The manuscript conducts a comparative analysis to assess the impact of noise on medical images using a proposed threshold value estimation approach. It applies an innovative method for edge detection on images of varying complexity, considering different noise types and concentrations of noise. Five edges are evaluated on images with low, medium, and high detail levels. This study focuses on medical images from three distinct datasets: retinal images, brain tumor segmentation, and lung segmentation from CT scans. The importance of noise analysis is heightened in medical imaging, as noise can significantly obscure the critical features and potentially lead to misdiagnoses. Images are categorized based on the complexity, providing a multidimensional view of noise’s effect on edge detection. The algorithm utilized the grid search (GS) method and random search with nine values (RS9). The results demonstrate the effectiveness of the proposed approach, especially when using the Canny operator, across diverse noise types and intensities. Laplace operators are most affected by noise, yet significant improvements are observed with the new approach, particularly when using the grid search method. The obtained results are compared with the most popular techniques for edge detection using deep learning like AlexNet, ResNet, VGGNet, MobileNetv2, and Inceptionv3. The paper presents the results via graphs and edge images, along with a detailed analysis of each operator’s performance with noisy images using the proposed approach.

Use of a nonlinear prediction method, such as machine learning, is a valuable choice in predicting progression rate of disease when applied to the highly variable and correlated biological data such as those in patients with chronic lymphocytic leukemia (CLL). In this work, decision-tree approach to cell phenotype-based prognosis of CLL was adopted. The panel of 33 (32 different phenotypic features and serum concentration of sCD23) parameters was simultaneously presented to the C4.5 decision tree which extracted the most informative of them and subsequently performed classification of CLL patients against the modified Rai staging system. It has been shown that substantial correlation between the percentage of expression of the CD23 molecule on CD19⁺ B-cells, the level of sCD23, the percentage of CD45RA⁺, and the absolute number of CD4CD45RA⁺RO⁺ T-cells and the clinical stages, exists. The prediction vector, composed of their concatenated values, was able to correctly associate 83% of the cases in the low-risk group (Rai stage 0), 100% of the cases in the intermediate-risk group (Rai stage I and II), and 89% of the cases in the high-risk group (Rai stage III and IV) of CLL patients. Predictivity of this vector was 100%, 95%, and 89%, respectively. In conclusion, from the described analysis, it may be inferred that two processes play important roles in the progression rate of CLL: 1. deregulated function of the CD23 gene in B-cells accompanied by the appearance of its cleaved product sCD23 in the sera; and 2. functionally impaired and imbalanced CD4 T-cell subpopulations found in the peripheral blood of CLL patients. Am. J. Hematol. 59:143–148, 1998.

This paper considers the characteristics of satellite television transmission in the world. An overview of the development of satellite television is given through the following characteristics: broadcasting systems - analog and digital (SDTV, HDTV, UHDTV), frequency band (C, Ku, Ka), broadcasting standards (DVB-S, DVB-S2, DigiCipher, DSS), as well as the availability of TV services Free-To-Air TV (FTA) and PAY TV. All of these characteristics were considered both at the global and at the regional level: North America, South America, Europe, Africa, Russia, Asia, and Australia. The gathered data are presented in tabular form and presented graphically for the period from 1996 to 2018. Based on the presented results, an analysis of the development of satellite television transmission was carried out in accordance with the characteristics of the broadcast.

Macrodiversity system with macrodiversity SC receiver and three microdiversity MRC (maximum ratio combining) receivers is considered. Independent k-μ short-term fading and correlated Gamma long-term fading are present at the inputs of microdiversity MRC receivers. For this model, the probability density function and the cumulative density function of microdiversity MRC receivers and macrodiversity SC receiver output signal envelopes are calculated. Influences of Gamma shadowing severity, k-μ multipath fading severity, Rician factor and correlation coefficient at probability density function, and cumulative density function of macrodiversity SC receiver output signal envelopes are graphically presented.

This paper provides an analysis of the multiplexed video signal transmission through the Dense Wavelength Division Multiplexing (DWDM) network based on a quality check algorithm, which determines where the interruption of the transmission quality starts. On the basis of this algorithm, simulations of transmission for specific values of fiber parameters ​​ are executed. The analysis of the results shows how the BER and Q-factor change depends on the length of the fiber, i.e. on the number of amplifiers, and what kind of an effect the number of multiplexed channels and the flow rate per channel have on a transmited signals. Analysis of DWDM systems is performed in the software package OptiSystem 7.0, which is designed for systems with flow rates of 2.5 Gb/s and 10 Gb/s per channel.