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  • Open Access

    ARTICLE

    Explicit ARL Computational for a Modified EWMA Control Chart in Autocorrelated Statistical Process Control Models

    Yadpirun Supharakonsakun1, Yupaporn Areepong2, Korakoch Silpakob3,*

    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

    Explicit ARL Computational for a Modified EWMA Control Chart in Autocorrelated Statistical Process Control Models

  • Open Access

    ARTICLE

    A Flexible Exponential Log-Logistic Distribution for Modeling Complex Failure Behaviors in Reliability and Engineering Data

    Hadeel AlQadi1, Fatimah M. Alghamdi2, Hamada H. Hassan3, Mohamed E. Mead4, Ahmed Z. Afify5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2029-2061, 2025, DOI:10.32604/cmes.2025.069801 - 31 August 2025

    Abstract Parametric survival models are essential for analyzing time-to-event data in fields such as engineering and biomedicine. While the log-logistic distribution is popular for its simplicity and closed-form expressions, it often lacks the flexibility needed to capture complex hazard patterns. In this article, we propose a novel extension of the classical log-logistic distribution, termed the new exponential log-logistic (NExLL) distribution, designed to provide enhanced flexibility in modeling time-to-event data with complex failure behaviors. The NExLL model incorporates a new exponential generator to expand the shape adaptability of the baseline log-logistic distribution, allowing it to capture a… More >

  • Open Access

    ARTICLE

    Statistical and Visual Evaluation of Artificial Neural Networks and Multiple Linear Regression Performances in Estimating Reference Crop Evapotranspiration for Mersin

    Fatma Bunyan Unel1,*, Lutfiye Kusak1, Murat Yakar1, Abdullah Sahin2, Hakan Dogan3, Fikret Demir4

    Revue Internationale de Géomatique, Vol.34, pp. 433-460, 2025, DOI:10.32604/rig.2025.065502 - 29 July 2025

    Abstract This study aimed to create a model for calculating the total reference crop evapotranspiration (ETo) in Mersin Province from May 2015 to 2020 and to generate maps using spatial analysis. Lemons from citrus play a significant role in Mersin’s agriculture, and because of lemons’ sensitivity to temperature, ETo is essential for them. It was observed that the ETo value () calculated using the Penman-Monteith (PM) method increased over the years. A model was developed using data from 36 Automated Weather Observing Systems (AWOS) in Mersin, Türkiye, which is located in a semi-arid climate zone. The… More >

  • Open Access

    ARTICLE

    Performance Analysis of Various Forecasting Models for Multi-Seasonal Global Horizontal Irradiance Forecasting Using the India Region Dataset

    Manoharan Madhiarasan*

    Energy Engineering, Vol.122, No.8, pp. 2993-3011, 2025, DOI:10.32604/ee.2025.068358 - 24 July 2025

    Abstract Accurate Global Horizontal Irradiance (GHI) forecasting has become vital for successfully integrating solar energy into the electrical grid because of the expanding demand for green power and the worldwide shift favouring green energy resources. Particularly considering the implications of the aggressive GHG emission targets, accurate GHI forecasting has become vital for developing, designing, and operational managing solar energy systems. This research presented the core concepts of modelling and performance analysis of the application of various forecasting models such as ARIMA (Autoregressive Integrated Moving Average), Elaman NN (Elman Neural Network), RBFN (Radial Basis Function Neural Network),… More >

  • Open Access

    ARTICLE

    A Novel Face-to-Skull Prediction Based on Face-to-Back Head Relation

    Tien-Tuan Dao1, Lan-Nhi Tran-Ngoc2,3, Trong-Pham Nguyen-Huu2,3, Khanh-Linh Dinh-Bui2,3, Nhat-Minh Nguyen2,3, Ngoc-Bich Le2,3, Tan-Nhu Nguyen2,3,*

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3345-3369, 2025, DOI:10.32604/cmc.2025.065279 - 03 July 2025

    Abstract Skull structures are important for biomechanical head simulations, but they are mostly reconstructed from medical images. These reconstruction methods harm the human body and have a long processing time. Currently, skull structures can be straightforwardly predicted from the head, but a full head shape must be available. Most scanning devices can only capture the face shape. Consequently, a method that can quickly predict the full skull structures from the face is necessary. In this study, a novel face-to-skull prediction procedure is introduced. Given a three-dimensional (3-D) face shape, a skull mesh could be predicted so… More >

  • Open Access

    ARTICLE

    FSFS: A Novel Statistical Approach for Fair and Trustworthy Impactful Feature Selection in Artificial Intelligence Models

    Ali Hamid Farea1,*, Iman Askerzade1,2, Omar H. Alhazmi3, Savaş Takan4

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1457-1484, 2025, DOI:10.32604/cmc.2025.064872 - 09 June 2025

    Abstract Feature selection (FS) is a pivotal pre-processing step in developing data-driven models, influencing reliability, performance and optimization. Although existing FS techniques can yield high-performance metrics for certain models, they do not invariably guarantee the extraction of the most critical or impactful features. Prior literature underscores the significance of equitable FS practices and has proposed diverse methodologies for the identification of appropriate features. However, the challenge of discerning the most relevant and influential features persists, particularly in the context of the exponential growth and heterogeneity of big data—a challenge that is increasingly salient in modern artificial… More >

  • Open Access

    ARTICLE

    Statistical Inference for Kumaraswamy Distribution under Generalized Progressive Hybrid Censoring Scheme with Application

    Magdy Nagy*

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 185-223, 2025, DOI:10.32604/cmes.2025.061865 - 11 April 2025

    Abstract In this present work, we propose the expected Bayesian and hierarchical Bayesian approaches to estimate the shape parameter and hazard rate under a generalized progressive hybrid censoring scheme for the Kumaraswamy distribution. These estimates have been obtained using gamma priors based on various loss functions such as squared error, entropy, weighted balance, and minimum expected loss functions. An investigation is carried out using Monte Carlo simulation to evaluate the effectiveness of the suggested estimators. The simulation provides a quantitative assessment of the estimates accuracy and efficiency under various conditions by comparing them in terms of More >

  • Open Access

    ARTICLE

    The Impact of Nursing Staff’s Work Attitude on the Fear of Patients Recovering from Benign Tumors: Family Support as a Mediating Variable

    Chengzhe Guo1, Aihua Cheng2,*, Jian Chen2, Gaojie Cheng3

    Psycho-Oncologie, Vol.18, No.4, pp. 291-303, 2024, DOI:10.32604/po.2024.054446 - 04 December 2024

    Abstract The perception of nursing staff’s attitude influences patient fear. Understanding this dynamic is crucial for fostering a supportive environment conducive to patient well-being and effective healthcare practices. The purpose of this research is to investigate how the attitudes and behaviours of nursing staff influence the fear and anxiety levels of patients recovering from benign tumors, aiming to improve patient care and recovery outcomes. Data was collected from a sample of 100 participants, comprising 20 nursing staff and 80 patients recovering from benign tumors. Surveys were administered to gather quantitative data on attitudes and fear levels.… More >

  • Open Access

    ARTICLE

    Impact of Land Requisition for Military Training during World War II on Farming and the South Downs Landscape, England

    Nigel Walford*

    Revue Internationale de Géomatique, Vol.33, pp. 445-464, 2024, DOI:10.32604/rig.2024.054535 - 25 October 2024

    Abstract The impact of World War II on the physical landscape of British towns and cities as a result of airborne assault is well known. However, less newsworthy but arguably no less significant is the impact of the war on agriculture and the countryside, especially in South-East England. This paper outlines the building of an historical Geographical Information System (GIS) from different data sources including the National Farm Survey (NFS), Luftwaffe and Royal Air Force (RAF) aerial photographs and basic topographic mapping for the South Downs in East and West Sussex. It explores the impact and… More >

  • Open Access

    ARTICLE

    Encrypted Cyberattack Detection System over Encrypted IoT Traffic Based on Statistical Intelligence

    Il Hwan Ji1, Ju Hyeon Lee1, Seungho Jeon2, Jung Taek Seo2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1519-1549, 2024, DOI:10.32604/cmes.2024.053437 - 27 September 2024

    Abstract In the early days of IoT’s introduction, it was challenging to introduce encryption communication due to the lack of performance of each component, such as computing resources like CPUs and batteries, to encrypt and decrypt data. Because IoT is applied and utilized in many important fields, a cyberattack on IoT can result in astronomical financial and human casualties. For this reason, the application of encrypted communication to IoT has been required, and the application of encrypted communication to IoT has become possible due to improvements in the computing performance of IoT devices and the development… More >

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