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HIV prevalence has been on the rise in many countries from which refugees emigrate and presents therapeutic challenges upon arrival to the United States. The HIV entry ban that previously prevented immigration of HIV-infected individuals into the United States has now been lifted. Refugees may acquire several risk factors prior to displacement and during migration. In addition, they may not have access to HIV treatment and prevention packages in conflict-ridden regions of the world. Therefore, refugee providers will need to be familiar with fundamental HIV testing and treatment principles, including for HIV-2, particularly as they pertain to refugees that may have co-morbid mental illness and/or who may be of child-bearing age. In addition, providers should recognize the clinical manifestations to diagnose and treat prevalent sexually transmitted infections among refugees, such as syphilis, gonorrhea, chancroid, granuloma inguinale, and lymphogranuloma venereum. This section will review the existing epidemiologic data from the Centers for Disease Control (CDC) and centers that provide care for refugees. It will also highlight key screening, testing, and management considerations for different HIV subtypes and other major sexually transmitted infections that are high-yield for providing care to refugee populations in a primary care setting. [ABSTRACT FROM AUTHOR]

This paper presents an effective method for decision level fusion of fingerprint and iris biometrics using binary ant colony optimization (ACO) technique to identify the imposter instances. ACO is an evolutionary method. The selection of a proper set of optimization parameters for ACO is a multi-objective decision making optimization problem. Initially the matching scores for individual biometric classifiers are computed. Next, a ACO-based procedure is followed to simultaneously optimize the parameters and the fusion rules for fingerprint and iris biometrics. The proposed method has been found to perform satisfactorily on several benchmark datasets. [ABSTRACT FROM AUTHOR]

The Global Geodynamics Project (GGP) is an international network of superconducting gravimeters (SG) first established in 1997 and further extended in 2003. It was decided during the last IUGG assembly in 2007 to move to a permanent network hosted by IAG and become part of GGOS. Several new locations are being planned to extend the network to about 30 stations in 2008/2009. One of the present tasks within GGP is to prepare raw GGP data (at sampling times of 1–5 s) for inclusion into the IRIS data set for the seismologists to include in normal mode studies of the Earth. Of continuing interest within GGP is the issue of combining measurements from absolute gravimeters and permanent GPS at the SG stations for a variety of long-term studies of the gravity field such as tectonic uplift, subduction zone slip, post-glacial rebound and present-day ice melting. One of the most interesting new ideas within GGOS is the determination of the geocenter using a combination of satellite and ground-based gravimetry. The GGP network can provide a unique contribution in this respect through continuous data at the stations where absolute gravimeters (AG) will be deployed. The continuous monitoring of time-variable gravity is a tool to investigate many aspects of global Earth dynamics and to contribute to other sciences such as seismology, oceanography, earth rotation, hydrology, volcanology, and tectonics. Another promising application is the use of SG sub-networks in Europe and Asia to validate time-varying satellite gravity observations (GRACE, GOCE) due to continental hydrology and large-scale seismic deformation. [ABSTRACT FROM AUTHOR]

Eye features are one of the most important clues for many computer vision applications. In this paper, an efficient method to automatically extract eye features is presented. The extraction is highly based on the usage of the common knowledge about face and eye structure. With the assumption of frontal face images, firstly coarse eye regions are extracted by removing skin pixels in the upper part of the face. Then, iris circle position and radius are detected by using Hough transform in a coarse-to-fine fashion. In the final step, edges created by upper and lower eyelids are detected and polynomials are fitted to those edges so that their intersection points are labeled as eye corners. The algorithm is experimented on the Bosphorus database and the obtained results demonstrate that it can locate eye features very accurately. The strength of the proposed method stems from its reproducibility due to the utilization of simple and efficient image processing methods while achieving remarkable results without any need of training. [ABSTRACT FROM AUTHOR]

During the video and fixed image acquisition procedure of an automatic iris recognition system, it is essential to acquire focused iris images. If defocus iris images are acquired, the performance of the iris recognition is degraded, because iris images don΄t have enough feature information. Therefore it΄s important to adopt the image quality evaluation method before the image processing. In this paper, it is analyzed and compared four representative quality assessment methods on the MBGC iris database. Through methods, it can fast grade the images and pick out the high quality iris images from the video sequence captured by real-time iris recognition camera. The experimental results of the four methods according to the receiver operating characteristic (ROC) curve are shown. Then the optimal method of quality evaluation that allows better performance in an automatic iris recognition system is founded. This paper also presents an analysis in terms of computation speed of the four methods. [ABSTRACT FROM AUTHOR]

Biometric systems are subjected to a variety of attacks. Stored biometric template attack is very severe compared to all other attacks. Providing security to biometric templates is an important issue in building a reliable personal identification system. Multi biometric systems are more resistive towards spoof attacks compared to unibiometric counterpart. This work provides security and revocability to iris and fingerprint templates using password hardened multimodal biometric fuzzy vault. Password hardening provides security and revocability to biometric templates. Security of the vault is measured in terms of min-entropy. [ABSTRACT FROM AUTHOR]

Biometric becomes nowadays, a strong tool to authenticate persons, because they are able to prove a true identity. Research shows that different applications are used in verification. Fingerprints, Face, Iris recognition are some examples. But most of them safer from FRR and FAR, so for those reasons more researches and new algorithms are needed to be developed and to solve this problem. This paper presents a system with an algorithm, uses a pair of biometrics print (fingerprint and Iris), used to gain access to personal resources, it is based on a statistical approach. Features are extracted and used to authenticate persons. Paper shows that the developed system solves the mentioned problem and accelerates matching process. [ABSTRACT FROM AUTHOR]

In this paper we propose a new biometric-based Iris feature extraction system. The system automatically acquires the biometric data in numerical format (Iris Images) by using a set of properly located sensors. We are considering camera as a high quality sensor. Iris Images are typically color images that are processed to gray scale images. Then the Feature extraction algorithm is used to detect ˵IRIS Effective Region (IER)″ and then extract features from ˵IRIS Effective Region (IER)″ that are numerical characterization of the underlying biometrics. Later on this work will be helping to identify an individual by comparing the feature obtained from the feature extraction algorithm with the previously stored feature by producing a similarity score. This score will be indicating the degree of similarity between a pair of biometrics data under consideration. Depending on degree of similarity, individual can be identified. [ABSTRACT FROM AUTHOR]