Article
Engineering, Marine
Philip Jonathan, David Randell, Jenny Wadsworth, Jonathan Tawn
Summary: In this study, the estimation of return values in the presence of uncertain extreme value model parameters is investigated using maximum likelihood and other estimation schemes. Four sample estimators for the N-year return value are considered, with the mean quantile q(2) showing the best overall performance. The study also found that judgements on the relative performance of estimators depend on the choice of utility function adopted.
Article
Engineering, Geological
Jung-Hyun Lee, Hanbeen Kim, Hyuck-Jin Park, Jun-Haeng Heo
Summary: This study examines the increasing frequency of extreme rainfall-induced landslides with the increase in frequency and intensity of heavy rainfall. By developing a new approach, it successfully evaluates the hazard of extreme rainfall-induced landslides in areas with incomplete data, estimating landslide hazards for different future time periods (1 to 200 years).
Article
Engineering, Mechanical
Ye-Yao Weng, Zhao-Hui Lu, Pei-Pei Li, Yan-Gang Zhao
Summary: In this study, a novel extreme value distribution (EVD) model is proposed to describe the probability distribution of extreme response in structural systems under nonstationary stochastic excitations. The EVD model consists of a truncated-shifted generalized lognormal distribution for the main body and a monotonic exponential model for the tail region. A criterion for determining the breakpoint between the main body and tail region is also proposed to ensure the accuracy and efficiency of the EVD model, particularly in its tail region. The proposed model is validated through numerical examples and shows excellent agreement with Monte Carlo simulation results.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Environmental Sciences
Anurag Barthwal
Summary: This study develops a Markov chain-based IoT system to monitor, analyze, and predict urban air quality. The proposed sensing setup is integrated with an automobile and used for collecting air quality information. An Android application transfers and stores the sensed data in the data cloud. The forecast error of the model was found to be 3.38% and 4.06% at the selected locations in Delhi-NCR.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2023)
Article
Chemistry, Analytical
Karoline K. Barkjohn, Amara L. Holder, Samuel G. Frederick, Andrea L. Clements
Summary: PurpleAir particulate matter sensors are used for real-time air quality information, but they may exhibit bias and nonlinearity. This study evaluated and corrected the sensors to ensure accurate and comparable data.
Article
Environmental Sciences
Abbas Miri, Ebrhaim Shirmohammadi, Armin Sorooshian
Summary: This study examines the relationship between meteorological factors, air pollutants, and ambient bacterial concentration. The results show that air quality indices (PM10, PM2.5, and AQI) have a significant impact on bacterial concentrations.
Article
Engineering, Marine
Ross Towe, David Randell, Jennifer Kensler, Graham Feld, Philip Jonathan
Summary: The design and reanalysis of offshore and coastal structures often involves estimating return values and associated values for metocean variables using extreme value analysis. This study examines different estimation methods for these values, taking into account sampling uncertainty. The results of a simulation experiment show that certain estimators perform better than others, and that models incorporating appropriate descriptions of marginal and dependence provide more accurate estimates. The study also suggests that probabilistic risk analysis incorporating full uncertainty propagation is preferable to summarising joint tail characteristics of metocean variables.
Article
Engineering, Marine
Ali Tian, Xufeng Shu, Jiaming Guo, Haoyun Li, Renchuan Ye, Peng Ren
Summary: This paper presents a statistical modeling approach to explore the dependence of extreme values in multi-site tidal water levels using hourly data from six tidal stations in the Kansai region, Japan. The proposed method utilizes a multi-site conditional extreme value model and a peak over threshold model with yearly order grouping to handle extreme value dependence and marginal modeling of tidal CEVM, respectively. The results demonstrate the effectiveness of the proposed approach in analyzing extreme value dependence among multiple sites and provide a more accurate basis for engineering construction and disaster prevention.
Article
Chemistry, Analytical
Ning Ma, Yanbing Bai, Shengwang Meng
Summary: The study utilized clustering to analyze seismic characteristics in different regions of Mainland China, using statistical models combined with geographic information for quantitatively analyzing future earthquake risks and accurately locating earthquake risks.
Article
Engineering, Civil
Jinping Zhang, Hang Zhang, Hongyuan Fang
Summary: This study established joint distribution models of rainstorm elements based on copula theory, derived design values using maximum probability and same frequency methods, and found that using SRP to calculate rainstorm return period is more reasonable than PRP.
WATER RESOURCES MANAGEMENT
(2022)
Article
Engineering, Environmental
Carlos Jose dos Reis, Amaury Souza, Renata Graf, Tomasz M. Kossowski, Marcel Carvalho Abreu, Jose Francisco de Oliveira-Junior, Widinei Alves Fernandes
Summary: This study aims to find the probabilities of extreme air temperatures in Cerrado, Pantanal, and Atlantic Forest biomes in Mato Grosso do Sul, Brazil. Using the Extreme Value Theory, the study estimates three probability distributions and recommends the most suitable distribution for different months. It also highlights the impact of deforestation, combustion, and extensive fires on extreme air temperatures, in addition to climate change.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2022)
Article
Construction & Building Technology
Hang Zhang, Jinping Zhang, Hongyuan Fang, Feng Yang
Summary: Research on urban flooding is crucial due to its impact on environment, economy, and society. This paper presents a new method for rainstorm pattern design using Copula theory, Most-Likely design realization method, and Monte Carlo simulation. The study also evaluates the urban flooding response to different rainstorm scenarios using a hydrodynamic model. The findings highlight the significance of short-duration rainstorms and the differences in rainfall volume and impact under different return periods.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Engineering, Civil
Songbai Song, Vijay P. Singh, Xiaoyan Song, Yan Kang
Summary: The probability distribution of drought duration is crucial for drought management. The new proposed geometric distribution II provides a more accurate description of drought duration, and its application was validated through examples from the Yellow River basin in China.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
S. Basso, G. Botter, R. Merz, A. Miniussi
Summary: The study highlights the physically-based alternative distribution PHEV for predicting flood magnitude and frequency, which has better predictive capabilities compared to statistical methods, especially for rare floods. The analysis results demonstrate the applicability of PHEV to long time series and observational datasets in various hydro-climatic regions, with reduced prediction uncertainty in estimating flood magnitudes.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Article
Geochemistry & Geophysics
Ziheng Xia, Penghui Wang, Ganggang Dong, Hongwei Liu
Summary: Radar automatic target recognition (RATR) using high-resolution range profiles (HRRP) has gained attention, but previous works primarily focus on closed set recognition and may lead to errors in open set environments. This article proposes open set recognition to address this issue by establishing a closed classification boundary. The proposed extreme value boundary theorem demonstrates that the maximum distance from known features to the cluster center follows a generalized extreme value distribution, enabling the determination of a closed classification boundary to distinguish between known and unknown classes. Extensive experiments on measured HRRP data validate the proposed theorem and method.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Telecommunications
Anurag Barthwal, Debopam Acharya
Summary: The deteriorating urban air quality is mainly caused by rapid urbanization, vehicular emissions, rise in industrial activities, burning of crop residues and garbage, thermal power plants, emissions from diesel generators, dust from construction sites, and household fuel use. An Internet of Things based system has been developed for monitoring, analyzing, and forecasting outdoor air quality to address this issue.
WIRELESS PERSONAL COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Nikhil Kumar, Debopam Acharya, Divya Lohani
Summary: Road accidents are a leading cause of death and disability among youth, and research is focused on reducing reporting time or improving accuracy of accident detection. IoT platforms are utilized to decrease rescue time. This work presents an IoT-based automotive accident detection and classification system that enhances rescue efficacy of emergency services.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Multidisciplinary
Anurag Barthwal, Kritika Sharma
Summary: The phenomenon of urban heat islands leads to high temperatures, increased energy demand and carbon emissions, and impacts community health. New technologies enable low-cost IoT systems to monitor, assess, and analyze urban temperatures and their effects.
INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT
(2022)
Article
Computer Science, Theory & Methods
Nikhil Kumar, Divya Lohani, Debopam Acharya
Summary: This paper presents an IoT system based on Android smartphones that can transmit accident information to emergency services and affected families. It develops a machine learning model to accurately detect and classify vehicle accidents, and proposes a multi-sensor fusion framework to enhance the classification efficacy of the system.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Environmental Studies
Shwetank Avikal, Rushali Pant, Anurag Barthwal, Mangey Ram, Rajesh Kumar Upadhyay
Summary: This study applies the DEMATEL-DANP approach to analyze the relationship among four factors and twelve sub factors and their contribution to the adoption of sustainable circular economy in the agro-produce supply chain. The integration of farmers and updated infrastructure and tools of the farm are identified as the primary drivers for implementing sustainable circular economy in the agro-produce supply chain.
MANAGEMENT OF ENVIRONMENTAL QUALITY
(2023)
Article
Environmental Sciences
Anurag Barthwal
Summary: This study develops a Markov chain-based IoT system to monitor, analyze, and predict urban air quality. The proposed sensing setup is integrated with an automobile and used for collecting air quality information. An Android application transfers and stores the sensed data in the data cloud. The forecast error of the model was found to be 3.38% and 4.06% at the selected locations in Delhi-NCR.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2023)
Article
Engineering, Electrical & Electronic
Chandra Prakash, Anurag Barthwal, Debopam Acharya
Summary: In recent years, flooding has become a major problem worldwide, causing damage to property and human life. However, the use of emerging technologies, such as IoT, can help predict floods in advance and mitigate the damage. This study developed an IoT-based prototype to collect hydrological and meteorological data for flood prediction. The collected data were analyzed and classified using the LSTM model, and the system accurately predicted the flood event state with high F1-scores.
IEEE SENSORS JOURNAL
(2023)
Article
Computer Science, Information Systems
Chandra Prakash, Anurag Barthwal, Debopam Acharya
Summary: In the past few decades, floods have caused significant damage worldwide, including economic losses, property damage, and loss of lives. Although floods cannot be eliminated or avoided, the use of advanced technologies like Machine Learning (ML) and Internet of Things (IoT) can help reduce the disastrous effects of floods. This study developed a working prototype that utilizes ML and IoT to collect and analyze hydro-meteorological data for flood prediction. The prediction efficiency of the models was evaluated using various metrics, and a novel technique was proposed to estimate river discharge based on sectional area and flow of the river.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Anshula Gupta, Anurag Barthwal, Harsh Vardhan, Shivani Kakria, Sumit Kumar, Ashish Singh Parihar
Summary: An authentication protocol is essential for ensuring the integrity and trust level of nodes during communication in distributed systems. With the absence of a centralized authority, authenticating nodes becomes complex. In the context of unmanned aerial vehicle-based networks, which are a special form of distributed networks, there is limited research on node authentication during information exchange. Our study explores various distributed authentication protocols and their exposure in flying ad hoc networks, providing a foundation to develop secure data transfer protocols for flying networks.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Chandra Prakash, Anurag Barthwal, Shwetank Avikal, Gyanendra Kumar Singh
Summary: The Internet of Things enables remote connection and observation of things or objects over the Internet. In the context of agriculture, this concept has been applied to enhance agricultural tasks, making them smart, secure, and automated. This study introduces a remote security management framework called the Farm Security Alert System (FSAS), which specifically monitors storage houses in crop fields. FSAS utilizes an energy efficient and low-cost system, consisting of a microcontroller-based passive infrared (PIR) sensor and a global system for mobile communication (GSM) module, to generate alerts for farm owners in the event of an intrusion. The FSAS is capable of monitoring induction motors and transmitting sensor signals to the cloud. It employs a Naive Bayes' prediction model to identify the level of intrusion threat and sends alerts to farm owners via smartphone applications or short message/phone call, regardless of their internet connectivity.
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
(2023)
Article
Management
Shwetank Avikal, Rohit Singh, Anurag Barthwal, Mangey Ram
Summary: The purpose of this study is to develop a method for finding preventive measures for COVID-19 and their priorities. The Kano model and Fuzzy-AHP are used to classify and prioritize these preventive measures.
INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT
(2023)
Article
Geosciences, Multidisciplinary
Chandra Prakash, Anurag Barthwal, Debopam Acharya
Summary: Floods are the most frequent natural disasters in India, caused by monsoon variations and asymmetric geomorphic features. IoT systems can monitor flood destruction and forecast floods. Hydro-meteorological parameters can be obtained from sensing devices in real-time for early flood alert. A novel technique is proposed to estimate river discharge, and the challenges of quantifying rainfall have been addressed.
JOURNAL OF EARTH SYSTEM SCIENCE
(2023)
Proceedings Paper
Materials Science, Multidisciplinary
Shwetank Avikal, Kritika Sharma, Anuragh Barthwal, K. C. Nithin Kumar, Gaurav Kumar Badhotiya
Summary: The study classified speakers of different age groups based on speech features and collected a speech corpus of Hindi speakers. Text prompts were recorded using neutral Hindi vocabulary, and the experimental results showed that the average age performance of multispeakers is around 94%.
MATERIALS TODAY-PROCEEDINGS
(2021)
