A Predictive-reactive Approach for JSP with Uncertain Processing Times

The paper is supported by the Asia-Link project funded by the European Commission (CN/ASIA-LINK/024 (109093)), the National Natural Science Foundation of China (50705076, 50705077), and the National Hi-Tech R&D Program of China (2007AA04Z187)JSP with discretely controllable processing times (JSP-DCPT) that are perturbed in a turbulent environment is formulated, based on which, a time-cost tradeoff based predictive-reactive scheduling approach is proposed for solving the problem. In the predictive scheduling process, on the basis of a proposed three-step decomposition approach for solving JSP-DCPT, a solution initialization algorithm is presented by incorporating a hybrid algorithm of tabu search and simulated annealing and a fast elitist non-dominated sorting genetic algorithm; in the reactive scheduling process, Pareto-optimal schedules are generated, among which every schedule that is not dominated by any initial schedule can be selected as the responding schedule so as to maintain optimality of the objective that is to minimize both the makespan and the cost. Experimental simulations demonstrate the effectiveness of the proposed approach

Regulation, Targets and Functions of CHK

Src family kinases (SFKs) play pivotal roles in multiple signaling pathways (Yeatman, 2004). SFK activity is inhibited by phosphorylation at its C-terminal tyrosine, by CSK (C-terminal Src kinase) and CHK (CSK-homologous kinase). CHK expression is restricted to normal hematopoietic cells, brain, and colon tissues. Downregulation of CHK in brain and colon tumors contributes to tumorigenicity in these tissues. CHK does not phosphorylate Src efficiently, however, in contrast to CSK, CHK inhibits Src kinase activity allosterically. Although the functions of CHK are still largely unknown, potential substrates of CHK including β-synuclein, α-tubulin, α-spectrin, 14-3-3, and Hsp90 have been identified. CHK is regulated epigenetically via promoter methylation. As the unknown roles of CHK are beginning to be revealed, current knowledge of regulation, molecular targets and functions of CHK is summarized, and important topics for future CHK research are discussed

Numerical Fitting-based Likelihood Calculation to Speed up the Particle Filter

The likelihood calculation of a vast number of particles is the computational bottleneck for the particle filter in applications where the observation information is rich. For fast computing the likelihood of particles, a numerical fitting approach is proposed to construct the Likelihood Probability Density Function (Li-PDF) by using a comparably small number of so-called fulcrums. The likelihood of particles is thereby analytically inferred, explicitly or implicitly, based on the Li-PDF instead of directly computed by utilizing the observation, which can significantly reduce the computation and enables real time filtering. The proposed approach guarantees the estimation quality when an appropriate fitting function and properly distributed fulcrums are used. The details for construction of the fitting function and fulcrums are addressed respectively in detail. In particular, to deal with multivariate fitting, the nonparametric kernel density estimator is presented which is flexible and convenient for implicit Li-PDF implementation. Simulation comparison with a variety of existing approaches on a benchmark 1-dimensional model and multi-dimensional robot localization and visual tracking demonstrate the validity of our approach.Comment: 42 pages, 17 figures, 4 tables and 1 appendix. This paper is a draft/preprint of one paper submitted to the IEEE Transaction

A Predictive-reactive Approach for JSP with Uncertain Processing Times

The paper is supported by the Asia-Link project funded by the European Commission (CN/ASIA-LINK/024 (109093)), the National Natural Science Foundation of China (50705076, 50705077), and the National Hi-Tech R&D Program of China (2007AA04Z187)International audienceJSP with discretely controllable processing times (JSP-DCPT) that are perturbed in a turbulent environment is formulated, based on which, a time-cost tradeoff based predictive-reactive scheduling approach is proposed for solving the problem. In the predictive scheduling process, on the basis of a proposed three-step decomposition approach for solving JSP-DCPT, a solution initialization algorithm is presented by incorporating a hybrid algorithm of tabu search and simulated annealing and a fast elitist non-dominated sorting genetic algorithm; in the reactive scheduling process, Pareto-optimal schedules are generated, among which every schedule that is not dominated by any initial schedule can be selected as the responding schedule so as to maintain optimality of the objective that is to minimize both the makespan and the cost. Experimental simulations demonstrate the effectiveness of the proposed approach

A Survey of Recent Advances in Particle Filters and Remaining Challenges for Multitarget Tracking

[EN]We review some advances of the particle filtering (PF) algorithm that have been achieved in the last decade in the context of target tracking, with regard to either a single target or multiple targets in the presence of false or missing data. The first part of our review is on remarkable achievements that have been made for the single-target PF from several aspects including importance proposal, computing efficiency, particle degeneracy/impoverishment and constrained/multi-modal systems. The second part of our review is on analyzing the intractable challenges raised within the general multitarget (multi-sensor) tracking due to random target birth and termination, false alarm, misdetection, measurement-to-track (M2T) uncertainty and track uncertainty. The mainstream multitarget PF approaches consist of two main classes, one based on M2T association approaches and the other not such as the finite set statistics-based PF. In either case, significant challenges remain due to unknown tracking scenarios and integrated tracking management

The Ratio of Sunflower Pollens Foraged by Apis mellifera Is More Than That of Apis cerana Does During Sunflower Blooming

Bias foraging of pollen is general in different pollinators since various nutrition demanding, co-evolution and interaction of insect-plant. To clarify the preference of pollen foraging during sunflower blooming, the pollen foraging behaviors of Apis mellifera Linnaeus and Apis cerana Fabricius were observed. Our results displayed that two summits of pollen foraging occurred in the morning before the ambient temperature climbed up to thirty-one degree centigrade and in the afternoon after the ambient temperature decreased below thirty-one degree centigrade, respectively. Notably, the first foraging summit of Apis cerana emerged one hour earlier than that of Apis mellifera. These results imply that Apis mellifera is less resistant to low temperature but more resistant to high temperature than Apis cerana does. The colonies were surrounded by sunflowers with sporadic weeds, while only few maize dispersed over two hundred meters away. However, no more than forty percent of total pollens foraged by Apis mellifera was from sunflower, and which was no more than twenty percent in Apis cerana group. These results suggest that sunflower pollens are not the prior choice for both honey bee species, while the ratio of sunflower pollens foraged by Apis mellifera is more than that of Apis cerana does