检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Garrabe, Emiland Jesawada, Hozefa Del Vecchio, Carmen Russo, Giovanni Department of Information and Electrical Engineering and Applied Mathematics University of Salerno Italy Department of Engineering University of Sannio Benevento Italy

This paper is concerned with a finite-horizon inverse control problem, which has the goal of reconstructing, from observations, the possibly non-convex and non-stationary cost driving the actions of an agent. In this context, we present a result enabling cost reconstruction by solving an optimization problem that is convex even when the agent cost is not and when the underlying dynamics is nonlinear, non-stationary and stochastic. To obtain this result, we also study a finite-horizon forward control problem that has randomized policies as decision variables. We turn our findings into algorithmic procedures and show the effectiveness of our approach via in-silico and hardware validations. All experiments confirm the effectiveness of our approach. © 2023, CC BY-NC-SA.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Discovering High Utility Episodes in Sequences

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2023年第3期4卷 473-486页

作者： Gan, Wensheng Lin, Jerry Chun-Wei Chao, Han-Chieh Yu, Philip S. Jinan University College of Cyber Security Guangzhou510632 China Pazhou Lab Guangzhou510330 China Western Norway University of Applied Sciences Department of Computing Mathematics and Physics Bergen5063 Norway National Dong Hwa University Department of Electrical Engineering Hualien974 Taiwan University of Illinois at Chicago Department of Computer Science ChicagoIL60607 United States

Sequence data are more commonly seen than other types of data (e.g., transaction data) in real-world applications. For the mining task from sequence data, several problems have been formulated, such as sequential pattern mining, episode mining, and sequential rule mining. As one of the fundamental problems, episode mining has often been studied. The common wisdom is that discovering frequent episodes is not useful enough. In this article, we propose an efficient utility mining approach, namely, UMEpi: utility mining of high-utility episodes from complex event sequences. We propose the concept of remaining utility of episodes and achieve a tighter upper bound, namely, episode-weighted utilization (EWU), which will provide better pruning. Thus, the optimized EWU-based pruning strategies can achieve better improvements in mining efficiency. The search space of UMEpi w.r.t. a prefix-based lexicographic sequence tree is spanned and determined recursively for mining high-utility episodes, by prefix-spanning in a depth-first way. Finally, extensive experiments on four real-life datasets demonstrate that UMEpi can discover the complete high-utility episodes from complex event sequences. Furthermore, the improved variants of UMEpi significantly outperform the baseline in terms of execution time, memory consumption, and scalability. © 2020 IEEE.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

End-to-End Learning of Transmitter and Receiver Filters in Bandwidth Limited Fiber Optic Communication Systems

arXiv

引用

arXiv 2024年

作者： Nielsen, Søren Føns Da Ros, Francesco Schmidt, Mikkel N. Zibar, Darko Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Department of Electrical and Photonics Engineering Technical University of Denmark Denmark

This paper investigates the application of end-to-end (E2E) learning for joint optimization of pulse-shaper and receiver filter to reduce intersymbol interference (ISI) in bandwidth-limited communication systems. We investigate this in two numerical simulation models: 1) an additive white Gaussian noise (AWGN) channel with bandwidth limitation and 2) an intensity modulated direct detection (IM/DD) link employing an electro-absorption modulator. For both simulation models, we implement a wavelength division multiplexing (WDM) scheme to ensure that the learned filters adhere to the bandwidth constraints of the WDM channels. Our findings reveal that E2E learning greatly surpasses traditional single-sided transmitter pulse-shaper or receiver filter optimization methods, achieving significant performance gains in terms of symbol error rate with shorter filter lengths. These results suggest that E2E learning can decrease the complexity and enhance the performance of future high-speed optical communication systems. © 2024, CC BY.

关键词： Bandwidth

来源：评论

学校读者我要写书评

暂无评论

Experimental Investigation of the Performance of a Thermoelectric Generator 20

Experimental Investigation of the Performance of a Thermoele...

引用

20th IEEE Jubilee World Symposium on applied Machine Intelligence and Informatics, SAMI 2022

作者： Varga, Zoltan Racz, Ervin Doctoral School of Applied Informatics and Applied Mathematics Óbuda University Budapest Hungary Kandó Kálmán Faculty of Electrical Engineering Óbuda University Power System Department Budapest Hungary

ISBN: (纸本)9781665497046

Thermoelectric generators (TEG) are used in many applications such as in computers, automobiles to generate electricity from the exhausted thermal gases. The waste heat recovery from the system can be used to generate electric current increasing the efficiency of the system. One of the methods to generate electric current from waste heat recovery is Seebeck-effect. In this paper, an experimental investigation is carried out in order to analyse the performance of a thermoelectric generator. To run experiment, a target system was built and a Peltier-cell was used as a thermoelectric generator. After measuring the electric currents and the temperature differences, heat and Seebeck-coefficient were calculated. The results show that a thermoelectric module is a promising and further looking device for waste heat recovery. Moreover, results show that 35 mA electric current can be generated with 15 °C of temperature difference. On the other hand, Seebeck coefficient was determined from the measured electrical voltage values. This experimental work gives useful information about the performance of the thermoelectric generator. The research was supported by the Ministry for Innovation and Technology: National Research, Development and Innovation Office. © 2022 IEEE.

关键词： Temperature measurement Performance evaluation Technological innovation Voltage measurement Current measurement Generators Waste heat

来源：评论

学校读者我要写书评

暂无评论

Sensing beyond the exceptional point for high detectivity

Sensing beyond the exceptional point for high detectivity

引用

2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Li, Zhichao Prasad, Ciril S. Wang, Xielin Zhang, Ding Naik, Gururaj V. Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States

ISBN: (纸本)9781957171395

Exceptional point (EP)-based optical sensors exhibit exceptional sensitivity but poor detectivity. Slightly off EP operation boosts detectivity without much loss in sensitivity. We experimentally demonstrate a high-detectivity-off-EP plasmonic-photonic hybrid sensor for anti-mouse IgG protein. CLEO 2024 © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Laser beams

来源：评论

学校读者我要写书评

暂无评论

On a Probabilistic Approach for Inverse Data-Driven Optimal Control

On a Probabilistic Approach for Inverse Data-Driven Optimal ...

引用

IEEE Conference on Decision and Control

作者： Émiland Garrabé Hozefa Jesawada Carmen Del Vecchio Giovanni Russo Department of Information and Electrical Engineering & Applied Mathematics University of Salerno Italy Department of Engineering University of Sannio Benevento Italy

We consider the problem of estimating the possibly non-convex cost of an agent by observing its interactions with a nonlinear, non-stationary and stochastic environment. For this inverse problem, we give a result that allows to estimate the cost by solving a convex optimization problem. To obtain this result we also tackle a forward problem. This leads to the formulation of a finite-horizon optimal control problem for which we show convexity and find the optimal solution. Our approach leverages certain probabilistic descriptions that can be obtained both from data and/or from first-principles. The effectiveness of our results, which are turned in an algorithm, is illustrated via simulations on the problem of estimating the cost of an agent that is stabilizing the unstable equilibrium of a pendulum.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Sensing beyond the exceptional point for high detectivity

Sensing beyond the exceptional point for high detectivity

引用

CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Hybrid sensors

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Neurological Diagnostics: Integrating 6G Technology with Deep Learning for Enhanced Detection of Multiple Sclerosis and Myelitis

Revolutionizing Neurological Diagnostics: Integrating 6G Tec...

引用

2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Noureldeen, Rana M. Elshshtawy, Rahma A. Elgohary, Omnia A. Wahba, Fatma Alzahraa A. Attia, Marco K. Abo Elazm, Zeinab B. Khattap, Mohamed G. Galal Eldeen Mohamed Ali Hassan, Hend Mostafa, Mariam Ibrahim, Nayra Ramadan, Reem Refaat, Yomna Khaled, Mennatallah Maher, Ali Abd Elaziz, Mohamed Gamal Abdellatif Ibrahim, Ahmed Faculty of Applied Health Sciences Galala University Suez435611 Egypt Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Air Defense College Department of Electronics and Electrical Communications Engineering Alexandria Egypt

ISBN: (纸本)9798350351408

This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Tell What You Hear From What You See - Video to Audio Generation Through Text

arXiv

引用

arXiv 2024年

作者： Liu, Xiulong Su, Kun Shlizerman, Eli Department of Electrical & Computer Engineering University of Washington Seattle United States Department of Applied Mathematics University of Washington Seattle United States

The content of visual and audio scenes is multi-faceted such that a video stream can be paired with various audio streams and vice-versa. Thereby, in video-to-audio generation task, it is imperative to introduce steering approaches for controlling the generated audio. While Video-to-Audio generation is a well-established generative task, existing methods lack such controllability. In this work, we propose VATT, a multi-modal generative framework that takes a video and an optional text prompt as input, and generates audio and optional textual description (caption) of the audio. Such a framework has two unique advantages: i) Video-to-Audio generation process can be refined and controlled via text which complements the context of the visual information, and ii) The model can suggest what audio to generate for the video by generating audio captions. VATT consists of two key modules: VATT Converter, which is an LLM that has been fine-tuned for instructions and includes a projection layer that maps video features to the LLM vector space, and VATT Audio, a bi-directional transformer that generates audio tokens from visual frames and from optional text prompt using iterative parallel decoding. The audio tokens and the text prompt are used by a pretrained neural codec to convert them into a waveform. Our experiments show that when VATT is compared to existing video-to-audio generation methods in objective metrics, such as VGGSound audiovisual dataset, it achieves competitive performance when the audio caption is not provided. When the audio caption is provided as a prompt, VATT achieves even more refined performance (with lowest KLD score of 1.41). Furthermore, subjective studies asking participants to choose the most compatible generated audio for a given silent video, show that VATT Audio has been chosen on average as a preferred generated audio than the audio generated by existing methods. VATT enables controllable video-to-audio generation through text as well as suggest

关键词： Vector spaces

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of K-means and NMF Clustering Algorithms 2

A Comparative Study of K-means and NMF Clustering Algorithms

引用

2nd International engineering Conference on electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Basiri, Fahimeh Amer, Ayman Ranjbar Naserabadi, Mohammad Javad Moghimi, Mohammad Mahdi Tarbiat Modares University Applied Mathematics Department Tehran Iran Zarqa University Faculty of Engineering Zarqa Jordan College of Engineering University of Business and Technology Jeddah21448 Saudi Arabia Petroleum University of Technology Technical Inspection Department Abadan Iran Yazd Branch Islamic Azad University Department of Electrical Engineering Yazd Iran

ISBN: (纸本)9798350373363

Cluster analysis, also known as clustering, is a multivariate data mining technique whose goal is to classify objects based on a set of selective features. Nonnegative matrix factorization (NMF), and K-means are the most used clustering methods. NMF is a method that breaks down a high-dimensional data matrix into two lower-dimensional matrices with positive elements;while K-means is an algorithm that assigns each data point to a cluster that has a centroid. The main objective of this algorithm is to minimize the total distance between the data points and their respective clusters. In this paper, four datasets, consist of data collected from newswires, radio programs, and television programs are prepared for assessing. Then, they are clustered via NMF and K-means techniques. Furthermore, the results are compared with Purity and Entropy criteria. It can be concluded that both algorithms work better in small dimension datasets rather than high-dimensional ones. Furthermore, NMF has generally a better accuracy. © 2023 IEEE.

关键词： Cluster analysis

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：