Journal articles: 'Cycle detection'

1

Cherkassky, Boris V., and Andrew V. Goldberg. "Negative-cycle detection algorithms." Mathematical Programming 85, no. 2 (June 1, 1999): 277–311. http://dx.doi.org/10.1007/s101070050058.

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Amir, Amihood, Estrella Eisenberg, Avivit Levy, Ely Porat, and Natalie Shapira. "Cycle detection and correction." ACM Transactions on Algorithms 9, no. 1 (December 2012): 1–20. http://dx.doi.org/10.1145/2390176.2390189.

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Moinuddin, Rizwan, Bulent Mamikoglu, Sameer Barkatullah, and Jacquelynne P. Corey. "Detection of the Nasal Cycle." American Journal of Rhinology 15, no. 1 (January 1, 2001): 35–39. http://dx.doi.org/10.2500/105065801781329473.

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Oliva, Gabriele, Roberto Setola, Luigi Glielmo, and Christoforos N. Hadjicostis. "Distributed Cycle Detection and Removal." IEEE Transactions on Control of Network Systems 5, no. 1 (March 2018): 194–204. http://dx.doi.org/10.1109/tcns.2016.2593264.

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Nivasch, Gabriel. "Cycle detection using a stack." Information Processing Letters 90, no. 3 (May 2004): 135–40. http://dx.doi.org/10.1016/j.ipl.2004.01.016.

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Cidon, I., J. M. Jaffe, and M. Sidi. "Local Distributed Deadlock Detection by Cycle Detection and Clusterng." IEEE Transactions on Software Engineering SE-13, no. 1 (January 1987): 3–14. http://dx.doi.org/10.1109/tse.1987.232560.

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Sumathi, S., P. Bhuvaneshwari, V. Harikrishnaveni, S. A. Sangami, and N. S. Shivanee Bhuvaneshwari. "A Deep Learning based Advanced Gait Detection." Journal of Physics: Conference Series 2325, no. 1 (August 1, 2022): 012056. http://dx.doi.org/10.1088/1742-6596/2325/1/012056.

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Abstract A gait is a biometric sign that people use to provide visual verification of viewing. Distinctive highlights need more than one movement cycle. In Gait Energy Image (GEI), for example, typical images of a frame with more than one cycle motion are analyzed. The unique stride highlights the required movement of an individual strolling more than one complete walking cycle. For instance, in Gait Energy Image (GEI), normal outline pictures of more than one entire walk cycle are processed. Be that as it may, there may be an incomplete step cycle in which information is accessible due to impediments. This research work has designed and developed a model for implementing stride arrangement and profound learning strategies. A separate walk dataset is used in our trial. The walk marks are removed from the Gait Energy Image (GEI) using the Convolution Neural Network (CNN). The classifier proposed here for grouping human gait postures is Mobile Net. Finally, the proposed methodology is evaluated on the OULP step dataset, affirming that the proposed design effectively reproduces total GEI even from the outrageously deficient walk cycles.

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Chen, Qusen, Hua Chen, Weiping Jiang, Xiaohui Zhou, and Peng Yuan. "A New Cycle Slip Detection and Repair Method for Single-Frequency GNSS Data." Journal of Navigation 71, no. 6 (May 9, 2018): 1492–510. http://dx.doi.org/10.1017/s0373463318000243.

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Cycle slip detection for single frequency Global Navigation Satellite System (GNSS) data is currently mainly based on measurement modelling or prediction, which cannot be effectively performed for kinematic applications and it is difficult to detect or repair small cycle slips such as half-cycle slips. In this paper, a new method that is based on the total differential of ambiguity and Least-Squares Adjustment (LSA) for cycle slip detection and repair is introduced and validated. This method utilises only carrier-phase observations to build an ambiguity function. LSA is then conducted for detecting and repairing cycle slips, where the coordinate and cycle slips are obtained successively. The performance of this method is assessed through processing short and long baselines in static and kinematic modes and the impact of linearization and atmospheric errors are analysed at the same time under a controlled variable method. The results indicate this method is very effective and reliable in detecting and repairing multiple cycle slips, especially small cycle slips.

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Misiaszek, M. "Experimental Detection of the CNO Cycle." Acta Physica Polonica B Proceedings Supplement 15, no. 3 (2022): 1. http://dx.doi.org/10.5506/aphyspolbsupp.15.3-a24.

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Bernal, D., E. Memarzadeh, and M. Ulriksen. "Limit cycle periods in damage detection." Mechanical Systems and Signal Processing 162 (January 2022): 108037. http://dx.doi.org/10.1016/j.ymssp.2021.108037.

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11

Fontaine, Gaëlle, Fabio Mogavero, Aniello Murano, Giuseppe Perelli, and Loredana Sorrentino. "Cycle Detection in Computation Tree Logic." Electronic Proceedings in Theoretical Computer Science 226 (September 13, 2016): 164–77. http://dx.doi.org/10.4204/eptcs.226.12.

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Yanagita, Emmy, Shingo Kamoshida, Naoko Imagawa, and Tomoo Itoh. "Immunohistochemistry-based Cell Cycle Detection (iCCD)." American Journal of Surgical Pathology 36, no. 5 (May 2012): 769–73. http://dx.doi.org/10.1097/pas.0b013e3182478b93.

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Weir, J. P., S. Koerner, B. Mack, J. Masek, and D. Vanderhoff. "VO2 PLATEAU DETECTION IN CYCLE ERGOMETRY." Medicine & Science in Sports & Exercise 33, no. 5 (May 2001): S45. http://dx.doi.org/10.1097/00005768-200105001-00260.

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14

Nesterenko, A. Yu. "Cycle detection algorithms and their applications." Journal of Mathematical Sciences 182, no. 4 (March 29, 2012): 518–26. http://dx.doi.org/10.1007/s10958-012-0755-x.

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Fontaine, Gaëlle, Fabio Mogavero, Aniello Murano, Giuseppe Perelli, and Loredana Sorrentino. "Cycle detection in computation tree logic." Information and Computation 262 (October 2018): 265–79. http://dx.doi.org/10.1016/j.ic.2018.09.007.

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16

Schall, Eric. "Parallel cycle detection in distributed databases." Information Systems 15, no. 5 (January 1990): 555–66. http://dx.doi.org/10.1016/0306-4379(90)90028-n.

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17

Yang, Xu, Qianxin Wang, and Guobin Chang. "A Solution for Real-Time Ionospheric Delay Using an Adaptive Kalman Filter Based on Estimating the Variance Component." Mathematical Problems in Engineering 2018 (August 29, 2018): 1–21. http://dx.doi.org/10.1155/2018/1721973.

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Real-time solution of Global Navigation Satellite System (GNSS) epoch-differenced ionospheric delay (DID) is of great significance for real-time cycle slip detection and repair of multi-GNSS dual-frequency or trifrequency undifferenced measurements under high ionospheric activity. We construct a dynamic model of DID and perform a real-time estimate of the noise level of DID based on estimating the variance component. The estimated and predicted values of DID are obtained by designing a new adaptive Kalman filter algorithm with colored noise. Combining the predicted value and the detection method for cycle slips for Melbourne-Wübbena (MW) and Geometry-Free (GF) combination and taking into account the correlation between the predicted value and the carrier signal, we estimate the cycle slip, N2, on the second frequency of the carrier signal. The prediction and estimate of DID and detection and repair of dual-frequency cycle slip of multisystem undifferenced phase observations are measured with the GNSS multisystem observational data at different sampling rates (30 s, 15 s, 10 s, and 1 s). The results show that the DID model constructed in this paper is correct. The predicted value of DID has a high accuracy, which can effectively assist in dual-frequency cycle slip detection and repair. (1) The obtained predicted values, the estimated value, and the difference value between the two values of DID are less than 1.2 cm (STD), 1.2 cm (STD), and 0.6 cm (STD), respectively; (2) the precisions of the detection of cycle slip for MW, GF, and N2 are less than 0.083 cycles (STD), 0.4 cm (STD), and 0.071 cycles (STD), respectively; (3) with the obtained predicted value of DID to aid the detection and repair of cycle slip in GNSS double-frequency signals, a success rate of 100% can be reached.

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18

ROBBIO, FEDERICO I., DIEGO M. ALONSO, and JORGE L. MOIOLA. "DETECTION OF LIMIT CYCLE BIFURCATIONS USING HARMONIC BALANCE METHODS." International Journal of Bifurcation and Chaos 14, no. 10 (October 2004): 3647–54. http://dx.doi.org/10.1142/s0218127404011491.

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In this paper, bifurcations of limit cycles close to certain singularities of the vector fields are explored using an algorithm based on the harmonic balance method, the theory of nonlinear feedback systems and the monodromy matrix. Period-doubling, pitchfork and Neimark–Sacker bifurcations of cycles are detected close to a Gavrilov–Guckenheimer singularity in two modified Rössler systems. This special singularity has a zero eigenvalue and a pair of pure imaginary eigenvalues in the linearization of the flow around its equilibrium. The presented results suggest that the proposed technique can be promising in analyzing limit cycle bifurcations arising in the unfoldings of other complex singularities.

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19

G.R, Sanma, and T. Nicho las. "On detection number of cycle related graphs." International Journal of Mathematics Trends and Technology 47, no. 4 (July 25, 2017): 248–52. http://dx.doi.org/10.14445/22315373/ijmtt-v47p534.

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20

Horner, Patrick J., Tessa Crowley, Jo Leece, Anthony Hughes, George Davey Smith, and E. Owen Caul. "Chlamydia trachomatis detection and the menstrual cycle." Lancet 351, no. 9099 (January 1998): 341–42. http://dx.doi.org/10.1016/s0140-6736(05)78335-5.

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21

Guo, Dongbai, and Peter Richardson. "Detection of cardiac cycle from intracoronary ultrasound." Ultrasound in Medicine & Biology 32, no. 3 (March 2006): 345–56. http://dx.doi.org/10.1016/j.ultrasmedbio.2005.12.011.

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22

Wang, Yucheng, Juan Zhang, Hao Jiang, and Zhijun Fang. "Road detection using cycle-consistent adversarial networks." Journal of Electronic Imaging 28, no. 05 (October 17, 2019): 1. http://dx.doi.org/10.1117/1.jei.28.5.053021.

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Hasimoto-Beltrán, Rogelio, and Roxana Ramírez-Ramírez. "Cycle detection for secure chaos-based encryption." Communications in Nonlinear Science and Numerical Simulation 16, no. 8 (August 2011): 3203–11. http://dx.doi.org/10.1016/j.cnsns.2010.11.002.

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24

Sugandhi, K., Farha Fatina Wahid, P. Nikesh, and G. Raju. "An overlap-based human gait cycle detection." International Journal of Biometrics 11, no. 2 (2019): 148. http://dx.doi.org/10.1504/ijbm.2019.099033.

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Raju, G., P. Nikesh, Farha Fatina Wahid, and K. Sugandhi. "An overlap-based human gait cycle detection." International Journal of Biometrics 11, no. 2 (2019): 148. http://dx.doi.org/10.1504/ijbm.2019.10020085.

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26

Faliva, Mario. "Trend-cycle detection as a filtering problem." Journal of the Italian Statistical Society 3, no. 3 (October 1994): 315–38. http://dx.doi.org/10.1007/bf02589022.

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27

Briens, L. A., and C. L. Briens. "Cycle detection and characterization in chemical engineering." AIChE Journal 48, no. 5 (May 2002): 970–80. http://dx.doi.org/10.1002/aic.690480507.

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28

Yu, Chengzhuang, Shijie Dai, Shanshan Li, Junwei Li, Hezhi Hu, Jiyu Meng, Chunyang Wei, and Jie Jayne Wu. "Nucleic Acid Detection with Ion Concentration Polarization Microfluidic Chip for Reduced Cycle Numbers of Polymerase Chain Reaction." Micromachines 13, no. 9 (August 26, 2022): 1394. http://dx.doi.org/10.3390/mi13091394.

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Nucleic acid detection is widely used in disease diagnosis, food safety, environmental monitoring and many other research fields. The continuous development of rapid and sensitive new methods to detective nucleic acid is very important for practical application. In this study, we developed a rapid nucleic-acid detection method using polymerase chain reaction (PCR) combined with electrokinetic preconcentration based on ion concentration polarization (ICP). Using a Nafion film, the proposed ICP microfluidic chip is utilized to enrich the nucleic acid molecules amplified by PCR thermal cycles. To demonstrate the capability of the microfluidic device and the hybrid nucleic-acid detection method, we present an animal-derived component detection experiment for meat product identification applications. With the reduced cycle numbers of 24 cycles, the detection can be completed in about 35 min. The experimental results show that this work can provide a microfluidic device and straightforward method for rapid detection of nucleic acids with reduced cycle numbers.

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Muslikhin, Muslikhin, Aris Nasuha, Fatchul Arifin, Suprapto Suprapto, and Anggun Winursito. "Troop camouflage detection based on deep action learning." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 3 (September 1, 2022): 859. http://dx.doi.org/10.11591/ijai.v11.i3.pp859-871.

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<p><span lang="EN-US">Detecting troop camouflage on the battlefield is crucial to beat or decide in critical situations to survive. This paper proposed a hybrid model based on deep action learning for camouflage recognition and detection. To involve deep action learning in this proposed system, deep learning based on you only look once (YOLOv3) with SquezeeNet and the fourth steps on action learning were engaged. Following the successful formulation of the learning cycle, an instrument examines the environment and performance in action learning with qualitative weightings; specific target detection experiments with view angle, target localization, and the firing point procedure were performed. For each deep action learning cycle, the complete process is divided into planning, acting, observing, and reflecting. If the results do not meet the minimal passing grade after the first cycle, the cycle will be repeated until the system succeeds in the firing point. Furthermore, this study found that deep action learning could enhance intelligence over earlier camouflage detection methods, while maintaining acceptable error rates. As a result, deep action learning could be used in armament systems if the environment is properly identified.</span></p>

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Chen, Hua Sheng, Yong Qi, and Wei Hua Li. "A Dynamic Model of Hierarchical Application Layer Multicast Tree Node Failure Epidemic." Applied Mechanics and Materials 321-324 (June 2013): 2780–84. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.2780.

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Failure Detection periodically detects node validity to maintain application layer network stability. The detection cycle interval value is a key parameter for detection scheme performance; there have been few studies on models of analyzing cycle interval value affecting the scheme. We propose a dynamic model of hierarchical application layer multicast tree node failure epidemic SIRS (NFE-SIRS). The NFE-SIRS analyzes statistical node failure in hierarchical application layer multicast tree structure, and models relationship between cycle interval value and detection scheme repair behavior, finally obtains the expected cycle interval value to improve detection scheme performance. Simulation shows that, the NFE-SIRS can dramatically improve detection scheme performance compared with common fixed cycle interval detection scheme.

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31

Cockerill, Franklin R. "Application of Rapid-Cycle Real-Time Polymerase Chain Reaction for Diagnostic Testing in the Clinical Microbiology Laboratory." Archives of Pathology & Laboratory Medicine 127, no. 9 (September 1, 2003): 1112–20. http://dx.doi.org/10.5858/2003-127-1112-aorrpc.

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Abstract Context.—Rapid-cycle real-time polymerase chain reaction (PCR) technology combines rapid thermocycling with real-time fluorescent probe detection of amplified target nucleic acids. Objectives.—To review and compare the method of rapid-cycle real-time PCR to conventional PCR methods. To describe the application of rapid-cycle real-time PCR for diagnostic testing in the microbiology laboratory. Data Selection.—Information is presented from published literature as well as from personal experience at the Mayo Clinical Microbiology Laboratory (Rochester, Minn). Conclusions.—Compared to conventional PCR methods, rapid-cycle real-time PCR diagnostics are much faster and easier to perform, and, because both PCR and probe detection occur in the same reaction vessel, the possibility of amplified product (amplicon) contamination is lessened. Furthermore, compared to conventional culture-based or direct antigen detection methods, rapid-cycle real-time PCR assays are frequently more sensitive and much more rapid techniques for detecting or quantifying microorganisms in human samples and for identifying genes or mutations in pathogens associated with antimicrobial resistance.

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Brehme, U., U. Stollberg, R. Holz, and T. Schleusener. "ALT pedometer – a new sensor-aided measurement system for improvement in oestrus detection." Research in Agricultural Engineering 52, No. 1 (February 7, 2012): 1–10. http://dx.doi.org/10.17221/4873-rae.

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Without sensor-aided animal data measuring systems far fewer oestrus cycles are recognized because cycle length, oestrus duration and oestrus intensity have developed negatively at high animal performance rates. This development makes it eminently clear that observation of the mating season in the dairy cattle sector is even more important than assumed so far if the financial losses due to insufficient herd fertility are not to become a business problem. Electronic identification and measuring systems represent key technologies for progressive automation in animal husbandry in modern, future-oriented livestock farming. Suitable objective measuring systems are needed in animals husbandry to quickly and safely recognize animal illness, normal oestrus cycle, silent heat or suffering from stress. Pedometer and transponder from different companies play an important role for measuring from animals data and statements in animals health and oestrus monitoring. Modern sensors (sensors, bio sensors), increasingly non-invasive measuring and transfer methods make crucial improvements in the potential for measuring animal data. A new type of pedometer, called ALT pedometer, for three measurement parameters (activity, lying time, temperature), a real time watch and a change measuring time interval was developed. With this system it is possible to select different time intervals between 1 and 60 min for continuous measuring. The results for oestrus detection are excellent. The high correspondence between the measuring parameters activity and lying time allow a statement to be made early and safely on animal illnesses and the time of the oestrus cycle.

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33

Lee, Sang-Un. "Cycle Detection in Discrete Logarithm Using a Queue." Journal of the Institute of Internet Broadcasting and Communication 17, no. 3 (June 30, 2017): 1–7. http://dx.doi.org/10.7236/jiibc.2017.17.3.1.

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Wang, Z., X. Wang, S. Ji, and W. Chen. "Optimal cycle slip detection and correction with reliability." Survey Review 48, no. 349 (March 30, 2016): 233–39. http://dx.doi.org/10.1179/1752270615y.0000000024.

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35

Mavrak, Dano. "Analytical model of deception detection in intelligence cycle." Vojno delo 68, no. 7 (2016): 129–63. http://dx.doi.org/10.5937/vojdelo1607129m.

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GUNGOR, ANIL, RIZWAN MOINUDDIN, ROBERT H. NELSON, and JACQUELYNNE P. COREY. "Detection of the Nasal Cycle with Acoustic Rhinometry." Otolaryngology–Head and Neck Surgery 120, no. 2 (February 1999): 238–47. http://dx.doi.org/10.1016/s0194-5998(99)70413-4.

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37

Lee, Howard, and Yi-Ping Phoebe Chen. "Cell cycle phase detection with cell deformation analysis." Expert Systems with Applications 41, no. 6 (May 2014): 2644–51. http://dx.doi.org/10.1016/j.eswa.2013.10.055.

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38

Kirner, Tereza G. "Detection of cycle in real-time system specification." ACM SIGPLAN Notices 29, no. 7 (July 1994): 43–50. http://dx.doi.org/10.1145/181593.181599.

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39

Kumamoto, Hiroyuki, Kenji Kimi, and Kiyoshi Ooya. "Detection of cell cycle-related factors in ameloblastomas." Journal of Oral Pathology and Medicine 30, no. 5 (May 2001): 309–15. http://dx.doi.org/10.1034/j.1600-0714.2001.300509.x.

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40

Jesus, Bruno, Jean-Luc Mouget, and Rupert G. Perkins. "DETECTION OF DIATOM XANTHOPHYLL CYCLE USING SPECTRAL REFLECTANCE1." Journal of Phycology 44, no. 5 (October 2008): 1349–59. http://dx.doi.org/10.1111/j.1529-8817.2008.00583.x.

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41

Allender, Eric, and Maria M. Klawe. "Improved lower bounds for the cycle detection problem." Theoretical Computer Science 36 (1985): 231–37. http://dx.doi.org/10.1016/0304-3975(85)90044-1.

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42

Park, Min-Hwa, Ki-Young Kwak, and Dong-Wook Kim. "Developing a portable gait cycle detection system using an inertial sensor and evaluating the accuracy of the gait cycle detection." Technology and Health Care 24, s1 (December 8, 2015): S69—S76. http://dx.doi.org/10.3233/thc-151054.

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43

Zhang, Kai, Jianxiang Yin, and Yunze He. "Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries." Sensors 21, no. 3 (January 21, 2021): 712. http://dx.doi.org/10.3390/s21030712.

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The health detection of lithium ion batteries plays an important role in improving the safety and reliability of lithium ion batteries. When lithium ion batteries are in operation, the generation of bubbles, the expansion of electrodes, and the formation of electrode cracks will produce stress waves, which can be collected and analyzed by acoustic emission technology. By building an acoustic emission measurement platform of lithium ion batteries and setting up a cycle experiment of lithium ion batteries, the stress wave signals of lithium ion batteries were analyzed, and two kinds of stress wave signals which could characterize the health of lithium ion batteries were obtained: a continuous acoustic emission signal and a pulse type acoustic emission signal. The experimental results showed that during the discharge process, the amplitude of the continuous acoustic emission signal decreased with the increase of the cycle times of batteries, which could be used to characterize performance degradation; there were more pulse type acoustic emission signals in the first cycle of batteries, less in the small number of cycles, and slowly increased in the large number of cycles, which was in line with the bathtub curve and could be used for aging monitoring. The research on the health of lithium ion batteries by acoustic emission technology provides a new idea and method for detecting the health lithium ion batteries.

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Dai, Zhen, Stefan Knedlik, and Otmar Loffeld. "Instantaneous Triple-Frequency GPS Cycle-Slip Detection and Repair." International Journal of Navigation and Observation 2009 (August 23, 2009): 1–15. http://dx.doi.org/10.1155/2009/407231.

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A real-time algorithm to detect, determine, and validate the cycle-slips for triple-frequency GPS is proposed. The cycle-slip detection is implemented by simultaneously applying two geometry-free phase combinations in order to detect more insensitive cycle-slips, and it is applicable for high data rate applications. The cycle-slip determination adaptively uses the predicted phase data and the code data. LAMBDA technique is applied to search for the cycle-slip candidates. The cycle-slip validation provides strict test criteria to identify the cycle-slip candidates under low phase noise. The reliability of the proposed algorithms is tested in different simulated scenarios.

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Rand, Zoe R., Jason D. Wood, and Julie N. Oswald. "Effects of duty cycles on passive acoustic monitoring of southern resident killer whale (Orcinus orca) occurrence and behavior." Journal of the Acoustical Society of America 151, no. 3 (March 2022): 1651–60. http://dx.doi.org/10.1121/10.0009752.

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Long-term passive acoustic monitoring of cetaceans is frequently limited by the data storage capacity and battery life of the recording system. Duty cycles are a mechanism for subsampling during the recording process that facilitates long-term passive acoustic studies. While duty cycles are often used, there has been little investigation on the impact that this approach has on the ability to answer questions about a species' behavior and occurrence. In this study, the effects of duty cycling on the acoustic detection of southern resident killer whales (SRKW) ( Orcinus orca) were investigated. Continuous acoustic data were subsampled to create 288 subsampled datasets with cycle lengths from 5 to 180 min and listening proportions from 1% to 67%. Duty cycles had little effect on the detection of the daily presence of SRKW, especially when using cycle lengths of less than an hour. However, cycle lengths of 15–30 min and listening proportions of at least 33% were required to accurately calculate durations of acoustic bouts and identify those bouts to ecotype. These results show that the optimal duty cycle depends on the scale of the research question and provide a framework for quantitative analysis of duty cycles for other marine species.

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Ning, Yipeng, Junye Cui, Wenshuo Zhao, Dashuai Chai, Yingjun Sun, Jianping Xing, and Shengli Wang. "A Novel Cycle Slips Detection and Repair Method with AR Model of BDS-3 Dual-Frequency Signal in Severe Multipath Environments." Applied Sciences 13, no. 1 (December 20, 2022): 27. http://dx.doi.org/10.3390/app13010027.

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High-level applications of geo-processing services generally lack accurate temporal and spatial information. BDS-3 provides high precision temporal and spatial reference for geoprocessing services, but their signal is prone to cycle slips in a severe multipath environment. Aiming at the problem of the reliable detection and repair of cycle slips in BDS-3 (B1c+B2a) dual-frequency positioning in a severe multipath environment, an AR (autoregressive) model-assisted MW+GF BDS dual-frequency combined detection method (AMG method) is proposed in this research. A sliding-window autoregressive prediction strategy is introduced to correct the pseudorange observations interfered by a multipath, then an AR+MW+GF cycle slips detection model is constructed, and a cycle slips statistical completeness test index is established to verify the effectiveness of the algorithm. Six groups of cycle slips are artificially added into the different constellations and dual-frequency point phase observations of BDS-3 (B1c and B2a) in a multipath environment to demonstrate the cycle slips’ detection performance. The experimental results show that the traditional MW+GF method fails, but the proposed AMG method still maintains accurate cycle slip detection and repair capabilities. The detection success rate and repair success rate obtained by using the new method are significantly improved by 63.4%, and the cycle slips’ false detection rate and missed detection rate are reduced by 64.5% and 42.0%, respectively, even in harsh environments.

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47

Chen, Kun, Hongtao Li, Chunshu Li, Xinyue Zhao, Shujie Wu, Yuxiao Duan, and Jinshen Wang. "An Automatic Defect Detection System for Petrochemical Pipeline Based on Cycle-GAN and YOLO v5." Sensors 22, no. 20 (October 17, 2022): 7907. http://dx.doi.org/10.3390/s22207907.

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Defect detection of petrochemical pipelines is an important task for industrial production safety. At present, pipeline defect detection mainly relies on closed circuit television method (CCTV) to take video of the pipeline inner wall and then detect the defective area manually, so the detection is very time-consuming and has a high rate of false and missed detections. To solve the above issues, we proposed an automatic defect detection system for petrochemical pipeline based on Cycle-GAN and improved YOLO v5. Firstly, in order to create the pipeline defect dataset, the original pipeline videos need pre-processing, which includes frame extraction, unfolding, illumination balancing, and image stitching to create coherent and tiled pipeline inner wall images. Secondly, aiming at the problems of small amount of samples and the imbalance of defect and non-defect classes, a sample enhancement strategy based on Cycle-GAN is proposed to generate defect images and expand the data set. Finally, in order to detect defective areas on the pipeline and improve the detection accuracy, a robust defect detection model based on improved YOLO v5 and Transformer attention mechanism is proposed, with the average precision and recall as 93.10% and 90.96%, and the F1-score as 0.920 on the test set. The proposed system can provide reference for operators in pipeline health inspection, improving the efficiency and accuracy of detection.

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48

Goel, Sandeep. "Earnings management detection over earnings cycles: the financial intelligence in Indian corporate." Journal of Money Laundering Control 20, no. 2 (May 2, 2017): 116–29. http://dx.doi.org/10.1108/jmlc-06-2016-0023.

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Purpose It is largely believed that stock pricing is influenced by disclosure of earnings. This motivates the corporate to exercise earnings management practices. This paper aims to analyse and detect the earnings management practices of Indian firms over earnings cycles. The earnings behaviour of the firms has been analysed at three levels of earnings cycles for the pricing effect: complete, incomplete and prospective. In India, the corporate ownership model is promoter-dominated shareholders’model (PDSHM) which highlights the relevance of the study for earnings-management motivation. This paper contributes by examining earnings management of the units at three levels of earnings cycle with regard to stock pricing. Earnings cycles have been decomposed into three components: complete, incomplete and prospective. While earnings management has been studied extensively, virtually all studies have focused on firm-specific effects. This study relates earnings management to the cycle of the earnings for stock-price effect. Design/methodology/approach The cash-flow model has been used for the computation of accruals (Collins and Hribar, 1999), and D’Angelo model (for calculating discretionary accruals) has been used for detecting earnings management in the present study, being comprehensive in nature and detailed in approach. The results of the “complete earnings cycle”are measured by net income. The results of the “incomplete earnings cycle” are measured by the ratio of gross margin over sales multiplied by inventory. It yields an approximate measure of the unrealized holding gains and losses. The “prospective earnings cycle” stems from the management decision to choose a rate of income growth. Statistical tools have been used for testing the results. These include regression analysis and descriptive statistics like arithmetic mean, median and standard deviation. Findings An examination of the units shows that firms report more discretionary accruals (DACC) at complete cycle, i.e. when financial markets are more certain about their future prospects which influence their securities’ pricing. It verified that unrealized income and growth prospects have very little role to play in determining returns. The results indicated that each of the components of the earnings cycle has a relevance factor for returns. In complete earnings cycle, DACC had the highest significance on returns than operating cash flows (OCF) and non-discretionary accruals (NDACC). Its determination content is the highest. So, the firms report more negative DACC when financial markets are less certain about their future prospects. Stock-price responses to earnings surprises are moderated when firm-level uncertainty is high, consistent with performance being attributed more to chance rather than performance. Research limitations/implications The present study could be confined to only top 12 profit-making corporate enterprises in the private sector in India, leaving all other enterprises due to data non-availability. Of 25 enterprises, there were public sector undertakings too which had to be excluded. The period in the study is of five years (from 2003-2004 to 2007-2008) to highlight earnings management motivation. This period is best suited to identify the effects of global recession on the practice of earnings management in India. Researchers may like to select a different time-period based on their perspective. Practical implications It is hoped that the study would improve the understanding of the manner in which the capital markets process the publicly available earnings and its components for global firms. The findings of this study are significant not only for organisations that function in India but also for other companies that are based in economies with relatively mature corporate governance mechanisms. So, the authors’ findings have important policy implications for the Western world, as the sample companies are multinationals and operate globally. Similar efforts in other countries would be rewarding in controlling the management of reported earnings and enhance the reliability and transparency of reported earnings to promote economic efficiency. Social implications Evidence on this issue could bring a new dimension to how the capital markets interpret these reported earnings and its components (cash flows, DACC and NDACC) at different levels of earnings cycles for minority shareholders in particular. Further, the evidence could also provide insights into the economic incentives for discretionary accounting choice and disclosure of the results of these earnings cycles. Originality/value It is an original paper which highlights the earnings behaviour and its motivation in Indian corporate enterprises for earnings cycles with regard to stock pricing.

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Dong, Yanchen, Peipei Dai, Sen Wang, Jianping Xing, Yulei Xue, Shijie Liu, Shuai Han, Zhi Yang, and Xinchao Bai. "A Study on the Detecting Cycle Slips and a Repair Algorithm for B1/B3." Electronics 10, no. 23 (November 25, 2021): 2925. http://dx.doi.org/10.3390/electronics10232925.

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For the current problem of cycle slips in the observation data of the BDS-2 and BDS-3 (Bei Dou Navigation Satellite System), in this paper, BDS B1I and B3I signals are used as research objects to study the detection of cycle slips, and their repair algorithm. The Geometry-free (GF) and Melbourne–Wübeena (MW) combination algorithm are used for the detection of cycle slips. A new method of arc partition is proposed in this work to detect cycle slips as the boundary to delimit two different observation arcs. In this way, the different values of cycle slips can be divided and marked. Moreover, the gross errors can be removed. Finally, the detection of cycle slips and the analysis of all epochs can be completed and repaired. This work also analyzes the dual-frequency data effect of cycle slips on code multipath observation. The results showed that this method greatly improved the speed of detection of cycle slips.

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Farooq, Salma Zainab, Dongkai Yang, and Echoda Ngbede Joshua Ada. "A Cycle Slip Detection Framework for Reliable Single Frequency RTK Positioning." Sensors 20, no. 1 (January 6, 2020): 304. http://dx.doi.org/10.3390/s20010304.

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Single frequency real-time kinematic (RTK) positioning is expected to be the leading implementation platform for a variety of emerging GNSS mass-market applications. During RTK positioning, the most common source of measurement errors is carrier-phase cycle slips (CS). The presence of CS in carrier-phase measurements is tested by a CS detection technique and correspondingly taken care of. While using CS prone measurement data, positioning reliability is an area of concern for RTK users. Reliability can be linked with the CS detection scheme through a least squares (LS) adjustment process. This paper proposes a CS detection framework for reliable RTK positioning using single-frequency GNSS receivers. The scheme uses double differenced measurements for CS detection via LS adjustment using a detection, identification, and adaptation approach. For reliable positioning, the procedure to link the detection and identification stages is described. Through tests conducted on kinematic data, internal and external reliability are theoretically determined by calculating minimal detectable bias (MDB) and marginally detectable errors, respectively. After introducing CS, the actual values of MDB are found to be four cycles, which are higher than the theoretically obtained values of one and two cycles. Although CS detection for reliable positioning is implemented for single-frequency RTK users, the proposed procedure is generic and can be used whenever CS are detected through statistical tests during LS adjustment.

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Journal articles on the topic 'Cycle detection'

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