Analytic Web Research Articles

Sustainable Development of Civil Engineering, Construction and Building Technology

Sustainable development of civil engineering, construction and building technology can be supported by fundamental scientific achievements and development theories. The current paper aims at over viewing the state of the art in terms of published papers related to theoretical methods that are applied to support sustainable evaluation and selection processes in civil engineering. The review is limited solely to papers referred to in the Clarivate Analytic Web of Science core collection database. As the focus is on development, it aims at reviewing how the papers on developments and applications have been distributed and journals. The articles are grouped by research domains, problems analyzed and the decision-making approaches used. The findings of the current review paper show that Devekionebt if applications have been constantly growing and particularly increased in the last three years, confirming the great potential and prospects of sustainable development of civil engineering, construction and building technology.

A text mining and topic modeling based bibliometric exploration of information science research

This study investigates the evolution of information science research based on bibliometric analysis and semantic mining. The study discusses the value and application of metadata tagging and topic modeling. Forty-two thousand seven hundred thirty-eight articles were extracted from Clarivate Analytic's Web of Science Core Collection 2010-2020. This study was divided into two phases. Firstly, bibliometric analyzes were performed with VOSviewer. Secondly, the topic identification and evolution trends of information science research were conducted through the topic modeling approach latent dirichlet allocation (LDA) is often used to extract themes from a corpus, and the topic model was a representation of a collection of documents that is simplified using topic-modeling-toolkit (TMT). The top 10 core topics (tags) were information research design, information health-based, model data public, study information studies, analysis effect implications, knowledge support web, data research, social research study, study media information, and research impact time for the studied period. Not only does topic modeling assist in identifying popular topics or related areas within a researcher's area, but it may be used to discover emerging topics or areas of study throughout time.

CircadiOmics: circadian omic web portal.

Circadian rhythms are a foundational aspect of biology. These rhythms are found at the molecular level in every cell of every living organism and they play a fundamental role in homeostasis and a variety of physiological processes. As a result, biomedical research of circadian rhythms continues to expand at a rapid pace. To support this research, CircadiOmics (http://circadiomics.igb.uci.edu/) is the largest annotated repository and analytic web server for high-throughput omic (e.g. transcriptomic, metabolomic, proteomic) circadian time series experimental data. CircadiOmics contains over 290 experiments and over 100 million individual measurements, across >20 unique tissues/organs, and 11 different species. Users are able to visualize and mine these datasets by deriving and comparing periodicity statistics for oscillating molecular species including: period, amplitude, phase, P-value and q-value. These statistics are obtained from BIO_CYCLE and JTK_CYCLE and are intuitively aggregated and displayed for comparison. CircadiOmics is the most up-to-date and cutting-edge web portal for searching and analyzing circadian omic data and is used by researchers around the world.

Recent advances in linear and nonlinear Raman spectroscopy. Part XIV

AbstractThis article is an overview of advances in Raman spectroscopy published in 2019 in the Journal of Raman Spectroscopy (JRS) and, in addition, trends over the past decade across journals that have published papers important to the field of Raman spectroscopy. The trends are based on statistical data of article counts obtained from Clarivate Analytic's Web of Science Core Collection by year and by subfield of Raman spectroscopy. Normally in this review, coverage would be provided for presentations involving Raman Spectroscopy at the following four international conferences previously scheduled for this year: the International Conference on Raman Spectroscopy (ICORS 2020) in Rome, Italy; SCIX 2020 organized by the Federation of Analytical Chemistry and Spectroscopy Societies (FACSS) in Reno, Nevada, USA, in October; the European Conference on Nonlinear Optical Spectroscopy (ECONOS 2020) in Karlsrue, Germany, in April; and the International Conference on the GeoRaman Spectroscopy (GeoRaman 2020) in Bilbao, Spain, in November (originally scheduled for Weihai, China, in June). Of these, the ICORS 2020 has been rescheduled for 2021 at the same location; ECONOS 2020 has been canceled, but instead, a special issue section is being organized by invitation to commemorate the passing of JRS Board member Marcus Motzkus; SCIX 2020 has been changed to a virtual online conference; GeoRaman 2020 has been canceled, but online submission of abstracts will be made available with selected invitations to submit papers for a special issue of JRS. Finally, papers published in JRS in 2019 are highlighted and arranged by topics at the frontier of Raman spectroscopy. Based on these data, presentations, and publications, it is clear that Raman spectroscopy continues as an expanding field of research across a wide range of novel disciplines and applications that provide sensitive photonic information at the molecular level.

Overview of Trends in Global Single Cell Research Based on Bibliometric Analysis and LDA Model (2009–2019)

Abstract Purpose This article aims to describe the global research profile and the development trends of single cell research from the perspective of bibliometric analysis and semantic mining. Design/methodology/approach The literatures on single cell research were extracted from Clarivate Analytic's Web of Science Core Collection between 2009 and 2019. Firstly, bibliometric analyses were performed with Thomson Data Analyzer (TDA). Secondly, topic identification and evolution trends of single cell research was conducted through the LDA topic model. Thirdly, taking the post-discretized method which is used for topic evolution analysis for reference, the topics were also be dispersed to countries to detect the spatial distribution. Findings The publication of single cell research shows significantly increasing tendency in the last decade. The topics of single cell research field can be divided into three categories, which respectively refers to single cell research methods, mechanism of biological process, and clinical application of single cell technologies. The different trends of these categories indicate that technological innovation drives the development of applied research. The continuous and rapid growth of the topic strength in the field of cancer diagnosis and treatment indicates that this research topic has received extensive attention in recent years. The topic distributions of some countries are relatively balanced, while for the other countries, several topics show significant superiority. Research limitations The analyzed data of this study only contain those were included in the Web of Science Core Collection. Practical implications This study provides insights into the research progress regarding single cell field and identifies the most concerned topics which reflect potential opportunities and challenges. The national topic distribution analysis based on the post-discretized analysis method extends topic analysis from time dimension to space dimension. Originality/value This paper combines bibliometric analysis and LDA model to analyze the evolution trends of single cell research field. The method of extending post-discretized analysis from time dimension to space dimension is distinctive and insightful.

Recent advances in linear and nonlinear Raman spectroscopy. Part XIII

AbstractThis article is an overview of advances in Raman spectroscopy published in 2018 in the Journal of Raman Spectroscopy (JRS) and, in addition, trends over the past decade across journals that have published papers important to the field of Raman spectroscopy. The trends are based on statistical data of article counts obtained from Clarivate Analytic's Web of Science Core Collection by year and by subfield of Raman spectroscopy. Coverage is provided for presentations involving Raman spectroscopy at four international conferences this year: the Tenth International Conference on Advanced Vibrational Spectroscopy (ICAVS‐10) in Aukland, New Zealand in July; SCIX 2019 organized by the Federation of Analytical Chemistry and Spectroscopy Societies (FACSS) in Palm Springs, California USA in October; the European Conference on Nonlinear Optical Spectroscopy (ECONOS 2019) in Rouen, France in April; and the Tenth International Congress on the Application of Raman Spectroscopy in Art and Archaeology (RAA 2019) in Potsdam, Germany in September. Finally, papers published in JRS in 2018 are highlighted and arragned by topics at the frontier of Raman spectroscopy. Based on these data, presentations, and publications, it is clear that Raman spectroscopy continues as an expanding field of research across a wide range of novel disciplines and applications that provide sensitive photonic information at the molecular level.

Systematic polypharmacology and drug repurposing via an integrated L1000-based Connectivity Map database mining.

Drug repurposing aims to find novel indications of clinically used or experimental drugs. Because drug data already exist, drug repurposing may save time and cost, and bypass safety concerns. Polypharmacology, one drug with multiple targets, serves as a basis for drug repurposing. Large-scale databases have been accumulated in recent years, and utilization and integration of these databases would be highly helpful for polypharmacology and drug repurposing. The Connectivity Map (CMap) is a database collecting gene-expression profiles of drug-treated human cancer cells, which has been widely used for investigation of polypharmacology and drug repurposing. In this study, we integrated the next-generation L1000-based CMap and an analytic Web tool, the L1000FWD, for systematic analyses of polypharmacology and drug repurposing. Two different types of anti-cancer drugs were used as proof-of-concept examples, including histone deacetylase (HDAC) inhibitors and topoisomerase inhibitors. We identified KM-00927 and BRD-K75081836 as novel HDAC inhibitors and mitomycin C as a topoisomerase IIB inhibitor. Our study provides a prime example of utilization and integration of the freely available public resources for systematic polypharmacology analysis and drug repurposing.

Sustainable Decision-Making in Civil Engineering, Construction and Building Technology

Sustainable decision-making in civil engineering, construction and building technology can be supported by fundamental scientific achievements and multiple-criteria decision-making (MCDM) theories. The current paper aims at overviewing the state of the art in terms of published papers related to theoretical methods that are applied to support sustainable evaluation and selection processes in civil engineering. The review is limited solely to papers referred to in the Clarivate Analytic Web of Science core collection database. As the focus is on multiple-criteria decision-making, it aims at reviewing how the papers on MCDM developments and applications have been distributed by period of publishing, by author countries and institutions, and by journals. Detailed analysis of 2015–2017 journal articles from two Web of Science categories (engineering civil and construction building technology) is presented. The articles are grouped by research domains, problems analyzed and the decision-making approaches used. The findings of the current review paper show that MCDM applications have been constantly growing and particularly increased in the last three years, confirming the great potential and prospects of applying MCDM methods for sustainable decision-making in civil engineering, construction and building technology.

Developing an integrated 2D and 3D WebGIS-based platform for effective landslide hazard management

Collaborative effort for the improvement of landslide database is important during the long-term risk reduction process in large hilly and mountainous regions. This paper presents a novel 2D and 3D WebGIS-based platform for landslide multi-level management and emergency response. The scalable network architecture and three-tier software architecture are designed to support survey data improvement performed by geological surveys in different administrative levels, fast spatial decision support for rescue and evacuation after sudden hazard incidents, as well as prevention information for public access. The web service integration is widely applied in the platform, and proved useful for keeping landslide-related information consistent and up-to-date, since it relies on joint efforts from different government departments with expertise, rather than the local and independent storage pattern. The combined utilization of 2D and 3D WebGIS takes advantage of their respective superiorities, and generates a superior display and analytic web environment for local decision-makers. The 2D map in ArcGIS Flexviewer is mainly for hazard query, spatial statistics and map overlaying analysis during routines, while the 3D scene in Skyline ActiveX component is useful in terrain exploration, rainfall situation analysis and sketch map plotting in emergencies. After elaborating the main modules and key algorithms, the user-friendly platform has been experimented and accepted by three levels of geological surveys in Zhejiang Province, China, and presented as an integrated WebGIS environment for effective landslide hazard management in large prone areas.

Social Media como Canal Estratégico y Operativo dentro del Medio Digital

A Social Media Plan (SMP) basically consists of some main objectives: to determine the Key Performance Indicators (KPI) (as keys to financial or otherwise performance, used to quantify objectives that reflect the performance of an organiz ation and that are usually included in a strategic and achievement plan of the digital campaign according to the general) by means of a dashboard, metrics that convert or monetize, (disciplines that allow evaluating their achievement) and the tools to measure the achieved objectives (lined up with the objectives). From this perspective it is possible to integrate three related categories: the technique of the analytic web, the sum of the actions, mentions, and the monitoring or x-ray of the activity in the social media with global influence, into the impact of the Return on Investment (ROI) of a brand. All of it must match the global strategic objectives of the company.

Comparing the Effect of Matrix Factorization Techniquesin Reducing the Time Complexity for Traversing the Big Data of Recommendation Systems

 Abstract—In this fast trending technological era, data is growing very fast all around the globe. Today by analyzing large data sets, one can spot business trends, detect environmental changes, predict forthcoming social agendas and combat crime. This so-called Big Data analytics is challenging and dependent on time complexity. Amidst all this, we also know that space is becoming lesser day by day. In a time when computer imaging and web browsing demand the use of many different data, it is very important for us to be able to store all the types in reasonably sized matrices. A database is like a matrix but due to the growing data it will have a never ending addition of rows. To tackle this situation, we have tried to compare some matrix compression techniques that will help in efficient and fast working of analytic web recommendation systems and will decrease the effort of information retrieval from large data sets.

A Generic Model for Student Data Analytic Web Service (SDAWS)

Any university management system accumulates a cartload of data and analytics can be applied on it to gather useful information to aid the academic decision making process. This paper is a novel attempt to demonstrate the significance of a data analytic web service in the education domain. This can be integrated with the University Management System or any other application of the university easily. Analytics as a web service offers much benefits over the traditional analysis methods. The web service can be hosted on a web server and accessed over the internet or on to the private cloud of the campus. The data from various courses from different departments can be uploaded and analyzed easily. In this paper we design a web service framework to be used in educational data mining that provide analysis as a service.

Clear and Precise Specification of Ecological Data Management Processes and Dataset Provenance

With the availability of powerful computational and communication systems, scientists now readily access large, complicated derived datasets and build on those results to produce, through further processing, yet other derived datasets of interest. The scientific processes used to create such datasets must be clearly documented so that scientists can evaluate their soundness, reproduce the results, and build upon them in responsible and appropriate ways. Here, we present the concept of an analytic web, which defines the scientific processes employed and details the exact application of those processes in creating derived datasets. The work described here is similar to work often referred to as ?scientific workflow,? but emphasizes the need for a semantically rich, rigorously defined process definition language. We illustrate the information that comprises an analytic web for a scientific process that measures and analyzes the flux of water through a forested watershed. This is a complex and demanding scientific process that illustrates the benefits of using a semantically rich, executable language for defining processes and for supporting automatic creation of process provenance metadata.

Ensuring reliable datasets for environmental models and forecasts

At the dawn of the 21st century, environmental scientists are collecting more data more rapidly than at any time in the past. Nowhere is this change more evident than in the advent of sensor networks able to collect and process (in real time) simultaneous measurements over broad areas and at high sampling rates. At the same time there has been great progress in the development of standards, methods, and tools for data analysis and synthesis, including a new standard for descriptive metadata for ecological datasets (Ecological Metadata Language) and new workflow tools that help scientists to assemble datasets and to diagram, record, and execute analyses. However these developments (important as they are) are not yet sufficient to guarantee the reliability of datasets created by a scientific process — the complex activity that scientists carry out in order to create a dataset. We define a dataset to be reliable when the scientific process used to create it is (1) reproducible and (2) analyzable for potential defects. To address this problem we propose the use of an analytic web, a formal representation of a scientific process that consists of three coordinated graphs (a data-flow graph, a dataset-derivation graph, and a process-derivation graph) originally developed for use in software engineering. An analytic web meets the two key requirements for ensuring dataset reliability: (1) a complete audit trail of all artifacts (e.g., datasets, code, models) used or created in the execution of the scientific process that created the dataset, and (2) detailed process metadata that precisely describe all sub-processes of the scientific process. Construction of such metadata requires the semantic features of a high-level process definition language. In this paper we illustrate the use of an analytic web to represent the scientific process of constructing estimates of ecosystem water flux from data gathered by a complex, real-time multi-sensor network. We use Little-JIL, a high-level process definition language, to precisely and accurately capture the analytical processes involved. We believe that incorporation of this approach into existing tools and evolving metadata specifications (such as EML) will yield significant benefits to science. These benefits include: complete and accurate representations of scientific processes; support for rigorous evaluation of such processes for logical and statistical errors and for propagation of measurement error; and assurance of dataset reliability for developing sound models and forecasts of environmental change.

ANALYTIC WEBS SUPPORT THE SYNTHESIS OF ECOLOGICAL DATA SETS

A wide variety of data sets produced by individual investigators are now synthesized to address ecological questions that span a range of spatial and temporal scales. It is important to facilitate such syntheses so that "consumers" of data sets can be confident that both input data sets and synthetic products are reliable. Necessary documentation to ensure the reliability and validation of data sets includes both familiar descriptive metadata and formal documentation of the scientific processes used (i.e., process metadata) to produce usable data sets from collections of raw data. Such documentation is complex and difficult to construct, so it is important to help "producers" create reliable data sets and to facilitate their creation of required metadata. We describe a formal representation, an "analytic web," that aids both producers and consumers of data sets by providing complete and precise definitions of scientific processes used to process raw and derived data sets. The formalisms used to define analytic webs are adaptations of those used in software engineering, and they provide a novel and effective support system for both the synthesis and the validation of ecological data sets. We illustrate the utility of an analytic web as an aid to producing synthetic data sets through a worked example: the synthesis of long-term measurements of whole-ecosystem carbon exchange. Analytic webs are also useful validation aids for consumers because they support the concurrent construction of a complete, Internet-accessible audit trail of the analytic processes used in the synthesis of the data sets. Finally we describe our early efforts to evaluate these ideas through the use of a prototype software tool, SciWalker. We indicate how this tool has been used to create analytic webs tailored to specific data-set synthesis and validation activities, and suggest extensions to it that will support additional forms of validation. The process metadata created by SciWalker is readily adapted for inclusion in Ecological Metadata Language (EML) files.