pwc-archive/papers-with-abstracts huggingface dataset:
Enhance Local Consistency in Federated Learning: A Multi-Step Inertial Momentum Approach
Authors: Yixing Liu, Yan Sun, Zhengtao Ding, Li Shen, Bo Liu, DaCheng Tao
Date: 2023-02-11 00:00:00
Tasks: Edge-computing, Federated Learning

Federated learning (FL), as a collaborative distributed training paradigm with several edge computing devices under the coordination of a centralized server, is plagued by inconsistent local stationary points due to the heterogeneity of the local partial participation clients, which precipitates the local client-drifts problems and sparks off the unstable and slow convergence, especially on the aggravated heterogeneous dataset. To address these issues, we propose a novel federated learning algorithm, named FedMIM, which adopts the multi-step inertial momentum on the edge devices and enhances the local consistency for free during the training to improve the robustness of the heterogeneity. Specifically, we incorporate the weighted global gradient estimations as the inertial correction terms to guide both the local iterates and stochastic gradient estimation, which can reckon the global objective optimization on the edges' heterogeneous dataset naturally and maintain the demanding consistent iteration locally. Theoretically, we show that FedMIM achieves the $\mathcal{O}(\frac{1}{\sqrt{SKT}})$ convergence rate with a linear speedup property with respect to the number of selected clients $S$ and proper local interval $K$ in communication round $T$ without convex assumption. Empirically, we conduct comprehensive experiments on various real-world datasets and demonstrate the efficacy of the proposed FedMIM against several state-of-the-art baselines.
A Tractable Truthful Profit Maximization Mechanism Design with Autonomous Agents
Authors: Mina Montazeri, Hamed Kebriaei, Babak N. Araabi
Date: 2023-02-11 00:00:00

Task allocation is a crucial process in modern systems, but it is often challenged by incomplete information about the utilities of participating agents. In this paper, we propose a new profit maximization mechanism for the task allocation problem, where the task publisher seeks an optimal incentive function to maximize its own profit and simultaneously ensure the truthful announcing of the agent's private information (type) and its participation in the task, while an autonomous agent aims at maximizing its own utility function by deciding on its participation level and announced type. Our mechanism stands out from the classical contract theory-based truthful mechanisms as it empowers agents to make their own decisions about their level of involvement, making it more practical for many real-world task allocation scenarios. It has been proven that by considering a linear form of incentive function consisting of two decision functions for the task publisher the mechanism's goals are met. The proposed truthful mechanism is initially modeled as a non-convex functional optimization with the double continuum of constraints, nevertheless, we demonstrate that by deriving an equivalent form of the incentive constraints, it can be reformulated as a tractable convex optimal control problem. Further, we propose a numerical algorithm to obtain the solution.
Trajectory-based Robustness Analysis for Nonlinear Systems
Authors: Peter Seiler, Raghu Venkataraman
Date: 2023-02-11 00:00:00

This paper considers the robustness of an uncertain nonlinear system along a finite-horizon trajectory. The uncertain system is modeled as a connection of a nonlinear system and a perturbation. The analysis relies on three ingredients. First, the nonlinear system is approximated by a linear time-varying (LTV) system via linearization along a trajectory. This linearization introduces an additional forcing input due to the nominal trajectory. Second, the input/output behavior of the perturbation is described by time-domain, integral quadratic constraints (IQCs). Third, a dissipation inequality is formulated to bound the worst-case deviation of an output signal due to the uncertainty. These steps yield a differential linear matrix inequality (DLMI) condition to bound the worst-case performance. The robustness condition is then converted to an equivalent condition in terms of a Riccati Differential Equation. This yields a computational method that avoids heuristics often used to solve DLMIs, e.g. time gridding. The approach is demonstrated by a two-link robotic arm example.
On Safety of Passengers Entering a Bus Rapid Transit System from Scheduled Stops
Authors: Alejandra Valencia, Andreas A. Malikopoulos
Date: 2023-02-10 00:00:00
Tasks: Position, Scheduling

In this paper, we address the vehicle scheduling problem for improving passenger safety in bus rapid transit systems. Our focus is on passengers waiting at street stops to enter terminal stations. To enhance their safety, we minimize deviations from the proposed timetable, thereby minimizing passengers' initial waiting time. We formulate an optimization problem considering the position, speed deviation, and passenger count at each stop, solved using dynamic programming. Numerical simulations validate the effectiveness of our approach in enhancing passenger safety. Our work is the first attempt to minimize waiting time for improved safety and the first to utilize position tracking for departure time matching.
Identifying Resonant Poles by Visual Inspection of Pole-Zero Plots
Authors: Amro El-Jaroudi, Patrick Loughlin
Date: 2023-02-10 00:00:00

We derive the s- and z-plane pole regions for continuous-time and discrete-time LTI systems to yield resonance. In this way, resonance can be identified by visual inspection of the pole-zero plot, without the need for calculations.
An Overview of Uncertain Control Co-Design Formulations
Authors: Saeed Azad, Daniel R. Herber
Date: 2023-02-10 00:00:00

This article explores various uncertain control co-design (UCCD) problem formulations. While previous work offers formulations that are method-dependent and limited to only a handful of uncertainties (often from one discipline), effective application of UCCD to real-world dynamic systems requires a thorough understanding of uncertainties and how their impact can be captured. Since the first step is defining the UCCD problem of interest, this article aims at addressing some of the limitations of the current literature by identifying possible sources of uncertainties in a general UCCD context and then formalizing ways in which their impact is captured through problem formulation alone (without having to immediately resort to specific solution strategies). We first develop and then discuss a generalized UCCD formulation that can capture uncertainty representations presented in this article. Issues such as the treatment of the objective function, the challenge of the analysis-type equality constraints, and various formulations for inequality constraints are discussed. Then, more specialized problem formulations such as stochastic in expectation, stochastic chance-constrained, probabilistic robust, worst-case robust, fuzzy expected value, and possibilistic chance-constrained UCCD formulations are presented. Key concepts from these formulations, along with insights from closely-related fields, such as robust and stochastic control theory, are discussed, and future research directions are identified.
Optimal Design and Cascading Failure Evaluation of Remedial Action Schemes
Authors: Aditya Rangarajan, Line Roald
Date: 2023-02-10 00:00:00

Remedial action schemes (RAS) are often seen as an alternative to building new transmission infrastructure to relieve congestion in the system. Consequently, there has been a rapid growth in the number of RAS in electric power systems across the world. However, most RAS rely on fixed parameters and hence cannot adapt to the rapidly evolving nature of the electric grid. In this paper, an optimization framework (RAS-SCOPF) to automate the RAS design procedure is proposed. The proposed framework is a mixed integer quadratic program (MIQP) that chooses a set of optimal RAS actions and minimizes load shed when a contingency occurs. The cost of operation of the RAS-SCOPF is compared against those of standard OPF and SCOPF formulations. Moreover, the risk of cascading failure for the different formulations are evaluated using a DC power flow based cascading failure simulator (CFS). The proposed framework is applied to the RTS-96 24-bus network. The inclusion of RAS allows the system to be operated at a lower cost while preventing any contingency from evolving into cascading blackouts.
A Graph-based Framework for Complex System Simulating and Diagnosis with Automatic Reconfiguration
Authors: Martina Teruzzi, Nicola Demo, Gianluigi Rozza
Date: 2023-02-10 00:00:00
Tasks: Fault Detection

Fault detection has a long tradition: the necessity to provide the most accurate diagnosis possible for a process plant criticality is somehow intrinsic in its functioning. Continuous monitoring is a possible way for early detection. However, it is somehow fundamental to be able to actually simulate failures. Reproducing the issues remotely allows to quantify in advance their consequences, causing literally no real damage. Within this context, signed directed graphs have played an essential role within the years, managing to model with a relatively simple theory diverse elements of an industrial network, as well as the logic relations between them.\\ In this work we present a quantitative approach, employing directed graphs to the simulation and automatic reconfiguration of a fault in a network. To model the typical operation of industrial plants, we propose several additions with respect to the standard graphs: 1. a quantitative measure to control the overall residual capacity, 2. nodes of different categories - and then different behaviors - and 3. a fault propagation procedure based on the predecessors and the redundancy of the system. The obtained graph is able to mimic the behaviour of the real target plant when one or more faults occur. Additionally, we also implement a generative approach capable to activate a particular category of nodes in order to contain the issue propagation, equipping the network with the capability of reconfigure itself and resulting then in a mathematical tool useful not only for simulating and monitoring, but also to design and optimize complex plants. The final asset of the system is provided in output with its complete diagnostics, and a detailed description of the steps that have been carried out to obtain the final realization.
A Convex Hull Cheapest Insertion Heuristic for the Non-Euclidean TSP
Authors: Mithun Goutham, Meghna Menon, Sarah Garrow, Stephanie Stockar
Date: 2023-02-05 00:00:00

The convex hull cheapest insertion heuristic produces good solutions to the Euclidean Traveling Salesperson Problem, but it has never been extended to the non-Euclidean problem. This paper uses multidimensional scaling to first project the points from a non-Euclidean space into a Euclidean space, enabling the generation of a convex hull that initializes the algorithm. To evaluate the proposed algorithm, non-Euclidean spaces are created by adding separators to the TSPLIB data-set, or by using the L1 norm as a metric.
Individualized Treatment Allocation in Sequential Network Games
Authors: Toru Kitagawa, Guanyi Wang
Date: 2023-02-11 00:00:00

Designing individualized allocation of treatments so as to maximize the equilibrium welfare of interacting agents has many policy-relevant applications. Focusing on sequential decision games of interacting agents, this paper develops a method to obtain optimal treatment assignment rules that maximize a social welfare criterion by evaluating stationary distributions of outcomes. Stationary distributions in sequential decision games are given by Gibbs distributions, which are difficult to optimize with respect to a treatment allocation due to analytical and computational complexity. We apply a variational approximation to the stationary distribution and optimize the approximated equilibrium welfare with respect to treatment allocation using a greedy optimization algorithm. We characterize the performance of the variational approximation, deriving a performance guarantee for the greedy optimization algorithm via a welfare regret bound. We implement our proposed method in simulation exercises and an empirical application using the Indian microfinance data (Banerjee et al., 2013), and show it delivers significant welfare gains.
Set-Asides in USDA Food Procurement Auctions
Authors: Ni Yan, WenTing Tao
Date: 2023-02-11 00:00:00
Tasks: regression

We study the partial and full set-asides and their implication for changes in bidding behavior in first-price sealed-bid auctions in the context of United States Department of Agriculture (USDA) food procurement auctions. Using five years of bid data on different beef products, we implement weighted least squares regression models to show that partial set-aside predicts decreases in both offer prices and winning prices among large and small business bidders. Full set-aside predicts a small increase in offer prices and winning prices among small businesses. With these predictions, we infer that net profit of small businesses is unlikely to increase when set-asides are present.
Comparison Shopping: Learning Before Buying From Duopolists
Authors: Brian C. Albrecht, Mark Whitmeyer
Date: 2023-02-13 00:00:00

We explore a model of duopolistic competition in which consumers learn about the fit of each competitor's product. In equilibrium, consumers comparison shop: they learn only about the relative values of the products. When information is cheap, increasing the cost of information decreases consumer welfare; but when information is expensive, this relationship flips. As information frictions vanish, there is a limiting equilibrium that is ex post efficient.
Random Utility, Repeated Choice, and Consumption Dependence
Authors: Christopher Turansick
Date: 2023-02-11 00:00:00

We study consumption dependence in the context of random utility and repeated choice. We show that, in the presence of consumption dependence, the random utility model is a misspecified model of repeated rational choice. This misspecification leads to biased estimators and failures of standard random utility axioms. We characterize exactly when and by how much the random utility model is misspecified when utilities are consumption dependent. As one possible solution to this problem, we consider time disaggregated data. We offer a characterization of consumption dependent random utility when we observe time disaggregated data. Using this characterization, we develop a hypothesis test for consumption dependent random utility that offers computational improvements over the natural extension of Kitamura and Stoye (2018) to our setting.
An Error-Surface-Based Fractional Motion Estimation Algorithm and Hardware Implementation for VVC
Authors: Shushi Chen, Leilei Huang, Jiahao Liu, Chao Liu, Yibo Fan
Date: 2023-02-13 00:00:00
Tasks: 4k, 8k, Motion Estimation

Versatile Video Coding (VVC) introduces more coding tools to improve compression efficiency compared to its predecessor High Efficiency Video Coding (HEVC). For inter-frame coding, Fractional Motion Estimation (FME) still has a high computational effort, which limits the real-time processing capability of the video encoder. In this context, this paper proposes an error-surface-based FME algorithm and the corresponding hardware implementation. The algorithm creates an error surface constructed by the Rate-Distortion (R-D) cost of the integer motion vector (IMV) and its neighbors. This method requires no iteration and interpolation, thus reducing the area and power consumption and increasing the throughput of the hardware. The experimental results show that the corresponding BDBR loss is only 0.47% compared to VTM 16.0 in LD-P configuration. The hardware implementation was synthesized using GF 28nm process. It can support 13 different sizes of CU varying from 128x128 to 8x8. The measured throughput can reach 4K@30fps at 400MHz, with a gate count of 192k and power consumption of 12.64 mW. And the throughput can reach 8K@30fps at 631MHz when only quadtree is searched. To the best of our knowledge, this work is the first hardware architecture for VVC FME with interpolation-free strategies
gpcgc: a green point cloud geometry coding method
Authors: Qingyang Zhou, Shan Liu, C. -C. Jay Kuo
Date: 2023-02-13 00:00:00
Tasks: Quantization

A low-complexity point cloud compression method called the Green Point Cloud Geometry Codec (GPCGC), is proposed to encode the 3D spatial coordinates of static point clouds efficiently. GPCGC consists of two modules. In the first module, point coordinates of input point clouds are hierarchically organized into an octree structure. Points at each leaf node are projected along one of three axes to yield image maps. In the second module, the occupancy map is clustered into 9 modes while the depth map is coded by a low-complexity high-efficiency image codec, called the green image codec (GIC). GIC is a multi-resolution codec based on vector quantization (VQ). Its complexity is significantly lower than HEVC-Intra. Furthermore, the rate-distortion optimization (RDO) technique is used to select the optimal coding parameters. GPCGC is a progressive codec, and it offers a coding performance competitive with MPEG's V-PCC and G-PCC standards at significantly lower complexity.
Exploring High Tower Base Stations with Multi-User Massive MIMO for Rural Connectivity
Authors: Ammar El Falou, Mohamad-Slim Alouini
Date: 2023-02-13 00:00:00

The digital divide is a key issue worldwide. Almost 3 billion people, mainly in rural areas, are still not connected. In this paper, we explore the capability of high towers base station (HTBS) with massive multiple input multiple output (mMIMO) in offering low-cost rural connectivity. We previously showed the benefits of HTBS in the downlink. We focus in this work on the uplink (UL) where we compute the UL data rate per user for different values of transmit effective isotropic radiated power (EIRP). Our results show that the HTBS solution is viable as relatively good user UL rates are achieved with reasonable EIRPs. This is of high interest for covering rural areas, characterized by low population densities and a low number of active users, as the coverage is their main constraint, rather than the capacity as in urban areas. Techno-economical aspects such as the recommended frequency for HTBS, the number of covered persons, the average population density of covered rural areas, and potential low-cost locations for HTBS are provided. Non-technological challenges for the HTBS solution are also discussed.
Fabrication of a Low-Cost Real-Time Mobile ECG System for Health Monitoring
Authors: Soheil Khooyooz, Mohammad Ali Ahmadi Pajouh, Kamyab Azizi
Date: 2023-02-13 00:00:00

The electrocardiogram (ECG) signal is one of the most vital signals that can be used to investigate the performance of heart. Based on the ECG graph, we can identify different disorders and diseases. Therefore, monitoring this signal is of great importance. Many electrodes (usually 12) are employed to acquire this signal in clinics and hospitals; therefore, a nurse must install them on the body of the patient to record the signal. In this project, we built a device that can acquire the real-time ECG signal and display it on the mobile screen with the least number of electrodes (three electrodes) without requiring a nurse to install the electrodes using the simplest and cheapest type of ICs and transmitters including STM32F030F4P6 microcontroller, AD620 instrumentation amplifier, TL084 amplifier, TC7660 voltage converter, LM1117 regulator, and HC-05 Bluetooth module. Moreover, the device was designed in a way that could operate using a single 9V battery or power adaptor. First, to amplify the signal and remove a part of its noise, the ECG signal is given to the primary analog circuit. Then, in the digital section, using a microcontroller, the signal is discretized, processed, and finally transmitted to a mobile phone for final processing, information extraction, and displaying. In the mobile-written application, we developed a mathematical algorithm based on Pan-Tompkins algorithm to calculate the heartbeat rate, in which the signal peaks are determined after several processing steps using a threshold. In this regard, the ECG signals of 10 subjects were recorded and analyzed to calculate the optimum threshold. Finally, the power spectral density (PSD) and input referred noise were calculated and plotted to check the output signal quality. Based on the PSD and input referred noise amplitudes, we achieved a signal-to-noise ratio of 50dB.
Design and Performance Analysis of Wireless Legitimate Surveillance Systems with Radar Function
Authors: Mianyi Zhang, Yinghui He, Yunlong Cai, Guanding Yu, Naofal Al-Dhahir
Date: 2023-02-13 00:00:00
Tasks: Integrated sensing and communication, ISAC

Integrated sensing and communication (ISAC) has recently been considered as a promising approach to save spectrum resources and reduce hardware cost. Meanwhile, as information security becomes increasingly more critical issue, government agencies urgently need to legitimately monitor suspicious communications via proactive eavesdropping. Thus, in this paper, we investigate a wireless legitimate surveillance system with radar function. We seek to jointly optimize the receive and transmit beamforming vectors to maximize the eavesdropping success probability which is transformed into the difference of signal-to-interference-plus-noise ratios (SINRs) subject to the performance requirements of radar and surveillance. The formulated problem is challenging to solve. By employing the Rayleigh quotient and fully exploiting the structure of the problem, we apply the divide-and-conquer principle to divide the formulated problem into two subproblems for two different cases. For the first case, we aim at minimizing the total transmit power, and for the second case we focus on maximizing the jamming power. For both subproblems, with the aid of orthogonal decomposition, we obtain the optimal solution of the receive and transmit beamforming vectors in closed-form. Performance analysis and discussion of some insightful results are also carried out. Finally, extensive simulation results demonstrate the effectiveness of our proposed algorithm in terms of eavesdropping success probability.
Privacy Performance of MIMO Dual-Functional Radar-Communications with Internal Adversary
Authors: Isabella W. G. da Silva, Diana P. M. Osorio, Markku Juntti
Date: 2023-02-13 00:00:00

The co-design of radar sensing and communications in dual-functional radar communication systems brings promising advantages for next generation wireless networks by providing gains in terms of the efficient and flexible use of spectrum, reduced costs, and lower energy consumption than in two separate systems. Besides the challenges associated with the conciliation of the conflicting requirements to perform wireless communication and radar sensing in a real-time cooperation, privacy issues represent a cause of concern as the co-design can let the network prone to active attacks. This paper tackles this issue by evaluating the associated privacy risks with the design of transmit precoders that simultaneously optimise both the radar transmit beampattern and the signal-to-interference-plus-noise at the communication users. Our results show that if a malicious user can infer the transmitted precoder matrix with a certain accuracy, there is a reasonable risk of exposure of the location of the target and privacy breaches.