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AI & SOCIETY 2022年第1期37卷 195-204页

作者： Fonseca, Fred Penn State Univ Coll Informat Sci & Technol University Pk PA 16802 USA

Although true in some aspects, the suggested characterization of today's science as a dichotomy between traditional science and data-driven science misses some of the nuance, complexity, and possibility that exists between the two positions. Part of the problem is the claim that data Science works without theories. There are many theories behind the data that are used in science. However, for data science, the only theories that matter are those in mathematics, statistics, and computer science. In this conceptual paper, we add two other philosophy of science tenets, experiments and data, to the discussion to create a more nuanced view of how data science uses theories. Following Ihde's concept of technoscience and the incessant quest for more precision, magnification, and resolution, we argue that technology-driven science created a need for more technology-driven science, culminating in data science. Further, we adapt Hacking and Galison's views on physics to argue that data science is also an experimental science, which uses data objects in experiments. Drawing from Heelan (The Journal of Philosophy 85:515-524, 1988), we called these objects "data-objects-for-knowing". Finally, we conclude that data science is a science to study artificially created phenomena-a science to study the data manipulated by the equations and operations of AI. It disregards the connections between data and the real world that were carefully built by the theories from other sciences. In the experiments of data science, data are the world itself. The knowledge created by data science is purposely disconnected from any theory from other sciences;it is a knowledge for the sake of itself.

关键词： data science data objects Heelan Theory Experimental science

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PRACTICAL USE OF data objects IN R PROJECT

PRACTICAL USE OF DATA OBJECTS IN R PROJECT

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13th International Multidisciplinary Scientific Geoconference, SGEM 2013

作者： Stehlikova, Beata Horovcak, Pavel Tech Univ Kosice Inst Control & Informatizat Prod Proc Kosice Slovakia

ISBN: (纸本)9789549181890

The R project is open-source software which becomes a standard among statisticians and is widely used for statistical software development and data analysis. The paper is focused on the use of data objects in R project. Contribution characterizes data objects and deals with their usage. As the model data are used time entries of particular regimes of specified web service. The purpose is to present and describe ways to use object types in the program R.

关键词： R project data objects columns table structure

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Prototype Mechanisms for Supporting the Network of Links to Parameterized data objects

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Procedia Computer Science 2021年 190卷 317-323页

作者： Larisa Ismailova Sergey Kosikov Viacheslav Wolfengagen National Research Nuclear University "Moscow Engineering Physics Institute" Kashirskoye Shosse 31 Moscow 115409 Russia NAO "JurInfoR" M. Pirogovskaya str. 5 Moscow 119435 Russia

The paper considers methods to organize a network of links to parameterized data objects. A data object is an object identified by standard methods, including the network identifiers URI, URL and URN. The data objects can be either atomic or have a complex structure, including links to other objects, and this ensures the linking of objects into a network, which can be considered as an information graph. It turns out to be possible to formulate a number of criteria for supporting the integrity of such a structure; the paper proposes language tools to formulate such criteria. An essential feature of this network is the dependence of the objects’ information content on a number of parameters, first of all, on time. Depending on the parameter, the information content of the object can change both with the preservation of the integrity of the structure, and with its damage. The paper considers methods for a parameterized description of objects while maintaining integrity based on the formalism of category theory. The formalization used allows defining two relations between objects and their names (identifiers): access and links. The paper studies the basic properties of such relations and reveals the differences between them. Category theoretical means of describing objects require appropriate support tools for practical application. The paper proposes a configuration of support tools for a network of links to parameterized data objects based on a combination of conceptual modeling tools and applicative computing tools. The proposed tools provide basic methods of access to the network of information graphs. An essential feature of the proposed tools is the ability to determine the subjective way of considering the information graph (based on the category of correlations), as well as harmonizing an objective and subjective way of considering. The proposed tools were tested in the development of applied information systems in the field of implementation of the best availab

关键词： data objects object identification conceptual constructions informational graph semantics category theory model parametrization

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Graphical Framework for Categorizing data Capabilities and Properties of objects in the Internet of Things

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IEEE ACCESS 2020年 8卷 22366-22377页

作者： Eduardo Ibarra-Esquer, Jorge Fernando Gonzalez-Navarro, Felix Salvador Sanchez, J. Leticia Flores-Rios, Brenda Angelica Astorga-Vargas, Maria Luisa Gonzalez-Ramirez, Maria Univ Autonoma Baja California Fac Ingn Mexicali 21280 Baja California Mexico Univ Autonoma Baja California Inst Ingn Mexicali 21280 Baja California Mexico Univ Jaume 1 Dept Comp Languages & Syst Inst New Imaging Technol Castellon de La Plana 12071 Spain

Things are the core of the Internet of Things (IoT) and must be properly characterized according to the different functions they accomplish. Identifying their capabilities and combining them as sets provides a view on the single or joint properties of existing things and guide in properly designing and building new things while maximizing their potential benefits within an IoT system or application. Building on five essential but independent capabilities of things (Identification, Localization, Sensing, Actuation, and Processing), four categories or groups of things are defined. These groups comprise a particular view of the diversity of objects found in the IoT, as trackable, data, interactive, or smart objects. In this paper, a description of the aforementioned capabilities is presented, stating how each of the groups of objects includes them. Then, given that data are the most important assets for both organizations and individuals a further description of the data objects group is made, proposing a graphical categorization framework that thoroughly describes and measures the level in which each of these capabilities is contained and how it contributes to the performance and data properties of any data object.

关键词： data objects data properties Internet of Things things capabilities categorization framework

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The Construction of data Usability

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TECHNICAL COMMUNICATION QUARTERLY 2025年第2期34卷 199-217页

作者： Swarts, Jason North Carolina State Univ Raleigh NC USA

Technical communication aids in helping people envision the usability of technology. A similar need exists for constructing the usability of data sets, but the rhetorical work is less well documented. This article reports on how writers attribute meaning and usability to a geolocation data set and its derivative objects. This rhetorical work connects the data to existing and potential social realities, which provide a framework for thinking of that data set's usability.

关键词： data sets data objects user experience/usability/interaction design social construction

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STATE: A Clustering Algorithm Focusing on Edges Instead of Centers

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Chinese Journal of Electronics 2021年第5期30卷 902-908页

作者： ZHAO Boxiang WANG Shuliang LIU Chuanlu School of Computer Science and Technology Beijing Institute of Technology Institute of E-Government Beijing Institute of Technology

With the expansion of data scale and the increase in data complexity, it is particularly important to accurately identify clusters and efficiently save clustering results. To address this, we propose a novel clustering algorithm, Shape clustering based on data field(STATE),which can quickly identify clusters of arbitrary shapes and greatly reduce the storage space of clustering results in any datasets without reducing the accuracy. STATE mainly focuses on finding the edges of clusters and directions of edges instead of clustering centers through the data *** results of STATE are presented as the edges of clusters without data objects inside clusters and without *** experiments show that STATE can recognize complex data distribution in noisy environments without discrimination and greatly save the storage space of clustering results. When it is applied in a real-world scene,facial feature extraction, STATE can recognize eyes, nose,mouth, eyebrows and facial contours automatically without calibrating key features or training. Using the extracted facial features, we achieve facial recognition with high accuracy.

关键词： clustering algorithm focusing storage space data complexity data field complex data distribution data objects data scale pattern clustering Shape clustering edges instead face recognition feature extraction novel clustering algorithm

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Trusted Cloud Computing with Secure Resources and data Coloring

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IEEE INTERNET COMPUTING 2010年第5期14卷 14-22页

作者： Hwang, Kai Li, Deyi Univ So Calif Los Angeles CA 90089 USA Tsinghua Univ Beijing Peoples R China

Trust and security have prevented businesses from fully accepting cloud platforms. To protect clouds, providers must first secure virtualized data-center resources, uphold user privacy, and preserve data integrity. The authors suggest using a trust-overlay network over multiple data centers to implement a reputation system for establishing trust between service providers and data owners. data coloring and software watermarking techniques protect shared data objects and massively distributed software modules. These techniques safeguard multi-way authentications, enable single sign-on in the cloud, and tighten access control for sensitive data in both public and private clouds.

关键词： Internet clouds data centers data coloring network security reputation system software watermarking trust overlays Cloud Computing Trust Sensitive data data Quality data objects Secure single sign-on Color Network security CLOUDS Clouds Tightening data center

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ULTRASONIC REFLECTION MODE COMPUTED-TOMOGRAPHY THROUGH A SKULLBONE

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 1990年第11期37卷 1059-1066页

作者： YLITALO, J KOIVUKANGAS, J OKSMAN, J UNIV OULU DEPT ELECT ENGN SF-90570 OULU FINLAND OULU UNIV CENT HOSP DEPT NEUROSURG SF-90220 OULU FINLAND

An ultrasonic reflection-mode CT (computed tomography) method was applied to transskull imaging of the brain. The method involves only a single transducer and a single scan to acquire data from the object. In reconstruction an ordinary Fourier slice theorem is applied. The average velocity changes of ultrasound due to the skullbone can be compensated. In experiments the object immersed in water was scanned by a wide-angle transducer through the viewing angle of 360 degrees . When imaging through bone a simplified approach was used, in which a piece of skullbone (thickness 3-4 mm) was attached firmly to the transducer. For comparison, the same object was then imaged without the skullbone. A two-point resolution better than 3 mm was achieved for transskull imaging using 1 MHz ultrasound. The experiments with brain specimens show that transskull images compare well with the images of the same specimens obtained without the bone interference. The findings are clinically significant in terms of pediatric brain diagnosis and postoperative follow up. Based on the method, a clinical prototype imager is currently being developed especially for diagnosis of children's brain diseases.

关键词： Postoperative Period single scan Tomography Imaging Average speed X-Ray Computed Tomography Ultrasonic reflection Transducers piecing angle sensor Ultrasonic Waves data objects

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Co-arrays in the next Fortran Standard

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SCIENTIFIC PROGRAMMING 2007年第1期15卷 9-26页

作者： Reid, John Numrich, Robert W. Univ Minnesota Minnesota Supercomp Inst Minneapolis MN USA

The WG5 committee, at its meeting in Delft, May 2005, decided to include co-arrays in the next Fortran Standard. A Fortran program containing co-arrays is interpreted as if it were replicated a fixed number of times and all copies were executed asynchronously. Each copy has its own set of data objects and is called an image. The array syntax of Fortran is extended with additional trailing subscripts in square brackets to give a clear and straightforward representation of access to data on other images. References without square brackets are to local data, so code that can run independently is uncluttered. Any occurrence of square brackets is a warning about communication between images. The additional syntax requires support in the compiler, but it has been designed to be easy to implement and to give the compiler scope both to apply its optimizations within each image and to optimize the communication between images. The extension includes execution control statements for synchronizing images and intrinsic procedures to return the number of images, to return the index of the current image, and to perform collective operations. The paper does not attempt to describe the full details of the feature as it now appears in the draft of the new standard. Instead, we describe a subset and demonstrate the use of this subset with examples.

关键词： Subset Computer Programming Languages FORTRAN PROGRAMS Sketches syntax Current Pick Communication Research data objects compilers warning

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A Collision and Reaction Model of Feature Fusion: Mechanism and Realization

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IEEE INTELLIGENT SYSTEMS 2015年第5期30卷 56-65页

作者： Peng, Weimin Deng, Huifang S China Univ Technol Guangzhou Guangdong Peoples R China Hangzhou Dianzi Univ Hangzhou Zhejiang Peoples R China S China Univ Technol Sch Comp Sci & Engn Syst Simulat Lab Guangzhou Guangdong Peoples R China

Duplicate data must be properly handled in the process of intelligent search, surveillance, and tracking. To better detect and fuse this data, the authors take a new perspective on feature fusion based on the "collision and reaction"" mechanism of data objects. This mechanism can greatly facilitate differentiating duplicate and nonduplicate data in the fusion (reaction) probability. With this perspective, the fusion probability of a feature sample in a dataset is the cumulative effect of the microscopic collision (interaction) results between this sample and other samples. The operations on duplicate detection and feature fusion depend on the fusion probability and are finally realized when the collision process is finished. This new quantum-inspired feature fusion model gives interesting experimental results and could have great implications for some intelligent systems.

关键词： probability sensor fusion collision-and-reaction mechanism data duplication data objects feature fusion fusion probability microscopic collision quantum-inspired feature fusion model Feature extraction Integrated circuit modeling Intelligent systems Mathematical model Probability collision and reaction data fusion data representation duplicate detection feature fusion intelligent systems

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