Superplasticity in a high strength powder aluminum

The superplastic properties of a rapidly solidified, high strength P/M Al alloy and the same alloy reinforced with SiC particulates (SiC _p ) have been studied. To prepare superplastic test materials, a matrix alloy powder of composition 7.2Zn-2.4Mg-2Cu-0.2Zr-0.12Cr-0.2Co (Kaiser PM-64) and the powder mixed with 10 to 20 vol pct SiC _p (~5 μm diameter) were thermomechanically processed to very fine equiaxed grain structures of ~6 μm and ~8 μm, respectively. Superplasticity in these materials was evaluated by characterizing (1) high temperature stability, (2) dynamic grain growth, (3) strain rate sensitivity, (4) flow stress behavior, (5) cavitation and cavitation control, and (6) total superplastic strain. It was observed that the PM-64 alloy could achieve a total elongation of over 800 pct, while the SiC_p reinforced alloy could attain an elongation greater than 500 pct before failure. Also, it was shown that with the use of hydrostatic pressure during superplastic flow, cavitation could be controlled. Observations were made of the effect SiC _p reinforcement particles had on the superplastic flow stress behavior. Interpretations are proposed to explain the role of particulates during superplastic straining.     

Thermoplastic elastomeric composition based on maleic anhydride–grafted ground rubber tire

Ground rubber tire (GRT) powder was maleated in an internal mixer using maleic anhydride and dicumyl peroxide at 160°C. Maleated GRT was characterized by using X‐ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, wettability, and differential scanning calorimetry. The physical properties of the dynamically vulcanized 60 : 40, rubber : plastic composition based on acrylated high‐density polyethylene as the plastic phase and ethylene propylene diene rubber containing maleated GRT as the rubber phase were found to be greater than the corresponding composition containing nonmaleated GRT. The blend was found to be reprocessable, like themoplastic elastomers. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 84: 370–378, 2002; DOI 10.1002/app.10348     

Routing of a hazmat truck in the presence of weather systems

This paper focuses on the effects of weather systems on hazmat routing. We start by analyzing the effects of a weather system on a vehicle traversing a single link. This helps characterize the time-dependent attributes of a link due to movement of the weather systems. This analysis is used as a building block for the problem of finding a least risk path for hazmat transportation on a network exposed to such weather systems. Several methods are offered to solve the underlying problem, and computational results are reported. We draw two conclusions from this paper. First, it is possible to determine the time-dependent attributes for links on a network provided that some assumptions on the nature of the weather system are made. Second, heuristics can provide effective solutions for practical size problems while allowing for parking the vehicle to avoid weather system effects.     

Outcome of different treatment mixes in a multidimensional neuropsychological rehabilitation program.

Within a clinical demonstration program, 59 traumatically brain-injured patients were treated with 1 of 3 mixes of treatment. Mix 1 included cognitive remediation (CGR), small-group interpersonal (SGI) communication training, therapeutic community activities, and personal counseling. Mix 2 was similar to Mix 1 but stressed SGI exercises and eliminated CGR. Mix 3 emphasized CGR and eliminated SGI exercises. The efficacy of the treatment mixes was evaluated with performance on neuropsychological tests, improved independence in functional activities, measures of intra- and interpersonal functioning, and vocational outcome. Ss' participation in the program, irrespective of treatment mix, yielded improvements in (1) self-image, (2) quality of interpersonal relatedness and interaction, (3) involvement with others in naturalistic settings, and (4) vocational outcome. Overall, data point to the superiority of the balanced mix (Mix 1) over Mixes 2 and 3. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Component commonality effects on inventory costs

In this paper we study the effects of increasing component commonality for a single-period model. A two-product, two-level configuration under a general component cost structure is considered. The economic implications of replacing different products' components by common components are analyzed. We develop optimal solutions for the Commonality and Non-Commonality (Basic) Models and provide bounds on the total savings resulting from using commonality. We demonstrate, under general and specific component cost structures, that some forms of commonality may not always be a preferred strategy. Furthermore, we present conditions under which commonality should not be used. Finally, an extension to the two-product multicomponent model is provided.     

A two-stage MMSE multiuser decision feedback detector using successive/parallel interference cancellation

In this paper, we present a novel two-stage minimum-mean-squared-error (MMSE) multiuser decision feedback detector (DFD) for code division multiple access systems working in the frequency-selective multipath fading environment. The first stage of the proposed cascaded structure is the noise-predictive successive DFD (NP-S-DFD), in which the active users are detected successively using the conventional bell labs layered space-time (BLAST) ordering criterion. The second stage includes an adaptive successive/parallel DFD (SP-DFD), which uses the tentative decisions obtained at the first stage for multiuser interference cancellation and data detection. Therefore, the proposed two-stage DFD may be called noise-predictive successive SP-DFD (NP-S-SP-DFD). Simulation results are presented to demonstrate the substantial improvement in the bit error rate performance of NP-S-SP-DFD over the conventional single-stage and cascaded DFDs. It may be inferred that the proposed DFD provides additional performance gain, when the order in which the users are detected is optimized according to the BLAST ordering based on MMSE criterion.     

The importance of information localization in scene gist recognition.

People can recognize the meaning or gist of a scene from a single glance, and a few recent studies have begun to examine the sorts of information that contribute to scene gist recognition. The authors of the present study used visual masking coupled with image manipulations (randomizing phase while maintaining the Fourier amplitude spectrum; random image structure evolution [RISE]; J. Sadr & P. Sinha, 2004) to explore whether and when unlocalized Fourier amplitude information contributes to gist perception. In 4 experiments, the authors found that differences between scene categories in the Fourier amplitude spectrum are insufficient for gist recognition or gist masking. Whereas the global 1/f spatial frequency amplitude spectra of scenes plays a role in gist masking, local phase information is necessary for gist recognition and for the strongest gist masking. Moreover, the ability to recognize the gist of a target image was influenced by mask recognizability, suggesting that conceptual masking occurs even at the earliest stages of scene processing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Multiperson interaction recognition in images: A body keypoint based feature image analysis

Most interaction recognition approaches have been limited to single‐person action classification in videos. However, for still images where motion information is not available, the task becomes more complex. Aiming to this point, we propose an approach for multiperson human interaction recognition in images with keypoint‐based feature image analysis. Proposed method is a three‐stage framework. In the first stage, we propose feature‐based neural network (FCNN) for action recognition trained with feature images. Feature images are body features, that is, effective distances between a set of body part pairs and angular relation between body part triplets, rearranged in 2D gray‐scale image to learn effective representation of complex actions. In the later stage, we propose a voting‐based method for direction encoding to anticipate probable motion in steady images. Finally, our multiperson interaction recognition algorithm identifies which human pairs are interacting with each other using an interaction parameter. We evaluate our approach on two real‐world data sets, that is, UT‐interaction and SBU kinect interaction. The empirical experiments show that results are better than the state‐of‐the‐art methods with recognition accuracy of 95.83% on UT‐I set 1, 92.5% on UT‐I set 2, and 94.28% on SBU clean data set.     

High-utility and diverse itemset mining

High-utility Itemset Mining (HUIM) finds patterns from a transaction database with their utility no less than a user-defined threshold. The utility of an itemset is defined as the sum of the utilities of its items. The utility notion enables a data analyst to associate a profit score with each item and thereof to a pattern. We extend the notion of high-utility with diversity to define a new pattern type called High-utility and Diverse pattern (HUD). The notion of diversity of a pattern captures the extent of the different categories covered by the selected items in the pattern. An application of diverse-pattern lies in the recommendation task where a system can recommend to a customer a set of items from a new class based on her previously bought items. Our notion of diversity is easy to compute and also captures the basic essence of a previously proposed diversity notion. The existing algorithm to compute frequent-diverse patterns is 2-phase, i.e., in the first phase, frequent patterns are computed, out of which diverse patterns are filtered out in the second phase. We, in this paper, give an integrated algorithm that efficiently computes high-utility and diverse patterns in a single phase. Our experimental study shows that our proposed algorithm is very efficient as compared to a 2-phase algorithm that extracts high-utility itemsets in the first phase and filters out the diverse itemsets in the second phase.