This abstract outlines two significant innovations in AI and cybersecurity education within the "Deep HoriXons" 3D virtual campus, addressing the urgent need for skilled professionals in these domains. First, the paper introduces "Deep HoriXons," an immersive 3D virtual learning environment designed to democratize and enhance the educational experience for AI and cybersecurity. This innovation is notable for its global accessibility and ability to simulate real-world scenarios, providing an interactive platform for experiential learning, which is a marked departure from traditional educational models. The second innovation discussed is the strategic integration of ChatGPT as a digital educator and tutor within this virtual environment. ChatGPT's role is pivotal in offering tailored, real-time educational support, making complex AI and cybersecurity concepts more accessible and engaging for learners. This application of ChatGPT is an innovation worth noting for its ability to adapt to individual learning styles, provide interactive scenario-based learning, and support a deeper understanding of technical subjects through dynamic, responsive interaction. Together, these innovations represent a significant advancement in the field of AI and cybersecurity education, addressing the critical talent shortage by making high-quality, interactive learning experiences accessible on a global scale. The paper highlights the importance of these innovations in creating a skilled workforce capable of tackling the evolving challenges in AI and cybersecurity, underscoring the need for ongoing research and development in this area.
{"title":"Deep HoriXons: 3D virtual generative AI assisted campus for deep learning AI and cybersecurity","authors":"Robert Williams","doi":"10.1117/12.3011374","DOIUrl":"https://doi.org/10.1117/12.3011374","url":null,"abstract":"This abstract outlines two significant innovations in AI and cybersecurity education within the \"Deep HoriXons\" 3D virtual campus, addressing the urgent need for skilled professionals in these domains. First, the paper introduces \"Deep HoriXons,\" an immersive 3D virtual learning environment designed to democratize and enhance the educational experience for AI and cybersecurity. This innovation is notable for its global accessibility and ability to simulate real-world scenarios, providing an interactive platform for experiential learning, which is a marked departure from traditional educational models. The second innovation discussed is the strategic integration of ChatGPT as a digital educator and tutor within this virtual environment. ChatGPT's role is pivotal in offering tailored, real-time educational support, making complex AI and cybersecurity concepts more accessible and engaging for learners. This application of ChatGPT is an innovation worth noting for its ability to adapt to individual learning styles, provide interactive scenario-based learning, and support a deeper understanding of technical subjects through dynamic, responsive interaction. Together, these innovations represent a significant advancement in the field of AI and cybersecurity education, addressing the critical talent shortage by making high-quality, interactive learning experiences accessible on a global scale. The paper highlights the importance of these innovations in creating a skilled workforce capable of tackling the evolving challenges in AI and cybersecurity, underscoring the need for ongoing research and development in this area.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"63 1‐2","pages":"130580P - 130580P-13"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378127","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. Y. Alaba, Jack H. Prior, Chiranjibi Shah, M. M. Nabi, John E. Ball, Robert J. Moorhead, Matthew Campbell, Farron Wallace, Matthew D. Grossi
Accurate recognition of multiple fish species is essential in marine ecology and fisheries. Precisely classifying and tracking these species enriches our comprehension of their movement patterns and empowers us to create precise maps of species-specific territories. Such profound insights are pivotal in conserving endangered species, promoting sustainable fishing practices, and preserving marine ecosystems’ overall health and equilibrium. To partially address these needs, we present a proposed model that combines YOLOv8 for object detection with ByteTrack for tracking. YOLOv8’s oriented bounding boxes help to improve object detection across angles, while ByteTrack’s robustness in various scenarios makes it ideal for real-time tracking. Experimental results using the SEAMAPD21 dataset show the model’s effectiveness, with YOLOv8n being the lightweight yet modestly accurate option, suitable for constrained environments. The study also identifies challenges in fish tracking, such as lighting variations and fish appearance changes, and proposes solutions for future research. Overall, the proposed model shows promising fish tracking and counting results, which is essential for monitoring marine life.
{"title":"Multifish tracking for marine biodiversity monitoring","authors":"S. Y. Alaba, Jack H. Prior, Chiranjibi Shah, M. M. Nabi, John E. Ball, Robert J. Moorhead, Matthew Campbell, Farron Wallace, Matthew D. Grossi","doi":"10.1117/12.3013503","DOIUrl":"https://doi.org/10.1117/12.3013503","url":null,"abstract":"Accurate recognition of multiple fish species is essential in marine ecology and fisheries. Precisely classifying and tracking these species enriches our comprehension of their movement patterns and empowers us to create precise maps of species-specific territories. Such profound insights are pivotal in conserving endangered species, promoting sustainable fishing practices, and preserving marine ecosystems’ overall health and equilibrium. To partially address these needs, we present a proposed model that combines YOLOv8 for object detection with ByteTrack for tracking. YOLOv8’s oriented bounding boxes help to improve object detection across angles, while ByteTrack’s robustness in various scenarios makes it ideal for real-time tracking. Experimental results using the SEAMAPD21 dataset show the model’s effectiveness, with YOLOv8n being the lightweight yet modestly accurate option, suitable for constrained environments. The study also identifies challenges in fish tracking, such as lighting variations and fish appearance changes, and proposes solutions for future research. Overall, the proposed model shows promising fish tracking and counting results, which is essential for monitoring marine life.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"6 11","pages":"130610E - 130610E-7"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378676","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}
Jesse Brown, Robert Benson, Eric Bower, Jeffry Santman, Leon Desmarais, Rick Holasek, Duncan Spaulding
Corning Incorporated has leveraged its industry leading space based hyperspectral technology to create an advanced Low Earth Orbit (LEO) Satellite Payload. We outline the specifications, performance, and capabilities of this new standard in LEO Hyperspectral Imaging (HSI). Corning’s new product platform is capable of ⪅8m GSD imaging across the 400nm-2500nm spectral band with high dispersion. It has onboard computing, storage, and processing capabilities which enhance its exceptional optical and sensor performance. Corning’s design exceeds the launch stress requirements of standard LEO Transporter vehicles, such as the SpaceX Falcon-9, and has been proven on multiple successful LEO missions. The product platform contains a flexible electro-mechanical interface design suitable for a variety of host bus platforms and functions.
{"title":"Corning's standard low earth orbit (LEO) hyperspectral imaging platform","authors":"Jesse Brown, Robert Benson, Eric Bower, Jeffry Santman, Leon Desmarais, Rick Holasek, Duncan Spaulding","doi":"10.1117/12.3013430","DOIUrl":"https://doi.org/10.1117/12.3013430","url":null,"abstract":"Corning Incorporated has leveraged its industry leading space based hyperspectral technology to create an advanced Low Earth Orbit (LEO) Satellite Payload. We outline the specifications, performance, and capabilities of this new standard in LEO Hyperspectral Imaging (HSI). Corning’s new product platform is capable of ⪅8m GSD imaging across the 400nm-2500nm spectral band with high dispersion. It has onboard computing, storage, and processing capabilities which enhance its exceptional optical and sensor performance. Corning’s design exceeds the launch stress requirements of standard LEO Transporter vehicles, such as the SpaceX Falcon-9, and has been proven on multiple successful LEO missions. The product platform contains a flexible electro-mechanical interface design suitable for a variety of host bus platforms and functions.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"30 28","pages":"1306204 - 1306204-6"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379631","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}
Lulu Al Arfaj, Joon Suk Lee, Joseph A. Shelton, Zeynep Ertem, Thi Tran, Yu Chen
The widespread misinformation in the digital age has emerged as a significant societal challenge with far-reaching implications. While concerns about the threats of misinformation on the mental health of individuals have garnered attention, there remains a critical gap in our understanding of how misinformation uniquely affects the young generation, particularly those belonging to underrepresented groups. Emerging evidence suggests that underrepresented groups among the young generation, including marginalized communities, ethnic minorities, and socioeconomically disadvantaged individuals, often face heightened vulnerabilities to the harmful effects of misinformation. These groups encounter a unique intersection of social, economic, and cultural factors, exacerbating their susceptibility to false or harmful information. Understanding the differential impacts of misinformation within these communities is vital for creating targeted interventions and support mechanisms. With a long-term goal of offering a thorough understanding of the current state of knowledge in this critical area, this paper reports a preliminary literature review examining how false information about vaccines spreads on social media, creating a huge problem called an “infodemic” and revealing how misinformation against vaccines gets shared in social media and why people believe them. In addition, a small-scale case study is conducted based on the dataset collected by the team.
{"title":"The impact of misinformation on the health of underrepresented youth during public health crises: a preliminary study","authors":"Lulu Al Arfaj, Joon Suk Lee, Joseph A. Shelton, Zeynep Ertem, Thi Tran, Yu Chen","doi":"10.1117/12.3013295","DOIUrl":"https://doi.org/10.1117/12.3013295","url":null,"abstract":"The widespread misinformation in the digital age has emerged as a significant societal challenge with far-reaching implications. While concerns about the threats of misinformation on the mental health of individuals have garnered attention, there remains a critical gap in our understanding of how misinformation uniquely affects the young generation, particularly those belonging to underrepresented groups. Emerging evidence suggests that underrepresented groups among the young generation, including marginalized communities, ethnic minorities, and socioeconomically disadvantaged individuals, often face heightened vulnerabilities to the harmful effects of misinformation. These groups encounter a unique intersection of social, economic, and cultural factors, exacerbating their susceptibility to false or harmful information. Understanding the differential impacts of misinformation within these communities is vital for creating targeted interventions and support mechanisms. With a long-term goal of offering a thorough understanding of the current state of knowledge in this critical area, this paper reports a preliminary literature review examining how false information about vaccines spreads on social media, creating a huge problem called an “infodemic” and revealing how misinformation against vaccines gets shared in social media and why people believe them. In addition, a small-scale case study is conducted based on the dataset collected by the team.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"14 20","pages":"130580Y - 130580Y-17"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380134","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}
In previous work we have introduced our (proposed) architecture that connects a ‘Real’ and ‘Imaginary’ Neural Network. The ‘Real’ portion is represented by exploiting Striatal Beat Frequencies in an EEG with the patented Single-Period Single-Frequency (SPSF) method and the ‘Imaginary’ is represented by a convolutional neural network transformed into bi-directional associative memory matrices. We demonstrated that we could interconnect, i.e., bridge, the intermediate layers of two broken CNNs both of which were trained for object detection and still make a good prediction. In this work we will use a dual sensory CNN implementation of speech and object detection and we will incorporate Neural Decoding into the EEG SPSF method to emulate how to circumvent the broken neural networks in a human-computer interface situation.
{"title":"Circumventing broken neural networks, both real and imaginary, through SPSF-based neural decoding and interconnected associative memory matrices","authors":"James P. LaRue","doi":"10.1117/12.3014016","DOIUrl":"https://doi.org/10.1117/12.3014016","url":null,"abstract":"In previous work we have introduced our (proposed) architecture that connects a ‘Real’ and ‘Imaginary’ Neural Network. The ‘Real’ portion is represented by exploiting Striatal Beat Frequencies in an EEG with the patented Single-Period Single-Frequency (SPSF) method and the ‘Imaginary’ is represented by a convolutional neural network transformed into bi-directional associative memory matrices. We demonstrated that we could interconnect, i.e., bridge, the intermediate layers of two broken CNNs both of which were trained for object detection and still make a good prediction. In this work we will use a dual sensory CNN implementation of speech and object detection and we will incorporate Neural Decoding into the EEG SPSF method to emulate how to circumvent the broken neural networks in a human-computer interface situation.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"5 3","pages":"130580E - 130580E-14"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380267","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}
Feifei Tao, K. Chao, Jianwei Qin, Moon Kim, Thomas Burks
Celiac disease is a serious gluten-sensitive autoimmune disease of the small intestine affecting genetically susceptible individuals worldwide. A strict, lifelong gluten-free diet is the only treatment. Currently, the most commonly used methods for gluten test are based upon enzyme-linked immunosorbent assay, which is sample-destructive, and requires cumbersome processing procedures, and therefore are not suitable for high-throughput real-time screening detection of gluten in foods. In this study, a Fourier-Transform Infrared (FT-IR) spectroscopy-based approach was proposed for authentication of gluten-free flour. Three chemical standards including gliadin, gluten, and starch from wheat and 62 different types of flour products were scanned by FT-IR spectroscopy over the wavenumber range of 4000 and 400 cm-1. Notable absorbance differences were observed between the chemical standards of gliadin and gluten and starch from wheat over the wavenumber range of 1800-450 cm-1. The mean absorbance profiles of gluten-free and non-gluten free categories of flour demonstrated varying spectral characteristics between 1800 and 1500 cm-1. The Principal Component Analysis (PCA)- Linear Discriminant Analysis (LDA) models built upon the original absorbance of flour between 1800 and 1500 cm-1 achieved overall prediction accuracies of at least 95.7%. The potential of FT-IR technique in identifying and authenticating gluten-free flour was demonstrated.
{"title":"Authentication of gluten-free flour by Fourier-transform infrared spectroscopic technique","authors":"Feifei Tao, K. Chao, Jianwei Qin, Moon Kim, Thomas Burks","doi":"10.1117/12.3012663","DOIUrl":"https://doi.org/10.1117/12.3012663","url":null,"abstract":"Celiac disease is a serious gluten-sensitive autoimmune disease of the small intestine affecting genetically susceptible individuals worldwide. A strict, lifelong gluten-free diet is the only treatment. Currently, the most commonly used methods for gluten test are based upon enzyme-linked immunosorbent assay, which is sample-destructive, and requires cumbersome processing procedures, and therefore are not suitable for high-throughput real-time screening detection of gluten in foods. In this study, a Fourier-Transform Infrared (FT-IR) spectroscopy-based approach was proposed for authentication of gluten-free flour. Three chemical standards including gliadin, gluten, and starch from wheat and 62 different types of flour products were scanned by FT-IR spectroscopy over the wavenumber range of 4000 and 400 cm-1. Notable absorbance differences were observed between the chemical standards of gliadin and gluten and starch from wheat over the wavenumber range of 1800-450 cm-1. The mean absorbance profiles of gluten-free and non-gluten free categories of flour demonstrated varying spectral characteristics between 1800 and 1500 cm-1. The Principal Component Analysis (PCA)- Linear Discriminant Analysis (LDA) models built upon the original absorbance of flour between 1800 and 1500 cm-1 achieved overall prediction accuracies of at least 95.7%. The potential of FT-IR technique in identifying and authenticating gluten-free flour was demonstrated.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"105 3","pages":"1306009 - 1306009-6"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377918","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}
R. Dizor, Anil Raj, Bryan M. Gonzalez, Garhett Smith, zachary carter, domingues rodrigues, jacob newton
This paper introduces a pioneering approach for controlling a unilateral lower extremity exoskeleton designed for rehabilitation and enhancing the quality of life for individuals with neuromuscular weakness of the lower limbs. At the core of our methodology is the integration of Long Short-Term Memory (LSTM) networks with Proximal Policy Optimization (PPO) models, utilizing a deep reinforcement learning framework to interpret and predict user movement intentions in real time. By harnessing sensor fusion that combines surface electromyography (sEMG) and Inertial Measurement Units (IMU) from sensor arrays placed around the quadriceps and gastrocnemius muscles, our system employs an adaptive nonlinear sliding mode control with Pneumatic Artificial Muscles (PAMs), thereby directing the exoskeleton's movement and positioning. The LSTM network processes temporal sequences of sensor data to capture the dynamics of human motion, while the PPO model optimizes the control policy to ensure smooth and responsive movements aligned with the user intentions. Focusing initially on basic maneuvers integral to Activities of Daily Living (ADL), our system demonstrates promising preliminary results in mimicking natural limb movements, laying the groundwork for future clinical applications. This paper specifically delves into the utilization of the LSTM-PPO framework for controlling an avatar prior to testing the exoskeleton, representing a significant step towards realizing a responsive and intuitive exoskeleton control system.
{"title":"Deep reinforcement learning to assess lower extremity movement intention and assist a rehabilitation exoskeleton","authors":"R. Dizor, Anil Raj, Bryan M. Gonzalez, Garhett Smith, zachary carter, domingues rodrigues, jacob newton","doi":"10.1117/12.3013039","DOIUrl":"https://doi.org/10.1117/12.3013039","url":null,"abstract":"This paper introduces a pioneering approach for controlling a unilateral lower extremity exoskeleton designed for rehabilitation and enhancing the quality of life for individuals with neuromuscular weakness of the lower limbs. At the core of our methodology is the integration of Long Short-Term Memory (LSTM) networks with Proximal Policy Optimization (PPO) models, utilizing a deep reinforcement learning framework to interpret and predict user movement intentions in real time. By harnessing sensor fusion that combines surface electromyography (sEMG) and Inertial Measurement Units (IMU) from sensor arrays placed around the quadriceps and gastrocnemius muscles, our system employs an adaptive nonlinear sliding mode control with Pneumatic Artificial Muscles (PAMs), thereby directing the exoskeleton's movement and positioning. The LSTM network processes temporal sequences of sensor data to capture the dynamics of human motion, while the PPO model optimizes the control policy to ensure smooth and responsive movements aligned with the user intentions. Focusing initially on basic maneuvers integral to Activities of Daily Living (ADL), our system demonstrates promising preliminary results in mimicking natural limb movements, laying the groundwork for future clinical applications. This paper specifically delves into the utilization of the LSTM-PPO framework for controlling an avatar prior to testing the exoskeleton, representing a significant step towards realizing a responsive and intuitive exoskeleton control system.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"3 7","pages":"1305805 - 1305805-9"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380429","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}
Masanobu Yamamoto, John Jaiber Gonzalez Murillo, Keegan Hernandez, Valery Patsekin, J. P. Robinson
Single Photon Detection (SPD) is the essential technology for the future of quantum cytometry and quantum biology. We have been developing SPD technology previously reported at DCS2022 but recently achieved detection and recording of photoelectron (PE) pulse width ⪅500ps with 1Gcps saturation count with near 7LOG Dynamic Range (DR). The current challenge involves developing a spectral photon detection system that works in the range from ultraviolet to near infrared region. We have developed a six-decade dynamic range spectrometer from 360nm to 820nm, with a 42 channels fiber array (42CH) that distributes each spectral window onto an individual pixel-coupled silicon photomultiplier (SiPM), each channel has a 10.9nm bandwidth. The detected PE streams of the 42CH are captured with an FPGA at 10Gs/s with 100ps time resolution using multi-GHz electronics and thermoelectric cooling, and produce a huge data stream of 420Gs/s. We have identified interference problems on the system which arise from using conventional packaging with gold wire connection in dry nitrogen such as oscillation, crosstalk between adjacent channels and interference from external radiation such as Wi-Fi and cellular RF signals. To resolve electrical interference and improve signal quality, the sensor chips were mounted on an eight-layer Chip-On-Board (COB). Improving the sensor environment was the other focus for our system. We have designed a two stagesthermoelectric device targeted at -30°C with a moisture getter in the sensor package to reduce the thermal electron and the dark count of the SiPM. This design is an innovative approach in the packaging method that helps to control the environment inside the sensor. Earlier photon spectroscopy required a considerable time to scan a full spectral range using a monochromator. Our newly developed 42CH multiwavelength spectrometer allows the capture of a spectral fingerprint in microseconds to microseconds with potential readout in SI units. The system under development will contribute various applications in the fast-developing quantum field.
{"title":"Multiwavelength spectral photon detection system with 10.9nm resolution capable of perform data stream at 420Gs/s","authors":"Masanobu Yamamoto, John Jaiber Gonzalez Murillo, Keegan Hernandez, Valery Patsekin, J. P. Robinson","doi":"10.1117/12.3013438","DOIUrl":"https://doi.org/10.1117/12.3013438","url":null,"abstract":"Single Photon Detection (SPD) is the essential technology for the future of quantum cytometry and quantum biology. We have been developing SPD technology previously reported at DCS2022 but recently achieved detection and recording of photoelectron (PE) pulse width ⪅500ps with 1Gcps saturation count with near 7LOG Dynamic Range (DR). The current challenge involves developing a spectral photon detection system that works in the range from ultraviolet to near infrared region. We have developed a six-decade dynamic range spectrometer from 360nm to 820nm, with a 42 channels fiber array (42CH) that distributes each spectral window onto an individual pixel-coupled silicon photomultiplier (SiPM), each channel has a 10.9nm bandwidth. The detected PE streams of the 42CH are captured with an FPGA at 10Gs/s with 100ps time resolution using multi-GHz electronics and thermoelectric cooling, and produce a huge data stream of 420Gs/s. We have identified interference problems on the system which arise from using conventional packaging with gold wire connection in dry nitrogen such as oscillation, crosstalk between adjacent channels and interference from external radiation such as Wi-Fi and cellular RF signals. To resolve electrical interference and improve signal quality, the sensor chips were mounted on an eight-layer Chip-On-Board (COB). Improving the sensor environment was the other focus for our system. We have designed a two stagesthermoelectric device targeted at -30°C with a moisture getter in the sensor package to reduce the thermal electron and the dark count of the SiPM. This design is an innovative approach in the packaging method that helps to control the environment inside the sensor. Earlier photon spectroscopy required a considerable time to scan a full spectral range using a monochromator. Our newly developed 42CH multiwavelength spectrometer allows the capture of a spectral fingerprint in microseconds to microseconds with potential readout in SI units. The system under development will contribute various applications in the fast-developing quantum field.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"58 4","pages":"1305902 - 1305902-9"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376365","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}
Khaled Obaideen, Mohammad A. AlShabi, M. Bettayeb, S. A. Gadsden, Talal Bonny
This paper gives a bibliometric summary of Unscented Kalman Filter (UKF) in AI-infused robotics, highlighting its role in unifying control and cognition. Using a systematic approach that includes literature collection from IEEE Xplore, Web of Science and Google Scholar, rigorous screening and selection, and VOSviewer for a comprehensive bibliometric analysis. This analysis reports major trends, primary contributors and central themes, highlighting UKF’s pivotal role in improving robotics cognitive and control capacities. The study emphasizes the universally used UKF in many fields of robotics, i.e. in navigation and mapping, sensor fusion, and state estimation, as one of its principal developers, which illustrates its vital role in promoting robotic autonomy and intelligence. The integration of findings from the bibliometric analysis thus not only presents the current state of research but also identifies possible future research directions, highlighting the increasing unification of control theories and cognitive processes in robotics. This research adds to the body of knowledge by delivering a comprehensive map of the UKF application. In this light, the UKF will be able to penetrate AI-infused robotics, the future of robotic developments will rely on the deep fusion of control and cognition facilitated by UKF and alike.
本文对人工智能注入机器人技术中的无cented Kalman Filter（UKF）进行了文献计量学总结，强调了其在统一控制与认知方面的作用。本文采用系统方法，包括从 IEEE Xplore、Web of Science 和 Google Scholar 收集文献，进行严格筛选，并使用 VOSviewer 进行全面的文献计量分析。该分析报告了主要趋势、主要贡献者和中心主题，突出了 UKF 在提高机器人认知和控制能力方面的关键作用。研究强调，UKF 作为其主要开发者之一，在导航和绘图、传感器融合以及状态估计等多个机器人领域得到了普遍应用，这说明了它在促进机器人自主性和智能化方面的重要作用。因此，文献计量学分析结果的整合不仅展示了当前的研究状况，还确定了未来可能的研究方向，突出了机器人学中控制理论和认知过程的日益统一。这项研究提供了英国框架应用的综合地图，为知识体系增添了新的内容。有鉴于此，UKF 将能够渗透到人工智能注入的机器人技术中，未来的机器人发展将依赖于 UKF 和类似技术所促进的控制与认知的深度融合。
{"title":"The convergence of control and cognition: a bibliometric overview of UKF in AI-infused robotics","authors":"Khaled Obaideen, Mohammad A. AlShabi, M. Bettayeb, S. A. Gadsden, Talal Bonny","doi":"10.1117/12.3013841","DOIUrl":"https://doi.org/10.1117/12.3013841","url":null,"abstract":"This paper gives a bibliometric summary of Unscented Kalman Filter (UKF) in AI-infused robotics, highlighting its role in unifying control and cognition. Using a systematic approach that includes literature collection from IEEE Xplore, Web of Science and Google Scholar, rigorous screening and selection, and VOSviewer for a comprehensive bibliometric analysis. This analysis reports major trends, primary contributors and central themes, highlighting UKF’s pivotal role in improving robotics cognitive and control capacities. The study emphasizes the universally used UKF in many fields of robotics, i.e. in navigation and mapping, sensor fusion, and state estimation, as one of its principal developers, which illustrates its vital role in promoting robotic autonomy and intelligence. The integration of findings from the bibliometric analysis thus not only presents the current state of research but also identifies possible future research directions, highlighting the increasing unification of control theories and cognitive processes in robotics. This research adds to the body of knowledge by delivering a comprehensive map of the UKF application. In this light, the UKF will be able to penetrate AI-infused robotics, the future of robotic developments will rely on the deep fusion of control and cognition facilitated by UKF and alike.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"324 3","pages":"1305817 - 1305817-8"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380912","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}
Alex McCafferty-Leroux, Andrew Newton, S. A. Gadsden
Deployed for purposes of GPS, defense, atmospheric and space research, environmental monitoring, broadcasting, and communication, Earth observation satellites are complex systems that require the design of highly reliable control and estimation algorithms. A satellite’s Attitude Determination and Control System (ADCS) must be able to operate accurately, in a robust manner against unexpected conditions, especially in missions that demand more intricate tasks. The desire for optimal and robust performance in satellites has been the driving factor behind decades of attitude control research. With computers, the performance of spacecraft subject to some mission can be simulated to test new control methods, but the availability of real satellites to researchers for testing these algorithms is very limited. To solve this issue, attitude control simulators have been developed, such that algorithms and hardware can be tested inexpensively in a lab environment, while maintaining a high level of accuracy to the environment it emulates. The Nanosatellite Attitude Control Simulator (NACS) has been developed at McMaster University for this purpose. Consisting of a mock 1U CubeSat, an air-bearing configuration, and an Automatic Balancing System (ABS), rotational attitude control experiments are conducted in-lab without deployment, simulating the zero-gravity of space. The mechanism responsible for environment simulation is the ABS, which minimizes residual torque due to gravity by influencing the center of mass (CoM) of the system, thereby improving control performance and efficiency. The performance of the ABS in a balancing task is presented, where system parameters of inertia and CoM are estimated from response data. Three filtering strategies are investigated for this purpose, providing varying degrees of accuracy and computational cost.
地球观测卫星是一个复杂的系统，需要设计高度可靠的控制和估计算法，其部署目的包括全球定位系统、国防、大气和空间研究、环境监测、广播和通信。卫星的姿态确定和控制系统（ADCS）必须能够在意外情况下准确、稳健地运行，尤其是在执行要求更加复杂的任务时。对卫星最佳和稳健性能的渴望是几十年来姿态控制研究的驱动因素。利用计算机可以模拟航天器在某些任务中的性能，以测试新的控制方法，但可供研究人员测试这些算法的真实卫星非常有限。为了解决这个问题，人们开发了姿态控制模拟器，以便在实验室环境中以低成本测试算法和硬件，同时保持模拟环境的高精确度。麦克马斯特大学为此开发了超小型卫星姿态控制模拟器（NACS）。该模拟器由模拟 1U 立方体卫星、气浮配置和自动平衡系统（ABS）组成，在实验室内进行旋转姿态控制实验，无需部署，模拟太空零重力环境。负责环境模拟的机构是自动平衡系统，它通过影响系统的质心（CoM）将重力造成的残余扭矩降至最低，从而提高控制性能和效率。本文介绍了 ABS 在平衡任务中的性能，其中系统惯性和 CoM 参数是根据响应数据估算的。为此研究了三种滤波策略，它们提供了不同程度的精度和计算成本。
{"title":"Parameter estimation and control of an automatic balancing system for CubeSat research and applications","authors":"Alex McCafferty-Leroux, Andrew Newton, S. A. Gadsden","doi":"10.1117/12.3013732","DOIUrl":"https://doi.org/10.1117/12.3013732","url":null,"abstract":"Deployed for purposes of GPS, defense, atmospheric and space research, environmental monitoring, broadcasting, and communication, Earth observation satellites are complex systems that require the design of highly reliable control and estimation algorithms. A satellite’s Attitude Determination and Control System (ADCS) must be able to operate accurately, in a robust manner against unexpected conditions, especially in missions that demand more intricate tasks. The desire for optimal and robust performance in satellites has been the driving factor behind decades of attitude control research. With computers, the performance of spacecraft subject to some mission can be simulated to test new control methods, but the availability of real satellites to researchers for testing these algorithms is very limited. To solve this issue, attitude control simulators have been developed, such that algorithms and hardware can be tested inexpensively in a lab environment, while maintaining a high level of accuracy to the environment it emulates. The Nanosatellite Attitude Control Simulator (NACS) has been developed at McMaster University for this purpose. Consisting of a mock 1U CubeSat, an air-bearing configuration, and an Automatic Balancing System (ABS), rotational attitude control experiments are conducted in-lab without deployment, simulating the zero-gravity of space. The mechanism responsible for environment simulation is the ABS, which minimizes residual torque due to gravity by influencing the center of mass (CoM) of the system, thereby improving control performance and efficiency. The performance of the ABS in a balancing task is presented, where system parameters of inertia and CoM are estimated from response data. Three filtering strategies are investigated for this purpose, providing varying degrees of accuracy and computational cost.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"84 s373","pages":"130620M - 130620M-19"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376330","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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