Yudong Tian^1,2, Gonghui Liu¹, Yue Qi^1,2,*, Jun Li^1,3, Yan Xi^1,4, Wei Lian^1,3, Xiaojie Bai², Penglin Liu¹, Xiaoguang Geng²

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.11, pp. 2837-2845, 2023, DOI:10.32604/fdmp.2023.028805

Abstract Organic rich dark shale of Q Formation can be found in many areas (e.g., in the North of S Basin). The shale target stratum is easy to hydrate and often undergoes spallation. Therefore, centering the casing in the horizontal section of the irregular borehole is relatively difficult. Similarly, achieving a good cement flushing efficiency under complex borehole conditions is a complex task. Through technologies such as centralizer, efficient preflushing, multi-stage flushing and ductile cement slurry, better performances can be achieved. In this study, it is shown that the cementing rate in the DY2H horizontal section is 97.8%, which is more… More >

Xinsen Wei¹, Ying Guo^1,2,*, Yan Zhao¹

Molecular & Cellular Biomechanics, Vol.20, No.2, pp. 49-61, 2023, DOI:10.32604/mcb.2023.041173

Abstract As one of the most basal avian clades, the Confuciusornithids are ideal in revealing the early evolution of avian flight. Birds’ hindlimbs are functionally diverse and contain a wealth of information about their behavior. The hindlimb of Confuciusornis, however, has only been studied in detail in terms of functional morphology, and quantitative studies that directly assess locomotor ability are relatively lacking. This has led to certain controversies on the behavior of Confuciusornis. This paper reviews the debates over the life habits and take-off ability of Confuciusornis, which are closely related to their hindlimb function. Several methodologies adopted engineering techniques, including… More >

Héctor Alejandro Reza-Solis¹, Ofelia Adriana Hernández-Rodríguez^1,*, Andrés Francisco Martínez-Rosales², Dámaris Leopoldina Ojeda-Barrios¹

Phyton-International Journal of Experimental Botany, Vol.92, No.10, pp. 2737-2759, 2023, DOI:10.32604/phyton.2023.029851

Abstract Microalgae are mostly photoautotrophic microscopic organisms. According to their cellular structure, they are classified into two types, eukaryotes, and prokaryotes, and they are distributed in all types of ecosystems, presenting unique qualities due to the fact that they synthesize high value-added molecules used in various productive and environmental activities, and because their biomass is used as raw material to obtain various products. Therefore, the objective of this review was to collect, organize, and collate current information on the use of microalgae in the development of biotechnology involving the areas of agriculture, health, food, bioremediation, and biofuels. The results show that… More >

Yujing Ma¹, Zhongwang Wang², Xiaohui Yuan¹, Leilei Chen^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-2, 2023, DOI:10.32604/icces.2023.09662

Abstract The paper presents a novel fast calculation method for broadband Electromagnetic Scattering analysis. In this work, the isogeometric boundary element method is used to solve Helmholtz equations for the electromagnetic scattering problems. The non-uniform rational B-splines are employed to construct structural geometries and discretize electric and magnetic field integral equations [1,2]. To avoid timeconsuming multi-frequency calculations, the series expansion method is used to decouple the frequencydependent terms from the integrand in the boundary element method [3,4]. The second-order Arnoldi (SOAR) method is applied to construct a reduced-order model that retains the essential structures and key properties of the original model… More >

Denis Benka^*, Sabína Vašová, Michal Kebísek, Maximilián Strémy

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2519-2535, 2023, DOI:10.32604/iasc.2023.040799

Abstract Pattern recognition algorithms are commonly utilized to discover certain patterns, particularly in image-based data. Our study focuses on quasiperiodic oscillations (QPO) in celestial objects referred to as cataclysmic variables (CV). We are dealing with interestingly indistinct QPO signals, which we analyze using a power density spectrum (PDS). The confidence in detecting the latter using certain statistical approaches may come out with less significance than the truth. We work with real and simulated QPO data of a CV called MV Lyrae. Our primary statistical tool for determining confidence levels is sigma intervals. The aforementioned CV has scientifically proven QPO existence, but… More >

Ouyang Liu, Kun Li^*, Ziwei Yin, Deyun Gao, Huachun Zhou

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2955-2977, 2023, DOI:10.32604/iasc.2023.039995

Abstract Due to the many types of distributed denial-of-service attacks (DDoS) attacks and the large amount of data generated, it becomes a challenge to manage and apply the malicious behavior knowledge generated by DDoS attacks. We propose a malicious behavior knowledge base framework for DDoS attacks, which completes the construction and application of a multi-domain malicious behavior knowledge base. First, we collected malicious behavior traffic generated by five mainstream DDoS attacks. At the same time, we completed the knowledge collection mechanism through data pre-processing and dataset design. Then, we designed a malicious behavior category graph and malicious behavior structure graph for… More >

Seungmin Lee, Hyunghoon Kim, Haehyun Cho, Hyo Jin Jo^*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2941-2954, 2023, DOI:10.32604/iasc.2023.039992

Abstract Modern vehicles are equipped with multiple Electronic Control Units (ECUs) that support various convenient driving functions, such as the Advanced Driver Assistance System (ADAS). To enable communication between these ECUs, the Controller Area Network (CAN) protocol is widely used. However, since CAN lacks any security technologies, it is vulnerable to cyber attacks. To address this, researchers have conducted studies on machine learning-based intrusion detection systems (IDSs) for CAN. However, most existing IDSs still have non-negligible detection errors. In this paper, we propose a new filtering-based intrusion detection system (FIDS) to minimize the detection errors of machine learning-based IDSs. FIDS uses… More >

Sun-Woo Yun¹, Na-Eun Park¹, Il-Gu Lee^1,2,*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2897-2917, 2023, DOI:10.32604/iasc.2023.039940

Abstract As time and space constraints decrease due to the development of wireless communication network technology, the scale and scope of cyberattacks targeting the Internet of Things (IoT) are increasing. However, it is difficult to apply high-performance security modules to the IoT owing to the limited battery, memory capacity, and data transmission performance depending on the size of the device. Conventional research has mainly reduced power consumption by lightening encryption algorithms. However, it is difficult to defend large-scale information systems and networks against advanced and intelligent attacks because of the problem of deteriorating security performance. In this study, we propose wake-up… More >

Jie Zhang, Jianxun Zhang^*, Bowen Li, Jie Cao, Yifan Guo

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2883-2895, 2023, DOI:10.32604/iasc.2023.039805

Abstract With the improvement of image editing technology, the threshold of image tampering technology decreases, which leads to a decrease in the authenticity of image content. This has also driven research on image forgery detection techniques. In this paper, a U-Net with multiple sensory field feature extraction (MSCU-Net) for image forgery detection is proposed. The proposed MSCU-Net is an end-to-end image essential attribute segmentation network that can perform image forgery detection without any pre-processing or post-processing. MSCU-Net replaces the single-scale convolution module in the original network with an improved multiple perceptual field convolution module so that the decoder can synthesize the… More >

Ahmed S. Almasoud^*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2849-2863, 2023, DOI:10.32604/iasc.2023.039718

Abstract The Internet of Things (IoT) is considered the next-gen connection network and is ubiquitous since it is based on the Internet. Intrusion Detection System (IDS) determines the intrusion performance of terminal equipment and IoT communication procedures from IoT environments after taking equivalent defence measures based on the identified behaviour. In this background, the current study develops an Enhanced Metaheuristics with Machine Learning enabled Cyberattack Detection and Classification (EMML-CADC) model in an IoT environment. The aim of the presented EMML-CADC model is to detect cyberattacks in IoT environments with enhanced efficiency. To attain this, the EMML-CADC model primarily employs a data… More >