ASRIC Journal on Natural Sciences 2023 v3-i1
ISSN: 2795-3610
EISSN: 2795-3629
ASRIC Journal on Natural Sciences 2023 v3-i1
Published: 2023-12-29
Articles
Ctgan Adversarial Attack on Network Intrusion Detection Based on Lstm Algorithm
Ahmad Abubakar Yunusa, Fatima Umar. Zambuk, Badamasi Imam. Ya’u, Abubakar Umar, Abdulkadir Hassan Disina
Deep neural networks have proven successful in the intrusion detection domain. Cyber security experts and designers must develop a variety of network intrusion detection systems to secure networks and computers from black hackers who might breach the network system and steal or damage important data from databases. Regrettably, recent studies revealed that adversarial samples can affect deep neura
Advancing Environmental Technology Through Computational Fluid Dynamics (CFD) and Design Simulation Analysis for Enhanced Performance and Sustainability
Ewelike Asterius Dozie*, Nnadikwe Johnson, Iheme Chigozie, Chikodi Daberechi Alaka, Wopara Onuoha Fidelis, Akuchie Justin Chukwuma
Advancing environmental technology through computational fluid dynamics (CFD) and design simulation analysis has emerged as a powerful approach to enhance performance and sustainability. This innovative combination allows for the optimization of various structures and systems, such as buildings, vehicles, and renewable energy devices, while minimizing their environmental impact. By simulating and
Revolutionizing Industrial Cleaning Techniques: Harnessing the Power of Algae and Sponge Iron to Combact Co2 in Biogas Production
Julius Ibeawuchi Onyewudiala*, Nnadikwe Johnson, Iheme Chigozie, Ibe Raymond Obinna, Alaka, Amarachi Chekosiba, Onuruka Anthony Uzodinma
This research focuses on revolutionizing industrial cleaning techniques by Harnessing the power of algae and sponge Iron to combat Co2 in biogas production. The objectives are to align this innovative approach with the United Nations sustainable development Goals (SDGs) while addressing the challenges posed by high concentration of methane ideal tool for reducing CO2 levels. This approach not o
Cytotoxic Evaluation of the Aqueous Extract of some Selected Medicinal Plants Combinations on Lung Carcinoma Epithelial Cells A549 and Human Cervix Carcinoma HeLa S330194
Tossou Sandra Bénédicta Kadoukpè*, Luka Carrol Domkat, Emmanuel Adeyemi, Jeffrey Matthew, Taiwo Emmanuel Alemika
Many are the anti-cancer drugs currently in use but unfortunately, they fail to differentiate cancer cells from healthy cells. The aim of this study is to find an alternative way based only on medicinal plants to treat cancer by enhancing the immune system without damaging the healthy cells for the well-being of the patient. This study investigated the cytotoxic effect(s) of (04) Combined Plants
Issues
