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International Journal of Reconfigurable and Embedded Systems (IJRES)
Published by Institute of Advanced Engineering and Science
ISSN : 20894864     EISSN : 27222608     DOI : -
Core Subject : Economy,
Economics, Econometrics & Finance
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 456 Documents
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An approach to diagnosis of prostate cancer using fuzzy logic Rawat, Meena; Pathak, Pooja; Vats, Pooja
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i1.pp192-200

Abstract

Early diagnosis of cancers is a major requirement for patients and a complicated job for the oncologist. If it is diagnosed early, it could have made the patient more likely to live. For a few decades, fuzzy logic emerged as an emphatic technique in the identification of diseases like different types of cancers. The recognition of cancer diseases mostly operated with inexactness, inaccuracy, and vagueness. This paper aims to design the fuzzy expert system (FES) and its implementation for the detection of prostate cancer. Specifically, prostate-specific antigen (PSA), prostate volume (PV), age, and percentage free PSA (%FPSA) are used to determine prostate cancer risk (PCR), while PCR serves as an output parameter. Mamdani fuzzy inference method is used to calculate a range of PCR. The system provides a scale of risk of prostate cancer and clears the path for the oncologist to determine whether their patients need a biopsy. This system is fast as it requires minimum calculation and hence comparatively less time which reduces mortality and morbidity and is more reliable than other economic systems and can be frequently used by doctors.
Optimized Kalman filtering in dynamical environments for thumb robot motion estimation Herlambang, Teguh; Susanto, Fajar Annas; Firdaus, Aji Akbar; Kusuma, Vicky Andria; Suprapto, Sena Sukmananda; Muhaimin, Muhaimin; Arof, Hamzah
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i3.pp512-519

Abstract

Stroke, a prevalent nerve disorder in Indonesia, necessitates post-stroke rehabilitation like physical and occupational therapy. Hand and finger muscle training, crucial for restoring movement, often involves innovative solutions like finger prosthetic robotics arms. In particular, the advancement in thumb robotics emphasizes the estimation of thumb motion, where the ensemble Kalman filter square root (EnKF-SR) and H-infinity methods are deemed dependable for both linear and nonlinear models. Simulation results, using 400 ensembles, demonstrated nearly identical accuracy between the methods, exceeding 99%, with a 6-7% increase in accuracy compared to 200 ensembles. These advancements offer promising prospects for effective post-stroke rehabilitation and improved thumb movement restoration.
A novel ensemble deep network framework for scene text recognition Dasari, Sunil Kumar; Mehta, Shilpa; Steffi, Diana
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 2: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i2.pp403-413

Abstract

In recent years, scene text recognition (STR) has always been considered a sequence-to-sequence problem. Attention-based techniques have a greater potential for context-semantic modelling, but they tend to overfit inadequate training data. STR is one of the most important and difficult challenges in image-based sequence recognition. A novel framework ensemble deep network (EDN) is proposed, EDN comprises customized convolutional neural network (CNN), and deep autoencoder. Customized CNN is designed by introducing the optimal spatial transformation module for optimizing the input of irregular text to read for same size. Further, deep autoencoder is introduced with effective attention mechanism utilizing the inherent features. The proposed ensemble deep network-proposed system (EDN-PS) approach outperforms the existing state-of-art techniques for both irregular and regular scene-texts and upon further simulations, the proposed model generates better results for IIIT5K, ICDAR-13, ICDAR-15, and CUTE dataset in comparison with the existing system hence our proposed EDN-PS model outperforms the existing state-of-art methods.
Dual step hybrid routing protocol for network lifetime enhancement in WSN-IoT environment Yankanaik, Kalpavi C.; Munivenkatappa, Sujatha B.
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 2: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i2.pp323-331

Abstract

Recent development in internet of things (IoT) has been generating huge data due to the large number of nodes deployed and utilized for different applications. In addition, these applications utilize big data and require a more efficient mechanism for data sensing and data transmission. This research work proposes dual step hybrid routing (DSHR) protocol for efficient cluster-based routing. It comprises a two-phase algorithm, which aims at finding the optimal path considering clustering. It further comprises several processes such as cluster head selection, optimal path construction, integrating of nodes to cluster head and sensing range optimization. DSHR is evaluated considering the network lifetime; thereafter model is compared with the existing low energy adaptive clustering hierarchy (LEACH) protocol to prove the efficiency.
An exhaustive review of the stream ciphers and their performance analysis Ananth, Raghavendra; Ramaiah, Narayana Swamy
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 2: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i2.pp360-371

Abstract

The number of internet of things (IoT) applications has increased, which has increased the demand for low-resource gadgets. The data produced by these devices must be protected to guarantee security. The devices operate in conditions with limited space, computational power, memory, and energy. High-security standards are difficult to achieve with limited resources. The detailed analysis of various stream ciphers and their performance metrics is reviewed in this manuscript. The functionality of the stream ciphers is categorized and thoroughly discussed based on both the hardware and software viewpoints. The security attacks and their countermeasure methods using stream ciphers are discussed. The performance metrics of most hardware-based stream ciphers, including the ECRYPT stream cipher project (eSTREAM) ciphers, are discussed. Each hardware stream cipher design highlights the hardware constraints such as chip area, frequency, throughput, and hardware efficiency. The work also highlights the various applications using these stream ciphers. The current trends using these stream ciphers are discussed with futuristic goals.
Energy-efficient clustering and routing using fuzzy k-medoids and adaptive ranking-based wireless sensor network Sivaraman, Haritha K.; Leburu, Rangaiah
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i3.pp774-785

Abstract

The wireless sensor network (WSN) is a vital component of infrastructure that is seeing tremendous demand and quick expansion in a variety of industries, including forestry, airports, healthcare, and the military. Increasing network lifetime and reducing power consumption (PC) are now major goals in WSN research. This research proposes a unique energy-efficient cross-layer WSN design that aims to maximize network lifetime while maintaining quality of service (QoS) criteria to address these challenges. The research initially utilizes the fuzzy k-medoids (FKMeds) clustering technique to group sensor nodes (SN) to improve resilience, scalability, and minimize network traffic. Following that, the hybrid improved grey wolf and ant colony (HIGWAC) optimization approach is applied to choose cluster heads (CH), minimizing distances, reducing latency, and optimizing energy stability. Finally, data is transmitted through the shortest pathways using the adaptive ranking-based energy-efficient opportunistic routing (ARanEOR) protocol, which ensures effective and energy-conserving routing in WSN while dynamically lowering network overhead. Compared to existing approaches, the proposed method in this study outperforms them in terms of energy efficiency, latency, and network longevity.
Design and build an airbag system for elderly fall protection using the MPU6050 sensor module Suprapto, Sena Sukmananda; Kusuma, Vicky Andria; Firdaus, Aji Akbar; Putra, Wahyu Haryanto; Yuniar, Risty Jayanti
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i1.pp111-116

Abstract

The use of technology has a significant impact to reduce the consequences of accidents. Sensors, small components that detect interactions experienced by various components, play a crucial role in this regard. This study focuses on how the MPU6050 sensor module can be used to detect the movement of people who are falling, defined as the inability of the lower body, including the hips and feet, to support the body effectively. An airbag system is proposed to reduce the impact of a fall. The data processing method in this study involves the use of a threshold value to identify falling motion. The results of the study have identified a threshold value for falling motion, including an acceleration relative (AR) value of less than or equal to 0.38 g, an angle slope of more than or equal to 40 degrees, and an angular velocity of more than or equal to 30 °/s. The airbag system is designed to inflate faster than the time of impact, with a gas flow rate of 0.04876 m3 /s and an inflating time of 0.05 s. The overall system has a specificity value of 100%, a sensitivity of 85%, and an accuracy of 94%.
Continuous hand gesture segmentation and acknowledgement of hand gesture path for innovative effort interfaces Richhariya, Prashant; Chauhan, Piyush; Kane, Lalit; Dewangan, Bhupesh Kumar
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 2: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i2.pp286-295

Abstract

Human-computer interaction (HCI) has revolutionized the way we interact with computers, making it more intuitive and user-friendly. It is a dynamic field that has found it is applications in various industries, including multimedia and gaming, where hand gestures are at the forefront. The advent of ubiquitous computing has further heightened the interest in using hand gestures as input. However, recognizing continuous hand gestures presents a set of challenges, primarily stemming from the variable duration of gestures and the lack of clear starting and ending points. Our main objective is to propose a solution: the framework for “continuous palm motion analysis and retrieval” based on “Spatial-temporal and path knowledge”. Framework harnesses the power of cognitive deep learning networks (DLN), offering a significant advancement in the continuous hand gesture recognition domain. we conducted rigorous experiments using a diverse video dataset capturing hand gestures for boasting an impressive F-score of up to 0.99. The potential of our framework to significantly enhance the accuracy and reliability of hand gesture recognition in real-world applications.
Adaptive tunicate swarm optimization with partial transmit sequence for phase optimization in MIMO-OFDM Shaik, Abdul Lateef Haroon Phulara; Madhavan, Sowmya; Divakarachari, Parameshachari Bidare; de Prado, Rocío Pérez; Parameshwarappa, Paramesh Siddappa; Gowda, Kavitha Malali Vishveshwarappa
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i3.pp528-541

Abstract

Multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are widely utilized in wireless systems and maximum data rate communications. The MIMO-OFDM technology increases the efficiency of spectrum utilization. The peak-to-average-power ratio (PAPR) minimization in MIMO-OFDM is a complex task in wireless communications systems. In this research, an adaptive tunicate swarm optimization with partial transmit sequence (ATSO-PTS) algorithm is proposed for a reduction of PAPR in MIMO-OFDM. The nonsquare-matrix-based differential space time coding (N-DSTC) scheme is used for the encoding and decoding process of MIMO-OFDM. The N-DSTC encoding and decoding are linear error-correcting codes that are utilized for message transmission over noisy channels. The pre-specified quadrate phase shift keying (QPSK) symbol is deployed for the modulation and demodulation scheme. On the receiver side, the serial to parallel (S/P) conversion, and fast Fourier transform (FFT) are accomplished, alongside the received data bits being demodulated to obtain the output bits. The proposed ATSO-PTS method achieves better results according to performance metrices PAPR, bit error rate (BER) and signal-to-noise-ratio (SNR), with values of about 2.9, 0.01 and 0.025, respectively. This ensures superior results when compared to the existing methods of twin symbol hybrid optimization applied to partial transmit sequence (TSHO-PTS), selective level mapping and PTS (SLM-PTS), and particle swarm and grey wolf (PS-GW) with PTS, respectively.
Proximate node aware optimal and secure data aggregation in wireless sensor network based IoT environment Priyadarshini, Sushma; Parveen, Asma
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i1.pp143-150

Abstract

Internet of things (IoT) has become one of the eminent phenomena in human life along with its collaboration with wireless sensor networks (WSNs), due to enormous growth in the domain; there has been a demand to address the various issues regarding it such as energy consumption, redundancy, and overhead. Data aggregation (DA) is considered as the basic mechanism to minimize the energy efficiency and communication overhead; however, security plays an important role where node security is essential due to the volatile nature of WSN. Thus, we design and develop proximate node aware secure data aggregation (PNA-SDA). In the PNA-SDA mechanism, additional data is used to secure the original data, and further information is shared with the proximate node; moreover, further security is achieved by updating the state each time. Moreover, the node that does not have updated information is considered as the compromised node and discarded. PNA-SDA is evaluated considering the different parameters like average energy consumption, and average deceased node; also, comparative analysis is carried out with the existing model in terms of throughput and correct packet identification.

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