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IEEE International Conference on Consumer Electronics (ICCE)

作者： Xiang-Rui Huang Huai-Jhan Ke Szu-Yu Kuo Liang-Bi Chen Department of Electrical Engineering Master Program in Electrical Engineering and Computer Science National Penghu University of Science and Technology Penghu Taiwan Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Shipping and Transportation Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Lilies are popular in the global flower market, but consumers often lack information about specific varieties. To address this issue, this paper proposes a computer recognition platform based on the Vision Transformer (ViT) architecture. The proposed platform uses an improved vision transformer (ViT) architecture to classify different types of lilies, allowing consumers to access information and names of various Lilium species. The experimental results show that the proposed lily classification model achieved a 96.4% accuracy rate in classifying six lily species.

关键词： Computer vision Electric potential Accuracy Computational modeling Computer architecture Computer applications Flowering plants Network architecture Transformers Consumer electronics

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An Improved Vision Transformer Architecture-Based Computer Recognition Platform for Lilium Classification

An Improved Vision Transformer Architecture-Based Computer R...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Huang, Xiang-Rui Ke, Huai-Jhan Kuo, Szu-Yu Chen, Liang-Bi Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Shipping and Transportation Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan

ISBN: (纸本)9798331521165

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SMART quality control analysis of pavement condition data for pavement management applications

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International Journal of transportation Science and Technology 2024年

作者： Chang, Carlos M. Cheng, DingXin Smith, Roger E. Tan, Sui G. Hossain, Abid Department of Civil and Environmental Engineering Florida International University MiamiFL33174 United States Department of Civil Engineering California Preservation Center California State University ChicoCA 95929 United States Professor Emeritus Zachry Department of Civil Engineering Texas A&M University College StationTX77843 United States StreetSaver Program Manager Regional Streets & Roads Program Metropolitan Transportation Commission San FranciscoCA94105 United States

Assuring the accuracy and reliability of pavement condition data is crucial for effective decision-making in pavement management. Despite existing data collection protocols, concerns persist regarding data quality. This paper introduces SMART, a systematic statistical method designed to analyze the quality of pavement condition data from field surveys for pavement management applications. SMART employs a structured procedure that expands traditional descriptive statistics by applying interrater reliability statistics combined with bootstrapping methods and Modified Blant Altman diagrams to evaluate data quality. A comparative analysis of interrater statistics, including Cohen's Kappa (CK), Interclass Correlation (IC), Krippendorff's Alpha (KA), Percent Agreement (PA), and Weighted Cohen's Kappa (WCK), is conducted in the research study. As a result, the adoption of KA and Modified Bland-Altman diagrams for data analysis is recommended. KA demonstrates versatility across diverse data types, accommodating nominal, ordinal, interval, and ratio-level data, while Modified Bland-Altman diagrams facilitate data dispersion analysis to visualize possible bias trends for the condition ratings. A case study is presented to demonstrate the applicability of SMART to analyzing Pavement Condition Index (PCI) data provided by the Metropolitan transportation Commission (MTC) in California. This methodological approach aims to enhance pavement management decisions by ensuring the reliability of condition field survey data through the implementation of robust analytical quality control procedures. © 2024 Tongji University and Tongji University Press

关键词： Quality control

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Developing a sustainable development goals index for OECD countries: An effectiveness-based hierarchical data envelopment analysis

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Environmental Science and Policy 2024年 160卷

作者： Guo, Yongli Yu, Ming-Miin See, Kok Fong College of Engineering Shandong Xiandai University Jinan China Economics Program School of Distance Education Universiti Sains Malaysia Malaysia Department of Transportation Science National Taiwan Ocean University Taiwan

The Sustainable Development Goals (SDGs) consist of a set of multidimensional indicators comprising 17 goals and 169 targets from various perspectives. The use of a composite index is crucial for assessing the overall performance of each country in relation to the SDGs, given the extensive range of indicator measures involved. However, different weight schemes may lead to different results. Therefore, incorporating an objective weight is required to ensure the comparability and accuracy of the index. The main objective of this paper is to construct an SDG index for Organisation for Economic Co-operation and Development (OECD) countries using an effectiveness-based hierarchical data envelopment analysis (H-DEA) model and apply it to assess SDG effectiveness in OECD countries. The results of this study provide countries with more valuable insights based on the weights of the goals (indicators) that are endogenous to the dataset, assisting them in identifying priorities and strategies to improve future SDG performance. © 2024 Elsevier Ltd

关键词： Hierarchical data envelopment analysis Sustainable development goals

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Predictive Analysis Of a Highway Road Accident in Thailand:Using Machine Learning Approach

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SSRN 2022年

作者： Mohamad, Ittirit Jomnonkwao, Sajjakaj Ratanavaraha, Vatanavongs Program of Energy and logistics Management Engineering School of Mechanical Engineering Faculty of Engineering Suranaree University of Technology Nakhon Ratchasima Thailand School of Transportation Engineering Faculty of Engineering Suranaree University of Technology Nakhon Ratchasima Thailand

Accidents are a major obstacle to economic development and quality of life in developing countries. The same challenges are perceived today as major issues in Thailand. This research aims to assess the frequency and most common causes of road accidents that are most likely to result in fatalities. Machine learning technique is employed to examine the relation of factors in accidents, which are then applied to policymaking to lower the rate of road accidents and economic and human resource losses, as well as improve the overall efficiency of a country’s healthcare *** this article, the researcher has included information regarding the incidence of road accidents in Thailand during the years 2015–2020;a total of 167,820 events were recorded by the Thailand Department of Public Disaster Prevention and Mitigation, with total damages costing some 1.13 billion Thai baht (34 million USD). Although the overall data comprises the elements influencing the accidents, this article only considers the drivers who were the causes of fatal highway accidents. After eliminating the passengers and concentrating exclusively on the drivers, 24,559 events *** a result of the association rule, the factors that enhance the likelihood of fatality in highway road accidents are as follows: driver info, male;driver behavior, over speed limit;vehicle type, motorbike;roadway, straight, dry surface;and weather, clear. All of these variables are related, as the association rule shows an increased risk of injury or death in traffic accidents involving males riding motorcycles at speeds exceeding the posted limits on straight roads in clear weather. With all of these trends discovered, policymakers may be able to eliminate some of the factors implicated in highway traffic accidents and raise awareness to avoid risky driver conduct and even propose laws to control. © 2022, The Authors. All rights reserved.

关键词： Predictive analytics

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Integrated Vsl/Rm Control for Roadways with Multiple Bottlenecks to Reduce Emissions and Fuel Use

SSRN

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SSRN 2022年

作者： Michael Zhang, H. Gao, Hang Chen, Shenyang Department of Civil and Environmental Engineering University of California at Davis DavisCA95616 United States Transportation Technology and Policy Program Institute of Transportation Studies University of California DavisCA95616 United States

Variable speed limit (VSL) control has been used to smooth traffic flow, improve traffic safety and reduce traffic congestion. The majority of VSL control algorithms proposed in the literature, however, target roadways with a single bottleneck. Such VSL controls may fail to produce the intended improvements when applied to roadways with multiple bottlenecks. In this paper, we develop a global feedback VSL control scheme that 1) integrates VSL with ramp metering (RM) control, 2) coordinates VSL controls across multiple bottlenecks, and 3) brings traffic emissions to the near-minimal state for the studied roadway. This near-minimal state was obtained by analyzing the emission profiles under different operating conditions using the microscopic simulation tool SUMO. The new VSL control scheme is compared with several feedforward and feedback VSL control schemes using SUMO simulation and was found to reduce emissions and fuel consumption substantially over the other VSL schemes with no degradation in travel time. © 2022, The Authors. All rights reserved.

关键词： Traffic congestion

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Parameter Identification of Signal Attenuation for High Speed Rail Communication System Using Grey Box Neural Network

Parameter Identification of Signal Attenuation for High Spee...

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International Conference on Instrumentation Control and Automation (ICA)

作者： Selvi Lukman Yul Yunazwin Nazaruddin Endra Joelianto Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Department of Engineering Physics Instrumentation Control Research Group Institut Teknologi Bandung Bandung Indonesia National Center for Sustainable Transportation Technology Bandung Indonesia

A reliable connected digital railways must face a huge challenge of network and frequency planning in order to deploy a dedicated infrastructure for High Speed Rail (HSR). This paper investigates the parameter identification of signal attenuation for HSR in a free space propagation case. A neural network based optimization of Grey Box Neural Network (GBNN) is utilized to validate the parameter identification results. Satisfying results of minimum convergences of RMSE = 1.6371 and MAPE = 0.015 have been achieved. Furthermore, the ability of identified parameter in adjusting the dynamic scenario of the real signal attenuation measurement dataset is displayed when the distance is 118.45 meter and the path loss value is 116.82 dB. Through this applied neural network based technique, network designers are able to plan and design the best possible of network performances and frequency planning for HSR.

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PRODUCTION PLANNING AND CONTROL AS-IMAGINED AND AS-DONE: THE GAP AT THE LOOK-AHEAD LEVEL 29

PRODUCTION PLANNING AND CONTROL AS-IMAGINED AND AS-DONE: THE...

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29th Annual Conference of the International Group for Lean Construction, IGLC 2021

作者： Hamerski, Douglas Comassetto de Araujo Fernandes, Luara Lopes Porto, Mattheus Souza Saurin, Tarcisio Abreu Formoso, Carlos Torres Costa, Dayana Bastos Postgraduate Program in Civil Eng.: Construction and Infrastructure Federal University of Rio Grande do Sul Porto Alegre Brazil Postgraduate Program in Civil Engineering Federal University of Bahia Salvador Brazil Industrial Engineering and Transportation Department Federal University of Rio Grande do Sul Brazil School of Engineering Department of Structural and Construction Engineering Federal University of Bahia Salvador Brazil

ISBN: (纸本)9786124802546

The Last Planner® System (LPS) of Production Control is widely acknowledged as fit to tackle the complexity of construction projects. However, the implications of complexity in the implementation of LPS itself have not been investigated. Those implications are investigated in this paper by exploring the gap between production planning and control-as-imagined and as-done at the look-ahead level. For that purpose, a case study was conducted in the refurbishment of a department store in which the LPS was implemented. Data collection involved document analysis, participant observation at the look-ahead and short-term planning meetings, and unstructured interviews. The Functional Resonance Analysis Method (FRAM) was used for modeling variability and interactions between the managerial functions at the look-ahead planning level. Results indicated several differences between production planning and control-as-imagined and as-done, which reflect hidden activities required for the removal of constraints. These activities took time and effort from managers and therefore they can partly explain why the LPS was not strictly followed as-imagined in theory. © Prof. Luis F. Alarcón and Assoc. Prof. Vicente González, IGL2021 All rights reserved.

关键词： Planning

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Small Uncrewed Aircraft Systems-Based Orthophoto and Digital Elevation Model Creation and Accuracy Evaluation for Airfield Portland Cement Concrete Pavement Distress Detection and Rating

Small Uncrewed Aircraft Systems-Based Orthophoto and Digital...

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International Conference on transportation and Development 2022, ICTD 2022

作者： All Sourav, Md. Abdullah Ceylan, Halil Kim, Sunghwan Brooks, Colin Peshkin, David Dobson, Richard Brynick, Matthew Dipilato, Mike Dept. of Agricultural and Biosystems Engineering Iowa State Univ. AmesIA United States Dept. of Civil Construction and Environmental Engineering Program for Sustainable Pavement Engineering and Research Iowa State Univ. AmesIA United States Program for Sustainable Pavement Engineering and Research Institute for Transportation Iowa State Univ. AmesIA United States Transportation Practice Area Leader Michigan Tech Research Institute Ann ArborMI United States Applied Pavement Technology Inc. UrbanaIL United States Michigan Tech Research Institute Ann ArborMI United States Federal Aviation Administration Airport Pavement R&D Section William J. Hughes Technical Center NJ United States

ISBN: (数字)9780784484371

ISBN: (纸本)9780784484371

Early detection and repair of airfield pavement distresses are essential aspects of preserving airport pavements for the full spans of their design periods and maintaining their structural integrity, ride quality, and safety. In recent years, various studies have been conducted for pavement distress detection and mapping using alternate data collection methodologies, including small uncrewed aerial systems (sUAS). This study evaluates the usefulness of red-green-blue (RGB) orthophoto and digital elevation models (DEMs) generated from sUAS data in detecting various airfield Portland cement concrete (PCC) pavement distress. Fourteen airfield PCC pavement distresses with different severities were studied using RGB orthophotos with resolutions ranging from 0.8 mm/pixel to 21 mm/pixel and DEM resolutions ranging from 3.0 mm/pixel to 84 mm/pixel. The analysis showed that the RGB optical orthophotos and DEM were useful for detecting 13 out of 14 PCC pavement distresses and confirmation of the location of 11 out of 14 distresses, respectively. © ASCE. All rights reserved.

关键词： Portland cement

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Characterization of Binder, Mastic, and Fam Film Thickness within Asphalt Concrete Mixtures

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SSRN 2023年

作者： de Souza, Thiago Delgado Enríquez-León, Alexis Jair Mesquita, Andressa Rosa da Fonseca Martins Gomes, Otávio Ulsen, Carina Underwood, Benjamin Shane Aragão, Francisco Thiago Sacramento Civil Engineering Program - COPPE Federal University of Rio de Janeiro Rio de Janeiro21941-596 Brazil Transportation Engineering Program - COPPE Federal University of Rio de Janeiro Rio de Janeiro21941-596 Brazil Center for Mineral Technology - CETEM Rio de Janeiro21941-908 Brazil Mining and Petroleum Engineering Program - POLI-USP Universidade of São Paulo São Paulo05508-010 Brazil Civil Construction and Environmental Engineering Program North Carolina State University Raleigh27695-7908 United States

Aggregate particles within an asphalt mixture are coated in a thin film of binder. Several studies and even mix design procedures have been based on an implied correlation between the binder film thickness (BFT) and the mechanical properties of these mixtures. Those studies generally define the BFT based on a predictive equation linked to one or more theoretical considerations, but without direct experimental determination of the BFT. However, recent developments of powerful scanning electron microscopes (SEMs) and digital image processing (DIP) techniques allow one to perform detailed analysis of microstructural images and thus directly measure the BFT value. This paper presents an analysis of BFT and mastic film thickness (MFT) within asphalt concrete (AC) mixtures using high-resolution SEM images and DIP. Based on this methodology, the measured mean BFT and MFT values ranged from 5.6 µm to 10.8 µm, and from 20.8 µm to 28.2 µm, respectively. Additionally, a BFT analysis considering fine aggregate matrix (FAM) phase within the ACs was pursued. A criterion to obtain FAM BFT is proposed and it can be useful in volumetric FAM mix design and sample fabrication. © 2023, The Authors. All rights reserved.

关键词： Film thickness

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