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At least 217 records · Page 12Linked to original sources
arXiv2020

The anatomy of Reddit: An overview of academic research

Online forums provide rich environments where users may post questions and comments about different topics. Understanding how people behave in online forums may shed light on the fundamental mechanisms by which collective thinking emerges in a group of individuals, but it has also important practical applications, for instance to improve user experience, increase engagement or automatically identify bullying. Importantly, the datasets generated by the activity of the users are often openly available for researchers, in contrast to other sources of data in computational social science. In this survey, we map the main research directions that arose in recent years and focus primarily on the most popular platform, Reddit. We distinguish and categorise research depending on their focus on the posts or on the users, and point to different types of methodologies to extract information from the structure and dynamics of the system. We emphasize the diversity and richness of the research in terms of questions and methods, and suggest future avenues of research.

cs.SI↗
arXiv2005

A note on comparison of scientific impact expressed by the number of citations in different fields of science

Citation distributions for 1992, 1994, 1996, 1997, 1999, and 2001, which were published in the 2004 report of the National Science Foundation, USA, are analyzed. It is shown that the ratio of the total number of citations of any two broad fields of science remains close to constant over the analyzed years. Based on this observation, normalization of total numbers of citations with respect to the number of citations in mathematics is suggested as a tool for comparing scientific impact expressed by the number of citations in different fields of science.

math.ST↗
arXiv2010

Making Sense of the Evolution of a Scientific Domain: A Visual Analytic Study of the Sloan Digital Sky Survey Research

We introduce a new visual analytic approach to the study of scientific discoveries and knowledge diffusion. Our approach enhances contemporary co-citation network analysis by enabling analysts to identify co-citation clusters of cited references intuitively, synthesize thematic contexts in which these clusters are cited, and trace how research focus evolves over time. The new approach integrates and streamlines a few previously isolated techniques such as spectral clustering and feature selection algorithms. The integrative procedure is expected to empower and strengthen analytical and sense making capabilities of scientists, learners, and researchers to understand the dynamics of the evolution of scientific domains in a wide range of scientific fields, science studies, and science policy evaluation and planning. We demonstrate the potential of our approach through a visual analysis of the evolution of astronomical research associated with the Sloan Digital Sky Survey (SDSS) using bibliographic data between 1994 and 2008. In addition, we also demonstrate that the approach can be consistently applied to a set of heterogeneous data sources such as e-prints on arXiv, publications on ADS, and NSF awards related to the same topic of SDSS.

cs.GL↗
arXiv2022

Epistemological Equation for Analysing Uncontrollable States in Complex Systems: Quantifying Cyber Risks from the Internet of Things

To enable quantitative risk assessment of uncontrollable risk states in complex and coupled IoT systems, a new epistemological equation is designed and tested though comparative and empirical analysis. The comparative analysis is conducted on national digital strategies, followed by an empirical analysis of cyber risk assessment approaches. The new epistemological analysis approach enables the assessment of uncontrollable risk states in complex IoT systems, which begin to resemble artificial intelligence, and can be used for a quantitative self-assessment of IoT cyber risk posture.

cs.CY↗
arXiv2019

Towards a Science of Mind

The ancient mind/body problem continues to be one of deepest mysteries of science and of the human spirit. Despite major advances in many fields, there is still no plausible link between subjective experience (qualia) and its realization in the body. This paper outlines some of the elements of a rigorous science of mind (SoM) - key ideas include scientific realism of mind, agnostic mysterianism, careful attention to language, and a focus on concrete (touchstone) questions and results. A core suggestion is to focus effort on the (still mysterious) mapping from neural activity to subjective experience.

cs.GL↗
arXiv2013

Grasping Complexity

The century of complexity has come. The face of science has changed. Surprisingly, when we start asking about the essence of these changes and then critically analyse the answers, the result are mostly discouraging. Most of the answers are related to the properties that have been in the focus of scientific research already for more than a century (like non-linearity). This paper is Preface to the special issue "Grasping Complexity" of the journal "Computers and Mathematics with Applications". We analyse the change of era in science, its reasons and main changes in scientific activity and give a brief review of the papers in the issue.

cs.GL↗
arXiv2026

A realist theory of digital objects, digital systems, and digitalized systems

As human reliance on information technology (IT) increases, having a clear, precise, and comprehensive understanding of the nature of digital objects, digital systems, and digitalized systems becomes more critical. Otherwise, our ability to research, manage, control, and make reliable predictions about them will be limited. Accordingly, in this paper, we propose a new theory of digital objects, digital systems, and digitalized systems based on the adoption, adaptation, and extension of existing theories of ontology, semantics, and semiotics. The theory provides precise explanations of the nature of digital objects, digital systems, and digitalized systems. Ours is a realist theory that does not countenance the independent existence of nonmaterial or hybrid objects in the world. Accordingly, we are at odds with much of the prevailing discourse about digital phenomena. We show how our theory generates different insights and predictions from this the dominant discourse on the nature of the digital. Our predictions lay the groundwork for further empirical studies on the design, use, and impact of IT on individuals, organizations, and society.

cs.CY↗
arXiv2018

Opening the black box of energy modelling: Strategies and lessons learned

The global energy system is undergoing a major transition, and in energy planning and decision-making across governments, industry and academia, models play a crucial role. Because of their policy relevance and contested nature, the transparency and open availability of energy models and data are of particular importance. Here we provide a practical how-to guide based on the collective experience of members of the Open Energy Modelling Initiative (Openmod). We discuss key steps to consider when opening code and data, including determining intellectual property ownership, choosing a licence and appropriate modelling languages, distributing code and data, and providing support and building communities. After illustrating these decisions with examples and lessons learned from the community, we conclude that even though individual researchers' choices are important, institutional changes are still also necessary for more openness and transparency in energy research.

cs.CY↗
arXiv2019

Synergizing Roadway Infrastructure Investment with Digital Infrastructure for Infrastructure-Based Connected Vehicle Applications: Review of Current Status and Future Directions

The safety, mobility, environmental, energy, and economic benefits of transportation systems, which are the focus of recent connected vehicle (CV) programs, are potentially dramatic. However, realization of these benefits largely hinges on the timely integration of digital technology into upcoming as well as existing transportation infrastructure. CVs must be enabled to broadcast and receive data to and from other CVs [vehicle-to-vehicle (V2V) communication], to and from infrastructure [vehicle-to-infrastructure (V2I) communication], and to and from other road users, such as bicyclists or pedestrians (vehicle-to-other road users communication). Further, the infrastructure and transportation agencies that manage V2I-focused applications must be able to collect, process, distribute, and archive these data quickly, reliably, and securely. This paper focuses on V2I applications and investigates current digital roadway infrastructure initiatives. It highlights the importance of including digital infrastructure investment alongside investment in more traditional transportation infrastructure to keep up with the auto industry push toward increasing intervehicular communication. By studying current CV testbeds and smart-city initiatives, this paper identifies digital infrastructure being used by public agencies. It also examines public agencies limited budgeting for digital infrastructure and finds that current expenditure is inadequate for realizing the potential benefits of V2I applications. Finally, the paper presents a set of recommendations, based on a review of current practices and future needs, designed to guide agencies responsible for transportation infrastructure. It stresses the importance of collaboration for establishing national and international platforms for the planning, deployment, and management of digital infrastructure to support connected transportation systems.

cs.CY↗
arXiv2019

Brief Notes and History Computing in Mexico during 50 years

The history of computing in Mexico can not be thought without the name of Prof. Harold V. McIntosh (1929-2015). For almost 50 years, in Mexico he contributed to the development of computer science with wide international recognition. Approximately in 1964, McIntosh began working in the Physics Department of the Advanced Studies Center (CIEA) of the National Polytechnic Institute (IPN), now called CINVESTAV. In 1965, at the National Center of Calculus (CeNaC), he was a founding member of the Master in Computing, first in Latin America. With the support of Mario Baez Camargo and Enrique Melrose, McIntosh continues his research of Martin-Baltimore Computer Center and University of Florida at IBM 709.

cs.GL↗
arXiv2006

Optimal Traffic Networks

Inspired by studies on the airports' network and the physical Internet, we propose a general model of weighted networks via an optimization principle. The topology of the optimal network turns out to be a spanning tree that minimizes a combination of topological and metric quantities. It is characterized by a strongly heterogeneous traffic, non-trivial correlations between distance and traffic and a broadly distributed centrality. A clear spatial hierarchical organization, with local hubs distributing traffic in smaller regions, emerges as a result of the optimization. Varying the parameters of the cost function, different classes of trees are recovered, including in particular the minimum spanning tree and the shortest path tree. These results suggest that a variational approach represents an alternative and possibly very meaningful path to the study of the structure of complex weighted networks.

physics.soc-ph↗
arXiv2020

Achieving a quantum smart workforce

Interest in building dedicated Quantum Information Science and Engineering (QISE) education programs has greatly expanded in recent years. These programs are inherently convergent, complex, often resource intensive and likely require collaboration with a broad variety of stakeholders. In order to address this combination of challenges, we have captured ideas from many members in the community. This manuscript not only addresses policy makers and funding agencies (both public and private and from the regional to the international level) but also contains needs identified by industry leaders and discusses the difficulties inherent in creating an inclusive QISE curriculum. We report on the status of eighteen post-secondary education programs in QISE and provide guidance for building new programs. Lastly, we encourage the development of a comprehensive strategic plan for quantum education and workforce development as a means to make the most of the ongoing substantial investments being made in QISE.

physics.ed-ph↗
arXiv2012

Mathematicians take a stand

We survey the reasons for the ongoing boycott of the publisher Elsevier. We examine Elsevier's pricing and bundling policies, restrictions on dissemination by authors, and lapses in ethics and peer review, and we conclude with thoughts about the future of mathematical publishing.

math.HO↗
arXiv2018

Michael John Caldwell Gordon (FRS 1994), 28 February 1948 -- 22 August 2017

Michael Gordon was a pioneer in the field of interactive theorem proving and hardware verification. In the 1970s, he had the vision of formally verifying system designs, proving their correctness using mathematics and logic. He demonstrated his ideas on real-world computer designs. His students extended the work to such diverse areas as the verification of floating-point algorithms, the verification of probabilistic algorithms and the verified translation of source code to correct machine code. He was elected to the Royal Society in 1994, and he continued to produce outstanding research until retirement. His achievements include his work at Edinburgh University helping to create Edinburgh LCF, the first interactive theorem prover of its kind, and the ML family of functional programming languages. He adopted higher-order logic as a general formalism for verification, showing that it could specify hardware designs from the gate level right up to the processor level. It turned out to be an ideal formalism for many problems in computer science and mathematics. His tools and techniques have exerted a huge influence across the field of formal verification.

cs.GL↗
arXiv2018

Big Data: the End of the Scientific Method?

We argue that the boldest claims of Big Data are in need of revision and toning-down, in view of a few basic lessons learned from the science of complex systems. We point out that, once the most extravagant claims of Big Data are properly discarded, a synergistic merging of BD with big theory offers considerable potential to spawn a new scientific paradigm capable of overcoming some of the major barriers confronted by the modern scientific method originating with Galileo. These obstacles are due to the presence of nonlinearity, nonlocality and hyperdimensions which one encounters frequently in multiscale modelling.

cs.GL↗
arXiv2003

Signatures of small-world and scale-free properties in large computer programs

A large computer program is typically divided into many hundreds or even thousands of smaller units, whose logical connections define a network in a natural way. This network reflects the internal structure of the program, and defines the ``information flow'' within the program. We show that, (1) due to its growth in time this network displays a scale-free feature in that the probability of the number of links at a node obeys a power-law distribution, and (2) as a result of performance optimization of the program the network has a small-world structure. We believe that these features are generic for large computer programs. Our work extends the previous studies on growing networks, which have mostly been for physical networks, to the domain of computer software.

cond-mat.dis-nn↗
arXiv2023

AI-enabled Sound Pattern Recognition on Asthma Medication Adherence: Evaluation with the RDA Benchmark Suite

Asthma is a common, usually long-term respiratory disease with negative impact on global society and economy. Treatment involves using medical devices (inhalers) that distribute medication to the airways and its efficiency depends on the precision of the inhalation technique. There is a clinical need for objective methods to assess the inhalation technique, during clinical consultation. Integrated health monitoring systems, equipped with sensors, enable the recognition of drug actuation, embedded with sound signal detection, analysis and identification, from intelligent structures, that could provide powerful tools for reliable content management. Health monitoring systems equipped with sensors, embedded with sound signal detection, enable the recognition of drug actuation and could be used for effective audio content analysis. This paper revisits sound pattern recognition with machine learning techniques for asthma medication adherence assessment and presents the Respiratory and Drug Actuation (RDA) Suite (https://gitlab.com/vvr/monitoring-medication-adherence/rda-benchmark) for benchmarking and further research. The RDA Suite includes a set of tools for audio processing, feature extraction and classification procedures and is provided along with a dataset, consisting of respiratory and drug actuation sounds. The classification models in RDA are implemented based on conventional and advanced machine learning and deep networks' architectures. This study provides a comparative evaluation of the implemented approaches, examines potential improvements and discusses on challenges and future tendencies.

cs.SD↗