Volume 2, Issue 4
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Editorial
Front Cover

Publication Month: January 2022, Page(s): A1 – A1 

Editorial Board

Publication Month: January 2022, Page(s): B1 – B1

Editorial

Publication Month: January 2022, Page(s): C1 – C1

Table of Contents

Publication Month: January 2022, Page(s): D1 – D1

Articles
Graph-based Tool for Bandwidth Estimation, Health Monitoring and Update Planning in Broadband Networks

Gian Paolo Jesi, Andrea Odorizzi, Gianluca Mazzini

J. Engg. Res. & Sci. 2(4), 1-13 (2023);

This paper focuses on the genesis and evolution of our specific Company tool. It is aimed to tackle the problem of verifying the health status and availability of residual bandwidth between any node over the Lepida ScpA broadband network. In fact, there must be a correspondence between active contractual obligations signed by local network operators and the physical bandwidth which we allocate. This is the key factor that must be addressed in the early phases when processing any bandwidth requests from local customers. Before the introduction of our tool, this verification process has been carried out almost manually with a substantial cost in terms of time. The adoption of this in-house developed tool allowed us to substantially shrink of the verification time required and to provide an overview of the network status. Our tool is grounded on building a graph representation of the network and on well known graph algorithms.

An advanced load-line analysis software is devised for nonlinear circuit design and simulation of microwave low-distortion, high-efficiency and high-power GaN HEMT amplifiers. A single software package can incorporate DC, small- and large-signal performances of GaN HEMT devices, and then analyze nonlinear performance of amplitude-to-amplitude (AM-AM) and amplitude-to-phase (AM-PM) modulations, and finally evaluate intermodulation distortion (IMD) and error vector measurement (EVM). High speed and high accurate simulation become available with the use of behavioral modeling for representing nonlinear performance of GaN HEMT devices. In addition, the software employs a time-domain analysis using time-varying electrical waveform and thus give clear and deep insight into the nonlinear behavior of GaN HEMT devices as well as the nonlinear circuit design technique of low-distortion and high-efficiency amplifiers. In comparison with the harmonic-balance (HB) method, comparable performances have been successfully achieved for an L-band 10W GaN HEMT amplifier.

Classification of Rethinking Hyperspectral Images using 2D and 3D CNN with Channel and Spatial Attention: A Review

Muhammad Ahsan Aslam, Muhammad Tariq Ali, Sunwan Nawaz, Saima Shahzadi, Muhammad Ali Fazal

J. Engg. Res. & Sci. 2(4), 22-32 (2023);

It has been demonstrated that 3D Convolutional Neural Networks (CNN) are an effective technique for classifying hyperspectral images (HSI). Conventional 3D CNNs produce too many parameters to extract the spectral-spatial properties of HSIs. A channel service module and a spatial service module are utilized to optimize characteristic maps and enhance sorting performance in order to further study discriminating characteristics. In this article, evaluate CNN’s methods for hyperspectral image categorization (HSI). Examined the replacement of traditional 3D CNN with mixed feature maps by frequency to lessen spatial redundancy and expand the receptive field. Evaluates several CNN stories that use image classification algorithms, elaborating on the efficacy of these approaches or any remaining holes in methods. How do improve those gaps for better image classification?

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