Efficient Flow Processing in 5G-Envisioned SDN-Based Internet of Vehicles Using GPUs

Abbasi, Mahdi; Najafi, Ali; Rafiee, Milad; Khosravi, Mohammad R.; Menon, Varun G.; Muhammad, Ghulam

doi:10.1109/tits.2020.3038250

Cited by 27 publications

(9 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Abbasi and Rafiee [31] presented a new analysis framework for predicting the performance of packet classification algorithms on GPU-like highly threaded machines. Nowadays, the internet of things (IoT) has attracted many researchers and academics due to its innovative functions and applications in many fields, such as smart city applications [32] and intelligent transportation systems [33].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Wear Rates of UHMWPE Bearing in Hip Joint Prosthesis with Support Vector Model and Grey Wolf Optimization

Hammam

Attar

Amer

et al. 2022

Wireless Communications and Mobile Computing

Self Cite

View full text Add to dashboard Cite

One of the greatest challenges in joint arthroplasty is to enhance the wear resistance of ultrahigh molecular weight polyethylene (UHMWPE), which is one of the most successful polymers as acetabular bearings for total hip joint prosthesis. In order to improve UHMWPE wear rates, it is necessary to develop efficient methods to predict its wear rates in various conditions and therefore help in improving its wear resistance, mechanical properties, and increasing its life span inside the body. This article presents a support vector machine using a grey wolf optimizer (SVM-GWO) hybrid regression model to predict the wear rates of UHMWPE based on published polyethylene data from pin on disc (PoD) wear experiments typically performed in the field of prosthetic hip implants. The dataset was an aggregate of 29 different PoD UHMWPE datasets collected from Google Scholar and PubMed databases, and it consisted of 129 data points. Shapley additive explanations (SHAP) values were used to interpret the presented model to identify the most important and decisive parameters that affect the wear rates of UHMWPE and, therefore, predict its wear behavior inside the body under different conditions. The results revealed that radiation doses had the highest impact on the model’s prediction, where high values of radiation doses had a negative impact on the model output. The pronounced effect of irradiation doses and surface roughness on the wear rates of polyethylene was clear in the results when average disc surface roughness R a values were below 0.05 μm, and irradiation doses were above 95 kGy produced 0 mg/MC wear rate. The proposed model proved to be a reliable and robust model for the prediction of wear rates and prioritizing factors that most significantly affect its wear rates. The proposed model can help material engineers to further design polyethylene acetabular linings via improving the wear resistance and minimizing the necessity for wear experiments.

show abstract

Section: Introductionmentioning

confidence: 99%

Prediction of Wear Rates of UHMWPE Bearing in Hip Joint Prosthesis with Support Vector Model and Grey Wolf Optimization

Hammam

Attar

Amer

et al. 2022

Wireless Communications and Mobile Computing

Self Cite

View full text Add to dashboard Cite

show abstract

“…For example, look at how the pixels in these two images are arranged along the red line, Figs. (11)(12) Notice that how the two pixels in the zoomed image are placed side by side; they can be the same as the original diameter of the ellipse and can be considered to determine the angle of the actual diameter with the horizontal axis of the image rotation field, Fig. (13), Fig.…”

Section: Tilt and Rotation Of The Plate Improvementmentioning

confidence: 99%

“…This method produces acceptable results when captured license plate image is subjected to high intensity of light or when the vehicle and license plate area have approximately similar colors. Various factors such as camera quality, distance, and weather affect the quality and precision of algorithm performance discussed in this paper [11]. The proposed algorithm is robust to these issues with an acceptable level of accuracy.…”

Section: Introductionmentioning

confidence: 98%

Design and Matlab Simulation of Persian License Plate Recognition Using Neural Network and Image Filtering for Intelligent Transportation Systems

Akbarzadeh

Khosravi

Alex³

2022

ASP Trans. Pattern Recognit. Intell. Syst.

Self Cite

View full text Add to dashboard Cite

Vehicles play a vital role in modern-day intelligent transportation systems (ITS). Plate characters provide a standard means of identification for any vehicle. To serve this purpose, an automatic license plate recognition system is studied. In this paper, we intend to create an optimized algorithm for implementing the scheme. Firstly, we undertake several challenging stages. The first step is introduced as the determination of plate location. Then, in the second phase, we apply an initial improvement to decline the likely noises using the Gaussian function to provide an appropriate filter for this target. Next, the rest of the project is organized as follows, finding the edge of images, enhancing modified pictures, and selecting the exact place of the plate. Afterward, tilting and plate rotation improvement and plate characters' extraction are considered two essential steps in this regard. Eventually, the final step of this project consists of several stages, such as employing a neural network to extract the plate characters automatically.

show abstract

“…As a future application of the proposed approach, it can be used for future smart cities where high-performance energy systems in cooperation with many other technologies must be accessible, for example, IT infrastructure [26][27][28], wireless sensor systems [29], intelligent transport systems [30][31][32], industrial developments and cyber-physical systems [33-38], and monitoring systems [39-42].…”

Section: Transformers Technical Datamentioning

confidence: 99%

Optimized Economic Loading of Distribution Transformers Using Minimum Energy Loss Computing

Agha

Attar

Luhach

2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

This paper presents an approach to achieve the Economic Loading of Distribution Transformer (ELDT) based on minimizing the active energy loss. The effects of the transformer on-load and no-load losses, load factor (LF), and load loss factor (LSF) on the total energy losses are considered. The adopted technique in this paper consists of two phases, where ELDT is determined analytically in the first phase, and the load profile adequated (LSF) is statistically obtained in the second one. The results declare that the proposed technique is suitable for the shifts system mode of operation such as in industrial plants. Moreover, this paper investigates the effect of the total active and reactive power and energy losses on ELDT. Finally, numerical examples with software analyses are performed as a valuable tool, which supports the decision-makers to decide trustfully the size of the transformer and its capacity (kVA) during the design stage, as well as to determine the economic loading during the operation based on the effective factors, that is, total power, energy losses, and the load profile.

show abstract

Efficient Flow Processing in 5G-Envisioned SDN-Based Internet of Vehicles Using GPUs

Cited by 27 publications

References 25 publications

Prediction of Wear Rates of UHMWPE Bearing in Hip Joint Prosthesis with Support Vector Model and Grey Wolf Optimization

Prediction of Wear Rates of UHMWPE Bearing in Hip Joint Prosthesis with Support Vector Model and Grey Wolf Optimization

Design and Matlab Simulation of Persian License Plate Recognition Using Neural Network and Image Filtering for Intelligent Transportation Systems

Optimized Economic Loading of Distribution Transformers Using Minimum Energy Loss Computing

Contact Info

Product

Resources

About