Lifelog and Information Retrieval from Daily Digital Data: Narrative Review. (Preprint)

2021 ◽  
Author(s):  
Ricardo Ribeiro ◽  
Alina Trifan ◽  
António J. R. Neves
Keyword(s):  
Contextual Information ◽  
Life Quality ◽  
Research Area ◽  
Research Field ◽  
Narrative Review ◽  
Digital Data ◽  
Significant Information ◽  
Memory Problems ◽  
Wide Availability ◽  
And Behaviors

BACKGROUND The wide availability and small size, together with the decrease in pricing of different types of sensors, has made it possible, over the last decade, to acquire a huge amount of data about a person's life in real time. These sensors can be incorporated into personal electronic devices available at reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity and physiological signals, among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging. OBJECTIVE The goal of this article is to review the literature in the research area of lifelogging over the past decade and provide an historical overview on this research topic. To this purpose, we analyze lifelogging applications that monitor and assist people with memory problems. METHODS We follow a narrative review methodology to conduct a comprehensive search of relevant publications in Google Scholar and Scopus databases. In order to find these relevant publication, topic-related keywords were identified and combined based on different lifelogging type of data and applications. RESULTS A total of 124 publications were selected and included in this narrative review. 411 publications were retrieved and screened from the two scholar databases. Out of these, 114 publications were fully reviewed. In addition, 32 more publications were manually included based on our bibliographical knowledge in this research field. CONCLUSIONS The use of personal lifelogs can be beneficial to improve the life quality of people suffering from memory problems, such as dementia. Through the acquisition and analysis of lifelog data, lifelogging systems can create digital memories to be used as surrogate memory. Through this narrative we understand that contextual information can be extracted from the lifelogs and it provides significant information for understanding the daily life of people suffering from memory issues based on events, experiences and behaviors.

scholarly journals Optimization of bioethanol production from soybean molasses using different strains of Saccharomyces cerevisiae

2019 ◽  
Vol 73 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Zorana Roncevic ◽  
Bojana Bajic ◽  
Sinisa Dodic ◽  
Jovana Grahovac ◽  
Radmila Pajovic-Scepanovic ◽  
...  
Keyword(s):  
Fossil Fuels ◽  
Desirability Function ◽  
Sugar Content ◽  
Research Area ◽  
Cell Number ◽  
Research Field ◽  
Bioethanol Production ◽  
Fermentation Time ◽  
Wide Availability ◽  
Different Strains

Bioethanol technology represents an important scientific research area because of the high market value and wide availability of its primary and by-products. Worldwide interest in utilizing bioethanol as a renewable and sustainable energy source has significantly increased in the last few years due to limited reserves of fossil fuels and concerns about climate change. Therefore, improvement of the bioethanol production process is a priority research field at the international scale, due to both economic and environmental reasons. The aim of this study was to optimize production of bioethanol from soybean molasses based media using response surface methodology. Three different strains of the yeast Saccharomices cerevisiae, commercially available in dried form, were used as production microorganisms, and the best results were obtained by using dried baker?s yeast. The results of optimization of alcoholic fermentation using dried baker?s yeast indicate that the highest value of the overall desirability function (0.945) is obtained when the initial sugar content is 18.10 % (w/v) at the fermentation time of 48.00 h. At these conditions the model predicts that bioethanol concentration is 8.40 % (v/v), yeast cell number 2.21?108 cells/mL and the residual sugar content is 0.35 % (w/v).

scholarly journals Diketopyrrolopyrrole Fluorescent Probes, Photophysical and Biological Applications

Chemosensors ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 44
Author(s):  
Muhammad Aminu Auwalu ◽  
Shanshan Cheng
Keyword(s):  
Quantum Yield ◽  
Fluorescent Probes ◽  
Organic Dyes ◽  
Tumor Therapy ◽  
Research Area ◽  
Research Field ◽  
Review Article ◽  
Biological Applications ◽  
Chemistry Research ◽  
Cancer Tumor

Biological applications of fluorescent probes are rapidly increasing in the supramolecular chemistry research field. Several organic dyes are being utilized currently in developing and advancing this attractive research area, of which diketopyrrolopyrrole (DPP) organic dyes show an exceptional photophysical features (high-fluorescence quantum yield (FQY), good photochemical and thermal stability) that are essential properties for biological applications. Great efforts have been made in recent years towards developing novel fluorescent DPPs by different chemists for such applications, and some positive results have been reported. As a result, this review article gives an account of the progress that has so far been made very recently, mainly within the last decade, in that we selectively focus on and discuss more from 2015 to present on some recent scholarly achievements of fluorescent DPPs: quantum yield, aggregation-induced emission (AIE), solid-state emission, bio-imaging, cancer/tumor therapy, mitochondria staining and some polymeric fluorescent DPPs. Finally, this review article highlights researchers working on luminescent DPPs and the future prospects in some key areas towards designing DPP-based fluorescent probes in order to boost their photophysical and biological applications more effectively.

scholarly journals The Enabling Role of Digital Technologies in Sustainability Accounting: Findings from Norwegian Manufacturing Companies

Systems ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 33
Author(s):  
Olena Klymenko ◽  
Lise Lillebrygfjeld Halse ◽  
Bjørn Jæger
Keyword(s):  
Research Area ◽  
Digital Data ◽  
Manufacturing Companies ◽  
Sustainable Operations ◽  
Business Model Canvas ◽  
Automation And Control ◽  
Sustainability Accounting ◽  
And Control

Sustainability accounting is an emerging research area receiving growing awareness. This study examines the role of digital technology in manufacturing companies’ sustainability accounting. To guide the research, we use a triple layered business model canvas, which supports the accounting of a manufacturer’s performance for the economic, environmental, and social aspects of sustainability. We present an explorative case study of four Norwegian manufacturing companies representing different industries. The findings from the study indicate that while accounting for economic values is well taken care of, companies do not perform comprehensive environmental and social accounting. Furthermore, we observed a shift from a focus on sustainability issues related to the internal manufacturing process to a focus on sustainability issues for the life cycle of the product. Even though the manufacturers are at the forefront with regard to automation and control of production, with extensive use of robots giving a large amount of data, these data are not utilized towards sustainability accounting, showing that sustainability and digitalization are seen as two separate phenomena. This study sheds light on how digital data available from applied Industry 4.0 technologies could enhance sustainability accounting with limited efforts, linking sustainability and digitalization. The results provide insights for manufacturers and researchers in moving towards more sustainable operations and products.

scholarly journals Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4462 ◽  
Author(s):  
Paolo Baronti ◽  
Paolo Barsocchi ◽  
Stefano Chessa ◽  
Fabio Mavilia ◽  
Filippo Palumbo
Keyword(s):  
Social Interaction ◽  
Indoor Localization ◽  
Meaningful Use ◽  
Research Area ◽  
Low Energy ◽  
Bluetooth Low Energy ◽  
Novel Technologies ◽  
Wide Availability ◽  
Low Costs ◽  
Open Datasets

Indoor localization has become a mature research area, but further scientific developments are limited due to the lack of open datasets and corresponding frameworks suitable to compare and evaluate specialized localization solutions. Although several competitions provide datasets and environments for comparing different solutions, they hardly consider novel technologies such as Bluetooth Low Energy (BLE), which is gaining more and more importance in indoor localization due to its wide availability in personal and environmental devices and to its low costs and flexibility. This paper contributes to cover this gap by: (i) presenting a new indoor BLE dataset; (ii) reviewing several, meaningful use cases in different application scenarios; and (iii) discussing alternative uses of the dataset in the evaluation of different positioning and navigation applications, namely localization, tracking, occupancy and social interaction.

scholarly journals Usability Methods and Attributes Reported in Usability Studies of Mobile Apps for Health Care Education: Protocol for a Scoping Review

10.2196/19072 ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. e19072
Author(s):  
Susanne Grødem Johnson ◽  
Thomas Potrebny ◽  
Lillebeth Larun ◽  
Donna Ciliska ◽  
Nina Rydland Olsen
Keyword(s):  
Health Care ◽  
Scoping Review ◽  
Mobile Apps ◽  
Research Question ◽  
Grey Literature ◽  
Research Area ◽  
Research Field ◽  
Learning Technologies ◽  
Health Care Education ◽  
Care Education

Background E-learning technologies, including mobile apps, are used to a large extent in health care education. Mobile apps can provide extendable learning environments and motivate students for adaptive and collaborative learning outside the classroom context. Developers should design practical, effective, and easy-to-use mobile apps. Usability testing is an important part of app development in order to understand if apps meet the needs of users. Objective The aim of this study is to perform a scoping review of usability methods and attributes reported in usability studies of mobile apps for health care education. Methods The scoping review is guided by the methodological framework developed by Arksey & O’Malley and further developed by Levac et al and Kahlil et al. The stages we will follow are as follows: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies; (4) charting the data; and (5) summarizing and reporting the results. We have developed two research questions to meet the aim of the study, which are as follows: (1) What usability methods are used to evaluate the usability of mobile apps for health care education? and (2) What usability attributes are reported in the usability studies of mobile apps for health care education? We will apply a comprehensive search of the literature, including 10 databases, a reference search, and a search for grey literature. Two review authors will independently screen articles for eligibility. Results The initial electronic database searches were completed in March 2019. The literature search identified 14,297 unique references. Following title and abstract screening, the full texts of 369 records were obtained. The scoping review is expected to be completed in spring 2021. Conclusions We expect the overview of usability methods and attributes reported in usability studies of mobile apps for health care education to contribute to the knowledge base for researchers and developers. It will give an overview of the research field and provide researchers and developers with relevant and important information on the usability research area, including highlighting possible research gaps. International Registered Report Identifier (IRRID) DERR1-10.2196/19072

scholarly journals Reserva Extrativista Marinha Mestre Lucindo (PA): Processo de criação e perspectivas para o turismo

2017 ◽  
Vol 10 (2) ◽  
Author(s):  
Raul Ivan Raiol de Campos ◽  
Mara Dayane Silva Nascimento ◽  
Symone da Costa Mendonça
Keyword(s):  
Protected Area ◽  
Local Community ◽  
Marine Reserve ◽  
Life Quality ◽  
Field Research ◽  
Research Field ◽  
Daily Lives ◽  
Extractive Reserve ◽  
The People ◽  
Tourism Community

O objetivo geral do presente estudo foi analisar a participação e o envolvimento da comunidade local no processo de criação Reserva Extrativista Marinha Mestre Lucindo localizada no município de Marapanim no estado do Pará. Teve como objetivo específico identificar quais comunidades da REM que já trabalham com o turismo e saber as expectativas dos usuários da REM para o futuro do turismo na referida Unidade de Conservação. Para o desenvolvimento do estudo foram realizados levantamentos e análises em bibliografias que forneceram subsídios teóricos e conceituais para a pesquisa. A pesquisa de campo foi realizada com entrevistas e aplicação de questionários, bem como a observação do modo de vida de duas comunidades. Os resultados mostram que a maioria da população desconhece que seu território se tornou uma Unidade de Conservação, mas associam a criação da UC com a melhoria na qualidade de vida. O turismo acontece de forma desornada, embora a REM tenha grande potencial turístico. Porém, há falta de planejamento e organização. Propõe-se o planejamento do turismo de base comunitária para valorizar o conhecimento tradicional e atividades sustentáveis das comunidades locais. Mestre Lucindo Extractive Marine Reserve (PA, Brazil): Creation Process and Tourism Perspectives ABSTRACT The main objective of the current study was to analyze the participation and involvement of the local community in the process of creation of the Mestre Lucindo Extractive Marine Reserve located in the municipality of Marapanim in the state of Pará (Brazil). The specific objectives were to identify which communities of the Extractive Reserve already work with tourism and to know the expectations of the Reserve users for the future of tourism in this protected area. For the development of this study, surveys and analysis were conducted to provide theoretical and conceptual basis for the research. Field research was conducted involving interviews and application of questionnaires, and also observation of daily lives of two communities. The results indicate that the majority of the people living in the Reserve is unaware that their territory became a protected area, but they relate the protected area creation as an improvement of life quality. Tourism takes place disorganized, however the Reserve has a great touristic potential. But, it lacks proper planning and organization. It is proposed community-based tourism planning in order to value tradicional knwoledge and sustainable activities of local communities. KEYWORDS: Participation; Extractive Reserve; Protected Area; Tourism; Community.

Towards Personal, Social, and Urban Awareness

2014 ◽  
pp. 1-20 ◽  
Author(s):  
Bin Guo ◽  
Yunji Liang ◽  
Zhu Wang ◽  
Zhiwen Yu ◽  
Daqing Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
General System ◽  
Group Behavior ◽  
Research Area ◽  
Research Field ◽  
Urban Context ◽  
Urban Dynamics ◽  
Context Aware Computing ◽  
Social And Community Intelligence ◽  
New Research

In the past decades, numerous research efforts have been made to model and extract the contexts of users in pervasive computing environments. The recent explosion of sensor-equipped mobile phone market and the phenomenal growth of geo-tagged data (Twitter messages, Foursquare check-ins, etc.) have enabled the analysis of new dimensions of contexts that involve the social and urban context. The technology trend towards pervasive sensing and large-scale social and community computing is making “Social and Community Intelligence (SCI)” a new research area that aims at investigating individual/group behavior patterns, community and urban dynamics based on the “digital footprints.” It is believed that the SCI technology has the potential to revolutionize the field of context-aware computing. The aim of this chapter is to identify this emerging research area, present the research background, define the general system framework, characterize its unique properties, discuss the open research challenges, and present this emerging research field.

Assisted Authentication

2018 ◽  
pp. 104-134
Keyword(s):  
Research Field ◽  
Point Of View ◽  
Digital Data ◽  
Specific Domain ◽  
Current State ◽  
Speed Up ◽  
Information Manipulation ◽  
Manipulation Detection ◽  
Audio Video ◽  
Remarkable Progress

The present chapter deals with the issue of information manipulation detection from an algorithmic point of view, examining a variety of authentication methods, which target assisting average users and media professionals to secure themselves from forged content. The specific domain forms a very interesting, highly interdisciplinary research field, where remarkable progress has been conducted during the last years. The chapter outlines the current state of the art, providing an overview of the different modalities, aiming at evaluating the various types of digital data (text, image, audio, video), in conjunction with the associated falsification attacks and the available forensic investigation tools. In the coming years, the problem of fake news is expected to become even more complicated, as journalism is heading towards an era of heightened automation. Overall, it is anticipated that machine-driven verification assistance means can speed up the required validation processes, reducing the spread of unverified reports.

A Primer on Text-Data Analysis

2011 ◽  
pp. 3111-3118 ◽  
Author(s):  
Imad Rahal ◽  
Baoying Wang ◽  
James Schnepf
Keyword(s):  
Information Retrieval ◽  
Data Analysis ◽  
Language Processing ◽  
Information Filtering ◽  
Data Representation ◽  
Research Area ◽  
Research Field ◽  
Text Data ◽  
Document Collections ◽  
Text Data Analysis

Since the invention of the printing press, text has been the predominate mode for collecting, storing and disseminating a vast, rich range of information. With the unprecedented increase of electronic storage and dissemination, document collections have grown rapidly, increasing the need to manage and analyze this form of data in spite of its unstructured or semistructured form. Text-data analysis (Hearst, 1999) has emerged as an interdisciplinary research area forming a junction of a number of older fields like machine learning, natural language processing, and information retrieval (Grobelnik, Mladenic, & Milic-Frayling, 2000). It is sometimes viewed as an adapted form of a very similar research field that has also emerged recently, namely, data mining, which focuses primarily on structured data mostly represented in relational tables or multidimensional cubes. This article provides an overview of the various research directions in text-data analysis. After the “Introduction,” the “Background” section provides a description of a ubiquitous text-data representation model along with preprocessing steps employed for achieving better text-data representations and applications. The focal section, “Text-Data Analysis,” presents a detailed treatment of various text-data analysis subprocesses such as information extraction, information retrieval and information filtering, document clustering and document categorization. The article closes with a “Future Trends” section followed by a “Conclusion” section.

scholarly journals Automatic Gene Function Prediction in the 2020’s

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1264
Author(s):  
Stavros Makrodimitris ◽  
Roeland C. H. J. van Ham ◽  
Marcel J. T. Reinders
Keyword(s):  
Functional Annotation ◽  
Protein Sequences ◽  
Research Area ◽  
Function Prediction ◽  
Research Field ◽  
Model Species ◽  
Large Step ◽  
Gene Functions ◽  
Performance Gains ◽  
The Way

The current rate at which new DNA and protein sequences are being generated is too fast to experimentally discover the functions of those sequences, emphasizing the need for accurate Automatic Function Prediction (AFP) methods. AFP has been an active and growing research field for decades and has made considerable progress in that time. However, it is certainly not solved. In this paper, we describe challenges that the AFP field still has to overcome in the future to increase its applicability. The challenges we consider are how to: (1) include condition-specific functional annotation, (2) predict functions for non-model species, (3) include new informative data sources, (4) deal with the biases of Gene Ontology (GO) annotations, and (5) maximally exploit the GO to obtain performance gains. We also provide recommendations for addressing those challenges, by adapting (1) the way we represent proteins and genes, (2) the way we represent gene functions, and (3) the algorithms that perform the prediction from gene to function. Together, we show that AFP is still a vibrant research area that can benefit from continuing advances in machine learning with which AFP in the 2020s can again take a large step forward reinforcing the power of computational biology.

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