33 hasil untuk "Reem ALOTAIBI"
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Artikel Jurnal Teks lengkap
Radiation Dose Tracking in Computed Tomography Using Data Visualization
Radiation dose tracking is becoming very important due to the popularity of computerized tomography (CT) scans. One of the challenges of radiation dose tracking is that there are several variables that affect the dose from the patient side, machine side, and procedures side. Although some tracking…
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An analytical study on the awareness, attitude and practice during the COVID-19 pandemic in Riyadh, Saudi Arabia
BACKGROUND: Coronavirus disease (COVID-19) is an infectious disease caused by a new variable of the Coronaviridae family. COVID-19 spreads primarily by contacting the virus either from a COVID-19-infected individual through coughing or sneezing or from COVID-19-contaminated surfaces. On March 12…
Juga tersedia di: DOAJ
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Artikel Jurnal Teks lengkap
Adversarial attacks against supervised machine learning based network intrusion detection systems
Adversarial machine learning is a recent area of study that explores both adversarial attack strategy and detection systems of adversarial attacks, which are inputs specially crafted to outwit the classification of detection systems or disrupt the training process of detection systems. In this…
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DeepAIA: An Automatic Image Annotation Model Based on Generative Adversarial Networks and Transfer Learning
Automatic image annotation (AIA) has been adopted in different applications such as image retrieval and classification. Deep Learning is used in AIA to extract image features and then convert these features into text descriptions and labels. However, conventional AIA models that employ deep…
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HMATC: Hierarchical multi-label Arabic text classification model using machine learning
Multi-label classification assigns multiple labels to each document concurrently. Many real-world classification problems tend to employ high-dimensional label spaces, which can be naturally structured in a hierarchy. In this type of problem, each instance may belong to multiple labels and labels…
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Text-rating review discrepancy (TRRD): an integrative review and implications for research
Abstract The large number of online product and service review websites has created a substantial information resource for both individuals and businesses. Researching the abundance of text reviews can be a daunting task for both customers and business owners; however, rating scores are a concise…
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Modeling and design optimization of phosphor converted white light emitting diodes (pc-WLEDs)
The current study introduces a reduced order electro-thermal-optical framework for design and optimization of phosphor converted white light emitting diodes (pc-WLEDs). A general model has been applied to compare phosphor materials, packaging configuration, heat sink materials and operation…
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Simultaneous mobility of gateways and nodes in LoRaWAN: a key advancement for reliable soldier health monitoring
IntroductionMobility significantly influences the evaluation of wireless communication systems, particularly in real-time soldier health monitoring across isolated and dynamic environments where reliable communication is vital.MethodsThis study investigates the performance of Long Range Wide Area…
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AI–Social Media Integration for Crisis Management: A Systematic Review of Data and Learning Aspects
As natural disasters and crises increase globally in both frequency and severity, researchers have been exploring innovative technological solutions to manage them effectively. This systematic review examines the integration of artificial intelligence (AI) with social media platforms for crisis…
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HEAL: health-enhanced adaptive LoRaWAN for AI-based real-time soldier monitoring and status prediction
Abstract Continuous and reliable monitoring of soldiers’ health in remote and resource-constrained environments is essential for operational readiness and timely emergency interventions. Long Range Wide Area Network (LoRaWAN) provides an energy-efficient, long-range communication solution for…
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HLMCC: A Hybrid Learning Anomaly Detection Model for Unlabeled Data in Internet of Things
The Internet of Things (IoT) is a network of distributed devices or sensors connected through the internet to allow gathering and sharing of data. The data generated by these devices is affected by anomalies or abnormal behaviour due to attack issues, or breakdown in devices, as examples. However…
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A semi supervised approach to Arabic aspect category detection using Bert and teacher-student model
Aspect-based sentiment analysis tasks are well researched in English. However, we find such research lacking in the context of the Arabic language, especially with reference to aspect category detection. Most of this research is focusing on supervised machine learning methods that require the use…
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An insight into the stochastic solitonic features of the Maccari model using the solver technique
In this paper, the unified approach is used in acquiring some new results to the coupled Maccari system (MS) in Itô sense with multiplicative noise. The MS is a nonlinear model used in hydrodynamics, plasma physics, and nonlinear optics to represent isolated waves in a restricted region. We provide…
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Location allocation approach based on influence of points of dispensing
Abstract Public health emergencies, such as disease outbreaks, require health authorities to set up points of dispensing (PODs) to efficiently distribute vaccines and drugs to attempt to reduce infection spread within a short timeframe. A considerable amount of research has been conducted to…
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Routing Enhancement in MANET Using Particle Swarm Algorithm
A Mobile ad hoc Network (MANET) is a collection of wireless mobile nodes that temporarily establish a network without centralized administration or fixed infrastructure. Designing the routing of adequate routing protocols is a major challenge given the constraints of battery, bandwidth, multi-hop…
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Population Fusion Transformer for Subnational Population Forecasting
Abstract Forecasting the subnational population accurately is needed for sustainable development, including planning for the future, allocating resources, or providing health services. Two approaches are used for forecasting subnational populations: local forecasting where a model is trained for…
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Advancing Phishing Email Detection: A Comparative Study of Deep Learning Models
Phishing is one of the most dangerous attacks targeting individuals, organizations, and nations. Although many traditional methods for email phishing detection exist, there is a need to improve accuracy and reduce false-positive rates. Our work investigates one-dimensional CNN-based models…