The task of named entity recognition (NER) is to identify entities in the text and predict their categories. In real-life scenarios, the context of the text is often complex, and there may exist nested entities within an entity. This kind of entity is called a nested entity, and the task of recognizing entities with nested structures is referred to as nested named entity recognition. Most existing NER models can only handle flat entities, and there has been limited research progress in Chinese nested named entity recognition, resulting in relatively few models in this direction. General NER models have limited semantic extraction capabilities and cannot capture deep semantic information between nested entities in the text. To address these issues, this paper proposes a model that uses the GlobalPointer module to identify nested entities in the text and constructs the IDCNNLR semantic extraction module to extract deep semantic information. Furthermore, multiple-head self-attention mechanisms are incorporated into the model at multiple positions to achieve data denoising, enhancing the quality of semantic features. The proposed model considers each possible entity boundary through the GlobalPointer module, and the IDCNNLR semantic extraction module and multi-position attention mechanism are introduced to enhance the model’s semantic extraction capability. Experimental results demonstrate that the proposed model achieves F1 scores of 69.617% and 79.285% on the CMeEE Chinese nested entity recognition dataset and CLUENER2020 Chinese fine-grained entity recognition dataset, respectively. The model exhibits improvement compared to baseline models, and each innovation point shows effective performance enhancement in ablative experiments.
命名实体识别（NER）的任务是识别文本中的实体并预测其类别。在现实生活中，文本的上下文往往很复杂，实体中可能存在嵌套实体。这种实体被称为嵌套实体，识别具有嵌套结构的实体的任务被称为嵌套命名实体识别。现有的 NER 模型大多只能处理平面实体，而中文嵌套命名实体识别的研究进展有限，因此这方面的模型相对较少。一般的 NER 模型语义提取能力有限，无法捕捉文本中嵌套实体之间的深层语义信息。针对这些问题，本文提出了一种利用 GlobalPointer 模块识别文本中嵌套实体，并构建 IDCNNLR 语义提取模块提取深层语义信息的模型。此外，该模型还在多个位置加入了多头自关注机制，以实现数据去噪，提高语义特征的质量。提出的模型通过 GlobalPointer 模块考虑了每个可能的实体边界，并引入了 IDCNNLR 语义提取模块和多位置关注机制，以增强模型的语义提取能力。实验结果表明，所提出的模型在 CMeEE 中文嵌套实体识别数据集和 CLUENER2020 中文细粒度实体识别数据集上的 F1 分数分别达到了 69.617% 和 79.285%。与基线模型相比，该模型有所改进，每个创新点在消融实验中都显示出有效的性能提升。
{"title":"Research on Chinese Nested Entity Recognition Based on IDCNNLR and GlobalPointer","authors":"Weijun Li, Jintong Liu, Yuxiao Gao, Xinyong Zhang, Jianlai Gu","doi":"10.3390/asi7010008","DOIUrl":"https://doi.org/10.3390/asi7010008","url":null,"abstract":"The task of named entity recognition (NER) is to identify entities in the text and predict their categories. In real-life scenarios, the context of the text is often complex, and there may exist nested entities within an entity. This kind of entity is called a nested entity, and the task of recognizing entities with nested structures is referred to as nested named entity recognition. Most existing NER models can only handle flat entities, and there has been limited research progress in Chinese nested named entity recognition, resulting in relatively few models in this direction. General NER models have limited semantic extraction capabilities and cannot capture deep semantic information between nested entities in the text. To address these issues, this paper proposes a model that uses the GlobalPointer module to identify nested entities in the text and constructs the IDCNNLR semantic extraction module to extract deep semantic information. Furthermore, multiple-head self-attention mechanisms are incorporated into the model at multiple positions to achieve data denoising, enhancing the quality of semantic features. The proposed model considers each possible entity boundary through the GlobalPointer module, and the IDCNNLR semantic extraction module and multi-position attention mechanism are introduced to enhance the model’s semantic extraction capability. Experimental results demonstrate that the proposed model achieves F1 scores of 69.617% and 79.285% on the CMeEE Chinese nested entity recognition dataset and CLUENER2020 Chinese fine-grained entity recognition dataset, respectively. The model exhibits improvement compared to baseline models, and each innovation point shows effective performance enhancement in ablative experiments.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"15 7","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139445638","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}
Hajar Majjate, Youssra Bellarhmouch, Adil Jeghal, Ali Yahyaouy, H. Tairi, Khalid Alaoui Zidani
Over the past few decades, the education sector has achieved impressive advancements by incorporating Artificial Intelligence (AI) into the educational environment. Nevertheless, specific educational processes, particularly educational counseling, still depend on traditional procedures. The current method of conducting group sessions between counselors and students does not offer personalized assistance or individual attention, which can cause stress to students and make it difficult for them to make informed decisions about their coursework and career path. This paper proposes a counseling solution designed to aid high school seniors in selecting appropriate academic paths at the tertiary level. The system utilizes a predictive model that considers academic history and student preferences to determine students’ likelihood of admission to their chosen university and recommends similar alternative universities to provide more opportunities. We developed the model based on data from 500 graduates from 12 public high schools in Morocco, as well as eligibility criteria from 31 institutions and colleges. The counseling system comprises two modules: a recommendation module that uses popularity-based and content-based recommendations and a prediction module that calculates the likelihood of admission using the Huber Regressor model. This model outperformed 13 other machine learning modules, with a low MSE of 0.0017, RMSE of 0.0422, and the highest R-squared value of 0.9306. Finally, the system is accessible through a user-friendly web interface.
{"title":"AI-Powered Academic Guidance and Counseling System Based on Student Profile and Interests","authors":"Hajar Majjate, Youssra Bellarhmouch, Adil Jeghal, Ali Yahyaouy, H. Tairi, Khalid Alaoui Zidani","doi":"10.3390/asi7010006","DOIUrl":"https://doi.org/10.3390/asi7010006","url":null,"abstract":"Over the past few decades, the education sector has achieved impressive advancements by incorporating Artificial Intelligence (AI) into the educational environment. Nevertheless, specific educational processes, particularly educational counseling, still depend on traditional procedures. The current method of conducting group sessions between counselors and students does not offer personalized assistance or individual attention, which can cause stress to students and make it difficult for them to make informed decisions about their coursework and career path. This paper proposes a counseling solution designed to aid high school seniors in selecting appropriate academic paths at the tertiary level. The system utilizes a predictive model that considers academic history and student preferences to determine students’ likelihood of admission to their chosen university and recommends similar alternative universities to provide more opportunities. We developed the model based on data from 500 graduates from 12 public high schools in Morocco, as well as eligibility criteria from 31 institutions and colleges. The counseling system comprises two modules: a recommendation module that uses popularity-based and content-based recommendations and a prediction module that calculates the likelihood of admission using the Huber Regressor model. This model outperformed 13 other machine learning modules, with a low MSE of 0.0017, RMSE of 0.0422, and the highest R-squared value of 0.9306. Finally, the system is accessible through a user-friendly web interface.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"79 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139149196","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}
O. Santos, F. Ribeiro, J. Metrôlho, Rogério Dionísio
Reducing CO2 emissions is currently a key policy in most developed countries. In this article, we evaluate whether smart traffic lights can have a relevant role in reducing CO2 emissions in small cities, considering their specific traffic profiles. The research method is a quantitative modelling approach tested by computational simulation. We propose a novel microscopic traffic simulation framework, designed to simulate realistic vehicle kinematics and driver behaviour, and accurately estimate CO2 emissions. We also propose and evaluate a routing algorithm for smart traffic lights, specially designed to optimize CO2 emissions at intersections. The simulations reveal that deploying smart traffic lights at a single intersection can reduce CO2 emissions by 32% to 40% in the vicinity of the intersection, depending on the traffic density. The simulations show other advantages for drivers: an increase in average speed of 60% to 101% and a reduction in waiting time of 53% to 95%. These findings can be useful for city-level decision makers who wish to adopt smart technologies to improve traffic flows and reduce CO2 emissions. This work also demonstrates that the simulator can play an important role as a tool to study the impact of smart traffic lights and foster the improvement in smart routing algorithms to reduce CO2 emissions.
{"title":"Using Smart Traffic Lights to Reduce CO2 Emissions and Improve Traffic Flow at Intersections: Simulation of an Intersection in a Small Portuguese City","authors":"O. Santos, F. Ribeiro, J. Metrôlho, Rogério Dionísio","doi":"10.3390/asi7010003","DOIUrl":"https://doi.org/10.3390/asi7010003","url":null,"abstract":"Reducing CO2 emissions is currently a key policy in most developed countries. In this article, we evaluate whether smart traffic lights can have a relevant role in reducing CO2 emissions in small cities, considering their specific traffic profiles. The research method is a quantitative modelling approach tested by computational simulation. We propose a novel microscopic traffic simulation framework, designed to simulate realistic vehicle kinematics and driver behaviour, and accurately estimate CO2 emissions. We also propose and evaluate a routing algorithm for smart traffic lights, specially designed to optimize CO2 emissions at intersections. The simulations reveal that deploying smart traffic lights at a single intersection can reduce CO2 emissions by 32% to 40% in the vicinity of the intersection, depending on the traffic density. The simulations show other advantages for drivers: an increase in average speed of 60% to 101% and a reduction in waiting time of 53% to 95%. These findings can be useful for city-level decision makers who wish to adopt smart technologies to improve traffic flows and reduce CO2 emissions. This work also demonstrates that the simulator can play an important role as a tool to study the impact of smart traffic lights and foster the improvement in smart routing algorithms to reduce CO2 emissions.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"13 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139159490","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}
The mathematical modeling and the associated numerical simulation of the light–matter interaction (LMI) process are well-known to be quite complicated, particularly for media where several electronic transitions take place under electromagnetic excitation. As a result, numerical simulations of typical LMI processes usually require a high computational cost due to the involvement of a large number of coupled differential equations modeling electron and photon behavior. In this paper, we model the general LMI process involving an electromagnetic interaction medium and optical (light) excitation in one dimension (1D) via the use of a dynamic deep learning algorithm where the neural network coefficients can precisely adapt themselves based on the past values of the coefficients of adjacent layers even under the availability of very limited data. Due to the high computational cost of LMI simulations, simulation data are usually only available for short durations. Our aim here is to implement an adaptive deep learning-based model of the LMI process in 1D based on available temporal data so that the electromagnetic features of LMI simulations can be quickly decrypted by the evolving network coefficients, facilitating self-learning. This enables accurate prediction and acceleration of LMI simulations that can run for much longer durations via the reduction in the cost of computation through the elimination of the requirement for the simultaneous computation and discretization of a large set of coupled differential equations at each simulation step. Our analyses show that the LMI process can be efficiently decrypted using dynamic deep learning with less than 1% relative error (RE), enabling the extension of LMI simulations using simple artificial neural networks.
{"title":"Predictive Modeling of Light–Matter Interaction in One Dimension: A Dynamic Deep Learning Approach","authors":"Ö. E. Aşırım, Ece Z. Asirim, M. Kuzuoglu","doi":"10.3390/asi7010004","DOIUrl":"https://doi.org/10.3390/asi7010004","url":null,"abstract":"The mathematical modeling and the associated numerical simulation of the light–matter interaction (LMI) process are well-known to be quite complicated, particularly for media where several electronic transitions take place under electromagnetic excitation. As a result, numerical simulations of typical LMI processes usually require a high computational cost due to the involvement of a large number of coupled differential equations modeling electron and photon behavior. In this paper, we model the general LMI process involving an electromagnetic interaction medium and optical (light) excitation in one dimension (1D) via the use of a dynamic deep learning algorithm where the neural network coefficients can precisely adapt themselves based on the past values of the coefficients of adjacent layers even under the availability of very limited data. Due to the high computational cost of LMI simulations, simulation data are usually only available for short durations. Our aim here is to implement an adaptive deep learning-based model of the LMI process in 1D based on available temporal data so that the electromagnetic features of LMI simulations can be quickly decrypted by the evolving network coefficients, facilitating self-learning. This enables accurate prediction and acceleration of LMI simulations that can run for much longer durations via the reduction in the cost of computation through the elimination of the requirement for the simultaneous computation and discretization of a large set of coupled differential equations at each simulation step. Our analyses show that the LMI process can be efficiently decrypted using dynamic deep learning with less than 1% relative error (RE), enabling the extension of LMI simulations using simple artificial neural networks.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"1 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139159823","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}
Marilia Botelho Coelho, Daniel P. Lacerda, F. Piran, Débora Oliveira da Silva, M. Sellitto
The research question this study poses is how to measure the efficiency of project management activities. The purpose of this article is to quantify the efficiency of the execution of a project portfolio managed by a project management office (PMO) structure. The research subject is a PMO operating within a petrochemical manufacturing company in southern Brazil. The research method is quantitative modeling. The study employed data envelopment analysis (DEA) to calculate the relative efficiencies of projects in three classes according to complexity over a period of four years. Each project is a decision-making unit (DMU), as required by the DEA procedure. One novelty is the calculation of cost- and time-weighted efficiency values, which slightly differ from the average. The main results indicate that the average efficiency for classes of projects roughly stands between 40 and 80%. The results also indicate a learning process guided by the PMO, as the average efficiency increased over three years in two classes of projects, according to the prioritization imposed by the office. The study also pointed out that the most influential variables in determining project efficiency are accuracy in meeting deadlines and the time planned for completion. The most important implication is that, from now on, the company has a theoretical foundation to justify focusing further efforts on reducing and controlling time to completion, not only cost and scope conformity, to increase overall project efficiency. Future research should prioritize investigating management techniques that increase the likelihood of completing projects within their deadlines.
本研究提出的问题是如何衡量项目管理活动的效率。本文旨在量化由项目管理办公室（PMO）结构管理的项目组合的执行效率。研究对象是巴西南部一家石化制造公司的项目管理办公室。研究方法是定量建模。研究采用了数据包络分析法（DEA），根据项目的复杂程度计算出四年内三类项目的相对效率。按照 DEA 程序的要求，每个项目都是一个决策单元（DMU）。一个新颖之处是计算了成本和时间加权效率值，与平均值略有不同。主要结果表明，各类项目的平均效率大致在 40%至 80%之间。研究结果还表明，在项目管理办公室的指导下，有一个学习过程，因为根据办公室规定的优先次序，有两类项目的平均效率在三年内有所提高。研究还指出，决定项目效率的最有影响力的变量是遵守最后期限的准确性和计划完成的时间。最重要的意义在于，从现在开始，公司有了理论依据，可以进一步将工作重点放在缩短和控制完工时间上，而不仅仅是成本和范围的一致性上，以提高项目的整体效率。今后的研究应优先调查那些能提高在期限内完成项目的可能性的管理技术。
{"title":"Project Management Efficiency Measurement with Data Envelopment Analysis: A Case in a Petrochemical Company","authors":"Marilia Botelho Coelho, Daniel P. Lacerda, F. Piran, Débora Oliveira da Silva, M. Sellitto","doi":"10.3390/asi7010002","DOIUrl":"https://doi.org/10.3390/asi7010002","url":null,"abstract":"The research question this study poses is how to measure the efficiency of project management activities. The purpose of this article is to quantify the efficiency of the execution of a project portfolio managed by a project management office (PMO) structure. The research subject is a PMO operating within a petrochemical manufacturing company in southern Brazil. The research method is quantitative modeling. The study employed data envelopment analysis (DEA) to calculate the relative efficiencies of projects in three classes according to complexity over a period of four years. Each project is a decision-making unit (DMU), as required by the DEA procedure. One novelty is the calculation of cost- and time-weighted efficiency values, which slightly differ from the average. The main results indicate that the average efficiency for classes of projects roughly stands between 40 and 80%. The results also indicate a learning process guided by the PMO, as the average efficiency increased over three years in two classes of projects, according to the prioritization imposed by the office. The study also pointed out that the most influential variables in determining project efficiency are accuracy in meeting deadlines and the time planned for completion. The most important implication is that, from now on, the company has a theoretical foundation to justify focusing further efforts on reducing and controlling time to completion, not only cost and scope conformity, to increase overall project efficiency. Future research should prioritize investigating management techniques that increase the likelihood of completing projects within their deadlines.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"9 14","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138943960","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}
Josue-Rafael Montes-Martínez, Hugo Jiménez-Hernández, A. Herrera-Navarro, Luis-Antonio Díaz-Jiménez, Jorge-Luis Perez-Ramos, Julio-César Solano-Vargas
Artificial vision system applications have generated significant interest as they allow information to be obtained through one or several of the cameras that can be found in daily life in many places, such as parks, avenues, squares, houses, etc. When the aim is to obtain information from large areas, it can become complicated if it is necessary to track an object of interest, such as people or vehicles, due to the vision space that a single camera can cover; this opens the way to distributed zone monitoring systems made up of a set of cameras that aim to cover a larger area. Distributed zone monitoring systems add great versatility, becoming more complex in terms of the complexity of information analysis, communication, interoperability, and heterogeneity in the interpretation of information. In the literature, the development of distributed schemes has focused on representing data communication and sharing challenges. Currently, there are no specific criteria for information exchange and analysis in a distributed system; hence, different models and architectures have been proposed. In this work, the authors present a framework to provide homogeneity in a distributed monitoring system. The information is obtained from different cameras, where a global reference system is defined for generated trajectories, which are mapped independently of the model used to obtain the dynamics of the movement of people within the vision area of a distributed system, thus allowing for its use in works where there is a large amount of information from heterogeneous sources. Furthermore, we propose a novel similarity metric that allows for information queries from heterogeneous sources. Finally, to evaluate the proposed performance, the authors developed several distributed query applications in an augmented reality system based on realistic environments and historical data retrieval using a client–server model.
{"title":"Dynamic Queries through Augmented Reality for Intelligent Video Systems","authors":"Josue-Rafael Montes-Martínez, Hugo Jiménez-Hernández, A. Herrera-Navarro, Luis-Antonio Díaz-Jiménez, Jorge-Luis Perez-Ramos, Julio-César Solano-Vargas","doi":"10.3390/asi7010001","DOIUrl":"https://doi.org/10.3390/asi7010001","url":null,"abstract":"Artificial vision system applications have generated significant interest as they allow information to be obtained through one or several of the cameras that can be found in daily life in many places, such as parks, avenues, squares, houses, etc. When the aim is to obtain information from large areas, it can become complicated if it is necessary to track an object of interest, such as people or vehicles, due to the vision space that a single camera can cover; this opens the way to distributed zone monitoring systems made up of a set of cameras that aim to cover a larger area. Distributed zone monitoring systems add great versatility, becoming more complex in terms of the complexity of information analysis, communication, interoperability, and heterogeneity in the interpretation of information. In the literature, the development of distributed schemes has focused on representing data communication and sharing challenges. Currently, there are no specific criteria for information exchange and analysis in a distributed system; hence, different models and architectures have been proposed. In this work, the authors present a framework to provide homogeneity in a distributed monitoring system. The information is obtained from different cameras, where a global reference system is defined for generated trajectories, which are mapped independently of the model used to obtain the dynamics of the movement of people within the vision area of a distributed system, thus allowing for its use in works where there is a large amount of information from heterogeneous sources. Furthermore, we propose a novel similarity metric that allows for information queries from heterogeneous sources. Finally, to evaluate the proposed performance, the authors developed several distributed query applications in an augmented reality system based on realistic environments and historical data retrieval using a client–server model.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":" 7","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138960715","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}
João Vieira, João Poças Martins, Nuno Marques de Almeida, Hugo Patrício, João Morgado
While digital twins (DTs) have achieved significant visibility, they continue to face a problem of lack of harmonisation regarding their interpretation and definition. This diverse and interchangeable use of terms makes it challenging for scientific activities to take place and for organisations to grasp the existing opportunities and how can these benefit their businesses. This article aims to shift the focus away from debating a definition for a DT. Instead, it proposes a conceptual approach to the digital twinning of engineering physical assets as an ongoing process with variable complexity and evolutionary capacity over time. To accomplish this, the article presents a functional architecture of digital twinning, grounded in the foundational elements of the DT, to reflect the various forms and levels of digital twinning (LoDT) of physical assets throughout their life cycles. Furthermore, this work presents UNI-TWIN—a unified model to assist organisations in assessing the LoDT of their assets and to support investment planning decisions. Three case studies from the road and rail sector validate its applicability. UNI-TWIN helps to redirect the discussion around DTs and emphasise the opportunities and challenges presented by the diverse realities of digital twinning, namely in the context of engineering asset management.
{"title":"Reshaping the Digital Twin Construct with Levels of Digital Twinning (LoDT)","authors":"João Vieira, João Poças Martins, Nuno Marques de Almeida, Hugo Patrício, João Morgado","doi":"10.3390/asi6060114","DOIUrl":"https://doi.org/10.3390/asi6060114","url":null,"abstract":"While digital twins (DTs) have achieved significant visibility, they continue to face a problem of lack of harmonisation regarding their interpretation and definition. This diverse and interchangeable use of terms makes it challenging for scientific activities to take place and for organisations to grasp the existing opportunities and how can these benefit their businesses. This article aims to shift the focus away from debating a definition for a DT. Instead, it proposes a conceptual approach to the digital twinning of engineering physical assets as an ongoing process with variable complexity and evolutionary capacity over time. To accomplish this, the article presents a functional architecture of digital twinning, grounded in the foundational elements of the DT, to reflect the various forms and levels of digital twinning (LoDT) of physical assets throughout their life cycles. Furthermore, this work presents UNI-TWIN—a unified model to assist organisations in assessing the LoDT of their assets and to support investment planning decisions. Three case studies from the road and rail sector validate its applicability. UNI-TWIN helps to redirect the discussion around DTs and emphasise the opportunities and challenges presented by the diverse realities of digital twinning, namely in the context of engineering asset management.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"36 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139199779","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}
Soorim Yang, Kyoung-Hwan Kim, Hye-Ryeong Jeong, Seokjun Lee, Jaeho Kim
The COVID-19 pandemic has underscored the necessity for rapid contact tracing as a means to effectively suppress the spread of infectious diseases. Existing contact tracing methods leverage location-based or distance-based detection to identify contact with a confirmed patient. Existing contact tracing methods have encountered challenges in practical applications, stemming from the tendency to classify even casual contacts, which carry a low risk of infection, as close contacts. This issue arises because the transmission characteristics of the virus have not been fully considered. This study addresses the above problem by proposing IntelliTrace, an intelligent method that introduces methodological innovations prioritizing shared environmental context over physical proximity. This approach more accurately assesses potential transmission events by considering the transmission characteristics of the virus, with a special focus on COVID-19. In this study, we present space-based indoor Wi-Fi contact tracing using machine learning for indoor environments and trajectory-based outdoor GPS contact tracing for outdoor environments. For an indoor environment, a contact is detected based on whether users are in the same space with the confirmed case. For an outdoor environment, we detect contact through judgments based on the companion statuses of people, such as the same movements in their trajectories. The datasets obtained from 28 participants who installed the smartphone application during a one-month experiment in a campus space were utilized to train and validate the performance of the proposed exposure-detection method. As a result of the experiment, IntelliTrace exhibited an F1 score performance of 86.84% in indoor environments and 94.94% in outdoor environments.
{"title":"IntelliTrace: Intelligent Contact Tracing Method Based on Transmission Characteristics of Infectious Disease","authors":"Soorim Yang, Kyoung-Hwan Kim, Hye-Ryeong Jeong, Seokjun Lee, Jaeho Kim","doi":"10.3390/asi6060112","DOIUrl":"https://doi.org/10.3390/asi6060112","url":null,"abstract":"The COVID-19 pandemic has underscored the necessity for rapid contact tracing as a means to effectively suppress the spread of infectious diseases. Existing contact tracing methods leverage location-based or distance-based detection to identify contact with a confirmed patient. Existing contact tracing methods have encountered challenges in practical applications, stemming from the tendency to classify even casual contacts, which carry a low risk of infection, as close contacts. This issue arises because the transmission characteristics of the virus have not been fully considered. This study addresses the above problem by proposing IntelliTrace, an intelligent method that introduces methodological innovations prioritizing shared environmental context over physical proximity. This approach more accurately assesses potential transmission events by considering the transmission characteristics of the virus, with a special focus on COVID-19. In this study, we present space-based indoor Wi-Fi contact tracing using machine learning for indoor environments and trajectory-based outdoor GPS contact tracing for outdoor environments. For an indoor environment, a contact is detected based on whether users are in the same space with the confirmed case. For an outdoor environment, we detect contact through judgments based on the companion statuses of people, such as the same movements in their trajectories. The datasets obtained from 28 participants who installed the smartphone application during a one-month experiment in a campus space were utilized to train and validate the performance of the proposed exposure-detection method. As a result of the experiment, IntelliTrace exhibited an F1 score performance of 86.84% in indoor environments and 94.94% in outdoor environments.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"3 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139245068","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}
To depict the pump power characteristics of radial centrifugal pumps, a physical model was developed. The model relies on established empirical equations. To parameterize the model for specific pumps, physically interpretable tuning factors were integrated. The tuning factors are identified by using the Levenberg–Marquardt method, which was applied to the characteristic curve at a constant speed. A cross-validation of the physical model highlighted the advantage of representing the set of performance curves with less deviation compared to approximation functions. Calculating the entire set of performance curves requires only one pump characteristic curve at a constant speed. Therefore, only a single measurement is necessary. Furthermore, the physical model can be used to calculate the changes in the set of performance curves due to prewhirl. This increases the accuracy of flow rate calculations when prewhirl occurs.
{"title":"Physical Modelling of the Set of Performance Curves for Radial Centrifugal Pumps to Determine the Flow Rate","authors":"Nils Reeh, Gerd Manthei, Peter J. Klar","doi":"10.3390/asi6060111","DOIUrl":"https://doi.org/10.3390/asi6060111","url":null,"abstract":"To depict the pump power characteristics of radial centrifugal pumps, a physical model was developed. The model relies on established empirical equations. To parameterize the model for specific pumps, physically interpretable tuning factors were integrated. The tuning factors are identified by using the Levenberg–Marquardt method, which was applied to the characteristic curve at a constant speed. A cross-validation of the physical model highlighted the advantage of representing the set of performance curves with less deviation compared to approximation functions. Calculating the entire set of performance curves requires only one pump characteristic curve at a constant speed. Therefore, only a single measurement is necessary. Furthermore, the physical model can be used to calculate the changes in the set of performance curves due to prewhirl. This increases the accuracy of flow rate calculations when prewhirl occurs.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"47 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139265729","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}
(1) Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is typically first diagnosed in early childhood. Medication and cognitive behavioural therapy are considered effective in treating children with ADHD, whereas these treatments appear to have some side effects and restrictions. Virtual reality (VR), therefore, has been applied to exposure therapy for mental disorders. Previous studies have adopted VR in the cognitive behavioural treatment for children with ADHD; however, no research has used VR to develop social skills training for children with ADHD. This study aimed to develop a VR-based intervention (Social VR) to improve social skills in children with symptoms of ADHD. Prior to conducting the pilot trial to assess the effectiveness of Social VR, valuable user feedback was gathered regarding the mechanics of Social VR, satisfaction and motion sickness. This study presented the development and preliminary usability of Social VR to enhance social interaction skills among children with ADHD. (2) Methods: The development process of the Social VR intervention was demonstrated. The Social VR intervention consisted of three scenarios, namely MTR, Campus and Market and Restaurant. In the usability study, 25 children with ADHD were recruited to test the Social VR during the preliminary usability stage of a clinical trial at preinclusion. The participants completed a survey about their experience of playing Social VR, satisfaction, and motion sickness. (3) Results: The participants indicated the three conditions had easy-to-follow instructions, were easy to pick up, and that they understood when the situations changed. The control and beauty of the graphics of Market and Restaurant were relatively lower compared with those of MTR and Campus. The three scenarios are applicable to children diagnosed with any subtype of ADHD. (4) Conclusion: The participants were satisfied with Social VR. Social VR was generally considered realistic and immersive. Further trials to assess the feasibility and efficacy were discussed. If proven effective, VR-based intervention can be an adjunctive approach to current multimodal training for children with ADHD.
{"title":"Unlocking Potential: The Development and User-Friendly Evaluation of a Virtual Reality Intervention for Attention-Deficit/Hyperactivity Disorder","authors":"K. Wong, Bohan Zhang, Jing Qin","doi":"10.3390/asi6060110","DOIUrl":"https://doi.org/10.3390/asi6060110","url":null,"abstract":"(1) Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is typically first diagnosed in early childhood. Medication and cognitive behavioural therapy are considered effective in treating children with ADHD, whereas these treatments appear to have some side effects and restrictions. Virtual reality (VR), therefore, has been applied to exposure therapy for mental disorders. Previous studies have adopted VR in the cognitive behavioural treatment for children with ADHD; however, no research has used VR to develop social skills training for children with ADHD. This study aimed to develop a VR-based intervention (Social VR) to improve social skills in children with symptoms of ADHD. Prior to conducting the pilot trial to assess the effectiveness of Social VR, valuable user feedback was gathered regarding the mechanics of Social VR, satisfaction and motion sickness. This study presented the development and preliminary usability of Social VR to enhance social interaction skills among children with ADHD. (2) Methods: The development process of the Social VR intervention was demonstrated. The Social VR intervention consisted of three scenarios, namely MTR, Campus and Market and Restaurant. In the usability study, 25 children with ADHD were recruited to test the Social VR during the preliminary usability stage of a clinical trial at preinclusion. The participants completed a survey about their experience of playing Social VR, satisfaction, and motion sickness. (3) Results: The participants indicated the three conditions had easy-to-follow instructions, were easy to pick up, and that they understood when the situations changed. The control and beauty of the graphics of Market and Restaurant were relatively lower compared with those of MTR and Campus. The three scenarios are applicable to children diagnosed with any subtype of ADHD. (4) Conclusion: The participants were satisfied with Social VR. Social VR was generally considered realistic and immersive. Further trials to assess the feasibility and efficacy were discussed. If proven effective, VR-based intervention can be an adjunctive approach to current multimodal training for children with ADHD.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"38 4","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139268873","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}
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