Current Issue : April-June Volume : 2022 Issue Number : 2 Articles : 5 Articles
The underlying infrastructure paradigms behind the novel usage scenarios and services are becoming increasingly complex—from everyday life in smart cities to industrial environments. Both the number of devices involved and their heterogeneity make the allocation of software components quite challenging. Despite the enormous flexibility enabled by component-based software engineering, finding the optimal allocation of software artifacts to the pool of available devices and computation units could bring many benefits, such as improved quality of service (QoS), reduced energy consumption, reduction of costs, and many others. Therefore, in this paper, we introduce a model-based framework that aims to solve the software component allocation problem (CAP).We formulate it as an optimization problem with either single or multiple objective functions and cover both cases in the proposed framework. Additionally, our framework also provides visualization and comparison of the optimal solutions in the case of multi-objective component allocation. The main contributions introduced in this paper are: (1) a novel methodology for tackling CAP-alike problems based on the usage of model-driven engineering (MDE) for both problem definition and solution representation; (2) a set of Python tools that enable the workflow starting from the CAP model interpretation, after that the generation of optimal allocations and, finally, result visualization. The proposed framework is compared to other similar works using either linear optimization, genetic algorithm (GA), and ant colony optimization (ACO) algorithm within the experiments based on notable papers on this topic, covering various usage scenarios—from Cloud and Fog computing infrastructure management to embedded systems, robotics, and telecommunications. According to the achieved results, our framework performs much faster than GA and ACO-based solutions. Apart from various benefits of adopting a multi-objective approach in many cases, it also shows significant speedup compared to frameworks leveraging single-objective linear optimization, especially in the case of larger problem models....
Software reliability model is the tool to measure the software reliability quantitatively. Hazard-Rate model is one of the most popular ones. The purpose of our research is to propose the hazard-rate model considering fault level for Open Source Software (OSS). Moreover, we aim to adapt our proposed model to the hazard-rate considering the imperfect debugging environment. We have analyzed the trend of fault severity level by using fault data in Bug Tracking System (BTS) and proposed our model based on the result of analysis. Also, we have shown the numerical example for evaluating the performance of our proposed model. Furthermore, we have extended our proposed model to the hazard-rate considering the imperfect debugging environment and showed numerical example for evaluating the possibility of application. As the result, we found out that performance of our proposed model is better than typical hazard-rate models. Also, we verified the possibility of application of proposed model to hazard-rate model considering imperfect debugging....
As power grids and optical interconnection networks are interdependent, the reliabilities of the optical networks are critical issues in power systems. The optical networks hold prominent performance including wide bandwidth, low loss, strong antiinterference capability, high fidelity, and reliable performance. They are regarded as promising alternatives to electrical networks for parallel processing. This paper is aimed at taking the first step in understanding the communication efficiencies of optical networks. For that purpose, on optical networks, we propose a series of novel notions including communication pattern, r-communication graph, reduced diameter, enhanced connectivity, r-diameter, and r-connectivity. Using these notions, we determine that the r-diameter and r-connectivity of the optical n-dimensional hypercube network are dn/re and n 1 ! + n 2 ! +⋯+ n r ! , respectively. Since the parameter r is variable, we can adjust different values of r on the basis of the wavelength resources and load of the optical networks, achieving enhanced communication efficiencies of these networks. Compared with the electric n-dimensional hypercube network, the proposed communication pattern on the optical hypercube network not only reduces the maximum communication delay of the conventional electrical hypercube significantly but also improves its fault tolerance remarkably....
Recognizing facial expressions accurately and effectively is of great significance to medical and other fields. Aiming at problem of low accuracy of face recognition in traditional methods, an improved facial expression recognition method is proposed. )e proposed method conducts continuous confrontation training between the discriminator structure and the generator structure of the generative adversarial networks (GANs) to ensure enhanced extraction of image features of detected data set. )en, the highaccuracy recognition of facial expressions is realized. To reduce the amount of calculation, GAN generator is improved based on idea of residual network.)eimage is first reduced in dimension and then processed to ensure the high accuracy of the recognition method and improve real-time performance. Experimental part of the thesis uses JAFEE dataset, CK+ dataset, and FER2013 dataset for simulation verification. )e proposed recognition method shows obvious advantages in data sets of different sizes. )e average recognition accuracy rates are 96.6%, 95.6%, and 72.8%, respectively. It proves that the method proposed has a generalization ability....
This study aimed to determine and analyze the performance of an electric motor installed in a small city car, which was an internal combustion engine (ICE) car with manual transmission and front-wheel drive converted into an electric vehicle. A manual transmission vehicle was used, considering its type is the cheapest. This was to push aside the perception that electric cars are not accessible to the lower classes. Another technical matter was the focus on the power and torque performance of the electric motor and the transmission. A 7.5 KW three-phase induction motor was installed and assembled with 200 AH 76.8 VDC batteries. Electronic power steering (EPS) and the air conditioner (AC) were not operated, while power for the electrical accessories and power analyzer was obtained from a separate 12 VDC battery. Vehicle analysis focused on the power consumption, which was measured and acquired using a power analyzer. The vehicle was driven in real terms with three passengers. GPS was also used to determine the vehicle position and collect elevation data during testing. The derivatives of the GPS data were the speed, acceleration, and distance traveled by the vehicle. The initial hypothesis was that the car could cover a distance of 30 km with regular usage....
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