检索结果-内蒙古大学图书馆

MIT Art, design and Technology school of computing International Conference (MITADTSoCiCon)

作者： Shrikala Deshmukh Snehal Chaudhary Milind Gayakwad Kalyani Kadam Nitin S. More Amol Bhosale Amity University Mumbai India Department of Information Technology College of Engineering Bharati Vidyapeeth (Deemed to be University) Pune India College of Engineering Bharati Vidyapeeth (Deemed to be University) Pune India Symbiosis Institute of Technology Pune Symbiosis International (Deemed University) Pune India Department of CSE School of Computing MIT Art Design and Technology University Pune

ISBN: (数字)9798350362879

ISBN: (纸本)9798350362886

Facial Emotion Recognition (FER) has evolved significantly with the advent of deep learning techniques, offering novel approaches to interpret and process facial expressions. This paper reviews recent advancements in FER, emphasizing the role of deep neural network architectures and their application across diverse fields including security, health, and human-machine interfaces. We analyze various methodologies, technological advancements, challenges, and future trends in FER, providing insights into the current state-of-the-art. We conclude by discussing the limitations of current FER systems and propose future directions for research, particularly in extending emotion recognition beyond basic emotions and incorporating multimodal approaches.

关键词： Deep learning Training Emotion recognition Accuracy Reviews Face recognition Soft sensors

来源：评论

学校读者我要写书评

暂无评论

Mixture Gaussian Distribution-Based Collaborative Reinforcement Learning for 3D UAV Localization Optimization Against Jamming Attacks

Mixture Gaussian Distribution-Based Collaborative Reinforcem...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Yujiao Zhu Mingzhe Chen Sihua Wang Yuchen Liu Gaolei Li Changchuan Yin Tony Q.S. Quek Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Coral Gables FL USA Department of Computer Science North Carolina State University Raleigh NC USA School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In this paper, the optimization of unmanned aerial vehicle (UAV) localization under jamming attacks is studied. In the considered network, a base station (BS) collaborates with an active UAV to localize a target UAV. During this positioning process, a jamming UAV transmits discontinuous signals to passive UAVs to interfere the distance information measurement. To localize the target UAV under jamming attacks, the BS jointly use two localization methods: 1) generative adversarial network (GAN)-based positioning method and 2) time difference of arrival (TDOA)-based positioning method. Since GAN-based positioning method cannot defense in a strong jamming signal while TDOA-based positioning method may consume more energy and sacrifice localization accuracy, the BS must select an appropriate positioning method (GAN-based or TDOA-based methods) and four distance measurement information of passive UAVs to estimate the position of the target UAV. This problem is formulated as an optimization problem whose goal is to minimize the positioning error between the estimated and the ground truth positions of the target UAV while considering jamming attacks and the trajectory of passive UAVs. To solve this problem, we propose a mixture Gaussian distribution model-based collaborative reinforcement learning (RL) method which enables the active UAV to determine its transmit power and trajectory, and enables the BS to select the most appropriate subsets of distance measurement information and the optimal positioning method according to the movement of passive UAVs and the unknown jamming attack pattern of the jamming UAV. Simulation results show the proposed method can reduce the positioning error of the target UAV by up to 36.5% compared to the method that does not consider the GAN-based positioning method.

关键词： Location awareness Simulation Collaboration Reinforcement learning Gaussian distribution Autonomous aerial vehicles Distance measurement Trajectory Jamming Optimization

来源：评论

学校读者我要写书评

暂无评论

A Statistical Model to Assess the Team's Productivity in Agile Software Teams 4

A Statistical Model to Assess the Team's Productivity in Agi...

引用

4th IEEE International Conference and Workshop in Obuda on Electrical and Power engineering, CANDO-EPE 2021

作者： Mashmool, Amir Khosravi, Samiyeh Joloudari, Javad Hassannataj Inayat, Irum Gandomani, Taghi Javdani Mosavi, Amir University of Birjand Faculty of Engineering Computer Engineering Department Birjand Iran National University of Computer and Emerging Sciences School of Computing Department of Software Engineering Islamabad Pakistan Shahrekord University Department of Computer Science Shahrekord*** Iran Obuda University Institute of Software Design and Development Budapest1034 Hungary

ISBN: (纸本)9781665420235

Agile methods promise to achieve high productivity and provide high-quality software. Agile software development is the most important approach that has spread through the world of software development over the past decade. Software team productivity measurement is essential in agile teams to increase the performance of software development. Due to the prevalence of agile methodologies and increasing competition of software development companies, software team productivity has become one of the crucial challenges for agile software companies and teams. Awareness of the level of team productivity can help them to achieve better estimation results on the time and cost of the projects. However, to measure software productivity, there is no definitive solution or approach whether in traditional and agile software development teams that lead to the occurrence of many problems in achieving a reliable definition of software productivity. Hence, this study aims to propose a statistical model to assess the team's productivity in agile teams. A survey was conducted with forty software companies and measured the impact of six factors of the team on productivity in these companies. The results show that team effectiveness factors including inter-team relationship, quality conformance by the team, team vision, team leader, and requirements handled by the team had a significant impact on the team's productivity. Moreover, the results also state that inter-team relations affect the most on software teams' productivity. Finally, the model fit test showed that 80% of productivity depends on team effectiveness factors. © 2021 IEEE.

关键词： Productivity

来源：评论

学校读者我要写书评

暂无评论

Implementing a modified Smith predictor using chemical reaction networks and its application to protein translation 4

Implementing a modified Smith predictor using chemical react...

引用

4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Xiao, Yijun Lv, Hui Wang, Xing'an School of Software Engineering Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Liaoning Dalian116622 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Liaoning Shenyang110004 China College of Environmental and Chemical Engineering Dalian University Liaoning Dalian116622 China Dalian Chivy Biotechnology Co. Ltd Liaoning Dalian116622 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

In this article, a special attention is paid to the biochemical controller synthesis for time delay systems and try to implement the well-established Smith predictor approach in the context of biochemical systems. Then, chemical reaction networks (CRNs) are adopted to construct a modified Smith predictor scheme (integrating Smith predictor and feedback compensation controllers) for the first time. Taking a delayed protein translation model as the background, the CRNs-based proposed scheme has access to a method that can solve the effect of co-translated mRNA decay in protein translation. In addition, considering that the decay of mRNA affects mRNA stability and protein production, the co-translated mRNA degradation is treated as an interference input of the protein translation process. Our results show that the impact of a disturbance input (mRNA degradation) is restrained by the modified control strategy. The CRNs-based modified Smith predictor makes the protein translation process more robust and achieves protein output quickly and stably. © 2022 IEEE.

关键词： Time delay

来源：评论

学校读者我要写书评

暂无评论

Performance assessment of public transport networks: An AHP-ANP approach

引用

Heliyon 2024年第22期10卷 e40309页

作者： Lin, Gang Zhang, Qiuyi Zhang, Yiqun Shen, Che Xu, Honglei Wang, Shaoli School of Design Fujian University of Technology Fuzhou 350118 China School of Electrical Engineering Computing and Mathematical Sciences Curtin University Perth WA 6845 Australia Key Laboratory of Ecology and Energy Saving Study of Dense Habitat Ministry of Education China Graduate School of Global Environmental Studies Sophia University Tokyo 1028554 Japan

Multi-criteria decision-making (MCDM) methods have been extensively employed by researchers in the public transport (PT) sector. While many studies utilize a single MCDM method, employing multiple MCDM methods can achieve more robust results. Furthermore, integrated MCDM methods have the potential to address the weaknesses and limitations inherent in single MCDM method. In this study, we address the limitations of single MCDM methods by integrating the analytic hierarchy process (AHP) with the analytic network process (ANP) to evaluate public transport networks performance. Based on the established public transport criteria matrix AHP model, we identify interdependencies among criteria. The AHP-ANP method is then applied to assess public transport networks in three case study cities in Australia. The sensitivity analysis conducted on both the AHP and integrated AHP-ANP approaches highlights the influence of criteria interdependency. This research contributes to mitigating the limitations of AHP method and applies AHP-ANP model to provide decision-makers with insights to enhance PT network performance and achieve smart PT network management. © 2024 The Authors

关键词： AHP-ANP approach Comparison analysis Interdependencies MCDM Sensitivity analysis

来源：评论

学校读者我要写书评

暂无评论

Enhancing Physical Layer Communication Security through Generative AI with Mixture of Experts

arXiv

引用

arXiv 2024年

作者： Zhao, Changyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui In Kim, Dong Shen, Xuemin Letaief, Khaled B. CNRS@CREATE 1 Create Way 08-01 Create Tower 138602 Singapore College of Computing and Data Science Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Hong Kong University of Science and Technology Hong Kong

AI technologies have become more widely adopted in wireless communications. As an emerging type of AI technologies, the generative artificial intelligence (GAI) gains lots of attention in communication security. Due to its powerful learning ability, GAI models have demonstrated superiority over conventional AI methods. However, GAI still has several limitations, including high computational complexity and limited adaptability. Mixture of Experts (MoE), which uses multiple expert models for prediction through a gate mechanism, proposes possible solutions. Firstly, we review GAI model’s applications in physical layer communication security, discuss limitations, and explore how MoE can help GAI overcome these limitations. Furthermore, we propose an MoE-enabled GAI framework for network optimization problems for communication security. To demonstrate the framework’s effectiveness, we provide a case study in a cooperative friendly jamming scenario. The experimental results show that the MoE-enabled framework effectively assists the GAI algorithm, solves its limitations, and enhances communication security. © 2024, CC BY.

关键词： Network security

来源：评论

学校读者我要写书评

暂无评论

PanoMRT: Panoramic Infrared Thermography to Model Human Thermal Exposure and Comfort

SSRN

引用

SSRN 2022年

作者： Middel, Ariane Huff, Matthew Krayenhoff, SCOTT Eric Schneider, FLORIAN Arwed Udupa, Ananth School of Arts Media and Engineering School of Computing and Augmented Intelligence Arizona State University United States School of Computing and Augmented Intelligence Arizona State University United States School of Environmental Sciences University of Guelph CA United States School of Sustainability Arizona State University United States The Design School Arizona State University United States

As summer heat waves become the new normal worldwide, modeling human thermal exposure and comfort to assess and mitigate urban overheating is crucial to uphold livability in cities. We introduce PanoMRT , an open source human-biometeorological model to calculate Mean Radiant Temperature ( T MRT ), Physiologically Equivalent Temperature ( PET ), and the Universal Thermal Climate Index ( UTCI ) from thermal equirectangular 360° panoramas and standard weather information (air temperature, relative humidity, wind speed). We validated the model for hot, dry, clear summer days in Tempe, Arizona, USA with in-situ observations using a FLIR Duo Pro R thermal camera on a rotating arm and the mobile human-biometeorological instrument platform MaRTy. We observed and modeled T MRT and thermal comfort for 19 sites with varying ground cover (grass, concrete, asphalt), sky view factor, exposure (sun, shade), and shade type (engineered, natural) six times per day. PanoMRT performed well with a Root Mean Square Error ( RMSE ) of 4.1°C for T MRT , 2.6°C for PET , and 1.2°C for UTCI , meeting the accuracy requirement of ±5°C set in the ISO 7726 standard for heat and cold stress studies. RayMan reference model runs without measured surface temperature forcing reveal that accurate longwave radiative flux estimations are crucial to meet the ±5°C threshold, particularly for shaded locations and during midday when surface temperatures peak and longwave modeling errors are largest. This study demonstrates the importance of spatially resolved 3D surface temperature data for thermal exposure and comfort modeling to capture complex longwave radiation exposure patterns resulting from heterogeneity in built configuration and material radiative and thermal properties in the built environment. © 2022, The Authors. All rights reserved.

关键词： Surface temperature

来源：评论

学校读者我要写书评

暂无评论

Enhancing IoT-Edge Computation with Data Forwarding based Decentralized Deep Neural Networks 7

Enhancing IoT-Edge Computation with Data Forwarding based De...

引用

7th International Conference on Image Information Processing, ICIIP 2023

作者： Prasad, B.M.G. Jopate, Rachappa Savita, Pankaj Basi Reddy, A. Shankar, B. Prabu Arunkumar, M.S. Department of Cse Andhra Pradesh Kurnool518452 India University of Technology And Applied Sciences - Al Mussanah Department of Information Technology Al Muladha Muscat Oman Sagar Institute of Science & Technology Bhopal Organization-Sagar Institute of Science & Technology Department of Cse Madhya Pradesh Bhopal India Mohan Babu University School of Computing Department of Computer Science And Engineering Andhra Pradesh Tirupati India Alliance University Alliance College of Engineering And Design Department of Computer Science And Engineering Karnataka Banglore India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science And Technology Department of Computer Science And Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350371406

The incorporation of edge computing has become essential in the big data and Internet of Things age to tackle issues related to latency, real-time processing, and data scale. This paper delves into the imperative need for edge computing within the context of big data environments. Distributed deep learning methodologies are explored, encompassing a diverse array of deep learning models. Particularly, a novel paradigm named Data Forwarding based Decentralized Deep Neural Network (DF-DDNN) is introduced to achieve low latency IoT-Edge computation. In order to reduce latency in Io T ecosystems, the DF-DDNN model makes use of edge devices' processing capabilities. By strategically distributing data processing and computation at the edge, this model seeks to overcome inherent limitations of conventional Io T architectures, with a keen focus on network, processing, and overall latencies. The research provides a thorough performance evaluation that compares the DF-DDNN model's performance versus conventional IoT models in a number of areas. The outcomes demonstrate how much better the suggested DF-DDNN model is than traditional IoT systems. Notably, improvements are evident in terms of reduced network latency, accelerated processing speeds, and overall latency mitigation. This research underscores the critical importance of embracing edge computing in the context of big data and deep learning applications. The DF-DDNN model emerges as a promising avenue for advancing IoT-Edge computation, effectively addressing latency concerns and augmenting the performance of IoT-enabled systems. © 2023 IEEE.

关键词： Edge computing

来源：评论

学校读者我要写书评

暂无评论

Analyzing Children’s Behaviors Based on AI Recognition Approach to Promote Child-Friendly school-to-Home Street design 18th

Analyzing Children’s Behaviors Based on AI Recognition Appr...

引用

18th International Conference on Computer Science and Education, ICCSE 2023

作者： Zhang, Qianxi Wang, Gang Loo, Yat Ming Wang, Xinkai Xia, Xiumin Mu, Xingyu School of Design NingboTech University Ningbo315100 China Department of Architecture and Engineering University of Nottingham Ningbo China Ningbo315100 China The Bartlett Development Planning Unit University College London LondonWC1H 9EZ United Kingdom School of Computing and Data Engineering NingboTech University Ningbo315100 China Zhejiang Fashion Institute of Technology Ningbo315211 China

ISBN: (纸本)9789819707904

school-to-home streets are an important part of the public space network of child-friendly cities. The improvement of their child-friendliness needs to be based on the investigation and evaluation of the current usage status. The traditional site investigation methods are limited by manpower and time, lack of efficiency and effectiveness. This paper proposes a new analysis framework for children’s street behaviors based on AI recognition methods, including action recognition algorithm, human flow statistic algorithm, and target tracking algorithm. It takes one school-to-home street in the Mingdong community, Ningbo city as a case study. Based on the AI recognition of this street’s surveillance videos, the result data verifies the effectiveness of street usage analysis. This is valuable to promote the child-friendly school-to-home street design in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Target tracking

来源：评论

学校读者我要写书评

暂无评论

Exploring the Effects of User Control on Social Engagement in Virtual Reality 20

Exploring the Effects of User Control on Social Engagement i...

引用

Proceedings of the 32nd Australian Conference on Human-Computer Interaction

作者： Weijia Wang Steven Baker Andrew Irlitti The University of Melbourne Melbourne School of Engineering Australia Interaction Design Lab School of Computing and Information Systems The University of Melbourne Australia School of Computing and Information Systems University of Melbourne Australia

ISBN: (纸本)9781450389754

A key aspect of user experience in virtual reality (VR) is navigational control. However, when multiple users interact in a social VR environment, it is important that navigational control is designed to support social engagement. In this paper, we investigate the relationship between levels of navigational control, diminishing from fully independent to completely passive, and their potential impact on social engagement in a social VR environment. We conducted qualitative interviews with 12 participants who viewed video recordings demonstrating control methods and social interactions in a prototype social VR application. Our results demonstrate the diverse attitudes people hold about how social engagement is impacted by different navigational control methods, and how this might be impacted by individual preferences and cultural factors. Based on these results, we contribute design considerations for supporting group cohesion, interpersonal and cultural norms, as well as discoverability in social VR systems to better support social engagement.

关键词： social VR interaction methods virtual reality user control social engagement

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：