Alireza Bahmani^*

Journal on Internet of Things, Vol.7, pp. 1-17, 2025, DOI:10.32604/jiot.2025.060786 - 24 June 2025

Abstract With the development of the Internet of Things (IoT) technology and its widespread integration in various aspects of life, the risks associated with cyberattacks on these systems have increased significantly. Vulnerabilities in IoT devices, stemming from insecure designs and software weaknesses, have made attacks on them more complex and dangerous compared to traditional networks. Conventional intrusion detection systems are not fully capable of identifying and managing these risks in the IoT environment, making research and evaluation of suitable intrusion detection systems for IoT crucial. In this study, deep learning, multi-layer perceptron (MLP), Random Forest (RF),… More >

Ye Zeng^1,*, Bingmei M. FU^2,*

BIOCELL, Vol.49, No.6, pp. 925-930, 2025, DOI:10.32604/biocell.2025.065879 - 24 June 2025

Abstract This article has no abstract. More >

Nila Cecília Faria Lopes Medeiros^1,2, Gisele Amaral-Labat¹, Leonardo Iusuti de Medeiros^1,2, Alan Fernando Ney Boss¹, Beatriz Carvalho da Silva Fonseca¹, Manuella Gobbo de Castro Munhoz³, Guilherme F. B. Lenz e Silva³, Mauricio Ribeiro Baldan¹, Flavia Lega Braghiroli^4,*

Journal of Renewable Materials, Vol.13, No.6, pp. 1021-1042, 2025, DOI:10.32604/jrm.2025.02025-0017 - 23 June 2025

Abstract Biochar, a carbon-rich material derived from the thermochemical conversion of biomass under oxygen-free conditions, has emerged as a sustainable resource for radar-absorbing technologies. This study explores the production of activated biochars from end-of-life wood panels using a scalable and sustainable physical activation method with CO₂ at different temperatures, avoiding the extensive use of corrosive chemicals and complex procedures associated with chemical or vacuum activation. Compared to conventional chemically or vacuum-activated biochars, the physically activated biochar demonstrated competitive performance while minimizing environmental impact, operational complexity, and energy consumption. Furthermore, activation at 750°C reduces energy consumption by 14%… More > Graphic Abstract

Farah Syazwani Shahar¹, Thinesh Sharma Balakrishnan², Mohamed Thariq Hameed Sultan^2,3,*

Journal of Renewable Materials, Vol.13, No.6, pp. 1071-1101, 2025, DOI:10.32604/jrm.2024.02024-0011 - 23 June 2025

Abstract In this comprehensive review, the evolution and progress of bioplastics are examined, with an emphasis on their types, production methods, environmental impact, and biodegradability. In light of the increasing global efforts to address environmental degradation, bioplastics have emerged as a highly potential substitute for conventional petroleum-based plastics. This review classifies various categories of bioplastics, encompassing both biodegradable and bio-based variations, and assesses their environmental consequences using life cycle evaluations and biodegradability calculations. This paper analyzes the technological advancements that have enhanced the mechanical and thermal characteristics of bioplastics, hence increasing their feasibility for extensive commercial… More > Graphic Abstract

Panji Setya Utama Putra¹, Damar Rastri Adhika^2,3,*, Lia Amelia Tresna Wulan Asri⁴, Suprijadi Suprijadi^3,5

Journal of Renewable Materials, Vol.13, No.6, pp. 1043-1070, 2025, DOI:10.32604/jrm.2025.02024-0002 - 23 June 2025

Abstract The continuous increase in petroleum-based plastic food packaging has led to numerous environmental concerns. One effort to reduce the use of plastic packaging in food is through preservation using biopolymer-based packaging. Among the many types of biopolymers, chitosan is widely used and researched due to its non-toxic, antimicrobial, and antifungal properties. Chitosan is widely available since it is a compound extracted from seafood waste, especially shrimps and crabs. The biodegradability and biocompatibility of chitosan also showed good potential for various applications. These characteristics and properties make chitosan an attractive biopolymer to be implemented as food… More > Graphic Abstract

Canadian Journal of Urology, Vol.32, No.2, pp. 1767-1767, 2025

Abstract This article has no abstract. More >

Xingsi Xue¹, Himanshu Dhumras^2,*, Garima Thakur³, Rakesh Kumar Bajaj⁴, Varun Shukla⁵

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 583-606, 2025, DOI:10.32604/cmc.2025.066310 - 09 June 2025

Abstract Ensuring a sustainable and eco-friendly environment is essential for promoting a healthy and balanced social life. However, decision-making in such contexts often involves handling vague, imprecise, and uncertain information. To address this challenge, this study presents a novel multi-criteria decision-making (MCDM) approach based on picture fuzzy hypersoft sets (PFHSS), integrating the flexibility of Schweizer-Sklar triangular norm-based aggregation operators. The proposed aggregation mechanisms—weighted average and weighted geometric operators—are formulated using newly defined operational laws under the PFHSS framework and are proven to satisfy essential mathematical properties, such as idempotency, monotonicity, and boundedness. The decision-making model systematically… More >

Seungmin Lee¹, Beomseong Kim², Heesung Lee^3,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1397-1415, 2025, DOI:10.32604/cmc.2025.066152 - 09 June 2025

Abstract This study proposes an advanced vision-based technology for detecting glass products and identifying defects in a smart glass factory production environment. Leveraging artificial intelligence (AI) and computer vision, the research aims to automate glass detection processes and maximize production efficiency. The primary focus is on developing a precise glass detection and quality management system tailored to smart manufacturing environments. The proposed system utilizes the various YOLO (You Only Look Once) models for glass detection, comparing their performance to identify the most effective architecture. Input images are preprocessed using a Gaussian Mixture Model (GMM) to remove… More >

Mukesh Dalal^1,*, Payal Mittal²

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 57-91, 2025, DOI:10.32604/cmc.2025.066056 - 09 June 2025

Abstract Deep learning-based object detection has revolutionized various fields, including agriculture. This paper presents a systematic review based on the PRISMA 2020 approach for object detection techniques in agriculture by exploring the evolution of different methods and applications over the past three years, highlighting the shift from conventional computer vision to deep learning-based methodologies owing to their enhanced efficacy in real time. The review emphasizes the integration of advanced models, such as You Only Look Once (YOLO) v9, v10, EfficientDet, Transformer-based models, and hybrid frameworks that improve the precision, accuracy, and scalability for crop monitoring and More >

Ammar Odeh^*, Anas Abu Taleb

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 447-461, 2025, DOI:10.32604/cmc.2025.065426 - 09 June 2025

Abstract The increasing deployment of Internet of Things (IoT) devices has introduced significant security challenges, including identity spoofing, unauthorized access, and data integrity breaches. Traditional security mechanisms rely on centralized frameworks that suffer from single points of failure, scalability issues, and inefficiencies in real-time security enforcement. To address these limitations, this study proposes the Blockchain-Enhanced Trust and Access Control for IoT Security (BETAC-IoT) model, which integrates blockchain technology, smart contracts, federated learning, and Merkle tree-based integrity verification to enhance IoT security. The proposed model eliminates reliance on centralized authentication by employing decentralized identity management, ensuring tamper-proof… More >