Link Prediction in a Weighted Network Using Support Vector Machine

Link prediction is a field under network analysis that deals with the existence or emergence of links. In this study, we investigate the effect of using weighted networks for two link prediction techniques, which are the Vector Auto Regression (VAR) technique and our proposed modified VAR that uses Support Vector Machine (SVM). Using a co-authorship network from DBLP as the dataset and the Area Under the Receiver Operating Curve (AUC-ROC) as the fitness metric, the results show that the performance of both VAR and SVM are surprisingly lower in the weighted network than in the unweighted network. In an attempt to improve the results in the weighted network, we incorporated features from the unweighted network into the features of the weighted network. This enhancement improved the performance of both VAR and SVM, but the results are still inferior to those in the unweighted networks. We identified that the true positive rate was generally lower in the weighted network, thus resulting to a lower AUC

Improving the vector auto regression technique for time-series link prediction by using support vector machine

Predicting links between the nodes of a graph has become an important Data Mining task because of its direct applications to biology, social networking, communication surveillance, and other domains. Recent literature in time-series link prediction has shown that the Vector Auto Regression (VAR) technique is one of the most accurate for this problem. In this study, we apply Support Vector Machine (SVM) to improve the VAR technique that uses an unweighted adjacency matrix along with 5 matrices: Common Neighbor (CN), Adamic-Adar (AA), Jaccard’s Coefficient (JC), Preferential Attachment (PA), and Research Allocation Index (RA). A DBLP dataset covering the years from 2003 until 2013 was collected and transformed into time-sliced graph representations. The appropriate matrices were computed from these graphs, mapped to the feature space, and then used to build baseline VAR models with lag of 2 and some corresponding SVM classifiers. Using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) as the main fitness metric, the average result of 82.04% for the VAR was improved to 84.78% with SVM. Additional experiments to handle the highly imbalanced dataset by oversampling with SMOTE and undersampling with K-means clusters, however, did not improve the average AUC-ROC of the baseline SVM

Time-Series Link Prediction Using Support Vector Machines

The prominence of social networks motivates developments in network analysis, such as link prediction, which deals with predicting the existence or emergence of links on a given network. The Vector Auto Regression (VAR) technique has been shown to be one of the best for time-series based link prediction. One VAR technique implementation uses an unweighted adjacency matrix and five additional matrices based on the similarity metrics of Common Neighbor, Adamic-Adar, Jaccard’s Coefficient, Preferential Attachment and Research Allocation Index. In our previous work, we proposed the use of the Support Vector Machines (SVM) for such prediction task, and, using the same set of matrices, we gained better results. A dataset from DBLP was used to test the performance of the VAR and SVM link prediction models for two lags. In this study, we extended the VAR and SVM models by using three, four, and five lags, and these showed that both VAR and SVM improved with more data from the lags. The VAR and SVM models achieved their highest ROC-AUC values of 84.96% and 86.32% respectively using five lags compared to lower AUC values of 84.26% and 84.98% using two lags. Moreover, we identified that improving the predictive abilities of both models is constrained by the difficulty in the prediction of new links, which we define as links that do not exist in any of the corresponding lags. Hence, we created separate VAR and SVM models for the prediction of new links. The highest ROC-AUC was still achieved by using SVM with five lags, although at a lower value of 73.85%. The significant drop in the performance of VAR and SVM predictors for the prediction of new links indicate the need for more research in this problem space. Moreover, results showed that SVM can be used as an alternative method for time-series based link prediction

Geometrical problems deducible from the first six books of Euclid, arranged and solved: to which is added an appendix containing the elements of plane trigonometry. For the use of the younger students

A collection of geometrical problems with accompanying solutions

Use of CCTV to determine road accident factors in urban areas

This paper sets out to assess whether there is a potential use for images collected through the increasingly ubiquitous use of CCTV cameras in urban areas as a means of increasing understanding of the causes of road traffic accidents. Information on causation and contributory factors is essential as a means of understanding why accidents occurred and how the occurrence of similar events may be prevented in the future. CCTV records of accidents could provide an independent perspective on an accident and have the potential to increase both the quality and quantity of information available to the safety researcher. This study focuses on an area of central Leeds in the UK and shows that an existing CCTV camera system used for urban traffic management reasons has the potential to 1 record around a quarter of the accidents which occur in the area, based on patterns of past occurrence. Most city centres in the UK will have similar camera systems set up. By the introduction of additional strategically placed cameras and replacement of existing cameras with ones dedicated to accident recording, this figure could be increased substantially. The paper also considers how effective cameras and video records will be as a means of identifying contributory factor information once an accident is recorded. The contributory factor classification used by a recently introduced system in Britain is assessed in terms of how visible each of the factors is likely to be on video and their relative frequency of occurrence. It is concluded that CCTV has a high potential to provide corroborative evidence about many of the most commonly occurring factors, and to throw further light on accident causation

The domestic and gendered context for retirement

Against a global backdrop of population and workforce ageing, successive UK governments have encouraged people to work longer and delay retirement. Debates focus mainly on factors affecting individuals’ decisions on when and how to retire. We argue that a fuller understanding of retirement can be achieved by recognizing the ways in which individuals’ expectations and behaviours reflect a complicated, dynamic set of interactions between domestic environments and gender roles, often established over a long time period, and more temporally proximate factors. Using a qualitative data set, we explore how the timing, nature and meaning of retirement and retirement planning are played out in specific domestic contexts. We conclude that future research and policies surrounding retirement need to: focus on the household, not the individual; consider retirement as an often messy and disrupted process and not a discrete event; and understand that retirement may mean very different things for women and for men

A Qualitative Study of Perceived Risk for HIV Transmission among Police Officers in Dar es Salaam, Tanzania.

Understanding people's views about HIV transmission by investigating a specific population may help to design effective HIV prevention strategies. In addition, knowing the inherent sexual practices of such a population, as well as the risky circumstances that may facilitate HIV transmission, is crucial for the said strategies to become effective. In this article, we report how police officers in Dar es Salaam, Tanzania, perceived the problem of HIV and AIDS in their local context, particularly in relation to unsafe sexual practices. The study was done with the view to recommending ways by which HIV transmission could be minimised within the police force. The study was conducted among members of the police force in Dar es Salaam, Tanzania. Eight focus group discussions (FGDs) were conducted, with a total of 66 participants who were mixed in terms of age, gender, and marital status. Some of these were caregivers to patients with AIDS. Data were analysed using the interpretive description approach. The participants believed that both individual sexual behaviour and work-related circumstances were sources of HIV infection. They also admitted that they were being tempted to engage in risky sexual practices because of the institutional rules that prohibit officers from getting married during their training and for three years after. Nevertheless, as members of the Police Force, they stressed the fact that the risky sexual behaviour that exposes them to HIV is not limited to the force; it is rather a common problem that is faced by the general population. However, they complained, the nature of their job exposes them to road accident victims, subjecting them further to possible infection, especially when they have to handle these road accident casualties without proper protective gear. Individual sexual behaviour and job-related circumstances are worth investigating if proper advice is to be given to the police regarding HIV prevention strategies. In order to improve the lives of these police officers, there is a need to review the existing institutional rules and practices to accommodate individual sexual needs. In addition, improving their working environment may minimize the risk of HIV transmission from handling casualties in emergency situations

Solid phase extraction for removal of matrix effects in lipophilic marine toxin analysis by liquid chromatography-tandem mass spectrometry

The potential of solid phase extraction (SPE) clean-up has been assessed to reduce matrix effects (signal suppression or enhancement) in the liquid chromatography-tandem mass spectrometry (LC¿MS/MS) analysis of lipophilic marine toxins. A large array of ion-exchange, silica-based, and mixed-function SPE sorbents was tested. Polymeric sorbents were found to retain most of the toxins. Optimization experiments were carried out to maximize recoveries and the effectiveness of the clean-up. In LC¿MS/MS analysis, the observed matrix effects can depend on the chromatographic conditions used, therefore, two different HPLC methods were tested, using either an acidic or an alkaline mobile phase. The recovery of the optimized SPE protocol was around 90% for all toxins studied and no break-through was observed. The matrix effects were determined by comparing signal response from toxins spiked in crude and SPE-cleaned extracts with those derived from toxins prepared in methanol. In crude extracts, all toxins suffered from matrix effects, although in varying amounts. The most serious effects were observed for okadaic acid (OA) and pectenotoxin-2 (PTX2) in the positive electrospray ionization mode (ESI+). SPE clean-up on polymeric sorbents in combination with the alkaline LC method resulted in a substantial reduction of matrix effects to less than 15% (apparent recovery between 85 and 115%) for OA, yessotoxin (YTX) in ESI¿ and azaspiracid-1 (AZA1), PTX2, 13-desmethyl spirolides C (SPX1), and gymnodimine (GYM) in ESI+. In combination with the acidic LC method, the matrix effects after SPE were also reduced but nevertheless approximately 30% of the matrix effects remained for PTX2, SPX1, and GYM in ESI+. It was concluded that SPE of methanolic shellfish extracts can be very useful for reduction of matrix effects. However, the type of LC and MS methods used is also of great importance. SPE on polymeric sorbents in combination with LC under alkaline conditions was found the most effective method

Prospects for radical emissions reduction through behaviour and lifestyle change

Over the past two decades, scholars and practitioners across the social sciences, in policy and beyond have proposed, trialled and developed a wide range of theoretical and practical approaches designed to bring about changes in behaviours and lifestyles that contribute to climate change. With the exception of the establishment of a small number of iconic behaviours such as recycling, it has however proved extremely difficult to bring about meaningful transformations in personal greenhouse gas emissions at either the individual or societal level, with multiple reviews now pointing to the limited efficacy of current approaches. We argue that the majority of approaches designed to achieve mitigation have been constrained by the need to operate within prevailing social scientific, economic and political orthodoxies which have precluded the possibility of non-marginal change. In this paper we ask what a truly radical approach to reducing personal emissions would look like from social science perspectives which challenge the unstated assumptions severely limiting action to date, and which explore new alternatives for change. We emphasise the difficulties likely to impede the instituting of genuinely radical societal change regarding climate change mitigation, whilst proposing ways that the ground could be prepared for such a transformation to take place

Experiences from the frontline : an exploration of personal advisers’ practice with claimants who have health-related needs within UK welfare-to-work provision

Recent UK welfare reforms have been less successful than expected by the Government in supporting unemployed people with long-term illness into work. Frontline workers remain a core element of the new welfare-to-work machinery, but operate within a changed organisational and policy landscape. These changes raise important questions regarding whether and how claimants’ health-related barriers to work are considered. This paper examines the UK welfare-to-work frontline worker’s role with claimants who have long-term illness. Fieldwork observations in three not for profit employment support services, and semi-structured interviews with 29 participants (claimants, frontline workers, healthcare professionals and managers) were conducted between 2011 and 2012. Participant observation of the wider welfare-to-work arena was initiated in 2009 and continued until 2013. A qualitative methodology drawing on ethnographic principles was adopted. Thematic analysis of the data was carried out. The findings show that the frontline worker plays a key role in assessing and addressing claimants’ health-related barriers to work. Two important health-related role dimensions were identified: a health promoter role which involved giving health promotional advice to claimants about their general health; and a health monitor role which involved observing and questioning claimants about their general health. Frontline workers’ practice approaches were shaped by organisational and individual factors. Integration between the National Health Service (NHS) and employment support services was limited, and the findings suggested improvements were required to ensure an adequate response to claimants’ health-related needs to support their journey into work