Ishaani Priyadarshini^*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 635-659, 2025, DOI:10.32604/cmc.2025.061062 - 26 March 2025

Abstract Predictive maintenance plays a crucial role in preventing equipment failures and minimizing operational downtime in modern industries. However, traditional predictive maintenance methods often face challenges in adapting to diverse industrial environments and ensuring the transparency and fairness of their predictions. This paper presents a novel predictive maintenance framework that integrates deep learning and optimization techniques while addressing key ethical considerations, such as transparency, fairness, and explainability, in artificial intelligence driven decision-making. The framework employs an Autoencoder for feature reduction, a Convolutional Neural Network for pattern recognition, and a Long Short-Term Memory network for temporal analysis.… More >

Jipu Li¹, Haidong Shao^2,*, Yun Kong³, Zhuyun Chen⁴

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3609-3613, 2025, DOI:10.32604/cmc.2024.062183 - 17 February 2025

Abstract This article has no abstract. More >

Robertas Damasevicius^*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1493-1538, 2025, DOI:10.32604/cmc.2024.057431 - 17 February 2025

Abstract Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering, economics, and computer science. These algorithms are designed to find high-quality solutions efficiently by balancing exploration of the search space and exploitation of promising solutions. While heuristic optimization algorithms vary in their specific details, they often exhibit common patterns that are essential to their effectiveness. This paper aims to analyze and explore common patterns in heuristic optimization algorithms. Through a comprehensive review of the literature, we identify the patterns that are commonly observed in these algorithms, including… More >

YARU DU^1,2,#, ZHIHUI PEI^1,3,#, SHUQIN HU⁴, CHUANWEN LIAO¹, SHUHAO LIU^1,*

Oncology Research, Vol.33, No.2, pp. 309-325, 2025, DOI:10.32604/or.2024.058273 - 16 January 2025

Abstract Objectives: KH-type splicing regulatory protein (KHSRP) is an RNA-binding protein involved in several cellular processes, including nuclear splicing, mRNA localization, and cytoplasmic degradation. While KHSRP’s role has been studied in other cancers, its specific involvement in gastric cancer remains poorly understood. This study aims to explore KHSRP expression in gastric cancer and its potential effects on tumor progression and immune response. Methods: KHSRP expression in gastric cancer tissues and normal tissues was analyzed using data from The Cancer Genome Atlas (TCGA) database. The correlation between KHSRP expression, patient survival, and immune response was also assessed.… More >

Xinwei Wang^1,2,*, Ming Li¹, Hankun Bing¹, Dongxing Zhang¹, Yuanshu Zhang¹

Energy Engineering, Vol.121, No.12, pp. 3875-3898, 2024, DOI:10.32604/ee.2024.056237 - 22 November 2024

Abstract After long-term operation, the performance of components in the GTCC system deteriorates and requires timely maintenance. Due to the inability to directly measure the degree of component malfunction, it is necessary to use advanced exergy analysis diagnosis methods to characterize the components’ health condition (degree of malfunction) through operation data of the GTCC system. The dissipative temperature is used to describe the degree of malfunction of different components in the GTCC system, and an advanced exergy analysis diagnostic method is used to establish a database of overall operating condition component malfunctions in the GTCC system.… More >

Yizhuo Zhu¹, Shaosi He², Deming Lei^2,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 843-866, 2024, DOI:10.32604/cmc.2024.054473 - 15 October 2024

Abstract Unrelated parallel machine scheduling problem (UPMSP) is a typical scheduling one and UPMSP with various real-life constraints such as additional resources has been widely studied; however, UPMSP with additional resources, maintenance, and energy-related objectives is seldom investigated. The Artificial Bee Colony (ABC) algorithm has been successfully applied to various production scheduling problems and demonstrates potential search advantages in solving UPMSP with additional resources, among other factors. In this study, an energy-efficient UPMSP with additional resources and maintenance is considered. A dynamical artificial bee colony (DABC) algorithm is presented to minimize makespan and total energy consumption… More >

Md Naeem Hossain¹, Md Mustafizur Rahman^1,2,*, Devarajan Ramasamy¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 951-996, 2024, DOI:10.32604/cmes.2024.056022 - 27 September 2024

Abstract Conventional fault diagnosis systems have constrained the automotive industry to damage vehicle maintenance and component longevity critically. Hence, there is a growing demand for advanced fault diagnosis technologies to mitigate the impact of these limitations on unplanned vehicular downtime caused by unanticipated vehicle breakdowns. Due to vehicles’ increasingly complex and autonomous nature, there is a growing urgency to investigate novel diagnosis methodologies for improving safety, reliability, and maintainability. While Artificial Intelligence (AI) has provided a great opportunity in this area, a systematic review of the feasibility and application of AI for Vehicle Fault Diagnosis (VFD)… More > Graphic Abstract

Khalilallah Memarzadeh¹, Hamed Kazemipoor^1,*, Mohammad Fallah¹, Babak Farhang Moghaddam²

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1275-1304, 2024, DOI:10.32604/cmes.2024.050306 - 27 September 2024

Abstract Motivated by a critical issue of airline planning process, this paper addresses a new two-stage scenario-based robust optimization in operational airline planning to cope with uncertainty and possible flight disruptions. Following the route network scheme and generated flight timetables, aircraft maintenance routing and crew scheduling are critical factors in airline planning and operations cost management. This study considers the simultaneous assignment of aircraft fleet and crew to the scheduled flight while satisfying a set of operational constraints, rules, and regulations. Considering multiple locations for airline maintenance and crew bases, we solve the problem of integrated… More > Graphic Abstract

V. G. Saranya^*, S. Karthik

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 127-150, 2024, DOI:10.32604/cmes.2024.053825 - 20 August 2024

Abstract Wireless Sensor Networks (WSNs) are a collection of sensor nodes distributed in space and connected through wireless communication. The sensor nodes gather and store data about the real world around them. However, the nodes that are dependent on batteries will ultimately suffer an energy loss with time, which affects the lifetime of the network. This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability. The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization (MFOA-EACO), where the Mayfly Optimization Algorithm (MFOA) is used to… More >

Chao-Lung Yang^1,*, Melkamu Mengistnew Teshome¹, Yu-Zhen Yeh¹, Tamrat Yifter Meles²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3519-3547, 2024, DOI:10.32604/cmc.2024.048462 - 20 June 2024

Abstract In this study, we introduce a novel multi-objective optimization model tailored for modern manufacturing, aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance. Central to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel, addressing a crucial gap in the integration of maintenance personnel dispatching and station selection. Our model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and cost-effectiveness. The core of our methodology is the NSGA III+ Dispatch, an advanced adaptation… More >