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Smartphone-based colorimetric detection of formaldehyde in the air

Building Simulation 2024年第11期17卷 2007-2015页

作者： Meng Yang Jin Ye Tao Yu Ying Song Hua Qian Tianyi Liu Yang Chen Junqi Wang Shi-jie Cao Cong Liu School of Energy and Environment Southeast UniversityNanjing210096China School of Energy and Power Jiangsu University of Science and TechnologyZhenjiangJiangsu212100China Wuhan Second Ship Design and Research Institute Wuhan430205China Hubei Provincial Engineering and Technology Research Center for Food Quality and Safety Test Hubei Provincial Institute for Food Supervision and TestWuhan430075China Laboratory of Image Science and Technology the School of Computer Science and EngineeringSoutheast UniversityNanjingChina Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Southeast UniversityNanjingChina School of Cyber Science and Engineering Southeast UniversityNanjingChina Key Laboratory of Computer Network and Information Integration Southeast UniversityMinistry of EducationNanjingChina School of Architecture Southeast UniversityNanjingChina Jiangsu Province Engineering Research Center of Urban Heat and Pollution Control Southeast UniversityNanjingChina Global Centre for Clean Air Research(GCARE) University of SurreyGuildfordUK

Adverse impacts of exposure to formaldehyde on human health significantly increases attention in monitoring formaldehyde concentrations in the *** formaldehyde detection methods typically rely on large and costly instruments and requires high skills of expertise,preventing it from being widely accessible to *** study introduced a novel approach utilizing smartphone-based colorimetric *** of green channel signals of digital images by a smartphone successfully capture variation of purple color of 4-amino-3-hydrazino-5-mercapto-1,2,4-triazol solution,which is proportional to formaldehyde *** is because that green and purple are complimentary color pairs.A calibration curve was established between green channel signals and formaldehyde concentrations,with a correlation coefficient of *** limit of the smartphone-based method is 0.008 mg/m^(3).Measurement errors decrease as formaldehyde concentrations increase,with median relative errors of 34%,17%,and 6%for concentration ranges of 0–0.06 mg/m^(3),0.06–0.12 mg/m^(3),and 0.12–0.35 mg/m^(3),*** method replaced scientific instrumentation with ordinary items,greatly reducing cost and operation *** would provide an opportunity to realize onsite measurements for formaldehyde by occupants themselves and increase awareness of air quality for better health protection.

关键词： indoor air quality VOC RGB color identification machine vision

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Compliance Management of IaC-Based Cloud Deployments During Runtime 23

Compliance Management of IaC-Based Cloud Deployments During ...

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Proceedings of the IEEE/ACM 16th International Conference on Utility and Cloud Computing

作者： Ghareeb Falazi Lukas Harzenetter Kálmán Képes Frank Leymann Uwe Breitenbücher Evangelos Ntentos Uwe Zdun Martin Becker Elena Heldwein Institute of Architecture of Application Systems University of Stuttgart Stuttgart Germany Reutlingen University Reutlingen Germany Research Group Software Architecture Faculty of Computer Science University of Vienna Vienna Austria IBM Deutschland Böblingen Germany

ISBN: (纸本)9798400702341

Modern cloud applications increasingly depend on Infrastructure-as-Code (IaC) practices for infrastructure automation to help manage the complexity of deploying large-scale architectures. Additionally, the deployment of cloud applications is commonly subject to compliance rules. Moreover, designing compliant IaC-based cloud deployments is not enough since runtime changes to the infrastructure or the configuration of individual components may introduce compliance violations. Often, the process of checking and fixing such violations is done manually, which is time-consuming and error-prone. Therefore, this work aims to define and implement a method for runtime IaC compliance management that reduces the complexity, effort, and uncertainty of checking and enforcing compliance rules against IaC-based cloud deployments at runtime. To this end, we follow the design-science research methodology to design and implement (i) the Runtime IaC Compliance Management (RICMa) method and (ii) the IaC Compliance Management Framework (IaCMF) that supports the execution of the RICMa method. We prototypically implement IaCMF and evaluate it using a qualitative interview study with industry experts.

关键词： infrastructure-as-code IaC IT compliance cloud compliance compliance management

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Effects of Adopting Industry 4.0 on a Manufacturing Plant

Effects of Adopting Industry 4.0 on a Manufacturing Plant

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International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Pranav Waghanna Akash Reddy Sarthak Deshpande Siddhant Chavan Vishal R. Jaiswal Vishal Naranje BE IT Department of Pune Institute of Computer Technology Pune IT Department of Pune Institute of Computer Technology Pune School of Engineering Architecture and Interior Design Amity University Dubai

ISBN: (数字)9798350350357

ISBN: (纸本)9798350350364

In the era of Industry 4.0, Smart Manufacturing is reshaping how things are made. At the heart of it is the Industrial Internet of Things (IIoT), where smart sensors and connections create a digital system for factories. This paper highlights how IIoT facilitates real-time data exchange, aiding quick decision-making and creating adaptable manufacturing setups. Cyber-Physical Systems (CPS) integration is also discussed, showing how the line between physical and digital elements in manufacturing is getting blurred. Big Data Analytics is another game-changer, supporting data-driven decisions and predictive maintenance. The paper also digs into Artificial Intelligence and Machine Learning, showing how they automate tasks and continuously learn, improving manufacturing processes. Real-world applications are examined, including Digital Twins, advanced robotics like collaborative robots (Cobots), 3D printing, and smart supply chain management. While Smart Manufacturing offers numerous benefits, it's not without challenges. The survey talks about security and privacy concerns, emphasizing the need for strong cybersecurity. Interoperability, ensuring different technologies work seamlessly together, and addressing the workforce skills gap are also explored. The paper ends with examples of successful implementations and looks at future trends, such as the impact of 5G, blockchain in supply chain management, human augmentation, and the push for sustainability in Smart Manufacturing. This survey is a practical guide for anyone interested in understanding the current state and where Smart Manufacturing is headed in the world of Industry 4.0.

关键词： Industries Surveys Technological innovation Supply chain management Market research Fourth Industrial Revolution Sustainable development

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What Drives I4.0 Adoption? Establishing the Importance of Strategy

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IEEE engineering Management Review 2023年第3期51卷 33-41页

作者： Arcidiacono, Francesco Ancarani, Alessandro Di Mauro, Carmela Schupp, Florian University of Catania Department of Electrical Electronic and Computer Engineering Catania95124 Italy Schaeffler Automotive Bühl Bühl77815 Germany University of Catania Department of Civil Engineering and Architecture Catania95124 Italy Corvinus University of Budapest Corvinus Institute for Advanced Studies Budapest1093 Hungary Constructor University School of Business Social and Decision Sciences Bremen28759 Germany

This article investigates the adoption patterns of Industry 4.0 (I4.0) technologies in the automotive component sector and links I4.0 adoption to competitive strategies. Analysis of survey data concerning 288 automotive suppliers reveals that most firms currently focus on implementing real-time collection and analysis of production data (i.e., the Internet of Things, Big Data, and Artificial Intelligence), while other technologies, such as additive manufacturing and blockchain, are infrequently adopted. I4.0 adoption is associated with a simultaneous strategic emphasis on cost, quality, and delivery, thus suggesting automotive suppliers look at I4.0 as a mean to overcome performance tradeoffs. Findings also confirm that small- and medium-sized firms are less likely to adopt I4.0. Based on these results, implications for academics, managers, and policymakers are suggested. © 1973-2011 IEEE.

关键词： Supply chains

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FAST CHARGING ELECTRIC BUSES IN MARIBOR: A COMPARATIVE ANALYSIS OF SIMULATION AND REAL-WORLD RESULTS 12th

FAST CHARGING ELECTRIC BUSES IN MARIBOR: A COMPARATIVE ANALY...

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12th International Conference on Environmental engineering, ICEE 2023

作者： Klemenčič, Mitja Španer, Marijan Lep, Marjan Moharić, Matej Department of Transportation Engineering Faculty of Civil Engineering Transportation Engineering and Architecture University of Maribor Smetanova 17 Maribor Slovenia Laboratory for Power Electronics Institute of Robotics Faculty of Electrical Engineering and Computer Science University of Maribor Koroška cesta 46 Maribor Slovenia

This paper presents a study of the energy consumption of a full electric bus charged at a fast-charging station with pantographs in the city of Maribor. The results of simulated and real tests on the PT line 6 are compared and analysed. The partly electrified PT line 6 provides insights on comparison between simulated energy consumption and re-al-life energy consumption, charging time and reliability of charging. The results reveal that the simulation considered several important factors like real life turnaround time, driving cycle, regenerative braking, charging time, peak hour charging time, heating/cooling systems, full passenger load as important and critical to identify the appropriate concept for charging. Technical and operational errors were identified in real world, due to connectivity failures or driver errors in positioning the vehicle, which were not considered in the simulation. The real-world data and procedure for selection of the most appropriate charging technology represent a good basis for full electrified Public Transport in Maribor. © 2023 The Author(s). Published by Vilnius Gediminas Technical university.

关键词： Electric buses

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LIAS: A Lightweight Incentive Authentication Scheme for Forensic Services in IoV

LIAS: A Lightweight Incentive Authentication Scheme for Fore...

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作者： Zhang, Mingyue Zhou, Junlong Cong, Peijin Zhang, Gongxuan Zhuo, Cheng Hu, Shiyan Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China Institute of Computing Technology Chinese Academy of Sciences State Key Laboratory of Computer Architecture Beijing100190 China Zhejiang University Department of Information Science and Electronic Engineering Hangzhou310027 China University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom

Internet of Vehicles (IoV) has become an indispensable data sensing and processing platform in Internet of Things (IoT) for intelligent transportation. The mounted cameras on the vehicles along with the fixed roadside cameras are utilized to provide pictorial services for IoV users and law enforcement agencies. For such forensic services, ensuring the security and privacy of vehicles while guaranteeing the efficiency of data transmission among vehicles is important. In this paper, we propose a lightweight incentive authentication scheme (LIAS) for forensic services in IoV. LIAS is developed on a three-tier architecture containing cloud layer, fog layer, and user layer. LIAS uses pairing-free certificateless signcryption, pseudonym update mechanism, and incentive mechanism to realize a secure anonymous authentication efficiently. We conduct correctness and security analysis, as well as performance analysis and evaluation to validate the high security and efficiency of LIAS. Experimental results reveal that, the communication and computation overheads as well as the message delay and packet loss of LIAS are much lower than those of state-of-the-art techniques. Note to Practitioners - This paper is motivated by the security and privacy issues of forensic services in IoV for intelligent transportation. Our goal is to improve the security and privacy of vehicles while guaranteeing the lightweight and incentive of data transmission among the vehicles. Fog-assisted IoV is introduced to fully utilize the capacities of near-user edge devices as well as the connections between fog nodes and devices. However, it still faces the difficulties in ensuring vehicles' security and privacy. Moreover, vehicles' information dissemination could be easily monitored because of the unavoidable defect of wireless communication. Thereby, it is essential to guarantee the security and privacy of vehicles while enhancing the efficiency of vehicles' data transmission during the forensic service.

关键词： Authentication

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Distributed Learning by Local Training ADMM 63

Distributed Learning by Local Training ADMM

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Ren, Xiaoxing Bastianello, Nicola Johansson, Karl H. Parisini, Thomas Kth Royal Institute of Technology 2School of Electrical Engineering and Computer Science and Digital Futures Stockholm Sweden Imperial College London Department of Electrical and Electronic Engineering London United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Trieste Italy

ISBN: (纸本)9798350316339

In this paper, we focus on distributed learning over peer-to-peer networks. In particular, we address the challenge of expensive communications (which arise when e.g. training neural networks), by proposing a novel local training algorithm, LTADMM. We extend the distributed ADMM enabling the agents to perform multiple local gradient steps per communication round (local training). We present a preliminary convergence analysis of the algorithm under a graph regularity assumption, and show how the use of local training does not compromise the accuracy of the learned model. We compare the algorithm with the state of the art for a classification task, and in different set-ups. The results are very promising showing a great performance of LT-ADMM, and paving the way for future important theoretical developments. © 2024 IEEE.

关键词： Peer to peer networks

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Intelligent Detection of Stratigraphy Boundary Based on Deep Learning 3rd

Intelligent Detection of Stratigraphy Boundary Based on Deep...

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3rd China Intelligent Robotics Annual Conference, CCF CIRAC 2022

作者： Zhao, Qin Wang, Tilin Liu, Yanming Yang, Mingsong Ning, Xiaojuan Hei, Xinhong School of Civil Engineering and Architecture Xi’an University of Technology Xi’an China China Railway First Survey and Design Institute Group Ltd. Xi’an China School of Computer Science and Engineering Xi’an University of Technology Xi’an China

ISBN: (纸本)9789819903009

Robotic exploration technology is widely used in various fields such as information acquisition and topographic photography. Due to dimensional transformation and data loss in data transmission, an additional manual pre-processing is required, which is very time consuming and difficult to ensure the data accuracy. In this paper, we propose an intelligent recognition method of stratigraphy boundaries of engineering geological images based on the Hough prior deep learning network (HT-LCNN). We annotate geological drawing datasets manually at first. And then improve the binary matrix size of the original network, retrain the network on a self-constructed dataset. Finally we design experiments to compare and analyze model learning capabilities so that the optimal model can be adopted to detect negligible gaps on graphical junctions. Experimental results demonstrate that our method outform HT-LCNN in recognizing strata features. It gives the robot the capability to intelligently recognize geological images and can accurately identify over 96% of stratigraphy boundaries and junctions location, thus improving the fluidity of data in the design process and reducing time costs. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Stratigraphy

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Enhanced satellite imagery analysis for post-disaster building damage assessment using integrated ResNet-U-Net model

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Multimedia Tools and Applications 2025年第5期84卷 2689-2714页

作者： Bhardwaj, Diwakar Nagabhooshanam, N. Singh, Ajeet Selvalakshmi, B. Angadi, Sanjeevkumar Shargunam, S. Guha, Tapas Singh, Gurkirpal Rajaram, A. Computer Engineering and Applications GLA University Chaumuhan India Department of Research Analytics Saveetha Dental College and Hospitals Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Aditya University Surampalem Andhra Pradesh India VIT Bhopal University Madhya Pradesh Bhopal466114 India Department of Computing Science and Engineering Tagore Engineering College Rathinamangalam Tamil Nadu Chennai600127 India Department of Computing Science and Engineering Nutan College of Engineering and Research Talegaon Dabhade Maharashtra 410507 India Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamil Nadu Srivilliputhur626126 India Department of CSE Techno International New Town West Bengal Kolkata700156 India Department of Architecture PTU Punjab Mohali140307 India Department of Electronics and Communication Engineering E.G.S. Pillay Engineering College Tamil Nadu Nagapattinam611002 India

In the aftermath of natural disasters, timely and accurate building damage assessment is crucial for effective disaster response. This research introduces an innovative integrated ResNet-U-Net ensemble model that significantly enhances the accuracy and efficiency of damage detection from satellite imagery. The model combines the deep feature extraction capabilities of ResNet with the precise localization advantages of U-Net, supplemented by attention mechanisms to focus on critical damage indicators. Methodologically, the research employs a dataset of high-resolution satellite images from post-Hurricane Iota, processed through normalization and augmentation techniques. The model demonstrates exceptional accuracy, achieving 96.91% on an unbalanced dataset representative of real-world conditions, and 89.35% on a balanced dataset. This performance indicates a substantial improvement over existing approaches, offering a rapid and reliable tool for aiding disaster relief efforts. The proposed model's computational efficiency and generalizability underscore its potential to transform disaster management practices. Future work will explore the model's application to various disaster types and integration with real-time data processing systems. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Satellite imagery

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A Nonlinear Convolution Network for Image Enhancement and Translation Tasks

SSRN

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SSRN 2024年

作者： Bhattacharya, Jhilik Carini, Alberto Marsi, Stefano Ramponi, Giovanni Department of Computer Science and Engineering Thapar Institute of Engineering and Technology Patiala India Department of Architecture and Engineering University of Trieste Italy

In this paper we introduce a special nonlinear convolution block with sine and cosine transformations, channel gating and local linear filter operations, which allows improved nonlinear CNN-based modeling with small network sizes. We motivate and demonstrate significant improvement in the task performances with a major reduction in the network size, thanks to the use of such a nonlinear convolution block. We perform extensive experiments to verify the performance of the network for different image transformation tasks such as deraining, dehazing, deblurring, low to bright light and night to day transformation. For all instances the network either shows acceptable or better performances when compared to State-of-Art (SoA) techniques for each task using benchmark datasets. © 2024, The Authors. All rights reserved.

关键词： Image enhancement

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