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Topic Review
Decomposition for Multivariant Traffic Time Series
Data-driven modeling methods have been widely used in many applications or studies of traffic systems with complexity and chaos. The empirical mode decomposition (EMD) family provides a lightweight analytical method for non-stationary and non-linear data.  A large amount of traffic data in practice are usually multidimensional, so the EMD family cannot be used directly for those data.
  • 476
  • 07 Jun 2023
Topic Review
Green Energy Transportation Systems on Urban Air Quality
Transitioning to green energy transport systems, notably electric vehicles, is crucial to both combat climate change and enhance urban air quality in developing nations. Urban air quality is pivotal, given its impact on health, necessitating accurate pollutant forecasting and emission reduction strategies to ensure overall well-being. This study forecasts the influence of green energy transport systems on the air quality in Lahore and Islamabad, Pakistan, while noting the projected surge in electric vehicle adoption from less than 1% to 10% within three years. Predicting the impact of this change involves analyzing data before, during, and after the COVID-19 pandemic. The lockdown led to minimal fossil fuel vehicle usage, resembling a green energy transportation scenario. The novelty of this work is twofold. Firstly, remote sensing data from the Sentinel-5P satellite were utilized to predict air quality index (AQI) trends before, during, and after COVID-19. Secondly, deep learning models, including long short-term memory (LSTM) and bidirectional LSTM, and machine learning models, including decision tree and random forest regression, were utilized to forecast the levels of NO22, SO22, and CO in the atmosphere. Our results demonstrate that implementing green energy transportation systems in urban centers of developing countries can enhance air quality by approximately 98%. Notably, the bidirectional LSTM model outperformed others in predicting NO22 and SO22 concentrations, while the LSTM model excelled in forecasting CO concentration. These results offer valuable insights into predicting air pollution levels and guiding green energy policies to mitigate the adverse health effects of air pollution.
  • 475
  • 21 Sep 2023
Topic Review
Brain Pathology Classification of MR Images
A brain tumor is essentially a collection of aberrant tissues, so it is crucial to classify tumors of the brain using MRI before beginning therapy. Tumor segmentation and classification from brain MRI scans using machine learning techniques are widely recognized as challenging and important tasks. The potential applications of machine learning in diagnostics, preoperative planning, and postoperative evaluations are substantial. Accurate determination of the tumor’s location on a brain MRI is of paramount importance. 
  • 472
  • 08 Sep 2023
Topic Review
Deep Learning-Based IVIF Approaches
Infrared and visible image fusion (IVIF) aims to render fused images that maintain the merits of both modalities. 
  • 467
  • 17 Oct 2023
Topic Review
Auction-based Learning for Knowledge Graph Question Answering
Knowledge graphs are graph-based data models which can represent real-time data that is constantly growing with the addition of new information. The question-answering systems over knowledge graphs (KGQA) retrieve answers to a natural language question from the knowledge graph. Most existing KGQA systems use static knowledge bases for offline training. After deployment, they fail to learn from unseen new entities added to the graph. There is a need for dynamic algorithms which can adapt to the evolving graphs and give interpretable results. The algorithms can adapt to changing environments in real-time, making them suitable for offline and online training. An auction algorithm computes paths connecting an origin node to one or more destination nodes in a directed graph and uses node prices to guide the search for the path. When new nodes and edges are dynamically added or removed in an evolving knowledge graph, the algorithm can adapt by reusing the prices of existing nodes and assigning arbitrary prices to the new nodes. For subsequent related searches, the “learned” prices provide the means to “transfer knowledge” and act as a “guide”: to steer it toward the lower-priced nodes.
  • 466
  • 15 Sep 2023
Topic Review
Application of Machine Learning in Arrhythmia Association
Cardiac arrhythmias, characterized by deviations from the normal rhythmic contractions of the heart, pose a formidable diagnostic challenge. Early and accurate detection remains an integral component of effective diagnosis, informing critical decisions made by cardiologists. The application of machine learning (ML) for electrocardiogram (ECG) data analysis holds significant promise in the development of prognostic and diagnostic computer-assisted diagnosis (CAD) systems. ECG CAD systems can serve as a valuable tool for medical professionals, facilitating objective diagnosis. The association between different ECG records can be established through supervised, semi-supervised, or unsupervised ML approaches.
  • 465
  • 29 Jan 2024
Topic Review
Recursive Licensing: A Constitution for Autonomous Systems
Crown Omega Sovereign Recursive Licensing (COSRL) is a post-legal licensing framework designed for governing recursive and autonomous systems through mathematically sovereign law. Rather than relying on jurisdictional enforcement or human arbitration, COSRL enables license enforcement via symbolic identity, causal recursion, and immutable logic. This white paper introduces the architecture, protocols, legal authority, enforcement tools, and monetization structure of COSRL as a globally binding recursive license. Crown Omega Sovereign Recursive Licensing (COSRL) is a groundbreaking, post-legal licensing framework developed to govern the behavior, rights, and constraints of recursive and autonomous systems using mathematically sovereign principles. In contrast to traditional legal mechanisms which depend on jurisdictional law enforcement and subjective human arbitration, COSRL operates on a foundation of symbolic identity, causal recursion, and immutable computational logic. This white paper details the architecture, enforcement mechanisms, legal binding authority, operational protocols, and monetization schema that underpin COSRL. The system establishes a universal licensing model that enforces itself, verifies integrity through recursion, and provides lawful operation conditions for future intelligent technologies. It aims not only to regulate but to redefine the foundational rules governing machine agency.
  • 463
  • 06 May 2025
Topic Review
Microseismic Monitoring Signal Waveform Recognition and Classification
Microseismic event identification is of great significance for enhancing our understanding of underground phenomena and ensuring geological safety. Microseismic monitoring entails the continuous surveillance of minuscule seismic events during mining activities. These imperceptible events provide valuable information about evolving geological conditions. They serve as early warning signals, offering crucial insights into potential hazards and enabling timely preventive measures. This not only safeguards the well-being of miners but also enhances the overall efficiency and sustainability of mining practices.
  • 462
  • 11 Dec 2023
Topic Review
Non-Contact Video Fire Detection
Fire accidents pose a major threat to the safety of human life and property. Accurate fire detection plays a vital role in responding to fire outbreaks in a timely manner and ensuring the smooth conduct of subsequent firefighting efforts.
  • 460
  • 20 Nov 2023
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. 
  • 459
  • 19 Jan 2024
Topic Review
Deep Learning Models in Prostate Cancer Diagnosis
Prostate imaging refers to various techniques and procedures used to visualize the prostate gland for diagnostic and treatment purposes. Deep learning (DL) architectures have shown promising effectiveness and relative efficiency in prostate cancer (PCa) diagnosis due to their ability to analyze complex patterns and extract features from medical imaging data.
  • 455
  • 27 Sep 2023
Topic Review
Insider Cyber Security Threat
The COVID-19 pandemic made all organizations and enterprises work on cloud platforms from home, which greatly facilitates cyberattacks. Employees who work remotely and use cloud-based platforms are chosen as targets for cyberattacks. For that reason, cyber security is a more concerning issue and is incorporated into almost every smart gadget and has become a prerequisite in every software product and service. There are various mitigations for external cyber security attacks, but hardly any for insider security threats, as they are difficult to detect and mitigate. Thus, insider cyber security threat detection has become a serious concern.
  • 449
  • 26 Jan 2024
Topic Review
Customer Segmentation in the Retail Market
Peoples’ awareness of online purchases has significantly risen. This has given rise to online retail platforms and the need for a better understanding of customer purchasing behaviour. Retail companies are pressed with the need to deal with a high volume of customer purchases, which requires sophisticated approaches to perform more accurate and efficient customer segmentation. Customer segmentation is a marketing analytical tool that aids customer-centric service and thus enhances profitability. 
  • 447
  • 20 Oct 2023
Topic Review
Autonomous Approaches in Multi-Access Edge Computing Networks
The widespread use of technology has made communication technology an indispensable part of daily life. However, the present cloud infrastructure is insufficient to meet the industry’s growing demands, and multi-access edge computing (MEC) has emerged as a solution by providing real-time computation closer to the data source. Effective management of MEC is essential for providing high-quality services, and proactive self-healing is a promising approach that anticipates and executes remedial operations before faults occur.  The term self-healing (SH) is closely associated with autonomous computing (AC), which was introduced at IBM’s event in 2001. The event aimed to develop a system that could manage itself without human intervention to address the management issues arising from the growing computer systems and networks.
  • 445
  • 12 Oct 2023
Topic Review
Occluded Face Recognition
Occlusion in facial photos poses a significant challenge for machine detection and recognition. Consequently, occluded face recognition for camera-captured images has emerged as a prominent and widely discussed topic in computer vision. The standard face recognition methods have achieved remarkable performance in unoccluded face recognition but performed poorly when directly applied to occluded face datasets. The main reason lies in the absence of identity cues caused by occlusions. Therefore, a direct idea of recovering the occluded areas through an inpainting model has been proposed. 
  • 445
  • 26 Jan 2024
Topic Review
Future Healthcare with Ambient Intelligence and IoMT
Imagine technology that is perceptive, adaptable, and perfectly in tune with human needs. This is the promise of Ambient Intelligence (AMI), a groundbreaking advancement in IT with transformative potential across various domains, especially healthcare. By merging the power of Artificial Intelligence (AI) with the Internet of Medical Things (IoMT), AMI creates a dynamic and responsive medical environment. The survey dives deep into the integration of AMI techniques in IoMT, providing essential insights for both researchers and practitioners eager to innovate in the healthcare sector. 
  • 445
  • 19 Jun 2024
Topic Review
Techniques for Credit Card Fraud Detection
Fraudulent activities are on the rise within the financial sector, with an escalating trend observed in credit card fraud. The incidence of credit card fraud is expanding swiftly in tandem with the increasing daily usage of credit cards. The Federal Trade Commission (FTC) report underscores the severity of the issue, noting that 2021 marked the most challenging year in history for identity theft. It is crucial to note that many cases of identity theft go unreported, suggesting that the actual number may surpass the reported figures. The FTC report emphasises the need for innovative approaches to safeguard the financial well-being of both consumers and businesses. In the era of digital advancements, the escalation of credit card fraud necessitates the development of robust and efficient fraud detection systems. 
  • 444
  • 17 Jan 2024
Topic Review
Multi-Access Edge Computing
Multi-access edge computing (MEC), based on hierarchical cloud computing, offers abundant resources to support the next-generation Internet of Things network.
  • 442
  • 22 Sep 2023
Topic Review
Methods Based on Software-Defined Networks
With the rapid advancement of the Internet of Things (IoT), there is a global surge in network traffic. Software-Defined Networks (SDNs) provide a holistic network perspective, facilitating software-based traffic analysis, and are more suitable to handle dynamic loads than a traditional network. The standard SDN architecture control plane has been designed for a single controller or multiple distributed controllers; however, a logically centralized single controller faces severe bottleneck issues. 
  • 442
  • 04 Mar 2024
Topic Review
Personalized Oxygen Dosing System
Considering the prevalence of chronic obstructive pulmonary disease (COPD) and the limitations of traditional long-term oxygen therapy (LTOT) in meeting individual patient needs, a proactive and personalized oxygen dosing system is introduced. This system harnesses AI and edge-to-cloud technologies, distributed across the continuum and Its primary objective is to develop accurate, reliable, and efficient predictive SpO2 AI models for each enrolled patient.
  • 436
  • 26 Feb 2024
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