An Optimization on the Neuronal Networks Based on the ADEX Biological Model in Terms of LUT-State Behaviors: Digital Design and Realization on FPGA Platforms

Wang, Yule; Taylan, Osman; Alkabaa, Abdulaziz S.; Ahmad, Ijaz; Eldin, Sayed M.; Nazemi, Ehsan; Balubaid, Mohammed; Alqabbaa, Hanan Saud

doi:10.3390/biology11081125

Cited by 7 publications

(4 citation statements)

References 20 publications

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“…Mold can be caused by high humidity levels, which can also result in financial damage. A low-level humidity produces various respiratory illnesses and also increase cancer rate and different diseases [58][59][60][61][62] and makes it easier for viruses to proliferate, while a high humidity level leads to condensation and mold growth.…”

Section: Discussionmentioning

confidence: 99%

Smart Android Based Home Automation System Using Internet of Things (IoT)

et al. 2022

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Recently, home automation system has getting significant attention because of the fast and advanced technology, making daily living more convenient. Almost everything has been digitalized and automated. The development of home automation will become easier and more popular because of the use of the Internet of Things (IoT). This paper described various interconnection systems of actuators, sensors to enable multiple home automation implementations. The system is known as HAS (Home automation system). It operates by connecting the robust Application Programming Interface (API), which is the key to a universal communication method. The HAS used devices, often implemented the actuators or sensors that have an upwards communication network followed by HAS (API). Most of the devices of the HAS (home automation system) used Raspberry Pi boards and ESP8285 chips. A smartphone application has been developed that allows users to control a wide range of home appliances and sensors from their smartphones. The application is user-friendly, adaptable, and beneficial for consumers and disabled people. It has the potential to be further extended via the use of various devices. The main objectives of this work are to make our home automation system, more secure and intelligent. HAS is a highly effective and efficient computational system that may be enhanced with a variety of devices and add-ons.

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Section: Discussionmentioning

confidence: 99%

Smart Android Based Home Automation System Using Internet of Things (IoT)

et al. 2022

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“…For BTs categorization and detection, various ML/DL models were employed [36]. DL model plays an important role in detection and classification in different areas [37][38][39][40][41][42][43][44][45]. In the literature, several alternative ways of identifying and classifying BTs have been established using magnetic resonance (MR) FLAIR images.…”

Section: Related Workmentioning

confidence: 99%

“…The hybrid DeepTumorNet model consists of CNN as a fundamental model hybrid with GoogleNet. Initially, to train the CNN model may occasionally take a few days and is a difficult task [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48]. It is preferable to first train the proposed model implements the TL model before hybridizing the CNN model.…”

Section: Proposed Modelmentioning

confidence: 99%

Brain Tumor Classification and Detection Using Hybrid Deep Tumor Network

et al. 2022

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Brain tumor (BTs) is considered one of the deadly, destructive, and belligerent disease, that shortens the average life span of patients. Patients with misdiagnosed and insufficient medical treatment of BTs have less chance of survival. For tumor analysis, magnetic resonance imaging (MRI) is often utilized. However, due to the vast data produced by MRI, manual segmentation in a reasonable period of time is difficult, which limits the application of standard criteria in clinical practice. So, efficient and automated segmentation techniques are required. The accurate early detection and segmentation of BTs is a difficult and challenging task in biomedical imaging. Automated segmentation is an issue because of the considerable temporal and anatomical variability of brain tumors. Early detection and treatment are therefore essential. To detect brain cancers or tumors, different classical machine learning (ML) algorithms have been utilized. However, the main difficulty with these models is the manually extracted features. This research provides a deep hybrid learning (DeepTumorNetwork) model of binary BTs classification and overcomes the above-mentioned problems. The proposed method hybrid GoogLeNet architecture with a CNN model by eliminating the 5 layers of GoogLeNet and adding 14 layers of the CNN model that extracts features automatically. On the same Kaggle (Br35H) dataset, the proposed model key performance indicator was compared to transfer learning (TL) model (ResNet, VGG-16, SqeezNet, AlexNet, MobileNet V2) and different ML/DL. Furthermore, the proposed approach outperformed based on a key performance indicator (Acc, Recall, Precision, and F1-Score) of BTs classification. Additionally, the proposed methods exhibited high classification performance measures, Accuracy (99.51%), Precision (99%), Recall (98.90%), and F1-Score (98.50%). The proposed approaches show its superiority on recent sibling methods for BTs classification. The proposed method outperformed current methods for BTs classification using MRI images.

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“…Plenty of potential and research are evident in this area. MiStore [ 18 ] is considered a medical and health insurance system using blockchain that secures and encrypts health-related data [ 1 , 9 , 10 , 14 , 18 , 19 , 20 , 21 , 22 ]. The present research article discusses and reviews the work currently being carried out in the field of healthcare blockchain applications along with its challenges, open issues in the existing scenario, future investigations of the blockchain in the healthcare sector, and a research perspective for securing healthcare data by presenting a novel approach verified by results and comparison with the existing approach.…”

Section: Introductionmentioning

confidence: 99%

A Novel Decentralized Blockchain Architecture for the Preservation of Privacy and Data Security against Cyberattacks in Healthcare

Kumar

Singh

Ahmad

et al. 2022

Sensors

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Nowadays, in a world full of uncertainties and the threat of digital and cyber-attacks, blockchain technology is one of the major critical developments playing a vital role in the creative professional world. Along with energy, finance, governance, etc., the healthcare sector is one of the most prominent areas where blockchain technology is being used. We all are aware that data constitute our wealth and our currency; vulnerability and security become even more significant and a vital point of concern for healthcare. Recent cyberattacks have raised the questions of planning, requirement, and implementation to develop more cyber-secure models. This paper is based on a blockchain that classifies network participants into clusters and preserves a single copy of the blockchain for every cluster. The paper introduces a novel blockchain mechanism for secure healthcare sector data management, which reduces the communicational and computational overhead costs compared to the existing bitcoin network and the lightweight blockchain architecture. The paper also discusses how the proposed design can be utilized to address the recognized threats. The experimental results show that, as the number of nodes rises, the suggested architecture speeds up ledger updates by 63% and reduces network traffic by 10 times.

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An Optimization on the Neuronal Networks Based on the ADEX Biological Model in Terms of LUT-State Behaviors: Digital Design and Realization on FPGA Platforms

Cited by 7 publications

References 20 publications

Smart Android Based Home Automation System Using Internet of Things (IoT)

Smart Android Based Home Automation System Using Internet of Things (IoT)

Brain Tumor Classification and Detection Using Hybrid Deep Tumor Network

A Novel Decentralized Blockchain Architecture for the Preservation of Privacy and Data Security against Cyberattacks in Healthcare

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