Journal articles on the topic 'Mapping of data usage'
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1
Shah, Reena, and Ruchi Tewari. "Mapping Emoji Usage Among Youth." Journal of Creative Communications 16, no. 1 (January 21, 2021): 113–25. http://dx.doi.org/10.1177/0973258620982541.
Abstract:
Emoji is now a popular inclusion in technology-mediated communication and a part of everyday expression of users. Yet, there is a dearth of scientifically designed research studies focussing on the human implications of the use of emojis. Limited systematic inquiry in this area is restricted to technical studies focussing on algorithm analysis of humongous quantitative data ignoring the people who are posting these emojis. Therefore, in the present study, an attempt is made to study the use of emojis from an individual’s behavioural perspective borrowing from the classic ‘contagion theory’ and the ‘information-signal theory’. A mixed research approach was adopted to study young university student’s emoji usage behaviour. Focus group discussion (FGD) was conducted on 11 participants with an average age of 22.5 years. The discussion was transcribed and thematic analysis was then conducted from which a survey instrument was developed which was administered to 250 university students. These survey data were then analysed using exploratory factor analysis. Results show that social media platforms, linguistic pattern, social relationships, emotional connect and level of formality and gender emerged as important factors that drive emoji usage. The findings of the study indicate the psychological implications and socio-behavioural impact of emoji usage which can be used for creating regulations and norms. What appears to be casual pictorial supplement of textual messages holds the power to be developed as a stand-alone language which could impact the usage of language-dependent communication.
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Langham, S., N. Pooley, and S. Weir. "Mapping European Database Usage: An Analysis of Published Data Types." Value in Health 17, no. 7 (November 2014): A553. http://dx.doi.org/10.1016/j.jval.2014.08.1812.
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R, Kamatchi, Kimaya Ambekar, and Yash Parikh. "Security Mapping of a Usage Based Cloud System." Network Protocols and Algorithms 8, no. 4 (January 15, 2017): 56. http://dx.doi.org/10.5296/npa.v8i4.10240.
Abstract:
The popularity of cloud computing technology is increasing tremendously. There is no disagreement about the effectiveness of the data storage and the data transition techniques of clouds. Earlier it used distributed computing just for sharing resources. However, with technology advancement, cloud computing has become more and more powerful as well as more adaptive in various business sectors. However, with the increase in number of users, there is also an increase in the security threats affecting the users’ privacy, personal data, identity and confidentiality. In this paper, we have aimed at categorizing security and privacy threats based on the kind of usage of cloud. We have also presented an algorithm to find the appropriate solution to address the security and privacy related issues as per the usage category. This paper helps in improving security and privacy of cloud technology users without compromising the benefits of data storage.
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Savin, I. Yu. "Usage of satellite data for soil mapping: modern tendencies and problems." Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa 13, no. 6 (2016): 29–39. http://dx.doi.org/10.21046/2070-7401-2016-13-6-29-39.
5
Meland, Per, Shukun Tokas, Gencer Erdogan, Karin Bernsmed, and Aida Omerovic. "A Systematic Mapping Study on Cyber Security Indicator Data." Electronics 10, no. 9 (May 5, 2021): 1092. http://dx.doi.org/10.3390/electronics10091092.
Abstract:
A security indicator is a sign that shows us what something is like or how a situation is changing and can aid us in making informed estimations on cyber risks. There are many different breeds of security indicators, but, unfortunately, they are not always easy to apply due to a lack of available or credible sources of data. This paper undertakes a systematic mapping study on the academic literature related to cyber security indicator data. We identified 117 primary studies from the past five years as relevant to answer our research questions. They were classified according to a set of categories related to research type, domain, data openness, usage, source, type and content. Our results show a linear growth of publications per year, where most indicators are based on free or internal technical data that are domain independent. While these indicators can give valuable information about the contemporary cyber risk, the increasing usage of unconventional data sources and threat intelligence feeds of more strategic and tactical nature represent a more forward-looking trend. In addition, there is a need to take methods and techniques developed by the research community from the conceptual plane and make them practical enough for real-world application.
6
IJMTST061248. "Automated User Behavior Mapping Using Web Usage Mining." International Journal for Modern Trends in Science and Technology 6, no. 12 (December 13, 2020): 257–61. http://dx.doi.org/10.46501/ijmtst061247.
Abstract:
Automated User Behavior Mapping is an application of web usage mining using which we can see the real-time behavior of end user visiting a particular web page automatically. The technologies used in this are socket programming for real-time communication between the server and the user accessing the website for collection of web log data and selenium web driver for automating the user behavior using web log files.
7
Sawłuk, Karol, and Marek Miłosz. "Comparison of object-relational data mapping technology in Symfony 3 framework." Journal of Computer Sciences Institute 8 (November 30, 2018): 235–40. http://dx.doi.org/10.35784/jcsi.687.
Abstract:
The article presents the results of a comparative analysis of object-relation mapping technologies in the framework Symfony 3: Doctrine and Propel. The analysis was performed in terms of script execution speed and memory usage during database operations. The analysis allowed to identify the technology with faster and more efficient algorithms. Doctrine is up to three times faster than Propel.
8
Hecht, Robert, Matthias Kalla, and Tobias Krüger. "Crowd-sourced data collection to support automatic classification of building footprint data." Proceedings of the ICA 1 (May 16, 2018): 1–7. http://dx.doi.org/10.5194/ica-proc-1-54-2018.
Abstract:
Human settlements are mainly formed by buildings with their different characteristics and usage. Despite the importance of buildings for the economy and society, complete regional or even national figures of the entire building stock and its spatial distribution are still hardly available. Available digital topographic data sets created by National Mapping Agencies or mapped voluntarily through a crowd via Volunteered Geographic Information (VGI) platforms (e.g. OpenStreetMap) contain building footprint information but often lack additional information on building type, usage, age or number of floors. For this reason, predictive modeling is becoming increasingly important in this context. The capabilities of machine learning allow for the prediction of building types and other building characteristics and thus, the efficient classification and description of the entire building stock of cities and regions. However, such data-driven approaches always require a sufficient amount of ground truth (reference) information for training and validation. The collection of reference data is usually cost-intensive and time-consuming. Experiences from other disciplines have shown that crowdsourcing offers the possibility to support the process of obtaining ground truth data. Therefore, this paper presents the results of an experimental study aiming at assessing the accuracy of non-expert annotations on street view images collected from an internet crowd. The findings provide the basis for a future integration of a crowdsourcing component into the process of land use mapping, particularly the automatic building classification.
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Diener, Matthias, Eduardo H. M. Cruz, Laércio L. Pilla, Fabrice Dupros, and Philippe O. A. Navaux. "Characterizing communication and page usage of parallel applications for thread and data mapping." Performance Evaluation 88-89 (June 2015): 18–36. http://dx.doi.org/10.1016/j.peva.2015.03.001.
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Otto, J. C., K. Kleinod, O. König, M. Krautblatter, M. Nyenhuis, I. Roer, M. Schneider, B. Schreiner, and R. Dikau. "HRSC-A data: a new high-resolution data set with multipurpose applications in physical geography." Progress in Physical Geography: Earth and Environment 31, no. 2 (April 2007): 179–97. http://dx.doi.org/10.1177/0309133307076479.
Abstract:
The analysis and interpretation of remote sensing data facilitates investigation of land surface complexity on large spatial scales. We introduce here a geometrically high-resolution data set provided by the airborne High Resolution Stereo Camera (HRSC-A). The sensor records digital multispectral and panchromatic stereo bands from which a very high-resolution ground elevation model can be produced. After introducing the basic principles of the HRSC technique and data, applications of HRSC data within the multidisciplinary Research Training Group 437 are presented. Applications include geomorphologic mapping, geomorphometric analysis, mapping of surficial grain-size distribution, rock glacier kinematic analysis, vegetation monitoring and three-dimensional landform visualization. A final evaluation of the HRSC data based on three years of multipurpose usage concludes this presentation. A combination of image and elevation data opens up various possibilities for visualization and three-dimensional analysis of the land surface, especially in geomorphology. Additionally, the multispectral imagery of the HRSC data has potential for land cover mapping and vegetation monitoring. We consider HRSC data a valuable source of high-resolution terrain information with high applicability in physical geography and earth system science.
11
Kamínek, Jiří, and Martin Klimánek. "Mobile usage of digital geographical data in the Apple iPhone device." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 58, no. 4 (2010): 89–96. http://dx.doi.org/10.11118/actaun201058040089.
Abstract:
This article deals with the possible deployment of the Apple iPhone device as mobile geoinformation technology. An examination of the possibilities of the device, the development tools and the Web Mapping Service (WMS) was followed by developing a prototype of an application called WhateverMap. The application uses maps from the WMS, which are available in the field through mobile data communication. The application interface was designed around the User Experience model so that its control is easy to grasp and intuitive. It also features support to the determination of the current location. To make working with the application more comfortable it integrates a database of WMS servers. The user is thus given an overview of all the maps available and can easily add them as desired. The application can be downloaded free of charge from Apple’s AppStore on the internet.
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Vreeman, Daniel J., John Hook, and Brian E. Dixon. "Learning from the crowd while mapping to LOINC." Journal of the American Medical Informatics Association 22, no. 6 (July 29, 2015): 1205–11. http://dx.doi.org/10.1093/jamia/ocv098.
Abstract:
Abstract Objective To describe the perspectives of Regenstrief LOINC Mapping Assistant (RELMA) users before and after the deployment of Community Mapping features, characterize the usage of these new features, and analyze the quality of mappings submitted to the community mapping repository. Methods We evaluated Logical Observation Identifiers Names and Codes (LOINC) community members’ perceptions about new “wisdom of the crowd” information and how they used the new RELMA features. We conducted a pre-launch survey to capture users’ perceptions of the proposed functionality of these new features; monitored how the new features and data available via those features were accessed; conducted a follow-up survey about the use of RELMA with the Community Mapping features; and analyzed community mappings using automated methods to detect potential errors. Results Despite general satisfaction with RELMA, nearly 80% of 155 respondents to our pre-launch survey indicated that having information on how often other users had mapped to a particular LOINC term would be helpful. During the study period, 200 participants logged into the RELMA Community Mapping features an average of 610 times per month and viewed the mapping detail pages a total of 6686 times. Fifty respondents (25%) completed our post-launch survey, and those who accessed the Community Mapping features unanimously indicated that they were useful. Overall, 95.3% of the submitted mappings passed our automated validation checks. Conclusion When information about other institutions’ mappings was made available, study participants who accessed it agreed that it was useful and informed their mapping choices. Our findings suggest that a crowd-sourced repository of mappings is valuable to users who are mapping local terms to LOINC terms.
13
Nikolaeva, O. N. "THE USAGE OF INTEGRATED MAPPING OF HETEROGENEOUS NATURAL RESOURCES DATA FOR NATURAL RESOURCES MANAGEMENT." Proceedings of the International conference “InterCarto/InterGIS” 1, no. 21 (January 1, 2015): 171–74. http://dx.doi.org/10.24057/2414-9179-2015-1-21-171-174.
14
González-Ladrón-de-Guevara, Fernando, Marta Fernández-Diego, and Chris Lokan. "The usage of ISBSG data fields in software effort estimation: A systematic mapping study." Journal of Systems and Software 113 (March 2016): 188–215. http://dx.doi.org/10.1016/j.jss.2015.11.040.
15
Kejzlar, Pavel, Zuzana Andršová, Martin Švec, Lukáš Voleský, and Michal Tregler. "Possibilities of Usage of EBSD for Study of DC06 Steel Deformation." Materials Science Forum 891 (March 2017): 101–5. http://dx.doi.org/10.4028/www.scientific.net/msf.891.101.
Abstract:
EBSD is an analytical technique, which uses diffraction of backscattered electrons on the sample’s crystal lattice to determine the crystal structure and orientation. Point-by-point mapping of crystal orientation and misorientation, calculation of sub-grain boundaries angles and statistical processing of grain data allow identifying and displaying elastically and plastically deformed zones, textures. Orientation mapping and pole-and inverse pole figures allow to identify preferred slip planes and texture, however misorientation reveals areas where higher stress concentration appears, dislocation arrays and internal defects.
16
Sakas, Damianos P., and Nikolaos Th Giannakopoulos. "Big Data Contribution in Desktop and Mobile Devices Comparison, Regarding Airlines’ Digital Brand Name Effect." Big Data and Cognitive Computing 5, no. 4 (September 26, 2021): 48. http://dx.doi.org/10.3390/bdcc5040048.
Abstract:
Rising demand for optimized digital marketing strategies has led firms in a hunt to harvest every possible aspect indicating users’ experience and preference. People visit, regularly through the day, numerous websites using both desktop and mobile devices. For businesses to acknowledge device’s usage rates is extremely important. Thus, this research is focused on analyzing each device’s usage and their effect on airline firms’ digital brand name. In the first phase of the research, we gathered web data from 10 airline firms during an observation period of 180 days. We then proceeded in developing an exploratory model using Fuzzy Cognitive Mapping, as well as a predictive and simulation model using Agent-Based Modeling. We inferred that various factors of airlines’ digital brand name are affected by both desktop and mobile usage, with mobile usage having a slightly bigger impact on most of them, with gradually rising values. Desktop device usage also appeared to be quite significant, especially in traffic coming from referral sources. The paper’s contribution has been to provide a handful of time-accurate insights for marketeers, regarding airlines’ digital marketing strategies.
17
Leichter, A., U. Feuerhake, and M. Sester. "DETERMINATION OF PARKING SPACE AND ITS CONCURRENT USAGE OVER TIME USING SEMANTICALLY SEGMENTED MOBILE MAPPING DATA." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2021 (June 28, 2021): 185–92. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2021-185-2021.
Abstract:
Abstract. Public space is a scarce good in cities. There are many concurrent usages, which makes an adequate allocation of space both difficult and highly attractive. A lot of space is allocated by parking cars – even if the parking spaces are not occupied by cars all the time. In this work, we analyze space demand and usage by parking cars, in order to evaluate, when this space could be used for other purposes. The analysis is based on 3D point clouds acquired at several times during a day. We propose a processing pipeline to extract car bounding boxes from a given 3D point cloud. For the car extraction we utilize a label transfer technique for transfers from semantically segmented 2D RGB images to 3D point cloud data. This semantically segmented 3D data allows us to identify car instances. Subsequently, we aggregate and analyze information about parking cars. We present an exemplary analysis of the urban area where we extracted 15.000 cars at five different points in time. Based on this aggregated we present analytical results for time dependent parking behavior, parking space availability and utilization.
18
Maharani, Sang Ayu Isnu, and I. Wayan Mulyawan. "The Usage Specification of Registers in Social Media Instagram." Lingual: Journal of Language and Culture 11, no. 1 (May 26, 2021): 42. http://dx.doi.org/10.24843/ljlc.2021.v11.i01.p08.
Abstract:
This research is entitled ‘The Usage Specification of Registers in Social Media Instagram’. The aims of this research are identifying and mapping the usage specification of registers in social media Instagram. It also aims at finding find out the function of the usage of the registers. This research is a combination of qualitative and quantitative research. The method applied for this research was observation method with note-taking techniques. The method used to analyze the data was discourse analysis method. To answer the problems formulated in this research, the register theory of Halliday was applied (1994).
Keywords: specification, register, social media, instagram
This research is entitled ‘The Usage Specification of Registers in Social Media Instagram’. The aims of this research are identifying and mapping the usage specification of registers in social media Instagram. It also aims at finding find out the function of the usage of the registers. This research is a combination of qualitative and quantitative research. The method applied for this research was observation method with note-taking techniques. The method used to analyze the data was discourse analysis method. To answer the problems formulated in this research, the register theory of Halliday was applied (1994).
Keywords: specification, register, social media, instagram
19
Paladin, Lisanna, Mathieu Schaeffer, Pascale Gaudet, Monique Zahn-Zabal, Pierre-André Michel, Damiano Piovesan, Silvio C. E. Tosatto, and Amos Bairoch. "The Feature-Viewer: a visualization tool for positional annotations on a sequence." Bioinformatics 36, no. 10 (January 27, 2020): 3244–45. http://dx.doi.org/10.1093/bioinformatics/btaa055.
Abstract:
Abstract Summary The Feature-Viewer is a lightweight library for the visualization of biological data mapped to a protein or nucleotide sequence. It is designed for ease of use while allowing for a full customization. The library is already used by several biological data resources and allows intuitive visual mapping of a full spectra of sequence features for different usages. Availability and implementation The Feature-Viewer is open source, compatible with state-of-the-art development technologies and responsive, also for mobile viewing. Documentation and usage examples are available online.
20
Kubota, Naoto, and Mikita Suyama. "Mapping of promoter usage QTL using RNA-seq data reveals their contributions to complex traits." PLOS Computational Biology 18, no. 8 (August 29, 2022): e1010436. http://dx.doi.org/10.1371/journal.pcbi.1010436.
Abstract:
Genomic variations are associated with gene expression levels, which are called expression quantitative trait loci (eQTL). Most eQTL may affect the total gene expression levels by regulating transcriptional activities of a specific promoter. However, the direct exploration of genomic loci associated with promoter activities using RNA-seq data has been challenging because eQTL analyses treat the total expression levels estimated by summing those of all isoforms transcribed from distinct promoters. Here we propose a new method for identifying genomic loci associated with promoter activities, called promoter usage quantitative trait loci (puQTL), using conventional RNA-seq data. By leveraging public RNA-seq datasets from the lymphoblastoid cell lines of 438 individuals from the GEUVADIS project, we obtained promoter activity estimates and mapped 2,592 puQTL at the 10% FDR level. The results of puQTL mapping enabled us to interpret the manner in which genomic variations regulate gene expression. We found that 310 puQTL genes (16.1%) were not detected by eQTL analysis, suggesting that our pipeline can identify novel variant–gene associations. Furthermore, we identified genomic loci associated with the activity of “hidden” promoters, which the standard eQTL studies have ignored. We found that most puQTL signals were concordant with at least one genome-wide association study (GWAS) signal, enabling novel interpretations of the molecular mechanisms of complex traits. Our results emphasize the importance of the re-analysis of public RNA-seq datasets to obtain novel insights into gene regulation by genomic variations and their contributions to complex traits.
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Kneale, Dylan, Praveetha Patalay, James Thomas, Meena Khatwa, Claire Stansfield, and Emla Fitzsimons. "A systematic approach to mapping longitudinal data usage: Reflections on tracking Millennium Cohort Study activity." F1000Research 7 (September 26, 2018): 1559. http://dx.doi.org/10.12688/f1000research.15990.1.
Abstract:
Background: The Millennium Cohort Study is the youngest of the UK’s four national birth cohort studies, but the only study (to our knowledge) where a systematic approach to exploring data usage has been undertaken. Methods: In this paper we: (i) explore previous exercises and provide justification for our approach; (ii) share headline findings of our research, (iii) outline the challenges of intersecting systematic review methods with survey design methods; and (iv) discuss the implications for future survey design as well as for future exercises tracking survey data usage. All of the results were obtained through undertaking systematic searches across 30 databases which generated over 4000 results. We then searched these records, first on title and abstract and then on the full text and extracted data on studies that fell within our specific areas of interest. Results: A total of 481 studies were identified as using MCS data in novel analyses. Among these studies, measures that have been collected across sweeps—diet, BMI, SDQ and screen time—are all comparatively well used. Data that were collected from the child’s own reports (e.g. friendships and feelings) have seldom been utilised in comparison to data collected through parental reports and using validated tools (e.g. SDQ). Imposing thresholds on data was found to be problematic in some cases, for example for BMI, where a number of different thresholds for overweight and obesity were in use. The use of different thresholds can lead to substantial differences in the results obtained. Conclusions: Longitudinal consistency in measures is key to identifying change over time, and the review helped map the degree of consistency in measures, and their utility. The findings shaped decisions around inclusion of variables in MCS7 (age 17 years), as well as the way in which existing data were deposited.
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Naufal, Naufal, Andi Asriadi, and Sutrisno Absar. "Avoiding Mistakes in Drone Usage in Participatory Mapping: Methodological Considerations during the Pandemic." Forest and Society 6, no. 1 (February 1, 2022): 226–42. http://dx.doi.org/10.24259/fs.v6i1.14117.
Abstract:
Participatory mapping has continued to evolve with the onset of new methodologies and technology. Conventional methods for sketching have now expanded to incorporate the use of drone imagery and other sophisticated mapping approaches as a base map. However, the use of ultra-high resolution drone imagery does not mean that it will facilitate more participatory processes nor improve the quality of data and uses of information. Indeed, it has long been known that ultra-high spatial resolution can cause misinterpretation. During COVID-19, innovations are emerging to apply more remote technologies in participatory mapping. Mobility concerns, requirements, and preferences for physical distancing discourages active participation of local communities and are especially complex in contexts involving Indigenous People. This paper specifically explores the mistakes that can arise from over-reliance on employing drones as a tool in participatory mapping methods. This paper is based on a case study of participatory mapping conducted at 43 villages (around forest area) of Central Sulawesi Province and West Sulawesi Province. The participatory mapping was carried out by the Sulawesi Community Foundation (SCF) from 2019-2021. The result of the study found at least six signs of potentially negative outcomes from the use of ultra-high resolution drone imagery, starting from disorientation, misperception over the periods of drone acquisition, homogeneous land cover conditions, similar types of plants, numerous signs of nature, and labeling affixed on map. We also encourage the development of ultra-high-resolution drone imagery to take place under certain conditions and see its role as an interpretation dictionary or as a targeted tool in local contexts. In addition, we found that the level of active participation in participatory mapping during the Pandemic was higher than before the pandemic but requires some improvisations in meeting design
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Francis, Roxane J., Kate J. Brandis, and Justin A. McCann. "Offline Imagery Checks for Remote Drone Usage." Drones 6, no. 12 (December 3, 2022): 395. http://dx.doi.org/10.3390/drones6120395.
Abstract:
Drones are increasingly used for a wide range of applications including mapping, monitoring, detection, tracking and videography. Drone software and flight mission programs are, however, still largely marketed for “urban” use such as property photography, roof inspections or 3D mapping. As a result, much of the flight mission software is reliant upon an internet connection and has built-in cloud-based services to allow for the mosaicking of imagery as a direct part of the image collection process. Another growing use for drones is in conservation, where drones are monitoring species and habitat change. Naturally, much of this work is undertaken in areas without internet connection. Working remotely increases field costs, and time in the field is often aligned with specific ecological seasons. As a result, pilots in these scenarios often have only one chance to collect appropriate data and an opportunity missed can mean failure to meet research aims and contract deliverables. We provide a simple but highly practical piece of code allowing drone pilots to quickly plot the geographical position of captured photographs and assess the likelihood of the successful production of an orthomosaic. Most importantly, this process can be performed in the field with no reliance on an internet connection, and as a result can highlight any missing sections of imagery that may need recollecting, before the opportunity is missed. Code is written in R, a familiar software to many ecologists, and provided on a GitHub repository for download. We recommend this data quality check be integrated into a pilot’s standard image capture process for the dependable production of mosaics and general quality assurance of drone collected imagery.
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Wang, Jianmin, Bo Zhang, Tongrang Fan, Zijian Fu, and Wenbin Zhao. "Research on multi-attribute controller for virtual data domain based on software definition network." International Journal of Distributed Sensor Networks 15, no. 7 (July 2019): 155014771986041. http://dx.doi.org/10.1177/1550147719860416.
Abstract:
Currently, large data sets are deployed on large-scale clusters, which require a large amount of physical resources. However, current network architecture does not have flexible deployment, making it difficult to adjust physical resources after deployment. Based on software definition network, this article proposes a framework for building virtual data domain, which establishes a multi-attribute decision model by network nodes for optimizing the deployment of control layer, so as to realize large-scale deployment. By analyzing the actual usage and virtual distribution of the underlying data resources, a mapping algorithm of network resource overhead–allocation ratio is proposed for adjusting the mapping space of network flow based on the mapping result, so as to meet more virtual domain applications. At the same time, the reasonable utilization of resources is helpful to reduce the communication delay in domain. Simulation results show that compared with the shortest path mapping and greedy resource mapping algorithms, the virtual domain established by the network resource overhead–allocation algorithm can improve the resource utilization rate by 10% and reduce the intra-domain communication delay by 30%. Therefore, under the background of the expanding scale of data domain, this framework can solve the problem that the current backward network architecture cannot adapt to the development trend of the information field.
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Demberg, Vera, Merel C. J. Scholman, and Fatemeh Torabi Asr. "How compatible are our discourse annotation frameworks? Insights from mapping RST-DT and PDTB annotations." Dialogue & Discourse 10, no. 1 (June 14, 2019): 87–135. http://dx.doi.org/10.5087/dad.2019.104.
Abstract:
Discourse-annotated corpora are an important resource for the community, but they are often annotated according to different frameworks. This makes joint usage of the annotations difficult, preventing researchers from searching the corpora in a unified way, or using all annotated data jointly to train computational systems. Several theoretical proposals have recently been made for mapping the relational labels of different frameworks to each other, but these proposals have so far not been validated against existing annotations. The two largest discourse relation annotated resources, the Penn Discourse Treebank and the Rhetorical Structure Theory Discourse Treebank, have however been annotated on the same texts, allowing for a direct comparison of the annotation layers. We propose a method for automatically aligning the discourse segments, and then evaluate existing mapping proposals by comparing the empirically observed against the proposed mappings. Our analysis highlights the influence of segmentation on subsequent discourse relation labelling, and shows that while agreement between frameworks is reasonable for explicit relations, agreement on implicit relations is low. We identify several sources of systematic discrepancies between the two annotation schemes and discuss consequences for future annotation and for usage of the existing resources.
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Kamada, Mahito, Junpei Ando, Takashi Someya, and Miki Asai. "Mapping potential habitats for 53 forest communities: exemplified usage of data collected through national vegetation survey." Landscape Ecology and Management 19, no. 2 (2014): 91–103. http://dx.doi.org/10.5738/jale.19.91.
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Savage, Jeff P., Mengge Li, Scott F. Turner, Donald E. Hatfield, and Laura B. Cardinal. "Mapping Patent Usage in Management Research: The State of Prior Art." Journal of Management 46, no. 6 (May 11, 2020): 1121–55. http://dx.doi.org/10.1177/0149206320916233.
Abstract:
Patents play an important, and increasingly influential, role in management scholarship. In this study, we conduct a broad and systematic review of patent-based empirical work in the management field, which involves mapping the ways in which scholars are using patent-based measures to represent concepts and assessing this usage based on measurement principles. With respect to mapping, our review identifies the different types of measures that researchers have constructed based on different types of patent data (e.g., patent counts, backward citations) as well as delineates the classes of theoretical concepts that are being represented by those measures. In terms of assessing, as a complement to prior surveys of patent-based research that have assessed patents as indicators based on features of patents, patenting, and patent offices, we develop a framework that is based on measurement principles. Using this framework, our assessment of patent-based research in management reveals important patterns surrounding foundational measurement issues, i.e., method bias, validation threats, model misspecification. Our review makes two core contributions: one centering on summarizing how patents have been used in management research and one focusing on guiding management scholars in terms of common measurement issues for patent-based indicators. These contributions have important implications for future scholarly work in management.
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Zunino, Alejandro, Guillermo Velázquez, Juan Pablo Celemín, Cristian Mateos, Matías Hirsch, and Juan Manuel Rodriguez. "Evaluating the Performance of Three Popular Web Mapping Libraries: A Case Study Using Argentina’s Life Quality Index." ISPRS International Journal of Geo-Information 9, no. 10 (September 29, 2020): 563. http://dx.doi.org/10.3390/ijgi9100563.
Abstract:
Recent Web technologies such as HTML5, JavaScript, and WebGL have enabled powerful and highly dynamic Web mapping applications executing on standard Web browsers. Despite the complexity for developing such applications has been greatly reduced by Web mapping libraries, developers face many choices to achieve optimal performance and network usage. This scenario is even more complex when considering different representations of geographical data (raster, raw data or vector) and variety of devices (tablets, smartphones, and personal computers). This paper compares the performance and network usage of three popular JavaScript Web mapping libraries for implementing a Web map using different representations for geodata, and executing on different devices. In the experiments, Mapbox GL JS achieved the best overall performance on mid and high end devices for displaying raster or vector maps, while OpenLayers was the best for raster maps on all devices. Vector-based maps are a safe bet for new Web maps, since performance is on par with raster maps on mid-end smartphones, with significant less network bandwidth requirements.
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Mears, Meghann, Paul Brindley, Paul Barrows, Miles Richardson, and Ravi Maheswaran. "Mapping urban greenspace use from mobile phone GPS data." PLOS ONE 16, no. 7 (July 7, 2021): e0248622. http://dx.doi.org/10.1371/journal.pone.0248622.
Abstract:
Urban greenspace is a valuable component of the urban form that has the potential to improve the health and well-being of residents. Most quantitative studies of relationships between health and greenspace to date have investigated associations only with what greenspace exists in the local environment (i.e. provision of greenspace), rather than to what extent it is used. This is due to the difficulty of obtaining usage data in large amounts. In recent years, GPS functionality integrated into mobile phones has provided a potential solution to this problem by making it possible to track which parts of the environment people experience in their day-to-day lives. In this paper, we demonstrate a method to derive cleaned, trip-level information from raw GPS data collected by a mobile phone app, then use this data to investigate the characteristics of trips to urban greenspace by residents of the city of Sheffield, UK. We find that local users of the app spend an average of an hour per week visiting greenspaces, including around seven trips per week and covering a total distance of just over 2.5 km. This may be enough to provide health benefits, but is insufficient to provide maximal benefits. Trip characteristics vary with user demographics: ethnic minority users and users from more socioeconomically deprived areas tend to make shorter trips than White users and those from less deprived areas, while users aged 34 years and over make longer trips than younger users. Women, on average, make more frequent trips than men, as do those who spent more time outside as a child. Our results suggest that most day-to-day greenspace visits are incidental, i.e. travelling through rather than to greenspace, and highlight the importance of including social and cultural factors when investigating who uses and who benefits from urban greenspace.
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Steensen, T., S. Müller, M. Jandewerth, and O. Büscher. "Mapping Biomass Availability to Decrease the Dependency on Fossil Fuels." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7 (September 19, 2014): 165–71. http://dx.doi.org/10.5194/isprsarchives-xl-7-165-2014.
Abstract:
To decrease the dependency on fossil fuels, more renewable energy sources need to be explored. Over the last years, the consumption of biomass has risen steadily and it has become a major source for re-growing energy. Besides the most common sources of biomass (forests, agriculture etc.) there are smaller supplies available in mostly unused areas like hedges, vegetation along streets, railways, rivers and field margins. However, these sources are not mapped and in order to obtain their potential for usage as a renewable energy, a method to quickly assess their spatial distribution and their volume is needed. We use a range of data sets including satellite imagery, GIS and elevation data to evaluate these parameters. With the upcoming Sentinel missions, our satellite data is chosen to match the spatial resolution of Sentinel-2 (10–20 m) as well as its spectral characteristics. To obtain sub-pixel information from the satellite data, we use a spectral unmixing approach. Additional GIS data is provided by the German Digital Landscape Model (ATKIS Base-DLM). To estimate the height (and derive the volume) of the vegetation, we use LIDAR data to produce a digital surface model. These data sets allow us to map the extent of previously unused biomass sources. This map can then be used as a starting point for further analyses about the feasibility of the biomass extraction and their usage as a renewable energy source.
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Koppler, Rainer, Siegfried Grabner, and Jens Volkert. "Visualization of Distributed Data Structures for High Performance Fortran-Like Languages." Scientific Programming 6, no. 1 (1997): 115–26. http://dx.doi.org/10.1155/1997/504101.
Abstract:
This article motivates the usage of graphics and visualization for efficient utilization of High Performance Fortran's (HPF's) data distribution facilities. It proposes a graphical toolkit consisting of exploratory and estimation tools which allow the programmer to navigate through complex distributions and to obtain graphical ratings with respect to load distribution and communication. The toolkit has been implemented in a mapping design and visualization tool which is coupled with a compilation system for the HPF predecessor Vienna Fortran. Since this language covers a superset of HPF's facilities, the tool may also be used for visualization of HPF data structures.
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Chiarello, Filippo, Elena Coli, Vito Giordano, Gualtiero Fantoni, and Andrea Bonaccorsi. "DATA FOR ENGINEERING DESIGN: MAPS AND GAPS." Proceedings of the Design Society 1 (July 27, 2021): 821–30. http://dx.doi.org/10.1017/pds.2021.82.
Abstract:
AbstractData, information and knowledge are strongly involved in Engineering Design (ED) process. Despite the crucial role played by data in the design process, there is a lack of studies about how different data are used and generated by the various phases of the ED process. This study is a first attempt to fill this gap by mapping which data types are involved in the different ED phases from a research perspective.In order to achieve this objective, we used a methodology based on Text Mining. Firstly, we retrieve a corpus of scientific papers related to ED; then, we build two lexicons to recognize ED phases and data types; finally, we collect these entities within ED papers and map the relations between them.The methodology application allows the building of a network graph for visualizing the relations among data lexicon and ED lexicon. Then, we investigate the specific relations among data types and ED phases by building a heatmap to investigate data types from 3 different perspective.The insight coming from our analysis shows that ED studies have a great potential in the usage of many data sources, but also that there exist some gaps to be solved in order to reach a more effective data usage in the context of ED.
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Koshev, Nikolay, Nikolay Yavich, Mikhail Malovichko, Ekaterina Skidchenko, and Maxim Fedorov. "FEM-based Scalp-to-Cortex EEG data mapping via the solution of the Cauchy problem." Journal of Inverse and Ill-posed Problems 28, no. 4 (August 1, 2020): 517–32. http://dx.doi.org/10.1515/jiip-2019-0065.
Abstract:
AbstractWe propose an approach and the numerical algorithm for mapping the electroencephalographic (EEG) data from the scalp to the cortex. The algorithm is based on the solution of ill-posed Cauchy problem for the Laplace’s equation using tetrahedral finite elements. The FEM-based scheme allows to calculate the volumetric distribution of a potential over the head volume. We demonstrate the usage of the the algorithm for accurate estimation of the depth of electric sources in the head. The algorithm sufficiently increases the spatial resolution of the EEG technique making it comparable with intracranial techniques.
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Daniel, Sharon, and Karen O'Rourke. "Mapping the Database: Trajectories and Perspectives." Leonardo 37, no. 4 (August 2004): 287–96. http://dx.doi.org/10.1162/0024094041724553.
Abstract:
The authors attempt to re-imagine classification systems as emergent systems—where names, categories and associated data structures arise from the bottom up through collective usage. Each has employed cartographic methodology as an interaction metaphor in the design of dynamic, evolving systems that allow participants to create and archive their own itineraries and maps on-line. These systems explore the aesthetic dimensions of the database. The authors have presented and tested prototypes of two developing systems, Subtract the Sky and A Map Larger Than the Territory, in a workshop/exhibition. This article provides a brief description of the premise and implementation of both projects. It concludes with some preliminary findings from the workshop/exhibition and the authors' shared research.
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Gilfoil, David M. "Mapping Social Media Tools For Sell vs Buy Activities Into Emerging And Developed Markets." International Journal of Management & Information Systems (IJMIS) 16, no. 1 (December 22, 2011): 69. http://dx.doi.org/10.19030/ijmis.v16i1.6723.
Abstract:
This paper studies usage patterns of global sellers and buyers using five forms of Web 2.0 social broadcast behaviors - blogging, micro-blogging, social networking, online video, and online photo uploading. A survey and analysis of the number of people using these tools to sell something (sellers), as compared those people using these same tools to buy something (buyers), is conducted on an emerging vs developed market basis. The data is obtained from an ongoing panel study and is a continuation of research already published in this area. Findings show that the tools are used quite differentially into emerging vs. developed markets. Social networking and micro-blogging platforms are used significantly more in emerging economies (regardless of sell or buy motivation) while the other three tools exhibit no consistent usage differences across economies. Findings also show that these same two platforms are favored for sell activities in emerging economies vs. developed economies. Blogging and micro-blogging are significantly favored tools of choice where buying is the motivation - blogging is favored by emerging economies and micro-blogging is favored by developed economies. Interestingly, photo uploading is the only tool which showed no differential usage across emerging/developed economies for any kind of sell or buy activity. Average sell/buy usage data for each social broadcast behavior is reported for each country in the emerging and developed markets. In order to better understand the eWOM implications of the current market participation conditions, some areas requiring further investigation are suggested.
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Sawale, Arti. "Text Mining of Twitter data for Mapping the Digital Humanities Research Trends." DESIDOC Journal of Library & Information Technology 43, no. 04 (August 1, 2023): 258–65. http://dx.doi.org/10.14429/djlit.43.04.19236.
Abstract:
Digital humanities have become a more relevant field of study due to the extraordinary growth in digitisation of the humanities data. Due to collaborative development of humanities and computing, many academics are convinced of the worth of digital humanities (DH) that actually provides the best insight into humanities studies. The panoramic view of the development of big data in humanities reflects its trendy directions and evoked new challenges in DH. It is complicated to analysed the objectives of digital humanities data with simple data analysis tools where as text mining can help to facilitate the qualitative findings in DH. In the humanities disciplines, data is often in the form of unstructured and text mining is a way of structuring and analysing digitised text-as-data. Twitter is a online social networking platform which offers an opportunity for quality information sharing, collaborative participation digital humanities community. This paper is attempted to study the extensibility of digital humanities on twitter and also to interpret the evolution of twitter usage by analysing tweets posted related to DH via python data analysis.
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Bastidas Fuertes, Andrés, María Pérez, and Jaime Meza Hormaza. "Transpilers: A Systematic Mapping Review of Their Usage in Research and Industry." Applied Sciences 13, no. 6 (March 13, 2023): 3667. http://dx.doi.org/10.3390/app13063667.
Abstract:
Transpilers refer to a special type of compilation that takes source code and translates it into target source code. This type of technique has been used for different types of implementations in scientific studies. A review of the research areas related to the use of transpilers allows the understanding of the direction in this branch of knowledge. The objective was to carry out an exhaustive and extended mapping of the usage and implementation of transpilers in research studies in the last 10 years. A systematic mapping review was carried out for answering the 5 research questions proposed. The PSALSAR method is used as a guide to the steps needed for the review. In total, from 1181 articles collected, 683 primary studies were selected, reviewed, and analyzed. Proposals from the industry were also analyzed. A new method for automatic data tabulation has been proposed for the mapping objective, using a relational database and SQL language. It was identified that the most common uses of transpilers are related to performance optimizations, parallel programming, embedded systems, compilers, testing, AI, graphics, and software development. In conclusion, it was possible to determine the extent and identification of research sub-areas and their impact on the usage of the transpilers. Future research could be considered about the usage of transpilers in transactional software, migration strategies for legacy systems, AI, math, multiplatform games and apps, automatic source code generation, and networking.
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Pal, S. K., T. J. Majumdar, and A. K. Bhattacharya. "Usage of ERS SAR data over the Singhbhum Shear Zone, India for structural mapping and tectonic studies." Geocarto International 22, no. 4 (December 2007): 285–95. http://dx.doi.org/10.1080/10106040701337642.
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HENTSCHEL, G., and O. O. TARANENKO. "BILINGUALISM OR TRICODALISM: UKRAINIAN, RUSSIAN AND «SURŽYK» IN UKRAINE (analysis and linguistic-geographical mapping)." Movoznavstvo 322, no. 1 (February 22, 2022): 21–50. http://dx.doi.org/10.33190/0027-2833-322-2022-1-002.
Abstract:
The study aims to show that the different usage frequencies of Ukrainian, Russian and «Suržyk» in everyday life in Ukraine can be described and mapped as a continuum of «tricodalism». This sets it apart from previous representations that usually assume a historical-political demarcation of sub-areas and consequently tend to indicate a linguistic bisection of the country into a Ukrainian-speaking area encompassing the west and the central region, and a Russian-speaking area in the east and south. The approach proposed here employs empirical data on usage of the three codes as the basis for its structuration. Starting from the mean frequencies of code usage in individual oblasts, a cluster analysis groups these into larger areas and clarifies their internal variation. This result is not just a more continuous picture of the linguistic landscape in Ukraine, but also a more coherent one.
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Carus, Jasmin, Leona Trübe, Philip Szczepanski, Sylvia Nürnberg, Hanna Hees, Stefan Bartels, Alice Nennecke, Frank Ückert, and Christopher Gundler. "Mapping the Oncological Basis Dataset to the Standardized Vocabularies of a Common Data Model: A Feasibility Study." Cancers 15, no. 16 (August 11, 2023): 4059. http://dx.doi.org/10.3390/cancers15164059.
Abstract:
In their joint effort against cancer, all involved parties within the German healthcare system are obligated to report diagnostics, treatments, progression, and follow-up information for tumor patients to the respective cancer registries. Given the federal structure of Germany, the oncological basis dataset (oBDS) operates as the legally required national standard for oncological reporting. Unfortunately, the usage of various documentation software solutions leads to semantic and technical heterogeneity of the data, complicating the establishment of research networks and collective data analysis. Within this feasibility study, we evaluated the transferability of all oBDS characteristics to the standardized vocabularies, a metadata repository of the observational medical outcomes partnership (OMOP) common data model (CDM). A total of 17,844 oBDS expressions were mapped automatically or manually to standardized concepts of the OMOP CDM. In a second step, we converted real patient data retrieved from the Hamburg Cancer Registry to the new terminologies. Given our pipeline, we transformed 1773.373 cancer-related data elements to the OMOP CDM. The mapping of the oBDS to the standardized vocabularies of the OMOP CDM promotes the semantic interoperability of oncological data in Germany. Moreover, it allows the participation in network studies of the observational health data sciences and informatics under the usage of federated analysis beyond the level of individual countries.
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Pandey, Ramendra Pati, Riya Mukherjee, and Chung-Ming Chang. "[Final accepted version, unedited] Antimicrobial resistance surveillance system mapping in different countries." Drug Target Insights 16, no. 1 (November 10, 2022): 1. http://dx.doi.org/10.33393/dti.2022.2482.
Abstract:
ObjectivesExcessive use of antibiotics has extensively increased antimicrobial resistance worldwide which is the major public concern among the countries. To control this threat proper monitoring of the antimicrobial usage with the increasing rate of antimicrobial resistance (AMR) is required. Moreover, alternatives for antibiotics are surveyed and are being researched for quick use in the future. Thus, intervention of multisector is highly encouraged for better outcomes. In this research paper, six different European countries are discussed in terms of antimicrobial usage and AMR in the human and livestock sectors with the help of literature study and various reports published by different organizations. MethodsData study has been conducted to collect the data for comparison study. Data sources of AMR and antimicrobial usage are analyzed and a thorough comparison of both antimicrobial use and AMR are conducted. ResultsThis article provides surveillance systems that are formed to keep a track on the upcoming situation of AMR and the consumption of antimicrobials by the humans as well as animals. The article firmly allows the readers to get acknowledged with the broad information about the antimicrobial resistance across the six countries of Europe. These annual reports have highly helped the government to decide for alternatives and have focused in many training activities to combat the AMR situation globally. ConclusionAs antibiotic resistance genes persist on an interface between environment and animal and animal health, an approach is required in all three areas that stress the concept of ‘One Approach to Health’.
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Denil, Mauli, I. Wayan Simpen, I. Nyoman Suparwa, and Anak Agung Putu Putra. "The Motif of Language Dominance that Used on Coffee Shop Signboards in Padang City." Randwick International of Education and Linguistics Science Journal 5, no. 2 (June 30, 2024): 439–52. http://dx.doi.org/10.47175/rielsj.v5i2.982.
Abstract:
This study offers a fresh perspective on Linguistic Landscapes (LL) by employing language mapping to analyze the frequency and distribution of language usage. The population data comprised 60 signboards from coffee shops and tourism spots in Padang city center. Qualitative methods were utilized for data collection, with analysis conducted using GIS (Geographic et al.) and Adobe Photoshop, representing innovative approaches in LL research. The analysis commenced with quantifying language usage, encompassing mono/bi/multilingual forms on coffee shop signboards. Subsequently, language mapping was employed to illustrate language distribution and highlight motif of linguistic dominance that used on coffee shop signboards in specific areas on the map. Findings revealed the presence of 12 languages on coffee shop signage, reflecting the global influence and societal preference for modernization. Despite the prominence of foreign languages, Indonesian emerged as the most frequently used, indicating relatively successful implementation of Presidential Regulation No.63 of 2019, although inconsistencies persist
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Petrushevsky, N., M. Manzoni, and A. M. Guarnieri. "HIGH-RESOLUTION URBAN MAPPING BY FUSION OF SAR AND OPTICAL DATA." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 28, 2021): 273–78. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-273-2021.
Abstract:
Abstract. Mapping the exact extent of urban areas is a critical prerequisite in many remote sensing applications, such as hazard evaluation and change detection. The usage of Synthetical Aperture Radar (SAR) data has gained popularity due to the unique characteristics of the backscattered radio signal from human-made targets. The Sentinel-1 (S1) constellation, with a global revisit time of 6–12 days in Interferometric Wide Swath (IW) mode and free and open access to the data, allows the development of new applications to monitor urban sites. However, S1 is rarely considered when fine resolution is required due to the large pixel size and the need for spatial averaging to obtain robust estimators. We propose a method to improve Sentinel-1 urban classification performance by exploiting one Multi-Spectral (MS) image acquired by Sentinel-2 (S2). MS data is used for tracing the precise natural boundaries in a scene through superpixels segmentation. A machine learning approach is then applied to interpret the thematic context of each segment from short temporal stacks of coregistered SAR data. We use a short sensing period (around two months), so rapid changes can be traces. The proposed fusion of S1 and S2 data was tested in the area of Milan (Italy), with a total accuracy of about 90%. The ability to follow high-resolution details in a mixed environment is demonstrated, opening the possibility of efficiently tracing the human footprint.
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Idrizi, Bashkim, and Neriman Selimi. "Mapping the surrounding environment by pupils. Case study: Primary school “Ismail Qemali” in Chair - Skopje." Proceedings of the ICA 4 (December 3, 2021): 1–6. http://dx.doi.org/10.5194/ica-proc-4-46-2021.
Abstract:
Abstract. Cartography in primary schools in the Republic of North Macedonia is present as part of geography subject, for four years from sixth to ninth level, per two hours weekly. Program is limited only on usage of paper maps aimed for learning geospatial phenomena, without information for map making process.Step forward toward increasing the awareness for including mapping in practical part of curricula in geography and other related subjects, are the activities undertaken by the Geo-SEE Institute from Skopje, by giving practical lectures to pupils in Primary School “Ismail Qemali” in Chair municipality, for usage the digital cartography tools via GIS software.Training was designed to be used FOSS for GIS and open geospatial data by teachers and pupils. Field identification and collection of geospatial data based on ortho images and other base materials, as well usage of smart phones have been used as supplementary methodology for establishing geospatial database aimed for map compilation. Voluntary geographic information and crowd sourcing methodologies as opportunities for usage in teaching and learning process in primary schools not only for geography but for all subjects that intersects with geospatial information, were explained to attendees. Within very short period of one and half month, before pandemic on march 2020, pupils achieved to work with basic tools of QGIS software, as well to compile two maps, one geographical map of North Macedonia, and a map of neighbourhood “Topansko Pole (Fushë Topanë)” as city map of the settlement in which the primary school is located.
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Kuodytė, Vilija, and Linas Petkevičius. "Education-to-Skill Mapping Using Hierarchical Classification and Transformer Neural Network." Applied Sciences 11, no. 13 (June 24, 2021): 5868. http://dx.doi.org/10.3390/app11135868.
Abstract:
Skills gained from vocational or higher education form an essential component of country’s economy, determining the structure of the national labor force. Therefore, knowledge on how people’s education converts to jobs enables data-driven choices concerning human resources within an ever-changing job market. Moreover, the relationship between education and occupation is also relevant in times of global crises, such as the COVID-19 pandemic. Healthcare system overload and skill shortage on one hand, and job losses related to lock-downs on the other, have exposed a necessity to identify target groups with relevant education backgrounds in order to facilitate their occupational transitions. However, the relationship between education and employment is complex and difficult to model. This study aims to propose the methodology that would allow us to model education-to-skill mapping. Multiple challenges arising from administrative datasets, namely imbalanced data, complex labeling, hierarchical structure and textual data, were addressed using six neural network-based algorithms of incremental complexity. The final proposed mathematical model incorporates the textual data from descriptions of education programs that are transformed into embeddings, utilizing transformer neural networks. The output of the final model is constructed as the hierarchical classification task. The effectiveness of the proposed model is demonstrated using experiments on national level data, which covers whole population of Lithuania. Finally, we provide the recommendations for the usage of proposed model. This model can be used for practical applications and scenario forecasting. Some possible applications for such model usage are demonstrated and described in this article. The code for this research has been made available on GitHub.
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Joy, Jibin, and Dr S. Devaraju. "Secure Deduplication For Cloud Storage Using Memory Mapping Technique For Improving Performance And Security." Journal of University of Shanghai for Science and Technology 23, no. 09 (September 1, 2021): 1–13. http://dx.doi.org/10.51201/jusst/21/08498.
Abstract:
Data deduplication is a crucial technique for packing data and reducing duplication when transferring data. It is widely used in the cloud to restrict the usage of capacity memory and aids in transmission capacity sparing. Before redistributing data, an encryption mechanism is used to ensure the integrity of sensitive data during the deduplication process. The SHA algorithm is being used to save data in text format. To generate the security bits, padding is appended to the text. In de-duplication, it calculates the hash, i.e. hexadecimal number, string, and integer data. Hash-based de-duplication is the implementation of whole file hashing to the entire file. Text data’s hash values are considered to as feature properties. In contrast to traditional deduplication solutions, clients that transfer data to the cloud certify duplication inside the cloud data. In virtualization, both limiting primary memory size and memory blockage are considered important bottlenecks. Memory deduplication identifies pages with the same content and merges them into a single data file, reducing memory usage, memory parceling, and improving execution. In cloud storage, the MPT is used to deduplication so that it is used in single copies of the same data for different data owners. If any data users try to replicate the same data, it will be mapped and related to the archive data, implying that the data can’t be stored away. To ensure cloud data security, encryption techniques are used to encrypt data throughout deduplication procedures and prior to outsourcing cloud data.
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Pisařovic, Ivo, David Procházka, Jaromír Landa, Jan Kolomazník, Karel Zídek, and Lukáš Franěk. "Effective Collaborative Mapping Based on Mobile Devices." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 65, no. 6 (2017): 2067–72. http://dx.doi.org/10.11118/actaun201765062067.
Abstract:
There are numerous situations when it is utmost important to share efficiently some spatial data among a group of people. Floods can be taken as an obvious example. Many stakeholders including mayor or rescue service workers must have actual information about the conditions in the terrain. And most importantly, all of these can contribute to the information. Among these situations involving the crisis management, we dare to mention especially the inventory process. Traffic signs, road lanes, trees, lights and many other different object must be regularly maintained. Most of the organizations use some kind of geographical information system to keep the information about the maintained property. Our article is focused on development of mobile application that allows to acquire spatial data that are later used in these information systems. Thanks to real-time data synchronization between multiple devices, field workers can cooperate and share data immediately to an operating center or with the other workers. We describe the design of our mobile mapping application, comparison with other existing solutions and problems of real-time synchronization between different devices. Finally, we provide details about application usage in different municipalities.
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Reed, S. C. "Development of a parametric-based indirect aircraft structural usage monitoring system using artificial neural networks." Aeronautical Journal 111, no. 1118 (April 2007): 209–30. http://dx.doi.org/10.1017/s0001924000004474.
Abstract:
The development of a parametric-based indirect aircraft structural usage monitoring system using artificial neural networks is described. Flight parametric data, captured during Operational Loads Measurement have been used to predict strains or stresses at key structural locations for several military aircraft types, using mapping relationships determined by artificial neural networks. A framework for the development of a neural network-based structural usage monitor is discussed and the basic architecture of the multilayer perceptron artificial neural network is described. Additionally, results from case studies are presented. It is concluded that this technology could provide the basis for accurate, cost-effective structural usage monitoring systems across the range of military aircraft types and roles.
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Hanna, Alexander, Ben Sayre, Leticia Bode, JungHwan Yang, and Dhavan Shah. "Mapping the Political Twitterverse: Candidates and Their Followers in the Midterms." Proceedings of the International AAAI Conference on Web and Social Media 5, no. 1 (August 3, 2021): 510–13. http://dx.doi.org/10.1609/icwsm.v5i1.14179.
Abstract:
Twitter provides a new and important tool for political actors. In the 2010 midterm elections, the vast majority of candidates for the U.S. House of Representatives and virtually all candidates for U.S. Senate and governorships used Twitter to reach out to potential supporters, direct them to particular pieces of information, request campaign contributions from them, and mobilize their political action. Despite the level of activity, we have little understanding of what the political Twitterverse looks like in terms of communication and discourse. This project seeks to remedy that lack of understanding by mapping candidates and their followers according to their use of hashtags (keywords) and user mentions (direct mentioning of other Twitter users). We have a unique data set constructed from tweets of most of the candidates running for the U.S. House of Representatives in 2010, all the candidates for the Senate and governorships, and a random sample of their followers. From this we utilize multidimensional scaling to construct a visual map based on hashtag and user mention usage. We find that our data have both local and global interpretations that reflect both political leaning and strategies of communication. This study provides insight into innovation in new media usage in political behavior in particular and a bounded topic space in general.
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Thiele, Samuel T., Zakaria Bnoulkacem, Sandra Lorenz, Aurélien Bordenave, Niccolò Menegoni, Yuleika Madriz, Emmanuel Dujoncquoy, Richard Gloaguen, and Jeroen Kenter. "Mineralogical Mapping with Accurately Corrected Shortwave Infrared Hyperspectral Data Acquired Obliquely from UAVs." Remote Sensing 14, no. 1 (December 21, 2021): 5. http://dx.doi.org/10.3390/rs14010005.
Abstract:
While uncrewed aerial vehicles are routinely used as platforms for hyperspectral sensors, their application is mostly confined to nadir imaging orientations. Oblique hyperspectral imaging has been impeded by the absence of robust registration and correction protocols, which are essential to extract accurate information. These corrections are especially important for detecting the typically small spectral features produced by minerals, and for infrared data acquired using pushbroom sensors. The complex movements of unstable platforms (such as UAVs) require rigorous geometric and radiometric corrections, especially in the rugged terrain often encountered for geological applications. In this contribution we propose a novel correction methodology, and associated toolbox, dedicated to the accurate production of hyperspectral data acquired by UAVs, without any restriction concerning view angles or target geometry. We make these codes freely available to the community, and thus hope to trigger an increasing usage of hyperspectral data in Earth sciences, and demonstrate them with the production of, to our knowledge, the first fully corrected oblique SWIR drone-survey. This covers a vertical cliff in the Dolomites (Italy), and allowed us to distinguish distinct calcitic and dolomitic carbonate units, map the qualitative abundance of clay/mica minerals, and thus characterise seismic scale facies architecture.