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SHB-AE: Spherical harmonic beamforming based Ambisonics encoding and upscaling method for smartphone microphone array
Announce Type: new Abstract: With the rapid development of virtual reality (VR) and augmented reality (AR), spatial audio recording and reproduction have gained increasing research interest. Higher Order Ambisonics (HOA) stands out for its adaptability to various playback devices and its ability to integrate head orientation. However, current HOA recordings often rely on bulky spherical microphone arrays (SMA), and portable devices like smartphones are limited by array configuration and...
Learning to model pediatric asthma exacerbation from multiple risk factors: a case study in coastal Virginia
Announce Type: new Abstract: Childhood asthma is a common illness exacerbated by air pollution as well as meteorological and neighborhood-level socioeconomic factors. Modeling asthma exacerbation (AE) in large spatiotemporal datasets requires disentangling impacts from multiple contributors. In this case study, we compared three techniques that balance predictive power with interpretability to predict AE in Hampton Roads, a coastal Virginia region comprising 7 cities and over 1.5 million people.
Diamond: End-to-End Forward-secure and Compact Authenticated Encryption for Internet of Things
arXiv:2601.00353v4 Announce Type: replace Abstract: Resource-constrained Internet of Things (IoT) devices, from medical implants to small drones, must transmit sensitive telemetry under adversarial wireless channels while operating under stringent computing and energy budgets. Authenticated Encryption (AE) is essential to ensure confidentiality, integrity, and authenticity. However, existing lightweight AE standards lack forward-security guarantees, compact tag aggregation, and...
BBOmix: A Tabular Benchmark for Hyperparameter Optimization of Unsupervised Biological Representation Learning
Announce Type: new Abstract: The rapid advancement of high-throughput sequencing has led to large, high-dimensional omics datasets. Deep unsupervised learning architectures, particularly Autoencoders (AEs), are increasingly used for dimensionality reduction and representation learning in this domain. However, AEs are highly sensitive to architectural choices and hyperparameters, and unsupervised optimization typically relies on reconstruction loss, which may be a poor proxy for downstream...
Diamond: End-to-End Forward-secure and Compact Authenticated Encryption for Internet of Things
arXiv:2601.00353v3 Announce Type: replace Abstract: Resource-constrained Internet of Things (IoT) devices, from medical implants to small drones, must transmit sensitive telemetry under adversarial wireless channels while operating under stringent computing and energy budgets. Authenticated Encryption (AE) is essential to ensure confidentiality, integrity, and authenticity. However, existing lightweight AE standards lack forward-security guarantees, compact tag aggregation, and...
Learning Control-Affine Reduced-Order Models via Autoencoders
Announce Type: cross Abstract: We present in this paper a framework for the identification of control-affine reduced-order models (ROMs). The proposed method utilizes autoencoders (AEs) to transform the high-dimensional states, and potentially the high-dimensional inputs, into reduced latent ones suitable for control-affine state-space dynamics. This is achieved by simultaneous training of the AE and the state-space model.
Automated Essay Scoring and Language Certification: Assessing Generalizability, Agreement and Validity for French
arXiv:2606.02009v1 Announce Type: new Abstract: In Automated Essay Scoring (AES), benchmarking practices have fostered minimalist evaluation practices, in contrast with the broader-view recommendations of evaluation frameworks, such as the argument-based validation framework (ABV), which argued in favor of a multidimensional assessment of systems, especially in the context of high-stakes language tests. In this paper, we introduce an enhanced and more practical version of the ABV framework,...
Fine-scale landscape genomics show asymmetric patterns of gene flow for the invasive mosquito Aedes albopictus
Mosquito-borne viruses like dengue, Zika, and chikungunya pose increasing health risks in the United States due to the expanding range of Aedes albopictus, a highly invasive mosquito species that now has a global distribution. Aedes albopictus thrive in artificial containers associated with anthropogenic land use, allowing populations to reach high numbers in urban and suburban environments. While the global spread of Ae.
Kim Jong Un parades teen successor daughter around naval destroyer as he reveals nuclear warship plans
Kim Jong Un parades teen successor daughter around naval destroyer as he reveals nuclear warship plans Kim Jong Un and his teenage daughter were snapped among military officials on a chilling warship days before a visit from China's Xi Jinping North Korea's Kim Jong Un has brought his teenage daughter along with him to another military visit, with the pair viewing the dictator's newest warship. His daughter Kim Ju Ae, who is believed to be 13 years old, was snapped with her dad as they...
Attention-Guided Autoencoder Fusion for Insulator Defect Detection Using UAV Transmission-Line Imaging
arXiv:2606.06536v1 Announce Type: new Abstract: Automated defect detection in high-voltage transmission-line insulators remains challenging due to severe class imbalance, large scale variation, and the small spatial extent of defect instances in Unmanned Aerial Vehicle (UAV) imagery. To address these challenges, this paper proposes AE-YOLO, an Attention-Guided AutoEncoder-Enhanced YOLO framework for robust insulator defect detection. The architecture integrates lightweight bottleneck...