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2025 International Technical Meeting of The Institute of Navigation, ITM 2025

作者： Jia, Qiongqiong Zhao, Yuchen China Civil Aviation University Tianjin Key Laboratory of Intelligent Signal and Image Processing Tianjin300000 China

ISBN: (纸本)9780936406404

Acquisition is a key step for Global Navigation Satellite System (GNSS) receivers to achieve positioning and other functions, and the acquisition speed directly affects the Time To First Fix (TTFF) of the receiver. The acquisition process typically involves generating local reference signals for all satellite signals and matching them with the received signals. For each satellite signal, this matching involves searching in the unknown Doppler frequency and code phase space. Traditional parallel acquisition methods can only perform parallel processing in either the Doppler frequency dimension or the code phase dimension, and still require linear search in the other dimension. To reduce the computational load and improve the acquisition efficiency, this paper proposes a high-efficiency parallel acquisition method based on A-GPS. This method utilizes the auxiliary information provided by the A-GPS base station to convert the linear search of visible star signals in Doppler frequency into a single parallel search in the Doppler search space, thereby reducing the computational load required for acquisition to 1/N of the conventional method, where N is the total number of frequency bands searched. The paper verifies through theoretical analysis and experimental results that the proposed method can significantly improve acquisition efficiency while ensuring acquisition performance. © 2025 Proceedings of the International Technical Meeting of The Institute of Navigation, ITM. All rights reserved.

关键词： Global positioning system

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Design of Dual-mode DPE Receiver Based on GPS L1/BDS B1C signals

Design of Dual-mode DPE Receiver Based on GPS L1/BDS B1C Sig...

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2025 International Technical Meeting of The Institute of Navigation, ITM 2025

作者： Jia, Qiongqiong Guo, Qiqi Tianjin Key Laboratory of Intelligent Signal and Image Processing Civil Aviation University of China Tianjin300000 China

ISBN: (纸本)9780936406404

With the expanding applications of the Global Navigation Satellite System (GNSS), its operating environment has become increasingly complex, with challenges such as multipath effects, non-line-of-sight (NLOS) propagation, and signal attenuation caused by tall urban buildings and trees. This complexity poses additional challenges for traditional GNSS receivers. Direct Position Estimation (DPE) addresses some of the limitations of traditional receivers by accumulating signals from all visible satellites directly in the navigation domain. However, when severe obstructions result in a reduced number of visible satellites, DPE may fail to function properly. The introduction of multiconstellation satellite signals can help mitigate the issue of insufficient visible satellites in complex environments. Based on this, this paper designs a dual-mode DPE receiver utilizing Global Positioning System (GPS) L1 signals and BeiDou Navigation Satellite System (BDS) B1C signals. © 2025 Proceedings of the International Technical Meeting of The Institute of Navigation, ITM. All rights reserved.

关键词： Global positioning system

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Tratamiento de los tumores malignos del oído

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EMC - Otorrinolaringología 2025年第1期54卷 1-12页

作者： G. Creff F. Jegoux Service d’oto-rhino-laryngologie – chirurgie cervicofaciale CHU de Rennes 2 rue Henri-Le-Guilloux 35000 Rennes France MediCIS LTSI (Image and Signal Processing Laboratory) Inserm U1099 2 avenue du Professeur-Léon-Bernard 35043 Rennes France

Los tumores malignos del oído engloban lesiones desarrolladas a partir de entidades anatómicas compuestas por estructuras tisulares diferentes, lo que explica su gran disparidad de forma clínica y, por tanto, de tratamiento. En primer lugar, la mayoría de los tumores del pabellón son tumores cutáneos (carcinoma basocelular, epidermoide, melanoma) y su estrategia diagnóstica y terapéutica es idéntica a la de otras localizaciones de tumores dermatológicos. En el conducto auditivo externo (CAE), las lesiones tumorales simulan la sintomatología de las otitis externas. Se debe realizar una biopsia sistemáticamente en caso de otitis externa refractaria al tratamiento médico bien realizado. En esta localización, además de los tumores cutáneos habituales, se observan los adenocarcinomas y los carcinomas adenoides quísticos, desarrollados a partir de las células ceruminosas y glandulares del CAE. Los tumores del oído medio son menos frecuentes y pueden ser difíciles de diferenciar de los tumores del CAE que invaden el oído medio. Por último, los tumores malignos del conducto auditivo interno son principalmente schwannomas malignos, bien primarios, bien secundarios a la irradiación de un schwannoma benigno. Los tumores del saco endolinfático suelen diagnosticarse de forma tardía, debido a su evolución lenta, y obligan a buscar un síndrome de Von Hippel-Lindau. Los tumores óseos del peñasco suelen ser primarios (sarcomas) o secundarios (metástasis óseas de cánceres de pulmón, gastrointestinales, renales o de mama). Por último, en los niños, el diagnóstico mayoritario es el de histiocitosis de células de Langerhans. Por tanto, la presentación clínica y el tratamiento dependen de la localización tumoral, pero también de la accesibilidad a la biopsia diagnóstica.

关键词： Carcinoma basocelular Carcinoma epidermoide Melanoma Pabellón auricular Conducto auditivo externo Oído medio Conducto auditivo interno Schwannoma Saco endolinfático Histiocitosis de células de Langerhans

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Efficient Fault Detection in Nonlinear Industrial Process: A Reduced Kernel PCA-Based Spectral Clustering Approach

Efficient Fault Detection in Nonlinear Industrial Process: A...

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Artificial Intelligence, Applications, Innovation and Ethics (AI2E), International Conference for

作者： Khadija Attouri Majdi Mansouri Mansour Hajji Kais Bouzrara Laboratory of Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Tunisia Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Muscat Oman Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir Tunisia

ISBN: (数字)9798331513733

ISBN: (纸本)9798331513740

The challenges posed by nonlinearities in industrial systems necessitate innovative techniques that outperform the limitations of traditional methods such as principal component analysis (PCA). While Kernel Principal Component Analysis (KPCA) offers a robust solution to handle nonlinear data, its computational requirements are a significant issue, especially for large-sized datasets. In this work, we propose a novel technique, namely, reduced kernel principal component analysis-based spectral clustering (RKPCA SpC ), to monitor and detect faults in the benchmark Tennessee Eastman process. The suggested approach addresses the complexity associated with KPCA by reducing data size during the model training phase. This reduction involves retaining only the principal components, preserving informative features, and selecting pertinent samples without compromising the original data's content. The efficacy of the proposed method is evaluated through key performance metrics, including false alarm rate (FAR), missed detection rate (MDR), detection time delay (DTD), and computation time (CT). Additionally, gained execution time (GET), gained storage space (GSP), and loss function (LF) are considered, providing a comprehensive assessment of the developed paradigms' effectiveness. The results demonstrate the promising capabilities of our proposed scheme.

关键词： Training Measurement Technological innovation Fault detection Delay effects Computational modeling Complexity theory Kernel Monitoring Principal component analysis

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Short-Term Photovoltaic Power Forecasting-Based Kernel Ridge Regression

Short-Term Photovoltaic Power Forecasting-Based Kernel Ridge...

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Artificial Intelligence, Applications, Innovation and Ethics (AI2E), International Conference for

作者： Manel Marweni Majdi Mansouri Mansour Hajji Mohamed Faouzi Mimouni Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir Tunisia Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Muscat Oman Laboratory of Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kasserine Tunisia

ISBN: (数字)9798331513733

ISBN: (纸本)9798331513740

The modern energy landscape is undergoing a seismic change from traditional, finite energy sources and toward cleaner, renewable alternatives. The restrictions faced by traditional sources, which are not only finite but increasingly shrink in the face of burgeoning global energy demands driven by population increase and industrial expansion, are driving this change. Although promising, renewable energy poses complications, particularly the reliance on climatic conditions. An important aspect of addressing these difficulties is effective energy management within distribution systems, which includes forecasting and optimization phases. This research focuses on forecasting using an advanced machine learning (ML) approach. Accurately forecasting renewable energy generation over time is critical for improving energy management. This technique is evaluated using a variety of performance indicators, including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the Coefficient of Determination (R 2 ). Empirical studies support the method's usefulness, demonstrating noteworthy performance with low error rates.

关键词： Photovoltaic systems Renewable energy sources Technological innovation Accuracy Machine learning Predictive models Forecasting Kernel Energy management Optimization

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Autonomous Path Planning via Sand Cat Swarm Optimization With Multi-Strategy Mechanism for Unmanned Aerial Vehicles in Dynamic Environment

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IEEE Internet of Things Journal 2025年

作者： Deng, Wu Feng, Jiayi Zhao, Huimin Civil Aviation University of China College of Electronic Information and Automation Tianjin300300 China Civil Aviation University of China Tianjin Key Lab Intelligent Signal and Image Processing Tianjin300300 China State Key Laboratory of Rail Transit Vehicle System of Southwest Jiaotong University Chengdu610031 China

Unmanned Aerial Vehicles (UAVs) face critical challenges in path planning in dynamic environment. Sand Cat Swarm Optimization (SCSO) algorithm has demonstrated promise in addressing complex optimization challenges. However, SCSO is limited by slow convergence, susceptibility to local optima, and insufficient adaptability. To overcome these shortcomings, an enhanced SCSO with the spiral search, Livy flight, tent chaotic mapping, and adaptive sparrow alert mechanism, namely TSLS-SCSO is developed to propose an autonomous path planning method for UAVs in dynamic environment. In TSLS-SCSO, a new population initialization strategy with tent chaotic mapping is designed to achieve a large dynamic range and coverage capability. Then a new spiral search strategy is designed to broaden the search range in the search phase. And a new Livy flight strategy is employed to enrich the diversity of population in the attacking prey phase. A new sparrow alert mechanism with integrating the sand cat group with the sparrow alert is designed to obtain faster convergence speed and accuracy. The experiment results on CEC 2017 and CEC 2022 show that the TSLS-SCSO obtains higher accuracy and more stable solutions and exhibits better competitiveness. Furthermore, the proposed UAV path planning method successfully found effective paths with an obstacle avoidance effectiveness of 95.5%. The obtained results validate the effectiveness and competitiveness of TSLS-SCSO in UAV path planning in the dynamic environment. © 2014 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Segmentation of Welding Defects using Level Set Methods

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2012年第6期7卷 1001-1008页

作者： Mohammed, Halimi Naim, Ramou Image and Signal Processing Laboratory. Welding and Control Research Center

Non-destructive testing (NDT) is a technique used in science and industry to evaluate the properties of a material without causing damage. In this paper we propose a method for segmenting radiographic images of welding in order to extract the welding defects which may occur during the welding process. We study different methods of level set and choose the model adapted to our application. The methods presented here take the property of local segmentation geodesic active contours and have the ability to change the topology automatically. The computation time is considerably reduced after taking into account a new level set function which eliminates the re-initialization procedure. Satisfactory results are obtained after applying this algorithm both on synthetic and real images.

关键词： image segmentation Level set Weld defects Radiographic image

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A Novel Construction of Two-Dimensional Z-Complementary Array Code Sets Based on Extended Boolean Functions

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IEEE Transactions on Vehicular Technology 2025年

作者： Tian, Liying Song, Xiaoshi Li, Yubo Zhang, Haijun Northeastern University School of Computer Science and Engineering Shenyang110819 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110189 China Yanshan University School of Information Science and Engineering Qinhuangdao066004 China Hebei Key Laboratory of Information Transmission and Signal Processing Qinhuangdao066004 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China

Two-dimensional (2-D) array sets with good 2-D correlation properties have received considerable attention in wireless communication systems. This paper focuses on 2-D Z-complementary array code sets (ZCACSs), which have ideal 2-D correlation properties within a rectangular zone around the origin. By developing a theory linking 2-D extended Boolean functions with 2-D arrays, we establish an efficient construction of 2-D ZCACSs. In contrast to previous work, the proposed construction is capable of producing 2-D ZCACSs with new flexible parameters. Constructions of three-dimensional (3-D) and higher-dimensional ZCACSs are further investigated. We remark that 2-D and higher-dimensional complete complementary codes (CCCs) can also be generated from the proposed constructions. © 1967-2012 IEEE.

关键词： Codes (symbols)

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EXTRAPOLATION ALGORITHMS FOR DISCRETE signalS WITH APPLICATION IN SPECTRAL ESTIMATION

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND signal processing 1981年第4期29卷 830-845页

作者： JAIN, AK RANGANATH, S Signal and Image Processing Laboratory University of California Davis CA USA

In this paper we present some new algorithms useful for extrapolation and spectral estimation of band-limited sequences in one and two dimensions. First we show that many of the existing extrapolation algorithms for noiseless observations are unified under the criterion of minimum norm least squares (MNLS) extrapolation. For example, the iterative algorithms proposed in [2] and [8]-[10] are shown to be special cases of a one-step gradient algorithm which has linear convergence. Convergence and other numerical properties are improved by going to a conjugate gradient algorithm. For noisy observations, these algorithms could be extended by considering a mean-square extrapolation criterion which gives rise to a mean-square extrapolation filter and also to a recursive extrapolation filter. Examples and application of these methods are given. Extension of these algorithms is made for problems where the signal is known to be periodic. A new set of functions called the periodic-discrete prolate spheroidal sequences (P-DPSS), analogous to DPSS [21], [22], are introduced and their properties are studied. Finally, several of these algorithms are generalized to two dimensions and the relevant equations are given.

关键词： Extrapolation Iterative algorithms Filters signal analysis Least squares methods Convergence of numerical methods Equations Fourier transforms signal processing image processing

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Analyzing Cognitive Patterns in Gifted Children Using MRI and Morphometric Similarity Networks

Analyzing Cognitive Patterns in Gifted Children Using MRI an...

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18th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2025

作者： Han, Shuning Duan, Feng Vilaseca, Gemma Vilaró, Núria Caiafa, Cesar F. Sun, Zhe Solé-Casals, Jordi Data and Signal Processing Research Group University of Vic-Central University of Catalonia Vic Catalonia Spain Image Processing Research Group RIKEN Center for Advanced Photonics RIKEN Saitama Wako-Shi Japan Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation Nankai University Tianjin China Psychological Department Oms and Prat school Fundació Catalunya- La Pedrera Catalonia Manresa Spain Oms Foundation Catalonia Manresa Spain Instituto Argentino de Radioastronomıa-CCT La Plata CONICET / CIC-PBA / UNLP Argentina Faculty of Health Data Science Juntendo University Chiba Urayasu Japan Department of Psychiatry University of Cambridge Cambridge United Kingdom

Advances in non-invasive neuroimaging, such as structural magnetic resonance imaging (sMRI), have en abled the construction of structural brain networks (SBNs), allowing in vivo mapping of anatomical connec tions. This study investigates brain network structural differences linked to different intelligence levels in children by individual morphometric similarity networks (MSNs) derived from sMRI data. Through group and individual-level analyses, we aim to uncover key topological features associated with cognitive perfor mance and to identify a suitable connection density for SBN analysis. Connection density strongly affects global and nodal topological features, with a range of p = 0.05 to 0.15 recommended for stable and optimal results. Gifted individuals exhibit stronger intra-hemispheric and intra-modular connectivity, a more balanced distribution of left-to-right intra-hemispheric connections, and lower mean versatility, supporting efficient and stable cognitive processing. Moreover, anatomical modularity analyses based on von Economo indicate that higher cognitive performance is linked to enhanced connectivity in specific areas (such as secondary sensory area, motor to association area and secondary sensory to limbic area), alongside selective reduction in cer tain modular connections (such as motor to insular area, association to secondary sensory area and motor to secondary sensory area). Furthermore, topological features, including participation coefficient and local effi ciency, are linked to cognitive performance. These findings provide valuable insights into the SBNs underlying cognitive levels in children. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Brain mapping

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