Online scheduling is a rapidly developed branch in scheduling theory. In this paper, we present an extensive survey for online over time scheduling on parallel-batch machines. Some open problems are proposed for further research.

/pdf/online-over-time-scheduling-on-parallel-batch-machines-a-2fhki6ofo5.pdf

Online Over Time Scheduling on Parallel-Batch Machines: A Survey

Ultrathin multifunctional electromagnetic interference shielding MXene/AgNWs/PEDOT:PSS coatings with superior electro/photo-thermal transition ability and water repellency

During the last two decades, online and semi-online scheduling problems have received considerable research interest This chapter provides definitions of several online paradigms, including online over list, online over time, and semi-online This chapter presents details of the basic online algorithms and referencing other significant results

Online and Semi-online Scheduling

In the face of increased heat dissipation requirements of high-power electronic devices, the fabrication of graphitic foil with high thermal conductivity is urgently needed. In this work, graphitic foil with the thickness ranging from 424 to 900 μm is innovatively prepared by blade coating, hot-pressing, and graphitization process through solution-derived graphene oxide (GO), employing Vitamin C (VC) as reductant and binder. VC amount is optimized, the acting mechanism of VC is clarified, and the morphology and structure evolution of GO film are extensively investigated. The results indicate that VC can mildly reduce the oxygen-containing function group of GO, and the cross-linked derivatives of VC can effectively fuse the multilayer reduced graphene oxide (rGO) films and regulate the microstructure of graphitic foil. When the VC/GO mass ratio is 1, the prepared graphitic foil with a thickness of 680 µm has the best thermal diffusion ability and mechanical strength. It has a high thermal conductivity of 1042 W m−1 K−1 and tensile strength of 42.05 MPa. The thermal diffusion ability, expressed as h × K value, reaches as high as 0.708 W K−1. This study provides a pioneering strategy for constructing advanced thermal conductive materials. 

Preparation of graphitic foil with high thermal conductivity using Vitamin C as reductant and binder

In this article, Co0.40Zn0.40Cu0.20Fe2O4 (CoZCF) nanoparticles were synthesized using sol-gel method. The Field Emission Scanning Electron Microscopy (FESEM) micrographs delineate the proper encapsulation of the soft magnetic nanoparticles inside the matrix of multi-walled carbon nanotubes (MWCNTs) and ensuring proper fabrication of the CoZCF-MWCNT nanocomposites. The X-ray Diffraction (XRD) analysis and Raman spectroscopy confirms the presence of the multi-phase nature of CoZCF-MWCNT nanocomposites. The static magnetic development of the nanocomposites as a function of temperature and the shielding effectiveness behavior in X-band and Ku-band of microwave radiation have been studied herein. Different static magnetic quantities were extracted. The magnetic observation confirms the presence of ferrimagnetic state with magnetization of 48.4 and 44.8 emu g−1 respectively at room temperature (RT) in CoZCF-MWCNT nanocomposites. The variation of hysteresis loop area with the lowering of temperature depicts the transformation of CoZCF-MWCNT nanocomposites from superparamagnetic to ferromagnetic state. The shielding effectiveness study was conducted in the X- and Ku- bands of electromagnetic radiation and the observation shows a high value of total shielding effectiveness (SET) of ∼ −31.3 dB corresponding to 10.7 GHz. This is due to the high of attenuation of > 99.9% and wide bandwidth. This improved SET of CoZCF-MWCNT nanocomposites gives us completely new insights for the construction of microwave absorber/Radar Absorbing Materials (RAMs) that can contest against harmful electromagnetic pollution.

Shielding effectiveness study of CoZCF-MWCNT nanocomposite materials and its possible application as EM pollution reducer

Online algorithms for scheduling unit length jobs on parallel-batch machines with lookahead

Carbon materials with three-dimensional (3D) conductive network draw considerable research and commercial interest due to the low density and high electrical conductivity toward electromagnetic interference (EMI) shielding. This work reported...

Reduced Graphene Oxide Layers with Full of Bubbles for Electromagnetic Interference Shielding

Channel knowledge map (CKM) emerges as a promising framework to acquire location-specific channel information without consuming wireless resources, creating new horizons for advanced wireless network design and optimization. Despite its potential, the practical application of CKM in beam training faces several challenges. On one hand, the user's precise location is typically unavailable prior to beam training, which limits the utility of CKM since its effectiveness relies heavily on accurate input of position data. On the other hand, the intricate interplay among CKM, real-time observations, and training strategies has not been thoroughly studied, leading to suboptimal performance and difficulties in practical implementation. In this paper, we present a framework for CKM-aided beam training that addresses these limitations. For single-user scenario, we propose a reward-motivated beam-potential hierarchical strategy which integrates partial position information and CKM. This strategy models the user equipment (UE) position uncertainty and formulates the hierarchical searching process as a pruned binary search tree. An optimal hierarchical searching strategy with minimal overhead is derived by evaluating the weights and rewards of potential codewords. Furthermore, a low-complexity two-layer lookahead scheme is designed to balance overhead and computational demands. For multi-user scenario, we develop a correlation-driven position-pruning training scheme, where sidelobe gains from inter-user interference are exploited to provide additional side information for overhead reduction, allowing all users to be simultaneously assigned their respective supportive beams. Simulations validate the superior performances of proposed approaches in advancing 6G beam training.

https://export.arxiv.org/pdf/2511.22902v1.pdf

Leveraging Channel Knowledge Map for Multi-User Hierarchical Beam Training Under Position Uncertainty

This paper investigates the capacity region of the optical intensity broadcast channels (OI-BCs), where the input is subject to a peak-intensity constraint, an average-intensity constraint, or both. By leveraging the decomposition results of several random variables, i.e., uniform, exponential, and truncated exponential random variables, and adopting a superposition coding (SC) scheme, the inner bound on the capacity region is derived. Then, the outer bound is derived by applying the conditional entropy power inequality (EPI). In the high signal-to-noise ratio (SNR) regime, the inner bound asymptotically matches the outer bound, thus characterizing the high-SNR asymptotic capacity region. The bounds are also extended to the general K-user BCs without loss of high-SNR asymptotic optimality.

pdf/on-the-capacity-region-of-optical-intensity-broadcast-1c12rd78.pdf

On the Capacity Region of Optical Intensity Broadcast Channels

This paper proposes new upper bounds on the capacity of multiple-antenna optical intensity channels based on a sphere-packing method. The inputs of this channel are subject to peak- or/and average-power constraints. For the multiple-input multiple-output (MIMO) channel constrained by the peak power, we use a hyperellipsoid to approximate the volume of the output space and derive the capacity bounds. For the multiple-input single-output (MISO) channel constrained by the peak and average power, we first transform it into a scalar channel and then adopt a similar process to derive the capacity bounds. The derived bounds give good approximations of channel capacity.

Upper Bounds on the Capacity of Multiple-Antenna Optical Intensity Channels: A Sphere-Packing Perspective

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