Local Algorithms for Block Models with Side Information

There has been a recent interest in understanding the power of local algorithms for optimization and inference problems on sparse graphs. Gamarnik and Sudan (2014) showed that local algorithms are weaker than global algorithms for finding large independent sets in sparse random regular graphs. Montanari (2015) showed that local algorithms are suboptimal for finding a community with high connectivity in the sparse Erd\H{o}s-R\'enyi random graphs. For the symmetric planted partition problem (also named community detection for the block models) on sparse graphs, a simple observation is that local algorithms cannot have non-trivial performance. In this work we consider the effect of side information on local algorithms for community detection under the binary symmetric stochastic block model. In the block model with side information each of the $n$ vertices is labeled $+$ or $-$ independently and uniformly at random; each pair of vertices is connected independently with probability $a/n$ if both of them have the same label or $b/n$ otherwise. The goal is to estimate the underlying vertex labeling given 1) the graph structure and 2) side information in the form of a vertex labeling positively correlated with the true one. Assuming that the ratio between in and out degree $a/b$ is $\Theta(1)$ and the average degree $(a+b) / 2 = n^{o(1)}$, we characterize three different regimes under which a local algorithm, namely, belief propagation run on the local neighborhoods, maximizes the expected fraction of vertices labeled correctly. Thus, in contrast to the case of symmetric block models without side information, we show that local algorithms can achieve optimal performance for the block model with side information.Comment: Due to the limitation "The abstract field cannot be longer than 1,920 characters", the abstract here is shorter than that in the PDF fil

Fingerprint Based Hot Water Distribution System

This paper presents a modelling technique and an optimal scheme for automated hot water distribution which will be possible to distribute the HOT water equally to all candidates in hostels, so that everyone will get the equal amount of hot water. In urban areas, wastage of water and loss of electricity has become the serious problem. To minimize this problem, we can use this distribution system in order to reduce the wastage of water and save the electricity. The limitations to this model is distribution losses which ranges from 10%-40% of annual hot water energy consumption, depending upon factors such as hot water use quantity and patterns. Critical factors that affect the magnitude of the distribution loss include the layout of the distribution system and the magnitude and pattern of hot water loads within the hostels. This technique allows to allocate sufficient amount of water to the authenticated user by using biometric module and also control the flow of water and pressure

Type 2 immunity is controlled by IL-4/IL-13 expression in hematopoietic non-eosinophil cells of the innate immune system

Nippostrongylus brasiliensis infection and ovalbumin-induced allergic lung pathology are highly interleukin (IL)-4/IL-13 dependent, but the contributions of IL-4/IL-13 from adaptive (T helper [Th]2 cells) and innate (eosinophil, basophils, and mast cells) immune cells remain unknown. Although required for immunoglobulin (Ig)E induction, IL-4/IL-13 from Th2 cells was not required for worm expulsion, tissue inflammation, or airway hyperreactivity. In contrast, innate hematopoietic cell–derived IL-4/IL-13 was dispensable for Th2 cell differentiation in lymph nodes but required for effector cell recruitment and tissue responses. Eosinophils were not required for primary immune responses. Thus, components of type 2 immunity mediated by IL-4/IL-13 are partitioned between T cell–dependent IgE and an innate non-eosinophil tissue component, suggesting new strategies for interventions in allergic immunity

Importance of calculating various casting indices in predicting radiological outcomes of paediatric forearm fractures

Background: The present study is aimed at determining the importance of various casting indices in predicting the outcome of paediatric forearm fractures treated with closed reduction and plaster application in our department.Methods: Thirty children, aged 5 to 15 years, with closed forearm fractures not requiring surgical fixation were included to assess their casting indices and radiological outcomes using X-rays. After satisfactory casting, patients were followed up weekly till 6 weeks with anteroposterior (AP) and lateral X-ray.Results: Acceptable reduction was achieved in 26 cases, while re-manipulation was done in 4 cases. Cast Index ranged from 0.80±0.09 at first week to 0.78±0.09 at 6 weeks, Padding Index was 0.30±0.04 at first week and increased to 0.31±0.03 at 6 weeks, Canterbury Index was 1.07±0.24 at first week and 1.07±0.78 at 6 weeks, Gap Index 0.15±0.02 remained the same throughout, and Three Point Index changed from 0.81±0.08 at first week to 0.77±0.18 six weeks. Radial bow of children showed no significant change at various time points of assessment. Rotational mal-alignment was observed in 5 patients, one had a 0.5 cm radial overlap, while none had an ulnar overlap. Radial angulation was observed in five and six children on AP and lateral X-ray respectively. Ulnar angulation was seen in two and one child on AP and lateral X-ray respectively.Conclusions: Continued use of these casting indices to assess paediatric forearm cast adequacy is supported by this study

Program transformations using temporal logic side conditions

This paper describes an approach to program optimisation based on transformations, where temporal logic is used to specify side conditions, and strategies are created which expand the repertoire of transformations and provide a suitable level of abstraction. We demonstrate the power of this approach by developing a set of optimisations using our transformation language and showing how the transformations can be converted into a form which makes it easier to apply them, while maintaining trust in the resulting optimising steps. The approach is illustrated through a transformational case study where we apply several optimisations to a small program

Arguments Against a Configural Processing Account of Familiar Face Recognition

Face recognition is a remarkable human ability, which underlies a great deal of people's social behavior. Individuals can recognize family members, friends, and acquaintances over a very large range of conditions, and yet the processes by which they do this remain poorly understood, despite decades of research. Although a detailed understanding remains elusive, face recognition is widely thought to rely on configural processing, specifically an analysis of spatial relations between facial features (so-called second-order configurations). In this article, we challenge this traditional view, raising four problems: (1) configural theories are underspecified; (2) large configural changes leave recognition unharmed; (3) recognition is harmed by nonconfigural changes; and (4) in separate analyses of face shape and face texture, identification tends to be dominated by texture. We review evidence from a variety of sources and suggest that failure to acknowledge the impact of familiarity on facial representations may have led to an overgeneralization of the configural account. We argue instead that second-order configural information is remarkably unimportant for familiar face recognition