Verônica Távilla Ferreira Silva, Adriane Maria Ferreira Milagres^*

Journal of Renewable Materials, Vol.12, No.3, pp. 539-551, 2024, DOI:10.32604/jrm.2023.045726

Abstract This study was conducted to evaluate the effectiveness of enzymes in purifying and reducing the degree of polymerization of cellulose for the production of dissolving pulp. Our goal was to determine the contributions of xylanase (X) and endoglucanase (EG) in the treatment of pulp, specifically by quantifying the formation of soluble and insoluble reducing sugars using the dinitrosalycilic acid (DNS) test. Predominantly, the release of soluble reducing sugars (RSSol) was enhanced after xylanase treatment, while endoglucanase (EG) treatment led to changes in insoluble reducing sugars (RSIns). The maximum synergism was observed for RSIns when a high ratio of endoglucanase to… More > Graphic Abstract

ANIL KUMAR VEERAPANENI¹, CHANDRASEKAR KUPPAN^2,*, MURTHY CHAVALI^3,*

Journal of Polymer Materials, Vol.37, No.3-4, pp. 121-130, 2020, DOI:10.32381/JPM.2020.37.3-4.1

Abstract The mechanical properties of hybrid nanocomposites made of epoxy/glass fibre dispersed with nano-α-Al₂ O₃ powder at different weight percentages were studied.The effect of nano-α- Al₂O₃ size and wt% on mechanical properties like tensile, flexural, interlaminar shear stress and hardness enhanced because of their higher surface area and interfacial polymer-metal interaction. The nanoparticle embedded laminates have shown improvement in flexural strength,and hardness when compared to laminate without nano-α-Al₂ O₃. The properties varied with the loading and size of the nanoparticles. The tensile strength was highest for 0.5 wt% of 200nm nano-α-Al₂O₃, which is 167.80 N/m₂.The highest flexural strength was observed for… More >

Muhammad Binsawad^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3645-3663, 2024, DOI:10.32604/cmc.2024.048183

Abstract Malware is an ever-present and dynamic threat to networks and computer systems in cybersecurity, and because of its complexity and evasiveness, it is challenging to identify using traditional signature-based detection approaches. The study article discusses the growing danger to cybersecurity that malware hidden in PDF files poses, highlighting the shortcomings of conventional detection techniques and the difficulties presented by adversarial methodologies. The article presents a new method that improves PDF virus detection by using document analysis and a Logistic Model Tree. Using a dataset from the Canadian Institute for Cybersecurity, a comparative analysis is carried out with well-known machine learning… More >

Nguyen Vu Anh Duy, Nguyen Le Thai, Nguyen Huu Tho^*

Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 15-31, 2024, DOI:10.32604/iasc.2024.038272

Abstract In this paper, we consider a multi-crane scheduling problem in rail stations because their operations directly influence the throughput of the rail stations. In particular, the job is not only assigned to cranes but also the job sequencing is implemented for each crane to minimize the makespan of cranes. A dual cycle of cranes is used to minimize the number of working cycles of cranes. The rail crane scheduling problems in this study are based on the movement of containers. We consider not only the gantry moves, but also the trolley moves as well as the re-handle cases are also… More >

Thomas Leduc, Xenia Stavropulos-Laffaille, Ignacio Requena-Ruiz

Revue Internationale de Géomatique, Vol.31, No.2, pp. 241-263, 2022, DOI:10.3166/RIG.31.241-263©2022

Abstract The adaptation of public spaces to episodes of intense heat is now a major challenge for cities. With this in mind, this article presents a contribution aimed at delineating and handling the shadows on the ground or in a horizontal plane at a given height, whether it comes from buildings, street furniture or the tree cover. After a comparison with shadows obtained via two reference tools, we present two urban sites that mix shadows of different origins and, in addition, different indicators. The results of the simulations are compared with pyranometric surveys carried out on site. The aim of these… More >

Sharaf Alzoubi¹, Laith Abualigah^{2,3,4,5,6,7,8,*}, Mohamed Sharaf⁹, Mohammad Sh. Daoud¹⁰, Nima Khodadadi¹¹, Heming Jia¹²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2557-2604, 2024, DOI:10.32604/cmes.2023.045170

Abstract This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm (SSOA). The SSOA combines the principles of swarm intelligence and synergistic cooperation to search for optimal solutions efficiently. A synergistic cooperation mechanism is employed, where particles exchange information and learn from each other to improve their search behaviors. This cooperation enhances the exploitation of promising regions in the search space while maintaining exploration capabilities. Furthermore, adaptive mechanisms, such as dynamic parameter adjustment and diversification strategies, are incorporated to balance exploration and exploitation. By leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation, the SSOA… More >

Qi Zhuang^1,*, Dong Liu², Zhuo Chen³

Energy Engineering, Vol.121, No.3, pp. 821-834, 2024, DOI:10.32604/ee.2023.044054

Abstract Oil and gas pipelines are affected by many factors, such as pipe wall thinning and pipeline rupture. Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management. Aiming at the shortcomings of the BP Neural Network (BPNN) model, such as low learning efficiency, sensitivity to initial weights, and easy falling into a local optimal state, an Improved Sparrow Search Algorithm (ISSA) is adopted to optimize the initial weights and thresholds of BPNN, and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established. Taking 61 sets of pipelines blasting test data… More >

John Tshibangu Wa Ilunga^1,*, Donatien Kamutanda Kalombo¹, Olivier Ngoie Inabanza¹, Dikumbwa N’landu^1,2, Joseph Mukalay Muamba^1,3, Patrice Amisi Mwana¹, Urcel Kalenga Tshingomba¹, Junior Muyumba Munganga¹, Catherine Nsiami Mabiala¹

Revue Internationale de Géomatique, Vol.33, pp. 15-35, 2024, DOI:10.32604/rig.2024.046629

Abstract The mutation of spaces observed in the Katangese Copper Belt (KCB) causes significant topographical changes. Some colonial geodetic markers are easily noticeable on many of the hills making up the KCB. These hills are subject to mining which ruins the completeness of the network of triangulations: geometric and trigonometric Katangese. In order to keep control of the latter, the study shows on the one hand the possibility of using SRTM data (Shuttle Radar Topography Mission) in the monitoring of the macro-change of the reliefs, from 442 positions, and on the other hand, an indirect (remote) inventory method of the existing… More >

Li Zheng, Gang Xu^*, Wenbin Chen

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 935-957, 2024, DOI:10.32604/cmc.2023.046006

Abstract Drone logistics is a novel method of distribution that will become prevalent. The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption, resulting in cost savings for the company’s transportation operations. Logistics firms must discern the ideal location for establishing a logistics hub, which is challenging due to the simplicity of existing models and the intricate delivery factors. To simulate the drone logistics environment, this study presents a new mathematical model. The model not only retains the aspects of the current models, but also considers the degree of transportation difficulty from the logistics hub to… More >

Congjun Rao¹, Mengxi Li¹, Tingting Huang^2,*, Feiyu Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 699-724, 2024, DOI:10.32604/cmes.2023.044898

Abstract Stroke is a chronic cerebrovascular disease that carries a high risk. Stroke risk assessment is of great significance in preventing, reversing and reducing the spread and the health hazards caused by stroke. Aiming to objectively predict and identify strokes, this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost (Logistic-AB) based on machine learning. First, the categorical boosting (CatBoost) method is used to perform feature selection for all features of stroke, and 8 main features are selected to form a new index evaluation system to predict the risk of stroke. Second, the borderline synthetic minority oversampling technique (SMOTE)… More >