Minimizing Maximum Weighted Error for Imprecise Computation Tasks

We consider the problem of preemptively scheduling a set of imprecise computation tasks on m ≥ 1 identical processors, with each task T_i having two weights, w_i and w′_i. Two performance metrics are considered: (1) the maximum w′-weighted error; (2) the total w-weighted error subject to the constraint that the maximum w′-weighted error is minimized. For the problem of minimizing the maximum w′-weighted error, we give an algorithm which runs in O(n³ log²n) time for multiprocessors and O(n²) time for a single processor. For the problem of minimizing the total w-weighted error subject to the constraint that the maximum w′-weighted error is minimized, we give an algorithm which also has the same time complexity.     

Generation of 0.2-TW 5.5-fs optical pulses at 1 kHz using a differentially pumped hollow-fiber chirped-mirror compressor

Optical pulses with 1.1-mJ energy and 5.5-fs duration have been generated at 1-kHz repetition rate from a chirped pulse amplification Ti:Sapphire laser incorporating a differentially pumped hollow-fiber chirped-mirror compressor. The effects of self-focusing and multi-photon ionization during the beam propagation were minimized by differentially pumping the hollow fiber filled with neon. The spectral broadening at the hollow-fiber compressor was optimized by adjusting gas pressure, laser intensity, and laser chirp, covering from 540 nm to 950 nm. PACS 42.65.Jx; 42.65.Re     

Synthesis of poly-substituted nitrobenzene derivatives from Baylis-Hillman adducts via [3+3] annulation protocol

Poly-substituted nitrobenzenes were synthesized from Baylis-Hillman adducts via the [3+3] annulation strategy as the key step. 1,3-Dinitroalkanes served as the 1,3-dinucleophilic component and the Baylis-Hillman acetates as a 1,3-dielectrophilic part.     

A parametric representation of linguistic hedges in Zadeh’s fuzzy logic

This paper proposes a model for the parametric representation of linguistic hedges in Zadeh’s fuzzy logic. In this model each linguistic truth-value, which is generated from a primary term of the linguistic truth variable, is identified by a real number r depending on the primary term. It is shown that the model yields a method of efficiently computing linguistic truth expressions accompanied with a rich algebraic structure of the linguistic truth domain, namely De Morgan algebra. Also, a fuzzy logic based on the parametric representation of linguistic truth-values is introduced.     

Cellulose dimethylphenylcarbamate-bonded carbon-clad zirconia for chiral separation in high performance liquid chromatography.

Porous zirconia particles are very robust material and have received considerable attention as a stationary phase support for HPLC. We prepared cellulose dimethylphenylcarbamate-bonded carbon-clad zirconia (CDMPCCZ) as a chiral stationary phase (CSP) for separation of enantiomers of a set of 14 racemic compounds in normal phase (NP) and reversed-phase (RP) liquid chromatography. Retention and enantioselectivity on CDMPCCZ were compared to those on CDMPC-coated zirconia (CDMPCZ) to see how the change in immobilization method of the chiral selector affects the retention and chiral selectivity. In NPLC, retention was longer and the number of resolved racemates was smaller on CDMPCCZ than on CDMPCZ. However, chiral selectivity factors for some resolved racemates were better on CDMPCCZ than on CDMPCZ. The longer retention on CDMPCCZ is likely due to strong, non-chiral discriminating interactions with the carbon layer on CDMPCZ. In RPLC only two racemates were resolved on CDMPCCZ, but retention times were shorter than, and resolutions were comparable to, those in NPLC, indicating a potential for improving chromatographic performance of the CDMPCCZ column in RPLC with optimized column preparation and separation conditions.     

Phase transformation of Ni-B, Ni-P diffusion barrier deposited electrolessly on Cu interconnect

In this paper, we report that the phase transformation of Ni-B, Ni-P diffusion barriers deposited electrolessly on Cu, for the reason that the Ni-P layer is a more effective diffusion barrier than the Ni-B layer. The Ni₃B crystallized was decomposed to Ni and B₂O₃ above 400 °C and the Ni₃P crystallized was decomposed to Ni and P₂O₅ above 600 °C respectively in Ar atmosphere. Also, the Ni₃B was decomposed to Ni and free B above 400 °C and the Ni₃P was decomposed to Ni and free P above 600 °C respectively in H₂ atmosphere. The decomposed Ni formed a solid solution with Cu. The Cu diffusion occurred above 400 °C for Ni-B layer and above 600 °C for Ni-P layer, respectively. Because the decomposition temperature of Ni-P layer is about 200 °C higher than that of Ni-B layer, the Ni-P layer is a more effective barrier for Cu than the Ni-B layer.     

Temperature effect on deposition rate of silicon nitride films

Temperature effects on deposition rate of silicon nitride films were characterized by building a neural network prediction model. The silicon nitride films were deposited by using a plasma enhanced chemical vapor deposition system and process parameter effects were systematically characterized by 2⁶⁻¹ fractional factorial experiment. The process parameters involved include a radio frequency power, pressure, temperature, SiH₄, N₂, and NH₃ flow rates. The prediction performance of generalized regression neural network was drastically improved by optimizing multi-valued training factors using a genetic algorithm. Several 3D plots were generated to investigate parameter effects at various temperatures. Predicted variations were experimentally validated. The temperature effect on the deposition rate was a complex function of parameters but N₂ flow rate. Larger decreases in the deposition rate with the temperature were only noticed at lower SiH₄ (or higher NH₃) flow rates. Typical effects of SiH₄ or NH₃ flow rate were only observed at higher or lower temperatures. A comparison with the refractive index model facilitated a selective choice of either SiH₄ or NH₃ for process optimization.     

Synchronization of Genesio chaotic system via backstepping approach

Backstepping design is proposed for synchronization of Genesio chaotic system. Firstly, the control problem for the chaos synchronization of nominal Genesio systems without unknown parameters is considered. Next, an adaptive backstepping control law is derived to make the error signals between drive Genesio system and response Genesio system with an uncertain parameter asymptotically synchronized. Finally, the approach is extended to the synchronization problem for the system with three unknown parameters. The stability analysis in this article is proved by using a well-known Lyapunov stability theorem. Note that the approach provided here needs only a single controller to realize the synchronization. Two numerical simulations are presented to show the effectiveness of the proposed chaos synchronization scheme.     

In situ observations of domain wall motion in Mn–Zn and Ni–Zn ferrites by Lorentz microscopy and electron holography

Domain wall motion in Mn–Zn and Ni–Zn ferrites with applied magnetic fields is investigated by in situ observations with Lorentz microscopy and electron holography. It is found that both Mn–Zn and Ni–Zn ferrites have a mean grain size of approximately 10 μm and several pores with sizes ranging from 0.2 to 1.1 μm. In situ observations by Lorentz microscopy with an applied magnetic field reveals that in Mn–Zn ferrite, the domain walls move easily across the grain boundary, while in Ni–Zn ferrite, the domain walls move along the grain boundary but are pinned at the grain boundary and pores. From in situ observations of Ni–Zn ferrite by electron holography, it is clarified that domain wall pinning at the grain boundary retards a sensitive increase in magnetic flux parallel to the applied field direction, which is considered to result in high hysteresis loss.