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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Applied Engineering and Technology
Mohseni, Milad
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Evaluating the impact of COVID-19 on the monetary crisis by machine learning Mohseni, Milad
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 12, No 3: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v12i3.pp272-283

Abstract

In this study, machine learning is examined in relation to commercial machine learning's resilience to the COVID-19 pandemic-related crisis. Two approaches are used to assess the pandemic's impact on machine learning risk, as well as a method to prioritize sectors according to the crisis's potential negative consequences. I conducted the study to determine Santander machine learning's resilience. The data mining area offers prospects for COVID-19's future. A total of 13 machine learning demos were selected for its organization. The Hellweg strategy and the technique for order preference by similarity to ideal solution (TOPSIS) technique were utilized as direct request strategies. Parametric assessment of machine learning versatility in business was based on capital sufficiency, liquidity proportion, market benefits, and share in an arrangement of openings with a perceived disability, and affectability of machine learning's credit portfolio to monetary hazard. As a result of the COVID-19 pandemic, these enterprises were ranked according to their threat. Based on the findings of the research, machine learning worked the best for the pandemic. Meanwhile, machine learning suffered the most during the downturn. It can be seen, for example, in conversations about the impact of the pandemic on developing business sector soundness and managing financial framework solidity risk.
Implementation of a new coding scheme for improving the SET operations in Phase Change Memory (PCM) Mohseni, Milad
Applied Engineering and Technology Vol 2, No 2 (2023): August 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i2.1006

Abstract

Among Non-Volatile Memories (NVMs), PCMs are considered the best alternative to DRAM (dynamic random-access memories). As a result of its superior performance and scalability, there are several advantages over DRAM, including lower leakage and energy consumption, higher cell number, and smaller cells. This kind of memory does, however, suffer from a long write latency. In this article, we present a technique to reduce write latency by reducing the number of SET operations. The proposed method is an improved Write Time Speed-up (WTS) code scheme. In the proposed scheme, a new code based on hamming weight is given, and an appropriate algorithm is written to reduce the number of SET operations. Compared with current methods, the proposed scheme decreased SET and RESET operations by 3.9 percent, SET operations by 3.3 percent, and power consumption by 2.6 percent. Visual Basic 6 and GEM 5 simulations are used to simulate the suggested method
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