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International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering

作者： Leonid G.Dorosinskiy Nadezhda V. Budyldina Urals Technical Institute of Communication and Informatics Yekaterinburg Russia

ISBN: (纸本)9781509040704

The paper deals with an algorithm for detection of a broadband signal received from a multiple-unit source against the background with architecturally-like clutters that differ by location and additive space-uncorrelated noise. It is shown that the optimal detection algorithm represents the weight processing in the ?ray space? of the transformed vector of observed data and does not demand access of any large matrix. A maximum likelihood ratio is chosen as the optimality criterion. After determining the inverse of the correlation function, expression for the optimal weight function is obtained. The design ratios for determination of detection characteristics under the Gaussian statistics of signals and clutters are given. The results confirm the property of the suggested algorithm: at low signal/noise ratios, efficiency of point targets detection is better, and at the large ratios the distributed targets are better detected.

关键词： detection algorithm distributed clutter

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A Novel Partial Shading detection algorithm Utilizing Power Level Monitoring of Photovoltaic Panels

A Novel Partial Shading Detection Algorithm Utilizing Power ...

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International Power Electronics Conference

作者： Thusitha Randima Wellawatta Sung-Jin Choi School of Electrical Engineering University of Ulsan Ulsan South Korea

Maximum power point tracking (MPPT) under partial shading condition (PSC) is a challenging research topic in the PV array system. As the shaded PV module makes different peak patterns on the power versus voltage curve and misguides the MPPT algorithm, various kinds of global MPP (GMPP) detecting algorithms have been studied. Generally, too frequent execution of the GMPP tracking algorithm reduces the achievable power of PV module due to time spent on the scanning process. Thus, the partial shading detection algorithm is essential for efficient utilization of solar energy source. Based on the theoretical investigation of the characteristic curve patterns under various partial shading conditions, this paper presents a new detection algorithm utilizing power level monitoring. While conventional methods only focus on fast shading patterns, the proposed algorithm always shows superb performance regardless of the partial shading patterns.

关键词： Novel Partial Shading detection algorithm Photovoltaic Panels

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Robust automatic crater detection at all latitudes on Mars with deep-learning

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PLANETARY AND SPACE SCIENCE 2025年 260卷

作者： Martinez, L. Andrieu, F. Schmidt, F. Talbot, H. Bentley, M. S. Univ Paris Saclay CNRS GEOPS F-91405 Orsay France Inst Univ France IUF Paris France CentraleSupelec Paris Saclay Univ Inria Gif Sur Yvette France European Space Astron Ctr Camino Bajo CastilloUrb Villafranca CastilloVill Madrid 28692 Spain

Understanding the distribution and characteristics of impact craters on planetary surfaces is essential for unraveling geological processes and the evolution of celestial bodies. Several machine learning and AI-based approaches have been proposed to detect craters on planetary surface images automatically. However, designing a robust tool for an entire complex planet such as Mars, is still an open problem. This article presents a novel approach using the Faster Region-based Convolutional Neural Network (Faster R-CNN) for such a detection. The proposed method involves the pre-processing, training and crater detection steps, which are especially designed for robustness regarding latitude and complex geomorphological features. The objectives of this studies are to (i) be robust at all latitudes and (ii) for >= 1 km diameter crater sizes. (iii) To propose an open-source and re-usable algorithm that (iv) only needs an image to run. Extensive experiments on high-resolution planetary imagery demonstrate excellent performances with an average precision AP(50)>0.82 with an intersection over union criterion IoU >= 0.5, irrespective of crater scale. For mid and high latitudes (higher than 48 degrees north and south), performance decreases down to AP(50)similar to 0.7, which is still better than the current state of the art. Loss of performance is mostly due to strong shadowing effects. Our results also highlight the versatility and potential of our robust model for automating the analysis of craters across different celestial bodies. The automated crater detection tool presented in this article is publicly available as open-source and holds great promise for future scientific research of space exploration missions.

关键词： detection algorithm Impact craters Computer vision Artificial intelligence

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Entropic detection of chromatic community structures

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JOURNAL OF COMPLEX NETWORKS 2025年第1期13卷

作者： Delaplace, Franck Univ Evry Paris Saclay Univ IBISC Lab Evry Courcouronnes France

The identification of community structure represents a central challenge in the field of complex networks. The objective is to ascertain the internal organization of agents within a network and to provide a representative network partition. Each community is presumed to comprise nodes sharing a common objective or property. The identification of these communities is typically based on the difference in connectivity density between the interior and border of a community. Indeed, nodes sharing a common purpose or property are expected to interact closely. Although this rule appears to be relevant, it nevertheless fails to address fundamental scientific problems such as disease module detection, thereby highlighting the inability to meaningfully determine communities based solely on connectivity for this situation. Consequently, another paradigm is necessary to formalize this problem accurately and detect these communities objectively. In this article, we propose a new framework to study this novel community formation property. Considering that colors represent shared properties, the problem is to maximize groups of nodes of the same color within communities. We propose a novel algorithm for detecting community structure based on a new measurement, chromatic entropy, which quantitatively assesses the community structure based on color constraint.

关键词： community structure detection algorithm colored graph

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Patch-Wise Deep Learning Method for Intracranial Stenosis and Aneurysm detection-the Tromsø Study

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NEUROINFORMATICS 2025年第1期23卷 1-9页

作者： Bernecker, Luca Mathiesen, Ellisiv B. Ingebrigtsen, Tor Isaksen, Jorgen Johnsen, Liv-Hege Vangberg, Torgil Riise UiT Arctic Univ Norway Dept Clin Med Tromso Norway Univ Hosp North Norway PET Imaging Ctr Tromso Norway Univ Hosp North Norway Dept Radiol Tromso Norway Univ Hosp North Norway Dept Neurol Tromso Norway Univ Hosp North Norway Dept Neurosurg Ophthalmol & Otorhinolaryngol Tromso Norway

Intracranial atherosclerotic stenosis (ICAS) and intracranial aneurysms are prevalent conditions in the cerebrovascular system. ICAS causes a narrowing of the arterial lumen, thereby restricting blood flow, while aneurysms involve the ballooning of blood vessels. Both conditions can lead to severe outcomes, such as stroke or vessel rupture, which can be fatal. Early detection is crucial for effective intervention. In this study, we introduced a method that combines classical computer vision techniques with deep learning to detect intracranial aneurysms and ICAS in time-of-flight magnetic resonance angiography images. The process began with skull-stripping, followed by an affine transformation to align the images to a common atlas space. We then focused on the region of interest, including the circle of Willis, by cropping the relevant area. A segmentation algorithm was used to isolate the arteries, after which a patch-wise residual neural network was applied across the image. A voting mechanism was then employed to identify the presence of atrophies. Our method achieved accuracies of 76.5% for aneurysms and 82.4% for ICAS. Notably, when occlusions were not considered, the accuracy for ICAS detection improved to 85.7%. While the algorithm performed well for localized pathological findings, it was less effective at detecting occlusions, which involved long-range dependencies in the MRIs. This limitation was due to the architectural design of the patch-wise deep learning approach. Regardless, this can, in the future, be mitigated in a multi-scale patch-wise algorithm.

关键词： Intracranial Stenosis Aneurysms Deep learning detection algorithm

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Active RIS Assisted Index Modulation for Wireless Communication System

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IEEE WIRELESS COMMUNICATIONS LETTERS 2025年第2期14卷 420-424页

作者： Wu, Yun Zhang, Xiao Bai, Enjian Hai, Han Donghua Univ Sch Informat Sci & Technol Shanghai 201620 Peoples R China

Index modulation and reconfigurable intelligent surfaces (RIS) have garnered significant attention in recent years due to their promising potential in advancing wireless communications. In this letter, we combine these two techniques and propose an amplification factor-indexed modulation (AFIM) scheme to improve the spectral efficiency in active RIS (A-RIS) aided systems, where the optimized amplification factor of A-RIS is modulated to transmit additional information bits. A closed-form expression for the average bit error probability of AFIM is derived. Furthermore, we extend AFIM to an A-RIS assisted hybrid index modulation (A-RIS-HIM) system, which incorporates reflecting modulation and receive spatial modulation. Besides, two low-complexity detectors based on greedy detection (GD) are proposed for the A-RIS-HIM system. Simulation results are provided to substantiate the effectiveness of the proposed scheme in terms of bit error rate.

关键词： Modulation Reconfigurable intelligent surfaces Indexes Signal to noise ratio Reflection Error probability Vectors Receiving antennas Detectors Bit error rate Active RIS index modulation performance analysis detection algorithm

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A fast algorithm for community detection in temporal network

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2015年 429卷 87-94页

作者： He, Jialin Chen, Duanbing Univ Elect Sci & Technol China Web Sci Ctr Chengdu 611731 Peoples R China Univ Elect Sci & Technol China Big Data Res Ctr Chengdu 611731 Peoples R China

Many complex systems can be investigated using the framework of temporal networks, which consist of nodes and edges that vary in time. The community structure in temporal network contributes to the understanding of evolving process of entities in complex system. The traditional method on dynamic community detection for each time step is independent of that for other time steps. It has low efficiency for ignoring historic community information. In this paper, we present a fast algorithm for dynamic community detection in temporal network, which takes advantage of community information at previous time step and improves efficiency while maintaining the quality. Experimental studies on real and synthetic temporal networks show that the CPU running time of our method improves as much as 69% over traditional one. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Complex systems Temporal networks Dynamic community Community structure detection algorithm

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A hybrid algorithm for fast detection and classification of voltage disturbances in electric power systems

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EUROPEAN TRANSACTIONS ON ELECTRICAL POWER 2011年第1期21卷 555-564页

作者： Pouresmaeil, Edris Akorede, Mudathir Funsho Hojabri, Mojgan Univ Ilorin Dept Elect Engn Ilorin Nigeria Univ Politecn Cataluna Ctr Technol Innovat Static Converters & Drives CI Barcelona Spain Univ Putra Malaysia Dept Elect & Elect Engn Upm Serdang Selangor Malaysia

To minimize the adverse impacts of power quality disturbances on the electric power supply as well as on the customer equipment, there is clearly a need for detection and classification of such problems. In this paper, a fast detection algorithm for power quality disturbances is presented. The proposed method is a hybrid of two algorithms, abc-0dq transformation and 90 degrees phase shift algorithms. The proposed algorithm is fast and reliable in detecting most voltage disturbances in power systems such as voltage sags, voltage swells, interrupts, flicker, harmonics, etc. In the proposed approach, the three-phase utility voltages are sensed separately by each of the algorithms. These algorithms are combined to explore their individual strengths for a better performance. When a disturbance occurs, both algorithms work together to recognize this distortion and send trip signals to static transfer switches. This control method can be used for critical loads protection in case of utility voltage distortion. Simulation and analysis results obtained in this study illustrate high performance of the strategy in different single-phase and three-phase voltage distortions. Copyright (C) 2010 John Wiley & Sons, Ltd.

关键词： power quality voltage disturbance detection algorithm sag swell abc-0dq transformation

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Two-Step Pairing algorithm for Target Range and Velocity detection in FMCW Automotive Radar

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2015年第3期E98A卷 801-810页

作者： Hyun, Eugin Oh, Woojin Lee, Jong-Hun DGIST Daegu South Korea KiT Gumi Si Gyeongsangbuk D South Korea

In automotive frequency modulated continuous wave (FMCW) radar based on multiple ramps with different slope, an effective pairing algorithm is required to simultaneously detect the target range and velocity. That is, as finding beat-frequencies intersecting at a single point of the range-Doppler map, we extract the range and velocity of a target. Unlike the ideal case, however, in a real radar system, even though multiple beat frequencies are originated from the same target, these beat frequencies have many different intersection values, resulting in mismatch pairing during the pairing step. Moreover, this problem also reduces the detection accuracy and the radar detection performance. In this study, we found that mismatch pairing is caused by the round-off errors of the range-beat frequency and Doppler frequency, as well as their various combinations in the discrete frequency domain. We also investigated the effect of mismatch pairing on detection performance, and proposed a new approach to minimize this problem. First, we propose integer and half-integer frequency position-based pairing method during extraction of the range and Doppler frequencies in each ramp to increase detection accuracy. Second, we propose a window-based pairing method to identify the same target from range-Doppler frequencies extracted in the first step. We also find the appropriate window size to overcome pairing mismatch. Finally, we propose the method to obtain a higher accuracy of range and velocity by weighting the values determined in one window. To verify the detection performance of the proposed method by comparison with the typical method, simulations were conducted. Then, in a real field test using the developed radar prototype, the detection probability of the proposed algorithm showed more than 60% improvement in comparison with the conventional method.

关键词： FMCW radar pairing multi-target two-step detection algorithm detection probability

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An algorithm for the automatic detection of inclusions in an inspected object with a scanning digital X-ray imaging system (one-dimensional variant)

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RUSSIAN JOURNAL OF NONDESTRUCTIVE TESTING 2014年第6期50卷 359-368页

作者： Vorobeichikov, S. E. Udod, V. A. Klimenov, V. A. Shchetinkin, S. A. Tomsk State Univ Tomsk 634050 Russia Tomsk Polytech Univ Inst Introscopy Tomsk 634028 Russia Tech Univ State Inst Radio Engn Elect & Automat Inst Tech Facil Nondestruct Testing Moscow 119454 Russia

The mathematical model of an output digital signal from a single measuring channel of a scanning digital X-ray imaging system containing a line of detectors is presented for the case where the main type of signal distortions is the noise due to the quantum nature of radiation. This model is used to develop a one-dimensional algorithm for the automatic detection of local "critical" inclusions in an inspected object and to obtain the statistical estimates of its efficiency based on a model example.

关键词： detection algorithm inspected object local inclusions digital X-ray imaging scanning system

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