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  • Open Access

    ARTICLE

    NUMERICAL INVESTIGATION OF HEAT TRANSPORT IN A DIRECT METHANOL FUEL CELL WITH ANISOTROPIC GAS DIFFUSION LAYERS

    Zheng Miaoa, Ya-Ling Hea,*, Tian-Shou Zhaob, Wen-Quan Taoa

    Frontiers in Heat and Mass Transfer, Vol.2, No.1, pp. 1-10, 2011, DOI:10.5098/hmt.v2.1.3001

    Abstract A non-isothermal two-phase mass transport model is developed in this paper to investigate the heat generation and transport phenomena in a direct methanol fuel cell with anisotropic gas diffusion layers (GDLs). Thermal contact resistances at the GDL/CL (catalyst layer) and GDL/Rib interfaces, and the deformation of GDLs are considered together with the inherent anisotropy of the GDL. Latent heat effects due to condensation/evaporation of water and methanol between liquid and gas phases are also taken into account. Formulation of the two-phase mass transport across the membrane electrode assembly (MEA) is mainly based on the classical multiphase flow theory in the… More >

  • Open Access

    ARTICLE

    Coordinated Voltage Control of Distribution Network Considering Multiple Types of Electric Vehicles

    Liang Liu, Guangda Xu*, Yuan Zhao, Yi Lu, Yu Li, Jing Gao

    Energy Engineering, Vol.121, No.2, pp. 377-404, 2024, DOI:10.32604/ee.2023.041311

    Abstract The couple between the power network and the transportation network (TN) is deepening gradually with the increasing penetration rate of electric vehicles (EV), which also poses a great challenge to the traditional voltage control scheme. In this paper, we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV. In the first stage, the action of on-load tap changer and capacitor banks, etc., are determined by optimal power flow calculation, and the node electricity price is also determined based on dynamic time-of-use tariff mechanism. In the second stage, multiple operating scenarios of multiple types… More >

  • Open Access

    ARTICLE

    Deep Learning Based Vehicle Detection and Counting System for Intelligent Transportation

    A. Vikram1, J. Akshya2, Sultan Ahmad3,4, L. Jerlin Rubini5, Seifedine Kadry6,7,8, Jungeun Kim9,*

    Computer Systems Science and Engineering, Vol.48, No.1, pp. 115-130, 2024, DOI:10.32604/csse.2023.037928

    Abstract Traffic monitoring through remote sensing images (RSI) is considered an important research area in Intelligent Transportation Systems (ITSs). Vehicle counting systems must be simple enough to be implemented in real-time. With the fast expansion of road traffic, real-time vehicle counting becomes essential in constructing ITS. Compared with conventional technologies, the remote sensing-related technique for vehicle counting exhibits greater significance and considerable advantages in its flexibility, low cost, and high efficiency. But several techniques need help in balancing complexity and accuracy technique. Therefore, this article presents a deep learning-based vehicle detection and counting system for ITS (DLVDCS-ITS) in remote sensing images.… More >

  • Open Access

    REVIEW

    Carbon Monoxide Modulates Auxin Transport and Nitric Oxide Signaling in Plants under Iron Deficiency Stress

    Kaiyue Hong1,2, Yasmina Radani2, Waqas Ahmad2, Ping Li3, Yuming Luo1,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.1, pp. 45-61, 2024, DOI:10.32604/phyton.2023.046389

    Abstract Carbon monoxide (CO) and nitric oxide (NO) are signal molecules that enhance plant adaptation to environmental stimuli. Auxin is an essential phytohormone for plant growth and development. CO and NO play crucial roles in modulating the plant’s response to iron deficiency. Iron deficiency leads to an increase in the activity of heme oxygenase (HO) and the subsequent generation of CO. Additionally, it alters the polar subcellular distribution of Pin-Formed 1 (PIN1) proteins, resulting in enhanced auxin transport. This alteration, in turn, leads to an increase in NO accumulation. Furthermore, iron deficiency enhances the activity of ferric chelate reductase (FCR), as… More >

  • Open Access

    PROCEEDINGS

    Key Transport Mechanisms in Supercritical CO2 Based Pilot Micromodels Subjected to Bottom Heat and Mass Diffusion

    Karim Ragui1, Mengshuai Chen1,2, Lin Chen1,2,3,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-2, 2023, DOI:10.32604/icces.2023.010378

    Abstract The ambiguous dynamics associated with heat and mass transfer of invading carbon dioxide in sub-critical and supercritical states, as well as the response of pore-scale resident fluids, play a key role in understanding CO2 capture and storage (CCUS) and the corresponding phase equilibrium mechanisms. To this end, this paper reveals the transport mechanisms of invading supercritical carbon dioxide (sCO2) in polluted micromodels using a variant of Lattice-Boltzmann Color Fluid model and descriptive experimental data. The breakthrough time is evaluated by characterizing the displacement velocity, the capillary to pressuredifference ratio, and the transient heat and mass diffusion at a series of… More >

  • Open Access

    ARTICLE

    Hybrid Algorithm-Driven Smart Logistics Optimization in IoT-Based Cyber-Physical Systems

    Abdulwahab Ali Almazroi1,*, Nasir Ayub2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3921-3942, 2023, DOI:10.32604/cmc.2023.046602

    Abstract Effectively managing complex logistics data is essential for development sustainability and growth, especially in optimizing distribution routes. This article addresses the limitations of current logistics path optimization methods, such as inefficiencies and high operational costs. To overcome these drawbacks, we introduce the Hybrid Firefly-Spotted Hyena Optimization (HFSHO) algorithm, a novel approach that combines the rapid exploration and global search abilities of the Firefly Algorithm (FO) with the localized search and region-exploitation skills of the Spotted Hyena Optimization Algorithm (SHO). HFSHO aims to improve logistics path optimization and reduce operational costs. The algorithm’s effectiveness is systematically assessed through rigorous comparative analyses… More >

  • Open Access

    ARTICLE

    Analyzing the Impact of Blockchain Models for Securing Intelligent Logistics through Unified Computational Techniques

    Mohammed S. Alsaqer1, Majid H. Alsulami2,*, Rami N. Alkhawaji3, Abdulellah A. Alaboudi2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3943-3968, 2023, DOI:10.32604/cmc.2023.042379

    Abstract Blockchain technology has revolutionized conventional trade. The success of blockchain can be attributed to its distributed ledger characteristic, which secures every record inside the ledger using cryptography rules, making it more reliable, secure, and tamper-proof. This is evident by the significant impact that the use of this technology has had on people connected to digital spaces in the present-day context. Furthermore, it has been proven that blockchain technology is evolving from new perspectives and that it provides an effective mechanism for the intelligent transportation system infrastructure. To realize the full potential of the accurate and efficacious use of blockchain in… More >

  • Open Access

    ARTICLE

    YOLO and Blockchain Technology Applied to Intelligent Transportation License Plate Character Recognition for Security

    Fares Alharbi1, Reem Alshahrani2, Mohammed Zakariah3,*, Amjad Aldweesh1, Abdulrahman Abdullah Alghamdi1

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3697-3722, 2023, DOI:10.32604/cmc.2023.040086

    Abstract Privacy and trust are significant issues in intelligent transportation systems (ITS). Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless devices and routes such as radio channels, optical fiber, and blockchain technology. The Internet of Things (IoT) is a network of connected, interconnected gadgets. Privacy issues occasionally arise due to the amount of data generated. However, they have been primarily addressed by blockchain and smart contract technology. While there are still security issues with smart contracts, primarily due to the complexity of writing the code, there are still… More >

  • Open Access

    ARTICLE

    Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

    Othman S. Al-Heety1,*, Zahriladha Zakaria1,*, Ahmed Abu-Khadrah2, Mahamod Ismail3, Sarmad Nozad Mahmood4, Mohammed Mudhafar Shakir5, Sameer Alani6, Hussein Alsariera1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2103-2127, 2024, DOI:10.32604/cmes.2023.029509

    Abstract Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision. In this article, these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data. The framework integrates Kalman filtering and Q-learning. Unlike smoothing Kalman filtering, our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error. Unlike traditional Q-learning, our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road… More >

  • Open Access

    ARTICLE

    LARGE EDDY SIMULATION OF THE DIFFUSION PROCESS OF NUTRIENT-RICH UP-WELLED SEAWATER

    Shigenao Maruyamaa, Masud Behniab, Masasazumi Chisakic, Takuma Kogawac,*, Junnosuke Okajimaa, Atsuki Komiyaa

    Frontiers in Heat and Mass Transfer, Vol.4, No.2, pp. 1-6, 2013, DOI:10.5098/hmt.v4.2.3002

    Abstract The diffusion process of deep seawater drawn up by a vertical pipe deployed in the ocean is investigated. This vertical pipe is based on the principal of perpetual salt fountain. Numerical simulations of seawater upwelling from the pipe are performed based on experiments conducted in the Mariana trench region. Two turbulence modeling approaches were examined: k-ε model and Large Eddy Simulations (LES). The results in both models show that diffusion of the deep seawater diffusion after ejection from the pipe. The LES results show a 50% lower vertical penetration compared to the k-ε model as well as well as predicting… More >

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