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Journal articles on the topic 'MITIGATION ALGORITHM'

Author: Grafiati

Published: 11 September 2023

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1

Ding, Yi, Weiwei Fan, Zijing Zhang, Feng Zhou, and Bingbing Lu. "Radio Frequency Interference Mitigation for Synthetic Aperture Radar Based on the Time-Frequency Constraint Joint Low-Rank and Sparsity Properties." Remote Sensing 14, no. 3 (February 7, 2022): 775. http://dx.doi.org/10.3390/rs14030775.

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Synthetic aperture radar (SAR) is susceptible to radio frequency interference (RFI), which becomes especially commonplace in the increasingly complex electromagnetic environments. RFI severely detracts from SAR imaging quality, which hinders image interpretation. Therefore, some RFI mitigation algorithms have been introduced based on the partial features of RFI, but the RFI reconstruction models in these algorithms are rough and can be improved further. This paper proposes two algorithms for accurately modeling the structural properties of RFI and target echo signal (TES). Firstly, an RFI mitigation algorithm joining the low-rank characteristic and dual-sparsity property (LRDS) is proposed. In this algorithm, RFI is treated as a low-rank and sparse matrix, and the sparse matrix assumption is made for TES in the time–frequency (TF) domain. Compared with the traditional low-rank and sparse models, it can achieve better RFI mitigation performance with less signal loss and accelerated algorithm convergence. Secondly, the other RFI mitigation algorithm, named as TFC-LRS, is proposed to further reduce the signal loss. The TF constraint concept, in lieu of the special sparsity, is introduced in this algorithm to describe the structural distribution of RFI because of its aggregation characteristic in the TF spectrogram. Finally, the effectiveness, superiority, and robustness of the proposed algorithms are verified by RFI mitigation experiments on the simulated and measured SAR datasets.

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Dhineshkumar, K., and C. Subramani. "Kalman Filter Algorithm for Mitigation of Power System Harmonics." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 2 (April 1, 2018): 771. http://dx.doi.org/10.11591/ijece.v8i2.pp771-779.

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<p>The maiden application of a variant of Kalman Filter (KF) algorithms known as Local Ensemble Transform Kalman Filter (LET-KF) are used for mitigation and estimation power system harmonics are proposed in this paper. The proposed algorithm is applied for estimating the harmonic parameters of power signal containing harmonics, sub-harmonics and inter-harmonics in presence of random noise. The KF group of algorithms are tested and applied for both stationary as well as dynamic signal containing harmonics. The proposed LET-KF algorithm is compared with conventional KF based algorithms like KF, Ensemble Kalman Filter (En-KF) algorithms for harmonic estimation with the random noise values 0.001, 0.05 and 0.1. Among these three noises, 0.01 random noise results will give better than other two noises. Because the phase deviation and amplitude deviation less in 0.01 random noise. The proposed algorithm gives the better results to improve the efficiency and accuracy in terms of simplicity and computational features. Hence there are less multiplicative operations, which reduce the rounding errors. It is also less expensive as it reduces the requirement of storing large matrices, such as the Kalman gain matrix used in other KF based methods.</p>

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Majumder, Swarnadeep, Christopher G. Yale, Titus D. Morris, Daniel S. Lobser, Ashlyn D. Burch, Matthew N. H. Chow, Melissa C. Revelle, Susan M. Clark, and Raphael C. Pooser. "Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses." Quantum 7 (May 15, 2023): 1006. http://dx.doi.org/10.22331/q-2023-05-15-1006.

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Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that near term algorithms can be performed with proximate accuracy (like chemical accuracy for quantum chemistry problems). While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware codesign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations.

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Yousif, Tasneem, and Paul Blunt. "Interference Mitigation for GNSS Receivers Using FFT Excision Filtering Implemented on an FPGA." Eng 3, no. 4 (October 31, 2022): 439–66. http://dx.doi.org/10.3390/eng3040032.

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GNSS receivers process signals with very low received power levels (<−160 dBW) and, therefore GNSS signals are susceptible to interference. Interference mitigation algorithms have become common in GNSS receiver designs in both professional and mass-market applications to combat both unintentional and intentional (jamming) interference. Interference excision filters using fast Fourier transforms (FFTs) have been proposed in the past as a powerful method of interference mitigation. However, the hardware implementations of this algorithm mostly limited their use to military GNSS receivers where greater power and resources were available. Novel implementation of existing FPGA technology should make interference mitigation feasible with limited hardware resources. This paper details the practicalities of implementing excision filters on currently available FPGAs trading off the achievable performance against the required hardware resources. The hardware implementation of the FFT excision mitigation algorithm is validated with the GNSS software receiver. The results indicate that the desired performance of the developed algorithm has achieved the expectations and can provide significant improvement on mitigation techniques in current GNSS receiver hardware. Two hardware implementation designs (fixed-point and float-point data type format) are developed and compared to achieve the optimal design that can provide the best performance with the possible minimum hardware resources.

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Sánchez-Cartas, Juan Manuel, Alberto Tejero, and Gonzalo León. "Algorithmic Pricing and Price Gouging. Consequences of High-Impact, Low Probability Events." Sustainability 13, no. 5 (February 26, 2021): 2542. http://dx.doi.org/10.3390/su13052542.

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Algorithmic pricing may lead to more efficient and contestable markets, but high-impact, low-probability events such as terror attacks or heavy storms may lead to price gouging, which may trigger injunctions or get sellers banned from platforms such as Amazon or eBay. This work addresses how such events may impact prices when set by an algorithm and how different markets may be affected. We analyze how to mitigate these high-impact events by paying attention to external (market conditions) and internal (algorithm design) features surrounding the algorithms. We find that both forces may help in partially mitigating price gouging, but it remains unknown which forces or features may lead to complete mitigation.

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Ahmed, Mohamed, and Ezz Eldin Abdelkawy. "GPS correlated jammer mitigation utilizing MUSIC algorithm." International Conference on Electrical Engineering 7, no. 7 (May 1, 2010): 1–10. http://dx.doi.org/10.21608/iceeng.2010.33043.

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VU, Trung Kien, Sungoh KWON, and Sangchul OH. "Cooperative Interference Mitigation Algorithm in Heterogeneous Networks." IEICE Transactions on Communications E98.B, no. 11 (2015): 2238–47. http://dx.doi.org/10.1587/transcom.e98.b.2238.

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Akanji, Oluwatobi Shadrach, Opeyemi Aderiike Abisoye, and Mohammed Awwal Iliyasu. "MITIGATING SLOW HYPERTEXT TRANSFER PROTOCOL DISTRIBUTED DENIAL OF SERVICE ATTACKS IN SOFTWARE DEFINED NETWORKS." Journal of Information and Communication Technology 20, Number 3 (June 11, 2021): 277–304. http://dx.doi.org/10.32890/jict2021.20.3.1.

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Distributed Denial of Service (DDoS) attacks has been one of the persistent forms of attacks on information technology infrastructure connected to public networks due to the ease of access to DDoS attack tools. Researchers have been able to develop several techniques to curb volumetric DDoS which overwhelms the target with a large number of request packets. However, compared to slow DDoS, limited number of research has been executed on mitigating slow DDoS. Attackers have resorted to slow DDoS because it mimics the behaviour of a slow legitimate client thereby causing service unavailability. This paper provides the scholarly community with an approach to boosting service availability in web servers under slow Hypertext Transfer Protocol (HTTP) DDoS attacks through attack detection using Genetic Algorithm and Support Vector Machine which facilitates attack mitigation in a Software-Defined Networking (SDN) environment simulated in GNS3. Genetic algorithm was used to select the Netflow features which indicates the presence of an attack and also determine the appropriate regularization parameter, C, and gamma parameter for the Support Vector Machine classifier. Results obtained showed that the classifier had detection accuracy, Area Under Receiver Operating Curve (AUC), true positive rate, false positive rate and a false negative rate of 99.89%, 99.89%, 99.95%, 0.18%, and 0.05% respectively. Also, the algorithm for subsequent implementation of the selective adaptive bubble burst mitigation mechanism was presented. This study contributes to the ongoing research in detecting and mitigating slow HTTP DDoS attacks with emphasis on the use of machine learning classification and meta-heuristic algorithms.

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SHIN, J. H., J. HEO, S. YOON, and S. Y. KIM. "Interference Cancellation and Multipath Mitigation Algorithm for GPS Using Subspace Projection Algorithms." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E91-A, no. 3 (March 1, 2008): 905–8. http://dx.doi.org/10.1093/ietfec/e91-a.3.905.

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Garzia, Fabio, Johannes Rossouw van der Merwe, Alexander Rügamer, Santiago Urquijo, and Wolfgang Felber. "HDDM Hardware Evaluation for Robust Interference Mitigation." Sensors 20, no. 22 (November 13, 2020): 6492. http://dx.doi.org/10.3390/s20226492.

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Interference can significantly degrade the performance of global navigation satellite system (GNSS) receivers. Therefore, mitigation methods are required to ensure reliable operations. However, as there are different types of interference, robust, multi-purpose mitigation algorithms are needed. This paper describes the most popular state-of-the-art interference mitigation techniques. The high-rate DFT-based data manipulator (HDDM) is proposed as a possible solution to overcome their limitations. This paper presents a hardware implementation of the HDDM algorithm. The hardware HDDM module is integrated in three different receivers equipped with analog radio-frequency (RF) front-ends supporting signals with different dynamic range. The resource utilization and power consumption is evaluated for the three cases. The algorithm is compared to a low-end mass-market receiver and a high-end professional receiver with basic and sophisticated interference mitigation capabilities, respectively. Different type of interference are used to compare the mitigation capabilities of the receivers under test. Results of the HDDM hardware implementation achieve the similar or improved performance to the state of the art. With more complex interferences, like frequency hopping or pulsed, the HDDM shows even better performance.

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Andriansyah, Andriansyah, and Prima Denny Sentia. "PENENTUAN RUTE KENDARAAN PADA SISTEM DISTRIBUSI LOGISTIK PASCA BENCANA (STUDI KASUS)." Jurnal Manajemen Industri dan Logistik 2, no. 1 (December 4, 2018): 79–89. http://dx.doi.org/10.30988/jmil.v2i1.28.

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The success indicators of disaster mitigation can be seen from the disaster logistics system. Effective and efficient distribution network can make a good disaster logistics system. The problem that related to the design of this network is the vehicle routing problem. The objective is determined optimal route of relief distribution from warehouse to victims with minimum time duration. The problem is solved by branch and bound, insertion heuristic, and local search algorithms. The results obtained by branch and bound and local search algorithm are optimal global. Time duration of vehicle using these algoritm is 1.0562 hours. However, computation time using branch and bound algorithm is very long until 22 hours while local search algorithm only takes 60 seconds. The insertion heuristic algorithm also produces a good solution. Time duration of vehicle using this algoritm is 1,1030 hours. This solution is local optimal, but the computation time is very short, only 0.001 seconds.

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Acakpovi, Amevi, Dominique Kogue, Koudjo Mawuefam Koumadi, and Ibrahim Tahirou. "Inteference Mitigation in Femtocellular Networks." International Journal of Informatics and Communication Technology (IJ-ICT) 3, no. 2 (August 1, 2014): 113. http://dx.doi.org/10.11591/ijict.v3i2.pp113-121.

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<span lang="EN-US">Femtocells can significantly boost up wireless cellular network capacity by reducing communication distances to user equipment and also by reusing resources already utilized in the macrocell network on which they overlay. However, the deployment of femtocells within a macrocell coverage area, causes severe interference between the femtocell and the macrocell, which may have an impact on the overall performance of the femtocells. Avoiding such interference is very important for the effective co-existence </span><span lang="EN-US">of femtocells and macrocell. This paper proposes an algorithm to mitigate cross-tier interference between </span><span lang="EN-US">a femtocell and a macrocell using adaptive power control. The proposed approach is modeled and simulated using MATLAB. The impact on the performance of the </span><span lang="EN-US">femtocell using the proposed algorithm </span><span lang="EN-US">is analysed. Results show that the proposed adaptive power control algorithm has tremendously reduced the negative effects on the system throughput, delay and outage probability for voice and data traffics.</span>

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13

Chen, Chien-Sheng. "A non-line-of-sight error mitigation method for location estimation." International Journal of Distributed Sensor Networks 13, no. 1 (January 2017): 155014771668273. http://dx.doi.org/10.1177/1550147716682739.

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Because there are always non-line-of-sight effects in signal propagation, researchers have proposed various algorithms to mitigate the measured error caused by non-line-of-sight. Initially inspired by flocking birds, particle swarm optimization is an evolutionary computation tool for optimizing a problem by iteratively attempting to improve a candidate solution with respect to a given measure of quality. In this article, we propose a new location algorithm that uses time-of-arrival measurements to improve the mobile station location accuracy when three base stations are available. The proposed algorithm uses the intersections of three time-of-arrival circles based on the particle swarm optimization technique to give a location estimation of the mobile station in non-line-of-sight environments. An object function is used to establish the nonlinear relationship between the intersections of the three circles and the mobile station location. The particle swarm optimization finds the optimal solution of the object function and efficiently determines the mobile station location. The simulation results show that the proposed algorithm performs better than the related algorithms in wireless positioning systems, even in severe non-line-of-sight propagation conditions.

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Chakraborty, Soma, Rashmi Deka, and Jibendu Sekhar Roy. "Interference Mitigation in Cognitive Radio using Genetic Algorithm." International Journal of Computer Applications 70, no. 12 (May 17, 2013): 29–35. http://dx.doi.org/10.5120/12016-8059.

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15

Chen, Shaoping, and Tianren Yao. "Blind algorithm for RIBI mitigation in OFDM systems." Electronics Letters 38, no. 22 (2002): 1382. http://dx.doi.org/10.1049/el:20020895.

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16

ZHENG, Nan-shan, Liang-shi CAI, He-fang BIAN, and Cong LIN. "Hybrid particle filtering algorithm for GPS multipath mitigation." Transactions of Nonferrous Metals Society of China 24, no. 5 (May 2014): 1554–61. http://dx.doi.org/10.1016/s1003-6326(14)63225-8.

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17

Khodjaev, Jasurbek, Salvatore Tedesco, and Brendan O'Flynn. "IMPROVED NLOS ERROR MITIGATION BASED ON LTS ALGORITHM." Progress In Electromagnetics Research Letters 58 (2016): 133–39. http://dx.doi.org/10.2528/pierl15100103.

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18

Jianhua, Yang, Zhao Danfeng, Yue Li, and Zhao Chunhui. "Simplified iterative algorithm for OFDM phase noise mitigation." Journal of Systems Engineering and Electronics 18, no. 4 (December 2007): 716–20. http://dx.doi.org/10.1016/s1004-4132(08)60009-2.

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19

Mai, Yun Fei, Shao Long Liu, and Wen Jing Ding. "Design and MATLAB Simulation of a Composite PID Controller for EPS Test-Benches." Applied Mechanics and Materials 487 (January 2014): 635–38. http://dx.doi.org/10.4028/www.scientific.net/amm.487.635.

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For the problems that exist in EPS composite test-benches, PID control laws are expounded, a composite PID controller is designed, which is integrated with multiple advanced PID control algorithms (variable-integral PID algorithm, PID algorithm with filters, partial derivative PID algorithm, PID algorithm with dead zone), and it is simulated by MATLAB. The simulation results show that the improvement of accuracy and the impacts mitigation of the nonlinearity and external electromagnetic interferences are achieved well through the composite PID controller, and there is practical significance.

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Tang, Hong, Yongwan Park, and Tianshuang Qiu. "NLOS Mitigation for TOA Location Based on a Modified Deterministic Model." Research Letters in Signal Processing 2008 (2008): 1–4. http://dx.doi.org/10.1155/2008/970461.

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Wireless location becomes difficult due to contamination of measured time-of-arrival (TOA) caused by non-line-of-sight. In this letter, TOA measurements seen at base stations are adjusted by scale factors, and a modified deterministic model is built. An effective numerical solution is proposed to resolve the scale factors and mobile position. A simulation comparison of four algorithms indicates that the proposed algorithm outperforms the other three algorithms.

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Suchsland, Philippe, Francesco Tacchino, Mark H. Fischer, Titus Neupert, Panagiotis Kl Barkoutsos, and Ivano Tavernelli. "Algorithmic Error Mitigation Scheme for Current Quantum Processors." Quantum 5 (July 1, 2021): 492. http://dx.doi.org/10.22331/q-2021-07-01-492.

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We present a hardware agnostic error mitigation algorithm for near term quantum processors inspired by the classical Lanczos method. This technique can reduce the impact of different sources of noise at the sole cost of an increase in the number of measurements to be performed on the target quantum circuit, without additional experimental overhead. We demonstrate through numerical simulations and experiments on IBM Quantum hardware that the proposed scheme significantly increases the accuracy of cost functions evaluations within the framework of variational quantum algorithms, thus leading to improved ground-state calculations for quantum chemistry and physics problems beyond state-of-the-art results.

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Ding, Jicheng, Lin Zhao, Chun Jia, and Zhibin Luo. "BDS Multipath Parameter Estimation in the Presence of Impulsive Noise." International Journal of Antennas and Propagation 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/864327.

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This study focuses on mitigating the multipath, especially the short-delay multipath of the BeiDou navigation satellite system under impulsive noise conditions. A modified least meanp-norm (LMP) algorithm is developed to reduce the convergence time with the same steady-state error by predicting the updating trend of weights. The modified normalized power and the normalized polynomial least meanpth power are also directly provided according to a similar principle. According to the research work, an average filter has been utilized to improve the processing gain of designed mitigation scheme. Some significant simulation results verified the performance of the proposed adaption algorithm. Multipath parameter estimation tests have been conducted under different noise levels. Some comparative statistics performance assessments are quantified and verified under impulsive and additional white Gaussian noise environments. Results with various window widths of the average filtering and carrier-to-noise ratios indicate that the proposed scheme is able to improve the performance of the short-delay multipath mitigation under normal and degraded environments.

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Liu, Wen Ping, Meng Wang, and Zhen Jie Zhu. "Bottleneck Mitigation of Assembly Lines with Memetic Algorithms." Advanced Materials Research 655-657 (January 2013): 1631–35. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.1631.

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Bottlenecks heavily affect the material flow and workloads of assembly lines, and eventually constrain the productivity. The most economic way to eliminate or mitigate bottlenecks of a specific assembly line is to smooth the workloads at different stations towards a balanced system. This paper formulates a smoothness index, by which to measure the uniformity of workloads at serially located stations. To minimize the smoothness index, a Memetic algorithm is adopted and coding/decoding methods of the algorithm are devised. The effectiveness of the proposed algorithm is validated by a comparison with computing results of Package Lingo 11.0.

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Zhang, Ruicheng, Chengfa Gao, Qing Zhao, Zihan Peng, and Rui Shang. "An Improved Multipath Mitigation Method and Its Application in Real-Time Bridge Deformation Monitoring." Remote Sensing 13, no. 12 (June 9, 2021): 2259. http://dx.doi.org/10.3390/rs13122259.

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A multipath is a major error source in bridge deformation monitoring and the key to achieving millimeter-level monitoring. Although the traditional MHM (multipath hemispherical map) algorithm can be applied to multipath mitigation in real-time scenarios, accuracy needs to be further improved due to the influence of observation noise and the multipath differences between different satellites. Aiming at the insufficiency of MHM in dealing with the adverse impact of observation noise, we proposed the MHM_V model, based on Variational Mode Decomposition (VMD) and the MHM algorithm. Utilizing the VMD algorithm to extract the multipath from single-difference (SD) residuals, and according to the principle of the closest elevation and azimuth, the original observation of carrier phase in the few days following the implementation are corrected to mitigate the influence of the multipath. The MHM_V model proposed in this paper is verified and compared with the traditional MHM algorithm by using the observed data of the Forth Road Bridge with a seven day and 10 s sampling rate. The results show that the correlation coefficient of the multipath on two adjacent days was increased by about 10% after residual denoising with the VMD algorithm; the standard deviations of residual error in the L1/L2 frequencies were improved by 37.8% and 40.7%, respectively, which were better than the scores of 26.1% and 31.0% for the MHM algorithm. Taking a ratio equal to three as the threshold value, the fixed success rates of ambiguity were 88.0% without multipath mitigation and 99.4% after mitigating the multipath with MHM_V. The MHM_V algorithm can effectively improve the success rate, reliability, and convergence rate of ambiguity resolution in a bridge multipath environment and perform better than the MHM algorithm.

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Zhang, Wen Ming. "A Novel Spoofing Mitigation Method of GNSS Receiver." Applied Mechanics and Materials 239-240 (December 2012): 1206–12. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1206.

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Spoofing is more malignant to GNSS receiver than noise jamming, both military and civil GNSS users need to detect and avoid spoofing. This paper presents a novel spoofing mitigation method based on multi-antenna receiver architecture. The algorithm strengthen the authentic signals in noise jamming environment, and the algorithm will place null in the direction of spoofer and reset the receiver to tracking the authentic signals when spoofing attack successfully. The rule to distinguish spoofing signal from authentic signal is spoofing transmitters often transmit several signals from the same antenna. The strategy and performance of the proposed method is independent of the spoofer’s complexity and ability. Computer simulation confirm the availability of the algorithm.

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Qin, Yechen, Ehsan Hashemi, and Amir Khajepour. "Integrated Crash Avoidance and Mitigation Algorithm for Autonomous Vehicles." IEEE Transactions on Industrial Informatics 17, no. 11 (November 2021): 7246–55. http://dx.doi.org/10.1109/tii.2021.3058948.

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Joshi, Gargi, and A. K. Bongale. "Anomaly Extraction and Mitigation using Efficient-Web Miner Algorithm." International Journal of Computer Applications 100, no. 2 (August 20, 2014): 8–13. http://dx.doi.org/10.5120/17495-8024.

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Jie Li, Renbiao Wu, Dan Lu, and Wenyi Wang. "GPS Multipath Mitigation Algorithm Based on Signal Correlation Character." International Journal of Digital Content Technology and its Applications 7, no. 3 (February 15, 2013): 837–46. http://dx.doi.org/10.4156/jdcta.vol7.issue3.100.

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Wei, W., X. Jin-Yu, and Z. Zhong-Liang. "A New NLOS Error Mitigation Algorithm in Location Estimation." IEEE Transactions on Vehicular Technology 54, no. 6 (November 2005): 2048–53. http://dx.doi.org/10.1109/tvt.2005.858177.

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Fohlmeister, F., A. Iliopoulos, M. Sgammini, F. Antreich, and J. A. Nossek. "Dual polarization beamforming algorithm for multipath mitigation in GNSS." Signal Processing 138 (September 2017): 86–97. http://dx.doi.org/10.1016/j.sigpro.2017.03.012.

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Loehle, Craig. "Optimizing wildlife habitat mitigation with a habitat defragmentation algorithm." Forest Ecology and Management 120, no. 1-3 (July 1999): 245–51. http://dx.doi.org/10.1016/s0378-1127(98)00546-5.

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Padarti, Vijaya Kumar, and N. Venkateswara Rao. "Adaptive SOICAF Algorithm for PAPR Mitigation in OFDM Systems." Wireless Personal Communications 113, no. 2 (April 5, 2020): 927–43. http://dx.doi.org/10.1007/s11277-020-07260-y.

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Wu, Shixun, Dengyuan Xu, and Honggang Wang. "Adaptive NLOS Mitigation Location Algorithm in Wireless Cellular Network." Wireless Personal Communications 84, no. 4 (June 18, 2015): 3143–56. http://dx.doi.org/10.1007/s11277-015-2791-6.

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Le Vine, David M., Paolo de Matthaeis, Christopher S. Ruf, and David D. Chen. "Aquarius RFI Detection and Mitigation Algorithm: Assessment and Examples." IEEE Transactions on Geoscience and Remote Sensing 52, no. 8 (August 2014): 4574–84. http://dx.doi.org/10.1109/tgrs.2013.2282595.

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Ji, Jing, Jiantong Zhang, Wei Chen, and Deliang Su. "A Multipath Mitigation Algorithm for vehicle with Smart Antenna." IOP Conference Series: Earth and Environmental Science 114 (January 2018): 012010. http://dx.doi.org/10.1088/1755-1315/114/1/012010.

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Chien, Ying-Ren, Sendren Sheng-Dong Xu, and Shao-Hang Lu. "Cyclostationary impulsive noise mitigation algorithm for narrowband powerline communications." Journal of the Franklin Institute 357, no. 1 (January 2020): 687–703. http://dx.doi.org/10.1016/j.jfranklin.2019.10.026.

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Georgiev, Yuliyan, Richard Verhoeven, and Nirvana Meratnia. "Selfish Behavior in IEEE 802.11ah Networks: A Detection Algorithm and Mitigation Strategies." Sensors 22, no. 12 (June 13, 2022): 4472. http://dx.doi.org/10.3390/s22124472.

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One of the latest protocols developed for the Internet of Things networks is IEEE 802.11ah, proposed by the WiFi Alliance. The new channel access mechanism in IEEE 802.11ah, which is called Restricted Access Window, aims at reducing the contention between the stations by allowing only selected stations to transmit data at certain time slots. Stations may exhibit selfish behavior to maximize their own throughput. This will come at the cost of the overall network quality of service. In this paper, we first analyze the default behavior of the IEEE 802.11ah protocol in terms of fairness. We then introduce various percentages of selfish stations and observe how the network’s quality of service in terms of fairness, throughput and packet-loss are affected. After establishing the inherent fairness of IEEE 802.11ah, we analyze applicability of two existing selfish behavior detection algorithms designed for IEEE 802.11 to the IEEE 802.11ah protocol. Due to their poor performance, we propose a new definition of ’selfish behavior’ specifically for IEEE 802.11ah, based on which we present a new algorithm for detecting selfish behavior. To combat selfish behavior and to create a better fairness, throughput and lower packet loss, we consequently present a novel mitigation algorithm called Selfish Stations Quarantine Punishment Algorithm (SSQPA). The proposed algorithm takes advantage of the RAW grouping to isolate selfish stations from the honest stations, thus mitigating the effect of the selfish behavior. SSQPA comes in two variants: honest stations-centric and network-centric. Our experimental results show that both variants can successfully mitigate selfish behavior effects in IEEE 802.11ah networks and either one can be used depending on the goal of the network.

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Hui, Yong Tao, Bing Bing Li, Zhao Tong, Xing Wang Zhong, and Hao Liu. "A Short-Delay Multipath Mitigation Algorithm Based on Variable Step-Size LMS Adaptive Filtering." Applied Mechanics and Materials 571-572 (June 2014): 368–75. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.368.

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The multipath in the inter-spacecraft microwave ranging system is the short-delay multipath generally. The performance of existing multipath mitigation algorithms degrade in the short-delay scenario, and therefore an adaptive filtering algorithm based on variable step-size LMS is exploited for estimating the parameters of multipath signals. Firstly, the equation of variable step-size LMS is deduced. Then, the signals parameters are estimated recursively though the adaptive filtering algorithm. Multipath elimination is performed by substracting the estimated multipath effects from the measured correlation function. Simulation results validate that the proposed method is superior to the existing algorithms in the aspect of convergence rate and ranging accuracy for the short delay multipath. Therefore, it is a viable solution for achieving high accuracies measurements in microwave ranging system with short-delay multipath.

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Son, Pyo-Woong, Jongmin Park, Jaewon Yu, Suhui Jeong, Younghoon Han, and Tae Hyun Fang. "Skywave Detection and Mitigation for the MF R-Mode Continuously Operating Reference Station." Sensors 23, no. 11 (May 24, 2023): 5046. http://dx.doi.org/10.3390/s23115046.

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There is an increasing need for an independent terrestrial navigation system, owing to the increasing reliance on global navigation satellite systems (GNSS). The medium-frequency range (MF R-Mode) system is considered a promising alternative; however, the skywave effect caused by ionospheric changes at night can degrade its positioning accuracy. To address this problem, we developed an algorithm to detect and mitigate the skywave effect on MF R-Mode signals. The proposed algorithm was tested using data collected from Continuously Operating Reference Stations (CORS) monitoring the MF R-Mode signals. The skywave detection algorithm is based on the signal-to-noise ratio (SNR) induced by the groundwave and skywave composition, whereas the skywave mitigation algorithm was derived from the I and Q components of the signals obtained through IQ modulation. The results demonstrate a significant improvement in the precision and standard deviation of the range estimation using CW1 and CW2 signals. The standard deviations decreased from 39.01 and 39.28 m to 7.94 and 9.12 m, respectively, while the precision (2-sigma) increased from 92.12 and 79.82 m to 15.62 and 17.84 m, respectively. These findings confirm that the proposed algorithms can enhance the accuracy and reliability of MF R-Mode systems.

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Yao, Yuan, and Longyun Kang. "The Virtual Harmonic Power Droop Strategy to Mitigate the Output Harmonic Voltage of the Inverter." Energies 11, no. 9 (August 22, 2018): 2196. http://dx.doi.org/10.3390/en11092196.

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The harmonic voltage issue becomes a challenge for a distributed generation system. Considering that droop control is the most common control algorithm used in the distributed system, a virtual harmonic power droop strategy which aims to mitigate the harmonic voltage is proposed in this paper. First, the conventional droop control is analyzed. Based on that concept, the virtual power algorithm is introduced. Second, the output harmonic voltage issue and the mathematical model of the inverter are presented. In addition, the second-order generalized integrator is briefly discussed. Third, taking into consideration the algorithms and models presented, a virtual harmonic power droop strategy is proposed to implement the harmonic voltage mitigation. In this algorithm, signals in fundamental frequency and harmonic frequency are separated with the help of second-order generalized integrators. Unlike the conventional voltage–current dual loop structure which is used to mitigate system harmonics, this method only needs the virtual power feedback to mitigate the harmonic voltage. Based on these features, the system’s control structure is simplified. Simulation and experimental results verified the harmonic voltage mitigation ability of the proposed strategy.

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Aldhyani, Theyazn H. H., and Hasan Alkahtani. "Artificial Intelligence Algorithm-Based Economic Denial of Sustainability Attack Detection Systems: Cloud Computing Environments." Sensors 22, no. 13 (June 21, 2022): 4685. http://dx.doi.org/10.3390/s22134685.

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Cloud computing is currently the most cost-effective means of providing commercial and consumer IT services online. However, it is prone to new flaws. An economic denial of sustainability attack (EDoS) specifically leverages the pay-per-use paradigm in building up resource demands over time, culminating in unanticipated usage charges to the cloud customer. We present an effective approach to mitigating EDoS attacks in cloud computing. To mitigate such distributed attacks, methods for detecting them on different cloud computing smart grids have been suggested. These include hard-threshold, machine, and deep learning, support vector machine (SVM), K-nearest neighbors (KNN), random forest (RF) tree algorithms, namely convolutional neural network (CNN), and long short-term memory (LSTM). These algorithms have greater accuracies and lower false alarm rates and are essential for improving the cloud computing service provider security system. The dataset of nine injection attacks for testing machine and deep learning algorithms was obtained from the Cyber Range Lab at the University of New South Wales (UNSW), Canberra. The experiments were conducted in two categories: binary classification, which included normal and attack datasets, and multi-classification, which included nine classes of attack data. The results of the proposed algorithms showed that the RF approach achieved accuracy of 98% with binary classification, whereas the SVM model achieved accuracy of 97.54% with multi-classification. Moreover, statistical analyses, such as mean square error (MSE), Pearson correlation coefficient (R), and the root mean square error (RMSE), were applied in evaluating the prediction errors between the input data and the prediction values from different machine and deep learning algorithms. The RF tree algorithm achieved a very low prediction level (MSE = 0.01465) and a correlation R2 (R squared) level of 92.02% with the binary classification dataset, whereas the algorithm attained an R2 level of 89.35% with a multi-classification dataset. The findings of the proposed system were compared with different existing EDoS attack detection systems. The proposed attack mitigation algorithms, which were developed based on artificial intelligence, outperformed the few existing systems. The goal of this research is to enable the detection and effective mitigation of EDoS attacks.

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Patil, Sagargouda S., and H. A. Dinesha. "URL Redirection Attack Mitigation in Social Communication Platform using Data Imbalance Aware Machine Learning Algorithm." Indian Journal of Science and Technology 15, no. 11 (March 21, 2022): 481–88. http://dx.doi.org/10.17485/ijst/v15i11.1813.

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Bender, Emmanuel, Joseph B. Bernstein, and Duane S. Boning. "Mitigation of Thermal Stability Concerns in FinFET Devices." Electronics 11, no. 20 (October 14, 2022): 3305. http://dx.doi.org/10.3390/electronics11203305.

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Here, we developed a procedure for mitigating thermal hazards in packaged FinFET devices. A monitoring system was installed into devices, based on self-heating impact analysis in the system and device levels, to allow for the observation and alerting of chip temperature and reliability risks. A novel algorithm for reducing measurement noise by means of temperature fluctuation compensation and the filtering of invalid data is presented and demonstrated on packaged devices. The results presented in this work show that the proposed techniques make exceptional improvements to sensory accuracy. Using this methodology enables the mitigation of thermal concerns in systems, including large data servers, and accelerates development of smart resource allocation formations.

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Nweke, J. N., A. G. Gusau, and L. M. Isah. "Reliability and protection in distribution power system considering customer-based indices." Nigerian Journal of Technology 39, no. 4 (March 24, 2021): 1198–205. http://dx.doi.org/10.4314/njt.v39i4.28.

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A stable and reliable electric power supply system is a pre-requisite for the technological and economic growth of any nation. Nigeria's power supply has been experiencing incessant power interruptions caused by a failure in the distribution system. This paper developed a system planning approach as part of the key mitigation strategies for improved reliability and protection of the distribution network. The developed algorithm is tested using 33kV feeder supplying electricity to Kaura-Namoda, Zamfara State, Nigeria. A customer-based reliability index was used as a tool to evaluate the reliability assessment of the feeder test system. The result showed that alternative 3 gives better results in terms of improvement of the system average interruption duration index (SAIDI), which in turn gives the minimum interrupted energy. Also, it is found that a greater number of sectionalizing switches do not give better results. It is very important to place the sectionalizing switches at a strategic location. If it is located at such points that will facilitate to sectionalize the faulty sections faster and to make the supply available to the unfaulty part of the network. Hence the utility company should apply this mitigation algorithm for system reliability improvement, depending on their needs and requirements. Thus, utilities can optimize network performance and better serve customers by adopting mitigation strategies in addressing trouble-prone areas to achieve a stable and reliable supply Keywords: distribution system; reliability; reliability indices; system performance evaluation; protection system; mitigation algorithms and sectionalizing switches

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Steeb, Jan-Willem W., David B. Davidson, and Stefan J. Wijnholds. "Mitigation of Non-Narrowband Radio Frequency Interference Incorporating Array Imperfections." Journal of Astronomical Instrumentation 08, no. 01 (March 2019): 1940013. http://dx.doi.org/10.1142/s2251171719400130.

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In a recent paper, we presented a non-narrowband spatial radio frequency interference (RFI) mitigation algorithm for radio astronomy arrays. The algorithm constructs a 2nd-order filter by combining a 1st-order subspace subtraction method with a non-narrowband signal model. The model is based on the assumption that the frequency response is approximately flat and that the array is calibrated. In this paper, we consider the effects of array imperfections such as unknown complex gains and mutual coupling, incorporate these into the non-narrowband signal model and extend the RFI mitigation algorithm to include a calibration step. With a calibration step and no mutual coupling, the proposed algorithm was able to process twice the bandwidth per channel when compared to conventional narrowband techniques. This performance declines to 1.6 times greater bandwidth when the effect of mutual coupling is included. The evaluation of the algorithm was done using the layout of a Low Frequency Array (LOFAR) High Band Antenna (HBA) station and a digital audio broadcast recorded with a software defined radio.

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Hong, Haisheng, and Quanyuan Jiang. "Model Predictive Control-Based Coordinated Control Algorithm with a Hybrid Energy Storage System to Smooth Wind Power Fluctuations." Energies 12, no. 23 (December 3, 2019): 4591. http://dx.doi.org/10.3390/en12234591.

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Stochastically fluctuating wind power has an escalating impact on the stability of power grid operations. To smooth out short- and long-term fluctuations, this paper presents a coordinated control algorithm using model predictive control (MPC) to manage a hybrid energy storage system (HESS) consisting of ultra-capacitor (UC) and lithium-ion battery (LB) banks. In the HESS-computing period, the algorithm minimizes HESS operating costs in the subsequent prediction horizon by optimizing the time constant of a flexible first-delay filter (FDF) to obtain the UC power output. In the LB-computing period, the algorithm keeps the optimal time constant of the FDF from the previous period to directly obtain the power output of the UC bank to minimize the power output of the LB bank in the next prediction horizon. A relaxation technique is deployed when the problem is unsolvable. Thus, the fluctuation mitigation requirements are fulfilled with a large probability even in extreme conditions. A state-of-charge (SOC) feedback control strategy is proposed to regulate the SOC of the HESS within its proper range. Case studies and quantitative comparisons demonstrate that the proposed MPC-based algorithm uses a lower power rating and storage capacity than other conventional algorithms to satisfy one-minute and 30-min fluctuation mitigation requirements (FMR).

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Dai, Shaojun, Xuehua Li, Zhichao Bu, Yajun Chen, Jianxin He, Minghua Li, and Maojie Xiong. "Signal Simulation of Dual-Polarization Weather Radar and Its Application in Range Ambiguity Mitigation." Atmosphere 13, no. 3 (March 8, 2022): 432. http://dx.doi.org/10.3390/atmos13030432.

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In this paper, a dual-polarization weather radar echo signal simulation method is proposed for the evaluation of the performance enhancement of dual-polarization weather radar systems, the optimization of signal processing algorithms and the improvement of scanning strategies. The actual weather radar base data are used in the simulation as the reference weather scene, which avoids using a complex algorithm for weather modeling. Moreover, based on radar weather equations, the radar system parameters are added into the radar echo signal modeling to establish the relationship between the simulated echo signal and radar system. As a result, the final simulated echo signal not only shows both the time and frequency domain characteristics of the weather target, but also includes the effects of the important performance of the dual-polarization weather radar system. In addition, to evaluate the performance of range ambiguity mitigation using phase coding and batch working modes, two different simulation methods for the radar signal are established on the method above; one is for batch working mode with long-PRT (pulse repetition time) and short-PRT transmission and receiving, and the other is for phase-coded mode with phase-coded transmission and phase-uncoded receiving. Under the same weather scene, the observation of these two different methods of range ambiguity mitigation are simulated and compared. Results show that the performance of the phase coding mode for mitigating range ambiguity is better than that of the batch mode. Obviously, the simulation method can be used to directly show the observation of different algorithms for mitigation range ambiguity under the same weather process, and quickly compare and evaluate the algorithm’s performance, which is not possible for real radars.

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Olumoyin, K. D., A. Q. M. Khaliq, and K. M. Furati. "Data-Driven Deep-Learning Algorithm for Asymptomatic COVID-19 Model with Varying Mitigation Measures and Transmission Rate." Epidemiologia 2, no. 4 (September 24, 2021): 471–89. http://dx.doi.org/10.3390/epidemiologia2040033.

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Epidemiological models with constant parameters may not capture satisfactory infection patterns in the presence of pharmaceutical and non-pharmaceutical mitigation measures during a pandemic, since infectiousness is a function of time. In this paper, an Epidemiology-Informed Neural Network algorithm is introduced to learn the time-varying transmission rate for the COVID-19 pandemic in the presence of various mitigation scenarios. There are asymptomatic infectives, mostly unreported, and the proposed algorithm learns the proportion of the total infective individuals that are asymptomatic infectives. Using cumulative and daily reported cases of the symptomatic infectives, we simulate the impact of non-pharmaceutical mitigation measures such as early detection of infectives, contact tracing, and social distancing on the basic reproduction number. We demonstrate the effectiveness of vaccination on the transmission of COVID-19. The accuracy of the proposed algorithm is demonstrated using error metrics in the data-driven simulation for COVID-19 data of Italy, South Korea, the United Kingdom, and the United States.

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Ali, A., B. Chen, W. Raza, A. Ali, and H. Li. "An Intelligent Detoxification Function of Liver Algorithm-Partial Transmit Sequence (IDFLA-PTS) for the Reduction of Peak to Average Power Ratio in Underwater Acoustic OFDM Communication." Engineering, Technology & Applied Science Research 12, no. 1 (February 12, 2022): 8136–42. http://dx.doi.org/10.48084/etasr.4655.

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Intelligent algorithms in artificial intelligence have brought several benefits to digital signal processing. The boom in machine learning and intelligent systems provides new perspectives and methods to solve many research problems in Underwater Acoustic (UWA) Orthogonal Frequency Divisional Multiplexing (OFDM) communication. Partial transmit sequence is a tremendous technique for the mitigation of high Peak-to-Average Power Ratio (PAPR) in OFDM communication systems, but finding the optimum phase factors has still a few problems. In this paper, a Partial Transmit Sequence (PTS) based on an Intelligent Detoxification Function of Liver Algorithm-Partial Transmit Sequence (IDFLA-PTS) is proposed for the mitigation of PAPR in the UWA OFDM communication systems. This algorithm reduces the PAPR and the complexity of the proposed UWA OFDM model. The IDFLA-PTS is also compared with the Genetic Algorithm-Partial Transmit Sequence (GA-PTS). Besides this, the Bit Error Rate (BER) performance of the IDFLA-PTS is shown when a High Power Ampliﬁer (HPA) is used for the BELLHOP channel model. The experimental results of the proposed IDFLA-PTS method achieved nearly optimum results with fair complexity as compared to GA-PTS and boosted the BER performance.

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Chen, Qian, Ye Cao, Min Jie Guo, and Zheng Rong Tong. "A New Phase Noise and Channel Estimate Method in CO-OFDM System." Applied Mechanics and Materials 130-134 (October 2011): 2936–39. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.2936.

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High phase noise and low phase noise have been consideration in CO-OFDM systems, respectively. The hybrid mitigation algorithm is optimized to approach to high phase noise and low phase noise environment, and a hybrid half-blind phase noise compensation algorithm is proposed, which could be suitable to shifty DFB laser linewidth. 4QAM and 16QAM are used to modulate binary signal. The new proposed phase noise compensation algorithm is considered a mitigation method which has the ability of half-blind self-adaptation. It deduces the coefficient matrix in high and low phase noise compensation matrix and could improve performance under high or low modulation index situation.

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