{"title":"Using Extended Reality Technology in Science Education","authors":"Iman Cumberbatch, James Olatunji, S. Robila","doi":"10.1109/LISAT58403.2023.10179579","DOIUrl":"https://doi.org/10.1109/LISAT58403.2023.10179579","url":null,"abstract":"Across all scientific fields, the amount of data generated continues to grow exponentially, which creates both opportunities and challenges. Increased availability allows for new insights into phenomena and stimulates discovery. While traditional ways of interacting with data have focused mostly on flat displays, Extended Reality (XR) technologies have the potential to transform the way both research and education are done. They provide an immersive and interactive experience that allows participants to visualize and interact with data while also working collaboratively. In this paper, the research and development of immersive educational 3D visualization tools aligned with several science drivers including environmental science and sustainability and life sciences is described. Specifically, the development of two XR applications is discussed with emphasis on the innovative mechanisms introduced using head-mounted display technologies. Preliminary results from the prototype applications indicate that the use of the XR technologies significantly expands the visualization ability by integrating additional data sources and improving the user’s experience.","PeriodicalId":250536,"journal":{"name":"2023 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134444710","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}
S. Tulyakov, V. Mitin, Gyana R. Biswal, M. Yakimov, V. Tokranov, K. Sablon
{"title":"Object Recognition for Multiband Thermal Infrared Sensing","authors":"S. Tulyakov, V. Mitin, Gyana R. Biswal, M. Yakimov, V. Tokranov, K. Sablon","doi":"10.1109/LISAT58403.2023.10179497","DOIUrl":"https://doi.org/10.1109/LISAT58403.2023.10179497","url":null,"abstract":"The object recognition in thermal infrared spectrum can possibly be enhanced by capturing radiation signals in narrower subbands of this spectrum and performing recognition in color or multiple channel thermal infrared images. In this work, we investigate possible benefits of 2-channel thermal infrared images captured by commercial cameras. We performed experiments on our collected images containing persons and cars. Fusion of object recognition results obtained in different channels separately, gives some improvement over the use of a recognizer with single channel full spectrum images. We also present a proofof- concept design of adaptable thermal imager based on asymmetrically-doped double quantum well arrays, which can efficiently capture multiband images in the future.","PeriodicalId":250536,"journal":{"name":"2023 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121607973","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}