Long-term memory for the terrorist attack of September 11: Flashbulb memories, event memories, and the factors that influence their retention.

More than 3,000 individuals from 7 U.S. cities reported on their memories of learning of the terrorist attacks of September 11, as well as details about the attack, 1 week, 11 months, and/or 35 months after the assault. Some studies of flashbulb memories examining long-term retention show slowing in the rate of forgetting after a year, whereas others demonstrate accelerated forgetting. This article indicates that (a) the rate of forgetting for flashbulb memories and event memory (memory for details about the event itself) slows after a year, (b) the strong emotional reactions elicited by flashbulb events are remembered poorly, worse than nonemotional features such as where and from whom one learned of the attack, and (c) the content of flashbulb and event memories stabilizes after a year. The results are discussed in terms of community memory practices. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Comparisons of methods for multiple hypothesis testing in neuropsychological research.

Hypothesis testing with multiple outcomes requires adjustments to control Type I error inflation, which reduces power to detect significant differences. Maintaining the prechosen Type I error level is challenging when outcomes are correlated. This problem concerns many research areas, including neuropsychological research in which multiple, interrelated assessment measures are common. Standard p value adjustment methods include Bonferroni-, Sidak-, and resampling-class methods. In this report, the authors aimed to develop a multiple hypothesis testing strategy to maximize power while controlling Type I error. The authors conducted a sensitivity analysis, using a neuropsychological dataset, to offer a relative comparison of the methods and a simulation study to compare the robustness of the methods with respect to varying patterns and magnitudes of correlation between outcomes. The results lead them to recommend the Hochberg and Hommel methods (step-up modifications of the Bonferroni method) for mildly correlated outcomes and the step-down minP method (a resampling-based method) for highly correlated outcomes. The authors note caveats regarding the implementation of these methods using available software. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Hidden location prediction using check-in patterns in location-based social networks

Online product reviews nowadays are increasingly prevalent in E-commerce websites. People often refer to product reviews to evaluate the quality of a product before purchasing. However, there have been a large number of review spammers who often work collaboratively to promote or demote target products, which severely harm the review system. Much previous work exploits machine learning approaches to detect suspicious reviews/reviewers. In this paper, we introduce a top-down computing framework, namely GGSpam, to detect review spammer groups by exploiting the topological structure of the underlying reviewer graph which reveals the co-review collusiveness. A novel instantiation of GGSpam, namely GSBC, is designed by modeling spammer groups as bi-connected graphs. Given a reviewer graph, GSBC identifies all the bi-connected components whose spamicity scores exceed the given spam threshold. For large unsuspicious bi-connected graphs, the minimum cut algorithm is used to split the graph, and the smaller graphs are further processed recursively. A variety of group spam indicators are designed to measure the spamicity of a spammer group. Experimental study shows that the proposed approach is both effective and efficient and outperforms several state-of-the-art baselines, including graph based and non-graph based, by a large margin.     

Improved quality of reconstructed images using floating point arithmetic for moment calculation

Zernike moments which are superior to geometric moments because of their special properties of image reconstruction and immunity to noise, suffer from several discretization errors. These errors lead to poor quality of reconstructed image and wide variations in the numerical values of the moments. The predominant factor, as observed in this paper, is due to the discrete integer implementation of the steps involved in moment calculation. It is shown in this paper that by modifying the algorithms to include discrete float implementation, the quality of the reconstructed image improves significantly and the first-order moment becomes zero. Low-order Zernike moments have been found to be stable under linear transformations while the high-order moments have large variations. The large variations in high-order moments, however, do not greatly affect the quality of the reconstructed image, implying that they should be ignored when numerical values of moments are used as features. The 11 functions based on geometric moments have also been found to be stable under linear transformations and thus these can be used as features. Pixel level analysis of the images has been carried out to strengthen the results.     

Effect of underlap and gate length on device performance of an AlInN/GaN underlap MOSFET

We investigate the performance of an 18 nm gate length AlInN/GaN heterostructure underlap double gate MOSFET, using 2D Sentaurus TCAD simulation. The device uses lattice-matched wideband Al_0.83In_0.17N and narrowband GaN layers, along with high-k Al₂O₃ as the gate dielectric. The device has an ultrathin body and is designed according to the ITRS specifications. The simulation is done using the hydrodynamic model and interface traps are also considered. Due to the large two-dimensional electron gas (2DEG) density and high velocity, the maximal drain current density achieved is very high. Extensive device simulation of the major device performance metrics such as drain induced barrier lowering (DIBL), subthreshold slope (SS), delay, threshold voltage (V_t), I_on/I_off ratio and energy delay product have been done for a wide range of gate and underlap lengths. Encouraging results for delay, I_on, DIBL and energy delay product are obtained. The results indicate that there is a need to optimize the I_off and SS values for specific logic design. The proposed AlInN/GaN heterostructure underlap DG MOSFET shows excellent promise as one of the candidates to substitute currently used MOSFETs for future high speed applications.     

Hydrodynamic modeling of some gas injection procedures in ladle metallurgy operations

Experimental studies of flows generated in a 0.30 scale water model of a 150 ton steelmaking ladle are reported. These were used to test the adequacy of a generalized two-dimensional computational scheme for predicting flows generated by fully submerged and partially submerged gas injection lances. The roles of turbulence models and grid configuration were assessed. Predictions for flow fields generated in a 150 ton steelworks ladle with and without tapered side walls, and with and without surface baffles around the rising plume were considered.