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Identifying and Anticipating Cyberattacks That Could Cause Physical Damage to Industrial Control systems

IEEE Power and Energy Technology systems Journal 2019年第4期6卷 172-182页

作者： Angle, Matthew G. Madnick, Stuart Kirtley, James L. Khan, Shaharyar Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Sloan School of Management School of Engineering Massachusetts Institute of Technology CambridgeMA02139 United States System Design and Management Program Massachusetts Institute of Technology CambridgeMA02139 United States

Physical control systems are increasingly controlled by reconfigurable, network-enabled devices to increase flexibility and ease commissioning and maintenance. Such capability creates vulnerabilities. Devices may be remotely reprogrammed by a malicious actor to act in unintended ways, causing physical damage to mechanical equipment, infrastructure, and life and limb. In this paper, past examples of actual damage to cyber-physical systems are shown, threats posed by software-controlled variable frequency drives (VFDs) are analyzed, and a small-scale version of an attack on ubiquitous VFD equipment is demonstrated. © 2014 IEEE.

关键词： Embedded systems

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Mercury transformation processes in nature: Critical knowledge gaps and perspectives for moving forward

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Journal of Environmental Sciences 2022年第9期34卷 152-165页

作者： Zhiyuan Gao Wang Zheng Yanbin Li Yurong Liu Mengjie Wu Shouying Li Ping Li Guangliang Liu Xuewu Fu Shuxiao Wang Feiyue Wang Yong Cai Xinbin Feng Baohua Gu Huan Zhong Yongguang Yin Centre for Earth Observation Science and Department of Environment and GeographyUniversity of ManitobaWinnipegMB R3T 2N2Canada Institute of Surface-Earth System Science Tianjin UniversityTianjin 300192China Key Laboratory of Marine Chemistry Theory and Technology Ministry of Education and College of Chemistry and Chemical EngineeringOcean University of ChinaQingdao 266100China State Key Laboratory of Agricultural Microbiology Huazhong Agricultural UniversityWuhan 430070China School of the Environment Nanjing UniversityState Key Laboratory of Pollution Control and Resource ReuseNanjing 210023China State Key Laboratory of Environmental Geochemistry Institute of GeochemistryChinese Academy of SciencesGuiyang 550081China Department of Chemistry and Biochemistry Florida International UniversityMiamiFL 33199USA School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua UniversityBeijing 100084China Environmental Sciences Division Oak Ridge National LaboratoryOak RidgeTennessee 37831USA Environmental and Life Sciences Program(EnLS) Trent UniversityPeterboroughOntario K9L 0G2Canada Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China

The transformation of mercury(Hg) in the environment plays a vital role in the cycling of Hg and its risk to the ecosystem and human health. Of particular importance are Hg oxidation/reduction and methylation/demethylation processes driven or mediated by the dynamics of light, microorganisms, and organic carbon, among others. Advances in understanding those Hg transformation processes determine our capacity of projecting and mitigating Hg risk. Here, we provide a critical analysis of major knowledge gaps in our understanding of Hg transformation in nature, with perspectives on approaches moving forward. Our analysis focuses on Hg transformation processes in the environment, as well as emerging methodology in exploring these processes. Future avenues for improving the understanding of Hg transformation processes to protect ecosystem and human health are also explored.

关键词： Mercury oxidation reduction methylation demethylation isotope fractionation

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3D co-cultured multicellular spheroids on microfluidic chip for studying ecm-mediated drug resistance 24

3D co-cultured multicellular spheroids on microfluidic chip ...

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24th International Conference on Miniaturized systems for Chemistry and Life Sciences, MicroTAS 2020

作者： Goudar, Venkanagouda S. Lu, Long-Sheng Koduri, Manohar Prasad Tseng, Fan-Gang Engineering and System Science National Tsing Hua University Hsinchu Taiwan Department of Radiation Oncology Taipei Medical University Hospital Taipei Taiwan International Intercollegiate Ph.D. Program NTHU Hsinchu Taiwan Research Center for Applied Sciences Academia Sinica Taipei Taiwan Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Taiwan

ISBN: (纸本)9781733419017

Among various ECM proteins, collagen type-I is a widely distributed extracellular matrix (ECM) protein expressed in different types of cancers and induces tumor growth and drug resistance. To prove this, in the present work we co-cultured colon cancer cells (HCT-8) and fibroblast cells (NIH3T3) in a PDMS based open welled micro 3D (μ-3D) cell culture chip. This co-culture model was employed to study the interaction of cancer cells and stromal cells and revealed that collagen treatment before chemotherapy can be a game-changer in a colon cancer treatment. © 2020 CBMS-0001

关键词： Microfluidic chips

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Electrical Grid-Independent Machine Learning-Assisted Wearable Gait Analysis Device with Triboelectric-Electromagnetic Hybrid Energy Harvester

SSRN

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SSRN 2025年

作者： Ra, Yoonsang Kim, Dongjun Nam, Mi Song Cho, Sumin Kim, Yu-Seop Cho, Seongwoo Um, Jumyung Heo, Yun Jung Choi, Dongwhi Department of Mechanical Engineering Integrated Engineering Program Kyung Hee University 1732 Deogyeong-daero Gyeonggi Yongin17104 Korea Republic of Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore117576 Singapore National University of Singapore E6 L5 5 Engineering Drive 1 Singapore117608 Singapore Department of Artificial Intelligence Kyung Hee University Yongin17104 Korea Republic of Department of Mechanical Engineering Kyung Hee University Yongin17104 Korea Republic of Kyung Hee University Yongin17104 Korea Republic of Department of Industrial and Management System Engineering Kyung Hee University Yongin17104 Korea Republic of

The application of Artificial Intelligence (AI) to body motion analysis has garnered increasing interest for advancing the related technologies including individually optimized healthcare. Accordingly, an energy-efficient AI capable of onsite operation is required to advance the related fields to the next-generation such as in-sensor computing, near-sensor computing, on-device AI, and embedded AI. In this study, an Electrical grid-independent Machine learning-assisted Wearable device for Gait analysis (EMWG) with a ground reaction force (GRF) sensor was developed. Various machine learning architectures, including multi-layer perceptron (MLP), long short-term memory units, and gated recurrent units, were evaluated. MLP was found to be the optimal model in terms of analysis performance (accuracy of 88% and model conversion rate of 84.22%) and power consumption (discharging time of 1 h 47 min when using a 10 min-charged 110 mAh battery). The machine learning model was fine-tuned and deployed on a microcontroller unit. A triboelectric-electromagnetic hybrid energy harvesting module was developed to supply power to the AI-embedded microcontroller by harvesting walking energy of users. The hybrid energy harvester generates up to 184 V and 4.72 μA of voltage and current from the triboelectric nanogenerator and 32 V and 49 mA from the electromagnetic generator when the user moves. As a proof-of-concept demonstration, drunken person determination was performed using EMWG-mounted smart shoes with an accuracy of 88%. The concept of wearable gait analysis device with electrical grid-independent machine learning proposed in this work is expected to provide a technical guideline for developing next-generation motion data analysis systems. © 2025, The Authors. All rights reserved.

关键词： Microcontrollers

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Evaluation of GOFP over four forest plots using RAMI and UAV measurements

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International Journal of Digital Earth 2021年第10期14卷 1433-1451页

作者： Jun Geng Qian Zhang Feng Qiu J.M.Chen Yongguang Zhang Weiliang Fan Lili Tu Jianwei Huang Shaoteng Wang Lichen Xu Jinchao Li School of Civil Engineering Hefei University of TechnologyHefeiPeople’s Republic of China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of TechnologyHefeiPeople’s Republic of China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System ScienceNanjing UniversityNanjingPeople’s Republic of China Max Planck Institute for Biogeochemistry JenaGermany Key Laboratory of Information Perception and Systems for Public Security of MIIT Nanjing University of Science and TechnologyNanjingChina Department of Geography and Program in Planning University of TorontoTorontoCanada School of Geographical Science Fujian Normal UniversityFuzhouPeople’s Republic of China College of Environmental and Resource Science Zhejiang A&F UniversityLinanPeople’s Republic of China School of Resources and Environment Anhui Agricultural UniversityHefeiPeople’s Republic of China

Comparison and validation of canopy reflectance(CR)models are two important steps to ensure their *** forest plantations are an ideal type of forest for validating CR models because of their simple background and the low variance in the crown structures which are usually assumed to be identical in most CR models.A Geometric Optical Model for Forest Plantations(GOFP)was compared using dataset in two radiation transfer model intercomparison exercise(RAMI)stands and validated using in situ dataset of detailed optical and structural data of two forest plantations in the Saihanba Forestry Center,*** results show that(1)the tree distributions in stands described by the hypergeometric model in GOFP show good consistencies with the dataset in the two RAMI stands and measurements from the two Saihanba forest stands;and(2)the CRs simulated with GOFP are also compared well in the two RAMI stands and validated with measurements collected with unmanned aerial vehicles in the two Saihanba *** shows a better consistency with the CR measurements than those from CR models for natual forestsbecause the tree distribution in forest plantations is described more reasonably in GOFP.

关键词： Validation forest plantation GOFP tree distribution BRF hypergeometric model

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Handwriting prediction using the support vector machine method in web-based applications

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AIP Conference Proceedings 2022年第1期2659卷

作者： Syaifudin Dian Pratiwi Trubus Rahardiansyah Anasthesia Karunia Charles Hafiz Wijaya Khoirun Nisa 1Information System Study Program Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia 2Informatic Engineering Study Program Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia 3Department of Law Universitas Trisakti Jakarta Indonesia

Current technological advances have progressively encouraged individuals to use web-based applications. To determine the owner of a handwriting, one of the manual methods is generally done by people. And it can be done by a web application to find out the person’s handwriting. The Support Vector Machine (SVM) Method is a strategy of artificial intelligence used to recognize handwriting. This study intends to create a handwriting recognition framework using the Support Vector Machine (SVM) Method on a web-based application, with extraction features that are important as the basis for describing and characterizing handwritten images. The results obtained from predictions using the Support Vector Machine are by using 16 data and there are 80 tests carried out in total. The results obtained indicate that there are 25 incorrect prediction tests and 55 correct prediction tests so that the level of accuracy obtained is 68.75%.

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Effective approaches to disaster evacuation during a COVID-like pandemic

arXiv

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arXiv 2022年

作者： Tsai, Yi-Lin Sitepu, Dymasius Y. Chappell, Karyn E. Mediratta, Rishi P. Wang, C. Jason Kitanidis, Peter K. Field, Christopher B. Department of Civil and Environmental Engineering Stanford University StanfordCA United States Department of Engineering Science National University of Singapore Singapore Department of Engineering Imperial College London London United Kingdom Department of Pediatrics Stanford University School of Medicine StanfordCA United States Department of Health Policy Stanford University School of Medicine StanfordCA United States Woods Institute for the Environment Stanford University StanfordCA United States Bio-X Stanford University StanfordCA United States Institute for Computational and Mathematical Engineering Stanford University StanfordCA United States Department of Biology Stanford University StanfordCA United States Department of Earth System Science Stanford University StanfordCA United States Interdisciplinary Environmental Studies Program Stanford University StanfordCA United States

Since COVID-19 vaccines became available, no studies have quantified how different disaster evacuation strategies can mitigate pandemic risks in shelters. Therefore, we applied an age-structured epidemiological model, known as the Susceptible-Exposed-Infectious-Recovered (SEIR) model, to investigate to what extent different vaccine uptake levels and the Diversion protocol implemented in Taiwan decrease infections and delay pandemic peak occurrences. Taiwan’s Diversion protocol involves diverting those in self-quarantine due to exposure, thus preventing them from mingling with the general public at a congregate shelter. The Diversion protocol, combined with sufficient vaccine uptake, can decrease the maximum number of infections and delay outbreaks relative to scenarios without such strategies. When the diversion of all exposed people is not possible, or vaccine uptake is insufficient, the Diversion protocol is still valuable. Furthermore, a group of evacuees that consists primarily of a young adult population tends to experience pandemic peak occurrences sooner and have up to 180% more infections than does a majority elderly group when the Diversion protocol is implemented. However, when the Diversion protocol is not enforced, the majority elderly group suffers from up to 20% more severe cases than the majority young adult group. Copyright © 2022, The Authors. All rights reserved.

关键词： COVID-19

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Comparison of random forest algorithm, support vector machine and neural network for classification of student satisfaction towards higher education services

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AIP Conference Proceedings 2022年第1期2578卷 060003页

作者： Didi Supriyadi Purwanto Purwanto Budi Warsito Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang 50275 Indonesia Department of Information System Faculty of Informatics Institut Teknologi Telkom Purwokerto Banyumas 53147 Indonesia Department of Chemical Engineering Faculty of Engineering Diponegoro University Semarang 50275 Indonesia Department of Statistics Faculty of Sciences and Mathematics Diponegoro University Semarang 50275 Indonesia

Students are customers of a higher education institution. Various types of services and facilities are provided by universities for students, such as academic services, student services, and infrastructure including information technology services. Student satisfaction with the quality of the university services is one of the factors that affect the academic performance of the university. This study aims to compare the level of accuracy between the Random Forest method, Support Vector Machine and Neural Network for the classification of student satisfaction with the services provided by Higher Education. The dataset consisted of 430 respondents from private universities in Vietnam taken and adapted from previous research. The training and testing dataset uses a split proportion of 80:20 of the total available datasets. Model performance measurements using matrix confusion include accuracy, sensitivity (recall), and precision. The results showed that the Random Forest method can produce the best accuracy rate of 76.47%, followed by Neural Network and Support Vector Machine algorithms with an accuracy rate of 74.12% on each.

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Saturable intercalation doping enables scalable and selective graphene gas sensors on plastic

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Chemical engineering Journal 2025年 515卷

作者： Kwon, Bitnuri Lee, Jung Hun Jo, Sae Byeok Hwang, Jinhyun Lee, Donggeun Cha, Jonghyun Lim, Soomook Suk, Ji Won Lee, Wi Hyoung Department of Organic and Nano System Engineering Konkuk University Seoul05029 Cuba Department of Materials Science and Engineering and the Materials Research Center Northwestern University 2220 Campus Drive EvanstonIL60208-3108 United States School of Chemical Engineering Sungkyunkwan University Suwon16419 Cuba Sungkyunkwan University Suwon16419 Cuba Advanced Materials Program Department of Materials Science and Engineering Konkuk University Seoul05029 Cuba School of Mechanical Engineering Sungkyunkwan University Suwon16419 Cuba Department of Smart-Fab. Technology Sungkyunkwan University Suwon16419 Cuba Department of Materials Science and Engineering Konkuk University Seoul05029 Cuba

Developing highly sensitive and selective gas sensors for nitrogen dioxide (NO2) detection remains crucial for environmental monitoring and public health protection. Graphene-based chemiresistive sensors show promise due to their exceptional electronic properties and high surface area, which enhance gas adsorption. However, they face persistent challenges in selectivity, stability, and sensitivity characteristics. This study presents a facile one-step molecular intercalation doping approach that can effectively overcome these limitations. By intercalating carefully selected dopant molecules between graphene and flexible substrates during the wet-transfer process, we achieve uniform doping distribution while maintaining intrinsic carrier mobility. The resulting sensors demonstrate remarkable NO2 detection capabilities with a limit of detection of 1 ppb at room temperature. Importantly, the intercalated devices exhibit exceptional stability over extended periods of time and show minimal cross-sensitivity to common interfering gases. Moreover, the sensors retain their sensing characteristics under mechanical deformation, including fully transparent gas sensors with a dogbone structure, thereby enabling seamless integration into wearable monitoring systems. Our scalable fabrication process and comprehensive understanding of the intercalation doping mechanism provide a practical pathway for the development of reliable, flexible gas sensors capable of addressing real-world environmental and healthcare challenges. © 2025 Elsevier B.V.

关键词： pH sensors

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Enhancing the Effectiveness of Heat Adaptation Strategies Through Citizen Science-Based Outdoor Thermal Comfort

SSRN

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SSRN 2024年

作者： Kim, Eun Sub Lee, Dong Kun Bae, Chae Young Ko, Se Yean Won, Ji Eun Lee, Jae Hong Interdisciplinary Program in Landscape Architecture Seoul National University Seoul08826 Korea Republic of Seongnam Research Institute 46 Dallaenae-ro Sujeong-gu Gyeonggi-do Seongnam-si Korea Republic of Carbon-Neutral Strategy Institute Inc 103 Hyundai ESA2 122 Banpo-daero Seocho-gu Seoul06647 Korea Republic of Suwon Climate Change Education Center 46-38 Homaesil-ro Gwonseon-gu Gyeonggi-do Suwon-si Korea Republic of Specialized Graduate School of Intelligent Eco-Science 4 Dept. of Landscape Architecture Seoul National University Seoul08826 Korea Republic of Department of Landscape Architecture and Rural System Engineering Seoul National University Seoul08826 Korea Republic of

Urbanization and climate change increase heat stress and health risks in cities, necessitating effective response strategies. Traditional research has focused on thermal sensation in specific locales, overlooking the broad impacts of urban environments and the importance of regional and citizen input in crafting mitigation approaches. This study examines the effects of heat waves in Suwon City, analyzing thermal perception among residents across different urban spaces using citizen science. Data on temperature and subjective heat sensations were collected through homemade sensors over three years. The analysis investigated thermal sensation differences across spatial types— open high rise, open low rise, compact mid-rise, urban park, and lake park—utilizing boxplots, and examined thermal perception variations by age using the R program localized smoothing methodology. The results revealed significant differences in thermal sensation, especially above 32°C, with the highest discomfort reported in lake park areas and the lowest in open high-rise and low-rise zones. An age-related trend showed increased heat sensitivity among the 19–30 age group, decreasing in older participants. These findings underscore the limitations of one-size-fits-all heatwave responses and advocate for customized strategies informed by local conditions and resident experiences, highlighting the value of a bottom-up approach through citizen science. © 2024, The Authors. All rights reserved.

关键词： Climate change

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