Diffusion-Driven Proxy Learning Strategy with Secure Peer Interactions for Generative Intelligence in Cyber-Physical System.

Cyber-Physical System (CPS) blends computational intelligence with physical processes, which enables instant monitoring, decision-making capability, and automation services throughout various vital domains. Moreover, Generative Artificial Intelligence (AI) faces considerable barriers to deployment within CPS because distributed environments with sensitive data present serious privacy and security maintenance challenges. Current techniques, such as Federated Learning (FL), encounter difficulties both in their model diversity and the risk that privacy may be compromised.

An optimized domain-specific shrimp detection architecture integrating conditional GAN and weighted ensemble learning.

Deep learning primarily operates on images which contain hidden patterns that are quantified through pixel intensities. Deep learning is used to analyze the image patterns and to recognize the objects. The detection process includes the creation of labels with bounding boxes, and it will be evaluated by using accuracy scores.

Quantum alternating operator ansatz for the preparation and detection of long-lived singlet states in NMR.

Designing efficient and robust quantum control strategies is vital for developing quantum technologies. One recent strategy is the Quantum Alternating Operator Ansatz (QAOA) sequence that alternatively propagates under two noncommuting Hamiltonians, whose control parameters can be optimized to generate a gate or prepare a state. Here, we describe the design of a QAOA sequence to prepare long-lived singlet states (LLSs) from the thermal state in NMR.

A thermodynamic inspired AI based search algorithm for solving ordinary differential equations.

Solving Ordinary Differential Equations (ODEs) is an essential and very challenging computational problem in many areas of science and engineering like physics, biology, control system, and economics. However, traditional numerical methods such as Euler's method and the Runge-Kutta method generally suffer from problems like the grid dependency, propagation of errors and not all are applicable to nonlinear and systems that are complex. In return, metaheuristic algorithms have become promising alternatives that strongly transform the solution process into an optimization task.

New-onset conjunctivitis 3.5 years post SARS-CoV-2 infection in an inner-city population in the Bronx.

Background: A few studies have reported conjunctivitis is a complication associated with acute COVID-19. It is unknown whether SARS-CoV-2 infection increases the risk of conjunctivitis post-COVID-19 long term.

Objectives: This study investigated the incidence of new-onset conjunctivitis 3.