Impact of Vapor Barrier on Moisture Content of Fiberboard Insulation in Log Structure

The paper is focused on a verification of the moisture content of fiberboard insulations in the multilayer loadbearing log wall designed with and without the vapor barrier. Experimental verification was done using a sample of the multilayer loadbearing log wall built in a research timber structure building under in-situ conditions. Indoor properties of the building met conditions for human occupancy. The experiment was performed for 2 years and 3 months. Aims of the fiberboard insulations moisture content verification in the walls were to verify the effect of vapor barrier in various periods of the year and verify excessive moisture in the fiberboard insulations, which is undesirable in terms of biodegradation. The results of measuring the moisture content showed that after a certain period, the difference of insulation moisture content in the wall including and excluding vapor barrier is negligible, as well as other results and conclusions for designing the composition of multilayer loadbearing log walls.

THE CHURCH OF THEOTOKOS OF TIKHVIN IN YUDMOZERO, ARKHANGELSK REGION. HISTORY AND ARCHITECTURE

The article describes three stages of constructing the Church of the Theotokos of Tikhvin in the village of Yudmozero located in the Onega district of the Arkhangelsk region, which were discovered through the analysis of data retrieved from the State Archive of the Arkhangelsk Region, and the architectural features of these stages. The construction stages correlate with rebuilding the church in 1863 and replacing its porch and erecting a bell tower in 1907. The church is a quadrangle with a five-walled altar. The porch and the bell tower were lost. The on-site inspection of the monument enabled to classify this chapel church as a “chapel-type prayer house”, combining features of a chapel and a dwelling house. It differs from the chapels of the Arkhangelsk and Vologda regions or Karelia, since its core log structure is similar to a log cabin (“izba”). The chapel is distinguished by its dome and antechamber with a tent-like bell tower. The study resulted in reconstructing how the Yudmozero chapel looked between the late 18th and the early 20th centuries, and providing a brief analysis of the distinctive features of similar buildings in the villages of Vorzogory, Maloshuika, Nimenga, Podporozhye. The authors conclude that there are differences in the architectural traditions of Pomorye and the mainland Russian North, and put forward a hypothesis on the connection between the spread of chapel-type prayer houses and the Old Belief, which requires further study.

On a logarithmic version of the derived McKay correspondence

We globalize the derived version of the McKay correspondence of Bridgeland, King and Reid, proven by Kawamata in the case of abelian quotient singularities, to certain logarithmic algebraic stacks with locally free log structure. The two sides of the correspondence are given respectively by the infinite root stack and by a certain version of the valuativization (the projective limit of every possible logarithmic blow-up). Our results imply, in particular, that in good cases the category of coherent parabolic sheaves with rational weights is invariant under logarithmic blow-up, up to Morita equivalence.

Extracting of Positive and Negative Association Rules

Association rules analysis is a basic technique to expose how items/patterns are associated to each other. There are two common ways to measure association such as Support and Confidence. Several methods have been proposed in the literature to diminish the number of extracted association rules. Association Rule Mining is one of the greatest current data mining techniques designed to group objects together from huge databases aiming to take out the motivating correlation and relation with massive quantity of data. Association rule mining is used to discover the associated patterns from datasets. In this paper, we propose association rules from new methods on web usage mining. Generally, web usage log structure has several records so we have to overcome those unwanted records from large dataset. First of all the pre-processed data from the NASA dataset is clustered by the popular K-Means algorithm. Subsequently, the matrix calculation is progressed on that data. Further, the associations are performed on filtered data and get rid of the final associated page results. Positive and negative association rules are gathered by using new algorithm with Annul Object (𝒜𝒪). Wherever the object “𝒜𝒪” is presented those rules are known as negative association rule. Otherwise, the rules are positive association rules.

Scalable statistics of correlated random variables and extremes applied to deep borehole porosities

We analyze scale-dependent statistics of correlated random hydrogeological variables and their extremes using neutron porosity data from six deep boreholes, in three diverse depositional environments, as example. We show that key statistics of porosity increments behave and scale in manners typical of many earth and environmental (as well as other) variables. These scaling behaviors include a tendency of increments to have symmetric, non-Gaussian frequency distributions characterized by heavy tails that decay with separation distance or lag; power-law scaling of sample structure functions (statistical moments of absolute increments) in midranges of lags; linear relationships between log structure functions of successive orders at all lags, known as extended self-similarity or ESS; and nonlinear scaling of structure function power-law exponents with function order, a phenomenon commonly attributed in the literature to multifractals. Elsewhere we proposed, explored and demonstrated a new method of geostatistical inference that captures all of these phenomena within a unified theoretical framework. The framework views data as samples from random fields constituting scale mixtures of truncated (monofractal) fractional Brownian motion (tfBm) or fractional Gaussian noise (tfGn). Important questions not addressed in previous studies concern the distribution and statistical scaling of extreme incremental values. Of special interest in hydrology (and many other areas) are statistics of absolute increments exceeding given thresholds, known as peaks over threshold or POTs. In this paper we explore the statistical scaling of data and, for the first time, corresponding POTs associated with samples from scale mixtures of tfBm or tfGn. We demonstrate that porosity data we analyze possess properties of such samples and thus follow the theory we proposed. The porosity data are of additional value in revealing a remarkable cross-over from one scaling regime to another at certain lags. The phenomena we uncover are of key importance for the analysis of fluid flow and solute as well as particulate transport in complex hydrogeologic environments.

Extreme value statistics of scalable data exemplified by neutron porosities in deep boreholes

Spatial statistics of earth and environmental (as well as many other) data tend to vary with scale. Common manifestations of scale-dependent statistics include a tendency of increments to have symmetric, non-Gaussian frequency distributions characterized by heavy tails that decay with separation distance or lag; power-law scaling of sample structure functions (statistical moments of absolute increments) in midranges of lags; linear relationships between log structure functions of successive orders at all lags, known as extended self-similarity or ESS; and nonlinear scaling of structure function power-law exponents with function order, a phenomenon commonly attributed in the literature to multifractals. Elsewhere we proposed, explored and demonstrated a new method of geostatistical inference that captures all of these phenomena within a unified theoretical framework. The framework views data as samples from random fields constituting scale-mixtures of truncated (monofractal) fractional Brownian motion (tfBm) or fractional Gaussian noise (tfGn). Important questions not addressed in previous studies concern the distribution and statistical scaling of extreme incremental values. Of special interest in hydrology (and many other areas) are statistics of absolute increments exceeding given thresholds, known as peaks over thresholds or POTs. In this paper we explore for the first time the statistical behavior of POTs associated with samples from scale-mixtures of tfBm or tfGn. We are fortunate to have at our disposal thousands of neutron porosity values from six deep boreholes, in three diverse depositional environments, which we show possess the properties of such samples thus following the theory we proposed. The porosity data are of additional value in revealing a remarkable transition from one scaling regime to another at certain lags. The phenomena we uncover are of fundamental importance for the analysis of fluid flow and solute as well as particulate transport in complex hydrogeologic environments.

Towards building a forensics aware language for secure logging

Trustworthy system logs and application logs are crucial for digital forensics. Researchers have proposed different security mechanisms to ensure the integrity and confidentiality of logs. However, applying current secure logging schemes on heterogeneous formats of logs is tedious. Here, we propose Forensics Aware Language (FAL), a domain-specific language (DSL) through which we can apply a secure logging mechanism on any format of logs. Using FAL, we can define log structure, which represents the format of logs and ensures the security properties of a chosen secure logging scheme. This log structure can later be used by FAL to serve two purposes: it can be used to store system logs securely and it will help application developers for secure application logging by generating the required source code.