A new modularity measure for Fuzzy Community detection problems based on overlap and grouping functions

One of the main challenges of fuzzy community detection problems is to be able to measure the quality of a fuzzy partition. In this paper, we present an alternative way of measuring the quality of a fuzzy community detection output based on n-dimensional grouping and overlap functions. Moreover, the proposed modularity measure generalizes the classical Girvan–Newman (GN) modularity for crisp community detection problems and also for crisp overlapping community detection problems. Therefore, it can be used to compare partitions of different nature (i.e. those composed of classical, overlapping and fuzzy communities). Particularly, as is usually done with the GN modularity, the proposed measure may be used to identify the optimal number of communities to be obtained by any network clustering algorithm in a given network. We illustrate this usage by adapting in this way a well-known algorithm for fuzzy community detection problems, extending it to also deal with overlapping community detection problems and produce a ranking of the overlapping nodes. Some computational experiments show the feasibility of the proposed approach to modularity measures through n-dimensional overlap and grouping functions.

DUI program as OEF/OIF Veterans Outreach: Descriptive Data from Two Community-Based Outpatient Clinics

Although initially conceived as providing simply the preventive portion of an extended continuum of care for veterans, the Driving Under the Influence (DUI) program has turned out to be an important outreach service for active duty or recently discharged OEF/OIF (Operation Enduring Freedom/Operation Iraqi Freedom) veterans. Veterans receive empirically-based, state-mandated education and therapy under the only Department of Veterans Affairs (VA) - sponsored DUI program in the State of Colorado, with the advantage of having providers who are sensitive to symptoms of Post-Traumatic Stress Disorder (PTSD) and other relevant diagnoses specific to this population, including Traumatic Brain Injury (TBI). In this paper, the rapid growth of this program is described, as well as summary data regarding the completion, discontinuation, and augmentation of services from the original referral concern. Key results indicated that for nearly one third (31.9%) of the OEF/OIF veterans who were enrolled in the DUI program, this was their initial contact with the VA health care system. Furthermore, following their enrollment in the DUI program, more than one fourth (27.6%) were later referred to and attended other VA programs including PTSD rehabilitation and group therapy, anger management, and intensive inpatient or outpatient dual diagnosis programs. These and other findings from this study suggest that the DUI program may be an effective additional pathway for providing treatment that is particularly salient to the distinctive OEF/OIF population; one that may also result in earlier intervention for problem drinking and other problems related to combat. Relevant conclusions discussed herein primarily aim to improve providers' understanding of effective outreach, and to enhance the appropriate linkages between OEF/OIF veterans and existing VA services.