Pub Date : 2021-08-12DOI: 10.33423/jsis.v16i3.4448
{"title":"Technology Inhibition Modelling: Investigating the Flip Side of TAM","authors":"","doi":"10.33423/jsis.v16i3.4448","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4448","url":null,"abstract":"","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114613967","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 : 2021-08-12DOI: 10.33423/jsis.v16i3.4440
{"title":"Urban Development Change as a Response to Information Technology","authors":"","doi":"10.33423/jsis.v16i3.4440","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4440","url":null,"abstract":"","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"281 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121048697","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 : 2021-08-12DOI: 10.33423/jsis.v16i3.4450
{"title":"An Experiential Learning Project to Bridge the Gap Between Programming and CAD","authors":"","doi":"10.33423/jsis.v16i3.4450","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4450","url":null,"abstract":"","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116635053","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 : 2021-08-12DOI: 10.33423/jsis.v16i3.4442
{"title":"The Wedge Picking Model: A Theoretical Analysis of Graph Evolution Caused by Triadic Closure and Algorithmic Implications","authors":"","doi":"10.33423/jsis.v16i3.4442","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4442","url":null,"abstract":"","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129877380","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 : 2021-08-12DOI: 10.33423/jsis.v16i3.4444
Omar Nyabi
The novel coronavirus (COVID-19) pandemic has caused societal issues, economic and political tensions worldwide. This shows, once more, that dissemination of correct information based on scientific evidence together with a quick and concerted action is the key to build a sound capability for the management of biological emergencies. Here, we summarize the lessons learnedfrom our preparedness and intervention during (i) our deployment during the 2014-2016 Ebola outbreak in West Africa;(ii) our large-scale exercises from Horizon 2020 Security program where the focus is on handling intentional dispersion of infectious agents;and (iii) our fight against COVID-19: by the deployment of Biological Light Fieldable Laboratory for Emergencies (BLiFE mobile laboratory) in Turin and Novara, Piedmont Region, Italy. At the latter deployment, the ultimate goal was a large screening for COVID-19 prevalence in primo intervention individuals. It cannot be ignored that the COVID-19 pandemic is an ideal situation to whet our preparedness, coordination of response and risks monitoring in case of future biological threats or attacks.
{"title":"Deployment of a Mobile Laboratory for the Control and Monitoring of High-Consequence Infectious Diseases: An Illustration With the Ebola Virus, the Biowarfare Agents, and the COVID-19","authors":"Omar Nyabi","doi":"10.33423/jsis.v16i3.4444","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4444","url":null,"abstract":"The novel coronavirus (COVID-19) pandemic has caused societal issues, economic and political tensions worldwide. This shows, once more, that dissemination of correct information based on scientific evidence together with a quick and concerted action is the key to build a sound capability for the management of biological emergencies. Here, we summarize the lessons learnedfrom our preparedness and intervention during (i) our deployment during the 2014-2016 Ebola outbreak in West Africa;(ii) our large-scale exercises from Horizon 2020 Security program where the focus is on handling intentional dispersion of infectious agents;and (iii) our fight against COVID-19: by the deployment of Biological Light Fieldable Laboratory for Emergencies (BLiFE mobile laboratory) in Turin and Novara, Piedmont Region, Italy. At the latter deployment, the ultimate goal was a large screening for COVID-19 prevalence in primo intervention individuals. It cannot be ignored that the COVID-19 pandemic is an ideal situation to whet our preparedness, coordination of response and risks monitoring in case of future biological threats or attacks.","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128826812","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 : 2021-08-12DOI: 10.33423/jsis.v16i3.4443
{"title":"IoT Security: Problems and a Centralized Adaptive Approach as a Solution","authors":"","doi":"10.33423/jsis.v16i3.4443","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4443","url":null,"abstract":"","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127694221","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 : 2021-08-12DOI: 10.33423/jsis.v16i3.4441
{"title":"DIL - A Proof of Concept Study to Show the Efficacy of Conversational Agents for Heart Failure Patients","authors":"","doi":"10.33423/jsis.v16i3.4441","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4441","url":null,"abstract":"","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125954824","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 : 2021-08-12DOI: 10.33423/jsis.v16i3.4445
{"title":"Analyzing Student Learning in Sustainability: An International Exchange Case Study","authors":"","doi":"10.33423/jsis.v16i3.4445","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4445","url":null,"abstract":"","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126142836","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 : 2021-08-12DOI: 10.33423/jsis.v16i3.4447
A. E. Fernandez
Parameter identification of Unmanned Aerial Vehicles (UAV) is very helpful for understanding cause-effect relationships of physical phenomenon, investigating system performance and characteristics, fault diagnostics, control development/tuning, and more. Traditional ways of performing parameter identification involve establishing a mathematical model that describes the system’s behavior. The equations in the model contain parameters that are estimated indirectly from measured flight data. This parameter identification process requires knowledge of the physics involved. Also, it necessitates a careful consideration of the aircraft instrumentation for accurate measurements. It also requires careful design of the flight maneuvers to ensure thorough excitation of the flight dynamics involved. Finally, one must select a suitable identification method. The purpose of this paper is to show the application of machine learning for parameter identification of a UAV model. The machine learning algorithm does not require developing parameterized models; hence it is an equation-less identification method. To provide input to the system, a simulation model of the aircraft is generated. The parameters of the model can be modified in the simulation. The aircraft flight measurement data is obtained directly from the model as simulation outputs from a predetermined flight path. The data is submitted to a machine learning algorithm that can read and recognize the data. The machine learning algorithm is trained with a set of flight data that incorporates variations in the parameters to be identified. Finally, the algorithm is tested by feeding unknown flight data to predict the output. To achieve autonomous and consistent flights, a Software-In-the-Loop (SIL) simulation is constructed between X-Plane and Mission Planner. X-Plane is a realistic flight simulator where the UAV model is created, and flight physics are modeled. Mission Planner is the Ground Control Station (GCS) that generates and sends the flight commands to be executed in X-Plane. Several machine learning regression models are explored including linear
{"title":"UAV Parameter Estimation Through Machine Learning","authors":"A. E. Fernandez","doi":"10.33423/jsis.v16i3.4447","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4447","url":null,"abstract":"Parameter identification of Unmanned Aerial Vehicles (UAV) is very helpful for understanding cause-effect relationships of physical phenomenon, investigating system performance and characteristics, fault diagnostics, control development/tuning, and more. Traditional ways of performing parameter identification involve establishing a mathematical model that describes the system’s behavior. The equations in the model contain parameters that are estimated indirectly from measured flight data. This parameter identification process requires knowledge of the physics involved. Also, it necessitates a careful consideration of the aircraft instrumentation for accurate measurements. It also requires careful design of the flight maneuvers to ensure thorough excitation of the flight dynamics involved. Finally, one must select a suitable identification method. The purpose of this paper is to show the application of machine learning for parameter identification of a UAV model. The machine learning algorithm does not require developing parameterized models; hence it is an equation-less identification method. To provide input to the system, a simulation model of the aircraft is generated. The parameters of the model can be modified in the simulation. The aircraft flight measurement data is obtained directly from the model as simulation outputs from a predetermined flight path. The data is submitted to a machine learning algorithm that can read and recognize the data. The machine learning algorithm is trained with a set of flight data that incorporates variations in the parameters to be identified. Finally, the algorithm is tested by feeding unknown flight data to predict the output. To achieve autonomous and consistent flights, a Software-In-the-Loop (SIL) simulation is constructed between X-Plane and Mission Planner. X-Plane is a realistic flight simulator where the UAV model is created, and flight physics are modeled. Mission Planner is the Ground Control Station (GCS) that generates and sends the flight commands to be executed in X-Plane. Several machine learning regression models are explored including linear","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122225931","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 : 2021-08-12DOI: 10.33423/jsis.v16i3.4438
C. Hamilton
We address the issue of consumer privacy against the backdrop of the national priority of maintaining global leadership in artificial intelligence, the ongoing research in Artificial Cognitive Assistants, and the explosive growth in the development and application of Voice Activated Personal Assistants (VAPAs) such as Alexa and Siri, spurred on by the needs and opportunities arising out of the COVID-19 global pandemic. We first review the growth and associated legal issues of the of VAPAs in private homes, banks, healthcare, and education. We then summarize the policy guidelines for the development of VAPAs. Then, we classify these into five major categories with associated traits. We follow by developing a relative importance weight for each of the traits and categories;and suggest the establishment of a rating system related to the legal, ethical, functional, and social content policy guidelines established by these organizations. We suggest the establishment of an agency that will use the proposed rating system to inform customers of the implications of adopting a particular VAPA in their sphere.
{"title":"Developing a Measure of Social, Ethical, and Legal Content for Intelligent Cognitive Assistants","authors":"C. Hamilton","doi":"10.33423/jsis.v16i3.4438","DOIUrl":"https://doi.org/10.33423/jsis.v16i3.4438","url":null,"abstract":"We address the issue of consumer privacy against the backdrop of the national priority of maintaining global leadership in artificial intelligence, the ongoing research in Artificial Cognitive Assistants, and the explosive growth in the development and application of Voice Activated Personal Assistants (VAPAs) such as Alexa and Siri, spurred on by the needs and opportunities arising out of the COVID-19 global pandemic. We first review the growth and associated legal issues of the of VAPAs in private homes, banks, healthcare, and education. We then summarize the policy guidelines for the development of VAPAs. Then, we classify these into five major categories with associated traits. We follow by developing a relative importance weight for each of the traits and categories;and suggest the establishment of a rating system related to the legal, ethical, functional, and social content policy guidelines established by these organizations. We suggest the establishment of an agency that will use the proposed rating system to inform customers of the implications of adopting a particular VAPA in their sphere.","PeriodicalId":197350,"journal":{"name":"Journal of Strategic Innovation and Sustainability","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126954748","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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