Article
Chemistry, Multidisciplinary
Abdulatif Alabdulatif, Muneerah Al Asqah, Tarek Moulahi, Salah Zidi
Summary: ML systems are increasingly used for achieving high productivity and effectiveness, especially when combined with advanced technologies like IoT and e-Health systems. However, the execution environment of ML faces various threats, which can be addressed through blockchain technology. This paper proposes a secure approach to protect the decision process of learning models by incorporating smart contracts and deploying SVM and MLP classifiers on-chain. A case study on medical records demonstrates the effectiveness of this approach, with SVM showing higher prediction scores and MLP exhibiting higher time efficiency.
APPLIED SCIENCES-BASEL
(2023)
Article
Public, Environmental & Occupational Health
Xi Shi, Gorana Nikolic, Scott Fischaber, Michaela Black, Debbie Rankin, Gorka Epelde, Andoni Beristain, Roberto Alvarez, Monica Arrue, Joao Pita Costa, Marko Grobelnik, Luka Stopar, Juha Pajula, Adil Umer, Peter Poliwoda, Jonathan Wallace, Paul Carlin, Jarmo Paakkonen, Bart De Moor
Summary: This study aims to develop a novel health data platform that connects healthcare data and open data in a privacy-preserving manner to support evidence-based health policy decision-making. The platform has been successfully piloted in four European countries, turning previously isolated data into actionable information for policy-making.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Geosciences, Multidisciplinary
Omid Zabihi, Maryam Siamaki, Mohammad Gheibi, Mehran Akrami, Mostafa Hajiaghaei-Keshteli
Summary: Decision Support System (DSS) is used to manage man-made and natural phenomena, such as flood disasters, and achieve Sustainable Development Goals. The study designs different stages of a novel DSS system for monitoring, predicting, and controlling floods, using machine learning computations and multi-criteria decision-making techniques. The integration of artificial intelligence and Ward computations helps analyze heterogeneous rainfall data in different provinces of Iran, and prioritize strategies for early decision-making in flood disasters through Pre-FA, DFA, and Post-FA activities.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Article
Food Science & Technology
Jie Tang, Yifeng Zou, Ruhe Xie, Bo Tu, Guanghai Liu
Summary: In this paper, a compact supervisory system is designed to track refrigerated transportation and detect improper practices using temperature data. Through a testbed simulation and machine learning models, the system is able to classify the state of the door and the refrigeration system.
Article
Green & Sustainable Science & Technology
Mostafa Kermani, Behin Adelmanesh, Erfan Shirdare, Catalina Alexandra Sima, Domenico Luca Carni, Luigi Martirano
Summary: This paper presents a novel energy management architecture model based on complete Supervisory Control and Data Acquisition (SCADA) system duties in an educational building with an MG Laboratory. The LAMBDA MG Lab simulates a Smart Building on a small scale and is connected with the DIAEE electrical network.
Article
Environmental Sciences
Paul Kengfai Wan, Lizhen Huang, Zhichen Lai, Xiufeng Liu, Mariusz Nowostawski, Halvor Holtskog, Yongping Liu
Summary: Indoor air quality is crucial for protecting the health of occupants. Poor ventilation has been shown to increase the risk of airborne virus transmission. Existing ventilation systems are not designed for pandemic conditions, making indoor environments potential hotspots for virus transmission. To address this issue, we developed a blockchain-based prototype that integrates smart sensor data and infection risk assessments to support decision-making by building owners.
ENVIRONMENTAL RESEARCH
(2023)
Article
Computer Science, Information Systems
Normadiah Mahiddin, Zulaiha Ali Othman, Azuraliza Abu Bakar, Nur Arzuar Abdul Rahim
Summary: The nature of decision making in healthcare is complex and crucial. A proposed intelligent decision support system model based on data mining aims to improve decision-making accuracy by utilizing knowledge from previous and following treatment stages. The experiment results show improved accuracy and practicality as a healthcare solution.
Article
Chemistry, Multidisciplinary
Somaiieh Rokhsaritalemi, Abolghasem Sadeghi-Niaraki, Ho-San Kang, Jong-Won Lee, Soo-Mi Choi
Summary: The study proposes a ubiquitous tourist system based on context-awareness, multicriteria decision making, and augmented reality, providing hotel recommendations and information enhancement services to users, achieving personalized needs.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Wenxu Zhang, Dan Ma, Zhongkai Zhao, Feiran Liu
Summary: Electronic countermeasures are moving towards intelligence with the design of a cognitive jamming decision-making system based on reinforcement learning. This system can adaptively adjust the jamming mode and power according to the change of radar threat level.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Education, Scientific Disciplines
Matthew Zegarek, Rebecca Brienza, Noel Quinn
Summary: Shared decision making (SDM) is a collaborative process that involves discussing preference-sensitive decisions with patients in an accessible format, allowing them to select an option that aligns with their values and preferences within the context of evidence-based medicine. Although SDM has shown to improve certain quality of care metrics and is included in competencies developed by accreditation bodies, incorporating SDM competencies into clinical teaching can be challenging.
Article
Computer Science, Information Systems
Victor Bajenaru, Steven Lavoie, Brett Benyo, Christopher Riker, Mitchell Colby, James Vaccaro
Summary: We have implemented a new recommender system (RS) metaheuristic framework that reduces the solution search space in a nonlinear NP-hard decision-making problem. Our RS-based metaheuristic supports comprehensive evaluation criteria and is compatible with established RS evaluation metrics. It achieves near-optimal solution scores through deep learning training, enables fast parameter inference, and allows for the reuse of the trained RS module for traditional ranking. When tested, it significantly reduces computation time while maintaining high solution scores.
Article
Green & Sustainable Science & Technology
Domenica Lavorato, Palmira Piedepalumbo
Summary: In order to stay competitive, companies are redefining their decision-making and control models by adopting lean, efficient, and digitalised approaches. The use of smart technologies in food and beverage companies has a significant impact on control systems and decision-making processes. This study aims to explore the influence of smart technologies on these systems through a case study, filling the gap in existing literature.
Article
Multidisciplinary Sciences
Iqbal H. Sarker, Asif Irshad Khan, Yoosef B. Abushark, Fawaz Alsolami
Summary: This paper discusses the challenges and importance of adding personalized decision-making intelligence to mobile applications, proposing the use of machine-learning rules as knowledge base instead of traditional rules. Experimental results show that context-aware machine learning rules discovered from users' mobile phone data can help build a mobile expert system to solve specific problems.
Review
Multidisciplinary Sciences
Omid Askarisichani, Francesco Bullo, Noah E. Friedkin, Ambuj K. Singh
Summary: Machine learning and artificial intelligence have had a significant impact on our lives, particularly in domains such as health and learning. Human expertise and judgment can be combined with algorithmic inputs to consider social and interpersonal issues in AI decision making.
ANNALS OF THE NEW YORK ACADEMY OF SCIENCES
(2022)
Article
Computer Science, Information Systems
Faiza Samreen, Gordon S. Blair, Yehia Elkhatib
Summary: This article presents a transfer learning based decision support system that reduces time and cost in building new models for performance of new applications and cloud infrastructures.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
