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Topic Review
Scaling of Rain Attenuation Models
The scaling of rain attenuation models has been developed in several parts of the world. Since the climatic parameters are different in different parts of the world, the scaling parameters are also limited for the best fit in a particular geographical area. However, scaling models are always needed for better applicability, whose performance can be “fine-tuned” by the local climatic parameters.
  • 503
  • 19 Sep 2021
Topic Review
Industry 4.0 and Smart Data
The digital transformation of manufacturing firms, in addition to making operations more efficient, offers important opportunities both to promote the transition to a circular economy and to experiment with new techniques for designing smarter and greener products.
  • 968
  • 18 Sep 2021
Topic Review
Natural Language Processing for Telehealth
The natural language processing (NLP) technology can serve as an interaction between computers and humans using linguistic analysis and deep learning methods to obtain knowledge from an unstructured free text. The NLP systems have shown their uniqueness and importance in the areas of information retrieval mostly in the retrieval and processing of large amount of unstructured clinical records and return structured information by user-defined queries. In general, the NLP system is aimed at representing explicitly the knowledge that is expressed by the text written in a natural language. 
  • 1.3K
  • 18 Sep 2021
Topic Review
Survey of the Tactile Internet
The Tactile Internet (TI) is an innovation that facilitates interaction between human beings (possibly over a distance) with visual presence and haptic feedback. In June 2015, the Technical Activities Board Future Directions Committee launched the most current activity for the Institute of Electrical and Electronics Engineers (IEEE) Digital Senses Initiative (DSI). The DSI is devoted to propelling advancements that catch and recreate human activities such as sense, touch, hearing, taste, and sight from the external world.
  • 720
  • 18 Sep 2021
Topic Review
Machine Learning for Process Monitoring
In the last few decades, hot-melt extrusion (HME) has emerged as a rapidly growing technology in the pharmaceutical industry, due to its various advantages over other fabrication routes for drug delivery systems. After the introduction of the ‘quality by design’ (QbD) approach by the Food and Drug Administration (FDA), many research studies have focused on implementing process analytical technology (PAT), including near-infrared (NIR), Raman, and UV–Vis, coupled with various machine learning algorithms, to monitor and control the HME process in real time. This review gives a comprehensive overview of the application of machine learning algorithms for HME processes, with a focus on pharmaceutical HME applications. The main current challenges in the application of machine learning algorithms for pharmaceutical processes are discussed, with potential future directions for the industry.
  • 731
  • 17 Sep 2021
Topic Review
IoT for Smart Cities
Smart city is a collective term for technologies and concepts that are directed toward making cities efficient, technologically more advanced, greener and more socially inclusive. These concepts include technical, economic and social innovations. This term has been tossed around by various actors in politics, business, administration and urban planning since the 2000s to establish tech-based changes and innovations in urban areas. The idea of the smart city is used in conjunction with the utilization of digital technologies and at the same time represents a reaction to the economic, social and political challenges that post-industrial societies are confronted with at the start of the new millennium. The key focus is on dealing with challenges faced by urban society, such as environmental pollution, demographic change, population growth, healthcare, the financial crisis or scarcity of resources. In a broader sense, the term also includes non-technical innovations that make urban life more sustainable. So far, the idea of using IoT-based sensor networks for healthcare applications is a promising one with the potential of minimizing inefficiencies in the existing infrastructure. A machine learning approach is key to successful implementation of the IoT-powered wireless sensor networks for this purpose since there is large amount of data to be handled intelligently. 
  • 522
  • 15 Sep 2021
Topic Review
IoT Privacy Preservation Using Blockchain
IoT uses a large number of devices and most of these devices are resource-constrained. Blockchain being light-weighted is a great solution for privacy preservation in resource-constrained devices. The privacy aspect of blockchain comes from its ability to provide transparency in a distributed network.
  • 671
  • 15 Sep 2021
Topic Review
Internet-of-Things technologies for Assisted Living
An ambient assisted living (AAL) environment is an integration of stand-alone assistive technologies, solutions, and services. AAL (or simply assisted living) solutions can provide a positive influence on the health and quality of life of people, especially older people. 
  • 1.2K
  • 14 Sep 2021
Topic Review
Knowledge Distillation for ADHD
Attention Deficit Hyperactivity Disorder (ADHD) is a brain disorder with characteristics such as lack of concentration, excessive fidgeting, outbursts of emotions, lack of patience, difficulty in organizing tasks, increased forgetfulness, and interrupting conversation, and it is affecting millions of people worldwide. 
  • 640
  • 14 Sep 2021
Topic Review
RGB-D Data-Based Action Recognition
Early research on Human Action Recognition was dominated by the analysis of still images or videos, localizing the actor in a video spatio-temporally using bounding boxes, temporal extent, and a spatio-temporal cuboid which contains a particular action. Human Action Recognition has many applications, including the automated annotation of user videos, indexing and retrieving user videos, automated surveillance, monitoring elderly patients using specially adapted cameras, robot operations, and live blogging of actions. In recent times, the availability of massive amounts of video data has provided significance to the understanding of video data (through a sequence of images) with the possibility of solving problems such as scene identification, searching through video content, and interaction recognition through video scenes. RGB-D generally refers to Red, Green, Blue plus Depth data captured by RGB-D sensors. An RGB-D image provides a per-pixel depth information aligned with corresponding image pixels. An image formed through depth information is an image channel in which each pixel relates to a distance between the image plane and the corresponding object in the RGB image. The addition of depth information to conventional RGB image helps improve the accuracy and the denseness of the data.
  • 1.6K
  • 14 Sep 2021
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