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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. 
  • 526
  • 27 Feb 2023
Topic Review
Controlling Upper Limb Prostheses Using Sonomyography
A ground-breaking study by Zheng et al. investigated whether ultrasound imaging of the forearm might be used to control a powered prosthesis, and the term “sonomyography” (SMG) was coined by the group. Ultrasound signals have recently garnered the interest of researchers in the area of HMIs because they can collect information from both superficial and deep muscles and so provide more comprehensive information than other techniques. Due to the great spatiotemporal resolution and specificity of ultrasound measurements of muscle deformation, researchers have been able to infer fine volitional motor activities, such as finger motions and the dexterous control of robotic hands.
  • 345
  • 27 Feb 2023
Topic Review
Blockchain and Machine Learning for Future Smart Grids
A wide range of solutions, beyond the classical one of building more lines, cables and transformers, have been proposed to modernize the power grid with new technologies, enabling a more smart automatic networked system. These solutions, typically using new technology, go by the name “smart grids” (SG) or “smart-grid technology”. Blockchain technology (BC) is a viable solution to overcome the issues of centralized system. BC is an immutable, distributed and P2P network that provides security, privacy and trust among peers using cryptographic techniques. Machine learning (ML) techniques can be exploited to develop energy prediction algorithms and the proper scheduling of energy usage. A large amount of the energy consumption data of several users is generated from smart meters that also contain users’ private/confidential information as well as sensitive information of utility providers. This high volume of data increases the complexity of data analysis. 
  • 566
  • 27 Feb 2023
Topic Review
Cross-Lingual Document Retrieval
Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information.
  • 225
  • 24 Feb 2023
Topic Review
Hydrotropism
Hydrotropism is the movement or growth of a plant towards water. It is a type of tropism, or directional growth response, that is triggered by water. Plants are able to detect water through various stimuli, including changes in moisture levels and changes in water potential. 
  • 383
  • 23 Feb 2023
Topic Review
Fault Detection for Belt Conveyor Idlers
Bulk materials are transported worldwide using belt conveyors as an essential transport system. The majority of conveyor components are monitored continuously to ensure their reliability, but idlers remain a challenge to monitor due to the large number of idlers (rollers) distributed throughout the working environment. These idlers are prone to external noises or disturbances that cause a failure in the underlying system operations.
  • 1.4K
  • 22 Feb 2023
Topic Review
Deep Reinforcement Learning and Games
Deep learning (DL) algorithms were established in 2006 and have been extensively utilized by many researchers and industries in subsequent years. Ever since the impressive breakthrough on the ImageNet classification challenge in 2012, the successes of supervised deep learning have continued to pile up. Many researchers have started utilizing this new and capable family of algorithms to solve a wide range of new tasks, including ways to learn intelligent behaviors in reward–driven complex dynamic problems successfully. The agent––environment interaction expressed through observation, action, and reward channels is the necessary and capable condition of characterizing a problem as an object of reinforcement learning (RL). Learning environments can be characterized as Markov decision problems, as they satisfy the Markov property, allowing RL algorithms to be applied. From this family of environments, games could not be absent. In a game–based environment, inputs (the game world), actions (game controls), and the evaluation criteria (game score) are usually known and simulated. With the rise of DL and extended computational capability, classic RL algorithms from the 1990s could now solve exponentially more complex tasks such as games over time, traversing through huge decision spaces.
  • 387
  • 22 Feb 2023
Topic Review
DDoS Attacks against Cloud-Computing Environment
 Cloud computing (CC) plays a significant role in revolutionizing the information and communication technology (ICT) industry, allowing flexible delivery of new services and  computing resources at a fraction of the costs for end-users than traditional computing. Unfortunately, many potential cyber threats impact CC-deployed services due to the exploitation of CC’s characteristics, such as resource sharing, elasticity, and multi-tenancy. Researchers provides a comprehensive discussion on security issues and challenges facing CC for cloud service providers and their users. Furthermore, a new taxonomy for classifying CC attacks is proposed, distributed denial of service (DDoS) attacks, and DDoS attack detection approaches on CC. Researchers also provides a qualitative comparison with the existing surveys. Finally, they aims to serve as a guide and reference for other researchers working on new DDoS attack detection approaches within the CC environment. 
  • 1.2K
  • 20 Feb 2023
Topic Review
Impact of Artificial Intelligence on Dental Education
Most dental educators have limited knowledge and skills to assess AI applications, as they were not trained to do so. Also, AI technology has evolved exponentially. Factual reliability and opportunities with OpenAI Inc.’s ChatGPT are considered critical inflection points in the era of generative AI. Updating curricula at dental institutions is inevitable as advanced deep-learning approaches take over the clinical areas of dentistry and reshape diagnostics, treatment planning, management, and telemedicine screening. With advances in AI language models, communication with patients will change, and the foundations of dental education, including essay, thesis, or scientific paper writing, will need to adapt. However, there is a growing concern about its ethical and legal implications, and further consensus is needed for the safe and responsible implementation of AI in dental education.
  • 892
  • 20 Feb 2023
Topic Review
6G Enabled Light Weight Authentication Protocol for UAVs
In the 6G network, with blockchain and unmanned aerial vehicles (UAVs) authentication, the network decentralization and resource sharing would minimize resource under-utilization thereby facilitating PG targets. Furthermore, through an appropriate selection of blockchain type and consensus algorithms, the SG’s needs of UAV authentication in 6G network applications can also be readily addressed.
  • 605
  • 17 Feb 2023
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