University of Massachusetts Amherst

About: University of Massachusetts Amherst is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 37274 authors who have published 83965 publications receiving 3834996 citations. The organization is also known as: UMass Amherst & Massachusetts State College.

FDDB: A benchmark for face detection in unconstrained settings

Abstract: Despite the maturity of face detection research, it remains difficult to compare different algorithms for face detection. This is partly due to the lack of common evaluation schemes. Also, existing data sets for evaluating face detection algorithms do not capture some aspects of face appearances that are manifested in real-world scenarios. In this work, we address both of these issues. We present a new data set of face images with more faces and more accurate annotations for face regions than in previous data sets. We also propose two rigorous and precise methods for evaluating the performance of face detection algorithms. We report results of several standard algorithms on the new benchmark.

Information extraction

Abstract: here may be more text data in electronic form than ever before, but much of it is ignored. No human can read, understand, and synthesize megabytes of text on an everyday basis. Missed information— and lost opportunities—has spurred researchers to explore various information management strategies to establish order in the text wilderness. The most common strategies are information retrieval (IR) and information filtering [4]. A relatively new development—information extraction (IE)—is the subject of this article. We can view IR systems as combine harvesters that bring back useful material from vast fields of raw material. With large amounts of potentially useful information in hand, an IE system can then transform the raw material, refining and reducing it to a germ of the original text (see Figure 1). Suppose financial analysts are investigating production of semiconductor devices (see Figure 2). They might want to know several things:

Assessing the predictive validity of two methods of measuring self-image congruence

Abstract: The predictive validity of two measurement methods of self-image congruence—traditional versus new—were compared in six studies involving different consumer populations, products, consumption settings, and dependent variables (brand preference, preference for product form, consumer satisfaction/dissatisfaction, brand attitude, and program choice). The traditional method is based on tapping the subject’s perception of product-user image and the subject’s perception of his/her self-image along a predetermined set of image attributes and adding the self-congruity scores across all image dimensions. Three problems were identified and discussed in relation to the traditional method: (1) the use of discrepancy scores, (2) the possible use of irrelevant images, and (3) the use of the compensatory decision rule. The new method is based on tapping the psychological experience of self-congruity directly and globally. The findings demonstrated the predictive validity of the new method over and beyond the traditional method.

Root uptake and phytotoxicity of ZnO nanoparticles.

Abstract: Increasing application of nanotechnology highlights the need to clarify nanotoxicity. However, few researches have focused on phytotoxicity of nanomaterials; it is unknown whether plants can uptake and transport nanoparticles. This study was to examine cell internalization and upward translocation of ZnO nanoparticles by Lolium perenne (ryegrass). The dissolution of ZnO nanoparticles and its contribution to the toxicity on ryegrass were also investigated. Zn2+ ions were used to compare and verify the root uptake and phytotoxicity of ZnO nanoparticles in a hydroponic culture system. The root uptake and phytotoxicity were visualized by light, scanning electron, and transmission electron microscopies. In the presence of ZnO nanoparticles, ryegrass biomass significantly reduced, root tips shrank, and root epidermal and cortical cells highly vacuolated or collapsed. Zn2+ ion concentrations in bulk nutrient solutions with ZnO nanoparticles were lower than the toxicity threshold of Zn2+ to the ryegrass; shoot Zn...