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Microseismic monitoring of hydrofrac is an actively developing technology utilizing various acquizition arrays. In this paper we consider processing of microseismic data recorded by specific surface network geometry-patch arrays (far separated local receiver groups). The project aim is to produce an optimal partial stacking of the data within patches for improving a signal to noise ratio for micro
We present a novel approach to model the diffusion of a mutant in a geographical network. This is a key issue in the control of epidemics, since many diseases are transmitted by intermediate hosts that could be substituted with genetically modified organisms (GMOs) with a mutation that prevents them from spreading the pathogen. The main strength of our model lies in making analytically tractable t
Remote sensing is a key tool for precision agriculture applications as it is capable of capturing spatial and temporal variations in crop status. However, satellites often have an inadequate spatial resolution for precision agriculture applications. High-resolution Unmanned Aerial Vehicles (UAV) imagery can be obtained at flexible dates, but operational costs may limit the collection frequency. Th
Innovation and entrepreneurship are essential processes for human development, market growth, and technological breakthroughs, and it is vital for economic growth. Despite its importance, innovation is inherently difficult to measure and hence it is almost impossible for an individual or organization to know how they can improve their innovation output or claim that they are great at innovation. T
PalCom is a middleware toolkit for pervasive computing and internet-of-things. We discuss how PalCom supports exploration and live programming through three phases: exploring services, assembling them into applications, and exposing them as new services. We give an example of this workflow through the construction of a simple photo booth application.
We study a linear quadratic control problem for transportation optimization on a directed line graph. We show that the solution to the Riccati equation associated with this problem is highly structured. The feedback law is almost upper triangular, and the synthesis of the feedback law is given by a recursion, making it scalable. The structure of the feedback law also allows for an efficient realiz
Extreme winter events that damage vegetation are considered an important climatic cause of arctic browning - a reversal of the greening trend of the region - and possibly reduce the carbon uptake of northern ecosystems. Confirmation of a reduction in CO2 uptake due to winter damage, however, remains elusive due to a lack of flux measurements from affected ecosystems. In this study, we report eddy
Modern El Niño-Southern Oscillation (ENSO) events are characterized by their phase locking of variability to the seasonal cycle and tend to peak at the end of calendar year. Here, we show that in an idealized NCAR-CCSM3 simulation of the climate of the last 300,000 years, ENSO seasonal phase locking is shifted periodically following the precessional forcing: ENSO tends to peak in boreal winter whe
Cloud computing provides the illusion of infinite capacity to application developers. However, data center provisioning is complex and it is still necessary to handle the risk of capacity shortages. To handle capacity shortages, graceful degradation techniques sacrifice user experience for predictability. In all these cases, the decision making policy that determines the degradation interferes wit
The VIVE lighthouse system is evaluated for indoor positioning of micro unmanned aerialcvehicles (MUAVs). A detailed mathematical analysis is provided, including a Cramer-Raocbound derivation and performance analysis of the MUAV state estimate. The lighthousecmeasurements are fused with inertial measurements in a multiplicative extended Kalmanfilter (MEKF). We consider two implementations, one wit
Autonomous vehicle functions in safety-critical situations show promise in reducing the risk and saving lives in accidents compared to existing safety systems. Consequently, it is from many perspectives advantageous to be able to quantify the potential benefits of new autonomous systems for vehicle maneuvers at-the-limit of tire friction. Here, to estimate the potential in terms of saved lives and
The eutrophication problems in lakes on the Yangtze Plain of China have attracted global concern. However, a comprehensive assessment of the eutrophication status and its evolution is still lacking for these regional lakes, mostly because of technical difficulties and/or insufficient data to cover the large region. Our study attempts to fill this knowledge gap by using the entire archive of remote
The paper focuses on analysis of macro‐ and micromorphological characteristics of relict slope deposits in Serra da Estrela (Portugal) to understand the significance of different slope processes and paleoenvironmental settings. Micromorphology is a useful sedimentology technique allowing significant advances compared to macroscopic techniques. Results show that different processes are involved in
We present a method for solving the general mixed constrained convex quadratic programming problem using an active set method on the dual problem. The approach is similar to existing active set methods, but we present a new way of solving the linear systems arising in the algorithm. There are two main contributions; we present a new way of factorizing the linear systems, and show how iterative ref
Event-based sampling has been proposed as a general technique for lowering the average communication rate, energy consumption and computational burden in remote state estimation. However, the design of the event trigger is critical for good performance. In this paper, we study the combination of innovation-based triggering and state estimation of nonlinear dynamical systems using the particle filt
Internet-of-things systems are difficult to understand and debug due to their distributed nature and weak connectivity. We address this problem by using relational reference attribute grammars to model and analyze IoT systems with unreachable parts. A transitive device-dependency analysis is given as an example.
Efficient unit propagation for clausal constraints is a core building block of conflict-driven clause learning (CDCL) Boolean satisfiability (SAT) and lazy clause generation constraint programming (CP) solvers. Conflict-driven pseudo-Boolean (PB) solvers extend the CDCL paradigm from clausal constraints to integer linear constraints, also known as (linear) PB constraints. For PB solvers, many diff
Background and objective: New proposals to improve the regulation of hypnosis in anaesthesia based on the development of advanced control structures emerge continuously. However, a fair study to analyse the real benefits of these structures compared to simpler clinically validated PID-based solutions has not been presented so far. The main objective of this work is to analyse the performance limit
Deep learning has proven itself to be a powerful tool to develop datadriven signal processing algorithms for challenging engineering problems. By learning the key features and characteristics of the input signals instead of requiring a human to first identify and model them, learned algorithms can beat many human-made algorithms. In particular, deep neural networks are capable of learning the comp
