pwc-archive/papers-with-abstracts huggingface dataset:
Novel Stealthy Attack and Defense Strategies for Networked Control Systems
Date: 2020-04-25 00:00:00

This paper studies novel attack and defense strategies, based on a class of
stealthy attacks, namely the zero-dynamics attack (ZDA), for multi-agent
control systems. ZDA poses a formidable security challenge since its attack
signal is hidden in the null-space of the state-space representation of the
control system and hence it can evade conventional detection methods. An
intuitive defense strategy builds on changing the aforementioned representation
via switching through a set of carefully crafted topologies. In this paper, we
propose realistic ZDA variations where the attacker is aware of this
topology-switching strategy, and hence employs the following policies to avoid
detection: (i) pause, update and resume ZDA according to the knowledge of
switching topologies; (ii) cooperate with a concurrent stealthy topology attack
that alters network topology at switching times, such that the original ZDA is
feasible under the corrupted topology. We first systematically study the
proposed ZDA variations, and then develop defense strategies against them under
the realistic assumption that the defender has no knowledge of attack starting,
pausing, and resuming times and the number of misbehaving agents. Particularly,
we characterize conditions for detectability of the proposed ZDA variations, in
terms of the network topologies to be maintained, the set of agents to be
monitored, and the measurements of the monitored agents that should be
extracted, while simultaneously preserving the privacy of the states of the
non-monitored agents. We then propose an attack detection algorithm based on
the Luenberger observer, using the characterized detectability conditions. We
provide numerical simulation results to demonstrate our theoretical findings.
CubeSat Communications: Recent Advances and Future Challenges
Date: 2020-04-23 00:00:00

Given the increasing number of space-related applications, research in the
emerging space industry is becoming more and more attractive. One compelling
area of current space research is the design of miniaturized satellites, known
as CubeSats, which are enticing because of their numerous applications and low
design-and-deployment cost. The new paradigm of connected space through
CubeSats makes possible a wide range of applications, such as Earth remote
sensing, space exploration, and rural connectivity. CubeSats further provide a
complementary connectivity solution to the pervasive Internet of Things (IoT)
networks, leading to a globally connected cyber-physical system. This paper
presents a holistic overview of various aspects of CubeSat missions and
provides a thorough review of the topic from both academic and industrial
perspectives. We further present recent advances in the area of CubeSat
communications, with an emphasis on constellation-and-coverage issues, channel
modeling, modulation and coding, and networking. Finally, we identify several
future research directions for CubeSat communications, including Internet of
space things, low-power long-range networks, and machine learning for CubeSat
resource allocation.
AI-assisted PHY technologies for 6G and beyond wireless networks
Date: 2019-08-26 00:00:00

Machine Learning (ML) and Artificial Intelligence(AI) have become alternative
approaches in wireless networksbeside conventional approaches such as model
based solutionconcepts. Whereas traditional design concepts include the
mod-elling of the behaviour of the underlying processes, AI basedapproaches
allow to design network functions by learning frominput data which is supposed
to get mapped to specific outputs(training). Additionally, new input/output
relations can be learntduring the deployement phase of the function (online
learning)and make AI based solutions flexible, in order to react to
newsituations. Especially, new introduced use cases such as UltraReliable Low
Latency Communication (URLLC) and MassiveMachine Type Communications (MMTC) in
5G make this ap-proach necessary, as the network complexity is further
enhancedcompared to networks mainly designed for human driven traffic(4G, 5G
xMBB). The focus of this paper is to illustrate exemplaryapplications of AI
techniques at the Physical Layer (PHY) offuture wireless systems and therfore
they can be seen as candidatetechnologies for e.g. 6G systems.
CT Field of View Extension Using Combined Channels Extension and Deep Learning Methods
Date: 2019-08-26 00:00:00

This paper proposes a method to extend the field of view of computed
tomography images. In a first step, the field of view is increased by
extrapolating linearly the outer channels in the sinogram space. The modified
sinogram is then used to reconstruct extended field of view (EFoV) images
containing artifacts due to the channels extension. In a second step, those
artifacts are reduced by a deep learning network in image space. The proposed
method has been evaluated on a collection of clinical scans. The resulting
volumes have been checked for consistency and plausibility and compared to an
existing state of the art EFoV method.
Revenue Sharing in the Internet: A Moral Hazard Approach and a Net-neutrality Perspective
Date: 2019-08-26 00:00:00

Revenue sharing contracts between Content Providers (CPs) and Internet
Service Providers (ISPs) can act as leverage for enhancing the infrastructure
of the Internet. ISPs can be incentivized to make investments in network
infrastructure that improve Quality of Service (QoS) for users if attractive
contracts are negotiated between them and CPs. The idea here is that part of
the net profit gained by CPs are given to ISPs to invest in the network. The
Moral Hazard economic framework is used to model such an interaction, in which
a principal determines a contract, and an agent reacts by adapting her effort.
In our setting, several competitive CPs interact through one common ISP. Two
cases are studied: (i) the ISP differentiates between the CPs and makes a
(potentially) different investment to improve the QoS of each CP, and (ii) the
ISP does not differentiate between CPs and makes a common investment for both.
The last scenario can be viewed as \emph{network neutral behavior} on the part
of the ISP. We analyse the optimal contracts and show that the CP that can
better monetize its demand always prefers the non-neutral regime.
Interestingly, ISP revenue, as well as social utility, are also found to be
higher under the non-neutral regime.
Verification of Detectability Using Petri Nets and Detector
Date: 2019-08-26 00:00:00

Detectability describes the property of a system to uniquely determine, after
a finite number of observations, the current and subsequent states. In this
paper, to reduce the complexity of checking the detectability properties in the
framework of bounded labeled Petri nets, we use a new tool, which is called
detector, to verifying the strong detectability and periodically strong
detectability. First, an approach, which is based on the reachable graph and
its detector, is proposed. Then, we develop a novel approach which is based on
the analysis of the detector of the basis reachability graph. Without computing
the whole reachability space, and without building the observer, the proposed
approaches are more efficient.
Multilingual and Multimode Phone Recognition System for Indian Languages
Date: 2019-08-23 00:00:00

The aim of this paper is to develop a flexible framework capable of
automatically recognizing phonetic units present in a speech utterance of any
language spoken in any mode. In this study, we considered two modes of speech:
conversation, and read modes in four Indian languages, namely, Telugu, Kannada,
Odia, and Bengali. The proposed approach consists of two stages: (1) Automatic
speech mode classification (SMC) and (2) Automatic phonetic recognition using
mode-specific multilingual phone recognition system (MPRS). In this work, the
vocal tract and excitation source features are considered for speech mode
classification (SMC) task. SMC systems are developed using multilayer
perceptron (MLP). Further, vocal tract, excitation source, and tandem features
are used to build the deep neural network (DNN)-based MPRSs. The performance of
the proposed approach is compared with mode-dependent MPRSs. Experimental
results show that the proposed approach which combines both SMC and MPRS into a
single system outperforms the baseline mode-dependent MPRSs.
Expansion method for pricing foreign exchange options under stochastic volatility and interest rates
Authors: Kenji Nagami
Date: 2019-08-26 00:00:00

Some expansion methods have been proposed for approximately pricing options which has no exact closed formula. Benhamou et al. (2010) presents the smart expansion method that directly expands the expectation value of payoff function with respect to the volatility of volatility, then uses it to price options in the stochastic volatility model. In this paper, we apply their method to the stochastic volatility model with stochastic interest rates, and present the expansion formula for pricing options up to the second order. Then the numerical studies are performed to compare our approximation formula with the Monte-Carlo simulation. It is found that our formula shows the numerically comparable results with the method proposed by Grzelak et al. (2012) which uses the approximation of characteristic function.
On a geometric description of time dependent singular Lagrangians with applications to biological systems
Authors: Sudip Garai, A Ghose-Choudhury, Partha Guha
Date: 2019-08-20 00:00:00

We consider certain analytical features of a stochastic model that can explain among other things competition among species and simultaneous predation on the competing species from a geometric perspective which allows for a systematic description of models admitting singular Lagrangians. The model equations are shown to admit a Jacobi Last Multiplier which in turn allows for the construction of a Lagrangian. The Lagrangian is of singular nature so that construction of the Hamiltonian via a Legendre transformation is not possible. A Hamiltonian description of the model therefore requires the introduction of Dirac brackets. Explicit results are presented for the "Kill the winner" model and its reductions.
Industrial Concentration of the Brazilian Automobile Market and Positioning in the World Market
Date: 2019-08-26 00:00:00

This paper surveys the evolution of industrial concentration of the Brazilian
automotive market as well as its positioning in the worldmarket. Data available
by OICA (International Organization of Motor Vehicle Manufacturers) were used
to better understand the characteristics of the Brazilian market on the world
stage. A cluster analysis algorithm (by the k-means technique) ranks Brazil
with a concentration profile in a group of countries like US and South Korea,
in contrast to countries such as Germany, Canada and Japan, or even France and
Italy. It is rather usual to characterize the market structure through
industrial concentration indices: we revisit CR ratios (concentration ratios),
HHI (Herfindahl-Hirschman index), B (Rosenbluth index), and CCI (Horvath
comprehensive concentration index). Data of Anfavea-Brazil (Associacao Nacional
dos Fabricantes de Veiculos Automotores) were used to estimate these indices in
the period 2012-2018 for the national automobile industry. The values obtained
indicate that by 1998 the automotive sector was behaving as an
oligopoly-differentiated. However, the values of more recent periods
(particularly CR4) strongly indicate that the sector is currently moderately
concentrated and is changing for a quasi-devolved market.
Spatial pattern and city size distribution
Date: 2019-08-26 00:00:00

Many large cities are found at locations with certain first nature
advantages. Yet, those exogenous locational features may not be the most potent
forces governing the spatial pattern of cities. In particular, population size,
spacing and industrial composition of cities exhibit simple, persistent and
monotonic relationships. Theories of economic agglomeration suggest that this
regularity is a consequence of interactions between endogenous agglomeration
and dispersion forces. This paper reviews the extant formal models that explain
the spatial pattern together with the size distribution of cities, and
discusses the remaining research questions to be answered in this literature.
To obtain results about explicit spatial patterns of cities, a model needs to
depart from the most popular two-region and systems-of-cities frameworks in
urban and regional economics in which there is no variation in interregional
distance. This is one of the major reasons that only few formal models have
been proposed in this literature. To draw implications as much as possible from
the extant theories, this review involves extensive discussions on the behavior
of the many-region extension of these models. The mechanisms that link the
spatial pattern of cities and the diversity in city sizes are also discussed in
detail.
Diffusion probabilistic LMS algorithm
Date: 2019-08-22 00:00:00

In this paper, a novel diffusion estimation algorithm is proposed from a
probabilistic perspective by combining diffusion strategy and the probabilistic
least-mean-squares (PLMS) at all agents. The proposed method diffusion
probabilistic LMS (DPLMS) is more robust to input signal and impulsive
interference than the DSE-LMS, DRVSSLMS and DLLAD algorithms. Instead of
minimizing the estimate error, the DPLMS algorithm is derived from
approximating the posterior distribution with an isotropic Gaussian
distribution. The stability of mean performance and computational complexity
are analyzed theoretically. Results from the simulation indicate that the DPLMS
algorithm is more robust to input signal and impulsive interference than the
DSE-LMS, DRVSSLMS and DLLAD algorithms. These results suggest that the DPLMS
algorithm can perform better in identifying the unknown coefficients under the
complex and changeable impulsive interference environments.
Differential Transformation of a Motor Load Model for Time-Domain Simulation
Date: 2019-08-23 00:00:00

The Differential Transformation (DT) method has demonstrated its potential in
speeding up power system time-domain simulation by our previous work. This
letter further derives DTs about a motor load model and proves that the
nonlinear current injection equation about a motor load can be transformed into
a linear equation by means of DT.
Optimal life-cycle consumption and investment decisions under age-dependent risk preferences
Authors: Andreas Lichtenstern, Pavel V. Shevchenko, Rudi Zagst
Date: 2019-08-27 00:00:00

In this article we solve the problem of maximizing the expected utility of future consumption and terminal wealth to determine the optimal pension or life-cycle fund strategy for a cohort of pension fund investors. The setup is strongly related to a DC pension plan where additionally (individual) consumption is taken into account. The consumption rate is subject to a time-varying minimum level and terminal wealth is subject to a terminal floor. Moreover, the preference between consumption and terminal wealth as well as the intertemporal coefficient of risk aversion are time-varying and therefore depend on the age of the considered pension cohort. The optimal consumption and investment policies are calculated in the case of a Black-Scholes financial market framework and hyperbolic absolute risk aversion (HARA) utility functions. We generalize Ye (2008) (2008 American Control Conference, 356-362) by adding an age-dependent coefficient of risk aversion and extend Steffensen (2011) (Journal of Economic Dynamics and Control, 35(5), 659-667), Hentschel (2016) (Doctoral dissertation, Ulm University) and Aase (2017) (Stochastics, 89(1), 115-141) by considering consumption in combination with terminal wealth and allowing for consumption and terminal wealth floors via an application of HARA utility functions. A case study on fitting several models to realistic, time-dependent life-cycle consumption and relative investment profiles shows that only our extended model with time-varying preference parameters provides sufficient flexibility for an adequate fit. This is of particular interest to life-cycle products for (private) pension investments or pension insurance in general.
Comparative Analysis of Conventional and Modified H-Bridge Inverter Configuration
Date: 2019-08-27 00:00:00

In this paper, a comparative analysis is presented for conventional and
modified H Bridge configuration of 5 and 7 level inverter. A modified H Bridge
converter utilizes a reduced number of switches for the same level output as
compared to the conventional H-Bridge configuration. The lower number of
switches will result in reduced switching losses, installation cost and
converter cost. MATLAB/SIMULINK software is used for simulation of the
different configurations used for the comparison. R and RL type of load are
used and the corresponding voltage waveform is analyzed for its harmonic
content. It can be seen from the results obtained that the Total Harmonic
Distortion (THD) in the modified and conventional 7 level configuration is less
than that of the 5 level inverter configurations.
Development of a Robust Depth-Pressure Estimation Algorithm for a Vision-Based Breast Self-Examination Guidance System
Date: 2019-08-27 00:00:00

In the case of breast cancer, as with most cancers, early detection can
significantly improve a person's chances of survival. This makes it important
for there to be an effective and accessible means of regularly checking for
manifestations of the disease. A vision-based guidance system (VBGS) for breast
self-examination (BSE) is one way to improve a person's ability to detect the
cancerous systems. In response to this need, this study sought to develop a
depth-pressure estimation algorithm for the proposed VBGS. A large number of
BSE videos were used to train the model, and these samples were segmented
according to breast size, which was found to be a differentiation factor in the
depth-pressure estimation. The result was an algorithm that was applicable for
universal use. In addition to these, several feature extraction schemes were
tested with the objective of making the algorithm functional on average
technology. It was found that Law's Textures Histogram and Local Binary Pattern
Global Histogram were the most effective in estimating pressure using visual
data. Moreover, combinations of the two schemes further improved the accuracy
of the model in estimation. The resulting algorithm was thereby fit to be used
by the average consumer.
Interaction of a Hydrogen Refueling Station Network for Heavy-Duty Vehicles and the Power System in Germany for 2050
Date: 2019-08-27 00:00:00

A potential solution to reduce greenhouse gas (GHG) emissions in the
transport sector is to use alternatively fueled vehicles (AFV). Heavy-duty
vehicles (HDV) emit a large share of GHG emissions in the transport sector and
are therefore the subject of growing attention from global regulators. Fuel
cell and green hydrogen technologies are a promising option to decarbonize
HDVs, as their fast refueling and long vehicle ranges are in line with current
logistic operation concepts. Moreover, the application of green hydrogen in
transport could enable more effective integration of renewable energies (RE)
across different energy sectors. This paper explores the interplay between HDV
Hydrogen Refueling Stations (HRS) that produce hydrogen locally and the power
system by combining an infrastructure location planning model and an energy
system optimization model that takes grid expansion options into account. Two
scenarios - one sizing refueling stations in symbiosis with the power system
and one sizing them independently of it - are assessed regarding their impacts
on the total annual energy system costs, regional RE integration and the
levelized cost of hydrogen (LCOH). The impacts are calculated based on
locational marginal pricing for 2050. Depending on the integration scenario, we
find average LCOH of between 5.66 euro/kg and 6.20 euro/kg, for which nodal
electricity prices are the main determining factor as well as a strong
difference in LCOH between north and south Germany. From a system perspective,
investing in HDV-HRS in symbiosis with the power system rather than
independently promises cost savings of around one billion-euros per annum. We
therefore conclude that the co-optimization of multiple energy sectors is
important for investment planning and has the potential to exploit synergies.
Effects of a Coal Phase-Out on Market Dynamics: Results from a Simulation Model for Germany
Date: 2019-08-27 00:00:00

Modeling power market dynamics is increasingly challenging, as both spatial
and temporal imbalances of demand and supply are becoming more pronounced with
higher shares of variable renewable energy (VRE). Therefore, a high-resolution
spatial and temporal distribution of both VRE and conventional generation, as
well as the load, is necessary for modeling the effect of policy measures on
the electricity market. Besides, technical constraints must be considered in
detail, as they fundamentally influence market outcomes. This contribution
presents the results and findings from a power market simulation model for the
case of the German market zone under different scenarios phasing out coal-fired
power generation. It is shown that the developed spatially resolved model can
realistically reproduce market outcomes and is, therefore, suitable for the
analysis of future scenarios with increased VRE integration and reduced
conventional generation capacity.
A neuro-mathematical model for size and context related illusions
Date: 2019-08-27 00:00:00

We provide here a mathematical model of size/context illusions, inspired by
the functional architecture of the visual cortex. We first recall previous
models of scale and orientation, in particular the one in (Sarti et al., 2008),
and simplify it, only considering the feature of scale. Then we recall the
deformation model of illusion, introduced by (Franceschiello et al. 2017), to
describe orientation related GOIs, and adapt it to size illusions. We finally
apply the model to the Ebbinghaus and Delboeuf illusions, validating the
results by comparing with experimental data from (Massaro et al., 1971) and
(Roberts et al., 2005).
Martingale transport with homogeneous stock movements
Authors: Stephan Eckstein, Michael Kupper
Date: 2019-08-27 00:00:00

We study a variant of the martingale optimal transport problem in a multi-period setting to derive robust price bounds of a financial derivative. On top of marginal and martingale constraints, we introduce a time-homogeneity assumption, which restricts the variability of the forward-looking transitions of the martingale across time. We provide a dual formulation in terms of superhedging and discuss relaxations of the time-homogeneity assumption by adding market frictions. In financial terms, the introduced time-homogeneity corresponds to a time-consistency condition for call prices, given the state of the stock. The time homogeneity assumption leads to improved price bounds as market data from many time points can be incorporated effectively. The approach is illustrated with two numerical examples.