Prediction model of compressive strength development of fly-ash concrete

Based on experimental results concerning the compressive strength development of concrete containing fly ash, the authors derived an estimation equation for compressive strength development. The equation can express coefficient , which indicates the activity of fly ash as a binder, in the form of a function of age, fly-ash content, and Blaine specific surface area of fly ash.

This equation is capable of explaining the increases in the early strength due to fly ash in place of part of fine aggregate, the decreases in the early strength due to fly ash in place of part of cement, the increases in the long-term strength due to pozzolanic reaction, the relationship between the fly-ash replacement ratio and the ratio of strength increase/decrease, and the effect of fly ash's Blaine specific surface area on the strength.     

Surface diffusion in microporous media

The surface diffusion of He, Ne, H₂, Ar, O₂, N₂ and CO₂ through Vycor microporous glass was analyzed theoretically and experimentally in the low pressure range as a function of temperature. A statistical-mechanical treatment was carried out in terms of partition functions to derive a general equation of surface flow. It was possible to separate the surface diffusion from the total flow using a simplified working equation. The conventional method which assumes that there is no adsorbed flow for helium should be discarded, because the fraction of surface diffusion for helium ranges from 0.133 to 0.247. It is also illustrated how to predict the permeability of a new gas for the same porous medium.     

Sensing tool breakage in face milling with a neural network

A new approach using a neural network to process the features of the cutting force signal for the recognition of tool breakage in face milling is proposed. The cutting force signal is first compressed by averaging the cutting force signal per tooth. Then, the average cutting force signal is passed through a median filter to extract the features of the cutting force signal due to tool breakage. With the back propagation training process, the neural network memorizes the feature difference of the cutting force signal between with and without tool breakage. As a result, the neural network can be used to classify the cutting force signal with or without tool breakage. Experiments show this new approach can sense tool breakage in a wide range of face milling operations.     

Nitrogen removal using recycled polystyrene bottles as biofilm media

The performance of an attached growth wastewater treatment process was investigated in an effort to improve nitrogen removal efficiency. Recycled Yakult (lactic acid fermentation drink) bottles made of polystyrene were used as a biofilm media. The use of Yakult bottles as a biofilm media has been attempted by numerous researchers in Japan for the removal of solids and organics. However, these studies focused only on the removal of solids and organics. This study extended their application to the removal of nitrogen for domestic sewage treatment. Yakult media was placed in a reactor with 70% apparent reactor volume in a conventional A/O process. The bottom of the Yakult media was removed, and randomly filled Yakult media were effectively able to reduce the flow in tanks, resulting in an increase in the contact time between pollutants and microorganisms. With higher HRT, the nitrogen removal efficiency was increased by up to 83% with 12 hr of HRT. Nitrification appeared to be the limiting factor of nitrogen removal at an HRT that is less than 12 hr, indicating that the Yakult process requires more retention time to achieve nitrification compared to other biofilm processes. The removal efficiencies of organics and solids were high regardless of the change of operational parameters. This article is based on a presentation in “The 7th Korea-China Workshop On Advanced Materials” organized by the Korea-China Advanced Materials Cooperation Center and the China-Korea Advanced Materials Cooperation Center, held at Ramada Plaza Jeju Hotel, Jeju Island, Korea on August 24–27, 2003.     

Galvanic coupling effect on corrosion behavior of Al alloy-matrix composites

Galvanic coupling effect on the corrosion of SiC-reinforced aluminum alloy-matrix composites was investigated in a sodium chloride solution. The potentiodynamic polarization measurement indicated that pitting potentials of metal matrix composites (MMCs) and AA2124 matrix alloy were similar, and pitting potential of MMCs was almost same as corrosion potential, while pitting susceptibility of MMCs was higher than that of AA2124 alloy. Galvanic current by formation of galvanic couple between SiCw and matrix reveals very low value because of large cathodic polarization of SiC. However, by increasing potential of matrix to pitting potential by this galvanic couple and thus, forming pits easily at the weak passive film near SiC reinforcing phase preferentially, it is concluded that pitting susceptibility of MMCs increases highly than AA2124 alloy of matrix composition.     

A novel part-based approach to mean-shift algorithm for visual tracking

Visual tracking is one of the most important problems considered in computer vision. To improve the performance of the visual tracking, a part-based approach will be a good solution. In this paper, a novel method of visual tracking algorithm named part-based mean-shift (PBMS) algorithm is presented. In the proposed PBMS, unlike the standard mean-shift (MS), the target object is divided into multiple parts and the target is tracked by tracking each individual part and combining the results. For the part-based visual tracking, the objective function in the MS is modified such that the target object is represented as a combination of the parts and iterative optimization solution is presented. Further, the proposed PBMS provides a systematic and analytic way to determine the scale of the bounding box for the target from the perspective of the objective function optimization. Simulation is conducted with several benchmark problems and the result shows that the proposed PBMS outperforms the standard MS.

     

Synergistic effects of micro-/nano-fillers on conductive and electromagnetic shielding properties of polypropylene nanocomposites

This study presents the synergistic effects of graphene nanosheets (GNSs) and carbon fibers (CFs) additions on the electrical and electromagnetic shielding properties of GNS/CF/polypropylene (PP) composites. These composites were fabricated by the melt blending of different ratios of GNSs and CFs (20:0, 15:5, 10:10, 5:15 and 0:20 wt/wt%) into a PP polymer matrix using a Brabender mixer. Besides, the chemical and crystalline structures and the thermal stability of the resultant GNS/CF/PP composites were characterized by Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD) and thermogravimetric analysis (TGA). FT-IR and XRD showed that with the addition of GNSs content, transmittances at 1373.4?cm^?1 and 1454.4?cm^?1 became smaller and the characteristic peak at 26.82° became stronger. TGA showed that the GNS/CF/PP composite can be used at high temperature below 456°C. Blending 10?wt% CFs and 10?wt% GNSs into the PP polymer resulted in excellent conductivity (0.397 S/cm), which indicated the occurrence of the critical percolation threshold phenomenon, and also reached the maximum electromagnetic shielding effectiveness (EMSE) of 20?dB at 1.28–2.00?GHz. Laminated with five layers of composites, its EMSE achieved 25–38?dB at 0.3–3.0?GHz, corresponding to blocking of 94.38–98.74% electromagnetic waves.     

Analysis of pressure-driven electrokinetic flows in hydrophobic microchannels with slip-dependent zeta potential

The present study is an analysis of pressure-driven electrokinetic flows in hydrophobic microchannels with emphasis on the slip effects under coupling of interfacial electric and fluid slippage phenomena. Commonly used linear model with slip-independent zeta potential and the nonlinear model at limiting (high-K) condition with slip-dependent zeta potential are solved analytically. Then, numerical solutions of the electrokinetic flow model with zeta potential varying with slip length are analyzed. Different from the general notion of “the more hydrophobic the channel wall, the higher the flowrate,” the results with slip-independent and slip-dependent zeta potentials both disclose that flowrate becomes insensitive to the wall hydrophobicity or fluid slippage at sufficiently large slip lengths. Boundary slip not only assists fluid motion but also enhances counter-ions transport in EDL and, thus, results in strong streaming potential as well as electrokinetic retardation. With slip-dependent zeta potential considered, flowrate varies non-monotonically with increasing slip length due to competition of the favorable and adverse effects with more complicated interactions. The influence of the slip on the electrokinetic flow is eventually nullified at large slip lengths for balance of the counter effects, and the flowrate becomes insensitive to further hydrophobicity of the microchannel. The occurrence of maximum, minimum, and insensitivity on the flowrate-slip curves can be premature at a higher zeta potential and/or larger electrokinetic separation distance.     

The role of goal awareness and information technology self-efficacy on job satisfaction of healthcare system users

This paper investigates the influence of goal awareness and IT self-efficacy on job satisfaction based on the motivation sequence model, goal-setting theory, and social cognitive theory. Using a large-scale field survey of healthcare enterprise resource planning (ERP) system users (n?=?352), this study investigates these relationships and provides important insight to healthcare ERP system researchers and managers. Both goal awareness and IT self-efficacy influence positive job satisfaction of healthcare ERP system users, as expected. Furthermore, the influence of goal awareness is stronger when the role of ERP systems is highly perceived for decision-making of the job. There was no interaction effect between goal awareness and IT self-efficacy in the post hoc analysis. The model is significantly supported by the empirical test with the large number of field data from healthcare ERP system users in the healthcare company. Practical and academic implications are discussed in the paper.     

Internet-Based Smart-Space Navigation of a Car-Like Wheeled Robot Using Fuzzy-Neural Adaptive Control

In this paper, a navigation system is developed. The system includes path tracking and obstacle avoidance apparatus for a car-like wheeled robot (CLWR) within an Internet-based smart-space (IBSS) using fuzzy-neural adaptive control (FNAC). Two distributed charge-coupled device (CCD) cameras are installed to capture both the dynamic pose of the CLWR and the obstacle. Based on the control authority of these two CCD cameras, a suitable reference command that contains the desired steering angle and angular velocity for the FNAC built into the client computer is planned. Because of the delay encountered by the transmission through the Internet network (IN) and the wireless local area network (WLAN) and the nonlinear coupling features of the CLWR, a weighted combination of $N$ linear subsystems that are described by a state-space model with average-delay is implemented to approximate the dynamics of an IBSS-CLWR. The proposed FNAC contains a neural network consisting of a radial basis function (RBFNN) to learn the uncertainties due to the fuzzy-model error (e.g., the random time-varying delays and the slippage of the CLWR) and the interactions caused by other subsystems. The stability of the overall system is then investigated by adopting the Lyapunov stability theory. Finally, a sequence of experiments including the control of the off-ground CLWR (i.e., the CLWR does not make contact with the ground) and the navigation of the IBSS-CLWR as compared with the conventional proportional-integral-derivative (PID) control is performed to demonstrate the advantage of the proposed control system.