Yadpirun Supharakonsakun¹, Yupaporn Areepong², Korakoch Silpakob^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 699-720, 2025, DOI:10.32604/cmes.2025.067702 - 30 October 2025

Abstract This study presents an innovative development of the exponentially weighted moving average (EWMA) control chart, explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)_L under exponential white noise. Unlike previous works that rely on simplified models such as AR(1) or assume independence, this research derives for the first time an exact two-sided Average Run Length (ARL) formula for the Modified EWMA chart under SARMA(1,1)_L conditions, using a mathematically rigorous Fredholm integral approach. The derived formulas are validated against numerical integral equation (NIE) solutions, showing strong agreement and significantly reduced More > Graphic Abstract

Chenjun Ni, Kuo Tian^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.012069

Abstract The development of large-scale, high-precision aerospace structures has imposed increasingly stringent requirements on mechanical response monitoring during ground testing. Aiming at the long-standing limitations of mechanical response monitoring for ground tests in terms of accuracy and real-time performance, this study introduces an intelligent structural strength monitoring method using a dynamically evolving digital twin model.
First, a reduced-order modeling method that accounts for actual test deviations is established. By jointly sampling deviation and loading information as variables, a reduced-order model with full-field mechanical responses as output is constructed, enabling rapid updates to reflect the real test conditions.… More >

Mingyu Cai^1,2, Xingchun Li^1,2, Kunfeng Zhang^1,2,*, Shugang Yang^1,2, Shuangxing Liu^1,2, Ming Xue^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-2, 2025, DOI:10.32604/icces.2025.010490

Abstract Deep saline aquifers account for more than 90% of the global theoretical geological CO₂ sequestration capacity, making them the dominant choice for large-scale CO₂ storage. These aquifers offer vast storage potential, especially in comparison to oil and gas reservoirs, which are often considered for CO₂ geological sequestration. Despite their significant storage capacity, deep saline aquifers face several challenges that hinder their practical application. In particular, the lack of adequate geological infrastructure and exploration conditions for deep saline aquifers presents major obstacles to the effective monitoring of CO₂ migration and predicting leakage risks. These challenges are compounded by… More >

Tao Lin^1,*, Chengdai Chen¹, Liyao Chen¹, Fengqin Han¹, Guanghui He²

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1661-1680, 2025, DOI:10.32604/fhmt.2025.070787 - 31 October 2025

Abstract Targeting spontaneous coal combustion during stacking, we developed an efficient heat dissipation & self-supplied wireless temperature measurement system (SPWTM) with gravity heat pipe-thermoelectric integration for dual safety. The heat transfer characteristics and temperature measurement optimization of the system are experimentally investigated and verified in practical applications. The results show that, firstly, the effects of coal pile heat production power and burial depth, along with heat pipe startup and heat transfer characteristics. At 60 cm burial depth, the condensation section dissipates 98% coal pile heat via natural convection. Secondly, for the temperature measurement error caused by… More >

Roberto Caviglia¹, Daniyar Aliaskharov², Alessio Aceti¹, Mila Dalla Preda³, Paola Girdinio², Giovanni Battista Gaggero^2,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5327-5340, 2025, DOI:10.32604/cmc.2025.068509 - 23 October 2025

Abstract Industrial Control Systems (ICS) in Operational Technology (OT) environments face unique cybersecurity challenges due to legacy systems, critical operational needs, and incompatibility with standard IT security practices. To address these challenges, this paper presents the Security Operation and Event Management (SOEM) platform, a software designed to support Security Operations Centers (SOCs) in reaching full visibility of OT environments. SOEM integrates diverse log sources and intrusion detection systems, including logs generated by the control system itself and additional on-the-shelf products, to enhance situational awareness and enable rapid incident response. The pilot project was carried out within More >

Kunal Thakur¹, Ashu Taneja^1,*, Ali Alqahtani², Nayef Alqahtani³

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4827-4848, 2025, DOI:10.32604/cmc.2025.067901 - 23 October 2025

Abstract Accident detection plays a critical role in improving traffic safety by enabling timely emergency response and reducing the impact of road incidents. The main challenge lies in achieving real-time, reliable and highly accurate detection across diverse Internet-of-vehicles (IoV) environments. To overcome this challenge, this paper leverages deep learning to automatically learn patterns from visual data to detect accidents with high accuracy. A visual classification model based on the ResNet-50 architecture is presented for distinguishing between accident and non-accident images. The model is trained and tested on a labeled dataset and achieves an overall accuracy of… More >

Szymon Piątek¹, Anna Dańska-Bidzińska^2,*, Paweł Derlatka², Bartosz Szymanowski³, Renata Duchnowska³, Aleksandra Zielińska⁴, Natalia Sawicka⁴, Aleksander Gorzeń⁵, Wojciech Michalski⁶, Mariusz Bidziński¹

Oncology Research, Vol.33, No.11, pp. 3405-3416, 2025, DOI:10.32604/or.2025.068609 - 22 October 2025

Abstract Objectives: Monitoring of Cancer Antigen 125 (CA125) during ovarian cancer (OC) maintenance treatment with poly(ADP-ribose) polymerase inhibitors (PARPis) may be insufficient when using Gynecologic Cancer Intergroup (GCIG) biochemical progression criteria. This study aimed to evaluate the usefulness of CA125 monitoring in detecting OC recurrence during PARPis maintenance treatment. Methods: This multicenter retrospective cohort study included patients with primary OC who achieved complete or partial response after first-line platinum-based chemotherapy followed by PARPis maintenance treatment. Progression was defined using Response Evaluation Criteria in Solid Tumors (RECIST) and GCIG biochemical criteria. New biochemical progression definitions, based on… More >

J. S. V. Siva Kumar¹, Mahmad Mustafa², Sk. M. Unnisha Begum³, Badugu Suresh⁴, Rajanand Patnaik Narasipuram^5,*

Energy Engineering, Vol.122, No.10, pp. 3891-3904, 2025, DOI:10.32604/ee.2025.070052 - 30 September 2025

Abstract Electric vehicle (EV) monitoring systems commonly depend on IoT-based sensor measurements to track key performance parameters such as vehicle speed, state of charge (SoC), battery temperature, power consumption, motor RPM, and regenerative braking. While these systems enable real-time data acquisition, they are often hindered by sensor noise, communication delays, and measurement uncertainties, which compromise their reliability for critical decision-making. To overcome these limitations, this study introduces a comparative framework that integrates reference signals, a digital twin model emulating ideal system behavior, and real-time IoT measurements. The digital twin provides a predictive and noise-resilient representation of More >

Seunghwan Seo^1,2,*, Moonkyung Chung¹

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2893-2922, 2025, DOI:10.32604/cmes.2025.069668 - 30 September 2025

Abstract Excavation-induced deformations of earth-retaining walls (ERWs) can critically affect the safety of surrounding structures, highlighting the need for reliable prediction models to support timely decision-making during construction. This study utilizes traditional statistical ARIMA (Auto-Regressive Integrated Moving Average) and deep learning-based LSTM (Long Short-Term Memory) models to predict earth-retaining walls deformation using inclinometer data from excavation sites and compares the predictive performance of both models. The ARIMA model demonstrates strengths in analyzing linear patterns in time-series data as it progresses over time, whereas LSTM exhibits superior capabilities in capturing complex non-linear patterns and long-term dependencies within… More > Graphic Abstract

Atta Rahman^*, Fahad Abdullah Alatallah, Abdullah Jafar Almubarak, Haider Ali Alkhazal, Hasan Ali Alzayer, Younis Zaki Shaaban, Nasro Min-Allah, Aghiad Bakry, Khalid Aloup

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3507-3525, 2025, DOI:10.32604/cmc.2025.067547 - 23 September 2025

Abstract This study presents an automated system for monitoring Personal Protective Equipment (PPE) compliance using advanced computer vision techniques in industrial settings. Despite strict safety regulations, manual monitoring of PPE compliance remains inefficient and prone to human error, particularly in harsh environmental conditions like in Saudi Arabia’s Eastern Province. The proposed solution leverages the state-of-the-art YOLOv11 deep learning model to detect multiple safety equipment classes, including safety vests, hard hats, safety shoes, gloves, and their absence (no_hardhat, no_safety_vest, no_safety_shoes, no_gloves) along with person detection. The system is designed to perform real-time detection of safety gear while… More >