617,721 research outputs found

    Big Data Emerging Technology: Insights into Innovative Environment for Online Learning Resources

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    Digital devices like tablets, smart phones, and laptop have become increasingly raised and utilised in higher education. As a result, current trends on ICT (information and communication technology) used in education begin widely with focusing on teaching and learning. The new concept of big data in recent ICT domain extends the promising research direction on online learning and big data integration through promising content that can be tailored for each student based on the context and Internet behaviour of users in online learning. This paper aims to explore innovative design for innovative online learning in Higher education using Big Data approach. Critical review from referred journals and books was conducted using thematic analysis. This paper proposes model reference which can be implemented with the technology in teaching and learning to improve student learning environment and outcomes and to enhance students’ development, performance and achievement in learning process in higher education

    Medical Image Processing using Deep Learning Techniques in Big Data Perspective

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    Artificial intelligence and machine learning will be the driving forces behind the next computing revolution. These technologies rely on the ability to identify trends from historical information and predict future outcomes. One of the best machine learning techniques, deep learning is employed in a variety of applications, including object recognition, picture categorization, image analysis, and clinical archives. Image and video data are necessary for both diagnosing the patient's illness and determining its severity. Convolutional neural networks are efficient gears for digital picture classification and image understanding. The production of medical photographs has ex-ponentially increased as a result of the proliferation of digital devices and the development of camera technology, which creates Bigdata. Massive, difficult-to-manage volumes of structured, unstructured data are referred to as "Big data". The more data processed for analysis, the greater will be the analytical accuracy and also the greater would be the confidence in our decisions based on the analytical findings. In this paper, we proposed a novel method for early detection of pneumonia disease using deep learning techniques along with the big data storage and big data analytics to achieve more better performance. The results show that, the model achieved 91.16% of accuracy and 93.22% of F1-score

    New Policy Frame and Directions of Vocational Education, Training and Employment for Continuous Advances

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    This research is designed to suggest necessary education and training, new employment framework and main tasks for Korea to accomplish sustainable development based on foresight in a future society. First, the study reviews earlier studies regarding the future foresight and understood future trends, key drivers and uncertainty which have impacts on the education and training, and employment in the future. The STEEP (Society, Technology, Economy, Environment, Politics) analysis framework is laid out to carry out this study. Second, the research focuses to analyze earlier studies, policies and NAVER news related to the education, training and employment in a time sequence. With the collection of data, the research shows the vocational education and training system (relationship between education, training and employment) and its main issues by using big data analysis. Furthermore, the study draws the future issues on the education, training and employment through the keyword matrix analysis. Third, the research selects the crucial future trends, key drivers, and uncertainty in the education, training and employment sectors. Experts group meetings and Delphi study ran in parallel to create the foresight scenario based on the results. The survey contributes not only to draw the high feasible scenario with a desirable picture of our future but also to show the policy issues for the education, training and employment. Fourth, the research suggests the new education, training, framework and policy issues for future employment based upon the analysis and survey results. ..

    Topic-based analysis for technology intelligence

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    University of Technology Sydney. Faculty of Engineering and Information Technology.Since the past several decades, scientific literature, patents and other semi-structured technology indicators have been generating and accumulating at a very rapid rate. Their growth provides a wealth of information regarding technology development in both the public and private domain. However, it has also caused increasingly severe information overload problems whereby researchers, analysts and decision makers are not able to read, summarize and understand massive technical documents and records manually. The concept and tools of technology intelligence aims to handle this issue. In the current technology intelligence research, one of the big challenges is that, the frameworks and applications of existing technology intelligence conducted semantic content analysis and temporal trend estimation separately, lacking a comprehensive perspective on trend analysis of the detailed content within an area. In addition, existing research of technology intelligence is mainly constructed on the fundamentals of semantic properties of the semi-structured technology indicators; however, single keywords and their ranking alone, are too general or ambiguous to represent complex concepts and their corresponding temporal patterns. Thirdly, systematic post-processing, forecasting and evaluation on both content analysis and trend identification outputs are still in great demand, for diverse and flexible technological decision support and opportunity discovery. This research aims to handle these three challenges in both theoretical and practical aspects. It first quantitatively defines and presents temporal characteristics and semantic properties of typical semi-structured technology indicators. Then this thesis proposes a framework of topic-based technology intelligence, with three main functionalities, including data-driven trend identification, topic discovery and comprehensive topic evaluation, to synthetically process and analyse technological publication count sequence, textual data and metadata of target technology indicators. To achieve the three functionalities, this research proposes an empirical technology trend analysis method to extract temporal trend turning points and trend segments, which help with producing a more reasonable time-based measure; a topic-based technological forecasting method to first discover and characterize the semantic knowledge underlying in massive textual data of technology indicators, meanwhile estimating the future trends of the discovered topics; a comprehensive topic evaluation method that links metadata and discovered topics, to provide integrated landscape and technological insight in depth. In order to demonstrate the proposed topic-based technology intelligence framework and all the related methods, this research presents case studies with both patents and scientific literature. Experimental results on Australian patents, United States patents and scientific papers from Web of Science database, showed that the proposed framework and methods are well-suited in dealing with semi-structured technology indicators analysis, and can provide valuable topic-based knowledge to facilitate further technological decision making or opportunity discovery with good performance

    Triangulum City Dashboard: An Interactive Data Analytic Platform for Visualizing Smart City Performance

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    Cities are becoming smarter by incorporating hardware technology, software systems, and network infrastructure that provide Information Technology (IT) systems with real-time awareness of the real world. What makes a “smart city” functional is the combined use of advanced infrastructure technologies to deliver its core services to the public in a remarkably efficient manner. City dashboards have drawn increasing interest from both city operators and citizens. Dashboards can gather, visualize, analyze, and inform regional performance to support the sustainable development of smart cities. They provide useful tools for evaluating and facilitating urban infrastructure components and services. This work proposes an interactive web-based data visualization and data analytics toolkit supported by big data aggregation tools. The system proposed is a cloud-based prototype that supports visualization and real-time monitoring of city trends while processing and displaying large data sets on a standard web browser. However, it is capable of supporting online analysis processing by answering analytical queries and producing graphics from multiple resources. The aim of this platform is to improve communication between users and urban service providers and to give citizens an overall view of the city’s state. The conceptual framework and architecture of the proposed platform are explored, highlighting design challenges and providing insight into the development of smart cities. Moreover, results and the potential statistical analysis of important city services offered by the system are introduced. Finally, we present some challenges and opportunities identified through the development of the city data platform.publishedVersio

    Design Trend Forecasting by Combining Conceptual Analysis and Semantic Projections: New Tools for Open Innovation

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    [EN] In this paper, we describe a new trend analysis and forecasting method (Deflexor), which is intended to help inform decisions in almost any field of human social activity, including, for example, business, art and design. As a result of the combination of conceptual analysis, fuzzy mathematics and some new reinforcing learning methods, we propose an automatic procedure based on Big Data that provides an assessment of the evolution of design trends. The resulting tool can be used to study general trends in any field¿depending on the data sets used¿while allowing the evaluation of the future acceptance of a particular design product, becoming in this way, a new instrument for Open Innovation. The mathematical characterization of what is a semantic projection, together with the use of the theory of Lipschitz functions in metric spaces, provides a broad-spectrum predictive tool. Although the results depend on the data sets used, the periods of updating and the sources of general information, our model allows for the creation of specific tools for trend analysis in particular fields that are adaptable to different environments.This research was funded by Istituto Europeo di Design and Generalitat Valenciana, Cátedra de Transparencia y Gestión de Datos, Universitat Politècnica de València (PID2019-105708RBC21 (MICIU/FEDER,UE)).Manetti, A.; Ferrer Sapena, A.; Sánchez Pérez, EA.; Lara-Navarra, P. (2021). Design Trend Forecasting by Combining Conceptual Analysis and Semantic Projections: New Tools for Open Innovation. Journal of Open Innovation: Technology, Market, and Complexity. 7(1):1-26. https://doi.org/10.3390/joitmc7010092S1267

    What Role Do Tech Companies\u27 R&D Expenditures Play in Analysts Sales and Earnings Forecasts?

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    Many top market capitalization companies are information technology (IT) firms, including Apple, Google, Microsoft, and Facebook, each of which is valued at more than $300 billion. Facebook is less than 10 years old and is one of the top 10 companies in the world in terms of market capitalization. However, technologies change rapidly; website revenue—which once grew at a brisk rate—has slowed down, while mobile technology growth is increasing and technology trends are shifting toward cloud hosting and big data analytics. IT companies that have increased their R&D spending remain leaders throughout periods of technology change. Companies such as Facebook and Google have doubled and tripled their profits, respectively over` the past decade. In this dynamic environment, analysts play a critical role in evaluating IT company financial statements and estimating company sales and earnings per share (EPS). This study examines how changes in R&D spending are related to analysts’ sales and earnings estimate revisions. An analysis of data over a 20-year period shows that analysts typically revise their sales estimates based on changes in a company’s R&D expenditures. The correlation between analyst earnings estimates and R&D expenditures, however, varies based on company size and industry within the IT sector. Analysts play a particularly important role in small companies, where the correlation between R&D and sales changes is not as high as in large companies. Analysts are thus critical to the functioning of capital markets in the IT sector

    SparkFlow : towards high-performance data analytics for Spark-based genome analysis

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    The recent advances in DNA sequencing technology triggered next-generation sequencing (NGS) research in full scale. Big Data (BD) is becoming the main driver in analyzing these large-scale bioinformatic data. However, this complicated process has become the system bottleneck, requiring an amalgamation of scalable approaches to deliver the needed performance and hide the deployment complexity. Utilizing cutting-edge scientific workflows can robustly address these challenges. This paper presents a Spark-based alignment workflow called SparkFlow for massive NGS analysis over singularity containers. SparkFlow is highly scalable, reproducible, and capable of parallelizing computation by utilizing data-level parallelism and load balancing techniques in HPC and Cloud environments. The proposed workflow capitalizes on benchmarking two state-of-art NGS workflows, i.e., BaseRecalibrator and ApplyBQSR. SparkFlow realizes the ability to accelerate large-scale cancer genomic analysis by scaling vertically (HyperThreading) and horizontally (provisions on-demand). Our result demonstrates a trade-off inevitably between the targeted applications and processor architecture. SparkFlow achieves a decisive improvement in NGS computation performance, throughput, and scalability while maintaining deployment complexity. The paper’s findings aim to pave the way for a wide range of revolutionary enhancements and future trends within the High-performance Data Analytics (HPDA) genome analysis realm.Postprin

    Bibliometric Analysis of Citation Trends and Publications on E-government in Southern African Countries: A Human-computer Interactions and IT Alignment Debate

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    Due to technology adoption, many countries are embracing e-government. This study presents the growth and pattern of research on e-government articles and conference proceedings internationally, by scholars in the Southern African countries. It presents research patterns, trends and current gaps in e-government, as well as the most prolific authors and the level of outputs’ prominence. This paper uses bibliometric tools to present the analysis of articles on Web of Science, Scopus and Google Scholar databases. R computational programming for big data analysis was used to generate summarized metrics. The citation sample size was (n = 33,689), µ = 625, and the outputs impact based on total link strength of citations were; min =11.0, max = 1,686.0 and µ = 118.2, showing the Southern African scholars outputs visibility and prominence on e-government research. The findings present the most prolific authors in the Southern African region and the prominence of their outputs on e-governance. The study, through the computational synthesis of the data, also reveals some of the missing links in e-governance research designs and implementation. Furthermore, the study indicates that the service-oriented design of e-government platforms are still lacking, and the integration of Information Technology (IT) alignment, which is necessary to successfully implement e-government is lacking. The use and integration of mobile technology to enhance citizen-centric and participatory public governance platform and e-government implementation is not sufficiently addressed. Therefore, there is need to measure the maturity level of e-government IT deployment, its user-interfaces, as well as the design of an e-government that is able to respond to often embryonic and heterogeneous needs of citizens

    Bibliometric Analysis of Citation Trends and Publications on E-government in Southern African Countries: A Human-computer Interactions and IT Alignment Debate

    Get PDF
    Due to technology adoption, many countries are embracing e-government. This study presents the growth and pattern of research on e-government articles and conference proceedings internationally, by scholars in the Southern African countries. It presents research patterns, trends and current gaps in e-government, as well as the most prolific authors and the level of outputs’ prominence. This paper uses bibliometric tools to present the analysis of articles on Web of Science, Scopus and Google Scholar databases. R computational programming for big data analysis was used to generate summarized metrics. The citation sample size was (n = 33,689), µ = 625, and the outputs impact based on total link strength of citations were; min =11.0, max = 1,686.0 and µ = 118.2, showing the Southern African scholars outputs visibility and prominence on e-government research. The findings present the most prolific authors in the Southern African region and the prominence of their outputs on e-governance. The study, through the computational synthesis of the data, also reveals some of the missing links in e-governance research designs and implementation. Furthermore, the study indicates that the service-oriented design of e-government platforms are still lacking, and the integration of Information Technology (IT) alignment, which is necessary to successfully implement e-government is lacking. The use and integration of mobile technology to enhance citizen-centric and participatory public governance platform and e-government implementation is not sufficiently addressed. Therefore, there is need to measure the maturity level of e-government IT deployment, its user-interfaces, as well as the design of an e-government that is able to respond to often embryonic and heterogeneous needs of citizens
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