pwc-archive/papers-with-abstracts huggingface dataset:
Analysis of Molecular Communications on the Growth Structure of Glioblastoma Multiforme
Authors: Hamdan Awan, Andreani Odysseos, Niovi Nicolaou, Sasitharan Balasubramaniam
Date: 2021-04-30 00:00:00

In this paper we consider the influence of intercellular communication on the development and progression of Glioblastoma Multiforme (GBM), a grade IV malignant glioma which is defined by an interplay Grow i.e. self renewal and Go i.e. invasiveness potential of multiple malignant glioma stem cells. Firstly, we performed wet lab experiments with U87 malignant glioma cells to study the node-stem growth pattern of GBM. Next we develop a model accounting for the structural influence of multiple transmitter and receiver glioma stem cells resulting in the node-stem growth structure of GBM tumour. By using information theory we study different properties associated with this communication model to show that the growth of GBM in a particular direction (node to stem) is related to an increase in mutual information. We further show that information flow between glioblastoma cells for different levels of invasiveness vary at different points between node and stem. These findings are expected to contribute significantly in the design of future therapeutic mechanisms for GBM.
Cramér-Rao Bounds for Near-Field Localization
Authors: Andrea de Jesus Torres, Antonio Alberto D'Amico, Luca Sanguinetti, Moe Z. Win
Date: 2021-04-30 00:00:00

Multiple antenna arrays play a key role in wireless networks for communications but also localization and sensing. The use of large antenna arrays pushes towards a propagation regime in which the wavefront is no longer plane but spherical. This allows to infer the position and orientation of an arbitrary source from the received signal without the need of using multiple anchor nodes. To understand the fundamental limits of large antenna arrays for localization, this paper fusions wave propagation theory with estimation theory, and computes the Cram{\'e}r-Rao Bound (CRB) for the estimation of the three Cartesian coordinates of the source on the basis of the electromagnetic vector field, observed over a rectangular surface area. To simplify the analysis, we assume that the source is a dipole, whose center is located on the line perpendicular to the surface center, with an orientation a priori known. Numerical and asymptotic results are given to quantify the CRBs, and to gain insights into the effect of various system parameters on the ultimate estimation accuracy. It turns out that surfaces of practical size may guarantee a centimeter-level accuracy in the mmWave bands.
On the Computation of PSNR for a Set of Images or Video
Authors: Onur Keleş, M. Akin Yilmaz, A. Murat Tekalp, Cansu Korkmaz, Zafer Dogan
Date: 2021-04-30 00:00:00
Tasks: Video Restoration

When comparing learned image/video restoration and compression methods, it is common to report peak-signal to noise ratio (PSNR) results. However, there does not exist a generally agreed upon practice to compute PSNR for sets of images or video. Some authors report average of individual image/frame PSNR, which is equivalent to computing a single PSNR from the geometric mean of individual image/frame mean-square error (MSE). Others compute a single PSNR from the arithmetic mean of frame MSEs for each video. Furthermore, some compute the MSE/PSNR of Y-channel only, while others compute MSE/PSNR for RGB channels. This paper investigates different approaches to computing PSNR for sets of images, single video, and sets of video and the relation between them. We show the difference between computing the PSNR based on arithmetic vs. geometric mean of MSE depends on the distribution of MSE over the set of images or video, and that this distribution is task-dependent. In particular, these two methods yield larger differences in restoration problems, where the MSE is exponentially distributed and smaller differences in compression problems, where the MSE distribution is narrower. We hope this paper will motivate the community to clearly describe how they compute reported PSNR values to enable consistent comparison.
On the Efficient Implementation of an Implicit Discrete-Time Differentiator
Authors: José Eduardo Carvajal-Rubio, Juan Diego Sánchez-Torres, Michael Defoort, Mohamed Djemai, Alexander G. Loukianov
Date: 2021-05-01 00:00:00

New methodologies are designed to reduce the time complexity of an implicit discrete-time differentiator and the simulation time to implement it. They rely on Horner's method and the Shaw-Traub algorithm. The algorithms are compared for differentiators of orders 3, 7, and 10. The Half-Horner and Full-Horner methods showed the best performance and time complexity.
A note on a PDE approach to option pricing under xVA
Authors: Falko Baustian, Martin Fencl, Jan Pospíšil, Vladimír Švígler
Date: 2021-04-30 00:00:00

In this paper we study partial differential equations (PDEs) that can be used to model value adjustments. Different value adjustments denoted generally as xVA are nowadays added to the risk-free financial derivative values and the PDE approach allows their easy incorporation. The aim of this paper is to show how to solve the PDE analytically in the Black-Scholes setting to get new semi-closed formulas that we compare to the widely used Monte-Carlo simulations and to the numerical solutions of the PDE. Particular example of collateral taken as the values from the past will be of interest.
Fast Multiscale Diffusion on Graphs
Authors: Sibylle Marcotte, Amélie Barbe, Rémi Gribonval, Titouan Vayer, Marc Sebban, Pierre Borgnat, Paulo Gonçalves
Date: 2021-04-29 00:00:00

Diffusing a graph signal at multiple scales requires computing the action of the exponential of several multiples of the Laplacian matrix. We tighten a bound on the approximation error of truncated Chebyshev polynomial approximations of the exponential, hence significantly improving a priori estimates of the polynomial order for a prescribed error. We further exploit properties of these approximations to factorize the computation of the action of the diffusion operator over multiple scales, thus reducing drastically its computational cost.
A Review on Bio-Cyber Interfaces for Intrabody Molecular Communications Systems
Authors: Yevgeni Koucheryavy, Anastasia Yastrebova, Daniel P. Martins, Sasitharan Balasubramaniam
Date: 2021-04-30 00:00:00

The recent advancements in bio-engineering and wireless communications systems have motivated researchers to propose novel applications for telemedicine, therapeutics and human health monitoring. For instance, through wireless medical telemetry a healthcare worker can remotely measure biological signals and control certain processes in the organism required for the maintenance of the patient's health state. This technology can be further extended to use Bio-Nano devices to promote a real-time monitoring of the human health and storage of the gathered data in the cloud. This brings new challenges and opportunities for the development of biosensing network, which will depend on the extension of the current intrabody devices functionalities. In this paper we will cover the recent progress made on implantable micro-scale devices and introduce the perspective of improve them to foster the development of new theranostics based on data collected at the nanoscale level.
How Far Are We from Robust Voice Conversion: A Survey
Authors: Tzu-Hsien Huang, Jheng-Hao Lin, Chien-yu Huang, Hung-Yi Lee
Date: 2020-11-24 00:00:00
Tasks: Speaker Identification, Survey, Voice Conversion

Voice conversion technologies have been greatly improved in recent years with the help of deep learning, but their capabilities of producing natural sounding utterances in different conditions remain unclear. In this paper, we gave a thorough study of the robustness of known VC models. We also modified these models, such as the replacement of speaker embeddings, to further improve their performances. We found that the sampling rate and audio duration greatly influence voice conversion. All the VC models suffer from unseen data, but AdaIN-VC is relatively more robust. Also, the speaker embedding jointly trained is more suitable for voice conversion than those trained on speaker identification.
Multi-agent consensus with heterogeneous time-varying input and communication delays in digraphs
Authors: Wei Jiang, Kun Liu, Themistoklis Charalambous
Date: 2021-05-03 00:00:00

This paper investigates the distributed consensus tracking control problem for general linear multi-agent systems (MASs) with external disturbances and heterogeneous time-varying input and communication delays under a directed communication graph topology, containing a spanning tree. First, for all agents whose state matrix has no eigenvalues with positive real parts, a communication-delay-related observer, which is used to construct the controller, is designed for followers to estimate the leader's state information. Second, by means of the output regulation theory, the results are relaxed to the case that only the leader's state matrix eigenvalues have non-positive real parts and, under these relaxed conditions, the controller is redesigned. Both cases lead to a closed-loop error system of which the stability is guaranteed via a Lyapunov-Krasovskii functional with sufficient conditions in terms of input-delay-dependent linear matrix inequalities (LMIs). An extended LMI is proposed which, in conjunction with the rest of LMIs, results in a solution with a larger upper bound on delays than what would be feasible without it. It is highlighted that the integration of communication-delay-related observer and input-delay-related LMI to construct a fully distributed controller (which requires no global information) is scalable to arbitrarily large networks. The efficacy of the proposed scheme is demonstrated via illustrative numerical examples.
I-DREM MRAC with Time-Varying Adaptation Rate & No A Priori Knowledge of Control Input Matrix Sign to Relax PE Condition
Authors: Anton Glushchenko, Vladislav Petrov, Konstantin Lastochkin
Date: 2021-02-22 00:00:00

The known dynamic regressor extension and mixing method (DREM) is combined with the proposed filter of a new type, which uses the integration operation with forgetting, and the recursive least-squares method to develop the new I-DREM model reference adaptive control (MRAC) system. It does not require a priori knowledge of the sign or the elements values of the control input matrix of the plant. It also provides the exponential convergence of the adaptation process (with the automatically adjustable adaptation rate) without the regressor persistent excitation. Such control system allows to solve three actual problems of the adaptive control: 1) to provide the exponential convergence of the controller parameter error under the condition of the regressor initial excitation, 2) to make such convergence monotonic, 3) to calculate the adaptation rate online according to the current regressor value. Some numerical experiments are conducted to demonstrate the effectiveness of the proposed method.
Reachability of Black-Box Nonlinear Systems after Koopman Operator Linearization
Authors: Stanley Bak, Sergiy Bogomolov, Parasara Sridhar Duggirala, Adam R. Gerlach, Kostiantyn Potomkin
Date: 2021-05-03 00:00:00

Reachability analysis of nonlinear dynamical systems is a challenging and computationally expensive task. Computing the reachable states for linear systems, in contrast, can often be done efficiently in high dimensions. In this paper, we explore verification methods that leverage a connection between these two classes of systems based on the concept of the Koopman operator. The Koopman operator links the behaviors of a nonlinear system to a linear system embedded in a higher dimensional space, with an additional set of so-called observable variables. Although, the new dynamical system has linear differential equations, the set of initial states is defined with nonlinear constraints. For this reason, existing approaches for linear systems reachability cannot be used directly. In this paper, we propose the first reachability algorithm that deals with this unexplored type of reachability problem. Our evaluation examines several optimizations, and shows the proposed workflow is a promising avenue for verifying behaviors of nonlinear systems.
Robust Observer Based Methodology for Frequency and Rate of Change of Frequency Estimation in Power Systems
Authors: Abdul Saleem Mir, Abhinav Kumar Singh, Nilanjan Senroy
Date: 2021-05-03 00:00:00

An observer based adaptive detection methodology (ADM) is proposed for estimating frequency and its rate of change (RoCoF) of the voltage and/or current measurements acquired from an instrument transformer. With guaranteed convergence and stability, the proposed methodology effectively neutralizes the effect of the measurement distortions like harmonics, decaying DC components and outliers by adding its counter negative. It is robust to noise statistics, performs well while encountering step changes in amplitude/phase and is demonstrably superior to its precursors as established by test results. A benchmark IEEE NETS/NYPS 16 machine 68 bus power system has been used for performance evaluation of robust ADM against its precursors and scaled laboratory setup based on OP5600 multiprocessors was used for establishing its real-time applicability.
Performance analysis of frequency regulation services provided by aggregates of domestic thermostatically controlled loads
Authors: F. Conte, M. Crosa di Vergagni, S. Massucco, F. Silvestro, E. Ciapessoni, D. Cirio
Date: 2021-05-03 00:00:00

This paper proposes a control method for allowing aggregates of thermostatically controlled loads to provide synthetic inertia and primary frequency regulation services to the grid. The proposed control framework is fully distributed and basically consists in the modification of the thermostat logic as a function of the grid frequency. Three strategies are considered: in the first one, the load aggregate provides synthetic inertia by varying its active power demand proportionally to the frequency rate of change; in the second one, the load aggregate provides primary frequency regulation by varying its power demand proportionally to frequency; in the third one, the two services are combined. The performances of the proposed control solutions are analyzed in the forecasted scenario of the electric power system of Sardinia in 2030, characterized by a huge installation of wind and photovoltaic generation and no coil and combustible oil power plants. The considered load aggregate is composed by domestic refrigerators and water heaters. Results prove the effectiveness of the proposed approach and show that, in the particular case of refrigerators and water heaters, the contribution to the frequency regulation is more significant in the case of positive frequency variations. Finally, the correlation between the regulation performances and the level of penetration of the load aggregate with respect to the system total load is evaluated.
Autonomous parafoil precision landing using convex real-time optimized guidance and control
Authors: Antoine Leeman, Valentin Preda, Irene Huertas, Samir Bennani
Date: 2021-05-03 00:00:00

To overcome the limitations of current parafoil precision landing capabilities, an efficient real-time convex optimized guidance and control strategy is presented. Successive convexification of the parafoil guidance problem guarantees local optimality with polynomial convergence rate for efficient real-time implementation, where each iteration is dynamically feasible. Our approach shows reliable and fast numerical convergence through in-flight recalculation of time of flight and a new optimal trajectory to cope with time-varying dynamics. The efficiency of our strategy is demonstrated via a comparative analysis of the existing X-38 in-flight demonstrated guidance and control system. Exhaustive Monte-Carlo simulations show performance improvements of about one order of magnitude. The concept proposed is simple, yet general, as it scales to any atmospheric parafoil landing system and allows efficient implementation relying only on the turn rate information.
Robust Control for Lane Keeping System Using Linear Parameter Varying Approach with Scheduling Variables Reduction
Authors: Ying Shuai Quan, Jin Sung Kim, Chung Choo Chung
Date: 2021-05-03 00:00:00
Tasks: Scheduling

This paper presents a robust controller using a Linear Parameter Varying (LPV) model of the lane-keeping system with parameter reduction. Both varying vehicle speed and roll motion on a curved road influence the lateral vehicle model parameters, such as tire cornering stiffness. Thus, we use the LPV technique to take the parameter variations into account in vehicle dynamics. However, multiple varying parameters lead to a high number of scheduling variables and cause massive computational complexity. In this paper, to reduce the computational complexity, Principal Component Analysis (PCA)-based parameter reduction is performed to obtain a reduced model with a tighter convex set. We designed the LPV robust feedback controller using the reduced model solving a set of Linear Matrix Inequality (LMI). The effectiveness of the proposed system is validated with full vehicle dynamics from CarSim on an interchange road. From the simulation, we confirmed that the proposed method largely reduces the lateral offset error, compared with other controllers based on Linear Time-Invariant (LTI) system.
A guide to design disturbance observer based motion control systems
Authors: Emre Sariyildiz, Kouhei Ohnishi
Date: 2021-05-03 00:00:00

This paper proposes new practical design tools for the robust motion control systems based on disturbance observer (DOB). Although DOB has long been used in several motion control applications, it has insufficient analysis and design tools. The paper proposes a new practical robustness constraint, which improve the robustness at high frequencies, on the bandwidth of a DOB and nominal inertia. Although increasing the bandwidth of a DOB and nominal inertia improves the performance and stability, they are limited by the robustness constraint. Besides, a novel stability analysis method is proposed for reaction force observer (RFOB) based robust force control systems. It is shown that not only the performance, but also the stability changes significantly by the imperfect identification of inertia and torque coefficient. The robustness and stability of a DOB based motion control system are improved by proposing new design tools. The validity of the proposals are verified by experimental results.
Efficiency Assessment of a Residential DC Nanogrid with Low and High Distribution Voltages Using Realistic Data
Authors: Saeed Habibi, Ramin Rahimi, Pourya Shamsi, Mehdi Ferdowsi
Date: 2021-05-03 00:00:00

Direct Current (DC) power distribution has gained attention in the Residential Nanogrids (RNGs) due to the substantial increase in the number of roof-top Photovoltaic (PV) systems and internally DC appliances used in buildings. Using DC distribution improves the efficiency of the RNGs compared to AC distribution. This paper investigated the efficiency of a DC RNG for low and high distribution voltage levels by exploring reasons for power losses. The studied DC RNG consisted of various types of local loads, on-site PV generation, and battery storage systems. The realistic load, PV profiles, and converter efficiency curves were used to make the analysis more accurate. In addition, three load profiles with low, medium, and high power consumptions were considered to study the load impacts on the overall system efficiency.
Phase of Nonlinear Systems
Authors: Chao Chen, Di Zhao, Wei Chen, Sei Zhen Khong, Li Qiu
Date: 2020-11-30 00:00:00

In this paper, we propose a definition of phase for a class of stable nonlinear systems called semi-sectorial systems, from an input-output perspective. The definition involves the Hilbert transform as a critical instrument to complexify real-valued signals since the notion of phase arises most naturally in the complex domain. The proposed nonlinear system phase, serving as a counterpart of $\mathcal{L}_2$-gain, quantifies the passivity and is highly related to the dissipativity. It also possesses a nice physical interpretation which quantifies the tradeoff between the real energy and reactive energy. A nonlinear small phase theorem is then established for feedback stability analysis of semi-sectorial systems. Additionally, its generalized version is proposed via the use of multipliers. These nonlinear small phase theorems generalize a version of the classical passivity theorem and a recently appeared linear time-invariant small phase theorem.
Frequency-weighted H2-optimal model order reduction via oblique projection
Authors: Umair Zulfiqar, Victor Sreeram, Mian Ilyas Ahmad, Xin Du
Date: 2021-01-17 00:00:00
Tasks: Computational Efficiency

In projection-based model order reduction, a reduced-order approximation of the original full-order system is obtained by projecting it onto a reduced subspace that contains its dominant characteristics. The problem of frequency-weighted H2-optimal model order reduction is to construct a local optimum in terms of the H2-norm of the weighted error transfer function. In this paper, a projection-based model order reduction algorithm is proposed that constructs reduced-order models that nearly satisfy the first-order optimality conditions for the frequency-weighted H2-optimal model order reduction problem. It is shown that as the order of the reduced model is increased, the deviation in the satisfaction of the optimality conditions reduces further. Numerical methods are also discussed that improve the computational efficiency of the proposed algorithm. Three numerical examples are presented to demonstrate the efficacy of the proposed algorithm.
Load Oscillating Attacks of Smart Grids: Demand Strategies and Vulnerability Analysis
Authors: Falah Alanazi, Jinsub Kim, Eduardo Cotilla-Sanchez
Date: 2021-05-01 00:00:00

We investigate the vulnerability of a power transmission grid to load oscillation attacks. We demonstrate that an adversary with a relatively small amount of resources can launch a successful load oscillation attack to destabilize the grid. The adversary is assumed to be able to compromise smart meters at a subset of load buses and control their switches. In the studied attack scenarios the adversary estimates the line flow sensitivity factors (LFSFs) associated with the monitored tie lines by perturbing a small amount of load at compromised buses and observing the monitored lines flow changes. The learned LFSF values are used for selecting a target line and optimizing the oscillation attack to cause the target line to trip while minimizing the magnitude of load oscillation. We evaluated the attack impact using the COSMIC time-domain simulator with two test cases, the IEEE RTS 96 and Polish 2383-Bus Systems. The proposed attack strategy succeeded in causing 33% of load to be shed while oscillating only 7% of load in the IEEE RTS 96 test system, and full blackout after oscillating only 3% of the load in the Polish test system, which is much smaller than oscillation magnitudes used by other benchmarks.
Inversion-free feedforward hysteresis control using Preisach operator
Authors: Michael Ruderman
Date: 2021-05-01 00:00:00

We introduce a new inversion-free feedforward hysteresis control using the Preisach model. The feedforward scheme has a high-gain integral loop structure with Preisach hysteresis operator in negative feedback. This allows obtaining a dynamic quantity which corresponds to the inverse hysteresis output, as the loop error tends towards zero for a sufficiently high feedback gain. By analyzing the loop sensitivity function with hysteresis that acts as a state-varying phase lag, we demonstrate the achievable bandwidth and accuracy of the proposed control method. Remarkable fact is that the control bandwidth is theoretically infinite, provided the Preisach operator in feedback can be implemented in a way to ensure the $\mathcal{C}^0$ continuous hysteresis output. Numerical control examples with the Preisach hysteresis model in differential form are presented.