Material Design: User Input

2019 ◽  
pp. 127-150
Author(s):  
Venkata Keerti Kotaru
Keyword(s):  
Material Design ◽  
User Input

A Model for Structured Data Entry Based on Explicit Descriptional Knowledge

1994 ◽  
Vol 33 (05) ◽  
pp. 454-463 ◽  
Author(s):  
A. M. van Ginneken ◽  
J. van der Lei ◽  
J. H. van Bemmel ◽  
P. W. Moorman
Keyword(s):  
Domain Knowledge ◽  
Data Entry ◽  
Knowledge Bases ◽  
Structured Data ◽  
Research Quality ◽  
Free Text ◽  
Specific Knowledge ◽  
User Input ◽  
The One ◽  
Research Quality Assessment

Abstract:Clinical narratives in patient records are usually recorded in free text, limiting the use of this information for research, quality assessment, and decision support. This study focuses on the capture of clinical narratives in a structured format by supporting physicians with structured data entry (SDE). We analyzed and made explicit which requirements SDE should meet to be acceptable for the physician on the one hand, and generate unambiguous patient data on the other. Starting from these requirements, we found that in order to support SDE, the knowledge on which it is based needs to be made explicit: we refer to this knowledge as descriptional knowledge. We articulate the nature of this knowledge, and propose a model in which it can be formally represented. The model allows the construction of specific knowledge bases, each representing the knowledge needed to support SDE within a circumscribed domain. Data entry is made possible through a general entry program, of which the behavior is determined by a combination of user input and the content of the applicable domain knowledge base. We clarify how descriptional knowledge is represented, modeled, and used for data entry to achieve SDE, which meets the proposed requirements.

ORGANIC (1).pdf

2017 ◽  
Author(s):  
Benjamin Sanchez-Lengeling ◽  
Carlos Outeiral ◽  
Gabriel L. Guimaraes ◽  
Alan Aspuru-Guzik
Keyword(s):  
Machine Learning ◽  
Learning Community ◽  
Chemical Species ◽  
Material Design ◽  
Organic Photovoltaic ◽  
Generative Adversarial Networks ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Adversarial Networks ◽  
Photovoltaic Material

Molecular discovery seeks to generate chemical species tailored to very specific needs. In this paper, we present ORGANIC, a framework based on Objective-Reinforced Generative Adversarial Networks (ORGAN), capable of producing a distribution over molecular space that matches with a certain set of desirable metrics. This methodology combines two successful techniques from the machine learning community: a Generative Adversarial Network (GAN), to create non-repetitive sensible molecular species, and Reinforcement Learning (RL), to bias this generative distribution towards certain attributes. We explore several applications, from optimization of random physicochemical properties to candidates for drug discovery and organic photovoltaic material design.

New Insights into the Nature of the Band Gap of CuGeO3 Nanoparticles: Synthesis, Electronic Structure, and Optical and Photocatalytic Properties

2019 ◽  
Author(s):  
Victor Y. Suzuki ◽  
Luís Henrique Cardozo Amorin ◽  
Natália H. de Paula ◽  
Anderson R. Albuquerque ◽  
Julio Ricardo Sambrano ◽  
...  
Keyword(s):  
Electronic Structure ◽  
Band Gap ◽  
Material Design ◽  
Photocatalytic Properties ◽  
Critical Parameters ◽  
Synthetic Approach ◽  
Microwave Assisted ◽  
Theoretical Approaches ◽  
Nanoparticles Synthesis ◽  
First Time

<p>We report, for the first time, new insights into the nature of the band gap of <a>CuGeO<sub>3</sub> </a>(CGO) nanocrystals synthesized from a microwave-assisted hydrothermal method in the presence of citrate. To the best of our knowledge, this synthetic approach has the shortest reaction time and it works at the lowest temperatures reported in the literature for the preparation of these materials. The influence of the surfactant on the structural, electronic, optical, and photocatalytic properties of CGO nanocrystals is discussed by a combination of experimental and theoretical approaches, and that results elucidates the nature of the band gap of synthetized CGO nanocrystals. We believe that this particular strategy is one of the most critical parameters for the development of innovative applications and that result could shed some light on the emerging material design with entirely new properties.</p> <p><b> </b></p>

Pengembangan Bahan Ajar Mata Pelajaran Sosiologi Siswa Madrasah Aliyah

2017 ◽  
Vol 2 (1) ◽  
pp. 51
Author(s):  
Wagimin Wagimin
Keyword(s):  
High School ◽  
Small Group ◽  
Field Test ◽  
Instructional Material ◽  
Material Design ◽  
Teaching Sociology ◽  
One To One ◽  
Teaching Learning ◽  
Developing Method ◽  
Test Result

Abstract Penelitian ini bertujuan untuk mengembangkan perangkat materi pembelajaran untuk pengajaran sosiologi guna memotivasi siswa. Penelitian ini menggunakan metode penelitian dan pengembangan guna menformulasi produk dan mengukur efektifitasnya melalui validasi dan pengujian ahli di bidangnya. Ada tiga tipe test yang digunakan yaitu, one to one, small group, dan field test yang menunjukkan bahwa desain materi tersebut efektif. Setelah melalui revisi, desain meteri pembelajaran Sosiologi dianggap bermanfaat dan dapat digunakan dalam proses belajar mengajar Kata Kunci: Perangkat pembelajaran, mata pelajaran Sosiologi, siswa Madrasah Aliyah Abstract [Tittle: The Development of Sosiology Instructional Material for The Students fo Islamic Senior High School] . The research aims at developing a set of instructional material for teaching Sociology in order to motivate the students. The researcher employed a research and developing method to formulate a product and to measure its effectiveness through validation and trial-out by the experts of content-material and material-design. There were three types of trial to test the design; one to one, small group, and field test. Based on the test result, it was found that students in average can achieve 84% of overall score which indicate that the designed material is effective. After being revised several times in each stage, the design of instructional material for Sociology subject is considered as beneficial and able to be used in the teaching learning process

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

Ultrasonic Torsion Welding of Aging Resistant Al/CFRP Joints - Concepts, Mechanical and Microstructural Properties

2017 ◽  
Vol 742 ◽  
pp. 395-400 ◽  
Author(s):  
Florian Staab ◽  
Frank Balle ◽  
Johannes Born
Keyword(s):  
Mechanical Properties ◽  
Process Parameters ◽  
Materials Science ◽  
Dissimilar Materials ◽  
Material Design ◽  
Ultrasonic Welding ◽  
Fatigue Properties ◽  
Aviation Industry ◽  
Efficient Design ◽  
Engineering Structures

Multi-material-design offers high potential for weight saving and optimization of engineering structures but inherits challenges as well, especially robust joining methods and long-term properties of hybrid structures. The application of joining techniques like ultrasonic welding allows a very efficient design of multi-material-components to enable further use of material specific advantages and are superior concerning mechanical properties.The Institute of Materials Science and Engineering of the University of Kaiserslautern (WKK) has a long-time experience on ultrasonic welding of dissimilar materials, for example different kinds of CFRP, light metals, steels or even glasses and ceramics. The mechanical properties are mostly optimized by using ideal process parameters, determined through statistical test planning methods.This gained knowledge is now to be transferred to application in aviation industry in cooperation with CTC GmbH and Airbus Operations GmbH. Therefore aircraft-related materials are joined by ultrasonic welding. The applied process parameters are recorded and analyzed in detail to be interlinked with the resulting mechanical properties of the hybrid joints. Aircraft derived multi-material demonstrators will be designed, manufactured and characterized with respect to their monotonic and fatigue properties as well as their resistance to aging.

LIRKIS Global Collaborative Virtual Environments: Current State and Utilization Perspective

2020 ◽  
Vol 11 (1) ◽  
pp. 99-106
Author(s):  
Marián Hudák ◽  
Štefan Korečko ◽  
Branislav Sobota
Keyword(s):  
Virtual Reality ◽  
Virtual Environments ◽  
Smart Devices ◽  
Collaborative Virtual Environments ◽  
Web Based ◽  
Smart Client ◽  
Input Devices ◽  
User Input ◽  
History Of ◽  
Shared Virtual Environments

AbstractRecent advances in the field of web technologies, including the increasing support of virtual reality hardware, have allowed for shared virtual environments, reachable by just entering a URL in a browser. One contemporary solution that provides such a shared virtual reality is LIRKIS Global Collaborative Virtual Environments (LIRKIS G-CVE). It is a web-based software system, built on top of the A-Frame and Networked-Aframe frameworks. This paper describes LIRKIS G-CVE and introduces its two original components. The first one is the Smart-Client Interface, which turns smart devices, such as smartphones and tablets, into input devices. The advantage of this component over the standard way of user input is demonstrated by a series of experiments. The second component is the Enhanced Client Access layer, which provides access to positions and orientations of clients that share a virtual environment. The layer also stores a history of connected clients and provides limited control over the clients. The paper also outlines an ongoing experiment aimed at an evaluation of LIRKIS G-CVE in the area of virtual prototype testing.

scholarly journals Material-Driven Textile Design (MDTD): A Methodology for Designing Circular Material-Driven Fabrication and Finishing Processes in the Materials Science Laboratory

2021 ◽  
Vol 13 (3) ◽  
pp. 1268
Author(s):  
Miriam Ribul ◽  
Kate Goldsworthy ◽  
Carole Collet
Keyword(s):  
Design Research ◽  
Materials Science ◽  
Material Design ◽  
Scientific Development ◽  
Regenerated Cellulose ◽  
Science Laboratory ◽  
Textile Composite ◽  
Specific Product ◽  
Textile Design ◽  
Finishing Processes

In the context of the circular economy, materials in scientific development present opportunities for material design processes that begin at a raw state, before being introduced into established processes and applications. The common separation of the scientific development of materials from design intervention results in a lack of methodological approaches enabling designers to inform new processes that respond to new material properties. This paper presents the results of a PhD investigation that led to the development and application of a Material-Driven Textile Design (MDTD) methodology for design research based in the materials science laboratory. It also presents the development of the fabrication of a textile composite with regenerated cellulose obtained from waste textiles, resulting from the MDTD methodology informing novel textile processes. The methods and practice which make up this methodology include distinct phases of exploration, translation and activation, and were developed via three design-led research residencies in materials science laboratories in Europe. The MDTD methodology proposes an approach to design research in a scientific setting that is decoupled from a specific product or application in order to lift disciplinary boundaries for the development of circular material-driven fabrication and finishing processes at the intersection of materials science and design.

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