Fujian Zhang¹, Ziyang Wang¹, Xiang Gao¹, Zhongqiang Zhang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011736

Abstract Spontaneous droplet transport has broad application prospects in fields such as water collection and microfluidic chips. Despite extensive research in this area, droplet self-transport is still limited by issues such as slow transport velocity, short distance, and poor integrity. Here, a novel cross-hatch textured cone (CHTC) with multistage microchannels and circular grooves is proposed to realize ultrafast directional long-distance self-transport of multi-scale droplets. The CHTC triggers two modes of fluid transport: Droplet transport by Laplace pressure difference and capillary suction pressure-induced fluid transfer in microchannels on cone surfaces. By leveraging the coupling effect of the… More >

Jane Kim¹, Soojin Lee¹, Chan Yeob Yeun², Seung-Hyun Seo^1,3,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3495-3518, 2024, DOI:10.32604/cmc.2024.050461 - 20 June 2024

Abstract As big data, Artificial Intelligence, and Vehicle-to-Everything (V2X) communication have advanced, Intelligent Transportation Systems (ITS) are being developed to enable efficient and safe transportation systems. Electronic Toll Collection (ETC), which is one of the services included in ITS systems, is an automated system that allows vehicles to pass through toll plazas without stopping for manual payment. The ETC system is widely deployed on highways due to its contribution to stabilizing the overall traffic system flow. To ensure secure and efficient toll payments, designing a distributed model for sharing toll payment information among untrusted toll service… More >

Dmitry Gura^1,2, Bo Dong^3,*, Duaa Mehiar⁴, Nidal Al Said⁵

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1995-2014, 2024, DOI:10.32604/cmc.2024.048238 - 15 May 2024

Abstract The motivation for this study is that the quality of deep fakes is constantly improving, which leads to the need to develop new methods for their detection. The proposed Customized Convolutional Neural Network method involves extracting structured data from video frames using facial landmark detection, which is then used as input to the CNN. The customized Convolutional Neural Network method is the date augmented-based CNN model to generate ‘fake data’ or ‘fake images’. This study was carried out using Python and its libraries. We used 242 films from the dataset gathered by the Deep Fake… More >

Haosong Gou¹, Gaoyi Zhang¹, Renê Ripardo Calixto², Senthil Kumar Jagatheesaperumal³, Victor Hugo C. de Albuquerque^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1077-1102, 2024, DOI:10.32604/cmes.2024.047806 - 16 April 2024

Abstract Large-scale wireless sensor networks (WSNs) play a critical role in monitoring dangerous scenarios and responding to medical emergencies. However, the inherent instability and error-prone nature of wireless links present significant challenges, necessitating efficient data collection and reliable transmission services. This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs. The primary goal is to enhance the reliability of data collection and transmission services, ensuring a comprehensive and practical approach. Our approach focuses on refining the hop-count-based routing scheme to achieve… More >

Kai Jiang, Bin Cao^*, Jing Fan

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2965-2984, 2024, DOI:10.32604/cmes.2023.046348 - 11 March 2024

Abstract Multimodal sentiment analysis utilizes multimodal data such as text, facial expressions and voice to detect people’s attitudes. With the advent of distributed data collection and annotation, we can easily obtain and share such multimodal data. However, due to professional discrepancies among annotators and lax quality control, noisy labels might be introduced. Recent research suggests that deep neural networks (DNNs) will overfit noisy labels, leading to the poor performance of the DNNs. To address this challenging problem, we present a Multimodal Robust Meta Learning framework (MRML) for multimodal sentiment analysis to resist noisy labels and correlate More >

Dan Zhao¹, Yang You², Chuanwen Luo^3,*, Ting Chen^4,*, Yang Liu⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3063-3083, 2024, DOI:10.32604/cmes.2023.045400 - 11 March 2024

Abstract In recent years, the research field of data collection under local differential privacy (LDP) has expanded its focus from elementary data types to include more complex structural data, such as set-value and graph data. However, our comprehensive review of existing literature reveals that there needs to be more studies that engage with key-value data collection. Such studies would simultaneously collect the frequencies of keys and the mean of values associated with each key. Additionally, the allocation of the privacy budget between the frequencies of keys and the means of values for each key does not… More >

Maan Habib^1,*, Maan Okayli²

Revue Internationale de Géomatique, Vol.32, pp. 1-16, 2023, DOI:10.32604/rig.2023.043399 - 30 September 2023

Abstract This study provides a comprehensive overview of modern cartography innovations and emerging trends, highlighting the importance of geospatial representation in various fields. It discusses recent advancements in geospatial data collection techniques, including satellite and aerial imagery, Light Detection and Ranging (LiDAR) technology, and crowdsourcing. The research also investigates the integration of big data, machine learning, and real-time processing in Geographic Information Systems (GIS), as well as advances in geospatial visualization. In addition, it examines the role of cartography in addressing global challenges such as climate change, disaster management, and urban planning in line with the More >

Huanan Yu¹, Gang Han^1,*, Hansong Luo², He Wang¹

Energy Engineering, Vol.120, No.9, pp. 2029-2057, 2023, DOI:10.32604/ee.2023.028365 - 03 August 2023

Abstract Aiming at the problem that most of the cables in the power collection system of offshore wind farms are buried deep in the seabed, which makes it difficult to detect faults, this paper proposes a two-step fault location method based on compressed sensing and ranging equation. The first step is to determine the fault zone through compressed sensing, and improve the data measurement, dictionary design and algorithm reconstruction: Firstly, the phase-locked loop trigonometric function method is used to suppress the spike phenomenon when extracting the fault voltage, so that the extracted voltage value will not… More >

S. Ponnarasi^1,*, T. Rajendran²

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6039-6057, 2023, DOI:10.32604/cmc.2023.035499 - 29 April 2023

Abstract An efficient trust-aware secure routing and network strategy-based data collection scheme is presented in this paper to enhance the performance and security of wireless sensor networks during data collection. The method first discovers the routes between the data sensors and the sink node. Several factors are considered for each sensor node along the route, including energy, number of neighbours, previous transmissions, and energy depletion ratio. Considering all these variables, the Sink Reachable Support Measure and the Secure Communication Support Measure, the method evaluates two distinct measures. The method calculates the data carrier support value using… More >

Vani A. Hiremani^*, Kishore Kumar Senapati

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2603-2618, 2023, DOI:10.32604/csse.2023.027612 - 01 August 2022

Abstract The inter-class face classification problem is more reasonable than the intra-class classification problem. To address this issue, we have carried out empirical research on classifying Indian people to their geographical regions. This work aimed to construct a computational classification model for classifying Indian regional face images acquired from south and east regions of India, referring to human vision. We have created an Automated Human Intelligence System (AHIS) to evaluate human visual capabilities. Analysis of AHIS response showed that face shape is a discriminative feature among the other facial features. We have developed a modified convolutional… More >