Article
Environmental Sciences
Huaqiao Xing, Haihang Wang, Jinhua Zhang, Dongyang Hou
Summary: Land cover change has significant impacts on global climate change, energy cycle, carbon cycle, and water cycle, affecting human well-being. Web service-based online change detection applications have been developed for monitoring land cover change. However, the integration and sharing of services in the land cover domain have been overlooked, making it difficult for end-users to access LCC information in a timely manner.
Article
Computer Science, Artificial Intelligence
Roaa ElGhondakly, Sherin M. Moussa, Nagwa Badr
Summary: As service-oriented computing systems become more complex, fault prediction plays a crucial role in reducing testing cost and increasing the reliability of service compositions. This paper proposes a multilateral fault prediction and localization approach using deep learning techniques for web service compositions testing. The approach not only predicts faulty services, but also their count and severity, location of faults, and time of occurrence. Experimental analysis shows that the hybrid CNN_RNN model achieves higher accuracy and lower mean square error compared to the individual CNN and RNN models.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Information Systems
Yu Liang, Jidong Ge, Sheng Zhang, Jie Wu, Lingwei Pan, Tengfei Zhang, Bin Luo
Summary: The article discusses the key issues of distributed interactive applications, solves the shortcomings of traditional solutions through edge computing, and proposes an efficient service entity placement algorithm GPA. Through simulation evaluation, it is found that GPA is close to the optimal algorithm and generally outperforms the baseline algorithm.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2021)
Editorial Material
Computer Science, Theory & Methods
Sami Yangui, Andrzej Goscinski, Khalil Drira, Zahir Tari, Djamal Benslimane
Summary: Service-Oriented Computing (SOC) and SOC systems have been developed to address problems such as heterogeneity and poor latency, and have been widely applied across various fields. The increasing interconnectivity provided by wireless networks, along with the need for modularization and standardization, have led to a surge in research, development, and deployment of SOC systems. The future generation of SOC systems will need to focus on advanced research results to solve open research problems and have a significant impact on the field.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Computer Science, Information Systems
Soheila Sadeghiram, Hui Ma, Gang Chen
Summary: Web Service Composition (WSC) allows for effective reuse of services and added value, but current methods neglect the impact of data communication and service distribution on performance. Our proposed priority-based local search selection method for Distributed Data-intensive Web Service Composition (DDWSC) overcomes this issue and outperforms recent methods.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Information Systems
Chao Wang, Lei Gong, Xi Li, Qi Yu, Aili Wang, Patrick Hung, Xuehai Zhou
Summary: This paper introduces a services-oriented deep learning architecture, SOLAR, which utilizes various accelerators such as GPU and FPGA to improve performance. SOLAR provides a uniform programming model and leverages multi-target design space exploration to balance performance, power, energy, and efficiency.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2021)
Article
Biochemistry & Molecular Biology
Rodrigo Honorato, Panagiotis Koukos, Brian Jimenez-Garcia, Andrei Tsaregorodtsev, Marco Verlato, Andrea Giachetti, Antonio Rosato, Alexandre M. J. J. Bonvin
Summary: Structural biology focuses on studying the structural and dynamic properties of biological macromolecules at atomic level, which is crucial for understanding cellular processes and has applications in health and food sciences. The WeNMR project has provided web-based services and high throughput computing infrastructure to over 23,000 users worldwide for 10 years, facilitating complex workflows in structural biology research.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2021)
Article
Education & Educational Research
Julian Monsalve-Pulido, Jose Aguilar, Edwin Montoya
Summary: This paper presents a framework for adapting educational organizations to SOA, using the case study of an autonomous recommendation system. The framework includes a business model, organizational IT governance components, and a self-management process to achieve adaptation to the service architecture in educational organizations.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Review
Computer Science, Information Systems
Marcelo Fantinato, Sarajane Marques Peres, Eleanna Kafeza, Dickson K. W. Chiu, Patrick C. K. Hung
Summary: In recent years, machine learning and deep learning technologies have been widely used in data processing and analysis, providing valuable insights for businesses and policymakers. The current trends in information and communication technology are accelerating the widespread adoption of web services, supporting the development of service-oriented architecture (SOA).
JOURNAL OF DATABASE MANAGEMENT
(2021)
Article
Green & Sustainable Science & Technology
Daniel Amo, Sandra Cea, Nicole Marie Jimenez, Pablo Gomez, David Fonseca
Summary: Educational institutions are transferring analytics computing to the cloud to reduce costs, but privacy concerns are involved. A study provides tools for local educational data analysis and validates visualizations, while emphasizing the feasibility of local data analysis.
Review
Computer Science, Software Engineering
Mohammadreza Razian, Mohammad Fathian, Rami Bahsoon, Adel N. Toosi, Rajkumar Buyya
Summary: This paper presents a systematic literature review on service composition under uncertainty. It identifies and classifies existing studies, discusses trends and future research directions in this field.
JOURNAL OF SYSTEMS AND SOFTWARE
(2022)
Article
Computer Science, Information Systems
Alessandro Tundo, Marco Mobilio, Oliviero Riganelli, Leonardo Mariani
Summary: Continuous monitoring of cloud services is crucial for timely detection, compensation, and resolution of misbehaviors. Existing monitoring frameworks lack automation capabilities to easily and quickly adapt monitoring probes for dynamic cloud systems. This article presents a Monitoring-as-a-Service framework that automatically deploys and undeploys arbitrary probes based on user-defined indicators, effectively managing the lifecycle of probes and resolving deployment errors.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Information Systems
Johirul Islam, Tanesh Kumar, Ivana Kovacevic, Erkki Harjula
Summary: Edge Computing is a novel computing paradigm that moves server resources closer to end-devices, particularly important in the context of IoT. A three-tier IoT Edge architecture and virtual decentralized service platform based on nanoservices have been proposed for efficient and localized IoT services. A prototype implementation on the Raspberry Pi platform has shown that containerized deployment is more resource-efficient.
Article
Computer Science, Information Systems
Marco Pau, Markus Mirz, Jan Dinkelbach, Padraic Mckeever, Ferdinanda Ponci, Antonello Monti
Summary: Modern distribution grids require advanced management methods for secure and reliable operation. The Information and Communication Technology domain offers opportunities for smart design tools for grid operators. The modular architecture of microservices implemented via container technology enables intelligent deployment in Distribution Management Systems and opens up various possibilities.
Article
Operations Research & Management Science
Mohd Hilmi Hasan, Jafreezal Jaafar, Junzo Watada, Mohd Fadzil Hassan, Izzatdin Abdul Aziz
Summary: The paper proposes an interval type-2 fuzzy model for QoWS compliance monitoring, which is more effective in reducing the impact of uncertainties and can accurately perform compliance monitoring. The model is developed using the fuzzy C-means algorithm and optimized the number of clusters using a clustering validity index, further improving the accuracy of monitoring results.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Yo-Ming Hsieh, Mao-Sen Pan
ADVANCES IN ENGINEERING SOFTWARE
(2014)
Article
Construction & Building Technology
Yo-Ming Hsieh, Ya-Sue Lu
AUTOMATION IN CONSTRUCTION
(2012)
Article
Construction & Building Technology
Yo-Ming Hsieh, Yen-How Chen
AUTOMATION IN CONSTRUCTION
(2012)
Article
Engineering, Geological
Yo-Ming Hsieh, Hung-Hui Li, Tsan-Hwei Huang, Fu-Shu Jeng
ENGINEERING GEOLOGY
(2008)
Article
Engineering, Geological
Yo-Ming Hsieh, Kuo-Chen Lee, Fu-Shu Jeng, Tsan-Hwei Huang
ENGINEERING GEOLOGY
(2011)
Article
Engineering, Geological
M. C. Weng, F. S. Jeng, Y. M. Hsieh, T. H. Huang
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
(2008)
Article
Engineering, Geological
L. S. Tsai, Y. M. Hsieh, M. C. Weng, T. H. Huang, F. S. Jeng
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
(2008)
Article
Engineering, Geological
M. C. Weng, L. S. Tsai, Y. M. Hsieh, F. S. Jeng
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
(2010)
Article
Construction & Building Technology
I-Tung Yang, Yo-Ming Hsieh, Li-Ou Kung
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2012)
Article
Engineering, Multidisciplinary
Meng-Chia Weng, Fu-Shu Jeng, Li-Sheng Tsai, Yo-Ming Hsieh
JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS
(2010)
Article
Engineering, Geological
YM Hsieh, AJ Whittle, HS Yu
JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING
(2002)
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)
