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International Journal of Reconfigurable and Embedded Systems (IJRES)
ISSN : 20894864     EISSN : 27222608     DOI : -
Core Subject : Economy,
The centre of gravity of the computer industry is now moving from personal computing into embedded computing with the advent of VLSI system level integration and reconfigurable core in system-on-chip (SoC). Reconfigurable and Embedded systems are increasingly becoming a key technological component of all kinds of complex technical systems, ranging from audio-video-equipment, telephones, vehicles, toys, aircraft, medical diagnostics, pacemakers, climate control systems, manufacturing systems, intelligent power systems, security systems, to weapons etc. The aim of IJRES is to provide a vehicle for academics, industrial professionals, educators and policy makers working in the field to contribute and disseminate innovative and important new work on reconfigurable and embedded systems. The scope of the IJRES addresses the state of the art of all aspects of reconfigurable and embedded computing systems with emphasis on algorithms, circuits, systems, models, compilers, architectures, tools, design methodologies, test and applications.
Arjuna Subject : -
Articles 16 Documents
Search results for , issue "Vol 12, No 1: March 2023" : 16 Documents clear
Intrusion detection systems for internet of thing based big data: a review Imane Laassar; Moulay Youssef Hadi
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 12, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v12.i1.pp87-96

Abstract

Network security is one of the foremost anxieties of the modern time. Over the previous years, numerous studies have been accompanied on the intrusion detection system. However, network security is one of the foremost apprehensions of the modern era this is due to the speedy development and substantial usage of altered technologies over the past period. The vulnerabilities of these technologies security have become a main dispute intrusion detection system is used to classify unapproved access and unusual attacks over the secured networks. For the implementation of intrusion detection system different approaches are used machine learning technique is one of them. In order to comprehend the present station of application of machine learning techniques for solving the intrusion discovery anomalies in internet of thing (IoT) based big data this review paper conducted. Total 55 papers are summarized from 2010 and 2021 which were centering on the manner of the single, hybrid and collaborative classifier design. This review paper also includes some of the basic information like IoT, big data, and machine learning approaches are discussed.
Ultra-low leakage static random access memory design Didigam Anitha; Mohd. Masood Ahmad
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 12, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v12.i1.pp60-69

Abstract

An ultra-low leakage static random-access memory (SRAM) cell structure with 8 transistors is proposed in this paper. Compared to the 6T SRAM and other existing 8T SRAM cells, leakage power of the proposed cell in hold mode reduced significantly. The stability parameters of the proposed cell are calculated using butterfly method and also N-curve method. Proposed SRAM achieves better write margin with slightly less read margin than 6T SRAM. Proposed technique consumes 790 PW of power in hold mode, which is very less compared to other existing techniques. Therefore, the proposed cell is appropriate for hold mode applications. The simulations are carried out by using Cadence (Virtuoso Schematic and layout editor) tools with GPDK45-nm technology.
Effects of wood texture and color on aesthetic pleasure: two experimental studies Zetian Dai; Juan Xue; Shoushan Wang
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 12, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v12.i1.pp125-134

Abstract

The texture and color on wood are key factors that influence an individual's perception of it. However, little research has been done to confirm what kind of pattern in textures and colors are more likely to evoke individual aesthetic pleasure. Therefore, twenty-four decorative wood from northern China were selected, identified, and quantified in their colors with a CR-5 Colorimeter. We picked out eight kinds of wood with optimal texture characteristics through feature-fusion wood grain recognition (FWGR) and enhanced the texture features with photoshop in VR space. The result show that, in the color dimension, woods in the hue range of 20-25 and saturation of 65-75 were considered beautiful for individual perception of aesthetic. In the texture dimension, the size of the space affects the individual's preference for texture. When the pattern of the wood ray is continuous and clear, the individual's perception of its fluidity is enhanced; while for the fuzzy and interrupted pattern of the wood ray, the individual does not follow the fluidity of the line but focuses on the overall uniformity.
Application of artificial intelligence techniques in the intensive care unit Prabhudutta Ray; Sachin Sharma; Raj Raval
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 12, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v12.i1.pp42-50

Abstract

Intensive care unit deals with data that are dynamic in nature like real time measurement of health condition to laboratory test data that are continuously changes accordingly with time. Artificial intelligence (AI’s) potential ability to perform complex pattern analyses using large volumes of data. Generated pattern discovers the new symptoms of the disease in the Intensive care units (ICUs), helps the doctors to prescribe the new drug discovery which is helpful to intelligent use. Currently research work has been focused in the ICU making more efficient clinical workflow by generation of high-risk patterns from improved high volumes of data. Emerging area of AI in the ICU includes mortality prediction, uses of powerful sensors, new drug discovery, prediction of length of stay and legal role in uses of drugs for severity of disease. This review focuses latest application of AI drugs and other relevant issues for the ICU.
A systematic literature review on hardware implementation of image processing Zul Imran Azhari; Samsul Setumin; Anis Diyana Rosli; Siti Juliana Abu Bakar
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 12, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v12.i1.pp19-28

Abstract

Image processing has become under the spotlight recently and leads to a significant shift in various fields such as biomedical, satellite images, and graphical applications. Nevertheless, the poor quality of an image is one of the noticeable limitations of image processing as it restricts efficient data extraction to be conducted. Conventionally, the image was processed via software applications such as MATLAB. In spite of the software's ability to cater to the data extraction of low-quality image issues, it still suffers from the time-consuming issue. As the ability to obtain a rapid outcome is a favorable feature of efficient image processing, the use of hardware in image processing is deemed to keep the addressed issue at bay. Thus, the image enhancement techniques using hardware have gradually rising interest among researchers with numerous approaches such as field programmable gate array (FPGA). In this study, 25 different research papers published from 2016 to 2021 are studied and analyzed to focus on the performance of FPGA as hardware implementation in image processing techniques.
SDSFLF: fault localization framework for optical communication using software digital switching network Chitra Raju; Sudarmani Rajagopal; Kanagaraj Venusamy; Kannadhasan Suriyan; Manjunathan Alagarsamy
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 12, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v12.i1.pp113-124

Abstract

Optical network is an emerging technology for data communication inworldwide. The information is transmitted from the source to destination through the fiber optics. All optical network (AON) provides good transmission transparency, good expandability, large bandwidth, lower bit error rate (BER), and high processing speed. Link failure and node failure haveconsistently occurred in the traditional methods. In order to overcome the above mentioned issues, this paper proposes a robust software defined switching enabled fault localization framework (SDSFLF) to monitor the node and link failure in an AON. In this work, a novel faulty node localization (FNL) algorithm is exploited to locate the faulty node. Then, the software defined faulty link detection (SDFLD) algorithm that addresses the problem of link failure. The failures are localized in multi traffic stream (MTS) and multi agent system (MAS). Thus, the throughput is improved in SDSFLF compared than other existing methods like traditional routing and wavelength assignment (RWA), simulated annealing (SA) algorithm, attackaware RWA (A-RWA) convex, longest path first (LPF) ordering, and biggest source-destination node degree (BND) ordering. The performance of the proposed algorithm is evaluated in terms of network load, wavelength utilization, packet loss rate, and burst loss rate. Hence, proposed SDSFLF assures that high performance is achieved than other traditional techniques.

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