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共 64941 条记录，以下是141-150 订阅

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Risk Assessment of Urban Renewal Projects in Old Residential Areas Based on C-OWA Operator-FCE

Risk Assessment of Urban Renewal Projects in Old Residential...

引用

2024 International Conference on Construction and Real Estate Management: ESG Development in the Construction Industry, ICCREM 2024

作者： Wang, Zhikai Fang, Jun Dept. of Civil Engineering and Architecture Wuhan Univ. of Technology Wuhan China

ISBN: (数字)9780784485910

ISBN: (纸本)9780784485910

As an important part of urban renewal, old residential renovation projects have been gradually promoted throughout the country. However, due to the complex and diverse objects of renovation and the influence of a large number of people involved, there are high reconstruction risks. In order to manage and control risks reasonably and effectively, this paper firstly identified 22 risk factors through literature research and expert interviews and constructed a risk evaluation index system containing 6 risk dimensions. The Fuzzy comprehensive evaluation model (FCE) and C-OWA operator are introduced to weigh the risk indicators, and the fuzzy comprehensive evaluation model of old residential urban renewal project based on C-OWA is constructed to determine the risk level. Taking the reconstruction project of Rongdong Community in Qiaokou District of Wuhan as an example, the risk measure evaluation is carried out, and the scientific rationality of the model is verified. The risk evaluation results show that the overall risk evaluation of the project is medium risk, and the main risk influencing factors are urban renewal policy risk, financing risk, contract risk with the owner, land price risk, and enterprise competition risk, which points out the direction for risk management. © ASCE.

关键词： Risk management

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Enhanced Realtime Sign Language Detection and Multilingual Translation system

Enhanced Realtime Sign Language Detection and Multilingual T...

引用

2025 International Conference on Computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Kakkar, Madhur Daniel, John Sudha, D. Sathyabama Institute of Science and Technology Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331538538

Sign language is the communication medium that is utilized by the hearing-impaired community. The medium is visual and it uses hand signs and symbols for communication. Over 300 different types of sign languages present in the world today. Sign language uses gestures and hand movements for the majority of the words and finger spellings for the rest. Nonverbal speakers face a lot of challenges while interacting with verbal speakers. Even non-verbal speakers who speak different sign languages face difficulties communicating with each other. This project proposes an enhanced real-time system which detects gestures and finger spellings of multiple sign languages, and translates them into multiple spoken languages. The proposed system aims to utilize CNN network for finger spelling recognition and Long Short-Term Memory (LSTM) network for gesture interpretation. The system will use computer vision for accurate gesture detection and Google Translator API for recognizing signs which will be translated into multiple spoken languages. Initial tests with isolated datasets indicate promising accuracy for both finger spelling and gesture recognition. The goal of the completed system is to help aid communication between verbal and non-verbal speakers and to provide an efficient mode of communication between the two communities. © 2025 IEEE.

关键词： Interactive computer systems

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Real-Time Gaze Tracking for Online Examination

Real-Time Gaze Tracking for Online Examination

引用

2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Bisht, Preyanshu Kumar, Suresh Netaji Subhas University of Technology Dept. of Computer Science and Engineering Delhi India

ISBN: (纸本)9798331508685

The exponential growth in online education has increased the demand for automated systems to ensure academic integrity during online examinations. A real-time proctoring system addresses this need by monitoring a student's eye gaze and head movements during an exam. This system leverages Dlib's pre-trained frontal face detector and 68-point facial landmark predictor to detect facial features and track the direction of eye movement and head position. By analyzing these metrics, the system can flag behaviors associated with potential cheating, such as looking away from the screen for extended periods. This paper discusses the design and implementation of the proctoring system, details the detection algorithms, and evaluates its effectiveness for real-time monitoring. © 2025 IEEE.

关键词： Online systems

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Real-Time Object Detection from Surveillance using Deep Learning 3

Real-Time Object Detection from Surveillance using Deep Lear...

引用

3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Tanisha, A. Tanisha, N. Chaitra, M. Tejasri, P.R. Bnm Institute of Technology Vtu Dept. of Computer Science and Engineering Bangalore India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515911

Object detection in surveillance systems leverages advanced deep learning techniques to enhance security measures through real-time analysis of dynamic video feeds. This project integrates the YOLOv5 model for detecting weapons in both pre-recorded videos and live camera feeds. The model, trained on a dataset with 4000 images labeled for handguns and knives, utilizes image preprocessing steps such as resizing, normalization, and augmentation to improve detection accuracy. Implementing the system with OpenCV and Tkinter, the application processes video streams, identifying potential threats with high precision rate of 0.85 and recall rate of 0.90. The integration of a graphical user interface ensures user-friendly operation for security personnel. Key outcomes demonstrate the efficacy of deep learning models in real-time object detection, significantly contributing to proactive surveillance and enhanced situational awareness. © 2025 IEEE.

关键词： Graphical user interfaces

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Driver Drowsy Detection system Using Machine Learning and Open CV

Driver Drowsy Detection System Using Machine Learning and Op...

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2025 International Conference on Computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Akash, G.S. Palati, Madhu Rajesh Deepak, H.S. Bms Institute of Technology & Management Dept. of Electrical and Electronics Engineering Bengaluru India

ISBN: (纸本)9798331538538

Driver fatigue is another significant risk factor that claim a fairly good proportion of the accident rates globally. Fatigue affects the important human functions including decision making, ability to concentrate and reaction time making it of paramount importance to have good counter measures in place. That is why, the proposed Driver Drowsiness Detection system in this paper focuses on real-time video surveillance and machine learning to identify symptoms of drowsiness. The drowsiness detection of the system is made possible by integrating OpenCV and other computer vision algorithms that take pictures of the face via a camera and examine for patterns that are characteristic of drowsiness, which include yawning, blinking of the eyes frequently, or the closing of the eyes for too long. That is, the use of OpenCV in facial landmark detection and other computations such as EAR and MAR with the help of two well trained models on deep learning. The system uses adaptive thresholds and sophisticated preprocessing to ensure its performance stays high regardless of the conditions which include light, camera angle, and facial expressions. Such consistencies of both the methodologies in convergence help the system to assess the driver's alertness level and immediately produce an alert the moment the driver looks sleepy. Intended to be deployed in semi-autonomous vehicles, vehicles in commercial fleets, as well as individual automobiles, the proposed system can be implemented at a large-scale to help increase road safety. Thus, eliminating the risks related to fatigue-related accidents, it opens an opportunity to minimize fatality rates and change the future environment in transport. The technical issues, the difficulties and the realistic uses of the system are also described This paper focuses on the contribution of the system to enhance road safety and reduce the number of deaths. © 2025 IEEE.

关键词： Human reaction time

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Enhanced Super-Resolution with EDSR: Optimizing Image Quality across Multiple Scaling Factors 3

Enhanced Super-Resolution with EDSR: Optimizing Image Qualit...

引用

3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Venkat, Anika Kirana Kulkarni, Keerti Bnm Institute of Technology Dept. of Electronics and Communication. Engineering Bengaluru India

ISBN: (纸本)9798331515911

In today's world where high resolution visual content is preferred in domains like medical imaging, satellite imagery, and digital entertainment, effective image super resolution is crucial for success. This paper focuses on not just upscaling the resolution but restoring the lost details to improve the overall quality of images. The enhanced deep residual network (EDSR) is utilized to significantly improve image resolution and reduce blurring and outperforming traditional methods. While EDSR does not eliminate all forms of quality degradation, it effectively improves image sharpness, clarity and balancing computational efficiency with enhanced detail construction. The model's performance is elevated using traditional metrics like PSNR and SSIM to quantify the quality enhancement. In the end comparisons are drawn across the scaling factors of 2x, 3x and 4x to show the models ability to perform across various domains. Here, the approach was evaluated across various scaling factors of 2x, 3x, and 4x showing consistent improvement in image clarity, sharpness and structural integrity and surpassing traditional interpolation methods. © 2025 IEEE.

关键词： Medical imaging

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Analysis of Domestic Consumer Electricity Usage Pattern in Dhule City 3

Analysis of Domestic Consumer Electricity Usage Pattern in D...

引用

3rd International Conference on Electronics and Renewable systems, ICEARS 2025

作者： Jangid, Sheetal Joshi, Namra Joshi, Aparna More, Mrunali Jadhav, Bhagyashri SVKM's Institute of Technology Dept. of Electrical Engineering Maharashtra Dhule India

ISBN: (纸本)9798331509675

Energy is a key driving factor for everything. In this modern era, the world is facing two major issues one is an increment in population & and the second is the energy crisis. The conservation of energy is critical. It plays in the social economic development of the nation. Although with the new electrical generation options power demand and supply of electricity is somewhat managed. The usage pattern of electricity is also changed nowadays So;it is required to save energy by all means. The survey of a subsection of Dhule city is conducted. The consumer's data is gathered and further analysis is presented. This paper focused on the analysis of the electricity usage pattern of domestic consumers of Dhule City India. © 2025 IEEE.

关键词： BEE Electricity Usage Energy Saving

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Numerical Performance Evaluation of a Lime-Stabilized Coal Ash Slope Subjected to Rainfall

Numerical Performance Evaluation of a Lime-Stabilized Coal A...

引用

Geo-EnvironMeet 2025: Climate Change, Sustainability, and Resilience

作者： Srikanth, C.S.S.U. Ramaiah, B.J. Krishna, A.M. Dept. of Civil and Environmental Engineering Indian Institute of Technology Tirupati Tirupati India

ISBN: (数字)9780784485705

Global concerns surrounding coal ash pond failures, intensified by extreme rainfall events, necessitate effective mitigation strategies. Lime stabilization, a well-established technique with historical usage, has the potential to mitigate failures. The present paper utilizes Geostudio software to assess untreated and lime-stabilized coal ash slopes. The performance was evaluated for varying rainfall intensities (1, 4, 7, 15, and 40 mm/h), durations (1, 3, 6, 10, 18, 24, and 48 h), and patterns (uniform, advanced, normal, and delayed). While a performance enhancement was observed in slope stability, intensified rainfall (≥4 mm/h, 10 h) leads to notable reductions in the factor of safety (Fs). Moreover, delayed rainfall pattern led to critical Fs values at a critical rainfall intensity and duration. The study provides insights on the impact of rainfall characteristics on the slope stability in the face of challenging environmental conditions. © ASCE.

关键词： Coal ash

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Research on the Factors Influencing Employee Performance in Building Material Production Enterprises Based on ISM

Research on the Factors Influencing Employee Performance in ...

引用

2024 International Conference on Construction and Real Estate Management: ESG Development in the Construction Industry, ICCREM 2024

作者： Chen, Wei Gao, Rongke Xia, Yunfei Dept. of Civil Engineering and Architecture Wuhan Univ. of Technology Wuhan China

ISBN: (数字)9780784485910

ISBN: (纸本)9780784485910

Exploring the causes of issues in employee performance within building materials manufacturing enterprises and researching and optimizing the employee performance system play a crucial role in enhancing the overall level of employee performance assessment. This, in turn, significantly contributes to improving the comprehensive strength of building materials manufacturing enterprises and serves as an important means to ensure the healthy development of the construction industry and fulfill social responsibilities. Through literature analysis and field research, this paper summarizes the factors affecting employee performance in building materials manufacturing enterprises and further analyzes the key factors. It employs the Interpretive Structural Modeling (ISM) method to conduct a structured analysis of the hierarchical relationships among the main influencing factors. The results indicate that the factors affecting employee performance in building materials manufacturing enterprises are mainly divided into three levels: foundational, intermediate, and superficial. Based on the analysis of these results, the paper ultimately proposes several strategic recommendations for enhancing employee performance in building materials manufacturing enterprises. It also aims to provide references and insights for building materials manufacturing enterprises in implementing employee performance assessments. © ASCE.

关键词： Construction industry

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Wrist Fracture Detection Using Deep Learning

Wrist Fracture Detection Using Deep Learning

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2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Rafi, Shaik Mahmamad Anuradha, T. Srinivas, Kothapalli S. V. V. R. Velagapudi Ramakrishna Siddhartha Engineering College Dept. of Information Technology Kanuru India

ISBN: (纸本)9798331529833

Effective treatment of wrist bone fractures depends on early and precise identification. The finding shows that disparities in accessing timely emergency services translate into adverse patient outcomes, especially in regions with fewer healthcare facilities and extended distances, mostly rural areas. Distal radial fractures or wrist fractures are among the commonly encountered musculoskeletal injuries and the treatment and subsequent management depend on timely and precise identification of the fracture pattern. This paper discusses a wrist fracture detection scheme using a deep learning approach for diagnosing wrist bone fractures from X-ray images which can close the health disparities due to the lack of adequate early diagnosis. and his team developed the system using DenseNet-201, MobileNetV2, ResNet-50, EfficientNetV2, U-net and Inception V3 architecture because each was selected for a certain use effect patient outcome. Wrist fractures, among the most common musculoskeletal injuries, require early and accurate diagnosis to optimize treatment and rehabilitation. This project presents a deep learning-based system to detect wrist fractures in X-ray images, designed to bridge healthcare inequalities by facilitating early and automated diagnosis. The system integrates DenseNet-201, MobileNetV2, ResNet-50, EfficientNetV2, U-Net, and Inception V3 models, each chosen for specific roles. DenseNet-201, MobileNetV2, and ResNet-50 are classification networks for fracture detection while U-Net is segmentation network to segment fractured areas. Furthermore, the results using EfficientNetV2 and Inception V3 improve diagnostic capability and image *** work compares the pros and cons of each model in terms of accuracy, computational time, and loss and presents recommendations for the most appropriate models for clinical applications in practice. © 2025 IEEE.

关键词： Deep learning

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