pwc-archive/papers-with-abstracts huggingface dataset:
Laboratory Setup for Testing Low-Frequency Disturbances of Power Quality
Authors: Piotr Kuwałek, Grzegorz Wiczyński
Date: 2024-01-31 00:00:00

Low-frequency disturbances of power quality are one of the most common disturbances in the power grid. These disturbances are most often the result of the impact of power electronic and energy-saving devices, the number of which is increasing significantly in the power grid. Due to the simultaneous operation of various types of loads in the power grid, various types of simultaneous disturbances of power quality occur, such as voltage fluctuations and distortions. Therefore, there is a need to analyze this type of simultaneous interaction. For this purpose, a special and complementary laboratory setup has been prepared, which allows for the examination of actual states occurring in modern power networks. Selected research results are presented for this laboratory setup, which determine its basic properties. Possible applications and possibilities of the laboratory setup are presented from the point of view of current challenges.
Multi-Agent Phase-Balancing around Polar Curves with Bounded Trajectories: An Experimental Study using Crazyflies and MoCap System
Authors: Gaurav Singh Bhati, KKN Shyam Sathvik, Anuj Patil, Anoop Jain
Date: 2024-01-31 00:00:00

In this experimental work, we implement the control design from our earlier work on a swarm of Crazyflie 2.1 quad-copters by deriving the original control in terms of variables that are available to the user in this practical system. A suitable model is developed using the Crazyswarm2 package within ROS2 to facilitate the execution of the control law. We also discuss various components that are part of this experiment and the challenges we encountered during the experimentation. Extensive experimental results, along with the links to the YouTube videos for actual Crazyflie quad-copters, are provided.
On the Sum Secrecy Rate Maximisation for Wireless Vehicular Networks
Authors: Muhammad Farooq, Le-Nam Tran, Fatemeh Golpayegani, Nima Afraz
Date: 2024-01-31 00:00:00

Wireless communications form the backbone of future vehicular networks, playing a critical role in applications ranging from traffic control to vehicular road safety. However, the dynamic structure of these networks creates security vulnerabilities, making security considerations an integral part of network design. We address these security concerns from a physical layer security aspect by investigating achievable secrecy rates in wireless vehicular networks. Specifically, we aim to maximize the sum secrecy rate from all vehicular pairs subject to bandwidth and power resource constraints. For the considered problem, we first propose a solution based on the successive convex approximation (SCA) method, which has not been applied in this context before. To further reduce the complexity of the SCA-based method, we also propose a low-complexity solution based on a fast iterative shrinkage-thresholding algorithm (FISTA). Our simulation results for SCA and FISTA show a trade-off between convergence and runtime. While the SCA method achieves better convergence, the FISTA-based approach is at least 300 times faster than the SCA method.
Modeling and analysis of a flexible spinning Euler-Bernoulli beam with centrifugal stiffening and softening: A Linear Fractional Representation approach with application to spinning spacecraft
Authors: Ricardo Rodrigues, Daniel Alazard, Francesco Sanfedino, Tommaso Mauriello, Paolo Iannelli
Date: 2024-01-31 00:00:00
Tasks: Cantilever Beam

The derivation of a linear fractional representation (LFR) model for a flexible, spinning and uniform Euler-Bernoulli beam is accomplished using the {Lagrange} technique, fully capturing the centrifugal force generated by the spinning motion and accounting for its dependence on the angular velocity. This six degrees of freedom (DOF) model accounts for the behavior of deflection in the moving body frame, encompassing the bending, traction and torsion dynamics. The model is also designed to be compliant with the Two-Input-Two-Output Port (TITOP) approach, which offers the possibility to model complex multibody mechanical systems, while keeping the uncertain nature of the plant and condensing all the possible mechanical configurations in a single LFR. To evaluate the effectiveness of the model, various scenarios are considered and their results are tabulated. These scenarios include uniform beams with fixed root boundary conditions for different values of tip mass, root offset and angular velocity. The results from the analysis of the uniform cantilever beam are compared with solutions found in the literature and obtained from a commercial finite element software. Ultimately, this paper presents a multibody model for a spinning spacecraft mission scenario. A comprehensive analysis of the system dynamics is conducted, providing insights into the behavior of the spacecraft under spinning conditions.
Integrated Information Decomposition Unveils Major Structural Traits of $In$ $Silico$ and $In$ $Vitro$ Neuronal Networks
Authors: Gustavo Menesse, Akke Mats Houben, Jordi Soriano, Joaquin J. Torres
Date: 2024-01-30 00:00:00

The properties of complex networked systems arise from the interplay between the dynamics of their elements and the underlying topology. Thus, to understand their behaviour, it is crucial to convene as much information as possible about their topological organization. However, in a large systems such as neuronal networks, the reconstruction of such topology is usually carried out from the information encoded in the dynamics on the network, such as spike train time series, and by measuring the Transfer Entropy between system elements. The topological information recovered by these methods does not necessarily capture the connectivity layout, but rather the causal flow of information between elements. New theoretical frameworks, such as Integrated Information Decomposition ($\Phi$-ID), allow to explore the modes in which information can flow between parts of a system, opening a rich landscape of interactions between network topology, dynamics and information. Here, we apply $\Phi$-ID on $in$ $silico$ and $in$ $vitro$ data to decompose the usual Transfer Entropy measure into different modes of information transfer, namely synergistic, redundant or unique. We demonstrate that the unique information transfer is the most relevant measure to uncover structural topological details from network activity data, while redundant information only introduces residual information for this application. Although the retrieved network connectivity is still functional, it captures more details of the underlying structural topology by avoiding to take into account emergent high-order interactions and information redundancy between elements, which are important for the functional behavior, but mask the detection of direct simple interactions between elements constituted by the structural network topology.
Identification of spatial dynamic patterns of behavior using weighted Voronoi diagrams
Authors: Martha Lorena Avendaño-Garrido, Carlos Alberto Hernández-Linares, Brenda Zarahí Medina-Pérez, Varsovia Hernández, Porfirio Toledo, Alejandro León
Date: 2024-01-30 00:00:00

This study proposes an innovative approach to analyze spatial patterns of behavior by integrating information in weighted Voronoi diagrams. The objective of the research is to analyze the temporal distribution of an experimental subject in different regions of a given space, with the aim of identifying significant areas of interest. The methodology employed involves dividing the experimental space, determining representative points, and assigning weights based on the cumulative time the subject spends in each region. This process results in a set of generator points along with their respective weights, thus defining the Voronoi diagram. The study also presents a detailed and advanced perspective for understanding spatial behavioral patterns in experimental contexts.
Regularizing Fairness in Optimal Policy Learning with Distributional Targets
Authors: Anders Bredahl Kock, David Preinerstorfer
Date: 2024-01-31 00:00:00
Tasks: Fairness

A decision maker typically (i) incorporates training data to learn about the relative effectiveness of treatments, and (ii) chooses an implementation mechanism that implies an ``optimal'' predicted outcome distribution according to some target functional. Nevertheless, a fairness-aware decision maker may not be satisfied achieving said optimality at the cost of being ``unfair" against a subgroup of the population, in the sense that the outcome distribution in that subgroup deviates too strongly from the overall optimal outcome distribution. We study a framework that allows the decision maker to regularize such deviations, while allowing for a wide range of target functionals and fairness measures to be employed. We establish regret and consistency guarantees for empirical success policies with (possibly) data-driven preference parameters, and provide numerical results. Furthermore, we briefly illustrate the methods in two empirical settings.
Marginal treatment effects in the absence of instrumental variables
Authors: Zhewen Pan, Zhengxin Wang, Junsen Zhang, Yahong Zhou
Date: 2024-01-31 00:00:00

We propose a method for defining, identifying, and estimating the marginal treatment effect (MTE) without imposing the instrumental variable (IV) assumptions of independence, exclusion, and separability (or monotonicity). Under a new definition of the MTE based on reduced-form treatment error that is statistically independent of the covariates, we find that the relationship between the MTE and standard treatment parameters holds in the absence of IVs. We provide a set of sufficient conditions ensuring the identification of the defined MTE in an environment of essential heterogeneity. The key conditions include a linear restriction on potential outcome regression functions, a nonlinear restriction on the propensity score, and a conditional mean independence restriction that will lead to additive separability. We prove this identification using the notion of semiparametric identification based on functional form. And we provide an empirical application for the Head Start program to illustrate the usefulness of the proposed method in analyzing heterogenous causal effects when IVs are elusive.
Let's roll back! The challenging task of regulating temporary contracts
Authors: Davide Fiaschi, Cristina Tealdi
Date: 2024-01-31 00:00:00
Tasks: Time Series

In this paper, we evaluate the impact of a reform introduced in Italy in 2018 (Decreto Dignit\`a), which increased the rigidity of employment protection legislation (EPL) of temporary contracts, rolling back previous policies, to reduce job instability. We use longitudinal labour force data from 2016 to 2019 and adopt a time-series technique within a Rubin Casual Model (RCM) framework to estimate the causal effect of the reform. We find that the reform was successful in reducing persistence into temporary employment and increasing the flow from temporary to permanent employment, in particular among women and young workers in the North of Italy, with significant effects on the stocks of permanent employment (+), temporary employment (-) and unemployment (-). However, this positive outcome came at the cost of higher persistence into inactivity, lower outflows from unemployment to temporary employment and higher outflows from unemployment to inactivity among males and low-educated workers.
Filipino Use of Designer and Luxury Perfumes: A Pilot Study of Consumer Behavior
Authors: John Paul P. Miranda, Maria Anna D. Cruz, Dina D. Gonzales, Ma. Rebecca G. Del Rosario, Aira May B. Canlas, Joseph Alexander Bansil
Date: 2024-01-31 00:00:00

This study investigates the usage patterns and purposes of designer perfumes among Filipino consumers, employing purposive and snowball sampling methods as non-probability sampling techniques. Data was collected using Google Forms, and the majority of respondents purchased full bottles of designer perfumes from retailers, wholesalers, and physical stores, with occasional "blind purchases." Daily usage was common, with respondents applying an average of 5.88 sprays in the morning, favoring fresh scent notes and Eau De Parfum concentration. They tended to alternate perfumes daily, selecting different scent profiles according to the Philippine climate. The study reveals that Filipino respondents primarily use designer perfumes to achieve a pleasant and fresh fragrance. Additionally, these perfumes play a role in boosting self-esteem, elevating mood, and enhancing personal presentation. Some respondents reported fewer common applications, such as using perfume to address insomnia and migraines. Overall, the research highlights the significant role of perfume in the grooming routine of Filipino consumers. This study represents the first attempt to comprehend perfume usage patterns and purposes specifically within the Filipino context. Consequently, its findings are invaluable for manufacturers and marketers targeting the Filipino market, providing insights into consumer preferences and motivations.
Tradeoffs and Comparison Complexity
Authors: Cassidy Shubatt, Jeffrey Yang
Date: 2024-01-31 00:00:00

This paper develops a theory of how tradeoffs govern comparison complexity, and how this complexity generates systematic mistakes in choice. In our model, options are easier to compare when they involve less pronounced tradeoffs, in particular when they are 1) more similar feature-by-feature and 2) closer to dominance. These two postulates yield tractable measures of comparison complexity in the domains of multiattribute, lottery, and intertemporal choice. We show how our model organizes a range of behavioral regularities in choice and valuation, such as context effects, preference reversals, and apparent probability weighting and hyperbolic discounting. We test our model experimentally by varying the strength and nature of tradeoffs. First, we show that our complexity measures predict choice errors, choice inconsistency, and cognitive uncertainty in binary choice data across all three domains. Second, we document that manipulations of comparison complexity can reverse classic behavioral regularities, in line with the predictions of the theory. We apply our theory to study strategic obfuscation by firms in a pricing game.
What you know or who you know? The role of intellectual and social capital in opportunity recognition
Authors: Antonio Rafael Ramos-Rodriguez, Jose Aurelio Medina-Garrido, Jose Daniel Lorenzo-Gomez, Jose Ruiz-Navarro
Date: 2024-01-30 00:00:00

The recognition of business opportunities is the first stage in the entrepreneurial process. The current work analyzes the effects of individuals' possession of and access to knowledge on the probability of recognizing good business opportunities in their area of residence. The authors use an eclectic theoretical framework consisting of intellectual and social capital concepts. In particular, they analyze the role of individuals' educational level, their perception that they have the right knowledge and skills to start a business, whether they own and manage a firm, their contacts with other entrepreneurs, and whether they have been business angels. The hypotheses proposed here are tested using data collected for the GEM project in Spain in 2007. The results show that individuals' access to external knowledge through the social networks in which they participate is fundamental for developing the capacity to recognize new business opportunities.
Education Policy and Intergenerational Educational Persistence: Evidence from rural Benin
Authors: Christelle Zozoungbo
Date: 2024-01-30 00:00:00

This paper employs a nonlinear difference-in-differences approach to empirically examine the Maximally Maintained Inequality (MMI) hypothesis in rural Benin. The findings of this study confirm the MMI hypothesis. In particular, it is observed that when 76% of educated parents choose to educate their daughters in the absence of educational programs, in contrast to only 37% among non-educated parents, the average impact of tuition fee subsidy on enrollment probability in primary schools stands at 3.8\% for non-educated households and 0.27% for educated households. Conversely, in cases where only 27% of educated parents decide to educate their daughters without education programs, the average effect of tuition fee waivers on enrollment probability in primary schools increases to 19.64\% for non-educated households and 24\% for educated households. From the analysis of household education decisions influenced by a preference for education and budget constraints, three key conclusions emerge to explain the mechanism behind the MMI. Firstly, when the income advantage of educated households compared to non-educated households is significantly high, irrespective of the level of their preference advantage, reducing the financial cost of education induces a greater shift in education decisions among non-educated households. Secondly, in situations where educated households do not possess an income advantage relative to non-educated households, the reduction in education-related financial costs leads to a more pronounced change in education decisions among educated households. Lastly, for the low-income advantage of educated households, as the income advantage of educated households increases, non-educated households respond more to education policy than educated parents, if the preference advantage of educated households is relatively smaller.
Modeling how and why aquatic vegetation removal can free rural households from poverty-disease traps
Authors: Molly J Doruska, Christopher B Barrett, Jason R Rohr
Date: 2024-01-30 00:00:00

Infectious disease can reduce labor productivity and incomes, trapping subpopulations in a vicious cycle of ill health and poverty. Efforts to boost African farmers' agricultural production through fertilizer use can inadvertently promote the growth of aquatic vegetation that hosts disease vectors. Recent trials established that removing aquatic vegetation habitat for snail intermediate hosts reduces schistosomiasis infection rates in children, while converting the harvested vegetation into compost boosts agricultural productivity and incomes. Our model illustrates how this ecological intervention changes the feedback between the human and natural systems, potentially freeing rural households from poverty-disease traps. We develop a bioeconomic model that interacts an analytical microeconomic model of agricultural households' behavior, health status and incomes over time with a dynamic model of schistosomiasis disease ecology. We calibrate the model with field data from northern Senegal. We show analytically and via simulation that local conversion of invasive aquatic vegetation to compost changes the feedbacks among interlinked disease, aquatic and agricultural systems, reducing schistosomiasis infection and increasing incomes relative to the current status quo, in which villagers rarely remove vegetation. Aquatic vegetation removal disrupts the poverty-disease trap by reducing habitat for snails that vector the infectious helminth and by promoting production of compost that returns to agricultural soils nutrients that currently leach into surface water from on-farm fertilizer applications. The result is healthier people, more productive labor, cleaner water, more productive agriculture, and higher incomes.
Efficient estimation of parameters in marginals in semiparametric multivariate models
Authors: Ivan Medovikov, Valentyn Panchenko, Artem Prokhorov
Date: 2024-01-29 00:00:00

We consider a general multivariate model where univariate marginal distributions are known up to a parameter vector and we are interested in estimating that parameter vector without specifying the joint distribution, except for the marginals. If we assume independence between the marginals and maximize the resulting quasi-likelihood, we obtain a consistent but inefficient QMLE estimator. If we assume a parametric copula (other than independence) we obtain a full MLE, which is efficient but only under a correct copula specification and may be biased if the copula is misspecified. Instead we propose a sieve MLE estimator (SMLE) which improves over QMLE but does not have the drawbacks of full MLE. We model the unknown part of the joint distribution using the Bernstein-Kantorovich polynomial copula and assess the resulting improvement over QMLE and over misspecified FMLE in terms of relative efficiency and robustness. We derive the asymptotic distribution of the new estimator and show that it reaches the relevant semiparametric efficiency bound. Simulations suggest that the sieve MLE can be almost as efficient as FMLE relative to QMLE provided there is enough dependence between the marginals. We demonstrate practical value of the new estimator with several applications. First, we apply SMLE in an insurance context where we build a flexible semi-parametric claim loss model for a scenario where one of the variables is censored. As in simulations, the use of SMLE leads to tighter parameter estimates. Next, we consider financial risk management examples and show how the use of SMLE leads to superior Value-at-Risk predictions. The paper comes with an online archive which contains all codes and datasets.
Assessing Public Perception of Car Automation in Iran: Acceptance and Willingness to Pay for Adaptive Cruise Control
Authors: Sina Sahebi, Sahand Heshami, Mohammad Khojastehpour, Ali Rahimi, Mahyar Mollajani
Date: 2024-01-29 00:00:00

Adaptive cruise control (ACC) is a technology that can reduce fuel consumption and air pollution in the automotive industry. However, its availability in Iran is low compared to industrialized countries. This study examines the acceptance and willingness to pay (WTP) for ACC among Iranian drivers. Data from an online survey of 453 respondents were analyzed using the Technology Acceptance Model (TAM) and an ordered logit model. The results show that perceived ease of use and perceived usefulness affect attitudes toward using ACC, which in turn influence behavioral intentions. The logit model also shows that drivers who find ACC easy and useful, who have higher vehicle prices, and who are women with cruise control (CC) experience are more likely to pay for ACC. To increase the adoption of ACC in Iran, it is suggested to target early adopters, especially women and capitalists, who can influence others with their positive feedback. The benefits of ACC for traffic safety and environmental sustainability should also be emphasized.
Coordinating Resource Allocation during Product Transitions Using a Multifollower Bilevel Programming Model
Authors: Rahman Khorramfar, Osman Ozaltin, Reha Uzsoy, Karl Kempf
Date: 2024-01-30 00:00:00
Tasks: Management

We study the management of product transitions in a semiconductor manufacturing firm that requires the coordination of resource allocation decisions by multiple, autonomous Product Divisions using a multi-follower bilevel model to capture the hierarchical and decentralized nature of this decision process. Corporate management, acting as the leader, seeks to maximize the firm's total profit over a finite horizon. The followers consist of multiple Product Divisions that must share manufacturing and engineering resources to develop, produce and sell products in the market. Each Product Division needs engineering capacity to develop new products, and factory capacity to produce products for sale while also producing the prototypes and samples needed for the product development process. We model this interdependency between Product Divisions as a generalized Nash equilibrium problem at the lower level and propose a reformulation where Corporate Management acts as the leader to coordinate the resource allocation decisions. We then derive an equivalent single-level reformulation and develop a cut-and-column generation algorithm. Extensive computational experiments evaluate the performance of the algorithm and provide managerial insights on how key parameters and the distribution of decision authority affect system performance.