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Architecture of the proposed system, split in preprocessing to read the graph and assemble the data structures, and enumeration to identify the matches using intersections.

Low-Power Subgraph Isomorphism at the Edge Using FPGAs

IEEE Xplore Publish Date: 14 April 2025
Author(s): Roberto Bosio, Giovanni Brignone, Teodoro Urso, Mihai T. Lazarescu, Luciano Lavagno, Paolo Pasini
ff Graphical Abstract 5

Automated Models for Predicting Software Defects in Hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) Parallel Programs Using Deep Learning

IEEE Xplore Publish Date: 10 April 2025
Author(s): Amani Saad Althiban, Hajar M. Alharbi, Lama A. Al Khuzayem, Fathy Elbouraey Eassa
Frequency response with and without BESS-SC hybrid system.

Capacity Optimization and Location of BESS-SC Hybrid System for Grid Inertia Support With High Wind Power Penetration

IEEE Xplore Publish Date: 08 April 2025
Author(s): Shami Ahmad Assery, Nan Chen, Xiao-Ping Zhang
The network architecture consists of three interconnected workcells, each containing controllers, sensors, actuators, and cameras, all connected to a cell switch. These cell switches are further linked to a central core switch, which serves as the hub for communication and data aggregation. The core switch connects to a supervisor, which oversees the network and ensures smooth operation.

Network Design for Efficient Video Data Transmission With Real-Time Traffic Constraints in Networked Control Systems

IEEE Xplore Publish Date: 17 March 2025
Author(s): Moustafa M. Awad, Tarek Refaat, Ramez Daoud, Hany M. Elsayed, Hassanein H. Amer
Our system consists of two phases: 1) multi-camera calibration and 2) 3D human reconstruction. In the multi-camera calibration, we optimize camera parameters using a simple ball-wand as a marker. In the 3D human reconstruction, we reconstruct the geometry and appearance of 3d human using the optimized camera parameters and sparse input views.

Robust 3D Human Reconstruction System From Sparse Views in Outdoor Environments

IEEE Xplore Publish Date: 24 February 2025
Author(s): Hansoo Park, Soomin Kim, Bryan Heryanto, Hwasup Lim
The sum of the modal gain confinement factors can exceed 1 for TE and TM (shown) modes

Modal Gain and Loss in Three-Layer Optical Waveguides

IEEE Xplore Publish Date: 19 February 2025
Author(s): Nikhil Polley, Tso-Min Chou, Weida Zhang, Ethan Chou, Jerome K. Butler, Gary A. Evans
This figure shows the overall operational flow of the proposed ReTMiC (Reliability-Aware Thermal Management in Multicore Mixed-Criticality Embedded Systems) method. First, the scheduler receives software and hardware level parameters. As shown in this figure, the proposed method consists of two offline and online phases. In the offline phase, first, the minimum number of the required replica(s) for each task in the maximum v-f level to satisfy the reliability target is computed, and the task graph is extended to include replica(s). Then, the minimum v-f levels for each task are determined such that the reliability target is satisfied. In the next step, all the normal and overrun parts of each HC task and corresponding replicas are mapped to the cores and scheduled in a way that meets timing and TDP constraints. Next, LC tasks are mapped and scheduled in a way that satisfies the QoS and TPD constraints. In the final extracted schedule at the offline phase, all LC, HC, and corresponding replica tasks are scheduled in a way that meets the deadline, reliability, TPD, and QoS constraints even in the worst-case fault or overrun occurrence scenarios. However, since the actual temperatures of tasks are determined at run-time, the temperature should be balanced at runtime. Hence, at design time, the scheduler should determine the temperature balancing points and balancing factors that will be exploited at run-time. To this end, according to the scheduling, the proposed method specifies Balancing Points (BPs) and Balancing Factors (BFs) to balance the overall temperature of the chip at run-time.

ReTMiC: Reliability-Aware Thermal Management in Multicore Mixed-Criticality Embedded Systems

IEEE Xplore Publish Date: 17 February 2025
Author(s): Sepideh Safari, Mohsen Ansari, Shaahin Hessabi, Jörg Henkel
Fiber orientation analysis using baseline structure tensor and proposed structure tensor scale-space. The detected orientation of the fibers is represented through unique colors. Both methods produce generally correct results, but the proposed version provides sharper results in more complex areas and captures finer details in the central smaller fibers. All volumes are visualized with the background removed.

Feature-Centered First Order Structure Tensor Scale-Space in 2D and 3D

IEEE Xplore Publish Date: 08 January 2025
Author(s): Pawel Tomasz Pieta, Anders Bjorholm Dahl, Jeppe Revall Frisvad, Siavash Arjomand Bigdeli, Anders Nymark Christensen
(a) The proposed TRIO-TCAM cell design; (b), (c), and (d) The configuration of the TRIO-TCAM during TCAM mode operation.

TRIO-TCAM: An Area and Energy-Efficient Triple-State-in-Cell Ternary Content-Addressable Memory Architecture

IEEE Xplore Publish Date: 12 December 2024
Author(s): Thanh-Dat Nguyen, Sungju Ryu, Ik-Joon Chang
Review of biodegradable and renewable antennas for Green IoT sensors in various application domains.

Biodegradable and Renewable Antennas for Green IoT Sensors: A Review

IEEE Xplore Publish Date: 11 December 2024
Author(s): Amir Zahedi, Ranjith Liyanapathirana, Karthick Thiyagarajan