Indexing and efficient instance-based retrieval of process models using untanglings

Process-Aware Information Systems (PAISs) support executions of operational processes that involve people, resources, and software applications on the basis of process models. Process models describe vast, often infinite, amounts of process instances, i.e., workflows supported by the systems. With the increasing adoption of PAISs, large process model repositories emerged in companies and public organizations. These repositories constitute significant information resources. Accurate and efficient retrieval of process models and/or process instances from such repositories is interesting for multiple reasons, e.g., searching for similar models/instances, filtering, reuse, standardization, process compliance checking, verification of formal properties, etc. This paper proposes a technique for indexing process models that relies on their alternative representations, called untanglings. We show the use of untanglings for retrieval of process models based on process instances that they specify via a solution to the total executability problem. Experiments with industrial process models testify that the proposed retrieval approach is up to three orders of magnitude faster than the state of the art.

A comparison of the histochemical and image-derived proteoglycan content of articular cartilage

There are several methods for determining the proteoglycan content of cartilage in biomechanics experiments. Many of these include assay-based methods and the histochemistry or spectrophotometry protocol where quantification is biochemically determined. More recently a method based on extracting data to quantify proteoglycan content has emerged using the image processing algorithms, e.g., in ImageJ, to process histological micrographs, with advantages including time saving and low cost. However, it is unknown whether or not this image analysis method produces results that are comparable to those obtained from the biochemical methodology. This paper compares the results of a well-established chemical method to those obtained using image analysis to determine the proteoglycan content of visually normal (n=33) and their progressively degraded counterparts with the protocols. The results reveal a strong linear relationship with a regression coefficient (R2) = 0.9928, leading to the conclusion that the image analysis methodology is a viable alternative to the spectrophotometry.

Developing an evidence-based clinical pathway for the assessment, diagnosis and management of acute Charcot Neuro-Arthropathy : a systematic review

Background: Charcot Neuro-Arthropathy (CN) is one of the more devastating complications of diabetes. To the best of the authors' knowledge, it appears that no clinical tools based on a systematic review of existing literature have been developed to manage acute CN. Thus, the aim of this paper was to systematically review existing literature and develop an evidence-based clinical pathway for the assessment, diagnosis and management of acute CN in patients with diabetes. Methods: Electronic databases (Medline, PubMed, CINAHL, Embase and Cochrane Library), reference lists, and relevant key websites were systematically searched for literature discussing the assessment, diagnosis and/or management of acute CN published between 2002-2012. At least two independent investigators then quality rated and graded the evidence of each included paper. Consistent recommendations emanating from the included papers were then fashioned in a clinical pathway. Results: The systematic search identified 267 manuscripts, of which 117 (44%) met the inclusion criteria for this study. Most manuscripts discussing the assessment, diagnosis and/or management of acute CN constituted level IV (case series) or EO (expert opinion) evidence. The included literature was used to develop an evidence-based clinical pathway for the assessment, investigations, diagnosis and management of acute CN. Conclusions: This research has assisted in developing a comprehensive, evidence-based clinical pathway to promote consistent and optimal practice in the assessment, diagnosis and management of acute CN. The pathway aims to support health professionals in making early diagnosis and providing appropriate immediate management of acute CN, ultimately reducing its associated complications such as amputations and hospitalisations.

The relationship between kurtosis- and envelope-based indexes for the diagnostic of rolling element bearings

The coupling of kurtosis based-indexes and envelope analysis represents one of the most successful and widespread procedures for the diagnostics of incipient faults on rolling element bearings. Kurtosis-based indexes are often used to select the proper demodulation band for the application of envelope-based techniques. Kurtosis itself, in slightly different formulations, is applied for the prognostic and condition monitoring of rolling element bearings, as a standalone tool for a fast indication of the development of faults. This paper shows for the first time the strong analytical connection which holds for these two families of indexes. In particular, analytical identities are shown for the squared envelope spectrum (SES) and the kurtosis of the corresponding band-pass filtered analytic signal. In particular, it is demonstrated how the sum of the peaks in the SES corresponds to the raw 4th order moment. The analytical results show as well a link with an another signal processing technique: the cepstrum pre-whitening, recently used in bearing diagnostics. The analytical results are the basis for the discussion on an optimal indicator for the choice of the demodulation band, the ratio of cyclic content (RCC), which endows the kurtosis with selectivity in the cyclic frequency domain and whose performance is compared with more traditional kurtosis-based indicators such as the protrugram. A benchmark, performed on numerical simulations and experimental data coming from two different test-rigs, proves the superior effectiveness of such an indicator. Finally a short introduction to the potential offered by the newly proposed index in the field of prognostics is given in an additional experimental example. In particular the RCC is tested on experimental data collected on an endurance bearing test-rig, showing its ability to follow the development of the damage with a single numerical index.

Delirium knowledge and recognition : a randomized controlled trial of a web-based educational intervention for acute care nurses

Delirium is a significant problem for older hospitalized people and is associated with poor outcomes. It is poorly recognized and evidence suggests that a major reason is lack of education. Nurses, who are educated about delirium, can play a significant role in improving delirium recognition. This study evaluated the impact of a delirium specific educational website. A cluster randomized controlled trial, with a pretest/post-test time series design, was conducted to measure delirium knowledge (DK) and delirium recognition (DR) over three time-points. Statistically significant differences were found between the intervention and non-intervention group. The intervention groups' DK scores were higher and the change over time results were statistically significant [T3 and T1 (t=3.78 p=<0.001) and T2 and T1 baseline (t=5.83 p=<0.001)]. Statistically significant improvements were also seen for DR when comparing T2 and T1 results (t=2.56 p=0.011) between both groups but not for changes in DR scores between T3 and T1 (t=1.80 p=0.074). Participants rated the website highly on the visual, functional and content elements. This study supports the concept that web-based delirium learning is an effective and satisfying method of information delivery for registered nurses. Future research is required to investigate clinical outcomes as a result of this web-based education.

Acceptability-based QoE models for mobile video

Quality of experience (QoE) measures the overall perceived quality of mobile video delivery from subjective user experience and objective system performance. Current QoE computing models have two main limitations: 1) insufficient consideration of the factors influencing QoE, and; 2) limited studies on QoE models for acceptability prediction. In this paper, a set of novel acceptability-based QoE models, denoted as A-QoE, is proposed based on the results of comprehensive user studies on subjective quality acceptance assessments. The models are able to predict users’ acceptability and pleasantness in various mobile video usage scenarios. Statistical regression analysis has been used to build the models with a group of influencing factors as independent predictors, including encoding parameters and bitrate, video content characteristics, and mobile device display resolution. The performance of the proposed A-QoE models has been compared with three well-known objective Video Quality Assessment metrics: PSNR, SSIM and VQM. The proposed A-QoE models have high prediction accuracy and usage flexibility. Future user-centred mobile video delivery systems can benefit from applying the proposed QoE-based management to optimize video coding and quality delivery decisions.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Integrating time forgetting mechanisms into topic-based user interest profiling

The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

Product feature taxonomy learning based on user reviews

In recent years, the Web 2.0 has provided considerable facilities for people to create, share and exchange information and ideas. Upon this, the user generated content, such as reviews, has exploded. Such data provide a rich source to exploit in order to identify the information associated with specific reviewed items. Opinion mining has been widely used to identify the significant features of items (e.g., cameras) based upon user reviews. Feature extraction is the most critical step to identify useful information from texts. Most existing approaches only find individual features about a product without revealing the structural relationships between the features which usually exist. In this paper, we propose an approach to extract features and feature relationships, represented as a tree structure called feature taxonomy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature taxonomy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that our proposed approach is able to capture the product features and relations effectively.

A topic based document relevance ranking model

Topic modelling has been widely used in the fields of information retrieval, text mining, machine learning, etc. In this paper, we propose a novel model, Pattern Enhanced Topic Model (PETM), which makes improvements to topic modelling by semantically representing topics with discriminative patterns, and also makes innovative contributions to information filtering by utilising the proposed PETM to determine document relevance based on topics distribution and maximum matched patterns proposed in this paper. Extensive experiments are conducted to evaluate the effectiveness of PETM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models.

High performance electrochromic devices based on anodized nanoporous Nb2O5

Despite the predictions, the true potential of Nb2O5 for electrochromic applications has yet to be fully realized. In this work, three-dimensional (3D) compact and well-ordered nanoporous Nb2O5 films are synthesized by the electrochemical anodization of niobium thin films. These films are formed using RF sputtering and then anodized in an electrolyte containing ethylene glycol, ammonium fluoride, and small water content (4%) at 50 °C which resulted in low embedded impurities within the structure. Characterization of the anodized films shows that a highly crystalline orthorhombic phase of Nb2O5 is obtained after annealing at 450 °C. The 3D structure provides a template consisting of a large concentration of active sites for ion intercalation, while also ensuring low scattering directional paths for electrons. These features enhance the coloration efficiency to 47.0 cm2 C?1 (at 550 nm) for a 500 nm thick film upon Li+ ion intercalation. Additionally, the Nb2O5 electrochromic device shows a high bleached state transparency and large optical modulation.

An intuitive multi-touch surface and gesture based interaction for video surveillance systems

This paper discusses the idea and demonstrates an early prototype of a novel method of interacting with security surveillance footage using natural user interfaces in place of traditional mouse and keyboard interaction. Current surveillance monitoring stations and systems provide the user with a vast array of video feeds from multiple locations on a video wall, relying on the user’s ability to distinguish locations of the live feeds from experience or list based key-value pair of location and camera IDs. During an incident, this current method of interaction may cause the user to spend increased amounts time obtaining situational and location awareness, which is counter-productive. The system proposed in this paper demonstrates how a multi-touch screen and natural interaction can enable the surveillance monitoring station users to quickly identify the location of a security camera and efficiently respond to an incident.

Polycarbonate based non-chemically amplified photoresists for extreme ultraviolet lithography

Some initial EUVL patterning results for polycarbonate based non-chemically amplified resists are presented. Without full optimization the developer a resolution of 60 nm line spaces could be obtained. With slight overexposure (1.4 × E0) 43.5 nm lines at a half pitch of 50 nm could be printed. At 2x E0 a 28.6 nm lines at a half pitch of 50 nm could be obtained with a LER that was just above expected for mask roughness. Upon being irradiated with EUV photons, these polymers undergo chain scission with the loss of carbon dioxide and carbon monoxide. The remaining photoproducts appear to be non-volatile under standard EUV irradiation conditions, but do exhibit increased solubility in developer compared to the unirradiated polymer. The sensitivity of the polymers to EUV light is related to their oxygen content and ways to increase the sensitivity of the polymers to 10 mJ cm-2 is discussed.

Analysis of bilinear pairing-based accumulator for identity escrowing

An accumulator based on bilinear pairings was proposed at CT-RSA'05. Here, it is first demonstrated that the security model proposed by Lan Nguyen does lead to a cryptographic accumulator that is not collision resistant. Secondly, it is shown that collision-resistance can be provided by updating the adversary model appropriately. Finally, an improvement on Nguyen's identity escrow scheme, with membership revocation based on the accumulator, by removing the trusted third party is proposed.

Silicate-based bioceramics for periodontal regeneration

Periodontal disease is characterized by the destruction of the tissues that attach the tooth to the alveolar bone. Various methods for regenerative periodontal therapy including the use of barrier membranes, bone replacement grafts, and growth factor delivery have been investigated; however, true regeneration of periodontal tissue is still a significant challenge to scientists and clinicians. The focus on periodontal tissue engineering has shifted from attempting to recreate tissue replacements/constructs to the development of biomaterials that incorporate and release regulatory signals to achieve in situ periodontal regeneration. The release of ions and molecular cues from biomaterials may help to unlock latent regenerative potential in the body by regulating cell proliferation and differentiation towards different lineages (e.g. osteoblasts and cementoblasts). Silicate-based bioactive materials, including bioactive silicate glasses and ceramics, have become the materials of choice for periodontal regeneration, due to their favourable osteoconductivity and bioactivity. This article will focus on the most recent advances in the in vitro and in vivo biological application of silicate-based ceramics, specifically as it relates to periodontal tissue engineering.