Computer-aided system for extending the performance of diabetes analysis and prediction

Murad, Saydul Akbar; Azmi, Zafril Rizal M.; Hakami, Zaid; Prottasha, Nusrat Jahan; Kowsher,

doi:10.1109/icsecs52883.2021.00091

Cited by 11 publications

(6 citation statements)

References 15 publications

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“…With the passage of time, the online quiz has piqued the curiosity of both faculty and students. People in major cities and companies are realizing how much better and more efficient the online quiz system is [5]. This system has recently been introduced into the technological world.…”

Section: Imentioning

confidence: 99%

The Development and Deployment of an Online Exam System: A Web Application

Islam

Salah

Murad

et al. 2023

AJRCoS

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The rapid advancements in computer technology and the internet’s acceptance in every aspect of our lives, particularly in recent years, have made students and instructors vital in the teaching and learning sector. Web-based studies have also brought about advances in the education area, and numerous applications have become widespread in this field. In this paper, we suggested an online test multiple-choice question assessment system for students called the Online Exam System (OES). This system may be used by any university, college, or institution that has a computerized education system. The OES can be used by teachers to administer quizzes. The system will calculate the participant’s performance based on his response, and the following question will be created based on the participant’s performance. After the examination, the system will display the results and offer feedback based on the participant’s request. Administrative control over the entire system is available. A teacher has authority over the question bank and is responsible for creating test schedules. Therefore, the project will be very helpful for the beginner and mid-level programming learners. And also, will give a proper guideline to the students who are willing to learn programming and introduce the users with competitive programming and problem-solving skills.

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Section: Imentioning

confidence: 99%

The Development and Deployment of an Online Exam System: A Web Application

Islam

Salah

Murad

et al. 2023

AJRCoS

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“…The KNN method calculates the shortest distance between the selected neighbors. To determine distances between existing data points and any new data point, the KNN employs the Euclidean distance equation [10]. Euclidean distance can be measured as follows:…”

Section: Model Buildingmentioning

confidence: 99%

“…In [8], the author has created prediction algorithms to assess the health data for children with Asthma. These prediction models are developed using machine learning classifiers, including linear regression, decision trees, the Random Forest, KNN [9] and methods of the Naive Bayes [10,11]. They got a good accuracy [12] for random forest classifiers and it's around 91%.…”

Section: Introductionmentioning

confidence: 99%

AI Powered Asthma Prediction Towards Treatment Formulation: An Android App Approach

Murad¹,

Adhikary²,

Muzahid³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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Asthma is a disease which attacks the lungs and that affects people of all ages. Asthma prediction is crucial since many individuals already have asthma and increasing asthma patients is continuous. Machine learning (ML) has been demonstrated to help individuals make judgments and predictions based on vast amounts of data. Because Android applications are widely available, it will be highly beneficial to individuals if they can receive therapy through a simple app. In this study, the machine learning approach is utilized to determine whether or not a person is affected by asthma. Besides, an android application is being created to give therapy based on machine learning predictions. To collect data, we enlisted the help of 4,500 people. We collect information on 23 asthma-related characteristics. We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.

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“…However, this approach hampers the resource utilization of a cloud server because faster machines are more occupied than others, which also deteriorates the completion time of all tasks, referred to as makespan. Similarly, priority driven algorithms like PBFS [14] and SG-PBFS [15] perform scheduling by favoring shorter tasks to execute first, which also degrades the resource utilization and response time for bigger tasks. To handle all tasks and resources without any preferences for shorter/larger tasks or slower/faster machines, meta-heuristic algorithms have proven promising.…”

Section: Introductionmentioning

confidence: 99%

Parallel Enhanced Whale Optimization Algorithm for Independent Tasks Scheduling on Cloud Computing

Khan,

Aziz,

Osman

et al. 2024

IEEE Access

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Cloud computing has been imperative for computing systems worldwide since its inception. The researchers strive to leverage the efficient utilization of cloud resources to execute workload quickly in addition to providing better quality of service. Among several challenges on the cloud, task scheduling is one of the fundamental NP-hard problems. Meta-heuristic algorithms are extensively employed to solve task scheduling as a discrete optimization problem and therefore several meta-heuristic algorithms have been developed. However, they have their own strengths and weaknesses. Local optima, poor convergence, high execution time, and scalability are the predominant issues among meta-heuristic algorithms. In this paper, a parallel enhanced whale optimization algorithm is proposed to schedule independent tasks in the cloud with heterogeneous resources. The proposed algorithm improves solution diversity and avoids local optima using a modified encircling maneuver and an adaptive bubble net attacking mechanism. The parallelization technique keeps the execution time low despite its internal complexity. The proposed algorithm minimizes the makespan while improving resource utilization and throughput. It demonstrates the effectiveness of the proposed PEWOA against the best performing enhanced whale optimization algorithm (WOAmM) and Multi-core Random Matrix Particle Swarm Optimization (MRMPSO). The algorithm consistently produces better results with varying number of tasks on GoCJ dataset, indicating better scalability. The experiments are conducted in CloudSim utilizing a variety of GoCJ and HCSP instances. Various statistical tests are also conducted to evaluate the significance of the results.

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Computer-aided system for extending the performance of diabetes analysis and prediction

Cited by 11 publications

References 15 publications

The Development and Deployment of an Online Exam System: A Web Application

The Development and Deployment of an Online Exam System: A Web Application

AI Powered Asthma Prediction Towards Treatment Formulation: An Android App Approach

Parallel Enhanced Whale Optimization Algorithm for Independent Tasks Scheduling on Cloud Computing

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