Emmanouil Papadakis

Nikolaos I. Miridakis, Dimitrios D. Vergados, Emmanouil Papadakis

In this letter, following a cross-layer design concept, we propose a novel subcarrier grouping technique for Orthogonal Frequency and Code Division Multiplexing (OFCDM) multiuser systems. We adopt a two dimensional (2D) spreading, so as to achieve both frequency- and time-domain channel gain. Furthermore, we enable a receiver-centric approach, where the receiver rather than a potential sender controls the admission decision of the communication establishment. We study the robustness of the proposed scheme in terms of the Bit-Error-Rate (BER) and the outage probability. The derived results indicate that the proposed scheme outperforms the classical OFCDM approach.

Rajiv Kailasanathan, William R. Clements, Mohammad Reza Boskabadi et al.

The development of continuous biomanufacturing processes requires robust and early anomaly detection, since even minor deviations can compromise yield and stability, leading to disruptions in scheduling, reduced weekly production, and diminished economic performance. These processes are inherently complex and exhibit non-linear dynamics with intricate relationships between process variables, thus making advanced methods for anomaly detection essential for efficient operation. In this work, we present a novel framework for unsupervised anomaly detection in continuous biomanufacturing based on an ensemble of generative adversarial networks (GANs). We first establish a benchmark dataset simulating both normal and anomalous operation regimes in a continuous process for the production of a small molecule. We then demonstrate the effectiveness of our GAN-based framework in detecting anomalies caused by sudden feedstock variability. Finally, we evaluate the impact of using a hybrid quantum/classical GAN approach with both a simulated quantum circuit and a real photonic quantum processor on anomaly detection performance. We find that the hybrid approach yields improved anomaly detection rates. Our work shows the potential of hybrid quantum/classical approaches for solving real-world problems in complex continuous biomanufacturing processes.