Fabrication of Al/AlN composites by in situ reaction

The tensile properties and microstructures of various Al alloys fabricated by the pressureless infiltration method under a nitrogen atmosphere were examined. The spontaneous infiltration of molten metal into the powder bed occurred at 800 °C for 1 h under a nitrogen atmosphere. As a result, it was possible to fabricate Al alloys reinforced with AlN particles formed by in situ reaction. A significant strengthening even in the control alloy occurred due to the formation of in situ AlN particle even without an addition of artificial reinforcement. Strength values of the control alloy were increased with decreasing Al powders in bottom powders bed. In addition, tensile strength in Al–Mg alloys was increased with Mg content.     

A Lumped Parameter Model for Product Flow Times in Manufacturing Lines

Based upon basic drivers for the flow time, a lumped parameter model for a manufacturing line has been derived by using Kingman's approximation. The lumped parameter model for the flow time consists of a workstation and delay time. The workstation is characterized by the effective process time of the bottleneck workstation and the weighted sum of the coefficients of variation of all workstations. The delay time is determined by the sum of all effective process times of the nonbottleneck workstations. The advantage of the application of the lumped parameter model is that the variability of the total line is determined by a measurement at the operating point of the actual manufacturing line. This variability depends upon the operating point. Examples show that this dependency is not too strong for lines with a distinct bottleneck workstation in the actual line. From the derivation of the lumped parameter model it can be concluded that an improvement of the effective process time of the bottleneck workstation of the line results in an increase of the total variability of the line. This variability can be reduced by either reducing the variability of all workstations or the effective process times of the nonbottleneck workstations     

A Stress and Coping Model of Medication Adherence and Viral Load in HIV-Positive Men and Women on Highly Active Antiretroviral Therapy (HAART).

The authors tested a structural model that incorporated age, time since diagnosis, social support, coping, and negative mood as predictors of medication adherence and HIV viral load on 188 men and 134 women on highly active antiretroviral therapy (HAART). The authors used psychosocial latent factors formed from baseline measures to predict latent factors of adherence, as assessed by electronic monitoring and self-report, and viral load defined by indicators assessed over a 15-month period. Results from the model indicate that greater negative mood and lower social support are related to greater use of avoidance-oriented coping strategies. Use of these coping strategies by patients on HAART is related to poorer medication adherence and, subsequently, higher viral load. This model advances researchers' understanding of the contribution of psychosocial variables in predicting treatment adherence and disease progression in HIV-positive men and women. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ant colony optimization for routing and load-balancing: survey and new directions

Although an ant is a simple creature, collectively a colony of ants performs useful tasks such as finding the shortest path to a food source and sharing this information with other ants by depositing pheromone. In the field of ant colony optimization (ACO), models of collective intelligence of ants are transformed into useful optimization techniques that find applications in computer networking. In this survey, the problem-solving paradigm of ACO is explicated and compared to traditional routing algorithms along the issues of routing information, routing overhead and adaptivity. The contributions of this survey include 1) providing a comparison and critique of the state-of-the-art approaches for mitigating stagnation (a major problem in many ACO algorithms), 2) surveying and comparing three major research in applying ACO in routing and load-balancing, and 3) discussing new directions and identifying open problems. The approaches for mitigating stagnation discussed include: evaporation, aging, pheromone smoothing and limiting, privileged pheromone laying and pheromone-heuristic control. The survey on ACO in routing/load-balancing includes comparison and critique of ant-based control and its ramifications, AntNet and its extensions, as well as ASGA and SynthECA. Discussions on new directions include an ongoing work of the authors in applying multiple ant colony optimization in load-balancing.     

Realization of a self-recognition algorithm based on the biological immune system

As the use of the computer is popularized, the damage from computer viruses and hacking by malicious users is increasing rapidly. To block the hacking that is an intrusion into a person's computer, and the viruses that destroy data, a study into an intrusion detection and virus detection system based on the biological immune system is in progress. In this article, we describe a model of positive and negative selection for self-recognition, which has a similar function to the cytotoxic T cells that play an important role in the biological immune system. We propose a self/nonself discrimination algorithm for a computer system, which will the important when we detect data infected by a computer virus, of data modified by an intrusion from outside. We also show the validity and effectiveness of the proposed self-recognition algorithm by a computer simulation of some infected data obtained from cell changes and string changes in the self-file. This work was presented, in part, at the Seventh International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

An Experimental and Theoretical Comparison of Model Selection Methods

Machine Learning - We investigate the problem of model selection in the setting of supervised learning of boolean functions from independent random examples. More precisely, we compare methods for...     

Robust reweighted MAP motion estimation

This paper proposes a motion estimation algorithm that is robust to motion discontinuity and noise. The proposed algorithm is constructed by embedding the least median squares (LMedS) of robust statistics into the maximum a posteriori (MAP) estimator. Difficulties in accurate estimation of the motion field arise from the smoothness constraint and the sensitivity to noise. To cope robustly with these problems, a median operator and the concept of reweighted least squares (RLS) are applied to the MAP motion estimator, resulting in the reweighted robust MAP (RRMAP). The proposed RRMAP motion estimation algorithm is also generalized for multiple image frame cases. Computer simulation with various synthetic image sequences shows that the proposed algorithm reduces errors, compared to three existing robust motion estimation algorithms that are based on M-estimation, total least squares (TLS), and Hough transform. It is also observed that the proposed algorithm is statistically efficient and robust to additive Gaussian noise and impulse noise. Furthermore, the proposed algorithm yields reasonable performance for real image sequences     

Summative evaluation of the SINCGARS Tutor

In an earlier set of studies with a different Intelligently Coached Simulation (Orey, M.A., Fan, H., Park, J., Tzeng, S., & Gustafson, K. (1995). Evaluation of Device operator in a context of a coached simulation environment), we found a retention and a transfer problem. We tried to solve these problems while building a new Intelligently Coached Simulation (the SINCGARS Tutor). The solutions to the two problems were to use an interactive conceptual model for the retention problem and we used photographs of the equipment as the visuals of the simulation. We then tested this new tutor with a group of 22 officers who were not only required to know how to operate the SINCGARS radio, but would be responsible for teaching others in their unit when their training was complete. We had one group of officers train on the real equipment, in pairs, with one instructor available for guidance. The other group of 11 learned via the SINCGARS Tutor. The post test was to put an actual radio into operation while being observed by a trained observer. Results indicate that not only did the transfer problem go away, but officers trained on the computer performed the task more accurately both initially on the immediate post test and again on a surprise four-week delayed post test. The SINCGARS Tutor was found to be a very good training solution.     

Competitive analysis of incentive compatible on-line auctions

This paper studies auctions in a setting where the different bidders arrive at different times and the auction mechanism is required to make decisions about each bid as it is received. Such settings occur in computerized auctions of computational resources as well as in other settings. We call such auctions, on-line auctions.

We first characterize exactly on-line auctions that are incentive compatible, i.e. where rational bidders are always motivated to bid their true valuation. We then embark on a competitive worst-case analysis of incentive compatible on-line auctions. We obtain several results, the cleanest of which is an incentive compatible on-line auction for a large number of identical items. This auction has an optimal competitive ratio, both in terms of seller's revenue and in terms of the total social efficiency obtained.     

Negotiation Agents that Make Prudent Compromises and are Slightly Flexible in Reaching Consensus

The contribution of this work is designing and developing enhanced market-driven agents with the flexibility to (1) respond to changing market conditions, and (2) raise and relax trade aspirations. Previous theoretical analyses have shown that market-driven agents ( MDA s) make prudent compromises by reacting to changing market situations by taking into account factors such as competition, deadlines, and trading options. This work augments the design of an MDA with three fuzzy decision controllers that guide the agent in (i) relaxing trade aspiration in face of intense negotiation pressure, and (ii) raising trade aspiration in extremely favorable markets. Results from extensive simulations conducted using an implemented testbed suggest that when compared to MDA s, agents in this work achieved (1) higher success rates in reaching deals, (2) higher average utilities, and (3) higher expected utility.