scholarly journals Evolution of Entropy in Art Painting Based on the Wavelet Transform

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 883
Author(s):  
Hongyi Yang ◽  
Han Yang
Keyword(s):  
Comparative Research ◽  
Large Scale ◽  
Entropy Change ◽  
Important Change ◽  
Wavelet Entropy ◽  
Machine Learning Classification ◽  
Quantitative Studies ◽  
Rich Information ◽  
Wavelet Energy Entropy ◽  
Low Entropy

Quantitative studies of art and aesthetics are representative of interdisciplinary research. In this work, we conducted a large-scale quantitative study of 36,000 paintings covering both Eastern and Western paintings. The information entropy and wavelet entropy of the images were calculated based on their complexity and energy. Wavelet energy entropy is a feature that can characterize rich information in images, and this is the first study to introduce this feature into aesthetic analysis of art paintings. This study shows that the process of entropy change coincides with the development process of art painting. Further, the experimental results demonstrate an important change in the evolution of art painting, and since the rise of modern art in the twentieth century, the entropy values in painting have started to become diverse. In comparison with Western paintings, Eastern paintings have distinct low entropy characteristics in which the wavelet entropy feature of the images has better results in the machine learning classification task of Eastern and Western paintings (i.e., the F1 score can reach 97%). Our study can be the basis for future quantitative analysis and comparative research in the context of Western and Eastern art aesthetics.

Crowdfunding as an Alternative Method of Raising Capital

e-Finanse ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 56-66
Author(s):  
Katarzyna Wierzbicka
Keyword(s):  
Financial Market ◽  
Comparative Research ◽  
Large Scale ◽  
New Ventures ◽  
Secondary Data ◽  
Polish Literature ◽  
Investment Projects ◽  
Research Task ◽  
Type Of Institution ◽  
Insufficient Knowledge

AbstractCrowdfunding is a method of financing new ventures, commercial, cultural or social, often in return for future products or actions, engaged in by many investors. Currently, it is an important element in the structure of available sources of financing for investment projects. Despite the interest of potential investors, individual social sponsors and large-scale activities of institutions promoting knowledge about the functioning of crowdfunding aimed at encouraging and promoting it as a source of capital for new ventures, there is a lack of knowledge and, consequently, experience on its development and achievement. The aim of this study is to analyze this source of financing, assess its development globally and in Poland. In the preparation of the article,. a critical analysis of foreign and Polish literature was carried out, and descriptive and comparative research methods applied. The research task undertaken in the study was to analyze the crowdfunding market globally and in Poland. The Polish crowdfunding platforms were detailed and compared in terms of value in relation to the largest global platforms. The source for analyses of crowdfunding development in Poland was available literature on the analyzed topic and secondary data from the websites of specialized internet platforms. The article depicts a new, but important, aspect of financing the activity of enterprises, which is crowdfunding. It should be emphasized that there is still insufficient knowledge about this type of institution and, as a result, the importance and role that social financing plays in the financial market.

The Croonian Lecture, 1970 The structural basis of muscular contraction

1971 ◽  
Vol 178 (1051) ◽  
pp. 131-149 ◽  
Keyword(s):  
Large Scale ◽  
Muscular Contraction ◽  
Important Change ◽  
Structural Basis ◽  
X Ray Diffraction ◽  
New Era ◽  
X Ray ◽  
Biology I ◽  
The Times ◽  
Polypeptide Chains

A previous occasion on which the Croonian lecture was directly concerned with the mechanism of muscular contraction was in 1945, when it was delivered by Professor W. T. Astbury. On that occasion he commented that it was a sign of the times that a physicist should be asked to give the Croonian lecture, and went on to say, and I quote: ‘We are at the dawn of a new era, the era of “molecular biology”, as I like to call it, and there is an urgency about the need for more intensive application of physics and chemistry, and specially structural analysis, to biological problems.’ These were very prophetic words, and, as a physicist just entering biology, I was much interested to read them, and to learn about his experiments. The basic experimental finding which Astbury reported (1947) was that there did not seem to be any important change in the wide angle X-ray diagram from muscle upon contraction; hence it followed that muscles did not contract by any process which simply involved the large-scale disorientation of originally well-ordered polypeptide chains, nor by an alteration in chain configuration in the well-ordered parts of the structure. Astbury suggested instead that there might be ‘specifically active foci’ which one could perhaps paraphrase as ‘larger structural units’ (i.e. larger than individual polypeptide chains) concerned in contraction, which might be studied in the electron microscope or by low angle X-ray diffraction.

scholarly journals Applying Machine Learning for Improving Performance Classification on Driving Behavior

2021 ◽  
Vol 4 (1) ◽  
pp. 8
Author(s):  
Ahmad Iwan Fadli ◽  
Selo Sulistyo ◽  
Sigit Wibowo
Keyword(s):  
Machine Learning ◽  
Traffic Accident ◽  
Large Scale ◽  
Detection System ◽  
Difficult Problem ◽  
Sensor Data ◽  
Driving Safety ◽  
Support Vector ◽  
Classification Methods ◽  
Machine Learning Classification

Traffic accident is a very difficult problem to handle on a large scale in a country. Indonesia is one of the most populated, developing countries that use vehicles for daily activities as its main transportation.  It is also the country with the largest number of car users in Southeast Asia, so driving safety needs to be considered. Using machine learning classification method to determine whether a driver is driving safely or not can help reduce the risk of driving accidents. We created a detection system to classify whether the driver is driving safely or unsafely using trip sensor data, which include Gyroscope, Acceleration, and GPS. The classification methods used in this study are Random Forest (RF) classification algorithm, Support Vector Machine (SVM), and Multilayer Perceptron (MLP) by improving data preprocessing using feature extraction and oversampling methods. This study shows that RF has the best performance with 98% accuracy, 98% precision, and 97% sensitivity using the proposed preprocessing stages compared to SVM or MLP.

Research Challenges and Opportunities in Conducting Quantitative Studies on Large-Scale Agile Methodology

2020 ◽  
Vol 31 (2) ◽  
pp. 64-73
Author(s):  
Dinesh Batra
Keyword(s):  
Large Scale ◽  
Empirical Literature ◽  
Adoption Studies ◽  
Agile Methodology ◽  
Quantitative Studies ◽  
Balanced Approach ◽  
Research Challenges ◽  
Time Period ◽  
Dependent Variables ◽  
Challenges And Opportunities

This research note suggests five research challenges when conducting quantitative studies on large-scale agile methodology (LSAM). First, the LSAM empirical literature, which is mainly characterized by qualitative studies primarily focusing on coordination issues, provides limited background. Second, the notion of “large” in LSAM needs to be clarified because the existing research seems to have focused on “very large” or outlier projects. Third, the popular LSAM methods suggest broad and general maxims that may result in difficulty in operationalizing dependent variables, especially in innovation adoption studies. Fourth, the researcher may get overwhelmed when selecting independent variables from the plethora of suggested constructs. Finally, some of the problems associated with large-scale agile are mostly challenges of using conventional agile during a time-period when LSAM had not formally emerged. Researchers should take a balanced approach considering both benefits and challenges of using LSAM and focusing on project-level dependent measures such as success and acceptance.

scholarly journals Conducting quantitative studies with the participation of political elites: best practices for designing the study and soliciting the participation of political elites

2020 ◽  
Author(s):  
Barbara Vis ◽  
Sjoerd Stolwijk
Keyword(s):  
Decision Making ◽  
Best Practices ◽  
Quantitative Research ◽  
Large Scale ◽  
Response Rate ◽  
Response Rates ◽  
Political Elite ◽  
Political Elites ◽  
Future Studies ◽  
Quantitative Studies

Abstract Conducting quantitative research (e.g., surveys, a large number of interviews, experiments) with the participation of political elites is typically challenging. Given that a population of political elites is typically small by definition, a particular challenge is obtaining a sufficiently high number of observations and, thus, a certain response rate. This paper focuses on two questions related to this challenge: (1) What are best practices for designing the study? And (2) what are best practices for soliciting the participation of political elites? To arrive at these best practices, we (a) examine which factors explain the variation in response rates across surveys within and between large-scale, multi-wave survey projects by statistically analyzing a newly compiled dataset of 342 political elite surveys from eight projects, spanning 30 years and 58 countries, (b) integrate the typically scattered findings from the existing literature and (c) discuss results from an original expert survey among researchers with experience with such research (n = 23). By compiling a comprehensive list of best practices, systematically testing some widely held believes about response rates and by providing benchmarks for response rates depending on country, survey mode and elite type, we aim to facilitate future studies where participation of political elites is required. This will contribute to our knowledge and understanding of political elites’ opinions, information processing and decision making and thereby of the functioning of representative democracies.

scholarly journals A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons

2020 ◽  
Vol 117 (31) ◽  
pp. 18412-18423 ◽  
Author(s):  
Chia-Chen Hsu ◽  
Jiabao Xu ◽  
Bas Brinkhof ◽  
Hui Wang ◽  
Zhanfeng Cui ◽  
...  
Keyword(s):  
Stem Cells ◽  
Stem Cell ◽  
Single Cell ◽  
Raman Spectra ◽  
Large Scale ◽  
Developmental Stages ◽  
Single Cells ◽  
Classification Model ◽  
Label Free ◽  
Machine Learning Classification

Stem cells with the capability to self-renew and differentiate into multiple cell derivatives provide platforms for drug screening and promising treatment options for a wide variety of neural diseases. Nevertheless, clinical applications of stem cells have been hindered partly owing to a lack of standardized techniques to characterize cell molecular profiles noninvasively and comprehensively. Here, we demonstrate that a label-free and noninvasive single-cell Raman microspectroscopy (SCRM) platform was able to identify neural cell lineages derived from clinically relevant human induced pluripotent stem cells (hiPSCs). By analyzing the intrinsic biochemical profiles of single cells at a large scale (8,774 Raman spectra in total), iPSCs and iPSC-derived neural cells can be distinguished by their intrinsic phenotypic Raman spectra. We identified a Raman biomarker from glycogen to distinguish iPSCs from their neural derivatives, and the result was verified by the conventional glycogen detection assays. Further analysis with a machine learning classification model, utilizing t-distributed stochastic neighbor embedding (t-SNE)-enhanced ensemble stacking, clearly categorized hiPSCs in different developmental stages with 97.5% accuracy. The present study demonstrates the capability of the SCRM-based platform to monitor cell development using high content screening with a noninvasive and label-free approach. This platform as well as our identified biomarker could be extensible to other cell types and can potentially have a high impact on neural stem cell therapy.

scholarly journals The mergers in Abell 2256: displaced gas and its connection to the radio-emitting plasma

2020 ◽  
Vol 495 (4) ◽  
pp. 5014-5026 ◽  
Author(s):  
J P Breuer ◽  
N Werner ◽  
F Mernier ◽  
T Mroczkowski ◽  
A Simionescu ◽  
...  
Keyword(s):  
Surface Brightness ◽  
Large Scale ◽  
Cold Front ◽  
Low Frequency ◽  
Brightness Distribution ◽  
Analytical Models ◽  
Line Of Sight ◽  
Cluster Galaxy ◽  
X Ray ◽  
Low Entropy

ABSTRACT We present the results of deep Chandra and XMM–Newton X-ray imaging and spatially resolved spectroscopy of Abell 2256, a nearby (z = 0.058) galaxy cluster experiencing multiple mergers and displaying a rich radio morphology dominated by a large relic. The X-ray data reveal three subclusters: (i) the ‘main cluster’; (ii) the remnant of an older merger in the east of the cluster with an ∼600 kpc-long tail; (iii) a bright, bullet-like, low-entropy infalling system, with a large line-of-sight velocity component. The low-entropy system displays a 250 kpc-long cold front with a break and an intriguing surface brightness decrement. Interestingly, the infalling gas is not co-spatial with bright galaxies and the radio-loud brightest cluster galaxy of the infalling group appears dissociated from the low-entropy plasma by ∼50 kpc in projection, to the south of the eastern edge of the cold front. Assuming that the dark matter follows the galaxy distribution, we predict that it is also significantly offset from the low-entropy gas. Part of the low-frequency radio emission near the cold front might be revived by magnetic field amplification due to differential gas motions. Using analytical models and numerical simulations, we investigate the possibility that the supersonic infall of the subcluster generates a large-scale shock along our line of sight, which can be detected in the X-ray temperature map but is not associated with any clear features in the surface brightness distribution.

scholarly journals Effectiveness of birthing kits for clean childbirth: a systematic review

2019 ◽  
Vol 12 (1) ◽  
pp. 3-10 ◽  
Author(s):  
Zohra S Lassi ◽  
Zeshi Fisher ◽  
Prabha Andraweera ◽  
Alexandra Cummins ◽  
Claire T Roberts
Keyword(s):  
Large Scale ◽  
Positive Impact ◽  
Young Infant ◽  
Critical Factor ◽  
Neonatal Morbidity ◽  
Qualitative Studies ◽  
Current Evidence ◽  
Cochrane Library ◽  
Quantitative Studies ◽  
Life Threatening

Abstract Poor infection control practices during childbirth are recognised as a critical factor leading to life-threatening maternal and newborn sepsis. Therefore, this paper assesses the effectiveness of clean birth kits (CBKs) to ensure a safe birthing environment. We searched PubMed, Cochrane Library and CINAHL, as well as Google Scholar, to identify both qualitative and quantitative studies on CBKs published in English up to November 2018. Studies were included if the pregnant women or women giving birth intended to use or used a CBK. The methodological quality of included papers was assessed. A total of 37 studies, 26 quantitative and 11 qualitative studies, were included. Quantitative studies showed a positive impact of CBKs on reducing the incidence of puerperal sepsis and neonatal tetanus. The review also identified CBK use to be associated with a reduction in perinatal, neonatal and young infant mortality. Qualitative studies suggested that a lack of awareness of the importance of CBKs and clean delivery practices, unavailability of CBKs and financial constraints to purchase CBKs were the potential barriers. CBKs appear to be a promising strategy to reduce maternal and neonatal morbidity and mortality. However, the current evidence is limited and further large-scale trials are required.

scholarly journals Non-negative matrix analysis for effective feature extraction in X-ray spectromicroscopy

2014 ◽  
Vol 171 ◽  
pp. 357-371 ◽  
Author(s):  
Rachel Mak ◽  
Mirna Lerotic ◽  
Holger Fleckenstein ◽  
Stefan Vogt ◽  
Stefan M. Wild ◽  
...  
Keyword(s):  
Large Scale ◽  
Environmental Science ◽  
Matrix Analysis ◽  
Matrix Approximation ◽  
New Approach ◽  
X Ray ◽  
Rich Information ◽  
Preliminary Study ◽  
X Ray Absorption ◽  
Calculated Image

X-Ray absorption spectromicroscopy provides rich information on the chemical organization of materials down to the nanoscale. However, interpretation of this information in studies of “natural” materials such as biological or environmental science specimens can be complicated by the complex mixtures of spectroscopically complicated materials present. We describe here the shortcomings that sometimes arise in previously-employed approaches such as cluster analysis, and we present a new approach based on non-negative matrix approximation (NNMA) analysis with both sparseness and cluster-similarity regularizations. In a preliminary study of the large-scale biochemical organization of human spermatozoa, NNMA analysis delivers results that nicely show the major features of spermatozoa with no physically erroneous negative weightings or thicknesses in the calculated image.

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