Borgklausen9088

This paper investigates single machine scheduling problems where the actual processing time of a job is dependent on its starting time, processing position and the amount of resource allocation. We present two unified models and provide a bicriteria analysis for the general scheduling criteria and the total weighted resource consumption. We consider two different versions for treating the two criteria and show that the unified models can be applied to solve scheduling problems under various due window assignment considerations. We prove that two different versions of the problems can be solved in polynomial time, respectively.The balance between exploration and exploitation is critical to the performance of a Meta-heuristic optimization method. At different stages, a proper tradeoff between exploration and exploitation can drive the search process towards better performance. This paper develops a multi-objective grasshopper optimization algorithm (MOGOA) with a new proposed framework called the Multi-group and Co-evolution Framework which can archive a fine balance between exploration and exploitation. For the purpose, a grouping mechanism and a co-evolution mechanism are designed and integrated into the framework for ameliorating the convergence and the diversity of multi-objective optimization solutions and keeping the exploration and exploitation of swarm intelligence algorithm in balance. The grouping mechanism is employed to improve the diversity of search agents for increasing coverage of search space. The co-evolution mechanism is used to improve the convergence to the true Pareto optimal front by the interaction of search agents. Quantitative and qualitative outcomes prove that the framework prominently ameliorate the convergence accuracy and convergence speed of MOGOA. The performance of the presented algorithm has been benchmarked by several standard test functions, such as CEC2009, ZDT and DTLZ. The diversity and convergence of the obtained multi-objective optimization solutions are quantitatively and qualitatively compared with the original MOGOA by using two performance indicators (GD and IGD). The results on test suits show that the diversity and convergence of the obtained solutions are significantly improved. On several test functions, some statistical indicators are more than doubled. The validity of the results has been verified by the Wilcoxon rank-sum test.In this paper, a stage-structured jellyfish model with two time delays is formulated and analyzed, the first delay represents the time from the asexually reproduced young polyp to the mature polyp and the second denotes the time from the developed polyp to ephyra (incipient medusa). Global dynamics of the model are obtained via monotone dynamical theory the jellyfish populations go extinct and the trivial equilibrium is globally asymptotically stable if the survival rate of polyp during cloning and the survival rate of the incipient medusa during strobilation are less than their death rates. And if the survival rate of polyp during cloning and the survival rate of the incipient medusa during strobilation are larger than their death rates, a unique positive equilibrium is globally asymptotically stable. Moreover, it is proved that the only stage of polyps will continue without growing into medusa and the boundary equilibrium is globally asymptotically stable if the survival rate of polyp is larger than its death rate during cloning and if there is no survival of the incipient medusa. Numerical simulations are performed to verify our analytical results and to explore the dynamics with/without delays.The stability of the moisture content of the cigarette is an important index to evaluate the quality of the cigarette. The cooling moisture content after cut tobacco drying process is a key factor affecting the stability of the moisture content of the cigarette. In order to realize its accurate prediction and ensure the stability, in Honghe cigarette factory, a cooling moisture content prediction model is built based on a particle swarm optimization-extreme learning machine (PSO-ELM) algorithm via the historical production data. Besides, the proposed PSO-ELM algorithm is also compared with multiple linear regression (MLR), support vector machine (SVM) and the traditional extreme learning machine (ELM) algorithms in the same data set on the prediction. The prediction accuracy of PSO-ELM method is the highest and the average error of the prediction standard is the lowest. The results indicated the proposed method can achieve a better prediction performance over compared methods and it provides a new method to realize the prediction of the cooling moisture content after cut tobacco drying process.A (k,n) threshold secret image sharing (SIS) scheme divides a secret image into n shadows. One can reconstruct the secret image only when holding k or more than k shadows but cannot know any information on the secret from fewer than k shadows. Based on this characteristic, SIS has been widely used in access control, information hiding, distributed storage and other areas. Verifiable SIS aims to prevent malicious behaviour by attackers through verifying the authenticity of shadows and previous works did not solve this problem well. Our contribution is that we proposed a verifiable SIS scheme which combined CRT-based SIS and (2,n+1) threshold visual secret sharing(VSS). Our scheme is applicable no matter whether there exists a third party dealer. And it is worth mentioning that when the dealer is involved, our scheme can not only detect fake participants, but also locate dishonest participants. In general, loose screening criterion and efficient encoding and decoding rate of CRT-based SIS guarantee high-efficiency shadows generation and low recovery computation complexity. The uncertainty of the bits used for screening prevents malicious behavior by dishonest participants. In addition, our scheme has the advantages of lossless recovery, no pixel expansion and precise detection.Understanding light propagation in skin tissues with complex blood vessels can help improve clinical efficacy in the laser treatment of cutaneous vascular lesions. The voxel-based Monte Carlo (VMC) algorithm with simple blood vessel geometry is commonly used in studying the law of light propagation in tissues. However, unavoidable errors are expected in VMC because of the zigzag polygonal interface. A tetrahedron-based Monte Carlo with extended boundary condition (TMCE) solver is developed to discretize complex tissue boundaries accurately. Tetrahedra are generated along the interface, resulting in a polyhedron approximation to match the real interface. A comparison between TMCE and VMC shows neglected differences in the overall distribution of energy deposition of different models, but poor adaptability of the curved tissue interface in VMC leads to a higher energy deposition error than TMCE in a mostly deposited region in blood vessels. Replacing the real blood vessel with a cylinder-shaped vessel shows an error lower than that caused by VMC. Statistical significance analysis of energy deposition by TMCE shows that mean curvature has stronger relationship with energy deposition than the Gaussian curvature, which indicates the importance of this geometric parameter in predicting photon behavior in vascular lesions.We studied the effects of the aspheric transition zone on the optical wavefront aberrations, corneal surface displacement, and stress induced by the biomechanical properties of the cornea after conventional laser in situ keratomileusis (LASIK) refractive surgery. The findings in this study can help improve visual quality after refractive surgery. Hyperopia correction in 1-5D was simulated using five types of aspheric transition zones with finite element modeling. The algorithm for the simulations was designed according to the optical path difference. Wavefront aberrations were calculated from the displacements on the anterior and posterior corneal surfaces. The vertex displacements and stress on the corneal surface were also evaluated. The results showed that the aspheric transition zone has an effect on the postoperative visual quality. The main wavefront aberrations on the anterior corneal surface are defocus, y-primary astigmatism, x-coma, and spherical aberrations. The wavefront aberrations on the corneal posterior surface were relatively small and vertex displacements on the posterior corneal surface were not significantly affected by the aspheric transition zone. Stress analysis revealed that the stress on the cutting edge of the anterior corneal surface decreased with the number of aspheric transition zone increased, and profile #1 resulted in the maximum stress. The stress on the posterior surface of the cornea was more concentrated in the central region and was less than that on the anterior corneal surface overall. The results showed that the aspheric transition zone has an effect on postoperative aberrations, but wavefront aberrations cannot be eliminated. In addition, the aspheric transition zone influences the postoperative biomechanical properties of the cornea, which significantly affect the postoperative visual quality.Differential evolution (DE) is one of the most successful evolutionary algorithms. However, the performance of DE is significantly influenced by its mutation strategies. Generally, different mutation strategies may obtain different search directions. The improper search direction misleads the search and results in the poor performance of DE. Therefore, it is vital to consider the search direction when designing new mutation strategies. Based on this consideration, in this paper, the quasi-reflection-based mutation is proposed to enhance the performance of DE. The quasi-reflection-based mutation is able to provide the promising search direction to guide the search. To extensively evaluate the performance of our approach, 30 benchmark functions are chosen as the test suite. Combined with SHADE, Re-SHADE is presented. Compared with different advanced DE methods, Re-SHADE can obtain better results in terms of the accuracy and the convergence rate. Additionally, further experiments on the CEC2013 test suite also confirm the effectiveness of the proposed method.The endocrine and exocrine cells in pancreas originate initially from a group of apparently identical endoderm cells in the early gut. The endocrine and exocrine tissues are composed of islet/acinar and duct cells respectively. selleck To explore the mechanism of pancreas cell fate decisions, we first construct a minimal mathematical model related to pancreatic regulations. The regulatory mechanism of acinar-to-islet cell conversion is revealed by bifurcation analysis of the model. In addition, Notch signaling is critical in determining the fate of endocrine and exocrine in the developing pancreas and it is a typical mediator of lateral inhibition which instructs adjacent cells to make different fate decisions. Next, we construct a multicellular model of cell-cell communication mediated by Notch signaling with trans-activation and cis-inhibition. The roles of Notch signaling in regulating fate decisions of endocrine and exocrine cells during the differentiation of pancreatic cells are explored. The results indicate that high (or low) level of Notch signaling drive cells to select the fate of exocrine (or endocrine) progenitor cells.