检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Liu, Guangyuan Du, Hongyang Wang, Jiacheng Niyato, Dusit Kim, Dong In College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

The rapid advancement of immersive technologies has propelled the development of the Metaverse, where the convergence of virtual and physical realities necessitates the generation of high-quality, photorealistic images to enhance user experience. However, generating these images, especially through Generative Diffusion Models (GDMs), in mobile edge computing environments presents significant challenges due to the limited computing resources of edge devices and the dynamic nature of wireless networks. This paper proposes a novel framework that integrates contract-inspired contest theory, Deep Reinforcement Learning (DRL), and GDMs to optimize image generation in these resource-constrained environments. The framework addresses the critical challenges of resource allocation and semantic data transmission quality by incentivizing edge devices to efficiently transmit high-quality semantic data, which is essential for creating realistic and immersive images. The use of contest and contract theory ensures that edge devices are motivated to allocate resources effectively, while DRL dynamically adjusts to network conditions, optimizing the overall image generation process. Experimental results demonstrate that the proposed approach not only improves the quality of generated images but also achieves superior convergence speed and stability compared to traditional methods. This makes the framework particularly effective for optimizing complex resource allocation tasks in mobile edge Metaverse applications, offering enhanced performance and efficiency in creating immersive virtual environments. © 2025, CC BY.

关键词： Mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Haar Transform Architectures Using Efficient Addition Schemes 11

Energy-Efficient Haar Transform Architectures Using Efficien...

引用

11th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2020

作者： Seidel, Henrique Rosa, Morgana Da Paim, Guilherme Costa, Eduardo Da Almeida, Sergio Bampi, Sergio Graduate Program on Electronic Engineering and Computing Pelotas Brazil Porto Alegre Brazil

ISBN: (纸本)9781728134277

This paper proposes an energy-efficient Haar transform architecture using efficient adders circuits. Nine levels of decomposition in a fixed-point format are used in the architectures. The Processing Module (PM) of Haar explores efficient Parallel Prefix Adders (PPA) and adder compressors. Since power-of-two operations approximate one of the inputs of the PM module, efficient adder compressors implement them. It allowed a very high precision adjustment of the transform coefficient. The architectures were described in VHDL and synthesized using the ST 65nm CMOS cell library. The results show that the Haar architecture with 4-2 and 5-2 compressors in the PM module, both with the recombination line with a Sklansky (SK) adder, is more efficient. It has a reduction of 33.6% in the cell area, with a 35.7% reduction in total power in comparison with the literature. Moreover, the Haar architecture with 4-2 and 5-2 adder compressors is more efficient than the one using the tool-selected implementation of the behavioral "+" (sum) in VHDL, with 23% of power reduction. © 2020 IEEE.

关键词： Adders

来源：评论

学校读者我要写书评

暂无评论

A Multiplier-Less Level-3 Haar Wavelet Transform Approximation Requiring Five Additions Only

A Multiplier-Less Level-3 Haar Wavelet Transform Approximati...

引用

Proceedings of the IEEE Dallas Circuits and Systems Workshop (DCAS)

作者： Morgana M. A. Da Rosa Guilherme Paim Henrique B. Seidel Sé rgio Almeida Eduardo A. C. Da Costa Sergio Bampi Graduate Program on Electronic Engineering and Computing Universidade Cat&#x00F3 lica de Pelotas (UCPel) Brazil Graduate Program in Microelectronics (PGMICRO) Federal University of Rio Grande do Sul (UFRGS) Brazil

ISBN: (数字)9781665498852

ISBN: (纸本)9781665498869

Approximate transform kernels have emerged as an alternative design to reduce the hardware complexity of digital signal processors by exploiting the intrinsic error resilience of many embedded consumer electronics applications such as signal, image and video processing, and computer vision. The approximate level-4 Haar wavelet transform (AxHWT-4) is the state-of-the-art approximate transform for ECG (electrocardiogram) signal processing and reduces more than nine times the energy consumption compared to the exact transform. In this work, we propose an approximate level-3 Haar wavelet transform (AxHWT-3) for increasing the hardware design efficiency with related to the AxHWT-4 while obtaining higher R-peak detection accuracy in the electrocardiogram signal. Our AxHWT-3 approximation is performed in the Haar matrix kernel to eliminate its multiplications which in the hardware design results in savings of energy consumption and VLSI hardware area. Our AxHWT3 proposal achieves an R-peak detection accuracy of more than 99% and reduces the energy consumption by 15.98 times and the VLSI area by 12.64 times compared to the exact solution (i.e., the original level-3 Haar). In addition, the proposed AxHWT3 outperforms the state-of-the-art AxHWT-4 with a savings of about 32% in power dissipation and 19.5% in VLSI area.

关键词： Wavelet transforms Energy consumption Computer architecture Very large scale integration Electrocardiography Signal processing Hardware

来源：评论

学校读者我要写书评

暂无评论

Assistive technology with device for self-inflating bag in neonatology

引用

Research on Biomedical engineering 2025年第2期41卷

作者： Marcelino, Ana Carolina Rodovanski, Giovana Pascoali Bonetti, Karoline Panes, Caio Rabinovich de Almeida Martins, Fernando Moran, Cristiane Aparecida Araranguá Brazil Graduate Program in Neurosciences and Behavior Department of Experimental Psychology of the Institute of Psychology-University of São Paulo Sao Paulo Brazil Araranguá Brazil Computer Engineering Instituto Mauá de Tecnologia São Caetano do Sul Brazil Electronic Engineering and Computing with Emphasis on Electronic Devices and Systems at Instituto Tecnológico de Aeronáutica–ITA São Caetano do Sul Brazil Department of Physiotheraphy and at the Postgraduate Program in Rehabilitation Science of the Federal University of Santa Catarina-UFCS Ararangua Brazil

Purpose: The objectives of this study were to create a device with technological development of the self-inflating bag (SIB) equipment to measure the variables tidal volume, peak inspiratory pressure, and inspiratory flow and to evaluate the knowledge of undergraduate students in handling the SIB. To reduce the risks of mortality, length of hospital stay, and infections, SIB is a resource used to ventilate the patient through the inflation of the device, but it is not capable of measuring the ventilatory parameters. Excess ventilation and incorrect handling of the bag can cause lung injury in newborns. Therefore, measuring these parameters can prevent lung injury resulting from inadequate ventilation. Method: This is a cross-sectional and experimental study, with the development of a device SIB that allows the evaluation of variables of neonatal respiratory mechanics that were tested with an artificial lung. It was approved by the Research Ethics Committee and the research was developed in three stages: the first represents the search for scientific articles for the consensus of neonatal ventilatory variables for the construction of the SIB parameters;the second stage depicts the technological development of a device capable of monitoring such variables through the SIB. In the third stage, the content validation of the device with the handling of the SIB was carried out by students of medicine and physiotherapy courses of Brazil. Results: In this work, a device that analyzes the values of the main ventilatory parameters in neonatology was developed and to generate a safety range for the use of the device, curves with a tolerance of 10% up and down were created. All electronic components were coupled to the equipment, with a display that transmits the parameter values. The web page can be used on a cell phone, tablet, computer, or SmartTv, as long as it is connected to the "RespiratorIoT_AP" network. Among the 29 participants in the study, 8 said they were familiar w

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Supervised Score-Based Modeling by Gradient Boosting

arXiv

引用

arXiv 2024年

作者： Zhao, Changyuan Du, Hongyang Liu, Guangyuan Niyato, Dusit College of Computing and Data Science Nanyang Technological University Singapore CNRS@CREATE 1 Create Way # 08-01 Create Tower 138602 Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong The Energy Research Institute @ NTU Interdisciplinary Graduate Program Singapore

Score-based generative models can effectively learn the distribution of data by estimating the gradient of the distribution. Due to the multi-step denoising characteristic, researchers have recently considered combining score-based generative models with the gradient boosting algorithm, a multi-step supervised learning algorithm, to solve supervised learning tasks. However, existing generative model algorithms are often limited by the stochastic nature of the models and the long inference time, impacting prediction performances. Therefore, we propose a Supervised Score-based Model (SSM), which can be viewed as a gradient boosting algorithm combining score matching. We provide a theoretical analysis of learning and sampling for SSM to balance inference time and prediction accuracy. Via the ablation experiment in selected examples, we demonstrate the outstanding performances of the proposed techniques. Additionally, we compare our model with other probabilistic models, including Natural Gradient Boosting (NGboost), Classification and Regression Diffusion Models (CARD), Diffusion Boosted Trees (DBT), and non-probabilistic GBM models. The experimental results show that our model outperforms existing models in both accuracy and inference time. © 2024, CC BY.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Adaptive Contextual Caching for Mobile Edge Large Language Model Service

arXiv

引用

arXiv 2025年

作者： Liu, Guangyuan Liu, Yinqiu Wang, Jiacheng Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore

Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation (RAG) mitigates some challenges by integrating external knowledge bases, inefficient cache management can still result in high retrieval latency and frequent cache updates. To address these issues, we propose an Adaptive Contextual Caching (ACC) framework that anticipates user needs by proactively caching semantically relevant data for mobile-edge LLMs. ACC utilizes a deep reinforcement learning (DRL) module to refine cache replacement policies, balancing user context, document similarity, and the overhead associated with cache misses. Experimental results demonstrate that ACC increases cache hit rates to over 80% after only 11 training episodes, outperforming FIFO, LRU, and semantic-only caching while reducing retrieval latency by up to 40%. In particular, ACC also reduces local caching overhead (i.e., the cost of updating the cache when a miss occurs) by as much as 55%, enabling scalable, low-latency LLM services in resource-constrained edge environments. © 2025, CC BY.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

GraCo: Granularity-Controllable Interactive Segmentation

arXiv

引用

arXiv 2024年

作者： Zhao, Yian Li, Kehan Cheng, Zesen Qiao, Pengchong Zheng, Xiawu Ji, Rongrong Liu, Chang Yuan, Li Chen, Jie School of Electronic and Computer Engineering Peking University Shenzhen China Peng Cheng Laboratory Shenzhen China -Preferred Program Peking University Shenzhen Graduate School China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China Department of Automation and BNRist Tsinghua University Beijing China

Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity output and multi-granularity output. The latter aims to alleviate the spatial ambiguity present in the former. However, the multi-granularity output pipeline suffers from limited interaction flexibility and produces redundant results. In this work, we introduce Granularity-Controllable Interactive Segmentation (GraCo), a novel approach that allows precise control of prediction granularity by introducing additional parameters to input. This enhances the customization of the interactive system and eliminates redundancy while resolving ambiguity. Nevertheless, the exorbitant cost of annotating multi-granularity masks and the lack of available datasets with granularity annotations make it difficult for models to acquire the necessary guidance to control output granularity. To address this problem, we design an any-granularity mask generator that exploits the semantic property of the pre-trained IS model to automatically generate abundant mask-granularity pairs without requiring additional manual annotation. Based on these pairs, we propose a granularity-controllable learning strategy that efficiently imparts the granularity controllability to the IS model. Extensive experiments on intricate scenarios at object and part levels demonstrate that our GraCo has significant advantages over previous methods. This highlights the potential of GraCo to be a flexible annotation tool, capable of adapting to diverse segmentation scenarios. The project page: https://***/GraCo. Copyright © 2024, The Authors. All rights reserved.

关键词： Pipelines

来源：评论

学校读者我要写书评

暂无评论

A Power-Efficient FFT Hardware Architecture Exploiting Approximate Adders

A Power-Efficient FFT Hardware Architecture Exploiting Appro...

引用

IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Guilherme Ferreira Pedro T. L. Pereira Guilherme Paim Eduardo Costa Sergio Bampi Graduate Program in Microelectronics (PGMICRO) Federal University of Rio Grande do Sul (UFRGS) Brazil Graduate Program in Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Brazil

ISBN: (数字)9781728176703

ISBN: (纸本)9781728176710

This work presents an energy-efficient Fast Fourier Transform (FFT) hardware architecture exploiting approximate adder circuits. The FFT hardware architecture consists of a fixed-point fully sequential architecture with a radix-2 butterfly with decimation in time (DIT). In this paper, we explore a set of approximate adders (LOA, ETA-I, Copy-A, Copy-B, Trunc0, Trunc1) in the butterfly by varying the approximation level (K term). The Root-Mean-Square Error (RMSE) metric shows which approximate level term allows the FFT processing without widely signal losses. The results show that our best-proposed FFT employing Trunc0 approximate adder with K =10 saves up to 35% of power dissipation compared to the FFT with the original radix-2 butterfly using the synthesis tool operators.

关键词： Measurement Fast Fourier transforms Circuits and systems Hardware Energy efficiency Topology Power dissipation

来源：评论

学校读者我要写书评

暂无评论

Boosting the Efficiency of the Harmonics Elimination VLSI Architecture by Arithmetic Approximations

Boosting the Efficiency of the Harmonics Elimination VLSI Ar...

引用

IEEE International Conference on electronics, Circuits and Systems (ICECS)

作者： Patricia da Costa Pedro T. L. Pereira Guilherme Paim Eduardo da Costa Sergio Bampi Graduate Program in Microelectronics (PGMICRO) - Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Graduate Program in Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

Approximate computing emerged as a key alternative for trading off accuracy against energy efficiency and area reduction. Error-tolerant applications, such as multimedia processing, machine learning, and signal processing, can process the information with lower-than-standard accuracy at the circuit level while still fulfilling a good and acceptable service quality at the application level. Adaptive filtering-based systems have been demonstrating high resiliency against hardware errors due to their intrinsic self-healing characteristic. This paper investigates the design space exploration of arithmetic approximations in a Very Large-Scale Integration (VLSI) harmonic elimination (HE) hardware architecture based on Least Mean Square (LMS) adaptive filters. We evaluate the Pareto front of the area- and power versus quality curves by relaxing the arithmetic precision and by adopting both approximate multipliers (AxMs) in combination with approximate adders (AxAs). This paper explores the benefits and impacts of the Dynamic Range Unbiased (DRUM), Rounding-based Approximate (RoBA), and Leading one Bit-based Approximate (LoBA) multipliers in the power dissipation, circuit area, and quality of the VLSI HE architectures. Our results highlight the LoBA 0 as the most efficient AxM applied in the HE architecture. We combine the LoBA 0 with Copy and LOA AxAs with variations in the approximation level (L). Notably, LoBA 0 and LOA with $L=6$ resulted in savings of 43.7% in circuit area and 45.2% in power dissipation, compared to the exact HE, which uses multiplier and adder automatically selected by the logic synthesis tool. Finally, we demonstrate that the best hardware architecture found in our investigation successfully eliminates the contaminating spurious noise (i.e., 60 Hz and its harmonics) from the signal.

关键词： Power quality Computer architecture Very large scale integration Harmonic analysis Boosting Hardware Power dissipation

来源：评论

学校读者我要写书评

暂无评论

GraCo: Granularity-Controllable Interactive Segmentation

GraCo: Granularity-Controllable Interactive Segmentation

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yian Zhao Kehan Li Zesen Cheng Pengchong Qiao Xiawu Zheng Rongrong Ji Chang Liu Li Yuan Jie Chen School of Electronic and Computer Engineering Peking University Shenzhen China AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School China Peng Cheng Laboratory Shenzhen China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China Department of Automation and BNRist Tsinghua University Beijing China

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity out-put and multi-granularity output. The latter aims to allevi-ate the spatial ambiguity present in the former. However, the multi-granularity output pipeline suffers from limited interaction flexibility and produces redundant results. In this work, we introduce Granularity-Controllable Interactive Segmentation (GraCo), a novel approach that allows precise control of prediction granularity by introducing ad-ditional parameters to input. This enhances the customization of the interactive system and eliminates redundancy while resolving ambiguity. Nevertheless, the exorbitant cost of annotating multi-granularity masks and the lack of avail-able datasets with granularity annotations make it difficult for models to acquire the necessary guidance to control out-put granularity. To address this problem, we design an any-granularity mask generator that exploits the semantic property of the pre-trained IS model to automatically gen-erate abundant mask-granularity pairs without requiring additional manual annotation. Based on these pairs, we propose a granularity-controllable learning strategy that efficiently imparts the granularity controllability to the IS model. Extensive experiments on intricate scenarios at ob-ject and part levels demonstrate that our GraCo has signifi-cant advantages over previous methods. This highlights the potential of GraCo to be a flexible annotation tool, capable of adapting to diverse segmentation scenarios. The project page: https://***/GraCo.

关键词： Image segmentation Adaptation models Annotations Interactive systems Pipelines Semantics Redundancy

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：