Experience with model-based performance, reliability, and adaptability assessment of a complex industrial architecture

In this paper, we report on our experience with the application of validated models to assess performance, reliability, and adaptability of a complex mission critical system that is being developed to dynamically monitor and control the position of an oil-drilling platform. We present real-time modeling results that show that all tasks are schedulable. We performed stochastic analysis of the distribution of task execution time as a function of the number of system interfaces. We report on the variability of task execution times for the expected system configurations. In addition, we have executed a system library for an important task inside the performance model simulator. We report on the measured algorithm convergence as a function of the number of vessel thrusters. We have also studied the system architecture adaptability by comparing the documented system architecture and the implemented source code. We report on the adaptability findings and the recommendations we were able to provide to the system’s architect. Finally, we have developed models of hardware and software reliability. We report on hardware and software reliability results based on the evaluation of the system architecture.     

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%.     

Volatilization of hydrogen sulfide from a quiescent surface

Air-water mass transfer of hydrogen sulfide from a shallow tank with a quiescent surface under the influence of weak wind stress on the water surface was studied numerically using a two-dimensional model. The flow field in the tank was investigated using a computational code based on a finite volume, which is used to numerically solve momentum, mass and continuity conservation equations. The results show that water phase flow field is strongly dependent on the wind-induced surface velocity and the aspect ratio of the tank. Based on the numerical study, the liquid-side mass transfer coefficient is correlated with Reynolds number (R(e)), tank aspect ratio (AR) and Schmidt number (S(c)). Overall mass transfer coefficient (K(L)) values extend further downstream as the R(e) number increases.     

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.     

Adsorption of lead and copper on bentonite and grapeseed activated carbon in single- and binary-ion systems

In this study, bentonite originating from Turkey (Eski?ehir province) and activated carbon obtained from grapeseed were used as adsorbents for the removal of lead (Pb²⁺) and copper (Cu²⁺) ions from aqueous solutions. Experiments were performed in single- and binary-ion systems at constant temperature of 298 K and pH value of 5. In order to describe the adsorption mechanism Langmuir, Freundlich and Temkin isotherms were used. The total adsorption capacity values of adsorbents were compared. It was observed that the total adsorption capacity values were changed depending on the type of adsorbent used, type of metal ion and interaction between metal ions.     

Untersuchungen zum Transfer pharmakologisch wirksamer Substanzen aus der Nutztierhaltung in Porree und Weißkohl

Investigation on the transfer of pharmacologically active substances used in animal husbandry into leek and cabbage. The potential of leek and cabbage for uptake of highly prescribed veterinary drugs (antibiotics) was tested in hydroponically grown plants. For this purpose the antibiotics sulfadiazine (SFD), enrofloxacine (ENR), tetracycline (TC), chlortetracycline (CTC) and monensine (MON) were chosen. A further aim was to gain data on the situation of vegetables grown in agricultural practise with regard to antibiotic residues. The evident effects of the antibiotics on plants grown hydroponically (each antibiotic was administered at 5 μmol/l nutrient solution) were greatly different: With regard to leek there were no visible effects (MON, SFD), a weak bleaching of the younger leaf sections (CTC), and strong effects of ENR. The (phytotoxic) effects of antibiotics on cabbage were much more distinct. CTC caused a yellowing of the plant vasculature in cabbage. MON induced lesions on some leaves and finally led to leaf wilting. With administration of ENR a nearly complete bleaching of young leaves was observed. Using LC-MS/MS-methods (low-resolution and high-resolution MS) the administered antibiotics, as well as conversion products and metabolites, were separately identified and quantified in various organs of leek (roots, young and old sections of leaves) and cabbage (roots, stalks, young and old leaves). Depending on the type of antibiotic, vegetable species, and plant organ, the detected concentrations of antibiotic residues comprised several orders of magnitude ranging from μg/kg to mg/kg of fresh weight (fw). The highest concentrations of antibiotics were found in roots of both vegetable species: CTC and TC were detected at approximately 10 mg/kg fw in cabbage roots and at approximately 20 mg/kg fw in leek roots and ENR was determined at approximately 12 mg/kg fw in cabbage roots. Low amounts of ENR were metabolised to ciprofloxacine (CIP). ENR occurred at similar concentrations of approximately 7 mg/kg fw in roots and old leaves of cabbage, indicating a high transport rate of this antibiotic in the cabbage plant. In stalks, young and old leaves of cabbage and in young and old leaf sections of leek all administered antibiotics were detected. Within these antibiotics, ENR and CTC and their conversion products, e. g. demeclocycline (DMC) and TC, occurred at the highest concentrations. SFD and MON were found in considerably lower concentrations (<100 μg/kg fw). The results of our experiments in hydroponic cultures, using defined concentrations of antibiotics in the nutrient solution, evidently demonstrate that cabbage and leek have a very high potential for uptake of a number of veterinary antibiotic drugs, especially for tetracycline and ENR.     

COUPLED OPTIMIZATION IN STEADY-STATE THERMOELASTICITY

Necessary optimaliry conditions for a static optimization problem in thermoelasticity are derived by calculus of variations. Optimal boundary heat fluxes and surface tractions are then found by means of a numerical method of solution that utilizes the finite-element and conjugate-gradient methods. It is found that the coefficient of linear thermal expansion of the solid body serves as the coupling parameter, affecting the optimal temperature as well as the displacement fields, a property which is not seen in a classical analysis of steady-state thermoelasticity.     

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.