Cross-model face recognition poses a major challenge due to inconsistent embeddings produced by diverse face recognition models, limiting system interoperability. Enhancing compatibility among these models is essential for scalable, maintainable face recognition systems. This paper presents the Kolmogorov-Arnold Guided Alignment (KAGA) model, optimized with Mutual Decoupled Distillation (MDD), to effectively bridge embedding discrepancies. KAGA integrates a cross-attention mechanism and a learnable Guided Alignment Embedding to unify feature spaces, while Kolmogorov-Arnold Networks ensure robustness of the transformation. MDD facilitates selective knowledge transfer without compromising class separability, and bidirectional distillation refines feature representations for improved generalization. Extensive experiments across multiple face recognition benchmarks confirm KAGA's effectiveness, demonstrating substantial gains in accuracy and cross-model compatibility compared to state-of-the-art approaches.

We perform an in-depth analysis on the energy efficiency of a mobile robot employing a spherical type continuously variable transmission (S-CVT). The S-CVT permits the motor to operate in its most power-efficient regime of high-speed and low-torque, and allows for smooth operation of the mobile robot in all phases of forward, neutral, and reverse motion without the use of any brakes or clutches. Changes in steering direction are achieved by a novel pivoting device that enables the robot to rotate about its center. The current study takes into account features of the DC motors, the S-CVT, and the mobile robot dynamics to perform a comprehensive study on the overall system performance. We develop optimal control laws for both the reduction gear unit and S-CVT equipped mobile robots, and compare their energy efficiency through numerical studies. We then present numerical results that demonstrate the power savings possible front the use of the S-CVT mechanism over standard reduction gear units.

Introduces the design and analysis of a type of wheeled mobile robot that uses a spherical continuously variable transmission (S-CVT) element. The S-CVT is composed of a sphere, input and output discs, and variators, and power transmission is based on the friction force between the discs and the sphere. Use of the S-CVT allows for smooth operation of the mobile robot over all phases of forward, neutral, and reverse motion without the use of any brakes or clutches. The S-CVT also permits the motors to operate in their most power-efficient regimes. Motion in the plane, including pure rotation about its center is achieved by a novel pivoting device that eliminates the need for an actuated steering wheel, or an additional motor for differentiating the wheel velocities. We describe the conceptual principle behind our CVT-based mobile robot, and present a complete design and analysis of its capabilities based on a prototype currently under construction.