检索结果-内蒙古大学图书馆

OCEANS 2024 - Halifax, OCEANS 2024

作者： Ishijima, Ryoichi Ebihara, Tadashi Wakatsuki, Naoto Maeda, Yuka Mizutani, Koichi University of Tsukuba Graduate School of Science and Technology Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan

ISBN: (纸本)9798331540081

Underwater acoustic (UWA) communication is a promising technology for constructing underwater data links. We focus on multiple-input-multiple-output (MIMO)-signaling to achieve reliable UWA communication. This paper applies a global optimum solution of basis pursuit denoising (BPDN) in orthogonal signal division multiplexing (OSDM) to reduce computational complexity of channel estimation precess. Although MIMO signaling achieves the same data rate as single-input- multiple-output (SIMO) signaling with a lower baud rate, MIMO requires more computational time in signal processing due to the existence of numerous channel impulse responses compared with SIMO case. We also conducted a sea trial with a mobile boat to evaluate the proposed method in terms of communication quality and computational complexity. As a result, the proposed channel estimator achieves the same communication quality reducing 83% computational time. We expect that our channel estimator will play an important role in realizing reliable UWA communication. © 2024 IEEE.

关键词： Channel estimation

来源：评论

学校读者我要写书评

暂无评论

Individual Diffusion Auralize Display Using an Array of Audio Source Position Tracking Ultrasonic Speakers 24

Individual Diffusion Auralize Display Using an Array of Audi...

引用

2024 SIGGRAPH Asia 2024 Posters, SA 2024

作者： Auchi, Hyuma Fukuda, Akito Yamauchi, Yuta Kawamura, Homura Zempo, Keiichi College of Engineering Systems University of Tsukuba Tsukuba Japan Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan

ISBN: (纸本)9798400711381

We developed a prototype system called the "Individual Diffusion Auralize Display,"which independently generates each instrument's sound using multiple parametric array loudspeakers (PAL) and monitor speakers. The system adjusts the reflection points of the sounds based on the players' positions. In this study, we demonstrated that the system meets the expected requirements, with the monitor particularly offering an optimal acoustic environment for multi-person viewing © 2024 Copyright held by the owner/author(s).

关键词： Loudspeakers

来源：评论

学校读者我要写书评

暂无评论

Frequency-constrained Unit Commitments with Linear Rules Extracted from Simulation Results Considering Regulations from Battery Storage

引用

Journal of Modern Power systems and Clean Energy 2023年第4期11卷 1041-1052页

作者： Jiawei Zhang Zhichao Chen Ning Zhang Xianfeng Zhang State Key Lab of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Science and Technology Research Institute ChinaThreeGorgesCorporationBeijing100038China

Heavy renewable penetrations and high-voltage cross-regional transmission systems reduce the inertia and critical frequency stability of power systems after ***,the power system operators should ensure the frequency nadirs after possible disturbances are within the set restriction,e.g.,0.20 *** methods utilize linearized and simplified control models to quantify the frequency nadirs and achieve frequency-constrained unit commitments(FCUCs).However,the simplified models are hard to depict the frequency responses of practical units after ***,they usually neglect the regulations from battery *** paper achieves FCUCs with linear rules extracted from massive simulation *** simulate the frequency responses on typical thermal-hydro-storage systems under diverse unit online ***,we extract the rules of frequency nadirs after disturbances merely with linear support vector machine to evaluate the frequency stability of power *** algorithm holds a high accuracy in a wide range of frequency ***,we apply the rules to three typical cases to show the influences of frequency constraints on unit commitments.

关键词： Frequency regulation unit commitment machine learning rule extraction primary frequency regulation energy storage support vector machine

来源：评论

学校读者我要写书评

暂无评论

Processing flow for realization of multi-channel spatial acoustics using parametric speakers 13

Processing flow for realization of multi-channel spatial aco...

引用

13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Fukuda, Akito Auchi, Hyuma Yamauchi, Yuta Kawamura, Homura Zempo, Keiichi University of Tsukuba Graduate School of Science and Technology Tsukuba Japan University of Tsukuba College of Engineering Systems Tsukuba Japan University of Tsukuba Institute of Systems and Information Engineering Tsukuba Japan

ISBN: (纸本)9798350355079

Parametric speakers (PS) can reproduce hyperdirectional sound, which somebody can reflect off an object to generate a point sound source at the reflection point. We hypothesized that spatial placement and sound image control of multiple sound sources utilizing this property could realize non-wearable and dynamic multi-channel spatial acoustics. However, PS has problems with frequency-dependent response and sound quality degradation due to harmonic distortion, making it unsuitable for applications that require high sound quality, such as music listening. In this paper, we propose a sound processing flow that applies a frequency filter that takes into account the frequency response of the PS to the sound source to be played. Using the proposed method, we aim to realize high-quality multi-channel spatial sound using PS by reproducing only the sound suitable for each speaker's frequency characteristics. The sound reproduced from the PS is simulated by convolving the impulse response of the PS with a series of processed sound source files, and the sound quality improvement effect of the proposed method is evaluated. © 2024 IEEE.

关键词： Acoustic generators

来源：评论

学校读者我要写书评

暂无评论

LayOut Loud: An AI-Powered Augmented Reality and Mobile Application for Room Interior Design and Layout Optimization 4

LayOut Loud: An AI-Powered Augmented Reality and Mobile Appl...

引用

4th International Conference on Intelligent Cybernetics technology and Applications, ICICyTA 2024

作者： Cuevas, John Raphael G. Rili, John Kenneth R. Santillan, Anny Neolicia G. Agustin, Vivien A. Gonzales, Mary Grace N. Centeno, Criselle J. Regala, Richard C. College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Department of Information Technology Manila Philippines College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Department of Computer Science Manila Philippines Pamantasan ng Lungsod ng Maynila Faculty of College of Engineering and Technology Department of Information Technology Manila Philippines College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Department of Information Technology Manila Philippines Pamantasan ng Lungsod ng Maynila College of Engineering and Technology Department of Computer Science Manila Philippines

ISBN: (纸本)9798331506490

LayOut Loud is an AI-powered augmented reality (AR) and mobile application designed to revolutionize room interior design by offering tailored, real-time solutions for layout optimization. The primary objective of this tool is to design AI-powered features that analyze user-provided room dimensions, furniture types, and style preferences. By leveraging advanced algorithms, LayOut Loud generates personalized design suggestions that cater to the individual needs and aesthetic tastes of users, ensuring that each interior design experience is customized and unique. A key goal of the application is to enhance user experience and decision-making through a clustering algorithm. This algorithm categorizes furniture pieces based on their suitability and appearance in living spaces, streamlining the selection process for users. By enabling the visualization of these items in a 3D model, users can make informed decisions about their interior design choices, ensuring that each piece contributes to the overall aesthetic and functional harmony of the space. Additionally, LayOut Loud focuses on improving its AR capabilities by allowing users to capture their room layouts and view virtual furniture arrangements in real time. This feature provides practical, interactive design solutions, empowering users to experiment with different configurations and instantly see how potential changes would appear in their actual living environments. Ultimately, LayOut Loud offers a user-friendly, immersive platform that transforms the way individuals approach interior design. © 2024 IEEE.

关键词： Architectural design

来源：评论

学校读者我要写书评

暂无评论

Tropical Cyclone Intensity Prediction Using Deep Learning Techniques- A Survey 4

Tropical Cyclone Intensity Prediction Using Deep Learning Te...

引用

4th IEEE International Conference on Applied Electromagnetics, Signal Processing, and Communication, AESPC 2024

作者： Ilayaraja, V. Rajamohana, S.P. Jagadeesan, S. Aishwarya, V. Rakesh, M. School of Computer Science and Engineering Vellore Institute of Technology Tamilnadu Vellore632 014 India School of Engineering & Technology Pondicherry University Department of Computer Science Puducherry Karaikal India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Department of Software and Systems Engineering Tamil Nadu Vellore632 014 India

ISBN: (纸本)9798331528171

Tropical cyclones, characterized by strong winds and heavy rainfall, threaten human life in coastal regions crucial to the economy, including fisheries, agriculture, tourism, and infrastructure. Their frequent occurrence impacts communities reliant on these industries for livelihoods. Accurate estimation of tropical cyclone intensity is vital for disaster preparedness, risk assessment, and timely evacuations. Recent advancements in machine learning and deep learning have been applied to predict cyclone intensity from satellite images, providing insights into cyclone dynamics and enhancing disaster response. This paper analyzes recent research on intensity estimation using various machine learning algorithms and discusses future prospects for improving accuracy and reliability. © 2024 IEEE.

关键词： Tropical cyclone

来源：评论

学校读者我要写书评

暂无评论

Predicting Energy Consumption Using Stacked LSTM Snapshot Ensemble

引用

Big Data Mining and Analytics 2024年第2期7卷 247-270页

作者： Mona Ahamd Alghamdi Abdullah S.A.L-Malaise AL-Ghamdi Mahmoud Ragab Information Systems Department Faculty of Computing and Information Technology(FCIT)King Abdulaziz University(KAU)Jeddah 21589Kingdom of Saudi Arabia Information Systems Department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with School of EngineeringComputing and DesignDar Al-Hekma UniversityJeddah 22246Kingdom of Saudi Arabia Information Technology Department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with Mathematics DepartmentFaculty of ScienceAl-Azhar UniversityNaser City 11884Egypt

The ability to make accurate energy predictions while considering all related energy factors allows production plants,regulatory bodies,and governments to meet energy demand and assess the effects of energy-saving *** energy consumption falls within normal parameters,it will be possible to use the developed model to predict energy consumption and develop improvements and mitigating measures for energy *** objective of this model is to accurately predict energy consumption without data limitations and provide results that are easily *** proposed model is an implementation of the stacked Long Short-Term Memory(LSTM)snapshot ensemble combined with the Fast Fourier Transform(FFT)and *** and Berard’s Individual Household Electric-Power Consumption(IHEPC)dataset incorporated with weather data are used to analyse the model’s accuracy with predicting energy *** model is trained,and the results measured using Root Mean Square Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and coefficient of determination(R^(2))metrics are 0.020,0.013,0.017,and 0.999,*** stacked LSTM snapshot ensemble performs better than the compared models based on prediction accuracy and minimized *** results of this study show that prediction accuracy is high,and the model’s stability is high as *** model shows that high levels of accuracy prove accurate predictive ability,and together with high levels of stability,the model has good interpretability,which is not typically accounted for in ***,this study shows that it can be inferred.

关键词： energy consumption prediction Artificial Intelligence(AI) Deep Learning(DL) snapshot ensemble

来源：评论

学校读者我要写书评

暂无评论

IR-YOLO: Real-Time Infrared Vehicle and Pedestrian Detection

引用

Computers, Materials & Continua 2024年第2期78卷 2667-2687页

作者： Xiao Luo Hao Zhu Zhenli Zhang Department of Electrical Engineering and Automation Jiangxi University of Science and TechnologyGanzhou341000China Jiangxi Provincial Key Laboratory of Maglev Technology Ganzhou341000China Graduate School of Information Production and SystemsWaseda UniversityKitakyushu-shiFukuoka808-0135Japan

Road traffic safety can decrease when drivers drive in a low-visibility *** application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of *** tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small ***,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category ***,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection *** test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only *** contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource *** the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the *** improved algorithm has shown significant advancements in balancing accuracy and computati

关键词： Traffic safety infrared image pedestrians and vehicles focal GIoU distributed shift convolution

来源：评论

学校读者我要写书评

暂无评论

Complex Emotion Estimation using Analysis-by-Synthesis of Facial Expression Images

引用

IEEE Access 2025年 13卷 88731-88746页

作者： Khine, Win Shwe Sin Siritanawan, Prarinya Kotani, Kazunori Japan Advanced Institute of Science and Technology School of Information Science Japan Shinshu University Informatics and Interdisciplinary Systems Division Graduate School of Science and Technology Department of Engineering Nagano Japan Kanazawa University Faculty of Transdisciplinary Science Institute of Philosophy in Interdisciplinary Science Ishikawa Japan

This research proposes an approach for recognizing facial expressions for complex emotion estimation through the utilization of generated facial images. The proposed approach consists of two main parts: facial image generation and facial expression recognition. In the first part, we introduce Conditioned Emotion Generative Adversarial Networks (cEmoGANs) to synthesize images that convey complex facial expressions. Unlike previous methods, our generative model maintains face identity information and expresses various types of complex emotions. This capability encourages the generator to have control over the image generation process, resulting in enhanced image quality, reduced distortion, and increased diversity of generated images. The second part involves the design of a multiple-label classification based on a convolutional neural network trained on the complex facial expression images generated from the first part, which is employed in the recognition of complex facial expressions for emotion estimation. Our model, using images generated by cEmoGANs, demonstrates a notable performance surpassing the capabilities of the previous models in comparative evaluations. © 2013 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Device Identification using Network Traces in a Smart Home IoT Network 17

Device Identification using Network Traces in a Smart Home I...

引用

17th IEEE International Conference on Advanced Networks and Telecommunications systems, ANTS 2023

作者： Brahma, Jwngfu Matam, Rakesh Choudhury, Nikumani Indian Institute of Information Technology Dept. of Computer Science & Engineering Guwahati India Birla Institute of Technology & Science Dept. of Computer Science & Information Systems Hyderabad India

ISBN: (纸本)9798350307672

Device identification is a crucial aspect of securing networks, particularly in the context of the Internet of Things (IoT), where a vast variety of devices are interconnected. Recently, there has been significant research on developing techniques for identifying IoT devices based on their unique characteristics, called as device fingerprints. These techniques use machine learning algorithms, which can effectively learn and classify devices based on their features. However, device identification remains a challenging task due to the diversity of IoT devices and the constant evolution of their characteristics. This paper presents our attempt at device identification by analyzing distinct device characteristics observed during network communication and using different machine learning techniques. © 2023 IEEE.

关键词： Internet of things

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：