pwc-archive/papers-with-abstracts huggingface dataset:
Model Reduction in Capacity Expansion Planning Problems via Renewable Generation Site Selection
Authors: David Radu, Antoine Dubois, Mathias Berger, Damien Ernst
Date: 2021-04-12 00:00:00

The accurate representation of variable renewable generation (RES, e.g., wind, solar PV) assets in capacity expansion planning (CEP) studies is paramount to capture spatial and temporal correlations that may exist between sites and impact both power system design and operation. However, it typically has a high computational cost. This paper proposes a method to reduce the spatial dimension of CEP problems while preserving an accurate representation of renewable energy sources. A two-stage approach is proposed to this end. In the first stage, relevant sites are identified via a screening routine that discards the locations with little impact on system design. In the second stage, the subset of relevant RES sites previously identified is used in a CEP problem to determine the optimal configuration of the power system. The proposed method is tested on a realistic EU case study and its performance is benchmarked against a CEP set-up in which the entire set of candidate RES sites is available. The method shows great promise, with the screening stage consistently identifying 90% of the optimal RES sites while discarding up to 54% of the total number of candidate locations. This leads to a peak memory reduction of up to 41% and solver runtime gains between 31% and 46%, depending on the weather year considered.
Staircase Selective Harmonic Elimination in Multilevel Inverters to Achieve Wide Output Voltage Range
Authors: Amirhossein Pourdadashnia, Mohammad Farhadi-Kangarlu, Milad Sadoughi
Date: 2021-04-12 00:00:00

Multilevel inverters (MLIs) are popular because of their advantages such as improved output voltage quality, lower switching losses, low EMI, and ability to handle higher voltage and power levels. To generate the desired output voltage in the MLIs, there are different switching methods including multicarrier pulse-width modulation (PWM), selective harmonic elimination (SHE), and multilevel space-vector PWM (SVPWM) methods. The SHE method minimizes the number of switching and hence the switching losses. Also, the method eliminates or attenuates specified low-order harmonics and adjusts the fundamental output voltage to the desired value. However, problems arise in the low modulation indexes where the harmonic distortion of the output voltage increases considerably. To solve the problem, this paper proposes a method to adjust the DC voltage when the low output voltage is required. Therefore, the modulation index will increase and the output voltage quality will be improved. The proposed method is verified on a 7-level Cascaded H-Bridge (CHB) inverter using the SHE method solved by particle swarm optimization (PSO) algorithm.
Symbiotic behaviour in the Public Goods game with altruistic punishment
Authors: Lucas S. Flores, Heitor C. M. Fernandes, Marco A. Amaral, Mendeli H. Vainstein
Date: 2020-12-17 00:00:00
Tasks: Specificity

Finding ways to overcome the temptation to exploit one another is still a challenge in behavioural sciences. In the framework of evolutionary game theory, punishing strategies are frequently used to promote cooperation in competitive environments. Here, we introduce altruistic punishers in the spatial public goods game. This strategy acts as a cooperator in the absence of defectors, otherwise it will punish all defectors in their vicinity while bearing a cost to do so. We observe three distinct behaviours in our model: i) in the absence of punishers, cooperators (who don't punish defectors) are driven to extinction by defectors for most parameter values; ii) clusters of punishers thrive by sharing the punishment costs when these are low iii) for higher punishment costs, punishers, when alone, are subject to exploitation but in the presence of cooperators can form a symbiotic spatial structure that benefits both. This last observation is our main finding since neither cooperation nor punishment alone can survive the defector strategy in this parameter region and the specificity of the symbiotic spatial configuration shows that lattice topology plays a central role in sustaining cooperation. Results were obtained by means of Monte Carlo simulations on a square lattice and subsequently confirmed by a pairwise comparison of different strategies' payoffs in diverse group compositions, leading to a phase diagram of the possible states.
CFAR Line Detector for Polarimetric SAR Images Using Wilks’ Test Statistic
Authors: Ruijin Jin, Wei Zhou, Junjun Yin, and Jian Yang
Date: 2016-05-01 00:00:00

In this letter, a constant false-alarm rate line detector
for polarimetric synthetic aperture radar (Pol-SAR) images is presented based on Wilks’ test statistic, which can be used to test the
equality of two covariance matrices following the complex Wishart
distribution. Due to the two-tailed nature, Wilks’ test statistic can
detect both bright and dark features. The probability distribution
of the proposed detector is derived and verified using simulated
Pol-SAR images. Experimental results on both simulated and
measured Pol-SAR data show the effectiveness of the proposed
detector and its superiority over the traditional detector based on
the Wishart likelihood-ratio test statistic.
Optimal evolutionary decision-making to store immune memory
Authors: Oskar H Schnaack, Armita Nourmohammad
Date: 2020-07-02 00:00:00
Tasks: Decision Making, Specificity

The adaptive immune system provides a diverse set of molecules that can mount specific responses against a multitude of pathogens. Memory is a key feature of adaptive immunity, which allows organisms to respond more readily upon re-infections. However, differentiation of memory cells is still one of the least understood cell fate decisions. Here, we introduce a mathematical framework to characterize optimal strategies to store memory to maximize the utility of immune response over an organism's lifetime. We show that memory production should be actively regulated to balance between affinity and cross-reactivity of immune receptors for an effective protection against evolving pathogens. Moreover, we predict that specificity of memory should depend on the organism's lifespan, and shorter-lived organisms with fewer pathogenic encounters should store more cross-reactive memory. Our framework provides a baseline to gauge the efficacy of immune memory in light of an organism's coevolutionary history with pathogens.
A Novel Solution of Using Mixed Reality in Bowel and Oral and Maxillofacial Surgical Telepresence: 3D Mean Value Cloning algorithm
Authors: Arjina Maharjan, Abeer Alsadoon, P. W. C. Prasad, Nada AlSallami, Tarik A. Rashid, Ahmad AlRubaie, Sami Haddad
Date: 2021-03-17 00:00:00
Tasks: Mixed Reality

Background and aim: Most of the Mixed Reality models used in the surgical telepresence are suffering from discrepancies in the boundary area and spatial-temporal inconsistency due to the illumination variation in the video frames. The aim behind this work is to propose a new solution that helps produce the composite video by merging the augmented video of the surgery site and the virtual hand of the remote expertise surgeon. The purpose of the proposed solution is to decrease the processing time and enhance the accuracy of merged video by decreasing the overlay and visualization error and removing occlusion and artefacts. Methodology: The proposed system enhanced the mean value cloning algorithm that helps to maintain the spatial-temporal consistency of the final composite video. The enhanced algorithm includes the 3D mean value coordinates and improvised mean value interpolant in the image cloning process, which helps to reduce the sawtooth, smudging and discolouration artefacts around the blending region. Results: As compared to the state of the art solution, the accuracy in terms of overlay error of the proposed solution is improved from 1.01mm to 0.80mm whereas the accuracy in terms of visualization error is improved from 98.8% to 99.4%. The processing time is reduced to 0.173 seconds from 0.211 seconds. Conclusion: Our solution helps make the object of interest consistent with the light intensity of the target image by adding the space distance that helps maintain the spatial consistency in the final merged video.
Physics-oriented learning of nonlinear Schrödinger equation: optical fiber loss and dispersion profile identification
Authors: Takeo Sasai, Masanori Nakamura, Etsushi Yamazaki, Shuto Yamamoto, Hideki Nishizawa, Yoshiaki Kisaka
Date: 2021-04-13 00:00:00
Tasks: Management

In optical fiber communication, system identification (SI) for the nonlinear Schr\"odinger equation (NLSE) has long been studied mainly for fiber nonlinearity compensation (NLC). One recent line of inquiry to combine a behavioral-model approach like digital backpropagation (DBP) and a data-driven approach like neural network (NN). These works are aimed for more NLC gain; however, by directing our attention to the learned parameters in such a SI process, system status information, i.e., optical fiber parameters, will possibly be extracted. Here, we show that the model-based optimization and interpretable nature of the learned parameters in NN-based DBP enable transmission line monitoring, fully extracting the actual in-line NLSE parameter distributions. Specifically, we demonstrate that longitudinal loss and dispersion profiles along a multi-span link can be obtained at once, directly from data-carrying signals without any dedicated analog devices such as optical time-domain reflectometry. We apply the method to a long-haul (~2,080 km) link and various link conditions are tested, including excess loss inserted, different fiber input power, and non-uniform level diagram. The measurement performance is also investigated in terms of measurement range, accuracy, and fiber launch power. These results provide a path toward simplified and automated network management as another application of DBP.
Analysis of the tradeoff between health and economic impacts of the Covid-19 epidemic
Authors: Samson Lasaulce, Chao Zhang, Vineeth Varma, Irinel Constantin Morarescu
Date: 2021-04-12 00:00:00
Tasks: Decision Making, Management

Various measures have been taken in different countries to mitigate the Covid-19 epidemic. But, throughout the world, many citizens don't understand well how these measures are taken and even question the decisions taken by their government. Should the measures be more (or less) restrictive? Are they taken for a too long (or too short) period of time? To provide some quantitative elements of response to these questions, we consider the well-known SEIR model for the Covid-19 epidemic propagation and propose a pragmatic model of the government decision-making operation. Although simple and obviously improvable, the proposed model allows us to study the tradeoff between health and economic aspects in a pragmatic and insightful way. Assuming a given number of phases for the epidemic and a desired tradeoff between health and economic aspects, it is then possible to determine the optimal duration of each phase and the optimal severity level for each of them. The numerical analysis is performed for the case of France but the adopted approach can be applied to any country. One of the takeaway messages of this analysis is that being able to implement the optimal 4-phase epidemic management strategy in France would have led to 1.05 million infected people and a GDP loss of 231 billion euro instead of 6.88 million of infected and a loss of 241 billion euro. This indicates that, seen from the proposed model perspective, the effectively implemented epidemic management strategy is good economically, whereas substantial improvements might have been obtained in terms of health impact. Our analysis indicates that the lockdown/severe phase should have been more severe but shorter, and the adjustment phase occurred earlier. Due to the natural tendency of people to deviate from the official rules, updating measures every month over the whole epidemic episode seems to be more appropriate.
CFAR Edge Detector for Polarimetric SAR Images
Authors: Jesper Schou, Henning Skriver, Allan Aasbjerg Nielsen, and Knut Conradsen
Date: 2003-01-01 00:00:00
Tasks: Edge Detection

Finding the edges between different regions in an
image is one of the fundamental steps of image analysis, and
several edge detectors suitable for the special statistics of synthetic
aperture radar (SAR) intensity images have previously been
developed. In this paper, a new edge detector for polarimetric
SAR images is presented using a newly developed test statistic in
the complex Wishart distribution to test for equality of covariance
matrices. The new edge detector can be applied to a wide range
of SAR data from single-channel intensity data to multifrequency
and/or multitemporal polarimetric SAR data. By simply changing
the parameters characterizing the test statistic according to the
applied SAR data, constant false-alarm rate detection is always
obtained. An adaptive filtering scheme is presented, and the
distributions of the detector are verified using simulated polarimetric SAR images. Using SAR data from the Danish airborne
polarimetric SAR, EMISAR, it is demonstrated that superior
edge detection results are obtained using polarimetric and/or
multifrequency data compared to using only intensity data.
The Ruble Collapse in an Online Marketplace: Some Lessons for Market Designers
Authors: John Horton
Date: 2021-04-13 00:00:00

The sharp devaluation of the ruble in 2014 increased the real returns to Russians from working in a global online labor marketplace, as con- tracts in this market are dollar-denominated. Russians clearly noticed the opportunity, with Russian hours-worked increasing substantially, primarily on the extensive margin -- incumbent Russians already active were fairly inelastic. Contrary to the predictions of bargaining models, there was little to no pass-through of the ruble price changes in to wages. There was also no evidence of a demand-side response, with buyers not posting more "Russian friendly" jobs, suggesting limited cross-side externalities. The key findings -- a high extensive margin elasticity but low intensive margin elasticity; little pass-through into wages; and little evidence of a cross-side externality -- have implications for market designers with respect to pricing and supply acquisition.
A Maximum Principle approach to deterministic Mean Field Games of Control with Absorption
Authors: Paulwin Graewe, Ulrich Horst, Ronnie Sircar
Date: 2021-04-13 00:00:00

We study a class of deterministic mean field games on finite and infinite time horizons arising in models of optimal exploitation of exhaustible resources. The main characteristic of our game is an absorption constraint on the players' state process. As a result of the state constraint the optimal time of absorption becomes part of the equilibrium. This requires a novel approach when applying Pontyagin's maximum principle. We prove the existence and uniqueness of equilibria and solve the infinite horizon models in closed form. As players may drop out of the game over time, equilibrium production rates need not be monotone nor smooth.
On the effect of social norms on performance in teams with distributed decision makers
Authors: Ravshanbek Khodzhimatov, Stephan Leitner, Friederike Wall
Date: 2021-04-13 00:00:00

Social norms are rules and standards of expected behavior that emerge in societies as a result of information exchange between agents. This paper studies the effects of emergent social norms on the performance of teams. We use the NK-framework to build an agent-based model, in which agents work on a set of interdependent tasks and exchange information regarding their past behavior with their peers. Social norms emerge from these interactions. We find that social norms come at a cost for the overall performance, unless tasks assigned to the team members are highly correlated, and the effect is stronger when agents share information regarding more tasks, but is unchanged when agents communicate with more peers. Finally, we find that the established finding that the team-based incentive schemes improve performance for highly complex tasks still holds in presence of social norms.
Modular structure in labour networks reveals skill basins
Authors: Neave O'Clery, Stephen Kinsella
Date: 2019-09-08 00:00:00
Tasks: Community Detection

There is an emerging consensus in the literature that locally embedded capabilities and industrial know-how are key determinants of growth and diversification processes. In order to model these dynamics as a branching process, whereby industries grow as a function of the availability of related or relevant skills, industry networks are typically employed. These networks, sometimes referred to as industry spaces, describe the complex structure of the capability or skill overlap between industry pairs, measured here via inter-industry labour flows. Existing models typically deploy a local or 'nearest neighbour' approach to capture the size of the labour pool available to an industry in related sectors. This approach, however, ignores higher order interactions in the network, and the presence of industry clusters or groups of industries which exhibit high internal skill overlap. We argue that these clusters represent skill basins in which workers circulate and diffuse knowledge, and delineate the size of the skilled labour force available to an industry. By applying a multi-scale community detection algorithm to this network of flows, we identify industry clusters on a range of scales, from many small clusters to few large groupings. We construct a new variable, cluster employment, which captures the workforce available to an industry within its own cluster. Using UK data we show that this variable is predictive of industry-city employment growth and, exploiting the multi-scale nature of the industrial clusters detected, propose a methodology to uncover the optimal scale at which labour pooling operates.
The role of relatedness and strategic linkages between domestic and MNE sectors in regional branching and resilience
Authors: Mattie Landman, Sanna Ojanperä, Stephen Kinsella, Neave O'Clery
Date: 2021-04-12 00:00:00

Despite the key role of multinational enterprises (MNEs) in both international markets and domestic economies, there is no consensus on their impact on their host economy. In particular, do MNEs stimulate new domestic firms through knowledge spillovers? Here, we look at the impact of MNEs on the entry and exit of domestic industries in Irish regions before, during, and after the 2008 Financial Crisis. Specifically, we are interested in whether the presence of MNEs in a region results in knowledge spillovers and the creation of new domestic industries in related sectors. To quantify how related an industry is to a region's industry basket we propose two cohesion measures, weighted closeness and strategic closeness, which capture direct linkages and the complex connectivity structure between industries in a region respectively. We use a dataset of government-supported firms in Ireland (covering 90% of manufacturing and exporting) between 2006-2019. We find that domestic industries are both more likely to enter and less likely to leave a region if they are related to so-called 'overlapping' industries containing both domestic and MNE firms. In contrast, we find a negative impact on domestic entry and survival from cohesion to 'exclusive MNE' industries, suggesting that domestic firms are unable to 'leap' and thrive in MNE-proximate industries likely due to a technology or know-how gap. This dynamic was broken, with domestic firms entering MNE exclusive sectors, by a large injection of Brexit diversification funds in 2017-18. Finally, the type of cohesion matters. For example, strategic rather than weighted closeness to exclusive domestic sectors matters for both entries and exits.
Don't throw efficiency out with the bathwater: A reply to Jeffery and Verheijen (2020)
Authors: Bartosz Bartkowski
Date: 2021-04-12 00:00:00
Tasks: valid

In this paper, I reply to the recent article by Jeffery and Verheijen (2020) 'A new soil health policy paradigm: Pay for practice not performance!'. While expressing support for their call for a more pronounced role of soil protection in agri-environmental policy, I critically discuss the two main elements of their specific proposal: its emphasis of the concept of soil health and the recommendation to use action-based payments as the main policy instrument. I argue for using soil functions as a more established concept (and thus more adequate for policy purposes), which is also informationally richer than soil health. Furthermore, I provide a more differentiated discussion of the relative advantages and disadvantages of result-based and action-based payments, while addressing the specific criticisms towards the former that Jeffery and Verheijen voice. Also, I suggest an alternative approach (a hybrid model-based scheme) that addresses the limitations of both Jeffery and Verheijen's own proposal and the valid criticisms they direct at result-based payments.
We Live in a Motorized Civilization: Robert Moses Replies to Robert Caro
Authors: Geoff Boeing
Date: 2021-03-26 00:00:00
Tasks: Optical Character Recognition, Optical Character Recognition (OCR)

In 1974, Robert Caro published The Power Broker, a critical biography of Robert Moses's dictatorial tenure as the "master builder" of mid-century New York. Moses profoundly transformed New York's urban fabric and transportation system, producing the Brooklyn Battery Tunnel, the Verrazano Narrows Bridge, the Westside Highway, the Cross-Bronx Expressway, the Lincoln Center, the UN headquarters, Shea Stadium, Jones Beach State Park and many other projects. However, The Power Broker did lasting damage to his public image and today he remains one of the most controversial figures in city planning history. On August 26, 1974, Moses issued a turgid 23-page statement denouncing Caro's work as "full of mistakes, unsupported charges, nasty baseless personalities, and random haymakers." Moses's original typewritten statement survives today as a grainy photocopy in the New York City Parks Department archive. To better preserve and disseminate it, I have extracted and transcribed its text using optical character recognition and edited the result to correct errors. Here I compile my transcription of Moses's statement, alongside Caro's reply to it.
Lossless Coding of Light Fields based on 4D Minimum Rate Predictors
Authors: João M. Santos, Lucas A. Thomaz, Pedro A. A. Assunção, Luís A. da Silva Cruz, Luís Távora, Sérgio M. M. Faria
Date: 2021-04-13 00:00:00

Common representations of light fields use four-dimensional data structures, where a given pixel is closely related not only to its spatial neighbours within the same view, but also to its angular neighbours, co-located in adjacent views. Such structure presents increased redundancy between pixels, when compared with regular single-view images. Then, these redundancies are exploited to obtain compressed representations of the light field, using prediction algorithms specifically tailored to estimate pixel values based on both spatial and angular references. This paper proposes new encoding schemes which take advantage of the four-dimensional light field data structures to improve the coding performance of Minimum Rate Predictors. The proposed methods expand previous research on lossless coding beyond the current state-of-the-art. The experimental results, obtained using both traditional datasets and others more challenging, show bit-rate savings no smaller than 10%, when compared with existing methods for lossless light field compression.