Water quality prediction capabilities of WASP model for a tropical lake system

Water quality modelling facilitates our better understanding of the processes taking place in a lake system, and conservation plans to address them. The water quality analysis simulation programme (WASP) was used in this study to predict daily variations in water quality parameters, namely dissolved oxygen, nitrate, phosphate and chlorophyll‐a and biochemical oxygen demand concentrations in a tropical lake system. The lake was divided into eight segments with the respective morphological, environmental and flow details being model inputs. The monthly concentration of each water quality parameter also comprised model input. The model output was daily spatiotemporal variation in these parameters over a period of 476 days. This study also indicated that the occurrence of precipitation plays a major role in defining the water quality of a tropical lake. The heavy precipitation after a long gap, especially during the summer season, results in a large quantity of organic matter entering the lake through drains, thereby increasing the organic matter and phosphate in the water body, and subsequently resulting in high chlorophyll‐a concentrations in the lake. A reduced chlorophyll‐a concentration was observed during the heavy rains. The water quality fluctuations are more pronounced with precipitation, especially where polluted drains enter the lake. An improved water quality can be observed downstream, including increased dissolved oxygen and nitrate concentrations. Improved water quality was observed during the postmonsoon period, with increased salinity and dissolved oxygen concentrations, a finding that confirms generalized and specific conclusions can be achieved with the use of the WASP model.     

Bug localization using latent Dirichlet allocation

ContextSome recent static techniques for automatic bug localization have been built around modern information retrieval (IR) models such as latent semantic indexing (LSI). Latent Dirichlet allocation (LDA) is a generative statistical model that has significant advantages, in modularity and extensibility, over both LSI and probabilistic LSI (pLSI). Moreover, LDA has been shown effective in topic model based information retrieval. In this paper, we present a static LDA-based technique for automatic bug localization and evaluate its effectiveness.ObjectiveWe evaluate the accuracy and scalability of the LDA-based technique and investigate whether it is suitable for use with open-source software systems of varying size, including those developed using agile methods.MethodWe present five case studies designed to determine the accuracy and scalability of the LDA-based technique, as well as its relationships to software system size and to source code stability. The studies examine over 300 bugs across more than 25 iterations of three software systems.ResultsThe results of the studies show that the LDA-based technique maintains sufficient accuracy across all bugs in a single iteration of a software system and is scalable to a large number of bugs across multiple revisions of two software systems. The results of the studies also indicate that the accuracy of the LDA-based technique is not affected by the size of the subject software system or by the stability of its source code base.ConclusionWe conclude that an effective static technique for automatic bug localization can be built around LDA. We also conclude that there is no significant relationship between the accuracy of the LDA-based technique and the size of the subject software system or the stability of its source code base. Thus, the LDA-based technique is widely applicable.     

Water quality assessment of a tropical coastal lake system using multivariate cluster,principal component and factor analysis

Statistical techniques represent a reliable tool for classifying, modelling and interpreting surface water quality monitoring data, particularly for lakes. The complexity associated with the analysis of a large number of measured variables, however, is a major problem in water quality assessments. Multivariate analysis, such as cluster analysis and factor analysis (FA), was utilized in this study for the analysis of water quality data (including water discharges and 28 water quality parameters) for Akkulam–Veli Lake, a tropical coastal lake system in Kerala, India. This lake is partially divided into two sub‐systems, namely Veli Lake and Akkulam Lake. Akkulam Lake exhibits freshwater characteristics, in contrast to Veli Lake, which exhibits saline water characteristics because of its close proximity to the sea. Thus, studying this lake provides insights into water quality variations in both a freshwater and saline water lake in a tropical region. Water quality patterns and variations in Akkulam–Vela Lake over three seasons, including pre‐monsoon (PRM), monsoon (MON) and post‐monsoon (POM), also were studied, utilizing multivariate techniques. The organic pollution factor played a significant role on lake water quality during PRM. The influence of organic pollution tends to decrease during MON and POM, a particular situation faced by urban lakes in tropical regions. Polluted stretches in a lake system during different seasons can easily be ascertained by hierarchical cluster analysis. Further, the factors affecting a lake system as a whole, as well as for a particular sampling site, can easily be identified by FA. Improved water quality can be observed during POM. Akkulam and Vela lakes exhibit a wide variation in water quality during all seasons, a finding that corroborates a water flow obstruction from Akkulam Lake to Veli Lake because of the bund existing between the two lakes. The location of the bund is identified as the major reason for different hydrochemical processes in A–V Lake.     

Coupling metrics for ontology-based system

Measuring system coupling is a commonly accepted software engineering practice associated with producing high-quality software products. Coupling metrics traditionally measure data passed across a module interface to determine couplings between modules in a given system. XML has become common in Internet-based application domains such as business-to-business and business-to-consumer applications, and has formed a basis for service-oriented architectures such as Web services and the Semantic Web. We therefore need new coupling metrics that address these systems' unique requirements. We propose a set of coupling metrics for ontology-based systems represented in OWL: the number of external classes (NEC), reference to external classes (REC), and referenced includes (RI). To collect these metrics, we use a standard XML-based parser. This research reflects a new type of coupling measurement for system development that defines coupling metrics based on ontology data and its structure.     

Semantic software metrics computed from natural language design specifications

An approach using semantic metrics to provide insight into software quality early in the design phase of software development by automatically analysing natural language (NL) design specifications for object-oriented systems is presented. Semantic metrics are based on the meaning of software within the problem domain. In this paper, we extend semantic metrics to analyse design specifications. Since semantic metrics can now be calculated from early in design through software maintenance, they provide a consistent and seamless type of metric that can be collected through the entire lifecycle. We discuss our semMet system, an NL-based program comprehension tool we have expanded to calculate semantic metrics from design specifications. To validate semantic metrics from design specifications and to illustrate their seamless nature across the software lifecycle, we compare semantic metrics from different phases of the lifecycle, and we also compare them to syntactically oriented metrics calculated from the source code. Results indicate semantic metrics calculated from design specifications can give insight into the quality of the source code based on that design. Also, these results illustrate that semantic metrics provide a consistent and seamless type of metric that can be collected through the entire lifecycle.     

In Vitro Selection of a Single-Stranded DNA Molecular Recognition Element against Atrazine

Widespread use of the chlorotriazine herbicide, atrazine, has led to serious environmental and human health consequences. Current methods of detecting atrazine contamination are neither rapid nor cost-effective. In this work, atrazine-specific single-stranded DNA (ssDNA) molecular recognition elements (MRE) were isolated. We utilized a stringent Systematic Evolution of Ligands by Exponential Enrichment (SELEX) methodology that placed the greatest emphasis on what the MRE should not bind to. After twelve rounds of SELEX, an atrazine-specific MRE with high affinity was obtained. The equilibrium dissociation constant (K_d) of the ssDNA sequence is 0.62 ± 0.21 nM. It also has significant selectivity for atrazine over atrazine metabolites and other pesticides found in environmentally similar locations and concentrations. Furthermore, we have detected environmentally relevant atrazine concentrations in river water using this MRE. The strong affinity and selectivity of the selected atrazine-specific ssDNA validated the stringent SELEX methodology and identified a MRE that will be useful for rapid atrazine detection in environmental samples.     

Low-dispersion single-mode silica fibre with undoped core and three F-doped claddings

The refractive-index profile of an ideal single-mode silica fibre with undoped core and three F-doped claddings was optimised by calculation to realise two zeros of the chromatic dispersion at 1.30 and 1.55 ?m where the spectral loss has its local and absolute minima, respectively. The sensitivity of the chromatic dispersion due to different scale factors for the radial co-ordinate of the refractive-index profile is considered.     

Widening the usability of yttria stabilised zirconia by advanced cooling technology

The use of yttria stabilised zirconia as thermal barrier material for gas turbine applications is limited because of sintering effects within the coating at high temperatures. The sintering of the coating is accompanied by a deterioration of the mechanical properties which leads to a reduction in coating function, lifetime and reliability. Many research work is ongoing to develop new materials for thermal barrier applications with better sintering resistance. Another way to face the problem is the improvement of the gas turbine cooling technology. Because of the very good property mixture of yttria partial stabilised zirconia (low thermal conductivity, high thermal expansion, low young's modulus, established processes, availability …) this is a very promising way. Transpiration cooling shows a high potential for the temperature reduction at constant efficiency. The presentation shows some new aspects of coating technology caused by changed surface conditions of transpiration cooled surfaces as they are subject in the collaborative research center (SFB) 561 “Thermally highly loaded porous and cooled multilayer systems for combined cycle power plants”.