Anger cameras based on monolithic NaI scintillators read out by an array of PMTs are predominant in planar gamma imaging and SPECT. However, position estimation of gamma interactions is usually severely degraded near the edges of the scintillator which can be extremely undesirable for applications like breast imaging. Here we propose a relatively cost-effective solution based on the use of scintillators with absorptive edges with an unconventional light-guide-PMT layout employing a maximum likelihood positioning algorithm. The basic design on which we aim to improve consists of a monolithic NaI(Tl) scintillator read out by 3 × 5 square PMTs (conventional layout, CL) that could be suitable for molecular breast imaging. To better detect gamma interactions near the crystal's critical edge, we tried different set-ups: we replaced the 5 large PMTs near the edge by 11 smaller PMTs (small-sensor layout, SSL); we emulated rectangular PMTs along the critical edge by inserting a row of 5 rectangular light-guides that direct the light toward square PMTs placed behind (shifted layout, SL); we inserted rectangular light-guides alternatingly, such that the PMTs are in an interlocking pattern (alternating shifted layout, ASL). The performance of our designs was tested with Monte Carlo simulations. Results showed that SSL, SL, and ASL gave better spatial resolution near the critical edge than CL (3.4, 3.6, and 4.1 mm near the edge compared with 5.3 mm for CL), and thus resulted in a larger usable detector area. To conclude, for applications where small dead edges are crucial, our designs may be cost-effective solutions.
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http://dx.doi.org/10.1016/j.ejmp.2018.04.004 | DOI Listing |
Sensors (Basel)
January 2025
Department of Computer Science and Engineering, Yanbu Industrial College, Royal Commission for Jubail and Yanbu, Yanbu Industrial City 41912, Saudi Arabia.
This paper provides the complete details of current challenges and solutions in the cybersecurity of cyber-physical systems (CPS) within the context of the IIoT and its integration with edge computing (IIoT-edge computing). We systematically collected and analyzed the relevant literature from the past five years, applying a rigorous methodology to identify key sources. Our study highlights the prevalent IIoT layer attacks, common intrusion methods, and critical threats facing IIoT-edge computing environments.
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December 2024
Guangxi Key Laboratory of Machine Vision and Intelligent Control, Wuzhou University, Wuzhou 543000, China.
A high-quality optical path alignment is essential for achieving superior image quality in optical biological microscope (OBM) systems. The traditional automatic alignment methods for OBMs rely heavily on complex masker-detection techniques. This paper introduces an innovative, image-sensor-based optical path alignment approach designed for low-power objective (specifically 4×) automatic OBMs.
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December 2024
Directorate for Railways, Nemanjina 6, 11000 Belgrade, Serbia.
The manuscript conducts a comparative analysis to assess the impact of noise on medical images using a proposed threshold value estimation approach. It applies an innovative method for edge detection on images of varying complexity, considering different noise types and concentrations of noise. Five edges are evaluated on images with low, medium, and high detail levels.
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December 2024
AVIC Aeronautics Computing Technology Research Institute, Xi'an 710069, China.
The rapid deployment and enhanced communication capabilities of unmanned aerial vehicles (UAVs) have enabled numerous real-time sensing applications. These scenarios often necessitate task offloading and execution under stringent transmission delay constraints, particularly for time-critical applications such as disaster rescue and environmental monitoring. This paper investigates the improvement of MEC-based task offloading services in energy-constrained UAV networks using backscatter communication (BackCom) with non-orthogonal multiple access (BAC-NOMA).
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December 2024
Stony Brook Institute at Anhui University, Hefei 230000, China.
The Internet of Things (IoT) contains many devices that can compute and communicate, creating large networks. Industrial Internet of Things (IIoT) represents a developed application of IoT, connecting with embedded technologies in production in industrial operational settings to offer sophisticated automation and real-time decisions. Still, IIoT compels significant cybersecurity threats beyond jamming and spoofing, which could ruin the critical infrastructure.
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