MD Tausif Mallick¹, Saptarshi Banerjee², Nityananda Thakur³, Himadri Nath Saha^4,*, Amlan Chakrabarti¹

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 121-180, 2025, DOI:10.32604/cmc.2025.065250 - 29 August 2025

Abstract Addressing plant diseases and pests is not just crucial; it’s a matter of utmost importance for enhancing crop production and preventing economic losses. Recent advancements in artificial intelligence, machine learning, and deep learning have revolutionised the precision and efficiency of this process, surpassing the limitations of manual identification. This study comprehensively reviews modern computer-based techniques, including recent advances in artificial intelligence, for detecting diseases and pests through images. This paper uniquely categorises methodologies into hyperspectral imaging, non-visualisation techniques, visualisation approaches, modified deep learning architectures, and transformer models, helping researchers gain detailed, insightful understandings. The exhaustive… More >

Muhamad Ammar Hanif Arif¹, Amir Sharifuddin Ab Latip^1,*, Siti Balqis Mohd Tun¹, Nur Azlina Hariffin¹, Adel Gohari², Mohd Hakimi Abdul Rahman¹

Revue Internationale de Géomatique, Vol.34, pp. 691-705, 2025, DOI:10.32604/rig.2025.065949 - 29 August 2025

Abstract Digital Elevation Model (DEM) refers to a digital map of the surface of the Earth that only shows the bare ground, without any buildings, plants, or other characteristics. However, obtaining unlimited access to DEM data at high and medium resolutions is very hard. Consequently, users often question the accuracy of freely available DEMs and their suitability for various applications. By comparing them to Global Positioning System (GPS) elevation data, this study aimed to identify the most reliable and widely available DEM for various terrains. The objectives of this study were to generate DEMs from different… More >

Yizhou Wang¹, Qinghai Zhao^2,*, Guoqing Li¹, Xudong Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 763-789, 2025, DOI:10.32604/cmes.2025.067363 - 31 July 2025

Abstract Lattice structures have attracted extensive attention in the field of engineering materials due to their characteristics of lightweight and high strength. This paper combines topology optimization with additive manufacturing to investigate how pore shape in Triply Periodic Minimal Surface (TPMS) structures affects mechanical properties and energy absorption performance. The periodic lattice structures (Triangle lattice, rectangle lattice and Rectangle lattice) and aperiodic mixed structures are designed, including a variety of lattice structures such as circle-circle and triangle-triangle (CCTT), triangle-triangle and rectangle-rectangle (TTRR), circle-circle and rectangle-rectangle (CCRR), triangle-circle-circle-triangle (TCCT), rectangle-triangle-triangle-rectangle (RTTR) and rectangle-circle-circle-rectangle (RCCR). The anisotropy of… More >

Muhammad Usama¹, Arshad Aziz², Imtiaz Hassan², Shynar Akhmetzhanova³, Sultan Noman Qasem^4,*, Abdullah M. Albarrak⁴, Tawfik Al-Hadhrami⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 1225-1248, 2025, DOI:10.32604/cmes.2025.067098 - 31 July 2025

Abstract The increasing reliance on digital infrastructure in modern healthcare systems has introduced significant cybersecurity challenges, particularly in safeguarding sensitive patient data and maintaining the integrity of medical services. As healthcare becomes more data-driven, cyberattacks targeting these systems continue to rise, necessitating the development of robust, domain-adapted Intrusion Detection Systems (IDS). However, current IDS solutions often lack access to domain-specific datasets that reflect realistic threat scenarios in healthcare. To address this gap, this study introduces HCKDDCUP, a synthetic dataset modeled on the widely used KDDCUP benchmark, augmented with healthcare-relevant attributes such as patient data, treatments, and… More >

Cuiping Yuan^1,2,*, Sicun Zhong^1,3,*, Yijia Wu^1,3, Man Chen⁴, Ying Wang^1,3, Yinping Cao⁵, Jia Chen^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.7, pp. 1689-1710, 2025, DOI:10.32604/fdmp.2025.065151 - 31 July 2025

Abstract Field development practices in many shale gas regions (e.g., the Changning region) have revealed a persistent issue of suboptimal reserve utilization, particularly in areas where the effective drainage width of production wells is less than half the inter-well spacing (typically 400–500 m). To address this, infill drilling has become a widely adopted and effective strategy for enhancing reservoir contact and mobilizing previously untapped reserves. However, this approach has introduced significant inter-well interference, complicating production dynamics and performance evaluation. The two primary challenges hindering efficient deployment of infill wells are: (1) the quantitative assessment of hydraulic… More >

Haider Ali, Rashadul Islam Sumon, Abdul Rehman Khalid, Kounen Fathima, Hee Cheol Kim^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5445-5462, 2025, DOI:10.32604/cmc.2025.065992 - 30 July 2025

Abstract Artificial intelligence is reshaping radiology by enabling automated report generation, yet evaluating the clinical accuracy and relevance of these reports is a challenging task, as traditional natural language generation metrics like BLEU and ROUGE prioritize lexical overlap over clinical relevance. To address this gap, we propose a novel semantic assessment framework for evaluating the accuracy of artificial intelligence-generated radiology reports against ground truth references. We trained 5229 image–report pairs from the Indiana University chest X-ray dataset on the R2GenRL model and generated a benchmark dataset on test data from the Indiana University chest X-ray and… More >

Ayoub Mhaouch^1,*, Wafa Gtifa², Turke Althobaiti³, Hamzah Faraj⁴, Mohsen Machhout¹

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5637-5663, 2025, DOI:10.32604/cmc.2025.065525 - 30 July 2025

Abstract In medical imaging, accurate brain tumor classification in medical imaging requires real-time processing and efficient computation, making hardware acceleration essential. Field Programmable Gate Arrays (FPGAs) offer parallelism and reconfigurability, making them well-suited for such tasks. In this study, we propose a hardware-accelerated Convolutional Neural Network (CNN) for brain cancer classification, implemented on the PYNQ-Z2 FPGA. Our approach optimizes the first Conv2D layer using different numerical representations: 8-bit fixed-point (INT8), 16-bit fixed-point (FP16), and 32-bit fixed-point (FP32), while the remaining layers run on an ARM Cortex-A9 processor. Experimental results demonstrate that FPGA acceleration significantly outperforms the… More >

Xiaogang Yuan^*, Huan Pei, Yanlin Wu

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5555-5575, 2025, DOI:10.32604/cmc.2025.063537 - 30 July 2025

Abstract In the complex environment of Wireless Sensor Networks (WSNs), various malicious attacks have emerged, among which internal attacks pose particularly severe security risks. These attacks seriously threaten network stability, data transmission reliability, and overall performance. To effectively address this issue and significantly improve intrusion detection speed, accuracy, and resistance to malicious attacks, this research designs a Three-level Intrusion Detection Model based on Dynamic Trust Evaluation (TIDM-DTE). This study conducts a detailed analysis of how different attack types impact node trust and establishes node models for data trust, communication trust, and energy consumption trust by focusing… More >

Fatma Bunyan Unel^1,*, 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 >

Josh McNett¹, Jackie McNett^2,*

Journal of Cyber Security, Vol.7, pp. 279-306, 2025, DOI:10.32604/jcs.2025.067514 - 25 July 2025

Abstract This review explores the implementation and effectiveness of continuous evaluation programs in managing and mitigating insider threats within organizations. Continuous evaluation programs involve the ongoing assessment of individuals’ suitability for access to sensitive information and resources by monitoring their behavior, access patterns, and other indicators in real-time. The review was conducted using a comprehensive search across various academic and professional databases, including IEEE Xplore, SpringerLink, and Google Scholar and papers were selected from a time span of 2015–2023. The review outlines the importance of defining the scope and objectives of such programs, which should include… More >