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Topic Review
Predicting an Optimal Medication/Prescription Regimen Using Multi-Output Models
The discordant chronic comorbidities care (DC33) model shows how a change in a patient treatment plan can negatively impact symptoms and necessitate revisiting the plan. These interactions make treatment decisions, prioritization, and adherence for DCCs very complex and challenging for patients and their healthcare providers.
  • 221
  • 23 Jan 2024
Topic Review
Ransomware Detection Approaches and Techniques
In the Machine Learning approach, machine learning algorithms analyze and categorize ransomware behavior. Trained on datasets of both known ransomware and benign samples, these algorithms identify new ransomware based on learned characteristics. Machine learning techniques, such as Decision Trees, Support Vector Machines, and Artificial Neural Networks, are applied. Advantages include adaptability to new ransomware variations and scalability for handling large datasets.
  • 174
  • 23 Jan 2024
Topic Review
Software-Defined Networks and Software-Defined Radios in Maritime Communications
Effective maritime communication is vital for ensuring the safety of crew members, vessels, and cargo. The maritime industry is responsible for the transportation of a significant portion of global trade, and as such, the efficient and secure transfer of information is essential to maintain the flow of goods and services. With the increasing complexity of maritime operations, technological advancements such as unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs), and the Internet of Ships (IoS) have been introduced to enhance communication and operational efficiency.
  • 174
  • 22 Jan 2024
Topic Review
Machine Learning-Based Facial Palsy Detection and Evaluation
Automated solutions for medical diagnosis based on computer vision form an emerging field of science aiming to enhance diagnosis and early disease detection. The detection and quantification of facial asymmetries enable facial palsy evaluation.  Deep learning methods allow the automatic learning of discriminative deep facial features, leading to comparatively higher performance accuracies.
  • 249
  • 22 Jan 2024
Topic Review
Federated Learning for Intrusion Detection Systems in IoV
The Internet of Vehicles (IoV) has garnered significant attention from researchers and automotive industry professionals due to its expanding range of applications and services aimed at enhancing road safety and driver/passenger comfort. However, the massive amount of data spread across this network makes securing it challenging. The IoV network generates, collects, and processes vast amounts of valuable and sensitive data that intruders can manipulate. An intrusion detection system (IDS) is the most typical method to protect such networks. An IDS monitors activity on the road to detect any sign of a security threat and generates an alert if a security anomaly is detected. Federated Learning (FL) is a decentralized machine learning technique, FL allows model training on client devices while maintaining user data privacy.
  • 157
  • 22 Jan 2024
Topic Review
Anomaly Detection in Video Surveillance
The escalating use of security cameras has resulted in a surge in images requiring analysis, a task hindered by the inefficiency and error-prone nature of manual monitoring. Research on anomaly detection in CCTV videos is being actively conducted using various techniques.
  • 134
  • 22 Jan 2024
Topic Review
Vibrotactile Feedback in Virtual Reality
While substantial progress in computer graphics and sound rendering has resulted in highly realistic visual and auditory experiences in virtual reality (VR), achieving genuine immersion, interactivity, and the stimulation of imagination necessitates the integration of realistic tactile experiences, often facilitated through haptic feedback. The incorporation of vibrotactile feedback in VR allows users to fully engage their sense of touch, enabling them to explore, grasp, and manipulate virtual objects as if they were interacting with them in the physical world.
  • 566
  • 22 Jan 2024
Topic Review
Automatic Visual Pollution Detection
Visual pollution, characterized by disorderly and displeasing urban environments, is inherently subjective and challenging to quantify precisely. In recent years, substantial research efforts have been initiated to identify and categorize various forms of visual pollution by applying artificial intelligence and computer vision techniques. The automated recognition of visual disturbances using advanced deep learning methods can aid governmental bodies and relevant authorities in taking proactive measures. 
  • 199
  • 19 Jan 2024
Topic Review
Path Planning Technique for Mobile Robots
Mobile robot path planning involves designing optimal routes from starting points to destinations within specific environmental conditions. Even though there are well-established autonomous navigation solutions, it is worth noting that comprehensive, systematically differentiated examinations of the critical technologies underpinning both single-robot and multi-robot path planning are notably scarce. These technologies encompass aspects such as environmental modeling, criteria for evaluating path quality, the techniques employed in path planning and so on.
  • 529
  • 19 Jan 2024
Topic Review
Deep Learning in Neuro-Oncology Data Analysis
Machine Learning is entering a phase of maturity, but its medical applications still lag behind in terms of practical use. The field of oncological radiology (and neuro-oncology in particular) is at the forefront of these developments, now boosted by the success of Deep-Learning methods for the analysis of medical images. 
  • 129
  • 19 Jan 2024
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