Forthcoming and Online First Articles

International Journal of Systems, Control and Communications

International Journal of Systems, Control and Communications (IJSCC)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Systems, Control and Communications (3 papers in press)

Regular Issues

  • Enhancing radiology workflow: alert system for intracranial hemorrhages using deep learning and single-board computers   Order a copy of this article
    by Shanu Nizarudeen, Ganesh Ramaswamy Shanmughavel 
    Abstract: This study investigates the application of low-cost embedded platforms integrating deep learning models for intracranial hemorrhage classification using head CT images Two experiments were conducted: transfer learning feature extraction and benchmarking CTNet against four AI architectures TL achieved 96% accuracy in multi-label classification with ROC-AUC scores of 0.99-0.997 EfficientNetB0 outperformed other methods in classifying hemorrhage subtypes CTNet showed excellent grading performance in most bleeding types, but relatively weaker performance in subarachnoid hemorrhage. Models were implemented on a Raspberry Pi using TensorFlow Lite for real-time prediction and audio notifications image acquisition conditions impact on results was addressed CTNet demonstrated continuous improvement during training This research highlights the potential of low-cost embedded platforms with deep learning models for optimising workflow in emergency clinics, providing faster interpretation and improving patient care.
    Keywords: intracranial hemorrhage; ICH; single-board computers; classification; transfer learning; deep learning; embedded system.
    DOI: 10.1504/IJSCC.2023.10060081
     
  • IoT-based remote control for robotic arm   Order a copy of this article
    by Tri Nhut Do 
    Abstract: Robotic arms can perform various tasks with high accuracy, efficiency, and safety, especially in hazardous environments. This paper presents a 4 degrees of freedom robotic arm that can be controlled remotely by two methods: direct control via WiFi and indirect control via internet. We have designed an embedded system that allows the user to manipulate the robotic arm by moving the robot hand in different directions. We have also developed two software applications for remote control: one using MIT inventor 2 tool for direct control, and another using a web-based interface for indirect control. The software applications enable the user to adjust the angles of the four servo motors that drive the robotic arm in both clockwise and counter clockwise directions. We have conducted several experiments to demonstrate the feasibility and stability of our system under different scenarios. Our results show that our system can perform wireless control of the robotic arm effectively using various mobile devices such as phone, tablet, or computer such as laptop, personal computer.
    Keywords: internet of things; IoT; cloud computing; robotic arm; motor control.

  • HBBRGSO: an energy and spectral efficiency improvement by novel hybrid meta-heuristic development in massive MIMO communication system   Order a copy of this article
    by Amarender Reddy Byreddy, E. Logashanmugam 
    Abstract: The multi-objective function-based optimal design faces several issues in the MMIMO communication network. To conquer such challenges, an intelligent massive MIMO communication model is proposed by deriving the multi-objective function with a hybrid heuristic approach. Here, the parameters like the number of base station antennas, bandwidth allocation, beamforming vectors, transmit power allocation, and base station switching are optimised to increase the EE and SE in the MMIMO network system. Consequently, the objective function is derived using distinct constraints like Signal to Interference Noise Ratio (SINR), SE and EE, proportional rate, delay, and Quality of Service (QoS). In order to accomplish this function, a novel hybrid algorithm is developed by taking the hybrid binary battle royale galactic swarm optimisation (HBBRGSO). Hence, the proposed framework is analysed with diverse metrics and compared with other classical heuristic approaches. Therefore, extensive results are obtained that maximise the EE and SE in MMIMO communication systems.
    Keywords: energy and spectral efficiency improvement; massive MIMO communication system; hybrid binary battle Royale galactic swarm optimisation; multi-objective function; signal to interference noise ratio; SINR; quality of service; QoS.
    DOI: 10.1504/IJSCC.2023.10062653