检索结果-内蒙古大学图书馆

Channel Gain Map Estimation for Wireless Networks Based on Scatterer Model

IEEE Transactions on Wireless Communications 2025年

作者： Sun, He Zhu, Lipeng Zhang, Rui National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore The Chinese University of Hong Kong School of Science and Engineering Shenzhen Research Institute of Big Data Guangdong Shenzhen518172 China

Channel gain map (CGM) contains crucial large-scale fading information regarding wireless channels at specific frequency bands in wireless networks. Traditional CGM construction methods require either detailed propagation environment information or numerous channel measurements, rendering them practically cumbersome to implement. To overcome such difficulties, we propose in this paper a novel scatterer-based CGM construction framework to characterize the large-scale channel fading in a spatial region by estimating the scatterer responses from a few channel gain measurements at designated locations in the region. In particular, the region is divided into equally-spaced grids so as to smooth out the small-scale fading by averaging the channel power gain within each grid. As the average channel power gain within each grid can be expressed as a function of large-scale multi-path channel parameters such as the scatterer response coefficients and path-loss coefficients, an iterative algorithm is proposed to estimate these parameters based on only a sufficient number of channel gain measurements taken at random locations around each scatterer. Specifically, the proposed algorithm decomposes the parameter estimation problem into a set of univariate or linear estimation subproblems, which can be efficiently solved by one-dimensional (1D) line search and least-squares methods. Based on the estimated channel parameters, the CGM over the whole region can be estimated by calculating the average channel power gain for each grid. Simulation results under both the two-dimensional (2D) multipath channel model and the practical three-dimensional (3D) ray-tracing channel model verify that the proposed scatterer-based channel gain characterization can accurately capture the large-scale channel gain spatial distribution within a region, and the proposed CGM estimation framework outperforms other channel-measurement-based benchmarks in terms of estimation accuracy, while requiring a sign

关键词： Least squares approximations

来源：评论

学校读者我要写书评

暂无评论

Evaluating the Performance to Detecting Topic Shift of Large Language Models: A Study 9

Evaluating the Performance to Detecting Topic Shift of Large...

引用

9th International Conference on Intelligent Computing and Signal processing, ICSP 2024

作者： Tian, Pingfang Liu, Deting Department of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Institute of Scientific and Technical Information of China The Key Laboratory of the Rich Media Knowledge Organisation and Service of Digital Publishing Content Beijing100038 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Wuhan430065 China

ISBN: (纸本)9798350376548

Topic shift detection aims to identify whether there is a change in the current topic of conversation or if a change is needed. The study found previous work did not evaluate the performance of large language models like ChatGPT on the task of topic shift. Therefore, this paper's main task and innovation lie in analyzing ChatGPT's performance on topic shift detection. To provide a more comprehensive evaluation, we conducted topic shift detection tasks on ChatGPT from three aspects: single utterances, adjacent utterances, and contextual levels. Additionally, to gauge the performance of large language models, we conducted experiments on multiple small-scale models and compared the results of the two models. Experimental results on the publicly available English TIAGE dataset showed that small-scale models exhibited lower recall in all three aspects, while ChatGPT performed better in the recall. This suggests that compared to small-scale models, large models are more capable of accurately detecting topic shifts. However, large models also exhibited lower precision, indicating that while ChatGPT can recognize content differences in utterances, its judgment on whether these different contents belong to the same topic is poor. © 2024 IEEE.

关键词： adjacent utterances level ChatGPT contextual level single utterances level topic shift detection

来源：评论

学校读者我要写书评

暂无评论

Advancement of Artificial Intelligent and Its Impact on Medicinal Treatment and Pharmaceutical Industries 9

Advancement of Artificial Intelligent and Its Impact on Medi...

引用

9th International Conference on science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Jenifer, A. Ahmed, Syed Imran Sangeetha, G. Chakkaravarthy, A. Prabhu Kumar, Ashok Bakhare, Ruhi Rmk Engineerinh College Department of Electrical And Electronics Engineering Tamil Nadu Kavaraipettai601206 India Mj College Department of Electronics And Communication Engineering Telangana Hyderabad500053 India R.M.K College of Engineering And Technology Department of Artificial Intelligence And Data Science Tamil Nadu Thiruvallur India Srm Institute of Science And Technology Department of Networking And Communications Tamil Nadu Kattankulathur603203 India Banasthali Vidyapith Department of Computer Science Rajasthan 304022 India Dr. Ambedkar Institute of Management Studies And Research Department of Cse Deekshbhoomi Maharashtra 440010 India

ISBN: (纸本)9798350365092

In an unanticipatedly short period, a patient may seek advice from a computer prior to seeing a doctor, thus establishing the' standard' medical procedure of the future. Thanks to developments in artificial intelligence (AI), the days of misdiagnosing illnesses and treating their symptoms instead of their underlying causes may soon be over. It's possible that something like this will occur soon. To accommodate a complete 3D representation of an organ, imagine how much space would need to be cleared from your laptop or how many years' worth of blood pressure records would need to be eliminated. The image would require both of these things to be made possible. More uses of artificial intelligence and high performance data-driven medicine are made possible by the growing body of data generated in clinics and preserved in electronic medical records as a result of routine testing and medical imaging. These applications have led to the development of methods used by researchers and medical practitioners to address clinical concerns throughout time, and this trend is anticipated to continue. © 2024 IEEE.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

As an AI Language Model, "Yes I Would Recommend Calling the Police": Norm Inconsistency in LLM Decision-Making 24

As an AI Language Model, "Yes I Would Recommend Calling the ...

引用

Proceedings of the 2024 AAAI/ACM Conference on AI, Ethics, and Society

作者： Shomik Jain D. Calacci Ashia Wilson Institute for Data Systems and Society Massachusetts Institute of Technology College of Information Sciences and Technology Penn State University Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology

We investigate the phenomenon of norm inconsistency: where LLMs apply different norms in similar situations. Specifically, we focus on the high-risk application of deciding whether to call the police in Amazon Ring home surveillance videos. We evaluate the decisions of three state-of-the-art LLMs - GPT-4, Gemini 1.0, and Claude 3 Sonnet - in relation to the activities portrayed in the videos, the subjects' skin-tone and gender, and the characteristics of the neighborhoods where the videos were recorded. Our analysis reveals significant norm inconsistencies: (1) a discordance between the recommendation to call the police and the actual presence of criminal activity, and (2) biases influenced by the racial demographics of the neighborhoods. These results highlight the arbitrariness of model decisions in the surveillance context and the limitations of current bias detection and mitigation strategies in normative decision-making.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Novel Architecture for Efficient Mobile Communication based on Scattered and Diverse Combination using Prioritize and Postoperative Soft Modulation 7

A Novel Architecture for Efficient Mobile Communication base...

引用

7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Sumithra, J. Mercy Theresa, M. Geetha Priya, S. Jackson, Beulah Samuthira Pandi, V. Balamurugan, A. R. M. D Engineering College Department of Electronics and Communication Engineering Tamil Nadu India SRM Institute of Science and Technology Department of Data Science and Business Systems Tamil Nadu India R. M. D Engineering College Department of Computer Science and Engineering Tamil Nadu India Vel Tech Rangarajam Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu India SRM Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu India Chennai Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu India

ISBN: (纸本)9798350397253

The proposed work suggests a novel approach for the cooperation of geographically scattered individuals and the blending of different points of view. This work ensures that the center on heterogeneous networks in which nodes support both long-range low-rate Radio Frequency (RF) interfaces (like cellular) and short-range high-rate RF interfaces (such as IEEE802.11) that communicate over urban Rayleigh fading channels. These interfaces are used to connect the devices. The interfaces are what are used to link the various gadgets. This research work proposes and evaluates a wide variety of hierarchically distributed cooperation strategies that can function despite resource restrictions such as limited short-range RF bandwidth. These strategies are contained within the confines of this paradigm, which serves as the framework for proposed work. Post Soft-Demodulation Combining, often referred to as PSDC, and Priority Maximum Ratio Combining are the two approaches that come highly recommended by our team (PMRC). This work provides evidence that using the offered methods increases throughput, reliability, and signal-to-noise ratio. Moreover, this study found that PMRC and PSDC have the ability to improve throughput performance by more than an order of magnitude across a wide range of communication circumstances. © 2023 IEEE.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Deep Attention Driven Reinforcement Learning (DAD-RL) for Autonomous Decision-Making in Dynamic Environment

arXiv

引用

arXiv 2024年

作者： Chowdhury, Jayabrata Shivaraman, Venkataramanan Dangi, Sumit Sundaram, Suresh Sujit, P.B. Robert Bosch Centre for Cyber-Physical Systems Indian Institute of Science Bangalore India The Department of Aerospace Engineering Indian Institute of Science Bangalore India The Department of Data Science & Engineering and Electrical Engineering & Computer Science Indian Institute of Science Education and Research Bhopal India

Autonomous Vehicle (AV) decision-making in urban environments is inherently challenging due to the dynamic interactions with surrounding vehicles. For safe planning, AV/ego must understand the weightage of various spatiotemporal interactions in a scene. Contemporary works use colossal transformer architectures to encode interactions mainly for trajectory prediction, resulting in increased computational complexity. To address this issue without compromising spatiotemporal understanding and performance, we propose the simple Deep Attention Driven Reinforcement Learning (DAD-RL) framework, which dynamically assigns and incorporates the significance of surrounding vehicles into the ego’s RL-driven decision-making process. We introduce an AV-centric spatiotemporal attention encoding (STAE) mechanism for learning the dynamic interactions with different surrounding vehicles. To understand map and route context, we employ a context encoder to extract features from context maps. The spatiotemporal representations combined with contextual encoding provide a comprehensive state representation. The resulting model is trained using the Soft-Actor Critic (SAC) algorithm. We evaluate the proposed framework on the SMARTS urban benchmarking scenarios without traffic signals to demonstrate that DAD-RL outperforms recent state-of-the-art methods. Furthermore, an ablation study underscores the importance of the context-encoder and spatio-temporal attention encoder in achieving superior performance. © 2024, CC BY-SA.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Dimensionality and dynamics for next-generation artificial neural networks

引用

Patterns 2025年

作者： Wang, Ge Fan, Feng-Lei Department of Biomedical Engineering Department of Electrical Computer and Systems Engineering Department of Computer Science Center for Computational Innovations Biomedical Imaging Center Center for Biotechnology and Interdisciplinary Studies Rensselaer Polytechnic Institute TroyNY United States Department of Data Science City University of Hong Kong Kowloon Hong Kong

The recent awarding of the Nobel Prize in Physics to Geoffrey E. Hinton and John J. Hopfield highlights their profound impact on artificial neural networks. In this perspective, we explore how their foundational insights can drive the advancement of next-generation artificial intelligence (AI) models. We propose expanding beyond conventional architectures by introducing dimensionality through intra-layer links and dynamics via feedback loops. Network height and additional dimensions, alongside traditional width and depth, enhance learning capabilities, while entangled loops across scales induce emergent behaviors akin to phase transitions in physics. We discuss how these principles extend beyond transformers, fostering a new paradigm of intelligence inspired by physics-driven models and biological cognition mechanisms. © 2025 The Author(s)

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Development and Characterization of Zinc Dry Electrodes for Wearable Electrophysiology 46

Development and Characterization of Zinc Dry Electrodes for ...

引用

46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Rizq, Cassia D'Amico, Alessandro Truel, Aidan Faybishenko, Joelle Lee, Min Suk Kim, Jeong-Hoon Cauwenberghs, Gert De Sa, Virginia R. University of California San Diego Department of Bioengineering La Jolla United States University of California San Diego Department of Cognitive Science La Jolla United States University of California San Diego Halicioǧlu Data Science Institute La Jolla United States University of California San Diego Department of Electrical and Computer Engineering La Jolla United States

ISBN: (纸本)9798350371499

Zinc dry electrodes were fabricated and investigated for wearable electrophysiology recording. Results from electrochemical impedance spectroscopy and electromyography functionality testing show that zinc electrodes are suitable for use in electrophysiology. Two electrode configurations were tested: a standard disc and a custom tripolar concentric ring configuration. However, no functional benefit was observed with the tripolar concentric ring electrodes as compared to the disc electrodes. © 2024 IEEE.

关键词： Electromyography

来源：评论

学校读者我要写书评

暂无评论

Multimodal Imaging Feature Extraction with Reference Canonical Correlation Analysis Underlying Intelligence

Multimodal Imaging Feature Extraction with Reference Canonic...

引用

International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Ram Sapkota Bishal Thapaliya Pranav Suresh Bhaskar Ray Vince D. Calhoun Jingyu Liu Translational Research in Neuroimaging and Data Science (TReNDS) Department of Computer Science Georgia State University Atlanta USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta USA

With neuroimaging data scientists have gained substantial information of the neuronal underpinning of intelligence. Yet how to integrate multimodal neuronal features effectively in relation to intelligence remains elusive. In this paper, we have developed a reference Canonical Correlation Analysis (RCCA) model that extracts latent, correlated multimodal features while enhancing correlation to a reference of interest. We applied RCCA to gray matter and white matter images from 7874 participants, and compared the derived features with those from Principle Components Analysis (PCA) and sparse CCA (SCCA), in terms of association with intelligence and prediction effectiveness using LASSO regression models. Eight RCCA features explained 10%, 16% and 17% variance of fluid intelligence, crystallized intelligence, and total composite score, respectively, which are similar to the percentage of variance explained by over 100 principle components. SCCA features presented the least variance of intelligence. Our results indicate RCCA model can successfully extract features of interest. The top brain regions that contribute to intelligence include the frontal regions and cingulate gyrus.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Contract-Inspired Contest Theory for Controllable Image Generation in Mobile Edge Metaverse

引用

IEEE Transactions on Mobile Computing 2025年

作者： Liu, Guangyuan Du, Hongyang Wang, Jiacheng Niyato, Dusit Kim, Dong In Nanyang Technological University College of Computing and Data Science Energy Research Institute @ NTU Interdisciplinary Graduate Program Singapore University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Hong Kong Nanyang Technological University College of Computing and Data Science Singapore Sungkyunkwan University Department of Electrical and Computer Engineering 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. © 2002-2012 IEEE.

关键词： Resource allocation

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：