Comparative study of noise and digital filters for image processing

In recent years, in consumer electronics, the Health care system is the most important one to evaluate humans' diverse pathological activities. Collaborating with the biomedical field, electronics can find remedial designs for an artificial implant that functionalizes as a human organ to deal with different prostheses, therapy dialysis, etc., conditions and analyze the neural system responses. Using the advanced technological approach, the desired sub-blocks are to be designed to improve the Implant’s performance, especially in cost & market- production. This paper briefly explains the Bionic hearing-aid Implant recognized as a Cochlear implant and its architecture in.

Section: Finfet Trends In Cochlear Implantmentioning

confidence: 99%

Smart Medical Assistance using Soft Computing

Katikala,

Kumar,

Malapati

et al. 2023

“…This matter has been a focal point of investigation for an extended period. Anomaly and signature detection systems play a critical role in identifying and categorizing malicious activities [10][11][12][13][14][15][16]. In this study, the deep neural network technique is applied for detecting malicious instances, accompanied by a comprehensive range of metrics that assess the performance of the intrusion detection algorithm.…”

Section: Fig 3 Confusion Metric [System Generated]mentioning

confidence: 99%

Performance optimization for Intrusion Detection by Long Short Term Memory (LSTM)

Khatkar,

Kumar,

Kumar

et al. 2023

Concerns about cyber threats have emerged as the expansion of system connectivity and the proliferation of system applications intensified in the industry. This has underscored the necessity for a robust defense mechanism against various cyber threats, including potential intrusions from malicious actors within the network. A specially targeted system is the intrusion detection system (IDS), designed to safeguard the confidentiality, integrity, and availability of network traffic, especially in critical sectors like healthcare. Recent advancements in the area of IDS involve the utilization of artificial intelligence (AI) and deep learning (DL) based IDS to efficiently recognize network issues. Notably, the research at hand adopts a deep learning approach employing Long Short Term Memory (LSTM) models, applied to the CICIDS-2019 dataset that is sourced from New Brunswick University’s website. The focal point of evaluation lies in the precision, recall, F1-score, and accuracy metrics, specifically analyzing its performance in identifying Denial-of-Service (DoS) cyber-attacks. The findings of this study lighten the superior performance of the Long Short Term Memory method in the realm of intrusion detection systems. The LSTM model showcases its proficiency, particularly in discerning Denial of Service attacks by giving a loss of less than 0.03%.

“…The cost-effectiveness of various water desalination processes can be increased using AI technologies. Different machine learning algorithms, including random forest, support vector machine, image processing and digital filters [9,10], Deep learning and DSP [11,12], logistic regression, K-nearest neighbour, decision tree and AI-based algorithms, like the fuzzy inference system [7,[13][14][15][16][17][18][19][20], have been applied in recent studies. As a result, AI can enhance and support the processes of saltwater desalination and water treatment.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence in Water Desalination: A Novel Approach for Global Sustainability

Mahadeva,

Patel,

Ghosh

et al. 2023

Self Cite

Artificial intelligence (AI) is an efficient technique frequently used to tackle practical issues in various engineering and medical fields. Apart from different areas, water desalination is essential in surviving humans, animals, and plants. It is a crucial industry for a sustainable planet, and we cannot live without water. As a result, engineers and researchers are quite active in this area. Recent studies based on Elsevier’s Scopus database demonstrate how automation using emerging technologies has enhanced the traditional desalination process. AI offers enormous potential to address numerous problems and real-time optimization procedures. According to Elsevier’s Scopus database, water desalination has extensively used AI optimization tools, especially after 2010, such as artificial neural networks (ANN), genetic algorithms (GA), fuzzy logic, and natural swarm global optimization techniques to improve water quality and quantity. Finally, it was determined that AI technologies would surely pave the way for better operation, water resource management, and process automation in the water sector in an increasingly unstable climate.