Baishun Zhou^1,2, Haijiao Zhao³, Yuxin Wen², Gangyi Ding¹, Ying Xing^3,*, Xinyang Lin⁴, Lei Xiao⁵

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5201-5221, 2025, DOI:10.32604/cmc.2025.065726 - 30 July 2025

Abstract In recent years, with the rapid development of software systems, the continuous expansion of software scale and the increasing complexity of systems have led to the emergence of a growing number of software metrics. Defect prediction methods based on software metric elements highly rely on software metric data. However, redundant software metric data is not conducive to efficient defect prediction, posing severe challenges to current software defect prediction tasks. To address these issues, this paper focuses on the rational clustering of software metric data. Firstly, multiple software projects are evaluated to determine the preset number… More >

Farah Mohammad^1,2,*, Saad Al-Ahmadi^1,3, Jalal Al-Muhtadi^1,3

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5995-6014, 2025, DOI:10.32604/cmc.2025.063046 - 30 July 2025

Abstract Malware continues to pose a significant threat to cybersecurity, with new advanced infections that go beyond traditional detection. Limitations in existing systems include high false-positive rates, slow system response times, and inability to respond quickly to new malware forms. To overcome these challenges, this paper proposes OMD-RAS: Implementing Malware Detection in an Optimized Way through Real-Time and Adaptive Security as an extensive approach, hoping to get good results towards better malware threat detection and remediation. The significant steps in the model are data collection followed by comprehensive preprocessing consisting of feature engineering and normalization. Static… More >

Dae-Kyoo Kim^*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2549-2572, 2025, DOI:10.32604/cmc.2025.066190 - 03 July 2025

Abstract Quantum software development utilizes quantum phenomena such as superposition and entanglement to address problems that are challenging for classical systems. However, it must also adhere to critical quantum constraints, notably the no-cloning theorem, which prohibits the exact duplication of unknown quantum states and has profound implications for cryptography, secure communication, and error correction. While existing quantum circuit representations implicitly honor such constraints, they lack formal mechanisms for early-stage verification in software design. Addressing this constraint at the design phase is essential to ensure the correctness and reliability of quantum software. This paper presents a formal… More >

Smita Mahajan¹, Shilpa Gite^1,2, Biswajeet Pradhan^3,*, Abdullah Alamri⁴, Shaunak Inamdar⁵, Deva Shriyansh⁵, Akshat Ashish Shah⁵, Shruti Agarwal⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 2001-2026, 2025, DOI:10.32604/cmes.2025.058456 - 30 May 2025

Abstract The development of generative architectures has resulted in numerous novel deep-learning models that generate images using text inputs. However, humans naturally use speech for visualization prompts. Therefore, this paper proposes an architecture that integrates speech prompts as input to image-generation Generative Adversarial Networks (GANs) model, leveraging Speech-to-Text translation along with the CLIP + VQGAN model. The proposed method involves translating speech prompts into text, which is then used by the Contrastive Language-Image Pretraining (CLIP) + Vector Quantized Generative Adversarial Network (VQGAN) model to generate images. This paper outlines the steps required to implement such a… More >

Xiaobing Li^1,2, Yongsheng Liu¹, Limin Wei¹, Li Rao¹, Jingxin Mao^1,*, Xuemei Li^3,*

BIOCELL, Vol.49, No.5, pp. 813-832, 2025, DOI:10.32604/biocell.2025.062124 - 27 May 2025

Abstract Yeast-based models have become a powerful platform in pharmaceutical research, offering significant potential for producing complex drugs, vaccines, and therapeutic agents. While many current drugs were discovered before fully understanding their molecular mechanisms, yeast systems now provide valuable insights for drug discovery and personalized medicine. Recent advancements in genetic engineering, metabolic engineering, and synthetic biology have improved the efficiency and scalability of yeast-based production systems, enabling more sustainable and cost-effective manufacturing processes. This paper reviews the latest developments in yeast-based technologies, focusing on their use as model organisms to study disease mechanisms, identify drug targets,… More >

Yuling Luo^1,2, Xiaoguang Lin^1,2, Junxiu Liu^1,2,*, Qiang Fu^1,2, Sheng Qin^1,2, Zhen Min^1,2, Tinghua Hu^1,2

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5323-5343, 2025, DOI:10.32604/cmc.2025.063860 - 19 May 2025

Abstract The majors accredited by the Engineering Education Accreditation (EEA) reflect the accreditation agency’s recognition of the school’s engineering programs. Excellent accreditation management holds significant importance for the advancement of engineering education programs. However, the traditional engineering education system framework suffers from the opacity of raw education data and the difficulty for accreditation bodies to forensically examine the self-assessment reports. To solve these issues, an EEA framework based on Hyperledger Fabric blockchain technology is proposed in this work. Firstly, all relevant stakeholders and information interactions occur within the blockchain network, ensuring the authenticity of educational data More >

Qingqing Song^1,*, Shaoliang Xia¹, Zhen Wu²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2619-2642, 2025, DOI:10.32604/cmc.2025.062526 - 16 April 2025

Abstract Load time series analysis is critical for resource management and optimization decisions, especially automated analysis techniques. Existing research has insufficiently interpreted the overall characteristics of samples, leading to significant differences in load level detection conclusions for samples with different characteristics (trend, seasonality, cyclicality). Achieving automated, feature-adaptive, and quantifiable analysis methods remains a challenge. This paper proposes a Threshold Recognition-based Load Level Detection Algorithm (TRLLD), which effectively identifies different load level regions in samples of arbitrary size and distribution type based on sample characteristics. By utilizing distribution density uniformity, the algorithm classifies data points and ultimately… More >

Yue Liu¹, Qinglang Guo², Chunyao Yang¹, Yong Liao^1,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2555-2572, 2025, DOI:10.32604/cmc.2025.060318 - 16 April 2025

Abstract Processing police incident data in public security involves complex natural language processing (NLP) tasks, including information extraction. This data contains extensive entity information—such as people, locations, and events—while also involving reasoning tasks like personnel classification, relationship judgment, and implicit inference. Moreover, utilizing models for extracting information from police incident data poses a significant challenge—data scarcity, which limits the effectiveness of traditional rule-based and machine-learning methods. To address these, we propose TIPS. In collaboration with public security experts, we used de-identified police incident data to create templates that enable large language models (LLMs) to populate data More >

Nour Elhouda Chalabi¹, Abdelouahab Attia², Abdulaziz S. Almazyad³, Ali Wagdy Mohamed^4,5, Frank Werner⁶, Pradeep Jangir⁷, Mohammad Shokouhifar^8,9,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 967-1008, 2025, DOI:10.32604/cmes.2025.062332 - 11 April 2025

Abstract Multi-objective optimization is critical for problem-solving in engineering, economics, and AI. This study introduces the Multi-Objective Chef-Based Optimization Algorithm (MOCBOA), an upgraded version of the Chef-Based Optimization Algorithm (CBOA) that addresses distinct objectives. Our approach is unique in systematically examining four dominance relations—Pareto, Epsilon, Cone-epsilon, and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto front. Our comparison investigation, which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering, mechanical design, and power systems, reveals that the dominance approach More >

Ruhul Amin¹, Md. Jamil Khan¹, Tonway Deb Nath¹, Md. Shamim Reza², Jungpil Shin^3,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3907-3919, 2025, DOI:10.32604/cmc.2025.061645 - 06 March 2025

Abstract Heart disease includes a multiplicity of medical conditions that affect the structure, blood vessels, and general operation of the heart. Numerous researchers have made progress in correcting and predicting early heart disease, but more remains to be accomplished. The diagnostic accuracy of many current studies is inadequate due to the attempt to predict patients with heart disease using traditional approaches. By using data fusion from several regions of the country, we intend to increase the accuracy of heart disease prediction. A statistical approach that promotes insights triggered by feature interactions to reveal the intricate pattern… More >