arXiv preprints from January 1, 2026 through September 8, 2026 — 17:08:11 EST
Rising interest rates can expose life insurers to surrender risk by reducing the market value of their assets and raising policyholders' outside returns. This paper develops a minimal model of an insurance-specific run mechanism in which strategic interaction arises because early surrenders can deplete the asset pool backing...
We study causal moderation when treatment assignment is randomized but the moderator is not. We combine the parallel estimation framework with front-door adjustment to identify an average mediated treatment moderation effect. We apply this approach to 165 municipal assembly elections in Tokyo (1987-2023), where pamphlet positions are...
As an extension of existing Bayesian persuasion framework with inadequate message mechanism, we study direct recommendation when a sender is bound by an installed information policy only with probability $ρ$, the realization of binding is hidden, and the receiver does not observe the persistent structural environment. The receiver...
We study, theoretically and experimentally, how transparency about students' priorities and admission chances shapes their incentives to acquire information about their own preferences in school choice and college admissions. In the model, uninformed students choose schools based on a common prior. When they learn their own...
Firms perform online experiments with multi-armed bandits to personalize what consumers are shown while balancing exploration and exploitation. However, third-parties can infer consumers' underlying segments from observing which banners, ads, or recommendations consumers receive. To control this inference, we propose a privacy risk...
Fault diagnosis under unknown operating conditions remains challenging for dynamic industrial systems, as the distribution shift caused by changing operating conditions can significantly degrade the performance of diagnostic models in real-world applications. To address the problem, a condition-guided selective adaptation approach is...
The static loadability limit, defined as the demand at which the equilibrium equations lose their solution, is the standard basis for interconnection screening of large new loads. This letter shows that when part of the demand varies periodically, as for data-center loads, the steady state is a forced periodic orbit whose loadability...
The standard shortcut in slotted-waveguide array design -- solve one radiating stick, multiply its embedded pattern by the array factor of the intended aperture distribution, and accept the product as the array pattern -- is tested against a full-wave solution of the same metal. For a 16x16-slot planar array in WR-90 synthesised to a...
This paper presents a phased-array transmit beamformer design for beampattern matching and interference suppression. We propose an optimization framework jointly addressing these two objectives. The resulting non-convex problem is solved via alternating minimization, where each subproblem admits a closed-form solution, one of which...
Diffusion-based models are emerging in the speech enhancement domain and are achieving state-of-the-art performance across various benchmark datasets. A major downside of diffusion models is that data generation requires many evaluations of a typically large neural network, which results in high overall complexity. In this work, we...
LGE cardiac MRI is widely used for left atrial fibrosis assessment and ablation planning in atrial fibrillation patients as knowledge of fibrotic tissue regions identified from LGE-MRI is critical for catheter ablation. Often, poor quality images used during ablation planning can cause mis-localization of ablation targets, directly...
Speech enhancement on embedded digital signal processors (DSPs) imposes strict constraints on memory footprint, computational complexity, latency, and support for integer operations. Although recent DNN-based approaches have addressed these challenges individually, no unified framework in the literature simultaneously addresses all...
In this paper we discuss and analyze a method for lane-change intention anticipation of drivers on highways based on kinematic features and surrounding observations. The approach makes use of a recursive Bayesian filtering strategy, which can be interpreted as a hidden Markov model. We present two models for the likelihood term and...
Integrated sensing and communication (ISAC) has been identified as one primary usage scenario in the sixth-generation (6G) network. While techniques to preserve information privacy, such as cryptography, have been widely investigated, how to preserve sensing privacy is still an open problem in the literature. This paper makes an early...
Integrated sensing and communications (ISAC) is a key enabler for uncrewed aerial vehicles (UAVs) in the low-altitude economy. This paper proposes an ISAC waveform that embeds a unique word (UW) into orthogonal chirp division multiplexing (OCDM), termed UW-OCDM, together with corresponding communication reception and cooperative...
High-altitude platforms (HAPs) are key enablers of next-generation non-terrestrial networks (NTNs), offering wide coverage, long endurance, and rapid deployment. Despite these advantages, current NTN designs remain satellite-centric and rely on terrestrial cellular assumptions, limiting flexibility and scalability. To overcome these...
An uplink pinching-antenna system (PASS) is considered, where a segmented dielectric waveguide is employed to serve multiple users and one pinching antenna (PA) is activated on each segment. Extensive waveguide deployment reduces user-to-PA path loss but also creates differential propagation delays among the PA-assisted paths spanning...
Multistatic ranging with mobile receivers enables good tracking performance due to the combined adaptive sensor geometry. However, environments that contain signal obstructing obstacles require receiver trajectory planning to maintain line-of-sight (LOS) conditions with transmitters and the target of interest. In this letter, we...
We investigate how the realism of synthetic room impulse response (RIR) datasets affects the training of DeepFilterNet3 for single-channel speech enhancement. We compare a DNS4 image-source-method (ISM) RIR dataset with a higher-acoustic-fidelity dataset generated using hybrid wave-based and geometrical acoustics simulation. Rather...
This paper proposes a Square-Root Transformed $L_1$-norm ($SR\text{-}TL_{1}$) sparse recovery framework for single-measurement-vector (SMV) direction of arrival (DoA) estimation under highly-coherent overcomplete dictionaries with angular-dependent array imperfections. The proposed framework combines the square-root Least Absolute...
The ongoing energy transition challenges the stable operation of power systems and increases the need for rapid decision-making under uncertainty. While reinforcement learning has emerged as a promising framework for power system control and operation, existing applications typically focus on a single operational criterion, such as...
The certification of Unmanned Aerial Vehicle (UAV) swarms for safety-critical operations requires verifiable design assurance. Airworthiness standards demand deterministic reliability, whereas multi-agent coordination algorithms execute non-deterministic models. This paper proposes a mixed-criticality architectural framework that...
Accurate electricity price forecasting is critical for smart grid stability, yet the heavy reliance on historical price lags in modern predictive models often obscures the fundamental physical drivers of market volatility. This paper proposes a regime-sensitive, explainable artificial intelligence (XAI) framework to unmask the hidden...
Transportation networks, in particular multi-class transportation networks (i.e., networks with mixed vehicle types), are complex systems that are challenging to control. Recently, Deep Reinforcement Learning (DRL), which learns control policies from interactions with the environment, and Model Predictive Control (MPC), which uses a...
Probing every candidate location at each wireless-map update is costly. This letter develops electromagnetic-twin (ET) beamforming that converts sparse spatial probes into a sum-rate decision. The ET stores a location-dependent angular power spectrum, updates its innovation through graph-regularized estimation, and queries user...