Said Benkachcha^1,*, Mustapha Adar¹, Mohamed Maniana², Youssef Najih¹, Mourad Kaddiri¹, Mutapha Mabrouki¹

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.075406 - 27 May 2026

Abstract Accurate forecasting of solar photovoltaic (PV) power generation is essential for enabling reliable integration of renewable energy into modern power systems. Variability in solar production, driven by meteorological fluctuations and inherent nonlinear dynamics, presents significant challenges for grid stability, operational planning, and energy management. This study investigates and compares the performance of classical statistical forecasting techniques and advanced deep learning approaches using real PV production data from a Moroccan solar plant. The analysis focuses on accuracy, robustness, computational efficiency, and suitability for short-term operational applications. Among statistical approaches, the Holt–Winters model demonstrated strong capability in… More > Graphic Abstract

Kirill V. Chernov^1,#, Artemii M. Savin^1,#, Daria E. Otvodnikova¹, Oleg A. Kuchur^1,2, Sergey A. Tsymbal^1,2,*

Oncology Research, Vol.34, No.6, 2026, DOI:10.32604/or.2026.077445 - 21 May 2026

Abstract The formation of drug resistance poses the ultimate threat in modern oncology. Targeted therapy lacks versatility, while conventional therapy is famous for its side effects. However, for the new therapeutics to address the challenge of drug resistance, such compounds should combine properties of both modalities. In this review, we argue that metal-based therapeutics are paramount substances for achieving this goal. The unique physico-chemical properties and metabolism of these compounds, as well as metals themselves, allow to realize unique activities in normal and cancer cells, including precise targeting, non-apoptotic cell death, and disruption of critical signaling More > Graphic Abstract

Akash Garg^*

Journal on Artificial Intelligence, Vol.8, pp. 273-298, 2026, DOI:10.32604/jai.2026.079401 - 12 May 2026

Abstract As cyber threats continue to evolve in scale and sophistication, the need for intelligent and adaptive security mechanisms has become increasingly urgent. Intrusion Detection Systems (IDS) are critical components in safeguarding computer networks from malicious activities. This review paper presents a comprehensive analysis of recent advancements in deep learning-based IDS, examining various architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders, and generative adversarial networks (GANs). The study compares traditional intrusion detection techniques with modern deep learning approaches, highlighting their strengths, limitations, and suitability for real-world deployment. Special attention is given to… More >

Minhyeok Choi¹, Imran Ahsan², Hyunwook Yu¹, Taeyoung Choe¹, Mucheol Kim^1,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079504 - 08 May 2026

Abstract Large language models (LLMs) are increasingly integrated into recommender systems to support semantic reasoning, natural language understanding, and user-adaptive personalization. However, their reliance on static parametric knowledge and fixed representations limits robustness in dynamic environments, particularly under long-tail and cold-start conditions. Retrieval-augmented architectures have emerged to address these limitations by grounding LLMs in external, non-parametric knowledge sources. This systematic literature review synthesizes 138 peer-reviewed studies published between 2023 and 2025 in conferences and journals, focusing on retrieval-augmented and LLM-enhanced recommendation. We analyze these works through a three-dimensional framework covering: (i) domain application, (ii) semantic feature… More >

Ali Hamidoğlu^1,2, Ali Elghirani^3,4, Ömer Melih Gül^5,6,7, Seifedine Kadry^8,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077060 - 09 April 2026

Abstract Multi-Robot Task Allocation (MRTA) has proven its importance in the current and near-future era, wherein in every aspect of life, there will be robots to handle tasks effectively and efficiently. While there has been a growing interest in MRTA problems in the robotics industry, the question arises of how to make robots more decentralized and intelligent through rational decision-makers rather than ones that are centralized and filled with black boxes. This survey aims to address that question by examining recent MRTA literature and exploring topics including MRTA taxonomy, centralized and decentralized controls, static and dynamic… More >

Raed Alotaibi^1,*, Muhammad Atta Othman Ahmed², Omar Reyad^3,4,*, Nahla Fathy Omran⁵

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076156 - 09 April 2026

Abstract The widespread use of social media has made assessing users’ tastes and preferences increasingly complex and important. At the same time, the rapid dissemination of misinformation on these platforms poses a critical challenge, driving significant efforts to develop effective detection methods. This study offers a comprehensive analysis leveraging advanced Machine Learning (ML) techniques to classify news articles as fake or true, contributing to discourse on media integrity and combating misinformation. The suggested method employed a diverse dataset encompassing a wide range of topics. The method evaluates the performance of five ML models: Artificial Neural Networks… More >

Ehsan Momeni¹, Mohammad Dehghannezhad¹, Fereydoon Omidinasab¹, Danial Jahed Armaghani^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.077300 - 30 March 2026

Abstract In the last decade, the importance of sustainable construction and artificial intelligence (AI) in civil engineering has been underlined in many studies. Numerous studies highlighted the superiority of AI techniques over simple and mathematical regression analyses, which suffer from relatively poor generalization and an inability to capture highly non-linear relationships among inputs and output(s) parameters. In this study, to evaluate the compressive strength of concrete with glass powder (GP) and recycled aggregates, 600 concrete samples were tested in the laboratory, and their results were evaluated. For intelligent assessment of concrete compressive strength (CCS), the study… More >

Mahboobeh Attaei^1,2, Maria Vieira¹, Cinthia Maia Pederneiras^3,4,*, Filipa Clara Coimbra¹, David Bastos¹, Rosário Veiga³

Energy Engineering, Vol.123, No.4, 2026, DOI:10.32604/ee.2026.074246 - 27 March 2026

Abstract The construction industry is a significant contributor to global CO₂ emissions, and urgent innovation is needed to mitigate its environmental impact. This paper provides a comprehensive review of scalable approaches for CO₂ uptake in construction materials, including the injection of CO₂ into fresh concrete, the CO₂ curing of precast concrete, and the use of ceramics as CO₂ sinks. Among these three approaches, CO₂ curing methods for concrete represent the most advanced and widely adopted strategies within industrial practice, with substantial research supporting their effectiveness and scalability. The comparison of carbonation mineralisation across three distinct material groups reveals that… More > Graphic Abstract

Eshita Dhar^1,2, Muhammad Ashad Kabir³, Divyabharathy Ramesh Nadar⁴, Li-Jen Kuo⁵, Jitendra Jonnagaddala^6,7, Yaoru Huang¹, Mohy Uddin^8,*, Shabbir Syed-Abdul^1,2,9,*

Oncology Research, Vol.34, No.4, 2026, DOI:10.32604/or.2026.074385 - 23 March 2026

Abstract Objectives: Decisions regarding CT after nCCRT for locally advanced rectal cancer (LARC) are challenging due to limited evidence guiding treatment. This study aimed to (i) evaluate the predictive performance of machine learning (ML) models in patients treated with neoadjuvant concurrent chemoradiotherapy (nCCRT) alone vs. those receiving nCCRT plus chemotherapy (CT), (ii) identify features associated with treatment improvement, and (iii) derive ML-based thresholds for treatment response. Methods: This retrospective study included 409 patients with LARC treated at three affiliated hospitals of Taipei Medical University. Patients were categorised into two groups: nCCRT alone followed by surgery (n =… More >

Sophiette G. Hong^1,2, George F. Murphy², Christine G. Lian^2,*

Oncology Research, Vol.34, No.4, 2026, DOI:10.32604/or.2026.073894 - 23 March 2026

Abstract Malignant melanoma (MM) is a highly aggressive skin cancer known for its rapid progression, potential for metastasis, and resistance to treatment. Despite advances in targeted therapies and immunotherapy, the prognosis for metastatic melanoma remains unfavorable. Recent research has shed light on the significance of epigenetic modifications in the pathogenesis of melanoma, revealing critical mechanisms of melanoma development and progression. Epigenetic modifications, including DNA and RNA modifications, histone modifications, chromatin remodeling, and non-coding RNA regulation, disrupt normal gene expression without modifying the DNA sequence, leading to cellular transformation, invasion, immune evasion, and therapeutic resistance. The reversible… More >