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  1. Article ; Online: Open data in a deeply connected world.

    Cheifet, Barbara

    Genome biology

    2020  Volume 21, Issue 1, Page(s) 96

    MeSH term(s) Open Access Publishing ; Periodicals as Topic ; Preprints as Topic
    Keywords covid19
    Language English
    Publishing date 2020-04-20
    Publishing country England
    Document type Editorial
    ZDB-ID 2040529-7
    ISSN 1474-760X ; 1474-760X
    ISSN (online) 1474-760X
    ISSN 1474-760X
    DOI 10.1186/s13059-020-02010-6
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Open data in a deeply connected world

    Barbara Cheifet

    Genome Biology, Vol 21, Iss 1, Pp 1-

    2020  Volume 4

    Keywords Biology (General) ; QH301-705.5 ; Genetics ; QH426-470
    Language English
    Publishing date 2020-04-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article: Artificial Intelligence (AI) in cloud integrated, open access pathology publications: perspectives on 2020

    Diagnostic pathology, 5(1):276

    2019  

    Abstract: ... discussion of medical images, especially microscopic slides. 2019 DATA: The journal and its concurrent ... systems such as access to article integrated VS, data storage, or scientific data banks (atlas of fine ... on specific substantial differences between the physical real world and its virtual transformations guide ...

    Abstract GOAL: To describe, maintain and further develop the communication network of medical sciences www.diagnosticpathology.eu that publishes electronically submitted peer reviewed medical articles and fully takes advantage of its electronic environment, and to give the reader the opportunity to view digitized whole slide images (virtual slides, VS), to measure image objects, and to annotate images and text. Background: The unique open access, peer reviewed journal www.diagnosticpathology.eu is embedded in a communication environment of different cloud components. The components include several distributed servers and databank systems such as access to article integrated VS, data storage, or scientific data banks (atlas of fine granulate and natural and synthetic fiber hazards). IMPLEMENTATION SPECIFICITIES: Theoretical considerations on specific substantial differences between the physical real world and its virtual transformations guide the implementation. The differences include, for example, the minimum number of mandatory space dimensions, of their essential (ir)-reversibility of objects, structures, and functions as well as the relationship of image features to the observation time. The implemented system focuses on communication issues in tissue – based science only. Its volunteers allow disregard any predominantly financial impact such as financial profit. Artificial intelligence (AI) is used to maintain its sustainability, connectivity, distribution, measurement and discussion of medical images, especially microscopic slides. 2019 DATA: The journal and its concurrent operation of interactive communication demonstrate the advantage of AI in open access publication. VS are ready to be screened and annotated by any reader worldwide. QR codes provide DOI registration and upload of oral presentations by the auditorium. Interactive publication permits the release of a distinct continuous article chain. Annotations of VS images can be transferred in public or private databanks. The reader is invited to check his impression of marker scores by own automated measurements. PERSPECTIVES: Applications of AI in tissue – based diagnosis, communication and implementation are not limited to deep learning, quality assurance or so-called diagnosis assistants. AI is on the way to significantly modify medical diagnostics and treatment. These modifications will, in addition, modify our understanding of disease and life. www.diagnosticpathology.eu is one of the pathfinders and pioneers in this unavoidable process.
    Keywords Artificial Intelligence ; Deep Learning ; Open Access Journal ; Tissue – based Diagnosis ; Virtual Slide
    Language English
    Document type Article
    Database Repository for Life Sciences

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  5. Article ; Online: An Overview of Open Source Deep Learning-Based Libraries for Neuroscience

    Louis Fabrice Tshimanga / Federico Del Pup / Maurizio Corbetta / Manfredo Atzori

    Applied Sciences, Vol 13, Iss 5472, p

    2023  Volume 5472

    Abstract: ... of application (e.g., data type, neuroscience area, task), model engineering (e.g., programming language, model ... by knowing which modules may be improved, connected, or added. ... of scientific publications present applications of deep neural networks for biomedical data analysis. Due ...

    Abstract In recent years, deep learning has revolutionized machine learning and its applications, producing results comparable to human experts in several domains, including neuroscience. Each year, hundreds of scientific publications present applications of deep neural networks for biomedical data analysis. Due to the fast growth of the domain, it could be a complicated and extremely time-consuming task for worldwide researchers to have a clear perspective of the most recent and advanced software libraries. This work contributes to clarifying the current situation in the domain, outlining the most useful libraries that implement and facilitate deep learning applications for neuroscience, allowing scientists to identify the most suitable options for their research or clinical projects. This paper summarizes the main developments in deep learning and their relevance to neuroscience; it then reviews neuroinformatic toolboxes and libraries collected from the literature and from specific hubs of software projects oriented to neuroscience research. The selected tools are presented in tables detailing key features grouped by the domain of application (e.g., data type, neuroscience area, task), model engineering (e.g., programming language, model customization), and technological aspect (e.g., interface, code source). The results show that, among a high number of available software tools, several libraries stand out in terms of functionalities for neuroscience applications. The aggregation and discussion of this information can help the neuroscience community to develop their research projects more efficiently and quickly, both by means of readily available tools and by knowing which modules may be improved, connected, or added.
    Keywords deep learning ; machine learning ; neuroscience ; neuroinformatics ; open source ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 006
    Language English
    Publishing date 2023-04-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article: Open-source intelligence: a comprehensive review of the current state, applications and future perspectives in cyber security.

    Yadav, Ashok / Kumar, Atul / Singh, Vrijendra

    Artificial intelligence review

    2023  , Page(s) 1–32

    Abstract: The volume of data generated by today's digitally connected world is enormous, and a significant ... extracts information from a collection of publicly available and accessible data. OSINT can provide ... portion of it is publicly available. These data sources are web archives, public databases, and ...

    Abstract The volume of data generated by today's digitally connected world is enormous, and a significant portion of it is publicly available. These data sources are web archives, public databases, and social networks such as Facebook, Twitter, LinkedIn, Emails, Telegrams, etc. Open-source intelligence (OSINT) extracts information from a collection of publicly available and accessible data. OSINT can provide a solution to the challenges in extracting and gathering intelligence from various publicly available information and social networks. OSINT is currently expanding at an incredible rate, bringing new artificial intelligence-based approaches to address issues of national security, political campaign, the cyber industry, criminal profiling, and society, as well as cyber threats and crimes. In this paper, we have described the current state of OSINT tools/techniques and the state of the art for various applications of OSINT in cyber security. In addition, we have discussed the challenges and future directions to develop autonomous models. These models can provide solutions for different social network-based security, digital forensics, and cyber crime-based problems using various machine learning (ML), deep learning (DL) and artificial intelligence (AI) with OSINT.
    Language English
    Publishing date 2023-03-15
    Publishing country England
    Document type Journal Article
    ZDB-ID 1479828-1
    ISSN 1573-7462 ; 0269-2821
    ISSN (online) 1573-7462
    ISSN 0269-2821
    DOI 10.1007/s10462-023-10454-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Book ; Online: An overview of open source Deep Learning-based libraries for Neuroscience

    Tshimanga, Louis Fabrice / Atzori, Manfredo / Del Pup, Federico / Corbetta, Maurizio

    2022  

    Abstract: ... of application (e.g. data type, neuroscience area, task), model engineering (e.g. programming language, model ... available tools, and by knowing which modules may be improved, connected or added. ... of scientific publications present applications of deep neural networks for biomedical data analysis. Due ...

    Abstract In recent years, deep learning revolutionized machine learning and its applications, producing results comparable to human experts in several domains, including neuroscience. Each year, hundreds of scientific publications present applications of deep neural networks for biomedical data analysis. Due to the fast growth of the domain, it could be a complicated and extremely time-consuming task for worldwide researchers to have a clear perspective of the most recent and advanced software libraries. This work contributes to clarify the current situation in the domain, outlining the most useful libraries that implement and facilitate deep learning application to neuroscience, allowing scientists to identify the most suitable options for their research or clinical projects. This paper summarizes the main developments in Deep Learning and their relevance to Neuroscience; it then reviews neuroinformatic toolboxes and libraries, collected from the literature and from specific hubs of software projects oriented to neuroscience research. The selected tools are presented in tables detailing key features grouped by domain of application (e.g. data type, neuroscience area, task), model engineering (e.g. programming language, model customization) and technological aspect (e.g. interface, code source). The results show that, among a high number of available software tools, several libraries are standing out in terms of functionalities for neuroscience applications. The aggregation and discussion of this information can help the neuroscience community to devolop their research projects more efficiently and quickly, both by means of readily available tools, and by knowing which modules may be improved, connected or added.
    Keywords Quantitative Biology - Quantitative Methods ; Computer Science - Machine Learning ; Computer Science - Neural and Evolutionary Computing
    Subject code 006
    Publishing date 2022-12-19
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Demystifying MLOps and Presenting a Recipe for the Selection of Open-Source Tools

    Philipp Ruf / Manav Madan / Christoph Reich / Djaffar Ould-Abdeslam

    Applied Sciences, Vol 11, Iss 8861, p

    2021  Volume 8861

    Abstract: ... data, and system quality metrics are briefly discussed. By identifying aspects of machine learning ... Nowadays, machine learning projects have become more and more relevant to various real-world use ... which can be reused from project to project, open-source tools which help in specific parts of the pipeline ...

    Abstract Nowadays, machine learning projects have become more and more relevant to various real-world use cases. The success of complex Neural Network models depends upon many factors, as the requirement for structured and machine learning-centric project development management arises. Due to the multitude of tools available for different operational phases, responsibilities and requirements become more and more unclear. In this work, Machine Learning Operations (MLOps) technologies and tools for every part of the overall project pipeline, as well as involved roles, are examined and clearly defined. With the focus on the inter-connectivity of specific tools and comparison by well-selected requirements of MLOps, model performance, input data, and system quality metrics are briefly discussed. By identifying aspects of machine learning, which can be reused from project to project, open-source tools which help in specific parts of the pipeline, and possible combinations, an overview of support in MLOps is given. Deep learning has revolutionized the field of Image processing, and building an automated machine learning workflow for object detection is of great interest for many organizations. For this, a simple MLOps workflow for object detection with images is portrayed.
    Keywords MlOps ; tool comparison ; workflow automation ; quality metrics ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 670
    Language English
    Publishing date 2021-09-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Open Source Intelligence’s Methodology Applied to Organizational Communication

    Stefania Fantinelli / Domenico Franco Sivilli

    Mediterranean Journal of Social Sciences, Vol 6, Iss

    2015  Volume 2

    Abstract: ... the effectiveness of organizational communication and online reputation. Open source intelligence is already deeply ... system strictly connected with the external dynamic context. Later on, Butera (1992) defined ... scoped instrument to gather data and information for the organizations to improve decision-making ...

    Abstract Every minute in the world tons of information is generated online through the net. Every single bit could represent a source of potential knowledge for public and private organizations. The purpose of this study is to illustrate how implementing Open Source Intelligence (OSINT) methodology within organizational management can strengthen the brand reputation and competitive intelligence activities. OSINT technique could be also applied to the psychosocial research in order to extend its boundaries, for example in the field of sentiment analysis, opinion tracking and user profiling. The OSINT methodology has been analysed by the psychological organizational theories: Burns and Stalker (1971) claimed that the organization is an organic system strictly connected with the external dynamic context. Later on, Butera (1992) defined the organization as an organism concerned with both internal and external communication, therefore open source intelligence can facilitate a right management of information and knowledge. OSINT represents a new and wide-scoped instrument to gather data and information for the organizations to improve decision-making, conduct preventive risk analyses, enhance the due-diligence information acquisition processes, monitor the effectiveness of organizational communication and online reputation. Open source intelligence is already deeply linked with social sciences and should be part of enterprises’ organizational activity. What are the challenges related to implementing a successful OSINT strategy in the organization’s communication model? DOI:10.5901/mjss.2015.v6n2p233
    Keywords Social Sciences ; H
    Subject code 020
    Language English
    Publishing date 2015-03-01T00:00:00Z
    Publisher richtmann publishing
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Book: In situ monitoring of oxygen depletion in hypoxic ecosystems of coastal and open seas, and land-locked water bodies (HYPOX)

    Wojack, Heike

    Abstract: ... of the art world data centre. We will connect this project to the GOOS Regional Alliances and the SCOR ... sensitivity towards change: open ocean, oxic with high sensitivity to global warming (Arctic), semi-enclosed ... increased stratification, reduced deep-water circulation and changes in wind patterns affecting transport ...

    Institution Max-Planck-Gesellschaft zur Foerderung der Wissenschaften, Max-Planck-Institut fuer marine Mikrobiologie, Celsiusstr. 1, 28359, Bremen, DE
    Abstract Objective: Hypoxic (low oxygen) conditions in aquatic ecosystems increase in number, duration and extent due to global warming and eutrophication. Global warming will lead to degassing of oxygen, increased stratification, reduced deep-water circulation and changes in wind patterns affecting transport and mixing. Projected increases in hypoxia (e.g. doubling of dead zones) are accompanied by enhanced emission of greenhouse gases, losses in biodiversity, ecosystem functions and services such as fisheries, aquaculture and tourism. A better understanding of global changes in oxygen depletion requires a global observation system continuously monitoring oxygen at high resolution, including assessment of the role of the seafloor in controlling the sensitivity of aquatic systems to and recovery from hypoxia. Here we propose to monitor oxygen depletion and associated processes in aquatic systems that differ in oxygen status or sensitivity towards change: open ocean, oxic with high sensitivity to global warming (Arctic), semi-enclosed with permanent anoxia (Black Sea, Baltic Sea) and seasonally or locally anoxic land-locked systems (fjords, lagoons, lakes) subject to eutrophication. We will improve the capacity to monitor oxygen depletion globally, by implementing reliable long-term sensors to different platforms for in situ monitoring; and locally by training and implementing competence around the Black Sea. Our work will contribute to GEOSS tasks in the water, climate, ecosystem and biodiversity work plans, and comply to GEOSS standards by sharing of observations and products with common standards and adaptation to user needs using a state of the art world data centre. We will connect this project to the GOOS Regional Alliances and the SCOR working group and disseminate our knowledge to local, regional and global organisations concerned with water and ecosystem health and management.
    Keywords Sauerstoff ; Aquatisches Oekosystem ; Vermehrung ; Globale Erwaermung ; Eutrophierung ; Blei ; Schichtung ; Bewaesserung ; Zirkulation ; Wind ; Verkehr ; Sauerstoffmangel ; Emission ; Gewaechshaus ; Gasfoermiger Stoff ; Biologische Vielfalt ; Oekosystem ; Dienstleistung ; Fischerei ; Aquakultur ; Fremdenverkehr ; Globale Aspekte ; Sauerstoffbedarf ; Dauerbeobachtung ; Meeresboden ; Kontrollmassnahme ; Erholung ; Bildschirmgeraet ; Meer ; Geisteswissenschaften ; Lagune ; Werkzeug ; Sensor ; Bahnsteig ; In-Situ ; Monitoring ; Ausbildung ; Zustaendigkeit ; Arbeit ; Klima ; Plan (Planung) ; Produktbeobachtung ; Bedarf ; Staat ; Hohe See ; Datenzentrum ; Gans ; Gruppenarbeit ; Koerperschaft ; Gesundheit ; Kuestenoekosystem ; Ostsee
    Language English
    Document type Book
    Remark project start: 04/01/2009 project end: 03/31/2012 grant ID: 226213
    Database Environmental research database (UFORDAT) of the German Federal Environment Agency (UBA)

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