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Topic Review
AI-Based Model for Knowledge Evaluation in Public Organizations
In the construction of knowledge bases, it is very important to evaluate the quality of the knowledge entered into them. Artificial Intelligence (AI) development has led to the research of knowledge management tools for multi-user environments, among many other AI applications. In the knowledge management field, the construction of ontologies as knowledge repositories using various sources requires a means of evaluation of all: the input ontologies and the integration process on the output ontology. The results obtained from the evaluations serve as guides to measure the quality of the repository.
  • 501
  • 01 Nov 2023
Topic Review
Continually Improving the Performance of Autonomous Game Agents
Deep Reinforcement Learning (DRL) has been effectively performed in various complex environments, such as playing video games. In many game environments, DeepMind’s baseline Deep Q-Network (DQN) game agents performed at a level comparable to that of humans. However, these DRL models require many experience samples to learn and lack the adaptability to changes in the environment and handling complexity
  • 500
  • 09 Nov 2023
Topic Review
Spiking Neural Networks and Neuromorphic Modeling
Use of Spiking Neural Networks (SNNs) that can capture a model of organisms’ nervous systems, may be simply justified by their unparalleled energy/computational efficiency.
  • 499
  • 19 Sep 2023
Topic Review
Skeletal Fracture Detection with Deep Learning
Deep learning models have shown great promise in diagnosing skeletal fractures from X-ray images. Deep learning algorithms are always applied in X-rays and CT image processing, such as assessing the mineral bone density (BMD), detecting bone fractures, and recommending treatment 
  • 499
  • 26 Oct 2023
Topic Review
Advancing Glaucoma Care
Glaucoma, the leading cause of irreversible blindness worldwide, comprises a group of progressive optic neuropathies requiring early detection and lifelong treatment to preserve vision. Artificial intelligence (AI) technologies are now demonstrating transformative potential across the spectrum of clinical glaucoma care.
  • 498
  • 30 Jan 2024
Topic Review
Relational Cues and Tailoring of e-Coach Dialogues
Relational cues are extracts from actual verbal dialogues that help build the therapist–patient working alliance and stronger bond through the depiction of empathy, respect and openness. ECAs (Embodied conversational agents) are human-like virtual agents that exhibit verbal and non-verbal behaviours. In the digital health space, ECAs act as health coaches or experts.
  • 497
  • 12 Oct 2023
Topic Review
Linked Data Interfaces
In the era of big data, linked data interfaces play a critical role in enabling access to and management of large-scale, heterogeneous datasets. This research investigates forty-seven interfaces developed by the semantic web community in the context of the Web of Linked Data, displaying information about general topics and digital library contents. The interfaces are classified based on their interaction paradigm, the type of information they display, and the complexity reduction strategies they employ. The main purpose to be addressed is the possibility of categorizing a great number of available tools so that comparison among them becomes feasible and valuable. The analysis reveals that most interfaces use a hybrid interaction paradigm combining browsing, searching, and displaying information in lists or tables. Complexity reduction strategies, such as faceted search and summary visualization, are also identified. Emerging trends in linked data interface focus on user-centric design and advancements in semantic annotation methods, leveraging machine learning techniques for data enrichment and retrieval. Additionally, an interactive platform is provided to explore and compare data on the analyzed tools. Overall, there is no one-size-fits-all solution for developing linked data interfaces and tailoring the interaction paradigm and complexity reduction strategies to specific user needs is essential.
  • 496
  • 08 Sep 2023
Topic Review
Olive Leaf Disease Diagnosis
Artificial intelligence has many applications in various industries, including agriculture. It can help overcome challenges by providing efficient solutions, especially in the early stages of development. When working with tree leaves to identify the type of disease, diseases often show up through changes in leaf color. Therefore, it is crucial to improve the color brightness before using them in intelligent agricultural systems.
  • 494
  • 24 Nov 2023
Topic Review
Social Network Sentiment Analysis
The ever-increasing amount of information and opinions available on social networks has made it imperative to develop automatic methods for effective information classification and analysis. Sentiment analysis (SA) in social networks has, therefore, become a crucial process in numerous sectors at both social and business levels. 
  • 492
  • 06 Nov 2023
Topic Review
Deep-Learning and Privacy Techniques for Data-Driven Soft Sensors
The continuously increasing number of mobile devices actively being used in the world amounted to approximately 6.8 billion by 2022. Consequently, this implies a substantial increase in the amount of personal data collected, transported, processed, and stored. An integrated personal health data management system was designed and implemented, which considers data-driven software and hardware sensors, comprehensive data privacy techniques, and machine-learning-based algorithmic models. 
  • 489
  • 13 Mar 2023
Topic Review
Digital Twins for Access Networks
As the complexity and scale of modern networks continue to grow, the need for efficient, secure management, and optimization becomes increasingly vital. Digital twin (DT) technology has emerged as a promising approach to address these challenges by providing a virtual representation of the physical network, enabling analysis, diagnosis, emulation, and control. The emergence of Software-defined network (SDN) has facilitated a holistic view of the network topology, enabling the use of Graph neural network (GNN) as a data-driven technique to solve diverse problems in future networks.
  • 486
  • 06 Dec 2023
Topic Review
Modelling and Measuring Trust in Human–Robot Collaboration
Human–Robot Collaboration (HRC) has emerged as a critical area in the engineering and social sciences domain. In any kind of collaboration, including HRC, trust has been identified as a significant factor that can either motivate or hinder cooperation, especially in scenarios characterized by incomplete or uncertain information.
  • 486
  • 08 Mar 2024
Topic Review
Noise-Tolerant Data Reconstruction for Wireless Sensor Network
Maintaining data dependability within wireless sensor network (WSN) systems has significant importance. Nevertheless, the deployment of systems in unattended and hostile areas poses a major challenge in dealing with noise. Consequently, several investigations have been conducted to address the issue of noise-affected data recovery.
  • 484
  • 21 Sep 2023
Topic Review
Vehicular Routing and Intelligent Transportation Systems
Urban areas all over the world, from New York's skyscraper-filled skyline to Casablanca's busy streets, have been coping with an exponential surge in vehicle traffic in recent years. This phenomena highlights the larger socioeconomic dynamics influencing current period as well as the world's rising obsession with autos. The effects of this traffic increase are being felt most acutely in emerging powerhouses and developed countries with their advanced industries and economies that are rapidly industrializing and urbanizing. A series of difficulties have arisen as a result of the growth in vehicle traffic. Cities are now frequently congested with traffic, turning once-smooth thoroughfares into figurative parking lots during rush hours. In addition to trying commuters' patience, congestion like this has real-world economic repercussions.  The need for transportation increases logically as cities grow in population with younger citizens. What is particularly alarming, though, is the glaring inconsistency in many urban areas: while the number of automobiles increases, there is a glaring delay in improving road infrastructure and bolstering safety measures. The promise of effortless urban mobility is in danger of becoming an uncontrollable nightmare due to this imbalance.
  • 484
  • 10 Nov 2023
Topic Review
Digital Twins for Industrie 4.0 in Urban Planning
Digital twins are emerging as a prime analysis, prediction, and control concepts for enabling the Industrie 4.0 vision of cyber-physical production systems (CPPSs) as well as for modeling complex tasks such as urban planning. Today’s growing complexity and volatility cannot be handled by monolithic digital twins but require a fundamentally decentralized paradigm of cooperating and competing digital twins.
  • 482
  • 13 Dec 2023
Topic Review
Air-to-Sea Integrated Maritime Internet of Things
Future generation communication systems are exemplified by 5G and 6G wireless technologies, and the utilization of integrated air-to-sea (A2S) communication infrastructure is employed to extend network coverage and enhance data throughput to support data-driven maritime applications. These ground-breaking techniques have promoted the rapid development of the maritime internet of things (MIoT). MIoT is a special kind of IoT system and is very different from the IoT on land in terms of connection methods, device types, data transmission, and so on. The complexity and variability in the marine environment make the construction and application of the MIoT more extensive and has far-reaching significance. 
  • 482
  • 10 Jan 2024
Topic Review
Combining Self-Supervision with Knowledge Distillation
The current audio single-mode self-supervised classification mainly adopts a strategy based on audio spectrum reconstruction. Overall, its self-supervised approach is relatively single and cannot fully mine key semantic information in the time and frequency domains.
  • 481
  • 03 Jan 2024
Topic Review
Trustworthy Artificial Intelligence
Artificial Intelligence is an indispensable element of the modern world, constantly evolving and contributing to the emergence of new technologies. Artificial Intelligence techniques must inspire users’ trust because they significantly impact virtually every industry and person. For this reason, systems using Artificial Intelligence are subject to many requirements to verify their trustworthiness in various aspects.
  • 480
  • 30 Jan 2024
Topic Review
Semantic Video Segmentation
Recent approaches for fast semantic video segmentation have reduced redundancy by warping feature maps across adjacent frames, greatly speeding up the inference phase. Researchers build a non-key-frame CNN, fusing warped context features with current spatial details. Based on the feature fusion, the context feature rectification (CFR) module learns the model’s difference from a per-frame model to correct the warped features. 
  • 480
  • 22 Nov 2023
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.
  • 479
  • 07 Jun 2023
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