检索结果-内蒙古大学图书馆

IEEE Annual Conference on Pervasive Computing and Communications Workshops (PerCom)

作者： Changkun Liu Yukun Zhao Tristan Braud Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Division of Integrative Systems and Design The Hong Kong University of Science and Technology Hong Kong

Recent years have seen significant improvement in absolute camera pose estimation, paving the way for pervasive markerless Augmented Reality (AR). However, accurate absolute pose estimation techniques are computation- and storage-heavy, requiring computation offloading. As such, AR systems rely on visual-inertial odometry (VIO) to track the device’s relative pose between requests to the server. However, VIO suffers from drift, requiring frequent absolute repositioning. This paper introduces MobileARLoc, a new framework for on-device large-scale markerless mobile AR that combines an absolute pose regressor (APR) with a local VIO tracking system. Absolute pose regressors (APRs) provide fast on-device pose estimation at the cost of reduced accuracy. To address APR accuracy and reduce VIO drift, MobileARLoc creates a feedback loop where VIO pose estimations refine the APR predictions. The VIO system identifies reliable predictions of APR, which are then used to compensate for the VIO drift. We comprehensively evaluate MobileARLoc through dataset simulations. MobileARLoc halves the error compared to the underlying APR and achieves fast (80ms) on-device inference speed.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Embedding SDGs in Higher Education Curricula: A Case Study

Embedding SDGs in Higher Education Curricula: A Case Study

引用

IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Sri Devi Ravana Myat Noe Win Nasa Zata Dina Maria Fasli Department of Information Systems Faculty of Computer Science & Information Technology Universiti Malaya Kuala Lumpur Malaysia School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom

Data analytics has enabled evidence-based decision-making, monitoring, and implementation across multiple sectors, making datasets easier to collect, analyze, and understand. Data analytics presents an opportunity for the application of advanced techniques to address challenges in the real world including at the global level such as those associated with the Sustainable Development Goals (SDGs). In educating the next generation of professionals, instilling them with the desire to use technologies for public good and support the implementation of SDGs is highly desirable, but how to do this in higher education settings so as to develop talents and future professionals who can create meaningful impacts towards a nation's and global sustainable growth is not clear. It is still challenging to transform students' perspectives from seeing data analytics projects as purely academic exercises to developing real-world solutions that can have an impact on policy and sustainable development. This paper describes a case study on developing students as professionals and their understanding of SDGs utilizing the Data Analytics Group Project curriculum at the University of Malaya. With the findings, this paper intends to inspire academics to consider how SDGs can be included in the curriculum so that students as trained professionals can adopt a holistic viewpoint of their professional contributions to society and the SDGs in particular, taking into account the cultural, economic, and environmental influences on a country's sustainable development initiatives.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Early Experiences with Specifications Grading in Introductory CS Courses

Early Experiences with Specifications Grading in Introductor...

引用

Frontiers in Education (FIE) Conference

作者： Stephen H. Edwards Manuel A. Pérez-Quiñones Adrienne Decker Bob Edmison Audrey Rorrer Anmol Shukla Computer Science Virginia Tech Blacksburg VA USA Software and Information Systems UNC Charlotte Charlotte NC USA Engineering Education University at Buffalo Buffalo NY USA Computer Science UNC Charlotte Charlotte NC USA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This innovative practice paper describes our experiences with alternative grading practices in introductory computing courses and two large public universities in the United States. Computing classrooms often use traditional grading practices involving allocating points to assignments, deducting points for mistakes and tardiness, and combining assignment scores using a weighted average to determine grades. Recent research suggests that these practices may diminish achievement, discourage students, and suppress effort to such an extent that they are considered by some as detrimental. We approach our work as an exploratory case study, without predefined research questions or hypotheses. Our experiences began with the adoption of specifications grading. We outline the grading scheme applied to traditional programming assignments and exams/quizzes, and discuss the initial integration of these schemes with conventional auto-grading tools. We delve into student perceptions of alternative grading, their utilization of flexible deadlines, and resubmission opportunities. We conclude with a discussion of two challenges encountered during our exploration: student acceptance of a novel grading form, and the adaptation of tools designed for traditional grading to support alternative grading mechanisms. Our early exploration aims to inspire further research on the use of alternative grading in computing. It is clear from our observations that simply implementing the practices does not ensure the equitable and inclusive outcomes that can be achieved with these practices. If students are not prepared to use these practices, they find them difficult to understand and can feel that they are not being treated fairly. Additionally, we wish to foster a community of practice to assist faculty members exploring these changes, with the goal of creating more equitable and inclusive classrooms.

关键词： Programming profession

来源：评论

学校读者我要写书评

暂无评论

Empowering self-sustained agriculture: an IoT field tracking model driven by fog computing

引用

Discover Internet of Things 2025年第1期5卷 1-18页

作者： Singh, Gurpreet Singh, Jaspreet Juneja, Sapna Gulzar, Yonis Gupta, Deepali Ghafoor, Kayhan Zrar Kumar, Mukesh Department of Computer Science and Engineering Chandigarh University Punjab Chandigarh140413 India KIET Group of Institutions Delhi-NCR Uttar Pradesh Ghaziabad201206 India Department of Management Information Systems College of Business Administration King Faisal University Al-Ahsa31982 Saudi Arabia Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Information and Communication Technology Eng Erbil Polytechnic University 42VQ+756 120 Meter St Erbil Erbil Governorate Iraq Mechanical Engineering College of Engineering Assosa University Assosa5220 Ethiopia

Increasing availability of cost effective IoT (Internet of Things) devices have led to the development of IoT- based farm management systems. Smart Agriculture is a demanding approach that employs the use of technology-enabled information and communication to monitor farms. In India, somewhere around 60% of the organization’s operations mostly dependent on agriculture directly or indirectly. A nation’s advancement is typically influenced by concerns with agriculture. The most effective approach to addressing agriculture’s challenges is always to improve traditional agricultural practices as well as modernize them into smart agriculture. The smart agriculture technique offers beneficial data collection, highly precise control as well as automated monitoring strategies. This research proposed a IoT assisted fog-based model that promises to provide the cost-effective smart agriculture system. Fog platform brings computation and storing nearer at the network’s the border, allowing for the efficient processing of data produced by IoT devices across smart agricultural systems. The bibliometric evaluation of the Web of science database for the adoption of the IoT-Fog base infrastructure in the creation of smart agriculture systems is also highlighted in this paper. The proposed solution when implemented as well as when contrasted with existing IoT-based agriculture system exhibit better efficiency. The result revealed that proposed system brings down response time, error rate and standard deviation to significant level and improves the accuracy of current system exponentially. © The Author(s) 2025.

关键词： Agricultural robots

来源：评论

学校读者我要写书评

暂无评论

MobileARLoc: On-device Robust Absolute Localisation for Pervasive Markerless Mobile AR

arXiv

引用

arXiv 2024年

作者： Liu, Changkun Zhao, Yukun Braud, Tristan Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Division of Integrative Systems and Design The Hong Kong University of Science and Technology Hong Kong

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Time-Varying ZAI (Zhang Approximation Inverse) and SE (Simple "Optimal") Alternative Proposed for Solving Nonlinear Equations

Time-Varying ZAI (Zhang Approximation Inverse) and SE (Simpl...

引用

Intelligent Robotics and Automatic Control (IRAC), International Conference on

作者： Yunong Zhang Guanquan Wang School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (数字)9798350389807

ISBN: (纸本)9798350389814

Approximation inverse and nonlinear equations are critical topics in contemporary research. In this paper, we propose and utilize the concept of time-varying Zhang approximation inverse (TV-ZAI) to approximate the inverse of time-varying Jacobian matrix, and to solve the nonlinear equation. Specifically, we propose the norm based definitions and spectral-radius (SR) based definitions to complement the TV-ZAI. The TV-ZAI is capable of dealing with both continuous and discrete time-varying problems, which makes it more efficient in computation and easier to implement in digital computers compared with analog computers. In addition, we propose a simple alternative for the time-varying optimal Zhang approximation inverse (TV-OZAI). Besides, the corresponding numerical experimental results show the feasibility and effectiveness of the TV-ZAI and TV-OZAI-alternative solutions for solving nonlinear equations.

关键词： Jacobian matrices Digital computers Nonlinear equations Analog computers Computational efficiency Robots Convergence

来源：评论

学校读者我要写书评

暂无评论

Smart Surveillance Object Detection System

Smart Surveillance Object Detection System

引用

Artificial Intelligence For Internet of Things (AIIoT), International Conference on

作者： Gaurav Chaudhary Shreya Pathak Vikas Choudhary Love Chauhan Abhishek N Tripathi School of Electronics Engineering Vellore Institute of Technology Vellore India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore Vellore India

ISBN: (数字)9798350372120

ISBN: (纸本)9798350372137

This paper presents an integrated Internet of Things based approach to smart surveillance and urban parking management systems, emphasizing robust object detection and precise parking occupancy monitoring. Our solution adopts cost-effective hardware like the ESP32 CAM module, leveraging its built-in camera and powerful processor for real-time image processing. For surveillance applications, we implement a custom object detection model built with OpenCV, a renowned Python library. This model, finely-tuned for efficient person detection, runs directly on the ESP32 CAM, eliminating the need for external processing units. Additionally, the ESP32 CAM’s Wi-Fi connectivity enables seamless integration with existing networks, simplifying deployment. This integrated approach, combining the cost-effectiveness of ESP32 CAM modules with the image processing capabilities of OpenCV, offers a comprehensive solution for smart surveillance and urban parking management. By utilizing readily available hardware and open-source software, the system promotes widespread adoption and affordability, making it a valuable tool for creating smarter and more sustainable cities.

关键词： computer vision Surveillance Object detection Real-time systems Libraries Hardware Internet of Things

来源：评论

学校读者我要写书评

暂无评论

Empowering Consumer Healthcare Through Sensor-Rich Devices using Federated Learning for Secure Resource Recommendation

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Fathima, Afifa Salsabil Basha, Syed Muzamil Ahmed, Syed Thouheed Khan, Surbhi Bhatia Asiri, Fatima Basheer, Shakila Shukla, Madhu School of Computer Science and Engineering REVA University Karnataka Bengaluru India School of Computing and Information Technology REVA University Karnataka Bengaluru India Department of Data Science School of Science Engineering and Environment University of Salford Manchester United Kingdom Centre for Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India College of computer science Informatics and computer systems department King Khalid University Saudi Arabia Department of Information Systems College of computer and Information science Princess Nourah bint Abdulrahman University P.O. BOX 84428 Riyadh11671 Saudi Arabia the Department of CSE - AI ML & DS Marwadi University Gujarat Rajkot360003 India

When implementing zero-trust edge computing, offloading computational tasks and data access through traditional model training and usage approaches can lead to increased latency. Since the traditional methods often involve extensive communication with a central server, creating additional network hopping stations/nodes resulting in increased latency. The challenge is bound to allocate a befitting resource at a given consumer demand. In this proposed system, a federated learning model based data offloading and consumer medical resource recommendation of IoT is discussed and validated. The user/consumer group and local training models are aligned with edge servers for data preprocessing and customization with a series of resources demand creation and coordination. The consumer resource allocating priorities are fine-grained with the proposed blockchain based priority analyzer for recommendation and allocation. The computational parameter such as resource pool, average waiting time, energy consumption and transmission trust delays are observed and validated. The proposed framework fetches consumer resources logs and synchronizes the centralized training model for effective scheduling and allocation of resources with an accuracy of 94.92% under the 5G operating spectrum. The technique has demonstrated minimal latency in offloading the data request demand and resource allocation at the cloud servers. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Energy-Optimized Offloading of Delay-Sensitive Tasks in Hybrid Edge-Cloud Computing

Energy-Optimized Offloading of Delay-Sensitive Tasks in Hybr...

引用

IEEE International Conference on systems, Man and Cybernetics

作者： Haitao Yuan Shen Wang Yaofei Ma Jing Bi Jinhong Yang Jia Zhang MengChu Zhou School of Automation Science and Electrical Engineering Beihang University Beijing China College of Computer Beijing University of Technology Beijing China CSSC Systems Engineering Research Institute Beijing China Dept. of Computer Science Southern Methodist University Dallas TX USA Dept. of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Currently, a cloud-edge collaborative system combines almost unlimited storage and computing resources where tasks can be migrated to high-performance servers in edge servers or the cloud. However, resource allocation and task offloading present big challenges due to the competition among mobile devices (MDs) for communication and computing resources of edge servers. Therefore, it is significant to properly offload MDs' tasks to edge servers or the cloud. This work proposes a collaborative edge-cloud architecture, including a centralized cloud, edge servers, and MDs. Then, this work jointly considers computing power, task sizes, computing resources, transmission power of MDs, transmission rates, computing power, transmission power, computing resource of edge servers, and computing resource of the cloud. Considering the abovementioned factors, this work designs a mixed-integer non-linear programming problem. To solve it, a Genetic Simulated annealing-based Particle Swarm Optimization (GSPSO) algorithm is proposed to obtain the best solution. Building upon it, this work proposes an energy-minimized task offloading and resource allocation strategy, thereby minimizing the system's energy consumption while ensuring strict task response time limits. Experimental results show that GSPSO reduces the system's energy by 66.34%, 34.65%, and 4.95% more than particle swarm optimization (PSO), self-adaptive PSO, and Tyrannosaurus optimization.

关键词： Energy consumption Federated learning Collaboration Simulated annealing Programming Genetics Servers Resource management Particle swarm optimization Optimization

来源：评论

学校读者我要写书评

暂无评论

Enhancing Accessibility for Visually Impaired on Integrating Object, Distance and Face Detection

Enhancing Accessibility for Visually Impaired on Integrating...

引用

International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： C. Selvarathi R. Kannan Muthumanickam K P. Pandiaraja T. S. Venkateswaran R. Arunraj Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Department of Computer Science and Business Systems Saranathan College of Engineering Tiruchirapalli Tamilnadu India Department of Information Technology Kongunadu College of Engineering and Technology Trichy Tamil Nadu India Department of Computer Science and Business Systems M. Kumarasamy College of Engineering Karur Tamilnadu India Department of Information Technology K. Ramakrishnan college of Engineering Samayapuram Tamilnadu India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

This research presents a novel assistive technology system designed to empower visually impaired individuals by providing enhanced object, facial, and distance detection capabilities. The system aims to replace traditional electronic travel aids with a more comprehensive and cost-effective solution. By combining object and facial recognition with distance detection, the system enables users to navigate their surroundings independently and confidently. Additionally, the system incorporates threat detection capabilities, alerting users to potential dangers and triggering SOS alerts to contacts or authorities. This innovative system offers a more reliable and accessible solution for visually impaired individuals, providing them with the freedom and independence to navigate their daily lives with greater confidence and security.

关键词： Performance evaluation Navigation Face recognition Blindness Object detection User experience Threat assessment Face detection Security Reliability

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：