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MERLIN : A French-German space lidar mission dedicated to atmospheric methane

The MEthane Remote sensing Lidar missioN (MERLIN) aims at demonstrating the spaceborne active measurement of atmospheric methane, a potent greenhouse gas, based on an Integrated Path Differential Absorption (IPDA) nadir-viewing LIght Detecting and Ranging (Lidar) instrument. MERLIN is a joint French and German space mission, with a launch currently scheduled for the timeframe 2021/22. The German S

Autonomic deployment decision making for big data analytics applications in the cloud

When changes happen to big data analytics (BDA) applications in the Cloud at runtime, the affected BDA applications have to be re-deployed to accommodate the changes. Deciding the most suitable deployment is critical and complicated. Although there have been various research studies working on BDA application management, autonomic deployment decision making is still an open research issue. This pa

Efficient Solvers for Minimal Problems by Syzygy-based Reduction

In this paper we study the problem of automatically generatingpolynomial solvers for minimal problems. The maincontribution is a new method for finding small eliminationtemplates by making use of the syzygies (i.e. the polynomialrelations) that exist between the original equations. Usingthese syzygies we can essentially parameterize the setof possible elimination templates.We evaluate our method o

Low-Rank Optimization with Convex Constraints

The problem of low-rank approximation with convex constraints, which appears in data analysis, system identification, model order reduction, low-order controller design and low-complexity modelling is considered. Given a matrix, the objective is to find a low-rank approximation that meets rank and convex constraints, while minimizing the distance to the matrix in the squared Frobenius norm. In man

Model Predictive Control for Real-Time Point-to-Point Trajectory Generation

The problem of planning a trajectory for robots starting in an initial state and reaching a final state in a desired interval of time is tackled. We propose an approach based on model predictive control to solve the problem of point-to-point trajectory generation for a given final time. We discuss various choices of models, objective functions, and constraints for generating trajectories to transf

MIMO Nyquist interpretation of the large gain theorem

The Large Gain Theorem is an input-output stability result with intriguing applications in the field of control systems. This paper aims to increase understanding and appreciation of the Large Gain Theorem by presenting an interpretation of it for linear time-invariant systems using the well-known Nyquist stability criterion and illustrative examples of its use. The Large Gain Theorem is complemen

Controlling Evolutionary Dynamics in Networks : A Case Study

Due to their wide adaptability to different application fields spanning from opinion dynamics to biology, the analysis of evolutionary dynamics is a compelling problem in the science of networks and systems. In this paper, we deal with controlled evolutionary dynamics in networks. We discuss a novel approach to model these phenomena, which enables us to estimate the duration of the process dependi

On Robust Distributed Control of Transportation Networks

With the ever-growing traffic demands, the transportation networks are getting more and more congested. While expanding these networks with more roads is both costly and in many cities not even feasible, the rapid development of new sensing and communication techniques has made it possible to perform control of transportation networks in real-time. With the right usage of such technologies, existi

Assignment and Control of Two-Tiered Vehicle Traffic

This work considers the assignment of vehicle traffic consisting of both individual, opportunistic vehicles and a cooperative fleet of vehicles. The first set of vehicles seek a user-optimal policy and the second set seeks a fleet-optimal policy. We provide explicit sufficient conditions for the existence and uniqueness of a Nash equilibrium at which both policies are satisfied.We also propose two

SparseJSR: A fast algorithm to compute joint spectral radius via sparse SOS decompositions

This paper focuses on the computation of the joint spectral radius (JSR), when the involved matrices are sparse. We provide a sparse variant of the procedure proposed by Parrilo and Jadbabaie to compute upper bounds of the JSR by means of sum-of-squares (SOS) programming. Our resulting iterative algorithm, called SparseJSR, is based on the term sparsity SOS (TSSOS) framework developed by Wang, Mag

Attack Resilient Cloud-based Industrial Control Systems

Industrial control systems (ICSs) are a significant part of industry and they play an important role in monitoring and controlling industrial processes. Traditionally, ICSs have been isolated from the Internet, and thereby secured from various Internet-based security threats. In recent years, since the cloud can provide huge advantages regarding storage and computing resources, industry has been m

Storage Allocation for Camera Sensor Networks using Feedback-based Price Discrimination

Camera sensor networks, mainly with surveillance cameras, are growing in size and complexity. Storage space is the prime resource in such systems but current surveillance setups are still very much centralized and limited in resources due to cost and security constraints. Allocating the correct amount of storage to each camera sensor considering their large difference in characteristics and video

Limitations of time-delayed case isolation in heterogeneous SIR models

The lack of methods to evaluate mechanical function of donated hearts in the context of transplantation imposes large precautionary margins, translating into a low utilization rate of donor organs. This has spawned research into cyber-physical models constituting artificial afterloads (arterial trees), that can serve to evaluate the contractile capacity of the donor heart. The Windkessel model is

Combating district heating bottlenecks using load control

The 4th generation of district heating systems face a potential problem where lowered water temperatures lead to higher flow rates, which requires higher hydraulic capacity in terms of pipe and pump sizes. This increases the effect of the already existing issue of hydraulic bottlenecks, causing peripheral units (customers) to experience reduced flow rates. A coordinating control strategy is presen

A 19.5 GHz 28 nm CMOS Class-C VCO with Reduced 1/f Noise Upconversion

Class-C operation is leveraged to implement a K-band CMOS VCO where the upconversion of the 1/f noise from the core transistors is robustly contained at a minimal level. Implemented in a bulk 28 nm CMOS technology,the VCO shows a phase noise as low as -108.5 dBc/Hz at 1 MHz offset (-83 dBc/Hz at 100 kHz offset) from the 19.5 GHz carrier,while consuming 14.4 mW and featuring a 12% tuning range.

An 11 GHz-Bandwidth Variable Gain Ka-Band Power Amplifier for 5G Applications

A Ka-band,32-43 GHz,differential power amplifier (PA) for millimeter wave applications is presented. The PA is a three stage design with a nominal gain of 36 dB. A device periphery ratio of 1:2:4 is adopted for pre-driver,driver and final stage,respectively. To enable use of 2.7 V supply,a cascode topology was employed in all three stages. The input is 80 ω differential and the output load is 50 ω

The differential-algebraic Windkessel model with power as input

The lack of methods to evaluate mechanical function of donated hearts in the context of transplantation imposes large precautionary margins, translating into a low utilization rate of donor organs. This has spawned research into cyber-physical models constituting artificial afterloads (arterial trees), that can serve to evaluate the contractile capacity of the donor heart.The Windkessel model is a

Improved Cloud Parameterization in Global Climate Model : Aerosol effects and secondary ice production mechanisms

The response of clouds to the changes in climate is uncertain, and the representation of the cloud-climate feedback is a key challenge in the global circulation models (GCM) for future climate projections. Factors contributing to this uncertainty include processes that involve particles of various sizes and phases, as well as the interactions between these particles and the surrounding atmosphere.