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Topic Review
Secure Bluetooth Communication in Smart Healthcare Systems
Smart health presents an ever-expanding attack surface due to the continuous adoption of a broad variety of Internet of Medical Things (IoMT) devices and applications. IoMT is a common approach to smart city solutions that deliver long-term benefits to critical infrastructures, such as smart healthcare. Many of the IoMT devices in smart cities use Bluetooth technology for short-range communication due to its flexibility, low resource consumption, and flexibility. As smart healthcare applications rely on distributed control optimization, artificial intelligence (AI) and deep learning (DL) offer effective approaches to mitigate cyber-attacks. 
  • 961
  • 21 Nov 2022
Topic Review
Network Traffic Analysis
Network data traffic is increasing with expanded networks for various applications, with text, image, audio, and video for inevitable needs. Network traffic pattern identification and analysis of traffic of data content are essential for different needs and different scenarios. Many approaches have been followed, both before and after the introduction of machine and deep learning algorithms as intelligence computation. The network traffic analysis is the process of incarcerating traffic of a network and observing it deeply to predict what the manifestation in traffic of the network is. To enhance the quality of service (QoS) of a network, it is important to estimate the network traffic and analyze its accuracy and precision, as well as the false positive and negative rates, with suitable algorithms. 
  • 961
  • 14 Jul 2022
Topic Review
Lane Marking Detection Using Deep Neural Networks
Lane marking recognition is one of the most crucial features for automotive vehicles as it is one of the most fundamental requirements of all the autonomy features of Advanced Driver Assistance Systems (ADAS).
  • 960
  • 27 Oct 2022
Topic Review
Radiomics of Liver Metastases
Multidisciplinary management of patients with liver metastases (LM) requires a precision medicine approach, based on adequate profiling of tumor biology and robust biomarkers. Radiomics, defined as the high-throughput identification, analysis, and translational applications of radiological textural features, could fulfill this need. The present review aims to elucidate the contribution of radiomic analyses to the management of patients with LM. We performed a systematic review of the literature through the most relevant databases and web sources. English language original articles published before June 2020 and concerning radiomics of LM extracted from CT, MRI, or PET-CT were considered. Thirty-two papers were identified. Baseline higher entropy and lower homogeneity of LM were associated with better survival and higher chemotherapy response rates. A decrease in entropy and an increase in homogeneity after chemotherapy correlated with radiological tumor response. Entropy and homogeneity were also highly predictive of tumor regression grade. In comparison with RECIST criteria, radiomic features provided an earlier prediction of response to chemotherapy. Lastly, texture analyses could differentiate LM from other liver tumors. The commonest limitations of studies were small sample size, retrospective design, lack of validation datasets, and unavailability of univocal cut-off values of radiomic features. In conclusion, radiomics can potentially contribute to the precision medicine approach to patients with LM, but interdisciplinarity, standardization, and adequate software tools are needed to translate the anticipated potentialities into clinical practice.
  • 957
  • 06 Nov 2020
Topic Review
Machine Learning and Fuzzy Logic in Electronics
Machine learning is a part of artificial intelligence science and works in close collaboration with data science. The main aim is the collected big data to be processed and studied in such a way to give meaningful knowledge when problems have to be solved or decisions have to be made. Fuzzy logic is another scientific field that is used for modeling, description and evaluation of objects and systems with different levels of complexity, which are characterized with uncertainty, fuzziness and vagueness of their parameters and properties. The application of machine learning and fuzzy logic in electronics is studied to outline the current research topics, scientific achievements and directions for future exploration.
  • 957
  • 07 Dec 2021
Topic Review
Intelligent Power Management System
This is a cloud-based intelligent power management system that uses analytics as a control signal and processes balance achievement pointer, and describes operator acknowledgments that must be shared quickly, accurately, and safely. Current studies of it aims to introduce a conceptual and systematic structure with three main components: demand power (direct current (DC)-device), power mix between renewable energy (RE) and other power sources, and a cloud-based power optimization intelligent system.
  • 955
  • 01 Nov 2021
Topic Review
Dementia
Dementia is a syndrome that is characterised by the decline of different cognitive abilities. A high rate of deaths and high cost for detection, treatments, and patients care count amongst its consequences. Although there is no cure for dementia, a timely diagnosis helps in obtaining necessary support, appropriate medication, and maintenance, as far as possible, of engagement in intellectual, social, and physical activities. The early detection of Alzheimer Disease (AD) is considered to be of high importance for improving the quality of life of patients and their families. In particular, Virtual Reality (VR) is an expanding tool that can be used in order to assess cognitive abilities while navigating through a Virtual Environment (VE).
  • 954
  • 05 Feb 2021
Topic Review
Underwater Vision Enhancement
Underwater video images, as the primary carriers of underwater information, play a vital role in human exploration and development of the ocean. Due to the absorption and scattering of incident light by water bodies, the video images collected underwater generally appear blue-green and have an apparent fog-like effect. In addition, blur, low contrast, color distortion, more noise, unclear details, and limited visual range are the typical problems that degrade the quality of underwater video images. Underwater vision enhancement uses computer technology to process degraded underwater images and convert original low-quality images into a high-quality image. The problems of color bias, low contrast, and atomization of original underwater video images are effectively solved by using vision enhancement technology. Enhanced video images improve the visual perception ability and are benefificial for subsequent visual tasks. Therefore, underwater video image enhancement technology has important scientifific signifificance and application value. 
  • 953
  • 03 Mar 2022
Topic Review
AI and Self-Learning: Opportunities and Challenges
The integration of artificial intelligence (AI) and self-learning algorithms has revolutionized the field of machine learning. This research explores the opportunities, challenges, and risks associated with AI and self-learning, with a particular focus on the impact of different types of AI on self-learning. The research examines how AI algorithms are designed to learn from data and improve their performance over time with little or no human intervention. While AI and self-learning present significant opportunities for automation, efficiency, and innovation, they also pose challenges such as data privacy, security, and ethical concerns. The research provides several success stories of AI and self-learning in various industries and applications. Furthermore, the research outlines future directions for the development and implementation of AI and self-learning algorithms and provides recommendations for all involved parties.
  • 952
  • 22 May 2023
Topic Review
Quantum AI Integration for Industry Transformation
The fusion of quantum computing and artificial intelligence (AI) heralds a transformative era for Industry 4.0, offering unprecedented capabilities and challenges
  • 951
  • 11 Jun 2024
Topic Review
Design of Experiments in the Advancement of Biomaterial
Optimisation of tissue engineering (TE) processes requires models that can identify relationships between the parameters to be optimised and predict structural and performance outcomes from both physical and chemical processes. Design of Experiments (DoE) methods are commonly used for optimisation purposes in addition to playing an important role in statistical quality control and systematic randomisation for experiment planning. DoE is only used for the analysis and optimisation of quantitative data (i.e., number-based, countable or measurable), while it lacks the suitability for imaging and high dimensional data analysis.
  • 941
  • 18 Jan 2023
Topic Review
Hashtag Recommendation
Hashtag recommendation suggests hashtags to users while they write microblogs in social media platforms. Although researchers have investigated various methods and factors that affect the performance of hashtag recommendations in Twitter and Sina Weibo, a systematic review of these methods is lacking.
  • 937
  • 25 May 2021
Topic Review
Deepfake Detection
Deepfakes can compromise the privacy and societal security of both individuals and governments. In addition, deepfakes are a threat to national security, and democracies are progressively being harmed. To overcome/mitigate the impact of deepfakes, different methods and approaches have been introduced that can identify deepfakes and appropriate corrective actions can be taken. 
  • 935
  • 20 Jul 2022
Topic Review
Monitoring of Humans in Bed
Indeed, humans typically spend a significant portion of their daily lives in bed. This time becomes even longer in cases where the human is unwell. This is particularly the case for sick or older people, who spend even more time in bed. Their physical activity or inactivity patterns provide useful signatures that reflect the “state” of the person under observation. In the frame of activity monitoring endeavors, behavioral situations that are abnormal (these situations are more/extremely rare within the observation time window) are the ones that are of the highest interest when compared to behavioral situations that are rather normal (these ones occupy most of the observation time window).
  • 935
  • 24 Aug 2022
Topic Review
Data-Driven Predictive Maintenance
Cyber-physical systems in Industry 4.0 are reforming conventional decision-making processes, mainly through integrating entities and functionalities via telecommunication systems and intelligent data processing approaches. This reformulation brings new challenges and increases complexity. Nevertheless, these advancements might provide new solutions for typical problems, such as system failures, and thus, for maintenance approaches. Predictive Maintenance (PdM) is a data-based approach that emerged as a prominent field of research among many existing maintenance approaches. We have three main categories in PdM: model-based prognosis, knowledge-based prognosis, and data-driven prognosis. Data-driven PdM strategies appeared with great prominence and importance both in industry and academia.
  • 930
  • 28 Sep 2021
Topic Review
Unmanned Aerial Vehicles and Federated Learning
Unmanned aerial vehicles (UAVs) have gained increasing attention in boosting the performance of conventional networks due to their small size, high efficiency, low cost, and autonomously nature. The amalgamation of UAVs with both distributed/collaborative Deep Learning (DL) algorithms, such as Federated Learning (FL), and Blockchain technology have ushered in a new paradigm of Secure Multi-Access Edge Computing (S-MEC). Indeed, FL enables UAV devices to leverage their sensed data to build local DL models. The latter are then sent to a central node, e.g., S-MEC node, for aggregation, in order to generate a global DL model. Therefore, FL enables UAV devices to collaborate during several FL rounds in generating a learning model, while avoiding to share their local data, and thus ensuring UAVs’ privacy.
  • 928
  • 22 Jul 2022
Topic Review
Applications of Deep Reinforcement Learning in Other Industries
Reinforcement Learning (RL) is an approach to simulate the human’s natural learning process, whose key is to let the agent learn by interacting with the stochastic environment. 
  • 924
  • 29 Nov 2021
Topic Review
Artificial Intelligence Surgery
Most surgeons are skeptical as to the feasibility of autonomous actions in surgery. Interestingly, many examples of autonomous actions already exist and have been around for years. Since the beginning of this millennium, the field of artificial intelligence (AI) has grown exponentially with the development of machine learning (ML), deep learning (DL), computer vision (CV) and natural language processing (NLP). This entry will highlight the most recent issues regarding how AI will get us to more autonomous actions in surgery by discussing the different degrees of surgical autonomy, recent advances with reinforcement learning and the ethical roadblocks that lie ahead.
  • 921
  • 25 Aug 2021
Topic Review
Mars Rover Mastcam Images
The Curiosity rover has landed on Mars since 2012. One of the instruments onboard the rover is a pair of multispectral cameras known as Mastcams, which act as eyes of the rover.
  • 915
  • 28 Oct 2021
Topic Review
Business Recommender Systems
Besides the typical applications of recommender systems in B2C scenarios such as movie or shopping platforms, there is a rising interest in transforming the human-driven advice provided, e.g., in consultancy via the use of recommender systems. There are two main classes of recommender systems: information-filtering-based and knowledge-based systems. The former category selects items from a large collection of items based on user preferences and is further classified as collaborative-filtering recommenders and content-based filtering recommenders. The knowledge-based recommenders make recommendations by applying constraints or similarities based on domain or contextual knowledge. Common applications are in B2C scenarios such as e-commerce, tourism, news, movie, music, etc.
  • 912
  • 10 Jun 2022
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