Monitoring deterioration of waffle cooler thickness at Polokwane Smelter

Cooling elements in operating furnaces, such as waffle coolers, finger coolers, cooling staves, and plate coolers, are subject to wearing and deterioration over time. Ultrasonic (UT) pulse echo is an efficient nondestructive testing methodology to monitor the thickness and quality of the cooling blocks through periodical inspections; however, the highly dampening properties of copper and the high temperatures on the hot face of the cooling elements could cause errors in UT thickness measurements. To eliminate potential errors in UT measurements, a study was conducted to determine the correct temperature and velocity distributions and relationship in waffle coolers. In this study, a combination of mathematical modeling and experimental work was used to establish a relationship between the temperature and the speed of ultrasonic waves in copper elements.     

A model-based method for computation of correlation dimension,Lyapunov exponents and synchronization from depth-EEG signals

In order to predict epileptic seizures many precursory features, extracted from the EEG signals, have been introduced. Before checking out the performance of features in detection of pre-seizure state, it is required to see whether these features are accurately extracted. Evaluation of feature estimation methods has been less considered, mainly due to the lack of a ground truth for the real EEG signals’ features. In this paper, some simulated long-term depth-EEG signals, with known state spaces, are generated via a realistic neural mass model with physiological parameters. Thanks to the known ground truth of these synthetic signals, they are suitable for evaluating different algorithms used to extract the features. It is shown that conventional methods of estimating correlation dimension, the largest Lyapunov exponent, and phase coherence have non-negligible errors. Then, a parameter identification-based method is introduced for estimating the features, which leads to better estimation results for synthetic signals. It is shown that the neural mass model is able to reproduce real depth-EEG signals accurately; thus, assuming this model underlying real depth-EEG signals, can improve the accuracy of features’ estimation.     

Chromium supplementation and substitution of barley grain with corn: Effects on performance and lactation in periparturient dairy cows

Thirty-two multiparous Holstein cows were used to investigate the effects of chromium-l-methionine (Cr-Met) supplementation and dietary grain source on performance and lactation during the periparturient period. Cows were fed a total mixed ration consisting of either a barley-based diet (BBD) or a corn-based diet (CBD) from 21 d before anticipated calving through 28 d after calving. The Cr-Met was supplemented at dosages of 0 or 0.08 mg of Cr/kg of metabolic body weight. The study was designed as a randomized complete block design with 2 (Cr-Met levels) × 2 (grain sources) factorial arrangement. There was no Cr effect on prepartum dry matter intake (DMI) or postpartum DMI, body weight (BW), net energy balance, and whole tract apparent digestibility of nutrients. Prepartum DMI as a percentage of BW tended to increase with Cr-Met. Supplemental Cr-Met tended to increase milk yield whereas milk protein percentage decreased. Pre- and postpartum DMI, BW, net energy balance, milk yield, and milk composition were not affected by substituting ground barley with ground corn. The addition of Cr-Met increased prepartum DMI and tended to increase postpartum DMI of the BBD but not the CBD. The change in prepartum DMI was smaller when the BBD was supplemented with Cr-Met but remained unchanged when the CBD was supplemented with Cr-Met. Yields of crude protein and total solids in milk and prepartum digestibility of DM and organic matter tended to increase when Cr-Met was added to the BBD but remained unchanged when added to the CBD. Periparturient cows failed to respond to the grain source of the diet, whereas they showed greater response in milk yield to diets supplemented with Cr-Met. In conclusion, the present results demonstrate that the beneficial effect of Cr-Met supplementation during the periparturient period to improve feed intake may depend on the grain source of the diet.     

Investigation of Lifting-Based Hardware Architectures for Discrete Wavelet Transform

This paper investigates efficient hardware architectures for implementation of 1-D and 2-D discrete wavelet transforms (DWTs). The architectures are based on the lifting scheme. We propose a general structure to minimize the number of multipliers and adders for 1-D DWTs. Compared to previous conventional architectures, the architecture presented here is more efficient in terms of the required arithmetic units. Moreover, we describe a new frame scan method for a block-based 2-D DWT structure which provides a flexible trade-off between the required internal memory size and external memory access. In contrast, other 2-D DWT structures require a fixed memory size.     

Immobilization of organophosphorus hydrolase enzyme by covalent attachment on modified cellulose microfibers using different chemical activation strategies: Characterization and stability studies

The plant cellulose powder was activated by two different methods using 1,4-butanediol diglycidyl ether(BTDE)and 1,1′-Carbonyldiimidazole(CDI) as the chemical coupling agents.Organophosphorus hydrolase(OPH) from Flavobacterium ATCC 27551 was immobilized on any of activated support through covalent bonding.The optimal conditions of affecting parameters on enzyme immobilization in both methods were found, and it was demonstrated that the highest activity yields of immobilized OPH onto epoxy and CDI treated cellulose were 68.32%and 73.51%, respectively.The surface treatment of cellulose via covalent coupling with BTDE and CDI agents was proved by FTIR analysis.The kinetic constants of the free and immobilized enzymes were determined, and it was showed that both immobilization techniques moderately increased the Kmvalue of the free OPH.The improvements in storage and thermal stability were investigated and depicted that the half-life of immobilized OPH over the surface of epoxy modified cellulose had a better growth compared to the free and immobilized enzymes onto CDI treated support.Also, the pH stability of the immobilized preparations was enhanced relative to the free counterpart and revealed that all enzyme samples would have the same optimum pH value for stability at 9.0.Additionally, the immobilized OPH onto epoxy and CDI activated cellulose retained about 59% and 68% of their initial activity after ten turns of batch operation, respectively.The results demonstrated the high performance of OPH enzyme in immobilized state onto an inexpensive support with the potential of industrial applications.     

How Fast Is the k-Means Method?

We present polynomial upper and lower bounds on the number of iterations performed by the k-means method (a.k.a. Lloyds method) for k-means clustering. Our upper bounds are polynomial in the number of points, number of clusters, and the spread of the point set. We also present a lower bound, showing that in the worst case the k-means heuristic needs to perform (n) iterations, for n points on the real line and two centers. Surprisingly, the spread of the point set in this construction is polynomial. This is the first construction showing that the k-means heuristic requires more than a polylogarithmic number of iterations. Furthermore, we present two alternative algorithms, with guaranteed performance, which are simple variants of the k-means method. Results of our experimental studies on these algorithms are also presented.     

A genetic framework using contextual knowledge for segmentation and recognition of handwritten numeral strings

For the first time, a genetic framework using contextual knowledge is proposed for segmentation and recognition of unconstrained handwritten numeral strings. New algorithms have been developed to locate feature points on the string image, and to generate possible segmentation hypotheses. A genetic representation scheme is utilized to show the space of all segmentation hypotheses (chromosomes). For the evaluation of segmentation hypotheses, a novel evaluation scheme is introduced, in order to improve the outlier resistance of the system. Our genetic algorithm tries to search and evolve the population of segmentation hypotheses, and to find the one with the highest segmentation/recognition confidence. The NIST NSTRING SD19 and CENPARMI databases were used to evaluate the performance of our proposed method. Our experiments showed that proper use of contextual knowledge in segmentation, evaluation and search greatly improves the overall performance of the system. On average, our system was able to obtain correct recognition rates of 95.28% and 96.42% on handwritten numeral strings using neural network and support vector classifiers, respectively. These results compare favorably with the ones reported in the literature.     

Reliability of answers to queries in relational databases

The author studies the problem of determining the reliability of answers to queries in a relational database system, where the information in the database comes from various sources with varying degrees of reliability. An extended relational model is proposed in which each tuple in a relation is associated with an information source vector which identifies the information source(s) that contributed to that tuple. The author shows how relational algebra operations can be extended, and implemented using information source vectors, to calculate the vector corresponding to each tuple in the answer to a query, and hence, to identify information source(s) contributing to each tuple in the answer. This also enables the database system to calculate the reliability of each tuple in the answer to a query as a function of the reliability of information sources     

Logic programs with exceptions

We extend logic programming to deal with default reasoning by allowing the explicit representation of exceptions in addition to general rules. To formalise this extension, we modify the answer set semantics of Gelfond and Lifschitz, which allows both classical negation and negation as failure. We also propose a transformation which eliminates exceptions by using negation by failure. The transformed program can be implemented by standard logic programming methods, such as SLDNF. The explicit representation of rules and exceptions has the virtue of greater naturalness of expression. The transformed program, however, is easier to implement.