Liang Mu¹, Yurui Kang¹, Zixu Yan¹, Guangyu Zhu^2,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2495-2512, 2025, DOI:10.32604/cmc.2025.063208 - 03 July 2025

Abstract The accurate prediction and analysis of emergencies in Urban Rail Transit Systems (URTS) are essential for the development of effective early warning and prevention mechanisms. This study presents an integrated perception model designed to predict emergencies and analyze their causes based on historical unstructured emergency data. To address issues related to data structuredness and missing values, we employed label encoding and an Elastic Net Regularization-based Generative Adversarial Interpolation Network (ER-GAIN) for data structuring and imputation. Additionally, to mitigate the impact of imbalanced data on the predictive performance of emergencies, we introduced an Adaptive Boosting Ensemble… More >

Maria Gul¹, Imran Ali Khan¹, Gohar Zaman², Atta Rahman^3,*, Jamaluddin Mir², Sardar Asad Ali Biabani^4,5, May Issa Aldossary⁶, Mustafa Youldash⁷, Ashraf Saadeldeen⁸, Maqsood Mahmud⁹, Asiya Abdus Salam⁶, Dania Alkhulaifi³, Abdullah AlTurkey³

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1631-1657, 2024, DOI:10.32604/cmc.2024.048289 - 25 April 2024

Abstract Obstacle removal in crowd evacuation is critical to safety and the evacuation system efficiency. Recently, many researchers proposed game theoretic models to avoid and remove obstacles for crowd evacuation. Game theoretical models aim to study and analyze the strategic behaviors of individuals within a crowd and their interactions during the evacuation. Game theoretical models have some limitations in the context of crowd evacuation. These models consider a group of individuals as homogeneous objects with the same goals, involve complex mathematical formulation, and cannot model real-world scenarios such as panic, environmental information, crowds that move dynamically,… More >

Haosong Gou¹, Gaoyi Zhang¹, Renê Ripardo Calixto², Senthil Kumar Jagatheesaperumal³, Victor Hugo C. de Albuquerque^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1077-1102, 2024, DOI:10.32604/cmes.2024.047806 - 16 April 2024

Abstract Large-scale wireless sensor networks (WSNs) play a critical role in monitoring dangerous scenarios and responding to medical emergencies. However, the inherent instability and error-prone nature of wireless links present significant challenges, necessitating efficient data collection and reliable transmission services. This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs. The primary goal is to enhance the reliability of data collection and transmission services, ensuring a comprehensive and practical approach. Our approach focuses on refining the hop-count-based routing scheme to achieve… More >

Taiki Haga^1,*, Tomoyuki Masuyama², Yoshiro Hayashi³, Takahiro Atsumi⁴, Kenzo Ishii⁵, Shinsuke Fujiwara⁶

Congenital Heart Disease, Vol.17, No.1, pp. 31-43, 2022, DOI:10.32604/CHD.2022.017407 - 26 October 2021

Abstract Objectives: This study aimed to study the characteristics of in-hospital deterioration in patients with congenital heart disease who required rapid response system activation and identify risk factors associated with 1-month mortality. Methods: We retrospectively analysed data from a Japanese rapid response system registry with 35 participating hospitals. We included consecutive patients with congenital heart disease who required rapid response system activation between January 2014 and March 2018. Logistic regression analyses were performed to examine the associations between 1-month mortality and other patient-specific variables. Results: Among 9,607 patients for whom the rapid response system was activated, only 82… More >

Zoe S. Gan, Cheyenne Williams, Olivia O. Familusi, Ayah El-Fahmawi, Rayan Kabaha, Daniel J. Lee, David I. Lee

Canadian Journal of Urology, Vol.28, No.2, pp. 10614-10619, 2021

Abstract Introduction: During the coronavirus disease 2019 (COVID-19) pandemic, decreased presentations for various emergent conditions have been observed. Our objective was to compare the volume of patients with urologic emergencies presenting to emergency departments (EDs) within a single health system before and after the onset of the COVID-19 pandemic. Materials and methods: A retrospective chart review was performed for 3 EDs within a single health system in the United States to identify all ED consults to urology from January 1, 2019 to May 31, 2020. For emergent consults, covariates were extracted, including demographic information, insurance status,… More >

Jun Li^{1, 2}, Jieren Cheng^{2, *}, Naixue Xiong³, Lougao Zhan⁴, Yuan Zhang¹

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 723-741, 2020, DOI:10.32604/cmc.2020.011272 - 23 July 2020

Abstract Security and privacy issues have become a rapidly growing problem with the fast development of big data in public health. However, big data faces many ongoing serious challenges in the process of collection, storage, and use. Among them, data security and privacy problems have attracted extensive interest. In an effort to overcome this challenge, this article aims to present a distributed privacy preservation approach based on smart contracts and Intel Software Guard Extensions (SGX). First of all, we define SGX as a trusted edge computing node, design data access module, data protection module, and data… More >