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Text Spotting in the Wild with Embedded Device

& correlation , ‘Journal of Machine Learning Technologies’, 2011, Vol. 2, Issue 1, pp. 37–63. [7] Ye Q., Doermann D., Text Detection and Recognition in Imagery: A Survey , IEEE, ‘Transactions on Pattern Analysis and Machine Intelligence’, 2015, Vol. 37, Issue 7, pp. 1480–1500, DOI: 10.1109/TPAMI.2014.2366765. [8] Yin X., Zuo Z., Tian S., Text Detection, Tracking and Recognition in Video: A Comprehensive Survey , IEEE, ‘Transaction on Image Processinges’, 2016, Vol. 25, Issue 6, pp. 2752–2773, DOI: 10.1109/TIP.2016.2554321. [9] Jetson TX products , [online

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Bearing Capacity Investigation of Silty Sandy Soil Layer Using Kunzelstab Test

Kunzelstab Penetration Test” In: 5 th GEOINDO 2015 International Conference , Khon Kaen, Thailand. Geotechnical Engineering Research and Development (GERD), 2000, The Report Strength of Soil Layer in Footing Area. Kasetsart University, Bangkok, Thailand. Kaewwiset, N., Wiphathin, W. and Sootkhan, K., 2010. “The Correlation Between Engineering Properties of KKU soil and Results of Kunzelstab Penetration Test”, B.Eng. Project, Khon Kaen University, Khon Kaen, Thailand. Chanjeawchai, P., 2012. “Relationship between Kunzelstab number and unconfined

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Identification of Collision Mechanism at Seismogenic Fault Interface Using Finite Element Analysis Involving Plate Bending Applications Using Ant Colony Optimization

Greece, Tectonophysics 188 , 403-405. Varotsos, P., Alexopoulos, K., and Lazaridou, M. (1993), Latest aspects of earthquake prediction in Greece based on Seismic Electric Signals II, Tectonophysics224 , pp. 1-37. Varotsos, P. A., Sarlis, N. V., and Skordas., E. S. (2002), Long-range correlations in the electric signals that precede rupture. Physical Review E, 66-1, 011902. Varotsos, P. A., Sarlis, N. V., Skordas, E. S. (2003a), Long-range correlations in the electric signals that precede rupture: Further investigations, Phys. Rev. E , 67 , 021109

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Exploring the Energy Implication of Urban Density in Residential Buildings

Abstract

In the context of the Algerian energy policy, and through the review of the Algiers’ residential building stock, this paper explores the correlation between the energy consumption of gas and electricity with urban density. Based on a holistic approach of the 57 Algiers’ municipalities, the analysis is organized in two ways. Firstly, the spatial approach is conducted within a GIS implementation, carried out based on the 2013 aggregated annual energy consumption data. The cross analysis of Electricity and Gas consumption and density of population within a GIS spatial distribution approach shows effectively a strong correlation between urban density and energy consumption with a Pearson correlation of −56% and −65% of the Electricity and Gas consumption in the urban municipalities, respectively. Also, the household located in the suburban municipalities consume clearly more energy than the urban centered ones. Based on the electricity and gas consumption, density and carbon footprint we have clustered, within a PCA, the Algiers’ municipalities into three profiles: the “thrifty”, the “intermediate” and the “wasteful” profile.

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A Study of Groundwater Characteristics by Using of Groundwater Quality Index and Pollution Index in Zubair District, Basra Province, Iraq

Abstract

The present work evaluated the groundwater quality index (GWQI) depending on some physicochemical analyses of thirteen groundwater samples in the Zubair district in Basra Province, Iraq. The collected groundwater samples were subjected to an extensive physicochemical analysis to evaluate the characteristics of water for drinking purpose according to Iraqi standard. For calculating the (GWQI), twelve water quality parameters were considered; turbidity, pH, chloride, total dissolved solids, total hardness (TH), electrical conductivity (EC), sodium, sulphate, phosphate, calcium, nitrate, and magnesium. The analysis of the results reveals that all the samples surpassed the portability of drinking water limits. High values of the (GWQI) in the obtained groundwater samples could possibly be caused by the higher values of electrical conductivity, total hardness, chloride, total dissolved solids and sodium within the groundwater. The calculated GWQI values ranged from 73.36 to 595.92. The pollution index (PI) was calculated for the study area with values ranged from 2.97 to 8.26. Correlation coefficients amongst the chosen water parameters exhibited some strong relationships. Finally, the analysis shows that the groundwater in this particular area needs to be treated before its consumption, and in addition, it usually needs to avoid the hazard of contamination. Principal component analysis (PCA) and cluster analysis (CA) indicate that the acquiring-data from groundwater samples are explained 90.5 % of the variance in the data with a four-component system that explains a large portion of the total variance of collected data.

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Mathematical Modelling Of The Bridges Structural Monitoring II

Abstract

We have seen in the previous paper that in the case of resistance elements made of steel, at least in this case study, the structure’s response to strains, in this case sunshine, is uncertain, may or may not be linear. The analysis continues for the four characteristic months of 2013, respectively the second month (February), the fifth (May), the eighth (August) and the event (November), covering the four seasons and approximately the entire range of temperatures to which the resistance elements of the bridge are subject to along a calendar year - case study Incheon Grand Bridge, Seoul, South Korea. The number of data pairs recorded, as we have noted, every 15 minutes, is initially 11,616, being difficult to process. Some software (e.g. Table Curve 2D) can work with a maximum of 3000 data pairs. In what follows we will examine the behaviour of a reinforced concrete element of the North Bridge Gap front line and we will build a mathematical model of its behaviour to sunshine, from the input data, one recording every hours, thus reducing the number of measurements to 2904. The aim is to obtain a mathematical model with a correlation coefficient above 0.9, which is also verified and validated. This model will allow us to calculate the expected position of the sensor mounted on the resistance element for a certain temperature, the degree of confidence of the result, the interval of residual values. Because the history of the evolution of temperatures for each moment analyzed is different it produces different results, but ones that fit the specified regressive mathematical model.

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The Impact of Carbon Dioxide Concentration on the Human Health - Case Study

. Slovak Standard - European Norm, pp. 51. Herberger, S., Herold, M., Ulmer, H., Burdack-Freitag, A., Mayer, F., 2010. Detection of human effluents by a MOS gas sensor in correlation to VOC quantification by GC/MS. Building Environment , 45, pp. 2430-2439. Kapalo, P., Vilcekova, S., Vozniak, O., 2014. Using Experimental Measurements of the Concentrations of Carbon Dioxide for Determining the Intensity of Ventilation in the Rooms. Chemical Engineering Transactions , 39, pp. 1789-1794. Lis, A., Ujma, A., 2014. Changes in the External Environment and of

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Toward Building Energy Reduction Through Solar Energy Systems Retrofit Options: An Equest Model

consumption in different climates. Building and Environment , 46(1), pp. 223-234, https://doi.org/10.1016/j.buildenv.2010.07.016 . Wright, J.L., 1996. A correlation to quantify convective heat transfer between vertical window glazings. ASHRAE Transactions . Yu, J., Yang, C., Tian, L., 2008. Low-energy envelope design of residential building in hot summer and cold winter zone in China. Energy and Buildings , 40(8), pp. 1536-1546, https://doi.org/10.1016/j.enbuild.2008.02.020 . Zhu, Y., 2006. Applying computer-based simulation to energy auditing: A case

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