Defense + Commercial Sensing最新文献

{"title":"Working MOG optimization via opportunistic delays","authors":"Gennady Staskevich, Joseph Skufca","doi":"10.1117/12.3025179","DOIUrl":"https://doi.org/10.1117/12.3025179","url":null,"abstract":"In this paper, we systematically investigate the use of delays to optimize the throughput for the working Maximum-On-Ground (MOG) problem space. The MOG optimization refers to the management of the transport aircraft in-and-around an airfield. The working MOG refers to the fulfilling of the servicing requirements of the aircraft. The effective and efficient daily MOG management enables the U.S. Air Force (USAF) Air Mobility Command (AMC) to rapidly deploy and sustain the equipment, and personnel anywhere in the world. However, the seemingly solved problem can quickly grow out of hand when the number of interruptions exceed past a certain point; this due to the combinatorial nature of the scheduling problem, where the order, and the mission dependencies matter. The opportunistic delays optimization explores the trade-off space between the efficiency (throughput maximization) and the resilience to schedule disruptions.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378766","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}

{"title":"Integrating power beaming and communication through laser modulation","authors":"Daniel O'Flaherty, Mike Sanders, Charles Nelson","doi":"10.1117/12.3013604","DOIUrl":"https://doi.org/10.1117/12.3013604","url":null,"abstract":"Laser Power Transfer (LPT) can serve as a potential solution to powering solar cells that are out of contact with the sun. It also has the potential to be combined with communications through beam modulation. This research aimed to integrate LPT and communications into a dual-use system, thus decreasing the Size, Weight, and Power (SWaP) of a rover, which would in turn reduce its cost. The two main focuses of this research were to characterize data rate and power transfer to a solar cell through the modulation of a laser beam by comparing different modulation methods. An off-the-shelf monocrystalline solar cell detected 30kbps of LED modulation with a maximum loss in power of 5.5%, and it detected 2.7kbps of laser modulation with a maximum loss in power of 20.1%.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376501","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}

{"title":"Improvements to global ionospheric forecasting with a recurrent convolutional neural network","authors":"Joseph Dailey, Khanh D. Pham","doi":"10.1117/12.3023846","DOIUrl":"https://doi.org/10.1117/12.3023846","url":null,"abstract":"Single-frequency GNSS users are reliant on estimates of the Total Electron Content (TEC) along lines of sight to navigation satellites to correct for ionospheric propagation delay and the resulting positioning errors. The parametric correction methods in use (Klobuchar’s algorithm for GPS and the NeQuick-G model for Galileo) can compensate for a large fraction of the delay but are hindered by using only a few daily coefficients to describe the ground truth ionosphere state. This loss of state information is particularly detrimental during periods of high deviation from baseline TEC patterns, e.g. solar weather events. This work describes an autoregressive RNN/CNN approach for spatiotemporal TEC forecasting from windowed historical map products, preserving local temporal and geospatial dependence between samples. By leveraging a large dataset spanning from 2000-2020 and applying convolutional transformations over both the temporal and spatial dimensions of the data, this model exhibits improved performance for time horizons up to 48 hours, compared to neural network-based approaches described in the literature to date.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381460","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}

{"title":"Extracting functional connectivity signatures in substance use disorder using energy landscape analysis","authors":"Sravani Varanasi, Tianye Zhai, Hong Gu, Yihong Yang, Fow-Sen Choa","doi":"10.1117/12.3013694","DOIUrl":"https://doi.org/10.1117/12.3013694","url":null,"abstract":"Substance Use Disorder (SUD) is a complex condition with profound effects on brain function. Understanding the altered functional connectivity patterns in the brains of SUD patients is crucial for unraveling the neurological underpinnings of this disorder. This study employs Energy Landscape Analysis, an energy-based machine learning technique, to investigate whole brain Regions of Interest (ROI) functional connectivity differences between SUD patients and healthy controls. The challenge with Energy Landscape Analysis lies in selecting the appropriate ROI from the extensive brain atlas. In this study, seed-based connectivity was utilized to identify relevant ROIs, overcoming the limitation of analyzing only a limited number of ROIs. The dataset comprised 53 cocaine users and 52 age- and sex-matched healthy controls, with fMRI data preprocessed using the CONN toolbox. ROI-ROI seed-based pair connectivity was derived through first and second level analyses. The identified sub-ROIs were categorized into default CONN network affiliations and bundled into Superior Temporal Gyrus (STG), Inferior Temporal Gyrus, temporooccipital part (toITG), Visual Primary (VIS-P), Auditory (AUD), Cerebellum, Basal Ganglia (BSL), and Thalamus (THL). Significance testing revealed eight connectivity states among all above regions with p-values that satisfy Bonferroni correction between controls and patients. Notably, the connectivity states with the lowest p-values revealed a distinctive pattern: STG (auditory attention) toITG were disconnected from the rest of the networks. This finding underscores the importance of investigating specific network disruptions in SUD, shedding light on potential neural mechanisms underlying the disorder. In summary, our study utilizes Energy Landscape Analysis to explore whole brain ROI functional connectivity in SUD, revealing disrupted connectivity patterns that may have implications for understanding the neural basis of this disorder. These findings may ultimately inform targeted interventions and treatment strategies for individuals with SUD.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377967","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}

{"title":"Machine learning-based real-time task scheduling for Apache Storm","authors":"Cheng-Ying Wu, Qi Zhao, Cheng-Yu Cheng, Yuchen Yang, Muhammad Qureshi, Hang Liu, Genshe Chen","doi":"10.1117/12.3021842","DOIUrl":"https://doi.org/10.1117/12.3021842","url":null,"abstract":"Apache Storm is a popular open-source distributed computing platform for real-time big-data processing. However, the existing task scheduling algorithms for Apache Storm do not adequately take into account the heterogeneity and dynamics of node computing resources and task demands, leading to high processing latency and suboptimal performance. In this thesis, we propose an innovative machine learning-based task scheduling scheme tailored for Apache Storm. The scheme leverages machine learning models to predict task performance and assigns a task to the computation node with the lowest predicted processing latency. In our design, each node operates a machine learning-based monitoring mechanism. When the master node schedules a new task, it queries the computation nodes obtains their available resources, and processes latency predictions to make the optimal assignment decision. We explored three machine learning models, including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Deep Belief Networks (DBN). Our experiments showed that LSTM achieved the most accurate latency predictions. The evaluation results demonstrate that Apache Storm with the proposed LSTM-based scheduling scheme significantly improves the task processing delay and resource utilization, compared to the existing algorithms.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377815","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}

{"title":"Propagation of Laguerre-Gaussian beams through underwater optical turbulence","authors":"Nathaniel Ferlic, A. Laux, Linda J. Mullen","doi":"10.1117/12.3013120","DOIUrl":"https://doi.org/10.1117/12.3013120","url":null,"abstract":"In the ocean, underwater currents are driven by various natural effects attributed to heat transfer through water. The movement of heat subsequently affects light propagation due to changes in the water’s refractive index leading to optical phase distortions. Applications implementing laser beams containing structured phase profiles are prone to being distorted by this underwater optical turbulence. Typical distortions of these beams can include beam wander, intensity and phase variations, and beam spreading that can limit their effectiveness for applications including free-space optical communication, imaging, or sensing. Experimental and theoretical studies have shown optical vortices, a form of structured light, propagate differently through optical turbulence compared with Gaussian beams. Changes in propagation are observed by varying the amount of Orbital Angular Momentum (OAM) a vortex beam carries that increases the beam size as OAM increases. This experimental study intends to fairly compare Laguerre-Gaussian (LG) beams to Gaussian beams after propagation through underwater turbulence by normalizing the initial beam size using the RMS radius. The metrics chosen are the mean scintillation, on-axis intensity, and intensity correlation. Results show the scintillation and on-axis intensity, when chosen at locations along the LG beam annuli, are similar for different LG beams. When the initial beam waist is normalized, the speckle field correlation width and peak correlation energy decreases as RMS radius increases. These results show that structured light is not independent of the effects of beam size and divergence, similar to Gaussian beams, to determine propagation effectiveness or robustness.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379883","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}

{"title":"Adaptive SIF-EKF estimation for fault detection in attitude control experiments","authors":"Alex McCafferty-Leroux, W. Hilal, S. A. Gadsden, Mohammad A. AlShabi","doi":"10.1117/12.3013725","DOIUrl":"https://doi.org/10.1117/12.3013725","url":null,"abstract":"An inherent property of dynamic systems with real applications is their high degree of variability, manifesting itself in ways that are often harmful to system stability and performance. External disturbances, modeling error, and faulty components must be accounted for, either in the system design, or algorithmically through estimation and control methods. In orbital satellite systems, the ability to compensate for uncertainty and detect faults is vital. Satellites are responsible for many essential operations on Earth, including GPS tracking, radio communication/broadcasting, defense, and climate monitoring. They are also expensive to design and fabricate, to deploy, and currently impossible to fix if suddenly inoperable. In being subjected to unforeseen disturbances or minor system failures, communications with Earth can cease and valuable data can be lost. Researchers have been developing robust estimation and control strategies for several decades to mitigate the effects of these failure modes. For instance, fault detection methods can be employed in satellites to detect deviations in attitude or actuator states such that error or incorrect data does not propagate further across its long life cycle. The Kalman Filter (KF) is an optimal state estimation strategy with sub-optimal nonlinear variations, commonly applied in most dynamic systems, including satellites. However, in the presence of aforementioned uncertainties, these optimal estimators tend to degrade drastically in performance, and must be replaced for more robust methods. The newly developed Sliding-Innovation Filter (SIF) is one such candidate, as it has been demonstrated to perform state estimation robustly in faulty systems. Using an in-lab Nanosatellite Attitude Control Simulator (NACS), an adaptive hybrid formulation of the SIF and EKF is applied to a satellite system to detect faults and disturbances in experiments, based on the Normalized Innovation Squares (NIS) metric. This strategy was demonstrated to improve state estimation accuracy in the presence of multiple faults, compared to conventional methods.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376059","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}

{"title":"Exploring MOF-based micromotors as SERS sensors","authors":"Eric R. Languirand, Errie Parrilla, Nathaniel Smith, Matthew D. Collins, Angus Unruh, Lars Lefkowitz, Cecilia H. Phung, Ayusman Sen","doi":"10.1117/12.3017251","DOIUrl":"https://doi.org/10.1117/12.3017251","url":null,"abstract":"Active matter, such as Janus micromotors have been used for applications such as self-assembly, pollution mitigation, and drug delivery. Metal-Organic Framework (MOF)-based Janus micromotors have been recently explored as a method to increase the rate of decontamination for chemical warfare agents in solution due to favorable MOF-chemical interactions. To achieve active-matter decontamination, SiO2@UiO66@Ag MOF-based Janus micromotors were synthesized. In addition to decontamination, the MOF-based micromotors have favorable surface topography for maintaining a localized surface plasmon. This work explores the plasmonic capabilities of Ag@MOF Janus micromotors by systematically changing the amount of Ag, the size of the microparticle that is being used for the plasmonic sensing, and the underlying MOF structure. By changing these parameters, MOF-based micromotors may be able to be used as sensors by utilizing techniques such as Surface Enhanced Raman Spectroscopy (SERS).","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141375914","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}

{"title":"Neural cryptography: vulnerabilities and attack strategies","authors":"L. Beshaj, Gaurav Tyagi","doi":"10.1117/12.3013669","DOIUrl":"https://doi.org/10.1117/12.3013669","url":null,"abstract":"A number of research papers has been published using the architecture of adversarial neural networks to prove that communication between two neural net based on synchronized input can be achieved, and without knowledge of this synchronized information these systems can not be breached. In this paper we will try to evaluate these adversarial neural net architectures when a third party gain access to partial secret key, or a noisy secret key, or has knowledge about loss function, or loss values itself, or activation functions used during training of encryption layers. We explore the cryptanalysis side of it in which we will focus on vulnerabilities a neural-net based cryptography network can face. This can be used in future to improve the current neural net based cryptography architectures. In this paper we show that while the encryption key is necessary to decrypt the messages in neural network domain, the adversarial neural networks can occasionally decrypt messages or raise a concern which will require further training.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381645","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}

{"title":"Low-cost collision avoidance in microverse for unmanned aerial vehicle delivery networks","authors":"Qian Qu, Yu Chen, Xiaohua Li, Erik Blasch, Genshe Chen, Erika Ardiles-Cruz","doi":"10.1117/12.3013124","DOIUrl":"https://doi.org/10.1117/12.3013124","url":null,"abstract":"Unmanned Aerial Vehicles (UAV) have been widely adopted in many applications, from surveillance to delivery. More UAV delivery businesses are expected to be launched in the foreseeable future to meet food, goods, and medicine needs for residents living in smart cities, remote areas, or places lacking runways. As the density of UAVs operating in a community increases, collision avoidance becomes critical concerning the safety of personnel, property, and UAVs. In the last decade, many solutions have been suggested for collision avoidance scenarios, where typical solutions require integrated sensing, information exchange, and on-board decision-making. However, including these essential components increases the cost and makes it unaffordable for small-size UAVs in terms of payload weight and power consumption. Inspired by the Metaverse-enabled by Digital Twins, Blockchain, Augmented Reality (AR)/Virtual Reality (VR), and the fifth generation (5G) wireless communication technologies; we propose LoCASM, a low-cost collision avoidance scheme in Microverse, a local-scale Metaverse, for UAV delivery networks. LoCASM only requests position (GPS), altitude, velocity, and direction (PAVAD) information from each UAV; relieving the burden of expensive and energy-consuming components. By mirroring UAVs’ PAVAD information and the city landscape in the Microverse, the computing-intensive tasks, including UAV tracking, trajectory prediction, and collision avoidance management, are migrated to the Microverse server on the ground. A proof-of-concept prototype of the LoCASM system has been built, and the simulation experimental study has validated the design.","PeriodicalId":178341,"journal":{"name":"Defense + Commercial Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376176","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}