric representation that can be used in an on-road vehicle. The design of the proposed system uses the data collected from active a host vehicle and measures the relative speed between host vehicle and obstacle vehicles in real-time. The available distance to the target lanes measures the separated distance between the host and obstacle vehicles in real-time

Meta-heuristic optimization algorithms are the new gate in solving most of the complicated nonlinear systems. So, improving their robustness, reliability, and convergence speed is the main target to meet the requirements of various optimization problems. In the current work, three different fractional-order chaos maps (FC-maps), which have been introduced recently, are incorporated with the

Water buffalo (Bubalus bubalis) is an important source of meat and milk in countries with relatively warm weather. Compared to the cattle genome, a little has been done to reveal its genome structure and genomic traits. This is due to the complications stemming from the large genome size, the complexity of the genome, and the high repetitive content. In this paper, we introduce a high-quality

This paper is concerned with the evaluation of nuclear research reactor under two types of predictive controllers. The first one is Receding Horizon Predictive Controller (RHPC) which is considered a simple linear predictive controller. The other one is Neural Network Predictive Controller (NNPC) which is a type of nonlinear predictive controller. These controllers are applied over multi-point

Recently, the topology control solutions that use static transmission power, transmission range, and link quality, might not be useful. The objective of this paper adapts the transmission power to be adjusted with external changes by applying a machine learning algorithms. We develop a traffic signature algorithm based on traffic clusters of the network sites that have the same behavior then we

This paper presents the application of gaining sharing knowledge (GSK) based optimization algorithm to an uncertain solid transportation (UST) problem. The UST problem consists of supply, demand, and conveyance constraints under uncertain environment. To solve the said problem, the expected criterion model is considered so that the expected value of the objective function is minimized. 99-method

In 2017, pneumonia was the primary diagnosis for 1.3 million visits to the Emergency Department (ED) in the United States. The mortality rate was estimated to be 5%-10% of hospitalized patients, whereas it rises to 30% for severe cases admitted to the Intensive Care Unit (ICU). Among all cases admitted to ED, 30% were misdiagnosed, and they did not suffer from pneumonia, which raises a flag for