检索结果-内蒙古大学图书馆

A multi-model approach to construction site safety: Fault trees, Bayesian networks, and ontology reasoning

Expert Systems with Applications 2025年 288卷

作者： Shi, Donghui Gan, Shuling Zurada, Jozef Guan, Jian Wang, Feilong Weichbroth, Pawel School of Electronics and Information Engineering Anhui Jianzhu University Anhui Province Hefei230601 China Anhui Province Key Laboratory of Intelligent Building and Building Energy Saving Anhui Jianzhu University Anhui Hefei230022 China Department of Information Systems Analytics and Operations College of Business University of Louisville 2301 S 3rd St LouisvilleKY40292 United States School of Electronic Science and Engineering Hunan University of Information Technology Hunan Changsha410151 China Department of Software Engineering Faculty of Electronics Telecommunications and Informatics Gdansk University of Technology Narutowicza 11/12 pomorskie Gdansk80-233 Poland

With the rapid expansion of the construction industry, accidents on construction sites have been increasingly common. Among these, collapses of earthwork foundation pits are particularly significant due to the sheer weight of the collapsed materials and the vast affected areas, resulting in substantial casualties and economic losses. This study aims to determine the causes of these construction safety and collapse incidents and understand their relationships to enable effective supervision and prevention during construction. Initially, the LDA model is used to categorize historical construction safety accident reports, and text mining is applied utilizing R language platform and the TF-IDF measure to extract keywords related to accident causative factors from historical accident reports. Following this, risk factors are evaluated to find the basic, intermediate, and top events of the accident, constructing a fault tree of casualties from earthwork foundation pit collapse (EFPC) accidents and analyzing the structural significance of risk factors. The fault tree is converted into a Bayesian network through image and numerical mapping, allowing the analysis of node sensitivity and the prediction of top event probability for informed construction accident prediction and prevention. Lastly, the study constructs an ontology knowledge base and knowledge graph in the realm of building safety, and establishes an ontology reasoning model using the Pellet reasoning machine and SWRL reasoning rules. The novel approach in this study involves integrating multiple advanced methodologies and provides a comprehensive framework and knowledge foundation for enhancing construction accident prediction and prevention as well as understanding and mitigating the risk-causing factors of earthwork foundation pit collapses in the construction industry. © 2025 Elsevier Ltd

关键词： Construction industry

来源：评论

学校读者我要写书评

暂无评论

Towards Lightweight Super-Resolution with Dual Regression Learning

arXiv

引用

arXiv 2022年

作者： Guo, Yong Tan, Mingkui Deng, Zeshuai Wang, Jingdong Chen, Qi Cao, Jiezhang Xu, Yanwu Chen, Jian The School of Software Engineering South China University of Technology China The Max Planck Institute for Informatics Germany The Pazhou Laboratory Guangzhou China The Baidu Inc China The Faculty of Engineering The University of Adelaide Australia ETH Zürich Switzerland The School of Future Technology South China University of Technology China

Deep neural networks have exhibited remarkable performance in image super-resolution (SR) tasks by learning a mapping from low-resolution (LR) images to high-resolution (HR) images. However, the SR problem is typically an ill-posed problem and existing methods would come with several limitations. First, the possible mapping space of SR can be extremely large since there may exist many different HR images that can be super-resolved from the same LR image. As a result, it is hard to directly learn a promising SR mapping from such a large space. Second, it is often inevitable to develop very large models with extremely high computational cost to yield promising SR performance. In practice, one can use model compression techniques to obtain compact models by reducing model redundancy. Nevertheless, it is hard for existing model compression methods to accurately identify the redundant components due to the extremely large SR mapping space. To alleviate the first challenge, we propose a dual regression learning scheme to reduce the space of possible SR mappings. Specifically, in addition to the mapping from LR to HR images, we learn an additional dual regression mapping to estimate the downsampling kernel and reconstruct LR images. In this way, the dual mapping acts as a constraint to reduce the space of possible mappings. To address the second challenge, we propose a dual regression compression (DRC) method to reduce model redundancy in both layer-level and channel-level based on channel pruning. Specifically, we first develop a channel number search method that minimizes the dual regression loss to determine the redundancy of each layer. Given the searched channel numbers, we further exploit the dual regression manner to evaluate the importance of channels and prune the redundant ones. Extensive experiments show the effectiveness of our method in obtaining accurate and efficient SR models. Copyright © 2022, The Authors. All rights reserved.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

Agile Requirements Prioritization in Practice: Results of an Industrial Survey

引用

Procedia Computer Science 2020年 176卷 3446-3455页

作者： Aleksander Jarzębowicz Natalia Sitko Department of Software Engineering Faculty of Electronics Telecommunications and Informatics Gdańsk University of TechnologyGdańsk Poland

Agile software development stresses the importance of providing the customer with a product of a maximized business value. To achieve that, requirements prioritization is used. Agile development methods like Scrum define guidelines for prioritization, however practitioners do not necessarily have to follow them. Our goal was to investigate the industry practice related to requirements prioritization process, including its timing, participants, criteria used and prioritization techniques applied. We designed an on-line questionnaire (based on literature review) and conducted a survey involving practitioners from Polish IT industry. We received 69 valid responses indicating requirements prioritization practices in industrial Agile projects. We found out that despite the fact that business value is the most common criterion used to prioritize requirements, other criteria like complexity, stability and mutual interdependencies are considered as well. Other findings indicate that consideration of such multiple criteria requires different viewpoints, thus making requirements prioritization a process that has to involve many participants of different roles and competencies.

关键词： Agile Requirements engineering Requirements Prioritization Business Value Value-Based software engineering Survey

来源：评论

学校读者我要写书评

暂无评论

Enabling Human-Robot-Interaction for Remote Robotic Operation via Augmented Reality

Enabling Human-Robot-Interaction for Remote Robotic Operatio...

引用

IEEE International Symposium on World of Wireless Mobile and Multimedia Networks (WoWMoM)

作者： Chung Xue Yuansong Qiao Niall Murray Athlone Institute of Technology Ireland Software Research Institute Athlone Institute of Technology Faculty of Engineering & Informatics Athlone Ireland Computer & Software Engineering Faculty of Engineering & Informatics Athlone Institute of Technology Athlone Ireland

ISBN: (数字)9781728173740

ISBN: (纸本)9781728173757

Human-Robot Interaction (HRI) will be a crucial component of smart factories of the future (FoF). This demo presents a reliable and cost-effective HRI system based on Augmented Reality (AR). In this demonstration, we offer concepts and methods currently being developed to enable high-level human-robot collaboration and interaction. The user interaction and instructions are captured via AR and communicated to a Robot Operating System (ROS) powered robotic arm.

关键词： Manipulators Three-dimensional displays Augmented reality Human-robot interaction Task analysis Trajectory

来源：评论

学校读者我要写书评

暂无评论

An Efficient Liver Tumor Detection using Machine Learning

An Efficient Liver Tumor Detection using Machine Learning

引用

2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020

作者： Kalsoom, Anum Moin, Anam Maqsood, Muazzam Mehmood, Irfan Rho, Seungmin Comsats University Islamabad Department of Computer Science Pakistan University of Bradford Faculty of Engineering Informatics Department of Media Design and Technology United Kingdom Sejong University Department of Software Seoul Korea Republic of

ISBN: (纸本)9781728176246

Liver Cancer is among the most commonly diagnosed diseases in today's modern era. Liver tumor segmentation is a fundamental task to perform early diagnosis and recommend a treatment. Manual segmentation is the traditional approach to achieve the required results but it has always been a time-consuming process. There are some anomalies like ambiguous gray level color ranges similar to other neighboring organs, irregular tumor shapes, and various uneven tumor sizes which are overlooked. Due to these reasons, some semi-automated and even fully automated techniques have been put forward. However, the advancement of machine learning has been very accommodating for addressing this issue. In this paper, we propose an unsupervised machine learning technique combined with a supervised mechanism that accurately performs liver tumor segmentation. We perform clustering on our collected dataset and extract LBP features as well as HOG features from these clusters. Furthermore, we perform classification which is based on these extracted features using KNN. Furthermore, we have compared our results with two classifiers namely SVM and Ensemble to achieve a better understanding. Our proposed technique outperformed existing techniques and showed encouraging results when compared to other methods. © 2020 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

BERT based classification system for detecting rumours on Twitter

arXiv

引用

arXiv 2021年

作者： Anggrainingsih, Rini Hassan, Ghulam Mubashar Datta, Amitava Informatics Department of Mathematics and Natural Sciences Faculty Sebelas Maret University Surakarta Indonesia School of Computer Science and Software Engineering The University of Western Australia PerthWA Australia

The role of social media in opinion formation has far reaching implications in all spheres of society. Though social media provide platforms for expressing news and views, it is hard to control the quality of posts due to the sheer volumes of posts on platforms like Twitter and Facebook. Misinformation and rumours have lasting effects on society, as they tend to influence people's opinions and also may motivate people to act irrationally. It is therefore very important to detect and remove rumours from these platforms. The only way to prevent the spread of rumors is through automatic detection and classification of social media posts. Our focus in this paper is the Twitter social medium, as it is relatively easy to collect data from Twitter. The majority of previous studies used supervised learning approaches to classify rumours on Twitter. These approaches rely on feature extraction to obtain both content and context features from the text of tweets to distinguish rumours and non-rumours. Some researchers reported that tweets contain a linguistic pattern that can be used as a crucial features in identifying rumours on Twitter. Manually extracting features however is time consuming considering the volume of tweets. We propose a novel approach to deal with this problem by utilising sentence embedding using BERT to identify rumours on Twitter, rather than the usual feature extraction techniques. BERT is a novel transformer that can capture the contextual meaning of words. We use sentence embedding using BERT to represent each tweet's sentences into a vector according to the contextual meaning of the tweet. We classify those vectors into rumours or non-rumours by using various supervised learning techniques. Our BERT based models improved the accuracy by approximately 10% as compared to previous methods. Our best model uses a multi-layer perceptron and achieves 0.869 accuracy, 0.855 precision, 0.848 recall and 0.852 F1 score. Copyright © 2021, The Authors. All rights r

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

An Activity Recognition Framework for Overlapping Activities using Transfer Learning

An Activity Recognition Framework for Overlapping Activities...

引用

2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020

作者： Bilal, Muhammad Maqsood, Muazzam Mehmood, Irfan Javaid, Mubashir Rho, Seungmin Comsats University Islamabad Department of Computer Science Pakistan University of Bradford Faculty of Engineering Informatics Department of Media Design and Technology United Kingdom Sejong University Department of Software Seoul Korea Republic of

ISBN: (纸本)9781728176246

Activity recognition is gaining popularity with the increase in digital content. In video data, there is a lot of information hidden that needs to be explored. Human Activity Recognition (HAR) in video streams applies to many areas, such as video surveillance, patient health monitoring, and behavior analytics. Variation in the environment, view-point changes, occlusion, and illumination are some main challenges in HAR. Among other challenges, there is also a similar activity or overlapping activity issue that has not been explored much in past. Resolving overlapping activities classes issues can be a major contribution to overall Human Activity Recognition. Hand-crafted methods and traditional Machine Learning methods were extensively explored in past. Recently, many Deep Learning-based methods are achieved high accuracy. Convolutional Neural Network (CNN) and 3D CNN methods outperform other methods. In this paper, we proposed a Transfer Learning-based Human Activity Recognition (TLHAR) for video data streams. We used VGG16 and InceptionV3, two pre-trained CNN models, and utilized their prior training knowledge for efficient activity recognition. The purposed system outperformed existing activity recognition methods and showed state-of-the-art accuracy and less computational cost requirements than other techniques by taking the benefits of Transfer Learning. © 2020 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

An Improved Hybrid Approach for the Simultaneous Allocation of Dg Units and Tvvd Loads in Distribution Systems

SSRN

引用

SSRN 2022年

作者： Khan, Muhammad Faisal Nadeem Ahmed, Ali Kiani, Arooj Tariq Ullah, Nasim Khan, Muhammad Adnan Mosavi, Amir Department of Electrical Engineering University of Engineering and Technology Taxila Taxila47080 Pakistan Department of Electrical Engineering Air University Islamabad Islamabad44230 Pakistan Department of Electrical Engineering College of Engineering Taif University al-Hawiyah26571 Saudi Arabia Department of Software Gachon University Seongnam Korea Republic of Institute of Information Engineering Automation and Mathematics Slovak University of Technology Bratislava Slovakia John von Neumann Faculty of Informatics Obuda University Budapest Hungary Faculty of Civil Engineering TU-Dresden Dresden Germany

Distributed Generation (DG) studies are generally conducted considering a single type of DG units integrated with the Distribution System (DS). However, these studies may not evaluate optimum benefits offered by the DG integration. This paper presents a novel framework for individual and simultaneous allocation of different types of DG units in DS while considering varying load demand and probabilistic generation of DG units. A Salp Swarm Algorithm (SSA) and Particle Swarm Optimization (PSO) based new hybrid method that utilizes a single controlling parameter is proposed for simultaneous allocation of DG units, aiming to minimize a multi-objective index. The strength of the proposed SSA-PSO hybrid approach is validated on seventeen benchmark functions and the performance of the novel framework for optimal allocation of DG units is validated through implementation on the IEEE 69-bus system. The results demonstrate that the proposed hybrid approach performs better as compared to other meta-heuristics techniques. Moreover, simultaneous allocation significantly reduces the multi-objective index as compared to individual DG units’ integration. © 2022, The Authors. All rights reserved.

关键词： Distributed power generation

来源：评论

学校读者我要写书评

暂无评论

TIMED AUTOMATA ROBUSTNESS ANALYSIS VIA MODEL CHECKING

arXiv

引用

arXiv 2021年

作者： Bendík, Jaroslav Sencan, Ahmet Gol, Ebru Aydin Černá, Ivana Max Planck Institute for Software Systems Kaiserslautern Germany Department of Computer Engineering Middle East Technical University Ankara Turkey Faculty of Informatics Masaryk University Brno Czech Republic

Timed automata (TA) have been widely adopted as a suitable formalism to model time-critical systems. Furthermore, contemporary model-checking tools allow the designer to check whether a TA complies with a system specification. However, the exact timing constants are often uncertain during the design phase. Consequently, the designer is often able to build a TA with a correct structure, however, the timing constants need to be tuned to satisfy the specification. Moreover, even if the TA initially satisfies the specification, it can be the case that just a slight perturbation during the implementation causes a violation of the specification. Unfortunately, model-checking tools are usually not able to provide any reasonable guidance on how to fix the model in such situations. In this paper, we propose several concepts and techniques to cope with the above mentioned design phase issues when dealing with reachability and safety specifications. © 2021, CC BY.

关键词： Specifications

来源：评论

学校读者我要写书评

暂无评论

A Toolbox of Feminist Wonder: Theories and methods that can make a difference 26

A Toolbox of Feminist Wonder: Theories and methods that can ...

引用

26th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2023

作者： Hansson, Karin Bardzell, Shaowen Bhandari, Aparajita Boulicault, Marion Doyle, Dylan Thomas Erete, Sheena Cerratto Pargman, Teresa Lazem, Shaimaa Muller, Michael Normark, Maria Petterson, Adrian Rosén, Anton Poikolainen Taylor, Alex S. Thomas, Jakita O. Watson, Julia Södertörn University The School of Natural Sciences Technology and Environmental Studies Sweden Georgia Institute of Technology The School of Interactive Computing United States Cornell University Department of Communication United States University of Edinburgh Department of Philosophy United States University of Colorado Boulder Department of Information Science United States University of Maryland College of Information United States Stockholm University The Department of Computer and Systems Sciences Sweden City for Scientific Research and Technological Applications The Informatics Research Institute Egypt Ibm Research Human Centered Ai United States Uppsala University Department of Informatics and Media Sweden University of Toronto Faculty of Information Canada Aalto University The School of Arts Design and Architecture Finland City University of London The Centre for Human Computer Interaction Design United Kingdom Auburn University Department of Computer Science and Software Engineering United States University of Toronto Department of Computer Science Canada

ISBN: (纸本)9798400701290

This one-day hybrid workshop builds on previous feminist CSCW workshops to explore feminist theoretical and methodological approaches that have provided us with useful tools to see things differently and make space for change. Since its inception over a decade ago, feminist HCI has progressed from the margins to mainstream HCI, with numerous references in the literature. Feminist HCI has also evolved to incorporate other critical HCI practices such as Queer HCI, participatory design, and speculative design. While feminist approaches have grown in popularity and become mainstream, it is getting more difficult to distinguish the feminist emancipatory core from other attempts of developing and improving society in various ways. In this workshop, we therefore want to revisit our feminist roots, where theory is a liberatory and creative practice, motivated by affect, curiosity, and wonder. From this standpoint, we consider which of our feminist tools can make a significant difference today, in a highly datafied world. The goal of this workshop is to;1) create an inventory of feminist theories and concepts that have had an impact on our work as designers, educators, researchers, and activists;2) develop a feminist toolbox for the CSCW community to strengthen our feminist literacy. © 2023 Owner/Author.

关键词： Computation theory

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：