像素与矢量

智能对象的出现使得在Photoshop和Illustrator中使用像素和矢量之间的差别迅速消失。Derek Lea将会在制作一个结构完美且矢量明显的作品的同时为你解释原因。     

Effect of treatment with 13-cis-retinoic acid and ara-C on the hematopoietic stem cells of patients with myelodysplastic syndromes

PURPOSE: To assess the "in vivo" effect of 13-cis-retinoic acid and low dose Ara-C in MDS as well as to establish "in vitro" advantage of retinoid dose-related growth pattern on bone marrow cultures as defined by culture timing and CFU-GM proliferative response. PATIENTS AND METHODS: We evaluated 28 patients diagnosed of MDS according to FAB classification, of whom 4 cases had RA, 8 cases SRA, 14 cases RAEB and 2 cases RAEB-T. Patients who had RA and SRA were treated with oral 13-cis-retinoic acid at doses of 20-40 mg daily for 4 months and those cases with RAEB and RAEB-T had subcutaneous Ara-C at doses of 3 mg/m2 twice a day for 21 days. The "in vivo" and "in vitro" effect of retinoic acid on the haemopoietic differentiation was evaluated by the growth CFU-GM in semisolid cell culture methods. RESULTS: Increasing in vitro concentrations of 13-cis retinoic acid did not enhance the growth of myelodysplastic progenitors. Nevertheless, our study did not find any beneficial therapeutic effect of retinoic compounds in MDS patients. In this study, low-dose Ara-C (3 mg/m2) showed similar effects when compared with higher doses reported by others. Furthermore, in terms of CFU-GM proliferation the concentration of colonies before and after treatment were fairly similar in all but two patients. CONCLUSIONS: The results drawn from our study demonstrated that there is no beneficial advantage of 13-cis-retinoic acid as a differentiation inducing agent on myelodysplastic patients. In contrast, lower doses of Ara-C showed similar effects on haemopoiesis of MDS patients than standard doses of 10-20 mg/m2 but with less side effects.     

Unwrapping of Digital Speckle-Pattern Interferometry Phase Maps by use of a Minimum L(0)-Norm Algorithm

The performance of a minimum L(0)-norm unwrapping algorithm is investigated by use of synthetic digital speckle-pattern interferometry (DSPI) wrapped phase maps that simulate experimentally obtained data. This algorithm estimates its own weights to mask inconsistent pixels. Particular features usually included in DSPI wrapped phase distributions, such as shears, speckle noise, fringe cuts, object physical limits, and superimposed phase maps, are analyzed. Some adequate approaches to solving these features are discussed. Finally, it is shown that a complex case in which shears and fringe cuts coexist in the wrapped phase cannot be solved satisfactorily with the minimum L(0)-norm algorithm by itself. To cope with this problem, we propose a new scheme.     

Effects of heating in air and chlorine atmosphere on the crystalline structure of pure Ta2O5 or mixed with carbon

Structure changes undergone by pure amorphous hydrated tantalum oxide mixed with different types of carbon when heated in air or chlorine atmospheres were monitored by X-ray diffraction (XRD) and scanning electronic microscopy (SEM). Heating in air of pure Ta2O5 causes the appearance of the hexagonal structure -Ta2O5 at 973 K and the ortho-rhombic structure -Ta2O5 at 1173 K. Heating in chlorine atmosphere markedly lowers the temperature at which transformation to the orthorhombic phase occurs. This effect is attributed to recrystallization of tantalum oxide from tantalum chloride and oxygen, both in gaseous phase, formed in a previous chlorination step of the amorphous oxide. When the thermal treatment is performed in chlorine atmosphere the presence of carbon permits the detection of the hexagonal form at 753 K; this temperature varies with the type of carbon and the oxide : carbon ration. © 1998 Kluwer Academic Publishers     

Responses of the reflectance indices PRI and NDVI to experimental warming and drought in European shrublands along a north-south climatic gradient

The aim of this study was to evaluate the use of ground-based canopy reflectance measurements to detect changes in physiology and structure of vegetation in response to experimental warming and drought treatment at six European shrublands located along a North-South climatic gradient. We measured canopy reflectance, effective green leaf area index (green LAIe) and chlorophyll fluorescence of dominant species. The treatment effects on green LAIe varied among sites. We calculated three reflectance indices: photochemical reflectance index PRI [531 nm; 570 nm], normalized difference vegetation index NDVI₆₈₀ [780 nm; 680 nm] using red spectral region, and NDVI₅₇₀ [780 nm; 570 nm] using the same green spectral region as PRI. All three reflectance indices were significantly related to green LAIe and were able to detect changes in shrubland vegetation among treatments. In general warming treatment increased PRI and drought treatment reduced NDVI values. The significant treatment effect on photochemical efficiency of plants detected with PRI could not be detected by fluorescence measurements. However, we found canopy level measured PRI to be very sensitive to soil reflectance properties especially in vegetation areas with low green LAIe. As both soil reflectance and LAI varied between northern and southern sites it is problematic to draw universal conclusions of climate-derived changes in all vegetation types based merely on PRI measurements. We propose that canopy level PRI measurements can be more useful in areas of dense vegetation and dark soils.     

Algorithms for a realistic variant of flowshop scheduling

This paper deals with a realistic variant of flowshop scheduling, namely the hybrid flexible flowshop. A hybrid flowshop mixes the characteristics of regular flowshops and parallel machine problems by considering stages with parallel machines instead of having one single machine per stage. We also investigate the flexible version where stage skipping might occur, i.e., not all stages must be visited by all jobs. Lastly, we also consider job sequence dependent setup times per stage. The optimization criterion considered is makespan minimization. While many approaches for hybrid flowshops have been proposed, hybrid flexible flowshops have been rarely studied. The situation is even worse with the addition of sequence dependent setups. In this study, we propose two advanced algorithms that specifically deal with the flexible and setup characteristics of this problem. The first algorithm is a dynamic dispatching rule heuristic, and the second is an iterated local search metaheuristic. The proposed algorithms are evaluated by comparison against seven other high performing existing algorithms. The statistically sound results support the idea that the proposed algorithms are very competitive for the studied problem.     

The distributed permutation flowshop scheduling problem

This paper studies a new generalization of the regular permutation flowshop scheduling problem (PFSP) referred to as the distributed permutation flowshop scheduling problem or DPFSP. Under this generalization, we assume that there are a total of F identical factories or shops, each one with m machines disposed in series. A set of n available jobs have to be distributed among the F factories and then a processing sequence has to be derived for the jobs assigned to each factory. The optimization criterion is the minimization of the maximum completion time or makespan among the factories. This production setting is necessary in today's decentralized and globalized economy where several production centers might be available for a firm. We characterize the DPFSP and propose six different alternative mixed integer linear programming (MILP) models that are carefully and statistically analyzed for performance. We also propose two simple factory assignment rules together with 14 heuristics based on dispatching rules, effective constructive heuristics and variable neighborhood descent methods. A comprehensive computational and statistical analysis is conducted in order to analyze the performance of the proposed methods.     

Two-stage cascaded classification approach based on genetic fuzzy learning for speech/music discrimination

Automatic discrimination of speech and music is an important tool in many multimedia applications. The paper presents a robust and effective approach for speech/music discrimination, which relies on a two-stage cascaded classification scheme. The cascaded classification scheme is composed of a statistical pattern recognition classifier followed by a genetic fuzzy system. For the first stage of the classification scheme, other widely used classifiers, such as neural networks and support vector machines, have also been considered in order to assess the robustness of the proposed classification scheme. Comparison with well-proven signal features is also performed. In this work, the most commonly used genetic learning algorithms (Michigan and Pittsburgh) have been evaluated in the proposed two-stage classification scheme. The genetic fuzzy system gives rise to an improvement of about 4% in the classification accuracy rate. Experimental results show the good performance of the proposed approach with a classification accuracy rate of about 97% for the best trial.     

Graphical versus textual software measurement modelling: an empirical study

Model-driven Engineering (MDE) has attained great importance in both the Software Engineering industry and the research community, where it is now widely used to provide a suitable approach with which to improve productivity when developing software artefacts. In this scenario, measurement models (software artefacts) have become a fundamental point in improvement of productivity, where MDE and Software Measurement can reap mutual benefits. MDE principles and techniques can be used in software measurement to build more automatic and generic solutions, and to achieve this, it is fundamental to be able to develop software measurement models. To facilitate this task, a domain-specific language named “Software Measurement Modelling Language” (SMML) has been developed. This paper tackles the question of whether the use of SMML can assist in the definition of software measurement models. An empirical study was conducted, with the aim of verifying whether SMML makes it easier to construct measurement models which are more usable and maintainable as regards textual notation. The results show that models which do not use the language are more difficult—in terms of effort, correctness and efficiency—to understand and modify than those represented with SMML. Additional feedback was also obtained, to verify the suitability of the graphical representation of each symbol (element or relationship) of SMML.     

Size-reduction heuristics for the unrelated parallel machines scheduling problem

In this paper we study the unrelated parallel machines problem where n independent jobs must be assigned to one out of m parallel machines and the processing time of each job differs from machine to machine. We deal with the objective of the minimisation of the maximum completion time of the jobs, usually referred to as makespan or C_max. This is a type of assignment problem that has been frequently studied in the scientific literature due to its many potential applications. We propose a set of metaheuristics based on a size-reduction of the original assignment problem that produce solutions of very good quality in a short amount of time. The underlying idea is to consider only a few of the best possible machine assignments for the jobs and not all of them. The results are simple, yet powerful methods. We test the proposed algorithms with a large benchmark of instances and compare them with current state-of-the-art methods. In most cases, the proposed size-reduction algorithms produce results that are statistically proven to be better by a significant margin.