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In this paper we address the problem of resource allocation for alarm traffic in industrial Internet of Things networks using massive MIMO. We formulate the general problem of how to allocate pilot signals to alarm traffic such that delivery is guaranteed, while also minimising the number of pilots reserved for alarms, thus maximising the channel resources available for other traffic, such as indu
The problem of monotone smoothing splines with bounds is formulated as a constrained minimization problem of the calculus of variations. Existence and uniqueness of solutions of this problem is proved, as well as the equivalence of it to a finite dimensional but nonlinear optimization problem. A new algorithm for computing the solution which is a spline curve, using a branch and bound technique, i
Learning a computationally efficient kernel from data is an important machine learning problem. The majority of kernels in the literature do not leverage the geometry of the data, and those that do are computationally infeasible for contemporary datasets. Recent advances in approximation techniques have expanded the applicability of the kernel methodology to scale linearly with the data size. Data
Statement of Purpose: Chronic lung diseases are one of the major health problems that cause death and disability. Approximately 65 million people suffer from chronic lung diseases, and the number of patients is predicted to increase worldwide 1 . Lung transplantation is the only available treatment option for patients at end-stage disease. However, there is a chronic shortage of donor organs, re
Statement of Purpose: Many chronic pulmonary diseases, including idiopathic pulmonary fibrosis (IPF), pulmonary hypertension (PH) and chronic obstructive pulmonary disease (COPD), are complex and poorly understood. While great progress has been made to elucidate the cellular and molecular pathways underlying these diseases, treatment options remain limited. The dynamic alterations in mechanical pr
The problem of estimating receiver or sender node positions from measured receiver-sender distances is a key issue in different applications such as microphone array calibration, radio antenna array calibration, mapping and positioning using UWB or using round-trip-time measurements between mobile phones and WiFi-units. In this paper we address the problem of optimally estimating a receiver positi
In this paper we study the problem of estimating receiver and sender positions from time-difference-of-arrival measurements, assuming an unknown constant time-difference-of-arrival offset. This problem is relevant for example for repetitive sound events. In this paper it is shown that there are three minimal cases to the problem. One of these (the five receiver, five sender problem) is of particul
Software-Defined Networking (SDN) is a novel architectural model for cloud network infrastructure, improving resource utilization, scalability and administration. SDN deployments increasingly rely on virtual switches executing on commodity operating systems with large code bases, which are prime targets for adversaries attacking the network infrastructure. We describe and implement TruSDN, a frame
Purpose: Although basic objective measures (e.g., knee laxity, strength, and hop tests) have been related to subjective measures of function, associations between knee-specific objective and subjective measures have yet to be completed. The objective was to determine if knee joint contact and ligament forces differ between pre- and post-anterior cruciate ligament (ACL) reconstructed states and if
Precipitation in clouds can form by either warm-rain or ice crystal processes, referred to as warm and cold formation pathways, respectively. Here, we investigate the warm and cold pathway contributions to surface precipitation in simulated continental convective storms. We analyze three contrasting convective storms that are cold-based, slightly warm-based and very warm-based. We apply tracer-tag
In post-quantum cryptography (PQC), Learning With Errors (LWE) is one of the dominant underlying mathematical problems. For example, in NIST’s PQC standardization process, the Key Encapsulation Mechanism (KEM) protocol chosen for standardization was Kyber, an LWE-based scheme. Recently the dual attack surpassed the primal attack in terms of concrete complexity for solving the underlying LWE proble
In LWE-based KEMs, observed decryption errors leak information about the secret key in the form of equations or inequalities. Several practical fault attacks have already exploited such leakage by either directly applying a fault or enabling a chosen-ciphertext attack using a fault. When the leaked information is in the form of inequalities, the recovery of the secret key is not trivial. Recent me
We consider the statistical sparse jump model, a recently developed, robust and interpretable regime switching model, to identify features that drive the return dynamics of the largest cryptocurrencies. The approach simultaneously performs feature selection, parameter estimation, and state classification. Our large number of candidate features comprises cryptocurrency, sentiment, and financial mar
The reassigned spectrogram is a powerful tool for analysing non-stationary signals, and in an ideal setting it gives perfect time and frequency localisation. A method very well suited for oscillating transient signals is the matched window reassignment, which requires a matching window, i.e. the envelope of the transient, to be known or estimated beforehand. This paper proposes a novel method for
In this paper we propose a novel technique to estimate the parameters of two Gaussian envelope oscillatory signals, with the same time-locations and oscillatory frequencies but possibly different phases. The phase difference and the length of the Gaussian envelope are estimated directly from the slopes of the corresponding cross-spectrogram reassignment vectors. Including the phase difference and
Wireless sensor networks are susceptible to jamming attacks that can result in communication breakdowns. Preemptive measures to prevent jamming attacks is an active research field, but to stop an ongoing attack often requires that one is able to locate jammers in order to neutralize them. Several methods exist for the case when the network is corrupted by a single jammer, although these generally
This paper proposes an iterative algorithm to reconstruct missing samples from non-stationary signals. The proposed algorithm is based on the well-known amplitude-modulation frequency-modulation model for non-stationary signals. The method initially estimates the instantaneous frequencies of the observed multi-component signal. The estimated IFs are then used to de-chirp the corresponding componen
Kubernetes (K8s) is one of the best options available to deploy applications in large-scale infrastructures. Security has been a big concern for all practitioners in the K8s eco-system. Almost all cloud vendors have their security solution for K8s cluster, pods, workloads, etc. In recent years, a large number of open-source tools and projects related to K8s security have emerged to meet the increa
The generalized sparse iterative covariance-based estimation ( $q$ -SPICE) algorithm was recently introduced for scanning radar applications, resulting in substantial improvements in the angular resolution and quality of the processed images. Regrettably, the computational complexity and storage cost are high and quickly increase with growing data size, limiting the applicability of the estimator.
