Network in Sequential Form: Combine Tree Structure Components into Recurrent Neural Network

Zubair, Swaleha; Singha, Anjani Kumar

doi:10.1088/1757-899x/1017/1/012004

Cited by 11 publications

(4 citation statements)

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“…have had any specific benefit [25] [26] [27] [28] [29].According to those research [30] [31], pharmacotherapy seeks to improve perception as well as decrease nevertheless, symptoms; the therapeutic compounds provide only limited advantages to patients. (Cholinesterase inhibitors (Rivastigmine,Galantamine, Donepezil) and Memantine may help to slow or stop the progression of the disease [32].In particular, the new Memantine appears to just be beneficial in terms of mental ability at all stages of the disease, particularly in individuals with moderate mental disability [33].SSRIs have been proven to slow down the progression of initial mental deterioration in Alzheimer's disease, and in the absence of anxiety. It is most likely owing to SSRIs' effect on the development of -amyloid precursor protein, which is a histological basis of Alzheimer's disease.…”

Section: Resultsmentioning

confidence: 99%

Impact of music therapy treatment on brain structure in early stages of Alzheimer’s disease

Gupta¹

2022

JUSST

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Aim:The Object of this research is to exhibit the potency and advantage of music therapy for Keepers and Alzheimer’s disease (AD) people. Methods: From 2020 to 2021, a research group scrutinized and investigated 32 persons with Alzheimer’s Disease (ICD-10) medicated by general practitioners, music psychotherapists and neurologists through MMSE. The musical brain analysis with medical results of the patients was estimated and also the response of the tutors and the Patients of Alzheimer’s were Noted. In Family or Personal Sessions, musical instruments were added. The MMSE was used for the patient’s Evaluation Purpose. Under Neurologist’s Supervision, the examination was re-conducted every six months. Finally, 31 patients withAlzheimer’s Medication were Observed And calculated.

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Section: Resultsmentioning

confidence: 99%

Impact of music therapy treatment on brain structure in early stages of Alzheimer’s disease

Gupta¹

2022

JUSST

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“…phenomenon, for example, has been demonstrated in the neural network of the Caenorhabditis elegans worm [17]. Following discovered of similar topological characteristics in human brain networks, such as encephalography recordings [18], cortical connections analyses [19], and the medial reticular development of the brain stem [20]. The original gradient descent algorithm has been improved in several ways.…”

Section: Related Workmentioning

confidence: 99%

Performance Enhancement of Adaptive Neural Networks Based on燣earning燫ate

Zubair¹,

Singha²,

Pathak³

et al. 2023

Computers, Materials &Amp; Continua

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Deep learning is the process of determining parameters that reduce the cost function derived from the dataset. The optimization in neural networks at the time is known as the optimal parameters. To solve optimization, it initialize the parameters during the optimization process. There should be no variation in the cost function parameters at the global minimum. The momentum technique is a parameters optimization approach; however, it has difficulties stopping the parameter when the cost function value fulfills the global minimum (non-stop problem). Moreover, existing approaches use techniques; the learning rate is reduced during the iteration period. These techniques are monotonically reducing at a steady rate over time; our goal is to make the learning rate parameters. We present a method for determining the best parameters that adjust the learning rate in response to the cost function value. As a result, after the cost function has been optimized, the process of the rate Schedule is complete. This approach is shown to ensure convergence to the optimal parameters. This indicates that our strategy minimizes the cost function (or effective learning). The momentum approach is used in the proposed method. To solve the Momentum approach non-stop problem, we use the cost function of the parameter in our proposed method. As a result, this learning technique reduces the quantity of the parameter due to the impact of the cost function parameter. To verify that the learning works to test the strategy, we employed proof of convergence and empirical tests using current methods and the results are obtained using Python.

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“…This technology along with the Internet of Things has brought so many changes in the industries and helps to develop business models as well as distributed applications. There are reports that blockchain and the Internet of Things can work together to facilitate resource and service exchanges between devices [14,15]. Christidis et al [16] pointed out, that the point-point distribution and public ledger functions of blockchain will be a fit for the cloud computing services, and it includes the data sources, auditing, digital asset management, and the distributed consensus.…”

Section: Introductionmentioning

confidence: 99%

Smart Quarantine Environment Privacy through IoT Gadgets Using Blockchain

Pathak¹,

Siddiqui²,

Singha³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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The coronavirus, formerly known as COVID-19, has caused massive global disasters. As a precaution, most governments imposed quarantine periods ranging from months to years and postponed significant financial obligations. Furthermore, governments around the world have used cutting-edge technologies to track citizens' activity. Thousands of sensors were connected to IoT (Internet of Things) devices to monitor the catastrophic eruption with billions of connected devices that use these novel tools and apps, privacy and security issues regarding data transmission and memory space abound. In this study, we suggest a blockchain-based methodology for safeguarding data in the billions of devices and sensors connected over the internet. Various trial secrecy and safety qualities are based on cutting-edge cryptography. To evaluate the proposed model, we recommend using an application of the system, a Raspberry Pi single-board computer in an IoT system, a laptop, a computer, cell phones and the Ethereum smart contract platform. The models ability to ensure safety, effectiveness and a suitable budget is proved by the Gowalla dataset results.

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Network in Sequential Form: Combine Tree Structure Components into Recurrent Neural Network

Cited by 11 publications

References 0 publications

Impact of music therapy treatment on brain structure in early stages of Alzheimer’s disease

Impact of music therapy treatment on brain structure in early stages of Alzheimer’s disease

Performance Enhancement of Adaptive Neural Networks Based on燣earning燫ate

Smart Quarantine Environment Privacy through IoT Gadgets Using Blockchain

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