Toward seed-insensitive solutions to local community detection

Local community detection aims at finding a community structure starting from a seed which is a given vertex in a network without global information, such as online social networks that are too large and dynamic to ever be known fully. Nonetheless, the existing approaches to local community detection are usually sensitive to seeds, i.e., some seeds may lead to missing of some true communities. In this paper, we present a seed-insensitive method called GMAC and its variation iGMAC for local community detection. They estimate the similarity among vertices by investigating vertices’ neighborhoods, and reveal a local community by maximizing its internal similarity and minimizing its external similarity simultaneously. Extensive experimental results on both synthetic and real-world data sets verify the effectiveness of our algorithms.     

A review of interoperability assessment models

Interoperability is the ability of systems to provide services to and accept services from other systems, and to use the services exchanged so as to operate together in a more effective manner. The fact that interoperability can be improved means that the metrics for measuring interoperability can be defined. For the purpose of measuring the interoperability between systems, an interoperability assessment model is required. This paper deals with the existing interoperability assessment models. A compara- tive analysis among these models is provided to evaluate the similarities and differences in their philosophy and implementation. The analysis yields a set of recommendations for any party that is open to the idea of creating or improving an interoperability assessment model.     

Mesh Decomposition with Cross‐Boundary Brushes

We present a new intuitive UI, which we call cross‐boundary brushes, for interactive mesh decomposition. The user roughly draws one or more strokes across a desired cut and our system automatically returns a best cut running through all the strokes. By the different natures of part components (i.e., semantic parts) and patch components (i.e., flatter surface patches) in general models, we design two corresponding brushes: part‐brush and patch‐brush. These two types of brushes share a common user interface, enabling easy switch between them. The part‐brush executes a cut along an isoline of a harmonic field driven by the user‐specified strokes. We show that the inherent smoothness of the harmonic field together with a carefully designed isoline selection scheme lead to segmentation results that are insensitive to noise, pose, tessellation and variation in user's strokes. Our patch‐brush uses a novel facet‐based surface metric that alleviates sensitivity to noise and fine details common in region‐growing algorithms. Extensive experimental results demonstrate that our cutting tools can produce user‐desired segmentations for a wide variety of models even with single strokes. We also show that our tools outperform the state‐of‐art interactive segmentation tools in terms of ease of use and segmentation quality.     

Development of a web-based insulin decision aid for the elderly: usability barriers and guidelines

Universal Access in the Information Society - In recent years, researchers have attempted to shift patient decision aids (PDAs) from paper-based to web-based to increase its accessibility. Insulin...     

Spatial co-location pattern discovery without thresholds

Spatial co-location pattern mining discovers the subsets of features whose events are frequently located together in geographic space. The current research on this topic adopts a threshold-based approach that requires users to specify in advance the thresholds of distance and prevalence. However, in practice, it is not easy to specify suitable thresholds. In this article, we propose a novel iterative mining framework that discovers spatial co-location patterns without predefined thresholds. With the absolute and relative prevalence of spatial co-locations, our method allows users to iteratively select informative edges to construct the neighborhood relationship graph until every significant co-location has enough confidence and eventually to discover all spatial co-location patterns. The experimental results on real world data sets indicate that our framework is effective for prevalent co-locations discovery.     

Growth of SiC nanowires and nanocones using mixture of oil palm fibres and rice husk ash

3C-SiC nanowires and nanocones were grown by pyrolysing mixture of acid-treated oil palm empty fruit bunch fibres and rice husk ash (RHA), which acted as carbon and silicon source, respectively. The effects of different RHA amounts and pyrolysis temperature were studied. When the amount of RHA was increased to 80 % of the mixture, there was a change in the morphology from nanowires to nanocones. Overall, it was found that 40 % of RHA in the mixture was the ideal amount in growing the nanowires with the maximum yield and with the least amount of impurities. When the pyrolysis temperature was raised, there was an increase in the amount, diameter and length of the nanowires. The proposed main growth mechanism for the SiC nanowires were combination of solid-state reaction and vapour–solid mechanisms, with some nanowires grown under vapour–liquid–solid (VLS) mechanism induced by trace metals as well. The growth of the nanocones could also be related to VLS mechanism.     

Simultaneous quantification of free fatty acids,free sterols,squalene, and acylglycerol molecular species in palm oil by high-temperature gas chromatography-flame ionization detection

This paper discusses a rapid GC-FID technique for the simultaneous quantitative analysis of FFA, MAG, DAG, TAG, sterols, and squalene in vegetable oils, with special reference to palm oil. The FFA content determined had a lower SE compared with a conventional titrimetric method. Squalene and individual sterols, consisting of β-sitosterol, stigmasterol, campesterol, and cholesterol, were accurately quantified without any losses. This was achieved through elimination of tedious conventional sample pretreatments, such as saponification and preparative TLC. With this technique, the separation of individual MAG, consisting of 16∶0, 18∶0, and 18∶1 FA, and the DAG species, consisting of the 1,2(2,3)- and 1,3-positions, was sufficient to enable their quantification. This technique enabled the TAG to be determined according to their carbon numbers in the range of C₄₄ to C₅₆. Comparisons were made with conventional methods, and the results were in good agreement with those reported in the literature.     

X‐Region: A framework for location privacy preservation in mobile peer‐to‐peer networks

While enjoying various LBS (location‐based services), users also face the threats of location privacy disclosure. This is because even if the communications between users and LBS providers can be encrypted and anonymized, the sensitive information inside LBS queries may disclose the exact location or even the identity of a user. The existing research on location privacy preservation in mobile peer‐to‐peer (P2P) networks assumed that users trust each other and directly share location information with each other. Nonetheless, this assumption is not practical for most of the mobile P2P scenarios, for example, an adversary can pretend to be a normal user and collect the locations of other users. Aiming at this issue, this paper presents x‐region as a solution to preserve the location privacy in a mobile P2P environment where no trust relationships are assumed amongst mobile users. The main idea is to allow users to share a blurred region known as x‐region instead of their exact locations so that one cannot distinguish any user from others inside the region. We propose a theoretical metric for measuring the anonymity property of x‐region, together with three algorithms for generating an x‐region, namely, benchmark algorithm, weighted expanding algorithm, and aggressive weighted expanding algorithm. These algorithms achieve the anonymity and QoS requirements with different strategies. Our experiments verify the performance of the algorithms against three key metrics. Copyright © 2013 John Wiley & Sons, Ltd.     

Seepage Effects on Dune Dimensions

This note presents an experimental study of seepage effects on the dimensions of a dune: its height, length and lee-side slope. The critical slope of a cohesionless material was found to be related to the ratio of the hydraulic gradient of seepage to its critical value under the quick condition. The theoretical relationship is successfully used to predict seepage effects on the lee-side slope of dunes. Measured laboratory data support the assumption that the effect of seepage on the lee-side slope of dunes is the same as that on the critical slope of the sediment. The data reveal that the slope is reduced and increased with injection and suction, respectively. Additionally, the study explores seepage effects on the development of dune height and length. Experimental results show that suction and injection increase and decrease the equilibrium height of dunes by 25 and 40%, respectively. On the other hand, the dune length is found to increase by approximately 30% and decrease by 20% under the influence of suction and injection, respectively.