Relevant bibliographies by topics / Objective computational identifier

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Academic literature on the topic 'Objective computational identifier'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Objective computational identifier"

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Rodríguez-Cerdeira, Carmen, José Luís González-Cespón, and Roberto Arenas. "Current Status of Computational Intelligence Applications in Dermatological Clinical Practice." Open Dermatology Journal 14, no. 1 (2020): 6–13. http://dx.doi.org/10.2174/1874372202014010006.

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Background: The yeast infections are increasingly frequent and the correct diagnosis consists of the identification of the yeast fungus, which in our case we are going to refer to the different species of Candida. The prescription of a broad-spectrum antifungal without taking into account the etiological agent, leads to an increase in the resistance to these treatments. Objective: The objective of this work is to differentiate Candida albicans from other Candida species (Candida spp.) By means of digital images obtained from the optical microscope. Material and Methods: It has reviewed about 1
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Sikander, Rahu, Mujeebu Rehman, Tarique Ali Brohi, Arif Ahmed, Ali Ghulam, and Sultan Ahmed. "An Explainable Identifier of iGHBPs Peptides Based on Deep PSSM Features and Learning Approaches." Insights-Journal of Health and Rehabilitation 2, no. 2 (Health & Allied) (2024): 571–79. https://doi.org/10.71000/7dqqxs92.

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Growth hormone can be effectively and non-covalently communicated with by a growth hormone binding protein (GHBP), also referred to as a soluble carrier protein. Accurately recognizing the GHBP from a certain protein sequence is crucial for comprehending biological processes and cell growth. In the postgenomic era, a lot of protein sequence data has been gathered, which makes it even more urgent to build an integrated computational method that can quickly and precisely identify possible GHBPs from a huge number of candidate proteins. In this work, we provide iGHBP, a growth hormone binding pro
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Mozaffari, Ahmad, Nasser L. Azad, and Alireza Fathi. "Simultaneous knowledge-based identification and optimization of PHEV fuel economy using hyper-level Pareto-based chaotic Lamarckian immune algorithm, MSBA and fuzzy programming." International Journal of Intelligent Computing and Cybernetics 8, no. 1 (2015): 2–27. http://dx.doi.org/10.1108/ijicc-07-2014-0034.

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Purpose – The purpose of this paper is to probe the potentials of computational intelligence (CI) and bio-inspired computational tools for designing a hybrid framework which can simultaneously design an identifier to capture the underlying knowledge regarding a given plug-in hybrid electric vehicle’s (PHEVs) fuel cost and optimize its fuel consumption rate. Besides, the current investigation aims at elaborating the effectiveness of Pareto-based multiobjective programming for coping with the difficulties associated with such a tedious automotive engineering problem. Design/methodology/approach
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Wang, Tonghe, Songpu Ai, Junwei Cao, and Yuming Zhao. "A Blockchain-Based Distributed Computational Resource Trading Strategy for Internet of Things Considering Multiple Preferences." Symmetry 15, no. 4 (2023): 808. http://dx.doi.org/10.3390/sym15040808.

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The architecture of cloud–edge collaboration can improve the efficiency of Internet of Things (IoT) systems. Recent studies have pointed out that using IoT terminal devices as destinations for computing offloading can promote further optimized allocation of computational resources. However, in practice, this idea encounters the problem that participants might lack the motivation to take over computational tasks from others. Although the edge and the terminal are provided with symmetrical positions in collaborative offloading, their computational resources and capabilities are asymmetric. To mi
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Musa, I. S., and H. S. Haruna. "EVALUATION OF PROPHAGES AND ANTI MICROBIAL RESISTANCE PROFILE OF BACILLUS SUBTILIS USING IN SILICO APPROACH." FUDMA JOURNAL OF SCIENCES 8, no. 2 (2024): 247–49. http://dx.doi.org/10.33003/fjs-2024-0802-2349.

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The main objective of this study was to identify the prophages and antimicrobial resistance profile of Bacillus subtilis using computational methods. Prophages are potential therapeutic antimicrobial agents against antibiotic- resistant pathogens. The potential of prophage to induce antimicrobial resistance and increase pathogenicity in bacterial genomes resulted in renewed interest in the identification of prophage sequences and their associated antimicrobial resistant genes in bacterial genomes. Sequences of Bacillus subtilis retrieved from the sequence raw archive (SRA) of the National Cent
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Berman, Jules J. "Zero-Check: A Zero-Knowledge Protocol for Reconciling Patient Identities Across Institutions." Archives of Pathology & Laboratory Medicine 128, no. 3 (2004): 344–46. http://dx.doi.org/10.5858/2004-128-344-zazpfr.

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Abstract Context.—Large, multi-institutional studies often involve merging data records that have been de-identified to protect patient privacy. Unless patient identities can be reconciled across institutions, individuals with records held in different institutions will be falsely “counted” as multiple persons when databases are merged. Objective.—The purpose of this article is to describe a protocol that can reconcile individuals with records in multiple institutions. Design.—Institution A and Institution B each create a random character string and send it to the other institution. Each insti
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Patel, Dhavalkumar, Prem Timsina, Larisa Gorenstein, et al. "Traditional Machine Learning, Deep Learning, and BERT (Large Language Model) Approaches for Predicting Hospitalizations From Nurse Triage Notes: Comparative Evaluation of Resource Management." JMIR AI 3 (August 27, 2024): e52190. http://dx.doi.org/10.2196/52190.

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Background Predicting hospitalization from nurse triage notes has the potential to augment care. However, there needs to be careful considerations for which models to choose for this goal. Specifically, health systems will have varying degrees of computational infrastructure available and budget constraints. Objective To this end, we compared the performance of the deep learning, Bidirectional Encoder Representations from Transformers (BERT)–based model, Bio-Clinical-BERT, with a bag-of-words (BOW) logistic regression (LR) model incorporating term frequency–inverse document frequency (TF-IDF).
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Kim, Hee, Thomas Ganslandt, Thomas Miethke, Michael Neumaier, and Maximilian Kittel. "Deep Learning Frameworks for Rapid Gram Stain Image Data Interpretation: Protocol for a Retrospective Data Analysis." JMIR Research Protocols 9, no. 7 (2020): e16843. http://dx.doi.org/10.2196/16843.

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Background In recent years, remarkable progress has been made in deep learning technology and successful use cases have been introduced in the medical domain. However, not many studies have considered high-performance computing to fully appreciate the capability of deep learning technology. Objective This paper aims to design a solution to accelerate an automated Gram stain image interpretation by means of a deep learning framework without additional hardware resources. Methods We will apply and evaluate 3 methodologies, namely fine-tuning, an integer arithmetic–only framework, and hyperparame
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Kaido, Hiroaki, Francesca Molinari, and Jörg Stoye. "Confidence Intervals for Projections of Partially Identified Parameters." Econometrica 87, no. 4 (2019): 1397–432. http://dx.doi.org/10.3982/ecta14075.

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We propose a bootstrap‐based calibrated projection procedure to build confidence intervals for single components and for smooth functions of a partially identified parameter vector in moment (in)equality models. The method controls asymptotic coverage uniformly over a large class of data generating processes. The extreme points of the calibrated projection confidence interval are obtained by extremizing the value of the function of interest subject to a proper relaxation of studentized sample analogs of the moment (in)equality conditions. The degree of relaxation, or critical level, is calibra
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Luo, Gang, Bryan L. Stone, Xiaoming Sheng, Shan He, Corinna Koebnick, and Flory L. Nkoy. "Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis." JMIR Research Protocols 10, no. 5 (2021): e27065. http://dx.doi.org/10.2196/27065.

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Background Asthma and chronic obstructive pulmonary disease (COPD) impose a heavy burden on health care. Approximately one-fourth of patients with asthma and patients with COPD are prone to exacerbations, which can be greatly reduced by preventive care via integrated disease management that has a limited service capacity. To do this well, a predictive model for proneness to exacerbation is required, but no such model exists. It would be suboptimal to build such models using the current model building approach for asthma and COPD, which has 2 gaps due to rarely factoring in temporal features sh
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Book chapters on the topic "Objective computational identifier"

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Brüning, Markus, Paul Wunderlich, and Helene Dörksen. "Advanced Feature Extraction Workflow for Few Shot Object Recognition." In Bildverarbeitung in der Automation. Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-66769-9_4.

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AbstractObject recognition is well known to have a high importance in various fields. Example applications are anomaly detection and object sorting. Common methods for object recognition in images divide into neural and non-neural approaches: Neural-based concepts, e.g. using deep learning techniques, require a lot of training data and involve a resource intensive learning process. Additionally, when working with a small number of images, the development effort increases. Common non-neural feature detection approaches, such as SIFT, SURF or AKAZE, do not require these steps for preparation. Th
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Shagrir, Oron. "An Argument for the Semantic View." In The Nature of Physical Computation. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780197552384.003.0009.

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The chapter advances an argument for the semantic individuation of computational states. Its first and central premise is the simultaneous implementation of automata by physical systems. Simultaneous implementation (also known as “the indeterminacy of computation”) is a phenomenon whereby a physical system implements multiple formal structures at the same time, at the same location, and even with the same physical properties. The next premises are that, in a given context, a computational taxonomy often takes into account one of the implemented formalisms, and that content determines, at least
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Venkataraman, Aravind Pitchai, Veeramani Veerapathran, Suleyman Malikmyradovich Nokerov, Khalid Ali Khan, and Subramanian Pitchai Venkataraman. "Simple Recursive Technique to Improve Closed Loop System Time Domain Analysis." In Advances in Transdisciplinary Engineering. IOS Press, 2023. http://dx.doi.org/10.3233/atde230516.

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The control systems research society is highly focused on achieving the closed loop response with minimum time domain specifications such as rise time and settling time. By achieving the desired closed loop response with less performance indices and less time domain specifications, the objective of robust control design for a plant or process is achieved. In this paper, a novel computational method Error Recursion – Reduction Computational (ERRC) technique has been proposed to control dynamics in the industrial process, the proposed technique has been highly focus on reducing error and time do
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Radhika, R., and A. Muthukumaravel. "Intelligent Surveillance on Wireless Sensing and Recognition of Suspicious Activities in Crowded Environments." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-4672-4.ch011.

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Intelligent surveillance systems are crucial for monitoring densely populated areas for a wide range of applications, including security and crowd control. The primary objective of this study is to use wireless sensing technologies in order to identify and analyze the actions of subspecies inside various habitats. The suggested system utilizes sophisticated machine learning algorithms to differentiate and evaluate various actions in congested areas, hence improving situational awareness and decision-making. Wireless sensors facilitate the gathering of data in real-time, allowing for prompt rea
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Derbali, Abdelkader Mohamed Sghaier. "Analysis of Systemic Risk in the Asia Region." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-7112-1.ch004.

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The primary objective of this research is to investigate the systemic risk prevalent within the Asian region during the year 2023. During this analysis, we utilize SRISK as a quantitative measure for systemic risk, aiming to encapsulate the pressure and prospective systemic repercussions confronting financial institutions across various nations. These metrics serve not only to assess the susceptibility of individual financial entities but also to consider the interconnections among them, alongside the relationships between systemic risk and determinants such as Gross Domestic Product (GDP), ma
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Barrera-Cámara, Ricardo A., Angel Vázquez-González, and Fernando E. Sánchez-Martínez. "Automation of Social Services Based on Chatbots and Recommendation Systems to Facilitate Access to Social Assistance Programs." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-8161-8.ch002.

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Social programs are initiatives developed by government and non-governmental institutions to address needs and improve people's well-being and quality of life. In this context, a chatbot acts as a human agent, facilitating the management and dissemination of information about social programs or directing attention to human personnel when necessary. The objective is to develop a chatbot designed to assist citizens in searching for and accessing social programs. The methodology created for the design of the conversational system is not directly linked to a platform, and can be applied to any pro
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Lappas, Georgios. "Machine Learning and Web Mining." In Data Mining Applications for Empowering Knowledge Societies. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-59904-657-0.ch005.

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This chapter reviews research on machine learning and Web mining methods that are related to areas of social benefit. It shows that machine learning and Web mining methods may provide intelligent Web services of social interest. The chapter reveals a growing interest for using advanced computational methods, such as machine learning and Web mining, for better services to the public, as most research identified in the literature has been conducted during the last years. The chapter objective is to help researchers and academics from different disciplines to understand how Web mining and machine
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Gohwong, Srirath Goi. "Leveraging Khon Symbolism and Governmental Power Marketing in the VU-CHAOS World to Address Kakistoscryptocracy." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9286-7.ch020.

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The study's objectives were to compare the actors in kakistoscryptocracy with Khon symbolism and to suggest a meaningful way to deal with kakistoscryptocracy in the VU-CHAOS world by utilizing Khon symbolism and governmental power marketing. The study utilized documentary research. The results distinctly showed that five key Khon figures (namely Phra Ram, Thotsakan, Hanuman, Sita, and small animals) were identified as embodying the roles of all actors in a kakistoscryptocracy, especially in Thailand. Moreover, the Thai government could strategically implement “governmental power marketing” tec
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Waga, Abderrahim, Said Benhlima, and Ali Bekri. "Enhanced Autonomous Driving." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-1399-3.ch010.

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The process of repairing potholes entails significant financial and temporal resources. This article presents cutting-edge approaches to pothole detection employing convolutional neural network techniques, focusing exclusively on RGB input images. The primary objective of this research is to assess the performance of three iterations of the You Only Look Once model, namely, YOLOv8 Nano, Small, and Medium, for pothole detection. Additionally, the proposal suggests a system to alert drivers about identified potholes and recommend alternative routes. The design of the solution enables it to funct
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Babu, C. V. Suresh, Shifa Sherin M., and S. Rufus. "Green Software Development." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-8034-5.ch008.

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This study explores the integration of artificial intelligence (AI) in green software development, aiming to enhance energy efficiency and reduce the environmental footprint of digital systems. Employing a comprehensive literature review, case studies, and expert interviews, the research identifies best practices and innovative approaches for embedding sustainability metrics within the software lifecycle. Key findings reveal that AI can significantly optimize resource utilization and drive sustainable practices, yet challenges remain in adapting traditional development methodologies to meet th
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Conference papers on the topic "Objective computational identifier"

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Potsdam, Mark, Vineet Ahuja, Chandrashekhar Kannepalli, Andrea Zambon, and Hadassah Lapin. "Unsteady Blade Shape Optimization for Rotorcraft." In Vertical Flight Society 70th Annual Forum & Technology Display. The Vertical Flight Society, 2014. http://dx.doi.org/10.4050/f-0070-2014-9453.

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Design Optimization for rotorcraft blades is challenging given that inherently unsteady phenomena and varying freestream conditions affect the aerodynamic performance of these blades. Consequently, steady design optimization methods may be of limited use in carrying out design studies for rotorcraft blades. On the other hand, the process of unsteady design optimization is handicapped by the cost of computing the unsteady aerodynamic objective function. The authors have developed a novel unsteady optimization approach that combines Computational Fluid Dynamics (CFD), a modified Proper Orthogona
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Hersey, Sean, Ondrej Juhasz, Omri Rand, Roberto Celi, Mark Tischler, and Vladimir Khromov. "State-Space Inflow Model Identification and Flight Dynamics Coupling for an Advanced Coaxial Rotorcraft Configuration." In Vertical Flight Society 73rd Annual Forum & Technology Display. The Vertical Flight Society, 2017. http://dx.doi.org/10.4050/f-0073-2017-12113.

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In order to consider the stability and controllability of advanced coaxial configurations, a better understanding of the aerodynamic interactions between rotors is required. Modern aerodynamic analysis tools such as free wake models can accurately model the behavior of the inflow of a coaxial configuration, without the inclusion of theoretical limitations and approximations used by classical-simplified schemes. They are not, however, expressed in state-space form and therefore can not be readily analyzed as a linear flight dynamics problem and are often computationally expensive. The objective
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Saddawi, Salwan David, Timoleon Kipouros, and Mark Savill. "Computational Engineering Design for Micro-Scale Combustion Devices: A Thermally Improved Configuration." In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gt2013-94599.

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A multi-objective design optimisation study has been carried out with the objectives to improve the overall efficiency of the device and to reduce the fuel consumption for the proposed micro-scale combustor design configuration. In a previous study we identified the topology of the combustion chamber that produced improved behaviour of the device in terms of the above design criteria. We now extend our design approach, and we propose a new configuration by the addition of a micro-cooling channel that will improve the thermal behaviour of the design as previously suggested in literature. Our in
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Robison, Andrew J., and Andrea Vacca. "Multi-Objective Geometric Optimization of Elliptical-Toothed Gerotor Pumps for Kinematics and Wear by Genetic Algorithm." In BATH/ASME 2018 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/fpmc2018-8876.

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A computationally efficient gerotor gear generation algorithm has been developed that creates elliptical-toothed gerotor gear profiles, identifies conditions to guarantee a feasible geometry, evaluates several performance objectives, and is suitable to use for geometric optimization. Five objective functions are used in the optimization: minimize pump size, flow ripple, adhesive wear, subsurface fatigue (pitting), and tooth tip leakage. The gear generation algorithm is paired with the NSGA-II optimization algorithm to minimize each of the objective functions subject to the constraints to defin
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Wang, Ting, and Patrick W. Rousset. "Design of a Turbopiston Pump Guided by Computational Analysis." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10636.

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Abstract An innovative pump, TurboPiston Pump (TPP), has been invented to incorporate the merits of centrifugal, axial, and positive displacement pumps. The TPP is designed to deliver large flow rates with a potential at high pressure of up to 1000 psia with one stage. To improve the original design, an understanding of the flow behavior inside the pump is needed. The objective of this study is to simulate the flow field inside the pump and study its performance to guide the design process. This study includes modeling the pump with the transient sliding mesh scheme using a commercial computat
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Qidwai, M. A. Siddiq, A. B. Geltmacher, A. C. Lewis, D. J. Rowenhorst, and G. Spanos. "High-Fidelity Reconstruction and Computational Modeling of Metallic Microstructure." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-42007.

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The end-objective of this research is to identify critical microstructural features in metals that precipitate plastic flow, and therefore, cause degradation of mechanical performance at higher scales. The material focus is a titanium alloy-β21s. The three-dimensional (3D) microstructure in the mesoscale range was obtained using serial sectioning, optical microscopy, electron backscatter diffraction (EBSD) and computerized 3D reconstruction techniques. The reconstructed volumes, comprising hundreds of beta-Ti grains, provide information on morphology and crystallography. This data was used as
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Stabile, P., F. Ballo, M. Gobbi, and G. Previati. "Multi-Objective Structural Optimization of Vehicle Wheels." In ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-71062.

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Abstract This work focuses on the development of an innovative design methodology for lightweight wheels of road vehicles. In particular, the activity is carried out for the specific case of a wheel designed for an ultra-efficient vehicle for Shell Eco-marathon competition, with the aim of finding preliminary design solutions. A simplified finite element model of the tire structure is employed for an accurate modelling of the forces acting at the tire/rim interface. The material properties of the tire structure are identified by means of experimental tests. The computed tire/rim force distribu
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Krishnamurty, S., and D. A. Turcic. "Nonlinear Goal Programming Techniques in the Synthesis of Mechanisms." In ASME 1987 Design Technology Conferences. American Society of Mechanical Engineers, 1987. http://dx.doi.org/10.1115/detc1987-0022.

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Abstract The development of an effective optimization approach for the solution of synthesis problems in mechanisms is presented. The optimization procedure is based on the technique of nonlinear goal programming. In this approach, the generalized variables describing the mechanism are determined by first prioritizing the various objectives of the problem and then by minimizing the value of the achievement function, which represents how closely the designed mechanism meets the specified set of requirements. The following are the main advantages to such an optimization technique. The many confl
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Mathew, Nithin Tom, and Kanthababu Mani. "Multi-Objective Optimization of Microturning Process Parameters Using Particle Swarm Technique." In ASME 2013 International Manufacturing Science and Engineering Conference collocated with the 41st North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/msec2013-1011.

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In this work, for the first time an attempt has been made to carry out multi-objective optimization for tool based microturning process parameters using particle swarm optimization (PSO) technique. The input microturning process parameters considered are speed, feed and depth of cut. The output parameters considered are material removal rate (MRR), surface roughness (Ra) and tool wear (TW). The significant parameters are identified individually using ANOVA and main effect plots. However, it is observed that the main goal of the manufacturers is to produce high quality products in shorter inter
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Zhang, Zhidong, Nickolas Vlahopoulos, T. Allen, and K. Y. Zhang. "A Source Reconstruction Process Based on an Indirect Variational Boundary Element Formulation." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-1624.

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Abstract The objective of the work presented in this paper is the development of a computational capability for recreating the vibration of a source from acoustic field data. The formulation is based on the indirect variational boundary element method (IVBEM). The vibration of the source is computed from transfer functions defined between the field points and the surface of the source. The capability to account for the presence of obstacles in the field adjacent to the vibrating sources and the treatment of irregular frequencies are included in the IVBEM formulation. A singular value decomposi
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Reports on the topic "Objective computational identifier"

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Rimpel, Aaron. PR-316-17200-R03 A Study of the Effects of Liquid Contamination on Seal Performance. Pipeline Research Council International, Inc. (PRCI), 2021. http://dx.doi.org/10.55274/r0012015.

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This project is a continuation of research to enhance dry gas seal (DGS) reliability. Previous work reviewed failures from literature and experience of manufacturers and end-users and identified that liquid contamination was the most common cause, but it was concluded there was insufficient quantitative data to base recommendations on for further DGS reliability enhancements. Therefore, experimental and analytical investigations were pursued to fill the void. The ultimate objective was to be able to predict DGS failures due to liquid contamination, which could lead to greater DGS reliability t
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Pawlowski, Wojtek P., and Avraham A. Levy. What shapes the crossover landscape in maize and wheat and how can we modify it. United States Department of Agriculture, 2015. http://dx.doi.org/10.32747/2015.7600025.bard.

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Meiotic recombination is a process in which homologous chromosomes engage in the exchange of DNA segments, creating gametes with new genetic makeup and progeny with new traits. The genetic diversity generated in this way is the main engine of crop improvement in sexually reproducing plants. Understanding regulation of this process, particularly the regulation of the rate and location of recombination events, and devising ways of modifying them, was the major motivation of this project. The project was carried out in maize and wheat, two leading crops, in which any advance in the breeder’s tool
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Or, Etti, David Galbraith, and Anne Fennell. Exploring mechanisms involved in grape bud dormancy: Large-scale analysis of expression reprogramming following controlled dormancy induction and dormancy release. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7587232.bard.

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The timing of dormancy induction and release is very important to the economic production of table grape. Advances in manipulation of dormancy induction and dormancy release are dependent on the establishment of a comprehensive understanding of biological mechanisms involved in bud dormancy. To gain insight into these mechanisms we initiated the research that had two main objectives: A. Analyzing the expression profiles of large subsets of genes, following controlled dormancy induction and dormancy release, and assessing the role of known metabolic pathways, known regulatory genes and novel se
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Styling Parameter Optimization of the Type C Recreational Vehicle Air Drag. SAE International, 2021. http://dx.doi.org/10.4271/2021-01-5094.

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Recreational vehicles have a lot of potential consumers in China, especially the type C recreational vehicle is popular among consumers due to its advantages, prompting an increase in the production and sales volumes. The type C vehicle usually has a higher air drag than the common commercial vehicles due to its unique appearance. It can be reduced by optimizing the structural parameters, thus the energy consumed by the vehicle can be decreased. The external flow field of a recreational vehicle is analyzed by establishing its computational fluid dynamic (CFD) model. The characteristic of the R
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