Timber and wood are natural materials with a wide range of physical and mechanical properties, making them challenging to measure. Some methods for evaluating these properties are destructive and time-consuming, while...
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the article explores character recognition using convolutional neural networks (CNNs) optimized withthe CUDA platform to enhance computational efficiency. It outlines the CNN architecture, methods for leveraging GPU-...
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ISBN:
(数字)9798331531836
ISBN:
(纸本)9798331531843
the article explores character recognition using convolutional neural networks (CNNs) optimized withthe CUDA platform to enhance computational efficiency. It outlines the CNN architecture, methods for leveraging GPU-based parallel data processing, and presents experimental results derived from the MNIST dataset. the study highlights that implementing CUDA drastically reduces processing time while maintaining a high level of predictive accuracy. the findings emphasize the potential of GPU acceleration in handling intensive computational tasks, making it a promising approach for real-time applications in image recognition and machine learning.
this paper presents an optimized implementation of the Apriori algorithm tailored for large-scale data mining in cloud-native, serverless environments, utilizing real-world fuel datasets. Our approach achieves a 28% r...
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It is known that the multiplier is widely applied, and to produce the outputs for the next stage, there is a reliance on the previous stage. Due to this, the multiplication process takes time to complete. As the binar...
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ISBN:
(数字)9798331544607
ISBN:
(纸本)9798331544614
It is known that the multiplier is widely applied, and to produce the outputs for the next stage, there is a reliance on the previous stage. Due to this, the multiplication process takes time to complete. As the binary bit counts of the multiplier and multiplicand increase, it takes longer to generate the output. this longer delay can severely impair the overall performance of digital systems, especially in applications requiring high-speed computations. therefore, optimizing the Multiplier for both speed and power efficiency is crucial to enhancing the performance of modern computing architectures. To achieve this optimization, various techniques such as parallelprocessing and reduced gate counts can be employed. Moreover, utilising advanced algorithms and hardware accelerators can enhance the efficiency of these multipliers in challenging computational settings. this will affect the circuit performance. A new technique known as the reordering technique is implemented in this project to enhance the multiplier in terms of speed and efficiency. this method is implemented by separating the high-state bits from the low-state bits using the reordering circuit, and then the separated bits are processed in the usual manner. this helps in the reduction of critical path latency, which benefits by enhancing the circuit's power consumption as less power is being released as heat or another form.
Secure Multiparty Computation (SMC) facilitates secure collaboration among multiple parties while safeguarding the privacy of their confidential data. this paper introduces a two-party quantum SMC protocol designed fo...
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Medical image segmentation is a critical process in identifying disease-infected regions for diagnostic and treatment purposes. this paper introduces an FPGA-based framework for implementing the Expectation Maximizati...
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ISBN:
(数字)9798331520762
ISBN:
(纸本)9798331520779
Medical image segmentation is a critical process in identifying disease-infected regions for diagnostic and treatment purposes. this paper introduces an FPGA-based framework for implementing the Expectation Maximization/Markov Random Field (E M/MP M) algorithm in 3D medical image segmentation. FPGA platforms offer unparalleled advantages in terms of parallelprocessing, speed, and energy efficiency, making them a promising choice for real-time medical image analysis. this proposed framework enables rapid segmentation of 3D images, leveraging the FPGA's on-chip memory and custom logic for efficient pixel classification and data processing. the adaptive design also supports the integration of external RAM for larger datasets. Simulated using Verilog HDL and Quartus Prime, this work demonstrates accurate segmentation results through virtual testing, thus showcasing the system's robustness for medical applications.
Docker image storage systems, like Docker registry, often employ deduplication to reduce storage overhead. Existing deduplication methods for these systems detect redundancy at either layer or file level, each with it...
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