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conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations applications IV

作者： Jameson, Stephen M. Crozier, Matthew D. Plunkett, Mary E. BAE Syst Inc 8201 Greensboro Dr 1200 Mclean VA 22102 USA

ISBN: (纸本)9781510651036;9781510651029

Future conflicts involving Joint All-Domain Operations (JADO) will require an unprecedented scale of standoff targeting against hardened, mobile, and dynamic targets that will only be possible through effective use of sensing, command and control (C2), and targeting assets across multi-domain (space/air/ground/sea) kill chains. Technologies such as Artificial Intelligence and Autonomy are critical to enabling effective, scalable, and timely kill chains, but only if applied appropriately to address kill chain limitations, informed by quantitative system of systems modeling and simulation at the data level. To address these challenges, BAE systems is developing a Virtual System of systems Testbed to enable detailed quantitative mission level analysis of kill chain performance in a variety of multi-domain scenarios, combining high fidelity platform and sensor simulation with detailed modeling of information flows through the kill chain. The Testbed uses Bohemia Interactive Simulation's Virtual Battlespace 4 (VBS4) to model virtual physical entities, and uses the VBS4 Simulation SDK to pass dynamic scenario data messages for real-time processing by advanced algorithm plug-ins including AI-based information dissemination and Autonomous mission management. In this paper, we will describe the challenges posed by JADO and the critical importance of system of system analysis to inform the application of advanced algorithmic technologies. We discuss the rationale and architecture of the Virtual System of systems testbed, the technologies incorporated, and the methodologies for system of systems analysis. We will present results assessing system of systems contribution of these technologies to improving mission-level metrics such as latency, scalability, and robustness of kill chain response.

关键词： JADO JADC2 System of systems kill chain simulation autonomy AI/ML

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22nd International conference on Next Generation Teletraffic and Wired/Wireless advanced Networks and systems, NEW2AN 2022

22nd International Conference on Next Generation Teletraffic...

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22nd International conference on Next Generation Teletraffic and Wired/Wireless advanced Networks and systems, NEW2AN 2022

ISBN: (纸本)9783031302572

The proceedings contain 58 papers. The special focus in this conference is on Next Generation Teletraffic and Wired/Wireless advanced Networks and systems. The topics include: TEDCTSSA: Trust Enabled Data Collection Technique Based Sparrow Search Algorithm for WSN-Based applications;ISTOA: An Improved Sooty Tern Optimization Algorithm for Multilevel Threshold Image Segmentation;implementing Digital Transformation in the Logistics System of Uzbekistan;Numerical Modeling of Vertical Axis Wind Turbines Using ANSYS Fluent Software;"i’ll wait 4 ur answr!" A Study on Modern Style of Cyber-Writing and User Reactions;improvement of Information Support in Intelligent Information Energy systems;the Assessment of the Effectiveness of the Development of Digital Technologies in Commercial Banks of Uzbekistan;the Study of the Impact of the Digital Economy on the Growth of E-Government Services in Uzbekistan;deep Learning Algorithm for Classifying Dilated Cardiomyopathy and Hypertrophic Cardiomyopathy in Transport Workers;comparison of Finite Difference Schemes of Different Orders of Accuracy for the Burgers Wave Equation Problem;eCommerce Benchmarking: Theoretical Background, Variety of Types, and Application of Competitive-Integration Benchmarking;cryptocurrencies as the Money of the Future;a Data Security Technique Combining Asymmetric Cryptography and Compressive Sensing for IoT Enabled Wireless sensor Networks;energy Efficient and Secure Scheme Based Compressive Sensing Method for Internet of Vehicles;impact of Digital Technologies on Women’s Employment;the Impact of Digitalisation on the Safe Development of Individuals in Society;econometric Evaluation of the Efficiency of the Management of the Enterprise Through the Supply of Raw Materials in Oil Enterprises in the Conditions of the Digital Economy;on Digital Twin Software and Cyber Threats.

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INFLUENCE OF SYNTHESIS CONDITIONS ON THE CHEMICAL STRUCTURE AND COMPOSITION OF ZnO NANOPARTICLES COMPOSITE systems / POLYMER FIBERS

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ARCHIVES OF METALLURGY AND MATERIALS 2022年第2期67卷 601-606页

作者： Calin, G. Sachelarie, L. Olaru, N. Apollonia Univ Iasi Fac Dent Med 11 Pacurari Str Iasi 700511 Romania Inst Macromol Chem Petru Poni Iasi Aleea Grigore Ghica Voda 41A Iasi 700487 Romania

Nanostructured systems based on ZnO nanoparticles composite systems/polymer fibers have attracted a lot of attention in the last years because of their applications in multiple areas. Nanofibres based on polymers are used in many domains such as nanocatalysis, controlled release of medicines, environmental protection and so on. This work show the synthesis of cellulose acetate butyrate (CAB) nanofiber useful as substrates for growing ZnO nanocrystals and that ZnO is an unorganic metal oxide nanoparticle used to improve the piezoelectric properties of the polymer. The piezoelectric propertiesof ZnO-doped polymeric was investigated with atomic force microscopy and measurements were performed, in contact technique, in piezoelectric response mode (PFM).In order to analyze the structural and textural features, the obtained materials were characterized using advanced physical-chemical techniques such as x-ray diffraction (xRD), Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM). The xRD patterns show the characteristic reflections of ZnO with a hexagonal type wurtzit structure and the broad peaks of the polymer. The SEM images reveal the presence of ZnO nanoparticles on top of the polymer *** most ZnO-based nanocomposites their morphology is uncontrolled (agglomerated granules), but in ase of using cellulose acetobutyrate this becomes controlled by observing through flower-like structures SEM and AFM) The study of the functional properties of ZnO/polymer fiber composite systems showed that they have piezoelectric properties which give them the characteristics of smart material with possible sensor and actuator *** literature reports that the synthesis and characterization of ZnO-polymer nanocomposites are more flexible materials for various applications.

关键词： polymer nanofibres composite ZnO polimer nanocomposites

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sensor-Agnostic Graph-Aware Kalman Filter for Multi-Modal Multi-Object Tracking 27th

Sensor-Agnostic Graph-Aware Kalman Filter for Multi-Modal Mu...

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27th International conference on Pattern Recognition, ICPR 2024

作者： Sani, Depanshu Iyer, Anirudh Rai, Prakhar Anand, Saket Srivastava, Anuj Kalyanaraman, Kaushik IIIT-Delhi New Delhi India Florida State University Tallahassee United States

ISBN: (纸本)9783031784439

Recent progress in open-source object detection techniques has significantly advanced Multi-Object Tracking (MOT) methodologies, primarily under the tracking-by-detection paradigm. To enhance the robustness and reliability of MOT systems, recent research has proposed integrating information gathered from diverse sensors. However, many Kalman filter-based MOT approaches assume the independence of object trajectories, overlooking potential inter-object relationships. While some efforts have been made to incorporate these relationships, they often concentrate on learning feature representations to facilitate better association. Moreover, the existing filter-based method for estimating graphs from noisy data is unsuitable for online MOT applications. To alleviate these problems, we introduce a sensor Agnostic Graph-Aware (SAGA) Kalman filter, which is the first online state estimation technique designed to fuse multi-modal graphs derived from noisy multi-sensor data. We validate the effectiveness of our proposed framework through extensive experiments conducted on both synthetic and real-world driving dataset (nuScenes). Our results showcase an improvement in MOTA and a reduction in estimated position errors (MOTP) and identity switches (IDS) for tracked objects using the SAGA-KF. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Kalman filters

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Map Merge and Accurate Localization in Multi-robot systems in Real Environments 6th

Map Merge and Accurate Localization in Multi-robot Systems i...

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6th Iberian Robotics conference (Robot)

作者： Martinelli, Dieisson Kalempa, Vivian Cremer de Oliveira, Andre Schneider Fed Univ Technol Parana UTFPR Ave Sete Setembro 3165 Curitiba Parana Brazil Univ Estado Santa Catarina UDESC Luiz Fernando Hastreiter St 180 Sao Bento Do Sul SC Brazil

ISBN: (纸本)9783031586750;9783031586767

This article presents an approach to map merged and precise position determination in multi-robot systems operating in real environments, using the matrix transformation technique and Particle Swarm Optimization (PSO). The primary objective is to combine information from multiple maps, represented by occupancy matrices, into a unique and comprehensive map. This map can be employed in applications that require cooperation and coordination among robots. To achieve the proposed objective, the PSO technique is applied to find the optimal values of rotation (psi), translation along the x-axis (dx), and translation along the y-axis ( dy) to optimize the map merged. The map merged is performed based on identified correspondences between the maps, using the Jaccard Similarity algorithm. The PSO approach is employed in this work to determine the best possible overlap between the maps. After obtaining the transformation values, they are used to find and update the real positions of the robots on the resulting fused map. Consequently, the proposed technique provides an advanced and efficient solution for map merged and robot positioning in real environments. This approach opens doors for the application of effective cooperation techniques and intelligent navigation for multiple robots in complex and dynamically changing scenarios. An experiment video has been produced and can be accessed through the following link https://***/RLQsJhlnMuQ.

关键词： Mobile robots multi-robot systems merge maps

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Experimental Study of a LoRa Based Wireless sensor Network for Low Power Localization in an Outdoor Environment 2

Experimental Study of a LoRa Based Wireless Sensor Network f...

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2nd International conference on Electronics, Energy and Measurement, IC2EM 2023

作者： Tobbal, Abdelhafid Bengherbia, Billel Bouziani, Anis Cherifi, Youcef University Yahia Fares of Medea Research Laboratory in Advanced Electronics Systems Lsea Medea Algeria

ISBN: (纸本)9798350314243

The Internet of Things (IoT) and Wireless sensor Network (WSN) have transformed industries by highlighting their crucial roles in sensing, communication, and data-driven decisions. One paramount feature in WSN is localization, enabling precise positioning of devices in real-world applications. Global Positioning systems (GPS) have long been the mainstay of high-precision localization, but their high energy consumption is a significant obstacle to their seamless integration with low-power devices. In the quest for suitable solutions, Low Power Wide Area Networks (LPWAN) have emerged as key players, providing energy-efficient connectivity. However, these advances raise questions about the localization accuracy within these networks. In this paper, we present the implementation of WSN based on Long Range (LoRa) technology to estimate the position of an object in an outdoor environment. We took advantage of LoRa technology to collect Received Signal Strength Indicator (RSSI) measurements over a long distance. An Artificial Neural Network (ANN) is then trained on a collected dataset to estimate the 2-dimensional position of the object. The results show an estimate of the position with an average absolute error of 40.5 meters in an area of 360 meters by 360 meters. A web interface is made with Node-Red to monitor the position of the mobile object. © 2023 IEEE.

关键词： Internet of things

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Design and Optimization of Antenna for Short Range applications in Ultra Wide Band 4

Design and Optimization of Antenna for Short Range Applicati...

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4th International conference on Smart Electronics and Communication, ICOSEC 2023

作者： Srividhya, R. Bennet, M. Anto Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350300888

This study presents the design and analysis of an Ultra-Wide Band (UWB) antenna specifically tailored for short-range communication applications. UWB technology enables high-speed data transmission and precise positioning capabilities, making it suitable for a wide range of applications such as wireless sensor networks, radar systems, and indoor localization. The proposed UWB antenna is designed to operate over a frequency range of 3.1 GHz to 10.6 GHz, covering the entire UWB spectrum allocated by regulatory bodies. The antenna is based on a compact planar structure, allowing for easy integration into small devices. It consists of a modified printed monopole radiator with a tapered shape and a ground plane with specific slots for impedance matching and radiation pattern optimization. Simulation tools such as ADS (advanced Design System) and electromagnetic modeling techniques are employed to analyze the antenna's performance parameters, including return loss, radiation pattern, and gain. The antenna design is optimized to achieve a low return loss and high radiation efficiency across the UWB frequency range. Additionally, specific techniques such as impedance matching and radiation pattern shaping are implemented to enhance the antenna's overall performance. The fabricated prototype of the UWB antenna is tested and evaluated using experimental measurements. The results demonstrate that the antenna achieves excellent performance characteristics, including a wide bandwidth, omni-directional radiation pattern, and good impedance matching. These features make it suitable for short-range communication applications, where high data rates and precise localization are required. In conclusion, this research presents a compact and efficient UWB antenna design for short-range applications. The proposed antenna offers excellent performance characteristics, making it a promising candidate for various wireless communication systems and localization applications in indoor environm

关键词： Ultra-wideband (UWB)

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Estimation Network Design framework for efficient distributed optimization 63

Estimation Network Design framework for efficient distribute...

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63rd IEEE conference on Decision and Control, CDC 2024

作者： Bianchi, Mattia Grammatico, Sergio Automatic Control Laboratory Eth Zürich Switzerland Tu Delft Delft Center for Systems and Control Netherlands

ISBN: (纸本)9798350316339

Distributed decision problems feature a group of agents that can only communicate over a peer-to-peer network, without a central memory. In applications such as network control and data ranking, each agent is only affected by a small portion of the decision vector: this sparsity is typically ignored in distributed algorithms, while it could be leveraged to improve efficiency and scalability. To address this issue, our recent paper [1] introduces Estimation Network Design (END), a graph theoretical language for analysis and design of distributed iterations. END methods can be tuned to exploit the sparsity of specific problem instances, reducing communication overhead and minimizing redundancy, yet without requiring case-by-case convergence analysis. In this paper, we showcase the flexibility of END in the context of distributed optimization. In particular, we study the sparsity-aware version of many established algorithms, including ADMM, AugDGM and PushSum DGD. Simulations on an estimation problem in sensor networks demonstrate that END algorithms can boost convergence speed and greatly reduce the communication cost. © 2024 IEEE.

关键词： Peer to peer networks

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Impact of Class Balancing on Intrusion Detection System for WSN-BFSF Dataset

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SN Computer Science 2024年第8期5卷 1105页

作者： Soni, Vaishali Kukreja, Deepika Malhotra, Amarjit Department of Information Technology Netaji Subhas University of Technology Dwarka Delhi India

Wireless sensor Networks (WSNs) are crucial to various applications within the Internet of Things (IoT), Industry 4.0, Cyber-Physical systems (CPS), and smart manufacturing. The rising incidences of cyber-attacks highlight the critical need for advanced security measures in WSNs. This study aims to develop a robust Intrusion Detection System (IDS) that leverages Machine Learning (ML) techniques to safeguard WSNs from network intrusions. In 2023, the WSN-BFSF dataset, which includes data on normal traffic and blackhole, selective forwarding, and flooding attacks, became available. As a crucial defense for securing WSNs, IDS detects and mitigates attacks by constantly monitoring network traffic for unusual activity, identifying specific attack patterns, and quickly isolating malicious nodes while updating routing protocols. This research proposes a novel IDS mechanism that employs the Synthetic Minority Oversampling Technique (SMOTE) for class balancing on the WSN-BFSF dataset. Class balancing enhances intrusion detection by reducing bias toward majority classes. Our new IDS model is compared to the original research that introduced the WSN-BFSF dataset. The results show significant performance improvements across various ML algorithms: Precision increased by 2.23–12.40%, Recall by 0.64–5.01%, F1-score by 3.63–9.12%, and overall accuracy by an average of 3.97%. These findings indicate that class balancing offers promising results for improving intrusion detection in WSNs. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Class balancing Intrusion detection Machine learning (ML) SMOTE Wireless sensor Networks

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Enhancing Human Pose Estimation Accuracy Using Synthetic Data 50

Enhancing Human Pose Estimation Accuracy Using Synthetic Dat...

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50th Annual conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Meiramov, Rakhat Balgabekova, Zarema Varol, Huseyin Atakan Yazici, Adnan Institute of Smart Systems and Artificial Intelligence Nazarbayev University Astana Kazakhstan Department of Computer Science Nazarbayev University Astana Kazakhstan

ISBN: (纸本)9781665464543

In industrial applications, Human Pose Estimation (HPE) is crucial for enhancing both automation and human-computer interaction. This study investigates the impact of synthetic data on HPE model efficacy, particularly examining the performance of the YOLOv8 algorithm. Using Nvidia Omniverse Isaac Sim, we created a synthetic dataset called ISAAC, designed for various complex scenarios. This tool was chosen for its ability to simulate highly realistic and intricate industrial contexts with advanced physics and AI capabilities. The inclusion of this synthetic dataset significantly enhances model accuracy, evidenced by up to a 19% increase in mean Average Precision (mAP) at an Intersection over Union (IoU) of 0.5, and a 12% improvement across the 0.5-0.95 IoU range compared to traditional datasets. These results highlight the substantial advantages of synthetic data in training more accurate and robust HPE models, advocating for the integration of innovative data solutions in the field of computer vision. © 2024 IEEE.

关键词： Computer Vision Human Pose Estimation Nvidia Omniverse Synthetic Data

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