Top-view fisheye cameras are widely used in personnel surveillance for their broad field of view, but their unique imaging characteristics pose challenges like distortion, complex scenes,scale variations, and small objects near image edges. To tackle these, we proposed peripheral focus you only look once(PF-YOLO), an enhanced YOLOv8n-based method. Firstly, we introduced a cutting-patch data augmentation strategy to mitigate the problem of insufficient small-object samples in various scenes. Secondly, to enhance the model's focus on small objects near the edges, we designed the peripheral focus loss, which uses dynamic focus coefficients to provide greater gradient gains for these objects, improving their regression accuracy. Finally, we designed the three dimensional(3D) spatial-channel coordinate attention C2f module, enhancing spatial and channel perception, suppressing noise, and improving personnel detection. Experimental results demonstrate that PF-YOLO achieves strong performance on the challenging events for person detection from overhead fisheye images(CEPDTOF) and in-the-wild events for people detection and tracking from overhead fisheye cameras(WEPDTOF) datasets. Compared to the original YOLOv8n model, PFYOLO achieves improvements on CEPDTOF with increases of 2.1%, 1.7% and 2.9% in mean average precision 50(mAP 50), mAP 50-95, and tively. On WEPDTOF, PF-YOLO achieves substantial improvements with increases of 31.4%,14.9%, 61.1% and 21.0% in 91.2% and 57.2%, respectively.
With the rapid growth of connected devices, traditional edge-cloud systems are under overload pressure. Using mobile edge computing(MEC) to assist unmanned aerial vehicles(UAVs)as low altitude platform stations(LAPS) for communication and computation to build air-ground integrated networks(AGINs) offers a promising solution for seamless network coverage of remote internet of things(IoT) devices in the future. To address the performance demands of future mobile devices(MDs), we proposed an MEC-assisted AGIN system. The goal is to minimize the long-term computational overhead of MDs by jointly optimizing transmission power, flight trajectories, resource allocation, and offloading ratios, while utilizing non-orthogonal multiple access(NOMA) to improve device connectivity of large-scale MDs and spectral efficiency. We first designed an adaptive clustering scheme based on K-Means to cluster MDs and established communication links, improving efficiency and load balancing. Then, considering system dynamics, we introduced a partial computation offloading algorithm based on multi-agent deep deterministic policy gradient(MADDPG), modeling the multi-UAV computation offloading problem as a Markov decision process(MDP). This algorithm optimizes resource allocation through centralized training and distributed execution, reducing computational overhead. Simulation results show that the proposed algorithm not only converges stably but also outperforms other benchmark algorithms in handling complex scenarios with multiple devices.
Poly(m-phenylene isophthalamide)(PMIA), a key aromatic polyamide, is widely used for its outstanding mechanical strength, high thermal stability, and excellent insulation properties.However, different applications demand varying dielectric properties, so tailoring its dielectric performance is essential. PMIA was first synthesized in this study, followed by introducing pores and developing porous PMIA films and PMIA-based composites with reduced dielectric constants.Porous PMIA films were fabricated using the wet phase inversion process with N, N-dimethylacetamide(DMAC) solvent and water as the non-solvent. The impact of casting solution composition and coagulation bath temperature on pore structures was analyzed. A film produced with 18%PMIA and 5% LiCl in a 35 ℃ coagulation bath achieved the lowest dielectric constant of 1.76 at 1 Hz, 48% lower than the standard PMIA film, which had a tensile strength of 18.5 MPa and an initial degradation temperature of 320 ℃.
With the progression of photolithography processes, the present technology nodes have attained 3 nm and even 2 nm, necessitating a transition in the precision standards for displacement measurement and alignment methodologies from the nanometer scale to the sub-nanometer scale.Metasurfaces, owing to their superior light field manipulation capabilities, exhibit significant promise in the domains of displacement measurement and positioning, and are anticipated to be applied in the advanced alignment systems of lithography machines. This paper primarily provides an overview of the contemporary alignment and precise displacement measurement technologies employed in photolithography stages, alongside the operational principles of metasurfaces in the context of precise displacement measurement and alignment. Furthermore, it explores the evolution of metasurface systems capable of achieving nano/sub-nano precision, and identifies the critical issues associated with sub-nanometer measurements using metasurfaces, as well as the principal obstacles encountered in their implementation within photolithography stages. The objective is to provide initial guidance for the advancement of photolithography technology.
The integrated waveguide polarizer is essential for photonic integrated circuits, and various designs of waveguide polarizers have been developed. As the demand for dense photonic integration increases rapidly, new strategies to minimize the device size are needed. In this paper, we have inversely designed an integrated transverse electric pass(TE-pass) polarizer with a footprint of 2.88 μm× 2.88 μm, which is the smallest footprint ever achieved. A direct binary search algorithm is used to inversely design the device for maximizing the transverse electric(TE) transmission while minimizing transverse magnetic(TM) transmission. Finally, the inverse-designed device provides an average insertion loss of 0.99 dB and an average extinction ratio of 33 dB over a wavelength range of 100 nm.
