Algorithm process. by Wei Cui (92129)

“…Traditional network intrusion detection systems often rely on manually engineered features, which are not only resource-intensive but also struggle to handle the diverse range of attack types. This paper aims to address these challenges by proposing an automated DDoS attack detection algorithm using the Informer model. …”

Comparison of PSNR values of different algorithms. by Xiaojun Wang (50332)

Subjects:

Changes in FID values of different algorithms. by Xiaojun Wang (50332)

Subjects:

Comparison of SSIM values of different algorithms. by Xiaojun Wang (50332)

Subjects:

Changes in loss values for different algorithms. by Xiaojun Wang (50332)

Subjects:

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Three sensor sample data with noise data. by Tang Ruipeng (20141334)

Subjects:

Notations and definitions used in the algorithm. by Nazym Alimbekova (22766158)

Temperature sensor 2 sample data and data curve after noise reduction. by Tang Ruipeng (20141334)

Subjects:

Temperature sensor 1 sample data and data curve after noise reduction. by Tang Ruipeng (20141334)

Subjects:

Temperature sensor 3 sample data and data curve after noise reduction. by Tang Ruipeng (20141334)

Subjects:

Action potential of sample points in model 1. by Hang Zhao (143592)

Subjects:

Action potential of sample points in model 2. by Hang Zhao (143592)

Subjects:

Action potential of sample points in model 0. by Hang Zhao (143592)

Subjects:

The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

Subjects:

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. Next, we examine the statistical effect of correlated prediction error and propose a method for Generalized Least Squares (GLS) on graphs. …”

The accuracy of all employed learning algorithms. by Quan Shao (20148209)

Algorithm for constructing Boot-t CIs. by Qin Gong (118801)

“…<div><p>This article explores the estimation of Shannon entropy and Rényi entropy based on the generalized inverse exponential distribution under the condition of stepwise Type II truncated samples. Firstly, we analyze the maximum likelihood estimation and interval estimation of Shannon entropy and Rényi entropy for the generalized inverse exponential distribution. …”

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

Comparison of results based on CycleGAN method. by Xiaojun Wang (50332)

Subjects: