82 hasil untuk "Musaed Alhussein"
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Artikel Jurnal
Monitoring Parkinson’s Disease in Smart Cities
Parkinson's Disease (PD) is one of the most severe neurological diseases prevalent in the world. A neurodegenerative disease, it impairs the body's balance, damages motor skills, and leads to disorder in speech production. These problems also affect decision-making processes and the expression of…
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Artikel Jurnal
Voice Pathology Detection Using Deep Learning on Mobile Healthcare Framework
The feasibility and popularity of mobile healthcare are currently increasing. The advancement of modern technologies, such as wireless communication, data processing, the Internet of Things, cloud, and edge computing, makes mobile healthcare simpler than before. In addition, the deep learning…
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Artikel Jurnal
Automatic Voice Pathology Monitoring Using Parallel Deep Models for Smart Healthcare
Recent advancements in wireless communication and machine learning technologies aid in the development of an accurate and affordable healthcare facility. In this paper, we propose a smart healthcare framework in a mobile platform using deep learning. In the framework, a smartphone records a voice…
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Artikel Jurnal
Convergence of Artificial Intelligence and Internet of Things in Smart Healthcare: A Case Study of Voice Pathology Detection
The integration of artificial intelligence (AI) and the Internet of Things (IoT) has tremendous prospects in smart healthcare. The advancement of AI in the form of deep learning brought a revolution in automatic classification and detection systems. In addition, next-generation wireless…
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Artikel Jurnal
Watermarking of Parkinson Disease Speech in Cloud-Based Healthcare Framework
Mobile healthcare in a cloud-based system increases the easiness and the ubiquitous nature of patient-doctor relationship. One of the major issues of this healthcare is secure transmission and data authenticity. If the data is not transmitted securely or not authenticated, the clients may face…
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Artikel Jurnal
Detection and Classification of Baseline-Wander Noise in ECG Signals Using Discrete Wavelet Transform and Decision Tree Classifier
An electrocardiogram (ECG) signal is usually contaminated with various noises, such as baseline-wander, power-line interference, and electromyogram (EMG) noise. Denoising must be performed to extract meaningful information from ECG signals for clinical detection of heart diseases. This work is…
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Artikel Jurnal
Analysis of Binary Image Coding Methods for Outdoor Applications of Wireless Vision Sensor Networks
The processing of images at the vision sensor nodes (VSN) requires a high computation power and their transmission requires a large communication bandwidth. The energy budget is limited in outdoor applications of wireless vision sensor networks (WVSN). This means that both the processing of images…
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Artikel Jurnal
Aspect Based Multi-Labeling Using SVM Based Ensembler
Sentiment analysis is one of the most prominent sub-areas of research in Natural Language Processing (NLP), where it is important to consider implicit or explicit emotions conveyed by review material. Researchers also recognized that the generic feelings derived from the textual material are…
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Artikel Jurnal
Data Reduction Using Change Coding for Remote Applications of Wireless Visual Sensor Networks
The data reduction capability of image compression schemes is limited by the underlying compression technique. For applications with minor changes between consecutive frames, change coding can be used to further reduce the data. We explored the efficiency of change coding for data reduction in a…
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Artikel Jurnal
Hybrid CNN-LSTM Model for Short-Term Individual Household Load Forecasting
Power grids are transforming into flexible, smart, and cooperative systems with greater dissemination of distributed energy resources, advanced metering infrastructure, and advanced communication technologies. Short-term electric load forecasting for individual residential customers plays a…
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Artikel Jurnal
An Unsupervised Retinal Vessel Segmentation Using Hessian and Intensity Based Approach
The structure of blood vessels play a crucial role in diagnoses of the various vision threatening diseases including Glaucoma and Diabetic Retinopathy (DR). The correct segmentation of retinal blood vessels is a crucial step in the study of retinal fundus images. We proposed a simple unsupervised…
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Artikel Jurnal Teks lengkap
Microgrid-Level Energy Management Approach Based on Short-Term Forecasting of Wind Speed and Solar Irradiance
Background: The Distributed Energy Resources (DERs) are beneficial in reducing the electricity bills of the end customers in a smart community by enabling them to generate electricity for their own use. In the past, various studies have shown that owing to a lack of awareness and connectivity, end…
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Artikel Jurnal
Retinal Vessel Segmentation Based on the Anam-Net Model
Accurate segmentation of retinal blood vessels can help ophthalmologists diagnose eye-related diseases such as diabetes and hypertension. The task of segmentation of the vessels comes with a number of challenges. Some of the challenges are due to haemorrhages and microaneurysms in fundus imaging…
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Artikel Jurnal
Vehicle License Plate Detection and Perspective Rectification
The character segmentation and perspective rectification of Vehicle License Plate (VLP) is essential in different applications, including traffic monitoring, car parking, stolen vehicle recovery, and toll payment. The character segmentation of the VLP and its horizontal as well as vertical (pan and…
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Artikel Jurnal
EEG Pathology Detection Based on Deep Learning
With the advancement of machine learning technologies, particularly deep learning, the automated systems to assist human life are flourishing. In this paper, we propose an automatic electroencephalogram (EEG) pathology detection system based on deep learning. Various types of pathologies can affect…
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Artikel Jurnal
Structured insight: an innovative disambiguation paradigm for semi-supervised partial label learning
Abstract Semi-Supervised Partial Label Learning (SPLL) aims to learn from both partial label data where each instance is associated with a candidate label set and unlabeled data. Most SPLL methods work by generating pseudo-candidate labels for unsupervised data. Since the pseudo candidate labels…
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Artikel Jurnal
Breast Cancer Survival Prediction Modeling Based on Genomic Data: An Improved Prognosis-Driven Deep Learning Approach
Breast cancer has a wide range of possible outcomes due to its complexity and heterogeneity. The process of manually detecting breast cancer is laborious, intricate, and inaccurate. It is essential for individualized treatment planning to have a reliable prognosis of patient survival. Increased…
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Artikel Jurnal
Research on Disease Prediction Based on Improved DeepFM and IoMT
In recent years, with the increase of computer computing power, Deep Learning has begun to be favored. Its learning of non-linear feature combinations has played a role that traditional machine learning cannot reach in almost every field. The application of Deep Learning has also driven the…
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Artikel Jurnal
A Pyramid-CNN Based Deep Learning Model for Power Load Forecasting of Similar-Profile Energy Customers Based on Clustering
With rapid advancements in renewable energy sources, billing mechanism (AMI), and latest communication technologies, the traditional control networks are evolving towards wise, versatile and collaborative Smart Grids (SG). The short term power load forecasting of individual as well as group of…
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Artikel Jurnal
A Fair Pricing Mechanism in Smart Grids for Low Energy Consumption Users
Based on energy demand, consumers can be broadly categorized into low energy consumers (LECs) and high energy consumers (HECs). HECs use heavy load appliances, e.g., electric heaters and air conditioners, and LECs do not use heavy load appliances. Thus, HECs demand more energy compared to LECs. The…