Article
Computer Science, Interdisciplinary Applications
Ali Calhan, Murtaza Cicioglu, Arif Ceylan
Summary: The study aims to construct a more realistic testbed platform in EHealth monitoring system by calculating the Early Warning Score using fuzzy logic and real-time data tracking of human health data.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Article
Geosciences, Multidisciplinary
Teboho E. Masupha, Mokhele E. Moeletsi, Mitsuru Tsubo
Summary: This review examines the status quo of agricultural drought early warning systems in South Africa and explores the potential of applying key lessons from established systems worldwide. Various characteristics of these systems were identified, with the most common being the ability to forecast impending drought, processing functionalities, and impact assessments. The study recommends the use of innovative technologies to translate hazards into impacts, provide value-added contingency plans, and enhance stakeholder communication for further advancements.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Chemistry, Analytical
Jiarong Wang, Junyi Liu, Tian Yan, Mingshan Xia, Jianshu Hong, Caiqiu Zhou
Summary: This paper discusses how to detect abnormal users in enterprise networks using individual user behavior models and peer-group behavior models, and proposes a fusion model to simultaneously consider individual behavioral dynamic changes and behavioral inconsistency among peers. Experimental results show that this method can accurately detect insider threats.
Article
Computer Science, Information Systems
Bo-Xiang Wang, Jiann-Liang Chen, Chiao-Lin Yu
Summary: The study introduces a network threat detection system, AI@NTDS, utilizing behavioral features of attackers and intelligent techniques. By combining data analysis, feature extraction, and evaluation, a detection model is constructed to aid in defending against network attacks using a more straightforward strategy.
Article
Computer Science, Information Systems
Haythem Ahmad Bany Salameh, Mohammad Fozi Dhainat, Elhadj Benkhelifa
Summary: This article introduces an integrated end-to-end wireless sensor network system for LPG detection and monitoring, which can operate flexibly in different environments. Through an efficient communication protocol, data exchange is organized, and experimental test data are used to demonstrate the reliability and accuracy of the system.
IEEE SYSTEMS JOURNAL
(2021)
Article
Computer Science, Information Systems
Li-Jie Peng, Xi-Gao Shao, Wan-Ming Huang
Summary: The rapid development of the Internet has led to the proliferation of social media networks, which has caused misleading information in network public opinion. In order to address this issue, a study has developed an early warning index system and model for internet public opinion, which showed higher accuracy compared to traditional methods when applied to a case study on the COVID-19 pandemic.
Article
Computer Science, Information Systems
Mohamed S. Abdalzaher, M. Sami Soliman, Sherif M. El-Hady, Abderrahim Benslimane, Mohamed Elwekeil
Summary: An earthquake early-warning system is crucial for saving lives. This study proposes a deep learning model that integrates autoencoder and convolutional neural network for swift and accurate determination of earthquake magnitude and location. The model utilizes the Internet of Things to transmit earthquake parameters to a centralized system, which then directs appropriate actions. The results demonstrate enhanced performance of the model in earthquake early-warning systems.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Multidisciplinary
Sutono, Selvia Lorena Br Ginting, Senny Luckyardi
Summary: The mosque implemented a Covid-19 early warning system using sensors to limit the number of worshipers and reduce the confirmed cases of Covid-19, showing positive impact on the worshipers. The data can be accessed through an application called PeduliL Protects.
JOURNAL OF ENGINEERING RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Zukang Hu, Wenlong Chen, Helong Wang, Pei Tian, Dingtao Shen
Summary: Data-driven anomaly detection and early warning are crucial in water distribution systems to identify abnormal events such as pipe bursts and sensor failures. This study proposes a framework comprising four modules to accurately detect anomalies and provide early warnings.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Computer Science, Software Engineering
Yutian Sha, Mohan Li, Huikun Xu, Shaohan Zhang, Tianxin Feng
Summary: This study conducts in-depth research and analysis on the intelligent monitoring and early warning of public safety machines in the construction of smart cities, taking risk management theory as the theoretical basis and combining it with the actual situation. It proposes a method suitable for the analysis of this study and provides detailed information on the overall design and robot application module design. The study also explores how communities carry out public safety risk prevention and control through research and interviews. It further provides insights on the development and implementation of the system and suggests directions for optimization based on test results.
SCIENTIFIC PROGRAMMING
(2022)
Article
Computer Science, Information Systems
Zhihua Chen, Gautam Srivastava
Summary: A security threat early warning technology based on blockchain is proposed for distance education systems to ensure their safe and stable operation. The experimental results demonstrate that this technology performs well in terms of transcoding rate for network behavior data and early warning accuracy, thus enabling effective security threat early warning in distance education systems.
JOURNAL OF INTERNET TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Saeed Ahmed, Noor Gul, Jahangir Khan, Junsu Kim, Su Min Kim
Summary: This article introduces a monitoring and early warning system based on cognitive Internet of things technology, aiming to extend the system's lifetime by conserving energy, and proposes two energy-efficient scheduling algorithms. Simulation results show that the proposed scheme can improve energy efficiency without sacrificing performance.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Engineering, Civil
Daniel Cusson, Cristian Rossi, Istemi F. Ozkan
Summary: This paper discusses the use of satellite data for monitoring bridge movement and early warning, with a focus on utilizing InSAR technology for data analysis and processing, monitoring bridge behavior through thermal sensitivity, and proposing specific calculation methods to determine the extent of thermal movement for bridges.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
(2021)
Article
Automation & Control Systems
Bardia Esmaeili, Amin Azmoodeh, Ali Dehghantanha, Hadis Karimipour, Behrouz Zolfaghari, Mohammad Hammoudeh
Summary: This article introduces a method called stateful query analysis (SQA) for detecting black-box adversarial attacks in industrial Internet of Things (IIoT). The method analyzes sequences of queries received by a malware classifier to detect attacks and abort them before completion. Experimental results demonstrate a detection rate of 93.1% across various adversarial examples.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Public, Environmental & Occupational Health
Siddhanth Sharma, Jaspreet Pannu, Sam Chorlton, Jacob L. Swett, David J. Ecker
Summary: Early detection of novel pathogens through metagenomic next-generation sequencing (mNGS) can effectively prevent or reduce the impact of biological incidents, such as pandemics. This article proposes a clinical mNGS architecture called Threat Net, which specifically focuses on using hospital emergency departments for surveillance. The study uses a simulation model to estimate the effectiveness of Threat Net in detecting and responding to respiratory pathogen outbreaks, providing insights on the cost and epidemiological impact of implementing routine clinical mNGS in the United States.
Article
Medicine, Legal
Ana Popovic, Marie Morelato, Claude Roux, Alison Beavis
Summary: Illicit drug trafficking, especially amphetamine-type stimulants, remains a major issue in Australia. Research shows that utilizing a dual approach can more effectively evaluate the linkage between illicit drugs compared to using a single approach.
FORENSIC SCIENCE INTERNATIONAL
(2021)
Article
Substance Abuse
Tina Lam, Monica J. Barratt, Mark Bartlett, Julie Latimer, Marianne Jauncey, Sarah Hiley, Nico Clark, Dimitri Gerostamoulos, Linda Glowacki, Claude Roux, Marie Morelato, Suzanne Nielsen
Summary: This study found limited evidence of unintentional fentanyl use among people who regularly inject heroin in Sydney and Melbourne, Australia, suggesting very little illicit fentanyl in Australian drug markets accessed by supervised injecting facilities attendees. The study demonstrates the feasibility of quick onsite testing to cost-effectively screen large samples for fentanyl; however, the high false positive rate emphasizes the need for confirmation of positive tests through advanced analytical techniques.
Article
Biochemical Research Methods
Ana Popovic, Marie Morelato, Simon Baechler, Adrian De Grazia, Mark Tahtouh, Claude Roux, Alison Beavis
Summary: The study utilized mathematical and statistical techniques to analyze chemical profiles of illicit drug seizures, revealing connections and insights into illegal drug markets to provide strategic intelligence support in combating drug trafficking.
DRUG TESTING AND ANALYSIS
(2022)
Article
Medicine, Legal
Theo Trincat, Michel Saner, Stefan Schaufelbuhl, Marie Gorka, Damien Rhumorbarbe, Alain Gallusser, Olivier Delemont, Denis Werner
Summary: This study aims to analyze the elements and traces related to 3D-printed firearms and study their exploitability. Testing with various Liberators, it was found that firearms printed via ME and PBF were able to fire, while those printed via VP were not.
FORENSIC SCIENCE INTERNATIONAL
(2021)
Article
Medicine, Legal
Ciara Devlin, Scott Chadwick, Sebastien Moret, Simon Baechler, Jennifer Raymond, Marie Morelato
Summary: The manufacture and distribution of fraudulent identity documents is a widespread and serious crime problem. There is a successful method in Europe to combat this crime, but it has not been widely implemented worldwide and there is limited knowledge about the Australian fraudulent document market. This pilot study suggests that the Australian document market may have organized criminal activities.
AUSTRALIAN JOURNAL OF FORENSIC SCIENCES
(2023)
Article
Criminology & Penology
Fiona Langlois, Damien Rhumorbarbe, Denis Werner, Nicolas Florquin, Stefano Caneppele, Quentin Rossy
Summary: Through analyzing 66 cases, this study examines how smugglers traffic arms from the US to foreign countries. It finds that most criminals prefer to operate according to established modus operandi, indicating the potential for professionalization.
Article
Biochemical Research Methods
Gregory Hayward, Lorenzo Gaborini, David Sims, Yorck Olaf Schumacher, Gregoire P. Millet, Damien Rhumorbarbe, Ronan Coquet, Neil Robinson
Summary: This study conducted a comprehensive assessment of the athletic demands in Olympic Games sports events and provides guidance for anti-doping organizations in developing risk assessments. By analyzing sport characteristics, it reveals how athletes may gain a competitive advantage through doping strategies and informs the allocation of testing resources.
DRUG TESTING AND ANALYSIS
(2022)
Article
Medicine, Legal
Marie Morelato, Liv Cadola, Maxime Berube, Olivier Ribaux, Simon Baechler
Summary: This article discusses the teaching and learning strategies in forensic intelligence, emphasizing on practical learning through real case scenarios to develop critical thinking and practical skills. The strategy breaks the current silos in forensic science discipline and offers students new job opportunities.
FORENSIC SCIENCE INTERNATIONAL
(2023)
Article
Substance Abuse
Suzanne Nielsen, Monica Barratt, Sarah Hiley, Mark Bartlett, Julie Latimer, Marianne Jauncey, Claude Roux, Marie Morelato, Nico Clark, Michala Kowalski, Michael Gilbert, Leanne Francia, Alexandra Shipton, Dimitri Gerostamoulos, Linda Glowacki, Tina Lam
Summary: Australia has not yet experienced widespread fentanyl-contaminated heroin, but there is interest in developing methods to monitor for fentanyl and other potentially harmful novel psychoactive substances (NPS) in the country. Testing was conducted using urine screens, drug checking strips, and laboratory analysis of injecting equipment associated with opioid overdoses. The results showed a low number of positive fentanyl cases and highlighted the need for confirmatory testing.
INTERNATIONAL JOURNAL OF DRUG POLICY
(2023)
Meeting Abstract
Substance Abuse
Tina Lam, Monica J. Barratt, Mark Bartlett, Julie Latimer, Marianne Jauncey, Sarah Hiley, Nico Clarke, Dimitri Gerostamoulos, Linda Glowacki, Claude Roux, Marie Morelato, Suzanne Nielsen
DRUG AND ALCOHOL REVIEW
(2021)
Article
Computer Science, Information Systems
Joshua Abraham, Ronnie Ng, Marie Morelato, Mark Tahtouh, Claude Roux
Summary: Forensic science has undergone a digital transformation, leading to heavy reliance on information technology in laboratories. This study investigates the application of machine learning classifier models for automatic classification of crime scene images, with the Tree-CNN model showing the greatest potential for further development and real-world use.
FORENSIC SCIENCE INTERNATIONAL-DIGITAL INVESTIGATION
(2021)
Review
Criminology & Penology
Denis Werner, Romain Berthod, Damien Rhumorbarbe, Alain Gallusser
Summary: In forensic cases involving firearms, identifying the firearm used to discharge questioned elements of ammunition found at the scene is a major issue. Analyzing the marks left on both questioned and reference ammunition elements before comparison is crucial, as manufacturing processes influence these marks. Accessing information on how the questioned firearm was produced can be challenging, but it is essential for identifying relevant marks for comparison purposes.
WILEY INTERDISCIPLINARY REVIEWS: FORENSIC SCIENCE
(2021)
Article
Medicine, Legal
Heitor S. D. Correa, Ivano Alessandri, Andrea Verzeletti
Summary: This research assessed the usefulness of Raman spectroscopy and gas chromatography-mass spectrometry in analyzing bones. The techniques were found to be useful in molecular taphonomy studies and forensic genetics.
FORENSIC SCIENCE INTERNATIONAL
(2024)
