Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10100028
Megan Watson, D. Al-Jumeily, J. Birkett, Iftikhar Khan, S. Assi
COVID-19 is a novel coronavirus first emerging in Wuhan, China in December 2019 and has since spread rapidly across the globe escalating into a worldwide pandemic causing millions of fatalities. Emergency response to the pandemic included social distancing and isolation measures as well as the escalation of vaccination programmes. The most popular COVID-19 vaccines are nucleic acid-based. The vast spread and struggles in containment of the virus has allowed a gap in the market to emerge for counterfeit vaccines. This study investigates the use of handheld Raman spectroscopy as a method for nucleic acid-based vaccine authentication and utilises machine learning analytics to assess the efficacy of the method. Conventional Raman spectroscopy requires a large workspace, is cumbersome and energy consuming, and handheld Raman systems show limitations with regards to sensitivity and sample detection. Surface Enhanced Raman spectroscopy (SERS) however, shows potential as an authentication technique for vaccines, allowing identification of characteristic nucleic acid bands in spectra. SERS showed strong identification potential through Correlation in Wavelength Space (CWS) with all vaccine samples obtaining an r value of approximately 1 when plotted against themselves. Variance was observed between some excipients and a selected number of DNA-based vaccines, possibly attributed to the stability of the SERS colloid where the colloid-vaccine complex had been measured over different time intervals. Further development of the technique would include optimisation of the SERS method, stability studies and more comprehensive analysis and interpretation of a greater sample size.
COVID-19是一种新型冠状病毒，于2019年12月首次在中国武汉出现，此后在全球迅速蔓延，升级为全球大流行，造成数百万人死亡。对大流行的紧急应对措施包括保持社会距离和隔离措施以及扩大疫苗接种规划。最流行的COVID-19疫苗是以核酸为基础的。病毒的广泛传播和控制工作的艰难使得假冒疫苗在市场上出现了空白。本研究调查了手持式拉曼光谱作为基于核酸的疫苗认证方法的使用，并利用机器学习分析来评估该方法的有效性。传统的拉曼光谱需要很大的工作空间，笨重且耗能，手持式拉曼系统在灵敏度和样品检测方面存在局限性。然而，表面增强拉曼光谱(SERS)显示出作为疫苗认证技术的潜力，允许在光谱中识别特征核酸带。SERS通过波长空间相关性(Correlation in Wavelength Space, CWS)显示出很强的识别潜力，所有疫苗样本与自身对比时的r值约为1。在一些赋形剂和一些选定的基于dna的疫苗之间观察到差异，这可能归因于在不同时间间隔测量胶体-疫苗复合物的SERS胶体的稳定性。该技术的进一步发展将包括SERS方法的优化、稳定性研究以及对更大样本量的更全面的分析和解释。
{"title":"Exploring the authentication of COVID-19 vaccines using Surface-enhanced handheld Raman spectroscopy (SERS) equipped with orbital Raster scattering and machine learning","authors":"Megan Watson, D. Al-Jumeily, J. Birkett, Iftikhar Khan, S. Assi","doi":"10.1109/DeSE58274.2023.10100028","DOIUrl":"https://doi.org/10.1109/DeSE58274.2023.10100028","url":null,"abstract":"COVID-19 is a novel coronavirus first emerging in Wuhan, China in December 2019 and has since spread rapidly across the globe escalating into a worldwide pandemic causing millions of fatalities. Emergency response to the pandemic included social distancing and isolation measures as well as the escalation of vaccination programmes. The most popular COVID-19 vaccines are nucleic acid-based. The vast spread and struggles in containment of the virus has allowed a gap in the market to emerge for counterfeit vaccines. This study investigates the use of handheld Raman spectroscopy as a method for nucleic acid-based vaccine authentication and utilises machine learning analytics to assess the efficacy of the method. Conventional Raman spectroscopy requires a large workspace, is cumbersome and energy consuming, and handheld Raman systems show limitations with regards to sensitivity and sample detection. Surface Enhanced Raman spectroscopy (SERS) however, shows potential as an authentication technique for vaccines, allowing identification of characteristic nucleic acid bands in spectra. SERS showed strong identification potential through Correlation in Wavelength Space (CWS) with all vaccine samples obtaining an r value of approximately 1 when plotted against themselves. Variance was observed between some excipients and a selected number of DNA-based vaccines, possibly attributed to the stability of the SERS colloid where the colloid-vaccine complex had been measured over different time intervals. Further development of the technique would include optimisation of the SERS method, stability studies and more comprehensive analysis and interpretation of a greater sample size.","PeriodicalId":346847,"journal":{"name":"2023 15th International Conference on Developments in eSystems Engineering (DeSE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115304587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10099492
Chow Man Pan, Kamalanathan Shanmugam, Muhammad Ehsan Rana, M. Jayabalan
The deadly virus COVID-19 has heavily impacted all countries and brought a dramatic loss of human life. It is an unprecedented scenario and poses an extreme challenge to the healthcare sector. The disruption to society and the economy is devastating, causing millions of people to live in poverty. Most citizens live in exceptional hardship and are exposed to the contagious virus while being vulnerable due to the inaccessibility of quality healthcare services. This study introduces ubiquitous computing as a state-of-the-art method to mitigate the spread of COVID-19 and spare more ICU beds for those truly needed. Ubiquitous computing offers a great solution with the concept of being accessible anywhere and anytime. As COVID-19 is highly complicated and unpredictable, people infected with COVID-19 may be unaware and still live on with their life. This resulted in the spread of COVID-19 being uncontrollable. Therefore, it is essential to identify the COVID-19 infection early, not only because of the mitigation of spread but also for optimal treatment. This way, the concept of wearable sensors to collect health information and use it as an input to feed into machine learning to determine COVID-19 infection or COVID-19 status monitoring is introduced in this study.
{"title":"Early Prediction of COVID-19 Infection with IoT and Machine Learning","authors":"Chow Man Pan, Kamalanathan Shanmugam, Muhammad Ehsan Rana, M. Jayabalan","doi":"10.1109/DeSE58274.2023.10099492","DOIUrl":"https://doi.org/10.1109/DeSE58274.2023.10099492","url":null,"abstract":"The deadly virus COVID-19 has heavily impacted all countries and brought a dramatic loss of human life. It is an unprecedented scenario and poses an extreme challenge to the healthcare sector. The disruption to society and the economy is devastating, causing millions of people to live in poverty. Most citizens live in exceptional hardship and are exposed to the contagious virus while being vulnerable due to the inaccessibility of quality healthcare services. This study introduces ubiquitous computing as a state-of-the-art method to mitigate the spread of COVID-19 and spare more ICU beds for those truly needed. Ubiquitous computing offers a great solution with the concept of being accessible anywhere and anytime. As COVID-19 is highly complicated and unpredictable, people infected with COVID-19 may be unaware and still live on with their life. This resulted in the spread of COVID-19 being uncontrollable. Therefore, it is essential to identify the COVID-19 infection early, not only because of the mitigation of spread but also for optimal treatment. This way, the concept of wearable sensors to collect health information and use it as an input to feed into machine learning to determine COVID-19 infection or COVID-19 status monitoring is introduced in this study.","PeriodicalId":346847,"journal":{"name":"2023 15th International Conference on Developments in eSystems Engineering (DeSE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116963500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10100115
A. Hassan, L. Al-Kindi, Amjad Barzan Abdulghafour
Smart Manufacturing is the deployment of big data processing, artificial intelligence, and sophisticated robotics technology, as well as their interconnectedness, to improve manufacturing performance and optimize energy and labor needs. To ensure a new development engine, the industrial sector wants to increase its competitiveness through the convergence of innovative ICT (Information and Communication Technology). Smart Manufacturing represents the Fourth Industrial Revolution and a New Paradigm. It is a set of cutting-edge technologies that facilitate effective and precise engineering decision-making in real time through the introduction of various ICT technologies and their convergence with current manufacturing technologies. This article describes and explores the smart manufacturing system, outlines its present stage of implementation, and discusses its accompanying technologies and their contributions to smart manufacturing technology. Moreover, a survey of the most recent advancements in this field and their effects, as well as the implementation challenges, opportunities, and future directions for smart manufacturing systems, were analyzed and presented in order to realize this rapidly expanding technology and cover all of its dimensions. The purpose of the literature study in this paper is to get a comprehensive understanding of smart manufacturing planning methodologies. Several papers and books produced over the previous five years are evaluated with a focus on the applications and kinds of systems.
{"title":"“Industrie 4.0” and Smart Manufacturing: A State of the Art Review","authors":"A. Hassan, L. Al-Kindi, Amjad Barzan Abdulghafour","doi":"10.1109/DeSE58274.2023.10100115","DOIUrl":"https://doi.org/10.1109/DeSE58274.2023.10100115","url":null,"abstract":"Smart Manufacturing is the deployment of big data processing, artificial intelligence, and sophisticated robotics technology, as well as their interconnectedness, to improve manufacturing performance and optimize energy and labor needs. To ensure a new development engine, the industrial sector wants to increase its competitiveness through the convergence of innovative ICT (Information and Communication Technology). Smart Manufacturing represents the Fourth Industrial Revolution and a New Paradigm. It is a set of cutting-edge technologies that facilitate effective and precise engineering decision-making in real time through the introduction of various ICT technologies and their convergence with current manufacturing technologies. This article describes and explores the smart manufacturing system, outlines its present stage of implementation, and discusses its accompanying technologies and their contributions to smart manufacturing technology. Moreover, a survey of the most recent advancements in this field and their effects, as well as the implementation challenges, opportunities, and future directions for smart manufacturing systems, were analyzed and presented in order to realize this rapidly expanding technology and cover all of its dimensions. The purpose of the literature study in this paper is to get a comprehensive understanding of smart manufacturing planning methodologies. Several papers and books produced over the previous five years are evaluated with a focus on the applications and kinds of systems.","PeriodicalId":346847,"journal":{"name":"2023 15th International Conference on Developments in eSystems Engineering (DeSE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127171827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10100021
Nadia I. Khalil, Hadeel N. Abdullah, L. A. Hassnawi
Path planning is one of the most fundamental problems that must be dealt with before the mobile robot can navigate and explore autonomously in any environment. A good path-planning algorithm can save time and reduce mobile robot wear and capital investment. Path computing time and average path length are important factors over cost functions that reflect the algorithm's effectiveness, such as power consumption or average trip time. The Artificial Bee Colony (ABC) represents one of the most important global search algorithms. The main problem with ABC is that it suffers from a slow convergence rate due to lousy exploitation and tends to get trapped in the local minima. This paper proposes and evaluates a new robot path-planning algorithm named Modified Artificial Bee Colony (MABC). MABC algorithm design is based on modifying the ABC algorithm by cross-layer design between ABC and Particle Swarm Optimization (PSO) algorithms. The MABC is different from the original ABC algorithm in that it modifies the original one to use PSO's exploitation rather than its exploitation. On the other hand, the PSO algorithm has better exploitation but poor exploration characteristics. The evaluation and analysis were performed for several performance metrics and under different evaluation scenarios. It has been observed from the results that the MABC-PSO outperforms the original ABC with respect to average path length and convergence time which leads to improving the planning of the path.
{"title":"A Hybrid Modified ABC-PSO Algorithm for Optimal Robotic Path Planner","authors":"Nadia I. Khalil, Hadeel N. Abdullah, L. A. Hassnawi","doi":"10.1109/DeSE58274.2023.10100021","DOIUrl":"https://doi.org/10.1109/DeSE58274.2023.10100021","url":null,"abstract":"Path planning is one of the most fundamental problems that must be dealt with before the mobile robot can navigate and explore autonomously in any environment. A good path-planning algorithm can save time and reduce mobile robot wear and capital investment. Path computing time and average path length are important factors over cost functions that reflect the algorithm's effectiveness, such as power consumption or average trip time. The Artificial Bee Colony (ABC) represents one of the most important global search algorithms. The main problem with ABC is that it suffers from a slow convergence rate due to lousy exploitation and tends to get trapped in the local minima. This paper proposes and evaluates a new robot path-planning algorithm named Modified Artificial Bee Colony (MABC). MABC algorithm design is based on modifying the ABC algorithm by cross-layer design between ABC and Particle Swarm Optimization (PSO) algorithms. The MABC is different from the original ABC algorithm in that it modifies the original one to use PSO's exploitation rather than its exploitation. On the other hand, the PSO algorithm has better exploitation but poor exploration characteristics. The evaluation and analysis were performed for several performance metrics and under different evaluation scenarios. It has been observed from the results that the MABC-PSO outperforms the original ABC with respect to average path length and convergence time which leads to improving the planning of the path.","PeriodicalId":346847,"journal":{"name":"2023 15th International Conference on Developments in eSystems Engineering (DeSE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124859158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10099939
Tam Kai Jun, Sathiapriya Ramiah
This paper studies the understanding and daily need of project management team in the software industry. With the rise in online working environment, the organizations emphasize on daily productivity in the hybrid working mode. To fulfill and solve the market need, Straper is proposed as a project management and collaboration tool to increase daily productivity and reduce the project development cost in the long run. This paper will focus on studying the background of online collaboration that is specific in project management topics. The problem that exists in online collaboration nowadays will be further explored and documented in detail. A total number of 10 literature reviews were conducted by the research in order to explore the domain knowledge and understand the related technology or standard process in-depth. Primary investigations were conducted through questionnaires and interviews to determine and validate the system requirement. Results and analysis show there is still a high value for Straper in the market and able to improve the quality of organization's working mode in the daily basis.
{"title":"Preliminary study: Professional Collaboration Application with Project Management Tools","authors":"Tam Kai Jun, Sathiapriya Ramiah","doi":"10.1109/DeSE58274.2023.10099939","DOIUrl":"https://doi.org/10.1109/DeSE58274.2023.10099939","url":null,"abstract":"This paper studies the understanding and daily need of project management team in the software industry. With the rise in online working environment, the organizations emphasize on daily productivity in the hybrid working mode. To fulfill and solve the market need, Straper is proposed as a project management and collaboration tool to increase daily productivity and reduce the project development cost in the long run. This paper will focus on studying the background of online collaboration that is specific in project management topics. The problem that exists in online collaboration nowadays will be further explored and documented in detail. A total number of 10 literature reviews were conducted by the research in order to explore the domain knowledge and understand the related technology or standard process in-depth. Primary investigations were conducted through questionnaires and interviews to determine and validate the system requirement. Results and analysis show there is still a high value for Straper in the market and able to improve the quality of organization's working mode in the daily basis.","PeriodicalId":346847,"journal":{"name":"2023 15th International Conference on Developments in eSystems Engineering (DeSE)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126750972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10099878
Goh Yih Shien, Kamalanathan Shanmugam, Muhammad Ehsan Rana
Surveillance camera has become an essential, ubiquitous technology in people's daily lives, whether applicable for home surveillance or extended to public workplace detection. The importance of the camera is irreplaceable in terms of the agent for an enclosed system to function correctly. The goal of ubiquitous computing is to keep different devices or technology communicating seamlessly, allowing them to expand to other areas instead of limiting it to one device. However, many research papers have been released on how the camera can aid in the current situation where COVID-19 is still raging worldwide, especially in crowded places. This paper aims to suggest a method by which surveillance cameras on the university campus can automatically detect student face mask status and notify them. Alongside that, this concept of applying a video management system within the university campus will assist in the automation of invigilating the student's daily mask status from the number of embedded surveillance cameras around the campus.
{"title":"Automated Face Mask Detection using Artificial Intelligence and Video Surveillance Management","authors":"Goh Yih Shien, Kamalanathan Shanmugam, Muhammad Ehsan Rana","doi":"10.1109/DeSE58274.2023.10099878","DOIUrl":"https://doi.org/10.1109/DeSE58274.2023.10099878","url":null,"abstract":"Surveillance camera has become an essential, ubiquitous technology in people's daily lives, whether applicable for home surveillance or extended to public workplace detection. The importance of the camera is irreplaceable in terms of the agent for an enclosed system to function correctly. The goal of ubiquitous computing is to keep different devices or technology communicating seamlessly, allowing them to expand to other areas instead of limiting it to one device. However, many research papers have been released on how the camera can aid in the current situation where COVID-19 is still raging worldwide, especially in crowded places. This paper aims to suggest a method by which surveillance cameras on the university campus can automatically detect student face mask status and notify them. Alongside that, this concept of applying a video management system within the university campus will assist in the automation of invigilating the student's daily mask status from the number of embedded surveillance cameras around the campus.","PeriodicalId":346847,"journal":{"name":"2023 15th International Conference on Developments in eSystems Engineering (DeSE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114519416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10099741
Sancharee Das, Rupal Bhargava
Fatigued driving has been reported to be a major cause of road accidents claiming millions of lives worldwide. Studies have shown that most road accidents occur either at night or early morning when the driver is already fatigued and there is insufficient light to notice obstacles. Some of the automated fatigue detection systems use physiological signals like EEG, ECG, and blood pressure movements. But, in most cases, the invasive nature of obtaining these signals makes them non-ideal. The recently developed computer vision based fatigue detection systems are too bulky or have limited accuracy due to prediction using single facial features or low-light conditions. Hence, the proposed method first enhances low-light images by improving the overall saturation and creating a uniform image using Gamma Correction. The enhanced images are then fed to a modified Multi-Task Cascaded Convolutional Neural Network for face detection and facial landmark extraction. Finally, the extracted eye state and mouth state features are fed to the LSTM network for fatigue classification. The output of this model decides whether the driver is fatigued or alert. The Mirror subset of the publicly available YawDD data set has been used for effective training and evaluation of the proposed model. The model achieved an exceptionally high F1 score of 0.98 and a Recall of 0.99 on the validation set.
{"title":"Vision-Based Fatigue Detection In Drivers Using Multi-Facial Feature Fusion","authors":"Sancharee Das, Rupal Bhargava","doi":"10.1109/DeSE58274.2023.10099741","DOIUrl":"https://doi.org/10.1109/DeSE58274.2023.10099741","url":null,"abstract":"Fatigued driving has been reported to be a major cause of road accidents claiming millions of lives worldwide. Studies have shown that most road accidents occur either at night or early morning when the driver is already fatigued and there is insufficient light to notice obstacles. Some of the automated fatigue detection systems use physiological signals like EEG, ECG, and blood pressure movements. But, in most cases, the invasive nature of obtaining these signals makes them non-ideal. The recently developed computer vision based fatigue detection systems are too bulky or have limited accuracy due to prediction using single facial features or low-light conditions. Hence, the proposed method first enhances low-light images by improving the overall saturation and creating a uniform image using Gamma Correction. The enhanced images are then fed to a modified Multi-Task Cascaded Convolutional Neural Network for face detection and facial landmark extraction. Finally, the extracted eye state and mouth state features are fed to the LSTM network for fatigue classification. The output of this model decides whether the driver is fatigued or alert. The Mirror subset of the publicly available YawDD data set has been used for effective training and evaluation of the proposed model. The model achieved an exceptionally high F1 score of 0.98 and a Recall of 0.99 on the validation set.","PeriodicalId":346847,"journal":{"name":"2023 15th International Conference on Developments in eSystems Engineering (DeSE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122121634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10100270
Megan Wilson, Dhiya Al-Jumeily Obe, Ismail Abbas, Iftikhar Khan, J. Birkett, Leung Tang, S. Assi
Near infrared (NIR) spectroscopy offers portable and rapid analysis of endogenous constituents and drugs within fingernails. Fingernails are a useful alternative biological matrix to blood and urine specimen as they provide the advantage of being non-invasive and require minimal sample size (1–3 mm). This work utilised NIR spectroscopy for the detection of (1) drugs in fingernails including benzocaine, calcium carbonate, cocaine hydrochloride (HCl), levamisole HCl, lidocaine HCl and procaine HCl; and (2) endogenous constituents such as carbohydrates, lipids, proteins and water. Fingernails were analysed initially ‘as received’ to identify the aforementioned endogenous constituents. Seven sets of fingernails were then spiked with one the identified drugs and measured over a six-week period. Spectra were exported into Matlab 2019a for spectral interpretation and machine learning analytics (MLAs). MLAs included correlation wavenumber space (CWS), principal component analysis (PCA) and Artificial Neural Networks Self-Organising Maps (SOM). The results showed that NIR spectra of spiked nails showed key characteristic features at specific wavelengths that corresponded to their spiked drug (1). When combined with CWS and PCA, NIR spectroscopy was able to differentiate between spiked and un-spiked nails and distinguish between the drugs that did not share similar chemical structures. CWS values (r values) and PCA loading scores highlighted spectra/spectral features that were significant. In addition, SOM showed further classes beyond PCA that corresponded to changes in physical properties of the fingernails. Thus, finding confirmed that NIR spectroscopy combined with MLAs possessed the ability to characterise fingernails based on their endogenous constituents and to detect the presence of drugs within fingernails.
{"title":"Palm-sized Near-Infrared Spectroscopy and Machine Learning Analytics for the Detection of Endogenous Constituents and Drugs in Human Fingernails","authors":"Megan Wilson, Dhiya Al-Jumeily Obe, Ismail Abbas, Iftikhar Khan, J. Birkett, Leung Tang, S. Assi","doi":"10.1109/DeSE58274.2023.10100270","DOIUrl":"https://doi.org/10.1109/DeSE58274.2023.10100270","url":null,"abstract":"Near infrared (NIR) spectroscopy offers portable and rapid analysis of endogenous constituents and drugs within fingernails. Fingernails are a useful alternative biological matrix to blood and urine specimen as they provide the advantage of being non-invasive and require minimal sample size (1–3 mm). This work utilised NIR spectroscopy for the detection of (1) drugs in fingernails including benzocaine, calcium carbonate, cocaine hydrochloride (HCl), levamisole HCl, lidocaine HCl and procaine HCl; and (2) endogenous constituents such as carbohydrates, lipids, proteins and water. Fingernails were analysed initially ‘as received’ to identify the aforementioned endogenous constituents. Seven sets of fingernails were then spiked with one the identified drugs and measured over a six-week period. Spectra were exported into Matlab 2019a for spectral interpretation and machine learning analytics (MLAs). MLAs included correlation wavenumber space (CWS), principal component analysis (PCA) and Artificial Neural Networks Self-Organising Maps (SOM). The results showed that NIR spectra of spiked nails showed key characteristic features at specific wavelengths that corresponded to their spiked drug (1). When combined with CWS and PCA, NIR spectroscopy was able to differentiate between spiked and un-spiked nails and distinguish between the drugs that did not share similar chemical structures. CWS values (r values) and PCA loading scores highlighted spectra/spectral features that were significant. In addition, SOM showed further classes beyond PCA that corresponded to changes in physical properties of the fingernails. Thus, finding confirmed that NIR spectroscopy combined with MLAs possessed the ability to characterise fingernails based on their endogenous constituents and to detect the presence of drugs within fingernails.","PeriodicalId":346847,"journal":{"name":"2023 15th International Conference on Developments in eSystems Engineering (DeSE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116591939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10099965
Chang Deng Khai, Julia Juremi
The advancement of information technology has stimulated the conversion of physical interactions to online activities, especially during the Covid-19 pandemic. Thus, users' awareness and cyber hygiene need to be emphasized when they are involved in the cyber world. A browser extension named “BEsafe” is developed to validate the websites and promote a safe browsing environment. It prevents users from falling prey to network-based attacks and raises their security awareness. To ensure users' privacy, the permissions needed for BEsafe are listed on the permission tab. Moreover, BEsafe will not be working on Incognito mode by default to promise that the private mode leaves no tracks. However, the user can still enable the extension to be functioning on Incognito mode by navigating to the Extension Details and turning on the relevant toggle.
{"title":"BEsafe - Validating URLs and Domains with the aid of Indicator of Compromise","authors":"Chang Deng Khai, Julia Juremi","doi":"10.1109/DeSE58274.2023.10099965","DOIUrl":"https://doi.org/10.1109/DeSE58274.2023.10099965","url":null,"abstract":"The advancement of information technology has stimulated the conversion of physical interactions to online activities, especially during the Covid-19 pandemic. Thus, users' awareness and cyber hygiene need to be emphasized when they are involved in the cyber world. A browser extension named “BEsafe” is developed to validate the websites and promote a safe browsing environment. It prevents users from falling prey to network-based attacks and raises their security awareness. To ensure users' privacy, the permissions needed for BEsafe are listed on the permission tab. Moreover, BEsafe will not be working on Incognito mode by default to promise that the private mode leaves no tracks. However, the user can still enable the extension to be functioning on Incognito mode by navigating to the Extension Details and turning on the relevant toggle.","PeriodicalId":346847,"journal":{"name":"2023 15th International Conference on Developments in eSystems Engineering (DeSE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128208825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1109/DeSE58274.2023.10099510
Amar Kumar, Rupal Bhargava, M. Jayabalan
COVID-19 crisis has led to an outburst of information that needs to be organized, validated, and made available to the seekers. Despite the rapid growth and success of BERT models in the last 3 years, COVID QA is a difficult task due to the lack of applicable datasets and a relevant language representation. Therefore, this study proposes a transformer-based Question Answering (QA) model for COVID-19 questions from the biomedical domain. Further, explored several datasets, and models required for question type prediction, no-answer prediction, and answer extraction and transfer learning strategies. It has been demonstrated that the exact match score can be significantly improved with limited amounts of training data from the biomedical domain. Finally, the findings of the study have been summarized as Factoid QA Finetuning Framework (FQFF), which can provide initial direction for domain-specific QA tasks with a limited amount of data.
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