The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (FFT iFFT BESSEL functions) is widely applied to obtain information with high precision accuracy...
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ISBN:
(纸本)9783031298561;9783031298578
The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (FFT iFFT BESSEL functions) is widely applied to obtain information with high precision accuracy. Signal processing has a wider implementation in general-purpose processors Our interest was focused on the use of FPGAs (Field-Programmable Gate Arrays) in order to minimize the computational complexity in single processor architecture then be accelerated on FPGA and meet realtime and energy efficiency ***-purpose processors are not efficient for signal processing. We implemented the acoustic backscattered signal processing model on the DE1SOC FPGA and compared it to Odroid xu4. By comparison, the computing latency of Odroid xu4 and FPGA are 60 s, and 20 s respectively. The detailed SoC FPGA-based system has shown that acoustic spectra are performed at up to 3 times faster than the Odroid xu4 implementation. FPGA-based system of processing algorithms is realized with an absolute error about 10(-2). This study underlines the increasing importance of embeddedsystems in underwater acoustics, especially in non-destructive testing. It is possible to obtain information related to the detection and characterization of submerged cells. So we have achieved good experimental results in realtime and energy efficiency.
Facial recognition plays a crucial role in various applications, as it tackles challenges such as changes in lighting, position, and facial expressions. This study aims to explore the effectiveness of ensemble learnin...
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Incremental memory checkpointing is a crucial primitive required by applications such as live migration, cloning, debugging etc. In many implementations of incremental checkpointing, the memory modifications are track...
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ISBN:
(纸本)9781665494236
Incremental memory checkpointing is a crucial primitive required by applications such as live migration, cloning, debugging etc. In many implementations of incremental checkpointing, the memory modifications are tracked by restricting write access to memory pages using the support provided in the memory management unit (MMU) hardware. Disabling write access impacts the performance of applications because of the page faults induced in the form of permission violation on memory store operations by the applications. In this paper, we propose LDT, a light-weight memory write monitoring mechanism to support efficient incremental checkpointing. LDT is designed to work in systems with MMU support for page dirty indicators (such as dirty-bit in x86 systems) by enabling polymorphic use of the indicators such that no other subsystem is impacted because of LDT. We design and implement LDT in the Linux kernel as an alternate to the existing writerestriction based technique. We establish the correctness and comparative efficiency of LDT through extensive experimental analysis. The results show that under write-heavy workloads, LDT outperforms write-restriction based technique by a factor of 2x in execution time. For real-world workload benchmarks such as Redis, LDT results in 2% to 8% throughput improvement compared to the state-of-the-art dirty tracking technique.
This research introduces a novel approach to multi-document summarization known as LLama2. Leveraging advanced language model capabilities, LLama2 efficiently condenses complex narratives into concise yet insightful s...
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This research develops and optimizes an optical character recognition (OCR) system for goat weighing scales using intelligent computer vision and distributed computing to enhance accuracy and efficiency in real-world ...
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The novel sensor for Leak detection, using Self-Plasma OES. This SP-OES can be used at dark chambers and even other dark locations. By using this sensor for realtime leak detection of metallization process, high ROI ...
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Cross-Site Scripting (XSS) remains one of the most persistent vulnerabilities in web applications, necessitating robust detection mechanisms to counter increasingly sophisticated attack patterns. This study proposes a...
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The emerging trend of small satellites for earth observation missions has enabled commercial organisations to exploit the horizon for various business applications related to weather forecasting/monitoring, Land Use L...
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ISBN:
(纸本)9781665488679
The emerging trend of small satellites for earth observation missions has enabled commercial organisations to exploit the horizon for various business applications related to weather forecasting/monitoring, Land Use Land Cover (LULC) classifications, disaster (such as oil spill or forest fire) monitoring etc. However, the limited power and computational capacity of these small satellites arising out of the size and weight restrictions have posed newer challenges, primarily related to low-power on-board data processing and transmission. One possible approach is to harness the capabilities of the evolving neuromorphic computing paradigm for such low-power computing requirements. One possible application can be lossless compression of high-resolution earth observation images before sending those downstream to ground stations for further analysis. In this paper, we propose a novel method of lossless image compression based on classical Arithmetic Encoding that exploits the low power computing capability of Spiking Neural Networks and neuromorphic platforms. We experimentally prove that our SNN approach achieves compression ratio at-par with state of the art ANN methods with an estimated 2.5x power efficiency and 50% lower latency with a much smaller model - thereby enabling on-board image compression and at the same time, saving on a corresponding amount of energy during transmission.
Isolating microalgae in in-situ liquid environment based on optoelectronic tweezers (OETs) enables providing specific species of microalgae in high-purity, thus has significant potential in environmental detection, aq...
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Computer Vision has changed how a lot of smart systems function. Cyber Physical systems, such as Advanced Driver Assistance systems (ADAS), make use of this technology to see their surroundings and act accordingly, bu...
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