scholarly journals Dynamic and on demand data streams

2019 ◽  
Vol 214 ◽  
pp. 04030
Author(s):  
Matteo Duranti ◽  
Valerio Formato ◽  
Valerio Vagelli

Replicability and efficiency of data processing on the same data samples are a major challenge for the analysis of data produced by HEP experiments. High level data analyzed by end-users are typically produced as a subset of the whole experiment data sample to study interesting selection of data (streams). For standard applications, streams may be eventually copied from servers and analyzed on local computing centers or user machine clients. The creation of streams as copy of a subset of the original data results in redundant information stored in filesystems and may be not efficient: if the definition of streams changes, it may force a reprocessing of the low-level files with consequent impact on the data analysis efficiency. We propose an approach based on a database of lookup tables intended for dynamic and on-demand definition of data streams. This enables the end-users, as the data analysis strategy evolves, to explore different definitions of streams with minimal cost in computing resources. We also present a prototype demonstration application of this database for the analysis of the AMS-02 experiment data.

2011 ◽  
Vol 86 ◽  
pp. 875-878 ◽  
Author(s):  
Zhi Fei Wu ◽  
Tie Wang ◽  
Rui Liang Zhang ◽  
Hong Mei Li

This paper introduces the installment method of experimental machine and gears, and the definition of stress levels, based on the contact fatigue experiment of 18Cr2Ni4WA carburizing and quenching gears, the few experimental points combination method was applied. The experimental points data was obtained by failure criteria. The S-N curve is fitted according to experiment data, and the experimental points data processing method is also explained in the paper.


1998 ◽  
Vol 3 (1) ◽  
pp. 13-36 ◽  
Author(s):  
Ruth Guttman ◽  
Charles W. Greenbaum

This article gives an overview of Facet Theory, a systematic approach to facilitating theory construction, research design, and data analysis for complex studies, that is particularly appropriate to the behavioral and social sciences. Facet Theory is based on (1) a definitional framework for a universe of observations in the area of study; (2) empirical structures of observations within this framework; (3) a search for correspondence between the definitional system and aspects of the empirical structure for the observations. The development of Facet Theory and Facet Design is reviewed from early scale analysis and the Guttman Scale, leading to the concepts of “mapping sentence,” “universe of content,” “common range,” “content facets,” and nonmetric multidimensional methods of data analysis. In Facet Theory, the definition of the behavioral domain provides a rationale for hypothesizing structural relationships among variables employed in a study. Examples are presented from various areas of research (intelligence, infant development, animal behavior, etc.) to illustrate the methods and results of structural analysis with Smallest Space Analysis (SSA), Multidimensional Scalogram Analysis (MSA), and Partial Order Scalogram Analysis (POSA). The “radex” and “cylindrex” of intelligence tests are shown to be outstanding examples of predicted spatial configurations that have demonstrated the ubiquitous emergence of the same empirical structures in different studies. Further examples are given from studies of spatial abilities, infant development, animal behavior, and others. The use of Facet Theory, with careful construction of theory and design, is shown to provide new insights into existing data; it allows for the diagnosis and discrimination of behavioral traits and makes the generalizability and replication of findings possible, which in turn makes possible the discovery of lawfulness. Achievements, issues, and future challenges of Facet Theory are discussed.


2019 ◽  
Vol 20 (1) ◽  
pp. 30-35
Author(s):  
Agus Prasetya

This article is motivated by the fact that the existence of the Street Vendor (PKL) profession is a manifestation of the difficulty of work and the lack of jobs. The scarcity of employment due to the consideration of the number of jobs with unbalanced workforce, economically this has an impact on the number of street vendors (PKL) exploding ... The purpose of being a street vendor is, as a livelihood, making a living, looking for a bite of rice for family, because of the lack of employment, this caused the number of traders to increase. The scarcity of jobs, causes informal sector migration job seekers to create an independent spirit, entrepreneurship, entrepreneurship, with capital, managed by traders who are true populist economic actors. The problems in street vendors are: (1) how to organize, regulate, empower street vendors in the cities (2) how to foster, educate street vendors, and (3) how to help, find capital for street vendors (4) ) how to describe grief as a Five-Foot Trader. This paper aims to find a solution to the problem of street vendors, so that cases of conflict, cases of disputes, clashes of street vendors with Satpol PP can be avoided. For this reason, the following solutions must be sought: (1) understanding the causes of the explosions of street vendors (2) understanding the problems of street vendors. (3) what is the solution to solving street vendors in big cities. (4) describe Street Vendors as actors of the people's economy. This article is qualitative research, the social paradigm is the definition of social, the method of retrieving observational data, in-depth interviews, documentation. Data analysis uses Interactive Miles and Huberman theory, with stages, Collection Data, Display Data, Data Reduction and Vervying or conclusions.


Author(s):  
Andrea Renda

This chapter assesses Europe’s efforts in developing a full-fledged strategy on the human and ethical implications of artificial intelligence (AI). The strong focus on ethics in the European Union’s AI strategy should be seen in the context of an overall strategy that aims at protecting citizens and civil society from abuses of digital technology but also as part of a competitiveness-oriented strategy aimed at raising the standards for access to Europe’s wealthy Single Market. In this context, one of the most peculiar steps in the European Union’s strategy was the creation of an independent High-Level Expert Group on AI (AI HLEG), accompanied by the launch of an AI Alliance, which quickly attracted several hundred participants. The AI HLEG, a multistakeholder group including fifty-two experts, was tasked with the definition of Ethics Guidelines as well as with the formulation of “Policy and Investment Recommendations.” With the advice of the AI HLEG, the European Commission put forward ethical guidelines for Trustworthy AI—which are now paving the way for a comprehensive, risk-based policy framework.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1388
Author(s):  
Daniele Oboe ◽  
Luca Colombo ◽  
Claudio Sbarufatti ◽  
Marco Giglio

The inverse Finite Element Method (iFEM) is receiving more attention for shape sensing due to its independence from the material properties and the external load. However, a proper definition of the model geometry with its boundary conditions is required, together with the acquisition of the structure’s strain field with optimized sensor networks. The iFEM model definition is not trivial in the case of complex structures, in particular, if sensors are not applied on the whole structure allowing just a partial definition of the input strain field. To overcome this issue, this research proposes a simplified iFEM model in which the geometrical complexity is reduced and boundary conditions are tuned with the superimposition of the effects to behave as the real structure. The procedure is assessed for a complex aeronautical structure, where the reference displacement field is first computed in a numerical framework with input strains coming from a direct finite element analysis, confirming the effectiveness of the iFEM based on a simplified geometry. Finally, the model is fed with experimentally acquired strain measurements and the performance of the method is assessed in presence of a high level of uncertainty.


Author(s):  
Ying Wang ◽  
Yiding Liu ◽  
Minna Xia

Big data is featured by multiple sources and heterogeneity. Based on the big data platform of Hadoop and spark, a hybrid analysis on forest fire is built in this study. This platform combines the big data analysis and processing technology, and learns from the research results of different technical fields, such as forest fire monitoring. In this system, HDFS of Hadoop is used to store all kinds of data, spark module is used to provide various big data analysis methods, and visualization tools are used to realize the visualization of analysis results, such as Echarts, ArcGIS and unity3d. Finally, an experiment for forest fire point detection is designed so as to corroborate the feasibility and effectiveness, and provide some meaningful guidance for the follow-up research and the establishment of forest fire monitoring and visualized early warning big data platform. However, there are two shortcomings in this experiment: more data types should be selected. At the same time, if the original data can be converted to XML format, the compatibility is better. It is expected that the above problems can be solved in the follow-up research.


2021 ◽  
Vol 47 (1) ◽  
Author(s):  
Houda Ajmi ◽  
Wissem Besghaier ◽  
Wafa Kallala ◽  
Abdelhalim Trabelsi ◽  
Saoussan Abroug

Abstract Background Children affected by Coronavirus disease 2019 (COVID-19) showed various manifestations. Some of them were severe cases presenting with multi-system inflammatory syndrome (MIS-C) causing multiple organ dysfunction. Case presentation We report the case of a 12-year-old girl with recent COVID-19 infection who presented with persistent fever, abdominal pain and other symptoms that meet the definition of MIS-C. She had lymphopenia and a high level of inflammatory markers. She was admitted to pediatric intensive care unit since she rapidly developed refractory catecholamine-resistant shock with multiple organ failure. Echocardiography showed a small pericardial effusion with a normal ejection fraction (Ejection Fraction = 60%) and no valvular or coronary lesions. The child showed no signs of improvement even after receiving intravenous immunoglobulin, fresh frozen plasma, high doses of Vasopressors and corticosteroid. His outcome was fatal. Conclusion Pediatric patients affected by the new COVID-19 related syndrome may show severe life-threatening conditions similar to Kawasaki disease shock syndrome. Hypotension in these patients results from heart failure and the decreased cardiac output. We report a new severe clinical feature of SARS-CoV-2 infection in children in whom hypotension was the result of refractory vasoplegia.


2021 ◽  
pp. 1-17
Author(s):  
N.I. Fisher ◽  
D.J. Trewin

Given the high level of global mobility, pandemics are likely to be more frequent, and with potentially devastating consequences for our way of life. With COVID-19, Australia is in relatively better shape than most other countries and is generally regarded as having managed the pandemic well. That said, we believe there is a critical need to start the process of learning from this pandemic to improve the quantitative information and related advice provided to policy makers. A dispassionate assessment of Australia’s health and economic response to the COVID-19 pandemic reveals some important inadequacies in the data, statistical analysis and interpretation used to guide Australia’s preparations and actions. For example, one key shortcoming has been the lack of data to obtain an early understanding of the extent of asymptomatic and mildly symptomatic cases or the differences across age groups, occupations or ethnic groups. Minimising the combined health, social and economic impacts of a novel virus depends critically on ongoing acquisition, integration, analysis, interpretation and presentation of a variety of data streams to inform the development, execution and monitoring of appropriate strategies. The article captures the essential quantitative components of such an approach for each of the four basic phases, from initial detection to post-pandemic. It also outlines the critical steps in each stage to enable policy makers to deal more efficiently and effectively with future such events, thus enhancing both the social and the economic welfare of its people. Although written in an Australian context, we believe most elements would apply to other countries as well.


Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1771
Author(s):  
Ferdinando Di Martino ◽  
Irina Perfilieva ◽  
Salvatore Sessa

Fuzzy transform is a technique applied to approximate a function of one or more variables applied by researchers in various image and data analysis. In this work we present a summary of a fuzzy transform method proposed in recent years in different data mining disciplines, such as the detection of relationships between features and the extraction of association rules, time series analysis, data classification. After having given the definition of the concept of Fuzzy Transform in one or more dimensions in which the constraint of sufficient data density with respect to fuzzy partitions is also explored, the data analysis approaches recently proposed in the literature based on the use of the Fuzzy Transform are analyzed. In particular, the strategies adopted in these approaches for managing the constraint of sufficient data density and the performance results obtained, compared with those measured by adopting other methods in the literature, are explored. The last section is dedicated to final considerations and future scenarios for using the Fuzzy Transform for the analysis of massive and high-dimensional data.


2021 ◽  
Author(s):  
Graziano Patti ◽  
Sabrina Grassi ◽  
Gabriele Morreale ◽  
Mauro Corrao ◽  
Sebastiano Imposa

AbstractThe occurrence of strong and abrupt rainfall, together with a wrong land use planning and an uncontrolled urban development, can constitute a risk for infrastructure and population. The water flow in the subsoil, under certain conditions, may cause underground cavities formation. This phenomena known as soil piping can evolve and generate the surface collapse. It is clear that such phenomena in densely urbanized areas represent an unpredictable and consistent risk factor, which can interfere with social activities. In this study a multidisciplinary approach aimed to obtain useful information for the mitigation of the risks associated with the occurrence of soil piping phenomena in urban areas has been developed. This approach is aimed at defining the causes of sudden soil subsidence events, as well as the definition of the extension and possible evolution of these instability areas. The information obtained from rainfall data analysis, together with a study of the morphological, geological and hydrogeological characteristics, have allowed us to evaluate the causes that have led to the formation of soil pipes. Furthermore, performance of 3D electrical resistivity surveys in the area affected by the instability have allowed us to estimate their extension in the subsoil and identifying the presence of further areas susceptible to instability.


Sign in / Sign up

Export Citation Format

Share Document