Due to the increased use of cloud computing services, cloud data centers are in search of solutions in order to better provide the services demanded by their users. Virtual machine consolidation is an appropriate solution to the trade-off between power consumption and service level agreement violation. The present study aimed to identify low, medium, and high load identification techniques, as well as the energy consumption and SLAv to minimize. In addition to the reduced costs of cloud providers, these techniques enhance the quality of the services demanded by the users. To this end, reallocation of resources to physical hosts was performed at the medium load level using a centralized method to classify the physical hosts. In addition, quartile was applied in each medium to reduce the energy consumption parameters and violation level. The three introduced SMT - NMT and FMT methods for reallocation of resources were tested and the best results were compared with previous methods.The proposed method was evaluated using the Cloudsim software with real Planet Lab data and five times run, the simulation results confirmed the efficiency of the proposed algorithm, which tradeoff between decreased the energy consumption and service level of agreement violation (SLAv) properly. Manuscript profile

Gastric cancer is the second most common cancer worldwide, responsible for the death of many people in society. One of the issues regarding this disease is the absence of early and accurate detection. In the medical industry, gastric cancer is diagnosed by conducting numerous tests and imagings, which are costly and time-consuming. Therefore, doctors are seeking a cost-effective and time-efficient alternative. One of the medical solutions is Chinese medicine and diagnosis by observing changes of the tongue. Detecting the disease using tongue appearance and color of various sections of the tongue is one of the key components of traditional Chinese medicine. In this study, a method is presented which can carry out the localization of tongue surface regardless of the different poses of people in images. In fact, if the localization of face components, especially the mouth, is done correctly, the components leading to the biggest distinction in the dataset can be used which is favorable in terms of time and space complexity. Also, since we have the best estimation, the best features can be extracted relative to those components and the best possible accuracy can be achieved in this situation. The extraction of appropriate features in this study is done using deep convolutional neural networks. Finally, we use the random forest algorithm to train the proposed model and evaluate the criteria. Experimental results show that the average classification accuracy has reached approximately 73.78 which demonstrates the superiority of the proposed method compared to other methods. Manuscript profile

The Air Traffic Management system is a complex issue that faces factors such as Aircraft Crash Prevention, air traffic controllers pressure, unpredictable weather conditions, flight emergency situations, airplane hijacking, and the need for autonomy on the fly. agent-based software engineering is a new aspect in software engineering that can provide autonomy. agent-based systems have some properties such: cooperation of agents with each other in order to meet their goals, autonomy in function, learning and Reliability that can be used for air traffic management systems. In this paper, we first study the agent-based software engineering and its methodologies, and then design a agent-based software model for air traffic management. The proposed model has five modules .this model is designed for aircraft ,air traffic control and navigations aids factors based on the Belief-Desire-Intention (BDI) architecture. The agent-based system was designed using the agent-tool under the multi-agent system engineering (MaSE) methodology, which was eventually developed by the agent-ATC toolkit. In this model, we consider agents for special occasions such as emergency flights’ and hijacking airplanes in airport air traffic management areas which is why the accuracy of the work increased. It also made the flight’s sequence arrangement in take-off and landing faster, which indicates a relative improvement in the parameters of the air traffic management Manuscript profile