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Signal apparition is a recent signal processing advance that has numerous applications in seismic data acquisition and processing. In this paper we review the basic principles of signal apparition and discuss applications related to simultaneous source acquisition. We discuss the generalization of the technique to large number of sources and the application in a full 3D configuration enabling larg
In this paper we develop a number of generic techniques and algorithms in spectral analysis of large linear approximations for use in cryptanalysis. We apply the developed tools for cryptanalysis of ZUC-256 and give a distinguishing attack with complexity around 2236 . Although the attack is only 220 times faster than exhaustive key search, the result indicates that ZUC-256 does not provide a sour
Iron can be a growth‐limiting nutrient for phytoplankton, modifying rates of net primary production, nitrogen fixation, and carbon export ‐ highlighting the importance of new iron inputs from the atmosphere. The bioavailable iron fraction depends on the emission source and the dissolution during transport. The impacts of anthropogenic combustion and land use change on emissions from industrial, do
In this paper, we propose a blind channel deconvolution method based on a sparse reconstruction framework exploiting a wideband dictionary under the (relatively weak) assumption that the transmitted signal may be assumed to be well modelled as a sum of sinusoids. Using a Toeplitz structured formulation of the received signal, we form an iterative blind deconvolution scheme, alternatively estimatin
One important open question in side-channel analysis is to find out whether all the leakage samples in an implementation can be exploited by an adversary, as suggested by masking security proofs. For attacks exploiting a divide-and-conquer strategy, the answer is negative: only the leakages corresponding to the first/last rounds of a block cipher can be exploited. Soft Analytical Side-Channel Atta
The central problem of this thesis is estimating receiver-sender node positions from measured receiver-sender distances or equivalent measurements. This problem arises in many applications such as microphone array calibration, radio antenna array calibration, mapping and positioning using ultra-wideband and mapping and positioning using round-trip-time measurements between mobile phones and Wi-Fi-
Global fire-vegetation models are widely used to assess impacts of environmental change on fire regimes and the carbon cycle and to infer relationships between climate, land use and fire. However, differences in model structure and parameterizations, in both the vegetation and fire components of these models, could influence overall model performance, and to date there has been limited evaluation
A growing number of connected IoT devices makesit more and more difficult for the network to provide the desiredreliability in any deployment scenario. The advent of NB-IoTtechnology opens new possibilities for low-power long-range IoTapplications. However, the design of the standard introduces highbattery drainage in the situations when the radio conditionsbetween the UE and the eNB are poor. Dev
Discontinuous Reception (DRX) has been included in 4G-LTE as the main power saving mechanism for User Equipment (UE). However, the existing 3-state DRX model is not sufficient for new use cases introduced by 4G and 5G. For example, the device discovery process in Device to Device (D2D) communication has a significant impact on delay and power consumption, but the existing conventional 3-state DRX
In this paper we study resilience of TDMA-based wireless sensor networks to node failures. We investigate exploiting mutlicast routing for providing redundancy in the number of gateways used by data streams, so as to protect them against gateway failures. To do this, we develop an optimization model aiming at packet traffic throughput maximization composed of three mixed-integer programming proble
Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. How
Low rank structures are present in many applications of computer vision and machine learning. A popular approach consists of explicitly parameterising the set or matrices with sought rank, leading to a bilinear factorisation, reducing the problem to find the bilinear factors. While such an approach can be efficiently implemented using second-order methods, such as Levenberg-Marquardt (LM) or Varia
We investigate the trade-off between energy usage and (packet) throughput in wireless mesh networks performing machine-to-machine communication. For this we provide a novel mixed-integer programming formulation to maximise the throughput while maintaining minimal energy usage, together with an effective price-and-branch solution algorithm based on column generation. The resulting optimisation mode
Open Source Security and Dependency Vulnerability Management (DVM) has become a more vital part of the software security stack in recent years as modern software tend to be more dependent on open source libraries. The largest open source of vulnerabilities is the National Vulnerability Database (NVD), which supplies developers with machine-readable vulnerabilities. However, sometimes Common Vulner
Estimating receiver and sender positions is often solved using a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. The second step can be seen as an affine upgrade. This affine upgrade is the focus of this paper. In the paper new efficient algorithms for solving for the upgrade parameters using minimal data are presented. It is als
We study a scenario where a monitor is interested in the freshest possible update from a remote sensor. The monitor also seeks to minimize the number of updates that exceed a certain freshness threshold, beyond which, the information is deemed to be too old. Previous work has presented results for First Come First Served (FCFS) systems. However, it has been shown that Last Come First Served (LCFS)
In this paper we address the energy consumption of the Constraint Application Protocol (CoAP) and the Message Queue Telemetry Transport (MQTT) protocol and compare their overhead. We also pay attention to the use case of security in IoT and analyze the energy consumption when using TLS/DTLS for the two protocols. In our experiments we use ESP32 with libcoap, MQTT, and mbed TLS libraries and conduc
In this thesis, we investigate and develop new methods for efficient and functional use of resources in edge networks. Setting this work aside from previous work, we study User Generated Content (UGC) such as social media information and data generated in the new emerging Internet of Things systems. We present efficient solutions for placing such content and managing which network resources should
Regression via classification (RvC) is a common method used for regression problems in deep learning, where the target variable belongs to a set of continuous values. By discretizing the target into a set of non-overlapping classes, it has been shown that training a classifier can improve neural network accuracy compared to using a standard regression approach. However, it is not clear how the set
This work considers direction-finding using a monostatic multiple-input multiple-output (MIMO) radar in the presence of impulsive noise. Employing a novel low-order covariance-based exponential kernel function, the proposed maximum likelihood (ML) formulation exploits an introduced quantum whale optimization algorithm (QWOA) to form the direction estimates. The resulting estimates are shown to be
