Topic Review
Embedded Machine Learning
Embedded machine learning (EML) can be applied in the areas of accurate computer vision schemes, reliable speech recognition, innovative healthcare, robotics, and more. However, there exists a critical drawback in the efficient implementation of ML algorithms targeting embedded applications. Machine learning algorithms are generally computationally and memory intensive, making them unsuitable for resource-constrained environments such as embedded and mobile devices. In order to efficiently implement these compute and memory-intensive algorithms within the embedded and mobile computing space, innovative optimization techniques are required at the algorithm and hardware levels. 
  • 329
  • 01 Nov 2021
Topic Review
Embedded Brain Computer Interface
We attempt to summarize the last two decades of embedded Brain-Computer Interface mostly because of the electroencephalography influence on these systems. Numerous noninvasive EBCIs have been developed, described, and tested. Noninvasive nature of the EEG-based BCIs made them the most popular BCI systems.
  • 281
  • 15 Jul 2021
Topic Review
Electrochemical Random-Access Memory
Electrochemical Random-Access Memory (ECRAM) is a type of non-volatile memory (NVM) with multiple levels per cell (MLC) designed for deep learning analog acceleration. An ECRAM cell is a three-terminal device composed of a conductive channel, an insulating electrolyte, an ionic reservoir, and metal contacts. The resistance of the channel is modulated by ionic exchange at the interface between the channel and the electrolyte upon application of an electric field. The charge-transfer process allows both for state retention in the absence of applied power, and for programming of multiple distinct levels, both differentiating ECRAM operation from the one of a field-effect transistor (FET). The write operation is deterministic and can result in symmetrical potentiation and depression, making ECRAM arrays attractive for acting as artificial synaptic weights in physical implementations of artificial neural networks (ANN). The technology challenges include open circuit potential (OCP) and semiconductor foundry compatibility associated with energy materials. Universities, government laboratories, and corporate research teams have contributed to the development of ECRAM for analog computing. Notably, Sandia National Laboratories designed a lithium-based cell inspired by solid-state battery materials, Stanford University built an organic proton-based cell, and International Business Machines (IBM) demonstrated in-memory selector-free parallel programming for a logistic regression task in an array of metal-oxide ECRAM designed for insertion in the back end of line (BEOL).
  • 9
  • 17 Nov 2022
Topic Review
Digital Twin Applications
Industrial Digital Twin (IDT) systems integrate physical and virtual data throughout a product life cycle.
  • 165
  • 05 May 2022
Dharma Prakash Agrawal
Professor Dharma P. Agrawal, our beloved friend, mentor, and Editor-in-Chief of Journal of Sensor and Actuator Networks, passed away on 15 February 2021. Professor Agrawal was a renowned computer scientist who specialized in Wireless Networks and Communications and Computer Architecture. Since 1998, he had been the Ohio Board of Regents Distinguished Professor of Electrical Engineering and Compu
  • 74
  • 01 Sep 2022
Topic Review
Delay Line Memory
Delay line memory is a form of computer memory, now obsolete, that was used on some of the earliest digital computers. Like many modern forms of electronic computer memory, delay line memory was a refreshable memory, but as opposed to modern random-access memory, delay line memory was sequential-access. Analog delay line technology had been used since the 1920s to delay the propagation of analog signals. When a delay line is used as a memory device, an amplifier and a pulse shaper are connected between the output of the delay line and the input. These devices recirculate the signals from the output back into the input, creating a loop that maintains the signal as long as power is applied. The shaper ensures the pulses remain well-formed, removing any degradation due to losses in the medium. The memory capacity is determined by dividing the time taken to transmit one bit into the time it takes for data to circulate through the delay line. Early delay-line memory systems had capacities of a few thousand bits, with recirculation times measured in microseconds. To read or write a particular bit stored in such a memory, it is necessary to wait for that bit to circulate through the delay line into the electronics. The delay to read or write any particular bit is no longer than the recirculation time. Use of a delay line for a computer memory was invented by J. Presper Eckert in the mid-1940s for use in computers such as the EDVAC and the UNIVAC I. Eckert and John Mauchly applied for a patent for a delay line memory system on October 31, 1947; the patent was issued in 1953. This patent focused on mercury delay lines, but it also discussed delay lines made of strings of inductors and capacitors, magnetostrictive delay lines, and delay lines built using rotating disks to transfer data to a read head at one point on the circumference from a write head elsewhere around the circumference.
  • 3
  • 01 Dec 2022
Topic Review
Databases in Metabolomics
Metabolomics has advanced from innovation and functional genomics tools and is currently a basis in the big data-led precision medicine era. Metabolomics is promising in the pharmaceutical field and clinical research.
  • 29
  • 27 Oct 2022
Topic Review
Cloud-Fog-Edge Computing for Smart Agriculture
Cloud Computing is a well-established paradigm for building service-centric systems. However, ultra-low latency, high bandwidth, security, and real-time analytics are limitations in Cloud Computing when analysing and providing results for a large amount of data. Fog and Edge Computing offer solutions to the limitations of Cloud Computing. The number of agricultural domain applications that use the combination of Cloud, Fog, and Edge is increasing in the last few decades.
  • 673
  • 08 Oct 2021
Topic Review
Blockchain–Cloud Integration
Blockchain is a new and emergent technology that is expected to change the way current markets work. It is a distributed digital ledger and is decentralized. With the current working capacity of blockchain, it has the potential to be the operating system of smart cities. Blockchain is technology that is open source and distributed and is used to record transactions between parties. It provides a way to develop a system that is both verifiable and secured. Blockchain is open source, so different versions of blockchain are available on the market. Each version is developed depending upon the different needs of the various industries. Blockchain is neither owned nor singly controlled by any one authority. Blockchain technology is evolving at a swift pace. It started with Bitcoin, and now there are many types of blockchain. Organizations are developing different versions of blockchain depending upon their need and benefits.
  • 123
  • 21 Jul 2022
Topic Review
Blockchain-Enabled Vehicular Ad Hoc Networks
Within the paradigm of distributed ledger technology (DLT), the communication models and practices for vehicular ad hoc networks (VANETs) have been revolutionized. VANETs introduce a network of self-organizing vehicles that act as mobile nodes. They confine the communication between vehicles and roadside units as V2V and V2R. They assists drivers in avoiding collisions, picking the shortest route on the basis of traffic optimization, identifying tolls and the nearest fuel stations, and in enhancing the safety of assets and lives. They facilitate the communication of vehicles across the network for real-time data transmission. They improve the road safety mechanism and provide instant alerts or information in order to concern the authorities in cases of emergency situations, such as rollovers, accidents, etc. The existing architecture of VANETs also exposes vulnerabilities, such as data sniffing, impersonation, and ransomware attacks.
  • 221
  • 07 Apr 2022
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