Hashtag-based topic evolution in social media

The rise of online social media has led to an explosion of metadata-containing user generated content. The tracking of metadata distribution is essential to understand social media. This paper presents two statistical models that detect interpretable topics over time along with their hashtags distribution. A topic is represented by a cluster of words that frequently occur together, and a context is represented by a cluster of hashtags, i.e., the hashtag distribution. The models combine a context with a related topic by jointly modeling words with hashtags and time. Experiments with real-world datasets demonstrate that the proposed models discover topics over time with related contexts effectively.     

Replica Placement Strategies in Data Grid

Replication is a technique used in Data Grid environments that helps to reduce access latency and network bandwidth utilization. Replication also increases data availability thereby enhancing system reliability. The research addresses the problem of replication in Data Grid environment by investigating a set of highly decentralized dynamic replica placement algorithms. Replica placement algorithms are based on heuristics that consider both network latency and user requests to select the best candidate sites to place replicas. Due to dynamic nature of Grid, the candidate site holds replicas currently may not be the best sites to fetch replicas in subsequent periods. Therefore, a replica maintenance algorithm is proposed to relocate replicas to different sites if the performance metric degrades significantly. The study of our replica placement algorithms is carried out using a model of the EU Data Grid Testbed 1 [Bell et al. Comput. Appl., 17(4), 2003] sites and their associated network geometry. We validate our replica placement algorithms with total file transfer times, the number of local file accesses, and the number of remote file accesses.     

Free and forced convection boundary layer flow through a porous medium with large suction

An analytical study is made of the free and forced convection boundary layer flow past a porous medium bounded by a semi-infinite vertical porous plate. Locally similar solutions are then obtained by a perturbation method for large suction. Solutions for the velocity and temperature distributions are shown graphically for various suction velocities and values of the driving parameter G_r/R, where G_r is the Grashof number and R_e is the Reynolds number. The corresponding values of the skin friction coefficient and the Nusselt number are finally shown in tabular form.     

Multiple expert classification: a new methodology for parallel decision fusion

Abstract. A new parallel hybrid decision fusion methodology is proposed. It is demonstrated that existing parallel multiple expert decision combination approaches can be divided into two broad categories based on the implicit decision emphasis implemented. The first category consists of methods implementing computationally intensive decision frameworks incorporating a priori information about the target task domain and the reliability of the participating experts, while the second category encompasses approaches implementing group consensus without assigning any importance to the reliability of the experts and ignoring other contextual information. The methodology proposed in this paper is a hybridisation of these two approaches and has shown significant performance enhancements in terms of higher overall recognition rates along with lower substitution rates. Detailed analysis using two different databases supports this claim. Received January 19, 1999 / Revised March 20, 2000     

GENOTOXICITY IN CHIRONOMUS KIIENSIS (CHIRONOMIDAE: DIPTERA) AFTER EXPOSURE TO POLLUTED SEDIMENTS FROM RIVERS OF NORTH PENINSULAR MALAYSIA: IMPLICATION FOR ECOTOXICOLOGICAL MONITORING

Rapid industrialization and urbanization has led to increasing input of chemical contaminants into the aquatic environment of Malaysia. Despite the threat civilization poses to the biota, there are still very few relevant studies on ecotoxicological testing of river ecosystems. To overcome this knowledge gap, we examined lethal and genotoxic effects of sediments from different rivers of the northern Malaysia against Chironomus kiiensis, a group well represented in the aquatic fauna of this region. We exposed the larvae to sediments from Selama River (SR), Permatang Rawa River (PRR) and Kilang Ubi River (KUR) at various durations (0, 6, 12, 24 and 48 h). The larval mortality was monitored, whereas DNA damage in survivors' cells was determined using the comet assay. Pollution level indexed by the amounts of heavy metals and other organic contaminants in the sediment showed progressive increases from SR to PRR to KUR. Highly polluted sediments (PRR to KUR) were detrimental to C. kiiensis larvae, most of which did not survive following exposure for long periods. DNA analyses revealed greater damages in nuclei derived from larvae maintained on polluted sediments, in particular, those from KUR. The effects on the genomic material of C. kiiensis larvae occurred in a time‐dependent manner, with damage level increasing as exposure time progressed. Our results highlight the genotoxic properties of polluted sediments. More importantly, this study showed that C. kiiensis larvae could respond to different levels of pollution with respect to exposure time. It is concluded that C. kiiensis larvae is a potential candidate for river ecotoxicological monitoring. Copyright © 2012 John Wiley & Sons, Ltd.     

Simplified Monthly Hydrology and Irrigation Water Use Model to Explore Sustainable Water Management Options in the Murray-Darling Basin

We aimed to provide whole-of-basin simulations of flows and diversions in the Murray-Darling Basin for economic and policy analysis. We describe a model based on a subdivision of the basin into 58 catchments. In each catchment, the monthly runoff, river flow and irrigation demand are modelled as lumped processes. This is the first single model of the whole of the Murray-Darling Basin. The model was calibrated using monthly flow and annual diversion records, both by trial and error and using an automated method. We use the model to examine the impact on the flow and diversions in the Murray-Darling Basin of proposed diversion reductions and climate change. The diversion reductions return water to the environment, increasing river flows below the main irrigation areas. However, a middle-of-the-range climate change projection may result in a 13 % decrease in total flows in 2030, which offsets the enhancement to flows gained by diversion reductions.     

Implications to stormwater management as a result of lot scale rainwater tank systems: a case study in Western Sydney, Australia

Rainwater tanks are increasingly adopted in Australia to reduce potable water demand and are perceived to reduce the volume of stormwater discharge from developments. This paper investigates the water balance of rainwater tanks, in particular the possible impacts these tanks could have in controlling the stormwater discharge volume. The study collected water quantity data from two sites in the Hawkesbury City Council area, New South Wales, Australia and utilised the collected data in a simple water balance model to assess the effectiveness of rainwater tanks in reducing the stormwater discharge volume. The results indicate that a significant reduction in discharge volume from a lot scale development can be achieved if the rainwater tank is connected to multiple end-uses, but is minimal when using irrigation alone. In addition, the commonly used volumetric runoff coefficient of 0.9 was found to over-estimate the runoff from the roof areas and to thereby under-estimate the available volume within the rainwater tanks for retention or detention. Also, sole reliance on the water in the rainwater tanks can make the users aware of their water use pattern and water availability, resulting in significant reductions in water use as the supply dwindles, through self-imposed water restrictions.     

A new external sorting algorithm with no additional disk space

This paper is concerned with an external sorting algorithm with no additional disk space. The proposed algorithm is a hybrid one that uses Quicksort and special merging process in two distinct phases. The algorithm excels in sorting a huge file, which is many times larger than the available memory of the computer. This algorithm creates no extra backup file for manipulating huge records. For this, the algorithm saves huge disk space, which is needed to hold the large file. Also our algorithm switches to special merging process after the first phase that uses Quicksort. This reduces the time complexity and makes the algorithm faster.     

Adaptive sliding mode approach for learning in a feedforward neural network

An adaptive learning algorithm is proposed for a feedforward neural network. The design principle is based on the sliding mode concept. Unlike the existing algorithms, the adaptive learning algorithm developed does not require a prioriknowledge of upper bounds of bounded signals. The convergence of the algorithm is established and conditions given. Simulations are presented to show the effectiveness of the algorithm.