Using segmented objects in ostensive video shot retrieval

This paper presents a system for video shot retrieval in which shots are retrieved based on matching video objects using a combination of colour, shape and texture. Rather than matching on individual objects, our system supports sets of query objects which in total reflect the user’s object-based information need. Our work also adapts to a shifting user information need by initiating the partitioning of a user’s search into two or more distinct search threads, which can be followed by the user in sequence. This is an automatic process which maps neatly to the ostensive model for information retrieval in that it allows a user to place a virtual checkpoint on their search, explore one thread or aspect of their information need and then return to that checkpoint to then explore an alternative thread. Our system is fully functional and operational and in this paper we illustrate several design decisions we have made in building it

Local Competition and Stochasticity for Adversarial Robustness in Deep Learning

This work addresses adversarial robustness in deep learning by considering deep networks with stochastic local winner-takes-all (LWTA) activations. This type of network units result in sparse representations from each model layer, as the units are organized in blocks where only one unit generates a non-zero output. The main operating principle of the introduced units lies on stochastic arguments, as the network performs posterior sampling over competing units to select the winner. We combine these LWTA arguments with tools from the field of Bayesian non-parametrics, specifically the stick-breaking construction of the Indian Buffet Process, to allow for inferring the sub-part of each layer that is essential for modeling the data at hand. Then, inference is performed by means of stochastic variational Bayes. We perform a thorough experimental evaluation of our model using benchmark datasets. As we show, our method achieves high robustness to adversarial perturbations, with state-of-the-art performance in powerful adversarial attack schemes.Comment: Accepted AISTATS 2021. arXiv admin note: text overlap with arXiv:2006.1062

Time-aware Sub-Trajectory Clustering in Hermes@PostgreSQL

In this paper, we present an efficient in-DBMS framework for progressive time-aware sub-trajectory cluster analysis. In particular, we address two variants of the problem: (a) spatiotemporal sub-trajectory clustering and (b) index-based time-aware clustering at querying environment. Our approach for (a) relies on a two-phase process: a voting-and-segmentation phase followed by a sampling-and-clustering phase. Regarding (b), we organize data into partitions that correspond to groups of sub-trajectories, which are incrementally maintained in a hierarchical structure. Both approaches have been implemented in Hermes@PostgreSQL, a real Moving Object Database engine built on top of PostgreSQL, enabling users to perform progressive cluster analysis via simple SQL. The framework is also extended with a Visual Analytics (VA) tool to facilitate real world analysis

Dietary management of celiac disease: revisiting the guidelines

Objective: Medical nutrition therapy (MNT), by lifelong compliance to a gluten free diet, is the only treatment of celiac disease (CD). Clinical practice guidelines (CPGs) regarding the management of CD emphasize on the role of MNT besides other treatment options. The aim of the present study was to review and critically appraise CD-specific MNT CPGs, and identify the areas in need of improvement for better adherence a¬¬nd outcomes. Research Methods & Procedures: A comprehensive search was performed at Pubmed, Guidelines International Network (GIN), Google Scholar and related websites for CPGs on the dietary management of CD, published in the English language. Results: A total of 12 CPGs were retrieved and critically appraised by three independent reviewers utilizing the AGREE II instrument. All CPGs were of low quality based on AGREE II tool. Among the 12 CPGs, the NICE ones achieved the highest score and was unanimously recommended without modifications by the three reviews, while AGA, AHS, BSPGHAN, CREST and FISPGHAN CPGs received the lowest score. Conclusions: The present study unveils the low quality of guidelines regarding the MNT of CD patients, indicating the need of updated and improved guidelines taking into consideration the proposed items of the AGREE II. Keywords: medical nutrition therapy; clinical practice; critical appraisal; gluten-free diet; autoimmune disease; nutrition intervention; evidence-based nutrition; gluten; CASP

The effect of nodal connectivity and strut density within stochastic titanium scaffolds on osteogenesis

Modern orthopaedic implants use lattice structures that act as 3D scaffolds to enhance bone growth into and around implants. Stochastic scaffolds are of particular interest as they mimic the architecture of trabecular bone and can combine isotropic properties and adjustable structure. The existing research mainly concentrates on controlling the mechanical and biological performance of periodic lattices by adjusting pore size and shape. Still, less is known on how we can control the performance of stochastic lattices through their design parameters: nodal connectivity, strut density and strut thickness. To elucidate this, four lattice structures were evaluated with varied strut densities and connectivity, hence different local geometry and mechanical properties: low apparent modulus, high apparent modulus, and two with near-identical modulus. Pre-osteoblast murine cells were seeded on scaffolds and cultured in vitro for 28 days. Cell adhesion, proliferation and differentiation were evaluated. Additionally, the expression levels of key osteogenic biomarkers were used to assess the effect of each design parameter on the quality of newly formed tissue. The main finding was that increasing connectivity increased the rate of osteoblast maturation, tissue formation and mineralisation. In detail, doubling the connectivity, over fixed strut density, increased collagen type-I by 140%, increased osteopontin by 130% and osteocalcin by 110%. This was attributed to the increased number of acute angles formed by the numerous connected struts, which facilitated the organization of cells and accelerated the cell cycle. Overall, increasing connectivity and adjusting strut density is a novel technique to design stochastic structures which combine a broad range of biomimetic properties and rapid ossification

A hybrid nonlinear-discriminant analysis feature projection technique

Feature set dimensionality reduction via Discriminant Analysis (DA) is one of the most sought after approaches in many applications. In this paper, a novel nonlinear DA technique is presented based on a hybrid of Artificial Neural Networks (ANN) and the Uncorrelated Linear Discriminant Analysis (ULDA). Although dimensionality reduction via ULDA can present a set of statistically uncorrelated features, but similar to the existing DA's it assumes that the original data set is linearly separable, which is not the case with most real world problems. In order to overcome this problem, a one layer feed-forward ANN trained with a Differential Evolution (DE) optimization technique is combined with ULDA to implement a nonlinear feature projection technique. This combination acts as nonlinear discriminant analysis. The proposed approach is validated on a Brain Computer Interface (BCI) problem and compared with other techniques. © 2008 Springer Berlin Heidelberg

Assessing the Physiological Effects of Traditional Regional Diets Targeting the Prevention of Cardiovascular Disease: A Systematic Review of Randomized Controlled Trials Implementing Mediterranean, New Nordic, Japanese, Atlantic, Persian and Mexican Dietary Interventions

Traditional regional diets are considered as sustainable dietary patterns, while many have been examined with regard to their health benefits. The aim of the present systematic review was to aggerate all evidence on the physiological effects of regional diets among adults at high risk for cardiovascular disease (CVD). Three databases were searched for randomized controlled trials (RCTs) implementing any regional diet (Mediterranean (MedD), Persian, Southern European Atlantic, Japanese, Chinese, new Nordic, or other) while examining cardiovascular risk factors among adults at increased risk. Primary outcomes included anthropometric indices and secondary outcomes involved blood lipid concentrations, glucose metabolism, inflammation and other markers of CVD progression. Twenty RCTs fulfilled the study’s criteria and were included in the qualitative synthesis, with the majority implementing a MedD. Adherence to most of the regional diets induced a reduction in the BW and anthropometric indices of the participants. The majority of RCTs with blood pressure endpoints failed to note a significant reduction in the intervention compared to the comparator arm, with the exception of some new Nordic and MedD ones. Despite the interventions, inflammation markers remained unchanged except for CRP, which was reduced in the intervention groups of one new Nordic, the older Japanese, and the Atlantic diet RCTs. With regard to blood lipids, regional diet interventions either failed to induce significant differences or improved selective blood lipid markers of the participants adhering to the experimental regional diet arms. Finally, in the majority of RCTs glucose metabolism failed to improve. The body of evidence examining the effect of regional dietary patterns on CVD risk among high-risk populations, while employing an RCT design, appears to be limited, with the exception of the MedD. More research is required to advocate for the efficacy of most regional diets with regard to CVD