scholarly journals Comparison of selected mathematical functions for the analysis of growth behavior of items and physical interpretation of AvramiWeibull function

2021 ◽  
Vol 21 ◽  
pp. 259-278
Author(s):  
Keshra Sangwal

Abstract Empirical data of sigmoidal-shaped y(t) growth behavior of different types of items, such as papers and citations earned by individual and all successively published papers of selected top-cited authors, germination of tomato seeds and three different bacteria, are analyzed and compared by Avrami-Weibull, Verhulst (logistic) and Gompertz functions. It was found that: (1) Avrami-Weibull function describes different types of the data better than Gompertz and Verhulst funtions, and (2), in comparison with Verhulst and Gompertz functions, Avrami-Weibull function, expressed in the form: y(t)/ymax = 1-exp[(t/Q)q] (where ymax is the maximum value of y(t) when t ® ¥, and Q and q are constants), is equally very versatile in explaining the generation rate dy(t)/dt of items in terms of its parameters Q and q. Using the basic concepts involved in the derivation of Avrami-Weibull function for overall crystallization from melt and supersaturated solution, the growth behavior of cumulative number y(t) of items produced at time t by individual (simple) sources and collectives or groups of simple sources (i.e. complex or composite sources) is presented. Comparison of the process of receiving of citations by papers with the processes of occurrence of chemical reactions and crystallization of solid phases from melts and supersaturated solutions shows that this process is similar to that of overall crystallization of solid phases from melts and solutions. Analysis of growth of citations using Avrami-Weibull function to individual papers published by different authors shows that 1 < q < 4 for most cases. This suggests that the process of citations to individual articles is mainly determined by progressive nucleation mode involving both diffusion and integration of published knowledge.  

2020 ◽  
Vol 13 (5) ◽  
pp. 884-892
Author(s):  
Sartaj Ahmad ◽  
Ashutosh Gupta ◽  
Neeraj Kumar Gupta

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.


AI ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 261-273
Author(s):  
Mario Manzo ◽  
Simone Pellino

COVID-19 has been a great challenge for humanity since the year 2020. The whole world has made a huge effort to find an effective vaccine in order to save those not yet infected. The alternative solution is early diagnosis, carried out through real-time polymerase chain reaction (RT-PCR) tests or thorax Computer Tomography (CT) scan images. Deep learning algorithms, specifically convolutional neural networks, represent a methodology for image analysis. They optimize the classification design task, which is essential for an automatic approach with different types of images, including medical. In this paper, we adopt a pretrained deep convolutional neural network architecture in order to diagnose COVID-19 disease from CT images. Our idea is inspired by what the whole of humanity is achieving, as the set of multiple contributions is better than any single one for the fight against the pandemic. First, we adapt, and subsequently retrain for our assumption, some neural architectures that have been adopted in other application domains. Secondly, we combine the knowledge extracted from images by the neural architectures in an ensemble classification context. Our experimental phase is performed on a CT image dataset, and the results obtained show the effectiveness of the proposed approach with respect to the state-of-the-art competitors.


Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 495
Author(s):  
Imayanmosha Wahlang ◽  
Arnab Kumar Maji ◽  
Goutam Saha ◽  
Prasun Chakrabarti ◽  
Michal Jasinski ◽  
...  

This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) has been done, using 2D echo images, 3D Doppler images, and videographic images. Secondly, based on different types of regurgitation, namely, Mitral Regurgitation (MR), Aortic Regurgitation (AR), Tricuspid Regurgitation (TR), and a combination of the three types of regurgitation are classified using videographic echo images. Two deep-learning methodologies are used for these purposes, a Recurrent Neural Network (RNN) based methodology (Long Short Term Memory (LSTM)) and an Autoencoder based methodology (Variational AutoEncoder (VAE)). The use of videographic images distinguished this work from the existing work using SVM (Support Vector Machine) and also application of deep-learning methodologies is the first of many in this particular field. It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. Overall, VAE performs better in 2D and 3D Doppler images (static images) while LSTM performs better in the case of videographic images.


Insects ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 169
Author(s):  
Federico Lessio ◽  
Alberto Alma

This paper reviews the existing predictive models concerning insects and mites harmful to grapevine. A brief conceptual description is given on the definition of a model and about different types of models: deterministic vs. stochastics, continuous vs. discrete, analytical vs. computer-based, and descriptive vs. data-driven. The main biological aspects of grapevine pests covered by different types of models are phenology, population growth and dynamics, species distribution, and invasion risk. A particular emphasis is put on forecasting epidemics of plant disease agents transmitted by insects with sucking-piercing mouthparts. The most investigated species or groups are the glassy-winged sharpshooter Homalodisca vitripennis (Germar) and other vectors of Xylella fastidiosa subsp. fastidiosa, a bacterium agent of Pierce’s disease; the European grape berry moth, Lobesia botrana (Denis and Schiffermuller); and the leafhopper Scaphoideus titanus Ball, the main vector of phytoplasmas agents of Flavescence dorée. Finally, the present and future of decision-support systems (DSS) in viticulture is discussed.


1979 ◽  
Vol 57 (4) ◽  
pp. 400-403 ◽  
Author(s):  
Anne Le Narvor ◽  
Pierre Saumagne

The ir spectra of mixtures of methyl propionate/water and methyl propionate/Ba2+ in dimethylsulfoxide and in acetonitrile have been recorded in the region of the νCO mode of the ester. Evidence is presented to indicate the presence of different types of complexes; their concentration was determined as a function of the composition of the medium. The spectroscopic results are compared to those from the kinetics of the alkaline hydrolysis in the same conditions. It is demonstrated that the orbital control explains the experimental results better than does the charge density on the carbon of the carbonyl group. [Journal translation]


2018 ◽  
Vol 74 (12) ◽  
pp. 1684-1691
Author(s):  
Marek L. Główka ◽  
Sylwia Kałużyńska ◽  
Malwina Krause ◽  
Katarzyna Gobis ◽  
Henryk Foks ◽  
...  

Tuberculosis still remains a very important problem, especially its multidrug resistant varieties (MDR-TB). Among the potential tuberculostatics, there are two benzimidazole derivatives, namely 5,6-dimethyl-2-phenylethylbenzo[d]imidazole (1) and (E)-5,6-dimethyl-2-styryl-1H-benzo[d]imidazole (2) which showed significant tuberculostatic activities, better than those of Pyrazinamide and Isoniazyd. Also, the cytotoxicity of 1 appeared promising. The compounds were studied (with the use of X-ray diffraction) in the form of the hemihydrate of 1, C17H18N2·0.5H2O (1a), the methanol hemisolvate of 2, C17H16N2·0.5CH3OH (2a), and the acid oxalate salt of 2, namely (E)-5,6-dimethyl-2-styryl-1H-benzo[d]imidazolium hydrogen oxalate, C17H17N2 +·C2HO4 − (2b). All three structures reveal a similar extended conformation, despite the flexible linker between the two aromatic systems and the different types of strong intermolecular hydrogen bonds. The molecules of 2a are practically planar due to the double bond in the linker, which enables conjugation along the whole molecule, while the molecules of 1a exhibit the possibility of parallel orientations of their aromatic systems, despite the aliphatic (ethyl) linker.


1973 ◽  
Vol 155 (3) ◽  
pp. 56-63
Author(s):  
Avraham Scherman ◽  
Marion Scherman

One-hundred thirty-six students enrolled in four classes of a counseling theories course served as the experimental subjects. In three classes students were randomly assigned to one of three modes of instruction: prose-text, linear programmed instruction, and branching programmed instruction. Subjects from the fourth class were given free choice to select the mode of instruction preferred. It was found that the free-choice group performed better than the linear and branching programmed instruction groups, although not significantly better than the prose-text group. In response to a questionnaire, males stated that when compared to traditional lecture-type courses, the programmed instruction approach helped them concentrate and resulted in a more efficient use of their time. Females did not think that the use of programmed instruction offered an interesting and stimulating approach.


1998 ◽  
Vol 37 (2) ◽  
pp. 227-234
Author(s):  
Julian D. Cox ◽  
Martin B. Padley ◽  
Joe Hannon

Destratification of reservoirs by the use of artificial mixing is a method of improving the impounded water quality. In order to design a destratification device at Stocks Reservoir, NW England, a Computational Fluid Dynamics model was used to trial different types and sizes of mixing device. It was found that a perforated pipe bubble mixing device performed far better than a large banana blade mixer at destratifying Stocks Reservoir. Two important criteria for the effective operation of a mixing device were established. These were a minimum upflow velocity of entrained water through the reservoir, and the need for a reverse flow along the surface of the reservoir away from the abstraction point. These criteria have been incorporated into design equations which can be extended to use at other reservoirs. A bubble mixer was installed at Stocks Reservoir, and has been shown to fully destratify the reservoir and to reduce the levels of dissolved manganese in the water by more than 50%.


2003 ◽  
Vol 18 ◽  
pp. 221-242 ◽  
Author(s):  
Michael Stausberg

The topic presented in this paper lies at the crossroads between ritual studies and ritual theory. In order to get an idea of the field of study, it may be useful to distinguish between the following general approaches to the study of ritual. To begin with, ritual theory in the strict sense, i.e. with explanatory ambitions etc., tends to focus on RITUAL as such: what IT is, what IT does, how IT works ("functions"), and why IT is as it is.Softer varieties of ritual theory, e.g. approaches that wish to foster a better "understanding" of what goes on when rituals are being performed, may focus on RITUALS in a semi-empirical and semi-theoretical fashion. As a matter of fact, to a large extent ritual "theory" seems to be the result of theoretical reflections on matters of empirical research. Apart from that, we find studies of this and that phenomenon (e.g. time, space, violence, aesthetics, media, etc.) in relation to rituals ("ritual  and time", "ritual and space", etc.). Then, of course, we have a good dose of studies on different "types", "classes", or "groups" of rituals. Most popular, (in the absence of any statistical evidence), are studies of "sacrifice", "rites of passage", and "initiations", with "healing rituals" and "pilgrimages" as ever more successful runner-ups. Correspondingly, there is a number of studies about any variety of any class of rituals among the so-and-so people ("initiation among the NN"). Moreover, there are plenty of books about the rituals of this and that religion or people — in colonial times often published under such titles as "The customs and ceremonies of the NN". Last but not least, there is an overwhelming amount of studies devoted to the presentation or analysis of single rituals.


BioResources ◽  
2020 ◽  
Vol 15 (4) ◽  
pp. 9401-9412
Author(s):  
Jaša Saražin ◽  
Detlef Schmiedl ◽  
Antonio Pizzi ◽  
Milan Šernek

Tannins and lignins, which are natural phenolic compounds, are gaining substantial interest in biobased wood adhesive research. In this study, several different biobased tannin-lignin-hexamine adhesive mixtures were prepared and compared in a lap-joint shear strength test. In the first part, the suitability of different types of kraft and organosolv lignins as part of the mixture used in the production of biobased adhesives (in combination with pine tannins) were observed. It was found that biobased adhesive mixtures containing kraft lignins performed significantly better than those that contained organosolv lignins. In the second part, unmodified kraft lignins were mixed with pine tannin in different proportions, ranging from 0% to 100%. The pressing parameters were set to 150 °C for 15 min after performing oscillatory tests with a rheometer. Pure tannin adhesives performed the best, but no significant differences or a trend line were observed among adhesives containing different proportions of tannins and lignins.


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