Mario Eugenio Sello^1,*, Rafael Adrian Maddio¹, Santiago Ignacio Hurtado¹, Daniel Alejandro Castillo¹, Daiana Vanesa Perri¹, Octavio Agusto Bruzzone², Marcos Horacio Easdale¹

Phyton-International Journal of Experimental Botany, Vol.93, No.9, pp. 2479-2498, 2024, DOI:10.32604/phyton.2024.053168 - 30 September 2024

Abstract Adaptive management in arid and semi-arid regions of Patagonia, Argentina, requires a thorough understanding of vegetative dynamics, which can be obtained via rangeland assessment and monitoring. These practices are essential for decision-making to prevent environmental degradation, especially in the light of drought aggravated by climate change. In turn, most methods used to evaluate rangelands focus on data obtained from field measurements and vegetation classifications based on remote sensing data. One of the most frequent problems is that field-based rangeland assessments, based on field measurements, turn out to be expensive because they require high efforts in… More >

Wei Liu^*, Tengteng Ren

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2979-3000, 2024, DOI:10.32604/cmc.2024.053627 - 15 August 2024

Abstract Feature Selection (FS) is a key pre-processing step in pattern recognition and data mining tasks, which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models. In recent years, meta-heuristic algorithms have been widely used in FS problems, so a Hybrid Binary Chaotic Salp Swarm Dung Beetle Optimization (HBCSSDBO) algorithm is proposed in this paper to improve the effect of FS. In this hybrid algorithm, the original continuous optimization algorithm is converted into binary form by the S-type transfer function and applied to the FS problem. By combining the… More >

Xueping Song^1,*, Jianming Yang¹, Shuyu Zhang¹, Jicun Zhang^1,2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4551-4572, 2024, DOI:10.32604/cmc.2024.049446 - 20 June 2024

Abstract To address the shortage of public datasets for customs X-ray images of contraband and the difficulties in deploying trained models in engineering applications, a method has been proposed that employs the Extract-Transform-Load (ETL) approach to create an X-ray dataset of contraband items. Initially, X-ray scatter image data is collected and cleaned. Using Kafka message queues and the Elasticsearch (ES) distributed search engine, the data is transmitted in real-time to cloud servers. Subsequently, contraband data is annotated using a combination of neural networks and manual methods to improve annotation efficiency and implemented mean hash algorithm for… More >

Qinyue Wu, Hui Xu^*, Mengran Liu

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4091-4107, 2024, DOI:10.32604/cmc.2024.048461 - 26 March 2024

Abstract Network traffic identification is critical for maintaining network security and further meeting various demands of network applications. However, network traffic data typically possesses high dimensionality and complexity, leading to practical problems in traffic identification data analytics. Since the original Dung Beetle Optimizer (DBO) algorithm, Grey Wolf Optimization (GWO) algorithm, Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) algorithm have the shortcomings of slow convergence and easily fall into the local optimal solution, an Improved Dung Beetle Optimizer (IDBO) algorithm is proposed for network traffic identification. Firstly, the Sobol sequence is utilized to initialize the… More >

Zhou Ji¹, Mengmeng Zhou², Qiang Wang², Jiandong Huang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1557-1582, 2024, DOI:10.32604/cmes.2023.046025 - 29 January 2024

Abstract To improve the prediction accuracy of the International Roughness Index (IRI) of Jointed Plain Concrete Pavements (JPCP) and Continuously Reinforced Concrete Pavements (CRCP), a machine learning approach is developed in this study for the modelling, combining an improved Beetle Antennae Search (MBAS) algorithm and Random Forest (RF) model. The 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this study. The importance scores of all input variables on the IRI of JPCP and CRCP were analysed as well. The results by the comparative analysis showed the prediction accuracy of… More > Graphic Abstract

Bilal Khan¹, Saifullah Jan^1,*, Wahab Khan¹, Muhammad Imran Chughtai²

Journal on Big Data, Vol.6, pp. 1-20, 2024, DOI:10.32604/jbd.2023.046223 - 26 January 2024

Abstract The extraction, transformation, and loading (ETL) process is a crucial and intricate area of study that lies deep within the broad field of data warehousing. This specific, yet crucial, aspect of data management fills the knowledge gap between unprocessed data and useful insights. Starting with basic information unique to this complex field, this study thoroughly examines the many issues that practitioners encounter. These issues include the complexities of ETL procedures, the rigorous pursuit of data quality, and the increasing amounts and variety of data sources present in the modern data environment. The study examines ETL… More >

Mohamed Ibrahim Waly^*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3159-3174, 2023, DOI:10.32604/csse.2023.035900 - 03 April 2023

Abstract Recently, computer assisted diagnosis (CAD) model creation has become more dependent on medical picture categorization. It is often used to identify several conditions, including brain disorders, diabetic retinopathy, and skin cancer. Most traditional CAD methods relied on textures, colours, and forms. Because many models are issue-oriented, they need a more substantial capacity to generalize and cannot capture high-level problem domain notions. Recent deep learning (DL) models have been published, providing a practical way to develop models specifically for classifying input medical pictures. This paper offers an intelligent beetle antenna search (IBAS-DTL) method for classifying medical… More >

S. Priya^1,*, K. Pradeep Mohan Kumar²

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3339-3353, 2023, DOI:10.32604/csse.2023.030630 - 03 April 2023

Abstract An intrusion detection system (IDS) becomes an important tool for ensuring security in the network. In recent times, machine learning (ML) and deep learning (DL) models can be applied for the identification of intrusions over the network effectively. To resolve the security issues, this paper presents a new Binary Butterfly Optimization algorithm based on Feature Selection with DRL technique, called BBOFS-DRL for intrusion detection. The proposed BBOFSDRL model mainly accomplishes the recognition of intrusions in the network. To attain this, the BBOFS-DRL model initially designs the BBOFS algorithm based on the traditional butterfly optimization algorithm More >

Musawwer Khan¹, Islam Ali¹, Shahzada Khurram², Salman Naseer³, Shafiq Ahmad⁴, Ahmed T. Soliman⁴, Akber Abid Gardezi⁵, Muhammad Shafiq^6,*, Jin-Ghoo Choi⁶

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3849-3863, 2023, DOI:10.32604/cmc.2023.027387 - 31 October 2022

Abstract The effectiveness of the Business Intelligence (BI) system mainly depends on the quality of knowledge it produces. The decision-making process is hindered, and the user’s trust is lost, if the knowledge offered is undesired or of poor quality. A Data Warehouse (DW) is a huge collection of data gathered from many sources and an important part of any BI solution to assist management in making better decisions. The Extract, Transform, and Load (ETL) process is the backbone of a DW system, and it is responsible for moving data from source systems into the DW system.… More >

K. Rajesh Kumar^1,*, M. Vijayakumar²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 819-832, 2023, DOI:10.32604/iasc.2023.030961 - 29 September 2022

Abstract In past decades, cellular networks have raised the usage of spectrum resources due to the victory of mobile broadband services. Mobile devices create massive data than ever before, facing the way cellular networks are installed presently for satisfying the increased traffic requirements. The development of a new exclusive spectrum offered to meet up the traffic requirements is challenging as spectrum resources are limited, hence costly. Cognitive radio technology is presented to increase the pool of existing spectrum resources for mobile users via Femtocells, placed on the top of the available macrocell network for sharing the… More >