Behavior of medium carbon steel under combined fatigue and wear

The combined fatigue-wear life of medium carbon steel (AISI 1045) was investigated under various combinations of loads and sliding wear conditions using a rotating beam test. The direction of the maximum tensile stress due to bending was perpendicular to that due to wear [1]. Tests were also performed with specimens plated with a thin layer of cadmium or nickel-gold. All of the tests were conducted in the high cycle regime. The results show that the fatigue life of all the specimens at a stress level higher than the endurance limit of the specimen was within the experimental scatter of a typical fatigue test. The effect of sliding wear on fatigue life is manifested primarily by the stress field imposed by the slider on the specimen. In the case of plated specimens, the fatigue life was not significantly affected, although the wear rate was decreased by an order of magnitude.     

Effect of cyclopentolate on human plasma cholinesterase

The beta-lactamase isoelectric focusing patterns of 37 strains of Yersinia enterocolitica from various serological and biochemical groups were examined. Strains of different serological groups generally had different patterns, but those of serological groups 1, 2, 3 and 9 were identical.     

A graphene pH sensor fabrication process for a nanotechnology laboratory course

A laboratory course experiment is described that combines traditional semiconductor fabrication techniques with the application of a nanotechnology-relevant material, graphene. Sensor devices made with graphene are integrated with a microfluidic device in order to introduce students to new applications of this technology in biology and medicine. The fabrication and test process for a pH sensor is used as a tangible example, exhibiting a changing resistance across graphene strips immersed in different pH buffer solutions. The processing and test equipment required is available in many Si device fabrication educational laboratories.     

Miscibility and synergistic effect of impact strength in polycarbonate/ABS blends

Miscibility and mechanical properties of polycarbonate/acrylonitrile-butadiene-styrene (PC/ABS) blends prepared by a continuous kneader-type extruder were investigated. It was found that the PC/ABS blend consists of the miscible PC/SAN phases and immiscible PC/PB phases, which agrees well with that predicted by the group contribution method of solubility parameters. Differences in calculated solubility parameter () are 0.20 (cal cm^–3)^1/2 for the PC/SAN pair and 1.85 (cal cm^–3)^1/2 for the PC/PB pair. Interestingly, the impact strength of the present PC/ABS blends exhibits a synergistic effect over a much wider range of polycarbonate content, i.e. 20%–80%, than that of the previously reported ones. This may be attributed to the enhanced mixing and low butadiene content. However, further work on the relationship with the rubber particle size is required to understand fully this observation.     

Configurable algorithms for complete exchange in 2D meshes

The interprocessor complete exchange communication pattern can be found in many important parallel algorithms. In this paper, we present algorithms for complete exchange on 2D mesh-connected multiprocessors. The unique feature of the proposed algorithms is that they are configurable where the time for message startups can be traded against larger message sizes. At one extreme, the algorithm minimizes the number of message startups at the expense of an increased amount of time spent in message transmission. At the other extreme, the time spent in message transmission is reduced at the expense of an increased number of message startups. The structure of the algorithms is such that intermediate solutions are feasible, i.e., the number of message startups can be increased slightly and the message transmission time is correspondingly reduced. The ability to configure these algorithms enables the algorithm characteristics to be matched with machine characteristics based on specific overheads for message initiation and link speeds to minimize overall execution time. In effect, the algorithms can be configured to strike the right balance between direct and message combining approaches on a specific architecture for a given problem size. We believe these algorithms are distinguished by this ability and contribute to efficient portable implementations of complete exchange algorithms     

Classification cost: An empirical comparison among traditional classifier, Cost-Sensitive Classifier, and MetaCost

Loan fraud is a critical factor in the insolvency of financial institutions, so companies make an effort to reduce the loss from fraud by building a model for proactive fraud prediction. However, there are still two critical problems to be resolved for the fraud detection: (1) the lack of cost sensitivity between type I error and type II error in most prediction models, and (2) highly skewed distribution of class in the dataset used for fraud detection because of sparse fraud-related data. The objective of this paper is to examine whether classification cost is affected both by the cost-sensitive approach and by skewed distribution of class. To that end, we compare the classification cost incurred by a traditional cost-insensitive classification approach and two cost-sensitive classification approaches, Cost-Sensitive Classifier (CSC) and MetaCost. Experiments were conducted with a credit loan dataset from a major financial institution in Korea, while varying the distribution of class in the dataset and the number of input variables. The experiments showed that the lowest classification cost was incurred when the MetaCost approach was used and when non-fraud data and fraud data were balanced. In addition, the dataset that includes all delinquency variables was shown to be most effective on reducing the classification cost.     

A robust lane recognition technique for vision-based navigation with a multiple clue-based filtration algorithm

This paper proposes a novel multiple clue-based filtration algorithm (MCFA), which is developed to detect lane markings on roads using camera vision images for autonomous mobile robot navigation. The main goal of the algorithm is the robust estimation of the relative position and angle of the lane in the image by using multiple clues based on different characteristics of the lane. In particular, robustness against environmental changes is enhanced greatly since a dynamic model of the lane, besides static features of the lane such as color, intensity, etc., is incorporated for reliable estimation. The efficiency of the algorithm is verified through mobile robot experiments under various extreme illumination conditions in outdoor environments. The increased robustness performance enables reliable closed-loop control of a mobile robot that operates in a variety of navigation-related missions.