Liqiu Suo¹, Lin Xia¹, Yoona Chung¹, Eunchan Kim^1,2,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.076329 - 10 February 2026

Abstract Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features. This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three layers: Basic, Conversion & Stability (efficiency and volatility across actions), and Advanced Interactions & Activity (cross-behavior synergies and intensity). Using real Taobao (Alibaba’s primary e-commerce platform) logs (57,976 records for 10,203 users; 25 November–03 December 2017), we conducted a hierarchical, layer-wise evaluation that holds data splits and hyperparameters fixed while varying only the feature set to quantify each layer’s marginal contribution. Across logistic regression (LR), decision… More >

Lishu Qin^*, Yu Gao, Xinyuan Lu

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074739 - 10 February 2026

Abstract With the rapid development of intelligent navigation technology, efficient and safe path planning for mobile robots has become a core requirement. To address the challenges of complex dynamic environments, this paper proposes an intelligent path planning framework based on grid map modeling. First, an improved Safe and Smooth A* (SSA*) algorithm is employed for global path planning. By incorporating obstacle expansion and corner-point optimization, the proposed SSA* enhances the safety and smoothness of the planned path. Then, a Partitioned Dynamic Window Approach (PDWA) is integrated for local planning, which is triggered when dynamic or sudden… More >

Zhendong Du^*, Hanliu Wang, Kenji Hashimoto

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074520 - 10 February 2026

Abstract Planning in lexical-prior-free environments presents a fundamental challenge for evaluating whether large language models (LLMs) possess genuine structural reasoning capabilities beyond lexical memorization. When predicates and action names are replaced with semantically irrelevant random symbols while preserving logical structures, existing direct generation approaches exhibit severe performance degradation. This paper proposes a symbol-agnostic closed-loop planning pipeline that enables models to construct executable plans through systematic validation and iterative refinement. The system implements a complete generate-verify-repair cycle through six core processing components: semantic comprehension extracts structural constraints, language planner generates text plans, symbol translator performs structure-preserving mapping,… More >

Sara Tehsin¹, Inzamam Mashood Nasir^1,*, Wiem Abdelbaki², Fadwa Alrowais³, Khalid A. Alattas⁴, Sultan Almutairi⁵, Radwa Marzouk⁶

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074416 - 10 February 2026

Abstract Objective: Deep learning is employed increasingly in Gastroenterology (GI) endoscopy computer-aided diagnostics for polyp segmentation and multi-class disease detection. In the real world, implementation requires high accuracy, therapeutically relevant explanations, strong calibration, domain generalization, and efficiency. Current Convolutional Neural Network (CNN) and transformer models compromise border precision and global context, generate attention maps that fail to align with expert reasoning, deteriorate during cross-center changes, and exhibit inadequate calibration, hence diminishing clinical trust. Methods: HMA-DER is a hierarchical multi-attention architecture that uses dilation-enhanced residual blocks and an explainability-aware Cognitive Alignment Score (CAS) regularizer to directly align… More >

Noura Mohammed Alaskar¹, Muzammil Hussain², Saif Jasim Almheiri¹, Atta-ur-Rahman³, Adnan Khan^4,5,6, Khan M. Adnan^7,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074041 - 10 February 2026

Abstract The increasing number of interconnected devices and the incorporation of smart technology into contemporary healthcare systems have significantly raised the attack surface of cyber threats. The early detection of threats is both necessary and complex, yet these interconnected healthcare settings generate enormous amounts of heterogeneous data. Traditional Intrusion Detection Systems (IDS), which are generally centralized and machine learning-based, often fail to address the rapidly changing nature of cyberattacks and are challenged by ethical concerns related to patient data privacy. Moreover, traditional AI-driven IDS usually face challenges in handling large-scale, heterogeneous healthcare data while ensuring data… More >

Feihong Xu¹, Jianbo Wu^1,*, Qing An^1,*, Fei Zhu^1,2, Zhaoyang Han³, Saru Kumari⁴

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073441 - 10 February 2026

Abstract The large-scale deployment of Internet of Things (IoT) technology across various aspects of daily life has significantly propelled the intelligent development of society. Among them, the integration of IoT and named data networks (NDNs) reduces network complexity and provides practical directions for content-oriented network design. However, ensuring data integrity in NDN-IoT applications remains a challenging issue. Very recently, Wang et al. (Entropy, 27(5), 471(2025)) designed a certificateless aggregate signature (CLAS) scheme for NDN-IoT environments. Wang et al. stated that their construction was provably secure under various types of security attacks. Using theoretical analysis methods, in… More >

Jianing Wu¹, Yufeng Chen^1,*, Li Yin¹, Huajun He², Panshuan Jin²

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072937 - 10 February 2026

Abstract To conduct marine surveys, multiple unmanned surface vessels (Multi-USV) with different capabilities perform collaborative mapping in multiple designated areas. This paper proposes a task allocation algorithm based on integer linear programming (ILP) with flow balance constraints, ensuring the fair and efficient distribution of sub-areas among USVs and maintaining strong connectivity of assigned regions. In the established grid map, a search-based path planning algorithm is performed on the sub-areas according to the allocation scheme. It uses the greedy algorithm and the A* algorithm to achieve complete coverage of the barrier-free area and obtain an efficient trajectory More >

Yingkai Ge, Jiasheng Zhang, Jiale Zhang, Zhenguo Ma, Yu Liu, Lihua Wang^*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072799 - 10 February 2026

Abstract With the continuous development of artificial intelligence and computer vision technology, numerous deep learning-based lane line detection methods have emerged. DeepLabv3+, as a classic semantic segmentation model, has found widespread application in the field of lane line detection. However, the accuracy of lane line segmentation is often compromised by factors such as changes in lighting conditions, occlusions, and wear and tear on the lane lines. Additionally, DeepLabv3+ suffers from high memory consumption and challenges in deployment on embedded platforms. To address these issues, this paper proposes a lane line detection method for complex road scenes… More >

Hui Chen¹, Mohammed A. H. Ali^1,*, Bushroa Abd Razak¹, Zhenya Wang², Yusoff Nukman¹, Shikai Zhang¹, Zhiwei Huang¹, Ligang Yao³, Mohammad Alkhedher⁴

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2026.065539 - 10 February 2026

Abstract Most existing path planning approaches rely on discrete expansions or localized heuristics that can lead to extended re-planning, inefficient detours, and limited adaptability to complex obstacle distributions. These issues are particularly pronounced when navigating cluttered or large-scale environments that demand both global coverage and smooth trajectory generation. To address these challenges, this paper proposes a Wave Water Simulator (WWS) algorithm, leveraging a physically motivated wave equation to achieve inherently smooth, globally consistent path planning. In WWS, wavefront expansions naturally identify safe corridors while seamlessly avoiding local minima, and selective corridor focusing reduces computational overhead in More >

Bo Su¹, Mwansa Chambalile¹, Shihao He¹, Wan Sun², Enyuan Zhang¹, Tong Guo³, Jianming Hao⁴, Md. Mahbub Alam^5,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.076681 - 06 February 2026

Abstract Predicting the precise impacts of climate change on extreme winds remains challenging, yet strong storms are widely expected to occur more frequently in a warming climate. Wind barriers are commonly used on bridges to reduce aerodynamic loads on trains through blocking effects. This study develops a novel wind barrier based on Tesla valves, which not only blocks incoming flow but also dissipates mechanical energy through fluid collision. To demonstrate this energy-dissipation capability, a Tesla plate is placed in a circular duct to examine its influence on pressure drop. Experimental tests and numerical simulations comparing a… More >