Local community detection with hints

Local community detection is a widely used method for identifying groups of nodes starting from seeding nodes. The seed(s) are usually selected either randomly or based only on structural properties of the network. However, in many cases the choice of seed(s) incorporates external knowledge that attaches to these nodes an additional importance for their community. This knowledge, may be derived from an expert on the domain, or may arise from the network’s side information and it constitutes our motivation for the present work; this additional information about the importance of seed(s) can be exploited for detection of better and more relevant communities. We call such biased seed(s), hint(s). Our approach, is to reflect the importance of hints by changing appropriately the network in their vicinity. To the best of our knowledge, no such viewpoint of the seeding nodes in local community detection has been considered before. The aim of this study is to identify a single community which contains the hint(s). Our key contribution is the proposed Hint Enhancement Framework(HEF) that applies a two-step procedure to discover the community of the hint(s): 1) it changes the network by amplifying the hint(s) using re-weighting or re-wiring strategies so as to materialize the bias towards them and 2) it applies local community detection algorithms on the altered network of step 1. We experimentally evaluate HEF in synthetic and real datasets, and demonstrate the positive aspects of the framework in identifying better communities, in comparison with plain local community detection algorithms as well as a global one.

     

Public–private partnership projects in Greece: risk ranking and preferred risk allocation

Project participants, through experience, have an initial perception and predisposition towards risk and the types of risks they are willing and able to undertake. This is equally true for parties interested in public–private partnership (PPP) projects. These initial positions have been registered for the major Greek PPP market stakeholders potentially involved in a PPP arrangement through a survey covering all candidate construction companies, interested financing institutes and a number of public sector entities to be involved in PPPs. Findings revealed that stakeholders were, for the majority of risks identified, in agreement as to preferred risk allocation. Risk allocation preferences for construction companies were compared with similar findings for the UK, a mature PPP market, indicating a possible learning/maturing process based on the particular country background. Conclusions add to other surveys carried out on the subject and should enable public sector clients to establish a more efficient framework for risk allocation, thus reducing negotiations prior to contract award and minimizing the risk of poor risk distribution.     

Glycemic control among Latinos with type 2 diabetes: The role of social-environmental support resources.

Objective: Although active diabetes self-management is required to achieve glycemic control, adherence is poor among ethnic minorities, especially Latinos. Research shows that individuals who report greater social-environmental support resources for disease management manage their diabetes more effectively than those with fewer support resources. Methods: Path analysis was conducted to investigate the value of a multiple-mediator model in explaining how support resources for disease management influence hemoglobin A1c (HbA1c) levels in a sample of 208 Latinos with Type 2 diabetes recruited from low-income serving community clinics in San Diego County. We hypothesized that the relationship between support resources for disease-management and HbA1c would be mediated by diabetes self-management and/or depression. Results: Participants who perceived greater support resources for disease-management reported better diabetes self-management (β = .40, p     

Stabilization of Nanoalumina Colloidal Slips

The processing of nanosized powders to produce dense components is a difficult task, mainly due to the strong agglomeration of nanoparticles. In this work, deagglomeration studies were carried out on sol–gel‐derived γ‐alumina suspensions through the addition of dispersant or dispersant in combination with ethylene glycol as binder and the proper wet ball‐milling. For this purpose, zeta‐potential, viscosity, and sedimentation studies were carried out, whereas dilatometric studies accompanied by XRD analyses were performed on the powders derived from the most stable suspensions. Sintering studies followed and the as received ceramics were evaluated by SEM. The optimum stabilization was achieved through the synergistic addition of 2.75 mg/g ammonium polymethacrylate with 1 wt% ethylene glycol. The respective powder, although it indicates a shift of the sintering start to higher temperature, leads to the densest ceramic with the finest (500 nm mean grain size) and the most homogeneous microstructure.     

Community detection in Social Media

The proposed survey discusses the topic of community detection in the context of Social Media. Community detection constitutes a significant tool for the analysis of complex networks by enabling the study of mesoscopic structures that are often associated with organizational and functional characteristics of the underlying networks. Community detection has proven to be valuable in a series of domains, e.g. biology, social sciences, bibliometrics. However, despite the unprecedented scale, complexity and the dynamic nature of the networks derived from Social Media data, there has only been limited discussion of community detection in this context. More specifically, there is hardly any discussion on the performance characteristics of community detection methods as well as the exploitation of their results in the context of real-world web mining and information retrieval scenarios. To this end, this survey first frames the concept of community and the problem of community detection in the context of Social Media, and provides a compact classification of existing algorithms based on their methodological principles. The survey places special emphasis on the performance of existing methods in terms of computational complexity and memory requirements. It presents both a theoretical and an experimental comparative discussion of several popular methods. In addition, it discusses the possibility for incremental application of the methods and proposes five strategies for scaling community detection to real-world networks of huge scales. Finally, the survey deals with the interpretation and exploitation of community detection results in the context of intelligent web applications and services.     

Project ARBRE: Lessons for bio-energy developers and policy-makers

Project Arable Biomass Renewable Energy (ARBRE) was a ‘flagship’ project in the UK to demonstrate electricity generation from dedicated energy crops, employing the high efficiency of gasification combined cycle technology while also contributing to the waste management problem of sewage disposal. The plant never reached commercial operation and this paper provides the first detailed public account of the reasons, drawing on interviews with the main actors. Project ARBRE failed due to three unfortunate developments: the withdrawal for reasons of commercial strategy of the main company that initiated and financed the project; bankruptcy of the turnkey contractor appointed to oversee the project; and technical problems with the gasification technology, which could not be resolved within the financial and time constraints. All these factors acted in reinforcing manner and they were individually preventable: documenting the process of failure is a learning experience that can prevent their recurrence.     

Bobo revisited: What the research says.

[Correction Notice: An erratum for this article was reported in Vol 17(2) of International Journal of Play Therapy (see record 2008-14897-001). A reference was incomplete. The correct reference is Trotter, K., Eshelman, D., & Landreth, G. (2003). A place for Bobo in play therapy. International Journal of Play Therapy, 12, 117-139.] There has been some discussion in the play therapy literature regarding whether to use a Bobo doll (bop bag) in the play therapy room. The following article reviews research studies from the fields of personality, learning, and social psychology, and underlying theories to help inform and assist play therapists in their decision-making regarding Bobo. Suggestions are offered regarding future empirical research in play therapy outcomes and the choices of play materials in the playroom. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Holographic reprocessing: Empirical evidence to reduce posttraumatic cognitions in women veterans with PTSD from sexual trauma and abuse.

Holographic reprocessing (HR) facilitates holistic reappraisal of attributions regarding interpersonal violence and maltreatment. The authors tested the feasibility to train therapists to run a protocol using HR to reduce negative thoughts associated with posttraumatic stress disorder (PTSD) in women veterans who have had sexual trauma or abuse. The study assessed pre- and postscores on the Posttraumatic Cognitions Inventory (PTCI) in a naturalistic clinical setting with 5 therapists. The protocol consisted of screening for PTSD, followed by an average of 9 HR treatment sessions. Twenty-two women were referred to the study; 17 enrolled and completed treatment (0% dropout rate). Significant decreases were found on all scales of the PTCI, with large effect sizes: total negative thoughts, t(16) = 4.42, p     

Proxy Cache Replacement Algorithms: A History-Based Approach

Accesing and circulation of Web objects has been facilitated by the design and implementation of effective caching schemes. Web caching has been integrated in prototype and commercial Web-based information systems in order to reduce the overall bandwidth and increase system's fault tolerance. This paper presents an overview of a series of Web cache replacement algorithms based on the idea of preserving a history record for cached Web objects. The number of references to Web objects over a certain time period is a critical parameter for the cache content replacement. The proposed algorithms are simulated and experimented under a real workload of Web cache traces provided by a major (Squid) proxy cache server installation. Cache and bytes hit rates are given with respect to different cache sizes and a varying number of request workload sets and it is shown that the proposed cache replacement algorithms improve both cache and byte hit rates.