Horizon-unbiased Investment with Ambiguity

In the presence of ambiguity on the driving force of market randomness, we consider the dynamic portfolio choice without any predetermined investment horizon. The investment criteria is formulated as a robust forward performance process, reflecting an investor's dynamic preference. We show that the market risk premium and the utility risk premium jointly determine the investors' trading direction and the worst-case scenarios of the risky asset's mean return and volatility. The closed-form formulas for the optimal investment strategies are given in the special settings of the CRRA preference

Efficient computation of the optimal strikes in the comonotonic upper bound for an arithmetic Asian option

In this paper, an efficient method is proposed which accelerates the computation of the optimal strikes in the comonotonic upper bound for the value of an arithmetic Asian option. Numerical applications are carried out in the setting of Heston's model, in which the distribution function of the underlying asset price is not available in closed form. These numerical results highlight the efficiency of the proposed method

CamoDiffusion: Camouflaged Object Detection via Conditional Diffusion Models

Camouflaged Object Detection (COD) is a challenging task in computer vision due to the high similarity between camouflaged objects and their surroundings. Existing COD methods primarily employ semantic segmentation, which suffers from overconfident incorrect predictions. In this paper, we propose a new paradigm that treats COD as a conditional mask-generation task leveraging diffusion models. Our method, dubbed CamoDiffusion, employs the denoising process of diffusion models to iteratively reduce the noise of the mask. Due to the stochastic sampling process of diffusion, our model is capable of sampling multiple possible predictions from the mask distribution, avoiding the problem of overconfident point estimation. Moreover, we develop specialized learning strategies that include an innovative ensemble approach for generating robust predictions and tailored forward diffusion methods for efficient training, specifically for the COD task. Extensive experiments on three COD datasets attest the superior performance of our model compared to existing state-of-the-art methods, particularly on the most challenging COD10K dataset, where our approach achieves 0.019 in terms of MAE

Improving the wind‐induced human comfort of the Beijing Olympic Tower by a double‐stage pendulum tuned mass damper

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154522/1/tal1704_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154522/2/tal1704.pd

PHOTOMETRIC OBSERVATION OF 3024 HAINAN, 3920 AUBIGNAN, AND 5951 ALICEMONET

Three minor planets were measured photometrically between 2012 September 4 and 21 using the SARA (Southeastern Association for Research in Astronomy) South telescope, located in Cerro Tololo Inter-American Observatory. The following synodic periods were found: 3024 Hainan, P = 11.785 ± 0.005 h; 3920 Aubignan, P = 4.4762 ± 0.0005 h; and 5951 Alicemonet, P = 3.8871 ± 0.0005 h