Fuzzy logic model for the prediction of bond strength of high-strength lightweight concrete

In this study, a fuzzy logic prediction model for the bond strength of lightweight concrete containing mineral admixtures under different curing conditions was devised. A control concrete mixture containing only Portland cement, another mixture having fly ash replacing 15% by mass of cement, and a third mixture having silica fume replacing 10% by mass of cement are produced, and all specimens from these three mixtures are cured in three different conditions, which are: (1) in water tank of 20 ± 2 °C, (2) sealed in plastic bags in the laboratory, and (3) in air in the laboratory. At the end of each curing period, three specimens out of each concrete combination and curing condition were tested for compressive and bond strengths, and the average of three values were taken. The results obtained from the fuzzy logic prediction model were compared with the average results of the experiments, and they were found to be remarkably close to each other. The results show that the fuzzy logic can be used to predict bond strength of lightweight concrete.     

A new approach based on discrete hidden Markov model using Rocchio algorithm for the diagnosis of the brain diseases

Transcranial Doppler (TCD) study of the adult intracerebral circulation has gained an important popularity in last 10 years, since it is a non-invasive, easy to apply and reliable technique. In this study, an implementation on biomedical system has been developed for classification of signals gathered from middle cerebral arteries in the temporal area via TCD for 24 healthy and 82 ill people which have one of the four different brain patients such as; cerebral aneurysm, brain hemorrhage, cerebral oedema and brain tumor. Basically, the system is composed of feature extraction and classification parts. In the feature extraction stage, the Linear Predictive Coding (LPC) Analysis and Cepstral Analysis were applied in order to extract the cepstral and delta-cepstral coefficients in frame level as feature vectors. In the classification stage a new Discrete Hidden Markov Model (DHMM) based approach was proposed for the diagnosis of brain diseases. This proposed method was developed via Rocchio algorithm. Therefore, to calculate DHMM parameters regulated according to maximum likelihood (ML) approach, both training samples of related class and other classes were included in calculation. Thus, DHMM model parameters presenting one class were suggested to represent the training samples related to that class better as well as not to represent the training samples related to other classes. The performance of the proposed DHMM with Rocchio approach was compared with some methods such as DHMM, Artificial Neural Network (ANN), neuro-fuzzy approaches and obtained better classification performance than these methods.     

Detection of heart valve diseases by using fuzzy discrete hidden Markov model

In the present study, biomedical based application was developed to classify the data belongs to normal and abnormal samples generated by Doppler ultrasound. This study consists of raw data obtaining and pre-processing, feature extraction and classification steps. In the pre-processing step, a high-pass filter, white de-noising and normalization were used. During the feature extraction step, wavelet entropy was applied by wavelet transform and short time fourier transform. Obtained features were classified by fuzzy discrete hidden Markov model (FDHMM). For this purpose, a FDHMM that consists of Sugeno and Choquet integrals and λ fuzzy measurement was defined to eliminate statistical dependence assumptions to increase the performance and to have better flexibility. Moreover, Sugeno integral was used together with triangular norms that are mentioned frequently in the literature in order to increase the performance. Experimental results show that recognition rate obtained by Sugeno fuzzy integral with triangular norm is more successful than recognition rates obtained by standard discrete HMM (DHMM) and Choquet integral based FDHMM. In addition to this, it is shown in this study that the performance of the Sugeno integral based method is better than the performances of artificial neural network (ANN) and HMM based classification systems that were used in previous studies of the authors.     

A hybrid system based on information gain and principal component analysis for the classification of transcranial Doppler signals

A transcranial Doppler (TCD) is a non-invasive, easy to apply and reliable technique which is used in the diagnosis of various brain diseases by measuring the blood flow velocities in brain arteries. This study aimed to classify the TCD signals, and feature ranking (information gain - IG) and dimension reduction methods (principal component analysis - PCA) were used as a hybrid to improve the classification efficiency and accuracy. In this context, each feature within the feature space was ranked depending on its importance for the classification using the IG method. Thus, the less important features were ignored and the highly important features were selected. Then, the PCA method was applied to the highly important features for dimension reduction. As a result, a hybrid feature reduction between the selection of the highly important features and the application of the PCA method on the reduced features were achieved. To evaluate the effectiveness of the proposed method, experiments were conducted using a support vector machine (SVM) classifier on the TCD signals recorded from the temporal region of the brain of 82 patients, as well as 24 healthy people. The experimental results showed that using the IG and PCA methods as a hybrid improves the classification efficiency and accuracy compared with individual usage.     

Q-switched giant pulsed erbium-doped all-fiber laser withV2ZnC MAX phase saturable absorber

MXenes, drawn from MAX phases, are special two-dimensional substances with numerous advantages in nonlinear optics, specifically in giant and ultrashort pulsed-laser applications. Ti3C2Tx and Ti2CTx nanosheets however rapidly deteriorate under ambient conditions, limiting their applications. This paper demonstrates how excellent modulation depth of one of the MAX phase compounds vanadium zinc carbide (V2ZnC) makes it a brilliant saturable absorber (SA) in passively Q-switched all-fiber pulsed lasers, integrated such that a 16.73-µm V2ZnC-polyvinyl alcohol (PVA) thin film acts as SA in the laser. Saturable and non-saturable absorptions were found to be 13.2% and 10.47%, while saturation optical intensity and modulation depth were 6.25 kW/cm2 and 12.43%, respectively, illustrating the optical nonlinearity. The superiority of MAX-PVA, fabricated in four distinct ratios, was demonstrated by the fact that it self-starts a giant pulsed laser at pump power as low as 22.5 mW and firmly accomplished 120.6 kHz repetition rate with a pulse width of 2.08 µs. It is a fine SA for the use of pulsed-laser production using all-fiber laser due to fabrication simplicity and great optical, thermophysical, and mechanical qualities.     

Graphene oxide-coated microbottle resonators for relative humidity sensing

Graphene oxide (GO) is a 2D coating material used to improve fiber optics sensors’ response to relative humidity. Microbottle resonators (MBRs) have garnered more attention as sensing media structures. An MBR with a 190 µm diameter was coated with GO. Then, tapered fiber light coupling was used to investigate the relative humidity sensing performance in the range of 35—70%RH at 25 °C. The MBR showed a higher Q factor before and after GO coating. The sensitivity of 0.115 dB/%RH was recorded with the 190 µm GO-coated MBR sample compared to a sensitivity of 0.022 dB/%RH for the uncoated MBR sample. These results show that the MBR can be used in fiber optic sensing applications for environmental sensing.     

The effect of surface modification on the cathodic disbondment rate of epoxy and alkyd coatings

Surface modification of carbon steel substrates using appropriate functionalised silanes was carried out to investigate their effect on the dry and wet adhesion strength, and the cathodic disbondment rate, of coating binders based on epoxy and alkyd chemistries. Results show that pre-treatment of the steel substrate with 3-glycidoxypropyltrimethoxy silane (3-GPS) enhanced the dry and wet adhesion of an epoxy-based coating. Similarly, pre-treatment with 3-aminopropyltriethoxy silane (3-APS) enhanced the dry and wet adhesion of alkyd-based systems. However, although pre-treatment with 3-GPS reduced the cathodic disbondment rate for epoxy by a factor of 3, no effect on the disbondment rate for alkyd-based binders on substrates pre-treated with 3-APS was found. This strongly suggests that cathodic disbondment of epoxy proceeds by disruption of interfacial bonds (i.e. at the binder/substrate interface) but that disbondment of alkyds proceeds by direct degradation of the binder and that the interface plays little part in the process.     

Structure of the toxaphene compound 2,5-endo,6-exo,8,9,9,10,10-octachlorobornene-2: a temperature-dependent formation of two rotamers

The irradiation of 2,2,3-exo,5-endo,6-exo,8,9,9,10,10-decachlorobornane in n-hexane at 254 nm leads to a spontaneous Cl2 elimination as the major reaction pathway. This results finally in the main product 2,5-endo,6-exo,8,9,9,10,10-octachlorobornene-2, of which the structure could be elucidated with the help of X-ray, 1H and 13C NMR, IR, and MS. Temperature-dependent 1H NMR spectroscopic investigations have shown that the -CHCl2 groups located at C1 and C7 are able to rotate slowly under normal circumstances. If such measurements, however, are exerted at low temperatures (-10 to -60 degrees C), so can be seen that two rotamers are formed due to the hindrance of the free rotation about the bonds C1-C10, C7-C8, and C7-C9, which for the first time could be revealed for a toxaphene compound. Furthermore, as all 1H NMR chlorobornane spectra known so far show only sharp and clear signals, it can be assumed that chlorobornane compounds as main toxaphene components have fixed bonds, which requires to indicate chlorine atoms within the tentacles such as "a", "b", and "c" for characterizing the correct position. Those fixed tentacles are probably the reason that many toxaphene congeners remain very stable in environmental compartments, and particularly the biotic and abiotic transformation may strongly be hindered by the inflexibility of the tentacles.     

Studies with microgels as matrices for molecular receptor and catalytic sites: stereoselectivity of copolymers of (−)-menthyl acrylate and N-methacryloyl-hydroxylamineversus chiral esters

The reactivity of 4-nitrophenyl esters has been studied against an optically active microgel copolymer containing hydroxamic acid pendant groups. Saturation phenomena are observed in the kinetics consistent with formation of a complex followed by reaction of the ester in the complexed species. The polymer discriminates between R- and S-forms of a chiral substrate in both complexing and catalytic steps. The data are consistent with the existence of chiral spaces in the microgel bead which accept the chiral substrate. The selectivity of the polymer for the chiral substrate (α ～ 2) compares favourably with that shown by conventional chiral chromatographic supports.     

The inhibition of the cathodic reduction of hypochlorite by films deposited at the cathode surface

Films, either organic or inorganic in nature, can form at electrode surfaces by naturally occurring processes or can be deliberately induced to form there. The behaviour of a deliberately formed Ca(OH)₂ film on the rate of cathodic hypochlorite reduction in an undivided brine electrolysis cell is examined. The results can be modelled in terms of electrode obscuration and the conditions for film formation and dissolution are also treated. It is shown that the latter is a self-limiting process.