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排序方式: 共有1755条查询结果,搜索用时 34 毫秒
41.
Aayushi Biswas Chhangte Vanlalveni Partha Pradip Adhikari Ralte Lalfakzuala Lalthazuala Rokhum 《IET nanobiotechnology / IET》2018,12(7):933
Green synthesis of nanoparticles is considered an efficient method when compared with chemical and physical methods because of its bulk production, eco‐friendliness and low cost norms. The present study reports, for the first time, green synthesis of silver nanoparticles (AgNPs) at room temperature using Solanum viarum fruit extract. The visual appearance of brownish colour with an absorption band at 450 nm, as detected by ultraviolet‐visible spectrophotometer analysis, confirmed the formation of AgNPs. X‐ray diffraction confirmed the AgNPs to be crystalline with a face‐centred lattice. The transmission electron microscopy‐energy dispersive X‐ray spectroscopy image showed the AgNPs are poly‐dispersed and are mostly spherical and oval in shape with particle size ranging from 2 to 40 nm. Furthermore, Fourier transform‐infrared spectra of the synthesised AgNPs confirmed the presence of phytoconstituents as a capping agent. The antimicrobial activity study showed that the AgNPs exhibited high microbial activity against Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus susp. aureus, Aspergillus niger, and Candida albicans. The highest antimicrobial activity of AgNPs synthesised by S. viarum fruit extract was observed in P. aeruginosa, S. aureus susp. aureus and C. albicans with zone of inhibition, 26.67 mm.Inspec keywords: nanomedicine, antibacterial activity, X‐ray chemical analysis, nanoparticles, transmission electron microscopy, particle size, infrared spectra, microorganisms, X‐ray diffraction, Fourier transform spectra, ultraviolet spectra, scanning electron microscopy, visible spectra, nanofabricationOther keywords: green biosynthesis, antimicrobial activities, silver nanoparticles, green synthesis, physical methods, study reports, solanum viarum fruit, ultraviolet‐visible spectrophotometer analysis, high microbial activity, highest antimicrobial activity, s. viarum fruit, transmission electron microscopy, energy dispersive X‐ray spectroscopy image 相似文献
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43.
Sriparna Saha Author Vitae Sanghamitra Bandyopadhyay Author Vitae 《Pattern recognition》2010,43(3):738-751
In this paper the problem of automatic clustering a data set is posed as solving a multiobjective optimization (MOO) problem, optimizing a set of cluster validity indices simultaneously. The proposed multiobjective clustering technique utilizes a recently developed simulated annealing based multiobjective optimization method as the underlying optimization strategy. Here variable number of cluster centers is encoded in the string. The number of clusters present in different strings varies over a range. The points are assigned to different clusters based on the newly developed point symmetry based distance rather than the existing Euclidean distance. Two cluster validity indices, one based on the Euclidean distance, XB-index, and another recently developed point symmetry distance based cluster validity index, Sym-index, are optimized simultaneously in order to determine the appropriate number of clusters present in a data set. Thus the proposed clustering technique is able to detect both the proper number of clusters and the appropriate partitioning from data sets either having hyperspherical clusters or having point symmetric clusters. A new semi-supervised method is also proposed in the present paper to select a single solution from the final Pareto optimal front of the proposed multiobjective clustering technique. The efficacy of the proposed algorithm is shown for seven artificial data sets and six real-life data sets of varying complexities. Results are also compared with those obtained by another multiobjective clustering technique, MOCK, two single objective genetic algorithm based automatic clustering techniques, VGAPS clustering and GCUK clustering. 相似文献
44.
Items made of glass, ceramic, etc. are normally stored in stacks and get damaged during the storage due to the accumulated stress of heaped stock. These items are known as breakable items. Here a multi-item inventory model of breakable items is developed, where demands of the items are stock dependent, breakability rates increase linearly with stock and nonlinearly with time. Due to non-linearity and complexity of the problem, the model is solved numerically and final decisions are made using Genetic Algorithm (GA). In a particular case, model is solved analytically as well as numerically and results are compared. Models are developed with both crisp and uncertain inventory costs. For uncertain inventory costs both fuzzy and stochastic parameters are considered. A chance constrained approach is followed to deal with simultaneous presence of stochastic and fuzzy parameters. Different numerical examples are used to illustrate the problem for different cases. 相似文献
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46.
Pre-processing is one of the vital steps for developing robust and efficient recognition system. Better pre-processing not
only aid in better data selection but also in significant reduction of computational complexity. Further an efficient frame
selection technique can improve the overall performance of the system. Pre-quantization (PQ) is the technique of selecting
less number of frames in the pre-processing stage to reduce the computational burden in the post processing stages of speaker
identification (SI). In this paper, we develop PQ techniques based on spectral entropy and spectral shape to pick suitable
frames containing speaker specific information that varies from frame to frame depending on spoken text and environmental
conditions. The attempt is to exploit the statistical properties of distributions of speech frames at the pre-processing stage
of speaker recognition. Our aim is not only to reduce the frame rate but also to maintain identification accuracy reasonably
high. Further we have also analyzed the robustness of our proposed techniques on noisy utterances. To establish the efficacy
of our proposed methods, we used two different databases, POLYCOST (telephone speech) and YOHO (microphone speech). 相似文献
47.
Automatic MR brain image segmentation using a multiseed based multiobjective clustering approach 总被引:2,自引:2,他引:0
In this paper, the automatic segmentation of a multispectral magnetic resonance image of the brain is posed as a clustering
problem in the intensity space. The automatic clustering problem is thereafter modelled as solving a multiobjective optimization
(MOO) problem, optimizing a set of cluster validity indices simultaneously. A multiobjective clustering technique, named MCMOClust, is used to solve this problem. MCMOClust utilizes a recently developed simulated annealing based multiobjective optimization method as the underlying optimization
strategy. Each cluster is divided into several small hyperspherical subclusters and the centers of all these small sub-clusters
are encoded in a string to represent the whole clustering. For assigning points to different clusters, these local sub-clusters
are considered individually. For the purpose of objective function evaluation, these sub-clusters are merged appropriately
to form a variable number of global clusters. Two cluster validity indices, one based on the Euclidean distance, XB-index,
and another recently developed point symmetry distance based cluster validity index, Sym-index, are optimized simultaneously to automatically evolve the appropriate number of clusters present in MR brain images.
A semi-supervised method is used to select a single solution from the final Pareto optimal front of MCMOClust. The present method is applied on several simulated T1-weighted, T2-weighted and proton density normal and MS lesion magnetic
resonance brain images. Superiority of the present method over Fuzzy C-means, Expectation Maximization clustering algorithms
and a newly developed symmetry based fuzzy genetic clustering technique (Fuzzy-VGAPS), are demonstrated quantitatively. The
automatic segmentation obtained by multiseed based multiobjective clustering technique (MCMOClust) is also compared with the available ground truth information. 相似文献
48.
Bhattacharya D Saha S Basu S Chakravarty S Chakravarty A Banerjee D Chakrabarti A 《Proteomics. Clinical applications》2010,4(5):480-488
Purpose: In (hemoglobin, Hb) HbEβ‐thalassemia, HbE (β‐26 Glu→Lys) interacts with β‐thalassemia to produce clinical manifestation of varying severity. This is the first proteomic effort to study changes in protein levels of erythrocytes isolated from HbEβ‐thalassemic patients compared to normal. Experimental design: We have used 2‐DE and MALDI‐MS/MS‐based techniques to investigate the differential proteome profiling of membrane and Hb‐depleted fraction of cytosolic proteins of erythrocytes isolated from the peripheral blood samples of HbEβ‐thalassemia patients and normal volunteers. Results: Our study showed that redox regulators such as peroxiredoxin 2, Cu‐Zn superoxide dismutase and thioredoxin and chaperones such as α‐hemoglobin stabilizing protein and HSP‐70 were upregulated in HbEβ‐thalassemia. We have also observed larger amounts of membrane associated globin chains and indications of disruption of spectrin‐based junctional complex in the membrane skeleton of HbEβ‐thalassemic erythrocytes upon detection of low molecular weight fragments of β‐spectrin and decrease in β‐actin and dematin content. Conclusion and clinical relevance: We have observed interesting changes in the proteomic levels of redox regulators and chaperons in the thalassemic hemolysates and have observed strong correlation or association of the extent of such proteomic changes with HbE levels. This could be important in understanding the role of HbE in disease progression and pathophysiology. 相似文献
49.
Sumit Misra Sanjoy Kumar Saha Chandan Mazumdar 《Innovations in Systems and Software Engineering》2017,13(4):261-269
Multiple data streams coming out of a complex system form the observable state of the system. The streams may correspond to various sensors attached with the system or outcome of internal processes. Such stream data may consist of multiple attributes and may differ in terms of their frequency of generation and observation. The streams may have dependency among themselves. One will have to rely on such data streams for monitoring the health of the system or to take any corrective measure. Predicting the value of certain stream data is an important task that can help one to take decision and act accordingly. In this work, a simple but generic visualization of a complex system is presented and thereafter a linear regression-based dynamic model for short-term prediction is proposed. The model is based on the past history of the attributes of multiple streams as suggested by the domain experts. But, it automatically determines the meaningful attributes and reformulates the model. The model is also re-computed if the prediction error exceeds the allowable tolerance. All these make the model dynamic. Experiment is carried out with stock market data streams to predict the close value well in advance. It is observed that in terms of quality of prediction and performance metric, the proposed model is quite effective. 相似文献
50.
Saha P.K. Udupa J.K. 《IEEE transactions on pattern analysis and machine intelligence》2001,23(7):689-706
Thresholding is a popular image segmentation method that converts a gray-level image into a binary image. The selection of optimum thresholds has remained a challenge over decades. Besides being a segmentation tool on its own, often it is also a step in many advanced image segmentation techniques in spaces other than the image space. We introduce a thresholding method that accounts for both intensity-based class uncertainty-a histogram-based property-and region homogeneity-an image morphology-based property. A scale-based formulation is used for region homogeneity computation. At any threshold, intensity-based class uncertainty is computed by fitting a Gaussian to the intensity distribution of each of the two regions segmented at that threshold. The theory of the optimum thresholding method is based on the postulate that objects manifest themselves with fuzzy boundaries in any digital image acquired by an imaging device. The main idea here is to select that threshold at which pixels with high class uncertainty accumulate mostly around object boundaries. To achieve this, a threshold energy criterion is formulated using class-uncertainty and region homogeneity such that, at any image location, a high energy is created when both class uncertainty and region homogeneity are high or both are low. Finally, the method selects that threshold which corresponds to the minimum overall energy. The method has been compared to a maximum segmented image information method. Superiority of the proposed method was observed both qualitatively on clinical medical images as well as quantitatively on 250 realistic phantom images generated by adding different degrees of blurring, noise, and background variation to real objects segmented from clinical images 相似文献