Durability properties of concrete with blended cements

The study of chloride‐induced corrosion started more than three decades ago, after extensive cases of damage were observed on reinforced concrete structures in coastal regions and on infrastructural objects exposed to salt action. Nowadays, the basis for sustainable concrete industry lies in these three aspects: reducing CO₂ emissions by using by‐products of other industries (slag, fly ash, silica fume) for cement production, conservation of natural resources by replacing part of the aggregate with recycled construction waste, as well as use of recycled water in concrete production, and finally, construction of durable concrete structures. Durability design procedures for reinforced concrete structures in aggressive environments are still to a large extent empirical, especially in the case of using blended cements. The type of cement has a considerable effect on the properties of concrete, especially concrete resistance to the penetration of chloride ions. The paper presents results of testing durability and deformational properties of concrete produced with quaternary‐blended cement. A clearer insight into these properties is a necessary starting point for the performance‐based design of concrete prepared with blended cements, leading to more durable and corrosion‐free concrete structures in aggressive environments.     

Parkinson’s Disease tremor classification – A comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.     

A new implementation of common matrix approach using third-order tensors for face recognition

In the classical common matrix approach (CMA), the common matrix for each individual face class is obtained using basis matrices calculated by Gram–Schmidt orthogonalization of the class covariance matrix. This common matrix represents the common or invariant properties of a given face class. The CMA idea relies on the concept of basis matrices of a face class which span the, so called, difference subspace of that class. In this paper, an alternative method to obtain the basis matrices for CMA is proposed. The basis matrices are obtained using the higher order singular value decomposition (HOSVD) of a third-order tensor constructed with face images and these basis matrices are utilized in the construction of CMA. In order to exemplify the improvements in the recognition rates, face recognition experiments are carried out via the AR face database. The original face matrices, as well as 2DPCA-, 2DSVD-, and 2DFDA-based feature matrices are applied as the input matrices for the two different implementations of CMA in the experimental studies. The results indicate that the recognition rates obtained by the proposed method are slightly higher than those obtained using the basis matrices calculated by Gram–Schmidt orthogonalization.     

Comparison of hemispheric asymmetry measurements for emotional recordings from controls

Four asymmetry measurements (conventional coherence function (CCF), cross wavelet correlation (CWC), phase lag index (PLI), and mean phase coherence (MPC)) have been compared to each other for the first time in order to recognize emotional states (pleasant (P), neutral (N), unpleasant (UP)) from controls in EEG sub-bands (delta (0–4 Hz), theta (4–8 Hz), alpha (8–16 Hz), beta (16–32 Hz), gamma (32–64 Hz)) mediated by affective pictures from the International Affective Picture Archiving System (IAPS). Eight emotional features, computed as hemispheric asymmetry between eight electrode pairs (Fp1 − Fp2, F7 − F8, F3 − F4, C3 − C4, T7 − T8, P7 − P8, P3 − P4, and O1 − O2), have been classified by using data mining methods. Results show that inter-hemispheric emotional functions are mostly mediated by gamma. The best classification is provided by a neural network classifier, while the best features are provided by CWC in time-scale domain due to non-stationary nature of electroencephalographic (EEG) series. The highest asymmetry levels are provided by pleasant pictures at mostly anterio-frontal (F3 − F4) and central (C3 − C4) electrode pairs in gamma. Inter-hemispheric asymmetry levels are changed by each emotional state at all lobes. In conclusion, we can state the followings: (1) Nonlinear and wavelet transform-based methods are more suitable for characterization of EEG; (2) The highest difference in hemispheric asymmetry was observed among emotional states in gamma; (3) Cortical emotional functions are not region-specific, since all lobes are effected by emotional stimuli at different levels; and (4) Pleasant stimuli can strongly mediate the brain in comparison to unpleasant and neutral stimuli.

     

Bit Impact Factor: Towards making fair vulnerability comparison

Reliability is becoming a major design concern in contemporary microprocessors since soft error rate is increasing due to technology scaling. Therefore, design time system vulnerability estimation is of paramount importance. Architectural Vulnerability Factor (AVF) is an early vulnerability estimation methodology. However, AVF considers that the value of a bit in a clock cycle is either required for Architecturally Correct Execution (i.e. ACE-bit) or not (i.e. unACE-bit); therefore, AVF cannot distinguish the vulnerability impact level of an ACE-bit. In this study, we present a new dimension which takes into account the vulnerability impact level of a bit. We introduce Bit Impact Factor metric which, we believe, will be helpful for extending AVF evaluation to provide a more accurate vulnerability analysis.     

Effect of steam curing on class C high-volume fly ash concrete mixtures

The effect of steam curing on concrete incorporating ASTM Class C fly ash (FA), which is widely available in Turkey, was investigated. Cement was replaced with up to 70% fly ash, and concrete mixtures with 360 kg/m³ cementitious content and a constant water/binder ratio of 0.4 were made. Compressive strength of concrete, volume stability of mortar bar specimens, and setting times of pastes were investigated. Test results indicate that, under standard curing conditions, only 1-day strength of fly ash concrete was low. At later ages, the strength values of even 50% and 60% fly ash concretes were satisfactory. Steam curing accelerated the 1-day strength but the long-term strength was greatly reduced. Setting time of fly ash-cement pastes and volume stability of mortars with 50% or less fly ash content were found to be satisfactory for standard specimens. In addition, for steam curing, this properties were acceptable for all replacement ratios.     

Detecting emotional state of a child in a conversational computer game

The automatic recognition of user’s communicative style within a spoken dialog system framework, including the affective aspects, has received increased attention in the past few years. For dialog systems, it is important to know not only what was said but also how something was communicated, so that the system can engage the user in a richer and more natural interaction. This paper addresses the problem of automatically detecting “frustration”, “politeness”, and “neutral” attitudes from a child’s speech communication cues, elicited in spontaneous dialog interactions with computer characters. Several information sources such as acoustic, lexical, and contextual features, as well as, their combinations are used for this purpose. The study is based on a Wizard-of-Oz dialog corpus of 103 children, 7–14 years of age, playing a voice activated computer game. Three-way classification experiments, as well as, pairwise classification between polite vs. others and frustrated vs. others were performed. Experimental results show that lexical information has more discriminative power than acoustic and contextual cues for detection of politeness, whereas context and acoustic features perform best for frustration detection. Furthermore, the fusion of acoustic, lexical and contextual information provided significantly better classification results. Results also showed that classification performance varies with age and gender. Specifically, for the “politeness” detection task, higher classification accuracy was achieved for females and 10–11 years-olds, compared to males and other age groups, respectively.     

Calcium-sensing receptor gene polymorphisms and cardiac valvular calcification in patients with chronic renal failure: A pilot study

Cardiac valvular calcification (VC) is a frequent finding in chronic hemodialysis patients. In addition to demographic and metabolic factors, genetic susceptibility may also influence the occurrence and severity of these abnormalities and account for interindividual variability among patients. In this report, we studied the relation of calcium-sensing receptor (CaSR) gene polymorphisms to the development of VC in chronic hemodialysis patients. A total of 41 chronic hemodialysis patients (26 male, mean age 47.23 ± 11.36 years vs. 15 females, mean age 48.13 ± 14.66 years) undergoing treatment for more than 1 year were evaluated with transthoracic echocardiography. In patients with and without VC, CaSR gene polymorphisms (A990G, C1011G) were investigated by PCR, using allele-specific primers. In randomly chosen subjects, PCR analysis was verified by DNA sequencing. Cardiac valve calcification was detected in 21 patients (51.2%). Five of these patients (12.2%) had mitral valve calcification, 4 (9.75%) had aortic valve calcification, and 12 (29.27%) had both. In patients with VC, the frequency of the A/G genotype was slightly higher than those with no VC with a borderline P value (42.9% vs. 15%, χ²=3.840, P=0.050). The frequency of the C/C genotype was similar in patients with and without VC (90.5% vs. 85%, P>0.05). The results of this study are not enough to prove the role of CaSR gene polymorphisms in the development of VC. There is a need for large-scale studies on this topic.