A self‐correction technique for real‐time simulation of regulated rivers

An automatic self‐correction scheme is presented for online adjustment of stream‐flow forecasts during simulation of river systems with regulating structures, when actual flow data for interior points are available in real time. Another scheme is presented which allows for the modelling of channel losses due to physical effects such as evapotranspiration, bank storage and diversions. A previously developed river simulation/reservoir management model has been modified to include both schemes. The model is particularly useful for real‐time, short‐term flood forecasting and reservoir operation. The model application is made to the Lower Colorado River in Texas.     

Aromatic products of 340 °C supercritical-toluene extraction of two Turkish lignites: an n.m.r. study

Fractions of Elbistan and Seyitomer (Turkish) lignites, extracted with supercritical toluene at 340 °C and 8 MPa, have been separated by solvent extraction and silica-gel chromatography. Analyses by n.m.r. and i.r. spectroscopies and other methods have been combined in structural-analysis schemes to yield information about the average molecule in aromatic extracts. Carbon aromaticities, f_a, derived from 22.63 MHz ¹H-decoupled pulse Fourier-transform (PFT) ¹³C-n.m.r. are more widely spread for Elbistan (0.34–0.56) than for Seyitomer (0.40–0.43), and are lower than for supercritical-gas (SCG) products from bituminous coals. ¹³C-n.m.r. also reveals the presence of aromatic ether-O in polar fractions. Narrow aromatic signals in 100 MHz ¹H-n.m.r. spectra suggest the presence of single-aromatic-ring average structures. In the hexane-soluble aromatics, 27% (Elbistan) and 29% (Seyitomer) of the available sites are substituted by alkyI groups, some of which are at least eight carbon atoms long; the hexane-soluble polar and asphaltene/asphaltol fractions contain fewer such groups.     

Trans FA and solid fat contents of margarines marketed in Turkey

Trans FA (TFA), solid fat contents (SFC), and slip melting points of 12 different tub and stick margarines marketed in Turkey were examined in this study. No trans isomers were found in four margarines, which suggests they were formulated from interesterified or blended fats and oils. The products with no TFA generally had more short-chain saturated FA, which suggests coconut oil-based oil components. TFA content of the other 10 products varied from 7.7 to 37.8%. Compared to the products formulated in North America, Turkish margarines contain more TFA and have higher SFC.     

A two-phase variable neighbourhood search algorithm for assembly line worker assignment and balancing problem type-II: an industrial case study

The assembly line worker assignment and balancing problem type-II (ALWABP-2) occurs when workers and tasks (where task times depend on workers’ skills) are to be simultaneously assigned to a fixed number of workstations with the goal of minimising the cycle time. In this study, a two-phase variable neighbourhood search (VNS) algorithm is proposed to solve the ALWABP-2 due to the NP-hard nature of this problem. In the first phase of the algorithm, a VNS approach is applied to assign tasks to workstations with the aim of minimising the cycle time while in the second phase, a variable neighbourhood descent method is applied to assign workers to workstations. The performance of the proposed algorithm is tested on well-known benchmark instances. In addition, the proposed algorithm has been used to solve a real case study from a consumer electronics company that manufactures LCD TVs. The results show that the algorithm is superior to the methods reported in the literature in terms of its higher efficiency and robustness. Furthermore, the algorithm is easy to implement and significantly improves the performance of the final assembly line for the investigated LCD TV real case study.     

Eigenclassifiers for combining correlated classifiers

In practice, classifiers in an ensemble are not independent. This paper is the continuation of our previous work on ensemble subset selection [A. Ula?, M. Semerci, O.T. Y?ld?z, E. Alpayd?n, Incremental construction of classifier and discriminant ensembles, Information Sciences, 179 (9) (2009) 1298–1318] and has two parts: first, we investigate the effect of four factors on correlation: (i) algorithms used for training, (ii) hyperparameters of the algorithms, (iii) resampled training sets, (iv) input feature subsets. Simulations using 14 classifiers on 38 data sets indicate that hyperparameters and overlapping training sets have higher effect on positive correlation than features and algorithms. Second, we propose postprocessing before fusing using principal component analysis (PCA) to form uncorrelated eigenclassifiers from a set of correlated experts. Combining the information from all classifiers may be better than subset selection where some base classifiers are pruned before combination, because using all allows redundancy.     

Cost-conscious comparison of supervised learning algorithms over multiple data sets

In the literature, there exist statistical tests to compare supervised learning algorithms on multiple data sets in terms of accuracy but they do not always generate an ordering. We propose Multi²Test, a generalization of our previous work, for ordering multiple learning algorithms on multiple data sets from “best” to “worst” where our goodness measure is composed of a prior cost term additional to generalization error. Our simulations show that Multi²Test generates orderings using pairwise tests on error and different types of cost using time and space complexity of the learning algorithms.     

Effect of a sulfonated azo dye and sulfanilic acid on nitrogen transformation processes in soil

Introduction of organic dyes into soil via wastewater and sludge applications has been of increasing concern especially in developing or under-developed countries where appropriate management strategies are scarce. Assessing the response of terrestrial ecosystems to organic dyes and estimating the inhibition concentrations will probably contribute to soil remediation studies in regions affected by the same problem. Hence, an incubation study was conducted in order to investigate the impact of a sulfonated azo dye, Reactive Black 5 (RB5) and sulfanilic acid (SA), a typical representative of aromatic sulfonated amines, on soil nitrogen transformation processes. The results apparently showed that nitrogen related processes in soil can be used as bioindicators of anthropogenic stress caused by organic dyes. It was found that urease activity, arginine ammonification rate, nitrification potential and ammonium oxidising bacteria numbers decreased by 10–20% and 7–28% in the presence of RB5 (>20 mg/kg dry soil) and SA (>8 mg/kg dry soil), respectively. Accordingly, it was concluded that organic dye pollution may restrict the nitrogen-use-efficiency of plants, thus further reducing the productivity of terrestrial ecosystems. Furthermore, the response of soil microbiota to SA suggested that inhibition effects of the organic dye may continue after the possible reduction of the parent dye to associated aromatic amines.     

REACTIONS OF METHOXY-SUBSTITUTED AROMATIC COAL MOOELS IN SUPERCRITICAL SOLVENTS

Abstract

Reactions of α- and β-methoxy naphthalene and anisole in supercritical benzene and toluene were studied at 420 °C and 3.9-4.4 MPa pressure. The decomposition of these lower rank coal related model compounds in both solvents was found to obey the first order rate law. While naphthols were present in the reaction mixture of methoxy naphthalenes, phenol and cresoles were present in that of anisole. In addition to these products, diphenyl or dibenzyl was also present in the reaction mixture of supercritical benzene or toluene, respectively. The reactions between models and solvents might be explained by free radical and intermolecular rearrangement reaction pathways.     

Global optimization method for controlling a plant

A control system that contains a generic plant has been built. Its controller parameters have been designed by using a global search algorithm for a given plant, and its performance has been evaluated for the heat control of a thermal system, and the speed control of a DC motor. This paper explains this control system with a DC motor as its plant, the speed of which is controlled by the controller.     

Dyslexic students in higher education and virtual learning environments: an exploratory study

This paper presents the results of an interview‐based study of the use of virtual learning environments (VLEs) among dyslexic students. Interviews were carried out with 12 informants who had been formally diagnosed as dyslexic. The informants were either enrolled in a university or college programme, or had graduated less than a year before the interview. The findings reveal that dyslexic students experience a number of challenges associated with VLE use, including information overload, imperfect word processing tools, inadequate search functions, and having to relate to more than one system at a time.