University at Buffalo

About: University at Buffalo is a education organization based out in Buffalo, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 33773 authors who have published 63840 publications receiving 2278954 citations. The organization is also known as: UB & State University of New York at Buffalo.

A Privacy-Preserving and Copy-Deterrence Content-Based Image Retrieval Scheme in Cloud Computing

Abstract: With the increasing importance of images in people’s daily life, content-based image retrieval (CBIR) has been widely studied. Compared with text documents, images consume much more storage space. Hence, its maintenance is considered to be a typical example for cloud storage outsourcing. For privacy-preserving purposes, sensitive images, such as medical and personal images, need to be encrypted before outsourcing, which makes the CBIR technologies in plaintext domain to be unusable. In this paper, we propose a scheme that supports CBIR over encrypted images without leaking the sensitive information to the cloud server. First, feature vectors are extracted to represent the corresponding images. After that, the pre-filter tables are constructed by locality-sensitive hashing to increase search efficiency. Moreover, the feature vectors are protected by the secure kNN algorithm, and image pixels are encrypted by a standard stream cipher. In addition, considering the case that the authorized query users may illegally copy and distribute the retrieved images to someone unauthorized, we propose a watermark-based protocol to deter such illegal distributions. In our watermark-based protocol, a unique watermark is directly embedded into the encrypted images by the cloud server before images are sent to the query user. Hence, when image copy is found, the unlawful query user who distributed the image can be traced by the watermark extraction. The security analysis and the experiments show the security and efficiency of the proposed scheme.

A Drug Burden Index to Define the Functional Burden of Medications in Older People

Abstract: Background Older people carry a high burden of illness for which medications are indicated, along with increased risk of adverse drug reactions. We developed an index to determine drug burden based on pharmacologic principles. We evaluated the relationship of this index to physical and cognitive performance apart from disease indication. Methods Data from the Health, Aging, and Body Composition Study on 3075 well-functioning community-dwelling persons aged 70 to 79 years were analyzed by multiple linear regression to assess the cross-sectional association of drug burden index with a validated composite continuous measure for physical function, and with the Digit Symbol Substitution Test for cognitive performance. Results Use of anticholinergic and sedative medications was associated with poorer physical performance score (anticholinergic exposure, 2.08 vs 2.21, P P P = .045; sedative exposure, 34.0 vs 35.5, P = .01). Associations were strengthened when exposure was calculated by principles of dose response. An increase of 1 U in drug burden index was associated with a deficit of 0.15 point ( P P = .01) on the Digit Symbol Substitution Test. These values were more than 3 times those associated with a single comorbid illness. Conclusions The drug burden index demonstrates that anticholinergic and sedative drug exposure is associated with poorer function in community-dwelling older people. This pharmacologic approach provides a useful evidence-based tool for assessing the functional effect of exposure to medications in this population.

Tumor Necrosis Factor-α in Sera of Obese Patients: Fall with Weight Loss

Abstract: In view of the recent demonstration that obesity in animals and humans is associated with an increase in tumor necrosis factor-alpha (TNFalpha) expression, that this expression falls with weight loss, and that TNFalpha may specifically inhibit insulin action, the possibility that TNFalpha may be a mediator of insulin resistance has been raised. We have undertaken this study to investigate whether serum TNFalpha concentrations are elevated in obese subjects, whether they fall after weight loss, and whether this fall parallels the fall in insulin release after glucose challenge. Obese patients (age range: 25-54, weight mean +/- SD: 96.4 +/- 13.8 kg, body mass index: 35.7 +/- 5.6 kg/m2) were started on a diet program. The mean weight fell to 84.5 +/- 11.3 (P < 0.0001) and body mass index to 31.3 +/- 4.9 (P < 0.0001). Plasma TNFalpha concentrations were markedly elevated in the obese (3.45 +/- 0.16 pg/mL), when compared with controls (0.72 +/- 0.28 pg/mL), and fell significantly (2.63 +/- 1.40 pg/mL) after weight loss (P < 0.02). The magnitude of insulin release after glucose (75 g) challenge (area under the curve) also fell significantly (P < 0.01) after weight loss. The magnitude of weight loss and fall in TNFalpha were related to basal body weight (r = 0.57, P < 0.001) and basal TNFalpha (r = 0.55, P < 0.001) concentrations, respectively, but not to each other or to the glucose-induced insulin release (area under the curve). We conclude that obesity is associated with increased plasma TNFalpha concentrations, which fall with weight loss. Because circulating TNFalpha may mediate insulin resistance in the obese, a fall in TNFalpha concentrations may contribute to the restoration of insulin resistance after weight loss, Thus, TNFalpha may be an important circulating cytokine, which may provide a potentially reversible mechanism for mediating insulin resistance.

Feature selection for text categorization on imbalanced data

Abstract: A number of feature selection metrics have been explored in text categorization, among which information gain (IG), chi-square (CHI), correlation coefficient (CC) and odds ratios (OR) are considered most effective. CC and OR are one-sided metrics while IG and CHI are two-sided. Feature selection using one-sided metrics selects the features most indicative of membership only, while feature selection using two-sided metrics implicitly combines the features most indicative of membership (e.g. positive features) and non-membership (e.g. negative features) by ignoring the signs of features. The former never consider the negative features, which are quite valuable, while the latter cannot ensure the optimal combination of the two kinds of features especially on imbalanced data. In this work, we investigate the usefulness of explicit control of that combination within a proposed feature selection framework. Using multinomial naive Bayes and regularized logistic regression as classifiers, our experiments show both great potential and actual merits of explicitly combining positive and negative features in a nearly optimal fashion according to the imbalanced data.

Description and performance of track and primary-vertex reconstruction with the CMS tracker

Abstract: A description is provided of the software algorithms developed for the CMS tracker both for reconstructing charged-particle trajectories in proton-proton interactions and for using the resulting tracks to estimate the positions of the LHC luminous region and individual primary-interaction vertices. Despite the very hostile environment at the LHC, the performance obtained with these algorithms is found to be excellent. For tt events under typical 2011 pileup conditions, the average track-reconstruction efficiency for promptly-produced charged particles with transverse momenta of p_T > 0.9GeV is 94% for pseudorapidities of |η| < 0.9 and 85% for 0.9 < |η| < 2.5. The inefficiency is caused mainly by hadrons that undergo nuclear interactions in the tracker material. For isolated muons, the corresponding efficiencies are essentially 100%. For isolated muons of p_T = 100GeV emitted at |η| < 1.4, the resolutions are approximately 2.8% in p_T, and respectively, 10μm and 30μm in the transverse and longitudinal impact parameters. The position resolution achieved for reconstructed primary vertices that correspond to interesting pp collisions is 10–12μm in each of the three spatial dimensions. The tracking and vertexing software is fast and flexible, and easily adaptable to other functions, such as fast tracking for the trigger, or dedicated tracking for electrons that takes into account bremsstrahlung.