Article
Engineering, Industrial
Chunguang Bai, Qingyun Zhu, Joseph Sarkis
Summary: Blockchain technology plays a key role in supply chain management, but selecting and evaluating the right blockchain platform is a complex process. Effective adoption and operation of blockchain require consideration of multiple vendors, service providers, and platforms to meet the needs of various users and stakeholders.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Article
Engineering, Multidisciplinary
Maliheh Haghgoo, Alberto Dognini, Antonello Monti
Summary: This article discusses the feasibility of using cloud computing and ontology combined with semantic web technology in modern distribution grids. It demonstrates how semantic information integration can support efficient data exchange and sharing, as well as advanced analytics and mining in smart energy applications. The proposed solution shows promising platform performances and provides insights for future deployments in smart energy platforms.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Anurina Tarafdar, Kamalesh Karmakar, Rajib K. Das, Sunirmal Khatua
Summary: This paper proposes a novel workflow scheduling approach for the Workflow as a Service (WaaS) platform, which reduces the average makespan of the workflows, improves energy efficiency, and reduces the resource renting cost of the Cloud resources. The scheduling model includes containers, virtual machines (VMs), and hosts, and a suitable scaling policy is proposed to improve resource utilization. Extensive simulations with real-world workflows and comparison with state-of-the-art algorithms demonstrate the efficacy of the approach in improving performance, energy efficiency, and reducing monetary cost.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Computer Science, Information Systems
Pavlos Charalampidis, Antonis Makrogiannakis, Nikolaos Karamolegkos, Stefanos Papadakis, Yannis Charalambakis, George Kamaratakis, Alexandros Fragkiadakis
Summary: The Internet of Things (IoT) is an emerging technology that connects a large number of smart objects to create ubiquitous networks, enabling various data-driven applications. In this work, a flexible platform is presented that offers cloud-based compilation and firmware over-the-air update functionalities for IoT devices. The system supports multiple embedded operating systems and hardware platforms, and a performance evaluation of a Proof-of-Concept deployment is conducted.
INTERNET OF THINGS
(2022)
Article
Multidisciplinary Sciences
Neven Saleh, Mohamed N. Gaber, Mohamed A. Eldosoky, Ahmed M. Soliman
Summary: The purchase of medical equipment requires proper planning, and selecting the most appropriate vendor is crucial for time, effort, and expense considerations. This study aims to choose the best vendor based on ECRI standards using the MOORA, SAW, and TOPSIS methods. The criteria for selection are categorized into general, technical, and financial aspects, and weighted using CRITIC, entropy, and expert judgment. A Vendor Evaluation Program for Medical Equipment (VEPME) is developed to automate the vendor selection process. The program is tested with medical imaging equipment, and the entropy-TOPSIS method is found to be the most effective. The results validate the robustness of the proposed methodology by comparing it to expert judgment.
SCIENTIFIC REPORTS
(2023)
Article
Business
Yu Xu, Simon Hazee, Kevin Kam Fung So, K. Daisy Li, Edward Carl Malthouse
Summary: Drawing upon the literature on ecosystem ecology and socio-cultural evolution, this study proposes an evolutionary framework to understand the dynamics of service platform ecosystems, identifying key components and an evolutionary model, as well as discussing directions for future research in the sharing economy.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Computer Science, Information Systems
Wen-Chung Shih, Chao-Tung Yang, Rajiv Ranjan, Chun- Chiang
Summary: This study investigates the performance evaluation of bare-metal, Docker containers, and virtual machines in virtualized environments, as well as the implementation of a container management platform. The results suggest that container-based virtualization may solve the issues associated with traditional virtualization and save significant time.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Erika Schneider, Erick M. Remer, Nancy A. Obuchowski, Charles A. McKenzie, Xiaobo Ding, Sankar D. Navaneethan
Summary: This study demonstrated good linearity, accuracy, and reproducibility for all investigated manufacturers and field strengths. However, significant vendor-dependent and field strength-dependent bias were found.
EUROPEAN RADIOLOGY
(2021)
Article
Economics
Rong Fan, Xuegang (Jeff) Ban
Summary: This paper proposes and investigates the concept of a commuting service platform (CSP) that connects commuters and worksites through emerging mobility services. By analyzing the conditions for its two-sidedness, the paper explores the impact of price allocation on the participation and profit of CSPs. It also presents a modeling framework that considers the locations of homes and worksites. The findings of this paper have practical implications for building CSPs and developing CSP-based travel demand management strategies.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Economics
Oksana Loginova, X. Henry Wang
Summary: A platform owner offers product A. A third-party firm develops a complementary product B, which creates additional value when consumed together. Access to the platform owner's customer base can expand the third-party firm's market reach. The quality of the third-party firm's product is chosen first, followed by simultaneous price-setting by the platform owner and the third-party firm. We find that higher product complementarity incentivizes the third-party firm to increase its product quality, but access to the platform may result in either higher or lower quality.
MANAGERIAL AND DECISION ECONOMICS
(2023)
Article
Geography, Physical
Dimitrios Bolkas, Gabriel Walton, Ryan Kromer, Timothy Sichler
Summary: This study presents an automated registration algorithm based on edge detection for multi-platform and multi-epoch point clouds, which offers high accuracy and reliability for geotechnical monitoring programs.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Computer Science, Information Systems
Qiushi Bai, Sadeem Alsudais, Chen Li
Summary: This paper introduces QueryBooster, a system that supports SQL query rewriting as a cloud service. It provides a powerful and user-friendly Web interface for users to rewrite queries using language rules or example query pairs. Multiple users can share rewriting knowledge and automatically receive suggestions for shared rewriting rules. The system does not require any modifications or plugin installations to applications or databases.
PROCEEDINGS OF THE VLDB ENDOWMENT
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Rajeev Nowrangi, Laurie A. Perry, Jennifer Regan, David Hulefeld, Sarah O'Brien, Timothy J. OConnor, Alexander J. Towbin
Summary: Transferring medical imaging studies between different institutions is a common practice in today's medical field. The traditional method of using physical media and human couriers for image transfer is slow, unreliable, and outdated. To overcome these issues, various electronic, cloud-based solutions have been developed by image-sharing vendors. However, a new challenge arises in the difficulty of sending or receiving images across different image-sharing platforms. This study presents a solution that allows for image sharing across multiple vendor platforms.
JOURNAL OF DIGITAL IMAGING
(2022)
Article
Computer Science, Theory & Methods
Jorge Pereira, Thais Batista, Everton Cavalcante, Arthur Souza, Frederico Lopes, Nelio Cacho
Summary: Developing smart city applications faces challenges like meeting complex requirements, integrating data sources, and considering geographical information. Despite many platforms available, most do not associate services with geographical information, do not support semantic queries, and have limitations.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Review
Computer Science, Theory & Methods
Sebastiao Pais, Joao Cordeiro, M. Luqman Jamil
Summary: This paper surveys the use of NLP in cloud computing, focusing on comparing cloud-based NLP services, discussing the challenges of NLP and big data, and emphasizing the importance of viable cloud-based NLP services.
JOURNAL OF BIG DATA
(2022)
Article
Computer Science, Information Systems
Dan Deng, Junxia Li, Rutvij H. H. Jhaveri, Prayag Tiwari, Muhammad Fazal Ijaz, Jiangtao Ou, Chengyuan Fan
Summary: This paper proposes an optimization algorithm based on nonorthogonal multiplex access and unmanned aerial vehicles (UAVs) to improve the energy efficiency of the Internet of Things (IoT).
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Wei Wei, Qiao Ke, Dawid Polap, Marcin Wozniak
Summary: Digital security in modern systems often relies on biometric methods, and new implementations continue to emerge. This can be seen in various applications, such as signing for a courier package pick-up. However, signature verification is a complex process due to variations in size, angle, and writing conditions. Therefore, new methods are constantly needed to evaluate signatures. In this article, the authors propose the use of spline interpolation and two types of artificial neural networks to verify the identity of a person based on selected local and global features extracted from signature images. Experimental results on the SVC2004 database demonstrate an accuracy of 87.7%.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Anwar Hussain, Shah Nazir, Fazlullah Khan, Lewis Nkenyereye, Ayaz Ullah, Sulaiman Khan, Sahil Verma, Kavita
Summary: Future communication technologies like 6G can provide higher mobility and better quality-of-service requirements to the Internet of Things (IoT). To handle the demands of large-scale heterogeneous IoT networks, reliable and scalable solutions are needed, such as the proxy mobile IPv6 (PMIPv6) protocol. In this article, a demand-based resource-efficient location-aware PMIPv6 extension is proposed, which utilizes location information and received signal strength (RSS) to enhance the performance of the PMIPv6 protocol in terms of signaling cost and load distribution. Comparison with existing RSS-based PMIPv6 extension protocols shows that the proposed scheme improves performance and is resource-friendly for next-generation large-scale IoT networks.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Mathematics
Aaysha Khan, Jana Shafi
Summary: In recent years, the Internet of Things (IoT) has been predicted to be a trend in the technology domain due to its superior intelligence and ability to access data and construct networks anywhere. Today, IoT devices are well implemented and have become a topic of interest. The emergence of Social Internet of Things (S-IoT) has further enhanced IoT networks by enabling social connections and interactions among devices, similar to humans, leading to more complex internet networks.
BOLETIM SOCIEDADE PARANAENSE DE MATEMATICA
(2023)
Article
Computer Science, Information Systems
Daisy Mui Hung Kee, Aizza Anwar, Sai Ling Gwee, Muhammad Fazal Ijaz
Summary: The Penang Youth Development Corporation launched the Penang Young Digital Talent Program to address the gap between Malaysian youth's current digital skills and emerging technologies market demands. The program offers various online courses, including web design and digital marketing. This study aims to assess the participants' digital competency and examine the impact of their digital skills on employability, with course quality as a mediator. The findings highlight the importance of digital skills acquisition for Malaysian youth's success in the workplace and have implications for educational policymakers.
Article
Multidisciplinary Sciences
Divya Gupta, Shalli Rani, Basant Tiwari, Thippa Reddy Gadekallu
Summary: Vehicular Content Networks (VCNs) are a key solution for fully distributed content distribution in vehicular infotainment applications. This study focuses on edge communication in VCNs by classifying regions and designing a theoretical model to determine the content fetching location for each vehicle. Transient content caching in vehicular network components is based on content caching probability. The proposed approach outperforms state of art caching strategies according to simulation results.
SCIENTIFIC REPORTS
(2023)
Article
Green & Sustainable Science & Technology
Shruti, Shalli Rani, Aman Singh, Reem Alkanhel, Dina S. M. Hassan
Summary: A fog-assisted strategy for secure and efficient data aggregation in smart grid is proposed in this research. The proposed scheme overcomes the limitations faced in existing methods and shows outstanding performance in terms of storage, communication cost, and transmission cost.
Article
Computer Science, Artificial Intelligence
Qingsen Yan, Axi Niu, Chaoqun Wang, Wei Dong, Marcin Wozniak, Yanning Zhang
Summary: Deep learning-based methods have achieved remarkable results in the field of super-resolution. However, the limitation of paired training image sets has led researchers to explore self-supervised learning. However, the assumption of inaccurate downscaling kernel functions often leads to degraded results. To address this issue, this paper introduces KGSR, a kernel-guided network that trains both upscaling and downscaling networks to generate high-quality high-resolution images even without knowing the actual downscaling process.
PATTERN RECOGNITION
(2024)
Article
Multidisciplinary Sciences
Ashu Taneja, Shalli Rani, Saleem Raza, Amar Jain, Shebnam M. Sefat
Summary: This research investigates the use of Intelligent Reflecting Surfaces (IRS) in energy-constrained 6G wireless networks to address the challenges brought by the rapid growth of IoT devices and the inclusion of artificial intelligence technology. The study finds that IRS can improve the energy efficiency of wireless networks and tests the impact of different numbers of reflecting elements and phase resolution on system performance.
SCIENTIFIC REPORTS
(2023)
Article
Energy & Fuels
Roopali Dogra, Shalli Rani, Gabriele Gianini
Summary: Wireless Sensor Networks (WSNs) are an essential component of the Internet of Things (IoT). Clustering protocols that group nodes into clusters have been adopted to save power and increase the lifetime of the network. However, current clustering techniques have problems with the clustering structure that negatively impact their performance. This paper presents an improved region-based routing protocol (REERP) for WSNs, which increases the network's useful life by adding new nodes to existing clusters, selecting new head nodes based on residual energy, setting up multi-hop communication in all network regions, and utilizing the energy hole reduction method.
Article
Multidisciplinary Sciences
Mohit Kumar, Priya Mukherjee, Sahil Verma, Kavita, Jana Shafi, Marcin Wozniak, Muhammad Fazal Ijaz
Summary: The Industrial Internet of Things (IIoT) faces challenges in data privacy and security. This research paper proposes a privacy preservation model in IIoT using artificial intelligent techniques. The model involves two stages: data sanitization and restoration. The sanitization process hides sensitive information and generates optimal keys using a new algorithm. The simulation results demonstrate the superiority of the proposed model over other state-of-the-art models in terms of performance metrics.
SCIENTIFIC REPORTS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Alan Popiel, Marcin Wozniak
Summary: This paper presents a model and an algorithm to optimize the placement of routers in a network system for the mining industry, with N chambers and N-1 or fewer connections between them. The model considers two types of routers with different signal strengths, and the algorithm has a computational complexity of O(n(2), as tested on sample graph structures.
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2022, PT II
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Jakub Silka, Michal Wieczorek, Martyna Kobielnik, Marcin Wozniak
Summary: Deep learning architectures are used for demanding analysis of complex data inputs, where regular neural networks may encounter issues. In this article, we propose a deep learning model based on a BiLSTM neural network architecture. The proposed model is trained using the Adam algorithm, and we also examine other latest algorithms to determine the best configuration. Results show that our proposed BiLSTM deep learning neural network achieves over 99% accuracy.
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2022, PT I
(2023)
Article
Computer Science, Information Systems
Jyotismita Chaki, Marcin Wozniak
Summary: This study proposes a reinforcement learning agent that can interact with brain tumor images to retrieve and categorize similar images. The proposed method utilizes a novel architecture and binary coding technique, as well as fuzzy logic-based sample generation, to improve brain tumor classification and retrieval.
Article
Computer Science, Artificial Intelligence
Marcin Wozniak, Jozef Szczotka, Andrzej Sikora, Adam Zielonka
Summary: This article presents a model of adjustable moisture control for historical buildings, utilizing a flexible IoT infrastructure and type-2 fuzzy logic reasoning to create an innovative intelligent system for interior conditions control. The developed system, tested in an old brewery building, showed efficient dehumidification results at a low cost.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)