When you think of different standards of encryption you may think of Data Encryption Standard, Advanced Encryption Standard or Elliptic Curve Cryptography. However, a new standard for encryption, called homomorphic encryption, is being researched and put into use. Homomorphic encryption is a cryptographic technique that has the potential to significantly impact the field of Artificial Intelligence (AI). It allows data to be processed in an encrypted form without first decrypting it, thus preserving privacy and security while still enabling meaningful computation. Homomorphic encryption can also be applied in federated learning, a decentralized approach to machine learning. Multiple parties can collaborate to train a machine learning model without sharing their individual data directly. Throughout this paper first we will discuss what homomorphic encryption is and then, we explore how homomorphic encryption can be used to ensure that data remains encrypted during model updates and aggregation, enhancing privacy.
{"title":"A look inside of homomorphic encryption for federated learning","authors":"L. Beshaj, Michel Hoefler","doi":"10.1117/12.3013713","DOIUrl":"https://doi.org/10.1117/12.3013713","url":null,"abstract":"When you think of different standards of encryption you may think of Data Encryption Standard, Advanced Encryption Standard or Elliptic Curve Cryptography. However, a new standard for encryption, called homomorphic encryption, is being researched and put into use. Homomorphic encryption is a cryptographic technique that has the potential to significantly impact the field of Artificial Intelligence (AI). It allows data to be processed in an encrypted form without first decrypting it, thus preserving privacy and security while still enabling meaningful computation. Homomorphic encryption can also be applied in federated learning, a decentralized approach to machine learning. Multiple parties can collaborate to train a machine learning model without sharing their individual data directly. Throughout this paper first we will discuss what homomorphic encryption is and then, we explore how homomorphic encryption can be used to ensure that data remains encrypted during model updates and aggregation, enhancing privacy.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"3 2","pages":"130580Q - 130580Q-10"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380489","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}
William Fairman, Paul S. Wills, Luis Vila, Bing Ouyang
Developing ocean-going unmanned robotic systems has been a focus for the marine research community for many years. Compared with earlier manned submersibles, the current state-of-the-art Autonomous Underwater Vehicles (AUVs), tethered Remotely Operated Vehicles (ROVs) and Unmanned Surface Vehicles (USVs) augmented with the advancement in the sensor technology offer dramatic improvements in safety, cost, and efficiency, especially for deep water sensing operations. However, coastal zones such as estuaries and river deltas that are highly productive habitats supporting a variety of fish and wildlife may be challenging for the current suite of platforms. The complex geographical features in these regions, such as land barriers, icebergs and tidal currents, may hinder the movements of the aforementioned platforms. For this reason, a complementary sensing paradigm that employs waterproof unmanned aerial vehicles (UAVs) integrated with underwater sensors is proposed. The implementation of such concept – the Hybrid Aerial Underwater Robotic System (HAUCS) is presented. The development of one HAUCS platform, the coaxial waterproof drone, is discussed.
{"title":"Waterproof UAVs for sensing in coastal zones and estuaries","authors":"William Fairman, Paul S. Wills, Luis Vila, Bing Ouyang","doi":"10.1117/12.3022720","DOIUrl":"https://doi.org/10.1117/12.3022720","url":null,"abstract":"Developing ocean-going unmanned robotic systems has been a focus for the marine research community for many years. Compared with earlier manned submersibles, the current state-of-the-art Autonomous Underwater Vehicles (AUVs), tethered Remotely Operated Vehicles (ROVs) and Unmanned Surface Vehicles (USVs) augmented with the advancement in the sensor technology offer dramatic improvements in safety, cost, and efficiency, especially for deep water sensing operations. However, coastal zones such as estuaries and river deltas that are highly productive habitats supporting a variety of fish and wildlife may be challenging for the current suite of platforms. The complex geographical features in these regions, such as land barriers, icebergs and tidal currents, may hinder the movements of the aforementioned platforms. For this reason, a complementary sensing paradigm that employs waterproof unmanned aerial vehicles (UAVs) integrated with underwater sensors is proposed. The implementation of such concept – the Hybrid Aerial Underwater Robotic System (HAUCS) is presented. The development of one HAUCS platform, the coaxial waterproof drone, is discussed.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"351 9","pages":"1306105 - 1306105-12"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380747","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 Ramiro Masaquiza Caiza, Denis Andres Maigualema Quimbita, M. Tropea
In recent years, the interest in Software-Defined Networking (SDN) has been very high. Many applications of traditional networking have been implemented in SDN environments in order to test the performance of the different network devices. In this paper, server Load-Balancing (LB) based on SDN has been developed and tested in order to verify the effectiveness of this approach inside the new networking approach. In our implementation, we have used a Ruy controller for controlling and managing network devices and two different LB algorithms have been implemented. We have performed an analysis of these two algorithms with a system without load balancing in a server-client system changing the number of servers and clients in order to show the performance of the SDN network.
近年来，人们对软件定义网络（SDN）兴趣浓厚。许多传统网络应用已在 SDN 环境中实施，以测试不同网络设备的性能。本文开发并测试了基于 SDN 的服务器负载平衡（LB），以验证这种方法在新网络方法中的有效性。在实施过程中，我们使用了鲁伊控制器来控制和管理网络设备，并实施了两种不同的负载平衡算法。我们对这两种算法与服务器-客户端系统中无负载平衡的系统进行了分析，改变了服务器和客户端的数量，以显示 SDN 网络的性能。
{"title":"Load balancing algorithms in SDN networks with multiple servers","authors":"Alex Ramiro Masaquiza Caiza, Denis Andres Maigualema Quimbita, M. Tropea","doi":"10.1117/12.3016784","DOIUrl":"https://doi.org/10.1117/12.3016784","url":null,"abstract":"In recent years, the interest in Software-Defined Networking (SDN) has been very high. Many applications of traditional networking have been implemented in SDN environments in order to test the performance of the different network devices. In this paper, server Load-Balancing (LB) based on SDN has been developed and tested in order to verify the effectiveness of this approach inside the new networking approach. In our implementation, we have used a Ruy controller for controlling and managing network devices and two different LB algorithms have been implemented. We have performed an analysis of these two algorithms with a system without load balancing in a server-client system changing the number of servers and clients in order to show the performance of the SDN network.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"4 6","pages":"1305818 - 1305818-11"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379494","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}
This study aims to improve the rotational motion and inertia parameters estimation performance of an Unscented Kalman Filter model (UKF) for a torque-free tumbling non-cooperative space object using the Gaussian Process (GP). The traditional UKF algorithm which is a physics-based estimation algorithm for non-linear systems is susceptible to the physical process, measurement sampling rate, and filter design. Consequently, slight inaccuracy in the assumed physical models, low sampling rates, or small variations of the filter parameters can result in poor estimation performance. Additionally, the UKF model might not predict the motion and inertia parameters with good accuracy in the absence of sensor measurements, also known as occlusion, a quite common challenge for space missions. To make a UKF model more robust to the factors above, we utilize multi-output GP models with periodic kernels to make long-term predictions of the position and attitude measurements obtained from a Laser Camera System (LCS). These measurement predictions from GP models are used as the sensor measurements for the UKF model. We implement a Fast Fourier Transform on the sensor measurements to determine the initial guess for periodicity hyper-parameters for the periodic kernels. Results from conducted simulations show that the proposed UKF model with GP-predicted measurements (UKF-GP model) performs remarkably well compared to the UKF model under the assumption of long-term occlusion. It is also observed from the results that, the UKF-GP model is more robust to sensor sampling rate, underlying physical process, and filter parameters even with occlusion, compared to the UKF model without occlusion.
本研究的目的是利用高斯过程（GP）改善无标记卡尔曼滤波模型（UKF）对无扭矩翻滚非合作空间物体的旋转运动和惯性参数估计性能。传统的 UKF 算法是一种基于物理的非线性系统估算算法，易受物理过程、测量采样率和滤波器设计的影响。因此，假定物理模型的轻微误差、低采样率或滤波器参数的微小变化都会导致估计性能低下。此外，在没有传感器测量的情况下，UKF 模型可能无法准确预测运动和惯性参数，这也被称为 "闭塞"，是太空任务中一个相当常见的挑战。为了使 UKF 模型对上述因素更加稳健，我们利用具有周期核的多输出 GP 模型，对从激光摄像系统（LCS）获得的位置和姿态测量结果进行长期预测。这些来自 GP 模型的测量预测结果被用作 UKF 模型的传感器测量结果。我们对传感器测量结果进行快速傅立叶变换，以确定周期核的周期性超参数初始猜测。模拟结果表明，在长期闭塞的假设条件下，采用 GP 预测测量值的 UKF 模型（UKF-GP 模型）与 UKF 模型相比表现非常出色。从结果中还可以看出，与没有闭塞的 UKF 模型相比，即使有闭塞，UKF-GP 模型对传感器采样率、基本物理过程和滤波器参数的鲁棒性也更强。
{"title":"Advanced motion estimations and predictions of a tumbling, non-cooperative space object during long-term occlusion","authors":"Rabiul Kabir, Xiaoli Bai","doi":"10.1117/12.3013101","DOIUrl":"https://doi.org/10.1117/12.3013101","url":null,"abstract":"This study aims to improve the rotational motion and inertia parameters estimation performance of an Unscented Kalman Filter model (UKF) for a torque-free tumbling non-cooperative space object using the Gaussian Process (GP). The traditional UKF algorithm which is a physics-based estimation algorithm for non-linear systems is susceptible to the physical process, measurement sampling rate, and filter design. Consequently, slight inaccuracy in the assumed physical models, low sampling rates, or small variations of the filter parameters can result in poor estimation performance. Additionally, the UKF model might not predict the motion and inertia parameters with good accuracy in the absence of sensor measurements, also known as occlusion, a quite common challenge for space missions. To make a UKF model more robust to the factors above, we utilize multi-output GP models with periodic kernels to make long-term predictions of the position and attitude measurements obtained from a Laser Camera System (LCS). These measurement predictions from GP models are used as the sensor measurements for the UKF model. We implement a Fast Fourier Transform on the sensor measurements to determine the initial guess for periodicity hyper-parameters for the periodic kernels. Results from conducted simulations show that the proposed UKF model with GP-predicted measurements (UKF-GP model) performs remarkably well compared to the UKF model under the assumption of long-term occlusion. It is also observed from the results that, the UKF-GP model is more robust to sensor sampling rate, underlying physical process, and filter parameters even with occlusion, compared to the UKF model without occlusion.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"5 13","pages":"1306209 - 1306209-14"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The advancement of Earth observation satellite research in past decades has demonstrated itself to be productive and increasingly important. Utilized for applications such as climate monitoring, communication, GPS, defense, and space research, our dependence on reliable satellite systems is ever-increasing. The success of satellites in these scenarios is fundamentally the result of its attitude determination system, consisting of control and estimation subsystems, which govern its sensors and actuators. For simple missions, attitude pose determination can be computed onboard the satellite. Typically, however, ground stations or other satellites (i.e. constellations) are involved in a satellite’s operation, processing large amounts of data or complex control algorithms. This information and control cycle is enabled through the application of Networked Control Systems (NCS). The NCS uses a wireless network or communication system as the intermediate line of communication between plant, actuators, sensors, and other systems. This enables relatively fast communication and data transmittance over long distances, as well as the decentralization of navigation and control through system distribution. However, this method is vulnerable to various forms of time delay and packet loss, which ultimately affects the control performance of a satellite. It is demonstrated in literature that the effects of these NCS properties can be mitigated, increasing its viability, through various implementations of smart systems into the satellite framework. Using techniques such as neural networks and reinforcement learning, the satellite can perceive and act based on environmental information, while considering experiential memory and attention allocation. The following comprehensive survey discusses methods for improving the robustness of networked satellite systems from a smart systems perspective, providing an advanced foundation for these concepts.
{"title":"Networked control systems and their applications to smart satellites: a survey","authors":"Alex McCafferty-Leroux, Yuandi Wu, S. A. Gadsden","doi":"10.1117/12.3013314","DOIUrl":"https://doi.org/10.1117/12.3013314","url":null,"abstract":"The advancement of Earth observation satellite research in past decades has demonstrated itself to be productive and increasingly important. Utilized for applications such as climate monitoring, communication, GPS, defense, and space research, our dependence on reliable satellite systems is ever-increasing. The success of satellites in these scenarios is fundamentally the result of its attitude determination system, consisting of control and estimation subsystems, which govern its sensors and actuators. For simple missions, attitude pose determination can be computed onboard the satellite. Typically, however, ground stations or other satellites (i.e. constellations) are involved in a satellite’s operation, processing large amounts of data or complex control algorithms. This information and control cycle is enabled through the application of Networked Control Systems (NCS). The NCS uses a wireless network or communication system as the intermediate line of communication between plant, actuators, sensors, and other systems. This enables relatively fast communication and data transmittance over long distances, as well as the decentralization of navigation and control through system distribution. However, this method is vulnerable to various forms of time delay and packet loss, which ultimately affects the control performance of a satellite. It is demonstrated in literature that the effects of these NCS properties can be mitigated, increasing its viability, through various implementations of smart systems into the satellite framework. Using techniques such as neural networks and reinforcement learning, the satellite can perceive and act based on environmental information, while considering experiential memory and attention allocation. The following comprehensive survey discusses methods for improving the robustness of networked satellite systems from a smart systems perspective, providing an advanced foundation for these concepts.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"13 2","pages":"130620K - 130620K-20"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378043","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}
Alisa Kunapinun, William Fairman, Paul S. Wills, S. Mejri, Magaleate Kostelnik, Bing Ouyang
Within the scope of aquaculture farm operation and research, monitoring fish larvae offers pivotal data about the operational conditions of the farm. For example, hypoxia may induce abnormal movements. Currently, precise monitoring of these diminutive entities (1 mm in size) hinges on superior water clarity and specialized equipment. While green laser may be preferred for extended range underwater imaging, it is visible to the fish. Hence it will disturb fish and potentially damage their vision system. This is of particular concern at our facility at the Harbor Branch Oceanographic Institute (HBOI). To address these challenges, our research has adapted a Time-of-Flight (ToF) camera, equipped initially with a 50mm lens, into a microscopic imager using an IR laser. This setup was capable of detailed but narrow depth field imaging, suitable for clear water conditions. Recent advancements have included transitioning to a 25mm lens, enhancing the camera’s ability to capture wider images (approximately 20 pixels wide for fish eggs) and observe finer details in medium turbidity conditions, though with a reduced depth field of 5mm. This modification has shifted the camera’s utility towards observing very small living organisms (100-200 microns) and reduced its effectiveness in depth measurement in highly turbid waters. This adaptation ensures more precise tracking of fish larvae and offers a fish-eye-safe imaging process due to the use of IR light. The integration of machine learning techniques further refines the system’s ability to accurately identify fish larvae in varying water conditions. Our approach presents a balanced solution, combining affordability, improved accuracy, and mindful consideration of the fish’s welfare, contributing positively to the field of fish larvae tracking.
{"title":"Innovative aquaculture biometrics analysis: harnessing IR lasers and ToF cameras for microscopic fish larvae tracking","authors":"Alisa Kunapinun, William Fairman, Paul S. Wills, S. Mejri, Magaleate Kostelnik, Bing Ouyang","doi":"10.1117/12.3014053","DOIUrl":"https://doi.org/10.1117/12.3014053","url":null,"abstract":"Within the scope of aquaculture farm operation and research, monitoring fish larvae offers pivotal data about the operational conditions of the farm. For example, hypoxia may induce abnormal movements. Currently, precise monitoring of these diminutive entities (1 mm in size) hinges on superior water clarity and specialized equipment. While green laser may be preferred for extended range underwater imaging, it is visible to the fish. Hence it will disturb fish and potentially damage their vision system. This is of particular concern at our facility at the Harbor Branch Oceanographic Institute (HBOI). To address these challenges, our research has adapted a Time-of-Flight (ToF) camera, equipped initially with a 50mm lens, into a microscopic imager using an IR laser. This setup was capable of detailed but narrow depth field imaging, suitable for clear water conditions. Recent advancements have included transitioning to a 25mm lens, enhancing the camera’s ability to capture wider images (approximately 20 pixels wide for fish eggs) and observe finer details in medium turbidity conditions, though with a reduced depth field of 5mm. This modification has shifted the camera’s utility towards observing very small living organisms (100-200 microns) and reduced its effectiveness in depth measurement in highly turbid waters. This adaptation ensures more precise tracking of fish larvae and offers a fish-eye-safe imaging process due to the use of IR light. The integration of machine learning techniques further refines the system’s ability to accurately identify fish larvae in varying water conditions. Our approach presents a balanced solution, combining affordability, improved accuracy, and mindful consideration of the fish’s welfare, contributing positively to the field of fish larvae tracking.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"19 1","pages":"130610F - 130610F-8"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381979","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, Yousuf Faroukh, Talal Bonny, Mohammad A. AlShabi, Ahmad Alobaid
This research plunges into the rapidly growing radar technology in the medical sector, putting emphasis on its possibility to revolutionize elderly care and health monitoring among the aging global population. Based on a systematic literature review and rigorous bibliometric analysis, we discuss radar technology application in healthcare, focusing on its potential for non-invasive, high-accuracy diagnosis and continuous patient monitoring. Our findings highlight the critical harmony between radar technology and the advances in machine learning, artificial intelligence, and data analytics, which open the door to smart healthcare solutions. These advancements will improve early disease detection, fall risk prevention, and real-time health monitoring, resulting in quick medical responses. This study endeavors to offer useful knowledge to researchers, practitioners, and policymakers who are working towards the use of technology for better health in the context of the demographic changes that the world is experiencing in terms of an ageing population by mapping the current research landscape, identifying the existing trends and gaps, and proposing the future direction of research.
{"title":"Quantifying knowledge: medical applications of radar aging through the lens of bibliometrics","authors":"Khaled Obaideen, Yousuf Faroukh, Talal Bonny, Mohammad A. AlShabi, Ahmad Alobaid","doi":"10.1117/12.3013860","DOIUrl":"https://doi.org/10.1117/12.3013860","url":null,"abstract":"This research plunges into the rapidly growing radar technology in the medical sector, putting emphasis on its possibility to revolutionize elderly care and health monitoring among the aging global population. Based on a systematic literature review and rigorous bibliometric analysis, we discuss radar technology application in healthcare, focusing on its potential for non-invasive, high-accuracy diagnosis and continuous patient monitoring. Our findings highlight the critical harmony between radar technology and the advances in machine learning, artificial intelligence, and data analytics, which open the door to smart healthcare solutions. These advancements will improve early disease detection, fall risk prevention, and real-time health monitoring, resulting in quick medical responses. This study endeavors to offer useful knowledge to researchers, practitioners, and policymakers who are working towards the use of technology for better health in the context of the demographic changes that the world is experiencing in terms of an ageing population by mapping the current research landscape, identifying the existing trends and gaps, and proposing the future direction of research.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"28 27","pages":"1305906 - 1305906-7"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378911","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}
Continuous Time Digital Signal Processing (CT-DSP) has the potential of being disruptive in four engineering disciplines: digital signal processing, control systems, compressive sensing, and spiking neural networks. In July 2022, a pipeline level crossing analog-to-digital architecture was published by Jungwirth and Crowe. In this paper a real-time level crossing sampling interpolation algorithm is introduced. Digital Signal Processing (DSP) systems are treated as Linear Time-Invariant (LTI) systems, and the reconstruction operator is also LTI. This provides DSP with some important advantages. It benefits from mature linear system theory, mature Discrete Time (DT) systems theory, the ability to postpone the reconstruction operator until the final stage, and the well understood Whittaker-Kotel'nikov-Shannon reconstruction. However, CT-DSP is not linear; the reconstruction is time-variant and complicated. Design of CT-DSP systems is more difficult than for DSP, but the justification for assuming this added difficulty is based on significant advantages in signal capture accuracy and in reduction in power requirements. For DSP, the quantization noise floor is determined by Bennett's quantization error equation, and it remains fixed, relative to the Analog-Digital-Converter's (ADC) input range. However, the noise floor for CT-DSP is largely determined by the reconstruction algorithm and is not entirely dependent on the number of quantization levels. For example, Tsividis demonstrated ~100 dB Signal-to-Noise and Distortion ratio (SINAD) for a 16-level (4-bit equivalent) level crossing ADC, using offline signal reconstruction. This implies that CT-DSP’s SINAD does not significantly degrade for weak signals. In addition to the Tsividis revelation of the accuracy of these signals, several demonstrations of the advantages of CT-DSP have been reported. Zhao and Prodic demonstrated reduced lag and a 3x reduction in overshoot in the controller for a DC-DC buck-boost converter. Qaisar and Hussain reported a 3x decrease in the number of sample points needed for accurate classification of arrythmias using level crossing Electrocardiogram (ECG) signals. Alier et al. have demonstrated a 10x reduction in sample data, when level crossing sampling is performed on audio speech waveforms. A novel real-time CT-DSP reconstruction algorithm is presented, for the first time, in this paper. The technique makes use of the aliased sinc (asinc) function in order to accomplish a compact, trigonometric spline interpolation. Although the technique is not strictly ideal, corrective measures have been included to maintain accuracy. It provides 20-40 dB SINAD improvement over comparable DSP systems, depending on the application. It is applicable to low lag, real time processing while allowing a trade-off between accuracy and computational complexity.
{"title":"Continuous time systems disruptive signal processing and accurate real time signal reconstruction","authors":"W. M. Crowe, Patrick Jungwirth","doi":"10.1117/12.3014164","DOIUrl":"https://doi.org/10.1117/12.3014164","url":null,"abstract":"Continuous Time Digital Signal Processing (CT-DSP) has the potential of being disruptive in four engineering disciplines: digital signal processing, control systems, compressive sensing, and spiking neural networks. In July 2022, a pipeline level crossing analog-to-digital architecture was published by Jungwirth and Crowe. In this paper a real-time level crossing sampling interpolation algorithm is introduced. Digital Signal Processing (DSP) systems are treated as Linear Time-Invariant (LTI) systems, and the reconstruction operator is also LTI. This provides DSP with some important advantages. It benefits from mature linear system theory, mature Discrete Time (DT) systems theory, the ability to postpone the reconstruction operator until the final stage, and the well understood Whittaker-Kotel'nikov-Shannon reconstruction. However, CT-DSP is not linear; the reconstruction is time-variant and complicated. Design of CT-DSP systems is more difficult than for DSP, but the justification for assuming this added difficulty is based on significant advantages in signal capture accuracy and in reduction in power requirements. For DSP, the quantization noise floor is determined by Bennett's quantization error equation, and it remains fixed, relative to the Analog-Digital-Converter's (ADC) input range. However, the noise floor for CT-DSP is largely determined by the reconstruction algorithm and is not entirely dependent on the number of quantization levels. For example, Tsividis demonstrated ~100 dB Signal-to-Noise and Distortion ratio (SINAD) for a 16-level (4-bit equivalent) level crossing ADC, using offline signal reconstruction. This implies that CT-DSP’s SINAD does not significantly degrade for weak signals. In addition to the Tsividis revelation of the accuracy of these signals, several demonstrations of the advantages of CT-DSP have been reported. Zhao and Prodic demonstrated reduced lag and a 3x reduction in overshoot in the controller for a DC-DC buck-boost converter. Qaisar and Hussain reported a 3x decrease in the number of sample points needed for accurate classification of arrythmias using level crossing Electrocardiogram (ECG) signals. Alier et al. have demonstrated a 10x reduction in sample data, when level crossing sampling is performed on audio speech waveforms. A novel real-time CT-DSP reconstruction algorithm is presented, for the first time, in this paper. The technique makes use of the aliased sinc (asinc) function in order to accomplish a compact, trigonometric spline interpolation. Although the technique is not strictly ideal, corrective measures have been included to maintain accuracy. It provides 20-40 dB SINAD improvement over comparable DSP systems, depending on the application. It is applicable to low lag, real time processing while allowing a trade-off between accuracy and computational complexity.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"89 s378","pages":"1305815 - 1305815-15"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377173","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}
Daniele Barbiero, F. Melison, L. Cocola, M. Fedel, Cristian Andrighetto, Paola De Dea, L. Poletto
Nowadays the Clostridium detection in milk for the dairy industry still is a challenging problem since traditional methods are time-consuming and lack specificity towards these bacteria. The use of microbiological techniques is possible but is expensive in terms of response time and requires qualified personnel. Pasteurization is ineffective against Clostridium spores which can survive the process and later revert to their vegetative form during cheese aging. The Clostridium metabolism is characterized by the production of carbon dioxide and hydrogen, which can lead to the formation of cracks and slits in the cheese altering its taste and structure. The analysis of gas production is indicative of the presence of Clostridia; therefore, it can be exploited to detect their presence. This study presents a Raman spectroscopy-based instrument for a rapid and cost-effective identification of Clostridium in milk. The methodology relies on the widely adopted Most Probable Number (MPN) method, as established by Brändle et al. (2016). However, our innovation lies in adoption of a Raman-based instrument to speed up the vial positivity detection. The instrument also enables the discrimination Clostridia infection from non-hydrogen-producing bacteria.
{"title":"Detection of bacteria contamination in milk through H2 and CO2 measurements by Raman gas spectroscopy","authors":"Daniele Barbiero, F. Melison, L. Cocola, M. Fedel, Cristian Andrighetto, Paola De Dea, L. Poletto","doi":"10.1117/12.3012992","DOIUrl":"https://doi.org/10.1117/12.3012992","url":null,"abstract":"Nowadays the Clostridium detection in milk for the dairy industry still is a challenging problem since traditional methods are time-consuming and lack specificity towards these bacteria. The use of microbiological techniques is possible but is expensive in terms of response time and requires qualified personnel. Pasteurization is ineffective against Clostridium spores which can survive the process and later revert to their vegetative form during cheese aging. The Clostridium metabolism is characterized by the production of carbon dioxide and hydrogen, which can lead to the formation of cracks and slits in the cheese altering its taste and structure. The analysis of gas production is indicative of the presence of Clostridia; therefore, it can be exploited to detect their presence. This study presents a Raman spectroscopy-based instrument for a rapid and cost-effective identification of Clostridium in milk. The methodology relies on the widely adopted Most Probable Number (MPN) method, as established by Brändle et al. (2016). However, our innovation lies in adoption of a Raman-based instrument to speed up the vial positivity detection. The instrument also enables the discrimination Clostridia infection from non-hydrogen-producing bacteria.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"3 12","pages":"1306007 - 1306007-6"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380485","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}
With the ever-increasing number of satellites orbiting the Earth for the purposes of communication and research, a significant emphasis is placed on Space Domain Awareness (SDA). The orbital environment contains millions of bodies that can endanger the operation and existence of satellites. As a result, companies and governments around the world have built several massive radar arrays tasked with detecting, tracking, and cataloguing tens of thousands of Resident Space Objects (RSOs). A cost-, size-, and spectrum-effective method to achieve space debris tracking is to use passive forward scatter radar. In this radar configuration, target baseline crossing events produce special phenomena in the time- and frequency- domains which may be used for unique target identification. Experimental demonstrations of these effects are explored in this paper.
{"title":"Demonstration of the frequency and correlation behavior of a forward scatter baseline crossing event","authors":"Justin K. A. Henry, Ram M. Narayanan","doi":"10.1117/12.3013568","DOIUrl":"https://doi.org/10.1117/12.3013568","url":null,"abstract":"With the ever-increasing number of satellites orbiting the Earth for the purposes of communication and research, a significant emphasis is placed on Space Domain Awareness (SDA). The orbital environment contains millions of bodies that can endanger the operation and existence of satellites. As a result, companies and governments around the world have built several massive radar arrays tasked with detecting, tracking, and cataloguing tens of thousands of Resident Space Objects (RSOs). A cost-, size-, and spectrum-effective method to achieve space debris tracking is to use passive forward scatter radar. In this radar configuration, target baseline crossing events produce special phenomena in the time- and frequency- domains which may be used for unique target identification. Experimental demonstrations of these effects are explored in this paper.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":"88 1","pages":"130620B - 130620B-8"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381111","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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