Journal of Artificial Intelligence Research & Advances
Volume 10, Issue 1 (2023)
Published
Table of contents
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Machine Learning Based Automated Detection of Sepsis: A Study
Abstract: Sepsis is a serious condition that occurs when the body's response to infection leads to tissue damage, organ failure, or death. Human body generally releases chemicals into the blood vessels to fight any kind of infection. Approximately 30 million people suffer from sepsis and 6 million people die from sepsis every year according to WHO. Around 4 million 200 thousand new-born and children are affected by sepsis all over the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 1–10 Read article
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Application of Generic Multi-criteria Economic Model for Line Balancing to a Hypothetical Organization Using Soft Computing Techniques
Abstract: Total Productive Manufacturing (TPM) is feasible only if the Overall Equipment Effectiveness (OEE) of the production line meets world-class standards. In the current research, crisp and fuzzy simulation models are developed and implemented for exploring OEE parameters for a hypothetical manufacturing organization. As OEE parameters, availability, performance efficiency, and quality, in turn, depend on several other parameters, a sort of cascaded effect is generated which can effectively be modeled as …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 105–122 Read article
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Detection of Cardiovascular Disease using AI and ML: A Review
Abstract: In the 21st century according to statistics, the risk of cardiovascular disease has become more common and the death rate caused by it is increasing way more. Around 17.9 million lives are taken by CVDs each year. There are various reasons causing it but most importantly it is caused by not identifying it, hence it becomes a very important task for the human race to identify the CVDs and deal …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 11–21 Read article
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Oculight: AI Based System for Visual Assistance to Blind and Visually Impaired People
Abstract: This research introduces a new captioning model that utilizes both image and caption models to produce textual descriptions of images. By combining a convolutional neural network (CNN) and a long short-term memory (LSTM) recurrent neural network (RNN), this deep learning architecture offers a promising solution for improving the quality of life and independence of blind people through AIbased systems. The system's implementation on an Android device ensures that it is …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 22–29 Read article
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Survey of Liver Disease Prediction Using Machine Learning
Abstract: Liver disease is one of the major causes of death in all over world that impacts the number of people around the world. Diagnosis of liver at early stages is crucial to reduce morality. As technology is growing in health care, machine learning significantly affects health care for predicting conditions at early stages. This study reviews the different approaches based on machine learning and deep learning to predict liver disease. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 30–38 Read article
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Use of Machine Learning to Identify Plant Disease: A Review
Abstract: As the population is increasing in India, there is a constant problem of food, its main reason is plant diseases. A lot of scientists are looking for new technology to solve this problem. One of the important techniques among them is machine learning. We can find plant diseases with the help of machine learning because machine learning by analysing the data (e.g., plant colour, leaf shape) finds the disease of …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 39–48 Read article
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An Efficient Deep Learning Classifiers Algorithm for Examining Public Perception of Covid SOPs
Abstract: In December 2019, Wuhan, China, reported the first coronavirus case, confirming the current pandemic. Following that, it swept across the entire world. The leading cause of this disease is still unknown, though. Governments are emphasizing physical distance and wearing masks in public places. The people mostly ignore the safety SOPs, which results in a surge in infected people rates and a healthcare burden on the national economy. Through the identification …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 49–70 Read article
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Comparing Algorithm Performance in Machine Learning for Landslide Susceptibility Studies: An Overview
Abstract: Machine learning algorithms have gained popularity over the past years, and with this comes the rise in their efficiencies; this study demonstrated that machine learning algorithms could successfully be used to identify landslide susceptibility areas. Machine learning algorithms like decision trees, support vector machines, K-Means, Hierarchical Clustering, Self-Organizing Maps (SOMs), artificial neural networks, and Bayesian networks have been used in recent studies. This study thus reviews several studies and results …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 71–89 Read article
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Prediction of Air Pollution LSTM Model Use in Machine Learning
Abstract: A major environmental problem that has an impact on the health and happiness of millions of people is air pollution. Accurate air quality forecasting is crucial for maintaining human health, the environment, and urban planning. In recent years, machine learning algorithms, such as Long Short-Term Memory (LSTM) models, have been increasingly used to predict air pollution levels. This study presents an abstract for a system that uses an LSTM model …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 90–98 Read article
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Data Maneuvering Identification
Abstract: Copy-move forgery detection (CMFD) is unquestionably one of the most active research areas in the field of blind image forensics. Most existing algorithms rely on block and key-point strategies, either separately or jointly. Recent applications of deep convolutional neural network (CNN) techniques include image forensics, image hashing retrieval, and picture classification. These techniques have outperformed more conventional techniques in many areas. In this study, a brand-new convolutional neural network based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 99–104 Read article