A New Fuzzy Additive Noise Reduction Method

In this paper we present a new alternative noise reduction method for color images that were corrupted with additive Gaussian noise. We illustrate that color images have to be processed in a different way than most of the state-of-the-art methods. The proposed method consists of two sub-filters. The main concern of the first subfilter is to distinguish between local variations due to noise and local variations due to image structures such as edges. This is realized by using the color component distances instead of component differences as done by most current filters. The second subfilter is used as a complementary filter which especially preserves differences between the color components. This is realized by calculating the local differences in the red, green and blue environment separately. These differences are then combined to calculate the local estimation of the central pixel. Experimental results show the feasibility of the proposed approach

The Physics of Star Cluster Formation and Evolution

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00689-4.Star clusters form in dense, hierarchically collapsing gas clouds. Bulk kinetic energy is transformed to turbulence with stars forming from cores fed by filaments. In the most compact regions, stellar feedback is least effective in removing the gas and stars may form very efficiently. These are also the regions where, in high-mass clusters, ejecta from some kind of high-mass stars are effectively captured during the formation phase of some of the low mass stars and effectively channeled into the latter to form multiple populations. Star formation epochs in star clusters are generally set by gas flows that determine the abundance of gas in the cluster. We argue that there is likely only one star formation epoch after which clusters remain essentially clear of gas by cluster winds. Collisional dynamics is important in this phase leading to core collapse, expansion and eventual dispersion of every cluster. We review recent developments in the field with a focus on theoretical work.Peer reviewe

Maxillary sinus elevation by lateral window approach : evolution of technology and technique

Context: The maxillary sinus elevation procedure has become an important pre-prosthetic surgical procedure for the creation of bone volume in the edentulous posterior maxilla for the placement of dental implants. Research and clinical experience over the past 30 years has increased the predictability of this procedure as well as reduced patient morbidity. Evidence Acquisition: Data on grafting materials and implant survival rates comes from 10 published evidence-based reviews that include all relevant published data from 1980 to 2012. Supporting clinical material comes from the experience of the authors. Evidence synthesis: The evidence-based reviews report and compare the implant survival rates utilizing various grafting materials, implant surfaces, and the use or non-use of barrier membranes over the lateral window. Clinical studies report on complication rates utilizing piezoelectric surgery and compare them to complication rates with rotary instrumentatio

Collagen Sponge Functionalized with Chimeric Anti-BMP-2 Monoclonal Antibody Mediates Repair of Critical-Size Mandibular Continuity Defects in a Nonhuman Primate Model

10.1155/2017/8094152BioMed Research International2017809415

Component Models for Fuzzy Data

informational paradigm, fuzzy data, distance measure for fuzzy data, principal component analysis, least squares approach,

Measuring the readability performance (RP) of aircraft maintenance technical orders by fuzzy MCDM method and RP index

Technical order, Readability performance index, Readability characteristics, Fuzzy multiple criteria decision-making (Fuzzy MCDM),

Use of soft computing techniques in renewable energy hydrogen hybrid systems

Soft computing techniques are important tools that significantly improve the performance of energy systems. This chapter reviews their many contributions to renewable energy hydrogen hybrid systems, namely those systems that consist of different technologies (photovoltaic and wind, electrolyzers, fuel cells, hydrogen storage, piping, thermal and electrical/electronic control systems) capable as a whole of converting solar energy, storing it as chemical energy (in the form of hydrogen) and turning it back into electrical and thermal energy. Fuzzy logic decision-making methodologies can be applied to select amongst renewable energy alternative or to vary a dump load for regulating wind turbine speed or find the maximum power point available from arrays of photovoltaic modules. Dynamic fuzzy logic controllers can furthermore be utilized to coordinate the flow of hydrogen to fuel cells or employed for frequency control in micro- grid power systems. Neural networks are implemented to model, design and control renewable energy systems and to estimate climatic data such as solar irradiance and wind speeds. They have been demonstrated to predict with good accuracy system power usage and status at any point of time. Neural controls can also help in the minimization of energy production costs by optimal scheduling of power units. Genetic or evolutionary algorithms are able to provide approximate solutions to several complex tasks with high number of variables and non-linearities, like optimal operational strategy of a grid-parallel fuel cell power plant, optimization of control strategies for stand-alone renewable systems and sizing of photovoltaic systems. Particle swarm optimization techniques are applied to find optimal sizing of system components in an effort to minimize costs or coping with system failures to improve service quality. These techniques can also be implemented together to exploit their potential synergies while, at the same time, coping with their possible limitations. This chapter covers soft computing methods applied to renewable energy hybrid hydrogen systems by providing a description of their single or mixed implementation and relevance, together with a discussion of advantages and/or disadvantages in their applications. \uc2\ua9 Springer-Verlag Berlin Heidelberg 2011