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Earthquake-induced landslides often pose a great threat to the safety of human life and property, especially in seismic active regions. This has motivated plentiful studies with a focus on coseismic landslides that collapsed during or shortly after an earthquake. However, long-term seismic effects that activated unstable landslides but without causing failures/collapse even after a long period since the earthquake (months to years) are typically ignored due to the minor ground changes caused compared to collapsed slopes. These landslides respond to seismic stress disturbances differently from failed coseismic/post-seismic landslides and their movements are typically accelerated with increased sliding velocity after earthquakes. The acceleration phenomenon of these earthquake accelerated landslides (EALs) could be maintained for a long time and they may generate continuous damage to the ground and develop into catastrophic failures in the future. As a new type of landslides associated with earthquakes, EALs have been largely neglected by the emerging research. In our study, we used satellite radar (Sentinel-1) observations from October 2014 to August 2020 to detect and investigate EALs in Central Italy. Distinguished from previous studies based on single or discrete landslides, we established a large EAL inventory and statistically quantified as a whole their spatial clustering features against a set of landslide conditioning factors. Results show that EALs did not rely on strong seismic shaking or hanging wall effects to occur and larger landslides were more likely to accelerate after earthquakes than smaller ones. We also discovered their accelerating-to-recovering sliding dynamics, and how they differed from the collapsed coseismic landslides. These investigations serve as an important supplement to the complete picture of the landslide inducing mechanism by earthquakes and contribute to a more comprehensive long-term assessment of landslide risk.

Landslides pose a destructive geohazard to people and infrastructure that results in hundreds of deaths and billions of dollars in damages every year. China is one of the countries worst affected by landslides in the world, and great efforts have been made to detect potential landslides over wide regions. However, a recent government work report shows that 80% of the newly formed landslides occurred outside the areas labelled as potential landslides, and 80% of them occurred in remote rural areas with limited capability of disaster prevention and mitigation. In this presentation, a multi‐source remote sensing technical framework is demonstrated to detect potential landslides over wide regions.

In recent years, an oil company has intensified its drilling activities in China Bohai Oilfield to meet challenging production targets and has almost doubled its drilled wells. Aiming to minimize environmental impacts of drilling activities on China Bohai Bay which is an internal bay with weak self-cleaning ability, this oil company has always been exploring continuous improvement to minimize the impact of its drilling and production operations on the environment. With the intention of recycling and reutilizing drilling and production waste including cuttings, wasted drilling and production fluids, many efforts are done. In design, well profile is downsized, cement top is restricted and reusable drilling fluids are developed to reduce waste from the root; In the field, environment protection ships (EPS) equipped with solid modified control system, cuttings closed transfer system and cuttings treatment system are used to recycle the produced the waste while drilling platform work as backup when weather is bad; Moreover, offshore waste management online system (OWMOS) has been developed covering the whole life cycle data chain of waste generation, collection, transportation, storage, disposal (utilization). Statistics from OWMOS show that the amount of the waste produced from downsized wells has been reduced by 41~65% compared to similar wells drilled before. Moreover, environmentally friendly drilling fluids with low solid content are developed and liquid phase after solid-liquid separation treatment can be reused. Consequently, the usage amount of drilling fluids has been decreased by 55~75%, while the solid content are packed and transported to onshore for disposal. These wastes can be turned into raw materials of cement stabilized soil and ceramic, which can also provide economy benefit and reduce impact on the environment. Waste recycling and reutilization technology has been successfully applied in more than 40 wells and lay the foundation for the digital transformation acceleration of waste management of offshore drilling and production waste, which can provide more practical reference for waste management of other similar offshore oilfield.

Earthquake triggered landslides often pose a great threat to human life and property. Emerging research has been devoted to documenting coseismic landslides failed during or shortly after earthquakes, however, the long-term seismic effect that causes unstable landslides only to accelerate, moderately or acutely, without immediate failures is largely neglected. Here we show the activation and recovery of these earthquake accelerated landslides (EALs) in Central Italy, based on satellite radar observations. Unlike previous studies based on single or discrete landslides, we established a large inventory of 819 EALs and statistically quantified their spatial clustering features against a set of conditioning factors, thus finding that EALs did not rely on strong seismic shaking or hanging wall effects to occur and larger landslides were more likely to accelerate after earthquakes than smaller ones. We also discovered their accelerating-to-recovering sliding dynamics, and how they differed from the collapsed 759 coseismic landslides. These findings contribute to a more comprehensive understanding of the earthquake-triggering landslide mechanism and are of great significance for long-term landslide risk assessment in seismically active areas.

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Methylparaben (MP) is an emerging pollutant, and the optimal conditions and kinetics of MP degradation using nano-zero-valent iron-activated persulfate (nZVI/PDS) need to be further investigated. This paper firstly investigated the response surface methodology (RSM) analysis of MP degradation by the heterogeneous system nZVI/PDS and concluded that the initial pH had the most significant effect on MP degradation. The optimal experimental conditions predicted by the RSM were as follows: initial pH 2.75, [nZVI]

SUMMARY The 2019 Mw 7.1 Ridgecrest earthquake opens an opportunity to investigate how soon we can produce a reliable fault geometry and subsequently a robust source model based on high-rate Global Positioning System (GPS) data. In this study, we conduct peak ground displacement (PGD) magnitude scaling, real-time centroid moment tensor (CMT) calculation and rapid kinematic slip inversion. We conclude that a four-station PGD warning with a magnitude of Mw 7.03 can be issued at 24 s after initiation of the rupture. Fast CMT inversion can initially recover the correct nodal planes at 30 s. The kinematic slip model reveals that the Mw 7.1 earthquake is a predominant dextral strike-slip event with both normal and thrust components resolved. The earthquake shows a bilateral rupture with a low propagation speed of ∼2.1 km s−1 and a slip maxima of ∼4 m. The total moment is 5.18 × 1019 N m (Mw 7.11). We further suggest that a reasonable source model will be available in a simulated real-time mode within 30 s after the earthquake occurring, without using full high-rate GPS waveforms. This research highlights the significance of high-rate GPS for rapid earthquake response and modelling of kinematic rupture, which is also generalized by the hypothetical real-time GPS analysis for the 2016 Mw 7.8 Kaikoura earthquake and the 2010 Mw 7.2 El Mayor-Cucapah earthquake.

A series of silylium cations [(R1R2R3Si)2H]+[B(C6F5)4]− (1–6) (1: R1 = R2 = R3 = Et; 2: R1 = R3 = H, R2 = Ph; 3: R1 = R3 = Me, R2 = Ph; 4: R1 = R2 = R3 = Ph; 5: R1 = R2 = R3 = iPr; 6: R1 = R2 = R3 = OEt) serve as highly efficient metal-free single-component cationic initiators for the cationic polymerization and copolymerization of chiral and achiral aryl isocyanides R–NC (a–k) (a: R = 2-C10H7 (NI); b: R = 4-(COOEt)–C6H4 (EPI); c: R = 3-[COOiPr]–C6H4 (IPI); d: R = 4-{COO-[(1S,2R,5S)-(2-iPr–5-Me–C6H6)]}–C6H4 (D-IMCI); e: R = 4-{COO-[(1R,2S,5R)-(2-iPr–5-Me–C6H6)]}–C6H4 (L-IMCI); f: R = 4-[4-(Ph)CC(Ph)2–C6H4]–C6H4 (ITPB); g: R = 4-{COO–(CH2)9–O–[4-(4-Ph–2-C9H5N)–C6H4]}–C6H4 (BNB); h: R = 4-{COO-[4-(4-Ph–2-C9H5N)–C6H4]}–C6H4 (PQPI); i: R = 4-(4-Ph–2-C9H5N)–C6H4 (IPQ); j: R = 4-{COO–(CH2)9–O–[4-(Ph)CC(4-N(C2H5)2–C6H4)2–C6H4]}–C6H4 (PPNI); k: R = 4-(NN–Ph)–C6H4 (IPD)). Nine homopoly(aryl isocyanide)s are prepared, in which optically active poly(d) and poly(e) exhibit obvious negative and positive Cotton effects at 364 nm and adopt one-handed helical conformations, the poly(f) containing tetraphenylethylene (TPE) substituent shows an aggregation-induced emission (AIE) nature, and the poly(g) containing 2,4-diphenylquinoline (DPQ) substituent serves as a new fluorescent probe for the detection of Fe3+ or Fe2+ ions. By fine-tuning the types of chiral and achiral aryl isocyanides, different degrees of chiral amplification of copolymer helicity can be achieved in the copolymerization of chiral aryl isocyanides d and e with achiral aryl isocyanides b, c, f, and k. Such chiral amplifications of the helical poly(e-co-b)s, poly(d/e-co-c)s, poly(d/e-co-f)s, and poly(d/e-co-k)s with the same helical sense as the corresponding poly(d) and poly(e) obey the “sergeants-and-soldiers” rule. Determination of reactivity ratios of these copolymerizations demonstrates that the different nonlinear relationship between the intensity of CD signals at 364 nm and the D/L-IMCI contents of these copolymers depends on the sequence distribution of chiral aryl isocyanide monomers in these copolymers. Based on the in situ1H NMR, FT-IR, and high resolution ESI-MS spectra, a possible cationic (co)polymerization mechanism is proposed.

On 21 May 2021 (UTC), an MW 7.4 earthquake jolted the east Bayan Har block in the Tibetan Plateau. The earthquake received widespread attention as it is the largest event in the Tibetan Plateau and its surroundings since the 2008 Wenchuan earthquake and in proximity to the seismic gaps on the east Kunlun fault. Here we use satellite interferometric synthetic aperture radar data and subpixel offset observations along the range directions to characterize the coseismic deformation of the earthquake. Rang offset displacements depict clear surface ruptures with a total length of ~170 km involving two possible activated fault segments in the earthquake. Coseismic modeling results indicate that the earthquake is dominated by left-lateral strike-slip motions of up to 7 m within top 12 km of the crust. The well-resolved slip variations are characterized by five major slip patches along strike and 64% of shallow slip deficit, suggesting a young seismogenic structure. Spatial-temporal changes of postseismic deformation are mapped from the early 6-day and 24-day InSAR observations, and are well explained by time-dependent afterslip models. Analysis of GPS velocity profiles and strain rates suggests that the eastward extrusion of plateau is diffusely distributed across the east Bayan Har block, but showing significant lateral heterogeneities as evidenced by magnetotelluric observations. The block-wide distributed deformation of the east Bayan Har block along with the significant co- and post-seismic stress loading from the Maduo earthquake imply high seismic risks on regional faults, especially the Tuosuo Lake and Maqin-Maqu segments of the Kunlun fault that known as seismic gaps.

Low‐rate (15 s) and high‐rate (1 s) Global Positioning System (GPS) solutions were employed to investigate the coseismic deformation associated with the 23 January 2018 Mw 7.9 Kodiak, Alaska, offshore earthquake. The coseismic displacements of kinematic (high‐rate observations) and quasi‐kinematic (2 hr of low‐rate observations after the earthquake) GPS solutions are consistent with those derived from static GPS daily solutions, and all three sets conform to the characteristics of a strike‐slip earthquake. A comparison between the static and quasi‐kinematic results suggests that postseismic deformation within the first four days was negligible. We inverted the static displacement field for the slip in a five‐segment model and inferred that the largest slip occurred on right‐lateral south‐southeast‐striking (2.27 m) and left‐lateral northeast‐striking (2.42 m) fault segments. The inverted geodetic moment is M09.66×1020 N⋅m (⁠Mw 7.92). The nine‐month postseismic horizontal displacements at 12 nearby GPS sites we studied are

Interferometric Synthetic Aperture Radar (InSAR) enables detailed investigation of surface landslide movements but lacks information about subsurface recognition/identification. It can be obtained by means of direct measurements (e.g., geotechnical data) and geophysical techniques. InSAR observations, seismic noise measurements, and geotechnical data were integrated to assess the deformation on the ground surface and to determine the depth of the failure surface of the Villa de Independencia landslide, Cochabamba (Bolivia) affecting the village. It is a compound slow-moving landslide (total area approximatively 3.8·106 m2) composed by three sub-blocks slide exhibiting diverse geometries, multiple failure surfaces, and magnitudes.For investigating the spatiotemporal characteristics of the landslide motion, Sentinel-1 time series from October 2014 to December 2019 were analysed. A new geometric inversion method was also proposed to determine the best-fit sliding direction and inclination of the landslide. Results of the Sentinel-1 time series show two substantial accelerations in early 2018 and 2019, coinciding with an increment of precipitations in the late rainy season. It allows supposing the rainy as the most likely triggers of the identified accelerations.The seismic noise measurements (more than one hundred spreaded over the whole landslide), analysed according to the Vertical to Horizontal Spectral Ratio technique (H/V), were calibrated and validated by means of the geotechnical data derived by three boreholes and 13 between rock and soil samples. H/V data allowed identifying the different dynamic characteristics of the three sub-blocks: movements are possibly due to the different properties of shallow and deep slip surfaces. The landslides caused damage on the edifices, probably mainly caused by the shallow slip interface (located at a mean depth of 5 m) since the foundation depth of the buildings is at most 2 m. In the town centre a deeper failure surfaces, approximatively with depth between 15 and 75 m, can be identified which may be responsible for its different direction and acceleration magnitude of sliding (inferred by InSAR) compared to the other parts of the landslides. Finally, the determination of the slip surface depths allowed to estimate the overall landslide volume assessed approximatively 9.18·107 m3.The study shows the great potential for landslide motion characterization and mechanism investigation by combing InSAR, seismic noise and geotechnical measurements.

Interferometric Synthetic Aperture Radar (InSAR) enables detailed investigation of surface landslide movements, but it cannot provide information about subsurface structures. In this work, InSAR measurements were integrated with seismic noise in situ measurements to analyse both the surface and subsurface characteristics of a complex slow-moving landslide exhibiting multiple failure surfaces. The landslide body involves a town of around 6000 inhabitants, Villa de la Independencia (Bolivia), where extensive damages to buildings have been observed. To investigate the spatial-temporal characteristics of the landslide motion, Sentinel-1 displacement time series from October 2014 to December 2019 were produced. A new geometric inversion method is proposed to determine the best-fit sliding direction and inclination of the landslide. Our results indicate that the landslide is featured by a compound movement where three different blocks slide. This is further evidenced by seismic noise measurements which identified that the different dynamic characteristics of the three sub-blocks were possibly due to the different properties of shallow and deep slip surfaces. Determination of the slip surface depths allows for estimating the overall landslide volume (9.18 · 107 m3). Furthermore, Sentinel-1 time series show that the landslide movements manifest substantial accelerations in early 2018 and 2019, coinciding with increased precipitations in the late rainy season which are identified as the most likely triggers of the observed accelerations. This study showcases the potential of integrating InSAR and seismic noise techniques to understand the landslide mechanism from ground to subsurface.

Rapid population growth combined with recent drought events and decades of political instability have left the residents of Kabul facing water scarcity, significantly relying on groundwater. Groundwater overexploitation might have induced various magnitudes of ground subsidence, however, to date, no comprehensive study of ground subsidence in Kabul has been conducted. In this study, we investigated the spatio-temporal evolution of ground deformation phenomena and its main governing processes in Kabul from 2014 to 2019 using C-Band Sentinel-1 derived Interferometric Synthetic Aperture Radar (InSAR) time-series from both ascending and descending orbits to extract the two-dimensional (2D) surface displacement field. Four subsidence bowls were distinguished with highly variable spatial extents and deformation magnitudes over four separate aquifer basins, with the maximum value of −5.3 cm/year observed in the Upper Kabul aquifer basin. A wavelet analysis suggests that there is a strong correlation between the groundwater level variations and subsidence. Investigation of hydrogeological data further reveals that the observed subsidence could be attributed to the presence of highly compressible clayey soils. This detailed space-borne regional survey provides new insights into the main governing mechanism of land subsidence in Kabul and may direct better mitigation plans of potential hazards.

In view of the disadvantages of the current intelligent substation optical fiber link measurement, such as low efficiency, unable to real-time monitoring and self diagnosis, this paper designs an intelligent diagnosis and monitoring system of optical fiber link in substation. The whole system consists of distributed intelligent diagnosis center and online monitoring system, which has the functions of optical port power measurement, online monitoring and status diagnosis. When the system is applied in practice, it can greatly improve the measurement efficiency, avoid the damage caused by repeatedly inserting and inserting optical fiber during the debugging process and the interference caused by human factors, and promote the transformation of the stubborn disease of optical fiber link fault from " post processing " to " advance prevention ". It has the characteristics of flexible distribution and connection, which can directly carry out the operation equipment and shutdown equipment, and truly achieve the online monitoring and diagnosis of the whole life cycle. The developed system has been tested in the laboratory, and the corresponding functions have been verified.

Satellite-based InSAR (Interferometric Synthetic Aperture Radar) provides an effective way to measure large-scale land surface motions. Currently, the atmospheric phase delay is one of the most critical issues in InSAR deformation monitoring. Generic Atmospheric Correction Online Service (GACOS) is a free, globally available and easy-to-implement tool to generate high-resolution zenith total delay maps, which could be used for InSAR atmospheric delay correction. The mean velocity could then be estimated by stacking multiple GACOS-corrected interferograms. We applied the proposed GACOS-corrected InSAR stacking method in the North China Plain and analysed its performance. Within the 549 interferograms, more than 85 % gained positive correction performances. The correlation between the phase-dZTD indicator and the performance reached 0.89, demonstrating a significant relationship. Deformation maps revealed by InSAR stacking with and without GACOS corrections showed that GACOS could mainly remove the topography-related and long wavelength signals.

Monitoring of slow landslide movement on a local scale with Interferometric Synthetic Aperture Radar (InSAR) observations can provide long-term deformation information and assist in identifying failure triggers. We combined three different tracks of satellite radar images spanning 12 years from ALOS-1 PALSAR-1, ALOS-2 PALSAR-2, and Sentinel-1 to assess the evolution of a landslide in Bolivia where the village of Independencia lies at the slope foot. For ALOS-1 PALSAR, SAR data was acquired on 15 dates during the period from 28 February 2007 to 11 March 2011 in ascending mode. For ALOS-2 PALSAR-2, eight acquisitions between 07 October 2015 and 29 November 2017 were available in ascending mode. The low temporal resolution of ALOS images makes the detection of deforming signal difficult though the L-band data captures more coherent pixels on vegetation areas than C-band. Sentinel-1 data with a minimum time interval of six days from 16 October 2014 to 08 September 2019 (144 images) is collected and processed to recover the dynamic behaviour of the landslide movement.To explore the sensitivity of different InSAR time series analysis methods on revealing the deformation pattern of the landslide, we respectively used Persistent Scatterer Interferometry (PSI), Small Baseline Subset (SBAS) algorithm and Distributed Scatterer Interferometry (DSI) based on phase eigenvalue-decomposition to process the mentioned multiple satellite radar observations. Overlapping valid pixels from these three methods share similar temporal evolution while SBAS and DSI trace more measurement points than PSI in spatial distribution. Preliminary results show that the village central exhibits extremely slow movements (

Although the Papuan fold and thrust belt (PFTB) is thought to accommodate convergence between the Pacific and Australian plates, the possible strain partitioning and its kinematic controls in the region are poorly understood. On 25 February 2018, a devastating Mw 7.5 earthquake jolted the southern area of the PFTB, central Papua New Guinea. The detailed imaging of the source parameters of this large earthquake is an urgent demand for a better understanding of the tectonism in the region. Here we used spaceborne interferometric synthetic aperture radar data to carefully determine the possible ruptured faults and associated fault geometries and further estimated the detailed slip of the 2018 Mw 7.5 earthquake. We find that the earthquake involved multiple faults failure, and a four‐segment fault model can reasonably produce the complex coseismic deformation, especially the observed bimodal displacements. The earthquake was dominated by reverse fault motion, and significant slip of up to ~0.7 m was documented on faults extending at depths great than 25 km. An integrated analysis of the fracture complexities suggests that possible strain partitioning in the PFTB could be tightly coupled with regional fault geometries and lithospheric properties. Our findings on the deep brittle failures suggest that crustal shortening across the PFTB could primarily control the growth of fold and thrust belt in the central Papua New Guinea.

We propose a fault prediction scheme using interpretable XGBoost based on actual datasets, which not only achieves high accuracy (99.72%) and low positive rate (0.18%), but also reveals the five most remarkable features that caused the fault.

An integrated navigation scheme based on multiple optical flow sensors and a strapdown inertial navigation system (SINS) are presented, instead of the global position system (GPS) aided. Multiple optical flow sensors are mounted on a micro air vehicle (MAV) at different positions with different viewing directions for detecting optical flow around the MAV. A fault-tolerant decentralized extended Kalman filter (EKF) is performed for estimating navigation errors by fusing the inertial and optical flow measurements, which can prevent the estimation divergence caused by the failure of the optical flow sensor. Then, the estimation of navigation error is inputted into the SINS settlement process for correcting the SINS measurements. The results verify that the navigation errors of SINS can be effectively reduced (even more than 9/10). Moreover, although the sensor is in a state of failure for 400 seconds, the fault-tolerant integrated navigation system can still work properly without divergence.

The 2019 Mw 7.5 New Ireland earthquake occurred at an equatorial area where the dense vegetation prevents remote sensing techniques such as C- or X-band interferometric synthetic aperture radar (SAR) from acquiring coherent phase measurements. Therefore, in this paper, multiple remote sensing techniques including the L-band interferometric SAR, the range and azimuth offset tracking of SAR intensities, and the offset tracking of optical images were employed to map its co-seismic deformation field and to determine the slip distribution. The surface rupture was clearly and consistently captured by all offset observations, with the ground fault trace striking at an angel of 315° and extending over 10 km. An iterative weighting strategy based on the residual root mean square of inversions using individual datasets was developed to determine the relative weight of each dataset, allowing for the joint inversion of the fault geometry, the refinement of the dip angle, and the determination of the best fitting slip distribution. The resultant model indicates a nearly left-lateral strike-slip motion on the Weitin fault that ruptured to the surface with a maximum slip of 6.10 m, occurring at a depth of ~10 km, and a geodetic moment release of 1.03 × 1020 Nm, corresponding to a magnitude of Mw 7.31. The distribution of aftershocks shows about 70% of aftershocks were located in the area with increased Coulomb failure stress and few aftershocks in the subduction zone to the south of the Weitin fault were triggered by this event.

As one of the most promising photocatalysts, graphitic carbon nitride (g-C3N4) shows a visible light response and great chemical stability. However, its relatively low photocatalytic efficiency is a major obstacle to actual applications. Here an effective and feasible method to dramatically increase the visible light photocatalytic efficiency by forming C3N4/BiFeO3 ferroelectric heterojunctions is reported, wherein the band alignment and piezo-/ferroelectricity have synergistic positive effects in accelerating the separation of the photogenerated carriers. At the optimum composition of 10 wt% BiFeO3, the heterojunction shows 1.4 times improved photocatalytic efficiency than that of the pure C3N4. Most importantly, mechanical pressing and electrical poling can also improve the photocatalytic efficiencies by 1.3 times and 1.8 times, respectively. The optimized photocatalytic efficiency is even comparable with that of some noble metal based compounds. These results not only prove the improved photocatalytic activity of the C3N4-ferroelectric heterojunctions, but also provide a new approach for designing high-performance photocatalysts by taking advantage of ferroelectricity.

This paper presents a hardware-in-the-loop (HIL) simulator, named HIL-GSS, which aims to help the students of aerospace engineering learn control and missile guidance theories effectively by using interactive instrumentation. Electromechanical components and interactive panels are illustrated. Two case-based studies are presented to show the advantages that HIL-GSS offers to engineering education. Steady-state tracking errors of the PID controller based on the HIL-GSS are around zero. The final miss distance in the real-time HIL TV guidance engagement simulation is 0.2376 m. Those results show the reliability of the proposed HIL simulator. In addition, the students' average response to survey questions is 4.22 (1–5 grade scale), which indicates that students strongly agree or agree that HIL-GSS is an effective educational tool.

The synthesis of ultrathin magnetic nanosheets is significant for the development of next-generation nanodevices but remains to be a big challenge. Herein, we present facile approaches for large-scaled production of cell-unit-thick single-crystalline iron oxide nanostructures. The ultrathin hematite (α-Fe 2 O 3 ) nanosheets with unit-cell thickness of 1.3 nm are firstly synthesized using a metal-ion-intervened hydrothermal method. Then the α-Fe 2 O 3 nanosheets are converted to magnetic maghemite ( γ -Fe 2 O 3 ) nanosheets with unit-cell thickness of 0.8 nm by a simple calcination process. The Li-ion battery studies reveal that unit-cell-thick γ-Fe 2 O 3 nanosheets exhibit great enhanced electrochemical performances with high specific capacitance approaching to its theoretical value and excellent cycling stability.

A bio-inspired detector based on the artificial neural network (ANN) and genetic algorithm is proposed in the context of a coherent optical transmission system. The ANN is designed to mitigate 16-quadrature amplitude modulation system impairments, including linear impairment: Gaussian white noise, laser phase noise, in-phase/quadrature component imbalance, and nonlinear impairment: nonlinear phase. Without prior information or heuristic assumptions, the ANN, functioning as a machine learning algorithm, can learn and capture the characteristics of impairments from observed data. Numerical simulations were performed, and dispersion-shifted, dispersion-managed, and dispersion-unmanaged fiber links were investigated. The launch power dynamic range and maximum transmission distance for the bio-inspired method were 2.7 dBm and 240 km greater, respectively, than those of the maximum likelihood estimation algorithm. Moreover, the linewidth tolerance of the bio-inspired technique was 170 kHz greater than that of the k-means method, demonstrating its usability for digital signal processing in coherent systems.

This paper develops a missile formation algorithm. The general form of time-varying formation constraints in three-dimensional space for missiles is deduced, and the formation control under time-varying position constraints is transformed into constrained optimization problem. Based on discretization of trajectory and optimization of control outputs, an approach to design optimal feedback control algorithm is presented. The three degree of freedom simulation results of the missiles obtained by constraint optimization show that the formation strategy proposed in this paper is feasible in missile formation control under complex time-varying constraint.

A big-data-driven dynamic clustering and load balancing scheme of virtual base stations for 5G fronthaul network is proposed. The comparison of load balancing factor shows that the optimization effect of the scheme is obvious.

A novel multiple migration seamless handover scheme for vehicular networks is proposed in fog-based optical fronthaul. Simulation results show that the throughput and delay performance are improved. Additionally, the QoS of delay-sensitive-services for vehicular networks can be guaranteed preferentially.

With the enhancement of the anti-jamming ability of the target, it is difficult to track and strike the target stably and accurately by single guidance. It is necessary to use a variety of detectors as sensors to provide a variety of observation data to track the target stably and achieve accurate strike. In this paper, we mainly research the distributed multi-sensor estimation problem. First, the target motion model and observation model are established. Secondly, the central differential Kalman filter (CDKF) transformation is applied to address the non-linear filtering problem without the need for computation of Jacobian matrix. Then, a FCI fusion algorithm for the multi-sensor target tracking problem is proposed. Compared to the traditional covariance intersection fusion method, FCI is more efficient in computation without the need for complex optimization process. Finally, simulations are designed and implemented and the joint CDKF-FCI fusion estimation algorithm is validated.

We propose an adaptive failure prediction scheme based on LSTM leveraging actual datasets from network operator, the experimental results verify that the average accuracy of failure prediction is 93.8%.

The lack of the sufficient and diverse training data is one of the main challenges limiting performances of the machine learning enabled applications in optical networks. Here, we propose a deep learning based sequential data augmentation technique for the aggregate traffic data augmentation for diverse optical network scenarios. A generative adversarial network (GAN) model is trained with the experimental traffic data to automatically extract the substantial characteristics of the experimental traffic data through the zero-sum game theory and then augment the traffic data adaptively. The statistical evaluation parameters of the augmented traffic are mean, variance and Hurst exponent. To add comparisons, two other classical generative models including the statistical parameter configuration (SPC) model and the variational autoencoder (VAE) model are also adopted to generate the traffic data that are similar to the actual traffic data. The comprehensive comparisons among the proposed GAN, the SPC and VAE show that the performances of the GAN exceed those of the SPC and the VAE obviously. The mean and the variance of the augmented traffic data from the GAN are almost equal to those of the experimental traffic data, where the average deviations are both within 2%. The Hurst exponent of the augmented traffic data from the GAN is respectively near 90% and 96% of those of the experimental traffic data in the access network and the core network. To estimate the similarity intuitively, the well-known k-mean algorithm is used to cluster the augmented traffic data according to the centroids determined by the corresponding experimental traffic data and the clustering accuracies are all higher than 95% for 6 kinds of typical traffic types in the optical networks. These results demonstrate that the proposed GAN is able to effectively generate the traffic data that is very close to the experimental traffic data and is difficult to be distinguished for diverse traffic types. Moreover, a relatively small dataset with a few hundred pieces of experimental traffic data is required and the amount of the augmented traffic data from the GAN is unlimited in theory, which can be augmented as much as we need. The proposed traffic data augmentation technique also has the potential to be utilized in other sequential data augmentation applications for the optical networks.

Nowadays, many people like to share the places they visited to their friends in the location-based social networks (LBSNs). Therefore, LBSNs have accumulated large-scale user check-in data and the availability of these data enables many location-based services to users. As a location-based service, point-of-interests (POI) recommendation can provide services to people and promote merchants. Many researchers utilize user-based collaborative filtering and geographical influence for POI recommendation. However, existing studies have two limitations: (1) when modeling user-based CF, users' POI preferences are not fully considered; (2) when modeling geographical influence, geographical features have not been explored deeply. In this paper, we propose a POI recommendation approach by improved user-based CF and geographical-regional influence. Firstly, we construct the user-POI matrix by normalized check-in frequencies, which can effectively represent user preferences. Secondly, we find that each user's check-in POIs can be divided into several regions. Accordingly, we integrate geographical influence with the regional feature to produce recommendation. Finally, we utilize a unified framework to combine improved user-based CF with geographical-regional influence for POI recommendation. Our experimental results on real-world dataset show that the proposed approach outperforms the state-of-the-art POI recommendation methods substantially.

We propose an adaptive traffic data augmentation technique based on generative adversarial networks trained with partial experimental data for optical networks and verify that the augmented traffic is similar to experimental traffic under diverse scenarios.

We present a load-aware-based dynamic traffic migration strategy for achieving low latency in hierarchical edge cloud-based 5G optical fronthaul network. The experimental results demonstrate the proposed strategies achieve a five-fold delay reduction and release 22.7% burden of fronthaul bandwidth.