Career-path analysis using optimal matching and self-organizing maps

This paper is devoted to the analysis of career paths and employability. The state-of-the-art on this topic is rather poor in methodologies. Some authors propose distances well adapted to the data, but are limiting their analysis to hierarchical clustering. Other authors apply sophisticated methods, but only after paying the price of transforming the categorical data into continuous, via a factorial analysis. The latter approach has an important drawback since it makes a linear assumption on the data. We propose a new methodology, inspired from biology and adapted to career paths, combining optimal matching and self-organizing maps. A complete study on real-life data will illustrate our proposal.

Letter : anxiety score as a risk factor for radial artery vasospasm during radial interventions : a pilot study

I read with interest the article in Angiology that determined the role of anxiety level on radial artery spasm during transradial coronary angiography.1 As the importance of conducting more randomised controlled trials using anxiolytics to define the relation between anxiety and vasospasm was noted by the authors, I offer the following insights for investigators to consider when conducting such research. While previous research has already identified that moderate procedural sedation and opioid analgesia reduces the incidence of vasospasm,2 the identification of risk factors in the present study is hypothesis generating as to how outcomes might be even further improved. It is possible that selectively applying either even more intensive sedation and analgesia or complementary non-pharmacological stress-reducing therapies, such as music therapy or visualisation and attentive behaviour, to patients ‘at-risk’ of vasospasm (women and those with high levels of anxiety prior to the procedure) might lead to even better patient outcomes...

Integrating collaborative filtering and matching-based search for product recommendations

Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and, thus, help in making good decisions about which product to buy from the vast amount of product choices. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based approaches. These approaches are not directly applicable for recommending infrequently purchased products such as cars and houses as it is difficult to collect a large number of ratings data from users for such products. Many of the ecommerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user’s query are retrieved and recommended. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their interest. In this article, a simple user profiling approach is proposed to generate user’s preferences to product attributes (i.e., user profiles) based on user product click stream data. The user profiles can be used to find similarminded users (i.e., neighbours) accurately. Two recommendation approaches are proposed, namely Round- Robin fusion algorithm (CFRRobin) and Collaborative Filtering-based Aggregated Query algorithm (CFAgQuery), to generate personalized recommendations based on the user profiles. Instead of using the target user’s query to search for products as normal search based systems do, the CFRRobin technique uses the attributes of the products in which the target user’s neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAgQuery technique uses the attributes of the products that the user’s neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAgQuery perform better than the standard Collaborative Filtering and the Basic Search approaches, which are widely applied by the current e-commerce applications.

A people-to-people matching system using graph mining techniques

A people-to-people matching system (or a match-making system) refers to a system in which users join with the objective of meeting other users with the common need. Some real-world examples of these systems are employer-employee (in job search networks), mentor-student (in university social networks), consume-to-consumer (in marketplaces) and male-female (in an online dating network). The network underlying in these systems consists of two groups of users, and the relationships between users need to be captured for developing an efficient match-making system. Most of the existing studies utilize information either about each of the users in isolation or their interaction separately, and develop recommender systems using the one form of information only. It is imperative to understand the linkages among the users in the network and use them in developing a match-making system. This study utilizes several social network analysis methods such as graph theory, small world phenomenon, centrality analysis, density analysis to gain insight into the entities and their relationships present in this network. This paper also proposes a new type of graph called “attributed bipartite graph”. By using these analyses and the proposed type of graph, an efficient hybrid recommender system is developed which generates recommendation for new users as well as shows improvement in accuracy over the baseline methods.

A social matching system : using implicit and explicit information for personalized recommendation in online dating service

Online dating websites enable a specific form of social networking and their efficiency can be increased by supporting proactive recommendations based on participants' preferences with the use of data mining. This research develops two-way recommendation methods for people-to-people recommendation for large online social networks such as online dating networks. This research discovers the characteristics of the online dating networks and utilises these characteristics in developing efficient people-to-people recommendation methods. Methods developed support improved recommendation accuracy, can handle data sparsity that often comes with large data sets and are scalable for handling online networks with a large number of users.

Practical guidance for the use of a pattern-matching technique in case-study research : a case presentation

This paper reports on a study that demonstrates how to apply pattern matching as an analytical method in case-study research. Case-study design is appropriate for the investigation of highly-contextualized phenomena that occur within the social world. Case-study design is considered a pragmatic approach that permits employment of multiple methods and data sources in order to attain a rich understanding of the phenomenon under investigation. The findings from such multiple methods can be reconciled in case-study analysis, specifically through a pattern-matching technique. Although this technique is theoretically explained in the literature, there is scant guidance on how to apply the method practically when analyzing data. This paper demonstrates the steps taken during pattern matching in a completed case-study project that investigated the influence of cultural diversity in a multicultural nursing workforce on the quality and safety of patient care. The example highlighted in this paper contributes to the practical understanding of the pattern-matching process, and can also make a substantial contribution to case-study methods.

The effect of employment while in high school on educational attainment : a conditional difference-in-differences approach

Using American panel data from the National Education Longitudinal Study of 1988, this article investigates the effect of working during grade 12 on attainment.We employ, for the first time in the related literature, a semiparametric propensity score matching approach combined with difference-in-differences. We address selection on both observables and unobservables associated with part-time work decisions, without the need for instrumental variable. Once such factors are controlled for, little to no effects on reading and math scores are found. Overall, our results therefore suggest a negligible academic cost from part-time working by the end of high school.

Towards condition-invariant, top-down visual place recognition

In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.

Stiffness-damping matching method of an ECAS system based on LQG control

A novel method of matching stiffness and continuous variable damping of an ECAS (electronically controlled air suspension) based on LQG (linear quadratic Gaussian) control was proposed to simultaneously improve the road-friendliness and ride comfort of a two-axle school bus. Taking account of the suspension nonlinearities and target-height-dependent variation in suspension characteristics, a stiffness model of the ECAS mounted on the drive axle of the bus was developed based on thermodynamics and the key parameters were obtained through field tests. By determining the proper range of the target height for the ECAS of the fully-loaded bus based on the design requirements of vehicle body bounce frequency, the control algorithm of the target suspension height (i.e., stiffness) was derived according to driving speed and road roughness. Taking account of the nonlinearities of a continuous variable semi-active damper, the damping force was obtained through the subtraction of the air spring force from the optimum integrated suspension force, which was calculated based on LQG control. Finally, a GA (genetic algorithm)-based matching method between stepped variable damping and stiffness was employed as a benchmark to evaluate the effectiveness of the LQG-based matching method. Simulation results indicate that compared with the GA-based matching method, both dynamic tire force and vehicle body vertical acceleration responses are markedly reduced around the vehicle body bounce frequency employing the LQG-based matching method, with peak values of the dynamic tire force PSD (power spectral density) decreased by 73.6%, 60.8% and 71.9% in the three cases, and corresponding reduction are 71.3%, 59.4% and 68.2% for the vehicle body vertical acceleration. A strong robustness to variation of driving speed and road roughness is also observed for the LQG-based matching method.

Flexible design of decoupling and matching networks for two strongly coupled antennas

The flexible design of decoupling and matching networks for coupled antennas is introduced. The network includes three parts: circuits for impedance transformation, an element for odd-mode decoupling and conventional matching networks. It is found that all three parts are determined by one parameter of the ABCD matrix of the impedance transformation circuit. Thus a large variety of circuits with different element values can be used for decoupling which relaxes the practical design constraints.

Effect of ramipril on walking times and quality of life among patients with peripheral artery disease and intermittent claudication : a randomized controlled trial

Importance Approximately one-third of patients with peripheral artery disease experience intermittent claudication, with consequent loss of quality of life. Objective To determine the efficacy of ramipril for improving walking ability, patient-perceived walking performance, and quality of life in patients with claudication. Design, Setting, and Patients Randomized, double-blind, placebo-controlled trial conducted among 212 patients with peripheral artery disease (mean age, 65.5 [SD, 6.2] years), initiated in May 2008 and completed in August 2011 and conducted at 3 hospitals in Australia. Intervention Patients were randomized to receive 10 mg/d of ramipril (n = 106) or matching placebo (n = 106) for 24 weeks. Main Outcome Measures Maximum and pain-free walking times were recorded during a standard treadmill test. The Walking Impairment Questionnaire (WIQ) and Short-Form 36 Health Survey (SF-36) were used to assess walking ability and quality of life, respectively. Results At 6 months, relative to placebo, ramipril was associated with a 75-second (95% CI, 60-89 seconds) increase in mean pain-free walking time (P < .001) and a 255-second (95% CI, 215-295 seconds) increase in maximum walking time (P < .001). Relative to placebo, ramipril improved the WIQ median distance score by 13.8 (Hodges-Lehmann 95% CI, 12.2-15.5), speed score by 13.3 (95% CI, 11.9-15.2), and stair climbing score by 25.2 (95% CI, 25.1-29.4) (P < .001 for all). The overall SF-36 median Physical Component Summary score improved by 8.2 (Hodges-Lehmann 95% CI, 3.6-11.4; P = .02) in the ramipril group relative to placebo. Ramipril did not affect the overall SF-36 median Mental Component Summary score. Conclusions and Relevance Among patients with intermittent claudication, 24-week treatment with ramipril resulted in significant increases in pain-free and maximum treadmill walking times compared with placebo. This was associated with a significant increase in the physical functioning component of the SF-36 score. Trial Registration clinicaltrials.gov Identifier: NCT00681226

Settling the Pop Score : Pop Texts and Identity Politics [Book Review]

Review(s) of: Settling the Pop Score: Pop Texts and Identity Politics, Stan Hawkins, Aldershot, Hants. : Ashgate, 2002, ISBN 0 7546 0352 0; pb, 234pp, ill, music exx, bibl. , discog. , index. The scholarly study of popular music has its origins in sociology and cultural studies, disciplinary areas in which musical meaning is often attributed to aspects of economical and sociological function. Against this tradition, recent writers have offered what is now referred to as ‘popular musicology’: a method or approach that tends towards a specific engagement with ‘pop texts’ on aesthetic, and perhaps even ‘musical’ terms. Stan Hawkins uses the term popular musicology ‘at his own peril,’ clearly recognising the implicit scholarly danger in his approach, whereby ‘formalist questions of musical analysis’ are dealt with ‘alongside the more intertextual discursive theorisations of musical expression’ (p. xii). In other words, popular musicologists dare to tread that fine line between text and context. As editor of the journal Popular Musicology Online, Hawkins is a leading advocate of this practice, specifically in the application of music-analytical techniques to popular music. His methodology attests to the influence of other leading figures in the area, notably Richard Middleton, Allan F. Moore and Derek Scott (general editor of the Ashgate Popular and Folk Music Series in which this book is published).

Efficient fuzzy matching and intersection on private datasets

At Eurocrypt’04, Freedman, Nissim and Pinkas introduced a fuzzy private matching problem. The problem is defined as follows. Given two parties, each of them having a set of vectors where each vector has T integer components, the fuzzy private matching is to securely test if each vector of one set matches any vector of another set for at least t components where t < T. In the conclusion of their paper, they asked whether it was possible to design a fuzzy private matching protocol without incurring a communication complexity with the factor (T t ) . We answer their question in the affirmative by presenting a protocol based on homomorphic encryption, combined with the novel notion of a share-hiding error-correcting secret sharing scheme, which we show how to implement with efficient decoding using interleaved Reed-Solomon codes. This scheme may be of independent interest. Our protocol is provably secure against passive adversaries, and has better efficiency than previous protocols for certain parameter values.

Distributed private matching and set operations

Motivated by the need of private set operations in a distributed environment, we extend the two-party private matching problem proposed by Freedman, Nissim and Pinkas (FNP) at Eurocrypt’04 to the distributed setting. By using a secret sharing scheme, we provide a distributed solution of the FNP private matching called the distributed private matching. In our distributed private matching scheme, we use a polynomial to represent one party’s dataset as in FNP and then distribute the polynomial to multiple servers. We extend our solution to the distributed set intersection and the cardinality of the intersection, and further we show how to apply the distributed private matching in order to compute distributed subset relation. Our work extends the primitives of private matching and set intersection by Freedman et al. Our distributed construction might be of great value when the dataset is outsourced and its privacy is the main concern. In such cases, our distributed solutions keep the utility of those set operations while the dataset privacy is not compromised. Comparing with previous works, we achieve a more efficient solution in terms of computation. All protocols constructed in this paper are provably secure against a semi-honest adversary under the Decisional Diffie-Hellman assumption.

Do sex and atopy influence cough outcome measurements in children?

Background Despite the commonality of cough and its burden, there are no published data on the relationship between atopy or sex on objectively measured cough frequency or subjective cough scores in children. In 202 children with and without cough, we determined the effect of sex and atopy on validated cough outcome measurements (cough receptor sensitivity [CRS], objective cough counts, and cough scores). We hypothesized that in contrast to adult data, sex does not influence cough outcome measures, and atopy is not a determinant of these cough measurements. Methods We combined data from four previous studies. Atopy (skin prick test), the concentration of capsaicin causing two and five or more coughs (C2 and C5, respectively), objectively measured cough frequency, and cough scores were determined and their relationship explored. The children’s (93 girls, 109 boys) mean age was 10.6 years (SD 2.9), and 56% had atopy. Results In multivariate analysis, CRS was influenced by age (C2 coefficient, 5.9; P = .034; C5 coefficient, 29.1; P = .0001). Atopy and sex did not significantly influence any of the cough outcomes (cough counts, C2, C5, cough score) in control subjects and children with cough. Conclusions Atopy does not influence important cough outcome measures in children with and without chronic cough. However, age, but not sex, influences CRS in children. Unlike adult data, sex does not affect objective counts or cough score in children with and without chronic cough. Studies on cough in children should be age matched, but matching for atopic status and sex is less important.