Pub Date : 2023-04-27DOI: 10.1109/SIEDS58326.2023.10137807
Julia C. Arnsberger, Amelia J. Jacquat, Michael J. O'Keefe.
Inefficient workflows in hospitals are a growing problem as the demand for medical services increases faster than an institution's ability to assist patient needs. To support the population’s medical demand, hospitals must optimize their current patient visit cycles to lower cycle times with the aim of increasing throughput. This study focuses on identifying inefficiencies of the patient visit cycle at the Orthopedic Clinic of Children’s National Hospital in Washington, DC. The project goal compromises three main research questions: (i) How can the patient visit cycle be modeled to demonstrate interdependencies between the cycle segments and segment actions? (ii) How can the cycle segment times be represented as mathematical probability distributions? and (iii) How can simulation of the patient visit cycle assess time effects of new policies? To investigate the questions, the team conducted interviews, performed observational site visits, collected data, fit data to distributions, and used the distributions to develop a simulation model in Simioä of the patient visit cycle. The team will apply policies to the simulation to assess the effects on the patient time in system and total throughput. From this analysis, suggestions can be made to the clinic. The proposed improvements include adjustments to labor schedules, patient arrivals, and provider rooms that optimize the workflow of the Orthopedic Clinic at the Children’s National Hospital.
{"title":"Time Saves Lives: Optimizing Pediatric Clinic Patient Visit Times","authors":"Julia C. Arnsberger, Amelia J. Jacquat, Michael J. O'Keefe.","doi":"10.1109/SIEDS58326.2023.10137807","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137807","url":null,"abstract":"Inefficient workflows in hospitals are a growing problem as the demand for medical services increases faster than an institution's ability to assist patient needs. To support the population’s medical demand, hospitals must optimize their current patient visit cycles to lower cycle times with the aim of increasing throughput. This study focuses on identifying inefficiencies of the patient visit cycle at the Orthopedic Clinic of Children’s National Hospital in Washington, DC. The project goal compromises three main research questions: (i) How can the patient visit cycle be modeled to demonstrate interdependencies between the cycle segments and segment actions? (ii) How can the cycle segment times be represented as mathematical probability distributions? and (iii) How can simulation of the patient visit cycle assess time effects of new policies? To investigate the questions, the team conducted interviews, performed observational site visits, collected data, fit data to distributions, and used the distributions to develop a simulation model in Simioä of the patient visit cycle. The team will apply policies to the simulation to assess the effects on the patient time in system and total throughput. From this analysis, suggestions can be made to the clinic. The proposed improvements include adjustments to labor schedules, patient arrivals, and provider rooms that optimize the workflow of the Orthopedic Clinic at the Children’s National Hospital.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130386696","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 : 2023-04-27DOI: 10.1109/SIEDS58326.2023.10137793
Marben S. Ramos, John Raymond B. Barajas, Pee Jay N. Gealone, Nico O. Aspra, Oliver M. Padua, Arpon T. Lucero
This paper details an approach to identify multiple-choice questions that are most effective in discriminating deficiencies in mathematics competencies of incoming first-year engineering students who are graduates of the K-12 program that was recently implemented in the Philippines. To achieve this objective, machine learning algorithms such as the k-Nearest Neighbors (kNN), Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), and Gradient Boosting Machines (GBM) were implemented. From a question bank containing 1,300 questions covering Algebra (A), Advanced Algebra (AA), Plane and Spherical Trigonometry (T), Analytic Geometry (AG), and Solid Mensuration (SM), five domain experts identified the suitability of the questions as part of a diagnostic examination in mathematics. Specifically, using a 5-point Likert scale (5 being the highest), the experts rated the suitability of each question to test the proficiency of a student in 23 mathematics competencies based on what is prescribed by the Commission on Higher Education (CHED). The collected survey data were then used to train the machine learning models, which extracted patterns to identify the questions that would be most suitable to test the mathematics competencies of incoming first-year engineering students. With a precision recall score of 99.90%, the LR model was selected as the best performing model and analysis of how the LR model predicts the labels through the use of shap values revealed that the preference was given towards questions which test student proficiency in foundational mathematics competencies like that of Algebra and Analytical Geometry. Overall, these findings provided a better understanding of the questions that are most effective in discriminating student deficiencies in mathematics subjects.
{"title":"Enhancing the Admissions Process for Engineering Baccalaureate Programs: A Machine Learning Approach to Developing a Valid and Reliable Examination","authors":"Marben S. Ramos, John Raymond B. Barajas, Pee Jay N. Gealone, Nico O. Aspra, Oliver M. Padua, Arpon T. Lucero","doi":"10.1109/SIEDS58326.2023.10137793","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137793","url":null,"abstract":"This paper details an approach to identify multiple-choice questions that are most effective in discriminating deficiencies in mathematics competencies of incoming first-year engineering students who are graduates of the K-12 program that was recently implemented in the Philippines. To achieve this objective, machine learning algorithms such as the k-Nearest Neighbors (kNN), Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), and Gradient Boosting Machines (GBM) were implemented. From a question bank containing 1,300 questions covering Algebra (A), Advanced Algebra (AA), Plane and Spherical Trigonometry (T), Analytic Geometry (AG), and Solid Mensuration (SM), five domain experts identified the suitability of the questions as part of a diagnostic examination in mathematics. Specifically, using a 5-point Likert scale (5 being the highest), the experts rated the suitability of each question to test the proficiency of a student in 23 mathematics competencies based on what is prescribed by the Commission on Higher Education (CHED). The collected survey data were then used to train the machine learning models, which extracted patterns to identify the questions that would be most suitable to test the mathematics competencies of incoming first-year engineering students. With a precision recall score of 99.90%, the LR model was selected as the best performing model and analysis of how the LR model predicts the labels through the use of shap values revealed that the preference was given towards questions which test student proficiency in foundational mathematics competencies like that of Algebra and Analytical Geometry. Overall, these findings provided a better understanding of the questions that are most effective in discriminating student deficiencies in mathematics subjects.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131187298","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 : 2023-04-27DOI: 10.1109/SIEDS58326.2023.10137841
Rydia R. Weiland, Min Ji Kim, Elizabeth Phillips
Humanlikeness is a quality possessed by social robots tasked for human interaction. This quality has remained ambiguously defined in literature, despite the notion that social robots with humanlike qualities tend to be better received by users. Currently, the Anthropomorphic Robot (ABOT) Database serves as a validated resource for robot designers and researchers to reference a robot’s humanlikeness score. However, one of the limitations of this database is that the scores are based on 2D images of the robots, rather than based on the actual embodied robots. To combat this limitation, the current study aims to research if having the robots in a 3D Virtual Reality (VR) space makes a difference in the humanlikeness scores. This current study focuses on collecting the humanlikeness scores of robots in VR, and further aims to compare the scores with the scores that are currently listed in the ABOT Database. To accomplish this, 16 robot models were put in a VR environment where participants rated the humanlikeness of each robot. All the robots were previously rated in the current ABOT database so the scores from the VR environment and the ABOT database could be compared. Results from 11 participants show no significant difference between 2D humanlikeness scores and 3D/VR humanlikeness scores. The results of this paper will validate the progression of continuing to build a 3D visualized database of humanlike robots while providing further context for how perceptions of humanlikeness differ throughout 2 and 3-dimensional spaces.
{"title":"The Effect of 3D/VR on the Perception of Robot Humanlikeness *","authors":"Rydia R. Weiland, Min Ji Kim, Elizabeth Phillips","doi":"10.1109/SIEDS58326.2023.10137841","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137841","url":null,"abstract":"Humanlikeness is a quality possessed by social robots tasked for human interaction. This quality has remained ambiguously defined in literature, despite the notion that social robots with humanlike qualities tend to be better received by users. Currently, the Anthropomorphic Robot (ABOT) Database serves as a validated resource for robot designers and researchers to reference a robot’s humanlikeness score. However, one of the limitations of this database is that the scores are based on 2D images of the robots, rather than based on the actual embodied robots. To combat this limitation, the current study aims to research if having the robots in a 3D Virtual Reality (VR) space makes a difference in the humanlikeness scores. This current study focuses on collecting the humanlikeness scores of robots in VR, and further aims to compare the scores with the scores that are currently listed in the ABOT Database. To accomplish this, 16 robot models were put in a VR environment where participants rated the humanlikeness of each robot. All the robots were previously rated in the current ABOT database so the scores from the VR environment and the ABOT database could be compared. Results from 11 participants show no significant difference between 2D humanlikeness scores and 3D/VR humanlikeness scores. The results of this paper will validate the progression of continuing to build a 3D visualized database of humanlike robots while providing further context for how perceptions of humanlikeness differ throughout 2 and 3-dimensional spaces.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117038719","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 : 2023-04-27DOI: 10.1109/SIEDS58326.2023.10137908
Ekaterina M. Forkin, Carter A. Paulen, Matthew J. Swierczewski, Tanushri Roy, T. D. Costello, Davis C. Loose, Joi Y. Williams, David L. Slutzky, Thomas L. Polmateer, Karen Jackson, Daniel C. Hendrickson, J. Lambert
Container ports face the decision of investment into a variety of emerging technologies, including electric vehicles, autonomous equipment, and hydrogen-based power. This research paper presents a simulation-based optimization study of a port using simulation software to reduce carbon emissions and improve efficiency of operations of a maritime container port. Through capacity planning and electrification modeling, the port was provided with recommendations that will be used for 3-5 year-out planning focused on decreasing emissions and improving energy utilization. Research focused on reduction of operational emissions, existing simulations of ports, and emerging technologies including electric vehicles, liquid natural gas, hydrogen power. The methodology included modeling smaller sections of the port through simulation software. Use cases were extended to various forms of equipment and vehicles.Carbon emissions were also represented. These models allowed for the simulation of the effect of the changes in equipment and observation of resulting financial and time costs. Recommendations for the number of chargers and the number of additional vehicles to be purchased were also discussed. Use cases also allowed for the identification of beneficial expansion into electric vehicles according to fuel times and maintenance requirements, with consideration of financial constraints. Preliminary results revealed positive potential, both environmentally and economically, in regard to the transition towards electrification of heavy-duty port machinery and away from diesel-powered equipment. The findings of this study highlight the prospect of using simulation-based optimization to improve the sustainability of operations of the maritime container port and to reduce their overall carbon footprint.
{"title":"Capacity Planning and Investment for Electrification of Maritime Container Ports","authors":"Ekaterina M. Forkin, Carter A. Paulen, Matthew J. Swierczewski, Tanushri Roy, T. D. Costello, Davis C. Loose, Joi Y. Williams, David L. Slutzky, Thomas L. Polmateer, Karen Jackson, Daniel C. Hendrickson, J. Lambert","doi":"10.1109/SIEDS58326.2023.10137908","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137908","url":null,"abstract":"Container ports face the decision of investment into a variety of emerging technologies, including electric vehicles, autonomous equipment, and hydrogen-based power. This research paper presents a simulation-based optimization study of a port using simulation software to reduce carbon emissions and improve efficiency of operations of a maritime container port. Through capacity planning and electrification modeling, the port was provided with recommendations that will be used for 3-5 year-out planning focused on decreasing emissions and improving energy utilization. Research focused on reduction of operational emissions, existing simulations of ports, and emerging technologies including electric vehicles, liquid natural gas, hydrogen power. The methodology included modeling smaller sections of the port through simulation software. Use cases were extended to various forms of equipment and vehicles.Carbon emissions were also represented. These models allowed for the simulation of the effect of the changes in equipment and observation of resulting financial and time costs. Recommendations for the number of chargers and the number of additional vehicles to be purchased were also discussed. Use cases also allowed for the identification of beneficial expansion into electric vehicles according to fuel times and maintenance requirements, with consideration of financial constraints. Preliminary results revealed positive potential, both environmentally and economically, in regard to the transition towards electrification of heavy-duty port machinery and away from diesel-powered equipment. The findings of this study highlight the prospect of using simulation-based optimization to improve the sustainability of operations of the maritime container port and to reduce their overall carbon footprint.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131060005","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 : 2023-04-27DOI: 10.1109/SIEDS58326.2023.10137798
J. Barajas
This paper presents a multi-criterion decision analysis approach to developing a procurement capacity index for local government units (LGUs) in the Philippines. The index serves to assess the resilience of LGUs in times of crisis, particularly in the context of the COVID-19 pandemic. This study utilized two open datasets published by the Philippine government from January to June 2020, and identified five criteria for the procurement capacity index: total approved budget of the contract, internal revenue allotment, number of awarded tenders, number of tenders posted, and fund utilization rate. This study then employed the criterion impact loss (CILOS) method to determine the weight vectors of the identified set of criteria, and calculate the index as a weighted sum based on these vectors. This study found that the fund utilization rate and internal revenue allotment are the two most important criteria for determining the capacity of an LGU to secure goods or services during a crisis such as the pandemic. This insight is consistent with observations drawn from use cases in the US, UK, and Canada as revealed in reviewed literature. Results also revealed that LGUs can be categorized into three clusters based on their procurement capacities: low, medium, and high. Moreover, the developed index facilitated the ranking of LGUs according to their procurement capacity, revealing that LGUs located in Regions II, III, VI, VII, VIII, and X have insufficient budget allocation, thus strongly suggesting urgent intervention from the national government. Overall, the developed index can serve as a valuable decision aid tool to assist the government in identifying LGUs that need additional support to procure resources or services required to mitigate the consequences of a crisis.
{"title":"Uncovering the Most Vulnerable in Times of Crisis: Analyzing Procurement Capacity Index with Multi-Criteria Decision-Analysis","authors":"J. Barajas","doi":"10.1109/SIEDS58326.2023.10137798","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137798","url":null,"abstract":"This paper presents a multi-criterion decision analysis approach to developing a procurement capacity index for local government units (LGUs) in the Philippines. The index serves to assess the resilience of LGUs in times of crisis, particularly in the context of the COVID-19 pandemic. This study utilized two open datasets published by the Philippine government from January to June 2020, and identified five criteria for the procurement capacity index: total approved budget of the contract, internal revenue allotment, number of awarded tenders, number of tenders posted, and fund utilization rate. This study then employed the criterion impact loss (CILOS) method to determine the weight vectors of the identified set of criteria, and calculate the index as a weighted sum based on these vectors. This study found that the fund utilization rate and internal revenue allotment are the two most important criteria for determining the capacity of an LGU to secure goods or services during a crisis such as the pandemic. This insight is consistent with observations drawn from use cases in the US, UK, and Canada as revealed in reviewed literature. Results also revealed that LGUs can be categorized into three clusters based on their procurement capacities: low, medium, and high. Moreover, the developed index facilitated the ranking of LGUs according to their procurement capacity, revealing that LGUs located in Regions II, III, VI, VII, VIII, and X have insufficient budget allocation, thus strongly suggesting urgent intervention from the national government. Overall, the developed index can serve as a valuable decision aid tool to assist the government in identifying LGUs that need additional support to procure resources or services required to mitigate the consequences of a crisis.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115919525","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 : 2023-04-27DOI: 10.1109/SIEDS58326.2023.10137847
Atefe Sedaghat, M. Kang, Maryam Hamidi
Massive vessel trajectory data can be obtained from marine Automatic Identification Systems (AIS) to extract information about water traffic. To efficiently collect and process such a huge amount of data special methods are needed. This study designs a new system for collecting and processing AIS data in a real-time manner. The proposed system not only compresses vessel data while keeping useful information but also adds more attributes to raw trajectory data. The additional attributes include trip id, trip origin/destination, traffic density, and traffic flow. At first, this study presents a dynamic Extract, Transform, and Load (ETL) pipeline that collects AIS messages from vessels, processes those raw data, and loads the processed data in a central database. An optimized algorithm is developed that can process millions of records as fast as possible and send the processed data to production. Next, a user interface is developed to quantify traffic conditions and visualize them in graphs and maps. Finally, Gulf Intercoastal Waterway (GIWW) is considered as study area, where historical and real-time AIS data located in GIWW were collected to test the functionality of the method.
{"title":"A Heuristic ETL Process to Dynamically Separate and Compress AIS Data","authors":"Atefe Sedaghat, M. Kang, Maryam Hamidi","doi":"10.1109/SIEDS58326.2023.10137847","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137847","url":null,"abstract":"Massive vessel trajectory data can be obtained from marine Automatic Identification Systems (AIS) to extract information about water traffic. To efficiently collect and process such a huge amount of data special methods are needed. This study designs a new system for collecting and processing AIS data in a real-time manner. The proposed system not only compresses vessel data while keeping useful information but also adds more attributes to raw trajectory data. The additional attributes include trip id, trip origin/destination, traffic density, and traffic flow. At first, this study presents a dynamic Extract, Transform, and Load (ETL) pipeline that collects AIS messages from vessels, processes those raw data, and loads the processed data in a central database. An optimized algorithm is developed that can process millions of records as fast as possible and send the processed data to production. Next, a user interface is developed to quantify traffic conditions and visualize them in graphs and maps. Finally, Gulf Intercoastal Waterway (GIWW) is considered as study area, where historical and real-time AIS data located in GIWW were collected to test the functionality of the method.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130329945","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 : 2023-04-27DOI: 10.1109/SIEDS58326.2023.10137902
Elizabeth Breslin, Alyssa Freedman, Cutter Huston, Genesis Marrero-Garcia, Thomas Mossburg
The Russian invasion into Ukraine impacted global trade and economic networks a year after the COVID-19 pandemic did the same. The effects of the war are far reaching; among the areas affected are global food supply and prices, international export controls, energy supply, and the environment.The focus of the technical report is to understand the impact that a military invasion has on a major global food exporter and the countries that it supplies. Ramifications of the pandemic, extreme weather, and the energy crisis laid the groundwork for surging food prices, and Russia’s invasion of Ukraine exacerbated this issue. The decrease in the production capabilities of Ukraine as a result of the conflict with Russia caused massive disruptions in the global supply chain.The technical report will use the Russian invasion into Ukraine as a case study, compiling datasets on topics such as changes in global GDP, wheat and edible oil prices, oil and natural gas exports, and research about Ukraine’s crop production and food supply, to understand how potential future military aggression could impact global supply chains.
{"title":"Ukraine Food Crisis: Understanding the Impacts of War on the Global Supply Chain and Applying to Future Events","authors":"Elizabeth Breslin, Alyssa Freedman, Cutter Huston, Genesis Marrero-Garcia, Thomas Mossburg","doi":"10.1109/SIEDS58326.2023.10137902","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137902","url":null,"abstract":"The Russian invasion into Ukraine impacted global trade and economic networks a year after the COVID-19 pandemic did the same. The effects of the war are far reaching; among the areas affected are global food supply and prices, international export controls, energy supply, and the environment.The focus of the technical report is to understand the impact that a military invasion has on a major global food exporter and the countries that it supplies. Ramifications of the pandemic, extreme weather, and the energy crisis laid the groundwork for surging food prices, and Russia’s invasion of Ukraine exacerbated this issue. The decrease in the production capabilities of Ukraine as a result of the conflict with Russia caused massive disruptions in the global supply chain.The technical report will use the Russian invasion into Ukraine as a case study, compiling datasets on topics such as changes in global GDP, wheat and edible oil prices, oil and natural gas exports, and research about Ukraine’s crop production and food supply, to understand how potential future military aggression could impact global supply chains.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127635866","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 : 2023-04-27DOI: 10.1109/SIEDS58326.2023.10137809
Addison B. Bright, Jenna E. Cotter, N. Tenhundfeld
Automated systems, or systems that execute, either partially or fully, a function previously completed by a human operator, have become widely incorporated in society today. As the use of automated systems becomes more prevalent, over-trust and subsequent over-reliance on those systems can occur and users can become complacent in monitoring. To ensure the user is correctly monitoring a system, many companies have incorporated monitoring checks to increase situational awareness (SA) and performance; however, there has not been much research evaluating the consequences of repeated monitoring checks. These checks could have consequences that negatively affect the user’s trust, such as the "cry-wolf" effect, because the user is repeatedly reminded of imperfections in the system resulting in disuse of the system. In contrast, these checks could help calibrate trust, increase SA and performance, and promote appropriate use of the system. Understanding these consequences is essential in evaluating a user’s trust in the system. To test this, an experiment was designed that explored the impact of monitoring checks and reliability on the level of trust individuals report in the system. In this study, the 60s and 90s frequency of monitoring check conditions had the highest reported trust. However, not all significant results were consistent with previous knowledge of the impacts of reliability and the "cry-wolf" effect. The general pattern of results suggests that there is merit in highly reliable systems especially over intermediately reliable systems. Additionally, the results suggest a complex relationship between trust and the frequency of monitoring checks especially at the intermediate frequency groups.
{"title":"Degradations of Trust in Automation Associated with Repeated Monitoring Checks","authors":"Addison B. Bright, Jenna E. Cotter, N. Tenhundfeld","doi":"10.1109/SIEDS58326.2023.10137809","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137809","url":null,"abstract":"Automated systems, or systems that execute, either partially or fully, a function previously completed by a human operator, have become widely incorporated in society today. As the use of automated systems becomes more prevalent, over-trust and subsequent over-reliance on those systems can occur and users can become complacent in monitoring. To ensure the user is correctly monitoring a system, many companies have incorporated monitoring checks to increase situational awareness (SA) and performance; however, there has not been much research evaluating the consequences of repeated monitoring checks. These checks could have consequences that negatively affect the user’s trust, such as the \"cry-wolf\" effect, because the user is repeatedly reminded of imperfections in the system resulting in disuse of the system. In contrast, these checks could help calibrate trust, increase SA and performance, and promote appropriate use of the system. Understanding these consequences is essential in evaluating a user’s trust in the system. To test this, an experiment was designed that explored the impact of monitoring checks and reliability on the level of trust individuals report in the system. In this study, the 60s and 90s frequency of monitoring check conditions had the highest reported trust. However, not all significant results were consistent with previous knowledge of the impacts of reliability and the \"cry-wolf\" effect. The general pattern of results suggests that there is merit in highly reliable systems especially over intermediately reliable systems. Additionally, the results suggest a complex relationship between trust and the frequency of monitoring checks especially at the intermediate frequency groups.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134013855","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 : 2023-04-19DOI: 10.1109/SIEDS58326.2023.10137778
Hosam Alamleh, A. A. AlQahtani, Baker Al Smadi
The rise of smartphones has led to a significant increase in the usage of mobile payments. Mobile payments allow individuals to access financial resources and make transactions through their mobile devices while on the go. However, the current mobile payment systems were designed to align with traditional payment structures, which limits the full potential of smartphones, including their security features. This has become a major concern in the rapidly growing mobile payment market. To address these security concerns,in this paper we propose new mobile payment architecture. This architecture leverages the advanced capabilities of modern smartphones to verify various aspects of a payment, such as funds, biometrics, location, and others. The proposed system aims to guarantee the legitimacy of transactions and protect against identity theft by verifying multiple elements of a payment. The security of mobile payment systems is crucial, given the rapid growth of the market. Evaluating mobile payment systems based on their authentication, encryption, and fraud detection capabilities is of utmost importance. The proposed architecture provides a secure mobile payment solution that enhances the overall payment experience by taking advantage of the advanced capabilities of modern smartphones. This will not only improve the security of mobile payments but also offer a more user-friendly payment experience for consumers.
{"title":"Secure Mobile Payment Architecture Enabling Multi-factor Authentication","authors":"Hosam Alamleh, A. A. AlQahtani, Baker Al Smadi","doi":"10.1109/SIEDS58326.2023.10137778","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137778","url":null,"abstract":"The rise of smartphones has led to a significant increase in the usage of mobile payments. Mobile payments allow individuals to access financial resources and make transactions through their mobile devices while on the go. However, the current mobile payment systems were designed to align with traditional payment structures, which limits the full potential of smartphones, including their security features. This has become a major concern in the rapidly growing mobile payment market. To address these security concerns,in this paper we propose new mobile payment architecture. This architecture leverages the advanced capabilities of modern smartphones to verify various aspects of a payment, such as funds, biometrics, location, and others. The proposed system aims to guarantee the legitimacy of transactions and protect against identity theft by verifying multiple elements of a payment. The security of mobile payment systems is crucial, given the rapid growth of the market. Evaluating mobile payment systems based on their authentication, encryption, and fraud detection capabilities is of utmost importance. The proposed architecture provides a secure mobile payment solution that enhances the overall payment experience by taking advantage of the advanced capabilities of modern smartphones. This will not only improve the security of mobile payments but also offer a more user-friendly payment experience for consumers.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130607361","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 : 2023-04-14DOI: 10.1109/SIEDS58326.2023.10137850
Aram Bahrini, Mohammadsadra Khamoshifar, H. Abbasimehr, R. Riggs, Maryam Esmaeili, Rastin Mastali Majdabadkohne, Morteza Pasehvar
Developed by OpenAI, ChatGPT (Conditional Generative Pre-trained Transformer) is an artificial intelligence technology that is fine-tuned using supervised machine learning and reinforcement learning techniques, allowing a computer to generate natural language conversation fully autonomously. ChatGPT is built on the transformer architecture and trained on millions of conversations from various sources. The system combines the power of pre-trained deep learning models with a programmability layer to provide a strong base for generating natural language conversations. In this study, after reviewing the existing literature, we examine the applications, opportunities, and threats of ChatGPT in 10 main domains, providing detailed examples for the business and industry as well as education. We also conducted an experimental study, checking the effectiveness and comparing the performances of GPT-3.5 and GPT-4, and found that the latter performs significantly better. Despite its exceptional ability to generate natural-sounding responses, the authors believe that ChatGPT does not possess the same level of understanding, empathy, and creativity as a human and cannot fully replace them in most situations.
{"title":"ChatGPT: Applications, Opportunities, and Threats","authors":"Aram Bahrini, Mohammadsadra Khamoshifar, H. Abbasimehr, R. Riggs, Maryam Esmaeili, Rastin Mastali Majdabadkohne, Morteza Pasehvar","doi":"10.1109/SIEDS58326.2023.10137850","DOIUrl":"https://doi.org/10.1109/SIEDS58326.2023.10137850","url":null,"abstract":"Developed by OpenAI, ChatGPT (Conditional Generative Pre-trained Transformer) is an artificial intelligence technology that is fine-tuned using supervised machine learning and reinforcement learning techniques, allowing a computer to generate natural language conversation fully autonomously. ChatGPT is built on the transformer architecture and trained on millions of conversations from various sources. The system combines the power of pre-trained deep learning models with a programmability layer to provide a strong base for generating natural language conversations. In this study, after reviewing the existing literature, we examine the applications, opportunities, and threats of ChatGPT in 10 main domains, providing detailed examples for the business and industry as well as education. We also conducted an experimental study, checking the effectiveness and comparing the performances of GPT-3.5 and GPT-4, and found that the latter performs significantly better. Despite its exceptional ability to generate natural-sounding responses, the authors believe that ChatGPT does not possess the same level of understanding, empathy, and creativity as a human and cannot fully replace them in most situations.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131920543","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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