pwc-archive/papers-with-abstracts huggingface dataset:
Bounding Privacy Leakage in Smart Buildings
Date: 2020-03-30 00:00:00
Tasks: Management

Smart building management systems rely on sensors to optimize the operation
of buildings. If an unauthorized user gains access to these sensors, a privacy
leak may occur. This paper considers such a potential leak of privacy in a
smart residential building, and how it may be mitigated through corrupting the
measurements with additive Gaussian noise. This corruption is done in order to
hide the occupancy change in an apartment. A lower bound on the variance of any
estimator that estimates the change time is derived. The bound is then used to
analyze how different model parameters affect the variance. It is shown that
the signal to noise ratio and the system dynamics are the main factors that
affect the bound. These results are then verified on a simulator of the KTH
Live-In Lab Testbed, showing good correspondence with theoretical results.
Probabilistic Caching for Small-Cell Networks with Terrestrial and Aerial Users
Date: 2020-03-30 00:00:00
Tasks: Point Processes

The support for aerial users has become the focus of recent 3GPP
standardizations of 5G, due to their high maneuverability and flexibility for
on-demand deployment. In this paper, probabilistic caching is studied for
ultra-dense small-cell networks with terrestrial and aerial users, where a
dynamic on-off architecture is adopted under a sophisticated path loss model
incorporating both line-of-sight and non-line-of-sight transmissions.
Generally, this paper focuses on the successful download probability (SDP) of
user equipments (UEs) from small-cell base stations (SBSs) that cache the
requested files under various caching strategies. To be more specific, the SDP
is first analyzed using stochastic geometry theory, by considering the
distribution of such two-tier UEs and SBSs as Homogeneous Poisson Point
Processes. Second, an optimized caching strategy (OCS) is proposed to maximize
the average SDP. Third, the performance limits of the average SDP are developed
for the popular caching strategy (PCS) and the uniform caching strategy (UCS).
Finally, the impacts of the key parameters, such as the SBS density, the cache
size, the exponent of Zipf distribution and the height of aerial user, are
investigated on the average SDP. The analytical results indicate that the UCS
outperforms the PCS if the SBSs are sufficiently dense, while the PCS is better
than the UCS if the exponent of Zipf distribution is large enough. Furthermore,
the proposed OCS is superior to both the UCS and PCS.
Scheduling Flexible Non-Preemptive Loads in Smart-Grid Networks
Authors: Nathan Dahlin, Rahul Jain
Date: 2020-03-30 00:00:00
Tasks: Scheduling

A market consisting of a generator with thermal and renewable generation capability, a set of non-preemptive loads (i.e., loads which cannot be interrupted once started), and an independent system operator (ISO) is considered. Loads are characterized by durations, power demand rates and utility for receiving service, as well as disutility functions giving preferences for time slots in which service is preferred. Given this information, along with the generator's thermal generation cost function and forecast renewable generation, the social planner solves a mixed integer program to determine a load activation schedule which maximizes social welfare. Assuming price taking behavior, we develop a competitive equilibrium concept based on a relaxed version of the social planner's problem which includes prices for consumption and incentives for flexibility, and allows for probabilistic allocation of power to loads. Considering each load as representative of a population of identical loads with scaled characteristics, we demonstrate that the relaxed social planner's problem gives an exact solution to the original mixed integer problem in the large population limit, and give a market mechanism for implementing the competitive equilibrium. Finally, we evaluate via case study the benefit of incorporating load flexibility information into power consumption and generation scheduling in terms of proportion of loads served and overall social welfare.
Accelerated infection testing at scale: a proposal for inference with single test on multiple patients
Authors: Tarun Jain, Bijendra Nath Jain
Date: 2020-03-30 00:00:00

In pandemics or epidemics, public health authorities need to rapidly test a large number of individuals, both to determine the line of treatment as well as to know the spread of infection to plan containment, mitigation and future responses. However, the lack of adequate testing kits could be a bottleneck, especially in the case of unanticipated new diseases, such as COVID-19, where the testing technology, manufacturing capability, distribution, human skills and laboratories might be unavailable or in short supply. In addition, the cost of the standard PCR test is approximately USD 48, which is prohibitive for poorer patients and most governments. We address this bottleneck by proposing a test methodology that pools the sample from two (or more) patients in a single test. The key insight is that a single negative result from a pooled sample likely implies negative infection of all the individual patients. and It thereby rules out further tests for the patients. This protocol, therefore, requires significantly fewer tests. This may, however, result in somewhat increased false negatives. Our simulations show that combining samples from two patients with 7% underlying likelihood of infection implies that 36% fewer test kits are required, with 14% additional units of time for testing.
Fault tolerant controller design for a class of affine nonlinear systems based on adaptive virtual actuator
Date: 2020-03-30 00:00:00
Tasks: Fault Detection

An Adaptive Fault-tolerant Controller procedure for a class of the affine
nonlinear system is developed in this paper. This methodology hides both the
faults and external disturbances. Compare to the procedure that require
separate fault detection, isolation, and identification units, the suggested
method concentrates on fault hiding to reduce the units. The main merits of the
proposed method are 1) guaranteed stability of the closed loop system, 2)
convergence of the states of nominal and faulty systems to zero, and 3)
convergence of the tracking error to the origin. The robustness of presented
method is assured against external disturbances. Simulation result illustrate
the effectiveness of proposed fault tolerant control.
Efficient attention guided 5G power amplifier digital predistortion
Date: 2020-03-30 00:00:00

We investigate neural network (NN) assisted techniques for compensating the
non-linear behaviour and the memory effect of a 5G PA through digital
predistortion (DPD). Traditionally, the most prevalent compensation technique
computes the compensation element using a Memory Polynomial Model (MPM).
Various neural network proposals have been shown to improve on this
performance. However, thus far they mostly come with prohibitive training or
inference costs for real world implementations. In this paper, we propose a DPD
architecture that builds upon the practical MPM formulation governed by neural
attention. Our approach enables a set of MPM DPD components to individually
learn to target different regions of the data space, combining their outputs
for a superior overall compensation. Our method produces similar performance to
that of higher capacity NN models with minimal complexity. Finally, we view our
approach as a framework that can be extended to a wide variety of local
compensator types.
Distributed Collision-Free Motion Coordination on a Sphere: A Conic Control Barrier Function Approach
Date: 2020-06-23 00:00:00
Tasks: Collision Avoidance, Distributed Optimization

This letter studies a distributed collision avoidance control problem for a
group of rigid bodies on a sphere. A rigid body network, consisting of multiple
rigid bodies constrained to a spherical surface and an interconnection
topology, is first formulated. In this formulation, it is shown that motion
coordination on a sphere is equivalent to attitude coordination on the
3-dimensional Special Orthogonal group. Then, an angle-based control barrier
function that can handle a geodesic distance constraint on a spherical surface
is presented. The proposed control barrier function is then extended to a
relative motion case and applied to a collision avoidance problem for a rigid
body network operating on a sphere. Each rigid body chooses its control input
by solving a distributed optimization problem to achieve a nominal distributed
motion coordination strategy while satisfying constraints for collision
avoidance. The proposed collision-free motion coordination law is validated via
simulation.
Forecasting Models for Daily Natural Gas Consumption Considering Periodic Variations and Demand Segregation
Authors: Ergun Yukseltan, Ahmet Yucekaya, Ayse Humeyra Bilge, Esra Agca Aktunc
Date: 2020-02-29 00:00:00
Tasks: Time Series Analysis

Due to expensive infrastructure and the difficulties in storage, supply conditions of natural gas are different from those of other traditional energy sources like petroleum or coal. To overcome these challenges, supplier countries require take-or-pay agreements for requested natural gas quantities. These contracts have many pre-clauses; if they are not met due to low/high consumption or other external factors, buyers must completely fulfill them. A similar contract is then imposed on distributors and wholesale consumers. It is thus important for all parties to forecast their daily, monthly, and annual natural gas demand to minimize their risk. In this paper, a model consisting of a modulated expansion in Fourier series, supplemented by deviations from comfortable temperatures as a regressor is proposed for the forecast of monthly and weekly consumption over a one-year horizon. This model is supplemented by a day-ahead feedback mechanism for the forecast of daily consumption. The method is applied to the study of natural gas consumption for major residential areas in Turkey, on a yearly, monthly, weekly, and daily basis. It is shown that residential heating dominates winter consumption and masks all other variations. On the other hand, weekend and holiday effects are visible in summer consumption and provide an estimate for residential and industrial use. The advantage of the proposed method is the capability of long term projections and to outperform time series methods.
Intermediate frequency Upgrade design features of NASA D3R Weather Radar System
Authors: Mohit Kumar, Shashank Joshil, Manuel Vega, Robert Beauchamp, V Chandrasekar
Date: 2020-02-29 00:00:00
Tasks: Sensitivity

The NASA dual-frequency, dual-polarization, Doppler radar (D3R) is an important ground validation tool for the global precipitation measurement (GPM) mission dual-frequency precipitation radar (DPR). The D3R has undergone extensive field trials starting in 2011 and continues to provide observations that enhance our scientific knowledge. To further enhance its capabilities, the Intermediate frequency (IF) electronics, digital receiver and waveform generation subsystems have been upgraded. Due to the new, more flexible architecture, this upgrade enables more research frontiers to be explored with better performance. One of the primary motivations for this upgrade is to enable enhanced radar sensitivity and increase range resolution to 30 meters. In this work, the D3R system upgrade will be discussed with a focus on the key upgrade design features to obtain better sensitivity and a flexible waveform capability.
Tall wheatgrass (Thinopyrum ponticum (Podp)) in a real farm context, a sustainable perennial alternative to rye (Secale cereale L.) cultivation in marginal lands
Authors: Carlos S. Ciria, Carlos M. Sastre, Juan Carrasco, Pilar Ciria
Date: 2020-02-11 00:00:00

In order to face the expected increasing demand of energy crops without creating conflicts of land occupation sustainability, farmers need to find reliable alternatives in marginal agricultural areas where the production of food hardly ever is economically and environmentally sustainable. The purpose of this work was the study of the viability of the introduction of new non food crops in marginal areas of real farms. This study compares the profit margin and the energy and environmental performance of growing tall wheatgrass, in the marginal area of a rainfed farm versus rye, the annual crop sowed traditionally in the marginal area of the farm. The cited farm owned 300 ha of which about 13 percent was marginal. The methodology was based on the use of the profit margin of the crops as indicator for the economic assessment and Life Cycle Assessment LCA as technique for the energy and the environmental evaluations. Results of the economic analysis showed a slight enhancement of the profit margin for tall wheatgrass 156 Euro ha-1 y-1 compared to rye 145 Euro ha-1 y-1. Environmental LCA was driven by CO2 fixation due to soil organic matter increase and reduced inputs consumption for tall wheatgrass that produced a Global Warming Potential GWP of -1.9 Mg CO2 eq ha-1 y-1 versus 1.6 Mg CO2 eq ha-1 y-1 obtained for rye. Tall wheatgrass cultivation primary energy consumption was less than 40 percent of rye s consumption. According to the results achieved it was concluded that tall wheatgrass is better option than rye from the energy and the environmental point of views and slight better option from the economic view. Considering these results, monetarization of the CO2 eq reductions of tall wheatgrass compared to rye is essential to improve its profit margin and promote the implantation of this new crop in marginal areas of farms.
Combined Cooling, Heating, and Power System in Blockchain-Enabled Energy Management
Date: 2020-03-20 00:00:00
Tasks: energy management, energy trading, Management

The combined cooling, heating and power (CCHP) system is a typical
distributed, electricity-gas integrated energy scheme in a community. First, it
generates electricity by use of gas, and then exploits the waste heat to supply
community with heat and cooling. In this paper, we consider a smart city
consisting of a number of communities (CCHPs) and an agent of power grid (APG),
where CCHPs can sell energy to the APG according to its bid. To study all
utilities of entities in such a city from energy trading, a noncooperative
Stackelberg game between APG and CCHPs is formulated. Here, the APG gives a bid
for buying the energy from CCHPs, then CCHPs respond to the APG with their
optimal energy supply that maximizing their utilities according to this bid. We
show that the maximum profit to the APG and utilities to the CCHPs can be
obtained at the Stackelberg equilibrium, which is guaranteed to exist and
unique. Because the complete information about energy supply of each CCHP is
unknown to the APG in advance, we propose a distributed algorithm that is able
to find the point of equilibrium through a limited number of iterations. Taking
privacy protection and transaction security into consideration, we design a
blockchain-enabled energy management system. This system is composed of
Internet of Energy (IoE) sub-system and blockchain sub-system, where the
information interactions as well as energy transactions between APG and CCHPs
can be carried out effectively and safely. Finally, security analysis and
numerical simulations show the effectiveness and accuracy of our proposed
mechanism.
Use of fitted polynomials for the decentralized estimation of network variables in unbalanced radial LV feeders
Authors: Valentin Rigoni, Alireza Soroudi, Andrew Keane
Date: 2020-03-19 00:00:00

The lack of comprehensive monitoring equipment in low voltage (LV) residential feeders, impedes a near-term deployment of centralized schemes for the integration of domestic-scale distributed generation (DG). In this context, this paper introduces a technique that generates a set of fitted polynomials, derived from offline simulations and regression analysis, that characterise the magnitude of representative network variables (i.e. key for network operation) as a direct analytical expression of the controllable local conditions of any DG unit (i.e. active and reactive power injections). Crucially, the coefficients of these polynomials can be estimated, autonomously at the location of each DG unit, without the need for remote monitoring (i.e. using only locally available measurements). During online implementation, the method consists only of direct calculations (i.e. non-iterative), facilitating real-time operation. The accuracy of the polynomials to estimate the magnitude of the network variables is assessed under multiple scenarios on a representative radial LV feeder. Furthermore, the robustness of the method is demonstrated under the presence of new generation and electric vehicles.
Sustainable Banking; Evaluation of the European Business Models
Authors: Saeed Nosratabadi, Gergo Pinter, Amir Mosavi, Sandor Semperger
Date: 2020-03-18 00:00:00

Sustainable business models also offer banks competitive advantages such as increasing brand reputation and cost reduction. However, no framework is presented to evaluate the sustainability of banking business models. To bridge this theoretical gap, the current study using A Delphi-Analytic Hierarchy Process method, firstly, developed a sustainable business model to evaluate the sustainability of the business model of banks. In the second step, the sustainability performance of sixteen banks from eight European countries including Norway, the UK, Poland, Hungary, Germany, France, Spain, and Italy, assessed. The proposed business model components of this study were ranked in terms of their impact on achieving sustainability goals. Consequently, the proposed model components of this study, based on their impact on sustainability, are respectively value proposition, core competencies, financial aspects, business processes, target customers, resources, technology, customer interface, and partner network. The results of the comparison of the banks studied by each country disclosed that the sustainability of the Norwegian and German banks business models is higher than in other counties. The studied banks of Hungary and Spain came in second, the banks of the UK, Poland, and France ranked third, and finally, the Italian banks ranked fourth in the sustainability of their business models.
Modern alleles in archaic human Y chromosomes support origin of modern human paternal lineages in Asia rather than Africa
Authors: Hongyao Chen, Shi Huang
Date: 2020-03-26 00:00:00

Recent studies have shown that hybridization between modern and archaic humans was commonplace in the history of our species. After admixture, some individuals with admixed autosomes carried the modern Homo Sapiens uniparental DNAs, while the rest carried the archaic versions. Coevolution of admixed autosomes and uniparental DNAs is expected to cause some of the sites in modern uniparental DNAs to revert back to archaic alleles, while the opposite process would occur (from archaic to modern) in some of the sites in archaic uniparental DNAs. This type of coevolution is one of the elements that differentiate the two different models of the Y phylogenetic tree of modern humans, rooting it either in Africa or East Asia. The expected reversion to archaic alleles is assumed to occur and is easily traceable in the Asia model, but is absent in the Africa model due to its infinite site assumption, which also precludes the independent or convergent mutation to modern alleles in archaic uniparental DNAs since mutations are assumed to occur randomly across a neutral genome, and convergent evolution is assumed not to occur. Here, we examined newly published high coverage Y chromosome sequencing data of two Denisovan and two Neanderthal samples to determine whether they carry modern-Homo Sapiens alleles in sites where they are not supposed to according to the Africa model. The results showed that a significant fraction of the sites that, according to the Asia model, should differentiate the original modern Y from the original archaic Y carried modern alleles in the archaic Y samples here. Some of these modern alleles were shared among all archaic humans while others could differentiate Denisovans from Neanderthals. The observation is best accounted for by coevolution of archaic Y and admixed modern autosomes, and hence supports the Asia model, since it takes such coevolution into account.
Using MetaPrisms for Performance Improvement in Wireless Communications
Date: 2020-03-30 00:00:00

In this paper, we put forth the idea of metaprism, a passive and
non-reconfigurable metasurface acting as a metamirror with frequency-dependent
reflecting properties within the signal bandwidth. We show that, with an
appropriate design of the metaprism, it is possible to control that each data
stream in an orthogonal frequency division multiplexing (OFDM) system is
reflected in the desired direction without the need for control channels and
channel state information (CSI) estimation between the base station and the
metaprism, but simply by correctly assigning subcarriers to users. Furthermore,
the metaprism can also be designed so that it focuses the signal towards a
specific position depending on the subcarrier, provided that it is in the
near-field, with consequent path-loss reduction. A critical discussion is also
presented about the path-loss gain obtainable from metaprisms and, more
generally, from metasurfaces. The numerical results show that this solution is
surprisingly effective in extending the coverage in areas experiencing severe
non line-of-sight (NLOS) channel conditions, thus making it a very appealing
alternative to reconfigurable metasurfaces when low-cost, no energy
consumption, and backward compatibility with existing wireless standards are
required.
Dynamics of the COVID-1 -- Comparison between the Theoretical Predictions and the Real Data, and Predictions about Returning to Normal Life
Date: 2020-09-12 00:00:00

A new coronavirus disease, called COVID-19, appeared in the Chinese region of
Wuhan at the end of last year; since then the virus spread to other countries,
including most of Europe. We propose a differential equation governing the
evolution of the COVID-19. This dynamic equation also describes the evolution
of the number of infected people for 13 common respiratory viruses (including
the SARS-CoV-2). We validate our theoretical predictions with experimental data
for Italy, Belgium and Luxembourg, and compare them with the predictions of the
logistic model. We find that our predictions are in good agreement with the
real world since the beginning of the appearance of the COVID-19; this is not
the case for the logistic model that only applies to the first days. The second
part of the work is devoted to modelling the descending phase, i.e. the
decrease of the number of people tested positive for COVID-19. Also in this
case, we propose a new set of dynamic differential equations that we solved
numerically. We use our differential equations parametrised with experimental
data to make several predictions, such as the date when Italy, Belgium, and
Luxembourg will reach a peak number of SARS-CoV-2 infected people. The
descending curves provide valuable information such as the duration of the
COVID-19 epidemic in a given Country and therefore when it will be possible to
return to normal life. The study of the the dynamics of COVID-19 when the
population have been subject to less restrictive measures is beyond the scope
of this work and it will be matter of future works.