Hasil untuk "Men"

Robert M. Grant, Robert M. Grant, Robert M. Grant et al.

D. Bliuc, N. Nguyen, V. Milch et al.

S. Blair, H. Kohl, C. Barlow et al.

R. Jessop

R. Paffenbarger, R. T. Hyde, A. Wing et al.

Tuart, C. M., Obbe et al.

E. Beller

J. R. Center, T. Nguyễn, D. Schneider et al.

S. Murray

E. Arendt, R. Dick

M. Keane, K. Wolpin

This paper provides structural estimates of a dynamic model of schooling, work, and occupational choice decisions based on 11 years of observations on a sample of young men from the 1979 youth cohort of the National Longitudinal Surveys of Labor Market Experience (NLSY). The structural estimation framework that we adopt fully imposes the restrictions of the theory and permits an investigation of whether such a theoretically restricted model can succeed in quantitatively fitting the observed data patterns. We find that a suitably extended human capital investment model can in fact do an excellent job of fitting observed data on school attendance, work, occupational choices, and wages in the NLSY data on young men and also produces reasonable forecasts of future work decisions and wage patterns.

P. Galdas, F. Cheater, P. Marshall

T. Pischon, C. Girman, G. Hotamisligil et al.

M. Klag, P. Whelton, Bryan L. Randall et al.

A. Burke, A. Farb, G. Malcom et al.

J. Salmerón, A. Ascherio, E. Rimm et al.

Peter J Snyder, S. Bhasin, G. R. Cunningham et al.

M. Alsan, Marianne H. Wanamaker

Meiwen Men, Tao Zhou, Kaifeng Bao et al.

Orthogonal time frequency space (OTFS) modulation is a robust candidate waveform for future wireless systems, particularly in high-mobility scenarios, as it effectively mitigates the impact of rapidly time-varying channels by mapping symbols in the delay-Doppler (DD) domain. However, accurate frame synchronization in OTFS systems remains a challenge due to the performance limitations of conventional algorithms. To address this, we propose a low-complexity synchronization method based on a coarse-to-fine deep residual network (ResNet) architecture. Unlike traditional approaches relying on high-overhead preamble structures, our method exploits the intrinsic periodic features of OTFS pilots in the delay-time (DT) domain to formulate synchronization as a hierarchical classification problem. Specifically, the proposed architecture employs a two-stage strategy to first narrow the search space and then pinpoint the precise symbol timing offset (STO), thereby significantly reducing computational complexity while maintaining high estimation accuracy. We construct a comprehensive simulation dataset incorporating diverse channel models and randomized STO to validate the method. Extensive simulation results demonstrate that the proposed method achieves robust signal start detection and superior accuracy compared to conventional benchmarks, particularly in low signal-to-noise ratio (SNR) regimes and high-mobility scenarios.

Jingxuan Men, Mahdi Boloursaz Mashhadi, Ning Wang et al.

Token Communication (TokenCom) is a new paradigm, motivated by the recent success of Large AI Models (LAMs) and Multimodal Large Language Models (MLLMs), where tokens serve as unified units of communication and computation, enabling efficient semantic- and goal-oriented information exchange in future wireless networks. In this paper, we propose a novel Video TokenCom framework for textual intent-guided multi-rate video communication with Unequal Error Protection (UEP)-based source-channel coding adaptation. The proposed framework integrates user-intended textual descriptions with discrete video tokenization and unequal error protection to enhance semantic fidelity under restrictive bandwidth constraints. First, discrete video tokens are extracted through a pretrained video tokenizer, while text-conditioned vision-language modeling and optical-flow propagation are jointly used to identify tokens that correspond to user-intended semantics across space and time. Next, we introduce a semantic-aware multi-rate bit-allocation strategy, in which tokens highly related to the user intent are encoded using full codebook precision, whereas non-intended tokens are represented through reduced codebook precision differential encoding, enabling rate savings while preserving semantic quality. Finally, a source and channel coding adaptation scheme is developed to adapt bit allocation and channel coding to varying resources and link conditions. Experiments on various video datasets demonstrate that the proposed framework outperforms both conventional and semantic communication baselines, in perceptual and semantic quality on a wide SNR range.