Development of an unsupervised remote sensing methodology of detect surface leakage from terrestrial CO2 storage sites

Imperial Users onl

Data-driven analytics task management reasoning mechanism in edge computing

Internet of Things (IoT) applications have led to exploding contextual data for predictive analytics and exploration tasks. Consequently, computationally data-driven tasks at the network edge, such as machine learning models’ training and inference, have become more prevalent. Such tasks require data and resources to be executed at the network edge, while transferring data to Cloud servers negatively affects expected response times and quality of service (QoS). In this paper, we study certain computational offloading techniques in autonomous computing nodes (ANs) at the edge. ANs are distinguished by limited resources that are subject to a variety of constraints that can be violated when executing analytical tasks. In this context, we contribute a task-management mechanism based on approximate fuzzy inference over the popularity of tasks and the percentage of overlapping between the data required by a data-driven task and data available at each AN. Data-driven tasks’ popularity and data availability are fed into a novel two-stages Fuzzy Logic (FL) inference system that determines the probability of either executing tasks locally, offloading them to peer ANs or offloading to Cloud. We showcase that our mechanism efficiently derives such probability per each task, which consequently leads to efficient uncertainty management and optimal actions compared to benchmark models

Remote sensing studies and morphotectonic investigations in an arid rift setting, Baja California, Mexico

The Gulf of California and its surrounding land areas provide a classic example of recently rifted continental lithosphere. The recent tectonic history of eastern Baja California has been dominated by oblique rifting that began at ~12 Ma. Thus, extensional tectonics, bedrock lithology, long-term climatic changes, and evolving surface processes have controlled the tectono-geomorphological evolution of the eastern part of the peninsula since that time. In this study, digital elevation data from the Shuttle Radar Topography Mission (SRTM) from Baja California were corrected and enhanced by replacing artifacts with real values that were derived using a series of geostatistical techniques. The next step was to generate accurate thematic geologic maps with high resolution (15-m) for the entire eastern coast of Baja California. The main approach that we used to clearly represent all the lithological units in the investigated area was objectoriented classification based on fuzzy logic theory. The area of study was divided into twenty-two blocks; each was classified independently on the basis of its own defined membership function. Overall accuracies were 89.6 %, indicating that this approach was highly recommended over the most conventional classification techniques. The third step of this study was to assess the factors that affected the geomorphologic development along the eastern side of Baja California, where thirty-four drainage basins were extracted from a 15-m-resolution absolute digital elevation model (DEM). Thirty morphometric parameters were extracted; these parameters were then reduced using principal component analysis (PCA). Cluster analysis classification defined four major groups of basins. We extracted stream length-gradient indices, which highlight the differential rock uplift that has occurred along fault escarpments bounding the basins. Also, steepness and concavity indices were extracted for bedrock channels within the thirty-four drainage basins. The results were highly correlated with stream length-gradient indices for each basin. Nine basins, exhibiting steepness index values greater than 0.07, indicated a strong tectonic signature and possible higher uplift rates in these basins. Further, our results indicated that drainage basins in the eastern rift province of Baja California could be classified according to the dominant geomorphologic controlling factors (i.e., faultcontrolled, lithology-controlled, or hybrid basins)

A Human-Centric Approach to Data Fusion in Post-Disaster Managment: The Development of a Fuzzy Set Theory Based Model

It is critical to provide an efficient and accurate information system in the post-disaster phase for individuals\u27 in order to access and obtain the necessary resources in a timely manner; but current map based post-disaster management systems provide all emergency resource lists without filtering them which usually leads to high levels of energy consumed in calculation. Also an effective post-disaster management system (PDMS) will result in distribution of all emergency resources such as, hospital, storage and transportation much more reasonably and be more beneficial to the individuals in the post disaster period. In this Dissertation, firstly, semi-supervised learning (SSL) based graph systems was constructed for PDMS. A Graph-based PDMS\u27 resource map was converted to a directed graph that presented by adjacent matrix and then the decision information will be conducted from the PDMS by two ways, one is clustering operation, and another is graph-based semi-supervised optimization process. In this study, PDMS was applied for emergency resource distribution in post-disaster (responses phase), a path optimization algorithm based ant colony optimization (ACO) was used for minimizing the cost in post-disaster, simulation results show the effectiveness of the proposed methodology. This analysis was done by comparing it with clustering based algorithms under improvement ACO of tour improvement algorithm (TIA) and Min-Max Ant System (MMAS) and the results also show that the SSL based graph will be more effective for calculating the optimization path in PDMS. This research improved the map by combining the disaster map with the initial GIS based map which located the target area considering the influence of disaster. First, all initial map and disaster map will be under Gaussian transformation while we acquired the histogram of all map pictures. And then all pictures will be under discrete wavelet transform (DWT), a Gaussian fusion algorithm was applied in the DWT pictures. Second, inverse DWT (iDWT) was applied to generate a new map for a post-disaster management system. Finally, simulation works were proposed and the results showed the effectiveness of the proposed method by comparing it to other fusion algorithms, such as mean-mean fusion and max-UD fusion through the evaluation indices including entropy, spatial frequency (SF) and image quality index (IQI). Fuzzy set model were proposed to improve the presentation capacity of nodes in this GIS based PDMS

Book of Abstracts

no abstrac

Remote sensing studies and morphotectonic investigations in an arid rift setting, Baja California, Mexico

The Gulf of California and its surrounding land areas provide a classic example of recently rifted continental lithosphere. The recent tectonic history of eastern Baja California has been dominated by oblique rifting that began at ~12 Ma. Thus, extensional tectonics, bedrock lithology, long-term climatic changes, and evolving surface processes have controlled the tectono-geomorphological evolution of the eastern part of the peninsula since that time. In this study, digital elevation data from the Shuttle Radar Topography Mission (SRTM) from Baja California were corrected and enhanced by replacing artifacts with real values that were derived using a series of geostatistical techniques. The next step was to generate accurate thematic geologic maps with high resolution (15-m) for the entire eastern coast of Baja California. The main approach that we used to clearly represent all the lithological units in the investigated area was objectoriented classification based on fuzzy logic theory. The area of study was divided into twenty-two blocks; each was classified independently on the basis of its own defined membership function. Overall accuracies were 89.6 %, indicating that this approach was highly recommended over the most conventional classification techniques. The third step of this study was to assess the factors that affected the geomorphologic development along the eastern side of Baja California, where thirty-four drainage basins were extracted from a 15-m-resolution absolute digital elevation model (DEM). Thirty morphometric parameters were extracted; these parameters were then reduced using principal component analysis (PCA). Cluster analysis classification defined four major groups of basins. We extracted stream length-gradient indices, which highlight the differential rock uplift that has occurred along fault escarpments bounding the basins. Also, steepness and concavity indices were extracted for bedrock channels within the thirty-four drainage basins. The results were highly correlated with stream length-gradient indices for each basin. Nine basins, exhibiting steepness index values greater than 0.07, indicated a strong tectonic signature and possible higher uplift rates in these basins. Further, our results indicated that drainage basins in the eastern rift province of Baja California could be classified according to the dominant geomorphologic controlling factors (i.e., faultcontrolled, lithology-controlled, or hybrid basins)

Air Quality Monitoring, Assessment and Management

Human beings need to breathe oxygen diluted in certain quantity of inert gas for living. In the atmosphere, there is a gas mixture of, mainly, oxygen and nitrogen, in appropriate proportions. However, the air also contains other gases, vapours and aerosols that humans incorporate when breathing and whose composition and concentration vary spatially. Some of these are physiologically inert. Air pollution has become a problem of major concern in the last few decades as it has caused negative effects on human health, nature and properties. This book presents the results of research studies carried out by international researchers in seventeen chapters which can be grouped into two main sections: a) air quality monitoring and b) air quality assessment and management, and serves as a source of material for all those involved in the field, whether as a student, scientific researcher, industrialist, consultant, or government agency with responsibility in this area

Routing, Localization And Positioning Protocols For Wireless Sensor And Actor Networks

Wireless sensor and actor networks (WSANs) are distributed systems of sensor nodes and actors that are interconnected over the wireless medium. Sensor nodes collect information about the physical world and transmit the data to actors by using one-hop or multi-hop communications. Actors collect information from the sensor nodes, process the information, take decisions and react to the events. This dissertation presents contributions to the methods of routing, localization and positioning in WSANs for practical applications. We first propose a routing protocol with service differentiation for WSANs with stationary nodes. In this setting, we also adapt a sports ranking algorithm to dynamically prioritize the events in the environment depending on the collected data. We extend this routing protocol for an application, in which sensor nodes float in a river to gather observations and actors are deployed at accessible points on the coastline. We develop a method with locally acting adaptive overlay network formation to organize the network with actor areas and to collect data by using locality-preserving communication. We also present a multi-hop localization approach for enriching the information collected from the river with the estimated locations of mobile sensor nodes without using positioning adapters. As an extension to this application, we model the movements of sensor nodes by a subsurface meandering current mobility model with random surface motion. Then we adapt the introduced routing and network organization methods to model a complete primate monitoring system. A novel spatial cut-off preferential attachment model and iii center of mass concept are developed according to the characteristics of the primate groups. We also present a role determination algorithm for primates, which uses the collection of spatial-temporal relationships. We apply a similar approach to human social networks to tackle the problem of automatic generation and organization of social networks by analyzing and assessing interaction data. The introduced routing and localization protocols in this dissertation are also extended with a novel three dimensional actor positioning strategy inspired by the molecular geometry. Extensive simulations are conducted in OPNET simulation tool for the performance evaluation of the proposed protocol

Global Monitoring for Security and Stability (GMOSS) - Integrated Scientific and Technological Research Supporting Security Aspects of the European Union

This report is a collection of scientific activities and achievements of members of the GMOSS Network of Excellence during the period March 2004 to November 2007. Exceeding the horizon of classical remote-sensing-focused projects, GMOSS is characterized by the integration of political and social aspects of security with the assessment of remote sensing capabilities and end-users support opportunities. The report layout reflects the work breakdown structure of GMOSS and is divided into four parts. Part I Concepts and Integration addresses the political background of European Security Policy and possibilities for Earth Observation technologies for a contribution. Besides it illustrates integration activities just as the GMOSS Gender Action Plan or a description of the GMOSS testcases. Part II of this book presents various Application activities conducted by the network partners. The contributions vary from pipeline sabotage analysis in Iraq to GIS studies about groundwater vulnerability in Gaza Strip, from Population Monitoring in Zimbabwe to Post-Conflict Urban Reconstruction Assessments and many more. Part III focuses on the research and development of image processing methods and Tools. The themes range from SAR interferometry for the measurement of Surface Displacement to Robust Satellite Techniques for monitoring natural hazards like volcanoes and earthquakes. Further subjects are the 3D detection of buildings in VHR imagery or texture analysis techniques on time series of satellite images with variable illumination and many other more. The report closes with Part IV. In the chapter ¿The Way Forward¿ a review on four years of integrated work is done. Challenges and achievements during this period are depicted. It ends with an outlook about a possible way forward for integrated European security research.JRC.G.2-Support to external securit