Microprocessors and Microsystems
About: Microprocessors and Microsystems is an academic journal published by Elsevier BV. The journal publishes majorly in the area(s): Computer science & Field-programmable gate array. It has an ISSN identifier of 0141-9331. Over the lifetime, 4059 publications have been published receiving 35394 citations. The journal is also known as: Embedded hardware design & MICPRO.
Papers published on a yearly basis
TL;DR: The effectiveness of the proposed PSO-based algorithm is demonstrated by comparing it with the genetic algorithm, which is well-known population-based probabilistic heuristic, on randomly generated task interaction graphs.
Abstract: Task assignment is one of the core steps to effectively exploit the capabilities of distributed or parallel computing systems. The task assignment problem is an NP-complete problem. In this paper, we present a new task assignment algorithm that is based on the principles of particle swarm optimization (PSO). PSO follows a collaborative population-based search, which models over the social behavior of bird flocking and fish schooling. PSO system combines local search methods (through self experience) with global search methods (through neighboring experience), attempting to balance exploration and exploitation. We discuss the adaptation and implementation of the PSO search strategy to the task assignment problem. The effectiveness of the proposed PSO-based algorithm is demonstrated by comparing it with the genetic algorithm, which is well-known population-based probabilistic heuristic, on randomly generated task interaction graphs. Simulation results indicate that PSO-based algorithm is a viable approach for the task assignment problem.
TL;DR: This paper describes an application of Bluetooth technology in home automation and networking environment, and proposes a network, which contains a remote, mobile host controller and several client modules (home appliances).
Abstract: The past decade has seen significant advancement in the field of consumer electronics. Various ‘intelligent’ appliances such as cellular phones, air-conditioners, home security devices, home theatres, etc. are set to realize the concept of a smart home. They have given rise to a Personal Area Network in home environment, where all these appliances can be interconnected and monitored using a single controller. Busy families and individuals with physical limitation represent an attractive market for home automation and networking. A wireless home network that does not incur additional costs of wiring would be desirable. Bluetooth technology, which has emerged in late 1990s, is an ideal solution for this purpose. This paper describes an application of Bluetooth technology in home automation and networking environment. It proposes a network, which contains a remote, mobile host controller and several client modules (home appliances). The client modules communicate with the host controller through Bluetooth devices. q 2002 Elsevier Science B.V. All rights reserved.
TL;DR: This article is comparing the performance of ML (Support Vector Machine, Random Forest), Random Forest, Stochastic Gradient Descent (SGD), & DL (Inception-v3, V GG-16, VGG-19) in terms of citrus plant disease detection as DL methods perform better than that of ML methods in case of disease detection.
Abstract: Plants are recognized as essential as they are the primary source of humanity's energy production since they are having nutritious, medicinal, etc. values. At any time between crop farming, plant diseases can affect the leaf, resulting in enormous crop production damages and economic market value. Therefore, in the farming industry, identification of leaf disease plays a crucial role. It needs, however, enormous labor, greater preparation time, and comprehensive plant pathogen knowledge. For the identification of plant disease detection various machine learning (ML) as well as deep learning (DL) methods are developed & examined by various researchers, and many of the times they also got significant results in both cases. Motivated by those existing works, here in this article we are comparing the performance of ML (Support Vector Machine (SVM), Random Forest (RF), Stochastic Gradient Descent (SGD)) & DL (Inception-v3, VGG-16, VGG-19) in terms of citrus plant disease detection. The disease classification accuracy (CA) we received by experimentation is quite impressive as DL methods perform better than that of ML methods in case of disease detection as follows: RF-76.8% > SGD-86.5% > SVM-87% > VGG-19–87.4% > Inception-v3–89% > VGG-16–89.5%. From the result, we can tell that RF is giving the least CA whereas VGG-16 is giving the best in terms of CA.
TL;DR: Test results show that the harvesting circuit which acted as a plug-in to the router nodes manages energy harvesting and storage, and enables near-perpetual, harvesting aware operation of the router node.
Abstract: A unique method has been developed to scavenge energy from monocrystaline solar cells to power wireless router nodes used in indoor applications. The system's energy harvesting module consists of solar cells connected in series-parallel combination to scavenge energy from 34W fluorescent lights. A set of ultracapacitors were used as the energy storage device. Two router nodes were used as a router pair at each route point to minimize power consumption. Test results show that the harvesting circuit which acted as a plug-in to the router nodes manages energy harvesting and storage, and enables near-perpetual, harvesting aware operation of the router node.
TL;DR: The main aspects of CPS and the corresponding applications, technologies, and standards are surveyed and the existing security measures are presented and analyzed while identifying their main limitations.
Abstract: Typically, Cyber-Physical Systems (CPS) involve various interconnected systems, which can monitor and manipulate real objects and processes. They are closely related to Internet of Things (IoT) systems, except that CPS focuses on the interaction between physical, networking and computation processes. Their integration with IoT led to a new CPS aspect, the Internet of Cyber-Physical Things (IoCPT). The fast and significant evolution of CPS affects various aspects in people's way of life and enables a wider range of services and applications including e-Health, smart homes, e-Commerce, etc. However, interconnecting the cyber and physical worlds gives rise to new dangerous security challenges. Consequently, CPS security has attracted the attention of both researchers and industries. This paper surveys the main aspects of CPS and the corresponding applications, technologies, and standards. Moreover, CPS security vulnerabilities, threats and attacks are reviewed, while the key issues and challenges are identified. Additionally, the existing security measures are presented and analyzed while identifying their main limitations. Finally, several suggestions and recommendations are proposed benefiting from the lessons learned throughout this comprehensive review.