Article
Computer Science, Information Systems
Kashif Mehboob Khan, Junaid Arshad, Waheed Iqbal, Sidrah Abdullah, Hassan Zaib
Summary: This paper introduces a blockchain-based distributed infrastructure for achieving immutable and trustworthy SLA monitoring within cloud services. An in-depth empirical investigation is carried out for the scalability of the system to address the challenge of transparently enforcing real-time monitoring, leading to increased service transparency and credibility.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Article
Chemistry, Analytical
Yustus Eko Oktian, Thi-Thu-Huong Le, Uk Jo, Howon Kim
Summary: This paper proposes a solution to network congestion and real-time pricing using software-defined networks and blockchain technology. By implementing real-time pricing and utilizing the verification and transparency of blockchain, it reduces network congestion and ensures fairness and trustability.
Article
Computer Science, Artificial Intelligence
Fahim Ullah, Fadi Al-Turjman
Summary: Blockchain-based smart contracts are transforming the smart real estate sector in smart cities. This study explores the literature on blockchain smart contracts in smart real estate and proposes a conceptual framework for their adoption in smart cities. Through a systematic review of literature published between 2000 and 2020, ten key aspects of blockchain smart contracts are identified and organized into six layers. The study presents a decentralized application and its interactions with Ethereum Virtual Machine (EVM), along with a detailed design and interaction mechanism for real estate owners and users as parties to a smart contract. It also provides a stepwise procedure for establishing and terminating smart contracts, along with a list of functions for initiating, creating, modifying, or terminating a smart contract. The study has the potential to enhance the contracting process for users and create new business opportunities for real estate owners, property technologies companies, and real estate agents.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Wei-Chen Wu, Chit-Jie Chew, Ying-Chin Chen, Cheng-Han Wu, Tzu Hao Chen, Jung-San Lee
Summary: The utilization of cloud and edge computing has become a popular resource supply mechanism. However, traditional allocation architectures suffer from issues such as centralization, data security, and lack of trust. To address these problems, a real-time decentralized computing resource allocation platform based on blockchain and smart contract is designed.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2022)
Article
Chemistry, Analytical
Joonseok Park, Sumin Jeong, Keunhyuk Yeom
Summary: In this paper, a smart contract broker is proposed to enhance the reusability of smart contracts in a blockchain environment. The lack of a standardized approach for sharing and managing smart contracts on current blockchain platforms impedes developers' ability to reuse them, leading to inefficiency. The proposed smart contract broker utilizes tags to identify and organize smart contracts, offering a platform for comparison and reuse. Consequently, this improves smart contract reusability and overall efficiency. The suggested smart contract broker can serve as a reference model to enhance the flexibility and reusability of smart contract management in a blockchain environment.
Article
Information Science & Library Science
Arthur Carvalho, Jeffrey W. Merhout, Yogesh Kadiyala, John Bentley
Summary: Blockchain is praised for its ability to enable self-interested entities to share data without intermediaries. However, the decentralized nature of blockchain poses governance challenges when erroneous or malicious data are added. Solutions such as rollback, do nothing, and overturn have been adopted in public cases, providing insights for organizations considering blockchain technology for enterprise-level applications.
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT
(2021)
Article
Engineering, Electrical & Electronic
Peilin Zheng, Quanqing Xu, Zibin Zheng, Zhiyuan Zhou, Ying Yan, Hui Zhang
Summary: This article introduces a systematic study on sharded consortium blockchain, proposing a solution called Meepo to improve cross-shard efficiency through cross-epoch and cross-call strategies. It also designs a partial cross-call merging strategy to handle multi-state dependency in contract calls, and employs replay-epoch and shadow shard based recovery algorithm to ensure strict transaction atomicity and enhance shard robustness. In performance testing, Meepo demonstrates high throughput in cross-shard transactions.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Lejun Zhang, Zhijie Zhang, Weizheng Wang, Zilong Jin, Yansen Su, Huiling Chen
Summary: The combined covert communication model using smart contracts in the blockchain environment improves the concealment and security of communication, providing a tamper-resistant and low complexity solution.
IEEE SYSTEMS JOURNAL
(2022)
Article
Mathematics
Liehuang Zhu, Jiaqi Zhang, Can Zhang, Feng Gao, Zhuo Chen, Zhen Li
Summary: Reporting helps combat illegal activities and protecting the whistleblower's privacy is crucial. Existing blockchain-based anonymous reporting solutions address the issue of insufficient anonymity but not the problem of hiding the reporting behavior. This paper proposes an anonymous and covert reporting scheme and rewarding mechanism based on blockchain, ensuring both privacy and covertness.
Article
Computer Science, Information Systems
Daojing He, Rui Wu, Xinji Li, Sammy Chan, Mohsen Guizani
Summary: This article introduces common security vulnerabilities in blockchain smart contracts and classifies the detection tools into six categories, including formal verification, symbolic execution, fuzzy testing, intermediate representation, state analysis, and deep learning methods. The authors tested 27 detection tools and concluded that most of them only detect vulnerabilities in a single and old version of smart contracts. Although fewer types of vulnerabilities are detected, the deep learning method has higher accuracy and efficiency. Therefore, combining static detection methods like deep learning with dynamic methods like fuzzy testing to detect more types of vulnerabilities in multi-version smart contracts is a future research direction.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Automation & Control Systems
Peng Zhuang, Talha Zamir, Hao Liang
Summary: Blockchain technology, as an immutable distributed ledger, has garnered significant interest in the application of cybersecurity in the smart grid. Despite efforts to utilize blockchain in enhancing smart grid cybersecurity, a comprehensive survey on its application and technological aspects is lacking. This survey aims to provide insights on the latest ideas, architectures, and implementation techniques relevant to blockchain application in smart grid cybersecurity.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Green & Sustainable Science & Technology
Benoit Couraud, Valentin Robu, David Flynn, Merlinda Andoni, Sonam Norbu, Honorat Quinard
Summary: This paper proposes a framework for distributed residential battery aggregation, which places bids on wholesale energy markets in real time using a control algorithm. The results show that this approach significantly increases revenues and improves self-consumption for households.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Computer Science, Information Systems
Rini Handayani, Anak Agung Gde Agung
Summary: The concept of a smart grid has been proposed to ensure efficient distribution of electricity and secure transactions. This paper suggests using blockchain technology to manage transactions in the smart grid, providing security and immutability.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Hardware & Architecture
Rawya Mars, Saoussen Cheikhrouhou, Slim Kallel, Ahmed Hadj Kacem
Summary: This paper presents a systematic literature review of different approaches to smart contract generation and compares them based on automation paradigm and defined criteria. The paper also identifies gaps and potential challenges in the literature, strengthening the existing work. The study shows that existing works mainly focus on limited features such as authorization, asset control, and security, with inadequate attention to formal verification of smart contracts and data privacy.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Mercedes Rodriguez-Garcia, Miguel-Angel Sicilia, Juan Manuel Dodero
Summary: Sharing patient datasets curated by health institutions is critical for monitoring, surveillance and research, but privacy preserving data sharing techniques can minimize the risk of identification of patients. Blockchain technologies provide an opportunity to gather data consumers' requests and share and assemble datasets using privacy-preserving methods.
PEERJ COMPUTER SCIENCE
(2021)
Article
Computer Science, Interdisciplinary Applications
Zhaojing Wang, Hao Hu
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2017)
Article
Construction & Building Technology
Zhaojing Wang, Hao Hu, Jie Gong
AUTOMATION IN CONSTRUCTION
(2018)
Article
Engineering, Industrial
Zhaojing Wang, Hao Hu
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2018)
Article
Green & Sustainable Science & Technology
Zhaojing Wang, Hao Hu, Jie Gong
JOURNAL OF CLEANER PRODUCTION
(2018)
Article
Computer Science, Interdisciplinary Applications
Zhaojing Wang, Hao Hu, Mengyang Guo, Jie Gong
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2019)
Article
Construction & Building Technology
Zhaojing Wang, Hao Hu, Jie Gong
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2018)
Article
Engineering, Industrial
Zhaojing Wang, Hao Hu, Jie Gong, Xiaoping Ma
JOURNAL OF MANUFACTURING SYSTEMS
(2018)
Review
Green & Sustainable Science & Technology
Zhaojing Wang, Hao Hu, Jie Gong, Xiaoping Ma, Wuyue Xiong
JOURNAL OF CLEANER PRODUCTION
(2019)
Article
Green & Sustainable Science & Technology
Qingxue Liang, Hao Hu, Zhaojing Wang, Feng Hou
JOURNAL OF CLEANER PRODUCTION
(2019)
Article
Environmental Studies
Lei Dai, Hao Hu, Zhaojing Wang, Yifan Shi, Wenyi Ding
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2019)
Article
Construction & Building Technology
Zhaojing Wang, Yisheng Liu, Hao Hu, Lei Dai
Summary: The study introduces a hybrid rescheduling optimization model for precast production to minimize costs and ensure on-time delivery, optimized through genetic algorithm considering idle time of production lines and other factors, and verified the feasibility of potential reschedules in a real-world setting.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2021)
Article
Engineering, Industrial
Zhaojing Wang, Limin Jia, Xiaoping Ma, Xuehui Sun, Qianxue Tang, Sina Qian
Summary: This paper models the high-speed railway as a three-layer network and evaluates its integrated performance from the view of transportation accessibility. The prioritization of rail stations and comparison of their performances in different layers are conducted to analyze the limitations on the total integrated performance. A case study is conducted to verify the feasibility and superiority of the model. The findings provide management implications for rail transportation planning, organization, and operations.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Computer Science, Interdisciplinary Applications
Zhaojing Wang, Hao Hu, Wei Zhou
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2017)
Article
Construction & Building Technology
Jia Liang, Qipeng Zhang, Xingyu Gu
Summary: A lightweight PCSNet-based segmentation model is developed to address the issues of insufficient performance in feature extraction and boundary loss information. The introduction of generalized Dice loss improves prediction performance, and the visualization of class activation mapping enhances model interpretability.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Gilsu Jeong, Minhyuk Jung, Seongeun Park, Moonseo Park, Changbum Ryan Ahn
Summary: This study introduces a contextual audio-visual approach to recognize multi-equipment activities in tunnel construction sites, improving monitoring effectiveness. Tested against real-world operation data, the model achieved remarkable results, emphasizing the potential of contextual multimodal models in enhancing operational efficiency in complex construction sites.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Jin Wang, Zhigao Zeng, Pradip Kumar Sharma, Osama Alfarraj, Amr Tolba, Jianming Zhang, Lei Wang
Summary: This study presents a dual-path network for pavement crack segmentation, combining Convolutional Neural Network (CNN) and transformer. A lightweight CNN encoder is used for local feature extraction, while a novel transformer encoder integrates high-low frequency attention mechanism and efficient feedforward network for global feature extraction. Additionally, a complementary fusion module is introduced to aggregate intermediate features extracted from both encoders. Evaluation on three datasets confirms the superior performance of the proposed network.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Pierre Gilibert, Romain Mesnil, Olivier Baverel
Summary: This paper introduces a flexible method for crafting 2D assemblies adaptable to various geometric assumptions in the realm of sustainable construction. By utilizing digital fabrication technologies and optimization approaches, precise control over demountable buildings can be achieved, improving mechanical performance and sustainability.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Jorge Loy-Benitez, Myung Kyu Song, Yo-Hyun Choi, Je-Kyum Lee, Sean Seungwon Lee
Summary: This paper discusses the advancement of tunnel boring machines (TBM) through the application of artificial intelligence. It highlights the significance of AI-based management subsystems for automatic TBM operations and presents recent contributions in this field. The paper evaluates modeling, monitoring, and control subsystems and suggests research paths for integrating existing management subsystems into TBM automation.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Alireza Shamshiri, Kyeong Rok Ryu, June Young Park
Summary: This paper reviews the application of text mining and natural language processing in the construction field, highlighting the need for automation and minimizing manual tasks. The study identifies potential research opportunities in strengthening overlooked construction aspects, coupling diverse data formats, and leveraging pre-trained language models and reinforcement learning.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zhengyi Chen, Hao Wang, Keyu Chen, Changhao Song, Xiao Zhang, Boyu Wang, Jack C. P. Cheng
Summary: This study proposes an improved coverage path planning system that leverages building information modeling and robotic configurations to optimize coverage performance in indoor environments. Experimental validation shows the effectiveness and applicability of the system. Future research will focus on further enhancing coverage ratio and optimizing computation time.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Yonglin Fu, Junjie Chen, Weisheng Lu
Summary: This study presents a review of human-robot collaboration (HRC) in modular construction manufacturing (MCM), focusing on tasks, human roles, and interaction levels. The review found that HRC solutions are applicable to various MCM tasks, with a primary focus on timber component production. It also revealed the diverse collaborative roles humans can play and the varying levels of interaction with robots.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Qiong Liu, Shengbo Cheng, Chang Sun, Kailun Chen, Wengui Li, Vivian W. Y. Tam
Summary: This paper presents an approach to enhance the path-following capability of concrete printing by integrating steel cables into the printed mortar strips, and validates the feasibility and effectiveness of this approach through experiments.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Honghu Chu, Lu Deng, Huaqing Yuan, Lizhi Long, Jingjing Guo
Summary: The study proposes a method called Cascade CATransUNet for high-resolution crack image segmentation. This method combines the coordinate attention mechanism and self-cascaded design to accurately segment cracks. Through a customized feature extraction architecture and an optimized boundary loss function, the proposed method achieves impressive segmentation performance on HR images and demonstrates its practicality in UAV crack detection tasks.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Daniel Lamas, Andres Justo, Mario Soilan, Belen Riveiro
Summary: This paper introduces a new method for creating synthetic point clouds of truss bridges and demonstrates the effectiveness of a deep learning approach for semantic and instance segmentation of these point clouds. The proposed methodology has significant implications for the development of automated inspection and monitoring systems for truss bridges.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Kahyun Jeon, Ghang Lee, Seongmin Yang, Yonghan Kim, Seungah Suh
Summary: This study proposes two enhanced unsupervised text classification methods for domain-specific non-English text. The results of the tests show that these methods achieve excellent performance on Korean building defect complaints, outperforming state-of-the-art zero-shot and few-shot text classification methods, with minimal data preparation effort and computing resources.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Yoonhwa Jung, Julia Hockenmaier, Mani Golparvar-Fard
Summary: This study introduces a transformer-based natural language processing model, UNIfORMATBRIDGE, that automatically labels activities in a project schedule with Uniformat classification. Experimental results show that the model performs well in matching unstructured schedule data to Uniformat classifications. Additionally, the study highlights the importance of this method in developing new techniques.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi, Keivan Bamdad, Tosin Famakinwa
Summary: This paper introduces a digital twin technology combining Building Information Modelling and the Internet of Things for the construction industry, aiming to optimize building conditions. The technology is implemented in a university library, successfully achieving real-time data capture and visual representation of internal conditions.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zaolin Pan, Yantao Yu
Summary: The construction industry faces safety and workforce shortages globally, and worker-robot collaboration is seen as a solution. However, robots face challenges in recognizing worker intentions in construction. This study tackles these challenges by proposing a fusion method and investigating the best granularity for recognizing worker intentions. The results show that the proposed method can recognize multi-granular worker intentions effectively, contributing to seamless worker-robot collaboration in construction.
AUTOMATION IN CONSTRUCTION
(2024)