Optimisation of Bacillus thuringiensis var. israelensis (Vectobac) applications for the blackfly control programme on the Orange River, South Africa

The Orange River, South Africa’s largest river, is a critical water resource for the country. In spite of the clear economic benefits of regulating river flows through a series of impoundments, one of the significant undesirable ecological consequences of this regulation has been the regular outbreaks of the pest blackfly species Simulium chutteri and S. damnosum s.l. (Diptera: Simuliidae). The current control programme, carried out by the South African National Department of Agriculture, uses regular applications, by helicopter, of the target-specific bacterial larvicide Bacillus thuringiensis var. israelensis. While cost-benefit analyses show significant benefits to the control programme, benefits could potentially be further increased through applying smaller volumes of larvicide in an optimised manner, which incorporates upstream residual amounts of pesticide through downstream carry. Using an optimisation technique applied in the West African Onchocerciasis Control Programme, to a 136 km stretch of the Orange River which includes 31 blackfly breeding sites, we demonstrate that 28.5% less larvicide could be used to potentially achieve the same control of blackfly. This translates into potential annual savings of between R540 000 and R1 800 000. A comparison of larvicide volumes estimated using traditional vs. optimised approaches at different discharges, illustrates that the savings on optimisation decline linearly with increasing flow volumes. Larvicide applications at the lowest discharge considered (40 m³·s^-1) showed the greatest benefits from optimisations, with benefits remaining but decreasing to a theoretical 30% up to median flows of 100 m3·s-1. Given that almost 70% of flows in July are less than 100 m³·s^-1, we suggest that an optimised approach is appropriate for the Orange River Blackfly Control Programme, particularly for flow volumes of less than 100 m³·s^-1. We recommend that trials be undertaken over two reaches of the Orange River, one using the traditional approach, and another using the optimised approach, to test the efficacy of using optimised volumes of B.t.i.

Internet traffic clustering with constraints

Due to the limitations of the traditional port-based and payload-based traffic classification approaches, the past decade has seen extensive work on utilizing machine learning techniques to classify network traffic based on packet and flow level features. In particular, previous studies have shown that the unsupervised clustering approach is both accurate and capable of discovering previously unknown application classes. In this paper, we explore the utility of side information in the process of traffic clustering. Specifically, we focus on the flow correlation information that can be efficiently extracted from packet headers and expressed as instance-level constraints, which indicate that particular sets of flows are using the same application and thus should be put into the same cluster. To incorporate the constraints, we propose a modified constrained K-Means algorithm. A variety of real-world traffic traces are used to show that the constraints are widely available. The experimental results indicate that the constrained approach not only improves the quality of the resulted clusters, but also speeds up the convergence of the clustering process.

Breaking Boundaries : recasting the “local” newspaper as “geo-social” news in a digital landscape

This paper reconceptualises the role of the small “local” newspaper in a new media environment and argues that definitions and concepts currently used to describe and define such publications are becoming increasingly problematic as newspapers shift into both print and online formats. The paper highlights the continued importance of geography for such newspapers at a time when there is wide academic debate on the relevance of territory and boundaries and the impact of time–space compression in a new media world. It argues, however, that a focus on a newspaper’s geographic connection must also acknowledge the increasing boundlessness and openness of the social space in which a newspaper operates. Ultimately this paper suggests the concept of “geo-social” news may be a more appropriate framework for scholars to consider such publications. I draw on the work of geography scholars, and discussions around “space” and “place” to construct the notion of “geo-social” news, highlighting some exemplars of small commercial newsroom practices in Australia, the United Kingdom and Canada and discussions with newspaper editors in Australia to demonstrate the relevance of the “geo-social” concept.

Internet traffic classification using constrained clustering

Statistics-based Internet traffic classification using machine learning techniques has attracted extensive research interest lately, because of the increasing ineffectiveness of traditional port-based and payload-based approaches. In particular, unsupervised learning, that is, traffic clustering, is very important in real-life applications, where labeled training data are difficult to obtain and new patterns keep emerging. Although previous studies have applied some classic clustering algorithms such as K-Means and EM for the task, the quality of resultant traffic clusters was far from satisfactory. In order to improve the accuracy of traffic clustering, we propose a constrained clustering scheme that makes decisions with consideration of some background information in addition to the observed traffic statistics. Specifically, we make use of equivalence set constraints indicating that particular sets of flows are using the same application layer protocols, which can be efficiently inferred from packet headers according to the background knowledge of TCP/IP networking. We model the observed data and constraints using Gaussian mixture density and adapt an approximate algorithm for the maximum likelihood estimation of model parameters. Moreover, we study the effects of unsupervised feature discretization on traffic clustering by using a fundamental binning method. A number of real-world Internet traffic traces have been used in our evaluation, and the results show that the proposed approach not only improves the quality of traffic clusters in terms of overall accuracy and per-class metrics, but also speeds up the convergence.

Dominating set and network coding-based routing in wireless mesh networks

Wireless mesh networks are widely applied in many fields such as industrial controlling, environmental monitoring, and military operations. Network coding is promising technology that can improve the performance of wireless mesh networks. In particular, network coding is suitable for wireless mesh networks as the fixed backbone of wireless mesh is usually unlimited energy. However, coding collision is a severe problem affecting network performance. To avoid this, routing should be effectively designed with an optimum combination of coding opportunity and coding validity. In this paper, we propose a Connected Dominating Set (CDS)-based and Flow-oriented Coding-aware Routing (CFCR) mechanism to actively increase potential coding opportunities. Our work provides two major contributions. First, it effectively deals with the coding collision problem of flows by introducing the information conformation process, which effectively decreases the failure rate of decoding. Secondly, our routing process considers the benefit of CDS and flow coding simultaneously. Through formalized analysis of the routing parameters, CFCR can choose optimized routing with reliable transmission and small cost. Our evaluation shows CFCR has a lower packet loss ratio and higher throughput than existing methods, such as Adaptive Control of Packet Overhead in XOR Network Coding (ACPO), or Distributed Coding-Aware Routing (DCAR).

Multiple lines of evidence for the beneficial effects of environmental flows in two lowland rivers in Victoria, Australia

The aim of this study was to identify whether environmental flows released into two lowland rivers (the Glenelg and Wimmera Rivers, western Victoria, Australia) during the spring to autumn period had successfully ameliorated the negative effects of multiple human impacts. Macroinvertebrates and a range of physico-chemical variables were sampled from three reaches in each river. Both rivers were sampled during three environmental release seasons with average-sized releases (1997-1998, 1998-1999 and 2001-2002) and two drought seasons with limited releases (1999-2000 and 2000-2001). The effects of releasing average-sized environmental flows on macroinvertebrates and physico-chemical variables were assessed by comparison with data from the two drought seasons. For the Glenelg River, data from a reference season prior to the release of environmental flows (1995-1996) was also compared to data from the five environmental flow seasons. Multivariate analyses revealed four pieces of evidence indicating that the release of environmental flows effectively slowed the process of environmental degradation in the Glenelg River but not in the Wimmera River: (1) the magnitude of the river discharge was dependent on the size of environmental flow releases; (2) in the Wimmera River, water quality deteriorated markedly during the two drought seasons and correlated strongly with macroinvertebrate assemblage structure, but this was not observed in the Glenelg River; (3) the taxonomic composition of the macroinvertebrate assemblages among contrasting flow release seasons reflected the severe deterioration in water quality of the Wimmera River; (4) despite two drought seasons with minimal environmental flow releases, the macroinvertebrate assemblage in the Glenelg River did not differ from the average-release seasons, nor did it return to a pre-environmental flows condition. Therefore, it appears that environmental flow releases did sustain the macroinvertebrate assemblage and maintain reasonable water quality in the Glenelg River. However, in the Wimmera River, release volumes were too small to maintain low salinities and were associated with marked changes in the macroinvertebrate assemblage. Therefore, there are multiple lines of evidence that environmental flow releases of sufficient magnitude may slow the process of degradation in a regulated lowland river.

What determines migration flows from low-income to high-income countries? An empirical investigation of Fiji-U.S. migration 1972-2001

This article examines the long-run and short-run determinants of migration from Fiji to the United States between 1972 and 2001 using a human capital framework, which is extended to take account of political instability in Fiji. In the long-run the authors find that differences in income levels, disparities in police strength, disparities in the number of doctors, costs of moving, and political instability in Fiji are all statistically significant with the expected sign. In the short run the cost of moving, lagged migration, political instability, and differences in both police strength and medical care are the main determinants of Fiji-United States immigration.

Effect of environmental flows on deep, anoxic pools

A series of field surveys were carried out on two permanent pools of the upper Glenelg River in SW Victoria, Australia. One was representative of the wider and deeper pools while the other was representative of the more-narrow and shallower pools. Both pools showed a typical seasonal cycle of warm, brackish, oxygen-poor, summer conditions and cool, oxygen-rich, low-salinity, winter conditions. The summer salinity increases were larger than expected, suggesting possible saline groundwater inflow from unidentified springs. Both pools contained anoxic water in their deeper sections but this was permanent only in the deeper pool. A simple model of the flushing rate of such anoxic pools subject to flows, such as environmental flow releases, was developed, based on an energy balance between the potential energy required to lift the anoxic layer and the kinetic energy derived from the river flow. The results were tested against and in agreement with the field measurements. The model also suggests that the anoxic layers are resilient to all but the largest environmental flows.

Modelling immigration flows : an application of the bounds test to Fiji - Australia migration

This paper examines the long-run and short-run determinants of migration from Fiji to Australia between 1972 and 2001 using a human capital framework, which is extended to take account of political instability in Fiji. Our main findings are that in the long run the real wage differential and political instability in Fiji are the main determinants. In the short run, there is some evidence that the wage differential and transport costs are important factors, but this finding is not robust across all specifications. Lagged migration and political instability are the most important determinants in the short run.