A Secured Database Monitoring Method to Improve Data Backup and Recovery Operations in Cloud Computing

BOHR International Journal of Computer Science, Journal Year: 2023, Volume and Issue: 2(1), P. 1 - 7

Published: Jan. 1, 2023

In general, the company sometimes uses unregistered functions in database, which significantly improves performance, but does not leave possibility of recovery except for backup. That is, actions must be performed immediately after passing session. A queue problem is likely to cause data loss and downtime about a week. modern conditions, this can lead bankruptcy company. It seen that backup systems have been installed configured, despite this, they succeeded restoring within time frame specified SLA. study, secured database monitoring method was proposed improve operations cloud computing. method, speed directly proportional amount data, while having at least 30% annual growth. 3–4 years, doubled, some companies, number even higher, change. Those terms those SLAs were relevant years ago now need doubled. At same time, business requirements (recovery point objective/recovery objective) continue grow

Language: Английский

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Examination of the Effects of Long-term COVID-19 Impacts on Patients with Neurological Disabilities Using a Neuromachine Learning Model

Deleted Journal, Journal Year: 2022, Volume and Issue: 1(1), P. 21 - 28

Published: Dec. 5, 2022

Currently, studies have shown that one in three people infected with coronavirus disease-19 (COVID-19) is likely to had long-term exposure COVID-19, known as COVID-19. Clinical indicate many the severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) COVID-19 pandemic exposure. According study, it has been said diabetes and obesity, who received organ transplants, are more suffer from this effect of In article, effects on neurological disability patients analyzed help a neuromachine learning model. The proposed model also shows COVID problem does not depend factors such race, age, gender, socioeconomic status those people. model, suffering problems continue physical fatigue shortness breath regularly monitored classified per instructions. Even after they recover disease, various side seen.

Language: Английский

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Design of biosensor for synchronized identification of diabetes using deep learning

Results in Engineering, Journal Year: 2023, Volume and Issue: 20, P. 101382 - 101382

Published: Sept. 3, 2023

A highly sensitive biosensor for the synchronized identification of diabetes is designed using a deep learning approach. The built on cutting-edge platform that combines nanotechnology with electrochemical processes. This makes it possible to diagnose accurately and quickly by detecting both in single test. novel creates very selective combining techniques. With high precision, this can identify presence glucose molecules blood. Also, differentiate between diabetes, which crucial precise diagnosis diabetes. far more than other techniques now use, detect levels at range 0.5–5 mmol per liter. study uses medical deep-learning model biosensor. significant development creation It will aid enhancing precision effectiveness diagnosis, enabling improved management condition. lower cost increasing accessibility individuals who require it. might be revolutionized new platform, making simpler efficient. In an evaluation point, proposed MDML achieved 96.21% accuracy, 91.53% 94.21% recall, 97.98% f1-score 89.90% diagnostic odds ratio.

Language: Английский

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An innovation prediction of DNA damage of melanoma skin cancer patients using deep learning

2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT), Journal Year: 2023, Volume and Issue: unknown, P. 1 - 7

Published: July 6, 2023

There are now a variety of intriguing options for the study genetic data thanks to recent developments in artificial neural networks and deep learning. In this study, we use learning-based prediction model find possible DNA damage individuals with melanoma skin cancer. We create convolutional network (CNN) forecast susceptibility cancer cells using publically available genome sequencing dataset. This preprocesses genomic data, extracts features, categorises them. Comparing results our CNN those traditional logistic regression model, that reported superior performance identifying differences between healthy cancerous samples an accuracy nearly 96%. The can be used augment standard clinical diagnosis melanoma, which only uses visual assessment histology. By intervening sooner, clinicians put forward more personalized informed plans care surveillance each patient, reducing medical costs improving quality patient diagnosis.

Language: Английский

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The three dimensional dosimetry imaging for automated eye cancer classification using transfer learning model

2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT), Journal Year: 2023, Volume and Issue: unknown, P. 1 - 6

Published: July 6, 2023

Computer vision methods utilizing transfer learning can offer a promising approach for automated eye cancer diagnosis with three-dimensional dosimetry imaging. The latest advances in AI have encouraged researchers to use deep models classification. This paper presents novel using imaging ocular classification learning. uses combination of dataset augmentation methods. is adapted from the popular Inception V3 CNN architecture. Two different feature extraction approaches, namely mean and maximum pooling, are compared while extracting features output layers. extracted fed classifier which SVM linear kernel as its decision system. effectiveness this method evaluated on set 20 healthy images 26 suspicious images. overall accuracy achieved 94.85%. results obtained demonstrate that has potential an appropriate model.

Language: Английский

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Machine Learning-based Evaluation of Heart Rate Variability Response in Children with Autism Spectrum Disorder

Published: Feb. 2, 2023

At present, various electronic devices are used to monitor human heart rates. However, its functions avoid predicting the problems caused by rate variability in advance and analyzing implications. It makes it difficult diagnose variability. A should have an average of 72. same time, newborn's beat between 120 160 beats per minute. baby born with autism spectrum disorder may a lower-than-average rate. Complete blockage at birth is rare. Abnormal leads block. So, there high chance child's death due permanent any time. Most diseases children Autism Spectrum Disorder (ASD) present birth. significant congenital disability hole heart. Many people do not realize that having holes common occurrence. Before born, tiny form muscular wall divides into right left halves. This paper proposed Machine Learning-Based Evaluation identify Heart Rate Variability Response Children Disorder. The reasons for this yet be identified. 70 cent perforations resolve spontaneously before or after Exceptionally, close properly require surgery perforator brace, depending on location size perforation.

Language: Английский

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The Examination of the Effects of Long-term COVID-19 Impacts on Patients with Neurological Disabilities Using a Neuromachine Learning Model

Deleted Journal, Journal Year: 2023, Volume and Issue: 1(1), P. 22 - 29

Published: Jan. 1, 2023

Currently, studies have shown that one in three people infected with coronavirus disease-19 (COVID-19) is likely to had long-term exposure COVID-19, known as COVID-19. Clinical indicate many the severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) COVID-19 pandemic exposure. According study, it has been said diabetes and obesity, who received organ transplants, are more suffer from this effect of In article, effects on neurological disability patients analyzed help a neuromachine learning model. The proposed model also shows COVID problem does not depend factors such race, age, gender, socioeconomic status those people. model, suffering problems continue physical fatigue shortness breath regularly monitored classified per instructions. Even after they recover disease, various side seen.

Language: Английский

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An earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning model

Published: Feb. 9, 2023

Language: Английский

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Pattern Recognition of Acute Lymphoblastic Leukemia (ALL) Using Computational Deep Learning

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 29541 - 29553

Published: Jan. 1, 2023

Leukemia is a cancer of blood-producing cells, including the bone marrow. Abnormal white blood cells travel through vessels and multiply rapidly. Healthy in body become minority, imbalance increases chances infection body. or most common children ages 2 - 14. Most leukemia treated. Acute lymphocytic (ALL) type It progresses rapidly when immature are formed instead mature ones. Treatments for acute include drugs transfusions directly into veins, chemotherapy, all transplantation, which involve transferring organs tissues within from one person to another. In this paper, Pattern Recognition Lymphoblastic has been proposed using Computational Deep Learning. recognition technology uses mathematical algorithms identify patterns large datasets data. Analyzing data, can indicative certain states conditions. case ALL, algorithm would look cell count data that indicate presence ALL. These may changes number over time, composition levels proteins gene expressions associated with The ALLDM model achieved 81.53% (DDS) 87.92% (SDS) chemotherapy management, 79.16% 94.31% Stem Cell Transplantation Management, 63.77% 87.37% Radiation therapy Management 88.92% 85.86% Targeted management.

Language: Английский

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Challenges and Opportunities in Additive Manufacturing Polymer Technology: A Review Based on Optimization Perspective

Advances in Polymer Technology, Journal Year: 2023, Volume and Issue: 2023, P. 1 - 18

Published: April 19, 2023

In the emerging modern technology of additive manufacturing, need for optimization can be found in literature many places. Additive manufacturing (AM) is making an object layer by directly from digital data. Previous works have classified processes into seven types. However, there a lack comprehensive review describing challenges and opportunities material extrusion process (polymer technology) also FDM polymer materials application impeller making. this paper, specific method called multicriteria decision-making (MCDM) mathematical programming technique used (AMPT) discussed. The other topics such as different types techniques, applications MCDM tools their fields including AM, AMPT particularly are

Language: Английский

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