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12th IEEE Region 10 Humanitarian technology Conference, R10-HTC 2024

作者： Govindan, Niranjana Baskaran, Bharathi Azizan, Azizul Yakub, Fitri Dhamanti, Inge Dhaya, C. SRMIST Faculty of Engineering & Technology Department of Computing Technologies Kattankulathur Chennai India Faculty of Intelligence Kuala Lumpur Malaysia Malaysia-Japan International Institute of Technology UTM Electronic System Engineering Department Kuala Lumpur Malaysia Universitas Airlangga Faculty of Public Health Department of Health Policy and Administration Surabaya Indonesia Adhiparasakthi Engineering College Department of Computer Science and Technology Melmaruvathur India

ISBN: (纸本)9798350340204

Algorithmic trading has emerged as a powerful tool for making data-driven trading decisions in financial markets. In this paper, we present an innovative algorithmic trading model for stock price forecasting that integrates forest-based machine learning algorithms with the Golden Ratio strategy. Our proposed approach aims to leverage the predictive power of machine learning while incorporating insights from technical analysis to enhance trading performance and profitability. The methodology involves data collection and preprocessing, feature engineering, model development, and performance evaluation. Historical stock price data, financial indicators, and sentiment analysis data are gathered and pre-processed to ensure data quality. Feature engineering techniques are applied to extract relevant features, and forest-based machine learning algorithms are trained on the data to forecast stock prices. The Golden Ratio strategy is integrated into the trading model to identify the entry point and exit point. Empirical validation and performance evaluation demonstrate the effectiveness and robustness of the proposed approach. Through back testing and simulation-based testing, we evaluate the model's accuracy, profitability, and risk-adjusted returns. Our findings contribute to the advancement of algorithmic trading research and practice, offering insights into the potential benefits of combining machine learning algorithms with established trading strategies. The proposed hybrid model incorporates Golden Ratio Strategy, integrating Random Forest (RF). The results of the proposed random forest with Golden Ratio Strategy are compared with the results of individual model. This comparison helps in proving the efficiency of the proposed model. © 2024 IEEE.

关键词： Adversarial machine learning

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Hybrid Clutter Suppression Technique for FOPEN Target Imaging Radar 6

Hybrid Clutter Suppression Technique for FOPEN Target Imagin...

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6th IEEE Pune Section International Conference, PuneCon 2023

作者： Tingare, Pranavkumar De, Sampurna Bazil Raj, A.A. Defence Institute of Advanced Technology Radar System Laboratory Department of Electronics Engineering Pune411025 India Defence Institute of Advanced Technology Rf Photonics Laboratory Department of Electronics Engineering Pune411025 India

ISBN: (纸本)9798350324204

This paper presents a detailed exploration of Foliage Penetration Radar (FOPEN) technology, focusing on its advancements, challenges, and experimental implementation. Outlining the fundamental principles of radar, underscores the critical role of FOPEN radar in detecting objects concealed beneath dense vegetation. It delves into the challenges faced by FOPEN systems, particularly in discriminating between man-made targets and natural features within vegetation, emphasizes ongoing research efforts to optimize radar frequencies, improve signal processing algorithms. Linear Frequency Modulated Continuous Wave (LFMCW) FOPEN radar system is indigeneously designed, providing insights into its architecture and capabilities. Also, proposed methodology implementing Hybrid Clutter Suppression including noise removal, Doppler processing, and target detection, showcasing promising results in detecting concealed targets behind light foliage. The adaptability of the LFMCW-based FOPEN radar system, as demonstrated in the experimental results, positions it as a valuable tool for applications ranging from military surveillance to civilian geospatial imaging in challenging environments. A research for such systems can be pursued with a focus on minimizing false alarms, understanding the environmental impact, and exploring humanitarian and environmental monitoring applications of FOPEN radar. © 2023 IEEE.

关键词： Radar imaging

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Comparator Design Resistance Mitigation by using Cadence Virtuoso Tools in 45 Nanometer Process technology

Comparator Design Resistance Mitigation by using Cadence Vir...

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2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023

作者： Syn Yi, Michelle Ang Hussin, Razaidi Rokhani, Fakhrul Zaman University Malaysia Perlis Faculty of Electronic Engineering Technology Arau Malaysia University Putra Malaysia UPM Department of Computer and Communications System Engineering Serdang Malaysia

ISBN: (纸本)9798350333312

This paper presents the resistance mitigation techniques for comparator design. Resistance plays an important role to semiconductor field. If resistance value higher than the design specification value, this might cause the electronic device burning and destroy. This project implements the techniques to mitigate resistance for the comparator design layout which are using multiple metal layers for routing, routing track improvement, increase metal width, increase number of vias and using higher metal layer for routing by using Cadence Virtuoso tools in 45 nanometer process technology. Based on the result, the total percentage for resistance mitigation for using multiple metal layers for routing is 73.66%, routing track improvement is 67.67%, increase metal width is 51.74%, increase number of vias is 50% and using higher metal layer for routing is 18.79%. © 2023 IEEE.

关键词： Comparators (optical)

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Artificial-Intelligence-Based Quantitative Fault Diagnosability Analysis of Spacecraft: An Information Geometry Perspective

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 624-635页

作者： Wang, Dayi Fu, Fangzhou Yu, Han Chu, Weimeng Wu, Zhigang Li, Wenbo China Academy of Space Technology Beijing Institute of Spacecraft System Engineering Beijing100094 China Sun Yat-sen University School of Aeronautics and Astronautics Shenzhen518107 China Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China Dalian University of Technology School of Aeronautics and Astronautics Dalian116024 China China Academy of Space Technology Beijing Institute of Control Engineering Beijing100190 China

To provide a theoretical foundation for the design of spacecraft and a reference for their on-orbit adjustment, this study develops methods for the quantitative diagnosability analysis of spacecraft through the introduction of a Riemannian manifold and artificial intelligence into a diagnosability analysis framework. These developed methods have three main advantages. First, they do not rely on any assumption regarding the statistical distribution of the observations. Second, all types of faults can be analyzed without information loss. Third, the computational burden is reduced, making it possible to perform on-orbit fault diagnosability analysis. The effectiveness and feasibility of the proposed methods are then verified via a numerical simulation and a spacecraft attitude control system. © 2020 IEEE.

关键词： Spacecraft

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Postural Implications of Back and Front squat using Biomechanical simulation 5

Postural Implications of Back and Front squat using Biomecha...

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5th IEEE International Conference on Electrical, Computer and Communication Technologies, ICECCT 2023

作者： Renganathan, Gunarajulu Barnamehei, Hamidreza Palani, Poongavanam Kurita, Yuichi Hiroshima University Department of System Cybernetics Higashihiroshima Japan Islamic Azad University Department of Biomedical Engineering Tehran Iran Indian Institute of Technology Madras Department of Engineering Design Chennai India

ISBN: (纸本)9781665493604

Squat is a closed kinetic chain exercise widely used for strength and conditioning applications. This exercise also supports the preparedness for multiple sports. In Physical rehabilitation, squatting is widely incorporated to strengthen the disorders and activate the muscle extensors. This study collected 3D Motion capture data from 5 healthy, trained individuals. Subjects with a history of injury were excluded. The study aims to examine the difference in kinematic variables between Front and Back squats without load conditions and their postural changes. The Kinematic profile was analyzed using computational musculoskeletal software - OpenSim. Based on the statistical results, it is indicated that there is no significant difference in the lower body joints (p0.05), especially the spine. The peak joint angle value for the neck, spine, and shoulder in the sagittal plane during the Front squat were -21.53, 16.22, and 22.31 degrees, and during the Back squat were -31.68, 9.19, and 70.90 degrees, respectively. Further statistical test was performed using the Paired sample t-test, indicating a significant difference in knee, neck, spine, and shoulder. Hence, this study differentiates the joint angle variation during the two squat styles. The existence of a dominant component in the squat technique has been identified which potentially adds value and helps in curating the needs of patients requiring rehabilitative techniques. The variables analyzed in this study help identify additional parameters that aid in the qualitative and quantitative analysis of a dedicated posture restoration scheme, including squatting as part of the prescribed exercises. © 2023 IEEE.

关键词： Patient rehabilitation

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Consensus Control of Multi-Agent systems Using Fault-Estimation-in-the-Loop:Dynamic Event-Triggered Case

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1440-1451页

作者： Yamei Ju Derui Ding Xiao He Qing-Long Han Guoliang Wei Shanghai Key Lab of Modern Optical System the Department of Control Science and EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia Department of Automation BNRistTsinghua UniversityBeijing 100084China College of Science University of Shanghai for Science and TechnologyShanghai 200093China

The paper develops a novel framework of consensus control with fault-estimation-in-the-loop for multi-agent systems(MASs)in the presence of faults.A dynamic event-triggered protocol(DETP)by adding an auxiliary variable is utilized to improve the utilization of communication ***,a novel estimator with a noise bias is put forward to estimate the existed fault and then a consensus controller with fault compensation(FC)is adopted to realize the demand of reliability and safety of addressed ***,a novel consensus control framework with fault-estimation-in-the-loop is developed to achieve the predetermined consensus performance with the l_(2)-l_(∞)constraint by employing the variance analysis and the Lyapunov stability ***,the desired estimator and controller gains are obtained in light of the solution to an algebraic matrix equation and a linear matrix inequality in a recursive way,***,a simulation result is employed to verify the usefulness of the proposed design framework.

关键词： Consensus control dynamic event-triggered protocol(DETP) fault compensation(FC) fault estimation multi-agent systems(MASs)

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GNN-Assisted BiG-AMP: Joint Channel Estimation and Data Detection for Massive MIMO Receiver

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IEEE Transactions on Wireless Communications 2025年第6期24卷 4631-4646页

作者： Liu, Zishen Wu, Nan He, Dongxuan Yuan, Weijie Li, Yonghui Quek, Tony Q. S. School of Information and Electronics Beijing Institute of Technology Beijing100081 China School of System Design and Intelligent Manufacturing Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China School of Electrical and Information Engineering The University of Sydney SydneyNSW2008 Australia Singapore University of Technology and Design 487372 Singapore Department of Electronic Engineering Kyung Hee University Yongin17104 Korea Republic of

In this paper, we develop a graph neural network (GNN)-assisted bilinear inference approach to enhance the receiver performance of the MIMO system through message passing-based joint channel estimation and data detection (JCD). Specifically, based on the bilinear generalized approximate message passing (BiG-AMP) framework and conditional correlation of signal, we propose a GNN-assisted BiG-AMP (GNN-BiGAMP) approach, which integrates a GNN module into the data-detection-loop to compensate the inaccurate marginal likelihood approximation. By leveraging the coupling between the channel and received symbols, a bilinear GNN-assisted BiG-AMP (BiGNN-BiGAMP) JCD receiver is further proposed. This method incorporates two GNNs with similar graph representation into the bilinear posterior estimation loops, which not only compensates for approximation errors but also alleviates performance loss due to premature variance convergence, thereby enhancing the receiver performance significantly. To fully exploit the supervised information from channel estimation and data detection, we propose a multitask learning based training scheme, which coordinates GNNs with different tasks in two loops. Simulation results show that our proposed GNN-assisted JCD receivers significantly outperform other JCD counterparts in terms of both channel estimation and data detection. © 2025 IEEE. All rights reserved.

关键词： Graph neural networks

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Automatic License Plate Detection Using Information Processing system Vision and Deep Learning 2

Automatic License Plate Detection Using Information Processi...

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2nd International Conference on Recent Trends in Microelectronics, Automation, Computing, and Communications systems, ICMACC 2024

作者： Sharma, Avinash Dwivedi, Ishita Dawar, Divya Saxena, Rini Barua, Tarkcshwar Goyel, Parul Chandigarh Engineering Chandigarh Group of Colleges Department of information processing system Science and Engineering Mohali140307 India Mohali140307 India Roorkee Institute of Technology Computer Science & Engineering Department Roorkee India M. M. Engineering College Maharishi Markandeshwar University CSE Department Mullana Haryana Ambala133207 India

ISBN: (纸本)9798350366570

The content of this probe is to overcome the current cognitive content with ALPR playacting, with a special accent on developing a dead and impelling playacting for distinguishing License plates from video film. The study attempts to ameliorate the presentation norms of ALPR technology by utilizing the powerful accumulation of optical character identification (OCR)[20] and deep learning based object detection algorithmic program. The core of this occupation is the use of the cutting-edge YOLOv8. object distinguishing hypothesis, which has been pains taking and disciplined on an unequaled dataset premeditated with License plate detection in mind. Focusing on quality and efficiency, the YOLOv8 model accomplish an amazing 99.8 quality rate when it comes to accurately localization and categorization License plates[18] inside video frames. This occupation aims to formalize the willingness and dependability of the advisable ALPR playacting through extensive scientific research. The project aims to intensify ALPR technology and determinant the forthcoming of transport and police investigation playactings[18] by breaking through current obstruction and establishing new presentation norms. © 2024 IEEE.

关键词： Deep learning

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Deformation Behavior of Tool and Workpiece in Plate Compression 14th

Deformation Behavior of Tool and Workpiece in Plate Compress...

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14th International Conference on technology of Plasticity, ICTP 2023

作者： Hakoyama, Tomoyuki Jo, Kenta Yoshikawa, Yasuharu Wang, Zhigang Department of Mechanical Engineering Faculty of Engineering Gifu University Tokai National Higher Education and Research System Gifu501-1193 Japan Department of Materials Science and Processing Graduate School of Natural Science and Technology Gifu University Tokai National Higher Education and Research System Gifu501-1193 Japan Department of Mechanical Engineering Meijo University Aichi468-0073 Japan

ISBN: (纸本)9783031410222

The influence of the combinations of the materials of plate and die on the deformation behavior during unloading in compression of a plate with a high ratio between the diameter and the thickness is investigated by simulations. A plate becomes thicker by elastic recovery during unloading in plate compression for a small ratio of thickness reduction in loading. On the other hand, a plate becomes thinner by the additional compression caused by the elastic recovery of die during unloading for a large ratio of thickness reduction in loading. The turning points by the ratio of thickness reduction from thicker to thinner during unloading depend on the combination of the materials of plate and die. The amount of thickness reduction during unloading is evaluated using the increase in plate diameter during unloading. Increase in plate diameter is large for the conditions that the friction hill in loading is large. Deformation behaviors of a plate using crown dies which are designed to obtain a uniform thickness plate are also investigated. The additional reduction of the thickness during unloading contributes the flatness of the plate. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Low carbon steel

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Development of Portable Tethered Vertical Profiler for Underwater Monitoring 2

Development of Portable Tethered Vertical Profiler for Under...

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2nd International Conference for Advancement in technology, ICONAT 2023

作者： Sequeira, Steevan Loyd Manish, E.S. Rakshith Umesh, Pruthviraj Gangadharan, K.V. National Institute of Technology Department of Mechanical Engineering Karnataka Surathkal India National Institute of Technology Centre for System Design Karnataka Surathkal India National Institute of Technology Department of Water Resources and Ocean Engineering Karnataka Surathkal India

ISBN: (纸本)9781665475174

Human activities and industrial waste flow to water bodies will contaminate the coastal areas, leading to changes in the underwater ecosystem and affecting aquatic habitats. Understanding these ecosystems requires quick data collection, systematic process monitoring, and coastal resource preservation through proper decision-making. We can understand the variation of water properties with depth by deploying sensors from the surface, one of the most popular methods of gathering ocean data. However, high-resolution oceanographic data collection and long-term human observations are risky and expensive. Although some autonomous profiling systems address these issues, there is still scope for developing practical, affordable, and accurate data-providing systems. This paper discusses an open-source, economical, easily portable, propeller-driven underwater Vertical Profiler controlled by a joystick located in Ground Control system (GCS) using a Neutrally buoyant tether cable. Data from sensors, like temperature, pressure, and depth, are collected. The paper also discusses functionality and sensor tests conducted on the developed vehicle at a controlled environment/test site. The developed Profiler can perform basic manoeuvres and collect water quality data upstream of vented dams and rivers in and around the Dakshina Kannada district of Karnataka, India. © 2023 IEEE.

关键词： Water quality

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