Relevant bibliographies by topics / New tools for network analysis

Academic literature on the topic 'New tools for network analysis'

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Published: 14 March 2023

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Journal articles on the topic "New tools for network analysis"

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Scardoni, Giovanni, Gabriele Tosadori, Mohammed Faizan, Fausto Spoto, Franco Fabbri, and Carlo Laudanna. "Biological network analysis with CentiScaPe: centralities and experimental dataset integration." F1000Research 3 (July 1, 2014): 139. http://dx.doi.org/10.12688/f1000research.4477.1.

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The growing dimension and complexity of available experimental data generating biological networks has increased the need for tools allowing to categorize nodes by their topological relevance in biological networks. Here we present CentiScaPe, a Cytoscape app specifically designed to calculate centrality indexes for the identification of the most important nodes of a network. CentiScaPe is a comprehensive suite of algorithms dedicated to network nodes centrality analysis, computing several centralities for undirected, directed and weighted networks. The results of the topological analysis can be also integrated with data sets from lab experiments, such as expression or phosphorylation levels of the proteins represented in the network, using the graphical features of the tool. This opens a new perspective in the analysis of biological networks, since integration of topological analysis with lab experimental data can increase the predictive power of a bioinformatical analysis.
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Kryukov, Ya V., D. A. Pokamestov, E. V. Rogozhnikov, S. A. Novichkov, and D. V. Lakontsev. "Analysis of Computational Complexity and Processing Time Evaluation of the Protocol Stack in 5G New Radio." Proceedings of Tomsk State University of Control Systems and Radioelectronics 23, no. 3 (September 25, 2020): 31–37. http://dx.doi.org/10.21293/1818-0442-2020-23-3-31-37.

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Currently, an active deployment of radio access networks for mobile communication systems 5G New Radio is being observed. The architecture of networks is developing rapidly, where significant part of the functions is performed in a virtual cloud space of a personal computer. The computing power of a personal computer must be sufficient to execute network protocols in real time. To reduce the cost of deploying 5G NR networks, the configuration of each remote computer must be optimally matched to the scale of a particular network. Therefore, an urgent direction of research is the assessment of the execution time of the 5G NR protocol stack on various configurations of computers and the development of a mathematical model for data analysis, approximation of dependencies and making recommendations. In this paper, the authors provide an overview of the main 5G NR network architectures, as well as a description of the methods and tools that can be used to estimate the computational complexity of the 5G NR protocol stack. The final section provides an analysis of the computational complexity of the protocol stack, obtained during the experiments by colleagues in partner institutions.
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Arefeen, Ashraful, Xinshu Xiao, and Tao Jiang. "DeepPASTA: deep neural network based polyadenylation site analysis." Bioinformatics 35, no. 22 (April 25, 2019): 4577–85. http://dx.doi.org/10.1093/bioinformatics/btz283.

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Abstract Motivation Alternative polyadenylation (polyA) sites near the 3′ end of a pre-mRNA create multiple mRNA transcripts with different 3′ untranslated regions (3′ UTRs). The sequence elements of a 3′ UTR are essential for many biological activities such as mRNA stability, sub-cellular localization, protein translation, protein binding and translation efficiency. Moreover, numerous studies in the literature have reported the correlation between diseases and the shortening (or lengthening) of 3′ UTRs. As alternative polyA sites are common in mammalian genes, several machine learning tools have been published for predicting polyA sites from sequence data. These tools either consider limited sequence features or use relatively old algorithms for polyA site prediction. Moreover, none of the previous tools consider RNA secondary structures as a feature to predict polyA sites. Results In this paper, we propose a new deep learning model, called DeepPASTA, for predicting polyA sites from both sequence and RNA secondary structure data. The model is then extended to predict tissue-specific polyA sites. Moreover, the tool can predict the most dominant (i.e. frequently used) polyA site of a gene in a specific tissue and relative dominance when two polyA sites of the same gene are given. Our extensive experiments demonstrate that DeepPASTA signisficantly outperforms the existing tools for polyA site prediction and tissue-specific relative and absolute dominant polyA site prediction. Availability and implementation https://github.com/arefeen/DeepPASTA Supplementary information Supplementary data are available at Bioinformatics online.
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Nocke, T., S. Buschmann, J. F. Donges, N. Marwan, H. J. Schulz, and C. Tominski. "Review: visual analytics of climate networks." Nonlinear Processes in Geophysics 22, no. 5 (September 23, 2015): 545–70. http://dx.doi.org/10.5194/npg-22-545-2015.

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Abstract. Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.
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Nocke, T., S. Buschmann, J. F. Donges, N. Marwan, H. J. Schulz, and C. Tominski. "Review: visual analytics of climate networks." Nonlinear Processes in Geophysics Discussions 2, no. 2 (April 30, 2015): 709–80. http://dx.doi.org/10.5194/npgd-2-709-2015.

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Abstract. Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.
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Hafner-Burton, Emilie M., Miles Kahler, and Alexander H. Montgomery. "Network Analysis for International Relations." International Organization 63, no. 3 (July 2009): 559–92. http://dx.doi.org/10.1017/s0020818309090195.

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International relations research has regarded networks as a particular mode of organization, distinguished from markets or state hierarchies. In contrast, network analysis permits the investigation and measurement of network structures—emergent properties of persistent patterns of relations among agents that can define, enable, and constrain those agents. Network analysis offers both a toolkit for identifying and measuring the structural properties of networks and a set of theories, typically drawn from contexts outside international relations, that relate structures to outcomes. Network analysis challenges conventional views of power in international relations by defining network power in three different ways: access, brokerage, and exit options. Two issues are particularly important to international relations: the ability of actors to increase their power by enhancing and exploiting their network positions, and the fungibility of network power. The value of network analysis in international relations has been demonstrated in precise description of international networks, investigation of network effects on key international outcomes, testing of existing network theory in the context of international relations, and development of new sources of data. Partial or faulty incorporation of network analysis, however, risks trivial conclusions, unproven assertions, and measures without meaning. A three-part agenda is proposed for future application of network analysis to international relations: import the toolkit to deepen research on international networks; test existing network theories in the domain of international relations; and test international relations theories using the tools of network analysis.
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Goay, Chan Hong, Azniza Abd Aziz, Nur Syazreen Ahmad, and Patrick Goh. "Progress in neural network based techniques for signal integrity analysis–a survey." Bulletin of Electrical Engineering and Informatics 8, no. 1 (March 1, 2019): 276–82. http://dx.doi.org/10.11591/eei.v8i1.1405.

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With the increase in data rates, signal integrity analysis has become more time and memory intensive. Simulation tools such as 3D electromagnetic field solvers can be accurate but slow, whereas faster models such as design equations and equivalent circuit models lack accuracy. Artificial neural networks (ANNs) have recently gained popularity in the RF and microwave circuit modeling community as a new modeling tool. This has in turn spurred progress towards applications of neural networks in signal integrity. A neural network can learn from a set of data generated during the design process. It can then be used as a fast and accurate modeling tool to replace conventional approaches. This paper reviews the recent advancement of neural networks in the area of signal integrity modeling. Key advancements are considered, particularly those that assist the ability of the neural network to cope with an increasing number of inputs and handle large amounts of data.
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Boeing, Geoff. "Street Network Models and Measures for Every U.S. City, County, Urbanized Area, Census Tract, and Zillow-Defined Neighborhood." Urban Science 3, no. 1 (March 1, 2019): 28. http://dx.doi.org/10.3390/urbansci3010028.

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OpenStreetMap provides a valuable crowd-sourced database of raw geospatial data for constructing models of urban street networks for scientific analysis. This paper reports results from a research project that collected raw street network data from OpenStreetMap using the Python-based OSMnx software for every U.S. city and town, county, urbanized area, census tract, and Zillow-defined neighborhood. It constructed nonplanar directed multigraphs for each and analyzed their structural and morphological characteristics. The resulting data repository contains over 110,000 processed, cleaned street network graphs (which in turn comprise over 55 million nodes and over 137 million edges) at various scales—comprehensively covering the entire U.S.—archived as reusable open-source GraphML files, node/edge lists, and GIS shapefiles that can be immediately loaded and analyzed in standard tools such as ArcGIS, QGIS, NetworkX, graph-tool, igraph, or Gephi. The repository also contains measures of each network’s metric and topological characteristics common in urban design, transportation planning, civil engineering, and network science. No other such dataset exists. These data offer researchers and practitioners a new ability to quickly and easily conduct graph-theoretic circulation network analysis anywhere in the U.S. using standard, free, open-source tools.
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Zanin, Massimiliano, Miguel Romance, Santiago Moral, and Regino Criado. "Credit Card Fraud Detection through Parenclitic Network Analysis." Complexity 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/5764370.

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The detection of frauds in credit card transactions is a major topic in financial research, of profound economic implications. While this has hitherto been tackled through data analysis techniques, the resemblances between this and other problems, like the design of recommendation systems and of diagnostic/prognostic medical tools, suggest that a complex network approach may yield important benefits. In this paper we present a first hybrid data mining/complex network classification algorithm, able to detect illegal instances in a real card transaction data set. It is based on a recently proposed network reconstruction algorithm that allows creating representations of the deviation of one instance from a reference group. We show how the inclusion of features extracted from the network data representation improves the score obtained by a standard, neural network-based classification algorithm and additionally how this combined approach can outperform a commercial fraud detection system in specific operation niches. Beyond these specific results, this contribution represents a new example on how complex networks and data mining can be integrated as complementary tools, with the former providing a view to data beyond the capabilities of the latter.
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McDaid, Alexander, Eoghan Furey, and Kevin Curran. "Wireless Interference Analysis for Home IoT Security Vulnerability Detection." International Journal of Wireless Networks and Broadband Technologies 10, no. 2 (July 2021): 55–77. http://dx.doi.org/10.4018/ijwnbt.2021070104.

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The integrity of wireless networks that make up the clear majority of IoT networks lack the inherent security of their wired counterparts. With the growth of the internet of things (IoT) and its pervasive nature in the modern home environment, it has caused a spike in security concerns over how the network infrastructure handles, transmits, and stores data. New wireless attacks such as KeySniffer and other attacks of this type cannot be tracked by traditional solutions. Therefore, this study investigates if wireless spectrum frequency monitoring using interference analysis tools can aid in the monitoring of device signals within a home IoT network. This could be used enhance the security compliance guidelines set forth by OWASP and NIST for these network types and the devices associated. Active and passive network scanning tools are used to provide analysis of device vulnerability and as comparison for device discovery purposes. The work shows the advantages and disadvantages of this signal pattern testing technique compared to traditional network scanning methods. The authors demonstrate how RF spectrum analysis is an effective way of monitoring network traffic over the air waves but also possesses limitations in that knowledge is needed to decipher these patterns. This article demonstrates alternative methods of interference analysis detection.
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Dissertations / Theses on the topic "New tools for network analysis"

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Larhlimi, Abdelhalim [Verfasser]. "New concepts and tools in constraint-based analysis of metabolic networks / Abdelhalim Larhlimi." Berlin : Freie Universität Berlin, 2009. http://d-nb.info/1023579944/34.

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Trier, Matthias. "Towards a Social Network Intelligence Tool for visual Analysis of Virtual Communication Networks." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-140161.

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Communities of Practice regularly utilize virtual means of communication. The according software support provides its members with many sophisticated features for generating content and for communicating with each other via the internet or intranet. However, functionalities to monitor, assess, coordinate, and communicate the quality and development of the underlying electronic networks of experts are frequently missing. To meet this need of increased manageability, this contribution introduces a Social Network Intelligence software approach which aims at supporting the comprehension of the structure and value of electronic communities by automatically extracting and mining available electronic data of various types of virtual communication networks, like e-mail archives, discussion groups, or instant messaging communication. Experimental structural visualizations employing Social Network Analysis methods are combined with Keyword Extraction to move towards a Social Network Intelligence approach which generates transparency of complex virtual communication networks. Together with a comprehensive visualization method, an approach for software-supported communication network measurement and evaluation is suggested. It supports the identification of important participants, topics, or clusters in the network, evaluates the interpersonal communication structure and visually traces the evolvement of the knowledge exchange over time.
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Trier, Matthias. "Towards a Social Network Intelligence Tool for visual Analysis of Virtual Communication Networks." Technische Universität Dresden, 2006. https://tud.qucosa.de/id/qucosa%3A27871.

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Communities of Practice regularly utilize virtual means of communication. The according software support provides its members with many sophisticated features for generating content and for communicating with each other via the internet or intranet. However, functionalities to monitor, assess, coordinate, and communicate the quality and development of the underlying electronic networks of experts are frequently missing. To meet this need of increased manageability, this contribution introduces a Social Network Intelligence software approach which aims at supporting the comprehension of the structure and value of electronic communities by automatically extracting and mining available electronic data of various types of virtual communication networks, like e-mail archives, discussion groups, or instant messaging communication. Experimental structural visualizations employing Social Network Analysis methods are combined with Keyword Extraction to move towards a Social Network Intelligence approach which generates transparency of complex virtual communication networks. Together with a comprehensive visualization method, an approach for software-supported communication network measurement and evaluation is suggested. It supports the identification of important participants, topics, or clusters in the network, evaluates the interpersonal communication structure and visually traces the evolvement of the knowledge exchange over time.
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Subagadis, Yohannes Hagos. "A new integrated modeling approach to support management decisions of water resources systems under multiple uncertainties." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-189212.

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The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational framework. Such integrative research to link different knowledge domains faces several practical challenges. The complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. This thesis aims to overcome some of these challenges, and to demonstrate how new modeling approaches can provide successful integrative water resources research. It focuses on the development of new integrated modeling approaches which allow integration of not only physical processes but also socio-economic and environmental issues and uncertainties inherent in water resources systems. To achieve this goal, two new approaches are developed in this thesis. At first, a Bayesian network (BN)-based decision support tool is developed to conceptualize hydrological and socio-economic interaction for supporting management decisions of coupled groundwater-agricultural systems. The method demonstrates the value of combining different commonly used integrated modeling approaches. Coupled component models are applied to simulate the nonlinearity and feedbacks of strongly interacting groundwater-agricultural hydrosystems. Afterwards, a BN is used to integrate the coupled component model results with empirical knowledge and stakeholder inputs. In the second part of this thesis, a fuzzy-stochastic multiple criteria decision analysis tool is developed to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrates physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approaches are applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structures. The results show the effectiveness of the proposed methods. The first method can aid in the impact assessment of alternative management interventions on sustainability of aquifer systems while accounting for economic (agriculture) and societal interests (employment in agricultural sector) in the study area. Results from the second method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach suits to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. The new approaches can be applied to address the complexities and uncertainties inherent in water resource systems to support management decisions, while serving as a platform for stakeholder participation.
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MAZZA, ANDREA. "Innovative Approaches for Optimization of the Distribution System Operation." Doctoral thesis, Politecnico di Torino, 2015. http://hdl.handle.net/11583/2596760.

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The present work of thesis presents some innovative approaches aiming at analyzing and optimizing the distribution system. In the first part (composed of the Chapters 1–4), some innovative methods developed for distribution network reconfiguration, both in single objective framework and in multi- objective framework, are presented and applied. In particular, Chapter 1 shows the general problem of distribution network reconfigu- ration, while Chapter 2 presents the different types of Optimization Methods (OM), by focusing on their nature (deterministic or heuristic) and on the goal they have (single or multi-objective optimization). Chapter 3 introduces the decision-making methods, which have been used for the multi- objective optimization problems (whose application examples are reported in Chapter 5). Chapter 4 reports some innovative approach in the single objective optimization, by analyzing the possibility to apply intraday reconfiguration, by considering the cost of this operation with respect to the initial solution in which the actual configuration is maintained without any change. Chapter 6 presents some tools developed within the European Project SiNGULAR as functions of the main tool DERMAT, aiming at handling the different input data pattern, the correlation among loads and generators, as well as the presence of correlated harmonic sources in the network. Finally, in Appendix A the networks used during the doctoral work are shown, while Appendix B presents an overview of the general aspects and characteristics of the probability-based methods.
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Burns, Zackory T. "Quantifying the sociality of wild tool-using New Caledonian crows through an animal-borne technology." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:16db8026-53e4-4fb0-aa69-80d7cc34e183.

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New Caledonian crows (NC crows; Corvus moneduloides) are the most prolific avian tool-users and crafters, using up to three unique tool types derived from numerous plant materials. Since the discovery that wild populations of NC crows use and manufacture different tools in different locations with no measured environmental correlates to these distributions, the process by which NC crows acquire their tool-oriented behavior has been investigated. Two major findings were discovered in 2005: NC crows have a genetic predisposition to manipulate stick like objects, and they increase their rate of manipulation when exposed to social influences. Since then, much of the research into the sociality of wild NC crows has focused on direct social influences, especially the parent-juvenile relationship, yet no social network of wild NC crows has been described. In my thesis, I characterized a new proximity-logging device, Encounternet, and outline a four-step plan to assess error in animal borne devices; uncovered drivers, such as relatedness, space-use, and environmental factors, of wild NC crow sociality, and experimentally manipulated the social network, revealing immediate changes to the number of day-time and roosting partners, the breakdown of first-order relatedness driving sociality, and an increase in the amount of time NC crows associate; and revealed an indirect pathway via tools left behind by conspecifics allowing for the transmission of tool-properties between unrelated NC crows. Altogether, I furthered our understanding of wild NC crow sociality through the use of an animal-borne device, experimental manipulation in the wild measuring the response of the NC crow social network, and demonstrated the utility of animal-borne devices in mapping the network of a population of wild birds.
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Power, Jane Elizabeth. "New NMR tools for impurity analysis." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/new-nmr-tools-for-impurity-analysis(f6814907-cb3b-4c67-9702-dda58fbc726c).html.

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New NMR Tools for Impurity Analysis was written by Jane Power and submitted for the degree of Doctor of Philosophy in the Faculty of Engineering and Physical Sciences at the University of Manchester, on 31st March 2016.NMR spectroscopy is rich in structural information and is a widely used technique for structure elucidation and characterization of organic molecules; however, for impurity analysis it is not generally the tool of choice. While 1H NMR is quite sensitive, due to its narrow chemical shift range (0 - 10 ppm) and the high abundance of hydrogen atoms in most drugs, its resolution is often poor, with much signal overlap. Therefore, impurity signals, especially for chemically cognate species, are frequently obscured. 19F NMR on the other hand offers extremely high resolution for pharmaceutical applications. It exhibits far wider chemical shift ranges (± 300 ppm) than 1H NMR, and typical fluorinated drugs, of which there are many on the market, have only one or two fluorine atoms. In view of this, 19F NMR is being considered as an alternative for low-level impurity analysis and quantification, using a chosen example drug, rosuvastatin. Before 19F NMR can be effectively used for such analysis, the significant technical problem of pulse imperfections, such as sensitivity to B1 inhomogeneity and resonance-offset effects, has to be overcome. At present, due to the limited power of the radiofrequency amplifiers, only a fraction of the very wide frequency ranges encountered with nuclei such as fluorine can be excited uniformly at any one time. In this thesis, some of the limitations imposed by pulse imperfections are addressed and overcome. Two new pulse sequences are developed and presented, CHORUS and CHORUS Oneshot, which use tailored, ultra-broadband swept-frequency chirp pulses to achieve uniform constant amplitude and constant phase excitation and refocusing over very wide bandwidths (approximately 250 kHz), with no undue B1 sensitivity and no significant loss in sensitivity. CHORUS, for use in quantitative NMR, is demonstrated to give accuracies better than 0.1%. CHORUS Oneshot, a diffusion-ordered spectroscopic technique, exploits the exquisite sensitivity of the 19F chemical shift to its local environment, giving excellent resolution, which allows for accurate discrimination between diffusion coefficients with high dynamic range and over very wide bandwidths. Sulfur hexafluoride (SF6) is investigated and shown to be a suitable reference material for use in 19F NMR. The bandshape of the fluorine signal and its satellites is simple, without complex splitting patterns, and therefore good for reference deconvolution; in addition, it is sufficiently soluble in the solvent of choice, DMSO-d6.To demonstrate the functionality of the CHORUS sequences for low-level impurity analysis, 470 MHz 1H decoupled 19F spectra were acquired on a 500 MHz Bruker system, using a degraded sample of rosuvastatin, to reveal two low-level impurities. Using a standard Varian probe with a single high frequency channel, simultaneous 1H irradiation and 19F acquisition was made possible by time-sharing. Simultaneous 19F{1H} and 19F{13C} double decoupling was then performed using degraded and fresh samples of rosuvastatin, to reveal three low-level impurities (in the degraded sample) and low-level 1H and 13C modulation artefacts.
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Wong, David H. (David Hsing-Wang) 1976. "Finite state analysis with tools for network protocols." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80577.

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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
Includes bibliographical references (p. 147).
by David H. Wong.
S.B.and M.Eng.
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Gleeson, P. J. "New tools and specification languages for biophysically detailed neuronal network modelling." Thesis, University College London (University of London), 2012. http://discovery.ucl.ac.uk/1347263/.

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Increasingly detailed data are being gathered on the molecular, electrical and anatomical properties of neuronal systems both in vitro and in vivo. These range from the kinetic properties and distribution of ion channels, synaptic plasticity mechanisms, electrical activity in neurons, and detailed anatomical connectivity within neuronal microcircuits from connectomics data. Publications describing these experimental results often set them in the context of higher level network behaviour. Biophysically detailed computational modelling provides a framework for consolidating these data, for quantifying the assumptions about underlying biological mechanisms, and for ensuring consistency in the explanation of the phenomena across scales. Such multiscale biophysically detailed models are not currently in wide- spread use by the experimental neuroscience community however. Reasons for this include the relative inaccessibility of software for creating these models, the range of specialised scripting languages used by the available simulators, and the difficulty in creating and managing large scale network simulations. This thesis describes new solutions to facilitate the creation, simulation, analysis and reuse of biophysically detailed neuronal models. The graphical application neuroConstruct allows detailed cell and network models to be built in 3D, and run on multiple simulation platforms without detailed programming knowledge. NeuroML is a simulator independent language for describing models containing detailed neuronal morphologies, ion channels, synapses, and 3D network connectivity. New solutions have also been developed for creating and analysing network models at much closer to biological scale on high performance computing platforms. A number of detailed neocortical, cerebellar and hippocampal models have been converted for use with these tools. The tools and models I have developed have already started to be used for original scientific research. It is hoped that this work will lead to a more solid foundation for creating, validating, simulating and sharing ever more realistic models of neurons and networks.
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Banerji, C. "Network theoretic tools in the analysis of complex diseases." Thesis, University College London (University of London), 2015. http://discovery.ucl.ac.uk/1470036/.

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In this thesis we consider the application of network theoretic tools in the analysis of genome wide gene-expression data describing complex diseases, displaying defects in differentiation. After considering the literature, we motivate the construction of entropy based network rewiring methodologies, postulating that such an approach may provide a systems level correlate of the differentiation potential of a cellular sample, and may prove informative in the analysis of pathology. We construct, analytically investigate and validate three such network theoretic tools: Network Transfer Entropy, Signalling Entropy and Interactome Sparsification and Rewiring (InSpiRe). By considering over 1000 genome wide gene expression samples corresponding to healthy cells at different levels of differentiation, we demonstrate that signalling entropy is a strong correlate of cell potency confirming our initial postulate. The remainder of the thesis applies our network theoretic tools to two ends of the developmental pathology spectrum. Firstly we consider cancer, in which the power of cell differentiation is hijacked, to develop a malicious new tissue. Secondly, we consider muscular dystrophy, in which cell differentiation is inhibited, resulting in the poor development of muscle tissue. In the case of cancer we demonstrate that signalling entropy is a measure of tumour anaplasia and intra-tumour heterogeneity, which displays distinct values in different cancer subtypes. Moreover, we find signalling entropy to be a powerful prognostic indicator in epithelial cancer, outperforming conventional gene expression based assays. In the case of muscular dystrophy we focus on the most prevalent: facioscapulohumeral muscular dystrophy (FSHD). We demonstrate that muscle differentiation is perturbed in FSHD and that signalling entropy is elevated in myoblasts over-expressing the primary FSHD candidate gene DUX4. We subsequently utilise InSpiRe, performing a meta-analysis of FSHD muscle biopsy gene-expression data, uncovering a network of DUX4 driven rewired interactions in the pathology, and a novel therapeutic target which we validate experimentally.
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Books on the topic "New tools for network analysis"

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Abraham, Ajith, and Aboul Ella Hassanien. Computational social network analysis: Trends, tools and research advances. Dordrecht: Springer, 2010.

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Wehrle, Klaus. Modeling and Tools for Network Simulation. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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Ma'ayan, Avi, and Ben D. MacArthur, eds. New Frontiers of Network Analysis in Systems Biology. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4330-4.

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Airoldi, Edoardo, David M. Blei, Stephen E. Fienberg, Anna Goldenberg, Eric P. Xing, and Alice X. Zheng, eds. Statistical Network Analysis: Models, Issues, and New Directions. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73133-7.

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Leeuwen, Theo van. Discourse and practice: New tools for critical discourse analysis. New York: Oxford University Press, 2008.

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Pascual-Ferrá, Paola. How to Visualize and Interpret Social Media Networks Using Social Network Analysis Tools. 1 Oliver’s Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529610857.

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Borzemski, Leszek. Information systems architecture and technology: Information models, concepts, tools and applications. Wrocław: Oficyna Wydawnicza Politechniki Wrocławskiej, 2006.

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Aura, Reggiani, and Fabbri Daniele, eds. Network developments in economic spatial systems: New perspectives. Aldershot: Ashgate, 1999.

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Hillestad, R. J. New issues and tools for future military analysis: A workshop summary. Santa Monica, CA (P.O. Box 2138, Santa Monica 90407-2138): Rand, 1992.

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Qld.) APEC Gender Focal Point Network Workshop (2007 Cairns. Gender analysis: Concepts, tools, and practice : training manual for APEC 2007 Gender Focal Point Network Workshop. [Singapore]: Asia Pacific Economic Cooperation, 2007.

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Book chapters on the topic "New tools for network analysis"

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Yang, Pengfei, Renjue Li, Jianlin Li, Cheng-Chao Huang, Jingyi Wang, Jun Sun, Bai Xue, and Lijun Zhang. "Improving Neural Network Verification through Spurious Region Guided Refinement." In Tools and Algorithms for the Construction and Analysis of Systems, 389–408. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72016-2_21.

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AbstractWe propose a spurious region guided refinement approach for robustness verification of deep neural networks. Our method starts with applying the DeepPoly abstract domain to analyze the network. If the robustness property cannot be verified, the result is inconclusive. Due to the over-approximation, the computed region in the abstraction may be spurious in the sense that it does not contain any true counterexample. Our goal is to identify such spurious regions and use them to guide the abstraction refinement. The core idea is to make use of the obtained constraints of the abstraction to infer new bounds for the neurons. This is achieved by linear programming techniques. With the new bounds, we iteratively apply DeepPoly, aiming to eliminate spurious regions. We have implemented our approach in a prototypical tool DeepSRGR. Experimental results show that a large amount of regions can be identified as spurious, and as a result, the precision of DeepPoly can be significantly improved. As a side contribution, we show that our approach can be applied to verify quantitative robustness properties.
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Simon, Andreas. "Fuzzy and neural network controller — a new tool for stability analysis." In Computational Intelligence Theory and Applications, 428–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-62868-1_135.

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Cassez, Franck, Joanne Fuller, and Aditya Asgaonkar. "Formal Verification of the Ethereum 2.0 Beacon Chain." In Tools and Algorithms for the Construction and Analysis of Systems, 167–82. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99524-9_9.

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AbstractWe report our experience in the formal verification of the reference implementation of the Beacon Chain. The Beacon Chain is the backbone component of the new Proof-of-Stake Ethereum 2.0 network: it is in charge of tracking information about the validators, their stakes, their attestations (votes) and if some validators are found to be dishonest, to slash them (they lose some of their stakes). The Beacon Chain is mission-critical and any bug in it could compromise the whole network. The Beacon Chain reference implementation developed by the Ethereum Foundation is written in Python, and provides a detailed operational description of the state machine each Beacon Chain’s network participant (node) must implement. We have formally specified and verified the absence of runtime errors in (a large and critical part of) the Beacon Chain reference implementation using the verification-friendly language Dafny. During the course of this work, we have uncovered several issues, proposed verified fixes. We have also synthesised functional correctness specifications that enable us to provide guarantees beyond runtime errors. Our software artefact with the code and proofs in Dafny is available at https://github.com/ConsenSys/eth2.0-dafny.
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Yellin, Daniel M., and Gail Weiss. "Synthesizing Context-free Grammars from Recurrent Neural Networks." In Tools and Algorithms for the Construction and Analysis of Systems, 351–69. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72016-2_19.

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AbstractWe present an algorithm for extracting a subclass of the context free grammars (CFGs) from a trained recurrent neural network (RNN). We develop a new framework, pattern rule sets (PRSs), which describe sequences of deterministic finite automata (DFAs) that approximate a non-regular language. We present an algorithm for recovering the PRS behind a sequence of such automata, and apply it to the sequences of automata extracted from trained RNNs using the $$L^{*}$$ L ∗ algorithm. We then show how the PRS may converted into a CFG, enabling a familiar and useful presentation of the learned language.Extracting the learned language of an RNN is important to facilitate understanding of the RNN and to verify its correctness. Furthermore, the extracted CFG can augment the RNN in classifying correct sentences, as the RNN’s predictive accuracy decreases when the recursion depth and distance between matching delimiters of its input sequences increases.
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Peruffo, Andrea, Daniele Ahmed, and Alessandro Abate. "Automated and Formal Synthesis of Neural Barrier Certificates for Dynamical Models." In Tools and Algorithms for the Construction and Analysis of Systems, 370–88. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72016-2_20.

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AbstractWe introduce an automated, formal, counterexample-based approach to synthesise Barrier Certificates (BC) for the safety verification of continuous and hybrid dynamical models. The approach is underpinned by an inductive framework: this is structured as a sequential loop between a learner, which manipulates a candidate BC structured as a neural network, and a sound verifier, which either certifies the candidate’s validity or generates counter-examples to further guide the learner. We compare the approach against state-of-the-art techniques, over polynomial and non-polynomial dynamical models: the outcomes show that we can synthesise sound BCs up to two orders of magnitude faster, with in particular a stark speedup on the verification engine (up to three orders less), whilst needing a far smaller data set (up to three orders less) for the learning part. Beyond improvements over the state of the art, we further challenge the new approach on a hybrid dynamical model and on larger-dimensional models, and showcase the numerical robustness of our algorithms and codebase.
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Silva, Frutuoso G. M., Quoc Trong Nguyen, Acácio F. P. P. Correia, Filipe Manuel Clemente, and Fernando Manuel Lourenço Martins. "Network Analysis Tools." In Ultimate Performance Analysis Tool (uPATO), 1–4. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99753-7_1.

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Bayless, S., J. Backes, D. DaCosta, B. F. Jones, N. Launchbury, P. Trentin, K. Jewell, S. Joshi, M. Q. Zeng, and N. Mathews. "Debugging Network Reachability with Blocked Paths." In Computer Aided Verification, 851–62. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81688-9_39.

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AbstractIn this industrial case study we describe a new network troubleshooting analysis used by VPC Reachability Analyzer, an SMT-based network reachability analysis and debugging tool. Our troubleshooting analysis uses a formal model of AWS Virtual Private Cloud (VPC) semantics to identify whether a destination is reachable from a source in a given VPC configuration. In the case where there is no feasible path, our analysis derives a blocked path: an infeasible but otherwise complete path that would be feasible if a corresponding set of VPC configuration settings were adjusted.Our blocked path analysis differs from other academic and commercial offerings that either rely on packet probing (e.g., tcptrace) or provide only partial paths terminating at the first component that rejects the packet. By providing a complete (but infeasible) path from the source to destination, we identify for a user all the configuration settings they will need to alter to admit that path (instead of requiring them to repeatedly re-run the analysis after making partial changes). This allows users to refine their query so that the blocked path is aligned with their intended network behavior before making any changes to their VPC configuration.
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Jensen, Finn V. "Bayesian Network Analysis Tools." In Bayesian Networks and Decision Graphs, 201–24. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3502-4_6.

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Aggrawal, Niyati, and Adarsh Anand. "Social Network Analysis Tools." In Social Networks, 205–32. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003088066-12.

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Spadoni, Francesco, Flavio Tariffi, Raffaele Rossi, and Salvatore Lusso. "A Techno Social Collaborative Platform to Manage Optimize and Crowdfund Cultural Heritage Initiatives." In Proceedings e report, 187–94. Florence: Firenze University Press, 2018. http://dx.doi.org/10.36253/978-88-6453-707-8.43.

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This paper presents the first results of HERIBITS, a research project co-funded by the Tuscany Region Government, under the Operative Regional Program FESR POR 2014-2020. The project proposes an innovative methodology as well as advanced technology platform enabling a new paradigm for bottom-up and top-down management of cultural heritage initiatives. The techno-social platform integrates collaborative tools for CrowdSourcing, as well as analysis tools for rating project ideas and evaluate socio-economic impact, to propose best practices and to detect similar initiatives in order to avoid project duplications. The platform provides also social network capabilities and integrates an ad-hoc CrowdFunding shop.
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Conference papers on the topic "New tools for network analysis"

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Laucelli, D., O. Giustolisi, and E. Todini. "New Concepts and Tools for Pipe Network Design." In Water Distribution Systems Analysis 2008. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41024(340)22.

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Gulyás, A., J. Bíró, and F. Németh. "New stochastic network calculus for loss analysis." In 4th International ICST Conference on Performance Evaluation Methodologies and Tools. ICST, 2009. http://dx.doi.org/10.4108/icst.valuetools2009.7752.

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Kulawiak, Marek, Przemyslaw Falkowski-Gilski, and Marcin Kulawiak. "DAB+ Coverage Analysis: a New Look at Network Planning using GIS Tools." In 2018 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA). IEEE, 2018. http://dx.doi.org/10.23919/spa.2018.8563396.

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Anselmi, Jonatha. "A new framework supporting the bottleneck analysis of multiclass queueing networks." In 3rd International ICST Conference on Performance Evaluation Methodologies and Tools. ICST, 2008. http://dx.doi.org/10.4108/icst.valuetools2008.4383.

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Anselin, Luc, Serge Rey, and Andrew Winslow. "New tools for statistical point pattern analysis on networks with large datasets." In the 1st International Conference and Exhibition. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1823854.1823922.

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Mcdonald, Nick, David Leader, Cheng-Kao Chiang, Youry Khmelevsky, Rob Bartlett, and Alex Needham. "A new online tool for gamer network performance analysis." In 2016 IEEE International Conference on Cybercrime and Computer Forensic (ICCCF). IEEE, 2016. http://dx.doi.org/10.1109/icccf.2016.7740432.

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Silva, Frutuoso G. M., Abel J. P. Gomes, Quoc Trong Nguyen, Fernando M. L. Martins, and Filipe M. Clemente. "A new tool for network analysis on team sports the ultimate performance analysis tool." In 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC). IEEE, 2017. http://dx.doi.org/10.1109/ice.2017.8279918.

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Wang, Fu-Chung F., and Paul K. Wright. "Web-Based Cad Tools for a Networked Manufacturing Service." In ASME 1998 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/detc98/cie-5517.

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Abstract New techniques in Information Technology are now changing not only our daily life, but also the professional practice of product design and manufacturing for new product development. Internet technology in particular opens up another domain for building future CAD/CAM environments. This environment will be a global, network-centric environment with various members providing different software tools, manufacturing facilities, and analysis services for distributed design and fabrication. In this paper, we first briefly describe a vision and current development in a distributed design and manufacturing environment. The paper then emphasizes how current CAD tools will evolve to facilitate the distributed design and fabrication process. In particular, the development of a set of Web-based design tools for fabricating parts using a machining process via the Internet is presented. Experiments on machining 2-1/2 D and freeform parts through this Java-based design tool have shown the feasibility for a networked machining service via the Internet.
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Beirao, Fabio D., Joao V. Gomes, Pedro R. M. Inacio, Manuela Pereira, and Mario M. Freire. "NetOdyssey - A New Tool for Real-Time Analysis of Network Traffic." In 2010 9th IEEE International Symposium on Network Computing and Applications (NCA). IEEE, 2010. http://dx.doi.org/10.1109/nca.2010.43.

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Nagai, Yukari, Georgi V. Georgiev, and Toshiharu Taura. "Users’ Tactile Interactions With New Product Materials: An Analysis of Depth Impressions Based on Associative Concept Networks." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28613.

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Depth impressions are an inward associative layer of the expressed impressions of humans. To analyze tactile interaction, it is essential to examine what users feel and imagine and how they create depth impressions by touching and looking at different materials. On the basis of tactile interactions, this study captures and analyzes users’ depth impressions on materials. We propose impressionable new tactile material for design from the viewpoint of depth impressions and emotional engineering. We employed a concept networks-based method to analyze the experimentally obtained verbalized protocols and to identify the depth impressions. We found that the feel of materials’ tactile naturalness is related to the depth impressions and concept networks’ complexity. The depth impressions and concept network of the proposed micro-print material are distinct and beyond that of existing natural or artificial materials. These findings will help in employing new analysis tools and developing better tactile materials for designing products.
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Reports on the topic "New tools for network analysis"

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Wright, Alex, Peter Sanders, John Proust, Robin Workman, Tadas Andriejauskas, and Hao Ye. The new toolkit for highways asset management. TRL, September 2021. http://dx.doi.org/10.58446/ojct3729.

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The application of consistent, reliable information is a key component of highway asset management. However, the tools to understand asset performance have developed rapidly over the last decade. These include asset surveys, intelligent infrastructure monitoring, crowd sourcing, remote sensing, data analytics and visualisation. However, their potential is not yet being fully exploited within the highway environment. By bringing these components of sensing and measurement together we could better understand highway assets and improve reactive and proactive decisions. This paper discusses the tools now available to understand the performance of highway assets. It explores their current and future capabilities, the benefits they bring, and the possibilities that could be achieved through their application within an integrated toolkit. Whilst these tools are not in themselves “new”, a key objective of the paper has been to highlight their emerging capabilities, bring awareness to highway asset managers, and encourage their take up. Increased application will inevitably lead to further development in capability and, importantly, accessibility. There are a number of challenges to overcome to draw full value from these technologies. These include the technical, commercial, and social barriers that influence development and accessibility. The paper discusses actions that could help overcome these, which are presented within the context of a roadmap to the implementation of an integrated toolkit. The roadmap is not definitive - it aims to stimulate further thinking, debate and discussion. The effective management of infrastructure assets is essential to deliver a clean, efficient, safe, reliable and accessible network. A joined up and collaborative approach will help the community achieve the benefits of the integrated toolkit that will help asset managers achieve this.
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Rainer, Ilia, and Francesco Trebbi. New Tools for the Analysis of Political Power in Africa. Cambridge, MA: National Bureau of Economic Research, September 2012. http://dx.doi.org/10.3386/w18424.

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Kompaniets, Alla, Hanna Chemerys, and Iryna Krasheninnik. Using 3D modelling in design training simulator with augmented reality. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3740.

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The article is devoted to the theoretical consideration of the problem and the use of innovative technologies in the educational process in the educational establishment of secondary education in the process of studying the school course of computer science. The main advantages of using educational simulators in the educational process are considered, based on the new state standard of basic and complete general secondary education. Based on the analysis of scientific and methodological literature and network sources, the features of the development of simulators for educational purposes are described. Innovative tools for simulator development have been investigated, as augmented reality with the use of three-dimensional simulation. The peculiarities of using a simulator with augmented reality when studying the topic of algorithmization in the course of studying a school computer science are considered. The article also describes the implementation of augmented reality simulator for the formation of algorithmic thinking skills by students, presents the results of development and describes the functionality of the software product. In the further prospects of the study, it is planned to conduct an experimental study to determine the effectiveness of the use of software development in the learning process.
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Galili, Naftali, Roger P. Rohrbach, Itzhak Shmulevich, Yoram Fuchs, and Giora Zauberman. Non-Destructive Quality Sensing of High-Value Agricultural Commodities Through Response Analysis. United States Department of Agriculture, October 1994. http://dx.doi.org/10.32747/1994.7570549.bard.

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The objectives of this project were to develop nondestructive methods for detection of internal properties and firmness of fruits and vegetables. One method was based on a soft piezoelectric film transducer developed in the Technion, for analysis of fruit response to low-energy excitation. The second method was a dot-matrix piezoelectric transducer of North Carolina State University, developed for contact-pressure analysis of fruit during impact. Two research teams, one in Israel and the other in North Carolina, coordinated their research effort according to the specific objectives of the project, to develop and apply the two complementary methods for quality control of agricultural commodities. In Israel: An improved firmness testing system was developed and tested with tropical fruits. The new system included an instrumented fruit-bed of three flexible piezoelectric sensors and miniature electromagnetic hammers, which served as fruit support and low-energy excitation device, respectively. Resonant frequencies were detected for determination of firmness index. Two new acoustic parameters were developed for evaluation of fruit firmness and maturity: a dumping-ratio and a centeroid of the frequency response. Experiments were performed with avocado and mango fruits. The internal damping ratio, which may indicate fruit ripeness, increased monotonically with time, while resonant frequencies and firmness indices decreased with time. Fruit samples were tested daily by destructive penetration test. A fairy high correlation was found in tropical fruits between the penetration force and the new acoustic parameters; a lower correlation was found between this parameter and the conventional firmness index. Improved table-top firmness testing units, Firmalon, with data-logging system and on-line data analysis capacity have been built. The new device was used for the full-scale experiments in the next two years, ahead of the original program and BARD timetable. Close cooperation was initiated with local industry for development of both off-line and on-line sorting and quality control of more agricultural commodities. Firmalon units were produced and operated in major packaging houses in Israel, Belgium and Washington State, on mango and avocado, apples, pears, tomatoes, melons and some other fruits, to gain field experience with the new method. The accumulated experimental data from all these activities is still analyzed, to improve firmness sorting criteria and shelf-life predicting curves for the different fruits. The test program in commercial CA storage facilities in Washington State included seven apple varieties: Fuji, Braeburn, Gala, Granny Smith, Jonagold, Red Delicious, Golden Delicious, and D'Anjou pear variety. FI master-curves could be developed for the Braeburn, Gala, Granny Smith and Jonagold apples. These fruits showed a steady ripening process during the test period. Yet, more work should be conducted to reduce scattering of the data and to determine the confidence limits of the method. Nearly constant FI in Red Delicious and the fluctuations of FI in the Fuji apples should be re-examined. Three sets of experiment were performed with Flandria tomatoes. Despite the complex structure of the tomatoes, the acoustic method could be used for firmness evaluation and to follow the ripening evolution with time. Close agreement was achieved between the auction expert evaluation and that of the nondestructive acoustic test, where firmness index of 4.0 and more indicated grade-A tomatoes. More work is performed to refine the sorting algorithm and to develop a general ripening scale for automatic grading of tomatoes for the fresh fruit market. Galia melons were tested in Israel, in simulated export conditions. It was concluded that the Firmalon is capable of detecting the ripening of melons nondestructively, and sorted out the defective fruits from the export shipment. The cooperation with local industry resulted in development of automatic on-line prototype of the acoustic sensor, that may be incorporated with the export quality control system for melons. More interesting is the development of the remote firmness sensing method for sealed CA cool-rooms, where most of the full-year fruit yield in stored for off-season consumption. Hundreds of ripening monitor systems have been installed in major fruit storage facilities, and being evaluated now by the consumers. If successful, the new method may cause a major change in long-term fruit storage technology. More uses of the acoustic test method have been considered, for monitoring fruit maturity and harvest time, testing fruit samples or each individual fruit when entering the storage facilities, packaging house and auction, and in the supermarket. This approach may result in a full line of equipment for nondestructive quality control of fruits and vegetables, from the orchard or the greenhouse, through the entire sorting, grading and storage process, up to the consumer table. The developed technology offers a tool to determine the maturity of the fruits nondestructively by monitoring their acoustic response to mechanical impulse on the tree. A special device was built and preliminary tested in mango fruit. More development is needed to develop a portable, hand operated sensing method for this purpose. In North Carolina: Analysis method based on an Auto-Regressive (AR) model was developed for detecting the first resonance of fruit from their response to mechanical impulse. The algorithm included a routine that detects the first resonant frequency from as many sensors as possible. Experiments on Red Delicious apples were performed and their firmness was determined. The AR method allowed the detection of the first resonance. The method could be fast enough to be utilized in a real time sorting machine. Yet, further study is needed to look for improvement of the search algorithm of the methods. An impact contact-pressure measurement system and Neural Network (NN) identification method were developed to investigate the relationships between surface pressure distributions on selected fruits and their respective internal textural qualities. A piezoelectric dot-matrix pressure transducer was developed for the purpose of acquiring time-sampled pressure profiles during impact. The acquired data was transferred into a personal computer and accurate visualization of animated data were presented. Preliminary test with 10 apples has been performed. Measurement were made by the contact-pressure transducer in two different positions. Complementary measurements were made on the same apples by using the Firmalon and Magness Taylor (MT) testers. Three-layer neural network was designed. 2/3 of the contact-pressure data were used as training input data and corresponding MT data as training target data. The remaining data were used as NN checking data. Six samples randomly chosen from the ten measured samples and their corresponding Firmalon values were used as the NN training and target data, respectively. The remaining four samples' data were input to the NN. The NN results consistent with the Firmness Tester values. So, if more training data would be obtained, the output should be more accurate. In addition, the Firmness Tester values do not consistent with MT firmness tester values. The NN method developed in this study appears to be a useful tool to emulate the MT Firmness test results without destroying the apple samples. To get more accurate estimation of MT firmness a much larger training data set is required. When the larger sensitive area of the pressure sensor being developed in this project becomes available, the entire contact 'shape' will provide additional information and the neural network results would be more accurate. It has been shown that the impact information can be utilized in the determination of internal quality factors of fruit. Until now,
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Middleton, Don, and Mary Haley. Parallel analysis tools and new visualization techniques for ultra-large climate data set. Office of Scientific and Technical Information (OSTI), December 2014. http://dx.doi.org/10.2172/1165225.

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Raychev, Nikolay. Can human thoughts be encoded, decoded and manipulated to achieve symbiosis of the brain and the machine. Web of Open Science, October 2020. http://dx.doi.org/10.37686/nsrl.v1i2.76.

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This article discusses the current state of neurointerface technologies, not limited to deep electrode approaches. There are new heuristic ideas for creating a fast and broadband channel from the brain to artificial intelligence. One of the ideas is not to decipher the natural codes of nerve cells, but to create conditions for the development of a new language for communication between the human brain and artificial intelligence tools. Theoretically, this is possible if the brain "feels" that by changing the activity of nerve cells that communicate with the computer, it is possible to "achieve" the necessary actions for the body in the external environment, for example, to take a cup of coffee or turn on your favorite music. At the same time, an artificial neural network that analyzes the flow of nerve impulses must also be directed at the brain, trying to guess the body's needs at the moment with a minimum number of movements. The most important obstacle to further progress is the problem of biocompatibility, which has not yet been resolved. This is even more important than the number of electrodes and the power of the processors on the chip. When you insert a foreign object into your brain, it tries to isolate itself from it. This is a multidisciplinary topic not only for doctors and psychophysiologists, but also for engineers, programmers, mathematicians. Of course, the problem is complex and it will be possible to overcome it only with joint efforts.
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Moten, Margaret, and Daniel Evans. Functional Network Analysis: A New Way to Compare Frontier and Emerging Markets. Fort Belvoir, VA: Defense Technical Information Center, June 2012. http://dx.doi.org/10.21236/ada562876.

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Lagarda, Guillermo. The New Challenges of Greater Financial Complexity in Central America: A Network Analysis. Inter-American Development Bank, October 2017. http://dx.doi.org/10.18235/0000868.

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DeVivo, Joseph C. Inventories 2.0: A plan for the next generation of NPS natural resource inventories. National Park Service, 2019. http://dx.doi.org/10.36967/2266646.

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This Inventory 2.0 plan identifies IMD’s planned role in each of the ten inventories, and lays out a framework for ensuring the inventories led by IMD result in scientifically credible information for parks resource management, planning, and operations; and also identifies the means by which studies to collect new inventory data will be identified, prioritized, and implemented. Highlights include: IMD plans to lead three of the ten inventories (Species, Vegetation Community Mapping, and Surficial Geology/Soils Mapping), and contribute to the others in partnership with other programs. For the three IMD-led inventories, IMD will develop (or work with the Geologic Resources Division to develop) peer-reviewed inventory science plans that will lay out inventory objectives; and methods for data management, analysis, and integration to ensure that credible and useful inventory data are provided to parks in a timely manner. IMD will phase in implementation of IMD-led inventories during the first five years of program implementation. This will allow IMD to focus near-term efforts on meeting needs identified by the greatest number of parks (Species) while conducting necessary scoping to further refine needs for Vegetation Community Mapping and Surficial Geology/Soils Mapping inventories. During the next two years, IMD inventory efforts will be focused on implementing the Species Inventory, beginning with foundational work in advance of field data collection efforts to be funded in 2020. Additional scoping to identify suitable methods and minimum product specifications for Vegetation Community and Surficial Geology/Soils Mapping will be conducted in 2019-2020. These two new inventories will be phased in based on findings from scoping and progress toward closing out existing (1.0) inventory efforts. All I&M parks will be eligible for IMD funding to support inventories (see Appendix A). Non-I&M parks established before 2000 may be eligible for studies and activities to collect new inventory data pending approval of the project by the IMD Leadership Team. Inventories 2.0 funding cannot be spent to collect new data in parks established in 2000 or later, that are not currently served by an I&M network. Existing data from other sources may still be synthesized and delivered to these parks, however. Inventories 2.0 funding will not be used to fund programs or initiatives already funded or implemented by other programs or agencies. We will endeavor to partner with these entities when possible and appropriate to meet inventory needs identified in this plan, and to ensure IMD-created inventory (and monitoring) data are available to support other programs. Data and other information products resulting from new IMD-funded inventory studies will be managed by IMD rather than third-party repositories. This does not preclude sharing data with third parties or use of third-party tools or data distribution systems. At a minimum IMD commits to make inventory data available to others via the NPS Data Store (https://irma.nps.gov/DataStore/) as well as data and/or map services. To the extent possible, IMD management of inventory data will use the data management infrastructure used for managing monitoring data. This includes a commitment to leverage data, tools, systems, and expertise where it already exists. Because of IMD’s explicit mandate to integrate I&M data with planning, wherever practicable, IMD commits to work with NPS Planning to ensure map and data services are integrated into NPS Atlas projects for each park or other planning tools as they are developed over time.
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10

Bonthron, Leslie, Corey Beck, Alana Lund, Farida Mahmud, Xin Zhang, Rebeca Orellana Montano, Shirley J. Dyke, Julio Ramirez, Yenan Cao, and George Mavroeidis. Empowering the Indiana Bridge Inventory Database Toward Rapid Seismic Vulnerability Assessment. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317282.

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With the recent identification of the Wabash Valley Seismic Zone in addition to the New Madrid Seismic Zone, Indiana’s Department of Transportation (INDOT) has become concerned with ensuring the adequate seismic performance of their bridge network. While INDOT made an effort to reduce the seismic vulnerability of newly-constructed bridges, many less recent bridges still have the potential for vulnerability. Analyzing these bridges’ seismic vulnerability is a vital task. However, developing a detailed dynamic model for every bridge in the state using information from structural drawings is rather tedious and time-consuming. In this study, we develop a simplified dynamic assessment procedure using readily-available information from INDOT’s Bridge Asset Management Program (BIAS), to rapidly identify vulnerable bridges throughout the state. Eight additional data items are recommended to be added into BIAS to support the procedure. The procedure is applied in the Excel file to create a tool, which is able to automatically implement the simplified bridge seismic analysis procedure. The simplified dynamic assessment procedure and the Excel tool enable INDOT to perform seismic vulnerability assessment and identify bridges more frequently. INDOT can prioritize these bridges for seismic retrofits and efficiently ensure the adequate seismic performance of their assets.
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