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SSRN 2024年

作者： Zhang, Kaihang Chen, Zefang Wang, Dong Luo, Jinming Liu, Su Crittenden, John C. Brook Byers Institute of Sustainable Systems School of Civil and Environmental Engineering Georgia Institute of Technology AtlantaGA30332 United States

The research investigated the pulse potential effect on Electrochemical Advanced Oxidation Processes (EAOPs) for benzoic acid oxidation. The current efficiency of the electrooxidation is enhanced by changing the pulse frequency and potential on electrodes. The experiments showed that there are opposing phenomena affecting energy efficiency. On the one hand, pulse potential accelerates the mass transfer of benzoic acid in an electric field. On the other hand, pulse potential increases the non-faradic current that uses energy without causing oxidation. Using the Sand equation and the electric double-layer theory, we optimized the pulse frequency and voltage amplitude to achieve the highest energy efficiency for the pulse potential EAOPs. Compared with DC (Direct current) EAOPs, the pulse potential EAOPs save 50% EE/O and have a 41 % CE for the 4_2 V cycle at 50 Hz. Therefore, pulse potential EAOPs can achieve both high pollutant degradation efficiency and low energy consumption at the same time. © 2024, The Authors. All rights reserved.

关键词： Mass transfer

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Comparing Fairness of Generative Mobility Models

arXiv

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arXiv 2024年

作者： Wang, Daniel McFarland, Jack Mashhadi, Afra Ugurel, Ekin Computing and Software Systems University of Washington Bothell United States Department of Civil & Environmental Engineering University of Washington Seattle United States

Crowd flow data serves as a foundation for predictive modeling, aiding in understanding of city structure [3], epidemics [12], and visitation patterns [9]. Extensive mobility studies have applied variety of models in this area, however there has been little work in quantifying the fairness of them in terms of the equity of their performance across geographical space. Indeed, as recent evidence from the broader machine learning domain has shown, the systematic discrimination in making decisions against different groups has been shifted from people to autonomous algorithms [6]. In many applications, discrimination may be defined by different protected attributes, such as race, gender, ethnicity, and religion, that directly prevent favorable outcomes for a minority group in societal resource allocation, education equality, employment opportunity, etc [8]. Similarly, in the context of spatiotemporal data, mobility demand prediction algorithms have been shown to offer higher service quality to neighborhoods with a larger Caucasian population [4]. However, in such contexts, only a handful of recent studies exist that examine the fairness of location-based systems [13], and to the best of our knowledge, no effort has yet been made in measuring the fairness of generative mobility models and their resulting synthetic traces. In this paper, we seek to measure and compare these models based on fairness performance across multiple datasets. We do so by introducing metrics for evaluating both the utility of a generative model and the quality and fairness of their resulting traces, where accuracy is measured in terms of Common Part of Commuters (CPC). This metric is based on the Sørensen-Dice index and measures the similarity between real flows and generated flows (Equation 1) (Equation presented). Where ŷ is the generated flow, and y is the real flow between location i and j. It is worth noting that, CPC is always positive and contained in the closed interval [0,1] where 1 is a

关键词： Resource allocation

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Point Cloud Semantic Segmentation of Concrete Surface Defects Using Dynamic Graph CNN 38

Point Cloud Semantic Segmentation of Concrete Surface Defect...

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38th International Symposium on Automation and Robotics in Construction, ISARC 2021

作者： Bahreini, F. Hammad, A. Department of Building Civil and Environmental Engineering Concordia University Canada Concordia Institute for Information Systems Engineering Concordia University Canada

ISBN: (纸本)9789526952413

Obtaining accurate information of defective areas of infrastructures helps to perform repair actions more efficiently. Recently, LiDAR scanners are used for the inspection of surface defects. Moreover, machine learning methods have attracted the attention of researchers for semantic segmentation and classification based on point cloud data. Although much work has been done in the area of computer vision based on images, research on machine learning methods for point cloud semantic segmentation is still in its early stages, and the current available deep learning methods for semantic segmentation of the concrete surface defects are based on converting point clouds to images or voxels. This paper proposes an approach for detecting concrete surface defects (i.e. cracks and spalls) using a Dynamic Graph Convolutional Neural Network (Dynamic Graph CNN) model. The proposed method is applied to a point cloud dataset from four concrete bridges in Montreal. The experimental results show the usefulness and robustness of the proposed method in detecting concrete surface defects from 3D point cloud data. Based on the sensitivity analysis of the model using three cases defined with different number of input points, the best test results show the detection recall for cracks and spalls are 55.20% and 89.77%, respectively. © 2021 Proceedings of the International Symposium on Automation and Robotics in Construction. All rights reserved.

关键词： Semantic Segmentation

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Discrete Event Simulation of Multi-purpose Utility Tunnels Construction Using Microtunneling 38

Discrete Event Simulation of Multi-purpose Utility Tunnels C...

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38th International Symposium on Automation and Robotics in Construction, ISARC 2021

作者： Jorjam, S. Hammad, A. Department of Building Civil and Environmental Engineering Concordia University Canada Concordia Institute for Information Systems Engineering Concordia University Canada

ISBN: (纸本)9789526952413

The traditional method of burying underground utilities (e.g., water, sewer, gas pipes, and electrical cables) has been used for many decades. Repeated excavations related to this method cause many problems, such as traffic congestion and business disruption, which can significantly increase the social costs. Multi-purpose Utility Tunnels (MUTs) are a good alternative for buried utilities. Although MUTs are more expensive than the traditional method, social cost savings can make them more practical, especially in dense areas. The construction method is one of the most important factors that should be carefully assessed to have a successful MUT project. Simulation can be used for investigating the different construction methods of MUTs. In this paper, simulation of the MUT construction methods is done using Discrete Event Simulation (DES) to analyze the duration of MUT projects focusing on microtunneling. © 2021 Proceedings of the International Symposium on Automation and Robotics in Construction. All rights reserved.

关键词： Robotics

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CAPEES and FESE journal:Together to serve the environmental research community

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Frontiers of environmental Science & engineering 2022年第5期16卷 1-1页

作者： Xing Xie Jinkai Xue Hongliang Zhang School of Civil and Environmental Engineering Georgia Institute of TechnologyAtlantaGA 30339USA Environmental Systems Engineering Faculty of Engineering and Applied ScienceUniversity of ReginaRegina SK S4S 0A2Canada Department of Environmental Science and Engineering Fudan UniversityShanghai 200438China

Chinese scholars worldwide are active contributors in the environmental engineering and Science(EES)*** promote the scientific discovery,information exchange,professional growth,and career development of Chinese scholars in North America and beyond,as well as to pay back to the scholarly community and society at large,the Chinese-American Professors in environmental engineering and Science(CAPEES)was established in 2007 by pioneering and visionary Chinese American *** the vibrant presidency leaderships of 15 CAPEES presidents and effort by numerous officers since its establishment,CAPEES has become the largest academic association of Chinese EES scholars outside of China(***).

关键词： Together journal outside

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2D-HASAP: Two-Dimensional Heading-Aided Single-Anchor Positioning via Hidden Markov Model Map-Matching

2D-HASAP: Two-Dimensional Heading-Aided Single-Anchor Positi...

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2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration, SDF-MFI 2023

作者： Zobar, Serkan Çiydem, Mehmet Salor, Özgül Toth, Charles K. Yilmaz, Alper Aselsan Inc. Defence Systems Technologies Business Sector Ankara06200 Turkey Gazi University The Department of Electrical and Electronics Engineering Ankara06570 Turkey Gazi University Department of Electrical and Electronics Engineering Ankara06570 Turkey Kyrgyz-Turkish Manas University Department of Electrical and Electronics Engineering Bishkek720044 Kyrgyzstan The Ohio State University Department of Civil Environmental and Geodetic Engineering ColumbusOH43210 United States

ISBN: (纸本)9798350382587

This paper proposes a two-dimensonal positioning method based on a hidden Markov model map-matching scheme. The states of the hidden Markov model are generated by dividing the area of interest into a grid. At each time instant, the method considers two types of measurements: the platform's heading and the two-dimensional distance between the platform and the single-anchor. A recursive Bayesian estimator exploits these measurements to estimate the platform's position. The platform's heading measurement is used to calculate the prior probability distribution. Following this, observation likelihood is computed by considering the two-dimensional distance measurement as the observation of the hidden Markov model. Finally, the most probable projection of these measurements on the states of the hidden Markov model is estimated as the platform's position. The proposed method can be efficiently used, especially in constrained indoor and outdoor environments. Moreover, the method provides a two-dimensional positioning solution with an increased robustness thanks to the bounded error on the distance measurements. Simulation studies are provided to demonstrate the effectiveness of the proposed method. © 2023 IEEE.

关键词： Hidden Markov models

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Analysis of Energy Consumption Drivers in Building Rooms: A Case of the Commercial Complex in Chengdu 16th

Analysis of Energy Consumption Drivers in Building Rooms: A ...

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16th International Conference on Computer Science and its Applications, CSA 2024

作者： Zhong, Huiyang Ma, Haonan Hu, Pengcheng Zhou, Xiaojie Zhuang, Xucheng Lin, Yulei Zhang, Peiqi Ji, Yihang Zou, Jixin Wang, Ning Liu, Guodan Master of Civil and Hydraulic Engineering School of Environmental and Municipal Engineering Qingdao University of Technology Qingdao266525 China Shandong Engineering Research Center of Healthy Environment and Low-Carbon Energy Qingdao266525 China School of Environmental and Municipal Engineering Qingdao University of Technology Qingdao266525 China Civil Engineering School of Environmental and Municipal Engineering Qingdao University of Technology Qingdao266525 China Qingdao Hisense Hitachi Air-Conditioning Systems Co. Ltd. Qingdao266520 China

ISBN: (纸本)9789819656929

To enhance energy-saving potential in the architectural design phase, this study explores the energy consumption drivers of a standard floor in a commercial complex in Chengdu We collected the energy consumption data during the cooling season and the operational timings of air conditioning systems across rooms with different orientations, and calculated the Energy Consumption Index (ECI), defined as the energy usage per hour per unit area of a room. Our findings revealed a distinct pattern in ECI during the cooling season, with west-facing rooms exhibiting the highest ECI, followed by east, south, and north orientations in descending order. We employed the DeST-C software to simulate a range of standard buildings, varying both in orientation and window-to-floor ratio. The simulations demonstrated that, when rooms share an identical structural configuration but differ only in orientation, the ECI during the cooling season follows to the same trend as previously observed. Moreover, when examining rooms with the same orientation but different in window-to-floor ratio, we found that an increase in window-to-floor ratio correlates positively with an elevation in ECI during the cooling season. These findings highlight the critical importance of considering building orientation and window-to-floor ratio as pivotal factors in designing energy-efficient structures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Energy efficiency

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Analysis of Factors Affecting Air Conditioning Energy Consumption: The Case Study of a Commercial Building in Shenzhen 16th

Analysis of Factors Affecting Air Conditioning Energy Consum...

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16th International Conference on Computer Science and its Applications, CSA 2024

作者： Hu, Pengcheng Ji, Yihang Zhong, Huiyang Zhou, Xiaojie Zhuang, Xucheng Zhang, Peiqi Lin, Yulei Ma, Haonan Zou, Jixin Wang, Ning Liu, Guodan Civil and Hydraulic Engineering School of Environmental and Municipal Engineering Qingdao University of Technology Qingdao266525 China Shandong Engineering Research Center of Healthy Environment and Low-Carbon Energy Qingdao266525 China School of Environmental and Municipal Engineering Qingdao University of Technology Qingdao266525 China Civil Engineering School of Environmental and Municipal Engineering Qingdao University of Technology Qingdao266525 China Qingdao Hisense Hitachi Air-Conditioning Systems Co. Ltd. Qingdao266520 China

ISBN: (纸本)9789819656929

With the development of economy, building energy consumption increases rapidly. This paper used a commercial building in Shenzhen as a case study to analyze the factors influencing air conditioning energy consumption in commercial buildings and proposed recommendations for reducing building energy consumption. After analyzing the real-time data collected by the Internet of Things (IoT), it was found that there are significant differences in energy consumption among shops of the same type on the same floor (Shop 1, Shop 3, Shop 8). Comparison of the floor plan revealed that these high-energy-consuming shops are situated in the corner areas of the building. Using the DeST energy simulation software to model the building’s energy consumption, it was found that the solar radiant heat density and outdoor temperature have a significant impact on air conditioning energy consumption. This paper proposed replacing the existing glass with low-e glass, and energy consumption simulations based on this recommendation showed significant improvements in the results. This provides some ideas for reducing the operating cost of commercial buildings. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Active solar buildings

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Iris Liveness Detection Using Fragmental Energy of Haar Transformed Iris Images Using Ensemble of Machine Learning Classifiers

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Computer Modeling in engineering & Sciences 2023年第7期136卷 323-345页

作者： Smita Khade Shilpa Gite Sudeep D.Thepade Biswajeet Pradhan Abdullah Alamri Symbiosis International(Deemed University) Symbiosis Institute of TechnologyPune412115India Symbiosis Centre for Applied Artificial Intelligence Symbiosis International(Deemed University)Pune412115India Computer Engineering Pimpri Chinchwad College of EngineeringPune411044India Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS) School for Civil and Environmental EngineeringFaculty of Engineering and Information TechnologyUniversity of Technology SydneySydneyNew SouthWales2007Australia Earth Observation Center Institute of Climate ChangeUniversity Kebangsaan MalaysiaUKMBangiSelangor43600Malaysia Department of Geology&Geophysics College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

Contactless verification is possible with iris biometric identification,which helps prevent infections like COVID-19 from *** systems have grown unsteady and dangerous as a result of spoofing assaults employing contact lenses,replayed the video,and print *** work demonstrates an iris liveness detection approach by utilizing fragmental coefficients of Haar transformed Iris images as signatures to prevent spoofing attacks for the very first time in the identification of iris *** assorted feature creation ways are studied in the presented solutions,and these created features are explored for the training of eight distinct machine learning classifiers and *** predicted iris liveness identification variants are evaluated using recall,F-measure,precision,accuracy,APCER,BPCER,and *** standard datasets were used in the *** main contribution of our study is achieving a good accuracy of 99.18%with a smaller feature *** fragmental coefficients of Haar transformed iris image of size 8∗8 utilizing random forest algorithm showed superior iris liveness detection with reduced featured vector size(64 features).Random forest gave 99.18%***,conduct an extensive experiment on cross datasets for detailed *** results of our experiments showthat the iris biometric template is decreased in size tomake the proposed framework suitable for algorithmic verification in real-time environments and settings.

关键词： Iris images liveness identification Haar transform machine learning biometric feature formation ensemble model

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PeRP: Personalized Residual Policies For Congestion Mitigation Through Co-operative Advisory systems

PeRP: Personalized Residual Policies For Congestion Mitigati...

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International Conference on Intelligent Transportation

作者： Aamir Hasan Neeloy Chakraborty Haonan Chen Jung-Hoon Cho Cathy Wu Katherine Driggs-Campbell Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Department of Civil and Environmental Engineering (CEE) MIT Laboratory for Information & Decision Systems (LIDS) Massachusetts Institute of Technology Department of Civil and Environmental Engineering (CEE) MIT Laboratory for Information & Decision Systems (LIDS) Institute for Data Systems & Society (IDSS) at the Massachusetts Institute of Technology

Intelligent driving systems can be used to mitigate congestion through simple actions, thus improving many socioeconomic factors such as commute time and gas costs. However, these systems assume precise control over autonomous vehicle fleets, and are hence limited in practice as they fail to account for uncertainty in human behavior. Piecewise Constant (PC) Policies address these issues by structurally modeling the likeness of human driving to reduce traffic congestion in dense scenarios to provide action advice to be followed by human drivers. However, PC policies assume that all drivers behave similarly. To this end, we develop a co-operative advisory system based on PC policies with a novel driver trait conditioned Personalized Residual Policy, PeRP. PeRP advises drivers to behave in ways that mitigate traffic congestion. We first infer the driver's intrinsic traits on how they follow instructions in an unsupervised manner with a variational autoencoder. Then, a policy conditioned on the inferred trait adapts the action of the PC policy to provide the driver with a personalized recommendation. Our system is trained in simulation with novel driver modeling of instruction adherence. We show that our approach successfully mitigates congestion while adapting to different driver behaviors, with 4 to 22% improvement in average speed over baselines. 1

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