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Zeitschriftenartikel zum Thema „Error detection algorithms“

Autor: Grafiati

Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 29. Juli 2025

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1

Edam, Salaheldin, Doaa Abubakr, Roaa Rahma, and Roaa Yagoub. "Comparative evaluation of localization range-free algorithms in wireless sensor networks." International Journal of Engineering, Science and Technology 16, no. 2 (2024): 1–10. http://dx.doi.org/10.4314/ijest.v16i2.1.

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Localization in wireless sensor networks is essential not only for determining the location but also for routing, managing density, tracking, and a wide range of other communication network functions. There are two main categories of localization algorithms in wireless sensor networks: range-based algorithms and range-free techniques. Localization based on range-free algorithms has benefits in terms of requiring less hardware and energy, making it cost-efficient. This paper examines the impact of beacon nodes on range-free localization algorithms. The findings indicate that ADLA has intermedia

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Liu, Qing Min, Xue Li, and L. Zhang. "Realization Method for Detection on Arc Based on CCD." Applied Mechanics and Materials 687-691 (November 2014): 856–60. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.856.

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s: Arc detection is difficult for processing, assembly and testing of industrial production because of limitations of detection methods, algorithms and instruments. The least-squares algorithm is used to fit data in circle detection. The application of conventional least-squares algorithm is limited, as roundness error is bigger, precision is lower. For detecting arc with data points of non-uniform distribution, improved least-squares algorithm, developed an analysis algorithm for assessing the minimum zone roundness error. Center and radius can be solved, without iteration and truncation erro

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Abdulsattar, Ruaa Alaadeen, and Nada Hussein M. Ali. "Lookup Table Algorithm for Error Correction in Color Images." JOIV : International Journal on Informatics Visualization 2, no. 2 (2018): 63. http://dx.doi.org/10.30630/joiv.2.2.113.

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Error correction and error detection techniques are often used in wireless transmission systems. A color image of type BMP is considered as an application of developed lookup table algorithms to detect and correct errors in these images. Decimal Matrix Code (DMC) and Hamming code (HC) techniques were integrated to compose Hybrid Matrix Code (HMC) to maximize the error detection and correction. The results obtained from HMC still have some error not corrected because the redundant bits added by Hamming codes to the data are considered inadequate, and it is suitable when the error rate is low fo

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Achmad, Fauzi, Nurhayati, and Rahim Robbi. "Bit Error Detection and Correction with Hamming Code Algorithm." International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET) 3, no. 1 (2017): 76–81. https://doi.org/10.5281/zenodo.243775.

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Data communication performed at any time does not always go well, sometimes also happens that his name error when transmitting data. The detection and correction of errors in data transmission requires special algorithms in this study using the algorithm Hamming Code, the use of this algorithm due to ease in the detection and correction of bit damaged and is expected by this research easier for other researchers to develop algorithms Hamming Code for a variety of purposes in data transmission.

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Liu, Xiyuan, Lingxiao Wang, Jiahao Li, Khan Raqib Mahmud, and Shuo Pang. "Enhancing Wildfire Detection via Trend Estimation Under Auto-Regression Errors." Mathematics 13, no. 7 (2025): 1046. https://doi.org/10.3390/math13071046.

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In recent years, global weather changes have underscored the importance of wildfire detection, particularly through Uncrewed Aircraft System (UAS)-based smoke detection using Deep Learning (DL) approaches. Among these, object detection algorithms like You Only Look Once version 7 (YOLOv7) have gained significant popularity due to their efficiency in identifying objects within images. However, these algorithms face limitations when applied to video feeds, as they treat each frame as an independent image, failing to track objects across consecutive frames. To address this issue, we propose a par

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Morisette, Jeffrey T., Louis Giglio, Ivan Csiszar, et al. "Validation of MODIS Active Fire Detection Products Derived from Two Algorithms." Earth Interactions 9, no. 9 (2005): 1–25. http://dx.doi.org/10.1175/ei141.1.

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Abstract Fire influences global change and tropical ecosystems through its connection to land-cover dynamics, atmospheric composition, and the global carbon cycle. As such, the climate change community, the Brazilian government, and the Large-Scale Biosphere–Atmosphere (LBA) Experiment in Amazonia are interested in the use of satellites to monitor and quantify fire occurrence throughout Brazil. Because multiple satellites and algorithms are being utilized, it is important to quantify the accuracy of the derived products. In this paper the characteristics of two fire detection algorithms are ev

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Zhu, Yongkuan, Gurjot Singh Gaba, Fahad M. Almansour, Roobaea Alroobaea, and Mehedi Masud. "Application of data mining technology in detecting network intrusion and security maintenance." Journal of Intelligent Systems 30, no. 1 (2021): 664–76. http://dx.doi.org/10.1515/jisys-2020-0146.

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Abstract In order to correct the deficiencies of intrusion detection technology, the entire computer and network security system are needed to be more perfect. This work proposes an improved k-means algorithm and an improved Apriori algorithm applied in data mining technology to detect network intrusion and security maintenance. The classical KDDCUP99 dataset has been utilized in this work for performing the experimentation with the improved algorithms. The algorithm’s detection rate and false alarm rate are compared with the experimental data before the improvement. The outcomes of proposed a

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Kari, Lila, Stavros Konstantinidis, Steffen Kopecki, and Meng Yang. "Efficient Algorithms for Computing the Inner Edit Distance of a Regular Language via Transducers." Algorithms 11, no. 11 (2018): 165. http://dx.doi.org/10.3390/a11110165.

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The concept of edit distance and its variants has applications in many areas such as computational linguistics, bioinformatics, and synchronization error detection in data communications. Here, we revisit the problem of computing the inner edit distance of a regular language given via a Nondeterministic Finite Automaton (NFA). This problem relates to the inherent maximal error-detecting capability of the language in question. We present two efficient algorithms for solving this problem, both of which execute in time O ( r 2 n 2 d ) , where r is the cardinality of the alphabet involved, n is th

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Toghuj, Wael, and Ghazi I. Alkhatib. "Improved Algorithm for Error Correction." International Journal of Information Technology and Web Engineering 6, no. 1 (2011): 1–12. http://dx.doi.org/10.4018/jitwe.2011010101.

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Digital communication systems are an important part of modern society, and they rely on computers and networks to achieve critical tasks. Critical tasks require systems with a high level of reliability that can provide continuous correct operations. This paper presents a new algorithm for data encoding and decoding using a two-dimensional code that can be implemented in digital communication systems, electronic memories (DRAMs and SRAMs), and web engineering. The developed algorithms correct three errors in codeword and detect four, reaching an acceptable performance level. The program that is

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Kabaoğlu, Hatice, Fecir Duran, and Emine Uçar. "The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis." Sakarya University Journal of Computer and Information Sciences 8, no. 2 (2025): 301–11. https://doi.org/10.35377/saucis...1612668.

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This study focuses on developing a digital twin for baby incubators in neonatal intensive care units to enhance monitoring and care for premature infants. The digital twin employs a hybrid model integrating Long Short-Term Memory (LSTM) and Random Forest (RF) algorithms to predict potential errors and alarms. The LSTM algorithm was trained using sensor data provided by a health technology company to predict future measurements. Subsequently, the RF algorithm classifies these predictions into specific error conditions. The hybrid model demonstrates success with mean squared error and mean absol

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Zheng, Jiahui, Yi Wang, and Yadong Men. "Tightly Coupled SLAM Algorithm Based on Similarity Detection Using LiDAR-IMU Sensor Fusion for Autonomous Navigation." World Electric Vehicle Journal 15, no. 12 (2024): 558. https://doi.org/10.3390/wevj15120558.

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In recent years, the rise of unmanned technology has made Simultaneous Localization and Mapping (SLAM) algorithms a focal point of research in the field of robotics. SLAM algorithms are primarily categorized into visual SLAM and laser SLAM, based on the type of external sensors employed. Laser SLAM algorithms have become essential in robotics and autonomous driving due to their insensitivity to lighting conditions, precise distance measurements, and ease of generating navigation maps. Throughout the development of SLAM technology, numerous effective algorithms have been introduced. However, ex

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Nguyen, G. D. "Error-detection codes: algorithms and fast implementation." IEEE Transactions on Computers 54, no. 1 (2005): 1–11. http://dx.doi.org/10.1109/tc.2005.7.

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JUNG, YUNHO, SEONGJOO LEE, and JAESEOK KIM. "DESIGN AND IMPLEMENTATION OF SYMBOL DETECTOR FOR MIMO SPATIAL MULTIPLEXING SYSTEMS." Journal of Circuits, Systems and Computers 20, no. 04 (2011): 727–39. http://dx.doi.org/10.1142/s0218126611007578.

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In this paper, we propose an efficient symbol detection algorithm for multiple-input multiple-output spatial multiplexing (MIMO-SM) systems and present its design and implementation results. By enhancing the error performance of the first detected symbol that causes error propagation, the proposed algorithm achieves a considerable performance gain compared with the conventional sorted QR decomposition (SQRD) based detection and the ordered successive detection (OSD) algorithms. The bit error rate (BER) performance of the proposed detection algorithm is evaluated by a simulation. In the case of

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Oetama, Raymond, David Tjahjana, Iwan Prasetiawan, and Catherine Anastasia. "Image Error Detection: A Systematic Literature Review." G-Tech: Jurnal Teknologi Terapan 7, no. 3 (2023): 837–46. http://dx.doi.org/10.33379/gtech.v7i3.2494.

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The advancement of technology, as well as the creation of new techniques and methodologies for image analysis, is rapid. However, image detection may face some errors. Image error detection will be discussed in this comprehensive literature review. Throughout the papers, this work attempts to learn about the types of images used, algorithms that are frequently used, techniques that are frequently used, and metrics used to test the correctness of the suggested approach. The most commonly used image type is medical images such as Magnetic Resonance Imaging, the algorithm that is widely used is a

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Song, Yan, Haixu Tang, Haoyu Zhang, and Qin Zhang. "Overlap detection on long, error-prone sequencing reads via smooth q-gram." Bioinformatics 36, no. 19 (2020): 4838–45. http://dx.doi.org/10.1093/bioinformatics/btaa252.

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Abstract Motivation Third generation sequencing techniques, such as the Single Molecule Real Time technique from PacBio and the MinION technique from Oxford Nanopore, can generate long, error-prone sequencing reads which pose new challenges for fragment assembly algorithms. In this paper, we study the overlap detection problem for error-prone reads, which is the first and most critical step in the de novo fragment assembly. We observe that all the state-of-the-art methods cannot achieve an ideal accuracy for overlap detection (in terms of relatively low precision and recall) due to the high se

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Ali, Abdulrazzak, Nurul Akmar Emran, Safiza Suhana Kamal Baharin, et al. "Improving the efficiency of clustering algorithm for duplicates detection." Indonesian Journal of Electrical Engineering and Computer Science 30, no. 3 (2023): 1586. http://dx.doi.org/10.11591/ijeecs.v30.i3.pp1586-1595.

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Clustering method is a technique used for comparisons reduction between the candidates records in the duplicate detection process. The process of clustering records is affected by the quality of data. The more error-free the data, the more efficient the clustering algorithm, as data errors cause data to be placed in incorrect groups. Window algorithms suffer from the window size. The larger the window, the greater the number of unnecessary comparisons, and the smaller the window size may prevent the detection of duplicates that are supposed to be within the window. In this paper, we propose a

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Abdulrazzak, Ali, Akmar Emran Nurul, Suhana Kamal Baharin Safiza, et al. "Improving the efficiency of clustering algorithm for duplicates detection." Improving the efficiency of clustering algorithm for duplicates detection 30, no. 3 (2023): 1586–95. https://doi.org/10.11591/ijeecs.v30.i3.pp1586-1595.

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Clustering method is a technique used for comparisons reduction between the candidates records in the duplicate detection process. The process of clustering records is affected by the quality of data. The more error-free the data, the more efficient the clustering algorithm, as data errors cause data to be placed in incorrect groups. Window algorithms suffer from the window size. The larger the window, the greater the number of unnecessary comparisons, and the smaller the window size may prevent the detection of duplicates that are supposed to be within the window. In this paper, we propose a

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BADIEZADEGAN, SHIRIN, and HAMID SOLTANIAN-ZADEH. "DESIGN AND EVALUATION OF MATCHED WAVELETS WITH MAXIMUM CODING GAIN AND MINIMUM APPROXIMATION ERROR CRITERIA FOR R PEAK DETECTION IN ECG." International Journal of Wavelets, Multiresolution and Information Processing 06, no. 06 (2008): 799–825. http://dx.doi.org/10.1142/s0219691308002690.

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Recently, several wavelet-based algorithms have been proposed for feature extraction in non-stationary signals such as ECG. These methods, however, have mainly used general purpose (unmatched) wavelet bases such as Daubechies and Quadratic Spline. In this paper, five new matched wavelet bases, with minimum approximation error and maximum coding gain criteria, are designed and applied to ECG signal analysis. To study the effect of using different wavelet bases for this application, two different wavelet-based R peak detection algorithms are implemented: (1) a conventional wavelet-based method;

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Poborchaya, N. E. "REGULARIZING ALGORITHMS BASED ON KALMAN FILTERING FOR M-QAM SIGNAL DETECTION IN MIMO." T-Comm 16, no. 12 (2022): 4–10. http://dx.doi.org/10.36724/2072-8735-2022-16-12-4-10.

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The aim of the article is to increase the noise immunity of signal reception with a satisfactory computational complexity of signal processing algorithms. The article discusses two regularizing recurrent algorithms for detecting quadrature amplitude modulation (M-QAM) signal in a multiple-input and multiple-output (MIMO) method and a direct transform receiver based on the Kalman filter. Kalman filtering using for soft decision detection operates at a fixed point in time and estimates symbols in iterations. The proposed detection algorithms contain a regularizing parameter. For one algorithm, t

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Zhou, Qianqian, Tze Ping Loh, Tony Badrick, and Qianqian Zhou. "Impact of combining data from multiple instruments on performance of patient-based real-time quality control." Biochemia medica 31, no. 2 (2021): 276–82. http://dx.doi.org/10.11613/bm.2021.020705.

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It is unclear what is the best strategy for applying patient-based real-time quality control (PBRTQC) algorithm in the presence of multiple instruments. This simulation study compared the error detection capability of applying PBRTQC algorithms for instruments individually and in combination using serum sodium as an example. Four sets of random serum sodium measurements were generated with differing means and standard deviations to represent four simulated instruments. Moving median with winsorization was selected as the PBRTQC algorithm. The PBRTQC parameters (block size and control limits) w

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Nagaraj, Nithin. "Using cantor sets for error detection." PeerJ Computer Science 5 (January 14, 2019): e171. http://dx.doi.org/10.7717/peerj-cs.171.

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Error detection is a fundamental need in most computer networks and communication systems in order to combat the effect of noise. Error detection techniques have also been incorporated with lossless data compression algorithms for transmission across communication networks. In this paper, we propose to incorporate a novel error detection scheme into a Shannon optimal lossless data compression algorithm known as Generalized Luröth Series (GLS) coding. GLS-coding is a generalization of the popular Arithmetic Coding which is an integral part of the JPEG2000 standard for still image compression. G

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Wang, Lei, Bao Yu Zheng, and Jing Wu Cui. "New Recursive Algorithms for Signal Detection." Advanced Materials Research 271-273 (July 2011): 1059–62. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.1059.

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Based on the synthesis and analysis of recursive receivers, new algorithms are proposed to achieve satisfactory performance with moderate computational complexity. During the analysis, some interesting properties shared by the proposed procedures are described. Finally, the performance assessment shows that new schemes are superior to the linear detector and ordinary grouping algorithm, and achieve a bit-error rate close to that of the optimum receiver.

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Chen, Xin W., and Shimon Y. Nof. "Error Detection and Prediction Algorithms: Application in Robotics." Journal of Intelligent and Robotic Systems 48, no. 2 (2007): 225–52. http://dx.doi.org/10.1007/s10846-006-9094-9.

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Búa-Núñez, Iago, Julio E. Posada-Román, and José A. García-Souto. "Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers." Energies 14, no. 23 (2021): 7873. http://dx.doi.org/10.3390/en14237873.

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The detection of acoustic emissions with multiple channels and different kinds of sensors (external ultrasound electronic sensors and internal optical fiber sensors) for monitoring power transformers is presented. The source localization based on the times of arrival was previously studied, comparing different strategies for solving the location equations and the most efficient strategy in terms of computational and complexity costs versus performance was selected for analyzing the error propagation. The errors of the acoustic emission source location (localization process) are evaluated from

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Zhao, Kun, Jianguo Zhang, Jiangbo Li, and Guili Li. "Improved Active Contour Snake Model for Hollow Filter Bar Roundness Inspection." Advances in Materials Science and Engineering 2022 (November 3, 2022): 1–10. http://dx.doi.org/10.1155/2022/8728253.

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Cigarette filter rods are a kind of easily deformed and irregularly shaped parts, and the quality of cigarette filter rods is often measured by the filter rod roundness index, although they are affected by factors such as environment and humidity, which can affect the detection of filter rod roundness and show blurred images. For the detection of blurred filter rod image roundness, an improved active contour snake model algorithm is proposed. The experimental results show that in the analysis of the algorithm iteration number on the model performance, the model performance gradually leveled of

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Moroz, B. I., and O. O. Shyshatsky. "Methods, algorithms, and programs for error detection in a geospatial database: a case study of the state land cadastre." System technologies 2, no. 157 (2025): 82–92. https://doi.org/10.34185/1562-9945-2-157-2025-08.

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Maintaining large geospatial databases involves significant risks of errors, which can negatively impact data accuracy and subsequent usage processes. The primary causes of er-rors include human factors, technical inaccuracies in data integration, and discrepancies in storage projections. With the continuous growth of data volume, manual verification methods become inefficient, necessitating the development of automated error detection methods. The aim of this study is to develop and validate algorithms for error detection using the land parcel database of the State Land Cadastre of Ukraine as

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Dan-Dan Cui, Dan-Dan Cui, Chao Xu Dan-Dan Cui, and Hong-Chao Zhou Chao Xu. "A Method for Assembly Accuracy Detection and Intelligent Error Estimation Based on Computer Vision." 電腦學刊 34, no. 4 (2023): 119–26. http://dx.doi.org/10.53106/199115992023083404010.

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<p>This article focuses on the current situation of large assembly errors, easy omissions and errors in the mechanical assembly process. Computer vision is introduced in the assembly process, and visual images are used to estimate assembly errors, thereby improving assembly accuracy. To this end, through improvements to the neural network, the addition of attention and measurement mechanisms, the network&rsquo;s ability to extract and distinguish features from assembly images has been improved. Finally, deep learning algorithms are used to estimate assembly features in the image. Fin

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Chen, Liqiu, Chongshi Gu, Sen Zheng, and Yanbo Wang. "A Method for Identifying Gross Errors in Dam Monitoring Data." Water 16, no. 7 (2024): 978. http://dx.doi.org/10.3390/w16070978.

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Real and effective monitoring data are crucial in assessing the structural safety of dams. Gross errors, resulting from manual mismeasurement, instrument failure, or other factors, can significantly impact the evaluation process. It is imperative to eliminate such anomalous data. However, existing methods for detecting gross errors in concrete dam deformation often focus on analyzing a single monitoring effect quantity. This can lead to sudden jumps in values of effect quantity caused by changes in environmental variables being mistakenly identified as gross error. Therefore, a method based on

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Shi, Qi, Lu Li, Jiaqi Feng, Wen Chen, and Jinpei Yu. "Automated Model Hardening with Reinforcement Learning for On-Orbit Object Detectors with Convolutional Neural Networks." Aerospace 10, no. 1 (2023): 88. http://dx.doi.org/10.3390/aerospace10010088.

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On-orbit object detection has received extensive attention in the field of artificial intelligence (AI) in space research. Deep-learning-based object-detection algorithms are often computationally intensive and rely on high-performance devices to run. However, those devices usually lack space-qualified versions, and they can hardly meet the reliability requirement if directly deployed on a satellite platform, due to software errors induced by the space environment. In this paper, we evaluated the impact of space-environment-induced software errors on object-detection algorithms through large-s

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Wang, Yifan, Yang Li, Jiaqi Wang, Haofeng Lv, and Zeli Yang. "A Target Corner Detection Algorithm Based on the Fusion of FAST and Harris." Mathematical Problems in Engineering 2022 (April 2, 2022): 1–16. http://dx.doi.org/10.1155/2022/4611508.

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Corner detection is a common method to obtain image features, and the detection effect influences the performance of matching and tracking directly. A FAST-Harris fusion corner detection algorithm is proposed to improve the shortcomings of the Harris algorithm, such as the low detection accuracy and low positioning accuracy, and a corner detection fusion model is established. First, the detected target image is padded, and then the FAST algorithm is used with a 25% reduced contrast points to achieve fast capture roughly; in this way, a candidate corner set is obtained. Then, screening the cand

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Pavlenko, Serhii, and Petro Kuliabko. "Deduplication of error reports in software malfunction: Algorithms for comparing call stacks." Вісник Черкаського державного технологічного університету 28, no. 4 (2023): 59–69. http://dx.doi.org/10.62660/2306-4412.4.2023.59-69.

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In the software industry, the standard recognises automatic fault monitoring systems as mandatory for implementation. Considering the constant development of technologies and the high complexity of programmes, the importance of optimising processes for detecting and eliminating errors becomes a relevant task due to the need for reliability and stability of software. The purpose of this study is to conduct a detailed analysis of existing deduplication algorithms for reports from automatic systems collecting information about software failures. Among the algorithms considered were: the longest c

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Liu, Qirui. "Iterative algorithms and architectures in massive MIMO detection." Applied and Computational Engineering 6, no. 1 (2023): 1143–50. http://dx.doi.org/10.54254/2755-2721/6/20230491.

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Massive multiple-input multiple-output (MIMO) wireless systems play an important role in the 5G networks. The complexity of signal detection in massive MIMO is increasing rapidly due to the growth of the number of transmitting antennas. In this paper, we introduced different iterative algorithms to decrease the computational cost of the approximate minimum mean-square error (MMSE) algorithm, including the Neumann Series algorithm, Jacobi method, Gauss-Seidel method, Successive Over Relaxation method and the Conjugate Gradient method. In addition, the VLSI architecture implementations of algori

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Killian, Cédric, Camel Tanougast, Fabrice Monteiro, and Abbas Dandache. "A New Efficient and Reliable Dynamically ReconfigurableNetwork-on-Chip." Journal of Electrical and Computer Engineering 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/843239.

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We present a new reliableNetwork-on-Chip(NoC) suitable forDynamically Reconfigurable Multiprocessors on Chipsystems. The proposedNoCis based on routers performing online error detection of routing algorithm and data packet errors. Our work focuses on adaptive routing algorithms which allow to bypass faulty components or processor elements dynamically implemented inside the network. The proposed routing error detection mechanism allows to distinguish routing errors from bypasses of faulty components. The new router architecture is based on additional diagonal state indications and specific logi

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Goldman, Geoffrey H. "Analysis of turbulence and scattering effects on detecting elevated sources with a microphone array." Journal of the Acoustical Society of America 151, no. 4 (2022): A135. http://dx.doi.org/10.1121/10.0010897.

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Sound waves propagating in urban environments are affected by turbulence, scattering from numerous structures, and atmospheric refraction. These effects can be incorporated into beamforming algorithms but at the cost of increased processing time and algorithm complexity. An analysis of incorporating refraction effects into the beamformers for a simplified scenario is performed on detection algorithms based on four generalized beamforming algorithms. Simulated results for beamforming algorithms implemented with no model mismatch error are compared to results for classical beamforming algorithms

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Egiazarian, Karen, Pauli Kuosmanen, and Ciprian Bilcu. "Variable step-size LMS adaptive filters for CDMA multiuser detection." Facta universitatis - series: Electronics and Energetics 17, no. 1 (2004): 21–32. http://dx.doi.org/10.2298/fuee0401021e.

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Due to its simplicity the adaptive Least Mean Square (LMS) algorithm is widely used in Code-Division Multiple access (CDMA) detectors. However its convergence speed is highly dependent on the eigen value spread of the input covariance matrix. For highly correlated inputs the LMS algorithm has a slow convergence which require long training sequences and therefore low transmission speeds. Another drawback of the LMS is the trade-off between convergence speed and steady-state error since both are controlled by the same parameter, the step-size. In order to eliminate these drawbacks, the class of

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Pouliot, D. A., D. J. King, and D. G. Pitt. "Development and evaluation of an automated tree detectiondelineation algorithm for monitoring regenerating coniferous forests." Canadian Journal of Forest Research 35, no. 10 (2005): 2332–45. http://dx.doi.org/10.1139/x05-145.

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An algorithm is presented for automated detectiondelineation of coniferous tree regeneration that combines strategies of several existing algorithms, including image processing to isolate conifer crowns, optimal image scale determination, initial crown detection, and crown boundary segmentation and refinement. The algorithm is evaluated using 6-cm pixel airborne imagery in operational regeneration conditions typically encountered in the boreal forest 510 years after harvest. Detection omission and commission errors as well as an accuracy index combining both error types were assessed on a tr

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Lee, Seongjin, Wonteak Lim, and Myoungho Sunwoo. "Robust Parking Path Planning with Error-Adaptive Sampling under Perception Uncertainty." Sensors 20, no. 12 (2020): 3560. http://dx.doi.org/10.3390/s20123560.

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In automated parking systems, a path planner generates a path to reach the vacant parking space detected by a perception system. To generate a safe parking path, accurate detection performance is required. However, the perception system always includes perception uncertainty, such as detection errors due to sensor noise and imperfect algorithms. If the parking path planner generates the parking path under uncertainty, problems may arise that cause the vehicle to collide due to the automated parking system. To avoid these problems, it is a challenging problem to generate the parking path from t

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Young, G. E., M. R. Moan, and E. A. Misawa. "Transient Error Detection During UDUT Covariance Calculations Using Algorithm Based Fault Tolerance." Journal of Dynamic Systems, Measurement, and Control 119, no. 2 (1997): 284–86. http://dx.doi.org/10.1115/1.2801246.

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Algorithm based fault tolerance is studied for use with linear estimation algorithms such as the Kalman filter. Emphasis is placed on the study of algorithm based fault tolerance used in conjunction with the UDUT covariance calculation. A real-time simulation has been performed in a VMEbus environment utilizing a single board computer and a commercial real-time operating system.

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Yan, Xiao-Yan, Chen-Lu Yu, Xiao-Ting Guo, Hui-Hua Kong, and Xiu-Yuan Li. "Multi-Condition Constrained Pedestrian Localization Algorithm Based on IMU." Applied Sciences 15, no. 5 (2025): 2259. https://doi.org/10.3390/app15052259.

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The MEMS inertial sensors based on the pedestrian localization system assisted by the zero-velocity update (ZUPT) algorithm has gained widespread attention, due to its effective independent localization in indoor environments. However, in the realistic pedestrian localization test, the system often appears to drift because of the long-term error accumulation of inertial sensors and the limitation of the error suppression of traditional pedestrian localization algorithms. In this article, based on full analysis of existing constraint-based methods, a multi-condition constrained pedestrian local

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Huo, Li, Zhiyong Wu, Jiabin Wu, et al. "High-Precision Log-Ratio Spot Position Detection Algorithm with a Quadrant Detector under Different SNR Environments." Sensors 22, no. 8 (2022): 3092. http://dx.doi.org/10.3390/s22083092.

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In atmospheric laser communication, a beam is transmitted through an atmospheric channel, and the photocurrent output from a quadrant detector (QD) used as the tracking sensor fluctuates significantly. To ensure uninterrupted communication and to adapt to such fluctuations, in this paper we apply logarithmic amplifiers to process the output signals of a QD. To further improve the measurement accuracy of the spot position, we firstly propose an integral infinite log-ratio algorithm (IILRA) and an integral infinity log-ratio algorithm based on the signal-to-noise ratio (BSNR-IILRA) through analy

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Yan, Shi Hao, Jian Ping Xing, and De Qiang Wang. "Correlation between Estimation Error and Possible Region in Localization Algorithms." Advanced Materials Research 457-458 (January 2012): 1514–20. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.1514.

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Many localization algorithms in wireless sensor networks mention possible regions to increase the degree of localization precision. In this paper, we present the definite correlation between the estimation error and the possible region. The estimation error, which is the most important indictor to judge the performance of a localization algorithm, is proportional to the square root of the area of the possible region and the factor of proportionality relates to the shape of the possible region. We also propose two applications of the definite correlation, including estimation errors detection a

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Hosseini, Beheshti Moluksadat, and Qavidel Hadi Abdi. "Classification of Required Data Types and Methods for Text Error Detection and Standardization." Journal of Information Processing and Management 32, no. 4 (2017): 1143–70. https://doi.org/10.5281/zenodo.14002415.

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One of the fundamental stages of automatic text processing is the detection of spelling errors and the standardization of characters. Without passing through this stage, the storage of textual documents faces numerous challenges, leading to disruptions in their machine retrieval. Consequently, specialists in the fields of natural language processing and computational linguistics are continually striving to process various types of data by providing optimal methods and algorithms to achieve standardized data. In English and some other languages, numerous studies have been conducted in this area

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Ciriaco, Fernando, Taufik Abrão, and Paul Jean E. Jeszensky. "DS/CDMA Multiuser Detection with Evolutionary Algorithms." JUCS - Journal of Universal Computer Science 12, no. (4) (2006): 450–80. https://doi.org/10.3217/jucs-012-04-0450.

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This work analyses two heuristic algorithms based on the genetic evolution theory applied to direct sequence code division multiple access (DS/CDMA) com munication systems. For different phases of an evolutionary algorithm new biological processes are analyzed, specially adapted to the multiuser detection (MuD) problem in multipath fading channels. Monte Carlo simulation results show that the detection based on evolutionary heuristic algorithms is a viable option when compared with the optimum solution (ML maximum likelihood), even for hostile channel conditions and severe system operation.

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Pateriya, Nidhi, Zohaib Hasan, Jyoti Mehra, and Akash Sahu. "Innovative Techniques for Object Detection and Recognition: A Study on Accuracy and Efficiency Improvements." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 02 (2023): 1094–98. http://dx.doi.org/10.15680/ijircce.2024.1202063.

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In the domain of computer vision, object detection and recognition play essential roles in applications such as autonomous driving and surveillance. This paper presents a new approach aimed at improving both accuracy and efficiency in these technologies. The proposed method utilizes cutting-edge algorithms and structural enhancements to achieve substantial improvements. It demonstrates an accuracy of 95.8%, indicating its superior capability in detecting and classifying objects. The method also achieves a Root Mean Squared Error (RMSE) of 0.206, signifying low prediction errors, and a Mean Abs

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Njoki, Wanjiku Amani. "Statistical Challenges and Opportunities in Quantum Computing: A Review." IDOSR JOURNAL OF COMPUTER AND APPLIED SCIENCES 9, no. 1 (2024): 33–37. http://dx.doi.org/10.59298/jcas/2024/91.153337001.

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Quantum computing represents a transformative paradigm shift in computational capabilities by leveraging quantum mechanical principles such as superposition and entanglement. This article explores the intersection of quantum computing with statistical methods, focusing on key areas such as quantum error correction (QEC), statistical inference, data interpretation, and optimization of quantum algorithms. Quantum error correction is essential due to quantum systems' susceptibility to errors, requiring advanced statistical techniques for error detection and mitigation without collapsing quantum s

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Yang, Bo-Seung, Tae-Won Kang, Yong-Sik Choi, and Jin-Woo Jung. "Error-Resistant Movement Detection Algorithm for the Elderly with Smart Mirror." Applied Sciences 12, no. 14 (2022): 7024. http://dx.doi.org/10.3390/app12147024.

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As the elderly population increases globally, the demand for systems and algorithms that target the elderly is increasing. Focusing on the extendibility of smart mirrors, our purpose is to create a motion detection system based on video input by an attached device (an RGB camera). The motion detection system presented in this paper is based on an algorithm that returns a Boolean value indicating the detection of motion based on skeletal information. We analyzed the problems that occur when the adjacent frame subtraction method (AFSM) is used in the motion detection algorithm based on the skele

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K. Maithili, Et al. "Machine Learning-Based Approaches for Credit Card Fraud Detection: A Comprehensive Reviewz." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 1754–61. http://dx.doi.org/10.17762/ijritcc.v11i10.8751.

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The objective of data analytics is to discover hidden patterns and use them to guide wise judgements in a range of circumstances. Theft of credit cards has significantly grown as a result of modern technologies and has become a popular target for scam artists. Publicly available databases on credit card fraud are very unbalanced. As more people conduct business online, Fraud involving credit cards has grown to be a serious problem for both consumers and financial establishments. standard rule-based fraud detection strategies have shown to be insufficient to combat fraudsters' ever-evolving tac

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Sun, Guangpei, Peng Jiang, Huan Xu, et al. "Outlier Detection and Correction for Monitoring Data of Water Quality Based on Improved VMD and LSSVM." Complexity 2019 (February 3, 2019): 1–12. http://dx.doi.org/10.1155/2019/9643921.

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To improve the detection rate and reduce the correction error of abnormal data for water quality, an outlier detection and correction method is proposed based on the improved Variational Mode Decomposition (improved VMD) and Least Square Support Vector Machine (LSSVM) algorithms. The correlation coefficient is introduced, for solving the optimal parameter k of VMD algorithm, and an improved VMD algorithm is obtained. Combined with LSSVM algorithm, the outliers of water quality can be detected and repaired. This method is applied for the detection and correction of water quality monitoring outl

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Guardabasso, V., G. De Nicolao, M. Rocchetti, and D. Rodbard. "Evaluation of pulse-detection algorithms by computer simulation of hormone secretion." American Journal of Physiology-Endocrinology and Metabolism 255, no. 6 (1988): E775—E784. http://dx.doi.org/10.1152/ajpendo.1988.255.6.e775.

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A versatile method is presented for generating synthetic hormonal time series, containing peaks at known locations, to be used to objectively evaluate both the false-negative (F-) and false-positive (F+) statistical error rates of computerized pulse-detection algorithms. Synthetic data are generated by assuming hormone secretion to occur as a succession of instantaneous release pulses, distributed as Poisson events, separated by quiescent intervals. The pulses are convolved to simulate cumulation of consecutive events and clearance of the hormone. Randomly generated errors, corresponding in ma

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Manaswini Ramakrishnappa, Shruthi Modem, Hamsa Girish, Joseph Anthony Prathap,. "Faults Identification in Digital Counter Using Naïve-Bayes’ Algorithm." Tuijin Jishu/Journal of Propulsion Technology 44, no. 4 (2023): 1145–51. http://dx.doi.org/10.52783/tjjpt.v44.i4.989.

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This paper elaborates on the implementation of the Naïve Bayes Algorithm to identify the faults occurrence in the digital counter circuits. The digital counters are circuits utilized to count the values in increasing order, decreasing order, or both directions. The digital counters find applications in real time from simple wristwatches to the industrial conveyor belt that is automated based on timings. The fault happening in the digital counter circuit is to be identified using Fault detection methods such as modular redundancy methods and error detection methods. With the advent of Artificia

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