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Journal articles on the topic 'Propagation impairment mitigation techniques'
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Rafiqul, Islam Md, Ali Kadhim Lwas, Mohamed Hadi Habaebi, et al. "Analysis of Time Diversity Gain for Satellite Communication Link based on Ku-Band Rain Attenuation Data Measured in Malaysia." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 4 (2018): 2608. http://dx.doi.org/10.11591/ijece.v8i4.pp2608-2613.
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<p><span>This paper reports a study on mitigation of propagation impairments on Earth–space communication links. The study uses time diversity as a technique for mitigating rain propagation impairment in order to rectify rain fade. Rain attenuation time series along earth-to-satellite link were measured for two years period at 12.255 GHz in Malaysia. The time diversity technique was applied on measured rain fade to investigate the level of possible improvement in system. Time diversity gain from measured one-minute rain attenuation for two years period was estimated and significant improvement was observed with different delays of time. These findings will be utilized as a useful tool for link designers to apply time diversity as a rain fade mitigation technique in Earth-satellite communications systems.</span></p>
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Panagopoulos, Athanasios D., Pantelis-Daniel M. Arapoglou, and Panayotis G. Cottis. "Satellite communications at KU, KA, and V bands: Propagation impairments and mitigation techniques." IEEE Communications Surveys & Tutorials 6, no. 3 (2004): 2–14. http://dx.doi.org/10.1109/comst.2004.5342290.
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Mohebbi Nia, Masoud, Jafri Din, Hong Yin Lam, and Athanasios D. Panagopoulos. "Stochastic Approach to a Rain Attenuation Time Series Synthesizer for Heavy Rain Regions." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (2016): 2379. http://dx.doi.org/10.11591/ijece.v6i5.11741.
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<p>In this work, a new rain attenuation time series synthesizer based on the stochastic approach is presented. The model combines a well-known interest-rate prediction model in finance namely the Cox-Ingersoll-Ross (CIR) model, and a stochastic differential equation approach to generate a long-term gamma distributed rain attenuation time series, particularly appropriate for heavy rain regions. The model parameters were derived from maximum-likelihood estimation (MLE) and Ordinary Least Square (OLS) methods. The predicted statistics from the CIR model with the OLS method are in good agreement with the measurement data collected in equatorial Malaysia while the MLE method overestimated the result. The proposed stochastic model could provide radio engineers an alternative solution for the design of propagation impairment mitigation techniques (PIMTs) to improve the Quality of Service (QoS) of wireless communication systems such as 5G propagation channel, in particular in heavy rain regions.</p>
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Mohebbi Nia, Masoud, Jafri Din, Hong Yin Lam, and Athanasios D. Panagopoulos. "Stochastic Approach to a Rain Attenuation Time Series Synthesizer for Heavy Rain Regions." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (2016): 2379. http://dx.doi.org/10.11591/ijece.v6i5.pp2379-2386.
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<p>In this work, a new rain attenuation time series synthesizer based on the stochastic approach is presented. The model combines a well-known interest-rate prediction model in finance namely the Cox-Ingersoll-Ross (CIR) model, and a stochastic differential equation approach to generate a long-term gamma distributed rain attenuation time series, particularly appropriate for heavy rain regions. The model parameters were derived from maximum-likelihood estimation (MLE) and Ordinary Least Square (OLS) methods. The predicted statistics from the CIR model with the OLS method are in good agreement with the measurement data collected in equatorial Malaysia while the MLE method overestimated the result. The proposed stochastic model could provide radio engineers an alternative solution for the design of propagation impairment mitigation techniques (PIMTs) to improve the Quality of Service (QoS) of wireless communication systems such as 5G propagation channel, in particular in heavy rain regions.</p>
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Zhao, Jian, Yaping Liu, and Tianhua Xu. "Advanced DSP for Coherent Optical Fiber Communication." Applied Sciences 9, no. 19 (2019): 4192. http://dx.doi.org/10.3390/app9194192.
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In this paper, we provide an overview of recent progress on advanced digital signal processing (DSP) techniques for high-capacity long-haul coherent optical fiber transmission systems. Not only the linear impairments existing in optical transmission links need to be compensated, but also, the nonlinear impairments require proper algorithms for mitigation because they become major limiting factors for long-haul large-capacity optical transmission systems. Besides the time domain equalization (TDE), the frequency domain equalization (FDE) DSP also provides a similar performance, with a much-reduced computational complexity. Advanced DSP also plays an important role for the realization of space division multiplexing (SDM). SDM techniques have been developed recently to enhance the system capacity by at least one order of magnitude. Some impressive results have been reported and have outperformed the nonlinear Shannon limit of the single-mode fiber (SMF). SDM introduces the space dimension to the optical fiber communication. The few-mode fiber (FMF) and multi-core fiber (MCF) have been manufactured for novel multiplexing techniques such as mode-division multiplexing (MDM) and multi-core multiplexing (MCM). Each mode or core can be considered as an independent degree of freedom, but unfortunately, signals will suffer serious coupling during the propagation. Multi-input–multi-output (MIMO) DSP can equalize the signal coupling and makes SDM transmission feasible. The machine learning (ML) technique has attracted worldwide attention and has been explored for advanced DSP. In this paper, we firstly introduce the principle and scheme of coherent detection to explain why the DSP techniques can compensate for transmission impairments. Then corresponding technologies related to the DSP, such as nonlinearity compensation, FDE, SDM and ML will be discussed. Relevant techniques will be analyzed, and representational results and experimental verifications will be demonstrated. In the end, a brief conclusion and perspective will be provided.
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Dahman, Isabelle, Philippe Arbogast, Nicolas Jeannin, and Bouchra Benammar. "Rain attenuation prediction model for satellite communications based on the Météo-France ensemble prediction system PEARP." Natural Hazards and Earth System Sciences 18, no. 12 (2018): 3327–41. http://dx.doi.org/10.5194/nhess-18-3327-2018.
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Abstract. This paper presents an example of the usage of ensemble weather forecasting for the control of satellite-based communication systems. Satellite communication systems become increasingly sensitive to weather conditions as their operating frequency increases to avoid electromagnetic spectrum congestion and enhance their capacity. In the microwave domain, electromagnetic waves that are conveying information are attenuated between the satellite and Earth terminals in the presence of hydrometeors (mostly rain drops and more marginally cloud droplets). To maintain a reasonable level of service availability, even with adverse weather conditions considering the scarcity of amplification power in spacecraft, fade mitigation techniques have been developed. The general idea behind those fade mitigation techniques is to reroute, change the characteristics or reschedule the transmission in the case of too-significant propagation impairments. For some systems, a scheduling on how to use those mechanisms some hours in advance is required, making assumptions on the future weather conditions affecting the link. To this aim the use of weather forecast data to control the attenuation compensation mechanisms seems of particular interest to maximize the performances of the communication links and hence of the associated economic value. A model to forecast the attenuation on the link based on forecasted rainfall amounts from deterministic or ensemble weather forecasting is presented and validated. In a second phase, the model's application to a simplified telecommunication system allows us to demonstrate the valuable contribution of weather forecasting in the system's availability optimization or in the system's throughput optimization. The benefit of using ensemble forecasts rather than deterministic ones is demonstrated as well.
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Kumar, Amit, and Pallavi Kulkarni. "Pervasive Malware Propagation Mechanism and Mitigation Techniques." International Journal of Computer Applications 125, no. 4 (2015): 37–43. http://dx.doi.org/10.5120/ijca2015905893.
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Harverson, M., and T. R. Brunt. "Computer-aided evaluation of propagation impairment restoration techniques." International Journal of Satellite Communications 6, no. 3 (1988): 343–59. http://dx.doi.org/10.1002/sat.4600060312.
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Adegbindin, I. A., P. A. Owolawi, and M. O. Odhiambo. "Intelligent Weather Awareness Technique for Mitigating Propagation Impairment at SHF and EHF Satellite Network System in a Tropical Climate." SAIEE Africa Research Journal 107, no. 3 (2016): 136–45. http://dx.doi.org/10.23919/saiee.2016.8532238.
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Barral, Valentín, Carlos J. Escudero, José A. García-Naya, and Roberto Maneiro-Catoira. "NLOS Identification and Mitigation Using Low-Cost UWB Devices." Sensors 19, no. 16 (2019): 3464. http://dx.doi.org/10.3390/s19163464.
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Indoor location systems based on ultra-wideband (UWB) technology have become very popular in recent years following the introduction of a number of low-cost devices on the market capable of providing accurate distance measurements. Although promising, UWB devices also suffer from the classic problems found when working in indoor scenarios, especially when there is no a clear line-of-sight (LOS) between the emitter and the receiver, causing the estimation error to increase up to several meters. In this work, machine learning (ML) techniques are employed to analyze several sets of real UWB measurements, captured in different scenarios, to try to identify the measurements facing non-line-of-sight (NLOS) propagation condition. Additionally, an ulterior process is carried out to mitigate the deviation of these measurements from the actual distance value between the devices. The results show that ML techniques are suitable to identify NLOS propagation conditions and also to mitigate the error of the estimates when there is LOS between the emitter and the receiver.
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Closas, Pau, Carles Fernández-Prades, José Diez, and David de Castro. "Nonlinear Bayesian Tracking Loops for Multipath Mitigation." International Journal of Navigation and Observation 2012 (October 17, 2012): 1–15. http://dx.doi.org/10.1155/2012/359128.
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This paper studies Bayesian filtering techniques applied to the design of advanced delay tracking loops in GNSS receivers with multipath mitigation capabilities. The analysis includes tradeoff among realistic propagation channel models and the use of a realistic simulation framework. After establishing the mathematical framework for the design and analysis of tracking loops in the context of GNSS receivers, we propose a filtering technique that implements Rao-Blackwellization of linear states and a particle filter for the nonlinear partition and compare it to traditional delay lock loop/phase lock loop-based schemes.
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Galal, Shaimaa, Noha Nagy, and Mohamed E. El-Sharkawi. "CNMF: A Community-Based Fake News Mitigation Framework." Information 12, no. 9 (2021): 376. http://dx.doi.org/10.3390/info12090376.
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Fake news propagation in online social networks (OSN) is one of the critical societal threats nowadays directing attention to fake news mitigation and intervention techniques. One of the typical mitigation techniques focus on initiating news mitigation campaigns targeting a specific set of users when the infected set of users is known or targeting the entire network when the infected set of users is unknown. The contemporary mitigation techniques assume the campaign users’ acceptance to share a mitigation news (MN); however, in reality, user behavior is different. This paper focuses on devising a generic mitigation framework, where the social crowd can be employed to combat the influence of fake news in OSNs when the infected set of users is undefined. The framework is composed of three major phases: facts discovery, facts searching and, community recommendation. Mitigation news circulation is accomplished by recruiting a set of social crowd users (news propagators) who are likely to accept posting the mitigation news article. We propose a set of features that identify prospect OSN audiences and news propagators. Moreover, we inspect the variant properties of the news circulation process, such as incentivizing news propagators, determining the required number of news propagators, and the adaptivity of the MN circulation process. The paper pinpoints the significance of facts searching and news propagator’s behavior features introduced in the experimental results.
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Liao, Joy Y., Tung Ton, Nathan Slattengren, et al. "Jitter analysis of PLL-generated clock propagation using Jitter Mitigation techniques with laser voltage probing." Microelectronics Reliability 49, no. 9-11 (2009): 1127–31. http://dx.doi.org/10.1016/j.microrel.2009.07.017.
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Jeannin, Nicolas, Laurent Féral, Henri Sauvageot, Laurent Castanet, and Frédéric Lacoste. "A Large-Scale Space-Time Stochastic Simulation Tool of Rain Attenuation for the Design and Optimization of Adaptive Satellite Communication Systems Operating between 10 and 50 GHz." International Journal of Antennas and Propagation 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/749829.
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The design and optimization of propagation impairment techniques for space telecommunication systems operating at frequencies above 20 GHz require a precise knowledge of the propagation channel both in space and time. For that purpose, space-time channel models have to be developed. In this paper the description of a model for the simulation of long-term rain attenuation time series correlated both in space and time is described. It relies on the definition of a stochastic rain field simulator constrained by the rain amount outputs of the ERA-40 reanalysis meteorological database. With this methodology, realistic propagation conditions can be generated at the scale of satellite coverage (i.e., over Europe or USA) for many years. To increase the temporal resolution, a stochastic interpolation algorithm is used to generate spatially correlated time series sampled at 1 Hz, providing that way valuable inputs for the study of the performances of propagation impairment techniques required for adaptive SatCom systems operating at Ka band and above.
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Barral, Valentín, Carlos J. Escudero, José A. García-Naya, and Pedro Suárez-Casal. "Environmental Cross-Validation of NLOS Machine Learning Classification/Mitigation with Low-Cost UWB Positioning Systems." Sensors 19, no. 24 (2019): 5438. http://dx.doi.org/10.3390/s19245438.
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Indoor positioning systems based on radio frequency inherently present multipath-related phenomena. This causes ranging systems such as ultra-wideband (UWB) to lose accuracy when detecting secondary propagation paths between two devices. If a positioning algorithm uses ranging measurements without considering these phenomena, it will face critical errors in estimating the position. This work analyzes the performance obtained in a localization system when combining location algorithms with machine learning techniques applied to a previous classification and mitigation of the propagation effects. For this purpose, real-world cross-scenarios are considered, where the data extracted from low-cost UWB devices for training the algorithms come from a scenario different from that considered for the test. The experimental results reveal that machine learning (ML) techniques are suitable for detecting non-line-of-sight (NLOS) ranging values in this situation.
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Syrjälä, Ville, and Mikko Valkama. "Analysis and mitigation of phase noise and sampling jitter in OFDM radio receivers." International Journal of Microwave and Wireless Technologies 2, no. 2 (2010): 193–202. http://dx.doi.org/10.1017/s1759078710000309.
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This article addresses the analysis and digital signal processing (DSP)-based mitigation of phase noise and sampling clock jitter in orthogonal frequency division multiplexing (OFDM) radios. In the phase noise studies, the basic direct-conversion receiver architecture case is assumed with noisy downconverting oscillator. In the sampling jitter case, on the other hand, the so-called direct-radio-frequency-sampling receiver architecture is deployed utilizing bandpass sub-sampling principle. The basis for the DSP-based impairment mitigation techniques is first formed using analytical receiver modeling with incoming OFDM waveform, where the effects of both oscillator phase noise and sampling clock jitter are mapped to certain type subcarrier cross-talk and distortion compared to ideal receiver case. Then iterative detection principles and interpolation techniques are developed to essentially estimate and cancel the subcarrier distortion. Also some related practical aspects, like channel estimation, are addressed. The performance of the proposed mitigation techniques is analyzed and verified with extensive computer simulations. In the simulations, realistic phase-locked-loop-based oscillator models are used for phase noise and sampling clock jitter. In addition, different received signal conditions like plain additive white Gaussian noise channel and extended ITU-R Vehicular A multipath channel are considered for practical purposes. Altogether the obtained results indicate that the effects of oscillator and sampling clock instabilities can be efficiently reduced using the developed signal processing techniques.
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Ongkowijoyo, Citra S., Hemanta Doloi, and Anthony Mills. "Participatory-based risk impact propagation and interaction pattern analysis using social network analysis." International Journal of Disaster Resilience in the Built Environment 10, no. 5 (2019): 363–78. http://dx.doi.org/10.1108/ijdrbe-06-2017-0041.
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Purpose This paper aims to develop a novel risk analysis model that uses both participatory and computerized techniques to capture and model the dynamic of risk impact propagation and interaction pattern. Design/methodology/approach In this research, an integrated model, applying modified participatory method and novel dichotomize procedure in the perspectives of social network topological analysis, is developed. Findings Based on the analysis output, it is found that; (i) the risk propagation is characterized by its dynamic and non-linear impact pattern, and (ii) the risk interaction is distinguished based on the degree of connectedness between various risks. Research limitations/implications This research assumes that the risk impact propagation and interaction pattern within the risk network are static. Further research is required to analyze the risk network in dynamic circumstances. Practical implications This research contributes in delivering practical tools that could potentially provide a further path for developing mitigation strategy and policies that seek to address the complexity of risk phenomena, and thus enhance community resilience. Social implications This research reveals some underlying patterns of how the risk impact propagation and interaction pattern are structured. Thus, it can help decision-makers make formal arrangements of particular urban infrastructure (UI) governance visible toward building risk plan and mitigation strategies. Originality/value This research contributes to filling the risk management knowledge gap. It is suggested that analyzing risk using a network approach is suited to capture the intricate processes that shape the complexity of UI risk structural network. By validating the model, this research shows the applicability and capability of the model to improve both the RA accuracy and decision making effectiveness towards risk mitigation plan and strategy.
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Harika, S., S. Nagarjuna, T. V. Naveen, G. Sanjay Harshanth, K. Ch. Sri Kavya, and Sarat K. Kotamraju. "Analysis of rain fade mitigation using site diversity technique in southern tropical region of India." International Journal of Engineering & Technology 7, no. 1.1 (2017): 622. http://dx.doi.org/10.14419/ijet.v7i1.1.10790.
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In order to design a reliable earth to satellite microwave link at certain frequencies in tropical region due to multi propagation we come across fading which means variation of attenuation of a signal with time, geographical position and radio frequency. The radio waves propagating through the earth atmosphere is attenuated due to the presence of atmospheric particles such as water vapor, rain drops and the ice particles which absorb and scatter the radio waves and consequently degrade the performance of the microwave link and there is probability of loss of signal strength, to mitigate this problem Site Diversity Technique is used from the different Fade Mitigation Techniques. The analysis of Site Diversity Gain Model based on the measured rainfall data has been done.
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Ali, Farman, Shabbir Ahmad, Fazal Muhammad, Ziaul Haq Abbas, Usman Habib, and Sunghwan Kim. "Adaptive Equalization for Dispersion Mitigation in Multi-Channel Optical Communication Networks." Electronics 8, no. 11 (2019): 1364. http://dx.doi.org/10.3390/electronics8111364.
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Optical communication networks (OCNs) provide promising and cost-effective support for the ultra-fast broadband solutions, thus enabling them to address the ever growing demands of telecommunication industry such as high capacity and end users’ data rate. OCNs are used in both wired and wireless access networks as they offer many advantages over conventional copper wire transmission such as low power consumption, low cost, ultra-high bandwidth, and high transmission rates. Channel effects caused by light propagation through the fiber limits the performance, hence the data rate of the overall transmission. To achieve the maximum performance gain in terms of transmission rate through the OCN, an optical downlink system is investigated in this paper using feed forward equalizer (FFE) along with decision feedback equalizer (DFE). The simulation results show that the proposed technique plays a key role in dispersion mitigation in multi-channel optical transmission to uphold multi-Gb/s transmission. Moreover, bit error rate (BER) and quality factor (Q-factor) below 10 − 5 and above 5, respectively, are achieved with electrical domain equalizers for the OCN in the presence of multiple distortion effects showing the effectiveness of the proposed adaptive equalization techniques.
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Mehmood, Kashif, Muhammad Tabish Niaz, and Hyung Seok Kim. "Dynamic Fractional Frequency Reuse Diversity Design for Intercell Interference Mitigation in Nonorthogonal Multiple Access Multicellular Networks." Wireless Communications and Mobile Computing 2018 (July 15, 2018): 1–18. http://dx.doi.org/10.1155/2018/1231047.
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Nonorthogonal multiple access (NOMA) is one of the few promising techniques that can ensure the achievement of benefits foreseen in next-generation 5G wireless networks and beyond. By using superposition coding, NOMA allows multiple users to share the same time and frequency resources, thereby enhancing user connectivity, spectral efficiency, and a considerable increase in user throughput. Interference mitigation is an important consideration in NOMA and is considerably more influencing in multicellular environments. First, a brief description of the impairments that can arise in a NOMA cellular network along with responsible factors is provided. Second, different approaches adopted to minimize these impairments are discussed. Finally, a possible solution is proposed that consists of a coordinated approach between the individual cells in the NOMA domain to minimize interferences and improve user throughput. Adaptive fractional frequency reuse (FFR) is used to allocate distinct frequency resources to edge users of different cells to minimize intercell interference in NOMA. Simulation results prove that the proposed NOMA scheme plays an important role in minimizing impairment effects and enhancing the SINR and the throughput performance of edge users while ensuring fairness in its design.
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Drabik, Dominik, Grzegorz Chodaczek та Sebastian Kraszewski. "Effect of Amyloid-β Monomers on Lipid Membrane Mechanical Parameters–Potential Implications for Mechanically Driven Neurodegeneration in Alzheimer’s Disease". International Journal of Molecular Sciences 22, № 1 (2020): 18. http://dx.doi.org/10.3390/ijms22010018.
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Alzheimer’s disease (AD) is a neurodegenerative disease that results in memory loss and the impairment of cognitive skills. Several mechanisms of AD’s pathogenesis were proposed, such as the progressive accumulation of amyloid-β (Aβ) and τ pathology. Nevertheless, the exact neurodegenerative mechanism of the Aβ remains complex and not fully understood. This paper proposes an alternative hypothesis of the mechanism based on maintaining the neuron membrane’s mechanical balance. The incorporation of Aβ decreases the lipid membrane’s elastic properties, which eventually leads to the impairment of membrane clustering, disruption of mechanical wave propagation, and change in gamma oscillations. The first two disrupt the neuron’s ability to function correctly while the last one decreases sensory encoding and perception enabling. To begin discussing this mechanical-balance hypothesis, we measured the effect of two selected peptides, Aβ-40 and Aβ-42, as well as their fluorescently labeled modification, on membrane mechanical properties. The decrease of bending rigidity, consistent for all investigated peptides, was observed using molecular dynamic studies and experimental flicker-noise techniques. Additionally, wave propagation was investigated with molecular dynamic studies in membranes with and without incorporated neurodegenerative peptides. A change in membrane behavior was observed in the membrane system with incorporated Aβ.
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Poulos, Gregory S., Junhong Wang, Dean K. Lauritsen, and Harold L. Cole. "Targeted Dropwindsondes in Complex Terrain." Journal of Atmospheric and Oceanic Technology 24, no. 8 (2007): 1489–94. http://dx.doi.org/10.1175/jtech2065.1.
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Abstract The dropwindsonde (or dropsonde) is a frequently utilized tool in geophysical research and its use over ocean and flat terrain is a reliable and well-established practice. Its use in complex terrain, however, is complicated by signal acquisition challenges that can be directly related to the ground target location, local relief, and line of sight to flight tracks relevant to the observation sought. This note describes a straightforward technique to calculate the theoretical altitude above ground to which a ground-targeted dropsonde will provide data for a given airborne platform. It is found that this height HCq can be calculated from expected airborne platform horizontal velocity Uag, mean dropwindsonde vertical velocity Ws, the relevant barrier maximum HB, and the horizontal distance from the target area to the barrier maximum DB. Here, HCq is found to be weakly dependent on release altitude through Ws. An example from the Terrain-induced Rotor Experiment (T-REX) is used to show that for modern aircraft platforms and dropwindsondes signal loss can occur 1–2 km above ground if mitigation is not pursued. Practical mitigation techniques are described for those complex terrain cases where signal propagation problems would create a significant negative scientific impact.
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Tian, Shiwei, Luwen Zhao, and Guangxia Li. "A Support Vector Data Description Approach to NLOS Identification in UWB Positioning." Mathematical Problems in Engineering 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/963418.
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Non-line-of-sight (NLOS) propagation is one of the most important challenges in radio positioning, and, in recent years, significant attention has been drawn to the identification and mitigation of NLOS signals. This paper focuses on the identification of NLOS signals. The authors consider the NLOS identification problem as a one-class classification problem and apply the support vector data description (SVDD), providing accurate data descriptions utilizing kernel techniques, to perform NLOS identification in ultrawide bandwidth (UWB) positioning. Our work is based on the fact that some features extracted from the received signal waveforms, such as the kurtosis, the mean excess delay spread, and the root mean square delay spread, are different between line-of-sight (LOS) and NLOS signals. Numerical simulations are performed to demonstrate the performance, using a dataset derived from a measurement campaign.
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Jong, Siat Ling, Michele D’Amico, Jafri Din, and Hong Yin Lam. "Analysis of Fade Dynamic at Ku-Band in Malaysia." International Journal of Antennas and Propagation 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/741678.
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This work investigates fade dynamics of satellite communication systems in equatorial heavy rain region based on a one year of Ku-band propagation measurement campaign carried out in Universiti Teknologi Malaysia (UTM), Johor, Malaysia. First order statistics of rain attenuation are deduced and the results are found to be in good agreement with those obtained from other beacon measurements gathered within the same area (Kuala Lumpur). Moreover, the fade duration and slope statistics of the satellite signal variations are also carefully derived and subsequently compared with the ITU-R recommendation model. Such information is useful for the system operator and radio communication engineer for the design of appropriate fade mitigation techniques as well as the quality of service that could be offered to the user (according to the time interval for a typical day). Further evaluation on the performances of several ITU-R models in the heavy rain region are needed based on the measurement database available of this climatic region.
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Ghadge, Abhijeet, Maximilian Weiß, Nigel D. Caldwell, and Richard Wilding. "Managing cyber risk in supply chains: a review and research agenda." Supply Chain Management: An International Journal 25, no. 2 (2019): 223–40. http://dx.doi.org/10.1108/scm-10-2018-0357.
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Purpose In spite of growing research interest in cyber security, inter-firm based cyber risk studies are rare. Therefore, this study aims to investigate cyber risk management in supply chain contexts. Design/methodology/approach Adapting a systematic literature review process, papers from interdisciplinary areas published between 1990 and 2017 were selected. Different typologies, developed for conducting descriptive and thematic analysis, were established using data mining techniques to conduct a comprehensive, replicable and transparent review. Findings The review identifies multiple future research directions for cyber security/resilience in supply chains. A conceptual model is developed, which indicates a strong link between information technology, organisational and supply chain security systems. The human/behavioural elements within cyber security risk are found to be critical; however, behavioural risks have attracted less attention because of a perceived bias towards technical (data, application and network) risks. There is a need for raising risk awareness, standardised policies, collaborative strategies and empirical models for creating supply chain cyber-resilience. Research limitations/implications Different types of cyber risks and their points of penetration, propagation levels, consequences and mitigation measures are identified. The conceptual model developed in this study drives an agenda for future research on supply chain cyber security/resilience. Practical implications A multi-perspective, systematic study provides a holistic guide for practitioners in understanding cyber-physical systems. The cyber risk challenges and the mitigation strategies identified support supply chain managers in making informed decisions. Originality/value To the best of the authors’ knowledge, this is the first systematic literature review on managing cyber risks in supply chains. The review defines supply chain cyber risk and develops a conceptual model for supply chain cyber security systems and an agenda for future studies.
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Greer, Ashton D., Zachary B. Wilbanks, Leah D. Clifton, Bradford Wilson, and Andrew J. Graettinger. "GIS-Enabled Culvert Design: A Case Study in Tuscaloosa, Alabama." Advances in Civil Engineering 2018 (September 19, 2018): 1–10. http://dx.doi.org/10.1155/2018/4648134.
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A GIS-enabled culvert design module is presented. This module employs Python programming to combine a proposed culvert location, topography, land use, and rainfall data to automatically design a culvert. The module is embedded within ESRI ArcGIS 10.4 software, providing a seamless single platform that eliminates error propagation associated with cross-platform data transfer as well as providing 95% time savings over traditional calculation methods. The module uses United States Geological Survey digital elevation data to analyze watershed topography. Runoff coefficients are determined from data available through the National Land Cover Database. Rainfall data are retrieved from the National Oceanic and Atmospheric Administration and combined with watershed and land use information to calculate peak discharge using the rational method. Peak discharge is then combined with culvert design parameters to design a single-barrel culvert. The module was used to redesign ten existing culverts along a highway in Tuscaloosa, Alabama, resulting in designs for updated land cover and rainfall conditions. Results from the techniques developed herein can be used for planning purposes and to highlight vulnerabilities in the existing infrastructure. The automation methods may be extended to other hydrologic objectives and runoff mitigation design such as open-channel design and detention or retention ponds.
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Janaki, Sathya D., and K. Geetha. "Enhanced CAE system for detection of exudates and diagnosis of diabetic retinopathy stages in fundus retinal images using soft computing techniques." Polish Journal of Medical Physics and Engineering 25, no. 2 (2019): 131–39. http://dx.doi.org/10.2478/pjmpe-2019-0018.
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Abstract Diabetic Retinopathy (DR) is one of the leading causes of visual impairment. Diabetic Retinopathy is the most recent technique of identifying the intensity of acid secretion in the eye for diabetic patients. The identification of DR is performed by visual analysis of retinal images for exudates (fat deposits) and the main patterns are traced by ophthalmologists. This paper proposes a fully automated Computer Assisted Evaluation (CAE) system which comprises of a set of algorithms for exudates detection and to classify the different stages of Diabetics Retinopathy, which are identified as either normal or mild or moderate or severe. Experimental validation is performed on a real fundus retinal image database. The segmentation of exudates is achieved using fuzzy C-means clustering and entropy filtering. An optimal set obtained from the statistical textural features (GLCM and GLHM) is extracted from the segmented exudates for classifying the different stages of Diabetics Retinopathy. The different stages of Diabetic Retinopathy are classified using three classifiers such as Back Propagation Neural Network (BPN), Probabilistic Neural Network (PNN) and Support Vector Machine (SVM). The experimental results show that the SVM classifiers outperformed other classifiers for the examined fundus retinal image dataset. The results obtained confirm that with new a set of texture features, the proposed methodology provides better performance when compared to the other methods available in the literature. These results suggest that our proposed method in this paper can be useful as a diagnostic aid system for Diabetic Retinopathy.
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Taylor, Isabelle A., Elisa Carboni, Lucy J. Ventress, Tamsin A. Mather, and Roy G. Grainger. "An adaptation of the CO<sub>2</sub> slicing technique for the Infrared Atmospheric Sounding Interferometer to obtain the height of tropospheric volcanic ash clouds." Atmospheric Measurement Techniques 12, no. 7 (2019): 3853–83. http://dx.doi.org/10.5194/amt-12-3853-2019.
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Abstract. Ash clouds are a geographically far-reaching hazard associated with volcanic eruptions. To minimise the risk that these pose to aircraft and to limit disruption to the aviation industry, it is important to closely monitor the emission and atmospheric dispersion of these plumes. The altitude of the plume is an important consideration and is an essential input into many models of ash cloud propagation. CO2 slicing is an established technique for obtaining the top height of aqueous clouds, and previous studies have demonstrated that there is potential for this method to be used for volcanic ash. In this study, the CO2 slicing technique has been adapted for volcanic ash and applied to spectra obtained from the Infrared Atmospheric Sounding Interferometer (IASI). Simulated ash spectra are first used to select the most appropriate channels and then demonstrate that the technique has merit for determining the altitude of the ash. These results indicate a strong match between the true heights and CO2 slicing output with a root mean square error (RMSE) of less than 800 m. Following this, the technique was applied to spectra obtained with IASI during the Eyjafjallajökull and Grímsvötn eruptions in 2010 and 2011 respectively, both of which emitted ash clouds into the troposphere, and which have been extensively studied with satellite imagery. The CO2 slicing results were compared against those from an optimal estimation scheme, also developed for IASI, and a satellite-borne lidar is used for validation. The CO2 slicing heights returned an RMSE value of 2.2 km when compared against the lidar. This is lower than the RMSE for the optimal estimation scheme (2.8 km). The CO2 slicing technique is a relatively fast tool and the results suggest that this method could be used to get a first approximation of the ash cloud height, potentially for use for hazard mitigation, or as an input for other retrieval techniques or models of ash cloud propagation.
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Panic, Stefan R., Dushantha Nalin K. Jayakody, Sofiene Affes, and Palanivelu Muthuchidambaranathan. "Hardware Impaired Self-Energized Bidirectional Sensor Networks over Complex Fading Channels." Sensors 20, no. 19 (2020): 5574. http://dx.doi.org/10.3390/s20195574.
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Rapid emergence of wireless sensor networks (WSN) faces significant challenges due to limited battery life capacity of composing sensor nodes. It is substantial to construct efficient techniques to prolong the battery life of the connected sensors in order to derive their full potential in the future Internet of Things (IoT) paradigm. For that purpose, different energy harvesting (EH) schemes are relying on a wide array of sources. Following the same objective, in this work, we have observed a time-switching EH for half-duplex (HD) bidirectional WSN, which performed in-between relaying over Hoyt fading channels. For its comprehensive performance analysis, rapidly converging infinite-series expressions have been provided with focus on the outage probability (OP) and achievable throughput of the hardware-impaired system. Additionally, asymptotic behavior of these performance measures has also been provided. Further, an approach to the symbol-error probability (SEP) analysis is also presented in the context of the observed system. Finally, we consider the shadowing influence along the WSN propagation path. Performance analysis of observed EH system operating over Rician-shadowed fading channels has been carried out, with deriving exact corresponding infinite-series expressions for outage probability (OP) and achievable throughput of the system under the hardware impairment conditions. In addition, bidirectional relaying in a mixed fading environment has been considered.
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Poedts, Stefaan, Andrea Lani, Camilla Scolini, et al. "EUropean Heliospheric FORecasting Information Asset 2.0." Journal of Space Weather and Space Climate 10 (2020): 57. http://dx.doi.org/10.1051/swsc/2020055.
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Aims: This paper presents a H2020 project aimed at developing an advanced space weather forecasting tool, combining the MagnetoHydroDynamic (MHD) solar wind and coronal mass ejection (CME) evolution modelling with solar energetic particle (SEP) transport and acceleration model(s). The EUHFORIA 2.0 project will address the geoeffectiveness of impacts and mitigation to avoid (part of the) damage, including that of extreme events, related to solar eruptions, solar wind streams, and SEPs, with particular emphasis on its application to forecast geomagnetically induced currents (GICs) and radiation on geospace. Methods: We will apply innovative methods and state-of-the-art numerical techniques to extend the recent heliospheric solar wind and CME propagation model EUHFORIA with two integrated key facilities that are crucial for improving its predictive power and reliability, namely (1) data-driven flux-rope CME models, and (2) physics-based, self-consistent SEP models for the acceleration and transport of particles along and across the magnetic field lines. This involves the novel coupling of advanced space weather models. In addition, after validating the upgraded EUHFORIA/SEP model, it will be coupled to existing models for GICs and atmospheric radiation transport models. This will result in a reliable prediction tool for radiation hazards from SEP events, affecting astronauts, passengers and crew in high-flying aircraft, and the impact of space weather events on power grid infrastructure, telecommunication, and navigation satellites. Finally, this innovative tool will be integrated into both the Virtual Space Weather Modeling Centre (VSWMC, ESA) and the space weather forecasting procedures at the ESA SSCC in Ukkel (Belgium), so that it will be available to the space weather community and effectively used for improved predictions and forecasts of the evolution of CME magnetic structures and their impact on Earth. Results: The results of the first six months of the EU H2020 project are presented here. These concern alternative coronal models, the application of adaptive mesh refinement techniques in the heliospheric part of EUHFORIA, alternative flux-rope CME models, evaluation of data-assimilation based on Karman filtering for the solar wind modelling, and a feasibility study of the integration of SEP models.
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Tomiczek, Tori, Brittany Webbmartin, Steven Scyphers, Kiera O’Donnell, and Kelsi Furman. "INTERCONNECTIVITIES BETWEEN HAZARD, DAMAGE, AND SHORELINE TYPE: LESSONS LEARNED FROM HURRICANE IRMA’S IMPACT ON THE FLORIDA KEYS." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 82. http://dx.doi.org/10.9753/icce.v36.risk.82.
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The 2017 Atlantic hurricane season had 17 named storms, 10 hurricanes, and 6 major hurricanes, generating over 226 units of accumulated cyclone energy (ACE), a measure used by the National Oceanographic and Atmospheric Association (NOAA) that refers to the combined the intensity and duration of a hurricane. These statistics earned the hurricane season’s classification as “extremely active,†the most active since 2005. Preliminary estimates of damage due to Hurricanes Harvey, Irma, and Maria amount to over $200 billion dollars in the United States alone. Recent studies suggest that the frequency of these high intensity Category 4 and 5 hurricanes is increasing (e.g. Mendelsohn et al., 2012). The 2017 hurricane season may thus be representative of an expected season. Accounting for projected increases in mean sea level, storm impacts may be exacerbated in coastal regions. These trends emphasize the need for effective damage mitigation techniques that improve the robustness and resiliency of coastal communities. Structures must be designed to not only avoid wave and surge loads, but also resist these forces in the event of a wave impact. Furthermore, creative, cost-effective solutions are required to mitigate waves and surge before they reach developed coastal areas. Thus, engineers require a robust, science-based methodology for predicting details of wave propagation over land and inland effects to ensure life safety and reduce economic loss due to extreme events. While traditional engineering strategies (e.g. seawalls, bulkheads) have been used to prevent coastal erosion and mitigate inland effects of hurricane waves and surge, recent storm events have shown potential of nature and natural based features (e.g. dune vegetation, mangroves, wetlands, salt-marshes, coral reefs, and seagrass) to protect coastal structures during storm events.
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Toshkhujaev, Saidjalol, Kun Ho Lee, Kyu Yeong Choi, et al. "Classification of Alzheimer’s Disease and Mild Cognitive Impairment Based on Cortical and Subcortical Features from MRI T1 Brain Images Utilizing Four Different Types of Datasets." Journal of Healthcare Engineering 2020 (September 1, 2020): 1–14. http://dx.doi.org/10.1155/2020/3743171.
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Alzheimer’s disease (AD) is one of the most common neurodegenerative illnesses (dementia) among the elderly. Recently, researchers have developed a new method for the instinctive analysis of AD based on machine learning and its subfield, deep learning. Recent state-of-the-art techniques consider multimodal diagnosis, which has been shown to achieve high accuracy compared to a unimodal prognosis. Furthermore, many studies have used structural magnetic resonance imaging (MRI) to measure brain volumes and the volume of subregions, as well as to search for diffuse changes in white/gray matter in the brain. In this study, T1-weighted structural MRI was used for the early classification of AD. MRI results in high-intensity visible features, making preprocessing and segmentation easy. To use this image modality, we acquired four types of datasets from each dataset’s server. In this work, we downloaded 326 subjects from the National Research Center for Dementia homepage, 123 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) homepage, 121 subjects from the Alzheimer’s Disease Repository Without Borders homepage, and 131 subjects from the National Alzheimer’s Coordinating Center homepage. In our experiment, we used the multiatlas label propagation with expectation–maximization-based refinement segmentation method. We segmented the images into 138 anatomical morphometry images (in which 40 features belonged to subcortical volumes and the remaining 98 features belonged to cortical thickness). The entire dataset was split into a 70 : 30 (training and testing) ratio before classifying the data. A principal component analysis was used for dimensionality reduction. Then, the support vector machine radial basis function classifier was used for classification between two groups—AD versus health control (HC) and early mild cognitive impairment (MCI) (EMCI) versus late MCI (LMCI). The proposed method performed very well for all four types of dataset. For instance, for the AD versus HC group, the classifier achieved an area under curve (AUC) of more than 89% for each dataset. For the EMCI versus LMCI group, the classifier achieved an AUC of more than 80% for every dataset. Moreover, we also calculated Cohen kappa and Jaccard index statistical values for all datasets to evaluate the classification reliability. Finally, we compared our results with those of recently published state-of-the-art methods.
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Delrieu, Guy, Anil Kumar Khanal, Nan Yu, Frédéric Cazenave, Brice Boudevillain, and Nicolas Gaussiat. "Preliminary investigation of the relationship between differential phase shift and path-integrated attenuation at the X band frequency in an Alpine environment." Atmospheric Measurement Techniques 13, no. 7 (2020): 3731–49. http://dx.doi.org/10.5194/amt-13-3731-2020.
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Abstract. The RadAlp experiment aims at developing advanced methods for rainfall and snowfall estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed since 2016 in the Grenoble region of France. It is composed of an X-band radar operated by Météo-France on top of the Moucherotte mountain (1901 m above sea level; hereinafter MOUC radar). In the Grenoble valley (220 m above sea level; hereinafter a.s.l.), we operate a research X-band radar called XPORT and in situ sensors (weather station, rain gauge and disdrometer). In this paper we present a methodology for studying the relationship between the differential phase shift due to propagation in precipitation (Φdp) and path-integrated attenuation (PIA) at X band. This relationship is critical for quantitative precipitation estimation (QPE) based on polarimetry due to severe attenuation effects in rain at the considered frequency. Furthermore, this relationship is still poorly documented in the melting layer (ML) due to the complexity of the hydrometeors' distributions in terms of size, shape and density. The available observation system offers promising features to improve this understanding and to subsequently better process the radar observations in the ML. We use the mountain reference technique (MRT) for direct PIA estimations associated with the decrease in returns from mountain targets during precipitation events. The polarimetric PIA estimations are based on the regularization of the profiles of the total differential phase shift (Ψdp) from which the profiles of the specific differential phase shift on propagation (Kdp) are derived. This is followed by the application of relationships between the specific attenuation (k) and the specific differential phase shift. Such k–Kdp relationships are estimated for rain by using drop size distribution (DSD) measurements available at ground level. Two sets of precipitation events are considered in this preliminary study, namely (i) nine convective cases with high rain rates which allow us to study the ϕdp–PIA relationship in rain, and (ii) a stratiform case with moderate rain rates, for which the melting layer (ML) rose up from about 1000 up to 2500 m a.s.l., where we were able to perform a horizontal scanning of the ML with the MOUC radar and a detailed analysis of the ϕdp–PIA relationship in the various layers of the ML. A common methodology was developed for the two configurations with some specific parameterizations. The various sources of error affecting the two PIA estimators are discussed, namely the stability of the dry weather mountain reference targets, radome attenuation, noise of the total differential phase shift profiles, contamination due to the differential phase shift on backscatter and relevance of the k–Kdp relationship derived from DSD measurements, etc. In the end, the rain case study indicates that the relationship between MRT-derived PIAs and polarimetry-derived PIAs presents an overall coherence but quite a considerable dispersion (explained variance of 0.77). Interestingly, the nonlinear k–Kdp relationship derived from independent DSD measurements yields almost unbiased PIA estimates. For the stratiform case, clear signatures of the MRT-derived PIAs, the corresponding ϕdp value and their ratio are evidenced within the ML. In particular, the averaged PIA∕ϕdp ratio, a proxy for the slope of a linear k–Kdp relationship in the ML, peaks at the level of the copolar correlation coefficient (ρhv) peak, just below the reflectivity peak, with a value of about 0.42 dB per degree. Its value in rain below the ML is 0.33 dB per degree, which is in rather good agreement with the slope of the linear k–Kdp relationship derived from DSD measurements at ground level. The PIA∕ϕdp ratio remains quite high in the upper part of the ML, between 0.32 and 0.38 dB per degree, before tending towards 0 above the ML.
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Yeh, Harry, and Shinji Sato. "Special Issue on Uncertainties in Tsunami Effects." Journal of Disaster Research 11, no. 4 (2016): 613–14. http://dx.doi.org/10.20965/jdr.2016.p0613.
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The 2011 Heisei tsunami far exceeded the level previously anticipated, resulting in devastating impacts in Japan. This event made it clear that preparation for tsunami hazards, based on past historical data alone, is inadequate. It is because tsunami hazards are characterized by a lack of historical data – due to the fact tsunamis are rare, high impact phenomena. Hence, it is important to populate a dataset with more data by including events that might have occurred outside the recorded historical timeframe, such as those inferred from geologic evidence. The dataset can also be expanded with “imaginary” experiments performed numerically using proper models. Unlike historical data that directly represent actual tsunami events as fact, geologic evidence (for example, sediment deposits) remains a conjecture for tsunami occurrences, and tsunami runup conditions evaluated using geologic data are uncertain. Theoretical approaches require making hypotheses, assumptions, and approximations. Numerical simulations require not only the accurate initial and boundary conditions but also adequate modeling techniques and computational capacity. Therefore, it is crucial to quantify the uncertainties involved in geologic, theoretical, and modeling approaches. Approximately 30 years ago, research on paleo-tsunamis based on geologic evidence was initiated and has been significantly advanced in the intervening years. During the same period, substantial advances in computational modeling used to predict tsunami propagation and runup processes were made. Understanding tsunami behavior, characteristics, and physics have resulted primarily from the well-organized international effort of field surveys initiated by the 1992 Nicaragua Tsunami event. Such rapidly advancing knowledge and technologies were unfortunately not sufficiently implemented in practice in a timely manner. Had this been the case, the disaster of the 2011 event would have been reduced, possibly avoiding the infamous nuclear meltdown at the Fukushima Dai-ichi Nuclear Power Plant. Having learned lessons from the 2011 Heisei Tsunami, Japan is now attempting to develop a robust tsunami-mitigation strategy that consists of two-tier criteria: Level 1 Tsunami for structure-based tsunami protection and Level 2 Tsunami for evacuation-based disaster reduction. Tsunami intensities of Levels 1 and 2 are determined by experts’ analysis and judgments. In the United States, a probabilistic tsunami hazard analysis is now widely adopted: for example, the latest ASCE-7 inundation maps are based on the hazard level of a 2,500-year return period. But again, due to the lack of data, the probabilistic analysis must rely mainly on imaginary experiments and experts’ judgments. The topic of this special issue focuses on the theme of uncertainty involved in tsunami hazard prediction. We review and examine uncertainties associated with tsunami simulations, near-shore effects, flow velocities, tsunami effects on buildings, coastal infrastructure, and sediment transport and deposits. Substantial uncertainty regarding tsunami hazards is likely the result of tsunami generation processes. This component, however, is not discussed here because it is closely related to the topic of probabilistic ‘seismic’ hazard analysis. This special issue is a compilation of seven papers addressing the current status of predictabilities, and will hopefully stimulate continual research that will lead to further improvements. Presenting numerically simulated examples, the paper by Lynett shows that the accurate prediction of tsunami-induced currents are much more difficult to achieve than the prediction of inundation depths. A small difference in an input parameter in the numerical model results in a very large difference in currents, especially the currents associated with the eddy formations. Keon, Yeh, Pancake and Steinberg demonstrate that significant temporal and spatial variations in tsunami effects are exhibited in the GIS-based IT tool called the Data Explorer. The Data Explorer provides the means to explore and extract pre-computed numerical time-series data at any grid point specified by the user. The concept is simple, but it has the unique ability to retrieve the data extremely quickly from massive datasets. This capability allows us to directly analyze the time-series data and to perform comprehensive sensitivity analysis. In order to generate realistic tsunami waveforms in the laboratory, Hiraishi describes a novel laboratory apparatus equipped with a hybrid wavemaker system capable of producing a combination of currents, a large heave of water, and waves. With the use of this apparatus, the tsunami waveform observed off Japan’s Kamaishi coast is modeled in the laboratory tank. To attempt to numerically simulate the local effects, Arikawa and Tominta present their hybrid numerical model, combining a depth-averaged 2D model and a fully 3D hydrodynamic model with the use of a multi-grid numerical scheme. This approach is crucial because tsunamis are multi-scale phenomena. A typical tsunami wavelength in deep water is on the order of several tens to hundreds of kilometers. When a tsunami approaches the shore, it may break, so refinement of the grid size is necessary, and three-dimensional flows become important when evaluating the local effects. Jaffe, Goto, Sugawara, Gelfenbaum, and LaSelle provide a comprehensive review of the models used to estimate tsunami sediment/boulder transport and deposits, thereby inferring the tsunami runup conditions (inundation depths and flow speeds) based on the tsunami deposits. They suggest that techniques for uncertainty quantification are crucial to advance the science of tsunami sediment transport modeling. Yeh and Sato analyze the failure mechanisms of buildings and coastal protective structures observed following the 2011 tsunami. Revealing the mechanisms, some engineering considerations to achieve resiliency are proposed to cope with the so-called “beyond-the-design-basis” tsunami hazards, in which its uncertainty is uncertain. Manawasekara, Mizutani, and Aoki investigate the effects of buildings’ openings and orientations on tsunami loading by performing laboratory experiments. This paper is complementary with the one by Yeh and Sato in demonstrating that the detailed changes in structure design could make a significant difference in tsunami loading on the buildings. We express our sincere appreciation to the authors for their contributions, and to the reviewers for their time-consuming efforts. We hope you find the papers in this special issue interesting and useful.
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Pinzón Ardila, Omar. "Modelado de un Recuperador Dinámico de Tensión para el Mejoramiento de la Calidad de la Onda de Tensión." BISTUA REVISTA DE LA FACULTAD DE CIENCIAS BASICAS 14, no. 1 (2016): 62. http://dx.doi.org/10.24054/01204211.v1.n1.2016.1938.
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Kumar, Anil, and Karamjit Kaur. "Impact of System Parameters of Optical Fiber Link on Four Wave Mixing." Recent Advances in Computer Science and Communications 13 (December 27, 2019). http://dx.doi.org/10.2174/2666255813666191227143529.
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Background: The invention of WDM technology in optical communication system has completely revolutionized the telecomm industry through its high data carrying capacity and efficiency of transmission. Advanced optical modulation formats with high spectral efficiency, advanced components like Reconfigurable Optical Add Drop Multiplexers (ROADMS), OXC, and large bandwidth requirements contributed significantly in existence of dynamic, flexible translucent and transparent networks. In these networks, it is common practice to increase the power levels as much as possible to overcome the power penalty effects and better transmission, but this introduces several non-linear impairments in the link and hence degrades the quality of signal flowing. These impairments arise when several high strength optical fields of different wavelengths interact with molecular vibrations and acoustic waves. The different non-linear impacts include Self Phase Modulation (SPM), Cross Phase Modulation (XPM), Four Wave Mixing (FWM) and scattering effects like Stimulated Raman Scattering (SRS), Stimulated Brillouin Scattering (SBS. The main cause of these impairments is variation in refractive index of fiber (also called Kerr effect) due to intensity of signal flowing through fiber. Due to the degradation impact posed by these impairments, it is crucial to analyze their cause, their influence on system performance and mitigation techniques so as to improve the overall quality of transmission. The monitoring of impairments is quite a challenging task due to their dependency on time, present state of network, signals flowing in adjoining channels and fibers. Objective: The present work aims to identify and describe the role of FWM in optical networks. The mathematical model of FWM is studied to know the parameters influencing the overall impact on system performance. The power of optical source, channel spacing, distance of transmission and presence of dispersion are considered as key factors influencing FWM power being developed. Their impact on FWM power and hence, FWM efficiency is calculated. In addition, the influence of FWM on Quality of transmission is quantified in terms of BER and Q-factor. Method: The analysis is done through a two-channel transmitter system with varied power, channel spacing, distance of transmission and presence of other degradation factors (dispersion) is taken into account. The corresponding optical spectrums are analysed. Result & Conclusion: In this paper, the non-linear impairment FWM posing degradation effect on the signal quality has been discussed. The basics involved are presented along with the mathematical model. It has been found that FWM results in power transfer from one channel to generation of new waves which may lead to power depletion and interference. The new waves generated depend on the number of wavelengths travelling in the fiber and channel spacing. The influence of FWM on system performance is presented in terms of BER and Q-value. It has been concluded that the increased power of transmission and decreased channel spacing are the crucial factors increasing the magnitude of FWM and need to be closely monitored. On the other hand, increased distance of propagation and presence of certain level of dispersion leads to decrease in FWM power. Therefore, if selected carefully, they may act as source of FWM mitigation without requiring any external compensating device
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Y. K. Tulunay and P. A. Bradley. "The impact of space weather on communication." Annals of Geophysics 47, no. 2-3 Sup. (2009). http://dx.doi.org/10.4401/ag-3279.
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As a preliminary to the studies conducted by the individual Working Groups, a review has been undertaken of topics which are relevant to the space-weather phenomena that can occur. The ways in general that these can influence the state of the ionosphere are discussed. The various changes in propagation parameters that arise on Earth-space and terrestrial radio paths via the ionosphere are listed. International procedures for frequency allocation and assignment are explained and the extent to which these are influenced by propagation factors is addressed. The role of mitigation techniques to improve radio-system performance is also identified.
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Jain, Vishal, and Richa Bhatia. "Review on nonlinearity effect in radio over fiber system and its mitigation." Journal of Optical Communications, June 4, 2021. http://dx.doi.org/10.1515/joc-2021-0044.
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Abstract Modern communication generation for high data rate requirement is fifth generation. The fifth generation has many advantages like low delay, high spectrum availability, high reliability, low jitter, and more capacity. To combat with the high capacity and high data rate requirement, optical fiber helps in the backhaul of 5G network. When fiber is used as a mode of propagation, many nonlinearities arises. This nonlinearity effect in the optical fiber communication is one of the most undesirable phenomena for the modern communication system which results in harmonic distortion, intermodulation distortion, phase distortion, and adjacent channel interference, etc. In most fiber optic communication systems, the major fiber nonlinear effect is the Kerr nonlinearity and Scattering effect that produced due to the variation of refractive index due to signal intensity. To minimize the effect of nonlinear distortion, some techniques are used which considerably improve the transmission capacity by reducing or compensating the effect of nonlinear distortion along with minimal infrastructure modifications and minimum cost for implementation. To overcome the effect of nonlinearity, fiber nonlinearity mitigation techniques are preferred to achieve the significant performance gains. Mitigation techniques can be implemented to improve and optimize the performance of optical communication network. In this paper, a brief description of the fiber nonlinearity effect and a review of various fiber nonlinearity compensation techniques are described.
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"GPS: User Position Calculation Including Advanced Troposphere Delay Modeling." International Journal of Engineering and Advanced Technology 8, no. 6S3 (2019): 1781–87. http://dx.doi.org/10.35940/ijeat.f1339.0986s319.
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Objective of this project is to analyze and mitigate troposphere delays induced in GPS signals, which can result in very large position errors while estimating user position. The standard models currently present do not take into account all the various set of parameters or elements of the troposphere that can cause a significant delay. This project also includes study of troposphere propagation delays that improve the understanding of GPS signal propagation through the troposphere during irregular conditions. This characteristic is very important as it can play crucial role in real time surveying, navigation, precision farming and positioning for emergency services. Due to the tropical nature of the Indian climate the troposphere delay can be observed significantly in India sub-continent. In order to accurately estimate delay troposphere in real time conditions is taken into account, which are provided by the Indian meteorological department, by their automatic weather surveillance systems. GPS data for stations in India is obtained from CORS data for Bangalore, from where we obtain the observation and navigation files used in the calculations. Obtained data is processed and run through various algorithms like least squares satellite position calculation, error mitigation and ray tracing algorithms to mitigate troposphere and better estimate user position. Apart from these algorithms this project also includes a study on various concepts/formulas that help in using the forecasted real time data to be used in snell’s law to estimate delay as part of ray tracing techniques. All the code development in this project is done using MATLAB by math works and GUI is developed for an easier interface. For analysis purposes the data is analyzed with and without the advanced mitigation techniques to show the improvement in position estimation using advanced troposphere mitigation techniques.
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Jain, Shweta, Christian Barona, and Nicholas Madamopoulos. "Modelling Wireless Propagation for Indoor Localization." Journal of Cyber Security and Mobility, January 22, 2016. http://dx.doi.org/10.13052/2245-1439.443.
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This paper presents a ray-tracing technique to model the multi-path fading effect in indoor spaces. Random set P of points on all surfaces inside a given hypothetical indoor space are chosen. Each pi ∈ P is considered to be a point from which the transmitted signal reflects just before reaching the receiver. The received signal is the vector sum of various reflections that arrive at the receiver. The received signal strength (RSS) is then computed from the signal envelope. This technique provides RSS statistics that are similar to the models of signal propagation developed after extensive measurements in multi-path environments. In addition, this technique captures the spatial correlation of signal impairment. For example, path loss computed with this technique shows that co-moving receivers experience correlated signal fades while those moving in different spaces see un-correlated fading. The technique presented here is a low cost, first principle approach to simulate channel impairments due to multi-path effect and interference. It benefits any wireless simulation study that needs the signal-space mapping and context such as indoor localization. This randomized ray-tracing technique does not compete with or replace other, more accurate ray-tracing techniques that use either brute force or geometric optics to obtain site-specific signal-to-space mapping.
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Song, Huihui, Xuewei Zhang, Jinjie Wu, and Yanbin Qu. "Low-frequency oscillations in coupled phase oscillators with inertia." Scientific Reports 9, no. 1 (2019). http://dx.doi.org/10.1038/s41598-019-53953-1.
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AbstractThis work considers a second-order Kuramoto oscillator network periodically driven at one node to model low-frequency forced oscillations in power grids. The phase fluctuation magnitude at each node and the disturbance propagation in the network are numerically analyzed. The coupling strengths in this work are sufficiently large to ensure the stability of equilibria in the unforced system. It is found that the phase fluctuation is primarily determined by the network structural properties and forcing parameters, not the parameters specific to individual nodes such as power and damping. A new “resonance” phenomenon is observed in which the phase fluctuation magnitudes peak at certain critical coupling strength in the forced system. In the cases of long chain and ring-shaped networks, the Kuramoto model yields an important but somehow counter-intuitive result that the fluctuation magnitude distribution does not necessarily follow a simple attenuating trend along the propagation path and the fluctuation at nodes far from the disturbance source could be stronger than that at the source. These findings are relevant to low-frequency forced oscillations in power grids and will help advance the understanding of their dynamics and mechanisms and improve the detection and mitigation techniques.
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Trang, Ngo Thi Thu, Nguyen Duc Nhan, and Bui Trung Hieu. "Optical Back-Propagation for Nonlinear Compensation in OFDM-Based Long Range-Passive Optical Networks." VNU Journal of Science: Mathematics - Physics 36, no. 1 (2020). http://dx.doi.org/10.25073/2588-1124/vnumap.4455.
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In direct-detection optical OFDM system, the nonlinear impairment is the key factor that limits the system performance. The back-propagation techniques in digital and optical domains have been proposed to compensate the nonlinear effects, however they can be unsuitable for long-range passive optical networks (LR-PONs) due to their implementation at receiver. In this study, we propose an optical back propagation (OBP) approach for compensation of the nonlinear and dispersion distortions in direct-detection optical OFDM system. The proposed OBP using split-step Fourier method is implemented at transmitter that is suitable for high-rate OFDM-based LR-PONs applications. In this OBP, the fiber Bragg grating (FBG) is used as a step for dispersion compensation and the high-nonlinear fiber (HNLF) with a short length is used as a step for nonlinear compensation. The performance improvement based on our proposed approach has been demonstrated via Monte-Carlo simulations of the 100 Gbit/s direct-detection optical OFDM system with 80 km of standard single mode fiber link. The influence of optical conjugation process and launching conditions has been investigated. The obtained results show that the proposed OBP can improve remarkably the performance of system with the launched power range from -2 dBm to 6 dBm.
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Bhusal, Rajnish, and Kamesh Subbarao. "Uncertainty Quantification Using Generalized Polynomial Chaos Expansion for Nonlinear Dynamical Systems With Mixed State and Parameter Uncertainties." Journal of Computational and Nonlinear Dynamics 14, no. 2 (2019). http://dx.doi.org/10.1115/1.4041473.
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This paper develops a framework for propagation of uncertainties, governed by different probability distribution functions in a stochastic dynamical system. More specifically, it deals with nonlinear dynamical systems, wherein both the initial state and parametric uncertainty have been taken into consideration and their effects studied in the model response. A sampling-based nonintrusive approach using pseudospectral stochastic collocation is employed to obtain the coefficients required for the generalized polynomial chaos (gPC) expansion in this framework. The samples are generated based on the distribution of the uncertainties, which are basically the cubature nodes to solve expectation integrals. A mixture of one-dimensional Gaussian quadrature techniques in a sparse grid framework is used to produce the required samples to obtain the integrals. The familiar problem of degeneracy with high-order gPC expansions is illustrated and insights into mitigation of such behavior are presented. To illustrate the efficacy of the proposed approach, numerical examples of dynamic systems with state and parametric uncertainties are considered which include the simple linear harmonic oscillator system and a two-degree-of-freedom nonlinear aeroelastic system.
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Pagare, Rajendraprasad A., Santosh Kumar, and Abhilasha Mishra. "Modeling and comparative analysis of all-class converged-coexistence NG-PON2 network for 5G-IoT-FTTX-services and application." Journal of Optical Communications, August 13, 2021. http://dx.doi.org/10.1515/joc-2021-0116.
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Abstract We presented a concept of converged coexistence (CC) access network and generate, and test model is demonstrated for optimization of channel launch power PTODN in the distribution network which subsequently confirm power budget class of NG-PON2 in this paper. Multiplexing of wavelength and time (TWDM) technology is incorporated for multichannel NG-PON2 configurations for 5G, internet-of-things (IoT) applications, and fiber-to-the-x (FTTX) services. CC NG-PON2 symmetric configuration supporting 2.5 and 10 Gbps channels are analyzed and compared in the sight of channel nonlinear impairments includes Kerr-effect (γ) spanning from self phase modulation (SPM) and cross-phase modulation (CPM), chromatic dispersion (CD), and four wave mixing (FWM) in worst-case scenario. Intensity modulation (IM) technique incorporated before multiplexing the D/S channels by coexisting element (CEx) and coupled to wavelength routed (WR) optical distribution network (ODN). U/S channels are routed using wavelength select (WS) ODN. ODN is implemented using G.652 non zero dispersion shift (NZ-DSF) single-mode (SM) fiber. Multi-channel spectrum envelope propagating in either direction is optimized to PTODN = 3/5/7/9 dBm and 4 dBm, respectively. The theoretical modeling and simulative results confirms the proposed network configuration supports incremental receiver sensitivity (Rxs) as −42.19/−42/−39.75/−37.97 dBm and −35.45/−35.38/−33.45/0.38/−42 dBm for λ1 2.5 Gbps and λ8 10 Gbps TWDM and PtP WDM channels, respectively, for all-class networks supporting splitter configuration ratio of 640 at 50 km mitigating effect of channel nonlinearities like CD, SPM, cross-phase modulation (XPM), and FWM for λ8 10 Gbps channel.
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DEMJÉN, E., V. ABOŠI, and Z. TOMORI. "Eye Tracking Using Artificial Neural Networks for Human Computer Interaction." Physiological Research, October 17, 2011, 841–44. http://dx.doi.org/10.33549/physiolres.932117.
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This paper describes an ongoing project that has the aim to develop a low cost application to replace a computer mouse for people with physical impairment. The application is based on an eye tracking algorithm and assumes that the camera and the head position are fixed. Color tracking and template matching methods are used for pupil detection. Calibration is provided by neural networks as well as by parametric interpolation methods. Neural networks use back-propagation for learning and bipolar sigmoid function is chosen as the activation function. The user’s eye is scanned with a simple web camera with backlight compensation which is attached to a head fixation device. Neural networks significantly outperform parametric interpolation techniques: 1) the calibration procedure is faster as they require less calibration marks and 2) cursor control is more precise. The system in its current stage of development is able to distinguish regions at least on the level of desktop icons. The main limitation of the proposed method is the lack of head-pose invariance and its relative sensitivity to illumination (especially to incidental pupil reflections).
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Kilgore, Brian, Julian Lozos, Nick Beeler, and David Oglesby. "Laboratory Observations of Fault Strength in Response to Changes in Normal Stress." Journal of Applied Mechanics 79, no. 3 (2012). http://dx.doi.org/10.1115/1.4005883.
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Changes in fault normal stress can either inhibit or promote rupture propagation, depending on the fault geometry and on how fault shear strength varies in response to the normal stress change. A better understanding of this dependence will lead to improved earthquake simulation techniques, and ultimately, improved earthquake hazard mitigation efforts. We present the results of new laboratory experiments investigating the effects of step changes in fault normal stress on the fault shear strength during sliding, using bare Westerly granite samples, with roughened sliding surfaces, in a double direct shear apparatus. Previous experimental studies examining the shear strength following a step change in the normal stress produce contradictory results: a set of double direct shear experiments indicates that the shear strength of a fault responds immediately, and then is followed by a prolonged slip-dependent response, while a set of shock loading experiments indicates that there is no immediate component, and the response is purely gradual and slip-dependent. In our new, high-resolution experiments, we observe that the acoustic transmissivity and dilatancy of simulated faults in our tests respond immediately to changes in the normal stress, consistent with the interpretations of previous investigations, and verify an immediate increase in the area of contact between the roughened sliding surfaces as normal stress increases. However, the shear strength of the fault does not immediately increase, indicating that the new area of contact between the rough fault surfaces does not appear preloaded with any shear resistance or strength. Additional slip is required for the fault to achieve a new shear strength appropriate for its new loading conditions, consistent with previous observations made during shock loading.
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Xie, Heping, Jianbo Zhu, Tao Zhou, Kai Zhang, and Changtai Zhou. "Conceptualization and preliminary study of engineering disturbed rock dynamics." Geomechanics and Geophysics for Geo-Energy and Geo-Resources 6, no. 2 (2020). http://dx.doi.org/10.1007/s40948-020-00157-x.
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Abstract Many large engineering projects, e.g., the Sichuan–Tibet Railway, inevitably cross the earthquake active areas and the geology complicated zones, facing the challenges of dynamic disturbances and disasters. In view of this, the conceptualization of engineering disturbed rock dynamics is proposed in this paper, aiming to systematically study the rock dynamic behavior and response subjected to engineering disturbances, to establish the 3D rock dynamic theory, and to develop the disaster prevention and control technical measures. The classification standards of rock loading states based on strain rate are summarized and analyzed. The engineering disturbed rock dynamics is defined as the theoretical and applied science of rock dynamic behaviors, dynamic responses and their superposition caused by dynamic disturbances during engineering construction and operation periods. To achieve the goals of the proposed engineering disturbed rock dynamics, a combined methodology of theoretical analysis, laboratory experiment, numerical simulation and in situ tests is put forward. The associated research scopes are introduced, i.e., experimental and theoretical study of engineering disturbed rock dynamics, wave propagation, attenuation and superposition in rock masses, rock dynamic response of different loading conditions, dynamic response of engineering projects under construction disturbance and disaster mitigation techniques, and dynamic response of major engineering projects under operation disturbance and safety guarantee measures. Some theoretical, experimental and field preliminary studies were performed, including dynamic behavior of disturbed rock at varied depth and strain rates, dynamic response of rock mass subjected to blasting excavation disturbance and dynamic drilling disturbance, and disturbance of rock mass subjected to TBM excavation. Preliminary results showed that the rock masses are significantly disturbed by dynamic disturbances during construction and operation periods of engineering projects. The innovative conceptualization of engineering disturbed rock dynamics and the expected associated outcomes could facilitate establishing the 3D rock dynamic theory and offering theoretical fundamentals and technical guarantees for safety and reliability of the design, construction and operation of modern large engineering.