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共 2975 条记录，以下是2871-2880 订阅

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Innovative Traffic Optimization Techniques: Integrating Braess' Paradox and Vision Transformer architectures (ViT) for Novel Roadway Modalities 23

Innovative Traffic Optimization Techniques: Integrating Brae...

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Proceedings of the 2023 7th international conference on Natural Language processing and Information Retrieval

作者： Siddhant Singh Archit thanikella Memorial High School United States of America Panther Creek High School United States of America

ISBN: (纸本)9798400709227

the Traffic Management System employs Braess' paradox to reduce congestion by altering driving patterns and utilizes the Frank-Wolfe method to create efficient routes. Integrated with a state-of-the-art pothole detection model, which utilizes Vision Transformer and Transformer architectures, the system dynamically adapts to road conditions. this innovative approach, trained on a Mumbai Hyperloop station dataset, includes a Two-Way Transformer network for precise road condition analysis, enhancing traffic flow and safety. It has achieved a 35% decrease in traffic congestion, 47% faster incident response, and 33% shorter trip durations. the system's integration of advanced technologies paves the way for future autonomous vehicle networks and offers significant benefits for urban transportation and planning, simultaneously addressing the challenges of potholes and congestion.

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Evolution of nanomechanical olfactory sensor as an artificial nose

Evolution of nanomechanical olfactory sensor as an artificia...

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international conference and Workshop on Computing and Communication (IEMCON)

作者： Riya Dam Sahil Sarkar Rishab Sarbadhikary Avirup Ghosh Souvik Ghosh Mechanical Engineering Department University of Engineering & Management Kolkata Electronics and Communication Engineering Department University of Engineering & Management Kolkata

ISBN: (纸本)9781509009978

In this paper we have focussed in the working principle of the cantilever array based nanomechanical systems that are used for olfaction. In vertebrates, the physiology of olfaction is composed of a large number of cells which react in parallel but differential fashion to certain odours. Studies have shown that highly sensitive cantilevers, having high length to thickness ratio and capable of optical deflection measurement permit them to become extremely sensitive to force measurement in the dimension of pico-nanometer. Medical tests based on breath analysis can be benefited by this phenomenon. Our objective is to find out the prospects of differential olfactory characteristics that are materialized in the nanomechanical systems. Time based multiplexing of the signal for analysis and formation of a pattern through artificial neural network model can bring a huge development over faster and intelligent diagnosis of a variety of disease.

关键词： Micromechanical devices Signal processing Olfactory Sensor arrays Nanobioscience

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Skin Cancer Detection Based on Transfer Learning Techniques

Skin Cancer Detection Based on Transfer Learning Techniques

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international conference on Advanced Technologies for Signal and Image processing (ATSIP)

作者： Abdelkader Alrabai Amira Echtioui Fathi Kallel Advanced Technologies for Medicine and Signals Laboratory ‘ATMS’ National Engineering School of Sfax (ENIS) Sfax University Sfax Tunisia National School of Electronics and Communications Sfax University Sfax Tunisia

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

Skin cancer detection and classification are critical for early diagnosis and treatment, particularly with melanoma contributing significantly to global mortality rates. this paper presents a study that uses transfer learning with convolutional neural networks (CNNs) to classify skin cancer images as Benign or Malignant. Two pre-trained CNN architectures: InceptionV3, and Xception, are employed with transfer learning and fine-tuning and evaluated for their performance. Notably, InceptionV3 achieved a precision of 0.8914, recall of 0.8909, F1 score of 0.8910, accuracy of 0.8909, and ROC/AUC of 0.8911. these metrics, along with those from the Xception model, are compared to assess their efficacy in early detection. InceptionV3 outperforms state-of-the-art methods, demonstrating its superiority in skin cancer classification. the study aims to contribute to dermatological healthcare by enhancing skin cancer diagnosis through efficient image classification techniques.

关键词： Accuracy Image processing Transfer learning Refining Melanoma Medical services Convolutional neural networks

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A study of strategies to restrain the C&C activities of structured P2P botnets

A study of strategies to restrain the C&C activities of stru...

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international conference on Computer Sciences and Convergence Information Technology (ICCIT)

作者： Tianzuo Wang Bo Liu Huaimin Wang Hao Ren Xiaolong Ma School of Computer Science National Laboratory for Parallel and Distributed Processing National University of Defense and Technology Changsha China

Botnets are threatening the Internet heavily, and more and more botnets are utilizing the P2P technology to build their C&C (Command and Control) mechanisms. Some research have been made to compare the resilience of structured P2P botnets and unstructured ones, against elimination of nodes, but the problem that which eliminating strategy is the best is rarely studied. In this paper, we proposed a new metric called the half point, to measure the effectiveness of different strategies. We also selected seven different eliminating strategies and compared them. through extensive simulations, we find that RBC is the best eliminating strategy. Further analysis shows that for the strategy RBC, the average degree of nodes in the botnet have the most significant influence. the bigger the average degree is, the bigger the half point of RBC is, which implies that node eliminating may not be a reasonable choice for mitigating botnets with big average degree. Results of this paper can provide guidance for restraining structured P2P botnets.

关键词： C&C mechanism betweenness centrality coreness eliminating strategy half point restrain structured P2P botnets

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APR-16: the Physical Design of a Reconfigurable Array Processor Chip

APR-16: The Physical Design of a Reconfigurable Array Proces...

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international conference on Integrated Circuits and Microsystems (ICICM)

作者： Yangfan Xiao Rui Shan Zekun Ye Lin Jiang Wang Liao Baoxiang Zhang School of Electronic Engineering Xi’an University of Posts and Telecommunications Xi’an China School of Computer Science and Technology Xi’an University of science and technology Xi’an China Xi’an University of Posts and Telecommunications Xi’an China

ISBN: (纸本)9781665460583

In the physical chip design under the ultra-deep submicron (UDSM) process, interconnect delay, internal resistance drop (IR drop), and signal integrity (SI) has become the key factors affecting timing convergence and design cycle. this paper introduces a reconfigurable array processor architecture chip to solve the above problems. It discusses the requirements of the chip, the logic synthesis, and the physical design under the SMIC 55nm process in detail. First, four different timing optimization methods are employed to optimize the critical path that affects the timing, thus accelerating the execution time of the subsequent placement and routing. Secondly, the edge placement method based on data flow is adopted to reduce the interconnect length and delay of interconnection. Finally, the power network synthesis, placement, clock tree synthesis, and routing are completed. the results demonstrate that the working frequency can reach 320MHz. Meanwhile, the resource consumption is 80506 logic gates, and the chip area is 12mm 2 .

关键词： Windings Integrated circuit interconnections parallel processing Logic gates Routing Delays Logic arrays

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ComFaaS Distributed: Edge Computing with Function-as-a-Service in parallel Cloud Environments

ComFaaS Distributed: Edge Computing with Function-as-a-Servi...

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international conference on Information and Computer Technologies (ICICT)

作者： Jaden Jinu Lee Judah Nava Hanku Lee Computer Science and Information Systems Minnesota State University Moorhead Moorhead MN

ISBN: (数字)9798350385625

ISBN: (纸本)9798350385632

Function-as-a-Service (FaaS) has emerged as a revolutionary service platform, abstracting the complexities of hardware, operating systems, and web hosting services. this allows developers to focus solely on implementing their service applications, making FaaS an ideal platform for the scalable manipulation of large data sets. Traditionally deployed on the cloud, FaaS now faces a new frontier: the network edge. Leveraging the edge offers several potential benefits, including reduced latency and improved resource utilization, making it a promising approach for efficient FaaS deployment. As the daily volume and complexity of data we handle continues to grow, adopting a parallel computing paradigm has become increasingly important to ensure fast and efficient execution of computational tasks. Addressing this need, ComFaaS Distributed embarks on a comprehensive comparison of the capabilities of parallelized edge and cloud environments for FaaS deployment. Utilizing benchmark programs meticulously crafted to simulate event-triggered scenarios, ComFaaS Distributed aims to provide valuable insights into the performance and potential of FaaS at the edge, paving the way for a future where parallel computing empowers the efficient and scalable processing of ever-growing data volumes.

关键词： Cloud computing Computer architecture parallel processing Benchmark testing Computational efficiency Complexity theory Web sites

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MLIR-to-CGRA: A Versatile MLIR-Based Compiler Framework for CGRAs

MLIR-to-CGRA: A Versatile MLIR-Based Compiler Framework for ...

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international conference on Application Specific Systems (ASAP), architectures and Processors

作者： Tianyi Yu Omar Ragheb Stephen Wicklund Jason Anderson Dept. of Electrical and Computer Engineering University of Toronto Toronto Ontario Canada

ISBN: (数字)9798350349634

ISBN: (纸本)9798350349641

Coarse-grained reconfigurable architectures (CGRAs) are programmable hardware platforms with coarse-grained programmable logic blocks and word-wide configurable interconnect. In this paper, we describe a high-level compilation framework tailored for CGRAs. the input to the framework is a C-language program and description of the available CG RA architectural features. this work primarily focuses on automatically handling sequential rectangular loop access patterns. It achieves this by running automated design space exploration (DSE) written within the MLIR compiler representation [7] to leverage both spatial and temporal parallelism inherent in CG RAs. Furthermore, the compiler is engineered to be architecture-agnostic. It employs standard loop (and other) compiler optimization passes alongside CG RA-specific passes to generate a data flow graph (DFG) tailored for a CG RA implementation. In an experimental study, we optimize kernels to increase CG RA mappability and show the impact of automated DSE on the kernel performance. Moreover, the framework eases the task of compilation from software to RISC-V+CGRA hybrid systems.

关键词： Program processors Systems architecture parallel processing Software Space exploration Reconfigurable architectures Kernel

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Strengthening Healthcare Cybersecurity by Optimizing Adversarial Attack Defences in Deep Learning Models using GPU and parallel processing Technologies

Strengthening Healthcare Cybersecurity by Optimizing Adversa...

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international conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： Hridya Venugopal Mary Subaja Christo Department of Networking and Communications SRM Institute of Science and Technology Kattankulathur Campus Chengalpattu Tamilnadu India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

In healthcare, safeguarding patient data integrity is paramount, necessitating robust deep learning models. this research focuses on bolstering the cyber security defenses of these models, particularly against adversarial attacks, through the application of the Localized Adversarial Feature Attack (LAFEAT) technique. Leveraging Graphics processing Units (GPU) and the TensorFlow framework, the study explores algorithmic enhancements like the Fast Gradient Sign Method (FGSM) and Model-Agnostic Meta-Learning (MAML). these techniques perturb input data gradients or adapt model parameters, enhancing resilience against adversarial perturbations. Additionally, Particle Swarm Optimization (PSO), a metaheuristic optimization technique, is examined to fortify defense mechanisms further. parallel processing techniques, utilizing parallel GPU or distributed clusters, are implemented to expedite the optimization process, reducing computational burdens and enhancing scalability. Despite advancements, gaps remain in understanding how these models can be optimized for real-world healthcare applications, particularly in terms of balancing computational efficiency and robustness. the research demonstrates tangible benefits, with a significant 10% increase in success rates against adversarial attacks compared to baseline methods. Moreover, parallel processing implementation results in a 30% reduction in optimization time, improving the efficiency of cyber security defenses for deep learning models in healthcare. these numerical enhancements underscore the research’s value in fortifying healthcare systems against adversarial threats, ensuring the security and integrity of patient data while addressing existing gaps in the optimization of adversarial defenses in healthcare applications. the strengths of this research lie in its robust adversarial attack optimization techniques, integration of parallel processing for efficiency, and application to critical healthcare tasks. Comprehensive

关键词： Deep learning Adaptation models Computational modeling Graphics processing units Medical services parallel processing Data models

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Design of novel macro-cells for next generation ASIC cell library

Design of novel macro-cells for next generation ASIC cell li...

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IEEE international conference on Electronics, Circuits and Systems (ICECS)

作者： Kiseon Cho Minkyu Song Department of Semiconductor Science Dongguk University Seoul South Korea

ISBN: (纸本)0780365429

this paper describes a design methodology of novel macro-cells for next generation ASIC libraries that has a low-power consumption and high-speed operation. In order to satisfy the desired characteristics, novel architectures of adder, multiplier, and shifter are proposed. Further, automatic layout generation programs are proposed. they are designed on the basis of the standard-cell approach and they generate the layouts of the proposed macro-cells from 8-bit to 64-bit. the proposed macro-cells are designed with a novel compound logic that consists of both CMOS logic and pass-transistor logic. they are fabricated with 0.25 /spl mu/m 1-poly 5-metal CMOS process, and have desired experimental results.

关键词： Application specific integrated circuits Libraries CMOS logic circuits Logic design Automatic logic units Decoding Design methodology Electronic mail CMOS process Data processing

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GPU-Based acceleration of an automatic white matter segmentation algorithm using CUDA

GPU-Based acceleration of an automatic white matter segmenta...

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Annual international conference of the IEEE Engineering in Medicine and Biology Society

作者： Nicole Labra Miguel Figueroa Pamela Guevara Delphine Duclap Josselin Hoeunou Cyril Poupon Jean-Francois Mangin Dept. of Electrical Engineering Universidad de Concepcion I2BM Neurospin CEA Gif-sur-Yvette

ISBN: (纸本)9781457702150

this paper presents a parallel implementation of an algorithm for automatic segmentation of white matter fibers from tractography data. We execute the algorithm in parallel using a high-end video card with a Graphics processing Unit (GPU) as a computation accelerator, using the CUDA language. By exploiting the parallelism and the properties of the memory hierarchy available on the GPU, we obtain a speedup in execution time of 33.6 with respect to an optimized sequential version of the algorithm written in C, and of 240 with respect to the original Python/C++ implementation. the execution time is reduced from more than two hours to only 35 seconds for a subject dataset of 800,000 fibers, thus enabling applications that use interactive segmentation and visualization of small to medium-sized tractography datasets.

关键词： execution time White Matter Graphics processing Unit memory hierarchy segmentation Segmentation algorithms Speeding GRAPPER PICK UP Graphics Card AUTOMATIC parallel Lines COPPER ALLOY NO 240 Dataset Visualization

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