Fourier analysis of the light curves of eclipsing variables,XX

In the present paper _n ⁰ , for occulation and transit eclipses of partial phases, are evaluated numerically by means of the Runge-Kutta methods. Section 2 contains the required differential equations of _n ⁰ with respect to the modulusX orC, and Section 3 includes the numerical method of the solutions of these differential equations. Theoretical values of ₀ ⁰ and ₁ ⁰ , with corresponding values ofC, are also added in this section.     

Application of multivariate statistical techniques in the assessment of water quality in Sakarya River,Turkey

In this paper, the surface water quality of the Sakarya River in Turkey is assessed by using multivariate statistical techniques. These techniques were applied to the chemical parameters obtained from the five different surface water quality observation stations. Factor and principal component analysis results reveal that the agricultural, anthropogenic and domestic pollution caused differences in terms of water quality. Cluster analysis revealed two different clusters of similarities between the stations, reflecting different chemical properties and pollution levels in the studied river. Surface water quality downstream of the river was different from the water quality upstream. Thus, this study shows the usefulness of multivariate statistical techniques for analysis and interpretation in the surface water quality problem.     

Seismic loss assessment of seismically isolated buildings designed by the procedures of ASCE/SEI 7-16

Bulletin of Earthquake Engineering - This paper investigates the seismic loss assessment of seismically isolated and non-isolated buildings with steel moment or braced frames, designed by the...     

Automatic Building Extraction from Image and LiDAR Data with Active Contour Segmentation

Automatic building extraction is an important topic for many applications such as urban planning, disaster management, 3D building modeling and updating GIS databases. Its approaches mainly depend on two data sources: light detection and ranging (LiDAR) point cloud and aerial imagery both of which have advantages and disadvantages of their own. In this study, in order to benefit from the advantages of each data sources, LiDAR and image data combined together. And then, the building boundaries were extracted with the automated active contour algorithm implemented in MATLAB. Active contour algorithm uses initial contour positions to segment an object in the image. Initial contour positions were detected without user interaction by a series of image enhancements, band ratio and morphological operations. Four test areas with varying building and background levels of detail were selected from ISPRS’s benchmark Vaihingen and Istanbul datasets. Vegetation and shadows were removed from all the datasets by band ratio to improve segmentation quality. Subsequently, LiDAR point cloud data was converted to raster format and added to the aerial imagery as an extra band. Resulting merged image and initial contour positions were given to the active contour algorithm to extract building boundaries. In order to compare the contribution of LiDAR to the proposed method, the boundaries of the buildings were extracted from the input image before and after adding LiDAR data to the image as a layer. Finally extracted building boundaries were smoothed by the Awrangjeb (Int J Remote Sen 37(3): 551–579.  https://doi.org/10.1080/01431161.2015.1131868, 2016) boundary regularization algorithm. Correctness (Corr), completeness (Comp) and accuracy (Q) metrics were used to assess accuracy of segmented building boundaries by comparing extracted building boundaries with manually digitized building boundaries. Proposed approach shows the promising results with over 93% correctness, 92% completeness and 89% quality.     

http://www.sciencedirect.com/science/article/pii/S1674987113001382

The area from the Greater Caucasus to the southeast Turkey is characteri：;.ed and shaped by several major continental blocks. These are Scythian Platform, Pontian-Transcaucasu.,; Continent-Arc System （PTCAS）, the Anatolian-lranian and the Arabian Platforms. The aim of this paper is to define these continental blocks and describe and also compare their boundary relationships along the suture zones. The Scythian Platform displays the evidence of the Hercynian and Alpine orogens. This platform is separated from the PTCAS by the Greater Caucasus Suture Zone. The incipient collision began along this suture zone before middle-late Carboniferous whereas the final collision occurred before Oligocene. The PTCAS can be divided into four structural units： （1） the Georgian Block - northern part of the Pontian-Transcaucasian island-arc, （2） the southern and eastern Black Sea Coast-Adjara-Trialeti Unit, （3） the Artvin-Bolnisi Unit, comprising the northern part of the southern Transcaucasus, and （4） the Imbricated Bayburt-Garabagh Unit. The PTCAS could be separated from the Anatolian Iranian Platform by the North Anatolian-Lesser Caucasus Suture （NALCS） zone. The initial collision was developed in this suture zone during Senonian-early Eocene and final collision before middle Eocene or Oligocene-Miocene. The Anatolian-lranian Platform （AIP） is made up of the Tauride Platform and its metamorphic equivalents together with Iranian Platform. It could be separated from the Arabian Platform by the Southeastern Anatolian Suture （SEAS） zone. The collision ended before late Miocene along this suture zone. The southernmost continental block of the geotraverse is the Arabian Platform, which constitutes the northern part of the Arabian-African Plate. This platform includes a sequence from the Precambrian felsic volcanic and clastic rocks to the Campanian-early Maastrichtian fiyschoidal clastics. All the suture zones include MORB and SSZ-types ophiolites in different ages. However, the ages of the suture     

Prediction of the unconfined compressive strength of compacted granular soils by using inference systems

Adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) models have been extensively used to predict different soil properties in geotechnical applications. In this study, it was aimed to develop ANFIS and ANN models to predict the unconfined compressive strength (UCS) of compacted soils. For this purpose, 84 soil samples with different grain-size distribution compacted at optimum water content were subjected to the unconfined compressive tests to determine their UCS values. Many of the test results (for 64 samples) were used to train the ANFIS and the ANN models, and the rest of the experimental results (for 20 samples) were used to predict the UCS of compacted samples. To train these models, the clay content, fine silt content, coarse silt content, fine sand content, middle sand content, coarse sand content, and gravel content of the total soil mass were used as input data for these models. The UCS values of compacted soils were output data in these models. The ANFIS model results were compared with those of the ANN model and it was seen that the ANFIS model results were very encouraging. Consequently, the results of this study have important findings indicating reliable and simple prediction tools for the UCS of compacted soils.     

Ancient eco-technology of qanats for engineering a sustainable water supply in the Mediterranean Island of Cyprus

The qanat water supply technology, which gravity drains mountain aquifers into valleys, is considered as a culturally appropriate and ecological sustainable design to meet northern Cyprus’ drinking water development needs. This research estimates the boundary and water budget for the proposed qanat recharge area of 370 km², which is in the upper elevations of the limestone dominated Five Finger Mountain Range. The mountain drainage was analyzed using global elevation data from the Shuttle Ranging Topography Mission (SRTM). Efforts to use Tropical Rainfall Measuring Mission (TRMM) annual precipitation for water budget inputs failed due to extreme error when tested against 10–30 years of meteorological station data; TRMM under-estimated depths on the narrow mountain peaks. Gage records, while few in number, were area averaged to set average annual precipitation inputs at 530 mm year⁻¹. Evaporation was estimated using a complementary relationship areal evapotranspiration (CRAE) model, setting average atmospheric outputs at 221 mm year⁻¹. Recharge to the qanat aquifer was set by subtracting evaporation from precipitation, and then allocating 50% of the remaining water to environmental services. At 25% development, the qanat system supplies 14 mm³ year⁻¹ of water, meeting the drinking water deficit of 13 mm³.     

Assessment of Various Fuzzy c-Mean Clustering Validation Indices for Mapping Mineral Prospectivity: Combination of Multifractal Geochemical Model and Mineralization Processes

This paper describes the application of an unsupervised clustering method, fuzzy c-means (FCM), to generate mineral prospectivity models for Cu?±?Au?±?Fe mineralization in the Feizabad District of NE Iran. Various evidence layers relevant to indicators or potential controls on mineralization, including geochemical data, geological–structural maps and remote sensing data, were used. The FCM clustering approach was employed to reduce the dimensions of nine key attribute vectors derived from different exploration criteria. Multifractal inverse distance weighting interpolation coupled with factor analysis was used to generate enhanced multi-element geochemical signatures of areas with Cu?±?Au?±?Fe mineralization. The GIS-based fuzzy membership function MSLarge was used to transform values of the different evidence layers, including geological–structural controls as well as alteration, into a [0–1] range. Four FCM-based validation indices, including Bezdek’s partition coefficient (V_Pc) and partition entropy (V_Pe) indices, the Fukuyama and Sugeno (V_FS) index and the Xie and Beni (V_XB) index, were employed to derive the optimum number of clusters and subsequently generate prospectivity maps. Normalized density indices were applied for quantitative evaluation of the classes of the FCM prospectivity maps. The quantitative evaluation of the results demonstrates that the higher favorability classes derived from V_FS and V_XB (N_d?=?9.19) appear more reliable than those derived from V_Pc and V_Pe (N_d?=?6.12) in detecting existing mineral deposits and defining new zones of potential Cu?±?Au?±?Fe mineralization in the study area.