Liquefaction potential assessment in soil deposits using artificial neural networks

In the literature, several simplified methods can be found to assess nonlinear liquefaction potential of soil. Derived from several field and laboratory tests, various procedures, also named as conventional methods, have been developed by utilizing case studies and undisturbed soil samples. In order to examine the collective knowledge built up in the conventional liquefaction methods available in the literature, a General Regression Neural Network (GRNN) model is proposed herein, which incorporates the parameters ignored in the past and accordingly will eliminate the shortcomings of the existing design formulae. Two, separate sets of field data, based on the standard penetration test, SPT, and the cone penetration test, CPT were used to develop the GRNN model. The proposed GRNN model predicted the occurrence/nonoccurrence of soil liquefaction well in these sites. Furthermore, liquefaction decision supported by SPT test results is incorporated into CPT based soil and seismic data. Therefore, the model supports the data conversion of an SPT-to-CPT throughout the liquefaction potential analysis, which believed to be the primary limitation of the simplified techniques. Thus the proposed model provides a viable tool to geotechnical engineers in assessing seismic condition in sites susceptible to liquefactio

In Vitro Cytotoxicity of GuttaFlow Bioseal, GuttaFlow 2, AH-Plus and MTA Fillapex

Introduction: The aim of the present in vitro study was to evaluate the cytotoxicity of different sealers including GuttaFlow Bioseal, GuttaFlow 2, AH-Plus and MTA Fillapex on L929 murine fibroblasts. Methods and Materials: Samples of GuttaFlow Bioseal, GuttaFlow 2, AH-Plus and MTA Fillapex were fabricated in Teflon disks of 5 mm diameter and 3 mm thickness. L929 fibroblasts were exposed to the extracts of these materials for 3, 24, 72 and 168 h at 37°C with 5% CO2. Cell viability was evaluated by the 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay. Apoptosis was evaluated by the terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay. The data were analysed by ANOVA. Results: GuttaFlow Bioseal was nontoxic at all experimental time points (P>0.05), whereas MTA Fillapex and AH-Plus were toxic (P<0.001). At 7 days, there were more viable cells in the GuttaFlow 2 group than in the control group, and MTA Fillapex was more cytotoxic than AH-Plus. There were more apoptotic cells in the MTA Fillapex and AH-Plus groups than in the other groups at 3 h (P<0.001). Conclusion: GuttaFlow sealers are less cytotoxic than MTA Fillapex and AH-Plus. At all experimental time points, there was no significant difference in the cell viability between the GuttaFlow Bioseal group and the control group.Keywords: AH-Plus; Cytotoxicity; GuttaFlow Bioseal; GuttaFlow 2; MTA Fillapex; MTT Assay; TUNEL Assa

A probabilistic approach for evaluating earthquake-induced landslides

textEarthquake-induced sliding displacements are commonly used to assess the seismic performance of slopes. These displacements represent the cumulative, downslope movement of a sliding block due to earthquake shaking. While the sliding block model is a simplified representation of the field conditions, the displacements predicted from this model have been shown to be a useful index of seismic performance of slopes. Current evaluation procedures that use sliding block displacements to evaluate the potential for slope instability typically are based on a deterministic approach or a pseudo-probabilistic approach, in which the variabilities in the expected ground motion and predicted displacement are either ignored or not treated rigorously. Thus, there is no concept of the actual hazard (i.e., the annual probability of exceedance) associated with the computed displacement. This dissertation focuses on quantifying the risk for earthquake-induced landslides. The basic approach involves a probabilistic framework for computing the annual rate of exceedance of different levels of sliding displacement for a slope such that a hazard curve for sliding displacement can be developed. The framework incorporates the uncertainties in the prediction of earthquake ground shaking, in the prediction of sliding displacement, and in the assessment of soil properties. The framework considers two procedures that will yield a displacement hazard curve: the scalar hazard approach that utilizes a single ground motion parameter and its associated hazard curve to compute permanent sliding displacements; and a vector hazard approach that predicts displacements based on two (or more) ground motion parameters and the correlation between these parameters. Current predictive models for sliding displacement provide the expected level of displacement as a function of the characteristics of the slope (e.g., geometry, strength, yield acceleration) and the characteristics of earthquake shaking (e.g., peak ground acceleration, peak ground velocity). However, current models contain significant aleatory variability such that the range of predicted displacements is large. To reduce the variability in the sliding displacement prediction and to provide models appropriate for the presented probabilistic framework, sliding displacement predictive equations are developed that utilize single and multiple ground motion parameters. The developed framework is implemented to the Mint Canyon 7.5-minute quadrangle in California to generate a map of earthquake-induced landslide hazard. Application of the probabilistic procedure to a 7-1/2 minute quadrangle of California is an important exercise to identify potential difficulties in California Geological Survey’s (CGS) current application for hazard mapping, and for the eventual adoption by CGS and USGS.Civil, Architectural, and Environmental Engineerin

Yeni Endekslerle 2003-2010 Donemi Reel Efektif Doviz Kuru Gelismelerine Iliskin Gozlemler

Calismada Turkiye Cumhuriyet Merkez Bankasi (TCMB) tarafindan takip edilen reel efektif doviz kuru endekslerine iliskin guncelleme ozetlenmektedir. Olusturulan yeni endekslerle yakin donemdeki dis ticaret gelismelerinin efektif kur gostergeleri uzerine yansitilmasi amaclanmistir. Bu cecevede, hesaplamaya dahil edilen ulke sayisi artirilirken, ulke agirliklari 2006-2008 donemi ticaret akimlari kullanilarak guncellenmistir. Bunlara ek olarak, alternatif endeksler olusturularak, reel efektif doviz kuru gelismeleri farkli acilardan incelenmistir.

Turkiye icin Yeni Reel Efektif Doviz Kuru Endeksleri

Bu calismanin amaci Turkiye Cumhuriyet Merkez Bankasi tarafindan ilan edilen reel efektif doviz kuru endekslerinin guncellenmesidir. Bu cercevede olusturulan yeni endekslerle hesaplamaya dahil edilen ulke sayisi 19’dan 36’ya cikarilmis, ulke agirliklari icinse kullanilmakta olan 1988-1990 donemine ait ticaret verileri yerine 2006-2008 donemi ticaret akimlari kullanilarak, yakin donem ticaret gelismelerinin degisen agirliklar tarafindan kapsanmasi amaclanmistir. Bunlara ek olarak, fonksiyonel reel efektif kuru endeksleri olusturularak, bolgesel analize imkan veren, ic-dis pazar siniflandirmasinda rekabet kompozisyonu ayriminin yapilabilmesini saglayan endekslerle, TUFE ve UFE bazli endekslerin yaninda birim isgucu maliyetleri, gayri safi yurtici hasila deflatoru ve ihracat fiyatlari bazli endeksler de turetilmistir.Reel Efektif Doviz Kurur Endeksi, Turkiye

Dis Ticarette Kuresel Egilimler ve Turkiye Ekonomisi

Onceki yuzyil uluslararasi ticaretinin temelini olusturan endustriler arasi ticaret, yerini endustri içi ticarete birakirken, gelismekte olan ulkelerin ihracatinda sanayiinin, gelismis ulkelerin ihracatinda ise hizmetlerin payi artmistir. Teknolojik ilerlemeler, uluslararasi rekabetin artmasi, tasimacilik maliyetlerinin ve tarifelerin gerilemesi, uretim aktivitelerinin, farkli faktor yogunluguna sahip kucuk alt sureclere bolunerek, her bir surecin farkli bir ulkede gerceklestirilmesine olanak vermektedir. Yeni kuresel uretim surecleri bir taraftan gelismekte olan ulkelerin endustri urunleri ihracatini artirirken diger taraftan uretimin ithal sermaye ve aramali kullanimini artirmaktadir. Calismanin bulgulari, sekiz gelismekte olan ve sekiz gelismis ulke arasinda 1990'lardan 2000'lere dikey anlamda uretimde uzmanlasma yapisinin degistigini gostermektedir. Soz konusu donemde gelismis ulkelerin karsilastirmali ustunlukleri ara mallarinda kuvvetlenirken gelismekte olan ulkelerin nihai mallarda goreli avantajlari artmaktadir. Turkiye'nin tekstil ve makine-techizat sektorleri nihai mallarindaki aciklanmis karsilastirmali ustunluk endeksi, son on yilda, sinirli bir oranda iyilesme gosterirken, ana metal ve ulastirma araçlari sektorlerinde hizli bir sekilde artmistir. Gelismekte olan ulkeler arasinda Turkiye en yuksek, Cin ise en dusuk ara mali ithalat-ihracat oranina sahiptir. Sektorel olarak en fazla ara mali ithalati ulastirma araclari sektorunde yapilirken, onu ana metal sektorunun takip etmektedir. Cokuluslu sirketleri gelismekte olan ulkelerin uretim ve ihracat yapilarinin donusumunde onemli rol oynamaktadir. Turkiye'ye de ise dogrudan yatirimlar-ihracat ve buyume iliskisi goreli olarak daha zayifti.Dikey Uzmanlasma, Dogrudan yatirimlar, Ithalat bagimliligi, Aciklanmis karsilastirmali ustunluk.

Neural network model for liquefaction potential in soil deposits using Turkey and Taiwan earthquake data

Simplified methods have been practiced by researchers to assess nonlinear liquefaction potential of soil. Derived from several field and laboratory tests, various simplified procedures such as stress-based, strain-based, Chinese criteria, etc. have been developed by utilizing case studies and undisturbed soil specimens. In order to address the collective knowledge built up in conventional liquefaction engineering, an alternative general regression neural network model is proposed in this paper. To meet this objective, a total of 620 sets of data including 12 soil and seismic parameters are introduced into the model. The data includes the results of field tests from the two major earthquakes that took place in Turkey and Taiwan in 1999 and some of the desired input parameters are obtained from correlations existing in the literature. The proposed GRNN model was developed in four phases, mainly: identification phase, collection phase, implementation phase, and verification phase. An iterative procedure was followed to maximize the accuracy of the proposed model. The case records were divided randomly into testing, training, and validation datasets. Generating a model that takes into account of 12 soil and seismic parameters is not feasible by using simplified techniques; however, the proposed GRNN model effectively explored the complex relationship between the introduced soil and seismic input parameters and validated the liquefaction decision obtained by simplified methods. The proposed GRNN model predicted well the occurrence/nonoccurrence of soil liquefaction in these sites. The model provides a viable tool to geotechnical engineers in assessing seismic condition in sites susceptible to liquefaction. Abstract Copyright (2007) Elsevier, B.V

Evaluation of liquefaction potential of soil deposits using artificial neural networks

Purpose In the literature, several empirical methods can be found to predict the occurrence of nonlinear soil liquefaction in soil layers. These methods are limited to the seismic conditions and the parameters used in developing the model. This paper seeks to present General Regression Neural Network GRNN model that addresses the collective knowledge built in simplified procedure. Designmethodologyapproach The GRNN model incorporates the soil and seismic parameters of the region. It was developed in four phases identification, collection, implementation, and verification. The data used consisted of 3,895 case records, mostly from the cone penetration test CPT results produced from the two major earthquakes that took place in Turkey and Taiwan in 1999. The case records were divided randomly into training, testing and validation datasets. Soil liquefaction decision in terms of seismic demand and seismic capacity is determined by the stressbased method and strainbased method, and further tested with the wellknown Chinese criteria. Findings The results produced by the proposed GRNN model explore effectively the complex relationship between the soil and seismic input parameters and further forecast the liquefaction potential with an overall success ratio of 94 percent. Liquefaction decisions were further validated by the SPT, confirming the viability of the SPTtoCPT data conversion, which is the main limitation of most of the simplified methods. Originalityvalue The proposed GRNN model provides a viable tool to geotechnical engineers to predict seismic condition in sites susceptible to liquefaction. The model can be constantly updated when new data are available, which will improve its predictability

Exploring the attention process differentiation of attention deficit hyperactivity disorder (ADHD) symptomatic adults using artificial intelligence on electroencephalography (EEG) signals

Attention deficit and hyperactivity disorder (ADHD) onset in childhood and its symptoms can last up till adulthood. Recently, electroencephalography (EEG) has emerged as a tool to investigate the neurophysiological connection of ADHD and the brain. In this study, we investigated the differentiation of attention process of healthy subjects with or without ADHD symptoms under visual continuous performance test (VCPT). In our experiments, artificial neural network (ANN) algorithm achieved 98.4% classification accuracy with 0.98 sensitivity when P2 event related potential (ERP) was used. Additionally, our experimental results showed that fronto-central channels were the most contributing. Overall, we conclude that the attention process of adults with or without ADHD symptoms become a key feature to separate individuals especially in fronto-central regions under VCPT condition. In addition, using P2 ERP component under VCPT task can be a highly accurate approach to investigate EEG signal differentiation on ADHD-symptomatic adults