Visualization for compressed natural gas(CNG) secondary station refilling behaviors

Data visualizations are recently used for providing an access to complex data and information. In this paper, the visualization method is adopted to find possible ways of improving CNG secondary filling station’s refilling efficiency. Based on single attribute of volume, initial and final pressure, the visualization results show that one possible way to improve refilling efficiency is to by avoid abnormal inefficient refilling behaviors with small volume, higher initial pressure or lower final pressure. Based on time, the visualization results, considering the periodic property of refilling behaviors, present another possible way to improve refilling efficiency through reducing inefficient use of time. From the refilling log’s visualization, it is found that there is room for improvement in refilling efficiency and possible improving ways are primary studied. But the reasons of these abnormal actions are needed to be studied in future research.

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Visualization approaches to support healthy aging: A systematic review

Journal of Innovation in Health Informatics ◽

10.14236/jhi.v23i3.860 ◽

2016 ◽

Vol 23 (3) ◽

pp. 600 ◽

Cited By ~ 4

Author(s):

Uba Backonja ◽

Nai-Ching Chi ◽

Yong Choi ◽

Amanda K Hall ◽

Thai Le ◽

...

Keyword(s):

Older Adults ◽

Health Behaviors ◽

Healthy Aging ◽

A Priori ◽

Aging In Place ◽

Future Research ◽

Health Technologies ◽

Data Visualizations ◽

Informatics Tools

Background: Health technologies have the potential to support the growing number of older adults who are aging in place. Many tools include visualizations (data visualizations, visualizations of physical representations). However, the role of visualizations in supporting aging in place remains largely unexplored.Objective: To synthesize and identify gaps in the literature evaluating visualizations (data visualizations and visualizations of physical representations), for informatics tools to support healthy aging.Methods: We conducted a search in CINAHL, Embase, Engineering Village, PsycINFO, PubMed, and Web of Science using a priori defined terms for publications in English describing community-based studies evaluating visualizations used by adults aged ≥65 years.Results: Six out of the identified 251 publications were eligible. Most studies were user studies and varied methodological quality. Three visualizations of virtual representations supported performing at-home exercises. Participants found visual representations either (a) helpful, motivational, and supported their understanding of their health behaviors or (b) not an improvement over alternatives. Three data visualizations supported understanding of one’s health. Participants were able to interpret data visualizations that used precise data and encodings that were more concrete better than those that did not provide precision or were abstract. Participants found data visualizations helpful in understanding their overall health and granular data.Conclusions: Studies we identified used visualizations to promote engagement in exercises or understandings of one’s health. Future research could overcome methodological limitations of studies we identified to develop visualizations that older adults could use with ease and accuracy to support their health behaviors and decision-making.

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A Comprehensive Survey on Local Differential Privacy

Security and Communication Networks ◽

10.1155/2020/8829523 ◽

2020 ◽

Vol 2020 ◽

pp. 1-29 ◽

Cited By ~ 1

Author(s):

Xingxing Xiong ◽

Shubo Liu ◽

Dan Li ◽

Zhaohui Cai ◽

Xiaoguang Niu

Keyword(s):

Big Data ◽

Data Analysis ◽

Statistical Learning ◽

Data Privacy ◽

Statistical Estimation ◽

Differential Privacy ◽

Future Research ◽

Reference Source ◽

Complex Data ◽

Comprehensive Survey

With the advent of the era of big data, privacy issues have been becoming a hot topic in public. Local differential privacy (LDP) is a state-of-the-art privacy preservation technique that allows to perform big data analysis (e.g., statistical estimation, statistical learning, and data mining) while guaranteeing each individual participant’s privacy. In this paper, we present a comprehensive survey of LDP. We first give an overview on the fundamental knowledge of LDP and its frameworks. We then introduce the mainstream privatization mechanisms and methods in detail from the perspective of frequency oracle and give insights into recent studied on private basic statistical estimation (e.g., frequency estimation and mean estimation) and complex statistical estimation (e.g., multivariate distribution estimation and private estimation over complex data) under LDP. Furthermore, we present current research circumstances on LDP including the private statistical learning/inferencing, private statistical data analysis, privacy amplification techniques for LDP, and some application fields under LDP. Finally, we identify future research directions and open challenges for LDP. This survey can serve as a good reference source for the research of LDP to deal with various privacy-related scenarios to be encountered in practice.

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Aesthetics and Clarity in Information Visualization: The Designer’s Perspective

Arts ◽

10.3390/arts7040072 ◽

2018 ◽

Vol 7 (4) ◽

pp. 72

Author(s):

Annemarie Quispel ◽

Alfons Maes ◽

Joost Schilperoord

Keyword(s):

Mass Media ◽

Data Visualization ◽

Information Visualization ◽

Information Design ◽

Future Research ◽

Good Design ◽

The Public ◽

Objective Information ◽

Data Visualizations ◽

Important Design

Designers are increasingly involved in creating ‘popular’ data visualizations in mass media. Scientists in the field of information visualization propose collaborations between designers and scientists in popular data visualization. They assume that designers put more emphasis on aesthetics than on clarity in their representation of data, and that they aim to convey subjective, rather than objective, information. We investigated designers’ criteria for good design for a broad audience by interviewing professional designers and by reviewing information design handbooks. Additionally, we investigated what might make a visualization aesthetically pleasing (attractive) in the view of the designers. Results show that, according to the information designers, clarity and aesthetics are the main criteria, with clarity being the most important. They aim to objectively inform the public, rather than conveying personal opinions. Furthermore, although aesthetics is considered important, design literature hardly addresses the characteristics of aesthetics, and designers find it hard to define what makes a visualization attractive. The few statements found point at interesting directions for future research.

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Detection of Leek Rust Disease under Field Conditions Using Hyperspectral Proximal Sensing and Machine Learning

Remote Sensing ◽

10.3390/rs13071341 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1341

Author(s):

Simon Appeltans ◽

Jan G. Pieters ◽

Abdul M. Mouazen

Keyword(s):

Machine Learning ◽

Field Conditions ◽

Environmental Cost ◽

Supervised Machine Learning ◽

Future Research ◽

Complex Data ◽

Rust Disease ◽

Proximal Sensing ◽

Full Field ◽

Extensive Evaluation

Rust disease is an important problem for leek cultivation worldwide. It reduces market value and in extreme cases destroys the entire harvest. Farmers have to resort to periodical full-field fungicide applications to prevent the spread of disease, once every 1 to 5 weeks, depending on the cultivar and weather conditions. This implies an economic cost for the farmer and an environmental cost for society. Hyperspectral sensors have been extensively used to address this issue in research, but their application in the field has been limited to a relatively low number of crops, excluding leek, due to the high investment costs and complex data gathering and analysis associated with these sensors. To fill this gap, a methodology was developed for detecting leek rust disease using hyperspectral proximal sensing data combined with supervised machine learning. First, a hyperspectral library was constructed containing 43,416 spectra with a waveband range of 400–1000 nm, measured under field conditions. Then, an extensive evaluation of 11 common classifiers was performed using the scikit-learn machine learning library in Python, combined with a variety of wavelength selection techniques and preprocessing strategies. The best performing model was a (linear) logistic regression model that was able to correctly classify rust disease with an accuracy of 98.14 %, using reflectance values at 556 and 661 nm, combined with the value of the first derivative at 511 nm. This model was used to classify unlabelled hyperspectral images, confirming that the model was able to accurately classify leek rust disease symptoms. It can be concluded that the results in this work are an important step towards the mapping of leek rust disease, and that future research is needed to overcome certain challenges before variable rate fungicide applications can be adopted against leek rust disease.

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Developmental Assets of Adolescents and Young Adults With Chronic Illness and Comorbid Depression: Qualitative Study Using YouTube (Preprint)

10.2196/preprints.23960 ◽

2020 ◽

Author(s):

Katherine Zheng ◽

Maureen George ◽

Eugene Roehlkepartain ◽

John Santelli ◽

Jean-Marie Bruzzese ◽

...

Keyword(s):

Young Adults ◽

Chronic Illness ◽

Developmental Assets ◽

Adolescents And Young Adults ◽

Future Research ◽

Comorbid Depression ◽

Use Of Time ◽

Identity Commitment ◽

Internal Assets ◽

Asset Development

BACKGROUND Developmental assets provide a framework for optimizing development among adolescents but have not been studied in adolescents with chronic illness and comorbid depression, which is a group at risk for poor health outcomes. YouTube postings provide valuable insights to understand this understudied population. OBJECTIVE This study aims to explore asset development from the perspectives of adolescents and young adults (AYAs) with chronic illness and comorbid depression. METHODS YouTube was searched using 12 chronic illnesses (eg, diabetes) coupled with “depression” as keywords. Videos were included if they were uploaded by AYAs aged between 11 and 29 years and discussed living with chronic illness and depression during adolescence. Video transcripts were coded deductively for 40 internal and external assets that constitute the Developmental Assets Framework. Categories not captured by deductive coding were identified using conventional content analysis. Categories and their respective assets were labeled as being discussed either negatively or positively. RESULTS In total, 31 videos from 16 AYAs met the inclusion criteria. A total of 7 asset categories, support, constructive use of time, boundaries and expectations (external assets), identity, commitment to learning, positive values, and social competence (internal assets), reflecting 25 (13 internal; 12 external) assets, were discussed. Internal assets, particularly relating to identity, were commonly discussed by AYAs either in a negative way or fluctuated between positive and negative perspectives. CONCLUSIONS In this sample of AYAs with chronic illness and comorbid depression, internal assets were commonly discussed in a negative way. Future research is needed to better understand how assets develop and if the Developmental Assets Framework adequately represents the experiences of this population.

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Design and Manufacture of Composite CNG Cylinders

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.670-671.955 ◽

2014 ◽

Vol 670-671 ◽

pp. 955-959 ◽

Cited By ~ 2

Author(s):

Long Shi Gao

Keyword(s):

Natural Gas ◽

Future Research ◽

Compressed Natural Gas ◽

Filament Wound ◽

Filament Wound Composite ◽

Design And Manufacture ◽

Wound Composite

The design of filament-wound composite Compressed Natural Gas (CNG) cylinders was reviewed, including the liner and filament-wound reinforcement part. The domestic and abroad standards are discussed here. It is of great significance to improving composite CNG cylinders safely. The focus of future research is summarized finally.

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UNSUPERVISED ENSEMBLE CLASSIFICATION FOR BIOMETRIC APPLICATIONS

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001414560072 ◽

2014 ◽

Vol 28 (04) ◽

pp. 1456007 ◽

Cited By ~ 4

Author(s):

ANA CERNEA ◽

JUAN. LUIS. FERNÁNDEZ-MARTÍNEZ

Keyword(s):

Face Recognition ◽

Ensemble Learning ◽

Nearest Neighbor ◽

Ensemble Classification ◽

Future Research ◽

Ensemble Classifiers ◽

Ensemble Techniques ◽

Single Attribute ◽

Consensus Classification ◽

The Individual

In this paper, we propose different ensemble learning algorithms and their application to the face recognition problem. Three types of attributes are used for image representation: statistical, spectral, and segmentation features and regional descriptors. Classification is performed by nearest neighbor using different p-norms defined in the corresponding spaces of attributes. In this approach, each attribute together with its corresponding type of the analysis (local or global) and the distance criterion (norm or cosine), define a different classifier. The classification is unsupervised since no class information is used to improve the design of the different classifiers. Three different versions of ensemble classifiers are proposed in this paper: CAV1, CAV2, and CBAG, being the main differences among them the way the image candidates that perform the consensus are selected. The main results shown in this paper are the following: 1. The statistical attributes (local histogram and percentiles) are the individual classifiers that provided the higher accuracies, followed by the spectral methods (DWT), and the regional features (texture analysis). 2. No single attribute is able to provide systematically 100% accuracy over the ORL database. 3. The accuracy and stability of the classification is increased by consensus classification (ensemble learning techniques). 4. Optimum results are obtained by reducing the number of classifiers taking into account their diversity, and by optimizing the parameters of these classifiers using a member of the Particle Swarm Optimization (PSO) family. These results are in accord with the conclusions that are presented in the literature using ensemble learning methodologies, that is, it is possible to build strong classifiers by assembling different weak (or simple) classifiers based on different and diverse image attributes. Due to these encouraging results, future research will be devoted to the use of supervised ensemble techniques in face recognition and in other important biometric problems.

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Classification and Review of Pump-Controlled Differential Cylinder Drives

Energies ◽

10.3390/en12071293 ◽

2019 ◽

Vol 12 (7) ◽

pp. 1293 ◽

Cited By ~ 15

Author(s):

Søren Ketelsen ◽

Damiano Padovani ◽

Torben Andersen ◽

Morten Ebbesen ◽

Lasse Schmidt

Keyword(s):

Small Volume ◽

Hydraulic Cylinder ◽

Future Research ◽

Hydraulic Systems ◽

Hydraulic Circuit ◽

Variable Speed ◽

Electric Drives ◽

Variable Displacement ◽

Oil Tank ◽

Pump Controlled Cylinder

Pump-controlled hydraulic cylinder drives may offer improved energy efficiency, compactness, and plug-and-play installation compared to conventional valve-controlled hydraulic systems and thus have the potential of replacing conventional hydraulic systems as well as electro-mechanical alternatives. Since the late 1980s, research into how to configure the hydraulic circuit of pump-controlled cylinder drives has been ongoing, especially in terms of compensating the uneven flow requirements required by a differential cylinder. Recently, research has also focused on other aspects such as replacing a vented oil tank with a small-volume pressurized accumulator including the consequences of this in terms of thermal behavior. Numerous references describe the advantages and shortcomings of pump-controlled cylinder drives compared to conventional hydraulic systems or electro-mechanical drives. This paper presents a throughout literature review starting from the earliest concepts based on variable-displacement hydraulic pumps and vented reservoirs to newer concepts based on variable-speed electric drives and sealed reservoirs. By classifying these drives into several proposed classes it is found that the architectures considered in the literature reduce to a few basic layouts. Finally, the paper compares the advantages and shortcomings of each drive class and seek to predict future research tasks related to pump-controlled cylinder drives.

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Dam Siting: A Review

Water ◽

10.3390/w13152080 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2080

Author(s):

Yang Wang ◽

Yongzhong Tian ◽

Yan Cao

Keyword(s):

Machine Learning ◽

Power Generation ◽

Site Selection ◽

Flood Control ◽

Research Literature ◽

Future Research ◽

Complex Data ◽

Geological Conditions ◽

Selection Factors ◽

The Impact

Dams can effectively regulate the spatial and temporal distribution of water resources, where the rationality of dam siting determines whether the role of dams can be effectively performed. This paper reviews the research literature on dam siting in the past 20 years, discusses the methods used for dam siting, focuses on the factors influencing dam siting, and assesses the impact of different dam functions on siting factors. The results show the following: (1) Existing siting methods can be categorized into three types—namely, GIS/RS-based siting, MCDM- and MCDM-GIS-based siting, and machine learning-based siting. GIS/RS emphasizes the ability to capture and analyze data, MCDM has the advantage of weighing the importance of the relationship between multiple factors, and machine learning methods have a strong ability to learn and process complex data. (2) Site selection factors vary greatly, depending on the function of the dam. For dams with irrigation and water supply as the main purpose, the site selection is more focused on the evaluation of water quality. For dams with power generation as the main purpose, the hydrological factors characterizing the power generation potential are the most important. For dams with flood control as the main purpose, the topography and geological conditions are more important. (3) The integration of different siting methods and the siting of new functional dams in the existing research is not sufficient. Future research should focus on the integration of different methods and disciplines, in order to explore the siting of new types of dams.

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Spirals, spikes and spinning wheels: Temporal models challenging the sustainability agenda in relation to fast fashion consumption

Fashion Style & Popular Culture ◽

10.1386/fspc_00098_1 ◽

2021 ◽

Vol 8 (4) ◽

pp. 387-397 ◽

Cited By ~ 1

Author(s):

Helen Powell

Keyword(s):

Consumer Behaviour ◽

Temporal Dynamics ◽

Future Research ◽

Specific Reference ◽

Political Arena ◽

Fast Fashion ◽

Use Of Time ◽

Temporal Models ◽

Point Of Purchase ◽

Achievable Goal

Fast fashion has entered the political arena with specific reference to sustainability. To date the agenda has largely been informed by an examination of production methodologies and techniques documenting the rapid turnover of trends, the speed and efficiency of the production process and the lack of socially cohesive labour practices that it consistently engenders. Whilst governments seek to raise awareness and begin to generate initiatives to tackle the environmental fall out of fast fashion, this article turns its attention to the temporal patterns of consumer behaviour and why such a high percentage of what we buy is readily discarded soon after point of purchase. All stages in this linear model of consumption, it is argued, are shaped by a very specific relationship to time that ultimately informs our buying habits. Utilizing the work of the philosopher A. N. Whitehead and adopting a more psychosocial approach to fashion consumption, this article recognizes that even when purposefully seeking to consume sustainably, a greater need to align our use of time with a results-driven mindset locates the acquisition of something new as a highly achievable goal. As a consequence, rather than positioning the rationale for fashion purchases in the context of conspicuous consumption and emulation, here it functions to mitigate a lack of temporal control in other areas of our lives. In response, it is proposed that any successful attempts at tackling the problems associated with fast fashion must also seek to understand the temporal dynamics of consumption. For whilst governments’ attention is turned to ways to reduce the environmental impact associated with the production of clothing, increasing consumer demand derived from ‘neophilia’ will negate and indeed overturn any successes achieved. The conclusion will therefore suggest that promotional culture has a duty to explore ways in which it might engender greater emotional attachments to what we own. Future research into brand messaging, exploring the consequences of placing emphasis on quality over quantity and a subsequent potential deepening of a sense of brand loyalty, is also recommended as a way forward.

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