Toward an Optimal Observational Array for Improving Two Flavors of El Niño Predictions in the Whole Pacific

This paper investigates the optimal observational array for improving the prediction of the El Niño-Southern Oscillation (ENSO) by exploring sensitive areas for target observations of two types of El Niño events in the whole Pacific. A target observation method based on the particle filter and pre-industrial control runs from six coupled model outputs in Coupled Model Intercomparison Project Phase 5 (CMIP5) experiments are used to quantify the relative importance of the initial accuracy of sea surface temperature (SST) in different Pacific areas. The initial accuracy of the tropical Pacific, subtropical Pacific, and extratropical Pacific can all exert influences on both types of El Niño predictions. The relative importance of different areas changes along with different lead times of predictions. Tropical Pacific observations are crucial in decreasing the root mean square error of predictions of all lead times. Subtropical and extratropical observations play an important role in decreasing the prediction uncertainty, especially when the prediction is made before and throughout boreal spring. To consider different El Niño types and different start months for predictions, a quantitative frequency method based on frequency distribution is applied to determine the optimal observations of ENSO predictions. The final optimal observational array contains 31 grid points, including 21 grid points in the equatorial Pacific and 10 grid points in the north Pacific, suggesting the importance of the initial SST conditions for ENSO predictions not only in the tropical Pacific but also in the area outside the tropics. Furthermore, the predictions made by assimilating SST in sensitive areas have better prediction skills in the verification experiment, which can indicate the validity of the optimal observational array designed in this study.

Realization of Super-Large-Diameter Slurry Shield Passing through Settlement-Sensitive Area Based on Unreinforced Disturbance Control Technology

Due to the complex construction conditions of shield tunnels, ground disturbance is inevitable during the construction process, which leads to surface settlement and, in serious cases, damage to surrounding buildings (structures). Therefore, it is especially important to effectively control the constructive settlement of subway tunnels when crossing settlement-sensitive areas such as high-density shantytowns. Based on the project of Wuhan Metro Line 8 Phase I, the shield of Huangpu Road Station-Xujiapang Road Station interval crossing high-density shantytowns, we study the disturbance control technology of oversized diameter mud and water shield crossing unreinforced settlement-sensitive areas during the construction process. By optimizing the excavation parameters and evaluating the ground buildings, the excavation process can be monitored at the same time, and the water pressure, speed, and tool torque required during the excavation during the construction process can be finely adjusted; the control of tunneling process parameters can provide reference and basis for analyzing the construction control of large-diameter shield through old shantytowns.

Simulation, Precursor Analysis and Targeted Observation Sensitive Area Identification for Two Types of ENSO using ENSO-MC v1.0

The global impact of an El Niño-Southern Oscillation (ENSO) event can differ greatly depending on whether it is an Eastern-Pacific-type (EP-type) event or a Central-Pacific-type (CP-type) event. Reliable predictions of the two types of ENSO are therefore of critical importance. Here we construct a deep neural network with multichannel structure for ENSO (named ENSO-MC) to simulate the spatial evolution of sea surface temperature (SST) anomalies for the two types of events. We select SST, heat content, and wind stress (i.e., three key ingredients of Bjerknes feedback) to represent coupled ocean-atmosphere dynamics that underpins ENSO, achieving skillful forecasts for the spatial patterns of SST anomalies out to one year ahead. Furthermore, it is of great significance to analyze the precursors of EP-type or CP-type events and identify targeted observation sensitive area for the understanding and prediction of ENSO. Precursors analysis is to determine what type of initial perturbations will develop into EP-type or CP-type events. Sensitive area identification is to determine the regions where initial states tend to have greatest impacts on evolution of ENSO. We use saliency map method to investigate the subsurface precursors and identify the sensitive areas of ENSO. The results show that there are pronounced signals in the equatorial subsurface before EP events, while the precursory signals of CP events are located in the North Pacific. It indicates that the subtropical precursors seem to favor the generation of the CP-type El Niño and the EP-type El Niño is more related to the tropical thermocline dynamics. And the saliency maps show that the sensitive areas of the surface and the subsurface are located in the equatorial central Pacific and the equatorial western Pacific, respectively. The sensitivity experiments imply that additional observations in the identified sensitive areas can improve forecasting skills. Our results of precursors and sensitive areas are consistent with the previous theories of ENSO, demonstrating the potential usage and advantages of the ENSO-MC model in improving the simulation, understanding and observations of two ENSO types.

Non-Global Privacy Protection Facing Sensitive Areas in Face Images

Face images, as an information carrier, are naturally weak in privacy. If they are collected and analyzed by malicious third parties, personal privacy will leak, and many other unmeasurable losses will occur. Differential privacy protection of face images is mainly being studied under non-interactive frameworks. However, the ε-effect impacts the entire image under these frameworks. Besides, the noise influence is uniform across the protected image, during the realization of the Laplace mechanism. The differential privacy of face images under interactive mechanisms can protect the privacy of different areas to different degrees, but the total error is still constrained by the image size. To solve the problem, this paper proposes a non-global privacy protection method for sensitive areas in face images, known as differential privacy of landmark positioning (DPLP). The proposed algorithm is realized as follows: Firstly, the active shape model (ASM) algorithm was adopted to position the area of each face landmark. If the landmark overlaps a subgraph of the original image, then the subgraph would be taken as a sensitive area. Then, the sensitive area was treated as the seed for regional growth, following the fusion similarity measurement mechanism (FSMM). In our method, the privacy budget is only allocated to the seed; whether any other insensitive area would be protected depends on whether the area exists in a growing region. In addition, when a subgraph meets the criterion for merging with multiple seeds, the most reasonable seed to be merged would be selected by the exponential mechanism. Experimental results show that the DPLP algorithm satisfies ε-differential privacy, its total error does not change with image size, and the noisy image remains highly available.

DEVELOPING VALIDATION OF FOREST FIRE RISK MAPS BASED ON HISTORICAL FIRE INCIDENCES

Large forest lands are damaged every year due to wild fires in Turkey. Prompt detection and rapid intervention is the key factors of firefighting activities. To be well prepared for the wildfires, it is crucial to determine the fire sensitive areas and then to locate fire extinguishing structures such as fire lookout towers and the firefighting headquarters by consideration these areas. The accuracy of the fire risk maps plays important role in the effectiveness of the fire management strategies and decisions. In this paper, the accuracy of a fire risk map, which was developed by GIS techniques integrated with Multi-Criteria Decision Analysis (MCDA), was evaluated based on the previous fire incidence in the study area. Analytic Hierarchy Process (AHP) method was used to generate fire risk map based on topographic features and forest vegetation structures. Then, total of 19 forest fires recorded in the study area in last 50 years were evaluated to validate the risk map. It was found that 23.81% of the area was subject to extreme risk, while 25.81% was of high risk. The results indicated that about 42.10% of the fire events fell into the forested areas with extreme fire risk, while 31,58% were in the high fire risk. Thus, the fire risk map developed by using the GIS-based MCDA can be an effective way for accurate estimation of the fire sensitive areas.

Spatio-temporal analysis of hydropower projects with terrestrial environmentally sensitive areas of Nepal

Hydropower project construction is increasing, which can affect the terrestrial environment. Hydropower projects located in environmentally sensitive areas have higher environmental impacts, so I analyzed the spatiotemporal interaction between hydropower project locations and terrestrial environmentally sensitive areas of Nepal to visualize the probable environmental impacts. Most of the existing projects lie on the hill; however, future projects are moving northward. Among the 12 eco-regions of Nepal, hydropower projects are located in 10 eco-regions. Hydropower projects were found to interact with more than half of the biodiverse areas of the country (28 out of 45), and more than five thousand megawatts of hydropower projects are located completely inside these biodiverse areas. The study suggests that the interaction between hydropower projects and environmentally sensitive areas might increase in the future. Hydropower projects should avoid environmentally sensitive areas such as biodiverse areas and protected areas as much as possible to minimize the impacts. Rapid hydropower development is a necessity in countries such as Nepal, so further studies on the effects of hydropower projects on environmentally sensitive areas as well as improvement of the quality of the environmental assessment of the projects are necessary for environmentally friendly development.

Proposal of Study on Performance Analysis of OSPFV3 and EIGRP Applications in IPV6

The internet protocols are increasingly imposed in recent times, there is a need to propose a study on the performance analysis on OSPFV3 and EIGRP in IPV6 application. IP is currently involved in sensitive areas of internet protocols, remote sensing, telepresence, computer networks and so on. The IP exists in two versions (IPv4 and IPv6), the difference between these two protocols is distinguished in terms of features, operation, and performance. In this study, measuring and evaluation on the performance of the two IPv4 and IPv6 protocols in the networks of communicating companies are proposed for further studies based on the literature gaps identified. The study should be performed by varying the routing protocols RIP, RIPnG, OSPF, OSPFv3, IS-IS and ISIS v6. Further studies should conduct simulation on performance analysis of OSPFV3 and EIGRP in IPV6 applications. The gaps identified after reviewing a number of literature on OSPFV3 and EIGRP with IPV6 network needs to be done since it sought to bridge gaps in literature.