scholarly journals DATA DRIVEN PERFORMANCE EVALUATION IN SHIPBUILDING

Brodogradnja ◽  
2020 ◽  
Vol 71 (4) ◽  
pp. 39-51
Author(s):  
Umran Bilen ◽  
◽  
Sebnem Helvacioglu
Keyword(s):  
Cost Estimation ◽  
Structural Design ◽  
Data Science ◽  
Rapid Development ◽  
Estimation Algorithm ◽  
Data Driven ◽  
Medium Size ◽  
Analysis Techniques ◽  
Use Of Data ◽  
Evaluation Of Performance

Rapid development in data science keeps paving the way for use of data for many purposes in shipbuilding, both for product development and production, such as Industry 4.0 have been developing many industries. Similar to other industries the evaluation of performance in shipbuilding is the key to success which is closely connected to productivity and lowered costs. Data mining and analysis techniques are used to create effective algorithms to evaluate the performance, also by means of cost estimation based on parametric methods. However, it is usually not very clear how data are collected, organised and prepared for analysing and deriving valuable knowledge as well as algorithms. In most of the cases, having this data requires either continuous investment in expensive software or expensive external expertise which are generally not available for small and medium size shipyards. In this study, considering the needs of the small and medium sized shipyards, a step-by-step methodology is proposed which could be easily applied with widely available low budget software. The application is demonstrated with a case to evaluate the performance of early phase structural design with a data driven cost estimation algorithm.

Things and Data in Recent Biology

2018 ◽  
Vol 48 (5) ◽  
pp. 648-658
Author(s):  
Soraya de Chadarevian
Keyword(s):  
Life Cycle ◽  
Biological Material ◽  
Data Science ◽  
Data Driven ◽  
Special Issue ◽  
Data Link ◽  
Use Of Data ◽  
Data Practices ◽  
In Silico Biology ◽  
Biological World

There is much talk about data-driven and in silico biology, but how exactly does it work? This essay reflects on the relation of data practices to the biological things from which they are abstracted. Looking at concrete examples of computer use in biology, the essay asks: How are biological things turned into data? What organizes and limits the combination, querying, and re-use of data? And how does the work on data link back to the organismic or biological world? Considering the life cycle of data, the essay suggests that data remain linked to the biological material and the concrete context from which they are extracted and to which they always refer back. Consequently, the transition to data science is never complete. This essay is part of a special issue entitled Histories of Data and the Database edited by Soraya de Chadarevian and Theodore M. Porter.

scholarly journals Vernacular Visualization Practices

2019 ◽  
Author(s):  
Jaime Snyder
Keyword(s):  
Human Computer Interaction ◽  
Data Science ◽  
Evaluation Criteria ◽  
Visual Representations ◽  
Data Driven ◽  
Use Of Data ◽  
Methodological Approaches ◽  
The Creation ◽  
Computer Interaction

In this essay, I define and discuss vernacular visualization practices: the creation and use of data-driven visual representations by individuals untrained in design or data science, in contrast to formal or expert visualization practices. Vernacular visualization practices reflect local and situated resources, requirements, evaluation criteria, and final outputs. In these contexts, individuals sometimes choose to make design choices that differ from those vetted by experts. These differences surface opportunities for deeper understanding of visualizations in communicating data-driven information to diverse audiences and among stakeholders with heterogenous expertise and needs. To support this argument, I discuss the origins of the concept of vernacular visualization practices, highlight related trends in human-computer interaction (HCI) research, and then briefly describe some methodological approaches for studying them.

scholarly journals Flipped healthcare for better or worse

2019 ◽  
Vol 25 (3) ◽  
pp. 587-597 ◽  
Author(s):  
Helena Vallo Hult ◽  
Anders Hansson ◽  
Lars Svensson ◽  
Martin Gellerstedt
Keyword(s):  
Professional Practice ◽  
Cultural Change ◽  
Medical Profession ◽  
Rapid Development ◽  
Data Driven ◽  
Use Of Data ◽  
Resident Physicians ◽  
Clinical Scenarios ◽  
Online Sources

The medical profession is highly specialized, demanding continuous learning, while also undergoing rapid development in the rise of data-driven healthcare. Based on clinical scenarios, this study explores how resident physicians view their roles and practices in relation to informed patients and patient-centric digital technologies. The paper illustrates how the new role of patients alters physicians’ work and use of data to learn and update their professional practice. It suggests new possibilities for developing collegial competence and using patient experiences more systematically. Drawing on the notion of flipped healthcare, we argue that there is a need for new professional competencies in everyday data work, along with a change in attitudes, newly defined roles, and better ways to identify and develop reliable online sources. Finally, the role of patients, not only as consumers but also producers of healthcare, is a rather formidable and complex cultural change to be addressed.

Water bilayers on ZnO(101̄0) surfaces: data-driven structural search

RSC Advances ◽  
2016 ◽  
Vol 6 (37) ◽  
pp. 30928-30936 ◽  
Author(s):  
Hugh F. Wilson ◽  
Amanda S. Barnard
Keyword(s):  
Ab Initio ◽  
High Stability ◽  
Data Science ◽  
Data Driven ◽  
Science Methods ◽  
Large Set ◽  
Atomic Structures ◽  
Use Of Data ◽  
Structural Search

We demonstrate an approach for the use of data science methods for structural search for high-stability atomic structures in ab initio simulation, via the analysis of a large set of candidate structures.

STRATEGI PRODUK BORDIR DI KAPALO KOTO, KOTO TANGAH SIMALANGGANG, KOTA PAYAKUMBUH (Studi Kasus di Usaha Bordir Limpapeh”s Kebaya)

2019 ◽  
Vol 8 (1) ◽  
pp. 111
Author(s):  
Riris Susiani ◽  
Ernawati Ernawati
Keyword(s):  
Rapid Development ◽  
Secondary Data ◽  
Export Market ◽  
Product Strategy ◽  
Analysis Techniques ◽  
Product Service ◽  
Qualitative Descriptive ◽  
The Subject ◽  
The Times ◽  
Descriptive Method

AbstrakMasalah dalam penelitian ini yaitu pentingnya strategi produk dalam menjalankan sebuah usaha agar mampu bertahan dan bersaing  dengan perusahaan lain yang sejenis dalam kondisi persaingan yang ketat dan perkembangan zaman yang sangat cepat. Strategi produk sangat diperlukan dalam mememenuhi tuntutan konsumen seperti meningkatkan kualitas, menciptakan merek, pelayanan serta jaminan terhadap produk yang ditawarkan agar usaha mampu berkembang. Limpapeh”s Kebaya adalah usaha yang sedang berkembang dan telah mampu memasarkan produk bordirnya hingga menembus pasar ekspor. Penelitian ini bertujuan untuk mendeskripsikan strategi produk bordir di Limpapeh”s Kebaya, Kapalo Koto, Koto Tangah Simalanggang, Kota Payakumbuh. Metode penelitian menggunakan metode deskriftif kualitatif, jenis data berupa data primer dan  sekunder. Teknik pengumpulan data melalui observasi, wawancara dan dokumentasi. Teknik analisis data dilakukan dengan teknik analisa model interaktif yang berkaitan dengan pokok permasalahan yaitu dengan model reduksi data, penyajian data dan pengambilan kesimpulan. Hasil penelitian yaitu strategi produk yang dilakukan di Limpapeh”s Kebaya adalah dimulai dari menciptakan produk bordir yang berkualitas, desain motif bordir yang up to date dan kreatif, menyediakan ukuran yang special, memberi merek pada produk bordir, memberi kemasan yang menarik (paperbag) dan serbaguna, pelayanan yang cepat, tepat dan ramah serta pemberian jaminan terhadap produk border.Kata Kunci: strategi produk, pelayanan, bordir. AbstractThe problem in this study is the importance of product strategy in running a business in order to be able to survive and compete with other similar companies in conditions of intense competition and very rapid development of the times. Product strategy is very necessary in fulfilling consumer demands such as improving quality, creating brands, services and guarantees for products offered so that businesses are able to grow. Limpapeh's Kebaya is a growing business and has been able to market its embroidery products to penetrate the export market. This study aims to describe the strategy of embroidery products in Limpapeh's Kebaya, Kapalo Koto, Koto Tangah Simalanggang, Payakumbuh City. The research method uses qualitative descriptive method, the type of data in the form of primary and secondary data. The technique of collecting data through observation, interviews and documentation. Data analysis techniques are carried out with interactive model analysis techniques that are related to the subject matter, namely with a model of data reduction, data presentation and conclusion. The results of the research, namely the product strategy carried out at Limpapeh's Kebaya, are started from creating quality embroidery products, up-to-date and creative embroidery motifs, providing special sizes, giving brands to embroidery products, giving attractive packaging (paperbag) and versatile, fast, precise and friendly service and guarantee of embroidery products. Keywords: product, service, embroidery strategy.

The Oxford Handbook of Ethics of AI

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Rapid Development ◽  
Data Driven ◽  
International Human Rights Law ◽  
Human Knowledge ◽  
Human Rights Law ◽  
Ai Ethics ◽  
And Behavior ◽  
Control Complex

This book explores the intertwining domains of artificial intelligence (AI) and ethics—two highly divergent fields which at first seem to have nothing to do with one another. AI is a collection of computational methods for studying human knowledge, learning, and behavior, including by building agents able to know, learn, and behave. Ethics is a body of human knowledge—far from completely understood—that helps agents (humans today, but perhaps eventually robots and other AIs) decide how they and others should behave. Despite these differences, however, the rapid development in AI technology today has led to a growing number of ethical issues in a multitude of fields, ranging from disciplines as far-reaching as international human rights law to issues as intimate as personal identity and sexuality. In fact, the number and variety of topics in this volume illustrate the width, diversity of content, and at times exasperating vagueness of the boundaries of “AI Ethics” as a domain of inquiry. Within this discourse, the book points to the capacity of sociotechnical systems that utilize data-driven algorithms to classify, to make decisions, and to control complex systems. Given the wide-reaching and often intimate impact these AI systems have on daily human lives, this volume attempts to address the increasingly complicated relations between humanity and artificial intelligence. It considers not only how humanity must conduct themselves toward AI but also how AI must behave toward humanity.

scholarly journals On the Experimental, Numerical and Data-Driven Methods to Study Urban Flows

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1310
Author(s):  
Pablo Torres ◽  
Soledad Le Clainche ◽  
Ricardo Vinuesa
Keyword(s):  
Physical Phenomenon ◽  
Urban Pollution ◽  
Pollutant Dispersion ◽  
Urban Environments ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Thermal Fields ◽  
Use Of Data ◽  
Sustainability Challenges ◽  
New Research

Understanding the flow in urban environments is an increasingly relevant problem due to its significant impact on air quality and thermal effects in cities worldwide. In this review we provide an overview of efforts based on experiments and simulations to gain insight into this complex physical phenomenon. We highlight the relevance of coherent structures in urban flows, which are responsible for the pollutant-dispersion and thermal fields in the city. We also suggest a more widespread use of data-driven methods to characterize flow structures as a way to further understand the dynamics of urban flows, with the aim of tackling the important sustainability challenges associated with them. Artificial intelligence and urban flows should be combined into a new research line, where classical data-driven tools and machine-learning algorithms can shed light on the physical mechanisms associated with urban pollution.

scholarly journals Methodology for the Concept Design of Locally Reinforced Composites

2021 ◽  
Vol 11 (16) ◽  
pp. 7246
Author(s):  
Julius Moritz Berges ◽  
Georg Jacobs ◽  
Sebastian Stein ◽  
Jonathan Sprehe
Keyword(s):  
Cost Estimation ◽  
Structural Design ◽  
Early Stage ◽  
Parameter Study ◽  
Great Effort ◽  
Concept Design ◽  
Cost Weight ◽  
Reinforced Plastics ◽  
Fiber Reinforced Plastics ◽  
The Cost

Locally load-optimized fiber-based composites, the so-called tailored textiles (TT), offer the potential to reduce weight and cost compared to conventional fiber-reinforced plastics (FRP). However, the design of TT has a higher complexity compared to FRP. Current approaches, focusing on solving this complexity for multiple objectives (cost, weight, stiffness), require great effort and calculation time, which makes them unsuitable for serial applications. Therefore, in this paper, an approach for the efficient creation of simplified TT concept designs is presented. By combining simplified models for structural design and cost estimation, the most promising concepts, regarding the cost, weight, and stiffness of TT parts, can be identified. By performing a parameter study, the cost, weight, and stiffness optima of a sample part compared to a conventional FRP component can be determined. The cost and weight were reduced by 30% for the same stiffness. Applying this approach at an early stage of product development reduces the initial complexity of the subsequent detailed engineering design, e.g., by applying methods from the state of the art.

scholarly journals The INSESS-COVID19 Project. Evaluating the Impact of the COVID19 in Social Vulnerability While Preserving Privacy of Participants from Minority Subpopulations

2021 ◽  
Vol 11 (7) ◽  
pp. 3110
Author(s):  
Karina Gibert ◽  
Xavier Angerri
Keyword(s):  
Social Vulnerability ◽  
Data Science ◽  
Policy Design ◽  
Data Driven ◽  
Informed Decision Making ◽  
Technological Infrastructure ◽  
Moderate Number ◽  
Reliable Diagnosis ◽  
Multivariate Relationships ◽  
The Impact

In this paper, the results of the project INSESS-COVID19 are presented, as part of a special call owing to help in the COVID19 crisis in Catalonia. The technological infrastructure and methodology developed in this project allows the quick screening of a territory for a quick a reliable diagnosis in front of an unexpected situation by providing relevant decisional information to support informed decision-making and strategy and policy design. One of the challenges of the project was to extract valuable information from direct participatory processes where specific target profiles of citizens are consulted and to distribute the participation along the whole territory. Having a lot of variables with a moderate number of citizens involved (in this case about 1000) implies the risk of violating statistical secrecy when multivariate relationships are analyzed, thus putting in risk the anonymity of the participants as well as their safety when vulnerable populations are involved, as is the case of INSESS-COVID19. In this paper, the entire data-driven methodology developed in the project is presented and the dealing of the small subgroups of population for statistical secrecy preserving described. The methodology is reusable with any other underlying questionnaire as the data science and reporting parts are totally automatized.

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