Illia Khurtin^*, Mukesh Prasad

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-15, 2026, DOI:10.32604/cmc.2025.067481 - 09 December 2025

Abstract The field of artificial intelligence has advanced significantly in recent years, but achieving a human-like or Artificial General Intelligence (AGI) remains a theoretical challenge. One hypothesis suggests that a key issue is the formalisation of extracting meaning from information. Meaning emerges through a three-stage interpretative process, where the spectrum of possible interpretations is collapsed into a singular outcome by a particular context. However, this approach currently lacks practical grounding. In this research, we developed a model based on contexts, which applies interpretation principles to the visual information to address this gap. The field of computer… More >

Jinghua Yang¹, Bin Gong^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-2, 2025, DOI: 10.32604/icces.2025.011889

Abstract Geological stratification interpretation divides geological strata based on acquired well-logging data, providing comparative analysis results for strata and structures. This process serves as a fundamental framework for subsequent drilling and development design plans, making it a crucial step in oil exploration and development process. Traditional geological stratification interpretation methods are based primarily on geological, logging, and experimental data, with manual determination of strata boundaries to obtain interpretation results. However, manual interpretation is characterized by strong subjectivity and reliance on experience, which may compromise the quality and consistency of the results. To eliminate the dependency on… More >

Shubham Desai, Sai Sidhardh^*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1271-1334, 2025, DOI:10.32604/cmes.2025.068141 - 31 August 2025

Abstract The increasing integration of small-scale structures in engineering, particularly in Micro-Electro-Mechanical Systems (MEMS), necessitates advanced modeling approaches to accurately capture their complex mechanical behavior. Classical continuum theories are inadequate at micro- and nanoscales, particularly concerning size effects, singularities, and phenomena like strain softening or phase transitions. This limitation follows from their lack of intrinsic length scale parameters, crucial for representing microstructural features. Theoretical and experimental findings emphasize the critical role of these parameters on small scales. This review thoroughly examines various strain gradient elasticity (SGE) theories commonly employed in literature to capture these size-dependent effects… More >

Ali Mohammad Alqudah¹, Zahra Moussavi^1,2,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3753-3841, 2025, DOI:10.32604/cmc.2025.063643 - 19 May 2025

Abstract This review presents a comprehensive technical analysis of deep learning (DL) methodologies in biomedical signal processing, focusing on architectural innovations, experimental validation, and evaluation frameworks. We systematically evaluate key deep learning architectures including convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformer-based models, and hybrid systems across critical tasks such as arrhythmia classification, seizure detection, and anomaly segmentation. The study dissects preprocessing techniques (e.g., wavelet denoising, spectral normalization) and feature extraction strategies (time-frequency analysis, attention mechanisms), demonstrating their impact on model accuracy, noise robustness, and computational efficiency. Experimental results underscore the superiority of deep learning… More >

Steven P. Rowe^1,2,3, Andrew F. Voter^1,4, Rudolf A. Werner^1,5, Katherine A. Zukotynski^6,7,8, Martin G. Pomper^1,2,3, Michael A. Gorin⁹, Lilja B. Solnes^1,3

Canadian Journal of Urology, Vol.30, No.1, pp. 11432-11437, 2023

Abstract Prostate-specific membrane antigen (PSMA)-targeted positron emission tomography (PET) is rapidly becoming widely accepted as the standard-of-care for imaging of men with prostate cancer. Labeled indications for regulatoryapproved agents include primary staging and recurrent disease in men at risk of metastases. The first commercial PSMA PET agent to become available was 18F-DCFPyL (piflufolastat F 18), a radiofluorinated small molecule with high-affinity for PSMA. The regulatory approval of 18F-DCFPyL hinged upon two key, multi-center, registration trials, OSPREY (patient population: highrisk primary staging) and CONDOR (patient population: biochemical recurrence). In this manuscript, we will (1) review key findings More >

Ting Zhang, Yifei Wang, Xinxin Jin, Zhiwen Gu, Xiaoliang Zhang, Bin He^*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2267-2285, 2023, DOI:10.32604/cmes.2023.023229 - 23 November 2022

Abstract Auto-grading, as an instruction tool, could reduce teachers’ workload, provide students with instant feedback and support highly personalized learning. Therefore, this topic attracts considerable attentions from researchers recently. To realize the automatic grading of handwritten chemistry assignments, the problem of chemical notations recognition should be solved first. The recent handwritten chemical notations recognition solutions belonging to the end-to-end trainable category suffered from the problem of lacking the accurate alignment information between the input and output. They serve the aim of reading notations into electrical devices to better prepare relevant e-documents instead of auto-grading handwritten assignments.… More >

Muhammad Hasnain¹, Imran Ghani², Seung Ryul Jeong^3,*, Muhammad Fermi Pasha⁴, Sardar Usman⁵, Anjum Abbas⁶

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 783-799, 2023, DOI:10.32604/cmc.2023.030162 - 22 September 2022

Abstract Forecasting on success or failure of software has become an interesting and, in fact, an essential task in the software development industry. In order to explore the latest data on successes and failures, this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework? What human factors contribute to success or failure of a software? What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work? In order to… More >

Jie Chen¹, Jiabao Xu¹, Xuefeng Xi^1,*, Zhiming Cui¹, Victor S. Sheng²

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 747-761, 2023, DOI:10.32604/cmes.2022.020771 - 24 August 2022

Abstract Interpreting deep neural networks is of great importance to understand and verify deep models for natural language processing (NLP) tasks. However, most existing approaches only focus on improving the performance of models but ignore their interpretability. In this work, we propose a Randomly Wired Graph Neural Network (RWGNN) by using graph to model the structure of Neural Network, which could solve two major problems (word-boundary ambiguity and polysemy) of Chinese NER. Besides, we develop a pipeline to explain the RWGNN by using Saliency Map and Adversarial Attacks. Experimental results demonstrate that our approach can identify More >

Jintao Fu¹, Yong Zhou^1,*, Qian Qiu², Guangwei Xu³, Neng Wan³

Journal of Quantum Computing, Vol.4, No.3, pp. 147-163, 2022, DOI:10.32604/jqc.2022.038358 - 03 July 2023

Abstract In the field of computer research, the increase of data in result of societal progress has been remarkable, and the management of this data and the analysis of linked businesses have grown in popularity. There are numerous practical uses for the capability to extract key characteristics from secondary property data and utilize these characteristics to forecast home prices. Using regression methods in machine learning to segment the data set, examine the major factors affecting it, and forecast home prices is the most popular method for examining pricing information. It is challenging to generate precise forecasts… More >

D. L. Khokhlov^*

Journal of Quantum Computing, Vol.2, No.3, pp. 147-150, 2020, DOI:10.32604/jqc.2020.014734 - 31 December 2020

Abstract An interpretation of the entangled states is considered. Two-photon states of photon A on path a and photon B on path b with polarizations H, V are constructed. Two synchronized photons, 1 and 2, can take the paths a and b, with equal probability 50%. In the bases a, b and H, V, the states of the photons form the product states. In the basis 1, 2, the states of the photons form the entangled state. The states of the photons in the bases 1, 2; a, b; H, V are inseparable. The correlation of the photons due to the entanglement in the More >