Introduction to the Atna research area

2004 ◽  
pp. 1-4
Author(s):  
Arve M. Tvede ◽  
Gunnar Halvorsen
Keyword(s):  
Research Area

Piezoelectric β-polymorph formation of new textiles by surface modification with coating process based on interfacial interaction on the conformational variation of poly (vinylidene fluoride) (PVDF) chains

2020 ◽  
Vol 91 (3) ◽  
pp. 31301
Author(s):  
Nabil Chakhchaoui ◽  
Rida Farhan ◽  
Meriem Boutaldat ◽  
Marwane Rouway ◽  
Adil Eddiai ◽  
...  
Keyword(s):  
High Efficiency ◽  
Vinylidene Fluoride ◽  
Research Work ◽  
Research Area ◽  
Interfacial Interaction ◽  
Tetraethyl Orthosilicate ◽  
Poly Vinylidene Fluoride ◽  
Carbon Nanofillers ◽  
The Impact ◽  
Advanced Applications

Novel textiles have received a lot of attention from researchers in the last decade due to some of their unique features. The introduction of intelligent materials into textile structures offers an opportunity to develop multifunctional textiles, such as sensing, reacting, conducting electricity and performing energy conversion operations. In this research work nanocomposite-based highly piezoelectric and electroactive β-phase new textile has been developed using the pad-dry-cure method. The deposition of poly (vinylidene fluoride) (PVDF) − carbon nanofillers (CNF) − tetraethyl orthosilicate (TEOS), Si(OCH2CH3)4 was acquired on a treated textile substrate using coating technique followed by evaporation to transform the passive (non-functional) textile into a dynamic textile with an enhanced piezoelectric β-phase. The aim of the study is the investigation of the impact the coating of textile via piezoelectric nanocomposites based PVDF-CNF (by optimizing piezoelectric crystalline phase). The chemical composition of CT/PVDF-CNC-TEOS textile was detected by qualitative elemental analysis (SEM/EDX). The added of 0.5% of CNF during the process provides material textiles with a piezoelectric β-phase of up to 50% has been measured by FTIR experiments. These results indicated that CNF has high efficiency in transforming the phase α introduced in the unloaded PVDF, to the β-phase in the case of nanocomposites. Consequently, this fabricated new textile exhibits glorious piezoelectric β-phase even with relatively low coating content of PVDF-CNF-TEOS. The study demonstrates that the pad-dry-cure method can potentially be used for the development of piezoelectric nanocomposite-coated wearable new textiles for sensors and energy harvesting applications. We believe that our study may inspire the research area for future advanced applications.

Modified fuzzy-based greedy routing protocol for VANETs

2020 ◽  
Vol 39 (6) ◽  
pp. 8357-8364
Author(s):  
Thompson Stephan ◽  
Ananthnarayan Rajappa ◽  
K.S. Sendhil Kumar ◽  
Shivang Gupta ◽  
Achyut Shankar ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Routing Protocol ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Research Area ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Greedy Routing ◽  
Hoc Networks

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

Overview and initial results of the National Center for Health Statistics’ Research and Development Survey1

2020 ◽  
Vol 36 (4) ◽  
pp. 1199-1211
Author(s):  
Jennifer Parker ◽  
Kristen Miller ◽  
Yulei He ◽  
Paul Scanlon ◽  
Bill Cai ◽  
...  
Keyword(s):  
Survey Data ◽  
Evaluation Studies ◽  
Research Area ◽  
Production Cycle ◽  
Response Patterns ◽  
Health Statistics ◽  
Mode Effects ◽  
Research Areas ◽  
Statistical Agencies ◽  
Initial Results

The National Center for Health Statistics is assessing the usefulness of recruited web panels in multiple research areas. One research area examines the use of close-ended probe questions and split-panel experiments for evaluating question-response patterns. Another research area is the development of statistical methodology to leverage the strength of national survey data to evaluate, and possibly improve, health estimates from recruited panels. Recruited web panels, with their lower cost and faster production cycle, in combination with established population health surveys, may be useful for some purposes for statistical agencies. Our initial results indicate that web survey data from a recruited panel can be used for question evaluation studies without affecting other survey content. However, the success of these data to provide estimates that align with those from large national surveys will depend on many factors, including further understanding of design features of the recruited panel (e.g. coverage and mode effects), the statistical methods and covariates used to obtain the original and adjusted weights, and the health outcomes of interest.

A Review and evaluation of Machine Translation methods for Lumasaaba

2020 ◽  
pp. 3-17
Author(s):  
Peter Nabende
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Machine Translation ◽  
Language Processing ◽  
Research Area ◽  
Data Driven ◽  
East African ◽  
Data Set ◽  
African Languages ◽  
Translation Methods

Natural Language Processing for under-resourced languages is now a mainstream research area. However, there are limited studies on Natural Language Processing applications for many indigenous East African languages. As a contribution to covering the current gap of knowledge, this paper focuses on evaluating the application of well-established machine translation methods for one heavily under-resourced indigenous East African language called Lumasaaba. Specifically, we review the most common machine translation methods in the context of Lumasaaba including both rule-based and data-driven methods. Then we apply a state of the art data-driven machine translation method to learn models for automating translation between Lumasaaba and English using a very limited data set of parallel sentences. Automatic evaluation results show that a transformer-based Neural Machine Translation model architecture leads to consistently better BLEU scores than the recurrent neural network-based models. Moreover, the automatically generated translations can be comprehended to a reasonable extent and are usually associated with the source language input.

Institutional Support of Innovative R&D in the Formation of Single Research Area in the EU and Ukraine

2017 ◽  
Vol 13 (2) ◽  
pp. 5-23 ◽  
Author(s):  
I.Yu. Matyushenko ◽  
◽  
V.Ye. Khaustova ◽  
S.I. Kniaziev ◽  
◽  
...  
Keyword(s):  
Institutional Support ◽  
Research Area ◽  
The Eu

Aichi-Rinku New Energy Research Area

2010 ◽  
Vol 130 (6) ◽  
pp. 336-339
Author(s):  
Masayuki YODA ◽  
Kazuto YUKITA ◽  
Yuki OHSHIMA ◽  
Kiyonori BAN ◽  
Maki FUJINAGA
Keyword(s):  
Research Area ◽  
Energy Research ◽  
New Energy

Document Image Quality Assessment with Relaying Reference to Determine Minimum Readable Resolution for Compression

2020 ◽  
Vol 2020 (9) ◽  
pp. 323-1-323-8
Author(s):  
Litao Hu ◽  
Zhenhua Hu ◽  
Peter Bauer ◽  
Todd J. Harris ◽  
Jan P. Allebach
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Research Area ◽  
Input Image ◽  
Quality Score ◽  
Document Image ◽  
Digital Cameras ◽  
Active Research ◽  
Traditional Approaches

Image quality assessment has been a very active research area in the field of image processing, and there have been numerous methods proposed. However, most of the existing methods focus on digital images that only or mainly contain pictures or photos taken by digital cameras. Traditional approaches evaluate an input image as a whole and try to estimate a quality score for the image, in order to give viewers an idea of how “good” the image looks. In this paper, we mainly focus on the quality evaluation of contents of symbols like texts, bar-codes, QR-codes, lines, and hand-writings in target images. Estimating a quality score for this kind of information can be based on whether or not it is readable by a human, or recognizable by a decoder. Moreover, we mainly study the viewing quality of the scanned document of a printed image. For this purpose, we propose a novel image quality assessment algorithm that is able to determine the readability of a scanned document or regions in a scanned document. Experimental results on some testing images demonstrate the effectiveness of our method.

An Enhancement of Feature Selection Algorithm for EDM: A Review

2018 ◽  
Vol 8 (5) ◽  
pp. 29
Author(s):  
Manpreet Kaur ◽  
Chamkaur Singh
Keyword(s):  
Feature Selection ◽  
Educational Data Mining ◽  
Problem Formulation ◽  
Research Area ◽  
Education Quality ◽  
Educational Institutions ◽  
Selection Algorithm ◽  
Positive Role ◽  
Data Set ◽  
Selection Algorithms

Educational Data Mining (EDM) is an emerging research area help the educational institutions to improve the performance of their students. Feature Selection (FS) algorithms remove irrelevant data from the educational dataset and hence increases the performance of classifiers used in EDM techniques. This paper present an analysis of the performance of feature selection algorithms on student data set. .In this papers the different problems that are defined in problem formulation. All these problems are resolved in future. Furthermore the paper is an attempt of playing a positive role in the improvement of education quality, as well as guides new researchers in making academic intervention.

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