Blockchain-Based Internet of Medical Things

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(3), P. 1287 - 1287

Published: Jan. 18, 2023

IoMT sensor nodes, Internet of Things (IoT) wearable medical equipment, healthcare facilities, patients, and insurance firms are all increasingly being included in systems. Therefore, it is difficult to create a blockchain design for such systems, since scalability among the most important aspects technology. This realization prompted us comprehensively analyze blockchain-based solutions developed English between 2017 2022. review incorporates theoretical underpinnings large body work published highly regarded academic journals over past decade, standardize evaluation methods fully capture rapidly developing space. study categorizes blockchain-enabled applications across various industries as information management, privacy, healthcare, business, supply chains according structured, systematic evaluation, thematic content analysis literature that already identified. The gaps on topic have also been highlighted, with special focus restrictions posed by technology knock-on effects other fields. Based these results, several open research questions potential avenues further investigation likely be useful academics professionals alike pinpointed.

Language: Английский

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Data Mining Approach to Predict Success of Secondary School Students: A Saudi Arabian Case Study

Education Sciences, Journal Year: 2023, Volume and Issue: 13(3), P. 293 - 293

Published: March 9, 2023

A problem that pervades throughout students’ careers is their poor performance in high school. Predicting academic helps educational institutions many ways. Knowing and identifying the factors can affect of students at beginning thread help achieve goals by providing support to earlier. The aim this study was predict achievement early secondary students. Two sets data were used for school who graduated from Al-Baha region Kingdom Saudi Arabia. In study, three models constructed using different algorithms: Naïve Bayes (NB), Random Forest (RF), J48. Moreover, Synthetic Minority Oversampling Technique (SMOTE) technique applied balance extract features correlation coefficient. prediction has also been validated 10-fold cross-validation direct partition addition various evaluation metrics: accuracy curve, true positive (TP) rate, false (FP) accuracy, recall, F-Measurement, receiver operating characteristic (ROC) curve. NB model achieved a 99.34%, followed RF with 98.7%.

Language: Английский

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Prediction and detection of terminal diseases using Internet of Medical Things: A review

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 188, P. 109835 - 109835

Published: Feb. 24, 2025

Language: Английский

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Transfer Learning Approach to Seed Taxonomy: A Wild Plant Case Study

Big Data and Cognitive Computing, Journal Year: 2023, Volume and Issue: 7(3), P. 128 - 128

Published: July 4, 2023

Plant taxonomy is the scientific study of classification and naming various plant species. It a branch biology that aims to categorize organize diverse variety life on earth. Traditionally, has been performed using morphological anatomical characteristics, such as leaf shape, flower structure, seed fruit characters. Artificial intelligence (AI), machine learning, especially deep learning can also play an instrumental role in by automating process categorizing species based available features. This investigated transfer techniques analyze images plants extract features be used cluster hierarchically k-means clustering algorithm. Several pretrained models were employed evaluated. In this regard, two separate datasets comprising wild collected from Egypt. Extensive experiments method (DenseNet201) demonstrated proposed methods achieved superior accuracy compared traditional with highest 93% F1-score area under curve (AUC) 95%, respectively. That considerable contrast state-of-the-art approaches literature.

Language: Английский

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Oil and Gas Pipelines Leakage Detection Approaches: A Systematic Review of Literature

International Journal of Safety and Security Engineering, Journal Year: 2024, Volume and Issue: 14(3), P. 773 - 786

Published: June 24, 2024

In terms of its significance, the oil & gas industry is ranked among top global industries.Like any other industry, it also faces various problems, such as leakage and pipelines.The detection in pipelines essential for an or plant to operate properly maintain environmental safety well minimize supply-chain losses.The undergoing study systematically reviews literature comprising more than a decade (2010-2021) span summarize systems, methods techniques used pipeline detection.Likewise, this paper investigates effective low-cost systems with their pros cons.The existing are classified into three categories based on technical characteristics, named hardware-based (where some hardware deployed monitoring leakage), software-based software intelligent predictive algorithm detection) techniques.Each technique was reviewed according datasets used, preprocessing (mainly that imagery image largely like enhancement, denoising filtering), investigated classifiers' efficiencies, results, limitations.A comparative analysis conducted help determine which technology best given operational environment, software, hardware, hybrid.Further, highlights gaps research unresolved concerns regarding development dependable leak suggests possible directions mitigate it.

Language: Английский

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Assessing Acetabular Index Angle in Infants: A Deep Learning-Based Novel Approach

Journal of Imaging, Journal Year: 2023, Volume and Issue: 9(11), P. 242 - 242

Published: Nov. 6, 2023

Developmental dysplasia of the hip (DDH) is a disorder characterized by abnormal development that frequently manifests in infancy and early childhood. Preventing DDH from occurring relies on timely accurate diagnosis, which requires careful assessment medical specialists during X-ray scans. However, this process can be challenging for personnel to achieve without proper training. To address challenge, we propose computational framework detect pelvic imaging infants utilizes pipelined deep learning-based technique consisting two stages: instance segmentation keypoint detection models measure acetabular index angle assess affliction presented case. The main aim provide an objective unified approach diagnosis. model achieved average pixel error 2.862 ± 2.392 range 2.402 1.963° measurement relative ground truth annotation. Ultimately, deep-learning will integrated into fully developed mobile application make it easily accessible test evaluate. This reduce burden while providing explainable diagnosis infants, thereby increasing their chances successful treatment recovery.

Language: Английский

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Spam and Sentiment Detection in Arabic Tweets Using MARBERT Model

Mathematical Modelling and Engineering Problems, Journal Year: 2022, Volume and Issue: 9(6), P. 1574 - 1582

Published: Dec. 31, 2022

Saudi Telecom Company (STC) is among the most popular companies in Arabia, with many customers. Yet, there still a big room for improvement users' satisfaction. Social media robust platform to gauge satisfaction and determine their sentiments critics. Twitter social this regard. STC customers prefer use write feedback because it's fast way get responses due customer services account. One achieve demands improve service using Sentiment Analysis tool. on highly used of significant number tweets different opinions. Likewise, Deep learning best existing method, it has diverse models. Bidirectional Encoder Representations from Transformers (BERT) model one deep models which have achieved excellent results Natural Language Processing (NLP). NLP mainly investigated English language. However, Arabic, gap be filled. This study trained proposed MARBERT measured performance f1-score, precision, recall metrics. We an Arabic dataset 24,513 tweets, including 1,437 positive, 13,828 negative, 5,694 neutral, 1,221 sarcasm, 2,297 indeterminate tweets. The main goal analyze sentiment service. scheme promising terms accuracy contrast techniques literature.

Language: Английский

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Ensemble Machine Learning Based Identification of Adult Epilepsy

Mathematical Modelling and Engineering Problems, Journal Year: 2023, Volume and Issue: 10(1), P. 84 - 92

Published: Feb. 28, 2023

Epilepsy is a chronic non-communicable illness that affects brain individuals and impacts more than 50 million people globally.To predict epileptic seizures, we proposed machine learning-based ensemble learning technique in this study.In the preprocessed stage, applied some important techniques such as Power line noise reduction dividing record into windows of 5 seconds.The project created by help technique, which employs several algorithms, used following algorithms: decision tree, support vector machine, artificial neural networks, convolutional networks.We dataset from PhysioNet website contains adult EEG signals.Several layers were to extract features signals, after that, feature set utilized train classifier model, combines results.Our approach successfully reached 91% accuracy while sensitivity specificity, respectively.

Language: Английский

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Blockchain Security-Efficiency Analysis based on DEA-SBM Model

The Eurasia Proceedings of Science Technology Engineering and Mathematics, Journal Year: 2023, Volume and Issue: 23, P. 202 - 208

Published: Oct. 16, 2023

It is estimated that by 2023 the security market will reach a value of $1.4 billion. This growth primarily driven increasing use technology in sectors like finance, healthcare and logistics. As more companies adopt there growing need to protect their data from hacking other malicious activities. The network plays role ensuring implementation adoption technology. Given rise cyberattacks breaches it expected importance continue grow coming years. In this study we explore some specialize providing solutions. Our analysis be based on three factors two desired outcomes. selected include Hacken, Quantstamp, OpenZeppelin, Trail Bits, ConsenSys, Certik, LeastAuthority, PWC Switzerland, Slowmist Runtime Verification. purpose research paper assess effectiveness industry for decision makers, experts government entities. By gaining insights into sector enhancing measures implementations, across industries.

Language: Английский

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The Synergy of Artificial Intelligence and Cybersecurity

Published: Feb. 26, 2024

As the menace of cyber threats intensifies, artificial intelligence emerges as a crucial tool for enhancing cybersecurity. This article delves into advantages and drawbacks AI in The findings highlight positive outcomes preventing gathering information about attacks using AI. In summary, advancing is imperative to address attacks' escalating volume intricacy, recognizing that cybercriminals also leverage their malicious activities.

Language: Английский

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