Article
Business
Junhan Kim, Youngjung Geum
Summary: This study proposes a systematic and concrete framework to develop data-driven technology roadmaps, consisting of three phases: layer mapping, contents mapping, and opportunity finding. This contributes to the field by providing a systematic method for data-driven roadmapping and offering data-driven evidence for more reasonable decision-making by experts.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Review
Computer Science, Information Systems
Chetan Sharma, Isha Batra, Shamneesh Sharma, Arun Malik, A. S. M. Sanwar Hosen, In-Ho Ra
Summary: This study investigates the research trends and patterns in the field of smart cities, providing a comprehensive overview of smart cities research, including prominent countries, institutions, sources, and authors, as well as noteworthy research directions. The study also discusses scientific collaboration across countries, organizations, and authors, and presents a roadmap of smart cities research trends through experimental research.
Review
Health Care Sciences & Services
Lauryn J. Hagg, Stephanie S. Merkouris, Gypsy A. O'Dea, Lauren M. Francis, Christopher J. Greenwood, Matthew Fuller-Tyszkiewicz, Elizabeth M. Westrupp, Jacqui A. Macdonald, George J. Youssef
Summary: This scoping review examines the methodological approaches used in psychology research using latent Dirichlet allocation (LDA). The findings highlight the growing use of LDA in psychological science and the need for improved analytical reporting standards and evidence-based best practice recommendations.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Ning Wang, Jinling Guo, Jian Zhang, Yu Fan
Summary: Constructing an eco-civilization is crucial for green, low-carbon development. However, there are inconsistencies and imbalances between theoretical research and practical efforts. This paper analyzes China's progress towards eco-civilization at theoretical and practical levels. The results show that theory is moving towards interdisciplinary directions, while eco-civilization projects need to focus more on low-carbon research.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Geosciences, Multidisciplinary
Louis Ngamassi, Hesam Shahriari, Thiagarajan Ramakrishnan, Shahedur Rahman
Summary: This paper uses the LDA technique to analyze tweet data collected during Hurricane Harvey and identifies the themes of concern among people during the pre-crisis period. Based on these themes, recommendations are provided to assist disaster management agencies and policymakers in better preparing for and responding to disasters.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Agronomy
Jiyoung Ha, Seunghyun Lee, Sangtae Kim
Summary: This study analyzed the influence relationship between news articles on onions and the consumer selling price of onions in Korea. The findings showed that hypermarket onion sales, onion supply and demand stabilization measures, and inflation had a significant impact on the selling price of onions.
Article
Computer Science, Information Systems
Rajesh Chittor Sundaram, Elham Naghizade, Renata Borovica-Gajic, Martin Tomko
Summary: This article discusses the assessment of OpenStreetMap (OSM) data quality by examining issues documented through the FIXME tag. It presents a classification and analysis of these quality issues across USA and Australia, grounded in ISO-19157 standard. The research aims to inform the development of automated error correction methods for VGI datasets by linking established ISO data quality standards to OSM issue categorization.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2022)
Review
Hospitality, Leisure, Sport & Tourism
Marcello Mariani, Rodolfo Baggio
Summary: This research surveyed the body of research on big data and analytics in hospitality and tourism, revealing a fragmented research field with a lack of studies on important aspects such as BD analytics capabilities. Most of the outputs were published in academic journals, but the main reference area was unrelated to hospitality or tourism.
INTERNATIONAL JOURNAL OF CONTEMPORARY HOSPITALITY MANAGEMENT
(2022)
Article
Multidisciplinary Sciences
Leacky Muchene, Wende Safari
Summary: The study utilized a two-stage topic modeling approach, using Latent Dirichlet Allocation for per-document topic probability derivation in the first stage, and hierarchical clustering with Hellinger distance for final topic cluster discovery in the second stage. The analysis revealed dominant research themes at the University of Nairobi, including HIV and malaria research, agricultural and veterinary services research, as well as cross-cutting themes in humanities and social sciences, demonstrating the effectiveness of hierarchical clustering in organizing discovered latent topics into homogeneous clusters.
Article
Computer Science, Artificial Intelligence
Mimu Kawai, Hiroyuki Sato, Takayuki Shiohama
Summary: This study proposes hybrid recommender models that use content-based filtering and latent Dirichlet allocation (LDA)-based models to address the cold-start problem in recommender systems. Experimental results demonstrate that these models achieve similar prediction performances compared to baseline models, while providing better interpretability of user and item topics.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Biochemical Research Methods
Alan Min, Timothy Durham, Louis Gevirtzman, William Stafford Noble
Summary: Single cell ATAC-seq (scATAC-seq) enables the mapping of regulatory elements in fine-grained cell types. In this study, the authors propose using latent Dirichlet allocation (LDA) with nonuniform matrix priors to improve the analysis of scATAC-seq data. They demonstrate the effectiveness of this method in capturing cell type information from small scATAC-seq datasets from C. elegans nematodes and mouse skin cells.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Engineering, Industrial
JungHo Jeon, Suyash Padhye, Soojin Yoon, Hubo Cai, Makarand Hastak
Summary: The construction industry is a significant contributor to the US economy and global market, monitored by the Purdue Index for Construction (Pi-C) consisting of five dimensions. Using latent Dirichlet allocation (LDA), new metrics such as Technology, Education, and Sustainability were identified for the Development and Quality dimensions of Pi-C, improving understanding of the industry in terms of technology, education, and sustainability for data-driven decision-making and strategy development.
JOURNAL OF MANAGEMENT IN ENGINEERING
(2021)
Article
Development Studies
Zhimin Liu, Chao Ye, Ruishan Chen, Star X. Zhao
Summary: Sustainability research addressing the complexity, surprise and uncertainty of the coupled human-nature system is gaining worldwide interest. An understanding of the frontiers of sustainability research helps researchers identify significant issues, seek cooperation, and supports governments in setting strategic priorities for innovation. This study analyzed publications from 2013 to 2019 to identify six research frontiers, with primary contributors located in Asia, Europe, America, and Australia. The research also highlights the potential role of sustainability combined with smart technologies as a frontier for future development.
HABITAT INTERNATIONAL
(2021)
Article
Green & Sustainable Science & Technology
Jiaqi Hu, Rui Huang, Fangting Xu
Summary: This study proposes a new framework that combines data mining technology and evidence-based safety theory to explore and obtain latent safety evidence in coal-mine data, and improve the reliability and sustainability of coal-mine safety management.
Article
Health Care Sciences & Services
Mahendra Kumar Gourisaria, Satish Chandra, Himansu Das, Sudhansu Shekhar Patra, Manoj Sahni, Ernesto Leon-Castro, Vijander Singh, Sandeep Kumar
Summary: This study analyzes the psychological reactions and discourse of Twitter users regarding COVID-19, using LDA for topic modeling and BiLSTM and various classification techniques for sentiment analysis. The experimental results show that the BiLSTM approach outperforms other methods with an accuracy of 96.7%.
Editorial Material
Computer Science, Information Systems
Yulei Wu, Yi Pan, Payam Barnaghi, Zhiyuan Tan, Jingguo Ge, Hao Wang
Article
Computer Science, Artificial Intelligence
Honglin Li, Payam Barnaghi, Shirin Enshaeifare, Frieder Ganz
Summary: Continual learning models face the challenge of catastrophic forgetting in dynamic environments. To address this issue, a method called continual Bayesian learning networks (CBLNs) is proposed, which optimizes resource allocation and weight selection by maintaining a mixture of Gaussian posterior distributions to solve the problem of forgetting previously learned tasks.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Editorial Material
Computer Science, Information Systems
Meikang Qiu, Bhavani Thuraisingham, Mahmoud Daneshmand, Huansheng Ning, Payam Barnaghi
Summary: The development of the Internet of Things has made artificial intelligence a key component for applications, with deep learning technologies greatly improving traditional computer science and networking technologies. Furthermore, the convergence of AI and IoT allows data to be quickly explored and turned into significant decisions.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Farshad Firouzi, Bahar Farahani, Mahmoud Daneshmand, Kathy Grise, Jaeseung Song, Roberto Saracco, Lucy Lu Wang, Kyle Lo, Plamen Angelov, Eduardo Soares, Po-Shen Loh, Zeynab Talebpour, Reza Moradi, Mohsen Goodarzi, Haleh Ashraf, Mohammad Talebpour, Alireza Talebpour, Luca Romeo, Rupam Das, Hadi Heidari, Dana Pasquale, James Moody, Chris Woods, Erich S. Huang, Payam Barnaghi, Majid Sarrafzadeh, Ron Li, Kristen L. Beck, Olexandr Isayev, Nakmyoung Sung, Alan Luo
Summary: As COVID-19 continues to spread globally, the collaborative efforts of researchers, institutions, governments, and society have focused on utilizing IoT, AI, robotics, and blockchain as the key technological innovations to combat the pandemic. While these digital technologies offer insights into the disease and support frontline efforts, they are not the sole solution to the crisis.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Ethics
Christine Hine, Ramin Nilforooshan, Payam Barnaghi
Summary: This paper discusses the ethical issues arising from smart care systems, focusing on addressing these issues during the system design stage. While ethical principles for artificial intelligence have been established, governance mechanisms are still evolving. In healthcare settings, smart technology implementation follows existing frameworks for ethical review and governance. Designers can take preemptive measures to incorporate ethical considerations into the technology. Despite efforts to preempt them, ethical challenges may still arise during the implementation of smart care systems.
Article
Chemistry, Analytical
Rajesh Amerineni, Lalit Gupta, Nathan Steadman, Keshwyn Annauth, Charles Burr, Samuel Wilson, Payam Barnaghi, Ravi Vaidyanathan
Summary: This study introduces a set of input models to fuse information from wearable sensor ensembles, supporting human performance and telemedicine. By implementing dynamic time warping and convolutional neural networks with the input models, multiple classification models are proposed and demonstrated to outperform traditional uni-axial classifiers in action classification related to boxing and taekwondo. The results show that deep learning fusion classifiers excel in handling non-linear variations compared to dynamic time warping.
Article
Computer Science, Information Systems
Maitreyee Wairagkar, Maria R. Lima, Daniel Bazo, Richard Craig, Hugo Weissbart, Appolinaire C. Etoundi, Tobias Reichenbach, Prashant Iyengar, Sneh Vaswani, Christopher James, Payam Barnaghi, Chris Melhuish, Ravi Vaidyanathan
Summary: This study presents the design and validation of an Internet of Things-enabled social robot that can effectively convey emotions through its hybrid-face expression. The results demonstrate the recognition of robotic expressions by humans and the neurophysiological response to these expressions. The concept of the hybrid-face robot has been implemented and released in a commercial IoT robotic platform, showing comparable results to the original design. The study concludes that simplified hybrid-face abstraction enhances human-robot interaction by effectively conveying emotions.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Multidisciplinary Sciences
Elaheh Kalantari, Samaneh Kouchaki, Christine Miaskowski, Kord Kober, Payam Barnaghi
Summary: This study used network analysis to investigate the relationships among co-occurring symptoms in oncology patients during their treatment. Eight unique symptom clusters were identified. The findings suggest that these relationships vary depending on the chemotherapy cycle and cancer type. The evaluation of centrality measures provides insights into potential targets for symptom management interventions.
SCIENTIFIC REPORTS
(2022)
Article
Health Care Sciences & Services
Alina-Irina Serban, Eyal Soreq, Payam Barnaghi, Sarah Daniels, Rafael A. Calvo, David J. Sharp
Summary: The COVID-19 pandemic has affected the home behaviors of people living with dementia, with social isolation being a significant factor. A study conducted in the UK monitored the home activities of 31 individuals with dementia using remote home monitoring technology, revealing a decreased amount of time spent outside during lockdowns.
NPJ DIGITAL MEDICINE
(2022)
Article
Computer Science, Artificial Intelligence
Maria R. Lima, Maitreyee Wairagkar, Manish Gupta, Ferdinando Baena, Payam Barnaghi, David J. Sharp, Ravi Vaidyanathan
Summary: Socially assistive robots have the potential to assist older adults and people with dementia in human engagement and clinical contexts. However, there are still challenges in terms of trust, clinical translation, and patient benefit. This article reviews the state of the art in conversational affective SAR, discusses the role of user-centered approaches in design, and proposes future directions for advancing these robots in terms of user engagement, real-world deployment, and clinical translation.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2022)
Article
Medicine, General & Internal
Megan E. Parkinson, Melanie Dani, Michael Fertleman, Eyal Soreq, Payam Barnaghi, David J. Sharp, Lucia M. Li
Summary: The prevalence of traumatic brain injury (TBI) among older adults is increasing exponentially, but research on TBI in this population is sparse. A home monitoring system called Minder, developed by the UK Dementia Research Institute, will be used to passively collect sleep and activity data from older adults with TBI. The study aims to assess the feasibility of using this system to study changes in the health status of older adults in the early period post-TBI.
Article
Geriatrics & Gerontology
Michael C. B. David, Magdalena Kolanko, Martina Del Giovane, Helen Lai, Jessica True, Emily Beal, Lucia M. Li, Ramin Nilforooshan, Payam Barnaghi, Paresh A. Malhotra, Helen Rostill, David Wingfield, Danielle Wilson, Sarah Daniels, David J. Sharp, Gregory Scott
Summary: This study used IoT technology to remotely monitor physiological measurements of 82 people with dementia over a long period of time. The findings suggest that monitoring the physiology of dementia patients in their own homes is feasible and can improve the management of acute and chronic comorbidities. Future randomized trials are needed to determine the long-term impact of this system on health and quality of life outcomes.
Article
Computer Science, Information Systems
Maria R. Lima, Ting Su, Melanie Jouaiti, Maitreyee Wairagkar, Paresh Malhotra, Eyal Soreq, Payam Barnaghi, Ravi Vaidyanathan
Summary: Advancements in conversational AI have created opportunities to promote independence and well-being of older adults, but there is limited evidence of its direct impact in supporting target populations at home. This study introduces an infrastructure that combines IoT technologies with conversational technology to analyze behavioral patterns and track health and deterioration in households with PLWD. The results demonstrate the promise of conversational AI in digital health monitoring and offer a basis for timely interventions.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Proceedings Paper
Computer Science, Information Systems
Yuchen Zhao, Payam Barnaghi, Hamed Haddadi
Summary: In this paper, a multimodal and semi-supervised federated learning framework is proposed, which can extract shared or correlated representations from different local data modalities and train local autoencoders through a multimodal aggregation algorithm. The experimental results demonstrate that introducing data from multiple modalities can improve the classification performance of federated learning, and it is possible to use labelled data from only one modality for supervised learning and apply it to testing data from other modalities.
7TH ACM/IEEE CONFERENCE ON INTERNET-OF-THINGS DESIGN AND IMPLEMENTATION (IOTDI 2022)
(2022)
Article
Computer Science, Artificial Intelligence
Roonak Rezvani, Payam Barnaghi, Shirin Enshaeifar
Summary: The paper proposes a pattern representation method by representing time-series frames as vectors using PAA and Lagrangian Multipliers, which effectively addresses the challenges in IoT data stream analysis. The method achieves pattern representation for continuous data and introduces a new change point detection method using constructed patterns for analysis.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2021)