Predicting fraud in mobile money transfer using case-based reasoning

This paper proposes an improved CBR approach for the identification of money transfer fraud in Mobile Money Transfer (MMT) environments. Standard CBR capability is augmented by machine learning techniques to assign parameter weights in the sample dataset and automate k-value random selection in k-NN classification to improve CBR performance. The CBR system observes users’ transaction behaviour within the MMT service and tries to detect abnormal patterns in the transaction flows. To capture user behaviour effectively, the CBR system classifies the log information into five contexts and then combines them into a single dimension, instead of using the conventional approach where the transaction amount, time dimensions or features dimension are used individually. The applicability of the proposed augmented CBR system is evaluated using simulation data. From the results, both dimensions show good performance with the context of information weighted CBR system outperforming the individual features approach

Nematic-Isotropic Transition with Quenched Disorder

Nematic elastomers do not show the discontinuous, first-order, phase transition that the Landau-De Gennes mean field theory predicts for a quadrupolar ordering in 3D. We attribute this behavior to the presence of network crosslinks, which act as sources of quenched orientational disorder. We show that the addition of weak random anisotropy results in a singular renormalization of the Landau-De Gennes expression, adding an energy term proportional to the inverse quartic power of order parameter Q. This reduces the first-order discontinuity in Q. For sufficiently high disorder strength the jump disappears altogether and the phase transition becomes continuous, in some ways resembling the supercritical transitions in external field.Comment: 12 pages, 4 figures, to be published on PR

The influence of age on tooth supported fixed prosthetic restoration longevity. A systematic review

OBJECTIVE: The purpose of this study was to investigate the possible influence of age on the longevity of tooth supported fixed prosthetic restorations, using a systematic review process. DATA SOURCES: To identify relevant papers an electronic search was made using various databases (MEDLINE via Pubmed, EMBASE, The Cochrane Register of RCTs, the database of abstracts of Reviews of Effects-DARE), augmented by hand searching of key prosthodontic journals (International Journal of Prosthodontics, Journal of Prosthetic Dentistry and Journal of Prosthodontics) and reference cross-check. STUDY SELECTION: Assessment and selection of studies identified were conducted in a two phase procedure, by two independent reviewers utilizing specific inclusion and exclusion criteria. The minimum mean follow-up time was set at 5 years. RESULTS: The initial database search yielded 513 relevant titles. After the subsequent filtering process, 22 articles were selected for full-text analysis, finally resulting in 11 studies that met the inclusion criteria. All studies were classified as category C according to the strength of evidence. Meta-analysis was not possible due to the non-uniformity of the data available. The final studies were presented with conflicting results. The majority of the final studies did not report a statistically significant effect of age on fixed prostheses survival, whilst only one study reported poorer prognosis for elderly patients, and two studies reported poorer prognosis for middle-aged patients. CONCLUSIONS: The results of this systematic review showed that increased age of patients should not be considered as a risk factor for the survival of fixed prostheses. Although the majority of studies did not show any effect of age on the survival of fixed prostheses, there was some evidence that middle-aged patients may present with higher failure rates

Improved movie recommendations based on a hybrid feature combination method

Recommender systems help users find relevant items efficiently based on their interests and historical interactions with other users. They are beneficial to businesses by promoting the sale of products and to user by reducing the search burden. Recommender systems can be developed by employing different approaches, including collaborative filtering (CF), demographic filtering (DF), content-based filtering (CBF) and knowledge-based filtering (KBF). However, large amounts of data can produce recommendations that are limited in accuracy because of diversity and sparsity issues. In this paper, we propose a novel hybrid method that combines user–user CF with the attributes of DF to indicate the nearest users, and compare four classifiers against each other. This method has been developed through an investigation of ways to reduce the errors in rating predictions based on users’ past interactions, which leads to improved prediction accuracy in all four classification algorithms. We applied a feature combination method that improves the prediction accuracy and to test our approach, we ran an offline evaluation using the 1M MovieLens dataset, well-known evaluation metrics and comparisons between methods with the results validating our proposed method

Case Report: Resolution of a periodontoid rheumatoid pannus mass in an elderly patient treated with a rigid cervical collar: A case report and literature review

In patients with C2 rheumatoid pannus with spinal cord compression the treatment of choice is extensive surgery either through a transoral resection of the dens axis or a dorsal stabilisation, or both. We present a case of an 11-mm rheumatoid pannus with significant compression of the spinal cord, which failed surgical treatment with respect to dorsal stabilisation. Therefore, rigid cervical collar for 8 weeks followed by soft collar for another 4 weeks was chosen as a treatment option. During the follow-up period of 1 year, the pannus reduced significantly and the spinal cord decompressed. In cases where surgery is not an option or is technically very demanding, the alternative of cervical collar immobilisation is a satisfying option

Can one hear the shape of the Universe?

It is shown that the recent observations of NASA's explorer mission "Wilkinson Microwave Anisotropy Probe" (WMAP) hint that our Universe may possess a non-trivial topology. As an example we discuss the Picard space which is stretched out into an infinitely long horn but with finite volume.Comment: 4 page

Quenched disorder and spin-glass correlations in XY nematics

We present a theoretical study of the equilibrium ordering in a 3D XY nematic system with quenched random disorder. Within this model, treated with the replica trick and Gaussian variational method, the correlation length is obtained as a function of the local nematic order parameter and the effective disorder strength. These results clarify what happens in the limiting cases of diminishing order parameter and disorder strength, that is near a phase transition of a pure system. In particular, it is found that quenched disorder is irrelevant as the order parameter tends to zero and hence does not change the character of the continuous XY nematic to isotropic phase transition. We discuss how these results compare with experiments and simulationsComment: 19 pages, 6 figures, corrected typo

Gamification:using gaming mechanics to promote a business

The use of digital games and gamification has demonstrable potential to improve many aspects of how businesses provide training to staff, operate, and communicate with consumers. However, a need still exists for the benefits and potential of adopting games and gamification be effectively communicated to decision-makers across sectors. This article provides a structured review of existing literature on the use of games in the business sector, seeking to consolidate findings to address research questions regarding their perception, proven efficacy, and identify key areas for future work. The findings consolidate evidence showing serious games can have a positive and valuable impact in multiple areas of a business, including training, decision-support, and consumer outreach. They also highlight the challenges and pitfalls of applying serious games and gamification principles within a business context, and discuss the implications of development and evaluation methodologies on the success of a game-based solution

Gamification for servitization

The study described in this paper has set out to explore gamification from a servitization perspective to understand the opportunities and research challenges. A systematic literature review has been conducted to capture key characteristics of differing forms of gamification processes in a servitization context. The findings of our study focus on two area: (1) structural, organization’s physical bricksand-mortar attribute and (2) infrastructural, policies and practices in how structural aspects of servitization are to be managed. Six key findings are presented and collectively these contribute to our understanding of the broader gamification technologies that can help to transform servitization. The contribution of our research is twofold. First it captures a set of theoretical framework for analysing gamification in servitization context. Second, it provide an in-depth roadmap in how gamification can be applied to target major challenges in servitization

Audio-visual speech recognition with a hybrid CTC/attention architecture

Recent works in speech recognition rely either on connectionist temporal classification (CTC) or sequence-to-sequence models for character-level recognition. CTC assumes conditional independence of individual characters, whereas attention-based models can provide nonsequential alignments. Therefore, we could use a CTC loss in combination with an attention-based model in order to force monotonic alignments and at the same time get rid of the conditional independence assumption. In this paper, we use the recently proposed hybrid CTC/attention architecture for audio-visual recognition of speech in-the-wild. To the best of our knowledge, this is the first time that such a hybrid architecture architecture is used for audio-visual recognition of speech. We use the LRS2 database and show that the proposed audio-visual model leads to an 1.3% absolute decrease in word error rate over the audio-only model and achieves the new state-of-the-art performance on LRS2 database (7% word error rate). We also observe that the audio-visual model significantly outperforms the audio-based model (up to 32.9% absolute improvement in word error rate) for several different types of noise as the signal-to-noise ratio decreases