Autism Spectrum Diagnosis using Adaptive Learning Algorithm for Multiple MLP Classifier

Safara, Fatemeh

doi:10.54216/jisiot.020201

Cited by 6 publications

(4 citation statements)

References 20 publications

(27 reference statements)

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“…Clinical and wellbeing administrations are a perplexing complex, including infection counteraction, medical care, sickness conclusion and therapy, medical procedure, recovery, and subject logical examination. The intervention of smart medical care will bring huge opportunities and challenges to the medical and health industry [ 8 , 9 ]. Smart healthcare connects information related to medical construction in an intelligent and perceptible way to create an intelligent healthcare ecosystem [ 10 – 12 ].…”

Section: Smart Healthcare and Related Methodsmentioning

confidence: 99%

“…In any case, the deficiency of these examinations is that the models built utilizing shrewd clinical consideration are not sufficiently logical and the information should be gotten to the next level. e intervention of smart medical care will bring huge opportunities and challenges to the medical and health industry [8,9]. Smart healthcare connects information related to medical construction in an intelligent and perceptible way to create an intelligent healthcare ecosystem [10][11][12].…”

Section: Related Workmentioning

confidence: 99%

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Cleaning Quality Control Management of Medical Equipment in Hospital Disinfection Supply Room Based on Smart Medicine

Wang

Cheng

2022

Computational Intelligence and Neuroscience

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With the continuous improvement of medical level, the demand for medical devices increases year by year, and it is necessary to track the quality and safety of medical devices. Establishing the cleaning quality control management of medical devices can not only reduce medical accidents and inhibit the spread of counterfeit or substandard medical devices but also help enterprises find the source of problems, determine the flow of the same batch of products, and warn relevant enterprises to take measures after the occurrence of problem products, and ultimately ensure the rights and interests of consumers. This study aims to study the cleaning quality control management of medical equipment in the hospital disinfection supply room based on smart medical care and proposes related concepts of smart medical care, as well as related theories of Internet of Things technology and medical equipment tracking system and related concepts of medical equipment cleaning. In this study, by comparing the cleaning compliance rates of the two groups of medical devices through smart medical care, it can be seen that 100% of the research group applying program-based management is significantly higher than 76.6% of the conventional management path. There was statistical significance in the data comparison between groups ( P < 0.05 ). Therefore, programmatic management is more targeted than conventional management paths.

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Section: Smart Healthcare and Related Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Cleaning Quality Control Management of Medical Equipment in Hospital Disinfection Supply Room Based on Smart Medicine

Wang

Cheng

2022

Computational Intelligence and Neuroscience

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“…However, FL faces challenges in asset management, particularly in PM applications. The article proposes two federated algorithms, Federated Support Vector Machine (FedSVM) and Federated Long-Short Term Memory (FedLSTM) [18], for PM applications, which allow factories at the fog level to maximize the accuracy of their PM models without compromising privacy. The proposed algorithms aim to enable collaborative PM applications that are efficient, accurate, and secure.…”

Section: Literature Reviewmentioning

confidence: 99%

Flexible English Learning Platform using Collaborative Cloud-Fog-Edge Networking

Chen,

Tang

2023

SCPE

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In the modern age, developing practical online learning tools for English language learners is challenging due to existing systems’ shortcomings. These systems often need proper instructional design, are well-connected to motivational theories, and have limited infrastructure for data sharing, leading to poor learning outcomes and low motivation. To tackle these issues, a new approach called OAELT has been proposed in this paper. OAELT is an Online Assisted English Learning Tool that uses the Fuzzy Analytical Hierarchy Process (FAHP) and collaborative cloud-fog-edge networking to create a flexible learning design that adapts to the needs and preferences of individual learners. Using the FAHP approach, OAELT provides an improved learning experience by tailoring its design to each learner’s unique needs. The collaborative cloud-fog-edge networking approach uses each computing layer’s strengths to deliver a personalized and seamless learning experience. OAELT employs adaptive and dynamic approaches within a flexible instructional paradigm to ensure effective instructional design. This paradigm facilitates collective learning data exchange across cloud, fog, and edge computing layers. The effectiveness of OAELT was evaluated using a descriptive statistics approach, which included a five-dimension questionnaire for students covering cognition, emotion, action, cooperation, and literacy. The results demonstrated that OAELT could enhance learning effectiveness and motivation while providing a flexible and seamless learning experience. According to the experimental data of the proposed model, 46.8% of learners often read English magazines and newspapers to improve their flexibility in English learning. Additionally, 50.4% classified and memorized English according to their categories, while 59% of learners often used context to memorize. These findings suggest that the traditional methods for flexible English learning are not adequate, and the average score of the student’s methods and strategies is mediocre. However, after using OAELT, some students have been able to use different learning curricular reading. Overall, OAELT’s integration of cloud-fog-edge computing with a flexible English learning design can create a more effective and personalized learning system that addresses the challenges of modern learning.

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“…An adaptive learning system is a learning system designed and developed using arti cial intelligence techniques based on the learner's model [1]. It is a learning environment that meets the individual needs of learners, both in terms of theoretical study and technical functions.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Learning Model of English Vocabulary Based on Blockchain and Deep Learning

2022

Mobile Information Systems

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As one of the three basic elements of language, vocabulary is particularly important when learning English. Nowadays, many students are faced with problems such as boring vocabulary teaching, forgetting quickly after reciting, inefficient vocabulary learning, and lack of initiative. Therefore, it is imperative to seek a scientific and effective teaching mode to improve students’ vocabulary achievement. It builds an adaptive learning model of English vocabulary based on blockchain and deep learning, and tests the model. According to the experimental data, 46.8% of the learners will often read English newspapers or magazines to expand their English vocabulary. 50.4% of the students classified and memorized English vocabulary according to different categories. 59% of students often use context to memorize English vocabulary. The results show that before using the English vocabulary adaptive learning model based on blockchain and moderate learning, the average score of students’ methods and strategies is in the middle and lower levels. After using the adaptive learning model, some students have been able to use some learning strategies, and a small number of students have expanded their vocabulary through extracurricular reading.

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Autism Spectrum Diagnosis using Adaptive Learning Algorithm for Multiple MLP Classifier

Cited by 6 publications

References 20 publications

Cleaning Quality Control Management of Medical Equipment in Hospital Disinfection Supply Room Based on Smart Medicine

Cleaning Quality Control Management of Medical Equipment in Hospital Disinfection Supply Room Based on Smart Medicine

Flexible English Learning Platform using Collaborative Cloud-Fog-Edge Networking

Adaptive Learning Model of English Vocabulary Based on Blockchain and Deep Learning

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