11 research outputs found
Fast, Linear Time, m-Adic Hierarchical Clustering for Search and Retrieval using the Baire Metric, with linkages to Generalized Ultrametrics, Hashing, Formal Concept Analysis, and Precision of Data Measurement
We describe many vantage points on the Baire metric and its use in clustering
data, or its use in preprocessing and structuring data in order to support
search and retrieval operations. In some cases, we proceed directly to clusters
and do not directly determine the distances. We show how a hierarchical
clustering can be read directly from one pass through the data. We offer
insights also on practical implications of precision of data measurement. As a
mechanism for treating multidimensional data, including very high dimensional
data, we use random projections.Comment: 17 pages, 45 citations, 2 figure
Computational analysis of gene expression space associated with metastatic cancer
<p>Abstract</p> <p>Background</p> <p>Prostate carcinoma is among the most common types of cancer affecting hundreds of thousands people every year. Once the metastatic form of prostate carcinoma is documented, the majority of patients die from their tumors as opposed to other causes. The key to successful treatment is in the earliest possible diagnosis, as well as understanding the molecular mechanisms of metastatic progression. A number of recent studies have identified multiple biomarkers for metastatic progression. However, most of the studies consider only direct comparison between metastatic and non-metastatic classes of samples.</p> <p>Results</p> <p>We propose an alternative concept of analysis that considers the entire multidimensional space of gene expression and identifies the partition of this space in which metastatic development is possible. To apply this concept in cancer gene expression studies we utilize a modification of high-dimension natural taxonomy algorithm FOREL. Our analysis of microarray data containing primary and metastatic cancer samples has revealed not only differentially expressed genes, but also relations between different groups of primary and metastatic cancer. Metastatic samples tend to occupy a distinct partition of gene expression space. Further pathway analysis suggests that this partition is delineated by a specific pattern of gene expression in cytoskeleton remodeling, cell adhesion and apoptosis/cell survival pathways. We compare our findings with both report of original analysis and recent studies in molecular mechanism of metastasis.</p> <p>Conclusion</p> <p>Our analysis indicates a single molecular mechanism of metastasis. The new approach does not contradict previously reported findings, but reveals important details unattainable with traditional methodology.</p
ΠΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΡΡΡΠΊΡΡΡΡ Π² ΠΊΠΎΠ½ΡΠ΅ΠΊΡΡΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ Π²ΠΎΠΉΠ½ β ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΠΉ
The concept of information warfare involves
the use of information and communication technology to
achieve an advantage over a potential enemy. The goal is to
take decisions against their interests in the interests of their
enemies. Information structures are treated as systems that
process various types of information, provide its storage
and access to users. Such structures may include neural
networks, self-learning systems, etc. They must be prepared
to train, respond to threats and ensure the safety of their
existence, which is topical during the modern information
warfare. In this paper, the theoretical aspects related to the
security of information systems from the point of view of the
system theory and ontology approach will be considered.
Knowledge base for information structures can be elements
of artiο¬cial intelligence, which must be secured against
external threats. Ontologies have gained increasing interest
in the computer science community and their beneο¬ts are
now recognized for different applications
Knowledge-based ontology concept for numerical data clustering
Classical clustering algorithms are sufο¬ciently well
studied, they are used for grouping numerical data in similar
structures - clusters. Similar objects are placed in the same
cluster, different objects in another cluster. All of the classic
clustering algorithms have common parameters, and successful
selection of which also determines the clustering result. The
most important parameters characterizing clustering are: clus-
tering algorithm, metrics, initial number of clusters, criteria for
clustering accuracy. In recent years, there has been a tendency
towards the possibility of obtaining rules from clusters. Classical
clustering algorithms do not apply semantic knowledge. It creates
difο¬culties in interpreting the results of clustering. Presently, the
use of ontology opportunities is developing very rapidly, that
allows to gain knowledge about a certain data model. The paper
analyzes the concept of ontology and prototype development for
numerical data clusterization, which includes the most signiο¬cant
indicators characterizing clusterization. The aim of the work is
to develop a concept for analyzing clustering data with the help
of ontologies. As a result of the work, a study has been conducted
on the use of ontologies in this type of tasks
ΠΠΎΠ½ΡΠ΅ΠΏΡΠΈΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΠΉ Π² ΡΠΈΡΡΠ΅ΠΌΠ°Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠΈΡΠΊΠΎΠ²
The work is dedicated to the development of an
ontology concept for assessment risk of threats for information
systems on the Microsoft approach β the model of identifying
threats STRIDE and methodology DREAD for assessment risk
of threats. The aim of the study is to describe the security
implementation methodology of information systems offered by
Microsoft. The basic concepts and techniques of this model
are given and ontology concept of risk assessment is proposed,
some of the classes and subclasses of the developed ontology are
described.Π Π°Π±ΠΎΡΠ° ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΠΈ ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ
Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠΈΡΠΊΠΎΠ² ΡΠ³ΡΠΎΠ· ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠΌ ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌ
ΠΏΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ Microsoft - ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΡΠ³ΡΠΎΠ·
STRIDE ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ DREAD Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠΈΡΠΊΠΎΠ² ΡΠ³ΡΠΎΠ·.
ΠΠ°Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΠΏΠΎΠ½ΡΡΠΈΡ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ ΡΡΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈ
ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π° ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΡ ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΏΠΎ ΠΎΡΠ΅Π½ΠΊΠ΅ ΡΠΈΡΠΊΠΎΠ²,
ΠΎΠΏΠΈΡΠ°Π½Ρ Π½Π΅ΠΊΠΎΡΠΎΡΡΠ΅ ΠΊΠ»Π°ΡΡΡ ΠΈ ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΡ ΡΠ°Π·ΡΠ°Π±Π°ΡΡΠ²Π°Π΅ΠΌΠΎΠΉ ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ
ΠΠΎΠ½ΡΠ΅ΠΏΡΠΈΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΠΉ Π² ΡΠΈΡΡΠ΅ΠΌΠ°Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠΈΡΠΊΠΎΠ²
The work is dedicated to the development of an
ontology concept for assessment risk of threats for information
systems on the Microsoft approach β the model of identifying
threats STRIDE and methodology DREAD for assessment risk
of threats. The aim of the study is to describe the security
implementation methodology of information systems offered by
Microsoft. The basic concepts and techniques of this model
are given and ontology concept of risk assessment is proposed,
some of the classes and subclasses of the developed ontology are
described.Π Π°Π±ΠΎΡΠ° ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΠΈ ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ
Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠΈΡΠΊΠΎΠ² ΡΠ³ΡΠΎΠ· ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠΌ ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌ
ΠΏΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ Microsoft - ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΡΠ³ΡΠΎΠ·
STRIDE ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ DREAD Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠΈΡΠΊΠΎΠ² ΡΠ³ΡΠΎΠ·.
ΠΠ°Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΠΏΠΎΠ½ΡΡΠΈΡ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ ΡΡΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈ
ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π° ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΡ ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΏΠΎ ΠΎΡΠ΅Π½ΠΊΠ΅ ΡΠΈΡΠΊΠΎΠ²,
ΠΎΠΏΠΈΡΠ°Π½Ρ Π½Π΅ΠΊΠΎΡΠΎΡΡΠ΅ ΠΊΠ»Π°ΡΡΡ ΠΈ ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΡ ΡΠ°Π·ΡΠ°Π±Π°ΡΡΠ²Π°Π΅ΠΌΠΎΠΉ ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ
Dynamics of quasi-stationary systems: Finance as an example
We propose a combination of cluster analysis and stochastic process analysis
to characterize high-dimensional complex dynamical systems by few dominating
variables. As an example, stock market data are analyzed for which the
dynamical stability as well as transitions between different stable states are
found. This combined method also allows to set up new criteria for merging
clusters to simplify the complexity of the system. The low-dimensional approach
allows to recover the high-dimensional fixed points of the system by means of
an optimization procedure.Comment: 6 page
Through entrepreneursβ eyes: the Fab-spaces constellation
Fab-spaces provide individuals with access to numerous manufacturing equipment (including additive manufacturing), to carry out different types of projects. Although scholars are starting to speculate about the importance of these new organizational forms and their potential for future distributed innovation and production ecologies, this phenomenon is still largely unexplored. Building on existing multidisciplinary research, this paper offers the first empirical analysis of existing fab-spaces as providers of knowledge and production competencies. Amongst all the possible perspectives to derive a framework, we choose that of fab-spaces users who have an entrepreneurial intention. After deriving an analytical framework to position fab-spaces in the current academic discourse, the paper develops a classification, which considers the competences available to entrepreneurs, via fab-spaces, in conjunction with how these competences are provided. The resulting map reveals the complementarities amongst the different fab-spaces. It also shows that the current portfolio of fab-spaces supports mainly the distribution of innovation across locations and social groups. Several types of fab-spaces are currently well placed to support the transition from innovation to manufacturing, but their geographical distribution and range of manufacturing capabilities is not yet enough to provide a fully distributed manufacturing model. This study has practical consequences for entrepreneurs, in the better identification of the appropriate fab-spaces for their needs, and for policy makers, to help position the different types of fab-spaces as elements for national systems of innovation and production.Engineering and Physical Sciences Research Council (Grant ID: EP/K039598/1)This is the final version of the article. It first appeared from Taylor & Francis via http://dx.doi.org/10.1080/00207543.2016.119850