One-dimensional partitioning for heterogeneous systems: Theory and practice

We study the problem of one-dimensional partitioning of nonuniform workload arrays, with optimal load balancing for heterogeneous systems. We look at two cases: chain-on-chain partitioning, where the order of the processors is specified, and chain partitioning, where processor permutation is allowed. We present polynomial time algorithms to solve the chain-on-chain partitioning problem optimally, while we prove that the chain partitioning problem is NP-complete. Our empirical studies show that our proposed exact algorithms produce substantially better results than heuristics, while solution times remain comparable.     

Wavelet domain association rules for efficient texture classification

The wavelet domain association rules method is proposed for efficient texture characterization. The concept of association rules to capture the frequently occurring local intensity variation in textures. The frequency of occurrence of these local patterns within a region is used as texture features. Since texture is basically a multi-scale phenomenon, multi-resolution approaches such as wavelets, are expected to perform efficiently for texture analysis. Thus, this study proposes a new algorithm which uses the wavelet domain association rules for texture classification. Essentially, this work is an extension version of an early work of the Rushing et al. [10], [11], where the generation of intensity domain association rules generation was proposed for efficient texture characterization. The wavelet domain and the intensity domain (gray scale) association rules were generated for performance comparison purposes. As a result, Rushing et al. [10], [11] demonstrated that intensity domain association rules performs much more accurate results than those of the methods which were compared in the Rushing et al. work. Moreover, the performed experimental studies showed the effectiveness of the wavelet domain association rules than the intensity domain association rules for texture classification problem. The overall success rate is about 97%.     

Hypergraph Models and Algorithms for Data-Pattern-Based Clustering

In traditional approaches for clustering market basket type data, relations among transactions are modeled according to the items occurring in these transactions. However, an individual item might induce different relations in different contexts. Since such contexts might be captured by interesting patterns in the overall data, we represent each transaction as a set of patterns through modifying the conventional pattern semantics. By clustering the patterns in the dataset, we infer a clustering of the transactions represented this way. For this, we propose a novel hypergraph model to represent the relations among the patterns. Instead of a local measure that depends only on common items among patterns, we propose a global measure that is based on the cooccurences of these patterns in the overall data. The success of existing hypergraph partitioning based algorithms in other domains depends on sparsity of the hypergraph and explicit objective metrics. For this, we propose a two-phase clustering approach for the above hypergraph, which is expected to be dense. In the first phase, the vertices of the hypergraph are merged in a multilevel algorithm to obtain large number of high quality clusters. Here, we propose new quality metrics for merging decisions in hypergraph clustering specifically for this domain. In order to enable the use of existing metrics in the second phase, we introduce a vertex-to-cluster affinity concept to devise a method for constructing a sparse hypergraph based on the obtained clustering. The experiments we have performed show the effectiveness of the proposed framework.     

Active node determination for correlated data gathering in wireless sensor networks

In wireless sensor network applications where data gathered by different sensor nodes is correlated, not all sensor nodes need to be active for the wireless sensor network to be functional. Given that the sensor nodes that are selected as active form a connected wireless network, the inactive sensor nodes can be turned off. Allowing some sensor nodes to be active and some sensor nodes inactive interchangably during the lifecycle of the application helps the wireless sensor network to have a longer lifetime. The problem of determining a set of active sensor nodes in a correlated data environment for a fully operational wireless sensor network can be formulated as an instance of the connected correlation-dominating set problem. In this work, our contribution is twofold; we propose an effective and runtime-efficient iterative improvement heuristic to solve the active sensor node determination problem, and a benefit function that aims to minimize the number of active sensor nodes while maximizing the residual energy levels of the selected active sensor nodes. Extensive simulations we performed show that the proposed approach achieves a good performance in terms of both network lifetime and runtime efficiency.     

All-pole biquadratic filter realization with the minimum ripple due to parameter variations

In this work, the minimization of the ripple in the relative change of the transfer function amplitude due to parameter variations is studied for the signal-flow graph of the state equations realizing all-pole second-order transfer function. First the measure for the ripple is defined and then branch transmittances minimizing the measure are found. the results obtained in this study can be used in all-pole active filter realizations with the minimum ripple measure.     

Simultaneous enantioseparation and tandem UV-MS detection of eight beta-blockers in micellar electrokinetic chromatography using a chiral molecular micelle

The feasibility of using a new and more versatile polymeric chiral surfactant, i.e., poly(sodium N-undecenoxy carbonyl-L-leucinate (poly-L-SUCL) is investigated for simultaneous enantioseparation and detection of eight structurally similar beta-blockers with tandem UV and MS detection. Three optimization approaches, i.e., direct infusion-MS, capillary zone electrophoresis-MS, and chiral micellar electrokinetic chromatography-mass spectrometry (CMEKC-MS), were investigated to optimize sheath liquid parameters, spray chamber parameters, and CMEKC separation parameters for maximum sensitivity and chiral resolution. Compared to unpolymerized micelle of L-SUCL, the use of micelle polymer (i.e., poly-L-SUCL) provided significantly higher separation efficiency, lower separation current, and higher detection sensitivity for CMEKC-ESI-MS of beta-blockers. It was also observed that, unlike monomeric L-SUCL, polymeric L-SUCL provided enantioseparation of all beta-blockers even at the lowest surfactant concentration (i.e., 5 mM poly-L-SUCL). Under optimum CMEKC and ESI-MS conditions (15 mM poly-L-SUCL, 25 mM each of NH4OAc and TEA (pH 8.0); 80% (v/v) methanol sheath liquid containing 40 mM NH4OAc (pH 8.0); sheath liquid flow rate, 5.0 microL/min; drying gas flow rate, 5 L/min; drying gas temperature, 200 degrees C; nebulizing pressure, 6 psi (0.414 bar); capillary voltage, +2.5 kV; fragmentor voltage, 85 V), baseline enantioseparation of eight beta-blockers was achieved by tandem UV (in approximately 30 min) and MS (in approximately 60 min) detection. Calibration curves for all beta-blockers were linear in the range of 0.01-0.6 mM for both CMEKC-UV and CMEKC-MS methods, but the later method provided better concentration limit of detection with similar RSD for migration time and peak areas. The CMEKC-ESI-MS method appears suitable for use as a routine procedure for high-throughput separation of beta-blockers with high sensitivity.     

Heavy metal levels in leafy vegetables and some selected fruits

The aim of this study was to determine the levels of Cu, Zn, Fe, Pb and Cd in various fruits (tomato, cherry, grape, strawberry) and vegetables (parsley, onion, lettuce, garlic, nettle, peppermint, rocket, spinach, dill, broad bean, chard, purslane, grapevine leaves) grown in Manisa region. Flame and Graphite Furnace Atomic absorption spectrometry was used to estimate and evaluate the levels of these metals. Detected levels ranged from 0.56 to 329.7, 0.01 to 5.67, 0.26 to 30.68, 0.001 to 0.97 and 0 to 0.06 μg/g for Fe, Cu, Zn, Pb and Cd, respectively. While the highest mean levels of Cu and Zn were detected in grapevine leaves, the lowest mean levels of Fe and Pb were detected in nettle. Cd was not detected in most of the fruits and vegetables studied. The estimated daily intakes of Cu, Zn, Fe, Pb and Cd through fruits and vegetables were found to be below the maximum tolerable levels recommended by FAO/WHO. The element concentrations of fruits and vegetables analyzed in this study were within safety baseline levels for human consumption.     

Torque calculation between circular coils with inclined axes in air

In this paper we derive new semi‐analytical expressions for calculating the electromagnetic torque between inclined circular coils in air. The torque calculation has been obtained from the corresponding mutual inductance between inclined circular coils using the filament method. The coils of rectangular cross‐section whose centers are at the same and the different axes have been considered. From this general case it is possible to calculate the torque between all possible coil combinations either with rectangular or neglected cross‐section. Results obtained by the presented approach are in very good agreement with already published data. This method can be used for industrial electromagnetic devices such as torque sensors, transducers and torque‐measuring devices. Copyright © 2010 John Wiley & Sons, Ltd.     

Determination of Antioxidant Properties of Fruit Juice by Partial Least Squares and Principal Component Regression

The multivariate calibration methods—principal component regression and partial least squares—were employed for the prediction of antioxidant capacities of fruit juices. High-performance liquid chromatography and spectrophotometric approaches were used to determine the antioxidant capacities of fruit juices. The importance of calibration design was investigated by calculating the prediction and validation errors. The influences of using independent validation sets were emphasized. Calibration design is shown to have major effect on principal component regression and partial least squares errors. The models developed on the basis of the mean-centered data were able to predict the total antioxidant activity with a precision comparable to that of the reference [2,2-azino-di-(3-ethylbenzothialozine-sulfonic acid)] method. The partial least squares model seems preferable because of its predictive and describing abilities and good interpretability of the contribution of compounds to the antioxidant capacity. The contribution of individual phenolic compounds to the antioxidant capacity was identified by high-performance liquid chromatography.     

Mechanical performance of resol type phenolic resin/layered silicate nanocomposites

Clay addition has been shown to affect polymer resins positively in terms of several physical and chemical properties, including mechanical performance, high temperature endurance and durability. These increases are limited only to relatively low concentrations of reinforcement phase, but at these low concentrations polymer/layered silicate nanocomposites (P/LS NC) have shown to exhibit higher mechanical performance than fiber reinforced polymer composites. This is among the several reasons that make P/LS NC's one of the most widely studied class of materials today. In this study, the mechanical performance of resol type phenolic resin/layered silicate nanocomposite specimens was examined by carrying out 3‐point bending, Charpy impact and fracture toughness tests to couple the observations, microstructural analysis is done through X‐ray diffraction and scanning electron microscopy. The effects of especially three factors; cure method, clay amount, and clay modification were investigated. It was concluded that highest mechanical performance was obtained by the acid curing of the phenolic resin with very low amounts (e.g., 0.5%) of either very hydrophobic or very hydrophilic Na‐montmorillonite clay additions. Improvements as high as 7% in flexural strength, 11% in flexural strain at break, 16% in Charpy impact strength, and 66% in fracture toughness values were obtained. POLYM. COMPOS., 2009. © 2008 Society of Plastics Engineers