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Yayın The composition of acids in bitumen and in products from saponification of kerogen: Investigation of their role as connecting kerogen and mineral matrix(Elsevier Science BV, 2008-11-03) Razvigorova, Maria; Budinova, Temenuzhka K.; Tsyntsarski, Boyko G.; Petrova, Bilyana N.; Ekinci, Ekrem; Atakül, HüsnüIn order to obtain more information and to understand the nature of relation between organic and mineral matter in oil shales, the compositions of soluble bitumen fractions obtained by extraction from Bulgarian oil shales before and after demineralization with 10% HCl, concentrated HE and a HF/HCl mixture were investigated. The four extracts were quantitatively examined by IR and H-1 NMR spectroscopy. The investigation of isolated acidic material of the bitumen fractions showed that the fatty acids are present in bitumen fractions as free acids, esters and salts. The amount of free acids in bitumen is very small. The dominant part of bitumen acids is associated with mineral components of the oil shales as well as part of them is included in the mineral matrix, and can be separated only after deep demineralization. The kerogen of the oil shales, obtained after separation of the bitumen fractions and mineral components, was subjected to saponification in order to determine the amount of acids, bound as esters to the kerogen matrix. The major components found were n-carboxylic, alpha,omega,-di-carboxylic, and aromatic acids. The connection of kerogen with mineral components is accomplished by the participation of carboxylic and complicated ester bonds. Experimental data for the composition of bitumen acids give evidence that algae and terrestrial materials are initial sources in the formation of soluble organic matter of Bulgarian oil shale.Yayın Unsupervised textile defect detection using convolutional neural networks(Elsevier Ltd, 2021-12) Koulali, Imane; Eskil, Mustafa TanerIn this study, we propose a novel motif-based approach for unsupervised textile anomaly detection that combines the benefits of traditional convolutional neural networks with those of an unsupervised learning paradigm. It consists of five main steps: preprocessing, automatic pattern period extraction, patch extraction, features selection and anomaly detection. This proposed approach uses a new dynamic and heuristic method for feature selection which avoids the drawbacks of initialization of the number of filters (neurons) and their weights, and those of the backpropagation mechanism such as the vanishing gradients, which are common practice in the state-of-the-art methods. The design and training of the network are performed in a dynamic and input domain-based manner and, thus, no ad-hoc configurations are required. Before building the model, only the number of layers and the stride are defined. We do not initialize the weights randomly nor do we define the filter size or number of filters as conventionally done in CNN-based approaches. This reduces effort and time spent on hyper-parameter initialization and fine-tuning. Only one defect-free sample is required for training and no further labeled data is needed. The trained network is then used to detect anomalies on defective fabric samples. We demonstrate the effectiveness of our approach on the Patterned Fabrics benchmark dataset. Our algorithm yields reliable and competitive results (on recall, precision, accuracy and f1-measure) compared to state-of-the-art unsupervised approaches, in less time, with efficient training in a single epoch and a lower computational cost.Yayın Work and heat value of bound entanglement(Springer, 2019-12) Tuncer, Aslı; Izadyari, Mohsen; Müstecaplıoğlu, Özgür Esat; Özaydın, Fatih; Daǧ, Ceren B.Entanglement has recently been recognized as an energy resource which can outperform classical resources if decoherence is relatively low. Multi-atom entangled states can mutate irreversibly to so-called bound entangled (BE) states under noise. Resource value of BE states in information applications has been under critical study, and a few cases where they can be useful have been identified. We explore the energetic value of typical BE states. Maximal work extraction is determined in terms of ergotropy. Since the BE states are nonthermal, extracting heat from them is less obvious. We compare single and repeated interaction schemes to operationally define and harvest heat from BE states. BE and free entangled (FE) states are compared in terms of their ergotropy and maximal heat values. Distinct roles of distillability in work and heat values of FE and BE states are pointed out. Decoherence effects in dynamics of ergotropy and mutation of FE states into BE states are examined to clarify significance of the work value of BE states. Thermometry of distillability of entanglement using micromaser cavity is proposed.
