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Topic Review
Underwater Soft Robotics
Underwater exploration, much like space exploration, has been at the frontier of science and engineering ventures. Some of the early robotic systems sent by humans to explore marine life are known as remotely operated vehicles (ROVs).  ROVs are underwater robots, manually operated by a pilot, using tethered communication. Soft robots made from compliant materials can achieve shrinking and bending motion that allow them to navigate within narrow areas. The ability of soft robots to deform, change their shapes, exhibit infinite degrees of freedom, and perform complex motion, makes them a suitable candidate for the basis of biological emulation, especially that of underwater creatures, which are one of the sources of biomimetic inspiration for robotic and engineering systems.
  • 737
  • 09 Feb 2022
Topic Review
The Dichotomy of Neural Networks and Cryptography
Neural networks and cryptographic schemes have come together in war and peace; a cross-impact that forms a dichotomy deserving a comprehensive review study. Neural networks can be used against cryptosystems; they can play roles in cryptanalysis and attacks against encryption algorithms and encrypted data. This side of the dichotomy can be interpreted as a war declared by neural networks. On the other hand, neural networks and cryptographic algorithms can mutually support each other. Neural networks can help improve the performance and the security of cryptosystems, and encryption techniques can support the confidentiality of neural networks. The latter side of the dichotomy can be referred to as the peace. 
  • 737
  • 07 Jul 2022
Topic Review
Visual Simultaneous Localization and Mapping
Visual Simultaneous Localization and Mapping (VSLAM) methods refer to the SLAM approaches that employ cameras for pose estimation and map reconstruction and are preferred over Light Detection And Ranging (LiDAR)-based methods due to their lighter weight, lower acquisition costs, and richer environment representation.
  • 735
  • 30 Dec 2022
Topic Review
AI-Powered Diagnosis of Skin Cancer
Skin cancer continues to remain one of the major healthcare issues across the globe. If diagnosed early, skin cancer can be treated successfully. Artificial Intelligence (AI)-based methods can assist in the early detection of skin cancer and can consequently lower its morbidity, and, in turn, alleviate the mortality rate associated with it. Machine learning and deep learning are branches of AI that deal with statistical modeling and inference, which progressively learn from data fed into them to predict desired objectives and characteristics. 
  • 735
  • 27 Feb 2023
Topic Review
Using Colored Petri Net for Accounting System
Many learners who are not familiar with the accounting terms find blended learning very complex to understand with respect to the computerized accounting system, the journal entries process, and tracing the accounting transaction flows of accounting system. A simulation-based model is a viable option to help instructors and learners make understanding the accounting system components and monitoring the accounting transactions easier. This entry briefly introduce a colored Petri net (CPN)-based model.
  • 731
  • 28 Mar 2022
Topic Review
Internet-of-Things-Based Smart Monitoring System
With technological advancements, smart health monitoring systems are gaining growing importance and popularity. Today, business trends are changing from physical infrastructure to online services. With the restrictions imposed during COVID-19, medical services have been changed. The concepts of smart homes, smart appliances, and smart medical systems have gained popularity. The Internet of Things (IoT) has revolutionized communication and data collection by incorporating smart sensors for data collection from diverse sources.
  • 729
  • 29 May 2023
Topic Review
Palmprint Recognition
Palmprint recognition constitutes a pivotal biometric technology deployed in the identification and verification of individuals, relying on the distinctive patterns inherent in their palmprints. This method, known for its reliability and security, finds extensive applications in diverse fields, including access control, security systems, and forensic investigations. Palmprint image acquisition involves capturing high-quality palmprint images using various devices like cameras, scanners, or smartphones. These images are then subjected to preprocessing techniques, encompassing noise reduction, normalization, and enhancement, to ensure consistent submission despite any restrictions on the availability of materials and/or refined input data. Following preprocessing, relevant features are extracted, like minutiae points specific to an individual’s palm, ridges, and lines. These features are crucial for accurate identification and are obtained through advanced image processing methods.
  • 728
  • 10 Jan 2024
Topic Review
Artificial Intelligence (AI)-Empowered Echocardiography Interpretation
Echocardiography (Echo), a widely available, noninvasive, and portable bedside imaging tool, is the most frequently used imaging modality in assessing cardiac anatomy and function in clinical practice. Artificial-intelligence-empowered echo (AI-Echo) can potentially reduce inter-interpreter variability and indeterminate assessment and improve the detection of unique conditions as well as the management of various cardiac disorders.
  • 726
  • 28 Apr 2021
Topic Review
Artificial Intelligence in Adaptive and Intelligent Educational System
There has been much discussion among academics on how pupils may be taught online while yet maintaining a high degree of learning efficiency, in part because of the worldwide COVID-19 pandemic in the previous two years. Students may have trouble focusing due to a lack of teacher–student interaction, yet online learning has some advantages that are unavailable in traditional classrooms. The architecture of online courses for students is integrated into a system called the Adaptive and Intelligent Education System (AIES). In AIESs, reinforcement learning is often used in conjunction with the development of teaching strategies, and this reinforcement-learning-based system is known as RLATES.
  • 725
  • 21 Sep 2022
Topic Review
Internet of Things Applications in China’s Hospitality Industry
During the current post-epidemic period, hygiene requirements and health needs in the hospitality industry keep increasing, and consumers become more concerned about the cleanliness of hotels and have stronger demands for contactless services in hotels. The growth and popularity of IoT technology in China make it more accessible to a wider range of service industries and provides the basis for the application of IoT in the hospitality industry. The application of IoT devices in hotels mainly includes intelligent robots, intelligent guest control, systems, etc., which helps to realise contactless services in hotels. 
  • 724
  • 12 Jul 2022
Topic Review
Machine-Learning Based Methods for PV
This entry presents the state of the art ML models applied in solar energy’s forecasting field i.e., for solar irradiance and power production forecasting (both point and interval or probabilistic forecasting), electricity price forecasting and energy demand forecasting. Other applications of ML into the photovoltaic (PV) field taken into account are the modelling of PV modules, PV design parameter extraction, tracking the maximum power point (MPP), PV systems efficiency optimization, PV/Thermal (PV/T) and Concentrating PV (CPV) system design parameters’ optimization and efficiency improvement, anomaly detection and energy management of PV’s storage systems. While many review papers already exist in this regard, they are usually focused only on one specific topic, while in this paper are gathered all the most relevant applications of ML for solar systems in many different fields. It gives an overview of the most recent and promising applications of machine learning used in the field of photovoltaic systems.
  • 723
  • 28 Sep 2021
Topic Review
Image-Based Malware Detection
Image conversion of malicious binaries, or binary visualisation, is a relevant approach in the security community. It has exceeded the role of a single-file malware analysis tool and has become a part of Intrusion Detection Systems (IDSs) thanks to the adoption of Convolutional Neural Networks (CNNs).
  • 723
  • 16 Nov 2023
Topic Review
Segmentation of Liver Tumor in Computed Tomography Scan
Segmentation of images is a common task within medical image analysis and a necessary component of medical image segmentation. The segmentation of the liver and liver tumors is an important but challenging stage in screening and diagnosing liver diseases. Many automated techniques have been developed for liver and tumor segmentation; however, segmentation of the liver is still challenging due to the fuzzy & complex background of the liver position with other organs. As a result, creating a considerable automated liver and tumour division from computed tomography (CT) scans is critical for identifying liver cancer.
  • 721
  • 15 Sep 2022
Topic Review
Deep Anomaly Detection for In-Vehicle Monitoring
Deep learning approaches to the detection of visual data instances that markedly digress from regular sequences have been mostly focusing on outdoor video-surveillance scenarios, mainly regarding abnormal behaviour and suspicious or abandoned object detection. However, with the increasing importance of public and shared transportation for urban mobility, it becomes imperative to provide autonomous intelligent systems capable of detecting abnormal behaviour that threatens passenger safety. In-vehicle monitoring becomes particularly relevant for Shared Autonomous Vehicles, which do not have a driver responsible for assuring the well-being and safety of passengers; such vehicles must be accompanied by reliable autonomous in-vehicle surveillance systems.
  • 721
  • 17 Oct 2022
Topic Review
Sarcasm and Irony Detection in Social Media
Sarcasm and irony represent intricate linguistic forms in social media communication, demanding nuanced comprehension of context and tone. 
  • 721
  • 30 Nov 2023
Topic Review
Community-Specific Overview of Knowledge Graph Research
Knowledge graphs (KGs) have rapidly emerged as an important area in AI over the last ten years. Building on a storied tradition of graphs in the AI community, a KG may be simply defined as a directed, labeled, multi-relational graph with some form of semantics. In part, this has been fueled by increased publication of structured datasets on the Web, and well-publicized successes of large-scale projects such as the Google Knowledge Graph and the Amazon Product Graph. However, another factor that is less discussed, but which has been equally instrumental in the success of KGs, is the cross-disciplinary nature of academic KG research. Arguably, because of the diversity of this research, a synthesis of how different KG research strands all tie together could serve a useful role in enabling more ‘moonshot’ research and large-scale collaborations.
  • 720
  • 01 Apr 2022
Topic Review
Use of Deep Learning for Video Classification
Deep learning models, specifically convolutional neural networks (CNNs), are well known for understanding images. An artificial neural network (ANN) is an algorithm based on interconnected nodes to recognize the relationships in a set of data. Algorithms based on ANNs have shown a great success in modeling both the lineßar and the non-linear relationships in the underlying data. Due to the huge success rate of these algorithms, they are extensively being used for different real-time applications.
  • 718
  • 15 May 2023
Topic Review
Decentralized Multi-Robot Collision Avoidance
When deploying a multi-robot system, it is ensured that the hardware parts do not collide with each other or the surroundings, especially in symmetric environments. Two types of methods are used for collision avoidance: centralized and decentralized. The decentralized approach has mainly been used in recent times, as it is computationally less expensive.
  • 715
  • 19 Apr 2022
Topic Review
Lightweight Convolutional Neural Network
Biometrics has become an important research issue, and the use of deep learning neural networks has made it possible to develop more reliable and efficient recognition systems. Palms have been identified as one of the most promising candidates among various biometrics due to their unique features and easy accessibility.
  • 715
  • 31 Jul 2023
Topic Review
Privacy-Preserving and Explainable AI
The industrial environment has gone through the fourth revolution, also called “Industry 4.0”, where the main aspect is digitalization. Each device employed in an industrial process is connected to a network called the industrial Internet of things (IIOT). With IIOT manufacturers being capable of tracking every device, it has become easier to prevent or quickly solve failures. Specifically, the large amount of available data has allowed the use of artificial intelligence (AI) algorithms to improve industrial applications in many ways (e.g., failure detection, process optimization, and abnormality detection).
  • 714
  • 01 Jul 2022
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